Sample records for neural mechanisms evolution
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Germ layers, the neural crest and emergent organization in development and evolution.
Hall, Brian K
2018-04-10
Discovered in chick embryos by Wilhelm His in 1868 and named the neural crest by Arthur Milnes Marshall in 1879, the neural crest cells that arise from the neural folds have since been shown to differentiate into almost two dozen vertebrate cell types and to have played major roles in the evolution of such vertebrate features as bone, jaws, teeth, visceral (pharyngeal) arches, and sense organs. I discuss the discovery that ectodermal neural crest gave rise to mesenchyme and the controversy generated by that finding; the germ layer theory maintained that only mesoderm could give rise to mesenchyme. A second topic of discussion is germ layers (including the neural crest) as emergent levels of organization in animal development and evolution that facilitated major developmental and evolutionary change. The third topic is gene networks, gene co-option, and the evolution of gene-signaling pathways as key to developmental and evolutionary transitions associated with the origin and evolution of the neural crest and neural crest cells. © 2018 Wiley Periodicals, Inc.
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On the neural mechanisms subserving consciousness and attention
Directory of Open Access Journals (Sweden)
Catherine eTallon-Baudry
2012-01-01
Full Text Available Consciousness, as described in the experimental literature, is a multi-faceted phenomenon, that impinges on other well-studied concepts such as attention and control. Do consciousness and attention refer to different aspects of the same core phenomenon, or do they correspond to distinct functions? One possibility to address this question is to examine the neural mechanisms underlying consciousness and attention. If consciousness and attention pertain to the same concept, they should rely on shared neural mechanisms. Conversely, if their underlying mechanisms are distinct, then consciousness and attention should be considered as distinct entities. This paper therefore reviews neurophysiological facts arguing in favor or against a tight relationship between consciousness and attention. Three neural mechanisms that have been associated with both attention and consciousness are examined (neural amplification, involvement of the fronto-parietal network, and oscillatory synchrony, to conclude that the commonalities between attention and consciousness at the neural level may have been overestimated. Last but not least, experiments in which both attention and consciousness were probed at the neural level point toward a dissociation between the two concepts. It therefore appears from this review that consciousness and attention rely on distinct neural properties, although they can interact at the behavioral level. It is proposed that a "cumulative influence model", in which attention and consciousness correspond to distinct neural mechanisms feeding a single decisional process leading to behavior, fits best with available neural and behavioral data. In this view, consciousness should not be considered as a top-level executive function but should rather be defined by its experiential properties.
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Deciphering the Cognitive and Neural Mechanisms Underlying ...
International Development Research Centre (IDRC) Digital Library (Canada)
Deciphering the Cognitive and Neural Mechanisms Underlying Auditory Learning. This project seeks to understand the brain mechanisms necessary for people to learn to perceive sounds. Neural circuits and learning. The research team will test people with and without musical training to evaluate their capacity to learn ...
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Amphioxus and lamprey AP-2 genes: implications for neural crest evolution and migration patterns
Meulemans, Daniel; Bronner-Fraser, Marianne
2002-01-01
The neural crest is a uniquely vertebrate cell type present in the most basal vertebrates, but not in cephalochordates. We have studied differences in regulation of the neural crest marker AP-2 across two evolutionary transitions: invertebrate to vertebrate, and agnathan to gnathostome. Isolation and comparison of amphioxus, lamprey and axolotl AP-2 reveals its extensive expansion in the vertebrate dorsal neural tube and pharyngeal arches, implying co-option of AP-2 genes by neural crest cells early in vertebrate evolution. Expression in non-neural ectoderm is a conserved feature in amphioxus and vertebrates, suggesting an ancient role for AP-2 genes in this tissue. There is also common expression in subsets of ventrolateral neurons in the anterior neural tube, consistent with a primitive role in brain development. Comparison of AP-2 expression in axolotl and lamprey suggests an elaboration of cranial neural crest patterning in gnathostomes. However, migration of AP-2-expressing neural crest cells medial to the pharyngeal arch mesoderm appears to be a primitive feature retained in all vertebrates. Because AP-2 has essential roles in cranial neural crest differentiation and proliferation, the co-option of AP-2 by neural crest cells in the vertebrate lineage was a potentially crucial event in vertebrate evolution.
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Leininger, Elizabeth C; Kelley, Darcy B
2013-04-07
Independent or convergent evolution can underlie phenotypic similarity of derived behavioural characters. Determining the underlying neural and neuromuscular mechanisms sheds light on how these characters arose. One example of evolutionarily derived characters is a temporally simple advertisement call of male African clawed frogs (Xenopus) that arose at least twice independently from a more complex ancestral pattern. How did simplification occur in the vocal circuit? To distinguish shared from divergent mechanisms, we examined activity from the calling brain and vocal organ (larynx) in two species that independently evolved simplified calls. We find that each species uses distinct neural and neuromuscular strategies to produce the simplified calls. Isolated Xenopus borealis brains produce fictive vocal patterns that match temporal patterns of actual male calls; the larynx converts nerve activity faithfully into muscle contractions and single clicks. In contrast, fictive patterns from isolated Xenopus boumbaensis brains are short bursts of nerve activity; the isolated larynx requires stimulus bursts to produce a single click of sound. Thus, unlike X. borealis, the output of the X. boumbaensis hindbrain vocal pattern generator is an ancestral burst-type pattern, transformed by the larynx into single clicks. Temporally simple advertisement calls in genetically distant species of Xenopus have thus arisen independently via reconfigurations of central and peripheral vocal neuroeffectors.
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International Nuclear Information System (INIS)
Wang Rubin; Yu Wei
2005-01-01
In this paper, we investigate how the population of neuronal oscillators deals with information and the dynamic evolution of neural coding when the external stimulation acts on it. Numerically computing method is used to describe the evolution process of neural coding in three-dimensioned space. The numerical result proves that only the suitable stimulation can change the coupling structure and plasticity of neurons
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Neural Mechanisms of Selective Visual Attention.
Moore, Tirin; Zirnsak, Marc
2017-01-03
Selective visual attention describes the tendency of visual processing to be confined largely to stimuli that are relevant to behavior. It is among the most fundamental of cognitive functions, particularly in humans and other primates for whom vision is the dominant sense. We review recent progress in identifying the neural mechanisms of selective visual attention. We discuss evidence from studies of different varieties of selective attention and examine how these varieties alter the processing of stimuli by neurons within the visual system, current knowledge of their causal basis, and methods for assessing attentional dysfunctions. In addition, we identify some key questions that remain in identifying the neural mechanisms that give rise to the selective processing of visual information.
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Multiscale Quantum Mechanics/Molecular Mechanics Simulations with Neural Networks.
Shen, Lin; Wu, Jingheng; Yang, Weitao
2016-10-11
Molecular dynamics simulation with multiscale quantum mechanics/molecular mechanics (QM/MM) methods is a very powerful tool for understanding the mechanism of chemical and biological processes in solution or enzymes. However, its computational cost can be too high for many biochemical systems because of the large number of ab initio QM calculations. Semiempirical QM/MM simulations have much higher efficiency. Its accuracy can be improved with a correction to reach the ab initio QM/MM level. The computational cost on the ab initio calculation for the correction determines the efficiency. In this paper we developed a neural network method for QM/MM calculation as an extension of the neural-network representation reported by Behler and Parrinello. With this approach, the potential energy of any configuration along the reaction path for a given QM/MM system can be predicted at the ab initio QM/MM level based on the semiempirical QM/MM simulations. We further applied this method to three reactions in water to calculate the free energy changes. The free-energy profile obtained from the semiempirical QM/MM simulation is corrected to the ab initio QM/MM level with the potential energies predicted with the constructed neural network. The results are in excellent accordance with the reference data that are obtained from the ab initio QM/MM molecular dynamics simulation or corrected with direct ab initio QM/MM potential energies. Compared with the correction using direct ab initio QM/MM potential energies, our method shows a speed-up of 1 or 2 orders of magnitude. It demonstrates that the neural network method combined with the semiempirical QM/MM calculation can be an efficient and reliable strategy for chemical reaction simulations.
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Kolling, Nils; Behrens, Timothy EJ; Mars, Rogier B; Rushworth, Matthew FS
2012-01-01
Behavioural economic studies, involving limited numbers of choices, have provided key insights into neural decision-making mechanisms. By contrast, animals’ foraging choices arise in the context of sequences of encounters with prey/food. On each encounter the animal chooses to engage or whether the environment is sufficiently rich that searching elsewhere is merited. The cost of foraging is also critical. We demonstrate humans can alternate between two modes of choice, comparative decision-ma...
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Realistic thermodynamic and statistical-mechanical measures for neural synchronization.
Kim, Sang-Yoon; Lim, Woochang
2014-04-15
Synchronized brain rhythms, associated with diverse cognitive functions, have been observed in electrical recordings of brain activity. Neural synchronization may be well described by using the population-averaged global potential VG in computational neuroscience. The time-averaged fluctuation of VG plays the role of a "thermodynamic" order parameter O used for describing the synchrony-asynchrony transition in neural systems. Population spike synchronization may be well visualized in the raster plot of neural spikes. The degree of neural synchronization seen in the raster plot is well measured in terms of a "statistical-mechanical" spike-based measure Ms introduced by considering the occupation and the pacing patterns of spikes. The global potential VG is also used to give a reference global cycle for the calculation of Ms. Hence, VG becomes an important collective quantity because it is associated with calculation of both O and Ms. However, it is practically difficult to directly get VG in real experiments. To overcome this difficulty, instead of VG, we employ the instantaneous population spike rate (IPSR) which can be obtained in experiments, and develop realistic thermodynamic and statistical-mechanical measures, based on IPSR, to make practical characterization of the neural synchronization in both computational and experimental neuroscience. Particularly, more accurate characterization of weak sparse spike synchronization can be achieved in terms of realistic statistical-mechanical IPSR-based measure, in comparison with the conventional measure based on VG. Copyright © 2014. Published by Elsevier B.V.
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On the nature and evolution of the neural bases of human language
Lieberman, Philip
2002-01-01
The traditional theory equating the brain bases of language with Broca's and Wernicke's neocortical areas is wrong. Neural circuits linking activity in anatomically segregated populations of neurons in subcortical structures and the neocortex throughout the human brain regulate complex behaviors such as walking, talking, and comprehending the meaning of sentences. When we hear or read a word, neural structures involved in the perception or real-world associations of the word are activated as well as posterior cortical regions adjacent to Wernicke's area. Many areas of the neocortex and subcortical structures support the cortical-striatal-cortical circuits that confer complex syntactic ability, speech production, and a large vocabulary. However, many of these structures also form part of the neural circuits regulating other aspects of behavior. For example, the basal ganglia, which regulate motor control, are also crucial elements in the circuits that confer human linguistic ability and abstract reasoning. The cerebellum, traditionally associated with motor control, is active in motor learning. The basal ganglia are also key elements in reward-based learning. Data from studies of Broca's aphasia, Parkinson's disease, hypoxia, focal brain damage, and a genetically transmitted brain anomaly (the putative "language gene," family KE), and from comparative studies of the brains and behavior of other species, demonstrate that the basal ganglia sequence the discrete elements that constitute a complete motor act, syntactic process, or thought process. Imaging studies of intact human subjects and electrophysiologic and tracer studies of the brains and behavior of other species confirm these findings. As Dobzansky put it, "Nothing in biology makes sense except in the light of evolution" (cited in Mayr, 1982). That applies with as much force to the human brain and the neural bases of language as it does to the human foot or jaw. The converse follows: the mark of evolution on
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Neural mechanisms underlying morphine withdrawal in addicted patients: a review
Directory of Open Access Journals (Sweden)
Nima Babhadiashar
2015-06-01
Full Text Available Morphine is one of the most potent alkaloid in opium, which has substantial medical uses and needs and it is the first active principle purified from herbal source. Morphine has commonly been used for relief of moderate to severe pain as it acts directly on the central nervous system; nonetheless, its chronic abuse increases tolerance and physical dependence, which is commonly known as opiate addiction. Morphine withdrawal syndrome is physiological and behavioral symptoms that stem from prolonged exposure to morphine. A majority of brain regions are hypofunctional over prolonged abstinence and acute morphine withdrawal. Furthermore, several neural mechanisms are likely to contribute to morphine withdrawal. The present review summarizes the literature pertaining to neural mechanisms underlying morphine withdrawal. Despite the fact that morphine withdrawal is a complex process, it is suggested that neural mechanisms play key roles in morphine withdrawal.
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Neural responses to macronutrients: hedonic and homeostatic mechanisms.
Tulloch, Alastair J; Murray, Susan; Vaicekonyte, Regina; Avena, Nicole M
2015-05-01
The brain responds to macronutrients via intricate mechanisms. We review how the brain's neural systems implicated in homeostatic control of feeding and hedonic responses are influenced by the ingestion of specific types of food. We discuss how these neural systems are dysregulated in preclinical models of obesity. Findings from these studies can increase our understanding of overeating and, perhaps in some cases, the development of obesity. In addition, a greater understanding of the neural circuits affected by the consumption of specific macronutrients, and by obesity, might lead to new treatments and strategies for preventing unhealthy weight gain. Copyright © 2015 AGA Institute. Published by Elsevier Inc. All rights reserved.
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Wittgenstein running: neural mechanisms of collective intentionality and we-mode.
Becchio, Cristina; Bertone, Cesare
2004-03-01
In this paper we discuss the problem of the neural conditions of shared attitudes and intentions: which neural mechanisms underlie "we-mode" processes or serve as precursors to such processes? Neurophysiological and neuropsychological evidence suggests that in different areas of the brain neural representations are shared by several individuals. This situation, on the one hand, creates a potential problem for correct attribution. On the other hand, it may provide the conditions for shared attitudes and intentions.
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Neural mechanisms of selective attention in the somatosensory system.
Gomez-Ramirez, Manuel; Hysaj, Kristjana; Niebur, Ernst
2016-09-01
Selective attention allows organisms to extract behaviorally relevant information while ignoring distracting stimuli that compete for the limited resources of their central nervous systems. Attention is highly flexible, and it can be harnessed to select information based on sensory modality, within-modality feature(s), spatial location, object identity, and/or temporal properties. In this review, we discuss the body of work devoted to understanding mechanisms of selective attention in the somatosensory system. In particular, we describe the effects of attention on tactile behavior and corresponding neural activity in somatosensory cortex. Our focus is on neural mechanisms that select tactile stimuli based on their location on the body (somatotopic-based attention) or their sensory feature (feature-based attention). We highlight parallels between selection mechanisms in touch and other sensory systems and discuss several putative neural coding schemes employed by cortical populations to signal the behavioral relevance of sensory inputs. Specifically, we contrast the advantages and disadvantages of using a gain vs. spike-spike correlation code for representing attended sensory stimuli. We favor a neural network model of tactile attention that is composed of frontal, parietal, and subcortical areas that controls somatosensory cells encoding the relevant stimulus features to enable preferential processing throughout the somatosensory hierarchy. Our review is based on data from noninvasive electrophysiological and imaging data in humans as well as single-unit recordings in nonhuman primates. Copyright © 2016 the American Physiological Society.
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Neural mechanisms of hypnosis and meditation.
De Benedittis, Giuseppe
2015-12-01
Hypnosis has been an elusive concept for science for a long time. However, the explosive advances in neuroscience in the last few decades have provided a "bridge of understanding" between classical neurophysiological studies and psychophysiological studies. These studies have shed new light on the neural basis of the hypnotic experience. Furthermore, an ambitious new area of research is focusing on mapping the core processes of psychotherapy and the neurobiology/underlying them. Hypnosis research offers powerful techniques to isolate psychological processes in ways that allow their neural bases to be mapped. The Hypnotic Brain can serve as a way to tap neurocognitive questions and our cognitive assays can in turn shed new light on the neural bases of hypnosis. This cross-talk should enhance research and clinical applications. An increasing body of evidence provides insight in the neural mechanisms of the Meditative Brain. Discrete meditative styles are likely to target different neurodynamic patterns. Recent findings emphasize increased attentional resources activating the attentional and salience networks with coherent perception. Cognitive and emotional equanimity gives rise to an eudaimonic state, made of calm, resilience and stability, readiness to express compassion and empathy, a main goal of Buddhist practices. Structural changes in gray matter of key areas of the brain involved in learning processes suggest that these skills can be learned through practice. Hypnosis and Meditation represent two important, historical and influential landmarks of Western and Eastern civilization and culture respectively. Neuroscience has beginning to provide a better understanding of the mechanisms of both Hypnotic and Meditative Brain, outlining similarities but also differences between the two states and processes. It is important not to view either the Eastern or the Western system as superior to the other. Cross-fertilization of the ancient Eastern meditation techniques
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Computer simulations of neural mechanisms explaining upper and lower limb excitatory neural coupling
Directory of Open Access Journals (Sweden)
Ferris Daniel P
2010-12-01
Full Text Available Abstract Background When humans perform rhythmic upper and lower limb locomotor-like movements, there is an excitatory effect of upper limb exertion on lower limb muscle recruitment. To investigate potential neural mechanisms for this behavioral observation, we developed computer simulations modeling interlimb neural pathways among central pattern generators. We hypothesized that enhancement of muscle recruitment from interlimb spinal mechanisms was not sufficient to explain muscle enhancement levels observed in experimental data. Methods We used Matsuoka oscillators for the central pattern generators (CPG and determined parameters that enhanced amplitudes of rhythmic steady state bursts. Potential mechanisms for output enhancement were excitatory and inhibitory sensory feedback gains, excitatory and inhibitory interlimb coupling gains, and coupling geometry. We first simulated the simplest case, a single CPG, and then expanded the model to have two CPGs and lastly four CPGs. In the two and four CPG models, the lower limb CPGs did not receive supraspinal input such that the only mechanisms available for enhancing output were interlimb coupling gains and sensory feedback gains. Results In a two-CPG model with inhibitory sensory feedback gains, only excitatory gains of ipsilateral flexor-extensor/extensor-flexor coupling produced reciprocal upper-lower limb bursts and enhanced output up to 26%. In a two-CPG model with excitatory sensory feedback gains, excitatory gains of contralateral flexor-flexor/extensor-extensor coupling produced reciprocal upper-lower limb bursts and enhanced output up to 100%. However, within a given excitatory sensory feedback gain, enhancement due to excitatory interlimb gains could only reach levels up to 20%. Interconnecting four CPGs to have ipsilateral flexor-extensor/extensor-flexor coupling, contralateral flexor-flexor/extensor-extensor coupling, and bilateral flexor-extensor/extensor-flexor coupling could enhance
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Neural mechanisms of the mind, Aristotle, Zadeh, and fMRI.
Perlovsky, Leonid I
2010-05-01
Processes in the mind: perception, cognition, concepts, instincts, emotions, and higher cognitive abilities for abstract thinking, beautiful music are considered here within a neural modeling fields (NMFs) paradigm. Its fundamental mathematical mechanism is a process "from vague-fuzzy to crisp," called dynamic logic (DL). This paper discusses why this paradigm is necessary mathematically, and relates it to a psychological description of the mind. Surprisingly, the process from "vague to crisp" corresponds to Aristotelian understanding of mental functioning. Recent functional magnetic resonance imaging (fMRI) measurements confirmed this process in neural mechanisms of perception.
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Evolutionary mechanisms that generate morphology and neural-circuit diversity of the cerebellum.
Hibi, Masahiko; Matsuda, Koji; Takeuchi, Miki; Shimizu, Takashi; Murakami, Yasunori
2017-05-01
The cerebellum is derived from the dorsal part of the anterior-most hindbrain. The vertebrate cerebellum contains glutamatergic granule cells (GCs) and gamma-aminobutyric acid (GABA)ergic Purkinje cells (PCs). These cerebellar neurons are generated from neuronal progenitors or neural stem cells by mechanisms that are conserved among vertebrates. However, vertebrate cerebella are widely diverse with respect to their gross morphology and neural circuits. The cerebellum of cyclostomes, the basal vertebrates, has a negligible structure. Cartilaginous fishes have a cerebellum containing GCs, PCs, and deep cerebellar nuclei (DCNs), which include projection neurons. Ray-finned fish lack DCNs but have projection neurons termed eurydendroid cells (ECs) in the vicinity of the PCs. Among ray-finned fishes, the cerebellum of teleost zebrafish has a simple lobular structure, whereas that of weakly electric mormyrid fish is large and foliated. Amniotes, which include mammals, independently evolved a large, foliated cerebellum, which contains massive numbers of GCs and has functional connections with the dorsal telencephalon (neocortex). Recent studies of cyclostomes and cartilaginous fish suggest that the genetic program for cerebellum development was already encoded in the genome of ancestral vertebrates. In this review, we discuss how alterations of the genetic and cellular programs generated diversity of the cerebellum during evolution. © 2017 Japanese Society of Developmental Biologists.
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Benusková, L; Estok, S
1998-11-01
We propose an attractor neural network (ANN) model that performs rotation-invariant pattern recognition in such a way that it can account for a neural mechanism being involved in the image transformation accompanying the experience of mental rotation. We compared the performance of our ANN model with the results of the chronometric psychophysical experiments of Cooper and Shepard (Cooper L A and Shepard R N 1973 Visual Information Processing (New York: Academic) pp 204-7) on discrimination of alphanumeric characters presented in various angular departures from their canonical upright position. Comparing the times required for pattern retrieval in its canonical upright position with the reaction times of human subjects, we found agreement in that (i) retrieval times for clockwise and anticlockwise departures of the same angular magnitude (up to 180 degrees) were not different, (ii) retrieval times increased with departure from upright and (iii) increased more sharply as departure from upright approached 180 degrees. The rotation-invariant retrieval of the activity pattern has been accomplished by means of the modified algorithm of Dotsenko (Dotsenko V S 1988 J. Phys. A: Math. Gen. 21 L783-7) proposed for translation-, rotation- and size-invariant pattern recognition, which uses relaxation of neuronal firing thresholds to guide the evolution of the ANN in state space towards the desired memory attractor. The dynamics of neuronal relaxation has been modified for storage and retrieval of low-activity patterns and the original gradient optimization of threshold dynamics has been replaced with optimization by simulated annealing.
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Sameiro-Barbosa, Catia M; Geiser, Eveline
2016-01-01
The auditory system displays modulations in sensitivity that can align with the temporal structure of the acoustic environment. This sensory entrainment can facilitate sensory perception and is particularly relevant for audition. Systems neuroscience is slowly uncovering the neural mechanisms underlying the behaviorally observed sensory entrainment effects in the human sensory system. The present article summarizes the prominent behavioral effects of sensory entrainment and reviews our current understanding of the neural basis of sensory entrainment, such as synchronized neural oscillations, and potentially, neural activation in the cortico-striatal system.
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Sameiro-Barbosa, Catia M.; Geiser, Eveline
2016-01-01
The auditory system displays modulations in sensitivity that can align with the temporal structure of the acoustic environment. This sensory entrainment can facilitate sensory perception and is particularly relevant for audition. Systems neuroscience is slowly uncovering the neural mechanisms underlying the behaviorally observed sensory entrainment effects in the human sensory system. The present article summarizes the prominent behavioral effects of sensory entrainment and reviews our current understanding of the neural basis of sensory entrainment, such as synchronized neural oscillations, and potentially, neural activation in the cortico-striatal system. PMID:27559306
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Liu, Jinkun
2013-01-01
Radial Basis Function (RBF) Neural Network Control for Mechanical Systems is motivated by the need for systematic design approaches to stable adaptive control system design using neural network approximation-based techniques. The main objectives of the book are to introduce the concrete design methods and MATLAB simulation of stable adaptive RBF neural control strategies. In this book, a broad range of implementable neural network control design methods for mechanical systems are presented, such as robot manipulators, inverted pendulums, single link flexible joint robots, motors, etc. Advanced neural network controller design methods and their stability analysis are explored. The book provides readers with the fundamentals of neural network control system design. This book is intended for the researchers in the fields of neural adaptive control, mechanical systems, Matlab simulation, engineering design, robotics and automation. Jinkun Liu is a professor at Beijing University of Aeronautics and Astronauti...
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Soft tissue deformation modelling through neural dynamics-based reaction-diffusion mechanics.
Zhang, Jinao; Zhong, Yongmin; Gu, Chengfan
2018-05-30
Soft tissue deformation modelling forms the basis of development of surgical simulation, surgical planning and robotic-assisted minimally invasive surgery. This paper presents a new methodology for modelling of soft tissue deformation based on reaction-diffusion mechanics via neural dynamics. The potential energy stored in soft tissues due to a mechanical load to deform tissues away from their rest state is treated as the equivalent transmembrane potential energy, and it is distributed in the tissue masses in the manner of reaction-diffusion propagation of nonlinear electrical waves. The reaction-diffusion propagation of mechanical potential energy and nonrigid mechanics of motion are combined to model soft tissue deformation and its dynamics, both of which are further formulated as the dynamics of cellular neural networks to achieve real-time computational performance. The proposed methodology is implemented with a haptic device for interactive soft tissue deformation with force feedback. Experimental results demonstrate that the proposed methodology exhibits nonlinear force-displacement relationship for nonlinear soft tissue deformation. Homogeneous, anisotropic and heterogeneous soft tissue material properties can be modelled through the inherent physical properties of mass points. Graphical abstract Soft tissue deformation modelling with haptic feedback via neural dynamics-based reaction-diffusion mechanics.
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Vijayraghavan, Deepthi S; Davidson, Lance A
2017-01-30
Neural tube defects arise from mechanical failures in the process of neurulation. At the most fundamental level, formation of the neural tube relies on coordinated, complex tissue movements that mechanically transform the flat neural epithelium into a lumenized epithelial tube (Davidson, 2012). The nature of this mechanical transformation has mystified embryologists, geneticists, and clinicians for more than 100 years. Early embryologists pondered the physical mechanisms that guide this transformation. Detailed observations of cell and tissue movements as well as experimental embryological manipulations allowed researchers to generate and test elementary hypotheses of the intrinsic and extrinsic forces acting on the neural tissue. Current research has turned toward understanding the molecular mechanisms underlying neurulation. Genetic and molecular perturbation have identified a multitude of subcellular components that correlate with cell behaviors and tissue movements during neural tube formation. In this review, we focus on methods and conceptual frameworks that have been applied to the study of amphibian neurulation that can be used to determine how molecular and physical mechanisms are integrated and responsible for neurulation. We will describe how qualitative descriptions and quantitative measurements of strain, force generation, and tissue material properties as well as simulations can be used to understand how embryos use morphogenetic programs to drive neurulation. Birth Defects Research 109:153-168, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
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Potential Mechanisms and Functions of Intermittent Neural Synchronization
Directory of Open Access Journals (Sweden)
Sungwoo Ahn
2017-05-01
Full Text Available Neural synchronization is believed to play an important role in different brain functions. Synchrony in cortical and subcortical circuits is frequently variable in time and not perfect. Few long intervals of desynchronized dynamics may be functionally different from many short desynchronized intervals although the average synchrony may be the same. Recent analysis of imperfect synchrony in different neural systems reported one common feature: neural oscillations may go out of synchrony frequently, but primarily for a short time interval. This study explores potential mechanisms and functional advantages of this short desynchronizations dynamics using computational neuroscience techniques. We show that short desynchronizations are exhibited in coupled neurons if their delayed rectifier potassium current has relatively large values of the voltage-dependent activation time-constant. The delayed activation of potassium current is associated with generation of quickly-rising action potential. This “spikiness” is a very general property of neurons. This may explain why very different neural systems exhibit short desynchronization dynamics. We also show how the distribution of desynchronization durations may be independent of the synchronization strength. Finally, we show that short desynchronization dynamics requires weaker synaptic input to reach a pre-set synchrony level. Thus, this dynamics allows for efficient regulation of synchrony and may promote efficient formation of synchronous neural assemblies.
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A review on mechanical considerations for chronically-implanted neural probes
Lecomte, Aziliz; Descamps, Emeline; Bergaud, Christian
2018-06-01
This review intends to present a comprehensive analysis of the mechanical considerations for chronically-implanted neural probes. Failure of neural electrical recordings or stimulation over time has shown to arise from foreign body reaction and device material stability. It seems that devices that match most closely with the mechanical properties of the brain would be more likely to reduce the mechanical stress at the probe/tissue interface, thus improving body acceptance. The use of low Young’s modulus polymers instead of hard substrates is one way to enhance this mechanical mimetism, though compliance can be achieved through a variety of means. The reduction of probe width and thickness in comparison to a designated length, the use of soft hydrogel coatings and the release in device tethering to the skull, can also improve device compliance. Paradoxically, the more compliant the device, the more likely it will fail during the insertion process in the brain. Strategies have multiplied this past decade to offer partial or temporary stiffness to the device to overcome this buckling effect. A detailed description of the probe insertion mechanisms is provided to analyze potential sources of implantation failure and the need for a mechanically-enhancing structure. This leads us to present an overview of the strategies that have been put in place over the last ten years to overcome buckling issues. Particularly, great emphasis is put on bioresorbable polymers and their assessment for neural applications. Finally, a discussion is provided on some of the key features for the design of mechanically-reliable, polymer-based next generation of chronic neuroprosthetic devices.
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Neural Vascular Mechanism for the Cerebral Blood Flow Autoregulation after Hemorrhagic Stroke
Directory of Open Access Journals (Sweden)
Ming Xiao
2017-01-01
Full Text Available During the initial stages of hemorrhagic stroke, including intracerebral hemorrhage and subarachnoid hemorrhage, the reflex mechanisms are activated to protect cerebral perfusion, but secondary dysfunction of cerebral flow autoregulation will eventually reduce global cerebral blood flow and the delivery of metabolic substrates, leading to generalized cerebral ischemia, hypoxia, and ultimately, neuronal cell death. Cerebral blood flow is controlled by various regulatory mechanisms, including prevailing arterial pressure, intracranial pressure, arterial blood gases, neural activity, and metabolic demand. Evoked by the concept of vascular neural network, the unveiled neural vascular mechanism gains more and more attentions. Astrocyte, neuron, pericyte, endothelium, and so forth are formed as a communicate network to regulate with each other as well as the cerebral blood flow. However, the signaling molecules responsible for this communication between these new players and blood vessels are yet to be definitively confirmed. Recent evidence suggested the pivotal role of transcriptional mechanism, including but not limited to miRNA, lncRNA, exosome, and so forth, for the cerebral blood flow autoregulation. In the present review, we sought to summarize the hemodynamic changes and underline neural vascular mechanism for cerebral blood flow autoregulation in stroke-prone state and after hemorrhagic stroke and hopefully provide more systematic and innovative research interests for the pathophysiology and therapeutic strategies of hemorrhagic stroke.
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Statistical mechanics of attractor neural network models with synaptic depression
International Nuclear Information System (INIS)
Igarashi, Yasuhiko; Oizumi, Masafumi; Otsubo, Yosuke; Nagata, Kenji; Okada, Masato
2009-01-01
Synaptic depression is known to control gain for presynaptic inputs. Since cortical neurons receive thousands of presynaptic inputs, and their outputs are fed into thousands of other neurons, the synaptic depression should influence macroscopic properties of neural networks. We employ simple neural network models to explore the macroscopic effects of synaptic depression. Systems with the synaptic depression cannot be analyzed due to asymmetry of connections with the conventional equilibrium statistical-mechanical approach. Thus, we first propose a microscopic dynamical mean field theory. Next, we derive macroscopic steady state equations and discuss the stabilities of steady states for various types of neural network models.
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Research progress on neural mechanisms of primary insomnia by MRI
Directory of Open Access Journals (Sweden)
Man WANG
2018-04-01
Full Text Available In recent years, more and more researches focused on the neural mechanism of primary insomnia (PI, especially with the development and application of MRI, and researches of brain structure and function related with primary insomnia were more and more in-depth. According to the hyperarousal hypothesis, there are abnormal structure, function and metabolism under certain brain regions of the cortex and subcortex of primary insomnia patients, including amygdala, hippocampus, cingulate gyrus, insular lobe, frontal lobe and parietal lobe. This paper reviewed the research progress of neural mechanisms of primary insomnia by using MRI. DOI: 10.3969/j.issn.1672-6731.2018.03.003
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An Adaptive Neural Mechanism for Acoustic Motion Perception with Varying Sparsity.
Shaikh, Danish; Manoonpong, Poramate
2017-01-01
Biological motion-sensitive neural circuits are quite adept in perceiving the relative motion of a relevant stimulus. Motion perception is a fundamental ability in neural sensory processing and crucial in target tracking tasks. Tracking a stimulus entails the ability to perceive its motion, i.e., extracting information about its direction and velocity. Here we focus on auditory motion perception of sound stimuli, which is poorly understood as compared to its visual counterpart. In earlier work we have developed a bio-inspired neural learning mechanism for acoustic motion perception. The mechanism extracts directional information via a model of the peripheral auditory system of lizards. The mechanism uses only this directional information obtained via specific motor behaviour to learn the angular velocity of unoccluded sound stimuli in motion. In nature however the stimulus being tracked may be occluded by artefacts in the environment, such as an escaping prey momentarily disappearing behind a cover of trees. This article extends the earlier work by presenting a comparative investigation of auditory motion perception for unoccluded and occluded tonal sound stimuli with a frequency of 2.2 kHz in both simulation and practice. Three instances of each stimulus are employed, differing in their movement velocities-0.5°/time step, 1.0°/time step and 1.5°/time step. To validate the approach in practice, we implement the proposed neural mechanism on a wheeled mobile robot and evaluate its performance in auditory tracking.
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The Neural Mechanisms of Re-Experiencing Mental Fatigue Sensation: A Magnetoencephalography Study
Ishii, Akira; Karasuyama, Takuma; Kikuchi, Taiki; Tanaka, Masaaki; Yamano, Emi; Watanabe, Yasuyoshi
2015-01-01
There have been several studies which have tried to clarify the neural mechanisms of fatigue sensation; however fatigue sensation has multiple aspects. We hypothesized that past experience related to fatigue sensation is an important factor which contributes to future formation of fatigue sensation through the transfer to memories that are located within specific brain structures. Therefore, we aimed to investigate the neural mechanisms of fatigue sensation related to memory. In the present s...
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Vestigial preference functions in neural networks and túngara frogs.
Phelps, S. M.; Ryan, M. J.; Rand, A. S.
2001-01-01
Although there is a growing interest in understanding how perceptual mechanisms influence behavioral evolution, few studies have addressed how perception itself is shaped by evolutionary forces. We used a combination of artificial neural network models and behavioral experiments to investigate how evolutionary history influenced the perceptual processes used in mate choice by female túngara frogs. We manipulated the evolutionary history of artificial neural network models and observed an emer...
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Iriki, Atsushi; Taoka, Miki
2012-01-12
Hominin evolution has involved a continuous process of addition of new kinds of cognitive capacity, including those relating to manufacture and use of tools and to the establishment of linguistic faculties. The dramatic expansion of the brain that accompanied additions of new functional areas would have supported such continuous evolution. Extended brain functions would have driven rapid and drastic changes in the hominin ecological niche, which in turn demanded further brain resources to adapt to it. In this way, humans have constructed a novel niche in each of the ecological, cognitive and neural domains, whose interactions accelerated their individual evolution through a process of triadic niche construction. Human higher cognitive activity can therefore be viewed holistically as one component in a terrestrial ecosystem. The brain's functional characteristics seem to play a key role in this triadic interaction. We advance a speculative argument about the origins of its neurobiological mechanisms, as an extension (with wider scope) of the evolutionary principles of adaptive function in the animal nervous system. The brain mechanisms that subserve tool use may bridge the gap between gesture and language--the site of such integration seems to be the parietal and extending opercular cortices.
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Selective attention on representations in working memory: cognitive and neural mechanisms.
Ku, Yixuan
2018-01-01
Selective attention and working memory are inter-dependent core cognitive functions. It is critical to allocate attention on selected targets during the capacity-limited working memory processes to fulfill the goal-directed behavior. The trends of research on both topics are increasing exponentially in recent years, and it is considered that selective attention and working memory share similar underlying neural mechanisms. Different types of attention orientation in working memory are introduced by distinctive cues, and the means using retrospective cues are strengthened currently as it is manipulating the representation in memory, instead of the perceptual representation. The cognitive and neural mechanisms of the retro-cue effects are further reviewed, as well as the potential molecular mechanism. The frontal-parietal network that is involved in both attention and working memory is also the neural candidate for attention orientation during working memory. Neural oscillations in the gamma and alpha/beta oscillations may respectively be employed for the feedforward and feedback information transfer between the sensory cortices and the association cortices. Dopamine and serotonin systems might interact with each other subserving the communication between memory and attention. In conclusion, representations which attention shifts towards are strengthened, while representations which attention moves away from are degraded. Studies on attention orientation during working memory indicates the flexibility of the processes of working memory, and the beneficial way that overcome the limited capacity of working memory.
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Information content of neural networks with self-control and variable activity
International Nuclear Information System (INIS)
Bolle, D.; Amari, S.I.; Dominguez Carreta, D.R.C.; Massolo, G.
2001-01-01
A self-control mechanism for the dynamics of neural networks with variable activity is discussed using a recursive scheme for the time evolution of the local field. It is based upon the introduction of a self-adapting time-dependent threshold as a function of both the neural and pattern activity in the network. This mechanism leads to an improvement of the information content of the network as well as an increase of the storage capacity and the basins of attraction. Different architectures are considered and the results are compared with numerical simulations
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Artificial Neural Network Based Mission Planning Mechanism for Spacecraft
Li, Zhaoyu; Xu, Rui; Cui, Pingyuan; Zhu, Shengying
2018-04-01
The ability to plan and react fast in dynamic space environments is central to intelligent behavior of spacecraft. For space and robotic applications, many planners have been used. But it is difficult to encode the domain knowledge and directly use existing techniques such as heuristic to improve the performance of the application systems. Therefore, regarding planning as an advanced control problem, this paper first proposes an autonomous mission planning and action selection mechanism through a multiple layer perceptron neural network approach to select actions in planning process and improve efficiency. To prove the availability and effectiveness, we use autonomous mission planning problems of the spacecraft, which is a sophisticated system with complex subsystems and constraints as an example. Simulation results have shown that artificial neural networks (ANNs) are usable for planning problems. Compared with the existing planning method in EUROPA, the mechanism using ANNs is more efficient and can guarantee stable performance. Therefore, the mechanism proposed in this paper is more suitable for planning problems of spacecraft that require real time and stability.
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Two distinct neural mechanisms underlying indirect reciprocity.
Watanabe, Takamitsu; Takezawa, Masanori; Nakawake, Yo; Kunimatsu, Akira; Yamasue, Hidenori; Nakamura, Mitsuhiro; Miyashita, Yasushi; Masuda, Naoki
2014-03-18
Cooperation is a hallmark of human society. Humans often cooperate with strangers even if they will not meet each other again. This so-called indirect reciprocity enables large-scale cooperation among nonkin and can occur based on a reputation mechanism or as a succession of pay-it-forward behavior. Here, we provide the functional and anatomical neural evidence for two distinct mechanisms governing the two types of indirect reciprocity. Cooperation occurring as reputation-based reciprocity specifically recruited the precuneus, a region associated with self-centered cognition. During such cooperative behavior, the precuneus was functionally connected with the caudate, a region linking rewards to behavior. Furthermore, the precuneus of a cooperative subject had a strong resting-state functional connectivity (rsFC) with the caudate and a large gray matter volume. In contrast, pay-it-forward reciprocity recruited the anterior insula (AI), a brain region associated with affective empathy. The AI was functionally connected with the caudate during cooperation occurring as pay-it-forward reciprocity, and its gray matter volume and rsFC with the caudate predicted the tendency of such cooperation. The revealed difference is consistent with the existing results of evolutionary game theory: although reputation-based indirect reciprocity robustly evolves as a self-interested behavior in theory, pay-it-forward indirect reciprocity does not on its own. The present study provides neural mechanisms underlying indirect reciprocity and suggests that pay-it-forward reciprocity may not occur as myopic profit maximization but elicit emotional rewards.
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Selective attention on representations in working memory: cognitive and neural mechanisms
Directory of Open Access Journals (Sweden)
Yixuan Ku
2018-04-01
Full Text Available Selective attention and working memory are inter-dependent core cognitive functions. It is critical to allocate attention on selected targets during the capacity-limited working memory processes to fulfill the goal-directed behavior. The trends of research on both topics are increasing exponentially in recent years, and it is considered that selective attention and working memory share similar underlying neural mechanisms. Different types of attention orientation in working memory are introduced by distinctive cues, and the means using retrospective cues are strengthened currently as it is manipulating the representation in memory, instead of the perceptual representation. The cognitive and neural mechanisms of the retro-cue effects are further reviewed, as well as the potential molecular mechanism. The frontal-parietal network that is involved in both attention and working memory is also the neural candidate for attention orientation during working memory. Neural oscillations in the gamma and alpha/beta oscillations may respectively be employed for the feedforward and feedback information transfer between the sensory cortices and the association cortices. Dopamine and serotonin systems might interact with each other subserving the communication between memory and attention. In conclusion, representations which attention shifts towards are strengthened, while representations which attention moves away from are degraded. Studies on attention orientation during working memory indicates the flexibility of the processes of working memory, and the beneficial way that overcome the limited capacity of working memory.
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Chemo-mechanical control of neural stem cell differentiation
Geishecker, Emily R.
Cellular processes such as adhesion, proliferation, and differentiation are controlled in part by cell interactions with the microenvironment. Cells can sense and respond to a variety of stimuli, including soluble and insoluble factors (such as proteins and small molecules) and externally applied mechanical stresses. Mechanical properties of the environment, such as substrate stiffness, have also been suggested to play an important role in cell processes. The roles of both biochemical and mechanical signaling in fate modification of stem cells have been explored independently. However, very few studies have been performed to study well-controlled chemo-mechanotransduction. The objective of this work is to design, synthesize, and characterize a chemo-mechanical substrate to encourage neuronal differentiation of C17.2 neural stem cells. In Chapter 2, Polyacrylamide (PA) gels of varying stiffnesses are functionalized with differing amounts of whole collagen to investigate the role of protein concentration in combination with substrate stiffness. As expected, neurons on the softest substrate were more in number and neuronal morphology than those on stiffer substrates. Neurons appeared locally aligned with an expansive network of neurites. Additional experiments would allow for statistical analysis to determine if and how collagen density impacts C17.2 differentiation in combination with substrate stiffness. Due to difficulties associated with whole protein approaches, a similar platform was developed using mixed adhesive peptides, derived from fibronectin and laminin, and is presented in Chapter 3. The matrix elasticity and peptide concentration can be individually modulated to systematically probe the effects of chemo-mechanical signaling on differentiation of C17.2 cells. Polyacrylamide gel stiffness was confirmed using rheological techniques and found to support values published by Yeung et al. [1]. Cellular growth and differentiation were assessed by cell counts
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Theory of mind in schizophrenia: exploring neural mechanisms of belief attribution.
Lee, Junghee; Quintana, Javier; Nori, Poorang; Green, Michael F
2011-01-01
Although previous behavioral studies have shown that schizophrenia patients have impaired theory of mind (ToM), the neural mechanisms associated with this impairment are poorly understood. This study aimed to identify the neural mechanisms of ToM in schizophrenia, using functional magnetic resonance imaging (fMRI) with a belief attribution task. In the scanner, 12 schizophrenia patients and 13 healthy control subjects performed the belief attribution task with three conditions: a false belief condition, a false photograph condition, and a simple reading condition. For the false belief versus simple reading conditions, schizophrenia patients showed reduced neural activation in areas including the temporoparietal junction (TPJ) and medial prefrontal cortex (MPFC) compared with controls. Further, during the false belief versus false photograph conditions, we observed increased activations in the TPJ and the MPFC in healthy controls, but not in schizophrenia patients. For the false photograph versus simple reading condition, both groups showed comparable neural activations. Schizophrenia patients showed reduced task-related activation in the TPJ and the MPFC during the false belief condition compared with controls, but not for the false photograph condition. This pattern suggests that reduced activation in these regions is associated with, and specific to, impaired ToM in schizophrenia.
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An Adaptive Neural Mechanism with a Lizard Ear Model for Binaural Acoustic Tracking
DEFF Research Database (Denmark)
Shaikh, Danish; Manoonpong, Poramate
2016-01-01
expensive algorithms. We present a novel bioinspired solution to acoustic tracking that uses only two microphones. The system is based on a neural mechanism coupled with a model of the peripheral auditory system of lizards. The peripheral auditory model provides sound direction information which the neural...
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The neural sociometer: brain mechanisms underlying state self-esteem.
Eisenberger, Naomi I; Inagaki, Tristen K; Muscatell, Keely A; Byrne Haltom, Kate E; Leary, Mark R
2011-11-01
On the basis of the importance of social connection for survival, humans may have evolved a "sociometer"-a mechanism that translates perceptions of rejection or acceptance into state self-esteem. Here, we explored the neural underpinnings of the sociometer by examining whether neural regions responsive to rejection or acceptance were associated with state self-esteem. Participants underwent fMRI while viewing feedback words ("interesting," "boring") ostensibly chosen by another individual (confederate) to describe the participant's previously recorded interview. Participants rated their state self-esteem in response to each feedback word. Results demonstrated that greater activity in rejection-related neural regions (dorsal ACC, anterior insula) and mentalizing regions was associated with lower-state self-esteem. Additionally, participants whose self-esteem decreased from prescan to postscan versus those whose self-esteem did not showed greater medial prefrontal cortical activity, previously associated with self-referential processing, in response to negative feedback. Together, the results inform our understanding of the origin and nature of our feelings about ourselves.
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Neural mechanisms of emotional regulation and decision making
Gospic, Katarina
2011-01-01
Emotions influence our perception and decision making. It is of great importance to understand the neurophysiology behind these processes as they influence human core functions. Moreover, knowledge within this field is required in order to develop new medical therapies for pathological conditions that involve dysregulation of emotions. In this thesis the neural mechanisms of emotional regulation and decision making were investigated using different pharmacological manipul...
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Adams, Alyssa; Zenil, Hector; Davies, Paul C W; Walker, Sara Imari
2017-04-20
Open-ended evolution (OEE) is relevant to a variety of biological, artificial and technological systems, but has been challenging to reproduce in silico. Most theoretical efforts focus on key aspects of open-ended evolution as it appears in biology. We recast the problem as a more general one in dynamical systems theory, providing simple criteria for open-ended evolution based on two hallmark features: unbounded evolution and innovation. We define unbounded evolution as patterns that are non-repeating within the expected Poincare recurrence time of an isolated system, and innovation as trajectories not observed in isolated systems. As a case study, we implement novel variants of cellular automata (CA) where the update rules are allowed to vary with time in three alternative ways. Each is capable of generating conditions for open-ended evolution, but vary in their ability to do so. We find that state-dependent dynamics, regarded as a hallmark of life, statistically out-performs other candidate mechanisms, and is the only mechanism to produce open-ended evolution in a scalable manner, essential to the notion of ongoing evolution. This analysis suggests a new framework for unifying mechanisms for generating OEE with features distinctive to life and its artifacts, with broad applicability to biological and artificial systems.
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Neural mechanisms underlying cognitive control of men with lifelong antisocial behavior.
Schiffer, Boris; Pawliczek, Christina; Mu Ller, Bernhard; Forsting, Michael; Gizewski, Elke; Leygraf, Norbert; Hodgins, Sheilagh
2014-04-30
Results of meta-analyses suggested subtle deficits in cognitive control among antisocial individuals. Because almost all studies focused on children with conduct problems or adult psychopaths, however, little is known about cognitive control mechanisms among the majority of persistent violent offenders who present an antisocial personality disorder (ASPD). The present study aimed to determine whether offenders with ASPD, relative to non-offenders, display dysfunction in the neural mechanisms underlying cognitive control and to assess the extent to which these dysfunctions are associated with psychopathic traits and trait impulsivity. Participants comprised 21 violent offenders and 23 non-offenders who underwent event-related functional magnetic resonance imaging while performing a non-verbal Stroop task. The offenders, relative to the non-offenders, exhibited reduced response time interference and a different pattern of conflict- and error-related activity in brain areas involved in cognitive control, attention, language, and emotion processing, that is, the anterior cingulate, dorsolateral prefrontal, superior temporal and postcentral cortices, putamen, thalamus, and amygdala. Moreover, between-group differences in behavioural and neural responses revealed associations with core features of psychopathy and attentional impulsivity. Thus, the results of the present study confirmed the hypothesis that offenders with ASPD display alterations in the neural mechanisms underlying cognitive control and that those alterations relate, at least in part, to personality characteristics. Copyright © 2014. Published by Elsevier Ireland Ltd.
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Elastic Multi-scale Mechanisms: Computation and Biological Evolution.
Diaz Ochoa, Juan G
2018-01-01
Explanations based on low-level interacting elements are valuable and powerful since they contribute to identify the key mechanisms of biological functions. However, many dynamic systems based on low-level interacting elements with unambiguous, finite, and complete information of initial states generate future states that cannot be predicted, implying an increase of complexity and open-ended evolution. Such systems are like Turing machines, that overlap with dynamical systems that cannot halt. We argue that organisms find halting conditions by distorting these mechanisms, creating conditions for a constant creativity that drives evolution. We introduce a modulus of elasticity to measure the changes in these mechanisms in response to changes in the computed environment. We test this concept in a population of predators and predated cells with chemotactic mechanisms and demonstrate how the selection of a given mechanism depends on the entire population. We finally explore this concept in different frameworks and postulate that the identification of predictive mechanisms is only successful with small elasticity modulus.
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Separating monocular and binocular neural mechanisms mediating chromatic contextual interactions.
D'Antona, Anthony D; Christiansen, Jens H; Shevell, Steven K
2014-04-17
When seen in isolation, a light that varies in chromaticity over time is perceived to oscillate in color. Perception of that same time-varying light may be altered by a surrounding light that is also temporally varying in chromaticity. The neural mechanisms that mediate these contextual interactions are the focus of this article. Observers viewed a central test stimulus that varied in chromaticity over time within a larger surround that also varied in chromaticity at the same temporal frequency. Center and surround were presented either to the same eye (monocular condition) or to opposite eyes (dichoptic condition) at the same frequency (3.125, 6.25, or 9.375 Hz). Relative phase between center and surround modulation was varied. In both the monocular and dichoptic conditions, the perceived modulation depth of the central light depended on the relative phase of the surround. A simple model implementing a linear combination of center and surround modulation fit the measurements well. At the lowest temporal frequency (3.125 Hz), the surround's influence was virtually identical for monocular and dichoptic conditions, suggesting that at this frequency, the surround's influence is mediated primarily by a binocular neural mechanism. At higher frequencies, the surround's influence was greater for the monocular condition than for the dichoptic condition, and this difference increased with temporal frequency. Our findings show that two separate neural mechanisms mediate chromatic contextual interactions: one binocular and dominant at lower temporal frequencies and the other monocular and dominant at higher frequencies (6-10 Hz).
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Neural and psychosocial mechanisms of pain sensitivity in fibromyalgia.
English, Brian
2014-06-01
Fibromyalgia is a chronic musculoskeletal pain disorder that affects an estimated 5 million adults in the U.S. The hallmark is burning, searing, tingling, shooting, stabbing, deep aching, or sharp pain. Fibromyalgia is generally considered to be a "central sensitivity syndrome" where central sensitization is regarded as the cause of pain in its own right. Nonetheless, the case continues to be made that all central and spatially distributed peripheral components of fibromyalgia pain would fade if the peripheral generators could be silenced. Although neural mechanisms are clearly important in pain sensitivity, cognitive and social mechanisms also need to be considered. The aim of this review is to examine four mechanisms responsible for heightened pain sensitivity in fibromyalgia: peripheral sensitization, central sensitization, cognitive-emotional sensitization, and interpersonal sensitization. The purpose of framing the review in terms of pain sensitivity in fibromyalgia is to highlight that different mechanisms of sensitization are appropriately regarded as intervening variables when it comes to understanding individual differences in the experience of pain. The paper concludes by considering the implications of the findings of the review for explanations of fibromyalgia pain by nurses working in multidisciplinary teams. The trend appears to be able to explain the cause of fibromyalgia pain in terms of sensitization per se. The recommended alternative is to explain fibromyalgia pain in terms of changes in pain sensitivity and the role of underlying neural and psychosocial mechanisms. Copyright © 2014 American Society for Pain Management Nursing. Published by Elsevier Inc. All rights reserved.
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Neural Mechanisms Underlying Risk and Ambiguity Attitudes.
Blankenstein, Neeltje E; Peper, Jiska S; Crone, Eveline A; van Duijvenvoorde, Anna C K
2017-11-01
Individual differences in attitudes to risk (a taste for risk, known probabilities) and ambiguity (a tolerance for uncertainty, unknown probabilities) differentially influence risky decision-making. However, it is not well understood whether risk and ambiguity are coded differently within individuals. Here, we tested whether individual differences in risk and ambiguity attitudes were reflected in distinct neural correlates during choice and outcome processing of risky and ambiguous gambles. To these ends, we developed a neuroimaging task in which participants ( n = 50) chose between a sure gain and a gamble, which was either risky or ambiguous, and presented decision outcomes (gains, no gains). From a separate task in which the amount, probability, and ambiguity level were varied, we estimated individuals' risk and ambiguity attitudes. Although there was pronounced neural overlap between risky and ambiguous gambling in a network typically related to decision-making under uncertainty, relatively more risk-seeking attitudes were associated with increased activation in valuation regions of the brain (medial and lateral OFC), whereas relatively more ambiguity-seeking attitudes were related to temporal cortex activation. In addition, although striatum activation was observed during reward processing irrespective of a prior risky or ambiguous gamble, reward processing after an ambiguous gamble resulted in enhanced dorsomedial PFC activation, possibly functioning as a general signal of uncertainty coding. These findings suggest that different neural mechanisms reflect individual differences in risk and ambiguity attitudes and that risk and ambiguity may impact overt risk-taking behavior in different ways.
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The mouse that roared: neural mechanisms of social hierarchy.
Wang, Fei; Kessels, Helmut W; Hu, Hailan
2014-11-01
Hierarchical social status greatly influences behavior and health. Human and animal studies have begun to identify the brain regions that are activated during the formation of social hierarchies. They point towards the prefrontal cortex (PFC) as a central regulator, with brain areas upstream of the PFC conveying information about social status, and downstream brain regions executing dominance behavior. This review summarizes our current knowledge on the neural circuits that control social status. We discuss how the neural mechanisms for various types of dominance behavior can be studied in laboratory rodents by selective manipulation of neuronal activity or synaptic plasticity. These studies may help in finding the cause of social stress-related mental and physical health problems. Copyright © 2014 Elsevier Ltd. All rights reserved.
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Distinct Neural Mechanisms Mediate Olfactory Memory Formation at Different Timescales
McNamara, Ann Marie; Magidson, Phillip D.; Linster, Christiane; Wilson, Donald A.; Cleland, Thomas A.
2008-01-01
Habituation is one of the oldest forms of learning, broadly expressed across sensory systems and taxa. Here, we demonstrate that olfactory habituation induced at different timescales (comprising different odor exposure and intertrial interval durations) is mediated by different neural mechanisms. First, the persistence of habituation memory is…
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Music listening after stroke: beneficial effects and potential neural mechanisms.
Särkämö, Teppo; Soto, David
2012-04-01
Music is an enjoyable leisure activity that also engages many emotional, cognitive, and motor processes in the brain. Here, we will first review previous literature on the emotional and cognitive effects of music listening in healthy persons and various clinical groups. Then we will present findings about the short- and long-term effects of music listening on the recovery of cognitive function in stroke patients and the underlying neural mechanisms of these music effects. First, our results indicate that listening to pleasant music can have a short-term facilitating effect on visual awareness in patients with visual neglect, which is associated with functional coupling between emotional and attentional brain regions. Second, daily music listening can improve auditory and verbal memory, focused attention, and mood as well as induce structural gray matter changes in the early poststroke stage. The psychological and neural mechanisms potentially underlying the rehabilitating effect of music after stroke are discussed. © 2012 New York Academy of Sciences.
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International Nuclear Information System (INIS)
Erkaya, Selcuk
2012-01-01
Clearance is inevitable in the joints of mechanisms due primarily to the design, manufacturing and assembly processes or a wear effect. Excessive value of joint clearance plays a crucial role and has a significant effect on the kinematic and dynamic performances of the mechanism. In this study, effects of joint clearances on bearing vibrations of mechanism are investigated. An experimental test rig is set up, and a planar slider-crank mechanism having two imperfect joints with radial clearance is used as a model mechanism. Three accelerometers are positioned at different points to measure the bearing vibrations during the mechanism motion. For the different running speeds and clearance sizes, this work provides a neural model to predict and estimate the bearing vibrations of the mechanical systems having imperfect joints. The results show that radial basis function (RBF) neural network has a superior performance for predicting and estimating the vibration characteristics of the mechanical system
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Neural mechanisms of mindfulness and meditation: Evidence from neuroimaging studies
Institute of Scientific and Technical Information of China (English)
William; R; Marchand
2014-01-01
Mindfulness is the dispassionate,moment-by-moment awareness of sensations,emotions and thoughts.Mindfulness-based interventions are being increasingly used for stress,psychological well being,coping with chronic illness as well as adjunctive treatments for psychiatric disorders.However,the neural mechanisms associated with mindfulness have not been well characterized.Recent functional and structural neuroimaging studies are beginning to provide insights into neural processes associated with the practice of mindfulness.A review of this literature revealed compelling evidence that mindfulness impacts the function of the medial cortex and associated default mode network as well as insula and amygdala.Additionally,mindfulness practice appears to effect lateral frontal regions and basal ganglia,at least in some cases.Structural imaging studies are consistent with these findings and also indicate changes in the hippocampus.While many questions remain unanswered,the current literature provides evidence of brain regions and networks relevant for understanding neural processes associated with mindfulness.
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International Nuclear Information System (INIS)
Dominguez, Manuel
1998-01-01
In the frame of complex systems modelization, we describe in this report the contribution of neural networks to mechanical friction modelization. This thesis is divided in three parts, each one corresponding to every stage of the realized work. The first part takes stock of the properties of neural networks by replacing them in the statistic frame of learning theory (particularly: non-linear and non-parametric regression models) and by showing the existing links with other more 'classic' techniques from automatics. We show then how identification models can be integrated in the neural networks description as a larger nonlinear model class. A methodology of neural networks use have been developed. We focused on validation techniques using correlation functions for non-linear systems, and on the use of regularization methods. The second part deals with the problematic of friction in mechanical systems. Particularly, we present the main current identified physical phenomena, which are integrated in advanced friction modelization. Characterization of these phenomena allows us to state a priori knowledge to be used in the identification stage. We expose some of the most well-known friction models: Dahl's model, Reset Integrator and Canuda's dynamical model, which are then used in simulation studies. The last part links the former one by illustrating a real-world application: an electric jack from SFIM-Industries, used in the Very Large Telescope (VLT) control scheme. This part begins with physical system presentation. The results are compared with more 'classic' methods. We finish using neural networks compensation scheme in closed-loop control. (author) [fr
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Distinct neural mechanisms for body form and body motion discriminations
Vangeneugden, Joris; Peelen, Marius V; Tadin, Duje; Battelli, Lorella
2014-01-01
Actions can be understood based on form cues (e.g., static body posture) as well as motion cues (e.g., gait patterns). A fundamental debate centers on the question of whether the functional and neural mechanisms processing these two types of cues are dissociable. Here, using fMRI, psychophysics, and
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Directory of Open Access Journals (Sweden)
Junta Zeniarja
2015-05-01
Full Text Available Pelanggan merupakan bagian penting dalam memastikan keunggulan dan kelangsungan hidup perusahaan. Oleh karena itu perlu untuk memiliki sistem manajemen untuk memastikan pelanggan tetap setia dan tidak pindah ke pesaing lain, yang dikenal sebagai manajemen churn. Prediksi churn pelanggan adalah bagian dari manajemen churn, yang memprediksi perilaku pelanggan dengan klasifikasi pelanggan setia dan mana yang cenderung pindah ke kompetitor lain. Keakuratan prediksi ini mutlak diperlukan karena tingginya tingkat migrasi pelanggan ke perusahaan pesaing. Hal ini penting karena biaya yang digunakan untuk meraih pelanggan baru jauh lebih tinggi dibandingkan dengan mempertahankan loyalitas pelanggan yang sudah ada. Meskipun banyak studi tentang prediksi churn pelanggan yang telah dilakukan, penelitian lebih lanjut masih diperlukan untuk meningkatkan akurasi prediksi. Penelitian ini akan membahas penggunaan teknik data mining Backpropagation Neural Network (BPNN in hybrid dengan Strategi Evolution (ES untuk atribut bobot. Validasi model dilakukan dengan menggunakan validasi Palang 10-Fold dan evaluasi pengukuran dilakukan dengan menggunakan matriks kebingungan dan Area bawah ROC Curve (AUC. Hasil percobaan menunjukkan bahwa hibrida BPNN dengan ES mencapai kinerja yang lebih baik daripada Basic BPNN. Kata kunci: data mining, churn, prediksi, backpropagation neural network, strategi evolusi.
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Neural mechanisms of reactivation-induced updating that enhance and distort memory.
St Jacques, Peggy L; Olm, Christopher; Schacter, Daniel L
2013-12-03
We remember a considerable number of personal experiences because we are frequently reminded of them, a process known as memory reactivation. Although memory reactivation helps to stabilize and update memories, reactivation may also introduce distortions if novel information becomes incorporated with memory. Here we used functional magnetic resonance imaging (fMRI) to investigate the neural mechanisms mediating reactivation-induced updating in memory for events experienced during a museum tour. During scanning, participants were shown target photographs to reactivate memories from the museum tour followed by a novel lure photograph from an alternate tour. Later, participants were presented with target and lure photographs and asked to determine whether the photographs showed a stop they visited during the tour. We used a subsequent memory analysis to examine neural recruitment during reactivation that was associated with later true and false memories. We predicted that the quality of reactivation, as determined by online ratings of subjective recollection, would increase subsequent true memories but also facilitate incorporation of the lure photograph, thereby increasing subsequent false memories. The fMRI results revealed that the quality of reactivation modulated subsequent true and false memories via recruitment of left posterior parahippocampal, bilateral retrosplenial, and bilateral posterior inferior parietal cortices. However, the timing of neural recruitment and the way in which memories were reactivated contributed to differences in whether memory reactivation led to distortions or not. These data reveal the neural mechanisms recruited during memory reactivation that modify how memories will be subsequently retrieved, supporting the flexible and dynamic aspects of memory.
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Neural Mechanisms and Information Processing in Recognition Systems
Directory of Open Access Journals (Sweden)
Mamiko Ozaki
2014-10-01
Full Text Available Nestmate recognition is a hallmark of social insects. It is based on the match/mismatch of an identity signal carried by members of the society with that of the perceiving individual. While the behavioral response, amicable or aggressive, is very clear, the neural systems underlying recognition are not fully understood. Here we contrast two alternative hypotheses for the neural mechanisms that are responsible for the perception and information processing in recognition. We focus on recognition via chemical signals, as the common modality in social insects. The first, classical, hypothesis states that upon perception of recognition cues by the sensory system the information is passed as is to the antennal lobes and to higher brain centers where the information is deciphered and compared to a neural template. Match or mismatch information is then transferred to some behavior-generating centers where the appropriate response is elicited. An alternative hypothesis, that of “pre-filter mechanism”, posits that the decision as to whether to pass on the information to the central nervous system takes place in the peripheral sensory system. We suggest that, through sensory adaptation, only alien signals are passed on to the brain, specifically to an “aggressive-behavior-switching center”, where the response is generated if the signal is above a certain threshold.
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The evolution of cognitive mechanisms in response to cultural innovations.
Lotem, Arnon; Halpern, Joseph Y; Edelman, Shimon; Kolodny, Oren
2017-07-24
When humans and other animals make cultural innovations, they also change their environment, thereby imposing new selective pressures that can modify their biological traits. For example, there is evidence that dairy farming by humans favored alleles for adult lactose tolerance. Similarly, the invention of cooking possibly affected the evolution of jaw and tooth morphology. However, when it comes to cognitive traits and learning mechanisms, it is much more difficult to determine whether and how their evolution was affected by culture or by their use in cultural transmission. Here we argue that, excluding very recent cultural innovations, the assumption that culture shaped the evolution of cognition is both more parsimonious and more productive than assuming the opposite. In considering how culture shapes cognition, we suggest that a process-level model of cognitive evolution is necessary and offer such a model. The model employs relatively simple coevolving mechanisms of learning and data acquisition that jointly construct a complex network of a type previously shown to be capable of supporting a range of cognitive abilities. The evolution of cognition, and thus the effect of culture on cognitive evolution, is captured through small modifications of these coevolving learning and data-acquisition mechanisms, whose coordinated action is critical for building an effective network. We use the model to show how these mechanisms are likely to evolve in response to cultural phenomena, such as language and tool-making, which are associated with major changes in data patterns and with new computational and statistical challenges.
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Directory of Open Access Journals (Sweden)
Simmons David K
2012-01-01
Full Text Available Abstract Background Nervous systems are thought to be important to the evolutionary success and diversification of metazoans, yet little is known about the origin of simple nervous systems at the base of the animal tree. Recent data suggest that ctenophores, a group of macroscopic pelagic marine invertebrates, are the most ancient group of animals that possess a definitive nervous system consisting of a distributed nerve net and an apical statocyst. This study reports on details of the evolution of the neural cell type specifying transcription factor family of LIM homeobox containing genes (Lhx, which have highly conserved functions in neural specification in bilaterian animals. Results Using next generation sequencing, the first draft of the genome of the ctenophore Mnemiopsis leidyi has been generated. The Lhx genes in all animals are represented by seven subfamilies (Lhx1/5, Lhx3/4, Lmx, Islet, Lhx2/9, Lhx6/8, and LMO of which four were found to be represented in the ctenophore lineage (Lhx1/5, Lhx3/4, Lmx, and Islet. Interestingly, the ctenophore Lhx gene complement is more similar to the sponge complement (sponges do not possess neurons than to either the cnidarian-bilaterian or placozoan Lhx complements. Using whole mount in situ hybridization, the Lhx gene expression patterns were examined and found to be expressed around the blastopore and in cells that give rise to the apical organ and putative neural sensory cells. Conclusion This research gives us a first look at neural cell type specification in the ctenophore M. leidyi. Within M. leidyi, Lhx genes are expressed in overlapping domains within proposed neural cellular and sensory cell territories. These data suggest that Lhx genes likely played a conserved role in the patterning of sensory cells in the ancestor of sponges and ctenophores, and may provide a link to the expression of Lhx orthologs in sponge larval photoreceptive cells. Lhx genes were later co-opted into patterning more
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Mechanisms of adaptive evolution. Darwinism and Lamarckism restated.
Aboitiz, F
1992-07-01
This article discusses the conceptual basis of the different mechanisms of adaptive evolution. It is argued that only two such mechanisms may conceivably exist, Lamarckism and Darwinism. Darwinism is the fundamental process generating the diversity of species. Some aspects of the gene-centered approach to Darwinism are questioned, since they do not account for the generation of biological diversity. Diversity in biological design must be explained in relation to the diversity of interactions of organisms (or other higher-level units) with their environment. This aspect is usually overlooked in gene-centered views of evolution. A variant of the gene-selectionist approach has been proposed to account for the spread of cultural traits in human societies. Alternatively, I argue that social evolution is rather driven by what I call pseudo-Lamarckian inheritance. Finally, I argue that Lamarckian and pseudo-Lamarckian inheritance are just special cases of faithful replication which are found in the development of some higher-order units, such as multicellular organisms and human societies.
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Quantum mechanics formalism for biological evolution
International Nuclear Information System (INIS)
Bianconi, Ginestra; Rahmede, Christoph
2012-01-01
Highlights: ► Biological evolution is an off-equilibrium process described by path integrals over phylogenies. ► The phylogenies are sums of linear lineages for asexual populations. ► For sexual populations, each lineage is a tree and the path integral is given by a sum over these trees. ► Quantum statistics describe the stationary state of biological populations in simple cases. - Abstract: We study the evolution of sexual and asexual populations in fitness landscapes compatible with epistatic interactions. We find intriguing relations between the mathematics of biological evolution and quantum mechanics formalism. We give the general structure of the evolution of sexual and asexual populations which is in general an off-equilibrium process that can be expressed by path integrals over phylogenies. These phylogenies are the sum of linear lineages for asexual populations. For sexual populations, instead, each lineage is a tree of branching ratio two and the path integral describing the evolving population is given by a sum over these trees. Finally we show that the Bose–Einstein and the Fermi–Dirac distributions describe the stationary state of biological populations in simple cases.
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Neural mechanisms of sequence generation in songbirds
Langford, Bruce
Animal models in research are useful for studying more complex behavior. For example, motor sequence generation of actions requiring good muscle coordination such as writing with a pen, playing an instrument, or speaking, may involve the interaction of many areas in the brain, each a complex system in itself; thus it can be difficult to determine causal relationships between neural behavior and the behavior being studied. Birdsong, however, provides an excellent model behavior for motor sequence learning, memory, and generation. The song consists of learned sequences of notes that are spectrographically stereotyped over multiple renditions of the song, similar to syllables in human speech. The main areas of the songbird brain involve in singing are known, however, the mechanisms by which these systems store and produce song are not well understood. We used a custom built, head-mounted, miniature motorized microdrive to chronically record the neural firing patterns of identified neurons in HVC, a pre-motor cortical nucleus which has been shown to be important in song timing. These were done in Bengalese finch which generate a song made up of stereotyped notes but variable note sequences. We observed song related bursting in neurons projecting to Area X, a homologue to basal ganglia, and tonic firing in HVC interneurons. Interneuron had firing rate patterns that were consistent over multiple renditions of the same note sequence. We also designed and built a light-weight, low-powered wireless programmable neural stimulator using Bluetooth Low Energy Protocol. It was able to generate perturbations in the song when current pulses were administered to RA, which projects to the brainstem nucleus responsible for syringeal muscle control.
