Electroacupuncture in the repair of spinal cord injury: inhibiting the Notch signaling pathway and promoting neural stem cell proliferation

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Xin Geng

2015-01-01

Full Text Available Electroacupuncture for the treatment of spinal cord injury has a good clinical curative effect, but the underlying mechanism is unclear. In our experiments, the spinal cord of adult Sprague-Dawley rats was clamped for 60 seconds. Dazhui (GV14 and Mingmen (GV4 acupoints of rats were subjected to electroacupuncture. Enzyme-linked immunosorbent assay revealed that the expression of serum inflammatory factors was apparently downregulated in rat models of spinal cord injury after electroacupuncture. Hematoxylin-eosin staining and immunohistochemistry results demonstrated that electroacupuncture contributed to the proliferation of neural stem cells in rat injured spinal cord, and suppressed their differentiation into astrocytes. Real-time quantitative PCR and western blot assays showed that electroacupuncture inhibited activation of the Notch signaling pathway induced by spinal cord injury. These findings indicate that electroacupuncture repaired the injured spinal cord by suppressing the Notch signaling pathway and promoting the proliferation of endogenous neural stem cells.

Neural crest contributions to the lamprey head

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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.

Neural pathways for visual speech perception

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Lynne E Bernstein

2014-12-01

Full Text Available This paper examines the questions, what levels of speech can be perceived visually, and how is visual speech represented by the brain? Review of the literature leads to the conclusions that every level of psycholinguistic speech structure (i.e., phonetic features, phonemes, syllables, words, and prosody can be perceived visually, although individuals differ in their abilities to do so; and that there are visual modality-specific representations of speech qua speech in higher-level vision brain areas. That is, the visual system represents the modal patterns of visual speech. The suggestion that the auditory speech pathway receives and represents visual speech is examined in light of neuroimaging evidence on the auditory speech pathways. We outline the generally agreed-upon organization of the visual ventral and dorsal pathways and examine several types of visual processing that might be related to speech through those pathways, specifically, face and body, orthography, and sign language processing. In this context, we examine the visual speech processing literature, which reveals widespread diverse patterns activity in posterior temporal cortices in response to visual speech stimuli. We outline a model of the visual and auditory speech pathways and make several suggestions: (1 The visual perception of speech relies on visual pathway representations of speech qua speech. (2 A proposed site of these representations, the temporal visual speech area (TVSA has been demonstrated in posterior temporal cortex, ventral and posterior to multisensory posterior superior temporal sulcus (pSTS. (3 Given that visual speech has dynamic and configural features, its representations in feedforward visual pathways are expected to integrate these features, possibly in TVSA.

Qualitative analysis of the maintenance politics of the systems of a typical PWR by artificial neural networks

International Nuclear Information System (INIS)

Lourenco, Victor Hugo Moreno

2010-02-01

Proceedings and techniques in order to maximize the reliability and the availability of industrial plants have been used along the last decades by specialists and professionals of maintenance. However, the modem industrial systems' sizing, and the increasing complexity and interdependence among its components have become this activity's planning a more and more difficult task. Considering this scenario, the objective of the present work is to provide a computational tool which is able to help about the taking decision's task, and about planning policies of maintenance practiced in thermonuclear plants. The tool developed is based on the artificial neural networks (ANN) for the recognition of standards and establishment of correlations among events occurred in the components of pressurized water reactor (PWR) typical systems. The ANN work as miners of database of failure events, and are able to identify connections and to establish imperceptible inferences even for the most experienced specialists in maintenance of nuclear systems. The results were attained from realistic data and are confronted against the maintenance's classic policies which are practiced nowadays on PWR thermonuclear plants. These results show the solidity of the technique in valuing and predicting failures in a real power plant, and is able to be used as a tool for supporting decisions about planning maintenance policies on a typical PWR. (author)

Spatially Compact Neural Clusters in the Dorsal Striatum Encode Locomotion Relevant Information.

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Barbera, Giovanni; Liang, Bo; Zhang, Lifeng; Gerfen, Charles R; Culurciello, Eugenio; Chen, Rong; Li, Yun; Lin, Da-Ting

2016-10-05

An influential striatal model postulates that neural activities in the striatal direct and indirect pathways promote and inhibit movement, respectively. Normal behavior requires coordinated activity in the direct pathway to facilitate intended locomotion and indirect pathway to inhibit unwanted locomotion. In this striatal model, neuronal population activity is assumed to encode locomotion relevant information. Here, we propose a novel encoding mechanism for the dorsal striatum. We identified spatially compact neural clusters in both the direct and indirect pathways. Detailed characterization revealed similar cluster organization between the direct and indirect pathways, and cluster activities from both pathways were correlated with mouse locomotion velocities. Using machine-learning algorithms, cluster activities could be used to decode locomotion relevant behavioral states and locomotion velocity. We propose that neural clusters in the dorsal striatum encode locomotion relevant information and that coordinated activities of direct and indirect pathway neural clusters are required for normal striatal controlled behavior. VIDEO ABSTRACT. Published by Elsevier Inc.