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Diagnosis of mechanical pumping system using neural networks and system parameters analysis
International Nuclear Information System (INIS)
Tsai, Tai Ming; Wang, Wei Hui
2009-01-01
Normally, a mechanical pumping system is equipped to monitor some of the important input and output signals which are set to the prescribed values. This paper addressed dealing with these signals to establish the database of input- output relation by using a number of neural network models through learning algorithms. These signals encompass normal and abnormal running conditions. The abnormal running conditions were artificially generated. Meanwhile, for the purpose of setting up an on-line diagnosis network, the learning speed and accuracy of three kinds of networks, viz., the backpropagation (BPN), radial basis function (RBF) and adaptive linear (ADALINE) neural networks have been compared and assessed. The assessment criteria of the networks are compared with the correlation result matrix in terms of the neuron vectors. Both BPN and RBF are judged by the maximum vector based on the post-regression analysis, and the ADALINE is judged by the minimum vector based on the least mean square error analysis. By ignoring the neural network training time, it has been shown that if the mechanical diagnosis system is tackled off-line, the RBF method is suggested. However, for on-line diagnosis, the BPN method is recommended
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Diagnosis of mechanical pumping system using neural networks and system parameters analysis
Energy Technology Data Exchange (ETDEWEB)
Tsai, Tai Ming; Wang, Wei Hui [National Taiwan Ocean University, Keelung (China)
2009-01-15
Normally, a mechanical pumping system is equipped to monitor some of the important input and output signals which are set to the prescribed values. This paper addressed dealing with these signals to establish the database of input- output relation by using a number of neural network models through learning algorithms. These signals encompass normal and abnormal running conditions. The abnormal running conditions were artificially generated. Meanwhile, for the purpose of setting up an on-line diagnosis network, the learning speed and accuracy of three kinds of networks, viz., the backpropagation (BPN), radial basis function (RBF) and adaptive linear (ADALINE) neural networks have been compared and assessed. The assessment criteria of the networks are compared with the correlation result matrix in terms of the neuron vectors. Both BPN and RBF are judged by the maximum vector based on the post-regression analysis, and the ADALINE is judged by the minimum vector based on the least mean square error analysis. By ignoring the neural network training time, it has been shown that if the mechanical diagnosis system is tackled off-line, the RBF method is suggested. However, for on-line diagnosis, the BPN method is recommended
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The neural mechanisms of re-experiencing mental fatigue sensation: a magnetoencephalography study.
Directory of Open Access Journals (Sweden)
Akira Ishii
Full Text Available There have been several studies which have tried to clarify the neural mechanisms of fatigue sensation; however fatigue sensation has multiple aspects. We hypothesized that past experience related to fatigue sensation is an important factor which contributes to future formation of fatigue sensation through the transfer to memories that are located within specific brain structures. Therefore, we aimed to investigate the neural mechanisms of fatigue sensation related to memory. In the present study, we investigated the neural activity caused by re-experiencing the fatigue sensation that had been experienced during a fatigue-inducing session. Thirteen healthy volunteers participated in fatigue and non-fatigue experiments in a crossover fashion. In the fatigue experiment, they performed a 2-back test session for 40 min to induce fatigue sensation, a rest session for 15 min to recover from fatigue, and a magnetoencephalography (MEG session in which they were asked to re-experience the state of their body with fatigue that they had experienced in the 2-back test session. In the non-fatigue experiment, the participants performed a free session for 15 min, a rest session for 15 min, and an MEG session in which they were asked to re-experience the state of their body without fatigue that they had experienced in the free session. Spatial filtering analyses of oscillatory brain activity showed that the delta band power in the left Brodmann's area (BA 39, alpha band power in the right pulvinar nucleus and the left BA 40, and beta band power in the left BA 40 were lower when they re-experienced the fatigue sensation than when they re-experienced the fatigue-free sensation, indicating that these brain regions are related to re-experiencing the fatigue sensation. Our findings may help clarify the neural mechanisms underlying fatigue sensation.
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The neural mechanisms of re-experiencing mental fatigue sensation: a magnetoencephalography study.
Ishii, Akira; Karasuyama, Takuma; Kikuchi, Taiki; Tanaka, Masaaki; Yamano, Emi; Watanabe, Yasuyoshi
2015-01-01
There have been several studies which have tried to clarify the neural mechanisms of fatigue sensation; however fatigue sensation has multiple aspects. We hypothesized that past experience related to fatigue sensation is an important factor which contributes to future formation of fatigue sensation through the transfer to memories that are located within specific brain structures. Therefore, we aimed to investigate the neural mechanisms of fatigue sensation related to memory. In the present study, we investigated the neural activity caused by re-experiencing the fatigue sensation that had been experienced during a fatigue-inducing session. Thirteen healthy volunteers participated in fatigue and non-fatigue experiments in a crossover fashion. In the fatigue experiment, they performed a 2-back test session for 40 min to induce fatigue sensation, a rest session for 15 min to recover from fatigue, and a magnetoencephalography (MEG) session in which they were asked to re-experience the state of their body with fatigue that they had experienced in the 2-back test session. In the non-fatigue experiment, the participants performed a free session for 15 min, a rest session for 15 min, and an MEG session in which they were asked to re-experience the state of their body without fatigue that they had experienced in the free session. Spatial filtering analyses of oscillatory brain activity showed that the delta band power in the left Brodmann's area (BA) 39, alpha band power in the right pulvinar nucleus and the left BA 40, and beta band power in the left BA 40 were lower when they re-experienced the fatigue sensation than when they re-experienced the fatigue-free sensation, indicating that these brain regions are related to re-experiencing the fatigue sensation. Our findings may help clarify the neural mechanisms underlying fatigue sensation.
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Why we stay with our social partners: Neural mechanisms of stay/leave decision-making.
Heijne, Amber; Rossi, Filippo; Sanfey, Alan G
2017-09-03
How do we decide to keep interacting (e.g., stay) with a social partner or to switch (e.g., leave) to another? This paper investigated the neural mechanisms of stay/leave decision-making. We hypothesized that these decisions fit within a framework of value-based decision-making, and explored four potential mechanisms underlying a hypothesized bias to stay. Twenty-six participants underwent functional Magnetic Resonance Imaging (fMRI) while completing social and nonsocial versions of a stay/leave decision-making task. On each trial, participants chose between four alternative options, after which they received a monetary reward. Crucially, in the social condition, reward magnitude was ostensibly determined by the generosity of social partners, whereas in the nonsocial condition, reward amounts were ostensibly determined in a pre-programmed manner. Results demonstrated that participants were more likely to stay with options of relatively high expected value, with these values updated through Reinforcement Learning mechanisms and represented neurally within ventromedial prefrontal cortex. Moreover, we demonstrated that greater brain activity in ventromedial prefrontal cortex, caudate nucleus, and septo-hypothalamic regions for social versus nonsocial decisions to stay may underlie a bias towards staying with social partners in particular. These findings complement existing social psychological theories by investigating the neural mechanisms of actual stay/leave decisions.
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SOXE neofunctionalization and elaboration of the neural crest during chordate evolution
Tai, Andrew; Cheung, Martin; Huang, Yong-Heng; Jauch, Ralf; Bronner, Marianne E.; Cheah, Kathryn S. E.
2016-01-01
During chordate evolution, two genome-wide duplications facilitated acquisition of vertebrate traits, including emergence of neural crest cells (NCCs), in which neofunctionalization of the duplicated genes are thought to have facilitated development of craniofacial structures and the peripheral nervous system. How these duplicated genes evolve and acquire the ability to specify NC and their derivatives are largely unknown. Vertebrate SoxE paralogues, most notably Sox9/10, are essential for NC induction, delamination and lineage specification. In contrast, the basal chordate, amphioxus, has a single SoxE gene and lacks NC-like cells. Here, we test the hypothesis that duplication and divergence of an ancestral SoxE gene may have facilitated elaboration of NC lineages. By using an in vivo expression assay to compare effects of AmphiSoxE and vertebrate Sox9 on NC development, we demonstrate that all SOXE proteins possess similar DNA binding and homodimerization properties and can induce NCCs. However, AmphiSOXE is less efficient than SOX9 in transactivation activity and in the ability to preferentially promote glial over neuronal fate, a difference that lies within the combined properties of amino terminal and transactivation domains. We propose that acquisition of AmphiSoxE expression in the neural plate border led to NCC emergence while duplication and divergence produced advantageous mutations in vertebrate homologues, promoting elaboration of NC traits. PMID:27734831
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Neural circuit mechanisms of short-term memory
Goldman, Mark
Memory over time scales of seconds to tens of seconds is thought to be maintained by neural activity that is triggered by a memorized stimulus and persists long after the stimulus is turned off. This presents a challenge to current models of memory-storing mechanisms, because the typical time scales associated with cellular and synaptic dynamics are two orders of magnitude smaller than this. While such long time scales can easily be achieved by bistable processes that toggle like a flip-flop between a baseline and elevated-activity state, many neuronal systems have been observed experimentally to be capable of maintaining a continuum of stable states. For example, in neural integrator networks involved in the accumulation of evidence for decision making and in motor control, individual neurons have been recorded whose activity reflects the mathematical integral of their inputs; in the absence of input, these neurons sustain activity at a level proportional to the running total of their inputs. This represents an analog form of memory whose dynamics can be conceptualized through an energy landscape with a continuum of lowest-energy states. Such continuous attractor landscapes are structurally non-robust, in seeming violation of the relative robustness of biological memory systems. In this talk, I will present and compare different biologically motivated circuit motifs for the accumulation and storage of signals in short-term memory. Challenges to generating robust memory maintenance will be highlighted and potential mechanisms for ameliorating the sensitivity of memory networks to perturbations will be discussed. Funding for this work was provided by NIH R01 MH065034, NSF IIS-1208218, Simons Foundation 324260, and a UC Davis Ophthalmology Research to Prevent Blindness Grant.
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Synaptic energy drives the information processing mechanisms in spiking neural networks.
El Laithy, Karim; Bogdan, Martin
2014-04-01
Flow of energy and free energy minimization underpins almost every aspect of naturally occurring physical mechanisms. Inspired by this fact this work establishes an energy-based framework that spans the multi-scale range of biological neural systems and integrates synaptic dynamic, synchronous spiking activity and neural states into one consistent working paradigm. Following a bottom-up approach, a hypothetical energy function is proposed for dynamic synaptic models based on the theoretical thermodynamic principles and the Hopfield networks. We show that a synapse exposes stable operating points in terms of its excitatory postsynaptic potential as a function of its synaptic strength. We postulate that synapses in a network operating at these stable points can drive this network to an internal state of synchronous firing. The presented analysis is related to the widely investigated temporal coherent activities (cell assemblies) over a certain range of time scales (binding-by-synchrony). This introduces a novel explanation of the observed (poly)synchronous activities within networks regarding the synaptic (coupling) functionality. On a network level the transitions from one firing scheme to the other express discrete sets of neural states. The neural states exist as long as the network sustains the internal synaptic energy.
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Directory of Open Access Journals (Sweden)
Lena eUlm
2015-10-01
Full Text Available Little is known about the neural mechanisms by which transcranial direct current stimulation (tDCS impacts on language processing in post-stroke aphasia. This was addressed in a proof-of-principle study that explored the effects of tDCS application in aphasia during simultaneous functional magnetic resonance imaging (fMRI. We employed a single subject, cross-over, sham-tDCS controlled design and the stimulation was administered to an individualized perilesional stimulation site that was identified by a baseline fMRI scan and a picture naming task. Peak activity during the baseline scan was located in the spared left inferior frontal gyrus (IFG and this area was stimulated during a subsequent cross-over phase. tDCS was successfully administered to the target region and anodal- vs. sham-tDCS resulted in selectively increased activity at the stimulation site. Our results thus demonstrate that it is feasible to precisely target an individualized stimulation site in aphasia patients during simultaneous fMRI which allows assessing the neural mechanisms underlying tDCS application. The functional imaging results of this case report highlight one possible mechanism that may have contributed to beneficial behavioural stimulation effects in previous clinical tDCS trials in aphasia. In the future, this approach will allow identifying distinct patterns of stimulation effects on neural processing in larger cohorts of patients. This may ultimately yield information about the variability of tDCS-effects on brain functions in aphasia.
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Dextran as a fast resorbable and mechanically stiff coating for flexible neural probes
Kil, D.; Brancato, L.; Puers, R.
2017-11-01
In this paper we report on the use of dextran as a temporary, fast dissolving stiff coating for flexible neural probes. Although polymer-based neural implants offer several advantages, compared to their rigid silicon counterparts, they pose significant challenges during implantation. Due to their extreme flexibility, they have the tendency to buckle under the axial load applied during insertion. The structural stiffness of the implants can be temporarily increased by applying a bioresorbable dextran coating which eases the penetration of neural tissue. For this application three types of dextran with different molecular weights are analysed. The dissolution rate of the coatings is reported as well as the increased bending stiffness resulting from the dextran coating of Parylene C neural probes. Based on these findings the dissolution rate can be linked to parameters such as molecular weight, coating thickness and the surface area exposed to the dissolution medium. The mechanical characterization yields information on how the structural stiffness of neural probes can be tuned by varying the dextran’s molecular weight and coating thickness.
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Mechanical basis of morphogenesis and convergent evolution of spiny seashells
Chirat, R.; Moulton, D. E.; Goriely, A.
2013-01-01
Convergent evolution is a phenomenon whereby similar traits evolved independently in not closely related species, and is often interpreted in functional terms. Spines in mollusk seashells are classically interpreted as having repeatedly evolved as a defense in response to shell-crushing predators. Here we consider the morphogenetic process that shapes these structures and underlies their repeated emergence. We develop a mathematical model for spine morphogenesis based on the mechanical interaction between the secreting mantle edge and the calcified shell edge to which the mantle adheres during shell growth. It is demonstrated that a large diversity of spine structures can be accounted for through small variations in control parameters of this natural mechanical process. This physical mechanism suggests that convergent evolution of spines can be understood through a generic morphogenetic process, and provides unique perspectives in understanding the phenotypic evolution of this second largest phylum in the animal kingdom.
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Mechanical basis of morphogenesis and convergent evolution of spiny seashells
Chirat, R.
2013-03-25
Convergent evolution is a phenomenon whereby similar traits evolved independently in not closely related species, and is often interpreted in functional terms. Spines in mollusk seashells are classically interpreted as having repeatedly evolved as a defense in response to shell-crushing predators. Here we consider the morphogenetic process that shapes these structures and underlies their repeated emergence. We develop a mathematical model for spine morphogenesis based on the mechanical interaction between the secreting mantle edge and the calcified shell edge to which the mantle adheres during shell growth. It is demonstrated that a large diversity of spine structures can be accounted for through small variations in control parameters of this natural mechanical process. This physical mechanism suggests that convergent evolution of spines can be understood through a generic morphogenetic process, and provides unique perspectives in understanding the phenotypic evolution of this second largest phylum in the animal kingdom.
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Mechanism of bromine evolution at a graphite electrode
Janssen, L.J.J.; Hoogland, J.G.
1970-01-01
The mechanism of the electrochem. Br evolution at a graphite electrode is elucidated. Br is formed according to the Volmer-Heyrovsky mechanism, the Heyrovsky reaction being the rate-detg. step, Br- -> Brads + e and Br- + Brads -> Br2 + e. For a soln. contg. 4M NaBr, 0.1M Br2, and M H2SO4, the
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Moroz, Leonid L
2015-12-01
The origins of neural systems and centralized brains are one of the major transitions in evolution. These events might occur more than once over 570-600 million years. The convergent evolution of neural circuits is evident from a diversity of unique adaptive strategies implemented by ctenophores, cnidarians, acoels, molluscs, and basal deuterostomes. But, further integration of biodiversity research and neuroscience is required to decipher critical events leading to development of complex integrative and cognitive functions. Here, we outline reference species and interdisciplinary approaches in reconstructing the evolution of nervous systems. In the "omic" era, it is now possible to establish fully functional genomics laboratories aboard of oceanic ships and perform sequencing and real-time analyses of data at any oceanic location (named here as Ship-Seq). In doing so, fragile, rare, cryptic, and planktonic organisms, or even entire marine ecosystems, are becoming accessible directly to experimental and physiological analyses by modern analytical tools. Thus, we are now in a position to take full advantages from countless "experiments" Nature performed for us in the course of 3.5 billion years of biological evolution. Together with progress in computational and comparative genomics, evolutionary neuroscience, proteomic and developmental biology, a new surprising picture is emerging that reveals many ways of how nervous systems evolved. As a result, this symposium provides a unique opportunity to revisit old questions about the origins of biological complexity. © The Author 2015. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.
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Moroz, Leonid L.
2015-01-01
The origins of neural systems and centralized brains are one of the major transitions in evolution. These events might occur more than once over 570–600 million years. The convergent evolution of neural circuits is evident from a diversity of unique adaptive strategies implemented by ctenophores, cnidarians, acoels, molluscs, and basal deuterostomes. But, further integration of biodiversity research and neuroscience is required to decipher critical events leading to development of complex integrative and cognitive functions. Here, we outline reference species and interdisciplinary approaches in reconstructing the evolution of nervous systems. In the “omic” era, it is now possible to establish fully functional genomics laboratories aboard of oceanic ships and perform sequencing and real-time analyses of data at any oceanic location (named here as Ship-Seq). In doing so, fragile, rare, cryptic, and planktonic organisms, or even entire marine ecosystems, are becoming accessible directly to experimental and physiological analyses by modern analytical tools. Thus, we are now in a position to take full advantages from countless “experiments” Nature performed for us in the course of 3.5 billion years of biological evolution. Together with progress in computational and comparative genomics, evolutionary neuroscience, proteomic and developmental biology, a new surprising picture is emerging that reveals many ways of how nervous systems evolved. As a result, this symposium provides a unique opportunity to revisit old questions about the origins of biological complexity. PMID:26163680
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Neural mechanisms of reinforcement learning in unmedicated patients with major depressive disorder.
Rothkirch, Marcus; Tonn, Jonas; Köhler, Stephan; Sterzer, Philipp
2017-04-01
According to current concepts, major depressive disorder is strongly related to dysfunctional neural processing of motivational information, entailing impairments in reinforcement learning. While computational modelling can reveal the precise nature of neural learning signals, it has not been used to study learning-related neural dysfunctions in unmedicated patients with major depressive disorder so far. We thus aimed at comparing the neural coding of reward and punishment prediction errors, representing indicators of neural learning-related processes, between unmedicated patients with major depressive disorder and healthy participants. To this end, a group of unmedicated patients with major depressive disorder (n = 28) and a group of age- and sex-matched healthy control participants (n = 30) completed an instrumental learning task involving monetary gains and losses during functional magnetic resonance imaging. The two groups did not differ in their learning performance. Patients and control participants showed the same level of prediction error-related activity in the ventral striatum and the anterior insula. In contrast, neural coding of reward prediction errors in the medial orbitofrontal cortex was reduced in patients. Moreover, neural reward prediction error signals in the medial orbitofrontal cortex and ventral striatum showed negative correlations with anhedonia severity. Using a standard instrumental learning paradigm we found no evidence for an overall impairment of reinforcement learning in medication-free patients with major depressive disorder. Importantly, however, the attenuated neural coding of reward in the medial orbitofrontal cortex and the relation between anhedonia and reduced reward prediction error-signalling in the medial orbitofrontal cortex and ventral striatum likely reflect an impairment in experiencing pleasure from rewarding events as a key mechanism of anhedonia in major depressive disorder. © The Author (2017). Published by Oxford
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Neural mechanisms underlying social conformity in an ultimatum game
Directory of Open Access Journals (Sweden)
Zhenyu eWei
2013-12-01
Full Text Available When individuals’ actions are incongruent with those of the group they belong to, they may change their initial behavior in order to conform to the group norm. This phenomenon is known as social conformity. In the present study, we used event-related functional magnetic resonance imaging (fMRI to investigate brain activity in response to group opinion during an ultimatum game. Results showed that participants changed their choices when these choices conflicted with the normative opinion of the group they were members of, especially in conditions of unfair treatment. The fMRI data revealed that a conflict with group norms activated the brain regions involved in norm violations and behavioral adjustment. Furthermore, in the reject-unfair condition, we observed that a conflict with group norms activated the medial frontal gyrus. These findings contribute to recent research examining neural mechanisms involved in detecting violations of social norms, and provide information regarding the neural representation of conformity behavior in an economic game.
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Neural Circuit Mechanisms of Social Behavior.
Chen, Patrick; Hong, Weizhe
2018-04-04
We live in a world that is largely socially constructed, and we are constantly involved in and fundamentally influenced by a broad array of complex social interactions. Social behaviors among conspecifics, either conflictive or cooperative, are exhibited by all sexually reproducing animal species and are essential for the health, survival, and reproduction of animals. Conversely, impairment in social function is a prominent feature of several neuropsychiatric disorders, such as autism spectrum disorders and schizophrenia. Despite the importance of social behaviors, many fundamental questions remain unanswered. How is social sensory information processed and integrated in the nervous system? How are different social behavioral decisions selected and modulated in brain circuits? Here we discuss conceptual issues and recent advances in our understanding of brain regions and neural circuit mechanisms underlying the regulation of social behaviors. Copyright © 2018 Elsevier Inc. All rights reserved.
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Stereopsis in animals: evolution, function and mechanisms
Read, Jenny C. A.
2017-01-01
ABSTRACT Stereopsis is the computation of depth information from views acquired simultaneously from different points in space. For many years, stereopsis was thought to be confined to primates and other mammals with front-facing eyes. However, stereopsis has now been demonstrated in many other animals, including lateral-eyed prey mammals, birds, amphibians and invertebrates. The diversity of animals known to have stereo vision allows us to begin to investigate ideas about its evolution and the underlying selective pressures in different animals. It also further prompts the question of whether all animals have evolved essentially the same algorithms to implement stereopsis. If so, this must be the best way to do stereo vision, and should be implemented by engineers in machine stereopsis. Conversely, if animals have evolved a range of stereo algorithms in response to different pressures, that could inspire novel forms of machine stereopsis appropriate for distinct environments, tasks or constraints. As a first step towards addressing these ideas, we here review our current knowledge of stereo vision in animals, with a view towards outlining common principles about the evolution, function and mechanisms of stereo vision across the animal kingdom. We conclude by outlining avenues for future work, including research into possible new mechanisms of stereo vision, with implications for machine vision and the role of stereopsis in the evolution of camouflage. PMID:28724702
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Apoptosis in unicellular organisms: mechanisms and evolution.
Gordeeva, A V; Labas, Y A; Zvyagilskaya, R A
2004-10-01
Data about the programmed death (apoptosis) in unicellular organisms, from bacteria to ciliates, are discussed. Firstly apoptosis appeared in lower eukaryotes, but its mechanisms in these organisms are different from the classical apoptosis. During evolution, the apoptotic process has been improving gradually, with reactive oxygen species and Ca2+ playing an essential role in triggering apoptosis. All eukaryotic organisms have apoptosis inhibitors, which might be introduced by viruses. In the course of evolution, caspases and apoptosis-inducing factor appeared before other apoptotic proteins, with so-called death receptors being the last among them. The functional analogs of eukaryotic apoptotic proteins take parts in the programmed death of bacteria.
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On the Control of Social Approach-Avoidance Behavior: Neural and Endocrine Mechanisms.
Kaldewaij, Reinoud; Koch, Saskia B J; Volman, Inge; Toni, Ivan; Roelofs, Karin
The ability to control our automatic action tendencies is crucial for adequate social interactions. Emotional events trigger automatic approach and avoidance tendencies. Although these actions may be generally adaptive, the capacity to override these emotional reactions may be key to flexible behavior during social interaction. The present chapter provides a review of the neuroendocrine mechanisms underlying this ability and their relation to social psychopathologies. Aberrant social behavior, such as observed in social anxiety or psychopathy, is marked by abnormalities in approach-avoidance tendencies and the ability to control them. Key neural regions involved in the regulation of approach-avoidance behavior are the amygdala, widely implicated in automatic emotional processing, and the anterior prefrontal cortex, which exerts control over the amygdala. Hormones, especially testosterone and cortisol, have been shown to affect approach-avoidance behavior and the associated neural mechanisms. The present chapter also discusses ways to directly influence social approach and avoidance behavior and will end with a research agenda to further advance this important research field. Control over approach-avoidance tendencies may serve as an exemplar of emotional action regulation and might have a great value in understanding the underlying mechanisms of the development of affective disorders.
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Applications of neural networks to mechanics
International Nuclear Information System (INIS)
1997-01-01
Neural networks have become powerful tools in engineer's techniques. The aim of this conference was to present their application to concrete cases in the domain of mechanics, including the preparation and use of materials. Artificial neurons are non-linear organs which provide an output signal that depends on several differently weighted input signals. Their connection into networks allows to solve problems for which the driving laws are not well known. The applications discussed during this conference deal with: the driving of machines or processes, the control of machines, materials or products, the simulation and forecasting, and the optimization. Three papers dealing with the control of spark ignition engines, the regulation of heating floors and the optimization of energy consumptions in industrial buildings were selected for ETDE and one paper dealing with the optimization of the management of a reprocessed plutonium stock was selected for INIS. (J.S.)
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Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks
Rai, Man Mohan
2006-01-01
Genetic and evolutionary algorithms have been applied to solve numerous problems in engineering design where they have been used primarily as optimization procedures. These methods have an advantage over conventional gradient-based search procedures became they are capable of finding global optima of multi-modal functions and searching design spaces with disjoint feasible regions. They are also robust in the presence of noisy data. Another desirable feature of these methods is that they can efficiently use distributed and parallel computing resources since multiple function evaluations (flow simulations in aerodynamics design) can be performed simultaneously and independently on ultiple processors. For these reasons genetic and evolutionary algorithms are being used more frequently in design optimization. Examples include airfoil and wing design and compressor and turbine airfoil design. They are also finding increasing use in multiple-objective and multidisciplinary optimization. This lecture will focus on an evolutionary method that is a relatively new member to the general class of evolutionary methods called differential evolution (DE). This method is easy to use and program and it requires relatively few user-specified constants. These constants are easily determined for a wide class of problems. Fine-tuning the constants will off course yield the solution to the optimization problem at hand more rapidly. DE can be efficiently implemented on parallel computers and can be used for continuous, discrete and mixed discrete/continuous optimization problems. It does not require the objective function to be continuous and is noise tolerant. DE and applications to single and multiple-objective optimization will be included in the presentation and lecture notes. A method for aerodynamic design optimization that is based on neural networks will also be included as a part of this lecture. The method offers advantages over traditional optimization methods. It is more
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Neural mechanisms of social dominance
Watanabe, Noriya; Yamamoto, Miyuki
2015-01-01
In a group setting, individuals' perceptions of their own level of dominance or of the dominance level of others, and the ability to adequately control their behavior based on these perceptions are crucial for living within a social environment. Recent advances in neural imaging and molecular technology have enabled researchers to investigate the neural substrates that support the perception of social dominance and the formation of a social hierarchy in humans. At the systems' level, recent studies showed that dominance perception is represented in broad brain regions which include the amygdala, hippocampus, striatum, and various cortical networks such as the prefrontal, and parietal cortices. Additionally, neurotransmitter systems such as the dopaminergic and serotonergic systems, modulate and are modulated by the formation of the social hierarchy in a group. While these monoamine systems have a wide distribution and multiple functions, it was recently found that the Neuropeptide B/W contributes to the perception of dominance and is present in neurons that have a limited projection primarily to the amygdala. The present review discusses the specific roles of these neural regions and neurotransmitter systems in the perception of dominance and in hierarchy formation. PMID:26136644
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Neural mechanisms of social dominance
Directory of Open Access Journals (Sweden)
Noriya eWatanabe
2015-06-01
Full Text Available In a group setting, individuals’ perceptions of their own level of dominance or of the dominance level of others, and the ability to adequately control their behavior based on these perceptions are crucial for living within a social environment. Recent advances in neural imaging and molecular technology have enabled researchers to investigate the neural substrates that support the perception of social dominance and the formation of a social hierarchy in humans. At the systems’ level, recent studies showed that dominance perception is represented in broad brain regions which include the amygdala, hippocampus, striatum, and various cortical networks such as the prefrontal, and parietal cortices. Additionally, neurotransmitter systems such as the dopaminergic and serotonergic systems, modulate and are modulated by the formation of the social hierarchy in a group. While these monoamine systems have a wide distribution and multiple functions, it was recently found that the Neuropeptide B/W contributes to the perception of dominance and is present in neurons that have a limited projection primarily to the amygdala. The present review discusses the specific roles of these neural regions and neurotransmitter systems in the perception of dominance and in hierarchy formation.
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Homeostasis as the Mechanism of Evolution
Directory of Open Access Journals (Sweden)
John S. Torday
2015-09-01
Full Text Available Homeostasis is conventionally thought of merely as a synchronic (same time servo-mechanism that maintains the status quo for organismal physiology. However, when seen from the perspective of developmental physiology, homeostasis is a robust, dynamic, intergenerational, diachronic (across-time mechanism for the maintenance, perpetuation and modification of physiologic structure and function. The integral relationships generated by cell-cell signaling for the mechanisms of embryogenesis, physiology and repair provide the needed insight to the scale-free universality of the homeostatic principle, offering a novel opportunity for a Systems approach to Biology. Starting with the inception of life itself, with the advent of reproduction during meiosis and mitosis, moving forward both ontogenetically and phylogenetically through the evolutionary steps involved in adaptation to an ever-changing environment, Biology and Evolution Theory need no longer default to teleology.
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Zhang, Lixin; Zhang, Chuncui; He, Feng; Zhao, Xin; Qi, Hongzhi; Wan, Baikun; Ming, Dong
2015-10-01
Fatigue is an exhaustion state caused by prolonged physical work and mental work, which can reduce working efficiency and even cause industrial accidents. Fatigue is a complex concept involving both physiological and psychological factors. Fatigue can cause a decline of concentration and work performance and induce chronic diseases. Prolonged fatigue may endanger life safety. In most of the scenarios, physical and mental workloads co-lead operator into fatigue state. Thus, it is very important to study the interaction influence and its neural mechanisms between physical and mental fatigues. This paper introduces recent progresses on the interaction effects and discusses some research challenges and future development directions. It is believed that mutual influence between physical fatigue and mental fatigue may occur in the central nervous system. Revealing the basal ganglia function and dopamine release may be important to explore the neural mechanisms between physical fatigue and mental fatigue. Future effort is to optimize fatigue models, to evaluate parameters and to explore the neural mechanisms so as to provide scientific basis and theoretical guidance for complex task designs and fatigue monitoring.
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Directory of Open Access Journals (Sweden)
Hong Yang
2015-07-01
Full Text Available Thermally modified wood has high dimensional stability and biological durability.But if the process parameters of thermal modification are not appropriate, then there will be a decline in the physical properties of wood.A neural network algorithm was employed in this study to establish the relationship between the process parameters of high-temperature and high-pressure thermal modification and the mechanical properties of the wood. Three important parameters: temperature, relative humidity, and treatment time, were considered as the inputs to the neural network. Back propagation (BP neural network and radial basis function (RBF neural network models for prediction were built and compared. The comparison showed that the RBF neural network model had advantages in network structure, convergence speed, and generalization capacity. On this basis, the inverse model, reflecting the relationship between the process parameters and the mechanical properties of wood, was established. Given the desired mechanical properties of the wood, the thermal modification process parameters could be inversely optimized and predicted. The results indicated that the model has good learning ability and generalization capacity. This is of great importance for the theoretical and applicational studies of the thermal modification of wood.
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Neural mechanisms of order information processing in working memory
Directory of Open Access Journals (Sweden)
Barbara Dolenc
2013-11-01
Full Text Available The ability to encode and maintain the exact order of short sequences of stimuli or events is often crucial to our ability for effective high-order planning. However, it is not yet clear which neural mechanisms underpin this process. Several studies suggest that in comparison with item recognition temporal order coding activates prefrontal and parietal brain regions. Results of various studies tend to favour the hypothesis that the order of the stimuli is represented and encoded on several stages, from primacy and recency estimates to the exact position of the item in a sequence. Different brain regions play a different role in this process. Dorsolateral prefrontal cortex has a more general role in attention, while the premotor cortex is more involved in the process of information grouping. Parietal lobe and hippocampus also play a significant role in order processing as they enable the representation of distance. Moreover, order maintenance is associated with the existence of neural oscillators that operate at different frequencies. Electrophysiological studies revealed that theta and alpha oscillations play an important role in the maintenance of temporal order information. Those EEG oscillations are differentially associated with processes that support the maintenance of order information and item recognition. Various studies suggest a link between prefrontal areas and memory for temporal order, implying that EEG neural oscillations in the prefrontal cortex may play a role in the maintenance of information on temporal order.
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Nature vs Nurture: Effects of Learning on Evolution
Nagrani, Nagina
In the field of Evolutionary Robotics, the design, development and application of artificial neural networks as controllers have derived their inspiration from biology. Biologists and artificial intelligence researchers are trying to understand the effects of neural network learning during the lifetime of the individuals on evolution of these individuals by qualitative and quantitative analyses. The conclusion of these analyses can help develop optimized artificial neural networks to perform any given task. The purpose of this thesis is to study the effects of learning on evolution. This has been done by applying Temporal Difference Reinforcement Learning methods to the evolution of Artificial Neural Tissue controller. The controller has been assigned the task to collect resources in a designated area in a simulated environment. The performance of the individuals is measured by the amount of resources collected. A comparison has been made between the results obtained by incorporating learning in evolution and evolution alone. The effects of learning parameters: learning rate, training period, discount rate, and policy on evolution have also been studied. It was observed that learning delays the performance of the evolving individuals over the generations. However, the non zero learning rate throughout the evolution process signifies natural selection preferring individuals possessing plasticity.
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International Nuclear Information System (INIS)
Rong Bao; Rui Xiaoting; Tao Ling
2012-01-01
In this paper, a dynamic modeling method and an active vibration control scheme for a smart flexible four-bar linkage mechanism featuring piezoelectric actuators and strain gauge sensors are presented. The dynamics of this smart mechanism is described by the Discrete Time Transfer Matrix Method of Multibody System (MS-DTTMM). Then a nonlinear fuzzy neural network control is employed to suppress the vibration of this smart mechanism. For improving the dynamic performance of the fuzzy neural network, a genetic algorithm based on the MS-DTTMM is designed offline to tune the initial parameters of the fuzzy neural network. The MS-DTTMM avoids the global dynamics equations of the system, which results in the matrices involved are always very small, so the computational efficiency of the dynamic analysis and control system optimization can be greatly improved. Formulations of the method as well as a numerical simulation are given to demonstrate the proposed dynamic method and control scheme.
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Neural mechanisms of interference control in working memory capacity.
Bomyea, Jessica; Taylor, Charles T; Spadoni, Andrea D; Simmons, Alan N
2018-02-01
The extent to which one can use cognitive resources to keep information in working memory is known to rely on (1) active maintenance of target representations and (2) downregulation of interference from irrelevant representations. Neurobiologically, the global capacity of working memory is thought to depend on the prefrontal and parietal cortices; however, the neural mechanisms involved in controlling interference specifically in working memory capacity tasks remain understudied. In this study, 22 healthy participants completed a modified complex working memory capacity task (Reading Span) with trials of varying levels of interference control demands while undergoing functional MRI. Neural activity associated with interference control demands was examined separately during encoding and recall phases of the task. Results suggested a widespread network of regions in the prefrontal, parietal, and occipital cortices, and the cingulate and cerebellum associated with encoding, and parietal and occipital regions associated with recall. Results align with prior findings emphasizing the importance of frontoparietal circuits for working memory performance, including the role of the inferior frontal gyrus, cingulate, occipital cortex, and cerebellum in regulation of interference demands. © 2017 Wiley Periodicals, Inc.
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Fusaro, Robert L.; Jones, Steven P.; Jansen, Ralph
1996-01-01
A complete evaluation of the tribological characteristics of a given material/mechanical system is a time-consuming operation since the friction and wear process is extremely systems sensitive. As a result, experimental designs (i.e., Latin Square, Taguchi) have been implemented in an attempt to not only reduce the total number of experimental combinations needed to fully characterize a material/mechanical system, but also to acquire life data for a system without having to perform an actual life test. Unfortunately, these experimental designs still require a great deal of experimental testing and the output does not always produce meaningful information. In order to further reduce the amount of experimental testing required, this study employs a computer neural network model to investigate different material/mechanical systems. The work focuses on the modeling of the wear behavior, while showing the feasibility of using neural networks to predict life data. The model is capable of defining which input variables will influence the tribological behavior of the particular material/mechanical system being studied based on the specifications of the overall system.
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Artificial neural networks in prediction of mechanical behavior of concrete at high temperature
International Nuclear Information System (INIS)
Mukherjee, A.; Nag Biswas, S.
1997-01-01
The behavior of concrete structures that are exposed to extreme thermo-mechanical loading is an issue of great importance in nuclear engineering. The mechanical behavior of concrete at high temperature is non-linear. The properties that regulate its response are highly temperature dependent and extremely complex. In addition, the constituent materials, e.g. aggregates, influence the response significantly. Attempts have been made to trace the stress-strain curve through mathematical models and rheological models. However, it has been difficult to include all the contributing factors in the mathematical model. This paper examines a new programming paradigm, artificial neural networks, for the problem. Implementing a feedforward network and backpropagation algorithm the stress-strain relationship of the material is captured. The neural networks for the prediction of uniaxial behavior of concrete at high temperature has been presented here. The results of the present investigation are very encouraging. (orig.)
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International Nuclear Information System (INIS)
Reid, S.; Bell, G.E.C.; Edgemon, G.L.
1998-01-01
This paper describes the work undertaken to de-skill the complex procedure of determining corrosion mechanisms derived from electrochemical noise data. The use of neural networks is discussed and applied to the real time generated electrochemical noise data files with the purpose of determining characteristics particular to individual types of corrosion mechanisms. The electrochemical noise signals can have a wide dynamic range and various methods of raw data pre-processing prior to neural network analysis were investigated. Normalized data were ultimately used as input to the final network analysis. Various network schemes were designed, trained and tested. Factors such as the network learning schedule and network design were considered before a final network was implemented to achieve a solution. Neural networks trained using general and localized corrosion data from various material environment systems were used to analyze data from simulated nuclear waste tank environments with favorable results
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Mechanisms of texture evolution during annealing of Zr and Ti alloys
International Nuclear Information System (INIS)
Gerspacher, F.
2007-12-01
Zirconium and Titanium are hexagonal metals. Thus, they have a weaker symmetry than cubic metals, and a stronger crystalline anisotropy. Despite this strong anisotropy, the fundamental mechanisms of the texture evolution of these metals have not been deeply investigated yet. We studied here the texture and microstructure evolution during annealing after several conditions of deformation, and showed that: - slow texture change is expected in grain growth after severe rolling, because of oriented growth - rapid texture change after low reductions is due to oriented nucleation - transverse rolling gives rise to a correlation between orientation and stored energy in the deformed material, which also induces fast texture changes. These mechanisms have been explained on the basis of microstructure specificities. In addition, texture evolution during normal grain growth was studied and the use of modeling allowed to confirm some hypotheses made on boundary mobility anisotropy. The mechanisms of appearance of abnormal grain growth have also been clarified. (author)
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Hamamé, Carlos M; Cosmelli, Diego; Henriquez, Rodrigo; Aboitiz, Francisco
2011-04-26
Humans and other animals change the way they perceive the world due to experience. This process has been labeled as perceptual learning, and implies that adult nervous systems can adaptively modify the way in which they process sensory stimulation. However, the mechanisms by which the brain modifies this capacity have not been sufficiently analyzed. We studied the neural mechanisms of human perceptual learning by combining electroencephalographic (EEG) recordings of brain activity and the assessment of psychophysical performance during training in a visual search task. All participants improved their perceptual performance as reflected by an increase in sensitivity (d') and a decrease in reaction time. The EEG signal was acquired throughout the entire experiment revealing amplitude increments, specific and unspecific to the trained stimulus, in event-related potential (ERP) components N2pc and P3 respectively. P3 unspecific modification can be related to context or task-based learning, while N2pc may be reflecting a more specific attentional-related boosting of target detection. Moreover, bell and U-shaped profiles of oscillatory brain activity in gamma (30-60 Hz) and alpha (8-14 Hz) frequency bands may suggest the existence of two phases for learning acquisition, which can be understood as distinctive optimization mechanisms in stimulus processing. We conclude that there are reorganizations in several neural processes that contribute differently to perceptual learning in a visual search task. We propose an integrative model of neural activity reorganization, whereby perceptual learning takes place as a two-stage phenomenon including perceptual, attentional and contextual processes.
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Directory of Open Access Journals (Sweden)
Bo-Cheng Kuo
Full Text Available Attention is important for effectively comparing incoming perceptual information with the contents of visual short-term memory (VSTM, such that any differences can be detected. However, how attentional mechanisms operate upon these comparison processes remains largely unknown. Here we investigate the underlying neural mechanisms by which attention modulates the comparisons between VSTM and perceptual representations using functional magnetic resonance imaging (fMRI. Participants performed a cued change detection task. Spatial cues were presented to orient their attention either to the location of an item in VSTM prior to its comparison (retro-cues, or simultaneously (simultaneous-cues with the probe array. A no-cue condition was also included. When attention cannot be effectively deployed in advance (i.e. following the simultaneous-cues, we observed a distributed and extensive activation pattern in the prefrontal and parietal cortices in support of successful change detection. This was not the case when participants can deploy their attention in advance (i.e. following the retro-cues. The region-of-interest analyses confirmed that neural responses for successful change detection versus correct rejection in the visual and parietal regions were significantly different for simultaneous-cues compared to retro-cues. Importantly, we found enhanced functional connectivity between prefrontal and parietal cortices when detecting changes on the simultaneous-cue trials. Moreover, we demonstrated a close relationship between this functional connectivity and d' scores. Together, our findings elucidate the attentional and neural mechanisms by which items held in VSTM are compared with incoming perceptual information.
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Shen, Lin; Yang, Weitao
2018-03-13
Direct molecular dynamics (MD) simulation with ab initio quantum mechanical and molecular mechanical (QM/MM) methods is very powerful for studying the mechanism of chemical reactions in a complex environment but also very time-consuming. The computational cost of QM/MM calculations during MD simulations can be reduced significantly using semiempirical QM/MM methods with lower accuracy. To achieve higher accuracy at the ab initio QM/MM level, a correction on the existing semiempirical QM/MM model is an attractive idea. Recently, we reported a neural network (NN) method as QM/MM-NN to predict the potential energy difference between semiempirical and ab initio QM/MM approaches. The high-level results can be obtained using neural network based on semiempirical QM/MM MD simulations, but the lack of direct MD samplings at the ab initio QM/MM level is still a deficiency that limits the applications of QM/MM-NN. In the present paper, we developed a dynamic scheme of QM/MM-NN for direct MD simulations on the NN-predicted potential energy surface to approximate ab initio QM/MM MD. Since some configurations excluded from the database for NN training were encountered during simulations, which may cause some difficulties on MD samplings, an adaptive procedure inspired by the selection scheme reported by Behler [ Behler Int. J. Quantum Chem. 2015 , 115 , 1032 ; Behler Angew. Chem., Int. Ed. 2017 , 56 , 12828 ] was employed with some adaptions to update NN and carry out MD iteratively. We further applied the adaptive QM/MM-NN MD method to the free energy calculation and transition path optimization on chemical reactions in water. The results at the ab initio QM/MM level can be well reproduced using this method after 2-4 iteration cycles. The saving in computational cost is about 2 orders of magnitude. It demonstrates that the QM/MM-NN with direct MD simulations has great potentials not only for the calculation of thermodynamic properties but also for the characterization of
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Mirror neurons and the social nature of language: the neural exploitation hypothesis.
Gallese, Vittorio
2008-01-01
This paper discusses the relevance of the discovery of mirror neurons in monkeys and of the mirror neuron system in humans to a neuroscientific account of primates' social cognition and its evolution. It is proposed that mirror neurons and the functional mechanism they underpin, embodied simulation, can ground within a unitary neurophysiological explanatory framework important aspects of human social cognition. In particular, the main focus is on language, here conceived according to a neurophenomenological perspective, grounding meaning on the social experience of action. A neurophysiological hypothesis--the "neural exploitation hypothesis"--is introduced to explain how key aspects of human social cognition are underpinned by brain mechanisms originally evolved for sensorimotor integration. It is proposed that these mechanisms were later on adapted as new neurofunctional architecture for thought and language, while retaining their original functions as well. By neural exploitation, social cognition and language can be linked to the experiential domain of action.
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Continual and One-Shot Learning Through Neural Networks with Dynamic External Memory
DEFF Research Database (Denmark)
Lüders, Benno; Schläger, Mikkel; Korach, Aleksandra
2017-01-01
it easier to find unused memory location and therefor facilitates the evolution of continual learning networks. Our results suggest that augmenting evolving networks with an external memory component is not only a viable mechanism for adaptive behaviors in neuroevolution but also allows these networks...... a new task is learned. This paper takes a step in overcoming this limitation by building on the recently proposed Evolving Neural Turing Machine (ENTM) approach. In the ENTM, neural networks are augmented with an external memory component that they can write to and read from, which allows them to store...... associations quickly and over long periods of time. The results in this paper demonstrate that the ENTM is able to perform one-shot learning in reinforcement learning tasks without catastrophic forgetting of previously stored associations. Additionally, we introduce a new ENTM default jump mechanism that makes...
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Neural mechanisms of reactivation-induced updating that enhance and distort memory
St. Jacques, Peggy L.; Olm, Christopher; Schacter, Daniel L.
2013-01-01
We remember a considerable number of personal experiences because we are frequently reminded of them, a process known as memory reactivation. Although memory reactivation helps to stabilize and update memories, reactivation may also introduce distortions if novel information becomes incorporated with memory. Here we used functional magnetic resonance imaging (fMRI) to investigate the neural mechanisms mediating reactivation-induced updating in memory for events experienced during a museum tou...
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Consciousness and biological evolution.
Lindahl, B I
1997-08-21
It has been suggested that if the preservation and development of consciousness in the biological evolution is a result of natural selection, it is plausible that consciousness not only has been influenced by neural processes, but has had a survival value itself; and it could only have had this, if it had also been efficacious. This argument for mind-brain interaction is examined, both as the argument has been developed by William James and Karl Popper and as it has been discussed by C.D. Broad. The problem of identifying mental phenomena with certain neural phenomena is also addressed. The main conclusion of the analysis is that an explanation of the evolution of consciousness in Darwinian terms of natural selection does not rule out that consciousness may have evolved as a mere causally inert effect of the evolution of the nervous system, or that mental phenomena are identical with certain neural phenomena. However, the interactionistic theory still seems, more plausible and more fruitful for other reasons brought up in the discussion.
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Fitness landscape complexity and the emergence of modularity in neural networks
Lowell, Jessica
Previous research has shown that the shape of the fitness landscape can affect the evolution of modularity. We evolved neural networks to solve different tasks with different fitness landscapes, using NEAT, a popular neuroevolution algorithm that quantifies similarity between genomes in order to divide them into species. We used this speciation mechanism as a means to examine fitness landscape complexity, and to examine connections between fitness landscape complexity and the emergence of modularity.
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Vloet, Timo D.; Gilsbach, Susanne; Neufang, Susanne; Fink, Gereon R.; Herpertz-Dahlmann, Beate; Konrad, Kerstin
2010-01-01
Objective: Both executive functions and time perception are typically impaired in subjects with attention-deficit/hyperactivity disorder (ADHD). However, the exact neural mechanisms underlying these deficits remain to be investigated. Method: Fourteen subjects with ADHD and 14 age- and IQ-matched controls (aged 9 through 15 years) were assessed…
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Qu, Yang; Telzer, Eva H
2017-01-01
The current research examined whether culture shapes the beliefs, practices, and neural basis of emotion regulation. Twenty-nine American and Chinese participants reported their implicit theory of emotion and frequency of reappraisal use. They also underwent an fMRI scan while completing an emotion regulation task. Chinese (vs. American) participants reported more frequent use of reappraisal, which was mediated by their higher incremental theory of emotion (i.e., believing that emotion is changeable through effort). Although there were some cultural similarities in neural activation during emotion regulation, Chinese participants showed less ventrolateral prefrontal cortex (VLPFC) activation than American participants when regulating negative emotions. Lower VLPFC activation was associated with higher incremental theory of emotion and more frequent use of cognitive reappraisal. Findings suggest that culture may shape how individuals perceive and engage in emotion regulation, and ultimately, the neural mechanisms underlying emotion regulation. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
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Effects and mechanisms of melatonin on neural differentiation of induced pluripotent stem cells.
Shu, Tao; Wu, Tao; Pang, Mao; Liu, Chang; Wang, Xuan; Wang, Juan; Liu, Bin; Rong, Limin
2016-06-03
Melatonin, a lipophilic molecule mainly synthesized in the pineal gland, has properties of antioxidation, anti-inflammation, and antiapoptosis to improve neuroprotective functions. Here, we investigate effects and mechanisms of melatonin on neural differentiation of induced pluripotent stem cells (iPSCs). iPSCs were induced into neural stem cells (NSCs), then further differentiated into neurons in medium with or without melatonin, melatonin receptor antagonist (Luzindole) or Phosphatidylinositide 3 kinase (PI3K) inhibitor (LY294002). Melatonin significantly promoted the number of neurospheres and cell viability. In addition, Melatonin markedly up-regulated gene and protein expression of Nestin and MAP2. However, Luzindole or LY294002 attenuated these increase. The expression of pAKT/AKT were increased by Melatonin, while Luzindole or LY294002 declined these melatonin-induced increase. These results suggest that melatonin significantly increased neural differentiation of iPSCs via activating PI3K/AKT signaling pathway through melatonin receptor. Copyright © 2016 Elsevier Inc. All rights reserved.
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Modeling mechanical properties of cast aluminum alloy using artificial neural network
International Nuclear Information System (INIS)
Jokhio, M.H.; Panhwar, M.I.
2009-01-01
Modeling is widely used to investigate the mechanical properties of engineering materials due to increasing demand of low cost and high strength to weight ratio for many engineering applications. The aluminum casting alloys are cost competitive material and possess the desired properties. The mechanical properties largely depend upon composition of alloys and their processing method. Alloy design involves controlling mechanical properties via optimization of the composition and processing parameters. For optimization the possible root is empirical modeling and its more refined version is the analysis of the wide range of data using ANN (Artificial Neural Networks) modeling. The modeling of mechanical properties of the aluminum alloys are the main objective of present work. For this purpose, some data were collected and experimentally prepared using conventional casting method. A MLP (Multilayer Perceptron) network was developed, which is trained by using the error back propagation algorithm. (author)
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Neutron spectrometry and dosimetry by means of evolutive neural networks
International Nuclear Information System (INIS)
Ortiz R, J.M.; Martinez B, M.R.; Vega C, H.R.
2008-01-01
The artificial neural networks and the genetic algorithms are two relatively new areas of research, which have been subject to a growing interest during the last years. Both models are inspired by the nature, however, the neural networks are interested in the learning of a single individual, which is defined as fenotypic learning, while the evolutionary algorithms are interested in the adaptation of a population to a changing environment, that which is defined as genotypic learning. Recently, the use of the technology of neural networks has been applied with success in the area of the nuclear sciences, mainly in the areas of neutron spectrometry and dosimetry. The structure (network topology), as well as the learning parameters of a neural network, are factors that contribute in a significant way with the acting of the same one, however, it has been observed that the investigators in this area, carry out the selection of the network parameters through the essay and error technique, that which produces neural networks of poor performance and low generalization capacity. From the revised sources, it has been observed that the use of the evolutionary algorithms, seen as search techniques, it has allowed him to be possible to evolve and to optimize different properties of the neural networks, just as the initialization of the synaptic weights, the network architecture or the training algorithms without the human intervention. The objective of the present work is focused in analyzing the intersection of the neural networks and the evolutionary algorithms, analyzing like it is that the same ones can be used to help in the design processes and training of a neural network, this is, in the good selection of the structural parameters and of network learning, improving its generalization capacity, in such way that the same one is able to reconstruct in an efficient way neutron spectra and to calculate equivalent doses starting from the counting rates of a Bonner sphere
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Statistical mechanics and the evolution of polygenic quantitative traits
Barton, N.H.; De Vladar, H.P.
The evolution of quantitative characters depends on the frequencies of the alleles involved, yet these frequencies cannot usually be measured. Previous groups have proposed an approximation to the dynamics of quantitative traits, based on an analogy with statistical mechanics. We present a modified
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Diversity and evolution of drug resistance mechanisms in Mycobacterium tuberculosis
Directory of Open Access Journals (Sweden)
Al-Saeedi M
2017-10-01
Full Text Available Mashael Al-Saeedi, Sahal Al-Hajoj Department of Infection and Immunity, Mycobacteriology Research Section, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia Abstract: Despite the efficacy of antibiotics to protect humankind against many deadly pathogens, such as Mycobacterium tuberculosis, nothing can prevent the emergence of drug-resistant strains. Several mechanisms facilitate drug resistance in M. tuberculosis including compensatory evolution, epistasis, clonal interference, cell wall integrity, efflux pumps, and target mimicry. In this study, we present recent findings relevant to these mechanisms, which can enable the discovery of new drug targets and subsequent development of novel drugs for treatment of drug-resistant M. tuberculosis. Keywords: Mycobacterium tuberculosis, antibiotic resistance, compensatory evolution, epistasis, efflux pumps, fitness cost
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Quantum information and the problem of mechanisms of biological evolution.
Melkikh, Alexey V
2014-01-01
One of the most important conditions for replication in early evolution is the de facto elimination of the conformational degrees of freedom of the replicators, the mechanisms of which remain unclear. In addition, realistic evolutionary timescales can be established based only on partially directed evolution, further complicating this issue. A division of the various evolutionary theories into two classes has been proposed based on the presence or absence of a priori information about the evolving system. A priori information plays a key role in solving problems in evolution. Here, a model of partially directed evolution, based on the learning automata theory, which includes a priori information about the fitness space, is proposed. A potential repository of such prior information is the states of biologically important molecules. Thus, the need for extended evolutionary synthesis is discussed. Experiments to test the hypothesis of partially directed evolution are proposed. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
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Saltatory Evolution of the Ectodermal Neural Cortex Gene Family at the Vertebrate Origin
Feiner, Nathalie; Murakami, Yasunori; Breithut, Lisa; Mazan, Sylvie; Meyer, Axel; Kuraku, Shigehiro
2013-01-01
The ectodermal neural cortex (ENC) gene family, whose members are implicated in neurogenesis, is part of the kelch repeat superfamily. To date, ENC genes have been identified only in osteichthyans, although other kelch repeat-containing genes are prevalent throughout bilaterians. The lack of elaborate molecular phylogenetic analysis with exhaustive taxon sampling has obscured the possible link of the establishment of this gene family with vertebrate novelties. In this study, we identified ENC homologs in diverse vertebrates by means of database mining and polymerase chain reaction screens. Our analysis revealed that the ENC3 ortholog was lost in the basal eutherian lineage through single-gene deletion and that the triplication between ENC1, -2, and -3 occurred early in vertebrate evolution. Including our original data on the catshark and the zebrafish, our comparison revealed high conservation of the pleiotropic expression pattern of ENC1 and shuffling of expression domains between ENC1, -2, and -3. Compared with many other gene families including developmental key regulators, the ENC gene family is unique in that conventional molecular phylogenetic inference could identify no obvious invertebrate ortholog. This suggests a composite nature of the vertebrate-specific gene repertoire, consisting not only of de novo genes introduced at the vertebrate origin but also of long-standing genes with no apparent invertebrate orthologs. Some of the latter, including the ENC gene family, may be too rapidly evolving to provide sufficient phylogenetic signals marking orthology to their invertebrate counterparts. Such gene families that experienced saltatory evolution likely remain to be explored and might also have contributed to phenotypic evolution of vertebrates. PMID:23843192
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Evolution: from cosmogenesis to biogenesis
International Nuclear Information System (INIS)
Lukacs, B.; Berczi, Sz.; Molnar, I.; Paal, G.
1990-11-01
The volume contains the material of an interdisciplinary evolution symposium. The purpose was to shed some light on possible connections between steps of evolution of matter on different levels of organisation. The topics involved are as follow: cosmogenesis; galactic and stellar evolution; formation and evolution of the solar system; global atmospheric and tectonic changes of Earth; viral evolution; phylogeny and evolution of terrestrial life; evolution of neural system; hominization. The material also includes some discussions of the underlying phenomena and laws of nature. (author)
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Neural mechanisms tracking popularity in real-world social networks.
Zerubavel, Noam; Bearman, Peter S; Weber, Jochen; Ochsner, Kevin N
2015-12-08
Differences in popularity are a key aspect of status in virtually all human groups and shape social interactions within them. Little is known, however, about how we track and neurally represent others' popularity. We addressed this question in two real-world social networks using sociometric methods to quantify popularity. Each group member (perceiver) viewed faces of every other group member (target) while whole-brain functional MRI data were collected. Independent functional localizer tasks were used to identify brain systems supporting affective valuation (ventromedial prefrontal cortex, ventral striatum, amygdala) and social cognition (dorsomedial prefrontal cortex, precuneus, temporoparietal junction), respectively. During the face-viewing task, activity in both types of neural systems tracked targets' sociometric popularity, even when controlling for potential confounds. The target popularity-social cognition system relationship was mediated by valuation system activity, suggesting that observing popular individuals elicits value signals that facilitate understanding their mental states. The target popularity-valuation system relationship was strongest for popular perceivers, suggesting enhanced sensitivity to differences among other group members' popularity. Popular group members also demonstrated greater interpersonal sensitivity by more accurately predicting how their own personalities were perceived by other individuals in the social network. These data offer insights into the mechanisms by which status guides social behavior.
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[Neurally adjusted ventilatory assist (NAVA). A new mode of assisted mechanical ventilation].
Moerer, O; Barwing, J; Quintel, M
2008-10-01
The aim of mechanical ventilation is to assure gas exchange while efficiently unloading the respiratory muscles and mechanical ventilation is an integral part of the care of patients with acute respiratory failure. Modern lung protective strategies of mechanical ventilation include low-tidal-volume ventilation and the continuation of spontaneous breathing which has been shown to be beneficial in reducing atelectasis and improving oxygenation. Poor patient-ventilator interaction is a major issue during conventional assisted ventilation. Neurally adjusted ventilator assist (NAVA) is a new mode of mechanical ventilation that uses the electrical activity of the diaphragm (EAdi) to control the ventilator. First experimental studies showed an improved patient-ventilator synchrony and an efficient unloading of the respiratory muscles. Future clinical studies will have to show that NAVA is of clinical advantage when compared to conventional modes of assisted mechanical ventilation. This review characterizes NAVA according to current publications on this topic.
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Potential psychological & neural mechanisms in binge eating disorder: Implications for treatment.
Kober, Hedy; Boswell, Rebecca G
2018-03-01
Binge Eating Disorder (BED) is a newly-established eating disorder diagnosis in the 5th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Although systematic research on BED is in its infancy and many studies feature small samples, several observations emerge. First, we review diagnostic, developmental, and socio-demographic features of BED. Next, although BED and obesity are linked and frequently co-occur, we review data suggesting that BED is a distinct phenotype. Importantly, we take a mechanism-focused approach and propose four psychological processes with neurobiological bases that may uniquely differentiate BED from obesity: emotion reactivity, food-cue reactivity, food craving, and cognitive control. Further, we propose that interactions between impairments in cognitive control and increased emotional reactivity, food-cue reactivity, and craving may underlie emotion dysregulation and promote binge eating. Consistently, neuroimaging studies point towards neural alterations in the response to rewards and to food specifically, and suggest preliminary links between impaired cognitive-control-related neural activity and binge eating. However, additional systematic work is required in this area. We conclude with a detailed review of treatment approaches to BED; specifically, we suggest that psychological and pharmacological treatments that target core mechanisms - including cognitive control and emotion/craving dysregulation - may be particularly effective. Copyright © 2018 Elsevier Ltd. All rights reserved.
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Neural mechanisms linking social status and inflammatory responses to social stress.
Muscatell, Keely A; Dedovic, Katarina; Slavich, George M; Jarcho, Michael R; Breen, Elizabeth C; Bower, Julienne E; Irwin, Michael R; Eisenberger, Naomi I
2016-06-01
Social stratification has important implications for health and well-being, with individuals lower in standing in a hierarchy experiencing worse outcomes than those higher up the social ladder. Separate lines of past research suggest that alterations in inflammatory processes and neural responses to threat may link lower social status with poorer outcomes. This study was designed to bridge these literatures to investigate the neurocognitive mechanisms linking subjective social status and inflammation. Thirty-one participants reported their subjective social status, and underwent a functional magnetic resonance imaging scan while they were socially evaluated. Participants also provided blood samples before and after the stressor, which were analysed for changes in inflammation. Results showed that lower subjective social status was associated with greater increases in inflammation. Neuroimaging data revealed lower subjective social status was associated with greater neural activity in the dorsomedial prefrontal cortex (DMPFC) in response to negative feedback. Finally, results indicated that activation in the DMPFC in response to negative feedback mediated the relation between social status and increases in inflammatory activity. This study provides the first evidence of a neurocognitive pathway linking subjective social status and inflammation, thus furthering our understanding of how social hierarchies shape neural and physiological responses to social interactions. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
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Neural fields theory and applications
Graben, Peter; Potthast, Roland; Wright, James
2014-01-01
With this book, the editors present the first comprehensive collection in neural field studies, authored by leading scientists in the field - among them are two of the founding-fathers of neural field theory. Up to now, research results in the field have been disseminated across a number of distinct journals from mathematics, computational neuroscience, biophysics, cognitive science and others. Starting with a tutorial for novices in neural field studies, the book comprises chapters on emergent patterns, their phase transitions and evolution, on stochastic approaches, cortical development, cognition, robotics and computation, large-scale numerical simulations, the coupling of neural fields to the electroencephalogram and phase transitions in anesthesia. The intended readership are students and scientists in applied mathematics, theoretical physics, theoretical biology, and computational neuroscience. Neural field theory and its applications have a long-standing tradition in the mathematical and computational ...
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Neural mechanisms underlying human consensus decision-making.
Suzuki, Shinsuke; Adachi, Ryo; Dunne, Simon; Bossaerts, Peter; O'Doherty, John P
2015-04-22
Consensus building in a group is a hallmark of animal societies, yet little is known about its underlying computational and neural mechanisms. Here, we applied a computational framework to behavioral and fMRI data from human participants performing a consensus decision-making task with up to five other participants. We found that participants reached consensus decisions through integrating their own preferences with information about the majority group members' prior choices, as well as inferences about how much each option was stuck to by the other people. These distinct decision variables were separately encoded in distinct brain areas-the ventromedial prefrontal cortex, posterior superior temporal sulcus/temporoparietal junction, and intraparietal sulcus-and were integrated in the dorsal anterior cingulate cortex. Our findings provide support for a theoretical account in which collective decisions are made through integrating multiple types of inference about oneself, others, and environments, processed in distinct brain modules. Copyright © 2015 Elsevier Inc. All rights reserved.
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Mechanisms and Neural Basis of Object and Pattern Recognition: A Study with Chess Experts
Bilalic, Merim; Langner, Robert; Erb, Michael; Grodd, Wolfgang
2010-01-01
Comparing experts with novices offers unique insights into the functioning of cognition, based on the maximization of individual differences. Here we used this expertise approach to disentangle the mechanisms and neural basis behind two processes that contribute to everyday expertise: object and pattern recognition. We compared chess experts and…
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Basic processes and mechanisms of the water-rock system evolution
Shvartsev, Stepan Lvovich
2007-01-01
A new conception of progressive evolution and self-organizing presence in dead matter is developed; inner mechanisms and processes, realizing this development, are revealed. It is proven that the water-rock system satisfy these requirements
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Ahmadi, Bahman; Nariman-zadeh, Nader; Jamali, Ali
2017-06-01
In this article, a novel approach based on game theory is presented for multi-objective optimal synthesis of four-bar mechanisms. The multi-objective optimization problem is modelled as a Stackelberg game. The more important objective function, tracking error, is considered as the leader, and the other objective function, deviation of the transmission angle from 90° (TA), is considered as the follower. In a new approach, a group method of data handling (GMDH)-type neural network is also utilized to construct an approximate model for the rational reaction set (RRS) of the follower. Using the proposed game-theoretic approach, the multi-objective optimal synthesis of a four-bar mechanism is then cast into a single-objective optimal synthesis using the leader variables and the obtained RRS of the follower. The superiority of using the synergy game-theoretic method of Stackelberg with a GMDH-type neural network is demonstrated for two case studies on the synthesis of four-bar mechanisms.
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Neural Mechanisms Underlying the Cost of Task Switching: An ERP Study
Li, Ling; Wang, Meng; Zhao, Qian-Jing; Fogelson, Noa
2012-01-01
Background When switching from one task to a new one, reaction times are prolonged. This phenomenon is called switch cost (SC). Researchers have recently used several kinds of task-switching paradigms to uncover neural mechanisms underlying the SC. Task-set reconfiguration and passive dissipation of a previously relevant task-set have been reported to contribute to the cost of task switching. Methodology/Principal Findings An unpredictable cued task-switching paradigm was used, during which subjects were instructed to switch between a color and an orientation discrimination task. Electroencephalography (EEG) and behavioral measures were recorded in 14 subjects. Response-stimulus interval (RSI) and cue-stimulus interval (CSI) were manipulated with short and long intervals, respectively. Switch trials delayed reaction times (RTs) and increased error rates compared with repeat trials. The SC of RTs was smaller in the long CSI condition. For cue-locked waveforms, switch trials generated a larger parietal positive event-related potential (ERP), and a larger slow parietal positivity compared with repeat trials in the short and long CSI condition. Neural SC of cue-related ERP positivity was smaller in the long RSI condition. For stimulus-locked waveforms, a larger switch-related central negative ERP component was observed, and the neural SC of the ERP negativity was smaller in the long CSI. Results of standardized low resolution electromagnetic tomography (sLORETA) for both ERP positivity and negativity showed that switch trials evoked larger activation than repeat trials in dorsolateral prefrontal cortex (DLPFC) and posterior parietal cortex (PPC). Conclusions/Significance The results provide evidence that both RSI and CSI modulate the neural activities in the process of task-switching, but that these have a differential role during task-set reconfiguration and passive dissipation of a previously relevant task-set. PMID:22860090
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Neural mechanisms underlying the cost of task switching: an ERP study.
Directory of Open Access Journals (Sweden)
Ling Li
Full Text Available BACKGROUND: When switching from one task to a new one, reaction times are prolonged. This phenomenon is called switch cost (SC. Researchers have recently used several kinds of task-switching paradigms to uncover neural mechanisms underlying the SC. Task-set reconfiguration and passive dissipation of a previously relevant task-set have been reported to contribute to the cost of task switching. METHODOLOGY/PRINCIPAL FINDINGS: An unpredictable cued task-switching paradigm was used, during which subjects were instructed to switch between a color and an orientation discrimination task. Electroencephalography (EEG and behavioral measures were recorded in 14 subjects. Response-stimulus interval (RSI and cue-stimulus interval (CSI were manipulated with short and long intervals, respectively. Switch trials delayed reaction times (RTs and increased error rates compared with repeat trials. The SC of RTs was smaller in the long CSI condition. For cue-locked waveforms, switch trials generated a larger parietal positive event-related potential (ERP, and a larger slow parietal positivity compared with repeat trials in the short and long CSI condition. Neural SC of cue-related ERP positivity was smaller in the long RSI condition. For stimulus-locked waveforms, a larger switch-related central negative ERP component was observed, and the neural SC of the ERP negativity was smaller in the long CSI. Results of standardized low resolution electromagnetic tomography (sLORETA for both ERP positivity and negativity showed that switch trials evoked larger activation than repeat trials in dorsolateral prefrontal cortex (DLPFC and posterior parietal cortex (PPC. CONCLUSIONS/SIGNIFICANCE: The results provide evidence that both RSI and CSI modulate the neural activities in the process of task-switching, but that these have a differential role during task-set reconfiguration and passive dissipation of a previously relevant task-set.
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Neural Mechanisms of Encoding Social and Non-Social Context Information in Autism Spectrum Disorder
Greimel, Ellen; Nehrkorn, Barbara; Fink, Gereon R.; Kukolja, Juraj; Kohls, Gregor; Muller, Kristin; Piefke, Martina; Kamp-Becker, Inge; Remschmidt, Helmut; Herpertz-Dahlmann, Beate; Konrad, Kerstin; Schulte-Ruther, Martin
2012-01-01
Individuals with autism spectrum disorder (ASD) often fail to attach context to their memories and are specifically impaired in processing social aspects of contextual information. The aim of the present study was to investigate the modulatory influence of social vs. non-social context on neural mechanisms during encoding in ASD. Using…
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Handedness is related to neural mechanisms underlying hemispheric lateralization of face processing
Frässle, Stefan; Krach, Sören; Paulus, Frieder Michel; Jansen, Andreas
2016-06-01
While the right-hemispheric lateralization of the face perception network is well established, recent evidence suggests that handedness affects the cerebral lateralization of face processing at the hierarchical level of the fusiform face area (FFA). However, the neural mechanisms underlying differential hemispheric lateralization of face perception in right- and left-handers are largely unknown. Using dynamic causal modeling (DCM) for fMRI, we aimed to unravel the putative processes that mediate handedness-related differences by investigating the effective connectivity in the bilateral core face perception network. Our results reveal an enhanced recruitment of the left FFA in left-handers compared to right-handers, as evidenced by more pronounced face-specific modulatory influences on both intra- and interhemispheric connections. As structural and physiological correlates of handedness-related differences in face processing, right- and left-handers varied with regard to their gray matter volume in the left fusiform gyrus and their pupil responses to face stimuli. Overall, these results describe how handedness is related to the lateralization of the core face perception network, and point to different neural mechanisms underlying face processing in right- and left-handers. In a wider context, this demonstrates the entanglement of structurally and functionally remote brain networks, suggesting a broader underlying process regulating brain lateralization.
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Arbabi, Vahid; Pouran, Behdad; Campoli, Gianni; Weinans, Harrie; Zadpoor, Amir A
2016-03-21
One of the most widely used techniques to determine the mechanical properties of cartilage is based on indentation tests and interpretation of the obtained force-time or displacement-time data. In the current computational approaches, one needs to simulate the indentation test with finite element models and use an optimization algorithm to estimate the mechanical properties of cartilage. The modeling procedure is cumbersome, and the simulations need to be repeated for every new experiment. For the first time, we propose a method for fast and accurate estimation of the mechanical and physical properties of cartilage as a poroelastic material with the aid of artificial neural networks. In our study, we used finite element models to simulate the indentation for poroelastic materials with wide combinations of mechanical and physical properties. The obtained force-time curves are then divided into three parts: the first two parts of the data is used for training and validation of an artificial neural network, while the third part is used for testing the trained network. The trained neural network receives the force-time curves as the input and provides the properties of cartilage as the output. We observed that the trained network could accurately predict the properties of cartilage within the range of properties for which it was trained. The mechanical and physical properties of cartilage could therefore be estimated very fast, since no additional finite element modeling is required once the neural network is trained. The robustness of the trained artificial neural network in determining the properties of cartilage based on noisy force-time data was assessed by introducing noise to the simulated force-time data. We found that the training procedure could be optimized so as to maximize the robustness of the neural network against noisy force-time data. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Reaction Mechanism of Tar Evolution in Biomass Steam Gasification for Hydrogen Production
International Nuclear Information System (INIS)
Shingo Katayama; Masahiro Suzuki; Atsushi Tsutsumi
2006-01-01
Reaction mechanism of tar evolution in steam gasification of biomass was investigated with a continuous cross-flow moving bed type differential reactor, in which tar and gases can be fractionated according to reaction time. We estimated that time profile of tar and gas evolution in the gasification of cellulose, xylan, and lignin, and compared it with experimental product time profile of real biomass gasification. The experimental tar evolution rate is different from estimated tar evolution rate. The estimated tar evolution rate has a peak at 20 s. On the other hand, the experimental tar evolution rate at 20 s is little, and tar at initial stage includes more water-soluble and water-insoluble compounds. It can be concluded that in the real biomass steam gasification the evolution of tar from cellulose and lignin component was found to be precipitated by that from hemi-cellulose component. (authors)
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Koutsoukou, Antonia; Perraki, Helen; Orfanos, Stylianos E; Koulouris, Nikolaos G; Tromaropoulos, Andreas; Sotiropoulou, Christina; Roussos, Charis
2009-12-01
The aim of this study was to investigate the effect of mechanical ventilation (MV) before acute respiratory distress syndrome (ARDS) on subsequent evolution of respiratory mechanics and blood gases in protectively ventilated patients with ARDS. Nineteen patients with ARDS were stratified into 2 groups according to ARDS onset relative to the onset of MV: In group A (n = 11), MV was applied at the onset of ARDS; in group B (n = 8), MV had been initiated before ARDS. Respiratory mechanics and arterial blood gas were assessed in early (protectively ventilated patients with ARDS, late alteration of respiratory mechanics occurs more commonly in patients who have been ventilated before ARDS onset, suggesting that the history of MV affects the subsequent progress of ARDS even when using protective ventilation.
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Neural overlap in processing music and speech
Peretz, Isabelle; Vuvan, Dominique; Lagrois, Marie-Élaine; Armony, Jorge L.
2015-01-01
Neural overlap in processing music and speech, as measured by the co-activation of brain regions in neuroimaging studies, may suggest that parts of the neural circuitries established for language may have been recycled during evolution for musicality, or vice versa that musicality served as a springboard for language emergence. Such a perspective has important implications for several topics of general interest besides evolutionary origins. For instance, neural overlap is an important premise for the possibility of music training to influence language acquisition and literacy. However, neural overlap in processing music and speech does not entail sharing neural circuitries. Neural separability between music and speech may occur in overlapping brain regions. In this paper, we review the evidence and outline the issues faced in interpreting such neural data, and argue that converging evidence from several methodologies is needed before neural overlap is taken as evidence of sharing. PMID:25646513
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On the Use of Local Search in the Evolution of Neural Networks for the Diagnosis of Breast Cancer
Directory of Open Access Journals (Sweden)
Agam Gupta
2015-07-01
Full Text Available With the advancement in the field of Artificial Intelligence, there have been considerable efforts to develop technologies for pattern recognition related to medical diagnosis. Artificial Neural Networks (ANNs, a significant piece of Artificial Intelligence forms the base for most of the marvels in the former field. However, ANNs face the problem of premature convergence at a local minimum and inability to set hyper-parameters (like the number of neurons, learning rate, etc. while using Back Propagation Algorithm (BPA. In this paper, we have used the Genetic Algorithm (GA for the evolution of the ANN, which overcomes the limitations of the BPA. Since GA alone cannot fit for a high-dimensional, complex and multi-modal optimization landscape of the ANN, BPA is used as a local search algorithm to aid the evolution. The contributions of GA and BPA in the resultant approach are adjudged to determine the magnitude of local search necessary for optimization, striking a clear balance between exploration and exploitation in the evolution. The algorithm was applied to deal with the problem of Breast Cancer diagnosis. Results showed that under optimal settings, hybrid algorithm performs better than BPA or GA alone.
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Neural Conflict–Control Mechanisms Improve Memory for Target Stimuli
Krebs, Ruth M.; Boehler, Carsten N.; De Belder, Maya; Egner, Tobias
2015-01-01
According to conflict-monitoring models, conflict serves as an internal signal for reinforcing top-down attention to task-relevant information. While evidence based on measures of ongoing task performance supports this idea, implications for long-term consequences, that is, memory, have not been tested yet. Here, we evaluated the prediction that conflict-triggered attentional enhancement of target-stimulus processing should be associated with superior subsequent memory for those stimuli. By combining functional magnetic resonance imaging (fMRI) with a novel variant of a face-word Stroop task that employed trial-unique face stimuli as targets, we were able to assess subsequent (incidental) memory for target faces as a function of whether a given face had previously been accompanied by congruent, neutral, or incongruent (conflicting) distracters. In line with our predictions, incongruent distracters not only induced behavioral conflict, but also gave rise to enhanced memory for target faces. Moreover, conflict-triggered neural activity in prefrontal and parietal regions was predictive of subsequent retrieval success, and displayed conflict-enhanced functional coupling with medial-temporal lobe regions. These data provide support for the proposal that conflict evokes enhanced top-down attention to task-relevant stimuli, thereby promoting their encoding into long-term memory. Our findings thus delineate the neural mechanisms of a novel link between cognitive control and memory. PMID:24108799
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Advances on molecular mechanism of the adaptive evolution of Chiroptera (bats).
Yunpeng, Liang; Li, Yu
2015-01-01
As the second biggest animal group in mammals, Chiroptera (bats) demonstrates many unique adaptive features in terms of flight, echolocation, auditory acuity, feeding habit, hibernation and immune defense, providing an excellent system for understanding the molecular basis of how organisms adapt to the living environments encountered. In this review, we summarize the researches on the molecular mechanism of the adaptive evolution of Chiroptera, especially the recent researches at the genome levels, suggesting a far more complex evolutionary pattern and functional diversity than previously thought. In the future, along with the increasing numbers of Chiroptera species genomes available, new evolutionary patterns and functional divergence will be revealed, which can promote the further understanding of this animal group and the molecular mechanism of adaptive evolution.
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Damage evolution of TBC system under in-phase thermo-mechanical tests
International Nuclear Information System (INIS)
Kitazawa, R.; Tanaka, M.; Kagawa, Y.; Liu, Y.F.
2010-01-01
In-phase thermo-mechanical tests (TMF) of EB-PVD Y 2 O 3 -ZrO 2 thermal barrier coating (TBC) system (8 wt% Y 2 O 3 -ZrO 2 /CoNiCrAlY/IN-738 substrate) were done under a through-the-thick-direction thermal gradient from TBC surface temperature at 1150 deg. C to substrate temperature at 1000 deg. C. Deformation and failure behaviors of the TBC system were observed at the macroscopic and microscopic scales and damage evolution of the system under in-phase thermo-mechanical test was discussed. Special attention was paid to TBC layer cracking, thermally grown oxide (TGO) layer formation and void formation in bond coat and substrate. Effect of TMF conditions on the damage evolution behaviors was also discussed.
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Cellular packing, mechanical stress and the evolution of multicellularity
Jacobeen, Shane; Pentz, Jennifer T.; Graba, Elyes C.; Brandys, Colin G.; Ratcliff, William C.; Yunker, Peter J.
2018-03-01
The evolution of multicellularity set the stage for sustained increases in organismal complexity1-5. However, a fundamental aspect of this transition remains largely unknown: how do simple clusters of cells evolve increased size when confronted by forces capable of breaking intracellular bonds? Here we show that multicellular snowflake yeast clusters6-8 fracture due to crowding-induced mechanical stress. Over seven weeks ( 291 generations) of daily selection for large size, snowflake clusters evolve to increase their radius 1.7-fold by reducing the accumulation of internal stress. During this period, cells within the clusters evolve to be more elongated, concomitant with a decrease in the cellular volume fraction of the clusters. The associated increase in free space reduces the internal stress caused by cellular growth, thus delaying fracture and increasing cluster size. This work demonstrates how readily natural selection finds simple, physical solutions to spatial constraints that limit the evolution of group size—a fundamental step in the evolution of multicellularity.
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Muralidharan, Pooja; Sarmah, Swapnalee; Zhou, Feng C; Marrs, James A
2013-06-19
Fetal alcohol spectrum disorder (FASD), caused by prenatal alcohol exposure, can result in craniofacial dysmorphism, cognitive impairment, sensory and motor disabilities among other defects. FASD incidences are as high as 2% to 5 % children born in the US, and prevalence is higher in low socioeconomic populations. Despite various mechanisms being proposed to explain the etiology of FASD, the molecular targets of ethanol toxicity during development are unknown. Proposed mechanisms include cell death, cell signaling defects and gene expression changes. More recently, the involvement of several other molecular pathways was explored, including non-coding RNA, epigenetic changes and specific vitamin deficiencies. These various pathways may interact, producing a wide spectrum of consequences. Detailed understanding of these various pathways and their interactions will facilitate the therapeutic target identification, leading to new clinical intervention, which may reduce the incidence and severity of these highly prevalent preventable birth defects. This review discusses manifestations of alcohol exposure on the developing central nervous system, including the neural crest cells and sensory neural placodes, focusing on molecular neurodevelopmental pathways as possible therapeutic targets for prevention or protection.
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Directory of Open Access Journals (Sweden)
James A. Marrs
2013-06-01
Full Text Available Fetal alcohol spectrum disorder (FASD, caused by prenatal alcohol exposure, can result in craniofacial dysmorphism, cognitive impairment, sensory and motor disabilities among other defects. FASD incidences are as high as 2% to 5 % children born in the US, and prevalence is higher in low socioeconomic populations. Despite various mechanisms being proposed to explain the etiology of FASD, the molecular targets of ethanol toxicity during development are unknown. Proposed mechanisms include cell death, cell signaling defects and gene expression changes. More recently, the involvement of several other molecular pathways was explored, including non-coding RNA, epigenetic changes and specific vitamin deficiencies. These various pathways may interact, producing a wide spectrum of consequences. Detailed understanding of these various pathways and their interactions will facilitate the therapeutic target identification, leading to new clinical intervention, which may reduce the incidence and severity of these highly prevalent preventable birth defects. This review discusses manifestations of alcohol exposure on the developing central nervous system, including the neural crest cells and sensory neural placodes, focusing on molecular neurodevelopmental pathways as possible therapeutic targets for prevention or protection.
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Zhou, Yu-feng; Fang, Feng; Dong, Yong-sui; Zhou, Hua; Zhen, Hong; Liu, Jin; Li, Ge
2006-07-01
Cytomegalovirus (CMV) is the leading infectious cause of congenital anomalies of the central nervous system caused by intrauterine infection. However, the exact pathogenesis of these brain abnormalities has not been fully elucidated. It has been reported that periependymitis, periventricular necrosis and calcification are the most frequent findings in the brains of congenital CMV infection. Because a number of multipotential neural stem cells (NSCs) have been identified from ventricular zone, it is possible that NSCs in this area are primary targets for viral infection, which seems to be primarily responsible for the generation of the brain abnormalities. Therefore, the objective of the present study was to investigate the effect and mechanism of murine cytomegalovirus (MCMV) infection on neural stem cells' differentiation in vitro and its role in the mechanisms of brain abnormalities caused by congenital cytomegalovirus infection. NSCs were prepared from fetal BALB/c mouse and were infected with recombinant MCMV RM461 inserted with a report gene LacZ at 1 multiplicity of infection (MOI = 1). The effect of MCMV infection on neural stem cells' differentiation was observed by detecting the ratio of nestin, GFAP and NSE positive cells with immunohistochemistry and flow cytometry on day 2 postinfection. The effects of MCMV infection on gene expression of Wnt-1 and neurogenin 1 (Ngn1) related to neural differentiation were detected by RT-PCR. NSCs isolated from embryonic mouse brains strongly expressed nestin, a specific marker of NSCs and had the capacity to differentiate into NF-200 and NSE positive neurons or GFAP positive astrocytes. At MOI = 1, the results of flow cytometry assay showed that nestin positive cells' proportion in the infection group [(62.2 +/- 1.8)%] was higher than that in the normal group [(37.2 +/- 2.4)%] (t = 4.62, P differentiation, which may be primary causes of disorders of brain development in congenital CMV infection. The decreased
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Hormonal and neural mechanisms of food reward, eating behaviour and obesity.
Murray, Susan; Tulloch, Alastair; Gold, Mark S; Avena, Nicole M
2014-09-01
With rising rates of obesity, research continues to explore the contributions of homeostatic and hedonic mechanisms related to eating behaviour. In this Review, we synthesize the existing information on select biological mechanisms associated with reward-related food intake, dealing primarily with consumption of highly palatable foods. In addition to their established functions in normal feeding, three primary peripheral hormones (leptin, ghrelin and insulin) play important parts in food reward. Studies in laboratory animals and humans also show relationships between hyperphagia or obesity and neural pathways involved in reward. These findings have prompted questions regarding the possibility of addictive-like aspects in food consumption. Further exploration of this topic may help to explain aberrant eating patterns, such as binge eating, and provide insight into the current rates of overweight and obesity.
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Directory of Open Access Journals (Sweden)
ZHANG Yongzhi
2016-10-01
Full Text Available A dynamic fuzzy RBF neural network model was built to predict the mechanical properties of welded joints, and the purpose of the model was to overcome the shortcomings of static neural networks including structural identification, dynamic sample training and learning algorithm. The structure and parameters of the model are no longer head of default, dynamic adaptive adjustment in the training, suitable for dynamic sample data for learning, learning algorithm introduces hierarchical learning and fuzzy rule pruning strategy, to accelerate the training speed of model and make the model more compact. Simulation of the model was carried out by using three kinds of thickness and different process TC4 titanium alloy TIG welding test data. The results show that the model has higher prediction accuracy, which is suitable for predicting the mechanical properties of welded joints, and has opened up a new way for the on-line control of the welding process.
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Neural overlap in processing music and speech.
Peretz, Isabelle; Vuvan, Dominique; Lagrois, Marie-Élaine; Armony, Jorge L
2015-03-19
Neural overlap in processing music and speech, as measured by the co-activation of brain regions in neuroimaging studies, may suggest that parts of the neural circuitries established for language may have been recycled during evolution for musicality, or vice versa that musicality served as a springboard for language emergence. Such a perspective has important implications for several topics of general interest besides evolutionary origins. For instance, neural overlap is an important premise for the possibility of music training to influence language acquisition and literacy. However, neural overlap in processing music and speech does not entail sharing neural circuitries. Neural separability between music and speech may occur in overlapping brain regions. In this paper, we review the evidence and outline the issues faced in interpreting such neural data, and argue that converging evidence from several methodologies is needed before neural overlap is taken as evidence of sharing. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
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Separate neural mechanisms underlie choices and strategic preferences in risky decision making.
Venkatraman, Vinod; Payne, John W; Bettman, James R; Luce, Mary Frances; Huettel, Scott A
2009-05-28
Adaptive decision making in real-world contexts often relies on strategic simplifications of decision problems. Yet, the neural mechanisms that shape these strategies and their implementation remain largely unknown. Using an economic decision-making task, we dissociate brain regions that predict specific choices from those predicting an individual's preferred strategy. Choices that maximized gains or minimized losses were predicted by functional magnetic resonance imaging activation in ventromedial prefrontal cortex or anterior insula, respectively. However, choices that followed a simplifying strategy (i.e., attending to overall probability of winning) were associated with activation in parietal and lateral prefrontal cortices. Dorsomedial prefrontal cortex, through differential functional connectivity with parietal and insular cortex, predicted individual variability in strategic preferences. Finally, we demonstrate that robust decision strategies follow from neural sensitivity to rewards. We conclude that decision making reflects more than compensatory interaction of choice-related regions; in addition, specific brain systems potentiate choices depending on strategies, traits, and context.
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Hybrid discrete-time neural networks.
Cao, Hongjun; Ibarz, Borja
2010-11-13
Hybrid dynamical systems combine evolution equations with state transitions. When the evolution equations are discrete-time (also called map-based), the result is a hybrid discrete-time system. A class of biological neural network models that has recently received some attention falls within this category: map-based neuron models connected by means of fast threshold modulation (FTM). FTM is a connection scheme that aims to mimic the switching dynamics of a neuron subject to synaptic inputs. The dynamic equations of the neuron adopt different forms according to the state (either firing or not firing) and type (excitatory or inhibitory) of their presynaptic neighbours. Therefore, the mathematical model of one such network is a combination of discrete-time evolution equations with transitions between states, constituting a hybrid discrete-time (map-based) neural network. In this paper, we review previous work within the context of these models, exemplifying useful techniques to analyse them. Typical map-based neuron models are low-dimensional and amenable to phase-plane analysis. In bursting models, fast-slow decomposition can be used to reduce dimensionality further, so that the dynamics of a pair of connected neurons can be easily understood. We also discuss a model that includes electrical synapses in addition to chemical synapses with FTM. Furthermore, we describe how master stability functions can predict the stability of synchronized states in these networks. The main results are extended to larger map-based neural networks.
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Neural Control Mechanisms and Body Fluid Homeostasis
Johnson, Alan Kim
1998-01-01
The goal of the proposed research was to study the nature of afferent signals to the brain that reflect the status of body fluid balance and to investigate the central neural mechanisms that process this information for the activation of response systems which restore body fluid homeostasis. That is, in the face of loss of fluids from intracellular or extracellular fluid compartments, animals seek and ingest water and ionic solutions (particularly Na(+) solutions) to restore the intracellular and extracellular spaces. Over recent years, our laboratory has generated a substantial body of information indicating that: (1) a fall in systemic arterial pressure facilitates the ingestion of rehydrating solutions and (2) that the actions of brain amine systems (e.g., norepinephrine; serotonin) are critical for precise correction of fluid losses. Because both acute and chronic dehydration are associated with physiological stresses, such as exercise and sustained exposure to microgravity, the present research will aid in achieving a better understanding of how vital information is handled by the nervous system for maintenance of the body's fluid matrix which is critical for health and well-being.
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MCPH1: a window into brain development and evolution
Directory of Open Access Journals (Sweden)
Jeannette eNardelli
2015-03-01
Full Text Available The development of the mammalian cerebral cortex involves a series of mechanisms: from patterning, progenitor cell proliferation and differentiation, to neuronal migration. Many factors influence the development of the cerebral cortex to its normal size and neuronal composition. Of these, the mechanisms that influence the proliferation and differentiation of neural progenitor cells are of particular interest, as they may have the greatest consequence on brain size, not only during development but also in evolution. In this context, causative genes of human autosomal recessive primary microcephaly, such as ASPM and MCPH1, are attractive candidates, as many of them show positive selection during primate evolution. MCPH1 causes microcephaly in mice and humans and is involved in a diverse array of molecular functions beyond brain development, including DNA repair and chromosome condensation. Positive selection of MCPH1 in the primate lineage has led to much insight and discussion of its role in brain size evolution. In this review, we will present an overview of MCPH1 from these multiple angles, and whilst its specific role in brain size regulation during development and evolution remain elusive, the pieces of the puzzle will be discussed with the aim of putting together the full picture of this fascinating gene.
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Lotem, Arnon; Kolodny, Oren
2014-04-01
An associative learning account of mirror neurons should not preclude genetic evolution of its underlying mechanisms. On the contrary, an associative learning framework for cognitive development should seek heritable variation in the learning rules and in the data-acquisition mechanisms that construct associative networks, demonstrating how small genetic modifications of associative elements can give rise to the evolution of complex cognition.
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Directory of Open Access Journals (Sweden)
Lu Liu
2018-04-01
Full Text Available Internet gaming disorder (IGD is characterized by cognitive and emotional deficits. Previous studies have reported the co-occurrence of IGD and depression. However, extant brain imaging research has largely focused on cognitive deficits in IGD. Few studies have addressed the comorbidity between IGD and depression symptoms and underlying neural mechanisms. Here, we systematically investigated this issue by combining a longitudinal survey study, a cross-sectional resting-state functional connectivity (rsFC study and an intervention study. Autoregressive cross-lagged modeling on a longitudinal dataset of college students showed that IGD severity and depression are reciprocally predictive. At the neural level, individuals with IGD exhibited enhanced rsFC between the left amygdala and right dorsolateral prefrontal cortex (DLPFC, inferior frontal and precentral gyrus, compared with control participants, and the amygdala-frontoparietal connectivity at the baseline negatively predicted reduction in depression symptoms following a psychotherapy intervention. Further, following the intervention, individuals with IGD showed decreased connectivity between the left amygdala and left middle frontal and precentral gyrus, as compared with the non-intervention group. These findings together suggest that IGD may be closely associated with depression; aberrant rsFC between emotion and executive control networks may underlie depression and represent a therapeutic target in individuals with IGD.Registry name: The behavioral and brain mechanism of IGD;URL: https://www.clinicaltrials.gov/ct2/show/NCT02550405;Registration number: NCT02550405.
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Convergent evolution in mechanical design of lamnid sharks and tunas.
Donley, Jeanine M; Sepulveda, Chugey A; Konstantinidis, Peter; Gemballa, Sven; Shadwick, Robert E
2004-05-06
The evolution of 'thunniform' body shapes in several different groups of vertebrates, including whales, ichthyosaurs and several species of large pelagic fishes supports the view that physical and hydromechanical demands provided important selection pressures to optimize body design for locomotion during vertebrate evolution. Recognition of morphological similarities between lamnid sharks (the most well known being the great white and the mako) and tunas has led to a general expectation that they also have converged in their functional design; however, no quantitative data exist on the mechanical performance of the locomotor system in lamnid sharks. Here we examine the swimming kinematics, in vivo muscle dynamics and functional morphology of the force-transmission system in a lamnid shark, and show that the evolutionary convergence in body shape and mechanical design between the distantly related lamnids and tunas is much more than skin deep; it extends to the depths of the myotendinous architecture and the mechanical basis for propulsive movements. We demonstrate that not only have lamnids and tunas converged to a much greater extent than previously known, but they have also developed morphological and functional adaptations in their locomotor systems that are unlike virtually all other fishes.
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Damage evolution of TBC system under in-phase thermo-mechanical tests
Energy Technology Data Exchange (ETDEWEB)
Kitazawa, R.; Tanaka, M.; Kagawa, Y. [Research Center for Advanced Science and Technology, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8904 (Japan); Liu, Y.F., E-mail: yfliu@hyper.rcast.u-tokyo.ac.jp [Research Center for Advanced Science and Technology, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8904 (Japan)
2010-10-15
In-phase thermo-mechanical tests (TMF) of EB-PVD Y{sub 2}O{sub 3}-ZrO{sub 2} thermal barrier coating (TBC) system (8 wt% Y{sub 2}O{sub 3}-ZrO{sub 2}/CoNiCrAlY/IN-738 substrate) were done under a through-the-thick-direction thermal gradient from TBC surface temperature at 1150 deg. C to substrate temperature at 1000 deg. C. Deformation and failure behaviors of the TBC system were observed at the macroscopic and microscopic scales and damage evolution of the system under in-phase thermo-mechanical test was discussed. Special attention was paid to TBC layer cracking, thermally grown oxide (TGO) layer formation and void formation in bond coat and substrate. Effect of TMF conditions on the damage evolution behaviors was also discussed.
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Mechanisms of oxygen evolution
Energy Technology Data Exchange (ETDEWEB)
Radmer, R; Cheniae, G
1976-08-01
The production of O/sub 2/ from water requires the collaboration of four oxidizing equivalents. When dark-adapted O/sub 2/ evolving photosynthetic material is illuminated by a sequence of short (less than 2 ..mu..sec) saturating flashes, the amount of O/sub 2/ evolved per flash oscillates with a period of four. This indicates that a charge-collector, operating with its own reaction center, successively collects and stores four oxidizing equivalents, which are used in a concerted oxidation of two water molecules. Luminescence, fluorescence, and pH changes also reflect this cycle of four. The O/sub 2/ precursor states are quite stable; under some conditions they can have a lifetime of several minutes. The O/sub 2/-yielding reactions and reactions associated with trap recovery are fast relative to the rate-limiting step of photosynthesis. The molecular identity of the charge-collector is unknown, but correlative evidence suggests that a manganese containing catalyst (approximately 4 Mn/charge collector) participates, possibly directly. Formation of the active Mn-containing catalyst occurs via a multi-quantum process occurring within the System II reaction center. The photoactivated catalyst, located on the inner face of the thylakoid membrane, remains permanently active and essentially inaccessible to chemicals other than analogs of H/sub 2/O (e.g., NH/sub 3/, NH/sub 2/OH). This O/sub 2/ evolving catalyst can be deactivated by a variety of treatments that do not alter the system II reaction center. Anions such as chloride seem to participate rather directly in the O/sub 2/ evolution process via unknown mechanism(s).
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Mandal, Sumantra; Sivaprasad, P. V.; Dube, R. K.
2007-12-01
An artificial neural network (ANN) model was developed to predict the microstructural evolution of a 15Cr-15Ni-2.2Mo-Ti modified austenitic stainless steel (Alloy D9) during dynamic recrystallization (DRX). The input parameters were strain, strain rate, and temperature whereas microstructural features namely, %DRX and average grain size were the output parameters. The ANN was trained with the database obtained from various industrial scale metal-forming operations like forge hammer, hydraulic press, and rolling carried out in the temperature range 1173-1473 K to various strain levels. The performance of the model was evaluated using a wide variety of statistical indices and the predictability of the model was found to be good. The combined influence of temperature and strain on microstructural features has been simulated employing the developed model. The results were found to be consistent with the relevant fundamental metallurgical phenomena.
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Learning and adaptation: neural and behavioural mechanisms behind behaviour change
Lowe, Robert; Sandamirskaya, Yulia
2018-01-01
This special issue presents perspectives on learning and adaptation as they apply to a number of cognitive phenomena including pupil dilation in humans and attention in robots, natural language acquisition and production in embodied agents (robots), human-robot game play and social interaction, neural-dynamic modelling of active perception and neural-dynamic modelling of infant development in the Piagetian A-not-B task. The aim of the special issue, through its contributions, is to highlight some of the critical neural-dynamic and behavioural aspects of learning as it grounds adaptive responses in robotic- and neural-dynamic systems.
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Neural conflict-control mechanisms improve memory for target stimuli.
Krebs, Ruth M; Boehler, Carsten N; De Belder, Maya; Egner, Tobias
2015-03-01
According to conflict-monitoring models, conflict serves as an internal signal for reinforcing top-down attention to task-relevant information. While evidence based on measures of ongoing task performance supports this idea, implications for long-term consequences, that is, memory, have not been tested yet. Here, we evaluated the prediction that conflict-triggered attentional enhancement of target-stimulus processing should be associated with superior subsequent memory for those stimuli. By combining functional magnetic resonance imaging (fMRI) with a novel variant of a face-word Stroop task that employed trial-unique face stimuli as targets, we were able to assess subsequent (incidental) memory for target faces as a function of whether a given face had previously been accompanied by congruent, neutral, or incongruent (conflicting) distracters. In line with our predictions, incongruent distracters not only induced behavioral conflict, but also gave rise to enhanced memory for target faces. Moreover, conflict-triggered neural activity in prefrontal and parietal regions was predictive of subsequent retrieval success, and displayed conflict-enhanced functional coupling with medial-temporal lobe regions. These data provide support for the proposal that conflict evokes enhanced top-down attention to task-relevant stimuli, thereby promoting their encoding into long-term memory. Our findings thus delineate the neural mechanisms of a novel link between cognitive control and memory. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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Neuron-Based Heredity and Human Evolution
Directory of Open Access Journals (Sweden)
Don Marshall Gash
2015-06-01
Full Text Available Abstract:Abstract: It is widely recognized that human evolution has been driven by two systems of heredity: one DNA-based and the other based on the transmission of behaviorally acquired information via nervous system functions. The genetic system is ancient, going back to the appearance of life on Earth. It is responsible for the evolutionary processes described by Darwin. By comparison, the nervous system is relatively newly minted and in its highest form, responsible for ideation and mind-to-mind transmission of information. Here the informational capabilities and functions of the two systems are compared. While employing quite different mechanisms for encoding, storing and transmission of information, both systems perform these generic hereditary functions. Three additional features of neuron-based heredity in humans are identified: the ability to transfer hereditary information to other members of their population, not just progeny; a selection process for the information being transferred; and a profoundly shorter time span for creation and dissemination of survival-enhancing information in a population. The mechanisms underlying neuron-based heredity involve hippocampal neurogenesis and memory and learning processes modifying and creating new neural assemblages changing brain structure and functions. A fundamental process in rewiring brain circuitry is through increased neural activity (use strengthening and increasing the number of synaptic connections. Decreased activity in circuitry (disuse leads to loss of synapses. Use and disuse modifying an organ to bring about new modes of living, habits and functions are processes are in line with Neolamarckian concepts of evolution (Packard, 1901. Evidence is presented of bipartite evolutionary processes – Darwinian and Neolamarckian – driving human descent from a common ancestor shared with the great apes.
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Lekic, Tim; Klebe, Damon; Poblete, Roy; Krafft, Paul R; Rolland, William B; Tang, Jiping; Zhang, John H
2015-01-01
Neonatal brain hemorrhage (NBH) of prematurity is an unfortunate consequence of preterm birth. Complications result in shunt dependence and long-term structural changes such as posthemorrhagic hydrocephalus, periventricular leukomalacia, gliosis, and neurological dysfunction. Several animal models are available to study this condition, and many basic mechanisms, etiological factors, and outcome consequences, are becoming understood. NBH is an important clinical condition, of which treatment may potentially circumvent shunt complication, and improve functional recovery (cerebral palsy, and cognitive impairments). This review highlights key pathophysiological findings of the neonatal vascular-neural network in the context of molecular mechanisms targeting the posthemorrhagic hydrocephalus affecting this vulnerable infant population.
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Lekic, Tim; Klebe, Damon; Poblete, Roy; Krafft, Paul R.; Rolland, William B.; Tang, Jiping; Zhang, John H.
2015-01-01
Neonatal brain hemorrhage (NBH) of prematurity is an unfortunate consequence of preterm birth. Complications result in shunt dependence and long-term structural changes such as post-hemorrhagic hydrocephalus, periventricular leukomalacia, gliosis, and neurological dysfunction. Several animal models are available to study this condition, and many basic mechanisms, etiological factors, and outcome consequences, are becoming understood. NBH is an important clinical condition, of which treatment may potentially circumvent shunt complication, and improve functional recovery (cerebral palsy, and cognitive impairments). This review highlights key pathophysiological findings of the neonatal vascular-neural network in the context of molecular mechanisms targeting the post-hemorrhagic hydrocephalus affecting this vulnerable infant population. PMID:25620100
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Nowicki, Jessica; Pratchett, Morgan; Walker, Stefan; Coker, Darren James; O'Connell, Lauren A.
2017-01-01
Pair bonding has independently evolved numerous times among vertebrates. The governing neural mechanisms of pair bonding have only been studied in depth in the mammalian model species, the prairie vole, Microtus ochrogaster. In this species, oxytocin (OT), arginine vasopressin (AVP), dopamine (DA), and opioid (OP) systems play key roles in signaling in the formation and maintenance of pair bonding by targeting specific social and reward-mediating brain regions. By contrast, the neural basis of pair bonding is poorly studied in other vertebrates, and especially those of early origins, limiting our understanding of the evolutionary history of pair bonding regulatory mechanisms. We compared receptor gene expression between pair bonded and solitary individuals across eight socio-functional brain regions. We found that in females, ITR and V1aR receptor expression varied in the lateral septum-like region (the Vv/Vl), while in both sexes D1R, D2R, and MOR expression varied within the mesolimbic reward system, including a striatum-like region (the Vc); mirroring sites of action in M. ochrogaster. This study provides novel insights into the neurobiology of teleost pair bonding. It also reveals high convergence in the neurochemical mechanisms governing pair bonding across actinopterygians and sarcopterygians, by repeatedly co-opting and similarly assembling deep neurochemical and neuroanatomical homologies that originated in ancestral osteithes.
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Coubard, Olivier A
2016-01-01
Since the seminal report by Shapiro that bilateral stimulation induces cognitive and emotional changes, 26 years of basic and clinical research have examined the effects of Eye Movement Desensitization and Reprocessing (EMDR) in anxiety disorders, particularly in post-traumatic stress disorder (PTSD). The present article aims at better understanding EMDR neural mechanism. I first review procedural aspects of EMDR protocol and theoretical hypothesis about EMDR effects, and develop the reasons why the scientific community is still divided about EMDR. I then slide from psychology to physiology describing eye movements/emotion interaction from the physiological viewpoint, and introduce theoretical and technical tools used in movement research to re-examine EMDR neural mechanism. Using a recent physiological model for the neuropsychological architecture of motor and cognitive control, the Threshold Interval Modulation with Early Release-Rate of rIse Deviation with Early Release (TIMER-RIDER)-model, I explore how attentional control and bilateral stimulation may participate to EMDR effects. These effects may be obtained by two processes acting in parallel: (i) activity level enhancement of attentional control component; and (ii) bilateral stimulation in any sensorimotor modality, both resulting in lower inhibition enabling dysfunctional information to be processed and anxiety to be reduced. The TIMER-RIDER model offers quantitative predictions about EMDR effects for future research about its underlying physiological mechanisms.
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An integrative model for the neural mechanism of Eye Movement Desensitization and Reprocessing (EMDR
Directory of Open Access Journals (Sweden)
Olivier A. Coubard
2016-04-01
Full Text Available Since the seminal report by Shapiro that bilateral stimulation induces cognitive and emotional changes, twenty-six years of basic and clinical research have examined the effects of Eye Movement Desensitization and Reprocessing (EMDR in anxiety disorders, particularly in Post-Traumatic Stress Disorder (PTSD. The present article aims at better understanding EMDR neural mechanism. I first review procedural aspects of EMDR protocol and theoretical hypothesis about EMDR effects, and develop the reasons why the scientific community is still divided about EMDR. I then slide from psychology to physiology describing eye movements/emotion interaction from the physiological viewpoint, and introduce theoretical and technical tools used in movement research to re-examine EMDR neural mechanism. Using a recent physiological model for the neuropsychological architecture of motor and cognitive control, the Threshold Interval Modulation with Early Release-Rate of rIse Deviation with Early Release – TIMER-RIDER – model, I explore how attentional control and bilateral stimulation may participate to EMDR effects. These effects may be obtained by two processes acting in parallel: (i activity level enhancement of attentional control component; and (ii bilateral stimulation in any sensorimotor modality, both resulting in lower inhibition enabling dysfunctional information to be processed and anxiety to be reduced. The TIMER-RIDER model offers quantitative predictions about EMDR effects for future research about its underlying physiological mechanisms.
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Nowicki, Jessica
2017-11-14
Pair bonding has independently evolved numerous times among vertebrates. The governing neural mechanisms of pair bonding have only been studied in depth in the mammalian model species, the prairie vole, Microtus ochrogaster. In this species, oxytocin (OT), arginine vasopressin (AVP), dopamine (DA), and opioid (OP) systems play key roles in signaling in the formation and maintenance of pair bonding by targeting specific social and reward-mediating brain regions. By contrast, the neural basis of pair bonding is poorly studied in other vertebrates, and especially those of early origins, limiting our understanding of the evolutionary history of pair bonding regulatory mechanisms. We compared receptor gene expression between pair bonded and solitary individuals across eight socio-functional brain regions. We found that in females, ITR and V1aR receptor expression varied in the lateral septum-like region (the Vv/Vl), while in both sexes D1R, D2R, and MOR expression varied within the mesolimbic reward system, including a striatum-like region (the Vc); mirroring sites of action in M. ochrogaster. This study provides novel insights into the neurobiology of teleost pair bonding. It also reveals high convergence in the neurochemical mechanisms governing pair bonding across actinopterygians and sarcopterygians, by repeatedly co-opting and similarly assembling deep neurochemical and neuroanatomical homologies that originated in ancestral osteithes.
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Differences between mechanical and neural tuning at the apex of the intact guinea pig cochlea
Recio-Spinoso, Alberto; Oghalai, John S.
2018-05-01
While most of human speech information is contained within frequencies guinea pig cochlea using volumetric optical coherence tomography vibrometry (VOCTV). We found that vibrations within apical cochlear regions, with neural tuning below 2 kHz, demonstrate low-pass filter characteristics. There was evidence of a low-level of broad-band cochlear amplification that did not sharpen frequency selectivity. We compared the vibratory responses we measured to previously-measured single-unit auditory nerve tuning curves in the same frequency range, and found that mechanical responses do not match neural responses. These data suggest that, for low frequency cochlear regions, inner hair cells not only transduce vibrations of the organ of Corti but also sharpen frequency tuning.
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Developmental phonagnosia: Linking neural mechanisms with the behavioural phenotype.
Roswandowitz, Claudia; Schelinski, Stefanie; von Kriegstein, Katharina
2017-07-15
Human voice recognition is critical for many aspects of social communication. Recently, a rare disorder, developmental phonagnosia, which describes the inability to recognise a speaker's voice, has been discovered. The underlying neural mechanisms are unknown. Here, we used two functional magnetic resonance imaging experiments to investigate brain function in two behaviourally well characterised phonagnosia cases, both 32 years old: AS has apperceptive and SP associative phonagnosia. We found distinct malfunctioned brain mechanisms in AS and SP matching their behavioural profiles. In apperceptive phonagnosia, right-hemispheric auditory voice-sensitive regions (i.e., Heschl's gyrus, planum temporale, superior temporal gyrus) showed lower responses than in matched controls (n AS =16) for vocal versus non-vocal sounds and for speaker versus speech recognition. In associative phonagnosia, the connectivity between voice-sensitive (i.e. right posterior middle/inferior temporal gyrus) and supramodal (i.e. amygdala) regions was reduced in comparison to matched controls (n SP =16) during speaker versus speech recognition. Additionally, both cases recruited distinct potential compensatory mechanisms. Our results support a central assumption of current two-system models of voice-identity processing: They provide the first evidence that dysfunction of voice-sensitive regions and impaired connectivity between voice-sensitive and supramodal person recognition regions can selectively contribute to deficits in person recognition by voice. Copyright © 2017 Elsevier Inc. All rights reserved.
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Ortiz, M.; Pinales, J. C.; Graber, H. C.; Wilkinson, J.; Lund, B.
2016-02-01
Melt ponds on sea ice play a significant and complex role on the thermodynamics in the Marginal Ice Zone (MIZ). Ponding reduces the sea ice's ability to reflect sunlight, and in consequence, exacerbates the albedo positive feedback cycle. In order to understand how melt ponds work and their effect on the heat uptake of sea ice, we must quantify ponds through their seasonal evolution first. A semi-supervised neural network three-class learning scheme using a gradient descent with momentum and adaptive learning rate backpropagation function is applied to classify melt ponds/melt areas in the Beaufort Sea region. The network uses high resolution panchromatic satellite images from the MEDEA program, which are collocated with autonomous platform arrays from the Marginal Ice Zone Program, including ice mass-balance buoys, arctic weather stations and wave buoys. The goal of the study is to capture the spatial variation of melt onset and freeze-up of the ponds within the MIZ, and gather ponding statistics such as size and concentration. The innovation of this work comes from training the neural network as the melt ponds evolve over time; making the machine learning algorithm time-dependent, which has not been previously done. We will achieve this by analyzing the image histograms through quantification of the minima and maxima intensity changes as well as linking textural variation information of the imagery. We will compare the evolution of the melt ponds against several different array sites on the sea ice to explore if there are spatial differences among the separated platforms in the MIZ.
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Artificial neural networks a practical course
da Silva, Ivan Nunes; Andrade Flauzino, Rogerio; Liboni, Luisa Helena Bartocci; dos Reis Alves, Silas Franco
2017-01-01
This book provides comprehensive coverage of neural networks, their evolution, their structure, the problems they can solve, and their applications. The first half of the book looks at theoretical investigations on artificial neural networks and addresses the key architectures that are capable of implementation in various application scenarios. The second half is designed specifically for the production of solutions using artificial neural networks to solve practical problems arising from different areas of knowledge. It also describes the various implementation details that were taken into account to achieve the reported results. These aspects contribute to the maturation and improvement of experimental techniques to specify the neural network architecture that is most appropriate for a particular application scope. The book is appropriate for students in graduate and upper undergraduate courses in addition to researchers and professionals.
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International Nuclear Information System (INIS)
Xu Li; Chu Xiakun; Yan Zhiqiang; Zheng Xiliang; Zhang Kun; Zhang Feng; Yan Han; Wu Wei; Wang Jin
2016-01-01
In this review, we explore the physical mechanisms of biological processes such as protein folding and recognition, ligand binding, and systems biology, including cell cycle, stem cell, cancer, evolution, ecology, and neural networks. Our approach is based on the landscape and flux theory for nonequilibrium dynamical systems. This theory provides a unifying principle and foundation for investigating the underlying mechanisms and physical quantification of biological systems. (topical review)
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Without it no music: cognition, biology and evolution of musicality
Honing, Henkjan; ten Cate, Carel; Peretz, Isabelle; Trehub, Sandra E.
2015-01-01
Musicality can be defined as a natural, spontaneously developing trait based on and constrained by biology and cognition. Music, by contrast, can be defined as a social and cultural construct based on that very musicality. One critical challenge is to delineate the constituent elements of musicality. What biological and cognitive mechanisms are essential for perceiving, appreciating and making music? Progress in understanding the evolution of music cognition depends upon adequate characterization of the constituent mechanisms of musicality and the extent to which they are present in non-human species. We argue for the importance of identifying these mechanisms and delineating their functions and developmental course, as well as suggesting effective means of studying them in human and non-human animals. It is virtually impossible to underpin the evolutionary role of musicality as a whole, but a multicomponent perspective on musicality that emphasizes its constituent capacities, development and neural cognitive specificity is an excellent starting point for a research programme aimed at illuminating the origins and evolution of musical behaviour as an autonomous trait. PMID:25646511
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Modularity and Sparsity: Evolution of Neural Net Controllers in Physically Embodied Robots
Directory of Open Access Journals (Sweden)
Nicholas Livingston
2016-12-01
Full Text Available While modularity is thought to be central for the evolution of complexity and evolvability, it remains unclear how systems boot-strap themselves into modularity from random or fully integrated starting conditions. Clune et al. (2013 suggested that a positive correlation between sparsity and modularity is the prime cause of this transition. We sought to test the generality of this modularity-sparsity hypothesis by testing it for the first time in physically embodied robots. A population of ten Tadros — autonomous, surface-swimming robots propelled by a flapping tail — was used. Individuals varied only in the structure of their neural net control, a 2 x 6 x 2 network with recurrence in the hidden layer. Each of the 60 possible connections was coded in the genome, and could achieve one of three states: -1, 0, 1. Inputs were two light-dependent resistors and outputs were two motor control variables to the flapping tail, one for the frequency of the flapping and the other for the turning offset. Each Tadro was tested separately in a circular tank lit by a single overhead light source. Fitness was the amount of light gathered by a vertically oriented sensor that was disconnected from the controller net. Reproduction was asexual, with the top performer cloned and then all individuals entered into a roulette wheel selection process, with genomes mutated to create the offspring. The starting population of networks was randomly generated. Over ten generations, the population’s mean fitness increased two-fold. This evolution occurred in spite of an unintentional integer overflow problem in recurrent nodes in the hidden layer that caused outputs to oscillate. Our investigation of the oscillatory behavior showed that the mutual information of inputs and outputs was sufficient for the reactive behaviors observed. While we had predicted that both modularity and sparsity would follow the same trend as fitness, neither did so. Instead, selection gradients
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DEFF Research Database (Denmark)
Dasgupta, Sakyasingha; Goldschmidt, Dennis; Wörgötter, Florentin
2015-01-01
here, an artificial bio-inspired walking system which effectively combines biomechanics (in terms of the body and leg structures) with the underlying neural mechanisms. The neural mechanisms consist of (1) central pattern generator based control for generating basic rhythmic patterns and coordinated......Walking animals, like stick insects, cockroaches or ants, demonstrate a fascinating range of locomotive abilities and complex behaviors. The locomotive behaviors can consist of a variety of walking patterns along with adaptation that allow the animals to deal with changes in environmental...... conditions, like uneven terrains, gaps, obstacles etc. Biological study has revealed that such complex behaviors are a result of a combination of biomechanics and neural mechanism thus representing the true nature of embodied interactions. While the biomechanics helps maintain flexibility and sustain...
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Neural mechanisms underlying sound-induced visual motion perception: An fMRI study.
Hidaka, Souta; Higuchi, Satomi; Teramoto, Wataru; Sugita, Yoichi
2017-07-01
Studies of crossmodal interactions in motion perception have reported activation in several brain areas, including those related to motion processing and/or sensory association, in response to multimodal (e.g., visual and auditory) stimuli that were both in motion. Recent studies have demonstrated that sounds can trigger illusory visual apparent motion to static visual stimuli (sound-induced visual motion: SIVM): A visual stimulus blinking at a fixed location is perceived to be moving laterally when an alternating left-right sound is also present. Here, we investigated brain activity related to the perception of SIVM using a 7T functional magnetic resonance imaging technique. Specifically, we focused on the patterns of neural activities in SIVM and visually induced visual apparent motion (VIVM). We observed shared activations in the middle occipital area (V5/hMT), which is thought to be involved in visual motion processing, for SIVM and VIVM. Moreover, as compared to VIVM, SIVM resulted in greater activation in the superior temporal area and dominant functional connectivity between the V5/hMT area and the areas related to auditory and crossmodal motion processing. These findings indicate that similar but partially different neural mechanisms could be involved in auditory-induced and visually-induced motion perception, and neural signals in auditory, visual, and, crossmodal motion processing areas closely and directly interact in the perception of SIVM. Copyright © 2017 Elsevier B.V. All rights reserved.
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Central chemoreceptors and neural mechanisms of cardiorespiratory control
Directory of Open Access Journals (Sweden)
T.S. Moreira
2011-09-01
Full Text Available The arterial partial pressure (P CO2 of carbon dioxide is virtually constant because of the close match between the metabolic production of this gas and its excretion via breathing. Blood gas homeostasis does not rely solely on changes in lung ventilation, but also to a considerable extent on circulatory adjustments that regulate the transport of CO2 from its sites of production to the lungs. The neural mechanisms that coordinate circulatory and ventilatory changes to achieve blood gas homeostasis are the subject of this review. Emphasis will be placed on the control of sympathetic outflow by central chemoreceptors. High levels of CO2 exert an excitatory effect on sympathetic outflow that is mediated by specialized chemoreceptors such as the neurons located in the retrotrapezoid region. In addition, high CO2 causes an aversive awareness in conscious animals, activating wake-promoting pathways such as the noradrenergic neurons. These neuronal groups, which may also be directly activated by brain acidification, have projections that contribute to the CO2-induced rise in breathing and sympathetic outflow. However, since the level of activity of the retrotrapezoid nucleus is regulated by converging inputs from wake-promoting systems, behavior-specific inputs from higher centers and by chemical drive, the main focus of the present manuscript is to review the contribution of central chemoreceptors to the control of autonomic and respiratory mechanisms.
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Neural mechanisms of attentional control in mindfulness meditation
Directory of Open Access Journals (Sweden)
Peter eMalinowski
2013-02-01
Full Text Available The scientific interest in meditation and mindfulness practice has recently seen an unprecedented surge. After an initial phase of presenting beneficial effects of mindfulness practice in various domains, research is now seeking to unravel the underlying psychological and neurophysiological mechanisms. Advances in understanding these processes are required for improving and fine-tuning mindfulness-based interventions that target specific conditions such as eating disorders or attention deficit hyperactivity disorders. This review presents a theoretical framework that emphasizes the central role of attentional control mechanisms in the development of mindfulness skills. It discusses the phenomenological level of experience during meditation, the different attentional functions that are involved, and relates these to the brain networks that subserve these functions. On the basis of currently available empirical evidence specific processes as to how attention exerts its positive influence are considered and it is concluded that meditation practice appears to positively impact attentional functions by improving resource allocation processes. As a result, attentional resources are allocated more fully during early processing phases which subsequently enhance further processing. Neural changes resulting from a pure form of mindfulness practice that is central to most mindfulness programs are considered from the perspective that they constitute a useful reference point for future research. Furthermore, possible interrelations between the improvement of attentional control and emotion regulation skills are discussed.
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Directory of Open Access Journals (Sweden)
Oleg Bazaluk
2015-06-01
Full Text Available The book The Theory of Evolution: from the Space Vacuum to Neural Ensembles and Moving Forward, an edition of 100 copies, was published in Russian language, in December 2014 in Kiev. Its Russian version is here: http://en.bazaluk.com/journals.html. Introduction, Chapter 10 and Conclusion published in English for the first time. Since 2004 author have been researching in the field of theory of Evolution, Big History. The book was written on the base of analysis of more than 2000 primary sources of this research topic. The volume is 90,000 words (with Reference. The book is for a wide range of professionals, from students to professors and researchers working in the fields of: philosophical anthropology, philosophy, Big History, cosmology, biology, neuroscience and etc. In the book, the author defines the evolution as continuous and nonlinear complication of the structure of matter, the types of interaction and environments; analyzes existing in modern science and philosophy approaches to the research of the process of evolution, degree of development of the factors and causes of evolution. Unifying interdisciplinary researches of evolution in cosmology, biology, neuroscience and philosophy, the author presents his vision of the model of «Evolving Matter», which allows us to consider not only the laws of transition of space vacuum in neural ensembles but also to see our Universe as a complication, heterogeneous organization. Interdisciplinary amount of information on the theory of evolution is systematized and a new method of world perception is proposed in the book.
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Neural mechanism of facilitation system during physical fatigue.
Directory of Open Access Journals (Sweden)
Masaaki Tanaka
Full Text Available An enhanced facilitation system caused by motivational input plays an important role in supporting performance during physical fatigue. We tried to clarify the neural mechanisms of the facilitation system during physical fatigue using magnetoencephalography (MEG and a classical conditioning technique. Twelve right-handed volunteers participated in this study. Participants underwent MEG recording during the imagery of maximum grips of the right hand guided by metronome sounds for 10 min. Thereafter, fatigue-inducing maximum handgrip trials were performed for 10 min; the metronome sounds were started 5 min after the beginning of the handgrip trials. The metronome sounds were used as conditioned stimuli and maximum handgrip trials as unconditioned stimuli. The next day, they were randomly assigned to two groups in a single-blinded, two-crossover fashion to undergo two types of MEG recordings, that is, for the control and motivation sessions, during the imagery of maximum grips of the right hand guided by metronome sounds for 10 min. The alpha-band event-related desynchronizations (ERDs of the motivation session relative to the control session within the time windows of 500 to 700 and 800 to 900 ms after the onset of handgrip cue sounds were identified in the sensorimotor areas. In addition, the alpha-band ERD within the time window of 400 to 500 ms was identified in the right dorsolateral prefrontal cortex (Brodmann's area 46. The ERD level in the right dorsolateral prefrontal cortex was positively associated with that in the sensorimotor areas within the time window of 500 to 700 ms. These results suggest that the right dorsolateral prefrontal cortex is involved in the neural substrates of the facilitation system and activates the sensorimotor areas during physical fatigue.
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Giese, Martin A; Rizzolatti, Giacomo
2015-10-07
Action recognition has received enormous interest in the field of neuroscience over the last two decades. In spite of this interest, the knowledge in terms of fundamental neural mechanisms that provide constraints for underlying computations remains rather limited. This fact stands in contrast with a wide variety of speculative theories about how action recognition might work. This review focuses on new fundamental electrophysiological results in monkeys, which provide constraints for the detailed underlying computations. In addition, we review models for action recognition and processing that have concrete mathematical implementations, as opposed to conceptual models. We think that only such implemented models can be meaningfully linked quantitatively to physiological data and have a potential to narrow down the many possible computational explanations for action recognition. In addition, only concrete implementations allow judging whether postulated computational concepts have a feasible implementation in terms of realistic neural circuits. Copyright © 2015 Elsevier Inc. All rights reserved.
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Overcoming misconceptions in quantum mechanics with the time evolution operator
International Nuclear Information System (INIS)
Garcia Quijas, P C; Arevalo Aguilar, L M
2007-01-01
Recently, there have been many efforts to use the research techniques developed in the field of physics education research to improve the teaching and learning of quantum mechanics. In particular, part of this research is focusing on misconceptions held by students. For instance, a set of misconceptions is associated with the concept of stationary states. In this paper, we argue that a possible way to remove these is to solve the Schroedinger equation using the evolution operator method (EOM), and stress the fact that to find stationary states is only the first step in solving that equation. The EOM consists in solving the Schroedinger equation by direct integration, i.e. Ψ(x, t) = U(t)Ψ(x, 0), where U(t)=e -itH-hat/h is the time evolution operator, and Ψ(x, 0) is the initial state. We apply the evolution operator method in the case of the harmonic oscillator
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Censor, Nitzan; Cohen, Leonardo G
2011-01-01
In the last two decades, there has been a rapid development in the research of the physiological brain mechanisms underlying human motor learning and memory. While conventional memory research performed on animal models uses intracellular recordings, microfusion of protein inhibitors to specific brain areas and direct induction of focal brain lesions, human research has so far utilized predominantly behavioural approaches and indirect measurements of neural activity. Repetitive transcranial magnetic stimulation (rTMS), a safe non-invasive brain stimulation technique, enables the study of the functional role of specific cortical areas by evaluating the behavioural consequences of selective modulation of activity (excitation or inhibition) on memory generation and consolidation, contributing to the understanding of the neural substrates of motor learning. Depending on the parameters of stimulation, rTMS can also facilitate learning processes, presumably through purposeful modulation of excitability in specific brain regions. rTMS has also been used to gain valuable knowledge regarding the timeline of motor memory formation, from initial encoding to stabilization and long-term retention. In this review, we summarize insights gained using rTMS on the physiological and neural mechanisms of human motor learning and memory. We conclude by suggesting possible future research directions, some with direct clinical implications.
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Memristor-based neural networks
International Nuclear Information System (INIS)
Thomas, Andy
2013-01-01
The synapse is a crucial element in biological neural networks, but a simple electronic equivalent has been absent. This complicates the development of hardware that imitates biological architectures in the nervous system. Now, the recent progress in the experimental realization of memristive devices has renewed interest in artificial neural networks. The resistance of a memristive system depends on its past states and exactly this functionality can be used to mimic the synaptic connections in a (human) brain. After a short introduction to memristors, we present and explain the relevant mechanisms in a biological neural network, such as long-term potentiation and spike time-dependent plasticity, and determine the minimal requirements for an artificial neural network. We review the implementations of these processes using basic electric circuits and more complex mechanisms that either imitate biological systems or could act as a model system for them. (topical review)
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Directory of Open Access Journals (Sweden)
Elif Isbell
2016-12-01
Full Text Available While a growing body of research has identified experiential factors associated with differences in selective attention, relatively little is known about the contribution of genetic factors to the skill of sustained selective attention, especially in early childhood. Here, we assessed the association between the serotonin transporter linked polymorphic region (5-HTTLPR genotypes and the neural mechanisms of selective attention in young children from lower socioeconomic status (SES backgrounds. Event-related potentials (ERPs were recorded during a dichotic listening task from 121 children (76 females, aged 40–67 months, who were also genotyped for the short and long allele of 5-HTTLPR. The effect of selective attention was measured as the difference in ERP mean amplitudes elicited by identical probe stimuli embedded in stories when they were attended versus unattended. Compared to children homozygous for the long allele, children who carried at least one copy of the short allele showed larger effects of selective attention on neural processing. These findings link the short allele of the 5-HTTLPR to enhanced neural mechanisms of selective attention and lay the groundwork for future studies of gene-by-environment interactions in the context of key cognitive skills.
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Sequerra, Eduardo B; Goyal, Raman; Castro, Patricio A; Levin, Jacqueline B; Borodinsky, Laura N
2018-05-16
Failure of neural tube closure leads to neural tube defects (NTDs), which can have serious neurological consequences or be lethal. Use of antiepileptic drugs (AEDs) during pregnancy increases the incidence of NTDs in offspring by unknown mechanisms. Here we show that during Xenopus laevis neural tube formation, neural plate cells exhibit spontaneous calcium dynamics that are partially mediated by glutamate signaling. We demonstrate that NMDA receptors are important for the formation of the neural tube and that the loss of their function induces an increase in neural plate cell proliferation and impairs neural cell migration, which result in NTDs. We present evidence that the AED valproic acid perturbs glutamate signaling, leading to NTDs that are rescued with varied efficacy by preventing DNA synthesis, activating NMDA receptors, or recruiting the NMDA receptor target ERK1/2. These findings may prompt mechanistic identification of AEDs that do not interfere with neural tube formation. SIGNIFICANCE STATEMENT Neural tube defects are one of the most common birth defects. Clinical investigations have determined that the use of antiepileptic drugs during pregnancy increases the incidence of these defects in the offspring by unknown mechanisms. This study discovers that glutamate signaling regulates neural plate cell proliferation and oriented migration and is necessary for neural tube formation. We demonstrate that the widely used antiepileptic drug valproic acid interferes with glutamate signaling and consequently induces neural tube defects, challenging the current hypotheses arguing that they are side effects of this antiepileptic drug that cause the increased incidence of these defects. Understanding the mechanisms of neurotransmitter signaling during neural tube formation may contribute to the identification and development of antiepileptic drugs that are safer during pregnancy. Copyright © 2018 the authors 0270-6474/18/384762-12$15.00/0.
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Coubard, Olivier A.
2016-01-01
Since the seminal report by Shapiro that bilateral stimulation induces cognitive and emotional changes, twenty-six years of basic and clinical research have examined the effects of Eye Movement Desensitization and Reprocessing (EMDR) in anxiety disorders, particularly in Post-Traumatic Stress Disorder (PTSD). The present article aims at better understanding EMDR neural mechanism. I first review procedural aspects of EMDR protocol and theoretical hypothesis about EMDR effects, and develop the ...
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Modeling evolution of the mind and cultures: emotional Sapir-Whorf hypothesis
Perlovsky, Leonid I.
2009-05-01
Evolution of cultures is ultimately determined by mechanisms of the human mind. The paper discusses the mechanisms of evolution of language from primordial undifferentiated animal cries to contemporary conceptual contents. In parallel with differentiation of conceptual contents, the conceptual contents were differentiated from emotional contents of languages. The paper suggests the neural brain mechanisms involved in these processes. Experimental evidence and theoretical arguments are discussed, including mathematical approaches to cognition and language: modeling fields theory, the knowledge instinct, and the dual model connecting language and cognition. Mathematical results are related to cognitive science, linguistics, and psychology. The paper gives an initial mathematical formulation and mean-field equations for the hierarchical dynamics of both the human mind and culture. In the mind heterarchy operation of the knowledge instinct manifests through mechanisms of differentiation and synthesis. The emotional contents of language are related to language grammar. The conclusion is an emotional version of Sapir-Whorf hypothesis. Cultural advantages of "conceptual" pragmatic cultures, in which emotionality of language is diminished and differentiation overtakes synthesis resulting in fast evolution at the price of self doubts and internal crises are compared to those of traditional cultures where differentiation lags behind synthesis, resulting in cultural stability at the price of stagnation. Multi-language, multi-ethnic society might combine the benefits of stability and fast differentiation. Unsolved problems and future theoretical and experimental directions are discussed.
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National Research Council Canada - National Science Library
Greer, James
2002-01-01
This dissertation presents a systematic design methodology for directed product evolution that uses both rigid body and compliant mechanisms to facilitate component combination in the domain of mechanical products...
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Differential Evolution Algorithm with Self-Adaptive Population Resizing Mechanism
Directory of Open Access Journals (Sweden)
Xu Wang
2013-01-01
Full Text Available A differential evolution (DE algorithm with self-adaptive population resizing mechanism, SapsDE, is proposed to enhance the performance of DE by dynamically choosing one of two mutation strategies and tuning control parameters in a self-adaptive manner. More specifically, more appropriate mutation strategies along with its parameter settings can be determined adaptively according to the previous status at different stages of the evolution process. To verify the performance of SapsDE, 17 benchmark functions with a wide range of dimensions, and diverse complexities are used. Nonparametric statistical procedures were performed for multiple comparisons between the proposed algorithm and five well-known DE variants from the literature. Simulation results show that SapsDE is effective and efficient. It also exhibits much more superiorresultsthan the other five algorithms employed in the comparison in most of the cases.
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Sugarcane bagasse gasification: Global reaction mechanism of syngas evolution
International Nuclear Information System (INIS)
Ahmed, I.I.; Gupta, A.K.
2012-01-01
Highlights: ► Gasification of sugarcane bagasse has been investigated using a semi batch reactor. ► Global reaction mechanism combining pyrolysis and gasification reactions is presented. ► High flow rates of syngas supported fragmentation and secondary reactions. ► CO flow rate increased at higher heating rates at the expense of CO 2 production. ► At high temperatures merger between pyrolysis and char gasification occurs. -- Abstract: Steam gasification of sugarcane bagasse has been investigated. A semi batch reactor with a fixed amount of sugarcane bagasse sample placed in steady flow of high temperature steam at atmospheric pressure has been used. The gasification of bagasse was examined at reactor and steam temperatures of 800, 900 and 1000 °C. The evolution of syngas flow rate and chemical composition has been monitored. The evolution of chemical composition and total flow rate of the syngas has been used to formulate a global reaction mechanism. The mechanism combines pyrolysis reaction mechanisms from the literature and steam gasification/reforming reactions. Steam gasification steps include steam–hydrocarbons reforming, char gasification and water gas shift reactions. Evidence of fragmentation, secondary ring opening reactions and tertiary reactions resulting in formation of gaseous hydrocarbons is supported by higher flow rates of syngas and hydrogen at high heating rates and high reactor temperatures. Increase in carbon monoxide flow rate at the expense of carbon dioxide flow rate with the increase in reactor temperature has been observed. This increase in the ratio of CO/CO 2 flow rate confirms the production of CO and CO 2 from the competing reaction routes. At 1000 °C gasification a total merging between the pyrolysis step and the char gasification step has been observed. This is attributed to acceleration of char gasification reactions and acceleration of steam–hydrocarbons reforming reactions. These hydrocarbons are the precursors to
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A canonical neural mechanism for behavioral variability
Darshan, Ran; Wood, William E.; Peters, Susan; Leblois, Arthur; Hansel, David
2017-05-01
The ability to generate variable movements is essential for learning and adjusting complex behaviours. This variability has been linked to the temporal irregularity of neuronal activity in the central nervous system. However, how neuronal irregularity actually translates into behavioural variability is unclear. Here we combine modelling, electrophysiological and behavioural studies to address this issue. We demonstrate that a model circuit comprising topographically organized and strongly recurrent neural networks can autonomously generate irregular motor behaviours. Simultaneous recordings of neurons in singing finches reveal that neural correlations increase across the circuit driving song variability, in agreement with the model predictions. Analysing behavioural data, we find remarkable similarities in the babbling statistics of 5-6-month-old human infants and juveniles from three songbird species and show that our model naturally accounts for these `universal' statistics.
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Sensitive Periods, Vasotocin-Family Peptides, and the Evolution and Development of Social Behavior
Directory of Open Access Journals (Sweden)
Nicole M. Baran
2017-08-01
Full Text Available Nonapeptides, by modulating the activity of neural circuits in specific social contexts, provide an important mechanism underlying the evolution of diverse behavioral phenotypes across vertebrate taxa. Vasotocin-family nonapeptides, in particular, have been found to be involved in behavioral plasticity and diversity in social behavior, including seasonal variation, sexual dimorphism, and species differences. Although nonapeptides have been the focus of a great deal of research over the last several decades, the vast majority of this work has focused on adults. However, behavioral diversity may also be explained by the ways in which these peptides shape neural circuits and influence social processes during development. In this review, I synthesize comparative work on vasotocin-family peptides during development and classic work on early forms of social learning in developmental psychobiology. I also summarize recent work demonstrating that early life manipulations of the nonapeptide system alter attachment, affiliation, and vocal learning in zebra finches. I thus hypothesize that vasotocin-family peptides are involved in the evolution of social behaviors through their influence on learning during sensitive periods in social development.
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Seminar on support mechanisms to renewable energy sources and on electricity markets evolution
International Nuclear Information System (INIS)
Abadie, Pierre-Marie; Leinekugel Le Cocq, Thibaut; Najdawi, Celine; Rathmann, Max; Soekadar, Ann-Christin
2013-01-01
The French-German office for Renewable energies (OFAEnR) organised a Seminar on support mechanisms to renewable energy sources and on electricity markets evolution. In the framework of this French-German exchange of experience, about 150 participants exchanged views on support instruments to renewable energy sources in a context of decentralized power generation and evolving market design. This document brings together the available presentations (slides) made during this event: 1 - Overview of Support mechanisms to renewable energy sources and electricity market evolution in France (Pierre-Marie Abadie); 2 - Support mechanisms in Germany and in France. Similarities and Synergy potentials (Celine Najdawi); 3 - Keynote 'introduction to the French capacity market' (Thibaut Leinekugel Le Cocq); 4 - Power market design for a high renewables share (Max Rathmann); 5 - German electricity System and Integration of Renewable energies. The Current Discussion on the Necessity of Adapting the electricity Market Design (Ann-Christin Soekadar)
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Statistical mechanics of neocortical interactions: Path-integral evolution of short-term memory
Ingber, Lester
1994-05-01
Previous papers in this series of statistical mechanics of neocortical interactions (SMNI) have detailed a development from the relatively microscopic scales of neurons up to the macroscopic scales as recorded by electroencephalography (EEG), requiring an intermediate mesocolumnar scale to be developed at the scale of minicolumns (~=102 neurons) and macrocolumns (~=105 neurons). Opportunity was taken to view SMNI as sets of statistical constraints, not necessarily describing specific synaptic or neuronal mechanisms, on neuronal interactions, on some aspects of short-term memory (STM), e.g., its capacity, stability, and duration. A recently developed c-language code, pathint, provides a non-Monte Carlo technique for calculating the dynamic evolution of arbitrary-dimension (subject to computer resources) nonlinear Lagrangians, such as derived for the two-variable SMNI problem. Here, pathint is used to explicitly detail the evolution of the SMNI constraints on STM.
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Energy Technology Data Exchange (ETDEWEB)
Datta, S.
1999-10-01
The effect of composition and controlled thermomechanical process parameters on the mechanical properties of HSLA steels is modelled using the Widrow-Hoff's concept of training a neural net with feed-forward topology by applying Rumelhart's back propagation type algorithm for supervised learning, using a Petri like net structure. The data used are from laboratory experiments as well as from the published literature. The results from the neural network are found to be consistent and in good agreement with the experimented results. (author)
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Information-theoretic metamodel of organizational evolution
Sepulveda, Alfredo
2011-12-01
Social organizations are abstractly modeled by holarchies---self-similar connected networks---and intelligent complex adaptive multiagent systems---large networks of autonomous reasoning agents interacting via scaled processes. However, little is known of how information shapes evolution in such organizations, a gap that can lead to misleading analytics. The research problem addressed in this study was the ineffective manner in which classical model-predict-control methods used in business analytics attempt to define organization evolution. The purpose of the study was to construct an effective metamodel for organization evolution based on a proposed complex adaptive structure---the info-holarchy. Theoretical foundations of this study were holarchies, complex adaptive systems, evolutionary theory, and quantum mechanics, among other recently developed physical and information theories. Research questions addressed how information evolution patterns gleamed from the study's inductive metamodel more aptly explained volatility in organization. In this study, a hybrid grounded theory based on abstract inductive extensions of information theories was utilized as the research methodology. An overarching heuristic metamodel was framed from the theoretical analysis of the properties of these extension theories and applied to business, neural, and computational entities. This metamodel resulted in the synthesis of a metaphor for, and generalization of organization evolution, serving as the recommended and appropriate analytical tool to view business dynamics for future applications. This study may manifest positive social change through a fundamental understanding of complexity in business from general information theories, resulting in more effective management.