Recycling signals in the neural crest

OpenAIRE

Taneyhill, Lisa A.; Bronner-Fraser, Marianne E.

2006-01-01

Vertebrate neural crest cells are multipotent and differentiate into structures that include cartilage and the bones of the face, as well as much of the peripheral nervous system. Understanding how different model vertebrates utilize signaling pathways reiteratively during various stages of neural crest formation and differentiation lends insight into human disorders associated with the neural crest.

Recycling signals in the neural crest.

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Taneyhill, Lisa A; Bronner-Fraser, Marianne

2005-01-01

Vertebrate neural crest cells are multipotent and differentiate into structures that include cartilage and the bones of the face, as well as much of the peripheral nervous system. Understanding how different model vertebrates utilize signaling pathways reiteratively during various stages of neural crest formation and differentiation lends insight into human disorders associated with the neural crest.

The neural correlates of attachment security in typically developing children.

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Choi, Eun Jung; Taylor, Margot J; Hong, Soon-Beom; Kim, Changdai; Yi, Soon-Hyung

2018-07-01

This study investigated neural correlates of children's attachment security using functional magnetic resonance imaging. Fifty-one boys' attachment styles (age mean = 9.5 years, SD = 0.61) were assessed with the Separation Anxiety Test (SAT). We created an fMRI version of the SAT to activate children's attachment system in fMRI environment and contrasted two conditions in which children were instructed to infer the specific feeling of the boy in the picture or to identify objects or physical activities. In the final fMRI analysis (N = 21), attachment security could be detected at the neural level corresponding to the behavioural differences in the attachment interview. Securely attached children showed greater activation in the frontal, limbic and basal ganglia area which included the dorsolateral prefrontal cortex, amygdala, cingulate cortex and striatum, compared to other children who had lower quality of attachment. These regions have a key role in socio-emotional information processing and also represent a brain network related to approach and avoidance motivation in humans. Especially the striatum, strongly linked to reward processing underpinning social approach and avoidance motivation, showed the largest effects in these differences and also positively correlated with emotional openness scores in SAT. This suggests that the quality of attachment configures the approach and avoidance motivational system in our brain mediated by the striatum. Copyright © 2018 Elsevier Inc. All rights reserved.

CHD8 regulates neurodevelopmental pathways associated with autism spectrum disorder in neural progenitors

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Sugathan, Aarathi; Biagioli, Marta; Golzio, Christelle; Erdin, Serkan; Blumenthal, Ian; Manavalan, Poornima; Ragavendran, Ashok; Brand, Harrison; Lucente, Diane; Miles, Judith; Sheridan, Steven D.; Stortchevoi, Alexei; Kellis, Manolis; Haggarty, Stephen J.; Katsanis, Nicholas; Gusella, James F.; Talkowski, Michael E.

2014-01-01

Truncating mutations of chromodomain helicase DNA-binding protein 8 (CHD8), and of many other genes with diverse functions, are strong-effect risk factors for autism spectrum disorder (ASD), suggesting multiple mechanisms of pathogenesis. We explored the transcriptional networks that CHD8 regulates in neural progenitor cells (NPCs) by reducing its expression and then integrating transcriptome sequencing (RNA sequencing) with genome-wide CHD8 binding (ChIP sequencing). Suppressing CHD8 to levels comparable with the loss of a single allele caused altered expression of 1,756 genes, 64.9% of which were up-regulated. CHD8 showed widespread binding to chromatin, with 7,324 replicated sites that marked 5,658 genes. Integration of these data suggests that a limited array of direct regulatory effects of CHD8 produced a much larger network of secondary expression changes. Genes indirectly down-regulated (i.e., without CHD8-binding sites) reflect pathways involved in brain development, including synapse formation, neuron differentiation, cell adhesion, and axon guidance, whereas CHD8-bound genes are strongly associated with chromatin modification and transcriptional regulation. Genes associated with ASD were strongly enriched among indirectly down-regulated loci (P neurodevelopmental pathways in which many ASD-associated genes may converge on shared mechanisms of pathogenesis. PMID:25294932

Requirement of mouse BCCIP for neural development and progenitor proliferation.