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Isbell, Elif; Stevens, Courtney; Hampton Wray, Amanda; Bell, Theodore; Neville, Helen J
2016-12-01
While a growing body of research has identified experiential factors associated with differences in selective attention, relatively little is known about the contribution of genetic factors to the skill of sustained selective attention, especially in early childhood. Here, we assessed the association between the serotonin transporter linked polymorphic region (5-HTTLPR) genotypes and the neural mechanisms of selective attention in young children from lower socioeconomic status (SES) backgrounds. Event-related potentials (ERPs) were recorded during a dichotic listening task from 121 children (76 females, aged 40-67 months), who were also genotyped for the short and long allele of 5-HTTLPR. The effect of selective attention was measured as the difference in ERP mean amplitudes elicited by identical probe stimuli embedded in stories when they were attended versus unattended. Compared to children homozygous for the long allele, children who carried at least one copy of the short allele showed larger effects of selective attention on neural processing. These findings link the short allele of the 5-HTTLPR to enhanced neural mechanisms of selective attention and lay the groundwork for future studies of gene-by-environment interactions in the context of key cognitive skills. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
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International Nuclear Information System (INIS)
Yuan Wujie; Luo Xiaoshu; Jiang Pinqun
2007-01-01
In this paper, we propose a new model of weighted small-world biological neural networks based on biophysical Hodgkin-Huxley neurons with side-restrain mechanism. Then we study excitement properties of the model under alternating current (AC) stimulation. The study shows that the excitement properties in the networks are preferably consistent with the behavior properties of a brain nervous system under different AC stimuli, such as refractory period and the brain neural excitement response induced by different intensities of noise and coupling. The results of the study have reference worthiness for the brain nerve electrophysiology and epistemological science.
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Synthesis of dexterity measure of mechanisms by evolution of dissipative system
Directory of Open Access Journals (Sweden)
Grešl M.
2007-11-01
Full Text Available The paper deals with the new approach of solving traditional kinematical synthesis of mechanisms. The kinematical synthesis is reformulated as nonlinear dynamical problem. All searched parameters of the mechanism are in this dynamical dissipative system introduced as time-varying during motion of mechanism’s dimension iteration. The synthesis process is realized as the time evolution of such system. One of the most important objectives of the machine synthesis is the dexterity measure. The new approach is applied to optimization of this property.
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Without it no music: cognition, biology and evolution of musicality.
Honing, Henkjan; ten Cate, Carel; Peretz, Isabelle; Trehub, Sandra E
2015-03-19
Musicality can be defined as a natural, spontaneously developing trait based on and constrained by biology and cognition. Music, by contrast, can be defined as a social and cultural construct based on that very musicality. One critical challenge is to delineate the constituent elements of musicality. What biological and cognitive mechanisms are essential for perceiving, appreciating and making music? Progress in understanding the evolution of music cognition depends upon adequate characterization of the constituent mechanisms of musicality and the extent to which they are present in non-human species. We argue for the importance of identifying these mechanisms and delineating their functions and developmental course, as well as suggesting effective means of studying them in human and non-human animals. It is virtually impossible to underpin the evolutionary role of musicality as a whole, but a multicomponent perspective on musicality that emphasizes its constituent capacities, development and neural cognitive specificity is an excellent starting point for a research programme aimed at illuminating the origins and evolution of musical behaviour as an autonomous trait. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
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Pla, Patrick; Monsoro-Burq, Anne H
2018-05-28
The neural crest is induced at the edge between the neural plate and the nonneural ectoderm, in an area called the neural (plate) border, during gastrulation and neurulation. In recent years, many studies have explored how this domain is patterned, and how the neural crest is induced within this territory, that also participates to the prospective dorsal neural tube, the dorsalmost nonneural ectoderm, as well as placode derivatives in the anterior area. This review highlights the tissue interactions, the cell-cell signaling and the molecular mechanisms involved in this dynamic spatiotemporal patterning, resulting in the induction of the premigratory neural crest. Collectively, these studies allow building a complex neural border and early neural crest gene regulatory network, mostly composed by transcriptional regulations but also, more recently, including novel signaling interactions. Copyright © 2018. Published by Elsevier Inc.
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The Importance of ncRNAs as Epigenetic Mechanisms in Phenotypic Variation and Organic Evolution
Directory of Open Access Journals (Sweden)
Daniel Frías-Lasserre
2017-12-01
Full Text Available Neo-Darwinian explanations of organic evolution have settled on mutation as the principal factor in producing evolutionary novelty. Mechanistic characterizations have been also biased by the classic dogma of molecular biology, where only proteins regulate gene expression. This together with the rearrangement of genetic information, in terms of genes and chromosomes, was considered the cornerstone of evolution at the level of natural populations. This predominant view excluded both alternative explanations and phenomenologies that did not fit its paradigm. With the discovery of non-coding RNAs (ncRNAs and their role in the control of genetic expression, new mechanisms arose providing heuristic power to complementary explanations to evolutionary processes overwhelmed by mainstream genocentric views. Viruses, epimutation, paramutation, splicing, and RNA editing have been revealed as paramount functions in genetic variations, phenotypic plasticity, and diversity. This article discusses how current epigenetic advances on ncRNAs have changed the vision of the mechanisms that generate variation, how organism-environment interaction can no longer be underestimated as a driver of organic evolution, and how it is now part of the transgenerational inheritance and evolution of species.
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Quantum ballistic evolution in quantum mechanics: Application to quantum computers
International Nuclear Information System (INIS)
Benioff, P.
1996-01-01
Quantum computers are important examples of processes whose evolution can be described in terms of iterations of single-step operators or their adjoints. Based on this, Hamiltonian evolution of processes with associated step operators T is investigated here. The main limitation of this paper is to processes which evolve quantum ballistically, i.e., motion restricted to a collection of nonintersecting or distinct paths on an arbitrary basis. The main goal of this paper is proof of a theorem which gives necessary and sufficient conditions that T must satisfy so that there exists a Hamiltonian description of quantum ballistic evolution for the process, namely, that T is a partial isometry and is orthogonality preserving and stable on some basis. Simple examples of quantum ballistic evolution for quantum Turing machines with one and with more than one type of elementary step are discussed. It is seen that for nondeterministic machines the basis set can be quite complex with much entanglement present. It is also proven that, given a step operator T for an arbitrary deterministic quantum Turing machine, it is decidable if T is stable and orthogonality preserving, and if quantum ballistic evolution is possible. The proof fails if T is a step operator for a nondeterministic machine. It is an open question if such a decision procedure exists for nondeterministic machines. This problem does not occur in classical mechanics. Also the definition of quantum Turing machines used here is compared with that used by other authors. copyright 1996 The American Physical Society
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Distracted and down: neural mechanisms of affective interference in subclinical depression.
Kaiser, Roselinde H; Andrews-Hanna, Jessica R; Spielberg, Jeffrey M; Warren, Stacie L; Sutton, Bradley P; Miller, Gregory A; Heller, Wendy; Banich, Marie T
2015-05-01
Previous studies have shown that depressed individuals have difficulty directing attention away from negative distractors, a phenomenon known as affective interference. However, findings are mixed regarding the neural mechanisms and network dynamics of affective interference. The present study addressed these issues by comparing neural activation during emotion-word and color-word Stroop tasks in participants with varying levels of (primarily subclinical) depression. Depressive symptoms predicted increased activation to negative distractors in areas of dorsal anterior cingulate cortex (dACC) and posterior cingulate cortex (PCC), regions implicated in cognitive control and internally directed attention, respectively. Increased dACC activity was also observed in the group-average response to incongruent distractors, suggesting that dACC activity during affective interference is related to overtaxed cognitive control. In contrast, regions of PCC were deactivated across the group in response to incongruent distractors, suggesting that PCC activity during affective interference represents task-independent processing. A psychophysiological interaction emerged in which higher depression predicted more positively correlated activity between dACC and PCC during affective interference, i.e. greater connectivity between cognitive control and internal-attention systems. These findings suggest that, when individuals high in depression are confronted by negative material, increased attention to internal thoughts and difficulty shifting resources to the external world interfere with goal-directed behavior. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
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Evolution and development of brain networks: from Caenorhabditis elegans to Homo sapiens.
Kaiser, Marcus; Varier, Sreedevi
2011-01-01
Neural networks show a progressive increase in complexity during the time course of evolution. From diffuse nerve nets in Cnidaria to modular, hierarchical systems in macaque and humans, there is a gradual shift from simple processes involving a limited amount of tasks and modalities to complex functional and behavioral processing integrating different kinds of information from highly specialized tissue. However, studies in a range of species suggest that fundamental similarities, in spatial and topological features as well as in developmental mechanisms for network formation, are retained across evolution. 'Small-world' topology and highly connected regions (hubs) are prevalent across the evolutionary scale, ensuring efficient processing and resilience to internal (e.g. lesions) and external (e.g. environment) changes. Furthermore, in most species, even the establishment of hubs, long-range connections linking distant components, and a modular organization, relies on similar mechanisms. In conclusion, evolutionary divergence leads to greater complexity while following essential developmental constraints.
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Harlé, K.M.; Chang, L.J.; Wout, M. van 't; Sanfey, A.G.
2012-01-01
Though emotions have been shown to have sometimes dramatic effects on decision-making, the neural mechanisms mediating these biases are relatively unexplored. Here, we investigated how incidental affect (i.e. emotional states unrelated to the decision at hand) may influence decisions, and how these
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Cognitive abnormalities and neural mechanisms in post-traumatic stress disorder
Directory of Open Access Journals (Sweden)
Ting HU
2017-10-01
Full Text Available Post-traumatic stress disorder (PTSD is an anxiety disorder that develops usually in response to an overwhelmingly terrifying or a life-threatening event. The symptoms including intrusion, flashback, re-experiencing, hyperarousal and avoidance can seriously impair the cognitive functions. At present, the researches have found PTSD patients had the difficulty in retrieving autobiographical memory and narrative disorder, attention bias toward traumatic stimulus and intellectual decline. Decrease in hippocampus and amygdala's volumes, excess endoplasmic reticulum stress, medial prefrontal cortex's low activation and highly excited response of the amygdala to the traumatic stimulus may be the neural mechanisms of cognitive abnormalities. In- depth research on cognitive abnormalities provides directions for PTSD prevention and treatment, and the cognitive treatment by prolonged exposure and attention control may be the effective method. DOI: 10.11855/j.issn.0577-7402.2017.09.14
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Neural robust stabilization via event-triggering mechanism and adaptive learning technique.
Wang, Ding; Liu, Derong
2018-06-01
The robust control synthesis of continuous-time nonlinear systems with uncertain term is investigated via event-triggering mechanism and adaptive critic learning technique. We mainly focus on combining the event-triggering mechanism with adaptive critic designs, so as to solve the nonlinear robust control problem. This can not only make better use of computation and communication resources, but also conduct controller design from the view of intelligent optimization. Through theoretical analysis, the nonlinear robust stabilization can be achieved by obtaining an event-triggered optimal control law of the nominal system with a newly defined cost function and a certain triggering condition. The adaptive critic technique is employed to facilitate the event-triggered control design, where a neural network is introduced as an approximator of the learning phase. The performance of the event-triggered robust control scheme is validated via simulation studies and comparisons. The present method extends the application domain of both event-triggered control and adaptive critic control to nonlinear systems possessing dynamical uncertainties. Copyright © 2018 Elsevier Ltd. All rights reserved.
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Foss-Feig, Jennifer H; Adkinson, Brendan D; Ji, Jie Lisa; Yang, Genevieve; Srihari, Vinod H; McPartland, James C; Krystal, John H; Murray, John D; Anticevic, Alan
2017-05-15
Recent theoretical accounts have proposed excitation and inhibition (E/I) imbalance as a possible mechanistic, network-level hypothesis underlying neural and behavioral dysfunction across neurodevelopmental disorders, particularly autism spectrum disorder (ASD) and schizophrenia (SCZ). These two disorders share some overlap in their clinical presentation as well as convergence in their underlying genes and neurobiology. However, there are also clear points of dissociation in terms of phenotypes and putatively affected neural circuitry. We highlight emerging work from the clinical neuroscience literature examining neural correlates of E/I imbalance across children and adults with ASD and adults with both chronic and early-course SCZ. We discuss findings from diverse neuroimaging studies across distinct modalities, conducted with electroencephalography, magnetoencephalography, proton magnetic resonance spectroscopy, and functional magnetic resonance imaging, including effects observed both during task and at rest. Throughout this review, we discuss points of convergence and divergence in the ASD and SCZ literature, with a focus on disruptions in neural E/I balance. We also consider these findings in relation to predictions generated by theoretical neuroscience, particularly computational models predicting E/I imbalance across disorders. Finally, we discuss how human noninvasive neuroimaging can benefit from pharmacological challenge studies to reveal mechanisms in ASD and SCZ. Collectively, we attempt to shed light on shared and divergent neuroimaging effects across disorders with the goal of informing future research examining the mechanisms underlying the E/I imbalance hypothesis across neurodevelopmental disorders. We posit that such translational efforts are vital to facilitate development of neurobiologically informed treatment strategies across neuropsychiatric conditions. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights
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How synapses can enhance sensibility of a neural network
Protachevicz, P. R.; Borges, F. S.; Iarosz, K. C.; Caldas, I. L.; Baptista, M. S.; Viana, R. L.; Lameu, E. L.; Macau, E. E. N.; Batista, A. M.
2018-02-01
In this work, we study the dynamic range in a neural network modelled by cellular automaton. We consider deterministic and non-deterministic rules to simulate electrical and chemical synapses. Chemical synapses have an intrinsic time-delay and are susceptible to parameter variations guided by learning Hebbian rules of behaviour. The learning rules are related to neuroplasticity that describes change to the neural connections in the brain. Our results show that chemical synapses can abruptly enhance sensibility of the neural network, a manifestation that can become even more predominant if learning rules of evolution are applied to the chemical synapses.
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Broster, Lucas S; Li, Juan; Wagner, Benjamin; Smith, Charles D; Jicha, Gregory A; Schmitt, Frederick A; Munro, Nancy; Haney, Ryan H; Jiang, Yang
2018-02-20
Individuals with dementia of the Alzheimer type (AD) classically show disproportionate impairment in measures of working memory, but repetition learning effects are relatively preserved. As AD affects brain regions implicated in both working memory and repetition effects, the neural basis of this discrepancy is poorly understood. We hypothesized that the posterior repetition effect could account for this discrepancy due to the milder effects of AD at visual cortex. Participants with early AD, amnestic mild cognitive impairment (MCI), and healthy controls performed a working memory task with superimposed repetition effects while electroencephalography was collected to identify possible neural mechanisms of preserved repetition effects. Participants with AD showed preserved behavioral repetition effects and a change in the posterior repetition effect. Visual cortex may play a role in maintained repetition effects in persons with early AD.
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Melkikh, Alexey V; Khrennikov, Andrei
2017-11-01
A review of the mechanisms of speciation is performed. The mechanisms of the evolution of species, taking into account the feedback of the state of the environment and mechanisms of the emergence of complexity, are considered. It is shown that these mechanisms, at the molecular level, cannot work steadily in terms of classical mechanics. Quantum mechanisms of changes in the genome, based on the long-range interaction potential between biologically important molecules, are proposed as one of possible explanation. Different variants of interactions of the organism and environment based on molecular recognition and leading to new species origins are considered. Experiments to verify the model are proposed. This bio-physical study is completed by the general operational model of based on quantum information theory. The latter is applied to model of epigenetic evolution. We briefly present the basics of the quantum-like approach to modeling of bio-informational processes. This approach is illustrated by the quantum-like model of epigenetic evolution. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Directory of Open Access Journals (Sweden)
A. V. Pavlov
2014-01-01
Full Text Available A mechanism of cognitive dissonance reducing is demonstrated with approach for non-monotonic fuzzy-valued logics by Fourier-holography technique implementation developing. Cognitive dissonance occurs under perceiving of new information that contradicts to the existing subjective pattern of the outside world, represented by double Fourier-transform cascade with a hologram – neural layers interconnections matrix of inner information representation and logical conclusion. The hologram implements monotonic logic according to “General Modus Ponens” rule. New information is represented by a hologram of exclusion that implements interconnections of logical conclusion and exclusion for neural layers. The latter are linked by Fourier transform that determines duality of the algebra forming operations of conjunction and disjunction. Hologram of exclusion forms conclusion that is dual to the “General Modus Ponens” conclusion. It is shown, that trained for the main rule and exclusion system can be represented by two-layered neural network with separate interconnection matrixes for direct and inverse iterations. The network energy function is involved determining the cyclic dynamics character; dissipative factor causing convergence type of the dynamics is analyzed. Both “General Modus Ponens” and exclusion holograms recording conditions on the dynamics and convergence of the system are demonstrated. The system converges to a stable status, in which logical conclusion doesn’t depend on the inner information. Such kind of dynamics, leading to tolerance forming, is typical for ordinary kind of thinking, aimed at inner pattern of outside world stability. For scientific kind of thinking, aimed at adequacy of the inner pattern of the world, a mechanism is needed to stop the net relaxation; the mechanism has to be external relative to the model of logic. Computer simulation results for the learning conditions adequate to real holograms recording are
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Neural crest does not contribute to the neck and shoulder in the axolotl (Ambystoma mexicanum).
Epperlein, Hans-Henning; Khattak, Shahryar; Knapp, Dunja; Tanaka, Elly M; Malashichev, Yegor B
2012-01-01
A major step during the evolution of tetrapods was their transition from water to land. This process involved the reduction or complete loss of the dermal bones that made up connections to the skull and a concomitant enlargement of the endochondral shoulder girdle. In the mouse the latter is derived from three separate embryonic sources: lateral plate mesoderm, somites, and neural crest. The neural crest was suggested to sustain the muscle attachments. How this complex composition of the endochondral shoulder girdle arose during evolution and whether it is shared by all tetrapods is unknown. Salamanders that lack dermal bone within their shoulder girdle were of special interest for a possible contribution of the neural crest to the endochondral elements and muscle attachment sites, and we therefore studied them in this context. We grafted neural crest from GFP+ fluorescent transgenic axolotl (Ambystoma mexicanum) donor embryos into white (d/d) axolotl hosts and followed the presence of neural crest cells within the cartilage of the shoulder girdle and the connective tissue of muscle attachment sites of the neck-shoulder region. Strikingly, neural crest cells did not contribute to any part of the endochondral shoulder girdle or to the connective tissue at muscle attachment sites in axolotl. Our results in axolotl suggest that neural crest does not serve a general function in vertebrate shoulder muscle attachment sites as predicted by the "muscle scaffold theory," and that it is not necessary to maintain connectivity of the endochondral shoulder girdle to the skull. Our data support the possibility that the contribution of the neural crest to the endochondral shoulder girdle, which is observed in the mouse, arose de novo in mammals as a developmental basis for their skeletal synapomorphies. This further supports the hypothesis of an increased neural crest diversification during vertebrate evolution.
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Neural crest does not contribute to the neck and shoulder in the axolotl (Ambystoma mexicanum.
Directory of Open Access Journals (Sweden)
Hans-Henning Epperlein
Full Text Available BACKGROUND: A major step during the evolution of tetrapods was their transition from water to land. This process involved the reduction or complete loss of the dermal bones that made up connections to the skull and a concomitant enlargement of the endochondral shoulder girdle. In the mouse the latter is derived from three separate embryonic sources: lateral plate mesoderm, somites, and neural crest. The neural crest was suggested to sustain the muscle attachments. How this complex composition of the endochondral shoulder girdle arose during evolution and whether it is shared by all tetrapods is unknown. Salamanders that lack dermal bone within their shoulder girdle were of special interest for a possible contribution of the neural crest to the endochondral elements and muscle attachment sites, and we therefore studied them in this context. RESULTS: We grafted neural crest from GFP+ fluorescent transgenic axolotl (Ambystoma mexicanum donor embryos into white (d/d axolotl hosts and followed the presence of neural crest cells within the cartilage of the shoulder girdle and the connective tissue of muscle attachment sites of the neck-shoulder region. Strikingly, neural crest cells did not contribute to any part of the endochondral shoulder girdle or to the connective tissue at muscle attachment sites in axolotl. CONCLUSIONS: Our results in axolotl suggest that neural crest does not serve a general function in vertebrate shoulder muscle attachment sites as predicted by the "muscle scaffold theory," and that it is not necessary to maintain connectivity of the endochondral shoulder girdle to the skull. Our data support the possibility that the contribution of the neural crest to the endochondral shoulder girdle, which is observed in the mouse, arose de novo in mammals as a developmental basis for their skeletal synapomorphies. This further supports the hypothesis of an increased neural crest diversification during vertebrate evolution.
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The Temporal Derivative of Expected Utility: A Neural Mechanism for Dynamic Decision-making
Zhang, Xian; Hirsch, Joy
2012-01-01
Real world tasks involving moving targets, such as driving a vehicle, are performed based on continuous decisions thought to depend upon the temporal derivative of the expected utility (∂V/∂t), where the expected utility (V) is the effective value of a future reward. However, those neural mechanisms that underlie dynamic decision-making are not well understood. This study investigates human neural correlates of both V and ∂V/∂t using fMRI and a novel experimental paradigm based on a pursuit-evasion game optimized to isolate components of dynamic decision processes. Our behavioral data show that players of the pursuit-evasion game adopt an exponential discounting function, supporting the expected utility theory. The continuous functions of V and ∂V/∂t were derived from the behavioral data and applied as regressors in fMRI analysis, enabling temporal resolution that exceeded the sampling rate of image acquisition, hyper-temporal resolution, by taking advantage of numerous trials that provide rich and independent manipulation of those variables. V and ∂V/∂t were each associated with distinct neural activity. Specifically, ∂V/∂t was associated with anterior and posterior cingulate cortices, superior parietal lobule, and ventral pallidum, whereas V was primarily associated with supplementary motor, pre and post central gyri, cerebellum, and thalamus. The association between the ∂V/∂t and brain regions previously related to decision-making is consistent with the primary role of the temporal derivative of expected utility in dynamic decision-making. PMID:22963852
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The temporal derivative of expected utility: a neural mechanism for dynamic decision-making.
Zhang, Xian; Hirsch, Joy
2013-01-15
Real world tasks involving moving targets, such as driving a vehicle, are performed based on continuous decisions thought to depend upon the temporal derivative of the expected utility (∂V/∂t), where the expected utility (V) is the effective value of a future reward. However, the neural mechanisms that underlie dynamic decision-making are not well understood. This study investigates human neural correlates of both V and ∂V/∂t using fMRI and a novel experimental paradigm based on a pursuit-evasion game optimized to isolate components of dynamic decision processes. Our behavioral data show that players of the pursuit-evasion game adopt an exponential discounting function, supporting the expected utility theory. The continuous functions of V and ∂V/∂t were derived from the behavioral data and applied as regressors in fMRI analysis, enabling temporal resolution that exceeded the sampling rate of image acquisition, hyper-temporal resolution, by taking advantage of numerous trials that provide rich and independent manipulation of those variables. V and ∂V/∂t were each associated with distinct neural activity. Specifically, ∂V/∂t was associated with anterior and posterior cingulate cortices, superior parietal lobule, and ventral pallidum, whereas V was primarily associated with supplementary motor, pre and post central gyri, cerebellum, and thalamus. The association between the ∂V/∂t and brain regions previously related to decision-making is consistent with the primary role of the temporal derivative of expected utility in dynamic decision-making. Copyright © 2012 Elsevier Inc. All rights reserved.
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Evolution of neural crest and placodes: amphioxus as a model for the ancestral vertebrate?
Holland, L. Z.; Holland, N. D.
2001-01-01
Recent studies of protochordates (ascidian tunicates and amphioxus) have given insights into possible ancestors of 2 of the characteristic features of the vertebrate head: neural crest and placodes. The neural crest probably evolved from cells on either side of the neural plate-epidermis boundary in a protochordate ancestral to the vertebrates. In amphioxus, homologues of several vertebrate neural crest marker genes (BMP2/4, Pax3/7, Msx, Dll and Snail) are expressed at the edges of the neural plate and/or adjacent nonneural ectoderm. Some of these markers are also similarly expressed in tunicates. In protochordates, however, these cells, unlike vertebrate neural crest, neither migrate as individuals through embryonic tissues nor differentiate into a wide spectrum of cell types. Therefore, while the protochordate ancestor of the vertebrates probably had the beginnings of a genetic programme for neural crest formation, this programme was augmented in the earliest vertebrates to attain definitive neural crest. Clear homologues of vertebrate placodes are lacking in protochordates. However, both amphioxus and tunicates have ectodermal sensory cells. In tunicates these are all primary neurons, sending axons to the central nervous system, while in amphioxus, the ectodermal sensory cells include both primary neurons and secondary neurons lacking axons. Comparisons of developmental gene expression suggest that the anterior ectoderm in amphioxus may be homologous to the vertebrate olfactory placode, the only vertebrate placode with primary, not secondary, neurons. Similarly, biochemical, morphological and gene expression data suggest that amphioxus and tunicates also have homologues of the adenohypophysis, one of the few vertebrate structures derived from nonneurogenic placodes. In contrast, the origin of the other vertebrate placodes is very uncertain.
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Tian, Jianqiu; Liu, Enlong; Jiang, Lian; Jiang, Xiaoqiong; Sun, Yi; Xu, Ran
2018-06-01
In order to study the influence of particle shape on the microstructure evolution and the mechanical properties of granular materials, a two-dimensional DEM analysis of samples with three particle shapes, including circular particles, triangular particles, and elongated particles, is proposed here to simulate the direct shear tests of coarse-grained soils. For the numerical test results, analyses are conducted in terms of particle rotations, fabric evolution, and average path length evolution. A modified Rowe's stress-dilatancy equation is also proposed and successfully fitted onto simulation data.
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Wang, Cong; Hill, David J
2006-01-01
One of the amazing successes of biological systems is their ability to "learn by doing" and so adapt to their environment. In this paper, first, a deterministic learning mechanism is presented, by which an appropriately designed adaptive neural controller is capable of learning closed-loop system dynamics during tracking control to a periodic reference orbit. Among various neural network (NN) architectures, the localized radial basis function (RBF) network is employed. A property of persistence of excitation (PE) for RBF networks is established, and a partial PE condition of closed-loop signals, i.e., the PE condition of a regression subvector constructed out of the RBFs along a periodic state trajectory, is proven to be satisfied. Accurate NN approximation for closed-loop system dynamics is achieved in a local region along the periodic state trajectory, and a learning ability is implemented during a closed-loop feedback control process. Second, based on the deterministic learning mechanism, a neural learning control scheme is proposed which can effectively recall and reuse the learned knowledge to achieve closed-loop stability and improved control performance. The significance of this paper is that the presented deterministic learning mechanism and the neural learning control scheme provide elementary components toward the development of a biologically-plausible learning and control methodology. Simulation studies are included to demonstrate the effectiveness of the approach.
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Fracture Mechanics Method for Word Embedding Generation of Neural Probabilistic Linguistic Model.
Bi, Size; Liang, Xiao; Huang, Ting-Lei
2016-01-01
Word embedding, a lexical vector representation generated via the neural linguistic model (NLM), is empirically demonstrated to be appropriate for improvement of the performance of traditional language model. However, the supreme dimensionality that is inherent in NLM contributes to the problems of hyperparameters and long-time training in modeling. Here, we propose a force-directed method to improve such problems for simplifying the generation of word embedding. In this framework, each word is assumed as a point in the real world; thus it can approximately simulate the physical movement following certain mechanics. To simulate the variation of meaning in phrases, we use the fracture mechanics to do the formation and breakdown of meaning combined by a 2-gram word group. With the experiments on the natural linguistic tasks of part-of-speech tagging, named entity recognition and semantic role labeling, the result demonstrated that the 2-dimensional word embedding can rival the word embeddings generated by classic NLMs, in terms of accuracy, recall, and text visualization.
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TensorCalculator: exploring the evolution of mechanical stress in the CCMV capsid
Kononova, Olga; Maksudov, Farkhad; Marx, Kenneth A.; Barsegov, Valeri
2018-01-01
A new computational methodology for the accurate numerical calculation of the Cauchy stress tensor, stress invariants, principal stress components, von Mises and Tresca tensors is developed. The methodology is based on the atomic stress approach which permits the calculation of stress tensors, widely used in continuum mechanics modeling of materials properties, using the output from the MD simulations of discrete atomic and C_α -based coarse-grained structural models of biological particles. The methodology mapped into the software package TensorCalculator was successfully applied to the empty cowpea chlorotic mottle virus (CCMV) shell to explore the evolution of mechanical stress in this mechanically-tested specific example of a soft virus capsid. We found an inhomogeneous stress distribution in various portions of the CCMV structure and stress transfer from one portion of the virus structure to another, which also points to the importance of entropic effects, often ignored in finite element analysis and elastic network modeling. We formulate a criterion for elastic deformation using the first principal stress components. Furthermore, we show that von Mises and Tresca stress tensors can be used to predict the onset of a viral capsid’s mechanical failure, which leads to total structural collapse. TensorCalculator can be used to study stress evolution and dynamics of defects in viral capsids and other large-size protein assemblies.
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Spatial evolution of quantum mechanical states
Christensen, N. D.; Unger, J. E.; Pinto, S.; Su, Q.; Grobe, R.
2018-02-01
The time-dependent Schrödinger equation is solved traditionally as an initial-time value problem, where its solution is obtained by the action of the unitary time-evolution propagator on the quantum state that is known at all spatial locations but only at t = 0. We generalize this approach by examining the spatial evolution from a state that is, by contrast, known at all times t, but only at one specific location. The corresponding spatial-evolution propagator turns out to be pseudo-unitary. In contrast to the real energies that govern the usual (unitary) time evolution, the spatial evolution can therefore require complex phases associated with dynamically relevant solutions that grow exponentially. By introducing a generalized scalar product, for which the spatial generator is Hermitian, one can show that the temporal integral over the probability current density is spatially conserved, in full analogy to the usual norm of the state, which is temporally conserved. As an application of the spatial propagation formalism, we introduce a spatial backtracking technique that permits us to reconstruct any quantum information about an atom from the ionization data measured at a detector outside the interaction region.
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Differential evolution and simulated annealing algorithms for mechanical systems design
Directory of Open Access Journals (Sweden)
H. Saruhan
2014-09-01
Full Text Available In this study, nature inspired algorithms – the Differential Evolution (DE and the Simulated Annealing (SA – are utilized to seek a global optimum solution for ball bearings link system assembly weight with constraints and mixed design variables. The Genetic Algorithm (GA and the Evolution Strategy (ES will be a reference for the examination and validation of the DE and the SA. The main purpose is to minimize the weight of an assembly system composed of a shaft and two ball bearings. Ball bearings link system is used extensively in many machinery applications. Among mechanical systems, designers pay great attention to the ball bearings link system because of its significant industrial importance. The problem is complex and a time consuming process due to mixed design variables and inequality constraints imposed on the objective function. The results showed that the DE and the SA performed and obtained convergence reliability on the global optimum solution. So the contribution of the DE and the SA application to the mechanical system design can be very useful in many real-world mechanical system design problems. Beside, the comparison confirms the effectiveness and the superiority of the DE over the others algorithms – the SA, the GA, and the ES – in terms of solution quality. The ball bearings link system assembly weight of 634,099 gr was obtained using the DE while 671,616 gr, 728213.8 gr, and 729445.5 gr were obtained using the SA, the ES, and the GA respectively.
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Damage evolution and failure mechanisms in additively manufactured stainless steel
Energy Technology Data Exchange (ETDEWEB)
Carlton, Holly D., E-mail: carlton4@llnl.gov [Materials Engineering Division, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA 94550 (United States); Haboub, Abdel [Lincoln University, Life and Physical Sciences Department, 820 Chestnut St, Jefferson City, MO 65101 (United States); Gallegos, Gilbert F. [Materials Engineering Division, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA 94550 (United States); Parkinson, Dilworth Y.; MacDowell, Alastair A. [Advanced Light Source, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720 (United States)
2016-01-10
In situ tensile tests were performed on additively manufactured austenitic stainless steel to track damage evolution within the material. For these experiments Synchrotron Radiation micro-Tomography was used to measure three-dimensional pore volume, distribution, and morphology in stainless steel at the micrometer length-scale while tensile loading was applied. The results showed that porosity distribution played a larger role in affecting the fracture mechanisms than measured bulk density. Specifically, additively manufactured stainless steel specimens with large inhomogeneous void distributions displayed a flaw-dominated failure where cracks were shown to initiate at pre-existing voids, while annealed additively manufactured stainless steel specimens, which contained low porosity and randomly distributed pores, displayed fracture mechanisms that closely resembled wrought metal.
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Directory of Open Access Journals (Sweden)
Alexander eHuk
2012-10-01
Full Text Available A recent line of work has found remarkable success in relating perceptual decision-making and the spiking activity in the macaque lateral intraparietal area (LIP. In this review, we focus on questions about the neural computations in LIP that are not answered by demonstrations of neural correlates of psychological processes. We highlight three areas of limitations in our current understanding of the precise neural computations that might underlie neural correlates of decisions: (1 empirical questions not yet answered by existing data; (2 implementation issues related to how neural circuits could actually implement the mechanisms suggested by both physiology and psychology; and (3 ecological constraints related to the use of well-controlled laboratory tasks and whether they provide an accurate window on sensorimotor computation. These issues motivate the adoption of a more general encoding-decoding framework that will be fruitful for more detailed contemplation of how neural computations in LIP relate to the formation of perceptual decisions.
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Language and Cognition Interaction Neural Mechanisms
Directory of Open Access Journals (Sweden)
Leonid Perlovsky
2011-01-01
Full Text Available How language and cognition interact in thinking? Is language just used for communication of completed thoughts, or is it fundamental for thinking? Existing approaches have not led to a computational theory. We develop a hypothesis that language and cognition are two separate but closely interacting mechanisms. Language accumulates cultural wisdom; cognition develops mental representations modeling surrounding world and adapts cultural knowledge to concrete circumstances of life. Language is acquired from surrounding language “ready-made” and therefore can be acquired early in life. This early acquisition of language in childhood encompasses the entire hierarchy from sounds to words, to phrases, and to highest concepts existing in culture. Cognition is developed from experience. Yet cognition cannot be acquired from experience alone; language is a necessary intermediary, a “teacher.” A mathematical model is developed; it overcomes previous difficulties and leads to a computational theory. This model is consistent with Arbib's “language prewired brain” built on top of mirror neuron system. It models recent neuroimaging data about cognition, remaining unnoticed by other theories. A number of properties of language and cognition are explained, which previously seemed mysterious, including influence of language grammar on cultural evolution, which may explain specifics of English and Arabic cultures.
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Language and cognition interaction neural mechanisms.
Perlovsky, Leonid
2011-01-01
How language and cognition interact in thinking? Is language just used for communication of completed thoughts, or is it fundamental for thinking? Existing approaches have not led to a computational theory. We develop a hypothesis that language and cognition are two separate but closely interacting mechanisms. Language accumulates cultural wisdom; cognition develops mental representations modeling surrounding world and adapts cultural knowledge to concrete circumstances of life. Language is acquired from surrounding language "ready-made" and therefore can be acquired early in life. This early acquisition of language in childhood encompasses the entire hierarchy from sounds to words, to phrases, and to highest concepts existing in culture. Cognition is developed from experience. Yet cognition cannot be acquired from experience alone; language is a necessary intermediary, a "teacher." A mathematical model is developed; it overcomes previous difficulties and leads to a computational theory. This model is consistent with Arbib's "language prewired brain" built on top of mirror neuron system. It models recent neuroimaging data about cognition, remaining unnoticed by other theories. A number of properties of language and cognition are explained, which previously seemed mysterious, including influence of language grammar on cultural evolution, which may explain specifics of English and Arabic cultures.
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Language and Cognition Interaction Neural Mechanisms
Perlovsky, Leonid
2011-01-01
How language and cognition interact in thinking? Is language just used for communication of completed thoughts, or is it fundamental for thinking? Existing approaches have not led to a computational theory. We develop a hypothesis that language and cognition are two separate but closely interacting mechanisms. Language accumulates cultural wisdom; cognition develops mental representations modeling surrounding world and adapts cultural knowledge to concrete circumstances of life. Language is acquired from surrounding language “ready-made” and therefore can be acquired early in life. This early acquisition of language in childhood encompasses the entire hierarchy from sounds to words, to phrases, and to highest concepts existing in culture. Cognition is developed from experience. Yet cognition cannot be acquired from experience alone; language is a necessary intermediary, a “teacher.” A mathematical model is developed; it overcomes previous difficulties and leads to a computational theory. This model is consistent with Arbib's “language prewired brain” built on top of mirror neuron system. It models recent neuroimaging data about cognition, remaining unnoticed by other theories. A number of properties of language and cognition are explained, which previously seemed mysterious, including influence of language grammar on cultural evolution, which may explain specifics of English and Arabic cultures. PMID:21876687
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Binding and segmentation via a neural mass model trained with Hebbian and anti-Hebbian mechanisms.
Cona, Filippo; Zavaglia, Melissa; Ursino, Mauro
2012-04-01
Synchronization of neural activity in the gamma band, modulated by a slower theta rhythm, is assumed to play a significant role in binding and segmentation of multiple objects. In the present work, a recent neural mass model of a single cortical column is used to analyze the synaptic mechanisms which can warrant synchronization and desynchronization of cortical columns, during an autoassociation memory task. The model considers two distinct layers communicating via feedforward connections. The first layer receives the external input and works as an autoassociative network in the theta band, to recover a previously memorized object from incomplete information. The second realizes segmentation of different objects in the gamma band. To this end, units within both layers are connected with synapses trained on the basis of previous experience to store objects. The main model assumptions are: (i) recovery of incomplete objects is realized by excitatory synapses from pyramidal to pyramidal neurons in the same object; (ii) binding in the gamma range is realized by excitatory synapses from pyramidal neurons to fast inhibitory interneurons in the same object. These synapses (both at points i and ii) have a few ms dynamics and are trained with a Hebbian mechanism. (iii) Segmentation is realized with faster AMPA synapses, with rise times smaller than 1 ms, trained with an anti-Hebbian mechanism. Results show that the model, with the previous assumptions, can correctly reconstruct and segment three simultaneous objects, starting from incomplete knowledge. Segmentation of more objects is possible but requires an increased ratio between the theta and gamma periods.
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δ-Protocadherins: Organizers of neural circuit assembly.
Light, Sarah E W; Jontes, James D
2017-09-01
The δ-protocadherins comprise a small family of homophilic cell adhesion molecules within the larger cadherin superfamily. They are essential for neural development as mutations in these molecules give rise to human neurodevelopmental disorders, such as schizophrenia and epilepsy, and result in behavioral defects in animal models. Despite their importance to neural development, a detailed understanding of their mechanisms and the ways in which their loss leads to changes in neural function is lacking. However, recent results have begun to reveal roles for the δ-protocadherins in both regulation of neurogenesis and lineage-dependent circuit assembly, as well as in contact-dependent motility and selective axon fasciculation. These evolutionarily conserved mechanisms could have a profound impact on the robust assembly of the vertebrate nervous system. Future work should be focused on unraveling the molecular mechanisms of the δ-protocadherins and understanding how this family functions broadly to regulate neural development. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Common and distinct neural mechanisms of attentional switching and response conflict.
Kim, Chobok; Johnson, Nathan F; Gold, Brian T
2012-08-21
The human capacities for overcoming prepotent actions and flexibly switching between tasks represent cornerstones of cognitive control. Functional neuroimaging has implicated a diverse set of brain regions contributing to each of these cognitive control processes. However, the extent to which attentional switching and response conflict draw on shared or distinct neural mechanisms remains unclear. The current study examined the neural correlates of response conflict and attentional switching using event-related functional magnetic resonance imaging (fMRI) and a fully randomized 2×2 design. We manipulated an arrow-word version of the Stroop task to measure conflict and switching in the context of a single task decision, in response to a common set of stimuli. Under these common conditions, both behavioral and imaging data showed significant main effects of conflict and switching but no interaction. However, conjunction analyses identified frontal regions involved in both switching and response conflict, including the dorsal anterior cingulate cortex (dACC) and left inferior frontal junction. In addition, connectivity analyses demonstrated task-dependent functional connectivity patterns between dACC and inferior temporal cortex for attentional switching and between dACC and posterior parietal cortex for response conflict. These results suggest that the brain makes use of shared frontal regions, but can dynamically modulate the connectivity patterns of some of those regions, to deal with attentional switching and response conflict. Copyright © 2012 Elsevier B.V. All rights reserved.
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Neural crest contributions to the lamprey head
McCauley, David W.; Bronner-Fraser, Marianne
2003-01-01
The neural crest is a vertebrate-specific cell population that contributes to the facial skeleton and other derivatives. We have performed focal DiI injection into the cranial neural tube of the developing lamprey in order to follow the migratory pathways of discrete groups of cells from origin to destination and to compare neural crest migratory pathways in a basal vertebrate to those of gnathostomes. The results show that the general pathways of cranial neural crest migration are conserved throughout the vertebrates, with cells migrating in streams analogous to the mandibular and hyoid streams. Caudal branchial neural crest cells migrate ventrally as a sheet of cells from the hindbrain and super-pharyngeal region of the neural tube and form a cylinder surrounding a core of mesoderm in each pharyngeal arch, similar to that seen in zebrafish and axolotl. In addition to these similarities, we also uncovered important differences. Migration into the presumptive caudal branchial arches of the lamprey involves both rostral and caudal movements of neural crest cells that have not been described in gnathostomes, suggesting that barriers that constrain rostrocaudal movement of cranial neural crest cells may have arisen after the agnathan/gnathostome split. Accordingly, neural crest cells from a single axial level contributed to multiple arches and there was extensive mixing between populations. There was no apparent filling of neural crest derivatives in a ventral-to-dorsal order, as has been observed in higher vertebrates, nor did we find evidence of a neural crest contribution to cranial sensory ganglia. These results suggest that migratory constraints and additional neural crest derivatives arose later in gnathostome evolution.
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Discovering Multimodal Behavior in Ms. Pac-Man through Evolution of Modular Neural Networks.
Schrum, Jacob; Miikkulainen, Risto
2016-03-12
Ms. Pac-Man is a challenging video game in which multiple modes of behavior are required: Ms. Pac-Man must escape ghosts when they are threats and catch them when they are edible, in addition to eating all pills in each level. Past approaches to learning behavior in Ms. Pac-Man have treated the game as a single task to be learned using monolithic policy representations. In contrast, this paper uses a framework called Modular Multi-objective NEAT (MM-NEAT) to evolve modular neural networks. Each module defines a separate behavior. The modules are used at different times according to a policy that can be human-designed (i.e. Multitask) or discovered automatically by evolution. The appropriate number of modules can be fixed or discovered using a genetic operator called Module Mutation. Several versions of Module Mutation are evaluated in this paper. Both fixed modular networks and Module Mutation networks outperform monolithic networks and Multitask networks. Interestingly, the best networks dedicate modules to critical behaviors (such as escaping when surrounded after luring ghosts near a power pill) that do not follow the customary division of the game into chasing edible and escaping threat ghosts. The results demonstrate that MM-NEAT can discover interesting and effective behavior for agents in challenging games.
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Neural mechanisms of social influence in adolescence.
Welborn, B Locke; Lieberman, Matthew D; Goldenberg, Diane; Fuligni, Andrew J; Galván, Adriana; Telzer, Eva H
2016-01-01
During the transformative period of adolescence, social influence plays a prominent role in shaping young people's emerging social identities, and can impact their propensity to engage in prosocial or risky behaviors. In this study, we examine the neural correlates of social influence from both parents and peers, two important sources of influence. Nineteen adolescents (age 16-18 years) completed a social influence task during a functional magnetic resonance imaging (fMRI) scan. Social influence from both sources evoked activity in brain regions implicated in mentalizing (medial prefrontal cortex, left temporoparietal junction, right temporoparietal junction), reward (ventromedial prefrontal cortex), and self-control (right ventrolateral prefrontal cortex). These results suggest that mental state reasoning, social reward and self-control processes may help adolescents to evaluate others' perspectives and overcome the prepotent force of their own antecedent attitudes to shift their attitudes toward those of others. Findings suggest common neural networks involved in social influence from both parents and peers. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
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Rolling Force Prediction in Heavy Plate Rolling Based on Uniform Differential Neural Network
Directory of Open Access Journals (Sweden)
Fei Zhang
2016-01-01
Full Text Available Accurate prediction of the rolling force is critical to assuring the quality of the final product in steel manufacturing. Exit thickness of plate for each pass is calculated from roll gap, mill spring, and predicted roll force. Ideal pass scheduling is dependent on a precise prediction of the roll force in each pass. This paper will introduce a concept that allows obtaining the material model parameters directly from the rolling process on an industrial scale by the uniform differential neural network. On the basis of the characteristics that the uniform distribution can fully characterize the solution space and enhance the diversity of the population, uniformity research on differential evolution operator is made to get improved crossover with uniform distribution. When its original function is transferred with a transfer function, the uniform differential evolution algorithms can quickly solve complex optimization problems. Neural network structure and weights threshold are optimized by uniform differential evolution algorithm, and a uniform differential neural network is formed to improve rolling force prediction accuracy in process control system.
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Principles of neural information processing
Seelen, Werner v
2016-01-01
In this fundamental book the authors devise a framework that describes the working of the brain as a whole. It presents a comprehensive introduction to the principles of Neural Information Processing as well as recent and authoritative research. The books´ guiding principles are the main purpose of neural activity, namely, to organize behavior to ensure survival, as well as the understanding of the evolutionary genesis of the brain. Among the developed principles and strategies belong self-organization of neural systems, flexibility, the active interpretation of the world by means of construction and prediction as well as their embedding into the world, all of which form the framework of the presented description. Since, in brains, their partial self-organization, the lifelong adaptation and their use of various methods of processing incoming information are all interconnected, the authors have chosen not only neurobiology and evolution theory as a basis for the elaboration of such a framework, but also syst...
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The evolution of mechanical property change in irradiated austenitic stainless steels
International Nuclear Information System (INIS)
Lucas, G.E.
1993-01-01
The evolution of mechanical properties in austenitic stainless steels during irradiation is reviewed. Changes in strength, ductility and fracture toughness are strongly related to the evolution of the damage microstructure and microstructurally-based models for strengthening reasonably correlate the data. Irradiation-induced defects promote work softening and flow localization which in turn leads to significant reductions in ductility and fracture toughness beyond about 10 dpa. The effects of irradiation on fatigue appear to be modest except at high temperature where helium embrittlement becomes important. The swelling-independent component of irradiation creep strain increases linearly with dose and is relatively insensitive to material variables and irradiation temperature, except at low temperatures where accelerated creep may occur as a result of low vacancy mobility. Creep rupture life is a strong function of helium content, but is less sensitive to metallurgical conditions. Irradiation-induced stress corrosion cracking appears to be related to the evolution of radiation-induced segregation/depletion at grain boundaries, and hence may not be significant at low irradiation temperatures. (orig.)
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Learning-induced pattern classification in a chaotic neural network
International Nuclear Information System (INIS)
Li, Yang; Zhu, Ping; Xie, Xiaoping; He, Guoguang; Aihara, Kazuyuki
2012-01-01
In this Letter, we propose a Hebbian learning rule with passive forgetting (HLRPF) for use in a chaotic neural network (CNN). We then define the indices based on the Euclidean distance to investigate the evolution of the weights in a simplified way. Numerical simulations demonstrate that, under suitable external stimulations, the CNN with the proposed HLRPF acts as a fuzzy-like pattern classifier that performs much better than an ordinary CNN. The results imply relationship between learning and recognition. -- Highlights: ► Proposing a Hebbian learning rule with passive forgetting (HLRPF). ► Defining indices to investigate the evolution of the weights simply. ► The chaotic neural network with HLRPF acts as a fuzzy-like pattern classifier. ► The pattern classifier ability of the network is improved much.
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Neocortical arealization: evolution, mechanisms, and open questions.
Alfano, Christian; Studer, Michèle
2013-06-01
The mammalian neocortex is a structure with no equals in the vertebrates and is the seat of the highest cerebral functions, such as thoughts and consciousness. It is radially organized into six layers and tangentially subdivided into functional areas deputed to the elaboration of sensory information, association between different stimuli, and selection and triggering of voluntary movements. The process subdividing the neocortical field into several functional areas is called "arealization". Each area has its own cytoarchitecture, connectivity, and peculiar functions. In the last century, several neuroscientists have investigated areal structure and the mechanisms that have led during evolution to the rising of the neocortex and its organization. The extreme conservation in the positioning and wiring of neocortical areas among different mammalian families suggests a conserved genetic program orchestrating neocortical patterning. However, the impressive plasticity of the neocortex, which is able to rewire and reorganize areal structures and connectivity after impairments of sensory pathways, argues for a more complex scenario. Indeed, even if genetics and molecular biology helped in identifying several genes involved in the arealization process, the logic underlying the neocortical bauplan is still beyond our comprehension. In this review, we will introduce the present knowledge and hypotheses on the ontogenesis and evolution of neocortical areas. Then, we will focus our attention on some open issues, which are still unresolved, and discuss some recent studies that might open new directions to be explored in the next few years. Copyright © 2012 Wiley Periodicals, Inc.
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[Neural mechanism underlying autistic savant and acquired savant syndrome].
Takahata, Keisuke; Kato, Motoichiro
2008-07-01
It is well known that the cases with savant syndrome, demonstrate outstanding mental capability despite coexisting severe mental disabilities. In many cases, savant skills are characterized by its domain-specificity, enhanced memory capability, and excessive focus on low-level perceptual processing. In addition, impaired integrative cognitive processing such as social cognition or executive function, restricted interest, and compulsive repetition of the same act are observed in savant individuals. All these are significantly relevant to the behavioral characteristics observed in individuals with autistic spectrum disorders (ASD). A neurocognitive model of savant syndrome should explain these cognitive features and the juxtaposition of outstanding talents with cognitive disabilities. In recent neuropsychological studies, Miller (1998) reported clinical cases of "acquired savant," i.e., patients who improved or newly acquired an artistic savant-like skill in the early stage of frontotemporal dementia (FTD). Although the relationship between an autistic savant and acquired savant remains to be elucidated, the advent of neuroimaging study of ASD and the clarification of FTD patients with savant-like skills may clarify the shared neural mechanisms of both types of talent. In this review, we classified current cognitive models of savant syndrome into the following 3 categories. (1) A hypermnesic model that suggests that savant skills develop from existing or dormant cognitive functions such as memory. However, recent findings obtained through neuropsychological examinations imply that savant individuals solve problems using a strategy that is fairly different from a non-autistic one. (2) A paradoxical functional facilitation model (Kapur, 1996) that offers possible explanations about how pathological states in the brain lead to development of prodigious skills. This model emphasizes the role of reciprocal inhibitory interaction among adjacent or distant cortical regions
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Neural mechanisms of mental schema: a triplet of delta, low beta/spindle and ripple oscillations.
Ohki, Takefumi; Takei, Yuichi
2018-02-06
Schemas are higher-level knowledge structures that integrate and organise lower-level representations. As internal templates, schemas are formed according to how events are perceived, interpreted and remembered. Although these higher-level units are assumed to play a fundamental role in our daily life from an early age, the neuronal basis and mechanisms of schema formation and use remain largely unknown. It is important to elucidate how the brain constructs and maintains these higher-level units. In order to examine the possible neural underpinnings of schema, we recapitulate previous work and discuss their findings related to schemas as the brain template. We specifically focused on low beta/spindle oscillations, which are assumed to be the key components of schemas, and propose that the brain template is implemented with a triplet of neural oscillations, that is delta, low beta/spindle and ripple oscillations. © 2018 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
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Understanding Neurological Disease Mechanisms in the Era of Epigenetics
Qureshi, Irfan A.; Mehler, Mark F.
2015-01-01
The burgeoning field of epigenetics is making a significant impact on our understanding of brain evolution, development, and function. In fact, it is now clear that epigenetic mechanisms promote seminal neurobiological processes, ranging from neural stem cell maintenance and differentiation to learning and memory. At the molecular level, epigenetic mechanisms regulate the structure and activity of the genome in response to intracellular and environmental cues, including the deployment of cell type–specific gene networks and those underlying synaptic plasticity. Pharmacological and genetic manipulation of epigenetic factors can, in turn, induce remarkable changes in neural cell identity and cognitive and behavioral phenotypes. Not surprisingly, it is also becoming apparent that epigenetics is intimately involved in neurological disease pathogenesis. Herein, we highlight emerging paradigms for linking epigenetic machinery and processes with neurological disease states, including how (1) mutations in genes encoding epigenetic factors cause disease, (2) genetic variation in genes encoding epigenetic factors modify disease risk, (3) abnormalities in epigenetic factor expression, localization, or function are involved in disease pathophysiology, (4) epigenetic mechanisms regulate disease-associated genomic loci, gene products, and cellular pathways, and (5) differential epigenetic profiles are present in patient-derived central and peripheral tissues. PMID:23571666
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Phase Diagram of Spiking Neural Networks
Directory of Open Access Journals (Sweden)
Hamed eSeyed-Allaei
2015-03-01
Full Text Available In computer simulations of spiking neural networks, often it is assumed that every two neurons of the network are connected by a probablilty of 2%, 20% of neurons are inhibitory and 80% are excitatory. These common values are based on experiments, observations. but here, I take a different perspective, inspired by evolution. I simulate many networks, each with a different set of parameters, and then I try to figure out what makes the common values desirable by nature. Networks which are configured according to the common values, have the best dynamic range in response to an impulse and their dynamic range is more robust in respect to synaptic weights. In fact, evolution has favored networks of best dynamic range. I present a phase diagram that shows the dynamic ranges of different networks of different parameteres. This phase diagram gives an insight into the space of parameters -- excitatory to inhibitory ratio, sparseness of connections and synaptic weights. It may serve as a guideline to decide about the values of parameters in a simulation of spiking neural network.
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Online evolution of robot behaviour
Silva, Fernando Goulart da
2012-01-01
Tese de mestrado em Engenharia Informática (Interação e Conhecimento), apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2012 In this dissertation, we propose and evaluate two novel approaches to the online synthesis of neural controllers for autonomous robots. The first approach is odNEAT, an online, distributed, and decentralized version of NeuroEvolution of Augmenting Topologies (NEAT). odNEAT is an algorithm for online evolution in groups of embodied agents such a...
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The evolution of nervous system patterning: insights from sea urchin development
Angerer, Lynne M.; Yaguchi, Shunsuke; Angerer, Robert C.; Burke, Robert D.
2011-01-01
Recent studies of the sea urchin embryo have elucidated the mechanisms that localize and pattern its nervous system. These studies have revealed the presence of two overlapping regions of neurogenic potential at the beginning of embryogenesis, each of which becomes progressively restricted by separate, yet linked, signals, including Wnt and subsequently Nodal and BMP. These signals act to specify and localize the embryonic neural fields – the anterior neuroectoderm and the more posterior ciliary band neuroectoderm – during development. Here, we review these conserved nervous system patterning signals and consider how the relationships between them might have changed during deuterostome evolution. PMID:21828090
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Neural Parallel Engine: A toolbox for massively parallel neural signal processing.
Tam, Wing-Kin; Yang, Zhi
2018-05-01
Large-scale neural recordings provide detailed information on neuronal activities and can help elicit the underlying neural mechanisms of the brain. However, the computational burden is also formidable when we try to process the huge data stream generated by such recordings. In this study, we report the development of Neural Parallel Engine (NPE), a toolbox for massively parallel neural signal processing on graphical processing units (GPUs). It offers a selection of the most commonly used routines in neural signal processing such as spike detection and spike sorting, including advanced algorithms such as exponential-component-power-component (EC-PC) spike detection and binary pursuit spike sorting. We also propose a new method for detecting peaks in parallel through a parallel compact operation. Our toolbox is able to offer a 5× to 110× speedup compared with its CPU counterparts depending on the algorithms. A user-friendly MATLAB interface is provided to allow easy integration of the toolbox into existing workflows. Previous efforts on GPU neural signal processing only focus on a few rudimentary algorithms, are not well-optimized and often do not provide a user-friendly programming interface to fit into existing workflows. There is a strong need for a comprehensive toolbox for massively parallel neural signal processing. A new toolbox for massively parallel neural signal processing has been created. It can offer significant speedup in processing signals from large-scale recordings up to thousands of channels. Copyright © 2018 Elsevier B.V. All rights reserved.
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Directory of Open Access Journals (Sweden)
S. F Mousavi
2016-09-01
Full Text Available Introduction The diagnosis of agricultural machinery faults must be performed at an opportune time, in order to fulfill the agricultural operations in a timely manner and to optimize the accuracy and the integrity of a system, proper monitoring and fault diagnosis of the rotating parts is required. With development of fault diagnosis methods of rotating equipment, especially bearing failure, the security, performance and availability of machines has been increasing. In general, fault detection is conducted through a specific procedure which starts with data acquisition and continues with features extraction, and subsequently failure of the machine would be detected. Several practical methods have been introduced for fault detection in rotating parts of machineries. The review of the literature shows that both Artificial Neural Networks (ANN and Support Vector Machines (SVM have been used for this purpose. However, the results show that SVM is more effective than Artificial Neural Networks in fault detection of such machineries. In some smart detection systems, incorporating an optimized method such as Genetic Algorithm in the Neural Network model, could improve the fault detection procedure. Consequently, the fault detection performance of neural networks may also be improved by combining with the Genetic Algorithm and hence will be comparable with the performance of the Support Vector Machine. In this study, the so called Genetic Algorithm (GA method was used to optimize the structure of the Artificial Neural Networks (ANN for fault detection of the clutch retainer mechanism of Massey Ferguson 285 tractor. Materials and Methods The test rig consists of some electro mechanical parts including the clutch retainer mechanism of Massey Ferguson 285 tractor, a supporting shaft, a single-phase electric motor, a loading mechanism to model the load of the tractor clutch and the corresponding power train gears. The data acquisition section consists of a
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The molecular evolution of the p120-catenin subfamily and its functional associations.
Directory of Open Access Journals (Sweden)
Robert H Carnahan
2010-12-01
Full Text Available p120-catenin (p120 is the prototypical member of a subclass of armadillo-related proteins that includes δ-catenin/NPRAP, ARVCF, p0071, and the more distantly related plakophilins 1-3. In vertebrates, p120 is essential in regulating surface expression and stability of all classical cadherins, and directly interacts with Kaiso, a BTB/ZF family transcription factor.To clarify functional relationships between these proteins and how they relate to the classical cadherins, we have examined the proteomes of 14 diverse vertebrate and metazoan species. The data reveal a single ancient δ-catenin-like p120 family member present in the earliest metazoans and conserved throughout metazoan evolution. This single p120 family protein is present in all protostomes, and in certain early-branching chordate lineages. Phylogenetic analyses suggest that gene duplication and functional diversification into "p120-like" and "δ-catenin-like" proteins occurred in the urochordate-vertebrate ancestor. Additional gene duplications during early vertebrate evolution gave rise to the seven vertebrate p120 family members. Kaiso family members (i.e., Kaiso, ZBTB38 and ZBTB4 are found only in vertebrates, their origin following that of the p120-like gene lineage and coinciding with the evolution of vertebrate-specific mechanisms of epigenetic gene regulation by CpG island methylation.The p120 protein family evolved from a common δ-catenin-like ancestor present in all metazoans. Through several rounds of gene duplication and diversification, however, p120 evolved in vertebrates into an essential, ubiquitously expressed protein, whereas loss of the more selectively expressed δ-catenin, p0071 and ARVCF are tolerated in most species. Together with phylogenetic studies of the vertebrate cadherins, our data suggest that the p120-like and δ-catenin-like genes co-evolved separately with non-neural (E- and P-cadherin and neural (N- and R-cadherin cadherin lineages, respectively. The
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The critical chemical and mechanical regulation of folic acid on neural engineering.
Kim, Gloria B; Chen, Yongjie; Kang, Weibo; Guo, Jinshan; Payne, Russell; Li, Hui; Wei, Qiong; Baker, Julianne; Dong, Cheng; Zhang, Sulin; Wong, Pak Kin; Rizk, Elias B; Yan, Jiazhi; Yang, Jian
2018-04-03
The mandate of folic acid supplementation in grained products has reduced the occurrence of neural tube defects by one third in the U.S since its introduction by the Food and Drug Administration in 1998. However, the advantages and possible mechanisms of action of using folic acid for peripheral nerve engineering and neurological diseases still remain largely elusive. Herein, folic acid is described as an inexpensive and multifunctional niche component that modulates behaviors in different cells in the nervous system. The multiple benefits of modulation include: 1) generating chemotactic responses on glial cells, 2) inducing neurotrophin release, and 3) stimulating neuronal differentiation of a PC-12 cell system. For the first time, folic acid is also shown to enhance cellular force generation and global methylation in the PC-12 cells, thereby enabling both biomechanical and biochemical pathways to regulate neuron differentiation. These findings are evaluated in vivo for clinical translation. Our results suggest that folic acid-nerve guidance conduits may offer significant benefits as a low-cost, off-the-shelf product for reaching the functional recovery seen with autografts in large sciatic nerve defects. Consequently, folic acid holds great potential as a critical and convenient therapeutic intervention for neural engineering, regenerative medicine, medical prosthetics, and drug delivery. Copyright © 2018 Elsevier Ltd. All rights reserved.
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Mechanisms and impact of genetic recombination in the evolution of Streptococcus pneumoniae.
Chaguza, Chrispin; Cornick, Jennifer E; Everett, Dean B
2015-01-01
Streptococcus pneumoniae (the pneumococcus) is a highly recombinogenic bacterium responsible for a high burden of human disease globally. Genetic recombination, a process in which exogenous DNA is acquired and incorporated into its genome, is a key evolutionary mechanism employed by the pneumococcus to rapidly adapt to selective pressures. The rate at which the pneumococcus acquires genetic variation through recombination is much higher than the rate at which the organism acquires variation through spontaneous mutations. This higher rate of variation allows the pneumococcus to circumvent the host innate and adaptive immune responses, escape clinical interventions, including antibiotic therapy and vaccine introduction. The rapid influx of whole genome sequence (WGS) data and the advent of novel analysis methods and powerful computational tools for population genetics and evolution studies has transformed our understanding of how genetic recombination drives pneumococcal adaptation and evolution. Here we discuss how genetic recombination has impacted upon the evolution of the pneumococcus.
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Lee, Eunha
In this study, the microstructural evolution of Timetal 550 was investigated. Timetal 550 showed two types of phase transformations (martensitic and nucleation and growth) depending on the cooling rate from the beta region. The alpha phase initially precipitated at the prior beta grain boundaries, and it had a Burgers OR with one of the adjacent grains. It was found that colonies could grow, even in the fast-cooled Timetal 550 sample, from the grain boundary alpha into the prior beta grain with which it exhibited the Burgers OR. Three orientation relationships were also found between alpha laths in the basketweave microstructure. Microhardness testing demonstrated that fast-cooled Timetal 550 samples with basketweave microstructure were harder than slowly-cooled samples with colony microstructure. Orientation-dependent deformation was found in the colony microstructure. Specifically, when the surface normal is perpendicular to the [0001] of alpha, the material deforms easily in the direction perpendicular to the [0001] of alpha. Fuzzy logic and Bayesian neural network models were developed to predict the room temperature tensile properties of Timetal 550. This involved the development of a database relating microstructural features to mechanical properties. A Gleeble 3800 thermal-mechanical simulator was used to develop various microstructures. Microstructural features of tensile-tested samples were quantified using stereological procedures. The quantified microstructural features and the tensile properties were used as inputs and outputs, respectively, for modeling the relationships between them. The individual influence of five microstructural features on tensile properties was determined using the established models. The microstructural features having the greatest impact on UTS and YS were the thickness of alpha laths and the width of grain boundary alpha layer, and the microstructural features having the greatest impact on elongation were the thickness of
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Death and rebirth of neural activity in sparse inhibitory networks
Angulo-Garcia, David; Luccioli, Stefano; Olmi, Simona; Torcini, Alessandro
2017-05-01
Inhibition is a key aspect of neural dynamics playing a fundamental role for the emergence of neural rhythms and the implementation of various information coding strategies. Inhibitory populations are present in several brain structures, and the comprehension of their dynamics is strategical for the understanding of neural processing. In this paper, we clarify the mechanisms underlying a general phenomenon present in pulse-coupled heterogeneous inhibitory networks: inhibition can induce not only suppression of neural activity, as expected, but can also promote neural re-activation. In particular, for globally coupled systems, the number of firing neurons monotonically reduces upon increasing the strength of inhibition (neuronal death). However, the random pruning of connections is able to reverse the action of inhibition, i.e. in a random sparse network a sufficiently strong synaptic strength can surprisingly promote, rather than depress, the activity of neurons (neuronal rebirth). Thus, the number of firing neurons reaches a minimum value at some intermediate synaptic strength. We show that this minimum signals a transition from a regime dominated by neurons with a higher firing activity to a phase where all neurons are effectively sub-threshold and their irregular firing is driven by current fluctuations. We explain the origin of the transition by deriving a mean field formulation of the problem able to provide the fraction of active neurons as well as the first two moments of their firing statistics. The introduction of a synaptic time scale does not modify the main aspects of the reported phenomenon. However, for sufficiently slow synapses the transition becomes dramatic, and the system passes from a perfectly regular evolution to irregular bursting dynamics. In this latter regime the model provides predictions consistent with experimental findings for a specific class of neurons, namely the medium spiny neurons in the striatum.
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Turbulent Evolution of a Plasma Described Through Classical Mechanics Only
International Nuclear Information System (INIS)
Escande, D.F.; Elskens, Y.
2003-01-01
For the first time an old dream of the XIXth century comes true: the non trivial evolution of a macroscopic many-body system is described through classical mechanics only. This is done for the relaxation of a warm electron beam in a plasma, which results in the generation of Langmuir turbulence and in the formation of a plateau in the velocity distribution function of the electrons. Our derivation starts from the hamiltonian describing the one-dimensional N-body system corresponding to the beam and plasma bulk electrons in electrostatic interaction. For such a system, the dynamics can be reduced to the resonant interaction of M Langmuir waves with N'( > 1 Langmuir waves with N' >> 1 beam particles. This yields the proof of the classical quasilinear equations describing the coupled evolution of the wave spectrum and of the beam velocity distribution function in the strongly nonlinear regime where their validity is the matter of a longstanding controversy
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ROAD DETECTION BY NEURAL AND GENETIC ALGORITHM IN URBAN ENVIRONMENT
Directory of Open Access Journals (Sweden)
A. Barsi
2012-07-01
Full Text Available In the urban object detection challenge organized by the ISPRS WG III/4 high geometric and radiometric resolution aerial images about Vaihingen/Stuttgart, Germany are distributed. The acquired data set contains optical false color, near infrared images and airborne laserscanning data. The presented research focused exclusively on the optical image, so the elevation information was ignored. The road detection procedure has been built up of two main phases: a segmentation done by neural networks and a compilation made by genetic algorithms. The applied neural networks were support vector machines with radial basis kernel function and self-organizing maps with hexagonal network topology and Euclidean distance function for neighborhood management. The neural techniques have been compared by hyperbox classifier, known from the statistical image classification practice. The compilation of the segmentation is realized by a novel application of the common genetic algorithm and by differential evolution technique. The genes were implemented to detect the road elements by evaluating a special binary fitness function. The results have proven that the evolutional technique can automatically find major road segments.
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Fracture Mechanics Method for Word Embedding Generation of Neural Probabilistic Linguistic Model
Directory of Open Access Journals (Sweden)
Size Bi
2016-01-01
Full Text Available Word embedding, a lexical vector representation generated via the neural linguistic model (NLM, is empirically demonstrated to be appropriate for improvement of the performance of traditional language model. However, the supreme dimensionality that is inherent in NLM contributes to the problems of hyperparameters and long-time training in modeling. Here, we propose a force-directed method to improve such problems for simplifying the generation of word embedding. In this framework, each word is assumed as a point in the real world; thus it can approximately simulate the physical movement following certain mechanics. To simulate the variation of meaning in phrases, we use the fracture mechanics to do the formation and breakdown of meaning combined by a 2-gram word group. With the experiments on the natural linguistic tasks of part-of-speech tagging, named entity recognition and semantic role labeling, the result demonstrated that the 2-dimensional word embedding can rival the word embeddings generated by classic NLMs, in terms of accuracy, recall, and text visualization.
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DEFF Research Database (Denmark)
Stribeck, Norbert; Zeinolebadi, Ahmad; Ganjaee Sari, Morteza
2012-01-01
Small-angle X-ray scattering (SAXS) monitors tensile and load-cycling tests of metallocene isotactic polypropylene (PP), a blend of PP and montmorillonite (MMT), and two block copolymer compatibilized PP/MMT nanocomposites. Mechanical properties of the materials are similar, but the semicrystalline......%. Other results concern the evolution of Strobl’s block structure and void formation during tensile loading....
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Predictive Acoustic Tracking with an Adaptive Neural Mechanism
DEFF Research Database (Denmark)
Shaikh, Danish; Manoonpong, Poramate
2017-01-01
model of the lizard peripheral auditory system to extract information regarding sound direction. This information is utilised by a neural machinery to learn the acoustic signal’s velocity through fast and unsupervised correlation-based learning adapted from differential Hebbian learning. This approach...
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Apraxia: neural mechanisms and functional recovery.
Foundas, Anne L
2013-01-01
Apraxia is a cognitive-motor disorder that impacts the performance of learned, skilled movements. Limb apraxia, which is the topic of this chapter, is specific to disordered movements of the upper limb that cannot be explained by weakness, sensory loss, abnormalities of posture/tone/movement, or a lack of understanding/cooperation. Patients with limb apraxia have deficits in the control or programming of the spatial-temporal organization and sequencing of goal-directed movements. People with limb apraxia can have difficulty manipulating and using tools including cutting with scissors or making a cup of coffee. Two praxis systems have been identified including a production system (action plan and production) and a conceptual system (action knowledge). Dysfunction of the former produces ideomotor apraxia (e.g., difficulty using scissors), and dysfunction of the latter induces ideational apraxia (e.g., difficulty making a cup of coffee). Neural mechanisms, including how to evaluate apraxia, will be presented in the context of these two praxis systems. Information about these praxis systems, including the nature of the disordered limb movement, is important for rehabilitation clinicians to understand for several reasons. First, limb apraxia is a common disorder. It is common in patients who have had a stroke, in neurodegenerative disorders like Alzheimer disease, in traumatic brain injury, and in developmental disorders. Second, limb apraxia has real world consequences. Patients with limb apraxia have difficulty managing activities of daily living. This factor impacts healthcare costs and contributes to increased caregiver burden. Unfortunately, very few treatments have been systematically studied in large numbers of patients with limb apraxia. This overview of limb apraxia should help rehabilitation clinicians to educate patients and caregivers about this debilitating problem, and should facilitate the development of better treatments that could benefit many people in
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Genetic learning in rule-based and neural systems
Smith, Robert E.
1993-01-01
The design of neural networks and fuzzy systems can involve complex, nonlinear, and ill-conditioned optimization problems. Often, traditional optimization schemes are inadequate or inapplicable for such tasks. Genetic Algorithms (GA's) are a class of optimization procedures whose mechanics are based on those of natural genetics. Mathematical arguments show how GAs bring substantial computational leverage to search problems, without requiring the mathematical characteristics often necessary for traditional optimization schemes (e.g., modality, continuity, availability of derivative information, etc.). GA's have proven effective in a variety of search tasks that arise in neural networks and fuzzy systems. This presentation begins by introducing the mechanism and theoretical underpinnings of GA's. GA's are then related to a class of rule-based machine learning systems called learning classifier systems (LCS's). An LCS implements a low-level production-system that uses a GA as its primary rule discovery mechanism. This presentation illustrates how, despite its rule-based framework, an LCS can be thought of as a competitive neural network. Neural network simulator code for an LCS is presented. In this context, the GA is doing more than optimizing and objective function. It is searching for an ecology of hidden nodes with limited connectivity. The GA attempts to evolve this ecology such that effective neural network performance results. The GA is particularly well adapted to this task, given its naturally-inspired basis. The LCS/neural network analogy extends itself to other, more traditional neural networks. Conclusions to the presentation discuss the implications of using GA's in ecological search problems that arise in neural and fuzzy systems.
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Evolution of CAM and C4 carbon-concentrating mechanisms
Keeley, Jon E.; Rundel, Philip W.
2003-01-01
Mechanisms for concentrating carbon around the Rubisco enzyme, which drives the carbon-reducing steps in photosynthesis, are widespread in plants; in vascular plants they are known as crassulacean acid metabolism (CAM) and C4 photosynthesis. CAM is common in desert succulents, tropical epiphytes, and aquatic plants and is characterized by nighttime fixation of CO2. The proximal selective factor driving the evolution of this CO2-concentrating pathway is low daytime CO2, which results from the unusual reverse stomatal behavior of terrestrial CAM species or from patterns of ambient CO2 availability for aquatic CAM species. In terrestrials the ultimate selective factor is water stress that has selected for increased water use efficiency. In aquatics the ultimate selective factor is diel fluctuations in CO2 availability for palustrine species and extreme oligotrophic conditions for lacustrine species. C4 photosynthesis is based on similar biochemistry but carboxylation steps are spatially separated in the leaf rather than temporally as in CAM. This biochemical pathway is most commonly associated with a specialized leaf anatomy known as Kranz anatomy; however, there are exceptions. The ultimate selective factor driving the evolution of this pathway is excessively high photorespiration that inhibits normal C3 photosynthesis under high light and high temperature in both terrestrial and aquatic habitats. CAM is an ancient pathway that likely has been present since the Paleozoic era in aquatic species from shallow-water palustrine habitats. While atmospheric CO2 levels have undoubtedly affected the evolution of terrestrial plant carbon-concentrating mechanisms, there is reason to believe that past atmospheric changes have not played as important a selective role in the aquatic milieu since palustrine habitats today are not generally carbon sinks, and the selective factors driving aquatic CAM are autogenic. Terrestrial CAM, in contrast, is of increasing selective value under
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Quantum selfish gene (biological evolution in terms of quantum mechanics)
Ozhigov, Yuri I.
2013-01-01
I propose to treat the biological evolution of genoms by means of quantum mechanical tools. We start with the concept of meta- gene, which specifies the "selfish gene" of R.Dawkins. Meta- gene encodes the abstract living unity, which can live relatively independently of the others, and can contain a few real creatures. Each population of living creatures we treat as the wave function on meta- genes, which module squared is the total number of creatures with the given meta-gene, and the phase ...
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Molecular evolution of a peptide GPCR ligand driven by artificial neural networks.
Directory of Open Access Journals (Sweden)
Sebastian Bandholtz
Full Text Available Peptide ligands of G protein-coupled receptors constitute valuable natural lead structures for the development of highly selective drugs and high-affinity tools to probe ligand-receptor interaction. Currently, pharmacological and metabolic modification of natural peptides involves either an iterative trial-and-error process based on structure-activity relationships or screening of peptide libraries that contain many structural variants of the native molecule. Here, we present a novel neural network architecture for the improvement of metabolic stability without loss of bioactivity. In this approach the peptide sequence determines the topology of the neural network and each cell corresponds one-to-one to a single amino acid of the peptide chain. Using a training set, the learning algorithm calculated weights for each cell. The resulting network calculated the fitness function in a genetic algorithm to explore the virtual space of all possible peptides. The network training was based on gradient descent techniques which rely on the efficient calculation of the gradient by back-propagation. After three consecutive cycles of sequence design by the neural network, peptide synthesis and bioassay this new approach yielded a ligand with 70fold higher metabolic stability compared to the wild type peptide without loss of the subnanomolar activity in the biological assay. Combining specialized neural networks with an exploration of the combinatorial amino acid sequence space by genetic algorithms represents a novel rational strategy for peptide design and optimization.
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The shared neural basis of music and language.
Yu, Mengxia; Xu, Miao; Li, Xueting; Chen, Zhencai; Song, Yiying; Liu, Jia
2017-08-15
Human musical ability is proposed to play a key phylogenetical role in the evolution of language, and the similarity of hierarchical structure in music and language has led to considerable speculation about their shared mechanisms. While behavioral and electrophysioglocial studies have revealed associations between music and linguistic abilities, results from functional magnetic resonance imaging (fMRI) studies on their relations are contradictory, possibly because these studies usually treat music or language as single entities without breaking down to their components. Here, we examined the relations between different components of music (i.e., melodic and rhythmic analysis) and language (i.e., semantic and phonological processing) using both behavioral tests and resting-state fMRI. Behaviorally, we found that individuals with music training experiences were better at semantic processing, but not at phonological processing, than those without training. Further correlation analyses showed that semantic processing of language was related to melodic, but not rhythmic, analysis of music. Neurally, we found that performances in both semantic processing and melodic analysis were correlated with spontaneous brain activities in the bilateral precentral gyrus (PCG) and superior temporal plane at the regional level, and with the resting-state functional connectivity of the left PCG with the left supramarginal gyrus and left superior temporal gyrus at the network level. Together, our study revealed the shared spontaneous neural basis of music and language based on the behavioral link between melodic analysis and semantic processing, which possibly relied on a common mechanism of automatic auditory-motor integration. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.
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ChainMail based neural dynamics modeling of soft tissue deformation for surgical simulation.
Zhang, Jinao; Zhong, Yongmin; Smith, Julian; Gu, Chengfan
2017-07-20
Realistic and real-time modeling and simulation of soft tissue deformation is a fundamental research issue in the field of surgical simulation. In this paper, a novel cellular neural network approach is presented for modeling and simulation of soft tissue deformation by combining neural dynamics of cellular neural network with ChainMail mechanism. The proposed method formulates the problem of elastic deformation into cellular neural network activities to avoid the complex computation of elasticity. The local position adjustments of ChainMail are incorporated into the cellular neural network as the local connectivity of cells, through which the dynamic behaviors of soft tissue deformation are transformed into the neural dynamics of cellular neural network. Experiments demonstrate that the proposed neural network approach is capable of modeling the soft tissues' nonlinear deformation and typical mechanical behaviors. The proposed method not only improves ChainMail's linear deformation with the nonlinear characteristics of neural dynamics but also enables the cellular neural network to follow the principle of continuum mechanics to simulate soft tissue deformation.
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Directory of Open Access Journals (Sweden)
Mingbo eCai
2012-11-01
Full Text Available When observers experience a constant delay between their motor actions and sensory feedback, their perception of the temporal order between actions and sensations adapt (Stetson et al., 2006a. We present here a novel neural model that can explain temporal order judgments (TOJs and their recalibration. Our model employs three ubiquitous features of neural systems: 1 information pooling, 2 opponent processing, and 3 synaptic scaling. Specifically, the model proposes that different populations of neurons encode different delays between motor-sensory events, the outputs of these populations feed into rivaling neural populations (encoding before and after, and the activity difference between these populations determines the perceptual judgment. As a consequence of synaptic scaling of input weights, motor acts which are consistently followed by delayed sensory feedback will cause the network to recalibrate its point of subjective simultaneity. The structure of our model raises the possibility that recalibration of TOJs is a temporal analogue to the motion aftereffect. In other words, identical neural mechanisms may be used to make perceptual determinations about both space and time. Our model captures behavioral recalibration results for different numbers of adapting trials and different adapting delays. In line with predictions of the model, we additionally demonstrate that temporal recalibration can last through time, in analogy to storage of the motion aftereffect.
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A hypothesis on a role of oxytocin in the social mechanisms of speech and vocal learning.
Theofanopoulou, Constantina; Boeckx, Cedric; Jarvis, Erich D
2017-08-30
Language acquisition in humans and song learning in songbirds naturally happen as a social learning experience, providing an excellent opportunity to reveal social motivation and reward mechanisms that boost sensorimotor learning. Our knowledge about the molecules and circuits that control these social mechanisms for vocal learning and language is limited. Here we propose a hypothesis of a role for oxytocin (OT) in the social motivation and evolution of vocal learning and language. Building upon existing evidence, we suggest specific neural pathways and mechanisms through which OT might modulate vocal learning circuits in specific developmental stages. © 2017 The Authors.
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International Nuclear Information System (INIS)
De Geeter, N; Crevecoeur, G; Dupré, L; Leemans, A
2015-01-01
In transcranial magnetic stimulation (TMS), an applied alternating magnetic field induces an electric field in the brain that can interact with the neural system. It is generally assumed that this induced electric field is the crucial effect exciting a certain region of the brain. More specifically, it is the component of this field parallel to the neuron’s local orientation, the so-called effective electric field, that can initiate neuronal stimulation. Deeper insights on the stimulation mechanisms can be acquired through extensive TMS modelling. Most models study simple representations of neurons with assumed geometries, whereas we embed realistic neural trajectories computed using tractography based on diffusion tensor images. This way of modelling ensures a more accurate spatial distribution of the effective electric field that is in addition patient and case specific. The case study of this paper focuses on the single pulse stimulation of the left primary motor cortex with a standard figure-of-eight coil. Including realistic neural geometry in the model demonstrates the strong and localized variations of the effective electric field between the tracts themselves and along them due to the interplay of factors such as the tract’s position and orientation in relation to the TMS coil, the neural trajectory and its course along the white and grey matter interface. Furthermore, the influence of changes in the coil orientation is studied. Investigating the impact of tissue anisotropy confirms that its contribution is not negligible. Moreover, assuming isotropic tissues lead to errors of the same size as rotating or tilting the coil with 10 degrees. In contrast, the model proves to be less sensitive towards the not well-known tissue conductivity values. (paper)
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Malicious Botnet Survivability Mechanism Evolution Forecasting by Means of a Genetic Algorithm
Directory of Open Access Journals (Sweden)
Nikolaj Goranin
2012-04-01
Full Text Available Botnets are considered to be among the most dangerous modern malware types and the biggest current threats to global IT infrastructure. Botnets are rapidly evolving, and therefore forecasting their survivability strategies is important for the development of countermeasure techniques. The article propose the botnet-oriented genetic algorithm based model framework, which aimed at forecasting botnet survivability mechanisms. The model may be used as a framework for forecasting the evolution of other characteristics. The efficiency of different survivability mechanisms is evaluated by applying the proposed fitness function. The model application area also covers scientific botnet research and modelling tasks.
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Culture of Mouse Neural Stem Cell Precursors
Currle, D. Spencer; Hu, Jia Sheng; Kolski-Andreaco, Aaron; Monuki, Edwin S.
2007-01-01
Primary neural stem cell cultures are useful for studying the mechanisms underlying central nervous system development. Stem cell research will increase our understanding of the nervous system and may allow us to develop treatments for currently incurable brain diseases and injuries. In addition, stem cells should be used for stem cell research aimed at the detailed study of mechanisms of neural differentiation and transdifferentiation and the genetic and environmental signals that direct the...
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Stieglitz, T; Schuettler, M; Koch, K P
2004-04-01
Neural prostheses partially restore body functions by technical nerve excitation after trauma or neurological diseases. External devices and implants have been developed since the early 1960s for many applications. Several systems have reached nowadays clinical practice: Cochlea implants help the deaf to hear, micturition is induced by bladder stimulators in paralyzed persons and deep brain stimulation helps patients with Parkinson's disease to participate in daily life again. So far, clinical neural prostheses are fabricated with means of precision mechanics. Since microsystem technology opens the opportunity to design and develop complex systems with a high number of electrodes to interface with the nervous systems, the opportunity for selective stimulation and complex implant scenarios seems to be feasible in the near future. The potentials and limitations with regard to biomedical microdevices are introduced and discussed in this paper. Target specifications are derived from existing implants and are discussed on selected applications that has been investigated in experimental research: a micromachined implant to interface a nerve stump with a sieve electrode, cuff electrodes with integrated electronics, and an epiretinal vision prosthesis.
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Modeling of mechanical properties in alpha/beta-titanium alloys
Kar, Sujoy Kumar
2005-11-01
The accelerated insertion of titanium alloys in component application requires the development of predictive capabilities for various aspects of their behavior, for example, phase stability, microstructural evolution and property-microstructure relationships over a wide range of length and time scales. In this presentation some navel aspects of property-microstructure relationships and microstructural evolution in alpha/beta Ti alloys will be discussed. Neural Network (NN) Models based on a Bayesian framework have been developed to predict the mechanical properties of alpha/beta Ti alloys. The development of such rules-based model requires the population of extensive databases, which in the present case are microstructurally-based. The steps involved in database development include producing controlled variations of the microstructure using novel approaches to heat-treatments, the use of standardized stereology protocols to characterize and quantify microstructural features rapidly, and mechanical testing of the heat-treated specimens. These databases have been used to train and test NN Models for prediction of mechanical properties. In addition, these models have been used to identify the influence of individual microstructural features on the mechanical properties, consequently guiding the efforts towards development of more robust mechanistically based models. In order to understand the property-microstructure relationships, a detailed understanding of microstructure evolution is imperative. The crystallography of the microstructure developing as a result of the solid-state beta → beta+alpha transformation has been studied in detail by employing Scanning Electron Microscopy (SEM), Orientation Imaging Microscopy (in a high resolution SEM), site-specific TEM sample preparation using focused ion beam, and TEM based techniques. The influence of variant selection on the evolution of microstructure will be specifically addressed.
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Neural mechanisms mediating degrees of strategic uncertainty.
Nagel, Rosemarie; Brovelli, Andrea; Heinemann, Frank; Coricelli, Giorgio
2018-01-01
In social interactions, strategic uncertainty arises when the outcome of one's choice depends on the choices of others. An important question is whether strategic uncertainty can be resolved by assessing subjective probabilities to the counterparts' behavior, as if playing against nature, and thus transforming the strategic interaction into a risky (individual) situation. By means of functional magnetic resonance imaging with human participants we tested the hypothesis that choices under strategic uncertainty are supported by the neural circuits mediating choices under individual risk and deliberation in social settings (i.e. strategic thinking). Participants were confronted with risky lotteries and two types of coordination games requiring different degrees of strategic thinking of the kind 'I think that you think that I think etc.' We found that the brain network mediating risk during lotteries (anterior insula, dorsomedial prefrontal cortex and parietal cortex) is also engaged in the processing of strategic uncertainty in games. In social settings, activity in this network is modulated by the level of strategic thinking that is reflected in the activity of the dorsomedial and dorsolateral prefrontal cortex. These results suggest that strategic uncertainty is resolved by the interplay between the neural circuits mediating risk and higher order beliefs (i.e. beliefs about others' beliefs). © The Author(s) (2017). Published by Oxford University Press.
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Outsourcing neural active control to passive composite mechanics: a tissue engineered cyborg ray
Gazzola, Mattia; Park, Sung Jin; Park, Kyung Soo; Park, Shirley; di Santo, Valentina; Deisseroth, Karl; Lauder, George V.; Mahadevan, L.; Parker, Kevin Kit
2016-11-01
Translating the blueprint that stingrays and skates provide, we create a cyborg swimming ray capable of orchestrating adaptive maneuvering and phototactic navigation. The impossibility of replicating the neural system of batoids fish is bypassed by outsourcing algorithmic functionalities to the body composite mechanics, hence casting the active control problem into a design, passive one. We present a first step in engineering multilevel "brain-body-flow" systems that couple sensory information to motor coordination and movement, leading to behavior. This work paves the way for the development of autonomous and adaptive artificial creatures able to process multiple sensory inputs and produce complex behaviors in distributed systems and may represent a path toward soft-robotic "embodied cognition".
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Interactions between neural networks: a mechanism for tuning chaos and oscillations.
Wang, Lipo
2007-06-01
We show that chaos and oscillations in a higher-order binary neural network can be tuned effectively using interactions between neural networks. Our results suggest that network interactions may be useful as a means of adjusting the level of dynamic activities in systems that employ chaos and oscillations for information processing, or as a means of suppressing oscillatory behaviors in systems that require stability.
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Evolution of the new vertebrate head by co-option of an ancient chordate skeletal tissue.
Jandzik, David; Garnett, Aaron T; Square, Tyler A; Cattell, Maria V; Yu, Jr-Kai; Medeiros, Daniel M
2015-02-26
A defining feature of vertebrates (craniates) is a pronounced head that is supported and protected by a robust cellular endoskeleton. In the first vertebrates, this skeleton probably consisted of collagenous cellular cartilage, which forms the embryonic skeleton of all vertebrates and the adult skeleton of modern jawless and cartilaginous fish. In the head, most cellular cartilage is derived from a migratory cell population called the neural crest, which arises from the edges of the central nervous system. Because collagenous cellular cartilage and neural crest cells have not been described in invertebrates, the appearance of cellular cartilage derived from neural crest cells is considered a turning point in vertebrate evolution. Here we show that a tissue with many of the defining features of vertebrate cellular cartilage transiently forms in the larvae of the invertebrate chordate Branchiostoma floridae (Florida amphioxus). We also present evidence that during evolution, a key regulator of vertebrate cartilage development, SoxE, gained new cis-regulatory sequences that subsequently directed its novel expression in neural crest cells. Together, these results suggest that the origin of the vertebrate head skeleton did not depend on the evolution of a new skeletal tissue, as is commonly thought, but on the spread of this tissue throughout the head. We further propose that the evolution of cis-regulatory elements near an ancient regulator of cartilage differentiation was a major factor in the evolution of the vertebrate head skeleton.
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Diekhof, Esther K; Keil, Maria; Obst, Katrin U; Henseler, Ilona; Dechent, Peter; Falkai, Peter; Gruber, Oliver
2012-09-14
There is ample evidence of gender differences in neural processes and behavior. Differences in reward-related behaviors have been linked to either temporary or permanent organizational influences of gonadal hormones on the mesolimbic dopamine system and reward-related activation. Still, little is known about the association between biological gender and the neural underpinnings of the ability to resist reward-related impulses. Here we assessed with functional magnetic resonance imaging which neural processes enable men and women to successfully control their desire for immediate reward when this is required by a higher-order goal (i.e., during a 'desire-reason dilemma'; Diekhof and Gruber, 2010). Thirty-two participants (16 females) were closely matched for age, personality characteristics (e.g., novelty seeking) and behavioral performance in the 'desire-reason task'. On the neural level, men and women showed similarities in the general response of the nucleus accumbens and of the ventral tegmental area to predictors of immediate reward, but they differed in additional brain mechanisms that enabled self-controlled decisions against the preference for immediate reward. Firstly, men exhibited a stronger reduction of activation in the ventral pallidum, putamen, temporal pole and pregenual anterior cingulate cortex during the 'desire-reason dilemma'. Secondly, connectivity analyses revealed a significant change in the direction of the connectivity between anteroventral prefrontal cortex and nucleus accumbens during decisions counteracting the reward-related impulse when comparing men and women. Together, these findings support the view of a sexual dimorphism that manifested in the recruitment of gender-specific neural resources during the successful deployment of self-control. Copyright © 2012 Elsevier B.V. All rights reserved.
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The evolution of different forms of sociality: behavioral mechanisms and eco-evolutionary feedback.
Directory of Open Access Journals (Sweden)
Daniel J van der Post
Full Text Available Different forms of sociality have evolved via unique evolutionary trajectories. However, it remains unknown to what extent trajectories of social evolution depend on the specific characteristics of different species. Our approach to studying such trajectories is to use evolutionary case-studies, so that we can investigate how grouping co-evolves with a multitude of individual characteristics. Here we focus on anti-predator vigilance and foraging. We use an individual-based model, where behavioral mechanisms are specified, and costs and benefits are not predefined. We show that evolutionary changes in grouping alter selection pressures on vigilance, and vice versa. This eco-evolutionary feedback generates an evolutionary progression from "leader-follower" societies to "fission-fusion" societies, where cooperative vigilance in groups is maintained via a balance between within- and between-group selection. Group-level selection is generated from an assortment that arises spontaneously when vigilant and non-vigilant foragers have different grouping tendencies. The evolutionary maintenance of small groups, and cooperative vigilance in those groups, is therefore achieved simultaneously. The evolutionary phases, and the transitions between them, depend strongly on behavioral mechanisms. Thus, integrating behavioral mechanisms and eco-evolutionary feedback is critical for understanding what kinds of intermediate stages are involved during the evolution of particular forms of sociality.
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Compensatory recruitment of neural resources in chronic alcoholism.
Chanraud, Sandra; Sullivan, Edith V
2014-01-01
Functional recovery occurs with sustained sobriety, but the neural mechanisms enabling recovery are only now emerging. Theories about promising mechanisms involve concepts of neuroadaptation, where excessive alcohol consumption results in untoward structural and functional brain changes which are subsequently candidates for reversal with sobriety. Views on functional adaptation in chronic alcoholism have expanded with results from neuroimaging studies. Here, we first describe and define the concept of neuroadaptation according to emerging theories based on the growing literature in aging-related cognitive functioning. Then we describe findings as they apply to chronic alcoholism and factors that could influence compensation, such as functional brain reserve and the integrity of brain structure. Finally, we review brain plasticity based on physiologic mechanisms that could underlie mechanisms of neural compensation. Where possible, we provide operational criteria to define functional and neural compensation. © 2014 Elsevier B.V. All rights reserved.
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Conceptual evolution of Newtonian and relativistic mechanics
Ghosh, Amitabha
2018-01-01
This book provides an introduction to Newtonian and relativistic mechanics. Unlike other books on the topic, which generally take a 'top-down' approach, it follows a novel system to show how the concepts of the 'science of motion' evolved through a veritable jungle of intermediate ideas and concepts. Starting with Aristotelian philosophy, the text gradually unravels how the human mind slowly progressed towards the fundamental ideas of inertia physics. The concepts that now appear so obvious to even a high school student took great intellectuals more than a millennium to clarify. The book explores the evolution of these concepts through the history of science. After a comprehensive overview of the discovery of dynamics, it explores fundamental issues of the properties of space and time and their relation with the laws of motion. It also explores the concepts of spatio-temporal locality and fields, and offers a philosophical discussion of relative motion versus absolute motion, as well as the concept of an abso...
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Stevens, Courtney; Lauinger, Brittni; Neville, Helen
2009-01-01
Previous research indicates that children from lower socioeconomic backgrounds show deficits in aspects of attention, including a reduced ability to filter irrelevant information and to suppress prepotent responses. However, less is known about the neural mechanisms of group differences in attention, which could reveal the stages of processing at…
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Zhang, Yongjun; Song, Hongwen; Liu, Xiaoming; Tang, Dinghong; Chen, Yue-e; Zhang, Xiaochu
2017-01-01
Massive Multiple Online Role-Playing Games (MMORPGs) have increased in popularity among children, juveniles, and adults since MMORPGs’ appearance in this digital age. MMORPGs can be applied to enhancing language learning, which is drawing researchers’ attention from different fields and many studies have validated MMORPGs’ positive effect on language learning. However, there are few studies on the underlying behavioral or neural mechanism of such effect. This paper reviews the educational application of the MMORPGs based on relevant macroscopic and microscopic studies, showing that gamers’ overall language proficiency or some specific language skills can be enhanced by real-time online interaction with peers and game narratives or instructions embedded in the MMORPGs. Mechanisms underlying the educational assistant role of MMORPGs in second language learning are discussed from both behavioral and neural perspectives. We suggest that attentional bias makes gamers/learners allocate more cognitive resources toward task-related stimuli in a controlled or an automatic way. Moreover, with a moderating role played by activation of reward circuit, playing the MMORPGs may strengthen or increase functional connectivity from seed regions such as left anterior insular/frontal operculum (AI/FO) and visual word form area to other language-related brain areas. PMID:28303097
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Zhang, Yongjun; Song, Hongwen; Liu, Xiaoming; Tang, Dinghong; Chen, Yue-E; Zhang, Xiaochu
2017-01-01
Massive Multiple Online Role-Playing Games (MMORPGs) have increased in popularity among children, juveniles, and adults since MMORPGs' appearance in this digital age. MMORPGs can be applied to enhancing language learning, which is drawing researchers' attention from different fields and many studies have validated MMORPGs' positive effect on language learning. However, there are few studies on the underlying behavioral or neural mechanism of such effect. This paper reviews the educational application of the MMORPGs based on relevant macroscopic and microscopic studies, showing that gamers' overall language proficiency or some specific language skills can be enhanced by real-time online interaction with peers and game narratives or instructions embedded in the MMORPGs. Mechanisms underlying the educational assistant role of MMORPGs in second language learning are discussed from both behavioral and neural perspectives. We suggest that attentional bias makes gamers/learners allocate more cognitive resources toward task-related stimuli in a controlled or an automatic way. Moreover, with a moderating role played by activation of reward circuit, playing the MMORPGs may strengthen or increase functional connectivity from seed regions such as left anterior insular/frontal operculum (AI/FO) and visual word form area to other language-related brain areas.
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Chen, Nihong; Bi, Taiyong; Zhou, Tiangang; Li, Sheng; Liu, Zili; Fang, Fang
2015-07-15
Much has been debated about whether the neural plasticity mediating perceptual learning takes place at the sensory or decision-making stage in the brain. To investigate this, we trained human subjects in a visual motion direction discrimination task. Behavioral performance and BOLD signals were measured before, immediately after, and two weeks after training. Parallel to subjects' long-lasting behavioral improvement, the neural selectivity in V3A and the effective connectivity from V3A to IPS (intraparietal sulcus, a motion decision-making area) exhibited a persistent increase for the trained direction. Moreover, the improvement was well explained by a linear combination of the selectivity and connectivity increases. These findings suggest that the long-term neural mechanisms of motion perceptual learning are implemented by sharpening cortical tuning to trained stimuli at the sensory processing stage, as well as by optimizing the connections between sensory and decision-making areas in the brain. Copyright © 2015 Elsevier Inc. All rights reserved.
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Complex-Valued Neural Networks
Hirose, Akira
2012-01-01
This book is the second enlarged and revised edition of the first successful monograph on complex-valued neural networks (CVNNs) published in 2006, which lends itself to graduate and undergraduate courses in electrical engineering, informatics, control engineering, mechanics, robotics, bioengineering, and other relevant fields. In the second edition the recent trends in CVNNs research are included, resulting in e.g. almost a doubled number of references. The parametron invented in 1954 is also referred to with discussion on analogy and disparity. Also various additional arguments on the advantages of the complex-valued neural networks enhancing the difference to real-valued neural networks are given in various sections. The book is useful for those beginning their studies, for instance, in adaptive signal processing for highly functional sensing and imaging, control in unknown and changing environment, robotics inspired by human neural systems, and brain-like information processing, as well as interdisciplina...
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The octopus genome and the evolution of cephalopod neural and morphological novelties.
Albertin, Caroline B; Simakov, Oleg; Mitros, Therese; Wang, Z Yan; Pungor, Judit R; Edsinger-Gonzales, Eric; Brenner, Sydney; Ragsdale, Clifton W; Rokhsar, Daniel S
2015-08-13
Coleoid cephalopods (octopus, squid and cuttlefish) are active, resourceful predators with a rich behavioural repertoire. They have the largest nervous systems among the invertebrates and present other striking morphological innovations including camera-like eyes, prehensile arms, a highly derived early embryogenesis and a remarkably sophisticated adaptive colouration system. To investigate the molecular bases of cephalopod brain and body innovations, we sequenced the genome and multiple transcriptomes of the California two-spot octopus, Octopus bimaculoides. We found no evidence for hypothesized whole-genome duplications in the octopus lineage. The core developmental and neuronal gene repertoire of the octopus is broadly similar to that found across invertebrate bilaterians, except for massive expansions in two gene families previously thought to be uniquely enlarged in vertebrates: the protocadherins, which regulate neuronal development, and the C2H2 superfamily of zinc-finger transcription factors. Extensive messenger RNA editing generates transcript and protein diversity in genes involved in neural excitability, as previously described, as well as in genes participating in a broad range of other cellular functions. We identified hundreds of cephalopod-specific genes, many of which showed elevated expression levels in such specialized structures as the skin, the suckers and the nervous system. Finally, we found evidence for large-scale genomic rearrangements that are closely associated with transposable element expansions. Our analysis suggests that substantial expansion of a handful of gene families, along with extensive remodelling of genome linkage and repetitive content, played a critical role in the evolution of cephalopod morphological innovations, including their large and complex nervous systems.
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Directory of Open Access Journals (Sweden)
Christopher L Buckley
2018-01-01
Full Text Available During active behaviours like running, swimming, whisking or sniffing, motor actions shape sensory input and sensory percepts guide future motor commands. Ongoing cycles of sensory and motor processing constitute a closed-loop feedback system which is central to motor control and, it has been argued, for perceptual processes. This closed-loop feedback is mediated by brainwide neural circuits but how the presence of feedback signals impacts on the dynamics and function of neurons is not well understood. Here we present a simple theory suggesting that closed-loop feedback between the brain/body/environment can modulate neural gain and, consequently, change endogenous neural fluctuations and responses to sensory input. We support this theory with modeling and data analysis in two vertebrate systems. First, in a model of rodent whisking we show that negative feedback mediated by whisking vibrissa can suppress coherent neural fluctuations and neural responses to sensory input in the barrel cortex. We argue this suppression provides an appealing account of a brain state transition (a marked change in global brain activity coincident with the onset of whisking in rodents. Moreover, this mechanism suggests a novel signal detection mechanism that selectively accentuates active, rather than passive, whisker touch signals. This mechanism is consistent with a predictive coding strategy that is sensitive to the consequences of motor actions rather than the difference between the predicted and actual sensory input. We further support the theory by re-analysing previously published two-photon data recorded in zebrafish larvae performing closed-loop optomotor behaviour in a virtual swim simulator. We show, as predicted by this theory, that the degree to which each cell contributes in linking sensory and motor signals well explains how much its neural fluctuations are suppressed by closed-loop optomotor behaviour. More generally we argue that our results
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Buckley, Christopher L; Toyoizumi, Taro
2018-01-01
During active behaviours like running, swimming, whisking or sniffing, motor actions shape sensory input and sensory percepts guide future motor commands. Ongoing cycles of sensory and motor processing constitute a closed-loop feedback system which is central to motor control and, it has been argued, for perceptual processes. This closed-loop feedback is mediated by brainwide neural circuits but how the presence of feedback signals impacts on the dynamics and function of neurons is not well understood. Here we present a simple theory suggesting that closed-loop feedback between the brain/body/environment can modulate neural gain and, consequently, change endogenous neural fluctuations and responses to sensory input. We support this theory with modeling and data analysis in two vertebrate systems. First, in a model of rodent whisking we show that negative feedback mediated by whisking vibrissa can suppress coherent neural fluctuations and neural responses to sensory input in the barrel cortex. We argue this suppression provides an appealing account of a brain state transition (a marked change in global brain activity) coincident with the onset of whisking in rodents. Moreover, this mechanism suggests a novel signal detection mechanism that selectively accentuates active, rather than passive, whisker touch signals. This mechanism is consistent with a predictive coding strategy that is sensitive to the consequences of motor actions rather than the difference between the predicted and actual sensory input. We further support the theory by re-analysing previously published two-photon data recorded in zebrafish larvae performing closed-loop optomotor behaviour in a virtual swim simulator. We show, as predicted by this theory, that the degree to which each cell contributes in linking sensory and motor signals well explains how much its neural fluctuations are suppressed by closed-loop optomotor behaviour. More generally we argue that our results demonstrate the dependence
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Neural cryptography with feedback.
Ruttor, Andreas; Kinzel, Wolfgang; Shacham, Lanir; Kanter, Ido
2004-04-01
Neural cryptography is based on a competition between attractive and repulsive stochastic forces. A feedback mechanism is added to neural cryptography which increases the repulsive forces. Using numerical simulations and an analytic approach, the probability of a successful attack is calculated for different model parameters. Scaling laws are derived which show that feedback improves the security of the system. In addition, a network with feedback generates a pseudorandom bit sequence which can be used to encrypt and decrypt a secret message.
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Artificial Neural Networks for Nonlinear Dynamic Response Simulation in Mechanical Systems
DEFF Research Database (Denmark)
Christiansen, Niels Hørbye; Høgsberg, Jan Becker; Winther, Ole
2011-01-01
It is shown how artificial neural networks can be trained to predict dynamic response of a simple nonlinear structure. Data generated using a nonlinear finite element model of a simplified wind turbine is used to train a one layer artificial neural network. When trained properly the network is ab...... to perform accurate response prediction much faster than the corresponding finite element model. Initial result indicate a reduction in cpu time by two orders of magnitude....
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Artificial Neural Networks and the Mass Appraisal of Real Estate
Directory of Open Access Journals (Sweden)
Gang Zhou
2018-03-01
Full Text Available With the rapid development of computer, artificial intelligence and big data technology, artificial neural networks have become one of the most powerful machine learning algorithms. In the practice, most of the applications of artificial neural networks use back propagation neural network and its variation. Besides the back propagation neural network, various neural networks have been developing in order to improve the performance of standard models. Though neural networks are well known method in the research of real estate, there is enormous space for future research in order to enhance their function. Some scholars combine genetic algorithm, geospatial information, support vector machine model, particle swarm optimization with artificial neural networks to appraise the real estate, which is helpful for the existing appraisal technology. The mass appraisal of real estate in this paper includes the real estate valuation in the transaction and the tax base valuation in the real estate holding. In this study we focus on the theoretical development of artificial neural networks and mass appraisal of real estate, artificial neural networks model evolution and algorithm improvement, artificial neural networks practice and application, and review the existing literature about artificial neural networks and mass appraisal of real estate. Finally, we provide some suggestions for the mass appraisal of China's real estate.
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Evolution of an artificial neural network based autonomous land vehicle controller.
Baluja, S
1996-01-01
This paper presents an evolutionary method for creating an artificial neural network based autonomous land vehicle controller. The evolved controllers perform better in unseen situations than those trained with an error backpropagation learning algorithm designed for this task. In this paper, an overview of the previous connectionist based approaches to this task is given, and the evolutionary algorithms used in this study are described in detail. Methods for reducing the high computational costs of training artificial neural networks with evolutionary algorithms are explored. Error metrics specific to the task of autonomous vehicle control are introduced; the evolutionary algorithms guided by these error metrics reveal improved performance over those guided by the standard sum-squared error metric. Finally, techniques for integrating evolutionary search and error backpropagation are presented. The evolved networks are designed to control Carnegie Mellon University's NAVLAB vehicles in road following tasks.
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Neural mechanisms underlying sensitivity to reverse-phi motion in the fly.
Leonhardt, Aljoscha; Meier, Matthias; Serbe, Etienne; Eichner, Hubert; Borst, Alexander
2017-01-01
Optical illusions provide powerful tools for mapping the algorithms and circuits that underlie visual processing, revealing structure through atypical function. Of particular note in the study of motion detection has been the reverse-phi illusion. When contrast reversals accompany discrete movement, detected direction tends to invert. This occurs across a wide range of organisms, spanning humans and invertebrates. Here, we map an algorithmic account of the phenomenon onto neural circuitry in the fruit fly Drosophila melanogaster. Through targeted silencing experiments in tethered walking flies as well as electrophysiology and calcium imaging, we demonstrate that ON- or OFF-selective local motion detector cells T4 and T5 are sensitive to certain interactions between ON and OFF. A biologically plausible detector model accounts for subtle features of this particular form of illusory motion reversal, like the re-inversion of turning responses occurring at extreme stimulus velocities. In light of comparable circuit architecture in the mammalian retina, we suggest that similar mechanisms may apply even to human psychophysics.
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Neural mechanisms of information storage in visual short-term memory.
Serences, John T
2016-11-01
The capacity to briefly memorize fleeting sensory information supports visual search and behavioral interactions with relevant stimuli in the environment. Traditionally, studies investigating the neural basis of visual short term memory (STM) have focused on the role of prefrontal cortex (PFC) in exerting executive control over what information is stored and how it is adaptively used to guide behavior. However, the neural substrates that support the actual storage of content-specific information in STM are more controversial, with some attributing this function to PFC and others to the specialized areas of early visual cortex that initially encode incoming sensory stimuli. In contrast to these traditional views, I will review evidence suggesting that content-specific information can be flexibly maintained in areas across the cortical hierarchy ranging from early visual cortex to PFC. While the factors that determine exactly where content-specific information is represented are not yet entirely clear, recognizing the importance of task-demands and better understanding the operation of non-spiking neural codes may help to constrain new theories about how memories are maintained at different resolutions, across different timescales, and in the presence of distracting information. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Neural Mechanisms of Information Storage in Visual Short-Term Memory
Serences, John T.
2016-01-01
The capacity to briefly memorize fleeting sensory information supports visual search and behavioral interactions with relevant stimuli in the environment. Traditionally, studies investigating the neural basis of visual short term memory (STM) have focused on the role of prefrontal cortex (PFC) in exerting executive control over what information is stored and how it is adaptively used to guide behavior. However, the neural substrates that support the actual storage of content-specific information in STM are more controversial, with some attributing this function to PFC and others to the specialized areas of early visual cortex that initially encode incoming sensory stimuli. In contrast to these traditional views, I will review evidence suggesting that content-specific information can be flexibly maintained in areas across the cortical hierarchy ranging from early visual cortex to PFC. While the factors that determine exactly where content-specific information is represented are not yet entirely clear, recognizing the importance of task-demands and better understanding the operation of non-spiking neural codes may help to constrain new theories about how memories are maintained at different resolutions, across different timescales, and in the presence of distracting information. PMID:27668990
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Neural plasticity of development and learning.
Galván, Adriana
2010-06-01
Development and learning are powerful agents of change across the lifespan that induce robust structural and functional plasticity in neural systems. An unresolved question in developmental cognitive neuroscience is whether development and learning share the same neural mechanisms associated with experience-related neural plasticity. In this article, I outline the conceptual and practical challenges of this question, review insights gleaned from adult studies, and describe recent strides toward examining this topic across development using neuroimaging methods. I suggest that development and learning are not two completely separate constructs and instead, that they exist on a continuum. While progressive and regressive changes are central to both, the behavioral consequences associated with these changes are closely tied to the existing neural architecture of maturity of the system. Eventually, a deeper, more mechanistic understanding of neural plasticity will shed light on behavioral changes across development and, more broadly, about the underlying neural basis of cognition. (c) 2010 Wiley-Liss, Inc.
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Léonard, Angélique; Blacher, Silvia; Crine, Michel; Jomaa, Wahbi
2008-01-01
Porous carbon xerogels can be obtained by convective drying of resorcinol (R)-formaldehyde (F) hydrogels, followed by pyrolysis. Drying conditions have to be carefully controlled when crack-free monoliths with well-defined shape and size are required. The knowledge of the mechanical properties of the RF xerogels and their evolution with water content is essential to model their thermo-hygro-mechanical behavior during convective drying and avoid mechanical stresses leading to deformation and c...
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Dhole, Sumit; Stern, Caitlin A; Servedio, Maria R
2018-04-01
The evolution of mating displays as indicators of male quality has been the subject of extensive theoretical and empirical research for over four decades. Research has also addressed the evolution of female mate choice favoring such indicators. Yet, much debate still exists about whether displays can evolve through the indirect benefits of female mate choice. Here, we use a population genetic model to investigate how the extent to which females can directly detect male quality influences the evolution of female choosiness and male displays. We use a continuum framework that incorporates indicator mechanisms that are traditionally modeled separately. Counter to intuition, we find that intermediate levels of direct detection of male quality can facilitate, rather than impede, the evolution of female choosiness and male displays in broad regions of this continuum. We examine how this evolution is driven by selective forces on genetic quality and on the display, and find that direct detection of male quality results in stronger indirect selection favoring female choosiness. Our results imply that displays maybe more likely to evolve when female choosiness has already evolved to discriminate perceptible forms of male quality. They also highlight the importance of considering general female choosiness, as well as preference, in studies of "good genes." © 2018 The Author(s). Evolution © 2018 The Society for the Study of Evolution.
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Zhang, Yongjun; Song, Hongwen; Liu, Xiaoming; Tang, Dinghong; Chen, Yue-e; Zhang, Xiaochu
2017-01-01
Massive Multiple Online Role-Playing Games (MMORPGs) have increased in popularity among children, juveniles, and adults since MMORPGs’ appearance in this digital age. MMORPGs can be applied to enhancing language learning, which is drawing researchers’ attention from different fields and many studies have validated MMORPGs’ positive effect on language learning. However, there are few studies on the underlying behavioral or neural mechanism of such effect. This paper reviews the educational app...
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Hsu, Shen-Mou; Yang, Yu-Fang
2018-04-01
An important issue facing the empirical study of consciousness concerns how the contents of incoming stimuli gain access to conscious processing. According to classic theories, facial stimuli are processed in a hierarchical manner. However, it remains unclear how the brain determines which level of stimulus content is consciously accessible when facing an incoming facial stimulus. Accordingly, with a magnetoencephalography technique, this study aims to investigate the temporal dynamics of the neural mechanism mediating which level of stimulus content is consciously accessible. Participants were instructed to view masked target faces at threshold so that, according to behavioral responses, their perceptual awareness alternated from consciously accessing facial identity in some trials to being able to consciously access facial configuration features but not facial identity in other trials. Conscious access at these two levels of facial contents were associated with a series of differential neural events. Before target presentation, different patterns of phase angle adjustment were observed between the two types of conscious access. This effect was followed by stronger phase clustering for awareness of facial identity immediately during stimulus presentation. After target onset, conscious access to facial identity, as opposed to facial configural features, was able to elicit more robust late positivity. In conclusion, we suggest that the stages of neural events, ranging from prestimulus to stimulus-related activities, may operate in combination to determine which level of stimulus contents is consciously accessed. Conscious access may thus be better construed as comprising various forms that depend on the level of stimulus contents accessed. NEW & NOTEWORTHY The present study investigates how the brain determines which level of stimulus contents is consciously accessible when facing an incoming facial stimulus. Using magnetoencephalography, we show that prestimulus
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Chen, Zhencai; Lei, Xu; Ding, Cody; Li, Hong; Chen, Antao
2013-02-01
Previous studies have demonstrated that there are separate neural mechanisms underlying semantic and response conflicts in the Stroop task. However, the practice effects of these conflicts need to be elucidated and the possible involvements of common neural mechanisms are yet to be established. We employed functional magnetic resonance imaging (fMRI) in a 4-2 mapping practice-related Stroop task to determine the neural substrates under these conflicts. Results showed that different patterns of brain activations are associated with practice in the attentional networks (e.g., dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (ACC), and posterior parietal cortex (PPC)) for both conflicts, response control regions (e.g., inferior frontal junction (IFJ), inferior frontal gyrus (IFG)/insula, and pre-supplementary motor areas (pre-SMA)) for semantic conflict, and posterior cortex for response conflict. We also found areas of common activation in the left hemisphere within the attentional networks, for the early practice stage in semantic conflict and the late stage in "pure" response conflict using conjunction analysis. The different practice effects indicate that there are distinct mechanisms underlying these two conflict types: semantic conflict practice effects are attributable to the automation of stimulus processing, conflict and response control; response conflict practice effects are attributable to the proportional increase of conflict-related cognitive resources. In addition, the areas of common activation suggest that the semantic conflict effect may contain a partial response conflict effect, particularly at the beginning of the task. These findings indicate that there are two kinds of response conflicts contained in the key-pressing Stroop task: the vocal-level (mainly in the early stage) and key-pressing (mainly in the late stage) response conflicts; thus, the use of the subtraction method for the exploration of semantic and response conflicts
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Spiking Neural P Systems with Communication on Request.
Pan, Linqiang; Păun, Gheorghe; Zhang, Gexiang; Neri, Ferrante
2017-12-01
Spiking Neural [Formula: see text] Systems are Neural System models characterized by the fact that each neuron mimics a biological cell and the communication between neurons is based on spikes. In the Spiking Neural [Formula: see text] systems investigated so far, the application of evolution rules depends on the contents of a neuron (checked by means of a regular expression). In these [Formula: see text] systems, a specified number of spikes are consumed and a specified number of spikes are produced, and then sent to each of the neurons linked by a synapse to the evolving neuron. [Formula: see text]In the present work, a novel communication strategy among neurons of Spiking Neural [Formula: see text] Systems is proposed. In the resulting models, called Spiking Neural [Formula: see text] Systems with Communication on Request, the spikes are requested from neighboring neurons, depending on the contents of the neuron (still checked by means of a regular expression). Unlike the traditional Spiking Neural [Formula: see text] systems, no spikes are consumed or created: the spikes are only moved along synapses and replicated (when two or more neurons request the contents of the same neuron). [Formula: see text]The Spiking Neural [Formula: see text] Systems with Communication on Request are proved to be computationally universal, that is, equivalent with Turing machines as long as two types of spikes are used. Following this work, further research questions are listed to be open problems.
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Isbell, Elif; Wray, Amanda Hampton; Neville, Helen J.
2016-01-01
Selective attention, the ability to enhance the processing of particular input while suppressing the information from other concurrent sources, has been postulated to be a foundational skill for learning and academic achievement. The neural mechanisms of this foundational ability are both vulnerable and enhanceable in children from lower…
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Two social brains: neural mechanisms of intersubjectivity.
Vogeley, Kai
2017-08-19
It is the aim of this article to present an empirically justified hypothesis about the functional roles of the two social neural systems, namely the so-called 'mirror neuron system' (MNS) and the 'mentalizing system' (MENT, also 'theory of mind network' or 'social neural network'). Both systems are recruited during cognitive processes that are either related to interaction or communication with other conspecifics, thereby constituting intersubjectivity. The hypothesis is developed in the following steps: first, the fundamental distinction that we make between persons and things is introduced; second, communication is presented as the key process that allows us to interact with others; third, the capacity to 'mentalize' or to understand the inner experience of others is emphasized as the fundamental cognitive capacity required to establish successful communication. On this background, it is proposed that MNS serves comparably early stages of social information processing related to the 'detection' of spatial or bodily signals, whereas MENT is recruited during comparably late stages of social information processing related to the 'evaluation' of emotional and psychological states of others. This hypothesis of MNS as a social detection system and MENT as a social evaluation system is illustrated by findings in the field of psychopathology. Finally, new research questions that can be derived from this hypothesis are discussed.This article is part of the themed issue 'Physiological determinants of social behaviour in animals'. © 2017 The Author(s).
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Overcoming Deception in Evolution of Cognitive Behaviors
DEFF Research Database (Denmark)
Lehman, Joel; Miikkulainen, Risto
2014-01-01
When scaling neuroevolution to complex behaviors, cognitive capabilities such as learning, communication, and memory become increasingly important. However, successfully evolving such cognitive abilities remains difficult. This paper argues that a main cause for such difficulty is deception, i.......e. evolution converges to a behavior unrelated to the desired solution. More specifically, cognitive behaviors often require accumulating neural structure that provides no immediate fitness benefit, and evolution often thus converges to non-cognitive solutions. To investigate this hypothesis, a common...... evolutionary robotics T-Maze domain is adapted in three separate ways to require agents to communicate, remember, and learn. Indicative of deception, evolution driven by objective-based fitness often converges upon simple non- cognitive behaviors. In contrast, evolution driven to explore novel behaviors, i...
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Neural mechanisms of oculomotor abnormalities in the infantile strabismus syndrome.
Walton, Mark M G; Pallus, Adam; Fleuriet, Jérome; Mustari, Michael J; Tarczy-Hornoch, Kristina
2017-07-01
Infantile strabismus is characterized by numerous visual and oculomotor abnormalities. Recently nonhuman primate models of infantile strabismus have been established, with characteristics that closely match those observed in human patients. This has made it possible to study the neural basis for visual and oculomotor symptoms in infantile strabismus. In this review, we consider the available evidence for neural abnormalities in structures related to oculomotor pathways ranging from visual cortex to oculomotor nuclei. These studies provide compelling evidence that a disturbance of binocular vision during a sensitive period early in life, whatever the cause, results in a cascade of abnormalities through numerous brain areas involved in visual functions and eye movements. Copyright © 2017 the American Physiological Society.
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Neural network classifier of attacks in IP telephony
Safarik, Jakub; Voznak, Miroslav; Mehic, Miralem; Partila, Pavol; Mikulec, Martin
2014-05-01
Various types of monitoring mechanism allow us to detect and monitor behavior of attackers in VoIP networks. Analysis of detected malicious traffic is crucial for further investigation and hardening the network. This analysis is typically based on statistical methods and the article brings a solution based on neural network. The proposed algorithm is used as a classifier of attacks in a distributed monitoring network of independent honeypot probes. Information about attacks on these honeypots is collected on a centralized server and then classified. This classification is based on different mechanisms. One of them is based on the multilayer perceptron neural network. The article describes inner structure of used neural network and also information about implementation of this network. The learning set for this neural network is based on real attack data collected from IP telephony honeypot called Dionaea. We prepare the learning set from real attack data after collecting, cleaning and aggregation of this information. After proper learning is the neural network capable to classify 6 types of most commonly used VoIP attacks. Using neural network classifier brings more accurate attack classification in a distributed system of honeypots. With this approach is possible to detect malicious behavior in a different part of networks, which are logically or geographically divided and use the information from one network to harden security in other networks. Centralized server for distributed set of nodes serves not only as a collector and classifier of attack data, but also as a mechanism for generating a precaution steps against attacks.
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Neural Mechanisms of Episodic Retrieval Support Divergent Creative Thinking.
Madore, Kevin P; Thakral, Preston P; Beaty, Roger E; Addis, Donna Rose; Schacter, Daniel L
2017-11-17
Prior research has indicated that brain regions and networks that support semantic memory, top-down and bottom-up attention, and cognitive control are all involved in divergent creative thinking. Kernels of evidence suggest that neural processes supporting episodic memory-the retrieval of particular elements of prior experiences-may also be involved in divergent thinking, but such processes have typically been characterized as not very relevant for, or even a hindrance to, creative output. In the present study, we combine functional magnetic resonance imaging with an experimental manipulation to test formally, for the first time, episodic memory's involvement in divergent thinking. Following a manipulation that facilitates detailed episodic retrieval, we observed greater neural activity in the hippocampus and stronger connectivity between a core brain network linked to episodic processing and a frontoparietal brain network linked to cognitive control during divergent thinking relative to an object association control task that requires little divergent thinking. Stronger coupling following the retrieval manipulation extended to a subsequent resting-state scan. Neural effects of the episodic manipulation were consistent with behavioral effects of enhanced idea production on divergent thinking but not object association. The results indicate that conceptual frameworks should accommodate the idea that episodic retrieval can function as a component process of creative idea generation, and highlight how the brain flexibly utilizes the retrieval of episodic details for tasks beyond simple remembering. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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Neural mechanisms underlying melodic perception and memory for pitch.
Zatorre, R J; Evans, A C; Meyer, E
1994-04-01
The neural correlates of music perception were studied by measuring cerebral blood flow (CBF) changes with positron emission tomography (PET). Twelve volunteers were scanned using the bolus water method under four separate conditions: (1) listening to a sequence of noise bursts, (2) listening to unfamiliar tonal melodies, (3) comparing the pitch of the first two notes of the same set of melodies, and (4) comparing the pitch of the first and last notes of the melodies. The latter two conditions were designed to investigate short-term pitch retention under low or high memory load, respectively. Subtraction of the obtained PET images, superimposed on matched MRI scans, provides anatomical localization of CBF changes associated with specific cognitive functions. Listening to melodies, relative to acoustically matched noise sequences, resulted in CBF increases in the right superior temporal and right occipital cortices. Pitch judgments of the first two notes of each melody, relative to passive listening to the same stimuli, resulted in right frontal-lobe activation. Analysis of the high memory load condition relative to passive listening revealed the participation of a number of cortical and subcortical regions, notably in the right frontal and right temporal lobes, as well as in parietal and insular cortex. Both pitch judgment conditions also revealed CBF decreases within the left primary auditory cortex. We conclude that specialized neural systems in the right superior temporal cortex participate in perceptual analysis of melodies; pitch comparisons are effected via a neural network that includes right prefrontal cortex, but active retention of pitch involves the interaction of right temporal and frontal cortices.
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Harlé, Katia M; Chang, Luke J; van 't Wout, Mascha; Sanfey, Alan G
2012-05-15
Though emotions have been shown to have sometimes dramatic effects on decision-making, the neural mechanisms mediating these biases are relatively unexplored. Here, we investigated how incidental affect (i.e. emotional states unrelated to the decision at hand) may influence decisions, and how these biases are implemented in the brain. Nineteen adult participants made decisions which involved accepting or rejecting monetary offers from others in an Ultimatum Game while undergoing functional magnetic resonance imaging (fMRI). Prior to each set of decisions, participants watched a short video clip aimed at inducing either a sad or neutral emotional state. Results demonstrated that, as expected, sad participants rejected more unfair offers than those in the neutral condition. Neuroimaging analyses revealed that receiving unfair offers while in a sad mood elicited activity in brain areas related to aversive emotional states and somatosensory integration (anterior insula) and to cognitive conflict (anterior cingulate cortex). Sad participants also showed a diminished sensitivity in neural regions associated with reward processing (ventral striatum). Importantly, insular activation uniquely mediated the relationship between sadness and decision bias. This study is the first to reveal how subtle mood states can be integrated at the neural level to influence decision-making. Copyright © 2012 Elsevier Inc. All rights reserved.
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Directory of Open Access Journals (Sweden)
Serbielle Céline
2012-12-01
Full Text Available Abstract Background Gene duplications have been proposed to be the main mechanism involved in genome evolution and in acquisition of new functions. Polydnaviruses (PDVs, symbiotic viruses associated with parasitoid wasps, are ideal model systems to study mechanisms of gene duplications given that PDV genomes consist of virulence genes organized into multigene families. In these systems the viral genome is integrated in a wasp chromosome as a provirus and virus particles containing circular double-stranded DNA are injected into the parasitoids’ hosts and are essential for parasitism success. The viral virulence factors, organized in gene families, are required collectively to induce host immune suppression and developmental arrest. The gene family which encodes protein tyrosine phosphatases (PTPs has undergone spectacular expansion in several PDV genomes with up to 42 genes. Results Here, we present strong indications that PTP gene family expansion occurred via classical mechanisms: by duplication of large segments of the chromosomally integrated form of the virus sequences (segmental duplication, by tandem duplications within this form and by dispersed duplications. We also propose a novel duplication mechanism specific to PDVs that involves viral circle reintegration into the wasp genome. The PTP copies produced were shown to undergo conservative evolution along with episodes of adaptive evolution. In particular recently produced copies have undergone positive selection in sites most likely involved in defining substrate selectivity. Conclusion The results provide evidence about the dynamic nature of polydnavirus proviral genomes. Classical and PDV-specific duplication mechanisms have been involved in the production of new gene copies. Selection pressures associated with antagonistic interactions with parasitized hosts have shaped these genes used to manipulate lepidopteran physiology with evidence for positive selection involved in
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Study of microstructure evolution and strengthening mechanisms in novel TiZrAlB alloy
Energy Technology Data Exchange (ETDEWEB)
Liu, S.G.; Feng, Z.H.; Xia, C.Q.; Zhang, Z.G.; Zhang, X.; Zhang, X.Y., E-mail: xyzhang@ysu.edu.cn; Ma, M.Z.; Liu, R.P., E-mail: riping@ysu.edu.cn
2017-04-24
In this paper, the microstructural evolution and mechanical properties of the as-cast Ti-χZr-4Al-0.005B (TχZAB and χ=0, 10, 20, 30, 40 wt%) alloys were systematically investigated. Only the α phase was detected from the X-ray diffraction patterns of the as-cast TχZAB quaternary alloy series. As the Zr content increased, the average size and length-diameter ratio of the α grains were decreased from 69.8 μm to 17.1 µm and 37.5 to 8.4, respectively. The analysis of the results from the tensile and microhardness tests demonstrated that both the strength and hardness increased significantly as the Zr content increased (from 0 wt% to 40 wt%). Nevertheless, the ductility exhibited an opposite trend. The fracture mode of the ductile-brittle transfer was consistent with the ductility alteration. The as-cast Ti-40Zr-4Al-0.005B alloys demonstrated the highest tensile strength (σ{sub b}=1134 MPa), which increased by 53% compared to the Ti-4Al-0.005B alloys, whereas the lowest elongation-to-failure was of 6.77%. The mechanical properties of the TχZAB alloy series were discussed based on the microstructural evolution and the solid solution strengthening mechanisms.
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Energy Technology Data Exchange (ETDEWEB)
Fuller, Christian B., E-mail: christian.fuller@yahoo.com [Rockwell Scientific, 1049 Camino Dos Rios, Thousand Oaks, CA 93021 (United States); Mahoney, Murray W., E-mail: murraymahoney@comcast.net [Rockwell Scientific, 1049 Camino Dos Rios, Thousand Oaks, CA 93021 (United States); Calabrese, Mike [Rockwell Scientific, 1049 Camino Dos Rios, Thousand Oaks, CA 93021 (United States); Micona, Leanna [The Boeing Company, P.O. Box 3707 MC 19-HP, Seattle, WA 98124 (United States)
2010-04-15
The microstructural and mechanical property evolution of friction stir welded 7050-T7651 and 7075-T651 Al alloys were examined as a function of room temperature (natural) aging for up to 67,920 h. During the range of aging times studied, transverse tensile strengths continuously increased, and are still increasing, with improvements of 24% and 29% measured for the 7050-T7651 and 7075-T651 Al alloy friction stir welds, respectively. Microstructural evolution within the weld nugget and heat-affected zone was evaluated with both transmission electron microscopy (TEM) and differential scanning calorimetry (DSC). Formation of a high volume fraction of GP(II) zones produced a majority of the strength improvement within the weld nugget and HAZ regions. The rational for the microstructural changes are discussed in light of the mechanical properties.
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Directory of Open Access Journals (Sweden)
Garl
2016-07-01
Full Text Available Eric L Garland,1,2 Matthew O Howard,3 Sarah E Priddy,1 Patrick A McConnell,4 Michael R Riquino,1 Brett Froeliger4 1College of Social Work, 2Hunstsman Cancer Institute, University of Utah, Salt Lake City, UT, USA; 3School of Social Work, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; 4Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA Abstract: Dual-process models from neuroscience suggest that addiction is driven by dysregulated interactions between bottom-up neural processes underpinning reward learning and top-down neural functions subserving executive function. Over time, drug use causes atrophy in prefrontally mediated cognitive control networks and hijacks striatal circuits devoted to processing natural rewards in service of compulsive seeking of drug-related reward. In essence, mindfulness-based interventions (MBIs can be conceptualized as mental training programs for exercising, strengthening, and remediating these functional brain networks. This review describes how MBIs may remediate addiction by regulating frontostriatal circuits, thereby restoring an adaptive balance between these top-down and bottom-up processes. Empirical evidence is presented suggesting that MBIs facilitate cognitive control over drug-related automaticity, attentional bias, and drug cue reactivity, while enhancing responsiveness to natural rewards. Findings from the literature are incorporated into an integrative account of the neural mechanisms of mindfulness-based therapies for effecting positive behavior change in the context of addiction recovery. Implications of our theoretical framework are presented with respect to how these insights can inform the addiction therapy process. Keywords: mindfulness, frontostriatal, savoring, cue reactivity, hedonic dysregulation, reward, addiction
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Neural mechanisms underlying the induction and relief of perceptual curiosity
Directory of Open Access Journals (Sweden)
Marieke eJepma
2012-02-01
Full Text Available Curiosity is one of the most basic biological drives in both animals and humans, and has been identified as a key motive for learning and discovery. Despite the importance of curiosity and related behaviors, the topic has been largely neglected in human neuroscience; hence little is known about the neurobiological mechanisms underlying curiosity. We used functional magnetic resonance imaging (fMRI to investigate what happens in our brain during the induction and subsequent relief of perceptual curiosity. Our core findings were that (i the induction of perceptual curiosity, through the presentation of ambiguous visual input, activated the anterior insula and anterior cingulate cortex, brain regions sensitive to conflict and arousal; (ii the relief of perceptual curiosity, through visual disambiguation, activated regions of the striatum that have been related to reward processing; and (iii the relief of perceptual curiosity was associated with hippocampal activation and enhanced incidental memory. These findings provide the first demonstration of the neural basis of human perceptual curiosity. Our results provide neurobiological support for a classic psychological theory of curiosity, which holds that curiosity is an aversive condition of increased arousal whose termination is rewarding and facilitates memory.
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Neural Mechanisms of Emotion Regulation in Autism Spectrum Disorder
Richey, J. Anthony; Damiano, Cara R.; Sabatino, Antoinette; Rittenberg, Alison; Petty, Chris; Bizzell, Josh; Voyvodic, James; Heller, Aaron S.; Coffman, Marika C.; Smoski, Moria; Davidson, Richard J.; Dichter, Gabriel S.
2015-01-01
Autism spectrum disorder (ASD) is characterized by high rates of comorbid internalizing and externalizing disorders. One mechanistic account of these comorbidities is that ASD is characterized by impaired emotion regulation (ER) that results in deficits modulating emotional responses. We assessed neural activation during cognitive reappraisal of…
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Neural network approach for the calculation of potential coefficients in quantum mechanics
Ossandón, Sebastián; Reyes, Camilo; Cumsille, Patricio; Reyes, Carlos M.
2017-05-01
A numerical method based on artificial neural networks is used to solve the inverse Schrödinger equation for a multi-parameter class of potentials. First, the finite element method was used to solve repeatedly the direct problem for different parametrizations of the chosen potential function. Then, using the attainable eigenvalues as a training set of the direct radial basis neural network a map of new eigenvalues was obtained. This relationship was later inverted and refined by training an inverse radial basis neural network, allowing the calculation of the unknown parameters and therefore estimating the potential function. Three numerical examples are presented in order to prove the effectiveness of the method. The results show that the method proposed has the advantage to use less computational resources without a significant accuracy loss.
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The neural basis of financial risk taking.
Kuhnen, Camelia M; Knutson, Brian
2005-09-01
Investors systematically deviate from rationality when making financial decisions, yet the mechanisms responsible for these deviations have not been identified. Using event-related fMRI, we examined whether anticipatory neural activity would predict optimal and suboptimal choices in a financial decision-making task. We characterized two types of deviations from the optimal investment strategy of a rational risk-neutral agent as risk-seeking mistakes and risk-aversion mistakes. Nucleus accumbens activation preceded risky choices as well as risk-seeking mistakes, while anterior insula activation preceded riskless choices as well as risk-aversion mistakes. These findings suggest that distinct neural circuits linked to anticipatory affect promote different types of financial choices and indicate that excessive activation of these circuits may lead to investing mistakes. Thus, consideration of anticipatory neural mechanisms may add predictive power to the rational actor model of economic decision making.
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Fuller, Rebecca C
2009-07-01
The sensory bias model for the evolution of mating preferences states that mating preferences evolve as correlated responses to selection on nonmating behaviors sharing a common sensory system. The critical assumption is that pleiotropy creates genetic correlations that affect the response to selection. I simulated selection on populations of neural networks to test this. First, I selected for various combinations of foraging and mating preferences. Sensory bias predicts that populations with preferences for like-colored objects (red food and red mates) should evolve more readily than preferences for differently colored objects (red food and blue mates). Here, I found no evidence for sensory bias. The responses to selection on foraging and mating preferences were independent of one another. Second, I selected on foraging preferences alone and asked whether there were correlated responses for increased mating preferences for like-colored mates. Here, I found modest evidence for sensory bias. Selection for a particular foraging preference resulted in increased mating preference for similarly colored mates. However, the correlated responses were small and inconsistent. Selection on foraging preferences alone may affect initial levels of mating preferences, but these correlations did not constrain the joint evolution of foraging and mating preferences in these simulations.
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Imprinted X chromosome inactivation: evolution of mechanisms in distantly related mammals
Directory of Open Access Journals (Sweden)
Shafagh A. Waters
2015-03-01
Full Text Available In females, X chromosome inactivation (XCI ensures transcriptional silencing of one of the two Xs (either in a random or imprinted fashion in somatic cells. Comparing this silencing between species has offered insight into different mechanisms of X inactivation, providing clues into the evolution of this epigenetic process in mammals. Long-noncoding RNAs have emerged as a common theme in XCI of therian mammals (eutherian and marsupial. Eutherian X inactivation is regulated by the noncoding RNA product of XIST, within a cis-acting master control region called the X inactivation center (XIC. Marsupials XCI is XIST independent. Instead, XCI is controlled by the long-noncoding RNA Rsx, which appears to be a functional analog of the eutherian XIST gene, insofar that its transcript coats the inactive X and represses activity of genes in cis. In this review we discuss XCI in eutherians, and contrast imprinted X inactivation in mouse and marsupials. We provide particular focus on the evolution of genomic elements that confer the unique epigenetic features that characterize the inactive X chromosome.
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Morphology, defect evolutions and nano-mechanical anisotropy of behenic acid monolayer
International Nuclear Information System (INIS)
Yang Guanghong; Jiang Xiaohong; Dai Shuxi; Cheng Gang; Zhang Xingtang; Du Zuliang
2010-01-01
Langmuir-Blodgett monolayers of behenic acid (BA) were prepared by the vertical deposition method and their morphological evolutions and nano-mechanical anisotropy were studied by atomic force microscopy (AFM) and lateral force microscopy. Results show that there are platforms in the differential surface pressure-area (π-A) isotherm presenting linear relations between the chain tilting angles and surface pressures. The reorganization, appearance and disappearance of defects such as pinholes and holes can strongly affect the profile of π-A isotherm; AFM images reflect evolution rules from pinholes to holes, and from monolayer to bilayers along with compression and relaxation of structures in BA monolayer. Due to higher molecule density and larger real contact area, the tip-monolayer contacts at 15 and 25 mN/m correspond to the Derjaguin-Muller-Toporov (DMT) model showing long-ranged interaction forces. But owing to more easily-deformed conformations, contacts at 5 and 35 mN/m accord with the Johnson-Kendall-Robert and DMT transition cases exhibiting short-ranged interface interactions. A little higher friction is proved in the direction perpendicular to the deposition.
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Neural mechanisms of rapid sensitivity to syntactic anomaly
Directory of Open Access Journals (Sweden)
Albert E. Kim
2013-03-01
Full Text Available Recent psycholinguistic models hypothesize that anticipatory processing can speed the response to linguistic input during language comprehension by pre-activating representations necessary for word recognition. We investigated the neurocognitive mechanisms of anticipatory processing by recording event-related brain responses (ERPs to syntactically anomalous (The thief was caught by for police and well-formed (e.g., The thief was caught by the police sentences. One group of participants saw anomalies elicited by the same word in every instance (e.g., for; low-variability stimuli, providing high affordances for predictions about the word-form appearing in the critical position. A second group saw anomalies elicited by seven different prepositions (at, of, on, for, from, over, with; high-variability stimuli across the study, creating a more difficult prediction task. Syntactic category anomalies enhanced the occipital-temporal N170 component of the ERP, indicating rapid sensitivity—within 200 ms of word onset—to syntactic anomaly. For low-variability but not the high-variability stimuli, syntactic anomaly also enhanced the earlier occipital-temporal P1 component, around 130 ms after word-onset, indicating that affordances for prediction engendered earlier sensitivity to syntactic anomaly. Independent components analysis revealed three sources within the ERP signal whose functional dynamics were consistent with predictive processing and early responses to syntactic anomaly. Distributed neural source modeling (sLORETA of these early-active sources produced a candidate network for early responses to words during reading in the right posterior-occipital, left occipital-temporal, and medial parietal cortex.