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Yi-Yuan Huang

Full Text Available Multiple DNA repair pathways are involved in the orderly development of neural systems at distinct stages. The homologous recombination (HR pathway is required to resolve stalled replication forks and critical for the proliferation of progenitor cells during neural development. BCCIP is a BRCA2 and CDKN1A interacting protein implicated in HR and inhibition of DNA replication stress. In this study, we determined the role of BCCIP in neural development using a conditional BCCIP knock-down mouse model. BCCIP deficiency impaired embryonic and postnatal neural development, causing severe ataxia, cerebral and cerebellar defects, and microcephaly. These development defects are associated with spontaneous DNA damage and subsequent cell death in the proliferative cell populations of the neural system during embryogenesis. With in vitro neural spheroid cultures, BCCIP deficiency impaired neural progenitor's self-renewal capability, and spontaneously activated p53. These data suggest that BCCIP and its anti-replication stress functions are essential for normal neural development by maintaining an orderly proliferation of neural progenitors.

Neural electrical activity and neural network growth.

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Gafarov, F M

2018-05-01

The development of central and peripheral neural system depends in part on the emergence of the correct functional connectivity in its input and output pathways. Now it is generally accepted that molecular factors guide neurons to establish a primary scaffold that undergoes activity-dependent refinement for building a fully functional circuit. However, a number of experimental results obtained recently shows that the neuronal electrical activity plays an important role in the establishing of initial interneuronal connections. Nevertheless, these processes are rather difficult to study experimentally, due to the absence of theoretical description and quantitative parameters for estimation of the neuronal activity influence on growth in neural networks. In this work we propose a general framework for a theoretical description of the activity-dependent neural network growth. The theoretical description incorporates a closed-loop growth model in which the neural activity can affect neurite outgrowth, which in turn can affect neural activity. We carried out the detailed quantitative analysis of spatiotemporal activity patterns and studied the relationship between individual cells and the network as a whole to explore the relationship between developing connectivity and activity patterns. The model, developed in this work will allow us to develop new experimental techniques for studying and quantifying the influence of the neuronal activity on growth processes in neural networks and may lead to a novel techniques for constructing large-scale neural networks by self-organization. Copyright © 2018 Elsevier Ltd. All rights reserved.

Neural plasticity and its initiating conditions in tinnitus.

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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.

AKT signaling displays multifaceted functions in neural crest development.

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Sittewelle, Méghane; Monsoro-Burq, Anne H

2018-05-31

AKT signaling is an essential intracellular pathway controlling cell homeostasis, cell proliferation and survival, as well as cell migration and differentiation in adults. Alterations impacting the AKT pathway are involved in many pathological conditions in human disease. Similarly, during development, multiple transmembrane molecules, such as FGF receptors, PDGF receptors or integrins, activate AKT to control embryonic cell proliferation, migration, differentiation, and also cell fate decisions. While many studies in mouse embryos have clearly implicated AKT signaling in the differentiation of several neural crest derivatives, information on AKT functions during the earliest steps of neural crest development had remained relatively scarce until recently. However, recent studies on known and novel regulators of AKT signaling demonstrate that this pathway plays critical roles throughout the development of neural crest progenitors. Non-mammalian models such as fish and frog embryos have been instrumental to our understanding of AKT functions in neural crest development, both in neural crest progenitors and in the neighboring tissues. This review combines current knowledge acquired from all these different vertebrate animal models to describe the various roles of AKT signaling related to neural crest development in vivo. We first describe the importance of AKT signaling in patterning the tissues involved in neural crest induction, namely the dorsal mesoderm and the ectoderm. We then focus on AKT signaling functions in neural crest migration and differentiation. Copyright © 2018 Elsevier Inc. All rights reserved.

Artificial neural networks in NDT

International Nuclear Information System (INIS)

Abdul Aziz Mohamed

2001-01-01

Artificial neural networks, simply known as neural networks, have attracted considerable interest in recent years largely because of a growing recognition of the potential of these computational paradigms as powerful alternative models to conventional pattern recognition or function approximation techniques. The neural networks approach is having a profound effect on almost all fields, and has been utilised in fields Where experimental inter-disciplinary work is being carried out. Being a multidisciplinary subject with a broad knowledge base, Nondestructive Testing (NDT) or Nondestructive Evaluation (NDE) is no exception. This paper explains typical applications of neural networks in NDT/NDE. Three promising types of neural networks are highlighted, namely, back-propagation, binary Hopfield and Kohonen's self-organising maps. (Author)

Neural computation and the computational theory of cognition.