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The Evolution of Learning Mechanisms.
Garcia, John; Garcia y Robertson, Rodrigo
This paper introduces seven principles of learning, enduring over the last five centuries of psychological thought, to discuss the evolution of the "Biophyche" (the brain in action) in the development of humans and other large organisms. It describes the conditioning theories of Darwin, Pavlov, and Thorndike and critically reviews the…
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Directory of Open Access Journals (Sweden)
Poramate eManoonpong
2013-02-01
Full Text Available Living creatures, like walking animals, have found fascinating solutions for the problem of locomotion control. Their movements show the impression of elegance including versatile, energy-efficient, and adaptable locomotion. During the last few decades, roboticists have tried to imitate such natural properties with artificial legged locomotion systems by using different approaches including machine learning algorithms, classical engineering control techniques, and biologically-inspired control mechanisms. However, their levels of performance are still far from the natural ones. By contrast, animal locomotion mechanisms seem to largely depend not only on central mechanisms (central pattern generators, CPGs and sensory feedback (afferent-based control but also on internal forward models (efference copies. They are used to a different degree in different animals. Generally, CPGs organize basic rhythmic motions which are shaped by sensory feedback while internal models are used for sensory prediction and state estimations. According to this concept, we present here adaptive neural locomotion control consisting of a CPG mechanism with neuromodulation and local leg control mechanisms based on sensory feedback and adaptive neural forward models with efference copies. This neural closed-loop controller enables a walking machine to perform a multitude of different walking patterns including insect-like leg movements and gaits as well as energy-efficient locomotion. In addition, the forward models allow the machine to autonomously adapt its locomotion to deal with a change of terrain, losing of ground contact during stance phase, stepping on or hitting an obstacle during swing phase, leg damage, and even to promote cockroach-like climbing behavior. Thus, the results presented here show that the employed embodied neural closed-loop system can be a powerful way for developing robust and adaptable machines.
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Neural plasticity and its initiating conditions in tinnitus.
Roberts, L E
2018-03-01
Deafferentation caused by cochlear pathology (which can be hidden from the audiogram) activates forms of neural plasticity in auditory pathways, generating tinnitus and its associated conditions including hyperacusis. This article discusses tinnitus mechanisms and suggests how these mechanisms may relate to those involved in normal auditory information processing. Research findings from animal models of tinnitus and from electromagnetic imaging of tinnitus patients are reviewed which pertain to the role of deafferentation and neural plasticity in tinnitus and hyperacusis. Auditory neurons compensate for deafferentation by increasing their input/output functions (gain) at multiple levels of the auditory system. Forms of homeostatic plasticity are believed to be responsible for this neural change, which increases the spontaneous and driven activity of neurons in central auditory structures in animals expressing behavioral evidence of tinnitus. Another tinnitus correlate, increased neural synchrony among the affected neurons, is forged by spike-timing-dependent neural plasticity in auditory pathways. Slow oscillations generated by bursting thalamic neurons verified in tinnitus animals appear to modulate neural plasticity in the cortex, integrating tinnitus neural activity with information in brain regions supporting memory, emotion, and consciousness which exhibit increased metabolic activity in tinnitus patients. The latter process may be induced by transient auditory events in normal processing but it persists in tinnitus, driven by phantom signals from the auditory pathway. Several tinnitus therapies attempt to suppress tinnitus through plasticity, but repeated sessions will likely be needed to prevent tinnitus activity from returning owing to deafferentation as its initiating condition.
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Neural mechanisms underlying sensitivity to reverse-phi motion in the fly
Meier, Matthias; Serbe, Etienne; Eichner, Hubert; Borst, Alexander
2017-01-01
Optical illusions provide powerful tools for mapping the algorithms and circuits that underlie visual processing, revealing structure through atypical function. Of particular note in the study of motion detection has been the reverse-phi illusion. When contrast reversals accompany discrete movement, detected direction tends to invert. This occurs across a wide range of organisms, spanning humans and invertebrates. Here, we map an algorithmic account of the phenomenon onto neural circuitry in the fruit fly Drosophila melanogaster. Through targeted silencing experiments in tethered walking flies as well as electrophysiology and calcium imaging, we demonstrate that ON- or OFF-selective local motion detector cells T4 and T5 are sensitive to certain interactions between ON and OFF. A biologically plausible detector model accounts for subtle features of this particular form of illusory motion reversal, like the re-inversion of turning responses occurring at extreme stimulus velocities. In light of comparable circuit architecture in the mammalian retina, we suggest that similar mechanisms may apply even to human psychophysics. PMID:29261684
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Geological and rock mechanics aspects of the long-term evolution of a crystalline rock site
International Nuclear Information System (INIS)
Cosgrove, J.W.; Hudson, J.A.
2009-01-01
We consider the stability of a crystalline rock mass and hence the integrity of a radioactive waste repository contained therein by, firstly, identifying the geological evolution of such a site and, secondly, by assessing the likely rock mechanics consequences of the natural perturbations to the repository. In this way, the potency of an integrated geological-rock mechanics approach is demonstrated. The factors considered are the pre-repository geological evolution, the period of repository excavation, emplacement and closure, and the subsequent degradation and natural geological perturbations introduced by glacial loading. It is found that the additional rock stresses associated with glacial advance and retreat have a first order effect on the stress magnitudes and are likely to cause a radical change in the stress regime. There are many factors involved in the related geosphere stability and so the paper concludes with a systems diagram of the total evolutionary considerations before, during and after repository construction. (authors)
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Insights from amphioxus into the evolution of vertebrate cartilage.
Directory of Open Access Journals (Sweden)
Daniel Meulemans
2007-08-01
Full Text Available Central to the story of vertebrate evolution is the origin of the vertebrate head, a problem difficult to approach using paleontology and comparative morphology due to a lack of unambiguous intermediate forms. Embryologically, much of the vertebrate head is derived from two ectodermal tissues, the neural crest and cranial placodes. Recent work in protochordates suggests the first chordates possessed migratory neural tube cells with some features of neural crest cells. However, it is unclear how and when these cells acquired the ability to form cellular cartilage, a cell type unique to vertebrates. It has been variously proposed that the neural crest acquired chondrogenic ability by recruiting proto-chondrogenic gene programs deployed in the neural tube, pharynx, and notochord. To test these hypotheses we examined the expression of 11 amphioxus orthologs of genes involved in neural crest chondrogenesis. Consistent with cellular cartilage as a vertebrate novelty, we find that no single amphioxus tissue co-expresses all or most of these genes. However, most are variously co-expressed in mesodermal derivatives. Our results suggest that neural crest-derived cartilage evolved by serial cooption of genes which functioned primitively in mesoderm.
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Dediu, D.
2008-01-01
The causal correlations between human genetic variants and linguistic (typological) features could represent the mechanism required for gradual, accretionary models of language evolution. The causal link is mediated by the process of cultural transmission of language across generations in a population of genetically biased individuals. The particular case of Tone, ASPM and Microcephalin is discussed as an illustration. It is proposed that this type of genetically-influenced linguistic bias, c...
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Neural Behavior Chain Learning of Mobile Robot Actions
Directory of Open Access Journals (Sweden)
Lejla Banjanovic-Mehmedovic
2012-01-01
Full Text Available This paper presents a visual/motor behavior learning approach, based on neural networks. We propose Behavior Chain Model (BCM in order to create a way of behavior learning. Our behavior-based system evolution task is a mobile robot detecting a target and driving/acting towards it. First, the mapping relations between the image feature domain of the object and the robot action domain are derived. Second, a multilayer neural network for offline learning of the mapping relations is used. This learning structure through neural network training process represents a connection between the visual perceptions and motor sequence of actions in order to grip a target. Last, using behavior learning through a noticed action chain, we can predict mobile robot behavior for a variety of similar tasks in similar environment. Prediction results suggest that the methodology is adequate and could be recognized as an idea for designing different mobile robot behaviour assistance.
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Tandon, Shashank; Keefe, Kristen A; Taha, Sharif A
2017-02-15
The lateral habenula (LHb) has been implicated in regulation of drug-seeking behaviours through aversion-mediated learning. In this study, we recorded neuronal activity in the LHb of rats during an operant task before and after ethanol-induced conditioned taste aversion (CTA) to saccharin. Ethanol-induced CTA caused significantly higher baseline firing rates in LHb neurons, as well as elevated firing rates in response to cue presentation, lever press and saccharin taste. In a separate cohort of rats, we found that bilateral LHb lesions blocked ethanol-induced CTA. Our results strongly suggest that excitation of LHb neurons is required for ethanol-induced CTA, and point towards a mechanism through which LHb firing may regulate voluntary ethanol consumption. Ethanol, like other drugs of abuse, has both rewarding and aversive properties. Previous work suggests that sensitivity to ethanol's aversive effects negatively modulates voluntary alcohol intake and thus may be important in vulnerability to developing alcohol use disorders. We previously found that rats with lesions of the lateral habenula (LHb), which is implicated in aversion-mediated learning, show accelerated escalation of voluntary ethanol consumption. To understand neural encoding in the LHb contributing to ethanol-induced aversion, we recorded neural firing in the LHb of freely behaving, water-deprived rats before and after an ethanol-induced (1.5 g kg -1 20% ethanol, i.p.) conditioned taste aversion (CTA) to saccharin taste. Ethanol-induced CTA strongly decreased motivation for saccharin in an operant task to obtain the tastant. Comparison of LHb neural firing before and after CTA induction revealed four main differences in firing properties. First, baseline firing after CTA induction was significantly higher. Second, firing evoked by cues signalling saccharin availability shifted from a pattern of primarily inhibition before CTA to primarily excitation after CTA induction. Third, CTA induction reduced
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Keefe, Kristen A.; Taha, Sharif A.
2016-01-01
Key points The lateral habenula (LHb) has been implicated in regulation of drug‐seeking behaviours through aversion‐mediated learning.In this study, we recorded neuronal activity in the LHb of rats during an operant task before and after ethanol‐induced conditioned taste aversion (CTA) to saccharin.Ethanol‐induced CTA caused significantly higher baseline firing rates in LHb neurons, as well as elevated firing rates in response to cue presentation, lever press and saccharin taste.In a separate cohort of rats, we found that bilateral LHb lesions blocked ethanol‐induced CTA.Our results strongly suggest that excitation of LHb neurons is required for ethanol‐induced CTA, and point towards a mechanism through which LHb firing may regulate voluntary ethanol consumption. Abstract Ethanol, like other drugs of abuse, has both rewarding and aversive properties. Previous work suggests that sensitivity to ethanol's aversive effects negatively modulates voluntary alcohol intake and thus may be important in vulnerability to developing alcohol use disorders. We previously found that rats with lesions of the lateral habenula (LHb), which is implicated in aversion‐mediated learning, show accelerated escalation of voluntary ethanol consumption. To understand neural encoding in the LHb contributing to ethanol‐induced aversion, we recorded neural firing in the LHb of freely behaving, water‐deprived rats before and after an ethanol‐induced (1.5 g kg−1 20% ethanol, i.p.) conditioned taste aversion (CTA) to saccharin taste. Ethanol‐induced CTA strongly decreased motivation for saccharin in an operant task to obtain the tastant. Comparison of LHb neural firing before and after CTA induction revealed four main differences in firing properties. First, baseline firing after CTA induction was significantly higher. Second, firing evoked by cues signalling saccharin availability shifted from a pattern of primarily inhibition before CTA to primarily excitation after CTA
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Dewar, Alex D M; Wystrach, Antoine; Philippides, Andrew; Graham, Paul
2017-10-01
All organisms wishing to survive and reproduce must be able to respond adaptively to a complex, changing world. Yet the computational power available is constrained by biology and evolution, favouring mechanisms that are parsimonious yet robust. Here we investigate the information carried in small populations of visually responsive neurons in Drosophila melanogaster. These so-called 'ring neurons', projecting to the ellipsoid body of the central complex, are reported to be necessary for complex visual tasks such as pattern recognition and visual navigation. Recently the receptive fields of these neurons have been mapped, allowing us to investigate how well they can support such behaviours. For instance, in a simulation of classic pattern discrimination experiments, we show that the pattern of output from the ring neurons matches observed fly behaviour. However, performance of the neurons (as with flies) is not perfect and can be easily improved with the addition of extra neurons, suggesting the neurons' receptive fields are not optimised for recognising abstract shapes, a conclusion which casts doubt on cognitive explanations of fly behaviour in pattern recognition assays. Using artificial neural networks, we then assess how easy it is to decode more general information about stimulus shape from the ring neuron population codes. We show that these neurons are well suited for encoding information about size, position and orientation, which are more relevant behavioural parameters for a fly than abstract pattern properties. This leads us to suggest that in order to understand the properties of neural systems, one must consider how perceptual circuits put information at the service of behaviour.
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Neural Mechanisms of Cognitive Dissonance (Revised): An EEG Study.
Colosio, Marco; Shestakova, Anna; Nikulin, Vadim V; Blagovechtchenski, Evgeny; Klucharev, Vasily
2017-05-17
Cognitive dissonance theory suggests that our preferences are modulated by the mere act of choosing. A choice between two similarly valued alternatives creates psychological tension (cognitive dissonance) that is reduced by a postdecisional reevaluation of the alternatives. We measured EEG of human subjects during rest and free-choice paradigm. Our study demonstrates that choices associated with stronger cognitive dissonance trigger a larger negative frontocentral evoked response similar to error-related negativity, which has in turn been implicated in general performance monitoring. Furthermore, the amplitude of the evoked response is correlated with the reevaluation of the alternatives. We also found a link between individual neural dynamics (long-range temporal correlations) of the frontocentral cortices during rest and follow-up neural and behavioral effects of cognitive dissonance. Individuals with stronger resting-state long-range temporal correlations demonstrated a greater postdecisional reevaluation of the alternatives and larger evoked brain responses associated with stronger cognitive dissonance. Thus, our results suggest that cognitive dissonance is reflected in both resting-state and choice-related activity of the prefrontal cortex as part of the general performance-monitoring circuitry. SIGNIFICANCE STATEMENT Contrary to traditional decision theory, behavioral studies repeatedly demonstrate that our preferences are modulated by the mere act of choosing. Difficult choices generate psychological (cognitive) dissonance, which is reduced by the postdecisional devaluation of unchosen options. We found that decisions associated with a higher level of cognitive dissonance elicited a stronger negative frontocentral deflection that peaked ∼60 ms after the response. This activity shares similar spatial and temporal features as error-related negativity, the electrophysiological correlate of performance monitoring. Furthermore, the frontocentral resting
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FE Analysis of Rock with Hydraulic-Mechanical Coupling Based on Continuum Damage Evolution
Directory of Open Access Journals (Sweden)
Yongliang Wang
2016-01-01
Full Text Available A numerical finite element (FE analysis technology is presented for efficient and reliable solutions of rock with hydraulic-mechanical (HM coupling, researching the seepage characteristics and simulating the damage evolution of rock. To be in accord with the actual situation, the rock is naturally viewed as heterogeneous material, in which Young’s modulus, permeability, and strength property obey the typical Weibull distribution function. The classic Biot constitutive relation for rock as porous medium is introduced to establish a set of equations coupling with elastic solid deformation and seepage flow. The rock is subsequently developed into a novel conceptual and practical model considering the damage evolution of Young’s modulus and permeability, in which comprehensive utilization of several other auxiliary technologies, for example, the Drucker-Prager strength criterion, the statistical strength theory, and the continuum damage evolution, yields the damage variable calculating technology. To this end, an effective and reliable numerical FE analysis strategy is established. Numerical examples are given to show that the proposed method can establish heterogeneous rock model and be suitable for different load conditions and furthermore to demonstrate the effectiveness and reliability in the seepage and damage characteristics analysis for rock.
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Using neural networks in software repositories
Eichmann, David (Editor); Srinivas, Kankanahalli; Boetticher, G.
1992-01-01
The first topic is an exploration of the use of neural network techniques to improve the effectiveness of retrieval in software repositories. The second topic relates to a series of experiments conducted to evaluate the feasibility of using adaptive neural networks as a means of deriving (or more specifically, learning) measures on software. Taken together, these two efforts illuminate a very promising mechanism supporting software infrastructures - one based upon a flexible and responsive technology.
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Directory of Open Access Journals (Sweden)
Rogers Crystal D
2011-12-01
Full Text Available Abstract Background The molecular mechanism that initiates the formation of the vertebrate central nervous system has long been debated. Studies in Xenopus and mouse demonstrate that inhibition of BMP signaling is sufficient to induce neural tissue in explants or ES cells respectively, whereas studies in chick argue that instructive FGF signaling is also required for the expression of neural genes. Although additional signals may be involved in neural induction and patterning, here we focus on the roles of BMP inhibition and FGF8a. Results To address the question of necessity and sufficiency of BMP inhibition and FGF signaling, we compared the temporal expression of the five earliest genes expressed in the neuroectoderm and determined their requirements for induction at the onset of neural plate formation in Xenopus. Our results demonstrate that the onset and peak of expression of the genes vary and that they have different regulatory requirements and are therefore unlikely to share a conserved neural induction regulatory module. Even though all require inhibition of BMP for expression, some also require FGF signaling; expression of the early-onset pan-neural genes sox2 and foxd5α requires FGF signaling while other early genes, sox3, geminin and zicr1 are induced by BMP inhibition alone. Conclusions We demonstrate that BMP inhibition and FGF signaling induce neural genes independently of each other. Together our data indicate that although the spatiotemporal expression patterns of early neural genes are similar, the mechanisms involved in their expression are distinct and there are different signaling requirements for the expression of each gene.
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Wang, Chi-Hsu; Chen, Chun-Yao; Hung, Kun-Neng
2015-06-01
In this paper, a new adaptive self-organizing map (SOM) with recurrent neural network (RNN) controller is proposed for task assignment and path evolution of missile defense system (MDS). We address the problem of N agents (defending missiles) and D targets (incoming missiles) in MDS. A new RNN controller is designed to force an agent (or defending missile) toward a target (or incoming missile), and a monitoring controller is also designed to reduce the error between RNN controller and ideal controller. A new SOM with RNN controller is then designed to dispatch agents to their corresponding targets by minimizing total damaging cost. This is actually an important application of the multiagent system. The SOM with RNN controller is the main controller. After task assignment, the weighting factors of our new SOM with RNN controller are activated to dispatch the agents toward their corresponding targets. Using the Lyapunov constraints, the weighting factors for the proposed SOM with RNN controller are updated to guarantee the stability of the path evolution (or planning) system. Excellent simulations are obtained using this new approach for MDS, which show that our RNN has the lowest average miss distance among the several techniques.
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Brewin, Chris R; Gregory, James D; Lipton, Michelle; Burgess, Neil
2010-01-01
Involuntary images and visual memories are prominent in many types of psychopathology. Patients with posttraumatic stress disorder, other anxiety disorders, depression, eating disorders, and psychosis frequently report repeated visual intrusions corresponding to a small number of real or imaginary events, usually extremely vivid, detailed, and with highly distressing content. Both memory and imagery appear to rely on common networks involving medial prefrontal regions, posterior regions in the medial and lateral parietal cortices, the lateral temporal cortex, and the medial temporal lobe. Evidence from cognitive psychology and neuroscience implies distinct neural bases to abstract, flexible, contextualized representations (C-reps) and to inflexible, sensory-bound representations (S-reps). We revise our previous dual representation theory of posttraumatic stress disorder to place it within a neural systems model of healthy memory and imagery. The revised model is used to explain how the different types of distressing visual intrusions associated with clinical disorders arise, in terms of the need for correct interaction between the neural systems supporting S-reps and C-reps via visuospatial working memory. Finally, we discuss the treatment implications of the new model and relate it to existing forms of psychological therapy.
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Artificial intelligence: Deep neural reasoning
Jaeger, Herbert
2016-10-01
The human brain can solve highly abstract reasoning problems using a neural network that is entirely physical. The underlying mechanisms are only partially understood, but an artificial network provides valuable insight. See Article p.471
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Nonapeptides and the Evolution of Social Group Sizes in Birds
Directory of Open Access Journals (Sweden)
James L. Goodson
2011-03-01
Full Text Available Species-typical patterns of grouping have profound impacts on many aspects of physiology and behavior. However, prior to our recent studies in estrildid finches, neural mechanisms that titrate species-typical group size preferences, independent of other aspects of social organization (e.g., mating system and parental care, have been wholly unexplored, likely because species-typical group size is typically confounded with other aspects of behavior and biology. An additional complication is that components of social organization are evolutionarily labile and prone to repeated divergence and convergence. Hence, we cannot assume that convergence in social structure has been produced by convergent modifications to the same neural characters, and thus any comparative approach to grouping must include not only species that differ in their species-typical group sizes, but also species that exhibit convergent evolution in this aspect of social organization. Using five estrildid finch species that differ selectively in grouping (all biparental and monogamous we have demonstrated that neural motivational systems evolve in predictable ways in relation to species-typical group sizes, including convergence in two highly gregarious species and convergence in two relatively asocial, territorial species. These systems include nonapeptide (vasotocin and mesotocin circuits that encode the valence of social stimuli (positive-negative, titrate group-size preferences, and modulate anxiety-like behaviors. Nonapeptide systems exhibit functional and anatomical properties that are biased towards gregarious species, and experimental reductions of nonapeptide signaling by receptor antagonism and antisense oligonucleotides significantly decrease preferred group sizes in the gregarious zebra finch. Combined, these findings suggest that selection on species-typical group size may reliably target the same neural motivation systems when a given social structure evolves
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Neural synchrony in cortical networks: history, concept and current status
Directory of Open Access Journals (Sweden)
Peter Uhlhaas
2009-07-01
Full Text Available Following the discovery of context-dependent synchronization of oscillatory neuronal responses in the visual system, the role of neural synchrony in cortical networks has been expanded to provide a general mechanism for the coordination of distributed neural activity patterns. In the current paper, we present an update of the status of this hypothesis through summarizing recent results from our laboratory that suggest important new insights regarding the mechanisms, function and relevance of this phenomenon. In the first part, we present recent results derived from animal experiments and mathematical simulations that provide novel explanations and mechanisms for zero and nero-zero phase lag synchronization. In the second part, we shall discuss the role of neural synchrony for expectancy during perceptual organization and its role in conscious experience. This will be followed by evidence that indicates that in addition to supporting conscious cognition, neural synchrony is abnormal in major brain disorders, such as schizophrenia and autism spectrum disorders. We conclude this paper with suggestions for further research as well as with critical issues that need to be addressed in future studies.
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Hardware implementation of stochastic spiking neural networks.
Rosselló, Josep L; Canals, Vincent; Morro, Antoni; Oliver, Antoni
2012-08-01
Spiking Neural Networks, the last generation of Artificial Neural Networks, are characterized by its bio-inspired nature and by a higher computational capacity with respect to other neural models. In real biological neurons, stochastic processes represent an important mechanism of neural behavior and are responsible of its special arithmetic capabilities. In this work we present a simple hardware implementation of spiking neurons that considers this probabilistic nature. The advantage of the proposed implementation is that it is fully digital and therefore can be massively implemented in Field Programmable Gate Arrays. The high computational capabilities of the proposed model are demonstrated by the study of both feed-forward and recurrent networks that are able to implement high-speed signal filtering and to solve complex systems of linear equations.
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Newcomb, James M.; Sakurai, Akira; Lillvis, Joshua L.; Gunaratne, Charuni A.; Katz, Paul S.
2012-01-01
How neural circuit evolution relates to behavioral evolution is not well understood. Here the relationship between neural circuits and behavior is explored with respect to the swimming behaviors of the Nudipleura (Mollusca, Gastropoda, Opithobranchia). Nudipleura is a diverse monophyletic clade of sea slugs among which only a small percentage of species can swim. Swimming falls into a limited number of categories, the most prevalent of which are rhythmic left–right body flexions (LR) and rhythmic dorsal–ventral body flexions (DV). The phylogenetic distribution of these behaviors suggests a high degree of homoplasy. The central pattern generator (CPG) underlying DV swimming has been well characterized in Tritonia diomedea and in Pleurobranchaea californica. The CPG for LR swimming has been elucidated in Melibe leonina and Dendronotus iris, which are more closely related. The CPGs for the categorically distinct DV and LR swimming behaviors consist of nonoverlapping sets of homologous identified neurons, whereas the categorically similar behaviors share some homologous identified neurons, although the exact composition of neurons and synapses in the neural circuits differ. The roles played by homologous identified neurons in categorically distinct behaviors differ. However, homologous identified neurons also play different roles even in the swim CPGs of the two LR swimming species. Individual neurons can be multifunctional within a species. Some of those functions are shared across species, whereas others are not. The pattern of use and reuse of homologous neurons in various forms of swimming and other behaviors further demonstrates that the composition of neural circuits influences the evolution of behaviors. PMID:22723353
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Mammalian life histories: their evolution and molecular-genetic mechanisms
Energy Technology Data Exchange (ETDEWEB)
Sacher, G.A.
1978-01-01
Survival curves for various species of mammals are discussed and a table is presented to show recorded maximum life spans of about 30 species of mammals. The range of longevities is from one year for shrews and moles up to more than 80 years for the fin whale. The constitutional correlates of longevity are discussed with regard to body size, brain weight,metabolic rates, and body temperature. It is concluded that longevity evolved as a positive trait, associated with the evolution of large body size and brain size. Life table data for man, the thorough-bred horse, beagle dogs, and the laboratory rodents, Mus musculus and Peromyscus leucopus are discussed. The data show a pattern of exponential increase of death rate with age. A laboratory model using Mus musculus and Peromyscus leucopus for the study of the longevity-assurance mechanisms is described. (HLW)
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Fluoride contamination in the lakes region of the Ethiopian rift: origin, mechanism and evolution
International Nuclear Information System (INIS)
Travi, Y.; Chernet, T.
1998-01-01
The closed lake basins occupying the Main Ethiopian Rift are characterised by unique hydrogeological conditions which have resulted in very high contents of fluoride associated with highly concentrated sodium bicarbonate waters. The origin, mechanism and evolution of fluoride contents have been examined successively by studying (i) the reservoirs which provide this element in solution, (ii) the hydrochemical context, and (iii) the hydrological evolution which modifies the concentrations. Groundwaters of the ignimbrites present low values compared to those of the lacustrine sediments which can provide contents 5 to 10 times greater. The non equilibrium initial stage between the alkalinity and the calcium, derived from weathering of volcanic rocks, is responsible for the specific chemical evolution and the very high fluoride values. Furthermore, in the thermal waters, the high temperatures (especially those up to 100 deg. C) and the presence of large amounts of CO 2 coming from depth increase significantly the fluoride contents. Finally, the fluoride concentrations can change depending on the interrelation of ancient or present surface waters and groundwaters (mixing) and on the hydrological balance (concentration and dilution processes). (author)
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Adly, A. A.; Abd-El-Hafiz, S. K.
2018-05-01
It is well known that accurate modeling of magnetostrictive hysteresis is crucial to different industrial applications. Although several magnetostrictive models have been developed in the past, the accuracy-efficiency balance has always been crucial. Recently, the possibility of constructing a primitive vector hysteresis operator using a tri-node Hopfield Neural Network (HNN) was demonstrated. Based upon the fact that mechanical stress along a certain direction results in dimensional deformation, this paper introduces a novel extension to the aforementioned recently developed approach. More specifically, a stress-driven evolution of a tri-node HNN hysteresis operator pair is proposed, thus yielding a tripod-like HNN pair having different input offset values. Model identification, sample simulation results and comparison with experimental measurements are given in the paper.
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Sparrey, Carolyn J; Bailey, Jeannie F; Safaee, Michael; Clark, Aaron J; Lafage, Virginie; Schwab, Frank; Smith, Justin S; Ames, Christopher P
2014-05-01
The goal of this review is to discuss the mechanisms of postural degeneration, particularly the loss of lumbar lordosis commonly observed in the elderly in the context of evolution, mechanical, and biological studies of the human spine and to synthesize recent research findings to clinical management of postural malalignment. Lumbar lordosis is unique to the human spine and is necessary to facilitate our upright posture. However, decreased lumbar lordosis and increased thoracic kyphosis are hallmarks of an aging human spinal column. The unique upright posture and lordotic lumbar curvature of the human spine suggest that an understanding of the evolution of the human spinal column, and the unique anatomical features that support lumbar lordosis may provide insight into spine health and degeneration. Considering evolution of the skeleton in isolation from other scientific studies provides a limited picture for clinicians. The evolution and development of human lumbar lordosis highlight the interdependence of pelvic structure and lumbar lordosis. Studies of fossils of human lineage demonstrate a convergence on the degree of lumbar lordosis and the number of lumbar vertebrae in modern Homo sapiens. Evolution and spine mechanics research show that lumbar lordosis is dictated by pelvic incidence, spinal musculature, vertebral wedging, and disc health. The evolution, mechanics, and biology research all point to the importance of spinal posture and flexibility in supporting optimal health. However, surgical management of postural deformity has focused on restoring posture at the expense of flexibility. It is possible that the need for complex and costly spinal fixation can be eliminated by developing tools for early identification of patients at risk for postural deformities through patient history (genetics, mechanics, and environmental exposure) and tracking postural changes over time.
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Neural Networks and Micromechanics
Kussul, Ernst; Baidyk, Tatiana; Wunsch, Donald C.
The title of the book, "Neural Networks and Micromechanics," seems artificial. However, the scientific and technological developments in recent decades demonstrate a very close connection between the two different areas of neural networks and micromechanics. The purpose of this book is to demonstrate this connection. Some artificial intelligence (AI) methods, including neural networks, could be used to improve automation system performance in manufacturing processes. However, the implementation of these AI methods within industry is rather slow because of the high cost of conducting experiments using conventional manufacturing and AI systems. To lower the cost, we have developed special micromechanical equipment that is similar to conventional mechanical equipment but of much smaller size and therefore of lower cost. This equipment could be used to evaluate different AI methods in an easy and inexpensive way. The proved methods could be transferred to industry through appropriate scaling. In this book, we describe the prototypes of low cost microequipment for manufacturing processes and the implementation of some AI methods to increase precision, such as computer vision systems based on neural networks for microdevice assembly and genetic algorithms for microequipment characterization and the increase of microequipment precision.
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Agrawal, Anurag A
2017-08-01
A charm of biology as a scientific discipline is the diversity of life. Although this diversity can make laws of biology challenging to discover, several repeated patterns and general principles govern evolutionary diversification. Convergent evolution, the independent evolution of similar phenotypes, has been at the heart of one approach to understand generality in the evolutionary process. Yet understanding when and why organismal traits and strategies repeatedly evolve has been a central challenge. These issues were the focus of the American Society of Naturalists Vice Presidential Symposium in 2016 and are the subject of this collection of articles. Although naturalists have long made inferences about convergent evolution and its importance, there has been confusion in the interpretation of the pattern of convergence. Does convergence primarily indicate adaptation or constraint? How often should convergence be expected? Are there general principles that would allow us to predict where and when and by what mechanisms convergent evolution should occur? What role does natural history play in advancing our understanding of general evolutionary principles? In this introductory article, I address these questions, review several generalizations about convergent evolution that have emerged over the past 15 years, and present a framework for advancing the study and interpretation of convergence. Perhaps the most important emerging conclusion is that the genetic mechanisms of convergent evolution are phylogenetically conserved; that is, more closely related species tend to share the same genetic basis of traits, even when independently evolved. Finally, I highlight how the articles in this special issue further develop concepts, methodologies, and case studies at the frontier of our understanding of the causes and consequences of convergent evolution.
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Neural network models of categorical perception.
Damper, R I; Harnad, S R
2000-05-01
Studies of the categorical perception (CP) of sensory continua have a long and rich history in psychophysics. In 1977, Macmillan, Kaplan, and Creelman introduced the use of signal detection theory to CP studies. Anderson and colleagues simultaneously proposed the first neural model for CP, yet this line of research has been less well explored. In this paper, we assess the ability of neural-network models of CP to predict the psychophysical performance of real observers with speech sounds and artificial/novel stimuli. We show that a variety of neural mechanisms are capable of generating the characteristics of CP. Hence, CP may not be a special model of perception but an emergent property of any sufficiently powerful general learning system.
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Mechanisms of Evolution in High-Consequence Drug Resistance Plasmids.
He, Susu; Chandler, Michael; Varani, Alessandro M; Hickman, Alison B; Dekker, John P; Dyda, Fred
2016-12-06
The dissemination of resistance among bacteria has been facilitated by the fact that resistance genes are usually located on a diverse and evolving set of transmissible plasmids. However, the mechanisms generating diversity and enabling adaptation within highly successful resistance plasmids have remained obscure, despite their profound clinical significance. To understand these mechanisms, we have performed a detailed analysis of the mobilome (the entire mobile genetic element content) of a set of previously sequenced carbapenemase-producing Enterobacteriaceae (CPE) from the National Institutes of Health Clinical Center. This analysis revealed that plasmid reorganizations occurring in the natural context of colonization of human hosts were overwhelmingly driven by genetic rearrangements carried out by replicative transposons working in concert with the process of homologous recombination. A more complete understanding of the molecular mechanisms and evolutionary forces driving rearrangements in resistance plasmids may lead to fundamentally new strategies to address the problem of antibiotic resistance. The spread of antibiotic resistance among Gram-negative bacteria is a serious public health threat, as it can critically limit the types of drugs that can be used to treat infected patients. In particular, carbapenem-resistant members of the Enterobacteriaceae family are responsible for a significant and growing burden of morbidity and mortality. Here, we report on the mechanisms underlying the evolution of several plasmids carried by previously sequenced clinical Enterobacteriaceae isolates from the National Institutes of Health Clinical Center (NIH CC). Our ability to track genetic rearrangements that occurred within resistance plasmids was dependent on accurate annotation of the mobile genetic elements within the plasmids, which was greatly aided by access to long-read DNA sequencing data and knowledge of their mechanisms. Mobile genetic elements such as
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Neural networks for predictive control of the mechanism of ...
African Journals Online (AJOL)
In this paper, we are interested in the study of the control of orientation of a wind turbine like means of optimization of his output/input ratio (efficiency). The approach suggested is based on the neural predictive control which is justified by the randomness of the wind on the one hand, and on the other hand by the capacity of ...
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Tuning Neural Phase Entrainment to Speech.
Falk, Simone; Lanzilotti, Cosima; Schön, Daniele
2017-08-01
Musical rhythm positively impacts on subsequent speech processing. However, the neural mechanisms underlying this phenomenon are so far unclear. We investigated whether carryover effects from a preceding musical cue to a speech stimulus result from a continuation of neural phase entrainment to periodicities that are present in both music and speech. Participants listened and memorized French metrical sentences that contained (quasi-)periodic recurrences of accents and syllables. Speech stimuli were preceded by a rhythmically regular or irregular musical cue. Our results show that the presence of a regular cue modulates neural response as estimated by EEG power spectral density, intertrial coherence, and source analyses at critical frequencies during speech processing compared with the irregular condition. Importantly, intertrial coherences for regular cues were indicative of the participants' success in memorizing the subsequent speech stimuli. These findings underscore the highly adaptive nature of neural phase entrainment across fundamentally different auditory stimuli. They also support current models of neural phase entrainment as a tool of predictive timing and attentional selection across cognitive domains.
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Thermo-mechanically induced texture evolution and micro-structural change of aluminum metallization
DEFF Research Database (Denmark)
Brincker, Mads; Walter, Thomas; Kristensen, Peter Kjær
2018-01-01
During operation of high power electronic chips the topside metallization is subjected to cyclic compressive and tensile stresses leading to unwanted thermo-mechanical fatigue of the metallization layer. The stress is caused by the difference in the thermal expansion coefficients...... are not yet fully understood. In this work, we investigate the microstructural evolution of an Al metallization on high power diode chips subjected to passive thermal cycling between 20 and 100ºC. The texture of the Al film is analyzed ex-situ by a combination of electron backscatter diffraction and X...
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Semantic Congruence Accelerates the Onset of the Neural Signals of Successful Memory Encoding.
Packard, Pau A; Rodríguez-Fornells, Antoni; Bunzeck, Nico; Nicolás, Berta; de Diego-Balaguer, Ruth; Fuentemilla, Lluís
2017-01-11
As the stream of experience unfolds, our memory system rapidly transforms current inputs into long-lasting meaningful memories. A putative neural mechanism that strongly influences how input elements are transformed into meaningful memory codes relies on the ability to integrate them with existing structures of knowledge or schemas. However, it is not yet clear whether schema-related integration neural mechanisms occur during online encoding. In the current investigation, we examined the encoding-dependent nature of this phenomenon in humans. We showed that actively integrating words with congruent semantic information provided by a category cue enhances memory for words and increases false recall. The memory effect of such active integration with congruent information was robust, even with an interference task occurring right after each encoding word list. In addition, via electroencephalography, we show in 2 separate studies that the onset of the neural signals of successful encoding appeared early (∼400 ms) during the encoding of congruent words. That the neural signals of successful encoding of congruent and incongruent information followed similarly ∼200 ms later suggests that this earlier neural response contributed to memory formation. We propose that the encoding of events that are congruent with readily available contextual semantics can trigger an accelerated onset of the neural mechanisms, supporting the integration of semantic information with the event input. This faster onset would result in a long-lasting and meaningful memory trace for the event but, at the same time, make it difficult to distinguish it from plausible but never encoded events (i.e., related false memories). Conceptual or schema congruence has a strong influence on long-term memory. However, the question of whether schema-related integration neural mechanisms occur during online encoding has yet to be clarified. We investigated the neural mechanisms reflecting how the active
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Forecasting SPEI and SPI Drought Indices Using the Integrated Artificial Neural Networks
Directory of Open Access Journals (Sweden)
Petr Maca
2016-01-01
Full Text Available The presented paper compares forecast of drought indices based on two different models of artificial neural networks. The first model is based on feedforward multilayer perceptron, sANN, and the second one is the integrated neural network model, hANN. The analyzed drought indices are the standardized precipitation index (SPI and the standardized precipitation evaporation index (SPEI and were derived for the period of 1948–2002 on two US catchments. The meteorological and hydrological data were obtained from MOPEX experiment. The training of both neural network models was made by the adaptive version of differential evolution, JADE. The comparison of models was based on six model performance measures. The results of drought indices forecast, explained by the values of four model performance indices, show that the integrated neural network model was superior to the feedforward multilayer perceptron with one hidden layer of neurons.
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Dinning, Phil G; Wiklendt, Lukasz; Omari, Taher; Arkwright, John W; Spencer, Nick J; Brookes, Simon J H; Costa, Marcello
2014-01-01
Propulsive contractions of circular muscle are largely responsible for the movements of content along the digestive tract. Mechanical and electrophysiological recordings of isolated colonic circular muscle have demonstrated that localized distension activates ascending and descending interneuronal pathways, evoking contraction orally and relaxation anally. These polarized enteric reflex pathways can theoretically be sequentially activated by the mechanical stimulation of the advancing contents. Here, we test the hypothesis that initiation and propagation of peristaltic contractions involves a neuromechanical loop; that is an initial gut distension activates local and oral reflex contraction and anal reflex relaxation, the subsequent movement of content then acts as new mechanical stimulus triggering sequentially reflex contractions/relaxations at each point of the gut resulting in a propulsive peristaltic contraction. In fluid filled isolated rabbit distal colon, we combined spatiotemporal mapping of gut diameter and intraluminal pressure with a new analytical method, allowing us to identify when and where active (neurally-driven) contraction or relaxation occurs. Our data indicate that gut dilation is associated with propagating peristaltic contractions, and that the associated level of dilation is greater than that preceding non-propagating contractions (2.7 ± 1.4 mm vs. 1.6 ± 1.2 mm; P polarized enteric circuits. These produce propulsion of the bolus which activates further anally, polarized enteric circuits by distension, thus closing the neuromechanical loop.
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Energy Technology Data Exchange (ETDEWEB)
Mylvaganam, K [Centre for Advanced Materials Technology, University of Sydney, NSW 2006 (Australia); Zhang, L C [School of Mechanical and Manufacturing Engineering, University of New South Wales, NSW 2052 (Australia); Eyben, P; Vandervorst, W [IMEC, Kapeldreef 75, B-3001 Leuven (Belgium); Mody, J, E-mail: k.mylvaganam@usyd.edu.a, E-mail: Liangchi.zhang@unsw.edu.a, E-mail: eyben@imec.b, E-mail: jamody@imec.b, E-mail: vdvorst@imec.b [KU Leuven, Electrical Engineering Department, INSYS, Kasteelpark Arenberg 10, B-3001 Leuven (Belgium)
2009-07-29
This paper explores the evolution mechanisms of metastable phases during the nanoindentation on monocrystalline silicon. Both the molecular dynamics (MD) and the in situ scanning spreading resistance microscopy (SSRM) analyses were carried out on Si(100) orientation, and for the first time, experimental verification was achieved quantitatively at the same nanoscopic scale. It was found that under equivalent indentation loads, the MD prediction agrees extremely well with the result experimentally measured using SSRM, in terms of the depth of the residual indentation marks and the onset, evolution and dimension variation of the metastable phases, such as {beta}-Sn. A new six-coordinated silicon phase, Si-XIII, transformed directly from Si-I was discovered. The investigation showed that there is a critical size of contact between the indenter and silicon, beyond which a crystal particle of distorted diamond structure will emerge in between the indenter and the amorphous phase upon unloading.
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Directory of Open Access Journals (Sweden)
Ji-Hua Zhu
2016-11-01
Full Text Available Carbon fiber-reinforced polymer (CFRP is recognized as a promising anode material to prevent steel corrosion in reinforced concrete. However, the electrochemical performance of CFRP itself is unclear. This paper focuses on the understanding of electrochemical and mechanical properties of CFRP in an oxygen evolution environment by conducting accelerated polarization tests. Different amounts of current density were applied in polarization tests with various test durations, and feeding voltage and potential were measured. Afterwards, tensile tests were carried out to investigate the failure modes for the post-polarization CFRP specimens. Results show that CFRP specimens had two typical tensile-failure modes and had a stable anodic performance in an oxygen evolution environment. As such, CFRP can be potentially used as an anode material for impressed current cathodic protection (ICCP of reinforced concrete structures, besides the fact that CFRP can strengthen the structural properties of reinforced concrete.
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Psychological and neural mechanisms of experimental extinction: a selective review.
Delamater, Andrew R; Westbrook, R Frederick
2014-02-01
The present review examines key psychological concepts in the study of experimental extinction and implications these have for an understanding of the underlying neurobiology of extinction learning. We suggest that many of the signature characteristics of extinction learning (spontaneous recovery, renewal, reinstatement, rapid reacquisition) can be accommodated by the standard associative learning theory assumption that extinction results in partial erasure of the original learning together with new inhibitory learning. Moreover, we consider recent behavioral and neural evidence that supports the partial erasure view of extinction, but also note shortcomings in our understanding of extinction circuits as these relate to the negative prediction error concept. Recent work suggests that common prediction error and stimulus-specific prediction error terms both may be required to explain neural plasticity both in acquisition and extinction learning. In addition, we suggest that many issues in the content of extinction learning have not been fully addressed in current research, but that neurobiological approaches should be especially helpful in addressing such issues. These include questions about the nature of extinction learning (excitatory CS-No US, inhibitory CS-US learning, occasion setting processes), especially as this relates to studies of the micro-circuitry of extinction, as well as its representational content (sensory, motivational, response). An additional understudied problem in extinction research is the role played by attention processes and their underlying neural networks, although some research and theory converge on the idea that extinction is accompanied by attention decrements (i.e., habituation-like processes). Copyright © 2013 Elsevier Inc. All rights reserved.
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Öhlund, C.E.I.C.
2015-01-01
The research presented in this thesis aims to deepen our understanding of the effect of micro-alloying on the microstructure and mechanical property evolution during tempering of martensitic steel for fasteners. The ongoing trend of engine down-sizing has led to the need for stronger and more
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Beabout, Kathryn; McCurry, Megan D; Mehta, Heer; Shah, Akshay A; Pulukuri, Kiran Kumar; Rigol, Stephan; Wang, Yanping; Nicolaou, K C; Shamoo, Yousif
2017-11-10
The continuing rise of multidrug resistant pathogens has made it clear that in the absence of new antibiotics we are moving toward a "postantibiotic" world, in which even routine infections will become increasingly untreatable. There is a clear need for the development of new antibiotics with truly novel mechanisms of action to combat multidrug resistant pathogens. Experimental evolution to resistance can be a useful tactic for the characterization of the biochemical mechanism of action for antibiotics of interest. Herein, we demonstrate that the use of a diverse panel of strains with well-annotated reference genomes improves the success of using experimental evolution to characterize the mechanism of action of a novel pyrrolizidinone antibiotic analog. Importantly, we used experimental evolution under conditions that favor strongly polymorphic populations to adapt a panel of three substantially different Gram-positive species (lab strain Bacillus subtilis and clinical strains methicillin-resistant Staphylococcus aureus MRSA131 and Enterococcus faecalis S613) to produce a sufficiently diverse set of evolutionary outcomes. Comparative whole genome sequencing (WGS) between the susceptible starting strain and the resistant strains was then used to identify the genetic changes within each species in response to the pyrrolizidinone. Taken together, the adaptive response across a range of organisms allowed us to develop a readily testable hypothesis for the mechanism of action of the CJ-16 264 analog. In conjunction with mitochondrial inhibition studies, we were able to elucidate that this novel pyrrolizidinone antibiotic is an electron transport chain (ETC) inhibitor. By studying evolution to resistance in a panel of different species of bacteria, we have developed an enhanced method for the characterization of new lead compounds for the discovery of new mechanisms of action.
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Conserved gene regulatory module specifies lateral neural borders across bilaterians.
Li, Yongbin; Zhao, Di; Horie, Takeo; Chen, Geng; Bao, Hongcun; Chen, Siyu; Liu, Weihong; Horie, Ryoko; Liang, Tao; Dong, Biyu; Feng, Qianqian; Tao, Qinghua; Liu, Xiao
2017-08-01
The lateral neural plate border (NPB), the neural part of the vertebrate neural border, is composed of central nervous system (CNS) progenitors and peripheral nervous system (PNS) progenitors. In invertebrates, PNS progenitors are also juxtaposed to the lateral boundary of the CNS. Whether there are conserved molecular mechanisms determining vertebrate and invertebrate lateral neural borders remains unclear. Using single-cell-resolution gene-expression profiling and genetic analysis, we present evidence that orthologs of the NPB specification module specify the invertebrate lateral neural border, which is composed of CNS and PNS progenitors. First, like in vertebrates, the conserved neuroectoderm lateral border specifier Msx/vab-15 specifies lateral neuroblasts in Caenorhabditis elegans Second, orthologs of the vertebrate NPB specification module ( Msx/vab-15 , Pax3/7/pax-3 , and Zic/ref-2 ) are significantly enriched in worm lateral neuroblasts. In addition, like in other bilaterians, the expression domain of Msx/vab-15 is more lateral than those of Pax3/7/pax-3 and Zic/ref- 2 in C. elegans Third, we show that Msx/vab-15 regulates the development of mechanosensory neurons derived from lateral neural progenitors in multiple invertebrate species, including C. elegans , Drosophila melanogaster , and Ciona intestinalis We also identify a novel lateral neural border specifier, ZNF703/tlp-1 , which functions synergistically with Msx/vab- 15 in both C. elegans and Xenopus laevis These data suggest a common origin of the molecular mechanism specifying lateral neural borders across bilaterians.
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Synaptic E-I Balance Underlies Efficient Neural Coding.
Zhou, Shanglin; Yu, Yuguo
2018-01-01
Both theoretical and experimental evidence indicate that synaptic excitation and inhibition in the cerebral cortex are well-balanced during the resting state and sensory processing. Here, we briefly summarize the evidence for how neural circuits are adjusted to achieve this balance. Then, we discuss how such excitatory and inhibitory balance shapes stimulus representation and information propagation, two basic functions of neural coding. We also point out the benefit of adopting such a balance during neural coding. We conclude that excitatory and inhibitory balance may be a fundamental mechanism underlying efficient coding.
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Phase evolution and thermal stability of 2 Mg–Cu alloys processed by mechanical alloying
Energy Technology Data Exchange (ETDEWEB)
Martínez, C., E-mail: carola.martinezu@usach.cl [Departamento de Ingeniería Metalúrgica, Facultad de Ingeniería, Universidad de Santiago de Chile, Av. Lib. Bernardo O’Higgins 3363, Casilla de correo 10233, Santiago (Chile); Ordoñez, S., E-mail: stella.ordonez@usach.cl [Departamento de Ingeniería Metalúrgica, Facultad de Ingeniería, Universidad de Santiago de Chile, Av. Lib. Bernardo O’Higgins 3363, Casilla de correo 10233, Santiago (Chile); Guzmán, D. [Departamento de Ingeniería en Metalurgia, Facultad de Ingeniería, Universidad de Atacama y CRIDESAT, Av. Copayapu 485, Casilla de Correo 240, Copiapó (Chile); Serafini, D. [Departamento de Física, Facultad de Ciencia, Universidad de Santiago de Chile, Av. Lib. Bernardo O’Higgins 3363, Casilla de correo 307, Santiago (Chile); Iturriza, I. [CEIT, Manuel de Lardizábal 15, 20018 San Sebastián, España (Spain); Bustos, O. [Departamento de Ingeniería Metalúrgica, Facultad de Ingeniería, Universidad de Santiago de Chile, Av. Lib. Bernardo O’Higgins 3363, Casilla de correo 10233, Santiago (Chile)
2013-12-25
Highlights: •Study of phase evolution of elemental powders Mg and Cu by mechanical alloying. •The presence of an amorphous precursor which crystallizes to Mg{sub 2}Cu can be observed. •Establishing the sequence of phase transformations leading to the formation of Mg{sub 2}Cu. •The feasibility to obtain Mg{sub 2}Cu by means two possible routes has been established. -- Abstract: Phase evolution during mechanical alloying (MA) of elemental Mg and Cu powders and their subsequent heat treatment is studied. Elemental Mg and Cu powders in a 2:1 atomic ratio were mechanically alloyed in a SPEX 8000D mill using a 10:1 ball-to-powder ratio. X-ray diffraction (XRD) shows that the formation of the intermetallic Mg{sub 2}Cu takes place between 3 and 4 h of milling, although traces of elemental Cu are still present after 10 h of milling. The thermal behavior of different powder mixtures was evaluated by differential scanning calorimetry (DSC). The combination of DSC, heat treatment and XRD has shown a sequence of phase transformations that results in the intermetallic Mg{sub 2}Cu from an amorphous precursor. This amorphous phase is converted into Mg{sub 2}Cu by heating at low temperature (407 K). Short MA times and the formation of the amorphous precursor, together with its subsequent transformation into Mg{sub 2}Cu at low temperatures; represent an advantageous alternative route for its preparation.
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Neural network-based model reference adaptive control system.
Patino, H D; Liu, D
2000-01-01
In this paper, an approach to model reference adaptive control based on neural networks is proposed and analyzed for a class of first-order continuous-time nonlinear dynamical systems. The controller structure can employ either a radial basis function network or a feedforward neural network to compensate adaptively the nonlinearities in the plant. A stable controller-parameter adjustment mechanism, which is determined using the Lyapunov theory, is constructed using a sigma-modification-type updating law. The evaluation of control error in terms of the neural network learning error is performed. That is, the control error converges asymptotically to a neighborhood of zero, whose size is evaluated and depends on the approximation error of the neural network. In the design and analysis of neural network-based control systems, it is important to take into account the neural network learning error and its influence on the control error of the plant. Simulation results showing the feasibility and performance of the proposed approach are given.
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Using music to study the evolution of cognitive mechanisms relevant to language.
Patel, Aniruddh D
2017-02-01
This article argues that music can be used in cross-species research to study the evolution of cognitive mechanisms relevant to spoken language. This is because music and language share certain cognitive processing mechanisms and because music offers specific advantages for cross-species research. Music has relatively simple building blocks (tones without semantic properties), yet these building blocks are combined into rich hierarchical structures that engage complex cognitive processing. I illustrate this point with regard to the processing of musical harmonic structure. Because the processing of musical harmonic structure has been shown to interact with linguistic syntactic processing in humans, it is of interest to know if other species can acquire implicit knowledge of harmonic structure through extended exposure to music during development (vs. through explicit training). I suggest that domestic dogs would be a good species to study in addressing this question.
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Cognitive-affective neural plasticity following active-controlled mindfulness intervention
DEFF Research Database (Denmark)
Allen, Micah Galen
Mindfulness meditation is a set of attention-based, regulatory and self-inquiry training regimes. Although the impact of mindfulness meditation training (MT) on self-regulation is well established, the neural mechanisms supporting such plasticity are poorly understood. MT is thought to act through...... prefrontal cortex (mPFC), and right anterior insula during negative valence processing. Our findings highlight the importance of active control in MT research, indicate unique neural mechanisms for progressive stages of mindfulness training, and suggest that optimal application of MT may differ depending...
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Neuromuscular mechanisms and neural strategies in the control of time-varying muscle contractions.
Erimaki, Sophia; Agapaki, Orsalia M; Christakos, Constantinos N
2013-09-01
The organization of the neural input to motoneurons that underlies time-varying muscle force is assumed to depend on muscle transfer characteristics and neural strategies or control modes utilizing sensory signals. We jointly addressed these interlinked, but previously studied individually and partially, issues for sinusoidal (range 0.5-5.0 Hz) force-tracking contractions of a human finger muscle. Using spectral and correlation analyses of target signal, force signal, and motor unit (MU) discharges, we studied 1) patterns of such discharges, allowing inferences on the motoneuronal input; 2) transformation of MU population activity (EMG) into quasi-sinusoidal force; and 3) relation of force oscillation to target, carrying information on the input's organization. A broad view of force control mechanisms and strategies emerged. Specifically, synchronized MU and EMG modulations, reflecting a frequency-modulated motoneuronal input, accompanied the force variations. Gain and delay drops between EMG modulation and force oscillation, critical for the appropriate organization of this input, occurred with increasing target frequency. According to our analyses, gain compensation was achieved primarily through rhythmical activation/deactivation of higher-threshold MUs and secondarily through the adaptation of the input's strength expected during tracking tasks. However, the input's timing was not adapted to delay behaviors and seemed to depend on the control modes employed. Thus, for low-frequency targets, the force oscillation was highly coherent with, but led, a target, this timing error being compatible with predictive feedforward control partly based on the target's derivatives. In contrast, the force oscillation was weakly coherent, but in phase, with high-frequency targets, suggesting control mainly based on a target's rhythm.
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Learning in neural networks based on a generalized fluctuation theorem
Hayakawa, Takashi; Aoyagi, Toshio
2015-11-01
Information maximization has been investigated as a possible mechanism of learning governing the self-organization that occurs within the neural systems of animals. Within the general context of models of neural systems bidirectionally interacting with environments, however, the role of information maximization remains to be elucidated. For bidirectionally interacting physical systems, universal laws describing the fluctuation they exhibit and the information they possess have recently been discovered. These laws are termed fluctuation theorems. In the present study, we formulate a theory of learning in neural networks bidirectionally interacting with environments based on the principle of information maximization. Our formulation begins with the introduction of a generalized fluctuation theorem, employing an interpretation appropriate for the present application, which differs from the original thermodynamic interpretation. We analytically and numerically demonstrate that the learning mechanism presented in our theory allows neural networks to efficiently explore their environments and optimally encode information about them.
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On the identification of instabilities with neural networks on JET
International Nuclear Information System (INIS)
Murari, A.; Arena, P.; Buscarino, A.; Fortuna, L.; Iachello, M.
2013-01-01
JET plasmas are affected by various instabilities, which can be particularly dangerous in high performance discharges. An identification method, based on the use of advanced neural networks, called Recurrent Neural Networks (RNNs), has been applied to ELMs. The potential of the recurrent networks to identify the dynamics of the instabilities has been first tested using synthetic data. The networks have then been applied to JET experimental signals. An appropriate selection of the networks topology allows identifying quite well the time evolution of the edge temperature and of the magnetic fields, considered the best indicators of the ELMs. A quite limited number of periodic oscillations are used to train the networks, which then manage to follow quite well the dynamics of the instabilities, in a recurrent configuration on one of the inputs. The time evolution of the aforementioned signals, also during intervals not used in the training and never seen by the networks, are properly reproduced. A careful analysis of the various terms in the RNNs has the potential to give clear indications about the nature of these instabilities and their dynamical behaviour
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Nonlinear dynamics analysis of a self-organizing recurrent neural network: chaos waning.
Eser, Jürgen; Zheng, Pengsheng; Triesch, Jochen
2014-01-01
Self-organization is thought to play an important role in structuring nervous systems. It frequently arises as a consequence of plasticity mechanisms in neural networks: connectivity determines network dynamics which in turn feed back on network structure through various forms of plasticity. Recently, self-organizing recurrent neural network models (SORNs) have been shown to learn non-trivial structure in their inputs and to reproduce the experimentally observed statistics and fluctuations of synaptic connection strengths in cortex and hippocampus. However, the dynamics in these networks and how they change with network evolution are still poorly understood. Here we investigate the degree of chaos in SORNs by studying how the networks' self-organization changes their response to small perturbations. We study the effect of perturbations to the excitatory-to-excitatory weight matrix on connection strengths and on unit activities. We find that the network dynamics, characterized by an estimate of the maximum Lyapunov exponent, becomes less chaotic during its self-organization, developing into a regime where only few perturbations become amplified. We also find that due to the mixing of discrete and (quasi-)continuous variables in SORNs, small perturbations to the synaptic weights may become amplified only after a substantial delay, a phenomenon we propose to call deferred chaos.
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Staying cool when things get hot: Emotion regulation modulates neural mechanisms of memory encoding
Directory of Open Access Journals (Sweden)
Jasmeet P Hayes
2010-12-01
Full Text Available During times of emotional stress, individuals often engage in emotion regulation to reduce the experiential and physiological impact of negative emotions. Interestingly, emotion regulation strategies also influence memory encoding of the event. Cognitive reappraisal is associated with enhanced memory while expressive suppression is associated with impaired explicit memory of the emotional event. However, the mechanism by which these emotion regulation strategies affect memory is unclear. We used event-related fMRI to investigate the neural mechanisms that give rise to memory formation during emotion regulation. Twenty-five participants viewed negative pictures while alternately engaging in cognitive reappraisal, expressive suppression, or passive viewing. As part of the subsequent memory design, participants returned to the laboratory two weeks later for a surprise memory test. Behavioral results showed a reduction in negative affect and a retention advantage for reappraised stimuli relative to the other conditions. Imaging results showed that successful encoding during reappraisal was uniquely associated with greater co-activation of the left inferior frontal gyrus, amygdala and hippocampus, suggesting a possible role for elaborative encoding of negative memories. This study provides neurobehavioral evidence that engaging in cognitive reappraisal is advantageous to both affective and mnemonic processes.
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Baertsch, Nathan A; Baker-Herman, Tracy L
2015-04-15
In many neural networks, mechanisms of compensatory plasticity respond to prolonged reductions in neural activity by increasing cellular excitability or synaptic strength. In the respiratory control system, a prolonged reduction in synaptic inputs to the phrenic motor pool elicits a TNF-α- and atypical PKC-dependent form of spinal plasticity known as inactivity-induced phrenic motor facilitation (iPMF). Although iPMF may be elicited by a prolonged reduction in respiratory neural activity, iPMF is more efficiently induced when reduced respiratory neural activity (neural apnea) occurs intermittently. Mechanisms giving rise to iPMF following intermittent neural apnea are unknown. The purpose of this study was to test the hypothesis that iPMF following intermittent reductions in respiratory neural activity requires spinal TNF-α and aPKC. Phrenic motor output was recorded in anesthetized and ventilated rats exposed to brief intermittent (5, ∼1.25 min), brief sustained (∼6.25 min), or prolonged sustained (30 min) neural apnea. iPMF was elicited following brief intermittent and prolonged sustained neural apnea, but not following brief sustained neural apnea. Unlike iPMF following prolonged neural apnea, spinal TNF-α was not required to initiate iPMF during intermittent neural apnea; however, aPKC was still required for its stabilization. These results suggest that different patterns of respiratory neural activity induce iPMF through distinct cellular mechanisms but ultimately converge on a similar downstream pathway. Understanding the diverse cellular mechanisms that give rise to inactivity-induced respiratory plasticity may lead to development of novel therapeutic strategies to treat devastating respiratory control disorders when endogenous compensatory mechanisms fail. Copyright © 2015 the American Physiological Society.
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The evolution mechanism of the dislocation loops in irradiated lanthanum doped cerium oxide
International Nuclear Information System (INIS)
Miao, Yinbin; Aidhy, Dilpuneet; Chen, Wei-Ying; Mo, Kun; Oaks, Aaron; Wolf, Dieter; Stubbins, James F.
2014-01-01
Cerium dioxide, a non-radioactive surrogate of uranium dioxide, is useful for simulating the radiation responses of uranium dioxide and mixed oxide fuel (MOX). Controlled additions of lanthanum can also be used to form various levels of lattice oxide or anion vacancies. In previous transmission electron microscopy (TEM) experimental studies, the growth rate of dislocation loops in irradiated lanthanum doped ceria was reported to vary with lanthanum concentration. This work reports findings of the evolution mechanisms of the dislocation loops in cerium oxide with and without lanthanum dopants based on a combination of molecular statics and molecular dynamics simulations. These dislocation loops are found to be b=1/3〈111〉 interstitial type Frank loops. Calculations of the defect energy profiles of the dislocation loops with different structural configurations and radii reveal the basis for preference of nucleation as well as the driving force of growth. Frenkel pair evolution simulations and displacement cascade overlaps simulations were conducted for a variety of lanthanum doping conditions. The nucleation and growth processes of the Frank loop were found to be controlled by the mobility of cation interstitials, which is significantly influenced by the lanthanum doping concentration. Competition mechanisms coupled with the mobility of cation point defects were discovered, and can be used to explain the lanthanum effects observed in experiments
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Esteves, Francisco F; Springhorn, Alexander; Kague, Erika; Taylor, Erika; Pyrowolakis, George; Fisher, Shannon; Bier, Ethan
2014-09-01
In a broad variety of bilaterian species the trunk central nervous system (CNS) derives from three primary rows of neuroblasts. The fates of these neural progenitor cells are determined in part by three conserved transcription factors: vnd/nkx2.2, ind/gsh and msh/msx in Drosophila melanogaster/vertebrates, which are expressed in corresponding non-overlapping patterns along the dorsal-ventral axis. While this conserved suite of "neural identity" gene expression strongly suggests a common ancestral origin for the patterning systems, it is unclear whether the original regulatory mechanisms establishing these patterns have been similarly conserved during evolution. In Drosophila, genetic evidence suggests that Bone Morphogenetic Proteins (BMPs) act in a dosage-dependent fashion to repress expression of neural identity genes. BMPs also play a dose-dependent role in patterning the dorsal and lateral regions of the vertebrate CNS, however, the mechanism by which they achieve such patterning has not yet been clearly established. In this report, we examine the mechanisms by which BMPs act on cis-regulatory modules (CRMs) that control localized expression of the Drosophila msh and zebrafish (Danio rerio) msxB in the dorsal central nervous system (CNS). Our analysis suggests that BMPs act differently in these organisms to regulate similar patterns of gene expression in the neuroectoderm: repressing msh expression in Drosophila, while activating msxB expression in the zebrafish. These findings suggest that the mechanisms by which the BMP gradient patterns the dorsal neuroectoderm have reversed since the divergence of these two ancient lineages.
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Directory of Open Access Journals (Sweden)
Francisco F Esteves
2014-09-01
Full Text Available In a broad variety of bilaterian species the trunk central nervous system (CNS derives from three primary rows of neuroblasts. The fates of these neural progenitor cells are determined in part by three conserved transcription factors: vnd/nkx2.2, ind/gsh and msh/msx in Drosophila melanogaster/vertebrates, which are expressed in corresponding non-overlapping patterns along the dorsal-ventral axis. While this conserved suite of "neural identity" gene expression strongly suggests a common ancestral origin for the patterning systems, it is unclear whether the original regulatory mechanisms establishing these patterns have been similarly conserved during evolution. In Drosophila, genetic evidence suggests that Bone Morphogenetic Proteins (BMPs act in a dosage-dependent fashion to repress expression of neural identity genes. BMPs also play a dose-dependent role in patterning the dorsal and lateral regions of the vertebrate CNS, however, the mechanism by which they achieve such patterning has not yet been clearly established. In this report, we examine the mechanisms by which BMPs act on cis-regulatory modules (CRMs that control localized expression of the Drosophila msh and zebrafish (Danio rerio msxB in the dorsal central nervous system (CNS. Our analysis suggests that BMPs act differently in these organisms to regulate similar patterns of gene expression in the neuroectoderm: repressing msh expression in Drosophila, while activating msxB expression in the zebrafish. These findings suggest that the mechanisms by which the BMP gradient patterns the dorsal neuroectoderm have reversed since the divergence of these two ancient lineages.
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Neural mechanisms of song memory formation in juvenile zebra finches
Moorman, S.
2015-01-01
There are many parallels between the acquisition of spoken language in human infants and song learning in songbirds, at the behavioural, neural, genetic and cognitive levels. Both human infants and juvenile songbirds are able to imitate sounds from adults of the same species (often their parents),
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Oscillatory phase dynamics in neural entrainment underpin illusory percepts of time.
Herrmann, Björn; Henry, Molly J; Grigutsch, Maren; Obleser, Jonas
2013-10-02
Neural oscillatory dynamics are a candidate mechanism to steer perception of time and temporal rate change. While oscillator models of time perception are strongly supported by behavioral evidence, a direct link to neural oscillations and oscillatory entrainment has not yet been provided. In addition, it has thus far remained unaddressed how context-induced illusory percepts of time are coded for in oscillator models of time perception. To investigate these questions, we used magnetoencephalography and examined the neural oscillatory dynamics that underpin pitch-induced illusory percepts of temporal rate change. Human participants listened to frequency-modulated sounds that varied over time in both modulation rate and pitch, and judged the direction of rate change (decrease vs increase). Our results demonstrate distinct neural mechanisms of rate perception: Modulation rate changes directly affected listeners' rate percept as well as the exact frequency of the neural oscillation. However, pitch-induced illusory rate changes were unrelated to the exact frequency of the neural responses. The rate change illusion was instead linked to changes in neural phase patterns, which allowed for single-trial decoding of percepts. That is, illusory underestimations or overestimations of perceived rate change were tightly coupled to increased intertrial phase coherence and changes in cerebro-acoustic phase lag. The results provide insight on how illusory percepts of time are coded for by neural oscillatory dynamics.
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Directory of Open Access Journals (Sweden)
Laszlo Patthy
2011-08-01
Full Text Available In the accompanying papers we have shown that sequence errors of public databases and confusion of paralogs and epaktologs (proteins that are related only through the independent acquisition of the same domain types significantly distort the picture that emerges from comparison of the domain architecture (DA of multidomain Metazoan proteins since they introduce a strong bias in favor of terminal over internal DA change. The issue of whether terminal or internal DA changes occur with greater probability has very important implications for the DA evolution of multidomain proteins since gene fusion can add domains only at terminal positions, whereas domain-shuffling is capable of inserting domains both at internal and terminal positions. As a corollary, overestimation of terminal DA changes may be misinterpreted as evidence for a dominant role of gene fusion in DA evolution. In this manuscript we show that in several recent studies of DA evolution of Metazoa the authors used databases that are significantly contaminated with incomplete, abnormal and mispredicted sequences (e.g., UniProtKB/TrEMBL, EnsEMBL and/or the authors failed to separate paralogs and epaktologs, explaining why these studies concluded that the major mechanism for gains of new domains in metazoan proteins is gene fusion. In contrast with the latter conclusion, our studies on high quality orthologous and paralogous Swiss-Prot sequences confirm that shuffling of mobile domains had a major role in the evolution of multidomain proteins of Metazoa and especially those formed in early vertebrates.
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Romantic love: an fMRI study of a neural mechanism for mate choice.
Fisher, Helen; Aron, Arthur; Brown, Lucy L
2005-12-05
Scientists have described myriad traits in mammalian and avian species that evolved to attract mates. But the brain mechanisms by which conspecifics become attracted to these traits is largely unknown. Yet mammals and birds express mate preferences and make mate choices, and data suggest that this "attraction system" is associated with the dopaminergic reward system. It has been proposed that intense romantic love, a cross-cultural universal, is a developed form of this attraction system. To determine the neural mechanisms associated with romantic love we used functional magnetic resonance imaging (fMRI) and studied 17 people who were intensely "in love" (Aron et al. [2005] J Neurophysiol 94:327-337). Activation specific to the beloved occurred in the right ventral tegmental area and right caudate nucleus, dopamine-rich areas associated with mammalian reward and motivation. These and other results suggest that dopaminergic reward pathways contribute to the "general arousal" component of romantic love; romantic love is primarily a motivation system, rather than an emotion; this drive is distinct from the sex drive; romantic love changes across time; and romantic love shares biobehavioral similarities with mammalian attraction. We propose that this attraction mechanism evolved to enable individuals to focus their mating energy on specific others, thereby conserving energy and facilitating mate choice-a primary aspect of reproduction. Last, the corticostriate system, with its potential for combining diverse cortical information with reward signals, is an excellent anatomical substrate for the complex factors contributing to romantic love and mate choice. (c) 2005 Wiley-Liss, Inc.
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Chronic Pain and Mental Health Disorders: Shared Neural Mechanisms, Epidemiology, and Treatment.
Hooten, W Michael
2016-07-01
Chronic pain and mental health disorders are common in the general population, and epidemiological studies suggest that a bidirectional relationship exists between these 2 conditions. The observations from functional imaging studies suggest that this bidirectional relationship is due in part to shared neural mechanisms. In addition to depression, anxiety, and substance use disorders, individuals with chronic pain are at risk of other mental health problems including suicide and cigarette smoking and many have sustained sexual violence. Within the broader biopsychosocial model of pain, the fear-avoidance model explains how behavioral factors affect the temporal course of chronic pain and provides the framework for an array of efficacious behavioral interventions including cognitive-behavioral therapy, acceptance-based therapies, and multidisciplinary pain rehabilitation. Concomitant pain and mental health disorders often complicate pharmacological management, but several drug classes, including serotonin-norepinephrine reuptake inhibitors, tricyclic antidepressants, and anticonvulsants, have efficacy for both conditions and should be considered first-line treatment agents. Copyright © 2016 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.
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Neural correlates of HIV risk feelings.
Häcker, Frank E K; Schmälzle, Ralf; Renner, Britta; Schupp, Harald T
2015-04-01
Field studies on HIV risk perception suggest that people rely on impressions they have about the safety of their partner. The present fMRI study investigated the neural correlates of the intuitive perception of risk. First, during an implicit condition, participants viewed a series of unacquainted persons and performed a task unrelated to HIV risk. In the following explicit condition, participants evaluated the HIV risk for each presented person. Contrasting responses for high and low HIV risk revealed that risky stimuli evoked enhanced activity in the anterior insula and medial prefrontal regions, which are involved in salience processing and frequently activated by threatening and negative affect-related stimuli. Importantly, neural regions responding to explicit HIV risk judgments were also enhanced in the implicit condition, suggesting a neural mechanism for intuitive impressions of riskiness. Overall, these findings suggest the saliency network as neural correlate for the intuitive sensing of risk. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
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On the Same Wavelength: Face-to-Face Communication Increases Interpersonal Neural Synchronization
Yun, Kyongsik
2013-01-01
Understanding neural mechanisms of social interaction is important for understanding human social nature and for developing treatments for social deficits related to disorders such as autism. However, conventional cognitive and behavioral neuroscience has concentrated on developing novel experimental paradigms and investigating human–computer interactions, rather than studying interpersonal interaction per se. To fully understand neural mechanisms of human interpersonal interaction, we will l...
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Echoes in correlated neural systems
International Nuclear Information System (INIS)
Helias, M; Tetzlaff, T; Diesmann, M
2013-01-01
Correlations are employed in modern physics to explain microscopic and macroscopic phenomena, like the fractional quantum Hall effect and the Mott insulator state in high temperature superconductors and ultracold atoms. Simultaneously probed neurons in the intact brain reveal correlations between their activity, an important measure to study information processing in the brain that also influences the macroscopic signals of neural activity, like the electroencephalogram (EEG). Networks of spiking neurons differ from most physical systems: the interaction between elements is directed, time delayed, mediated by short pulses and each neuron receives events from thousands of neurons. Even the stationary state of the network cannot be described by equilibrium statistical mechanics. Here we develop a quantitative theory of pairwise correlations in finite-sized random networks of spiking neurons. We derive explicit analytic expressions for the population-averaged cross correlation functions. Our theory explains why the intuitive mean field description fails, how the echo of single action potentials causes an apparent lag of inhibition with respect to excitation and how the size of the network can be scaled while maintaining its dynamical state. Finally, we derive a new criterion for the emergence of collective oscillations from the spectrum of the time-evolution propagator. (paper)
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A neural model of mechanisms of empathy deficits in narcissism
Jankowiak-Siuda, Kamila; Zajkowski, Wojciech
2013-01-01
From a multidimensional perspective, empathy is a process that includes affective sharing and imagining and understanding the emotions of others. The primary brain structures involved in mediating the components of empathy are the anterior insula (AI), the anterior cingulate cortex (ACC), and specific regions of the medial prefrontal cortex (MPFC). The AI and ACC are the main nodes in the salience network (SN), which selects and coordinates the information flow from the intero- and exteroreceptors. AI might play a role as a crucial hub – a dynamic switch between 2 separate networks of cognitive processing: the central executive network (CEN), which is concerned with effective task execution, and the default mode network (DMN), which is involved with self-reflective processes. Given various classifications, a deficit in empathy may be considered a central dysfunctional trait in narcissism. A recent fMRI study suggests that deficit in empathy is due to a dysfunction in the right AI. Based on the acquired data, we propose a theoretical model of imbalanced SN functioning in narcissism in which the dysfunctional AI hub is responsible for constant DMN activation, which, in turn, centers one’s attention on the self. This might hinder the ability to affectively share and understand the emotions of others. This review paper on neural mechanisms of empathy deficits in narcissism aims to inspire and direct future research in this area. PMID:24189465
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Horizons and non-local time evolution of quantum mechanical systems
International Nuclear Information System (INIS)
Casadio, Roberto
2015-01-01
According to general relativity, trapping surfaces and horizons are classical causal structures that arise in systems with sharply defined energy and corresponding gravitational radius. The latter concept can be extended to a quantum mechanical matter state simply by means of the spectral decomposition, which allows one to define an associated ''horizon wave-function''. Since this auxiliary wave-function contains crucial information about the causal structure of space-time, a new proposal is formulated for the time evolution of quantum systems in order to account for the fundamental classical property that outer observers cannot receive signals from inside a horizon. The simple case of a massive free particle at rest is used throughout the paper as a toy model to illustrate the main ideas. (orig.)
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Optical neural network system for pose determination of spinning satellites
Lee, Andrew; Casasent, David
1990-01-01
An optical neural network architecture and algorithm based on a Hopfield optimization network are presented for multitarget tracking. This tracker utilizes a neuron for every possible target track, and a quadratic energy function of neural activities which is minimized using gradient descent neural evolution. The neural net tracker is demonstrated as part of a system for determining position and orientation (pose) of spinning satellites with respect to a robotic spacecraft. The input to the system is time sequence video from a single camera. Novelty detection and filtering are utilized to locate and segment novel regions from the input images. The neural net multitarget tracker determines the correspondences (or tracks) of the novel regions as a function of time, and hence the paths of object (satellite) parts. The path traced out by a given part or region is approximately elliptical in image space, and the position, shape and orientation of the ellipse are functions of the satellite geometry and its pose. Having a geometric model of the satellite, and the elliptical path of a part in image space, the three-dimensional pose of the satellite is determined. Digital simulation results using this algorithm are presented for various satellite poses and lighting conditions.
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Directory of Open Access Journals (Sweden)
John S. Watson
2005-01-01
Full Text Available A study of the evolution of agency in artificial life was designed to access the potential emergence of purposiveness and intentionality as these attributes of behavior have been defined in psychology and philosophy. The study involved Darwinian evolution of mobile neural nets (autonomous agents in terms of their adaptive weight patterning and structure (number of sensory, hidden, and memory units that controlled movement. An agent was embedded in a 10 × 10 toroidal matrix along with “containers” that held benefit or harm if entered. Sensory exposure to content of a container was only briefly available at a distance so that adaptive response to a nearby container required use of relevant memory. The best 20% of each generation of agents, based on net benefit consumed during limited lifetime, were selected to parent the following generation. Purposiveness emerged for all selected agents by 300 generations. By 4000 generations, 90% passed a test of purposive intentionality based on Piaget's criteria for Stage IV object permanence in human infants. An additional test of these agents confirmed that the behavior of 67% of them was consistent with the philosophical criterion of intention being “about” the container's contents. Given that the evolved neural structure of more than half of the successful agents had only 1 hidden and 1 memory node, it is argued that, contrary to common assumption, purposive and intentional aspects of adaptive behavior require an evolution of minimal complexity of supportive neural structure.
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Egervari, Gabor; Ciccocioppo, Roberto; Jentsch, J David; Hurd, Yasmin L
2018-02-01
Substance use disorders continue to impose increasing medical, financial and emotional burdens on society in the form of morbidity and overdose, family disintegration, loss of employment and crime, while advances in prevention and treatment options remain limited. Importantly, not all individuals exposed to abused substances effectively develop the disease. Genetic factors play a significant role in determining addiction vulnerability and interactions between innate predisposition, environmental factors and personal experiences are also critical. Thus, understanding individual differences that contribute to the initiation of substance use as well as on long-term maladaptations driving compulsive drug use and relapse propensity is of critical importance to reduce this devastating disorder. In this paper, we discuss current topics in the field of addiction regarding individual vulnerability related to behavioral endophenotypes, neural circuits, as well as genetics and epigenetic mechanisms. Expanded knowledge of these factors is of importance to improve and personalize prevention and treatment interventions in the future. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Differential neural network configuration during human path integration
Arnold, Aiden E. G. F; Burles, Ford; Bray, Signe; Levy, Richard M.; Iaria, Giuseppe
2014-01-01
Path integration is a fundamental skill for navigation in both humans and animals. Despite recent advances in unraveling the neural basis of path integration in animal models, relatively little is known about how path integration operates at a neural level in humans. Previous attempts to characterize the neural mechanisms used by humans to visually path integrate have suggested a central role of the hippocampus in allowing accurate performance, broadly resembling results from animal data. However, in recent years both the central role of the hippocampus and the perspective that animals and humans share similar neural mechanisms for path integration has come into question. The present study uses a data driven analysis to investigate the neural systems engaged during visual path integration in humans, allowing for an unbiased estimate of neural activity across the entire brain. Our results suggest that humans employ common task control, attention and spatial working memory systems across a frontoparietal network during path integration. However, individuals differed in how these systems are configured into functional networks. High performing individuals were found to more broadly express spatial working memory systems in prefrontal cortex, while low performing individuals engaged an allocentric memory system based primarily in the medial occipito-temporal region. These findings suggest that visual path integration in humans over short distances can operate through a spatial working memory system engaging primarily the prefrontal cortex and that the differential configuration of memory systems recruited by task control networks may help explain individual biases in spatial learning strategies. PMID:24808849
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Jerger, Kristin K; Lundegard, Laura; Piepmeier, Aaron; Faurot, Keturah; Ruffino, Amanda; Jerger, Margaret A; Belger, Aysenil
2018-01-01
Despite the enormous prevalence of autism spectrum disorder (ASD), its global impact has yet to be realized. Millions of families worldwide need effective treatments to help them get through everyday challenges like eating, sleeping, digestion, and social interaction. Qigong Sensory Training (QST) is a nonverbal, parent-delivered intervention recently shown to be effective at reducing these everyday challenges in children with ASD. This study tested the feasibility of a protocol for investigating QST's neural mechanism. During a single visit, 20 children, 4- to 7-year-old, with ASD viewed images of emotional faces before and after receiving QST or watching a video (controls). Heart rate variability was recorded throughout the visit, and power in the high frequency band (0.15-0.4 Hz) was calculated to estimate parasympathetic tone in 5-s nonoverlapping windows. Cerebral oximetry of prefrontal cortex was recorded during rest and while viewing emotional faces. 95% completion rate and 7.6% missing data met a priori standards confirming protocol feasibility for future studies. Preliminary data suggest: (1) during the intervention, parasympathetic tone increased more in children receiving massage (M = 2.9, SD = 0.3) versus controls (M = 2.5, SD = 0.5); (2) while viewing emotional faces post-intervention, parasympathetic tone was more affected (reduced) in the massage group ( p = 0.036); and (3) prefrontal cortex response to emotional faces was greater after massage compared to controls. These results did not reach statistical significance in this small study powered to test feasibility. This study demonstrates solid protocol feasibility. If replicated in a larger sample, these findings would provide important clues to the neural mechanism of action underlying QST's efficacy for improving sensory, social, and communication difficulties in children with autism.
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Li, Xiaoqing; Zhang, Yuping; Xia, Jinyan; Swaab, Tamara Y
2017-07-28
Although numerous studies have demonstrated that the language processing system can predict upcoming content during comprehension, there is still no clear picture of the anticipatory stage of predictive processing. This electroencephalograph study examined the cognitive and neural oscillatory mechanisms underlying anticipatory processing during language comprehension, and the consequences of this prediction for bottom-up processing of predicted/unpredicted content. Participants read Mandarin Chinese sentences that were either strongly or weakly constraining and that contained critical nouns that were congruent or incongruent with the sentence contexts. We examined the effects of semantic predictability on anticipatory processing prior to the onset of the critical nouns and on integration of the critical nouns. The results revealed that, at the integration stage, the strong-constraint condition (compared to the weak-constraint condition) elicited a reduced N400 and reduced theta activity (4-7Hz) for the congruent nouns, but induced beta (13-18Hz) and theta (4-7Hz) power decreases for the incongruent nouns, indicating benefits of confirmed predictions and potential costs of disconfirmed predictions. More importantly, at the anticipatory stage, the strongly constraining context elicited an enhanced sustained anterior negativity and beta power decrease (19-25Hz), which indicates that strong prediction places a higher processing load on the anticipatory stage of processing. The differences (in the ease of processing and the underlying neural oscillatory activities) between anticipatory and integration stages of lexical processing were discussed with regard to predictive processing models. Copyright © 2017 Elsevier Ltd. All rights reserved.
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DEFF Research Database (Denmark)
Manoonpong, Poramate; Dasgupta, Sakyasingha; Goldschmidt, Dennis
2014-01-01
Walking animals show fascinating locomotor abilities and complex behaviors. Biological study has revealed that such complex behaviors is a result of a combination of biomechanics and neural mechanisms. While biomechanics allows for flexibility and a variety of movements, neural mechanisms generate...... locomotion, make predictions, and provide adaptation. Inspired by this finding, we present here an artificial bio-inspired walking system which combines biomechanics (in terms of its body and leg structures) and neural mechanisms. The neural mechanisms consist of 1) central pattern generator-based control...... for generating basic rhythmic patterns and coordinated movements, 2) reservoir-based adaptive forward models with efference copies for sensory prediction as well as state estimation, and 3) searching and elevation control for adapting the movement of an individual leg to deal with different environmental...
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Neural mechanism for judging the appropriateness of facial affect.
Kim, Ji-Woong; Kim, Jae-Jin; Jeong, Bum Seok; Ki, Seon Wan; Im, Dong-Mi; Lee, Soo Jung; Lee, Hong Shick
2005-12-01
Questions regarding the appropriateness of facial expressions in particular situations arise ubiquitously in everyday social interactions. To determine the appropriateness of facial affect, first of all, we should represent our own or the other's emotional state as induced by the social situation. Then, based on these representations, we should infer the possible affective response of the other person. In this study, we identified the brain mechanism mediating special types of social evaluative judgments of facial affect in which the internal reference is related to theory of mind (ToM) processing. Many previous ToM studies have used non-emotional stimuli, but, because so much valuable social information is conveyed through nonverbal emotional channels, this investigation used emotionally salient visual materials to tap ToM. Fourteen right-handed healthy subjects volunteered for our study. We used functional magnetic resonance imaging to examine brain activation during the judgmental task for the appropriateness of facial affects as opposed to gender matching tasks. We identified activation of a brain network, which includes both medial frontal cortex, left temporal pole, left inferior frontal gyrus, and left thalamus during the judgmental task for appropriateness of facial affect compared to the gender matching task. The results of this study suggest that the brain system involved in ToM plays a key role in judging the appropriateness of facial affect in an emotionally laden situation. In addition, our result supports that common neural substrates are involved in performing diverse kinds of ToM tasks irrespective of perceptual modalities and the emotional salience of test materials.
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Directory of Open Access Journals (Sweden)
Alejandra Gomez-Perez
2016-12-01
Full Text Available Exogenously added lithocholic bile acid and some other bile acids slow down yeast chronological aging by eliciting a hormetic stress response and altering mitochondrial functionality. Unlike animals, yeast cells do not synthesize bile acids. We therefore hypothesized that bile acids released into an ecosystem by animals may act as interspecies chemical signals that generate selective pressure for the evolution of longevity regulation mechanisms in yeast within this ecosystem. To empirically verify our hypothesis, in this study we carried out a 3-step process for the selection of long-lived yeast species by a long-term exposure to exogenous lithocholic bile acid. Such experimental evolution yielded 20 long-lived mutants, 3 of which were capable of sustaining their considerably prolonged chronological lifespans after numerous passages in medium without lithocholic acid. The extended longevity of each of the 3 long-lived yeast species was a dominant polygenic trait caused by mutations in more than two nuclear genes. Each of the 3 mutants displayed considerable alterations to the age-related chronology of mitochondrial respiration and showed enhanced resistance to chronic oxidative, thermal and osmotic stresses. Our findings empirically validate the hypothesis suggesting that hormetic selective forces can drive the evolution of longevity regulation mechanisms within an ecosystem.
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Using Brain Stimulation to Disentangle Neural Correlates of Conscious Vision
Directory of Open Access Journals (Sweden)
Tom Alexander de Graaf
2014-09-01
Full Text Available Research into the neural correlates of consciousness (NCCs has blossomed, due to the advent of new and increasingly sophisticated brain research tools. Neuroimaging has uncovered a variety of brain processes that relate to conscious perception, obtained in a range of experimental paradigms. But methods such as fMRI or EEG do not always afford inference on the role these brain processes play in conscious vision. Such empirical neural correlates of consciousness could reflect neural prerequisites, neural consequences, or neural substrates of a conscious experience. Here, we take a closer look at the use of non-invasive brain stimulation (NIBS techniques in this context. We discuss and review how NIBS methodology can enlighten our understanding of brain mechanisms underlying conscious vision by disentangling the empirical neural correlates of consciousness.
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Evolution of microstructure and mechanical properties during annealing of cold-rolled AA8011 alloy
Energy Technology Data Exchange (ETDEWEB)
Roy, Rajat Kumar [Department of Metallurgical and Materials Engineering, Indian Institute of Technology, Kharagpur 721302 (India)], E-mail: r.roy@rediffmail.com; Kar, Sujoy [Department of Metallurgical and Materials Engineering, Indian Institute of Technology, Kharagpur 721302 (India); Department of Materials Science and Engineering, The Ohio State University, OH 43210 (United States); Das, Siddhartha [Department of Metallurgical and Materials Engineering, Indian Institute of Technology, Kharagpur 721302 (India)], E-mail: sdas@metal.iitkgp.ernet.in
2009-01-22
The evolution of recrystallized microstructure of cold-rolled aluminium alloy AA8011 is investigated with the help of optical metallography, orientation imaging microscopy (OIM), transmission electron microscopy (TEM), differential scanning calorimetry (DSC), electrical resistivity and microhardness measurements at different annealing conditions. Tensile testing of the isochronally annealed specimens is performed to examine the effect of annealing temperature and microstructure on mechanical properties. Precipitates affect the grain growth behaviour and texture evolution. Normal grain growth takes place prior to abnormal grain growth. A wide range of grain size distribution and a combination of cube, rolling and random texture is observed at complete recrystallized condition. Our results provide not only new insight into aluminium packaging materials (i.e., foils, cans, and air conditioning ducts) but also a platform to better understand the recrystallization of a wide range of related alloys.
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Emerson, Nichole M.; Farris, Suzan R.; Ray, Jenna N.; Jung, Youngkyoo; McHaffie, John G.; Coghill, Robert C.
2015-01-01
Mindfulness meditation reduces pain in experimental and clinical settings. However, it remains unknown whether mindfulness meditation engages pain-relieving mechanisms other than those associated with the placebo effect (e.g., conditioning, psychosocial context, beliefs). To determine whether the analgesic mechanisms of mindfulness meditation are different from placebo, we randomly assigned 75 healthy, human volunteers to 4 d of the following: (1) mindfulness meditation, (2) placebo conditioning, (3) sham mindfulness meditation, or (4) book-listening control intervention. We assessed intervention efficacy using psychophysical evaluation of experimental pain and functional neuroimaging. Importantly, all cognitive manipulations (i.e., mindfulness meditation, placebo conditioning, sham mindfulness meditation) significantly attenuated pain intensity and unpleasantness ratings when compared to rest and the control condition (p Mindfulness meditation reduced pain intensity (p = 0.032) and pain unpleasantness (p Mindfulness meditation also reduced pain intensity (p = 0.030) and pain unpleasantness (p = 0.043) ratings more than sham mindfulness meditation. Mindfulness-meditation-related pain relief was associated with greater activation in brain regions associated with the cognitive modulation of pain, including the orbitofrontal, subgenual anterior cingulate, and anterior insular cortex. In contrast, placebo analgesia was associated with activation of the dorsolateral prefrontal cortex and deactivation of sensory processing regions (secondary somatosensory cortex). Sham mindfulness meditation-induced analgesia was not correlated with significant neural activity, but rather by greater reductions in respiration rate. This study is the first to demonstrate that mindfulness-related pain relief is mechanistically distinct from placebo analgesia. The elucidation of this distinction confirms the existence of multiple, cognitively driven, supraspinal mechanisms for pain
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Zeidan, Fadel; Emerson, Nichole M; Farris, Suzan R; Ray, Jenna N; Jung, Youngkyoo; McHaffie, John G; Coghill, Robert C
2015-11-18
Mindfulness meditation reduces pain in experimental and clinical settings. However, it remains unknown whether mindfulness meditation engages pain-relieving mechanisms other than those associated with the placebo effect (e.g., conditioning, psychosocial context, beliefs). To determine whether the analgesic mechanisms of mindfulness meditation are different from placebo, we randomly assigned 75 healthy, human volunteers to 4 d of the following: (1) mindfulness meditation, (2) placebo conditioning, (3) sham mindfulness meditation, or (4) book-listening control intervention. We assessed intervention efficacy using psychophysical evaluation of experimental pain and functional neuroimaging. Importantly, all cognitive manipulations (i.e., mindfulness meditation, placebo conditioning, sham mindfulness meditation) significantly attenuated pain intensity and unpleasantness ratings when compared to rest and the control condition (p pain intensity (p = 0.032) and pain unpleasantness (p pain intensity (p = 0.030) and pain unpleasantness (p = 0.043) ratings more than sham mindfulness meditation. Mindfulness-meditation-related pain relief was associated with greater activation in brain regions associated with the cognitive modulation of pain, including the orbitofrontal, subgenual anterior cingulate, and anterior insular cortex. In contrast, placebo analgesia was associated with activation of the dorsolateral prefrontal cortex and deactivation of sensory processing regions (secondary somatosensory cortex). Sham mindfulness meditation-induced analgesia was not correlated with significant neural activity, but rather by greater reductions in respiration rate. This study is the first to demonstrate that mindfulness-related pain relief is mechanistically distinct from placebo analgesia. The elucidation of this distinction confirms the existence of multiple, cognitively driven, supraspinal mechanisms for pain modulation. Recent findings have demonstrated that mindfulness meditation
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Directory of Open Access Journals (Sweden)
Tao Teng
2016-02-01
Full Text Available In this article, a global adaptive neural dynamic surface control with predefined tracking performance is developed for a class of hypersonic flight vehicles, whose accurate dynamics is hard to obtain. The control scheme developed in this paper overcomes the limitations of neural approximation region by employing a switching mechanism which incorporates an additional robust controller outside the neural approximation region to pull the transient state variables back when they overstep the neural approximation region, such that globally uniformly ultimately bounded stability can be guaranteed. Especially, the developed global adaptive neural control also improves the tracking performance by introducing an error transformation mechanism, such that both transient and steady-state performance can be shaped according to the predefined bounds. Simulation studies on the hypersonic flight vehicle validate that the designed controller has good velocity modulation and velocity stability performance.
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Dynamic simulation of a steam generator by neural networks
International Nuclear Information System (INIS)
Masini, R.; Padovani, E.; Ricotti, M.E.; Zio, E.
1999-01-01
Numerical simulation by computers of the dynamic evolution of complex systems and components is a fundamental phase of any modern engineering design activity. This is of particular importance for risk-based design projects which require that the system behavior be analyzed under several and often extreme conditions. The traditional methods of simulation typically entail long, iterative, processes which lead to large simulation times, often exceeding the transients real time. Artificial neural networks (ANNs) may be exploited in this context, their advantages residing mainly in the speed of computation, in the capability of generalizing from few examples, in the robustness to noisy and partially incomplete data and in the capability of performing empirical input-output mapping without complete knowledge of the underlying physics. In this paper we present a novel approach to dynamic simulation by ANNs based on a superposition scheme in which a set of networks are individually trained, each one to respond to a different input forcing function. The dynamic simulation of a steam generator is considered as an example to show the potentialities of this tool and to point out the difficulties and crucial issues which typically arise when attempting to establish an efficient neural network simulator. The structure of the networks system is such to feedback, at each time step, a portion of the past evolution of the transient and this allows a good reproduction of also non-linear dynamic behaviors. A nice characteristic of the approach is that the modularization of the training reduces substantially its burden and gives this neural simulation tool a nice feature of transportability. (orig.)
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Rodríguez-Cattáneo, A; Aguilera, P; Cilleruelo, E; Crampton, W G R; Caputi, A A
2013-04-15
Previous studies describe six factors accounting for interspecific diversity of electric organ discharge (EOD) waveforms in Gymnotus. At the cellular level, three factors determine the locally generated waveforms: (1) electrocyte geometry and channel repertoire; (2) the localization of synaptic contacts on electrocyte surfaces; and (3) electric activity of electromotor axons preceding the discharge of electrocytes. At the organismic level, three factors determine the integration of the EOD as a behavioral unit: (4) the distribution of different types of electrocytes and specialized passive tissue forming the electric organ (EO); (5) the neural mechanisms of electrocyte discharge coordination; and (6) post-effector mechanisms. Here, we reconfirm the importance of the first five of these factors based on comparative studies of a wider diversity of Gymnotus than previously investigated. Additionally, we report a hitherto unseen aspect of EOD diversity in Gymnotus. The central region of the EO (which has the largest weight on the conspecific-received field) usually exhibits a negative-positive-negative pattern where the delay between the early negative and positive peaks (determined by neural coordination mechanisms) matches the delay between the positive and late negative peaks (determined by electrocyte responsiveness). Because delays between peaks typically determine the peak power frequency, this matching implies a co-evolution of neural and myogenic coordination mechanisms in determining the spectral specificity of the intraspecific communication channel. Finally, we define four functional species groups based on EO/EOD structure. The first three exhibit a heterogeneous EO in which doubly innervated electrocytes are responsible for a main triphasic complex. Group I species exhibit a characteristic cephalic extension of the EO. Group II species exhibit an early positive component of putative neural origin, and strong EO auto-excitability. Group III species exhibit
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Prediction of properties of polymer concrete composite with tire rubber using neural networks
International Nuclear Information System (INIS)
Diaconescu, Rodica-Mariana; Barbuta, Marinela; Harja, Maria
2013-01-01
Highlights: ► Using waste a new composite material was obtained with specific characteristics. ► The objective was to maximize tire powder content with the minimum resin content. ► By direct modeling, the maximum compressive strength was obtained for 30% tire powder. ► Inverse neural modeling was used for obtaining maximum values of strengths. -- Abstract: The neural network method was used to investigate the influence of filler and resin content on the mechanical properties of polymer concrete with powdered tire waste. The mechanical strengths of 10 experimentally determined combinations using mixed epoxy resin, aggregates and tire powder as filler were optimized using direct neural modeling and inverse neural modeling, by imposing a minimum cost (content in resin). Direct neural modeling gave the optimum composition for obtaining maximum values for compressive strength, flexural strength and split tensile strength. Inverse neural modeling analyzed the possibility of obtaining maximum values of mechanical properties by variations in the dosages of the epoxy resin and tire powder. Neural network modeling generated the mixes with the lowest cost and maximum strength. The modeling method has shown that two mechanical properties can be simultaneously optimized in the investigation domain. From direct modeling, the maximum compressive strength was obtained for a composition with 0.215 (fraction weight) epoxy resin and 0.3 (fraction weight) tire powder. Maximum flexural strength was obtained for experimental values of 0.23 epoxy resin and 0.17 tire powder with a severe reduction noted for smaller resin dosages. The maximum split tensile strength was obtained for a resin dosage of 0.24 and tire powder dosage of 0.17
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Changes in neural network homeostasis trigger neuropsychiatric symptoms.
Winkelmann, Aline; Maggio, Nicola; Eller, Joanna; Caliskan, Gürsel; Semtner, Marcus; Häussler, Ute; Jüttner, René; Dugladze, Tamar; Smolinsky, Birthe; Kowalczyk, Sarah; Chronowska, Ewa; Schwarz, Günter; Rathjen, Fritz G; Rechavi, Gideon; Haas, Carola A; Kulik, Akos; Gloveli, Tengis; Heinemann, Uwe; Meier, Jochen C
2014-02-01
The mechanisms that regulate the strength of synaptic transmission and intrinsic neuronal excitability are well characterized; however, the mechanisms that promote disease-causing neural network dysfunction are poorly defined. We generated mice with targeted neuron type-specific expression of a gain-of-function variant of the neurotransmitter receptor for glycine (GlyR) that is found in hippocampectomies from patients with temporal lobe epilepsy. In this mouse model, targeted expression of gain-of-function GlyR in terminals of glutamatergic cells or in parvalbumin-positive interneurons persistently altered neural network excitability. The increased network excitability associated with gain-of-function GlyR expression in glutamatergic neurons resulted in recurrent epileptiform discharge, which provoked cognitive dysfunction and memory deficits without affecting bidirectional synaptic plasticity. In contrast, decreased network excitability due to gain-of-function GlyR expression in parvalbumin-positive interneurons resulted in an anxiety phenotype, but did not affect cognitive performance or discriminative associative memory. Our animal model unveils neuron type-specific effects on cognition, formation of discriminative associative memory, and emotional behavior in vivo. Furthermore, our data identify a presynaptic disease-causing molecular mechanism that impairs homeostatic regulation of neural network excitability and triggers neuropsychiatric symptoms.
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Information-geometric measures estimate neural interactions during oscillatory brain states
Directory of Open Access Journals (Sweden)
Yimin eNie
2014-02-01
Full Text Available The characterization of functional network structures among multiple neurons is essential to understanding neural information processing. Information geometry (IG, a theory developed for investigating a space of probability distributions has recently been applied to spike-train analysis and has provided robust estimations of neural interactions. Although neural firing in the equilibrium state is often assumed in these studies, in reality, neural activity is non-stationary. The brain exhibits various oscillations depending on cognitive demands or when an animal is asleep. Therefore, the investigation of the IG measures during oscillatory network states is important for testing how the IG method can be applied to real neural data. Using model networks of binary neurons or more realistic spiking neurons, we studied how the single- and pairwise-IG measures were influenced by oscillatory neural activity. Two general oscillatory mechanisms, externally driven oscillations and internally induced oscillations, were considered. In both mechanisms, we found that the single-IG measure was linearly related to the magnitude of the external input, and that the pairwise-IG measure was linearly related to the sum of connection strengths between two neurons. We also observed that the pairwise-IG measure was not dependent on the oscillation frequency. These results are consistent with the previous findings that were obtained under the equilibrium conditions. Therefore, we demonstrate that the IG method provides useful insights into neural interactions under the oscillatory condition that can often be observed in the real brain.
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Neural Tube Defects, Folic Acid and Methylation
Imbard, Apolline; Benoist, Jean-François; Blom, Henk J.
2013-01-01
Neural tube defects (NTDs) are common complex congenital malformations resulting from failure of the neural tube closure during embryogenesis. It is established that folic acid supplementation decreases the prevalence of NTDs, which has led to national public health policies regarding folic acid. To date, animal studies have not provided sufficient information to establish the metabolic and/or genomic mechanism(s) underlying human folic acid responsiveness in NTDs. However, several lines of evidence suggest that not only folates but also choline, B12 and methylation metabolisms are involved in NTDs. Decreased B12 vitamin and increased total choline or homocysteine in maternal blood have been shown to be associated with increased NTDs risk. Several polymorphisms of genes involved in these pathways have also been implicated in risk of development of NTDs. This raises the question whether supplementation with B12 vitamin, betaine or other methylation donors in addition to folic acid periconceptional supplementation will further reduce NTD risk. The objective of this article is to review the role of methylation metabolism in the onset of neural tube defects. PMID:24048206
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Neural responses to exclusion predict susceptibility to social influence.
Falk, Emily B; Cascio, Christopher N; O'Donnell, Matthew Brook; Carp, Joshua; Tinney, Francis J; Bingham, C Raymond; Shope, Jean T; Ouimet, Marie Claude; Pradhan, Anuj K; Simons-Morton, Bruce G
2014-05-01
Social influence is prominent across the lifespan, but sensitivity to influence is especially high during adolescence and is often associated with increased risk taking. Such risk taking can have dire consequences. For example, in American adolescents, traffic-related crashes are leading causes of nonfatal injury and death. Neural measures may be especially useful in understanding the basic mechanisms of adolescents' vulnerability to peer influence. We examined neural responses to social exclusion as potential predictors of risk taking in the presence of peers in recently licensed adolescent drivers. Risk taking was assessed in a driving simulator session occurring approximately 1 week after the neuroimaging session. Increased activity in neural systems associated with the distress of social exclusion and mentalizing during an exclusion episode predicted increased risk taking in the presence of a peer (controlling for solo risk behavior) during a driving simulator session outside the neuroimaging laboratory 1 week later. These neural measures predicted risky driving behavior above and beyond self-reports of susceptibility to peer pressure and distress during exclusion. These results address the neural bases of social influence and risk taking; contribute to our understanding of social and emotional function in the adolescent brain; and link neural activity in specific, hypothesized, regions to risk-relevant outcomes beyond the neuroimaging laboratory. Results of this investigation are discussed in terms of the mechanisms underlying risk taking in adolescents and the public health implications for adolescent driving. Copyright © 2014 Society for Adolescent Health and Medicine. All rights reserved.
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Directory of Open Access Journals (Sweden)
Yongcheng Li
Full Text Available Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including 'random' and '4Q' (cultured neurons artificially divided into four interconnected parts neural network. Compared to the random cultures, the '4Q' cultures presented absolutely different activities, and the robot controlled by the '4Q' network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems.
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Zhang, Bin; Wang, Yuechao; Li, Hongyi
2015-01-01
Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including ‘random’ and ‘4Q’ (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the ‘4Q’ cultures presented absolutely different activities, and the robot controlled by the ‘4Q’ network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems. PMID:25992579
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Li, Yongcheng; Sun, Rong; Zhang, Bin; Wang, Yuechao; Li, Hongyi
2015-01-01
Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including 'random' and '4Q' (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the '4Q' cultures presented absolutely different activities, and the robot controlled by the '4Q' network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems.
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A neural network approach to the study of dynamics and structure of molecular systems
International Nuclear Information System (INIS)
Getino, C.; Sumpter, B.G.; Noid, D.W.
1994-01-01
Neural networks are used to study intramolecular energy flow in molecular systems (tetratomics to macromolecules), developing new techniques for efficient analysis of data obtained from molecular-dynamics and quantum mechanics calculations. Neural networks can map phase space points to intramolecular vibrational energies along a classical trajectory (example of complicated coordinate transformation), producing reasonably accurate values for any region of the multidimensional phase space of a tetratomic molecule. Neural network energy flow predictions are found to significantly enhance the molecular-dynamics method to longer time-scales and extensive averaging of trajectories for macromolecular systems. Pattern recognition abilities of neural networks can be used to discern phase space features. Neural networks can also expand model calculations by interpolation of costly quantum mechanical ab initio data, used to develop semiempirical potential energy functions
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The Neural Basis of and a Common Neural Circuitry in Different Types of Pro-social Behavior
Directory of Open Access Journals (Sweden)
Jun Luo
2018-06-01
Full Text Available Pro-social behaviors are voluntary behaviors that benefit other people or society as a whole, such as charitable donations, cooperation, trust, altruistic punishment, and fairness. These behaviors have been widely described through non self-interest decision-making in behavioral experimental studies and are thought to be increased by social preference motives. Importantly, recent studies using a combination of neuroimaging and brain stimulation, designed to reveal the neural mechanisms of pro-social behaviors, have found that a wide range of brain areas, specifically the prefrontal cortex, anterior insula, anterior cingulate cortex, and amygdala, are correlated or causally related with pro-social behaviors. In this review, we summarize the research on the neural basis of various kinds of pro-social behaviors and describe a common shared neural circuitry of these pro-social behaviors. We introduce several general ways in which experimental economics and neuroscience can be combined to develop important contributions to understanding social decision-making and pro-social behaviors. Future research should attempt to explore the neural circuitry between the frontal lobes and deeper brain areas.
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Energy Technology Data Exchange (ETDEWEB)
Tadayyon, Ghazal [Department of Metallurgical and Materials Engineering Faculty of Engineering, Ferdowsi University of Mashhad (Iran, Islamic Republic of); Centre for Research in Medical Devices (CURAM), National University of Ireland, Galway (Ireland); Mazinani, Mohammad, E-mail: mazinani@um.ac.ir [Department of Metallurgical and Materials Engineering Faculty of Engineering, Ferdowsi University of Mashhad (Iran, Islamic Republic of); Guo, Yina [Materials and Surface Science Institute, University of Limerick, Limerick (Ireland); Zebarjad, Seyed Mojtaba [Department of Materials Science and Engineering, School of Engineering, Shiraz University, Shiraz (Iran, Islamic Republic of); Tofail, Syed A.M. [Materials and Surface Science Institute, University of Limerick, Limerick (Ireland); Biggs, Manus J. [Centre for Research in Medical Devices (CURAM), National University of Ireland, Galway (Ireland)
2016-04-26
An investigation was carried out into the influence of the annealing temperatures on the thermo-mechanical behavior of Ti-rich NiTi alloy with regard to transformation temperatures, mechanical properties at room temperature and microstructure evolution under deformation. It was found that annealing above the recrystallization temperature (600 °C) modulated the mechanical behavior of the alloy significantly. Based on tensile and DSC analysis, it was observed that by increasing the annealing temperature, the shape memory behavior of the alloys improved. Scanning and transmission electron microscopy were used to investigate the fracture surfaces and microstructural evolution of the NiTi samples after failure. Fractography revealed the brittle fracture area produced through the propagation of cleavage cracks; however, ductile fracture via nucleation growth and coalescence of micro-dimples in the martensitic phase at room temperature were also observed. During plastic deformation, the NiTi alloy was also observed to undergo a detwinning process, dislocation slip and the formation of submicrocrystalline grains, nanocrystallization and amorphous bands.
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2018-01-01
Abstract Dopamine has been suggested to be crucially involved in effort-related choices. Key findings are that dopamine depletion (i) changed preference for a high-cost, large-reward option to a low-cost, small-reward option, (ii) but not when the large-reward option was also low-cost or the small-reward option gave no reward, (iii) while increasing the latency in all the cases but only transiently, and (iv) that antagonism of either dopamine D1 or D2 receptors also specifically impaired selection of the high-cost, large-reward option. The underlying neural circuit mechanisms remain unclear. Here we show that findings i–iii can be explained by the dopaminergic representation of temporal-difference reward-prediction error (TD-RPE), whose mechanisms have now become clarified, if (1) the synaptic strengths storing the values of actions mildly decay in time and (2) the obtained-reward-representing excitatory input to dopamine neurons increases after dopamine depletion. The former is potentially caused by background neural activity–induced weak synaptic plasticity, and the latter is assumed to occur through post-depletion increase of neural activity in the pedunculopontine nucleus, where neurons representing obtained reward exist and presumably send excitatory projections to dopamine neurons. We further show that finding iv, which is nontrivial given the suggested distinct functions of the D1 and D2 corticostriatal pathways, can also be explained if we additionally assume a proposed mechanism of TD-RPE calculation, in which the D1 and D2 pathways encode the values of actions with a temporal difference. These results suggest a possible circuit mechanism for the involvements of dopamine in effort-related choices and, simultaneously, provide implications for the mechanisms of TD-RPE calculation. PMID:29468191
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Probing Mechanism of Evolution of Simple Genomes
Pohorille, Andrew; Ditzler, Mark; Popovic, Milena; Wei, Chenyu
2016-01-01
Our overarching goal is to discover how the structure of the genotypic space of RNA polymers affects their ability to evolve. Specifically, we will address several fundamental questions that, so far, have remained largely unanswered. Was the genotypic space explored globally or only locally? Was the outcome of early evolution predictable or was it, instead, govern by chance? What was the role of neutral mutations in the evolution of increasing complex systems? As the first step, we study the problem in the example of RNA ligases. We obtain the complete, empirical fitness landscapes for short ligases and examine possible evolutionary paths for RNA molecules that are sufficiently long to preclude exhaustive search of the genotypic space.
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Neural Mechanisms of Circadian Regulation of Natural and Drug Reward
Directory of Open Access Journals (Sweden)
Lauren M. DePoy
2017-01-01
Full Text Available Circadian rhythms are endogenously generated near 24-hour variations of physiological and behavioral functions. In humans, disruptions to the circadian system are associated with negative health outcomes, including metabolic, immune, and psychiatric diseases, such as addiction. Animal models suggest bidirectional relationships between the circadian system and drugs of abuse, whereby desynchrony, misalignment, or disruption may promote vulnerability to drug use and the transition to addiction, while exposure to drugs of abuse may entrain, disrupt, or perturb the circadian timing system. Recent evidence suggests natural (i.e., food and drug rewards may influence overlapping neural circuitry, and the circadian system may modulate the physiological and behavioral responses to these stimuli. Environmental disruptions, such as shifting schedules or shorter/longer days, influence food and drug intake, and certain mutations of circadian genes that control cellular rhythms are associated with altered behavioral reward. We highlight the more recent findings associating circadian rhythms to reward function, linking environmental and genetic evidence to natural and drug reward and related neural circuitry.
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Lichtenberg, Tim; Golabek, Gregor J.; Gerya, Taras V.; Meyer, Michael R.
2016-08-01
The thermal history and internal structure of chondritic planetesimals, assembled before the giant impact phase of chaotic growth, potentially yield important implications for the final composition and evolution of terrestrial planets. These parameters critically depend on the internal balance of heating versus cooling, which is mostly determined by the presence of short-lived radionuclides (SLRs), such as 26Al and 60Fe, as well as the heat conductivity of the material. The heating by SLRs depends on their initial abundances, the formation time of the planetesimal and its size. It has been argued that the cooling history is determined by the porosity of the granular material, which undergoes dramatic changes via compaction processes and tends to decrease with time. In this study we assess the influence of these parameters on the thermo-mechanical evolution of young planetesimals with both 2D and 3D simulations. Using the code family I2ELVIS/I3ELVIS we have run numerous 2D and 3D numerical finite-difference fluid dynamic models with varying planetesimal radius, formation time and initial porosity. Our results indicate that powdery materials lowered the threshold for melting and convection in planetesimals, depending on the amount of SLRs present. A subset of planetesimals retained a powdery surface layer which lowered the thermal conductivity and hindered cooling. The effect of initial porosity was small, however, compared to those of planetesimal size and formation time, which dominated the thermo-mechanical evolution and were the primary factors for the onset of melting and differentiation. We comment on the implications of this work concerning the structure and evolution of these planetesimals, as well as their behavior as possible building blocks of terrestrial planets.
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On the mechanism of hydrogen evolution catalysis by proteins: A case study with bovine serum albumin
Energy Technology Data Exchange (ETDEWEB)
Doneux, Th., E-mail: tdoneux@ulb.ac.b [Chimie Analytique et Chimie des Interfaces, Faculte des Sciences, Universite Libre de Bruxelles, Boulevard du Triomphe 2, CP 255, B-1050 Bruxelles (Belgium); Institute of Biophysics, Academy of Sciences of the Czech Republic, Kralovopolska 135, 612 65 Brno (Czech Republic); Ostatna, Veronika [Institute of Biophysics, Academy of Sciences of the Czech Republic, Kralovopolska 135, 612 65 Brno (Czech Republic); Palecek, Emil, E-mail: palecek@ibp.cz [Institute of Biophysics, Academy of Sciences of the Czech Republic, Kralovopolska 135, 612 65 Brno (Czech Republic)
2011-10-30
Highlights: > Proteins catalyse hydrogen evolution at mercury electrodes. > The adsorbed protein is the mediator and the buffer proton donor is the substrate. > The characteristics of the catalytic peak are connected to the protein properties. - Abstract: The catalysis of the hydrogen evolution reaction (HER) by proteins has been known for decades but was only recently found to be useful for electroanalytical purposes. The mechanism of the catalytic process is investigated at hanging mercury drop electrodes by cyclic voltammetry, with bovine serum albumin as a model system. It is shown that the catalyst is the protein in the adsorbed state. The influence of various parameters such as the accumulation time, scan rate or buffer concentration is studied, and interpreted in the framework of a surface catalytic mechanism. Under the experimental conditions used in the work, a 'total catalysis' phenomenon takes place, the rate of HER being limited by the diffusion of the proton donor. The adequacy of the existing models is discussed, leading to a call for the development of more refined models.
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Automating the Incremental Evolution of Controllers for Physical Robots
DEFF Research Database (Denmark)
Faina, Andres; Jacobsen, Lars Toft; Risi, Sebastian
2017-01-01
the evolution of digital objects.…” The work presented here investigates how fully autonomous evolution of robot controllers can be realized in hardware, using an industrial robot and a marker-based computer vision system. In particular, this article presents an approach to automate the reconfiguration...... of the test environment and shows that it is possible, for the first time, to incrementally evolve a neural robot controller for different obstacle avoidance tasks with no human intervention. Importantly, the system offers a high level of robustness and precision that could potentially open up the range...
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Neural mechanisms of dissonance: an fMRI investigation of choice justification.
Kitayama, Shinobu; Chua, Hannah Faye; Tompson, Steven; Han, Shihui
2013-04-01
Cognitive dissonance theory proposes that difficult choice produces negatively arousing cognitive conflict (called dissonance), which motivates the chooser to justify her decision by increasing her preference for the chosen option while decreasing her preference for the rejected option. At present, however, neural mechanisms of dissonance are poorly understood. To address this gap of knowledge, we scanned 24 young Americans as they made 60 choices between pairs of popular music CDs. As predicted, choices between CDs that were close (vs. distant) in attractiveness (referred to as difficult vs. easy choices) resulted in activations of the dorsal anterior cingulate cortex (dACC), a brain region associated with cognitive conflict, and the left anterior insula (left aINS), a region often linked with aversive emotional arousal. Importantly, a separate analysis showed that choice-justifying attitude change was predicted by the in-choice signal intensity of the posterior cingulate cortex (PCC), a region that is linked to self-processing. The three regions identified (dACC, left aINS, and PCC) were correlated, within-subjects, across choices. The results were interpreted to support the hypothesis that cognitive dissonance plays a key role in producing attitudes that justify the choice. Copyright © 2012 Elsevier Inc. All rights reserved.
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Representation of neutron noise data using neural networks
International Nuclear Information System (INIS)
Korsah, K.; Damiano, B.; Wood, R.T.
1992-01-01
This paper describes a neural network-based method of representing neutron noise spectra using a model developed at the Oak Ridge National Laboratory (ORNL). The backpropagation neural network learned to represent neutron noise data in terms of four descriptors, and the network response matched calculated values to within 3.5 percent. These preliminary results are encouraging, and further research is directed towards the application of neural networks in a diagnostics system for the identification of the causes of changes in structural spectral resonances. This work is part of our current investigation of advanced technologies such as expert systems and neural networks for neutron noise data reduction, analysis, and interpretation. The objective is to improve the state-of-the-art of noise analysis as a diagnostic tool for nuclear power plants and other mechanical systems
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International Nuclear Information System (INIS)
Billerey, A.; Bouffioux, P.
2002-01-01
The complete paper follows. According to the fuel management policy in French PWR with respect to high burn-up, the prediction of the mechanical behavior of the irradiated fuel assembly is required as far as excessive deformations of fuel assembly might lead to incomplete Rod Cluster Control Assembly insertion (safety problems) and fretting wear lead to leaking rods (plant operation problems). One of the most important parameter is the evolution of the fuel rod support in the grid cell as it directly governs the mechanical behavior of the fuel assembly and consequently allows to predict the behavior of irradiated structure in terms of (i) axial and lateral deformation (global behavior of the assembly) and (ii) fretting wear (local behavior of the rod). Fuel rod support is provided by a spring-dimple system fixed on the grid. During irradiation, the spring force decreases and a gap between the rod and the spring might open. This phenomenon is due to (i) irradiation-induced stress relaxation for the spring and for the dimples, (ii) grid growth and (iii) reduction of rod diameter. Two models have been developed to predict the behavior of the rod in the grid cell. The first model is able to evaluate the spring force relaxation during irradiation. The second one is able to evaluate the rotation characteristic of the fuel rod in the cell, function of the spring force. The main input parameters are (i) the creep laws of the grid materials, (ii) the growth law of the grid, (iii) the evolution of rod diameter and (iv) the design of the fuel rod support. The objectives of this paper are to: (i) evaluate the consequences of grid support design modifications on the fretting sensitivity in terms of predicted maximum gap during irradiation and operational time to gap appearance; (ii) evaluate, using a non-linear Finite Element assembly model, the impact of the evolution of grid support under irradiation on the mechanical behavior of the full assembly in terms of axial and
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[The motive force of evolution based on the principle of organismal adjustment evolution.].
Cao, Jia-Shu
2010-08-01
From the analysis of the existing problems of the prevalent theories of evolution, this paper discussed the motive force of evolution based on the knowledge of the principle of organismal adjustment evolution to get a new understanding of the evolution mechanism. In the guide of Schrodinger's theory - "life feeds on negative entropy", the author proposed that "negative entropy flow" actually includes material flow, energy flow and information flow, and the "negative entropy flow" is the motive force for living and development. By modifying my own theory of principle of organismal adjustment evolution (not adaptation evolution), a new theory of "regulation system of organismal adjustment evolution involved in DNA, RNA and protein interacting with environment" is proposed. According to the view that phylogenetic development is the "integral" of individual development, the difference of negative entropy flow between organisms and environment is considered to be a motive force for evolution, which is a new understanding of the mechanism of evolution. Based on such understanding, evolution is regarded as "a changing process that one subsystem passes all or part of its genetic information to the next generation in a larger system, and during the adaptation process produces some new elements, stops some old ones, and thereby lasts in the larger system". Some other controversial questions related to evolution are also discussed.
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An Overview of Bayesian Methods for Neural Spike Train Analysis
Directory of Open Access Journals (Sweden)
Zhe Chen
2013-01-01
Full Text Available Neural spike train analysis is an important task in computational neuroscience which aims to understand neural mechanisms and gain insights into neural circuits. With the advancement of multielectrode recording and imaging technologies, it has become increasingly demanding to develop statistical tools for analyzing large neuronal ensemble spike activity. Here we present a tutorial overview of Bayesian methods and their representative applications in neural spike train analysis, at both single neuron and population levels. On the theoretical side, we focus on various approximate Bayesian inference techniques as applied to latent state and parameter estimation. On the application side, the topics include spike sorting, tuning curve estimation, neural encoding and decoding, deconvolution of spike trains from calcium imaging signals, and inference of neuronal functional connectivity and synchrony. Some research challenges and opportunities for neural spike train analysis are discussed.
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A review of organic and inorganic biomaterials for neural interfaces.
Fattahi, Pouria; Yang, Guang; Kim, Gloria; Abidian, Mohammad Reza
2014-03-26
Recent advances in nanotechnology have generated wide interest in applying nanomaterials for neural prostheses. An ideal neural interface should create seamless integration into the nervous system and performs reliably for long periods of time. As a result, many nanoscale materials not originally developed for neural interfaces become attractive candidates to detect neural signals and stimulate neurons. In this comprehensive review, an overview of state-of-the-art microelectrode technologies provided fi rst, with focus on the material properties of these microdevices. The advancements in electro active nanomaterials are then reviewed, including conducting polymers, carbon nanotubes, graphene, silicon nanowires, and hybrid organic-inorganic nanomaterials, for neural recording, stimulation, and growth. Finally, technical and scientific challenges are discussed regarding biocompatibility, mechanical mismatch, and electrical properties faced by these nanomaterials for the development of long-lasting functional neural interfaces.
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International Nuclear Information System (INIS)
Dudina, Dina V.; Lomovsky, Oleg I.; Valeev, Konstantin R.; Tikhov, Serguey F.; Boldyreva, Natalya N.; Salanov, Aleksey N.; Cherepanova, Svetlana V.; Zaikovskii, Vladimir I.; Andreev, Andrey S.; Lapina, Olga B.; Sadykov, Vladislav A.
2015-01-01
Highlights: • Phase formation during early stages of Cu–Al mechanical alloying was studied. • The products of mechanical alloying are of highly non-equilibrium character. • X-ray amorphous phases are present in the products of mechanical alloying. • An Al-rich X-ray amorphous phase is distributed between the crystallites. - Abstract: We report the phase and microstructure evolution of the Cu–13 wt.% Al mixture during treatment in a high-energy planetary ball mill with a particular focus on the early stages of mechanical alloying. Several characterization techniques, including X-ray diffraction phase analysis, nuclear magnetic resonance spectroscopy, differential dissolution, thermal analysis, and electron microscopy/elemental analysis, have been combined to study the evolution of the phase composition of the mechanically alloyed powders and describe the microstructure of the multi-phase products of mechanical alloying at different length scales. The following reaction sequence has been confirmed: Cu + Al → CuAl 2 (+Cu) → Cu 9 Al 4 + (Cu) → Cu(Al). The phase evolution was accompanied by the microstructure changes, the layered structure of the powder agglomerates disappearing with milling time. This scheme is further complicated by the processes of copper oxidation, reduction of copper oxides by metallic aluminum, and by variation of the stoichiometry of Cu(Al) solid solutions with milling time. Substantial amounts of X-ray amorphous phases were detected as well. Differential dissolution technique has revealed that a high content of aluminum in the Cu(Al) solid solution-based powders is due to the presence of Al-rich phases distributed between the Cu(Al) crystallites
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Mechanics Evolution Characteristics Analysis of Pressure-arch in Fully-mechanized Mining Field
Directory of Open Access Journals (Sweden)
S.R. Wang
2014-09-01
Full Text Available Based on a practical engineering, the three-dimension computational model was built using FLAC3D under the fullymechanized mining condition. Considering four variation factors, such as the distance of mining advancing, the strength of the surrounding rock, the speed of mining advancing and the dip angle of the coal seam, the mechanics evolution characteristics of the pressure-arch were analyzed. The result showed that for the horizontal seam, the geometric shape of the pressure-arch varied from flat arch to round arch gradually and the height and thickness of the pressure-arch also increased; the maximum principal stress in the skewback also increased with the working face advancing. With the strength of the surrounding rock from soft to hard, the arch thickness reduced, and the arch loading decreased. To improve the mining speed can do some contributions to the stability of the pressure-arch in the mining field. With the increase of dip angle of the seam, the pressure-arch displayed an asymmetric shape, the vault was tilted and moved to the upward direction. At the same time, the thickness of the pressure-arch increased, and the stress concentration in the skewback tended to be further intensified.
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Du, Mingde; Xu, Xianchen; Yang, Long; Guo, Yichuan; Guan, Shouliang; Shi, Jidong; Wang, Jinfen; Fang, Ying
2018-05-15
Subdural surface and penetrating depth probes are widely applied to record neural activities from the cortical surface and intracortical locations of the brain, respectively. Simultaneous surface and depth neural activity recording is essential to understand the linkage between the two modalities. Here, we develop flexible dual-modality neural probes based on graphene transistors. The neural probes exhibit stable electrical performance even under 90° bending because of the excellent mechanical properties of graphene, and thus allow multi-site recording from the subdural surface of rat cortex. In addition, finite element analysis was carried out to investigate the mechanical interactions between probe and cortex tissue during intracortical implantation. Based on the simulation results, a sharp tip angle of π/6 was chosen to facilitate tissue penetration of the neural probes. Accordingly, the graphene transistor-based dual-modality neural probes have been successfully applied for simultaneous surface and depth recording of epileptiform activity of rat brain in vivo. Our results show that graphene transistor-based dual-modality neural probes can serve as a facile and versatile tool to study tempo-spatial patterns of neural activities. Copyright © 2018 Elsevier B.V. All rights reserved.
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DEFF Research Database (Denmark)
Grinke, Eduard; Tetzlaff, Christian; Wörgötter, Florentin
2015-01-01
correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors) in the network to generate different turning angles with short-term memory for a walking...... dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a many degrees-of-freedom (DOFs) walking robot is a challenging task. Thus, in this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural...... mechanisms with plasticity, exteroceptive sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent neural network consisting of two fully connected neurons. Online...
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International Nuclear Information System (INIS)
He, D.; Zhu, J.C.; Lai, Z.H.; Liu, Y.; Yang, X.W.
2013-01-01
Highlights: ► Isothermal tensile deformations were carried on Ti–6Al–2Zr–1Mo–1V titanium alloy. ► Deformation activations were calculated based on kinetics rate equations. ► Deformation mechanisms are dislocation creep and self-diffusion at 800 and 850 °C. ► Microstructure globularization mechanisms varied with deformation temperature. ► Recrystallization mechanism changed from CDRX to DDRX as temperature increasing. - Abstract: Isothermal tensile tests have been performed to study the deformation mechanisms and microstructure evolution of Ti–6Al–2Zr–1Mo–1V titanium alloy in the temperature range 750–850 °C and strain rate range 0.001–0.1 s −1 . The deformation activations have been calculated based on kinetics rate equation to investigate the hot deformation mechanism. Microstructures of deformed samples have been analyzed by electron backscatter diffraction (EBSD) to evaluate the influences of hot deformation parameters on the microstructure evolution and recrystallization mechanism. The results indicate that deformation mechanisms vary with deformation conditions: at medium (800 °C) and high (850 °C) temperature, the deformation is mainly controlled by the mechanisms of dislocation creep and self-diffusion, respectively. The microstructure globularization mechanisms also depend on deformation temperature: in the temperature range from 750 to 800 °C, the high angle grain boundaries are mainly formed via dislocation accumulation or subgrain boundaries sliding and subgrains rotation; while at high temperature of 850 °C, recrystallization is the dominant mechanism. Especially, the evolution of the recrystallization mechanism with the deformation temperature is first observed and investigated in TA15 titanium alloy
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DEFF Research Database (Denmark)
Shibasaki, M.; Rasmussen, P.; Secher, Niels H.
2009-01-01
as an absence of sweating and cutaneous vasodilatation during a whole-body heat stress. Upon this confirmation, adenosine was perfused through one of the microdialysis probes to increase skin blood flow similar to that of the unblocked site. After internal temperature increased approximately 0.7 degrees C......During heat stress, isometric handgrip (IHG) exercise causes cutaneous vasoconstriction, but it remains controversial whether neural mechanisms are responsible for this observation. The objective of this study was to test the hypothesis that cutaneous vasoconstriction during IHG exercise in heat...... stressed individuals occurs via a neural mechanism. An axillary nerve blockade was performed to block efferent nerve traffic to the left forearm in seven healthy subjects. Two intradermal microdialysis probes were placed within forearm skin of the blocked area. Forearm skin blood flow was measured by laser...
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Indirect selection in Darwinian evolution : mechanisms and implications
Parsons, David
2011-01-01
The Aevol model is an in silico experimental evolution model that was specifically developped by Carole Knibbe to study the evolution of the structure of the genome. Using Aevol, a very strong second-order selective pressure towards a specific level of mutational variability of the phenotype was revealed: it was shown that since the survival of a lineage on the long term is conditionned to its ability to produce beneficial mutations while not loosing those previously found, a specific trade-o...
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Deformation mechanisms and grain size evolution in the Bohemian granulites - a computational study
Maierova, Petra; Lexa, Ondrej; Jeřábek, Petr; Franěk, Jan; Schulmann, Karel
2015-04-01
A dominant deformation mechanism in crustal rocks (e.g., dislocation and diffusion creep, grain boundary sliding, solution-precipitation) depends on many parameters such as temperature, major minerals, differential stress, strain rate and grain size. An exemplary sequence of deformation mechanisms was identified in the largest felsic granulite massifs in the southern Moldanubian domain (Bohemian Massif, central European Variscides). These massifs were interpreted to result from collision-related forced diapiric ascent of lower crust and its subsequent lateral spreading at mid-crustal levels. Three types of microstructures were distinguished. The oldest relict microstructure (S1) with large grains (>1000 μm) of feldspar deformed probably by dislocation creep at peak HT eclogite facies conditions. Subsequently at HP granulite-facies conditions, chemically- and deformation- induced recrystallization of feldspar porphyroclasts led to development of a fine-grained microstructure (S2, ~50 μm grain size) indicating deformation via diffusion creep, probably assisted by melt-enhanced grain-boundary sliding. This microstructure was associated with flow in the lower crust and/or its diapiric ascent. The latest microstructure (S3, ~100 μm grain size) is related to the final lateral spreading of retrograde granulites, and shows deformation by dislocation creep at amphibolite-facies conditions. The S2-S3 switch and coarsening was interpreted to be related with a significant decrease in strain rate. From this microstructural sequence it appears that it is the grain size that is critically linked with specific mechanical behavior of these rocks. Thus in this study, we focused on the interplay between grain size and deformation with the aim to numerically simulate and reinterpret the observed microstructural sequence. We tested several different mathematical descriptions of the grain size evolution, each of which gave qualitatively different results. We selected the two most
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Microstructural evolution and mechanical properties of Inconel 718 after thermal exposure
Energy Technology Data Exchange (ETDEWEB)
Yu, Z.S., E-mail: yuzaisong@tpri.com.cn [State Key Laboratory for Mechanical Behavior of Materials, Xi’an Jiaotong University, No. 28, Xianning West Road, Xi’an 710049 (China); Xi' an Thermal Power Research Institute Co. Ltd., No. 136, Xingqing Road, Xi’an 710032 (China); Zhang, J.X. [State Key Laboratory for Mechanical Behavior of Materials, Xi’an Jiaotong University, No. 28, Xianning West Road, Xi’an 710049 (China); Yuan, Y.; Zhou, R.C.; Zhang, H.J.; Wang, H.Z. [Xi' an Thermal Power Research Institute Co. Ltd., No. 136, Xingqing Road, Xi’an 710032 (China)
2015-05-14
Inconel 718 was subjected to various heat treatments, i.e., solution heat treatment, standard ageing treatment and standard ageing plus 700 °C thermal exposure. The mechanical properties of the alloys were determined using tensile tests and Charpy pendulum impact tests at 650 °C and room temperature, respectively. The highest yield strength of 988 MPa was attained in the standard aged specimen, whereas a maximum impact toughness of 217 J cm{sup −2} was attained in the solution-treated specimen. After thermal exposure, the mechanical properties of the specimens degrade. Both the yield strength and impact toughness decreased monotonically with increasing thermal exposure time. Subjected to a 10000-h long-term thermal exposure, the yield strength dramatically decreased to 475 MPa (almost 50% of the maximum strength), and the impact toughness reduced to only 18 J cm{sup −2}. The microstructures of the specimens were characterized using scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Coarsening of γ′ and γ″ and the transformation of γ″ to δ-Ni{sub 3}Nb was observed after thermal exposure. However, a complete transformation from metastable γ″ to δ-Ni{sub 3}Nb was never accomplished, even after the 10000-h long-term thermal exposure. Based on the obtained experimental results, the effects of the microstructural evolution on the mechanical properties are discussed.
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5-HTTLPR polymorphism modulates neural mechanisms of negative self-reflection.
Ma, Yina; Li, Bingfeng; Wang, Chenbo; Shi, Zhenhao; Sun, Yun; Sheng, Feng; Zhang, Yifan; Zhang, Wenxia; Rao, Yi; Han, Shihui
2014-09-01
Cognitive distortion in depression is characterized by enhanced negative thoughts about both environment and oneself. Carriers of a risk allele for depression, that is, the short (s) allele of the serotonin transporter promoter polymorphism (5-HTTLPR), exhibit amygdala hyperresponsiveness to negative environmental stimuli relative to homozygous long variant (l/l). However, the neural correlates of negative self-schema in s allele carriers remain unknown. Using functional MRI, we scanned individuals with s/s or l/l genotype of the 5-HTTLPR during reflection on their own personality traits or a friend's personality traits. We found that relative to l/l carriers, s/s carriers showed stronger distressed feelings and greater activity in the dorsal anterior cingulate (dACC)/dorsal medial prefrontal cortex (dmPFC) and the right anterior insula (AI) during negative self-reflection. The 5-HTTLPR effect on the distressed feelings was mediated by the AI/inferior frontal (IF) activity during negative self-reflection. The dACC/dmPFC activity explained 20% of the variation in harm-avoidance tendency in s/s but not l/l carriers. The genotype effects on distress and brain activity were not observed during reflection on a friend's negative traits. Our findings reveal that 5-HTTLPR polymorphism modulates distressed feelings and brain activities associated with negative self-schema and suggest a potential neurogenetic susceptibility mechanism for depression. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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Zhou, Xiaorun; Lu, Taiping; Zhu, Yadan; Zhao, Guangzhou; Dong, Hailiang; Jia, Zhigang; Yang, Yongzhen; Chen, Yongkang; Xu, Bingshe
2017-12-01
Surface morphology evolution mechanisms of InGaN/GaN multiple quantum wells (MQWs) during GaN barrier growth with different hydrogen (H 2 ) percentages have been systematically studied. Ga surface-diffusion rate, stress relaxation, and H 2 etching effect are found to be the main affecting factors of the surface evolution. As the percentage of H 2 increases from 0 to 6.25%, Ga surface-diffusion rate and the etch effect are gradually enhanced, which is beneficial to obtaining a smooth surface with low pits density. As the H 2 proportion further increases, stress relaxation and H 2 over- etching effect begin to be the dominant factors, which degrade surface quality. Furthermore, the effects of surface evolution on the interface and optical properties of InGaN/GaN MQWs are also profoundly discussed. The comprehensive study on the surface evolution mechanisms herein provides both technical and theoretical support for the fabrication of high-quality InGaN/GaN heterostructures.
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Directory of Open Access Journals (Sweden)
Gregory C Burgess
2010-09-01
Full Text Available A critical aspect of executive control is the ability to limit the adverse effects of interference. Previous studies have shown activation of left ventrolateral prefrontal cortex after the onset of interference, suggesting that interference may be resolved in a reactive manner. However, we suggest that interference control may also operate in a proactive manner to prevent effects of interference. The current study investigated the temporal dynamics of interference control by varying two factors - interference expectancy and fluid intelligence (gF - that could influence whether interference control operates proactively versus reactively.A modified version of the recent negatives task was utilized. Interference expectancy was manipulated across task blocks by changing the proportion of recent negative (interference trials versus recent positive (facilitation trials. Furthermore, we explored whether gF affected the tendency to utilize specific interference control mechanisms. When interference expectancy was low, activity in lateral prefrontal cortex replicated prior results showing a reactive control pattern (i.e., interference-sensitivity during probe period. In contrast, when interference expectancy was high, bilateral prefrontal cortex activation was more indicative of proactive control mechanisms (interference-related effects prior to the probe period. Additional results suggested that the proactive control pattern was more evident in high gF individuals, whereas the reactive control pattern was more evident in low gF individuals.The results suggest the presence of two neural mechanisms of interference control, with the differential expression of these mechanisms modulated by both experimental (e.g., expectancy effects and individual difference (e.g., gF factors.
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Evolution of lung breathing from a lungless primitive vertebrate.
Hoffman, M; Taylor, B E; Harris, M B
2016-04-01
Air breathing was critical to the terrestrial radiation and evolution of tetrapods and arose in fish. The vertebrate lung originated from a progenitor structure present in primitive boney fish. The origin of the neural substrates, which are sensitive to metabolically produced CO2 and which rhythmically activate respiratory muscles to match lung ventilation to metabolic demand, is enigmatic. We have found that a distinct periodic centrally generated rhythm, described as "cough" and occurring in lamprey in vivo and in vitro, is modulated by central sensitivity to CO2. This suggests that elements critical for the evolution of breathing in tetrapods, were present in the most basal vertebrate ancestors prior to the evolution of the lung. We propose that the evolution of breathing in all vertebrates occurred through exaptations derived from these critical basal elements. Copyright © 2015 Elsevier B.V. All rights reserved.
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Beloate, Lauren N; Coolen, Lique M
2017-12-01
Different factors influence the development of drug addiction in humans, including social reward experiences. In animals, experience with social rewards, such as sexual behavior, pair bonding, social and environmental enrichment, can be protective. However, loss or lack of social rewards can lead to a vulnerability to drug-seeking behavior. The effects of social reward experience on drug-seeking behavior are associated with changes in the neural pathways that control drug-related behavior. This review will provide an introduction and overview of the mesolimbic pathway and the influence of social reward experience on drug-seeking behavior in rodents. Moreover, the research from our laboratory on effects of sexual experience and loss of sex reward on psychostimulant and opiate reward will be reviewed. Finally, we will review current knowledge of the neural mechanisms that underlie these interactions. Investigations of the neural underpinnings by which social and drug rewards interact contribute to improved understanding of the neural basis of vulnerability for drug addiction and reward-related behaviors in general. Copyright © 2017 Elsevier Ltd. All rights reserved.
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International Nuclear Information System (INIS)
Mostafaei, Amir; Toman, Jakub; Stevens, Erica L.; Hughes, Eamonn T.; Krimer, Yuval L.; Chmielus, Markus
2017-01-01
In this study, we investigate the effect of powders resulting from different atomization methods on properties of binder jet printed and heat-treated samples. Air-melted gas atomized (GA) and water atomized (WA) nickel-based alloy 625 powders were used to binder jet print samples for a detailed comparative study on microstructural evolution and mechanical properties. GA printed samples achieved higher sintering density (99.2%) than WA samples (95.0%) due to differences in powder morphology and chemistry. Grain sizes of GA and WA samples at their highest density were 89 ± 21 μm and 88 ± 26 μm, respectively. Mechanical tests were conducted on optimally sintered samples and sintered plus aged samples; aging further improved microstructure and mechanical properties. This study shows that microstructural evolution (densification, and carbide, oxide and intermetallic phase formation) is very different for GA and WA binder jet printed and heat-treated samples. This difference in microstructural evolution results in different mechanical properties with the superior sintered and aged GA specimen reaching a hardness of 327 ± 7 HV_0_._1, yield strength of 394 ± 15 MPa, and ultimate tensile strength of 718 ± 14 MPa which are higher than cast alloy 625 values.
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Neural-Network Control Of Prosthetic And Robotic Hands
Buckley, Theresa M.
1991-01-01
Electronic neural networks proposed for use in controlling robotic and prosthetic hands and exoskeletal or glovelike electromechanical devices aiding intact but nonfunctional hands. Specific to patient, who activates grasping motion by voice command, by mechanical switch, or by myoelectric impulse. Patient retains higher-level control, while lower-level control provided by neural network analogous to that of miniature brain. During training, patient teaches miniature brain to perform specialized, anthropomorphic movements unique to himself or herself.
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Framework for Computer-Aided Evolution of Object-Oriented Designs
Ciraci, S.; van den Broek, P.M.; Aksit, Mehmet
2008-01-01
In this paper, we describe a framework for the computer aided evolution of the designs of object-oriented software systems. Evolution mechanisms are software structures that prepare software for certain type of evolutions. The framework uses a database which holds the evolution mechanisms, modeled
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Energy Technology Data Exchange (ETDEWEB)
Kakazey, M., E-mail: kakazey@hotmail.com [Centro de Investigación en Ingeniería y Ciencias Aplicadas, Universidad Autonoma del Estado de Morelos, Cuernavaca (Mexico); Vlasova, M. [Centro de Investigación en Ingeniería y Ciencias Aplicadas, Universidad Autonoma del Estado de Morelos, Cuernavaca (Mexico); Vorobiev, Y. [Unidad Querétaro del Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Querétaro (Mexico); Leon, I. [Centro de Investigaciones Quimicas, Universidad Autonoma del Estado de Morelos, Cuernavaca (Mexico); Cabecera Gonzalez, M. [Facultad de Ciencias Químicas e Ingeniería, Universidad Autonoma del Estado de Morelos, Cuernavaca (Mexico); Chávez Urbiola, Edgar Arturo [Unidad Querétaro del Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Querétaro (Mexico)
2014-11-15
Kinetics of microstructural evolution in ZnO and NiO black powder mixture during prolonged high-energy mechanical ball milling were investigated by Scanning Electron Microscopy, Laser Particle Sizer, X-ray diffraction, Electron Paramagnetic Resonance, Fourier Transform Infrared Spectroscopy and UV–vis Diffuse Reflection methods. The use of these methods allows us to control the macrostructural processes (ZnO particles and NiO granules grinding, the deagglomeration and “secondary agglomeration”), the microstructural processes (formation and annealing of different native defects in ZnO [V{sub Zn}{sup −}:Zn{sub i}{sup 0} (I), V{sub Zn}{sup −} (II), and (V{sub Zn}{sup −}){sub 2}{sup −} (III) centers] and NiO black) and the mechanothermal processes in samples. This allows to establish the relationship between microstructural evolution and the properties of the samples depending on the duration of the mechanical processing.
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International Nuclear Information System (INIS)
Mayer, T.
2012-01-01
This dissertation deals with the effective mechanical analysis of steam turbine parts which is not only required for the reliable and safe use of newly built steam turbines, but also for the remaining life assessment of components that have been exposed to service duty over long periods of time. This Thesis aims to develop a physically motivated evolutionary constitutive model for a low-alloy bainitic 2CrMoNiWV (23CrMoNiWV8-8) steam turbine rotor steels. A comprehensive experimental characterisation is performed concerning the mechanical and microstructural evolution of 2CrMoNiWV as subjected to low cycle fatigue (LCF) deformation at elevated temperatures, at different strain rates and for various strain amplitudes. This cyclic plastic deformation causes the rearrangement of dislocations in the microstructure of the steels used for such rotor applications. Symmetric, strain controlled LCF experiments have been carried out in the Laboratory of the High Temperature Integrity Group at the Swiss Federal Laboratories for Materials Science and Technology EMPA. These include mechanical tests in the temperature range between 20 °C to 600 °C at strain rates of 0.001%/s to 1.0%/s and strain amplitudes of ±0.25% to ±1.0%. The LCF experiments reported on comprehensively characterise the temperature, strain rate and strain amplitude dependent cyclic elastic-plastic behaviour of 2CrMoNiWV. Both complete single-specimen endurance tests and interrupted multi-specimen tests have been performed. On the basis of this experimental evidence, an evolutionary formulation of the model is further developed that excellently reproduces the strain amplitude dependent mechanical evolution of 2CrMoNiWV when subjected to LCF loading at different constant strain amplitudes but equal temperature and strain rate. The simulation of benchmark experiments introducing increasing or decreasing strain amplitude steps into the LCF deformation history provide promising results. A further important
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Energy Technology Data Exchange (ETDEWEB)
Mayer, T.
2012-07-01
This dissertation deals with the effective mechanical analysis of steam turbine parts which is not only required for the reliable and safe use of newly built steam turbines, but also for the remaining life assessment of components that have been exposed to service duty over long periods of time. This Thesis aims to develop a physically motivated evolutionary constitutive model for a low-alloy bainitic 2CrMoNiWV (23CrMoNiWV8-8) steam turbine rotor steels. A comprehensive experimental characterisation is performed concerning the mechanical and microstructural evolution of 2CrMoNiWV as subjected to low cycle fatigue (LCF) deformation at elevated temperatures, at different strain rates and for various strain amplitudes. This cyclic plastic deformation causes the rearrangement of dislocations in the microstructure of the steels used for such rotor applications. Symmetric, strain controlled LCF experiments have been carried out in the Laboratory of the High Temperature Integrity Group at the Swiss Federal Laboratories for Materials Science and Technology EMPA. These include mechanical tests in the temperature range between 20 °C to 600 °C at strain rates of 0.001%/s to 1.0%/s and strain amplitudes of ±0.25% to ±1.0%. The LCF experiments reported on comprehensively characterise the temperature, strain rate and strain amplitude dependent cyclic elastic-plastic behaviour of 2CrMoNiWV. Both complete single-specimen endurance tests and interrupted multi-specimen tests have been performed. On the basis of this experimental evidence, an evolutionary formulation of the model is further developed that excellently reproduces the strain amplitude dependent mechanical evolution of 2CrMoNiWV when subjected to LCF loading at different constant strain amplitudes but equal temperature and strain rate. The simulation of benchmark experiments introducing increasing or decreasing strain amplitude steps into the LCF deformation history provide promising results. A further important
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Forecasting solar proton event with artificial neural network
Gong, J.; Wang, J.; Xue, B.; Liu, S.; Zou, Z.
Solar proton event (SPE), relatively rare but popular in solar maximum, can bring hazard situation to spacecraft. As a special event, SPE always accompanies flare, which is also called proton flare. To produce such an eruptive event, large amount energy must be accumulated within the active region. So we can investigate the character of the active region and its evolving trend, together with other such as cm radio emission and soft X-ray background to evaluate the potential of SEP in chosen area. In order to summarize the omen of SPEs in the active regions behind the observed parameters, we employed AI technology. Full connecting neural network was chosen to fulfil this job. After constructing the network, we train it with 13 parameters that was able to exhibit the character of active regions and their evolution trend. More than 80 sets of event parameter were defined to teach the neural network to identify whether an active region was potential of SPE. Then we test this model with a data base consisting SPE and non-SPE cases that was not used to train the neural network. The result showed that 75% of the choice by the model was right.
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A comparative study of two neural networks for document retrieval
International Nuclear Information System (INIS)
Hui, S.C.; Goh, A.
1997-01-01
In recent years there has been specific interest in adopting advanced computer techniques in the field of document retrieval. This interest is generated by the fact that classical methods such as the Boolean search, the vector space model or even probabilistic retrieval cannot handle the increasing demands of end-users in satisfying their needs. The most recent attempt is the application of the neural network paradigm as a means of providing end-users with a more powerful retrieval mechanism. Neural networks are not only good pattern matchers but also highly versatile and adaptable. In this paper, we demonstrate how to apply two neural networks, namely Adaptive Resonance Theory and Fuzzy Kohonen Neural Network, for document retrieval. In addition, a comparison of these two neural networks based on performance is also given
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Neural network tagging in a toy model
International Nuclear Information System (INIS)
Milek, Marko; Patel, Popat
1999-01-01
The purpose of this study is a comparison of Artificial Neural Network approach to HEP analysis against the traditional methods. A toy model used in this analysis consists of two types of particles defined by four generic properties. A number of 'events' was created according to the model using standard Monte Carlo techniques. Several fully connected, feed forward multi layered Artificial Neural Networks were trained to tag the model events. The performance of each network was compared to the standard analysis mechanisms and significant improvement was observed
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Dynamic Information Encoding With Dynamic Synapses in Neural Adaptation
Li, Luozheng; Mi, Yuanyuan; Zhang, Wenhao; Wang, Da-Hui; Wu, Si
2018-01-01
Adaptation refers to the general phenomenon that the neural system dynamically adjusts its response property according to the statistics of external inputs. In response to an invariant stimulation, neuronal firing rates first increase dramatically and then decrease gradually to a low level close to the background activity. This prompts a question: during the adaptation, how does the neural system encode the repeated stimulation with attenuated firing rates? It has been suggested that the neural system may employ a dynamical encoding strategy during the adaptation, the information of stimulus is mainly encoded by the strong independent spiking of neurons at the early stage of the adaptation; while the weak but synchronized activity of neurons encodes the stimulus information at the later stage of the adaptation. The previous study demonstrated that short-term facilitation (STF) of electrical synapses, which increases the synchronization between neurons, can provide a mechanism to realize dynamical encoding. In the present study, we further explore whether short-term plasticity (STP) of chemical synapses, an interaction form more common than electrical synapse in the cortex, can support dynamical encoding. We build a large-size network with chemical synapses between neurons. Notably, facilitation of chemical synapses only enhances pair-wise correlations between neurons mildly, but its effect on increasing synchronization of the network can be significant, and hence it can serve as a mechanism to convey the stimulus information. To read-out the stimulus information, we consider that a downstream neuron receives balanced excitatory and inhibitory inputs from the network, so that the downstream neuron only responds to synchronized firings of the network. Therefore, the response of the downstream neuron indicates the presence of the repeated stimulation. Overall, our study demonstrates that STP of chemical synapse can serve as a mechanism to realize dynamical neural
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Directory of Open Access Journals (Sweden)
Mikiko Tanaka
2016-05-01
Full Text Available In gnathostomes, limb buds arise from the lateral plate mesoderm at discrete positions along the body axis. Specification of these limb-forming fields can be subdivided into several steps. The lateral plate mesoderm is regionalized into the anterior lateral plate mesoderm (ALPM; cardiac mesoderm and the posterior lateral plate mesoderm (PLPM. Subsequently, Hox genes appear in a nested fashion in the PLPM and provide positional information along the body axis. The lateral plate mesoderm then splits into the somatic and splanchnic layers. In the somatic layer of the PLPM, the expression of limb initiation genes appears in the limb-forming region, leading to limb bud initiation. Furthermore, past and current work in limbless amphioxus and lampreys suggests that evolutionary changes in developmental programs occurred during the acquisition of paired fins during vertebrate evolution. This review presents these recent advances and discusses the mechanisms of limb field specification during development and evolution, with a focus on the role of Hox genes in this process.
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Douglas, Zachary H; Maniscalco, Brian; Hallett, Mark; Wassermann, Eric M; He, Biyu J
2015-05-06
Conscious intention is a fundamental aspect of the human experience. Despite long-standing interest in the basis and implications of intention, its underlying neurobiological mechanisms remain poorly understood. Using high-definition transcranial DC stimulation (tDCS), we observed that enhancing spontaneous neuronal excitability in both the angular gyrus and the primary motor cortex caused the reported time of conscious movement intention to be ∼60-70 ms earlier. Slow brain waves recorded ∼2-3 s before movement onset, as well as hundreds of milliseconds after movement onset, independently correlated with the modulation of conscious intention by brain stimulation. These brain activities together accounted for 81% of interindividual variability in the modulation of movement intention by brain stimulation. A computational model using coupled leaky integrator units with biophysically plausible assumptions about the effect of tDCS captured the effects of stimulation on both neural activity and behavior. These results reveal a temporally extended brain process underlying conscious movement intention that spans seconds around movement commencement. Copyright © 2015 Douglas et al.
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Machine Learning and Quantum Mechanics
Chapline, George
The author has previously pointed out some similarities between selforganizing neural networks and quantum mechanics. These types of neural networks were originally conceived of as away of emulating the cognitive capabilities of the human brain. Recently extensions of these networks, collectively referred to as deep learning networks, have strengthened the connection between self-organizing neural networks and human cognitive capabilities. In this note we consider whether hardware quantum devices might be useful for emulating neural networks with human-like cognitive capabilities, or alternatively whether implementations of deep learning neural networks using conventional computers might lead to better algorithms for solving the many body Schrodinger equation.
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Neural Network on Photodegradation of Octylphenol using Natural and Artificial UV Radiation
Directory of Open Access Journals (Sweden)
Lorentz JÄNTSCHI
2011-09-01
Full Text Available The present paper comes up with an experimental design meant to point out the factors interferingin octylphenol’s degradation in surface waters under solar radiation, underlining each factor’sinfluence on the process observable (concentration of p-octylphenol. Multiple linear regressionanalysis and artificial neural network (Multi-Layer Perceptron type were applied in order to obtaina mathematical model capable to explain the action of UV-light upon synthetic solutions of OP inultra-pure water (MilliQ type. Neural network proves to be the most efficient method in predictingthe evolution of OP concentration during photodegradation process. Thus, determination in neuralnetwork’s case has almost double value versus the regression analysis.
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International Nuclear Information System (INIS)
Chomette, S.
2009-11-01
High Temperature Reactors (HTR), is one of the innovative nuclear reactor designed to be inherently safer than previous generation and to produce minimal waste. The most critical metallic component in that type of reactor is the Intermediate Heat exchanger (IHX). The constraints imposed by the conception and the severe operational conditions (high temperature of 850 C to 950 C, lifetime of 20,000 h) have guided the IHX material selection toward two solid solution nickel base alloys, the Inconel 617 and the Haynes 230. Inconel 617 is the primary candidate alloy thanks to its good high temperature mechanical and corrosion properties and the large data base developed in previous programs. However, its high cobalt content has to be considered as an issue (nuclear activation). The more recent alloy Haynes 230, in which most of the cobalt has been replaced by tungsten, present characteristics similar to the 617 alloy. The objective of this thesis is to study the high temperature mechanical behaviour of both alloys in relation with their microstructural evolutions. The as received microstructural observations have revealed primary carbides (M 6 C). Most of this precipitates are evenly distributed in the materials. Few M 23 C 6 secondary carbides are observed in both alloys in the as received state. Thermal ageing treatments at 850 C lead to an important M 23 C 6 precipitation on slip lines and at grain boundaries. The size of this carbides increases and their number decreases with increasing ageing duration. The intragranular precipitation of secondary carbides at 950 C is more limited and the intergranular evolution more important than at 850 C. The microstructural observations and the hardness evolution of both alloys show that the main microstructural evolutions occur before 1,000 h at both studied temperatures. The mechanical properties of the Inconel 617 and the Haynes 230 have been studied using tensile, creep, fatigue and relaxation-fatigue tests. Particularly, the
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Neural reactivation links unconscious thought to decision-making performance.
Creswell, John David; Bursley, James K; Satpute, Ajay B
2013-12-01
Brief periods of unconscious thought (UT) have been shown to improve decision making compared with making an immediate decision (ID). We reveal a neural mechanism for UT in decision making using blood oxygen level-dependent (BOLD) functional magnetic resonance imaging. Participants (N = 33) encoded information on a set of consumer products (e.g. 48 attributes describing four different cars), and we manipulated whether participants (i) consciously thought about this information (conscious thought), (ii) completed a difficult 2-back working memory task (UT) or (iii) made an immediate decision about the consumer products (ID) in a within-subjects blocked design. To differentiate UT neural activity from 2-back working memory neural activity, participants completed an independent 2-back task and this neural activity was subtracted from neural activity occurring during the UT 2-back task. Consistent with a neural reactivation account, we found that the same regions activated during the encoding of complex decision information (right dorsolateral prefrontal cortex and left intermediate visual cortex) continued to be activated during a subsequent 2-min UT period. Moreover, neural reactivation in these regions was predictive of subsequent behavioral decision-making performance after the UT period. These results provide initial evidence for post-encoding unconscious neural reactivation in facilitating decision making.
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Can Neural Activity Propagate by Endogenous Electrical Field?
Qiu, Chen; Shivacharan, Rajat S.; Zhang, Mingming
2015-01-01
It is widely accepted that synaptic transmissions and gap junctions are the major governing mechanisms for signal traveling in the neural system. Yet, a group of neural waves, either physiological or pathological, share the same speed of ∼0.1 m/s without synaptic transmission or gap junctions, and this speed is not consistent with axonal conduction or ionic diffusion. The only explanation left is an electrical field effect. We tested the hypothesis that endogenous electric fields are sufficient to explain the propagation with in silico and in vitro experiments. Simulation results show that field effects alone can indeed mediate propagation across layers of neurons with speeds of 0.12 ± 0.09 m/s with pathological kinetics, and 0.11 ± 0.03 m/s with physiologic kinetics, both generating weak field amplitudes of ∼2–6 mV/mm. Further, the model predicted that propagation speed values are inversely proportional to the cell-to-cell distances, but do not significantly change with extracellular resistivity, membrane capacitance, or membrane resistance. In vitro recordings in mice hippocampi produced similar speeds (0.10 ± 0.03 m/s) and field amplitudes (2.5–5 mV/mm), and by applying a blocking field, the propagation speed was greatly reduced. Finally, osmolarity experiments confirmed the model's prediction that cell-to-cell distance inversely affects propagation speed. Together, these results show that despite their weak amplitude, electric fields can be solely responsible for spike propagation at ∼0.1 m/s. This phenomenon could be important to explain the slow propagation of epileptic activity and other normal propagations at similar speeds. SIGNIFICANCE STATEMENT Neural activity (waves or spikes) can propagate using well documented mechanisms such as synaptic transmission, gap junctions, or diffusion. However, the purpose of this paper is to provide an explanation for experimental data showing that neural signals can propagate by means other than synaptic
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Implications of behavioral architecture for the evolution of self-organized division of labor.
Directory of Open Access Journals (Sweden)
A Duarte
Full Text Available Division of labor has been studied separately from a proximate self-organization and an ultimate evolutionary perspective. We aim to bring together these two perspectives. So far this has been done by choosing a behavioral mechanism a priori and considering the evolution of the properties of this mechanism. Here we use artificial neural networks to allow for a more open architecture. We study whether emergent division of labor can evolve in two different network architectures; a simple feedforward network, and a more complex network that includes the possibility of self-feedback from previous experiences. We focus on two aspects of division of labor; worker specialization and the ratio of work performed for each task. Colony fitness is maximized by both reducing idleness and achieving a predefined optimal work ratio. Our results indicate that architectural constraints play an important role for the outcome of evolution. With the simplest network, only genetically determined specialization is possible. This imposes several limitations on worker specialization. Moreover, in order to minimize idleness, networks evolve a biased work ratio, even when an unbiased work ratio would be optimal. By adding self-feedback to the network we increase the network's flexibility and worker specialization evolves under a wider parameter range. Optimal work ratios are more easily achieved with the self-feedback network, but still provide a challenge when combined with worker specialization.
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Implications of behavioral architecture for the evolution of self-organized division of labor.
Duarte, A; Scholtens, E; Weissing, F J
2012-01-01
Division of labor has been studied separately from a proximate self-organization and an ultimate evolutionary perspective. We aim to bring together these two perspectives. So far this has been done by choosing a behavioral mechanism a priori and considering the evolution of the properties of this mechanism. Here we use artificial neural networks to allow for a more open architecture. We study whether emergent division of labor can evolve in two different network architectures; a simple feedforward network, and a more complex network that includes the possibility of self-feedback from previous experiences. We focus on two aspects of division of labor; worker specialization and the ratio of work performed for each task. Colony fitness is maximized by both reducing idleness and achieving a predefined optimal work ratio. Our results indicate that architectural constraints play an important role for the outcome of evolution. With the simplest network, only genetically determined specialization is possible. This imposes several limitations on worker specialization. Moreover, in order to minimize idleness, networks evolve a biased work ratio, even when an unbiased work ratio would be optimal. By adding self-feedback to the network we increase the network's flexibility and worker specialization evolves under a wider parameter range. Optimal work ratios are more easily achieved with the self-feedback network, but still provide a challenge when combined with worker specialization.
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Spaced Learning Enhances Subsequent Recognition Memory by Reducing Neural Repetition Suppression
Xue, Gui; Mei, Leilei; Chen, Chuansheng; Lu, Zhong-Lin; Poldrack, Russell; Dong, Qi
2011-01-01
Spaced learning usually leads to better recognition memory as compared with massed learning, yet the underlying neural mechanisms remain elusive. One open question is whether the spacing effect is achieved by reducing neural repetition suppression. In this fMRI study, participants were scanned while intentionally memorizing 120 novel faces, half…
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Does bilingualism contribute to cognitive reserve? Cognitive and neural perspectives.
Guzmán-Vélez, Edmarie; Tranel, Daniel
2015-01-01
Cognitive reserve refers to how individuals actively utilize neural resources to cope with neuropathology to maintain cognitive functioning. The present review aims to critically examine the literature addressing the relationship between bilingualism and cognitive reserve to elucidate whether bilingualism delays the onset of cognitive and behavioral manifestations of dementia. Potential neural mechanisms behind this relationship are discussed. PubMed and PsycINFO databases were searched (through January 2014) for original research articles in English or Spanish languages. The following search strings were used as keywords for study retrieval: "bilingual AND reserve," "reserve AND neural mechanisms," and "reserve AND multilingualism." Growing scientific evidence suggests that lifelong bilingualism contributes to cognitive reserve and delays the onset of Alzheimer's disease symptoms, allowing bilingual individuals affected by Alzheimer's disease to live an independent and richer life for a longer time than their monolingual counterparts. Lifelong bilingualism is related to more efficient use of brain resources that help individuals maintain cognitive functioning in the presence of neuropathology. We propose multiple putative neural mechanisms through which lifelong bilinguals cope with neuropathology. The roles of immigration status, education, age of onset, proficiency, and frequency of language use on the relationship between cognitive reserve and bilingualism are considered. Implications of these results for preventive practices and future research are discussed. PsycINFO Database Record (c) 2015 APA, all rights reserved.
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Implementing Signature Neural Networks with Spiking Neurons.
Carrillo-Medina, José Luis; Latorre, Roberto
2016-01-01
Spiking Neural Networks constitute the most promising approach to develop realistic Artificial Neural Networks (ANNs). Unlike traditional firing rate-based paradigms, information coding in spiking models is based on the precise timing of individual spikes. It has been demonstrated that spiking ANNs can be successfully and efficiently applied to multiple realistic problems solvable with traditional strategies (e.g., data classification or pattern recognition). In recent years, major breakthroughs in neuroscience research have discovered new relevant computational principles in different living neural systems. Could ANNs benefit from some of these recent findings providing novel elements of inspiration? This is an intriguing question for the research community and the development of spiking ANNs including novel bio-inspired information coding and processing strategies is gaining attention. From this perspective, in this work, we adapt the core concepts of the recently proposed Signature Neural Network paradigm-i.e., neural signatures to identify each unit in the network, local information contextualization during the processing, and multicoding strategies for information propagation regarding the origin and the content of the data-to be employed in a spiking neural network. To the best of our knowledge, none of these mechanisms have been used yet in the context of ANNs of spiking neurons. This paper provides a proof-of-concept for their applicability in such networks. Computer simulations show that a simple network model like the discussed here exhibits complex self-organizing properties. The combination of multiple simultaneous encoding schemes allows the network to generate coexisting spatio-temporal patterns of activity encoding information in different spatio-temporal spaces. As a function of the network and/or intra-unit parameters shaping the corresponding encoding modality, different forms of competition among the evoked patterns can emerge even in the absence
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Delegation to automaticity: the driving force for cognitive evolution?
Shine, J M; Shine, R
2014-01-01
The ability to delegate control over repetitive tasks from higher to lower neural centers may be a fundamental innovation in human cognition. Plausibly, the massive neurocomputational challenges associated with the mastery of balance during the evolution of bipedality in proto-humans provided a strong selective advantage to individuals with brains capable of efficiently transferring tasks in this way. Thus, the shift from quadrupedal to bipedal locomotion may have driven the rapid evolution of distinctive features of human neuronal functioning. We review recent studies of functional neuroanatomy that bear upon this hypothesis, and identify ways to test our ideas.
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Directory of Open Access Journals (Sweden)
Belinda J. Liddell
2016-06-01
Full Text Available A significant body of literature documents the neural mechanisms involved in the development and maintenance of posttraumatic stress disorder (PTSD. However, there is very little empirical work considering the influence of culture on these underlying mechanisms. Accumulating cultural neuroscience research clearly indicates that cultural differences in self-representation modulate many of the same neural processes proposed to be aberrant in PTSD. The objective of this review paper is to consider how culture may impact on the neural mechanisms underlying PTSD. We first outline five key affective and cognitive functions and their underlying neural correlates that have been identified as being disrupted in PTSD: (1 fear dysregulation; (2 attentional biases to threat; (3 emotion and autobiographical memory; (4 self-referential processing; and (5 attachment and interpersonal processing. Second, we consider prominent cultural theories and review the empirical research that has demonstrated the influence of cultural variations in self-representation on the neural substrates of these same five affective and cognitive functions. Finally, we propose a conceptual model that suggests that these five processes have major relevance to considering how culture may influence the neural processes underpinning PTSD. Highlights of the article:
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Liddell, Belinda J; Jobson, Laura
2016-01-01
A significant body of literature documents the neural mechanisms involved in the development and maintenance of posttraumatic stress disorder (PTSD). However, there is very little empirical work considering the influence of culture on these underlying mechanisms. Accumulating cultural neuroscience research clearly indicates that cultural differences in self-representation modulate many of the same neural processes proposed to be aberrant in PTSD. The objective of this review paper is to consider how culture may impact on the neural mechanisms underlying PTSD. We first outline five key affective and cognitive functions and their underlying neural correlates that have been identified as being disrupted in PTSD: (1) fear dysregulation; (2) attentional biases to threat; (3) emotion and autobiographical memory; (4) self-referential processing; and (5) attachment and interpersonal processing. Second, we consider prominent cultural theories and review the empirical research that has demonstrated the influence of cultural variations in self-representation on the neural substrates of these same five affective and cognitive functions. Finally, we propose a conceptual model that suggests that these five processes have major relevance to considering how culture may influence the neural processes underpinning PTSD.
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Takiyama, Ken
2017-12-01
How neural adaptation affects neural information processing (i.e. the dynamics and equilibrium state of neural activities) is a central question in computational neuroscience. In my previous works, I analytically clarified the dynamics and equilibrium state of neural activities in a ring-type neural network model that is widely used to model the visual cortex, motor cortex, and several other brain regions. The neural dynamics and the equilibrium state in the neural network model corresponded to a Bayesian computation and statistically optimal multiple information integration, respectively, under a biologically inspired condition. These results were revealed in an analytically tractable manner; however, adaptation effects were not considered. Here, I analytically reveal how the dynamics and equilibrium state of neural activities in a ring neural network are influenced by spike-frequency adaptation (SFA). SFA is an adaptation that causes gradual inhibition of neural activity when a sustained stimulus is applied, and the strength of this inhibition depends on neural activities. I reveal that SFA plays three roles: (1) SFA amplifies the influence of external input in neural dynamics; (2) SFA allows the history of the external input to affect neural dynamics; and (3) the equilibrium state corresponds to the statistically optimal multiple information integration independent of the existence of SFA. In addition, the equilibrium state in a ring neural network model corresponds to the statistically optimal integration of multiple information sources under biologically inspired conditions, independent of the existence of SFA.
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International Nuclear Information System (INIS)
Zare, Mansour; Vahdati Khaki, Jalil
2012-01-01
Highlights: ► ANNs and ANFIS fairly predicted UTS and YS of warm compacted molybdenum prealloy. ► Effects of composition, temperature, compaction pressure on output were studied. ► ANFIS model was in better agreement with experimental data from published article. ► Sintering temperature had the most significant effect on UTS and YS. -- Abstract: Predictive models using artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) were successfully developed to predict yield strength and ultimate tensile strength of warm compacted 0.85 wt.% molybdenum prealloy samples. To construct these models, 48 different experimental data were gathered from the literature. A portion of the data set was randomly chosen to train both ANN with back propagation (BP) learning algorithm and ANFIS model with Gaussian membership function and the rest was implemented to verify the performance of the trained network against the unseen data. The generalization capability of the networks was also evaluated by applying new input data within the domain covered by the training pattern. To compare the obtained results, coefficient of determination (R 2 ), root mean squared error (RMSE) and average absolute error (AAE) indexes were chosen and calculated for both of the models. The results showed that artificial neural network and adaptive neuro-fuzzy system were both potentially strong for prediction of the mechanical properties of warm compacted 0.85 wt.% molybdenum prealloy; however, the proposed ANFIS showed better performance than the ANN model. Also, the ANFIS model was subjected to a sensitivity analysis to find the significant inputs affecting mechanical properties of the samples.
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Photosensitive-polyimide based method for fabricating various neural electrode architectures
Directory of Open Access Journals (Sweden)
Yasuhiro X Kato
2012-06-01
Full Text Available An extensive photosensitive polyimide (PSPI-based method for designing and fabricating various neural electrode architectures was developed. The method aims to broaden the design flexibility and expand the fabrication capability for neural electrodes to improve the quality of recorded signals and integrate other functions. After characterizing PSPI’s properties for micromachining processes, we successfully designed and fabricated various neural electrodes even on a non-flat substrate using only one PSPI as an insulation material and without the time-consuming dry etching processes. The fabricated neural electrodes were an electrocorticogram electrode, a mesh intracortical electrode with a unique lattice-like mesh structure to fixate neural tissue, and a guide cannula electrode with recording microelectrodes placed on the curved surface of a guide cannula as a microdialysis probe. In vivo neural recordings using anesthetized rats demonstrated that these electrodes can be used to record neural activities repeatedly without any breakage and mechanical failures, which potentially promises stable recordings for long periods of time. These successes make us believe that this PSPI-based fabrication is a powerful method, permitting flexible design and easy optimization of electrode architectures for a variety of electrophysiological experimental research with improved neural recording performance.
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Rana computatrix to human language: towards a computational neuroethology of language evolution.
Arbib, Michael A
2003-10-15
Walter's Machina speculatrix inspired the name Rana computatrix for a family of models of visuomotor coordination in the frog, which contributed to the development of computational neuroethology. We offer here an 'evolutionary' perspective on models in the same tradition for rat, monkey and human. For rat, we show how the frog-like taxon affordance model provides a basis for the spatial navigation mechanisms that involve the hippocampus and other brain regions. For monkey, we recall two models of neural mechanisms for visuomotor coordination. The first, for saccades, shows how interactions between the parietal and frontal cortex augment superior colliculus seen as the homologue of frog tectum. The second, for grasping, continues the theme of parieto-frontal interactions, linking parietal affordances to motor schemas in premotor cortex. It further emphasizes the mirror system for grasping, in which neurons are active both when the monkey executes a specific grasp and when it observes a similar grasp executed by others. The model of human-brain mechanisms is based on the mirror-system hypothesis of the evolution of the language-ready brain, which sees the human Broca's area as an evolved extension of the mirror system for grasping.
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Cors, Josep; Llibre, Jaume; Korobeinikov, Andrei
2015-01-01
The two parts of the present volume contain extended conference abstracts corresponding to selected talks given by participants at the "Conference on Hamiltonian Systems and Celestial Mechanics 2014" (HAMSYS2014) (15 abstracts) and at the "Workshop on Virus Dynamics and Evolution" (12 abstracts), both held at the Centre de Recerca Matemàtica (CRM) in Barcelona from June 2nd to 6th, 2014, and from June 23th to 27th, 2014, respectively. Most of them are brief articles, containing preliminary presentations of new results not yet published in regular research journals. The articles are the result of a direct collaboration between active researchers in the area after working in a dynamic and productive atmosphere. The first part is about Central Configurations, Periodic Orbits and Hamiltonian Systems with applications to Celestial Mechanics – a very modern and active field of research. The second part is dedicated to mathematical methods applied to viral dynamics and evolution. Mathematical modelling of biologi...
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New Insights on Neurobiological Mechanisms underlying Alcohol Addiction
Cui, Changhai; Noronha, Antonio; Morikawa, Hitoshi; Alvarez, Veronica A.; Stuber, Garret D.; Szumlinski, Karen K.; Kash, Thomas L.; Roberto, Marisa; Wilcox, Mark V.
2012-01-01
Alcohol dependence/addiction is mediated by complex neural mechanisms that involve multiple brain circuits and neuroadaptive changes in a variety of neurotransmitter and neuropeptide systems. Although recent studies have provided substantial information on the neurobiological mechanisms that drive alcohol drinking behavior, significant challenges remain in understanding how alcohol-induced neuroadaptations occur and how different neurocircuits and pathways cross-talk. This review article highlights recent progress in understanding neural mechanisms of alcohol addiction from the perspectives of the development and maintenance of alcohol dependence. It provides insights on cross talks of different mechanisms and reviews the latest studies on metaplasticity, structural plasticity, interface of reward and stress pathways, and cross-talk of different neural signaling systems involved in binge-like drinking and alcohol dependence. PMID:23159531
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Neural mechanisms of the influence of popularity on adolescent ratings of music.
Berns, Gregory S; Capra, C Monica; Moore, Sara; Noussair, Charles
2010-02-01
It is well-known that social influences affect consumption decisions. We used functional magnetic resonance imaging (fMRI) to elucidate the neural mechanisms associated with social influence with regard to a common consumer good: music. Our study population was adolescents, age 12-17. Music is a common purchase in this age group, and it is widely believed that adolescent behavior is influenced by perceptions of popularity in their reference group. Using 15-s clips of songs from MySpace.com, we obtained behavioral measures of preferences and neurobiological responses to the songs. The data were gathered with, and without, the overall popularity of the song revealed. Song popularity had a significant effect on the participants' likability ratings of the songs. fMRI results showed a strong correlation between the participants' rating and activity in the caudate nucleus, a region previously implicated in reward-driven actions. The tendency to change one's evaluation of a song was positively correlated with activation in the anterior insula and anterior cingulate, two regions that are associated with physiological arousal and negative affective states. Sensitivity to popularity was linked to lower activation levels in the middle temporal gyrus, suggesting a lower depth of musical semantic processing. Our results suggest that a principal mechanism whereby popularity ratings affect consumer choice is through the anxiety generated by the mismatch between one's own preferences and others'. This mismatch anxiety motivates people to switch their choices in the direction of the consensus. Our data suggest that this is a major force behind the conformity observed in music tastes in some teenagers. Copyright (c) 2009 Elsevier Inc. All rights reserved.
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Suzuki, Takumi; Sato, Makoto
2017-11-15
Diversification of neuronal types is key to establishing functional variations in neural circuits. The first critical step to generate neuronal diversity is to organize the compartmental domains of developing brains into spatially distinct neural progenitor pools. Neural progenitors in each pool then generate a unique set of diverse neurons through specific spatiotemporal specification processes. In this review article, we focus on an additional mechanism, 'inter-progenitor pool wiring', that further expands the diversity of neural circuits. After diverse types of neurons are generated in one progenitor pool, a fraction of these neurons start migrating toward a remote brain region containing neurons that originate from another progenitor pool. Finally, neurons of different origins are intermingled and eventually form complex but precise neural circuits. The developing cerebral cortex of mammalian brains is one of the best examples of inter-progenitor pool wiring. However, Drosophila visual system development has revealed similar mechanisms in invertebrate brains, suggesting that inter-progenitor pool wiring is an evolutionarily conserved strategy that expands neural circuit diversity. Here, we will discuss how inter-progenitor pool wiring is accomplished in mammalian and fly brain systems. Copyright © 2017 Elsevier Inc. All rights reserved.
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Li, Yongcheng; Sun, Rong; Wang, Yuechao; Li, Hongyi; Zheng, Xiongfei
2016-01-01
We propose the architecture of a novel robot system merging biological and artificial intelligence based on a neural controller connected to an external agent. We initially built a framework that connected the dissociated neural network to a mobile robot system to implement a realistic vehicle. The mobile robot system characterized by a camera and two-wheeled robot was designed to execute the target-searching task. We modified a software architecture and developed a home-made stimulation generator to build a bi-directional connection between the biological and the artificial components via simple binomial coding/decoding schemes. In this paper, we utilized a specific hierarchical dissociated neural network for the first time as the neural controller. Based on our work, neural cultures were successfully employed to control an artificial agent resulting in high performance. Surprisingly, under the tetanus stimulus training, the robot performed better and better with the increasement of training cycle because of the short-term plasticity of neural network (a kind of reinforced learning). Comparing to the work previously reported, we adopted an effective experimental proposal (i.e. increasing the training cycle) to make sure of the occurrence of the short-term plasticity, and preliminarily demonstrated that the improvement of the robot's performance could be caused independently by the plasticity development of dissociated neural network. This new framework may provide some possible solutions for the learning abilities of intelligent robots by the engineering application of the plasticity processing of neural networks, also for the development of theoretical inspiration for the next generation neuro-prostheses on the basis of the bi-directional exchange of information within the hierarchical neural networks.
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Directory of Open Access Journals (Sweden)
Yongcheng Li
Full Text Available We propose the architecture of a novel robot system merging biological and artificial intelligence based on a neural controller connected to an external agent. We initially built a framework that connected the dissociated neural network to a mobile robot system to implement a realistic vehicle. The mobile robot system characterized by a camera and two-wheeled robot was designed to execute the target-searching task. We modified a software architecture and developed a home-made stimulation generator to build a bi-directional connection between the biological and the artificial components via simple binomial coding/decoding schemes. In this paper, we utilized a specific hierarchical dissociated neural network for the first time as the neural controller. Based on our work, neural cultures were successfully employed to control an artificial agent resulting in high performance. Surprisingly, under the tetanus stimulus training, the robot performed better and better with the increasement of training cycle because of the short-term plasticity of neural network (a kind of reinforced learning. Comparing to the work previously reported, we adopted an effective experimental proposal (i.e. increasing the training cycle to make sure of the occurrence of the short-term plasticity, and preliminarily demonstrated that the improvement of the robot's performance could be caused independently by the plasticity development of dissociated neural network. This new framework may provide some possible solutions for the learning abilities of intelligent robots by the engineering application of the plasticity processing of neural networks, also for the development of theoretical inspiration for the next generation neuro-prostheses on the basis of the bi-directional exchange of information within the hierarchical neural networks.
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Deciphering Neural Codes of Memory during Sleep
Chen, Zhe; Wilson, Matthew A.
2017-01-01
Memories of experiences are stored in the cerebral cortex. Sleep is critical for consolidating hippocampal memory of wake experiences into the neocortex. Understanding representations of neural codes of hippocampal-neocortical networks during sleep would reveal important circuit mechanisms on memory consolidation, and provide novel insights into memory and dreams. Although sleep-associated ensemble spike activity has been investigated, identifying the content of memory in sleep remains challenging. Here, we revisit important experimental findings on sleep-associated memory (i.e., neural activity patterns in sleep that reflect memory processing) and review computational approaches for analyzing sleep-associated neural codes (SANC). We focus on two analysis paradigms for sleep-associated memory, and propose a new unsupervised learning framework (“memory first, meaning later”) for unbiased assessment of SANC. PMID:28390699
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Neural mechanism of deficits in Chinese developmental dyslexia%汉语发展性阅读障碍缺陷的神经机制
Institute of Scientific and Technical Information of China (English)
赵婧; 张逸玮; 毕鸿燕
2015-01-01
Objective To study on the neural mechanism of deficits in Chinese developmental dyslexia from the aspects of the phonological processing,orthographic skills,visual magnocellular function and cerebellum function.Methods Critical words in Chinese and English (e.g.dyslexia,reading development,Chinese,neural) and formula (e.g.Chinese and (reading development) and (neural or neuroimage or fMRI or ERP or brain area) related with the present topic were searched among the article abstracts in Chinese and foreign databases (e.g.CNKI,Pubmed,Sciencedirect) from July to December,2014.Results Fifty-two relevant articles were gained access to the database.Referring to the present topic,research on the neural mechanism of dyslexia with neuroimaging technique was reserved,while the studies in which the reading impairment of the participants was caused by acquired factors were eliminated.Finally,thirty-three valid articles were retained.Conclusion According to previous studies,although there might be similarities in cognitive deficits of dyslexia between alphabetic languages and Chinese,it was still found that the Chinese children with developmental dyslexia exhibited abnormal neural activities and impaired brain structures in areas associated with Chinese phonology (i.e.left middle frontal gyrus,which was different from the left inferior fiontal gyrus always related with phonological processing in alphabetic languages) and orthographic skills (right occipitotemporal areas which was responsible for the visuospatial processing),revealing language specificity of Chinese to some extent.However,some other studies reported the similarities in neural mechanisms of dyslexia across languages.Therefore,more studies were required to further examine the crosscultural mechanism of the neural activity regarding the developmental dyslexia.Meanwhile,researches on the aspects of general perception showed Chinese dyslexic individuals had deficits in visual magnocellular function,and cerebellum
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Energy Technology Data Exchange (ETDEWEB)
Liu, Dong, E-mail: ld20501@126.com; Chen, Chuansong, E-mail: chencs@sdnu.edu.cn; Man, Baoyuan, E-mail: byman@sdnu.edu.cn; Meng, Xue; Sun, Yanna, E-mail: sunyuannaa@163.com; Li, Feifei
2016-08-15
Highlights: • Investigate the evolution and succession of three types of fs-laser induced periodic surface structures (FLIPSSs). • Achieve the laser processing window of each type of the FLIPSS. • Explain the formation and evolvement of the ripple structure in the respective of surface plasma wave (SPW). • Ascribe the interaction between the transmitted laser and the reflected laser at the two surfaces of the biconvex lens to the formation of ring structure. - Abstract: This work investigates the femtosencond laser (fs-laser) induced periodical surface structures (FLIPSS) on titanium plate including the concentric rings, microgrooves and subwavelength ripples. The evolution of the three types of the structures at different laser fluence and shot number is investigated experimentally in detail. The competition mechanisms exist among the different FLIPSS. A processing window for each resulting FLIPSS is obtained. In order to give an overall understanding of the FLIPSS, the formation mechanisms of each type of FLIPSS are discussed. The formation of the ripples is well explained by the propagating of the surface plasma wave (SPW) on the air/Ti interface. The evolutions of the ripple distribution are well understood according to this model as well. It is concluded that the interaction of the scattered wave of the laser light with the surface wave is concluded to give rise to the microgroove structure. According to our observation, the shape of the concentric rings does not change with the variation of the laser fluence and pulse number. The structure could be originated from the optical interference between the transmitted and reflected laser beams by the two surfaces of the biconvex lens. This investigation could not only make a further understanding of the formations of FLIPSS but also provide the possibility to control the surface morphologies in laser processing.
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Neural Mechanisms Underlying Cross-Modal Phonetic Encoding.
Shahin, Antoine J; Backer, Kristina C; Rosenblum, Lawrence D; Kerlin, Jess R
2018-02-14
Audiovisual (AV) integration is essential for speech comprehension, especially in adverse listening situations. Divergent, but not mutually exclusive, theories have been proposed to explain the neural mechanisms underlying AV integration. One theory advocates that this process occurs via interactions between the auditory and visual cortices, as opposed to fusion of AV percepts in a multisensory integrator. Building upon this idea, we proposed that AV integration in spoken language reflects visually induced weighting of phonetic representations at the auditory cortex. EEG was recorded while male and female human subjects watched and listened to videos of a speaker uttering consonant vowel (CV) syllables /ba/ and /fa/, presented in Auditory-only, AV congruent or incongruent contexts. Subjects reported whether they heard /ba/ or /fa/. We hypothesized that vision alters phonetic encoding by dynamically weighting which phonetic representation in the auditory cortex is strengthened or weakened. That is, when subjects are presented with visual /fa/ and acoustic /ba/ and hear /fa/ ( illusion-fa ), the visual input strengthens the weighting of the phone /f/ representation. When subjects are presented with visual /ba/ and acoustic /fa/ and hear /ba/ ( illusion-ba ), the visual input weakens the weighting of the phone /f/ representation. Indeed, we found an enlarged N1 auditory evoked potential when subjects perceived illusion-ba , and a reduced N1 when they perceived illusion-fa , mirroring the N1 behavior for /ba/ and /fa/ in Auditory-only settings. These effects were especially pronounced in individuals with more robust illusory perception. These findings provide evidence that visual speech modifies phonetic encoding at the auditory cortex. SIGNIFICANCE STATEMENT The current study presents evidence that audiovisual integration in spoken language occurs when one modality (vision) acts on representations of a second modality (audition). Using the McGurk illusion, we show
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Zhang, Hai-Tao; Mo, Yun-Fei; Liu, Rang-Su; Tian, Ze-An; Liu, Hai-Rong; Hou, Zhao-Yang; Zhou, Li-Li; Liang, Yong-Chao; Peng, Ping
2018-03-01
To deeply understand the effects of high pressure on microstructural evolutions and crystallization mechanisms of liquid metal Ni during solidification process, MD simulation studies have been performed under 7 pressures of 0 ˜ 30 GPa, at cooling rate of 1.0 × 1011 K s-1. Adopting several microstructural analyzing methods, especially the cluster-type index method (CTIM-2) to analyze the local microstructures in the system. It is found that the pressure has important influence on the formation and evolution of microstructures, especially of the main basic clusters in the system. All the simulation systems are directly solidified into crystal structures, and the 1421, 1422, 1441 and 1661 bond-types, as well the FCC (12 0 0 0 12 0), HCP (12 0 0 0 6 6) and BCC (14 6 0 8 0 0) clusters play a key role in the microstructure transitions from liquid to crystal structures. The crystallization temperature T c is enhanced almost linearly with the increase of pressure. Highly interesting, it is found for the first time that there is an important phase transformation point from FCC to BCC structures between 20 ˜ 22.5 GPa during the solidification processes from the same initial liquid system at the same cooling rate. And the effect of increasing pressure is similar to that of decreasing cooling rate for the phase transformation of microstructures during solidification process of liquid metal Ni system, though they have different concrete effecting mechanisms.
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Race modulates neural activity during imitation
Losin, Elizabeth A. Reynolds; Iacoboni, Marco; Martin, Alia; Cross, Katy A.; Dapretto, Mirella
2014-01-01
Imitation plays a central role in the acquisition of culture. People preferentially imitate others who are self-similar, prestigious or successful. Because race can indicate a person's self-similarity or status, race influences whom people imitate. Prior studies of the neural underpinnings of imitation have not considered the effects of race. Here we measured neural activity with fMRI while European American participants imitated meaningless gestures performed by actors of their own race, and two racial outgroups, African American, and Chinese American. Participants also passively observed the actions of these actors and their portraits. Frontal, parietal and occipital areas were differentially activated while participants imitated actors of different races. More activity was present when imitating African Americans than the other racial groups, perhaps reflecting participants' reported lack of experience with and negative attitudes towards this group, or the group's lower perceived social status. This pattern of neural activity was not found when participants passively observed the gestures of the actors or simply looked at their faces. Instead, during face-viewing neural responses were overall greater for own-race individuals, consistent with prior race perception studies not involving imitation. Our findings represent a first step in elucidating neural mechanisms involved in cultural learning, a process that influences almost every aspect of our lives but has thus far received little neuroscientific study. PMID:22062193
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Neural networks for genetic epidemiology: past, present, and future
Directory of Open Access Journals (Sweden)
Motsinger-Reif Alison A
2008-07-01
Full Text Available Abstract During the past two decades, the field of human genetics has experienced an information explosion. The completion of the human genome project and the development of high throughput SNP technologies have created a wealth of data; however, the analysis and interpretation of these data have created a research bottleneck. While technology facilitates the measurement of hundreds or thousands of genes, statistical and computational methodologies are lacking for the analysis of these data. New statistical methods and variable selection strategies must be explored for identifying disease susceptibility genes for common, complex diseases. Neural networks (NN are a class of pattern recognition methods that have been successfully implemented for data mining and prediction in a variety of fields. The application of NN for statistical genetics studies is an active area of research. Neural networks have been applied in both linkage and association analysis for the identification of disease susceptibility genes. In the current review, we consider how NN have been used for both linkage and association analyses in genetic epidemiology. We discuss both the successes of these initial NN applications, and the questions that arose during the previous studies. Finally, we introduce evolutionary computing strategies, Genetic Programming Neural Networks (GPNN and Grammatical Evolution Neural Networks (GENN, for using NN in association studies of complex human diseases that address some of the caveats illuminated by previous work.
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Burst firing enhances neural output correlation
Directory of Open Access Journals (Sweden)
Ho Ka eChan
2016-05-01
Full Text Available Neurons communicate and transmit information predominantly through spikes. Given that experimentally observed neural spike trains in a variety of brain areas can be highly correlated, it is important to investigate how neurons process correlated inputs. Most previous work in this area studied the problem of correlation transfer analytically by making significant simplifications on neural dynamics. Temporal correlation between inputs that arises from synaptic filtering, for instance, is often ignored when assuming that an input spike can at most generate one output spike. Through numerical simulations of a pair of leaky integrate-and-fire (LIF neurons receiving correlated inputs, we demonstrate that neurons in the presence of synaptic filtering by slow synapses exhibit strong output correlations. We then show that burst firing plays a central role in enhancing output correlations, which can explain the above-mentioned observation because synaptic filtering induces bursting. The observed changes of correlations are mostly on a long time scale. Our results suggest that other features affecting the prevalence of neural burst firing in biological neurons, e.g., adaptive spiking mechanisms, may play an important role in modulating the overall level of correlations in neural networks.
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Mechanisms of odor-tracking: multiple sensors for enhanced perception and behavior
Directory of Open Access Journals (Sweden)
Alex Gomez-Marin
2010-03-01
Full Text Available Early in evolution, the ability to sense and respond to changing environments must have provided a critical survival advantage to living organisms. From bacteria and worms to flies and vertebrates, sophisticated mechanisms have evolved to enhance odor detection and localization. Here, we review several modes of chemotaxis. We further consider the relevance of a striking and recurrent motif in the organization of invertebrate and vertebrate sensory systems, namely the existence of two symmetrical olfactory sensors. By combining our current knowledge about the olfactory circuits of larval and adult Drosophila, we examine the molecular and neural mechanisms underlying robust olfactory perception and extend these analyses to recent behavioral studies addressing the relevance and function of bilateral olfactory input for gradient detection. Finally, using a comparative theoretical approach based on Braitenberg’s vehicles, we speculate about the relationships between anatomy, circuit architecture and stereotypical orientation behaviors.
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Energy Technology Data Exchange (ETDEWEB)
Hoekmark, Harald; Loennqvist, Margareta; Faelth, Billy (Clay Technology AB, Lund (Sweden))
2010-05-15
The present report addresses aspects of the Thermo-Hydro-Mechanical (THM) evolution of the repository host rock that are of potential importance to the SR-Site safety assessment of a KBS-3 type spent nuclear fuel repository. The report covers the evolution of rock temperatures, rock stresses, pore pressures and fracture transmissivities during the excavation and operational phase, the temperate phase and a glacial cycle on different scales. The glacial cycle is assumed to include a period of pre-glacial permafrost with lowered temperatures and with increased pore pressures in the rock beneath the impermeable permafrost layer. The report also addresses the question of the peak temperature reached during the early temperate phase in the bentonite buffer surrounding the spent fuel canisters. The main text is devoted exclusively to the projected THM evolution of the rock at the Forsmark site in central Sweden. The focus is on the potential for stress-induced failures, i.e. spalling, in the walls of the deposition holes and on changes in the transmissivity of fractures and deformation zones. All analyses are conducted by a combination of numerical tools (3DEC) and analytical solutions. All phases are treated separately and independently of each other, although in reality construction will overlap with heat generation because of the step-by-step excavation/deposition approach with some 50 years between deposition of the first and last canisters. It is demonstrated here that the thermal and thermo-mechanical evolution of the near-field will be independent of heat generated by canisters that were deposited in the past, provided that deposition is made in an orderly fashion, deposition area by deposition area. Peak temperatures and near-field stresses can, consequently, be calculated as if all canisters were deposited simultaneously. The canister and tunnel spacing is specified such that the peak buffer temperature will not exceed 100 deg C in any deposition hole, i.e. not
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A Neural Network Approach to Muon Triggering in ATLAS
Livneh, Ran; CERN. Geneva
2007-01-01
The extremely high rate of events that will be produced in the future Large Hadron Collider requires the triggering mechanism to make precise decisions in a few nano-seconds. This poses a complicated inverse problem, arising from the inhomogeneous nature of the magnetic fields in ATLAS. This thesis presents a study of an application of Artificial Neural Networks to the muon triggering problem in the ATLAS end-cap. A comparison with realistic results from the ATLAS first level trigger simulation was in favour of the neural network, but this is mainly due to superior resolution available off-line. Other options for applying a neural network to this problem are discussed.
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Lithium - an update on the mechanisms of action. Part two: neural ...
African Journals Online (AJOL)
... has a complicated multitude of diverse effects in the human nervous system. This new data is helping us understand the neurobiology of bipolar disorder. The focus of this review will be to distil this new knowledge.This, the second of a two part review will focus principally on neural effects and neuroanatomical substrates.
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Temporal-pattern learning in neural models
Genís, Carme Torras
1985-01-01
While the ability of animals to learn rhythms is an unquestionable fact, the underlying neurophysiological mechanisms are still no more than conjectures. This monograph explores the requirements of such mechanisms, reviews those previously proposed and postulates a new one based on a direct electric coding of stimulation frequencies. Experi mental support for the option taken is provided both at the single neuron and neural network levels. More specifically, the material presented divides naturally into four parts: a description of the experimental and theoretical framework where this work becomes meaningful (Chapter 2), a detailed specifica tion of the pacemaker neuron model proposed together with its valida tion through simulation (Chapter 3), an analytic study of the behavior of this model when submitted to rhythmic stimulation (Chapter 4) and a description of the neural network model proposed for learning, together with an analysis of the simulation results obtained when varying seve ral factors r...
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Effective evolution equations from many-body quantum mechanics
International Nuclear Information System (INIS)
Benedikter, Niels Patriz
2014-01-01
Systems of interest in physics often consist of a very large number of interacting particles. In certain physical regimes, effective non-linear evolution equations are commonly used as an approximation for making predictions about the time-evolution of such systems. Important examples are Bose-Einstein condensates of dilute Bose gases and degenerate Fermi gases. While the effective equations are well-known in physics, a rigorous justification is very difficult. However, a rigorous derivation is essential to precisely understand the range and the limits of validity and the quality of the approximation. In this thesis, we prove that the time evolution of Bose-Einstein condensates in the Gross-Pitaevskii regime can be approximated by the time-dependent Gross-Pitaevskii equation, a cubic non-linear Schroedinger equation. We then turn to fermionic systems and prove that the evolution of a degenerate Fermi gas can be approximated by the time-dependent Hartree-Fock equation (TDHF) under certain assumptions on the semiclassical structure of the initial data. Finally, we extend the latter result to fermions with relativistic kinetic energy. All our results provide explicit bounds on the error as the number of particles becomes large. A crucial methodical insight on bosonic systems is that correlations can be modeled by Bogolyubov transformations. We construct initial data appropriate for the Gross-Pitaevskii regime using a Bogolyubov transformation acting on a coherent state, which amounts to studying squeezed coherent states. As a crucial insight for fermionic systems, we point out a semiclassical structure in states close to the ground state of fermions in a trap. As a convenient language for studying the dynamics of fermionic systems, we use particle-hole transformations.
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Neural underpinnings of divergent production of rules in numerical analogical reasoning.
Wu, Xiaofei; Jung, Rex E; Zhang, Hao
2016-05-01
Creativity plays an important role in numerical problem solving. Although the neural underpinnings of creativity have been studied over decades, very little is known about neural mechanisms of the creative process that relates to numerical problem solving. In the present study, we employed a numerical analogical reasoning task with functional Magnetic Resonance Imaging (fMRI) to investigate the neural correlates of divergent production of rules in numerical analogical reasoning. Participants performed two tasks: a multiple solution analogical reasoning task and a single solution analogical reasoning task. Results revealed that divergent production of rules involves significant activations at Brodmann area (BA) 10 in the right middle frontal cortex, BA 40 in the left inferior parietal lobule, and BA 8 in the superior frontal cortex. The results suggest that right BA 10 and left BA 40 are involved in the generation of novel rules, and BA 8 is associated with the inhibition of initial rules in numerical analogical reasoning. The findings shed light on the neural mechanisms of creativity in numerical processing. Copyright © 2016 Elsevier B.V. All rights reserved.
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Energy Technology Data Exchange (ETDEWEB)
Cruz-Gandarilla, Francisco, E-mail: fcruz@ipn.mx [Instituto Politécnico Nacional, Escuela Superior de Física y Matemáticas, Edificio 9, U.P.A.L.M., Zacatenco, Del. G. A. Madero, México, D.F. C.P. 07738, México (Mexico); Salcedo-Garrido, Ana María, E-mail: salcedo_marya@yahoo.com.mx [Instituto Politécnico Nacional, Escuela Superior de Física y Matemáticas, Edificio 9, U.P.A.L.M., Zacatenco, Del. G. A. Madero, México, D.F. C.P. 07738, México (Mexico); Bolmaro, Raúl E., E-mail: bolmaro@ifir-conicet.gov.ar [Instituto de Física Rosario, Consejo Nacional de Investigaciones Científicas y Técnicas-CONICET, Universidad Nacional de Rosario, Ocampo y Esmeralda, 2000 Rosario (Argentina); Baudin, Thierry, E-mail: thierry.baudin@u-psud.fr [CNRS, UMR 8182, ICMMO, Lab. de Synthèse, Propriétés et Modélisation des Matériaux, Université de Paris-Sud, Orsay F-91405 (France); De Vincentis, Natalia S., E-mail: devincentis@ifir-conicet.gov.ar [Instituto de Física Rosario, Consejo Nacional de Investigaciones Científicas y Técnicas-CONICET, Universidad Nacional de Rosario, Ocampo y Esmeralda, 2000 Rosario (Argentina); and others
2016-08-15
Accumulative Roll Bonding (ARB) is one of the so-called severe plastic deformation (SPD) processes, allowing the production of metals and alloys with ultrafine (micro-nano) structures. Materials with ultrafine grains present attractive properties like the simultaneous increase in strength and ductility. Our interest in these materials is focused on their microstructural evolution during ARB processing, eventually responsible for the enhancement of those mechanical properties. In the current work we follow the evolution of the microstructure in an interstitial-free (IF) steel deformed by ARB after consecutive processing cycles, by means of Electron BackScatter Diffraction (EBSD) and X-ray diffraction (XRD). Particularly, we present results related to texture, grain (GS) and domain sizes, grain boundary character, density of Geometrically Necessary Dislocations (GND), Grain Orientation Spread (GOS), lattice parameters, microstrain, dislocation density and their spatial arrangement. After 5 ARB cycles the system shows a microstructure constituted mainly by submicrometric grains with high angle boundaries and low presence of dislocations inside the grains. - Highlights: •The evolution of microstructure is followed simultaneously by using GAM, GOS and GND (EBSD) and XRD. •LAGBs and subgrains disappear after few cycles SSDs and HAGBs persist at the end. •Dynamic recrystallization counterbalances dislocation arrays and diminishes hardening rate. •Grain size stabilization is revealed as a mechanism for increasing ductility after few ARB cycles.
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Neural dynamics of motion processing and speed discrimination.
Chey, J; Grossberg, S; Mingolla, E
1998-09-01
A neural network model of visual motion perception and speed discrimination is presented. The model shows how a distributed population code of speed tuning, that realizes a size-speed correlation, can be derived from the simplest mechanisms whereby activations of multiple spatially short-range filters of different size are transformed into speed-turned cell responses. These mechanisms use transient cell responses to moving stimuli, output thresholds that covary with filter size, and competition. These mechanisms are proposed to occur in the V1-->MT cortical processing stream. The model reproduces empirically derived speed discrimination curves and simulates data showing how visual speed perception and discrimination can be affected by stimulus contrast, duration, dot density and spatial frequency. Model motion mechanisms are analogous to mechanisms that have been used to model 3-D form and figure-ground perception. The model forms the front end of a larger motion processing system that has been used to simulate how global motion capture occurs, and how spatial attention is drawn to moving forms. It provides a computational foundation for an emerging neural theory of 3-D form and motion perception.
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Central neural pathways for thermoregulation
Morrison, Shaun F.; Nakamura, Kazuhiro
2010-01-01
Central neural circuits orchestrate a homeostatic repertoire to maintain body temperature during environmental temperature challenges and to alter body temperature during the inflammatory response. This review summarizes the functional organization of the neural pathways through which cutaneous thermal receptors alter thermoregulatory effectors: the cutaneous circulation for heat loss, the brown adipose tissue, skeletal muscle and heart for thermogenesis and species-dependent mechanisms (sweating, panting and saliva spreading) for evaporative heat loss. These effectors are regulated by parallel but distinct, effector-specific neural pathways that share a common peripheral thermal sensory input. The thermal afferent circuits include cutaneous thermal receptors, spinal dorsal horn neurons and lateral parabrachial nucleus neurons projecting to the preoptic area to influence warm-sensitive, inhibitory output neurons which control thermogenesis-promoting neurons in the dorsomedial hypothalamus that project to premotor neurons in the rostral ventromedial medulla, including the raphe pallidus, that descend to provide the excitation necessary to drive thermogenic thermal effectors. A distinct population of warm-sensitive preoptic neurons controls heat loss through an inhibitory input to raphe pallidus neurons controlling cutaneous vasoconstriction. PMID:21196160
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Using brain stimulation to disentangle neural correlates of conscious vision.
de Graaf, Tom A; Sack, Alexander T
2014-01-01
Research into the neural correlates of consciousness (NCCs) has blossomed, due to the advent of new and increasingly sophisticated brain research tools. Neuroimaging has uncovered a variety of brain processes that relate to conscious perception, obtained in a range of experimental paradigms. But methods such as functional magnetic resonance imaging or electroencephalography do not always afford inference on the functional role these brain processes play in conscious vision. Such empirical NCCs could reflect neural prerequisites, neural consequences, or neural substrates of a conscious experience. Here, we take a closer look at the use of non-invasive brain stimulation (NIBS) techniques in this context. We discuss and review how NIBS methodology can enlighten our understanding of brain mechanisms underlying conscious vision by disentangling the empirical NCCs.
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Stoddard, Joel; Tseng, Wan-Ling; Kim, Pilyoung; Chen, Gang; Yi, Jennifer; Donahue, Laura; Brotman, Melissa A; Towbin, Kenneth E; Pine, Daniel S; Leibenluft, Ellen
2017-01-01
Psychiatric comorbidity complicates clinical care and confounds efforts to elucidate the pathophysiology of commonly occurring symptoms in youths. To our knowledge, few studies have simultaneously assessed the effect of 2 continuously distributed traits on brain-behavior relationships in children with psychopathology. To determine shared and unique effects of 2 major dimensions of child psychopathology, irritability and anxiety, on neural responses to facial emotions during functional magnetic resonance imaging. Cross-sectional functional magnetic resonance imaging study in a large, well-characterized clinical sample at a research clinic at the National Institute of Mental Health. The referred sample included youths ages 8 to 17 years, 93 youths with anxiety, disruptive mood dysregulation, and/or attention-deficit/hyperactivity disorders and 22 healthy youths. The child's irritability and anxiety were rated by both parent and child on the Affective Reactivity Index and Screen for Child Anxiety Related Disorders, respectively. Using functional magnetic resonance imaging, neural response was measured across the brain during gender labeling of varying intensities of angry, happy, or fearful face emotions. In mixed-effects analyses, the shared and unique effects of irritability and anxiety were tested on amygdala functional connectivity and activation to face emotions. The mean (SD) age of participants was 13.2 (2.6) years; of the 115 included, 64 were male. Irritability and/or anxiety influenced amygdala connectivity to the prefrontal and temporal cortex. Specifically, irritability and anxiety jointly influenced left amygdala to left medial prefrontal cortex connectivity during face emotion viewing (F4,888 = 9.20; P differences in neural response to face emotions in several areas (F2, 888 ≥ 13.45; all P emotion dysregulation when very anxious and irritable youth process threat-related faces. Activation in the ventral visual circuitry suggests a mechanism
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Altered Synchronizations among Neural Networks in Geriatric Depression.
Wang, Lihong; Chou, Ying-Hui; Potter, Guy G; Steffens, David C
2015-01-01
Although major depression has been considered as a manifestation of discoordinated activity between affective and cognitive neural networks, only a few studies have examined the relationships among neural networks directly. Because of the known disconnection theory, geriatric depression could be a useful model in studying the interactions among different networks. In the present study, using independent component analysis to identify intrinsically connected neural networks, we investigated the alterations in synchronizations among neural networks in geriatric depression to better understand the underlying neural mechanisms. Resting-state fMRI data was collected from thirty-two patients with geriatric depression and thirty-two age-matched never-depressed controls. We compared the resting-state activities between the two groups in the default-mode, central executive, attention, salience, and affective networks as well as correlations among these networks. The depression group showed stronger activity than the controls in an affective network, specifically within the orbitofrontal region. However, unlike the never-depressed controls, geriatric depression group lacked synchronized/antisynchronized activity between the affective network and the other networks. Those depressed patients with lower executive function has greater synchronization between the salience network with the executive and affective networks. Our results demonstrate the effectiveness of the between-network analyses in examining neural models for geriatric depression.
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An interpretable LSTM neural network for autoregressive exogenous model
Guo, Tian; Lin, Tao; Lu, Yao
2018-01-01
In this paper, we propose an interpretable LSTM recurrent neural network, i.e., multi-variable LSTM for time series with exogenous variables. Currently, widely used attention mechanism in recurrent neural networks mostly focuses on the temporal aspect of data and falls short of characterizing variable importance. To this end, our multi-variable LSTM equipped with tensorized hidden states is developed to learn variable specific representations, which give rise to both temporal and variable lev...
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Multifactor-influenced energy consumption forecasting using enhanced back-propagation neural network
International Nuclear Information System (INIS)
Zeng, Yu-Rong; Zeng, Yi; Choi, Beomjin; Wang, Lin
2017-01-01
Reliable energy consumption forecasting can provide effective decision-making support for planning development strategies to energy enterprises and for establishing national energy policies. Accordingly, the present study aims to apply a hybrid intelligent approach named ADE–BPNN, the back-propagation neural network (BPNN) model supported by an adaptive differential evolution algorithm, to estimate energy consumption. Most often, energy consumption is influenced by socioeconomic factors. The proposed hybrid model incorporates gross domestic product, population, import, and export data as inputs. An improved differential evolution with adaptive mutation and crossover is utilized to find appropriate global initial connection weights and thresholds to enhance the forecasting performance of the BPNN. A comparative example and two extended examples are utilized to validate the applicability and accuracy of the proposed ADE–BPNN model. Errors of the test data sets indicate that the ADE–BPNN model can effectively predict energy consumption compared with the traditional back-propagation neural network model and other popular existing models. Moreover, mean impact value based analysis is conducted for electrical energy consumption in U.S. and total energy consumption forecasting in China to quantitatively explore the relative importance of each input variable for the improvement of effective energy consumption prediction. - Highlights: • Enhanced back-propagation neural network (ADE-BPNN) for energy consumption forecasting. • ADE-BPNN outperforms the current best models for two comparative cases. • Mean impact value approach explores socio-economic factors' relative importance. • ADE-BPNN's adjusted goodness-of-fit is 99.2% for China's energy consumption forecasting.
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Short-term plasticity as a neural mechanism supporting memory and attentional functions.
Jääskeläinen, Iiro P; Ahveninen, Jyrki; Andermann, Mark L; Belliveau, John W; Raij, Tommi; Sams, Mikko
2011-11-08
Based on behavioral studies, several relatively distinct perceptual and cognitive functions have been defined in cognitive psychology such as sensory memory, short-term memory, and selective attention. Here, we review evidence suggesting that some of these functions may be supported by shared underlying neuronal mechanisms. Specifically, we present, based on an integrative review of the literature, a hypothetical model wherein short-term plasticity, in the form of transient center-excitatory and surround-inhibitory modulations, constitutes a generic processing principle that supports sensory memory, short-term memory, involuntary attention, selective attention, and perceptual learning. In our model, the size and complexity of receptive fields/level of abstraction of neural representations, as well as the length of temporal receptive windows, increases as one steps up the cortical hierarchy. Consequently, the type of input (bottom-up vs. top down) and the level of cortical hierarchy that the inputs target, determine whether short-term plasticity supports purely sensory vs. semantic short-term memory or attentional functions. Furthermore, we suggest that rather than discrete memory systems, there are continuums of memory representations from short-lived sensory ones to more abstract longer-duration representations, such as those tapped by behavioral studies of short-term memory. Copyright © 2011 Elsevier B.V. All rights reserved.