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Piccinini, Gualtiero; Bahar, Sonya

2013-04-01

We begin by distinguishing computationalism from a number of other theses that are sometimes conflated with it. We also distinguish between several important kinds of computation: computation in a generic sense, digital computation, and analog computation. Then, we defend a weak version of computationalism-neural processes are computations in the generic sense. After that, we reject on empirical grounds the common assimilation of neural computation to either analog or digital computation, concluding that neural computation is sui generis. Analog computation requires continuous signals; digital computation requires strings of digits. But current neuroscientific evidence indicates that typical neural signals, such as spike trains, are graded like continuous signals but are constituted by discrete functional elements (spikes); thus, typical neural signals are neither continuous signals nor strings of digits. It follows that neural computation is sui generis. Finally, we highlight three important consequences of a proper understanding of neural computation for the theory of cognition. First, understanding neural computation requires a specially designed mathematical theory (or theories) rather than the mathematical theories of analog or digital computation. Second, several popular views about neural computation turn out to be incorrect. Third, computational theories of cognition that rely on non-neural notions of computation ought to be replaced or reinterpreted in terms of neural computation. Copyright © 2012 Cognitive Science Society, Inc.

Glucagon-like peptide-1 reduces pancreatic β-cell mass through hypothalamic neural pathways in high-fat diet-induced obese rats.

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Ando, Hisae; Gotoh, Koro; Fujiwara, Kansuke; Anai, Manabu; Chiba, Seiichi; Masaki, Takayuki; Kakuma, Tetsuya; Shibata, Hirotaka

2017-07-17

We examined whether glucagon-like peptide-1 (GLP-1) affects β-cell mass and proliferation through neural pathways, from hepatic afferent nerves to pancreatic efferent nerves via the central nervous system, in high-fat diet (HFD)-induced obese rats. The effects of chronic administration of GLP-1 (7-36) and liraglutide, a GLP-1 receptor agonist, on pancreatic morphological alterations, c-fos expression and brain-derived neurotrophic factor (BDNF) content in the hypothalamus, and glucose metabolism were investigated in HFD-induced obese rats that underwent hepatic afferent vagotomy (VgX) and/or pancreatic efferent sympathectomy (SpX). Chronic GLP-1 (7-36) administration to HFD-induced obese rats elevated c-fos expression and BDNF content in the hypothalamus, followed by a reduction in pancreatic β-cell hyperplasia and insulin content, thus resulting in improved glucose tolerance. These responses were abolished by VgX and SpX. Moreover, administration of liraglutide similarly activated the hypothalamic neural pathways, thus resulting in a more profound amelioration of glucose tolerance than native GLP-1 (7-36). These data suggest that GLP-1 normalizes the obesity-induced compensatory increase in β-cell mass and glucose intolerance through a neuronal relay system consisting of hepatic afferent nerves, the hypothalamus, and pancreatic efferent nerves.

Dopamine system: Manager of neural pathways

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Simon eHong

2013-12-01

Full Text Available There are a growing number of roles that midbrain dopamine (DA neurons assume, such as, reward, aversion, alerting and vigor. Here I propose a theory that may be able to explain why the suggested functions of DA came about. It has been suggested that largely parallel cortico-basal ganglia-thalamo-cortico loops exist to control different aspects of behavior. I propose that (1 the midbrain DA system is organized in a similar manner, with different groups of DA neurons corresponding to these parallel neural pathways (NPs. The DA system can be viewed as the manager of these parallel NPs in that it recruits and activates only the task-relevant NPs when they are needed. It is likely that the functions of those NPs that have been consistently activated by the corresponding DA groups are facilitated. I also propose that (2 there are two levels of DA roles: the How and What roles. The How role is encoded in tonic and phasic DA neuron firing patterns and gives a directive to its target NP: how vigorously its function needs to be carried out. The tonic DA firing is to maintain a certain level of DA in the target NPs to support their expected behavioral and mental functions; it is only when a sudden unexpected boost or suppression of activity is required by the relevant target NP that DA neurons in the corresponding NP act in a phasic manner. The What role is the implementational aspect of the role of DA in the target NP, such as binding to D1 receptors to boost working memory. This What aspect of DA explains why DA seems to assume different functions depending on the region of the brain in which it is involved. In terms of the role of the lateral habenula (LHb, the LHb is expected to suppress maladaptive behaviors and mental processes by controlling the DA system. The demand-based smart management by the DA system may have given animals an edge in evolution with adaptive behaviors and a better survival rate in resource-scarce situations.

Serotonin, neural markers and memory

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Alfredo eMeneses

2015-07-01

Full Text Available Diverse neuropsychiatric disorders present dysfunctional memory and no effective treatment exits for them; likely as result of the absence of neural markers associated to memory. Neurotransmitter systems and signaling pathways have been implicated in memory and dysfunctional memory; however, their role is poorly understood. Hence, neural markers and cerebral functions and dysfunctions are revised. To our knowledge no previous systematic works have been published addressing these issues. The interactions among behavioral tasks, control groups and molecular changes and/or pharmacological effects are mentioned. Neurotransmitter receptors and signaling pathways, during normal and abnormally functioning memory with an emphasis on the behavioral aspects of memory are revised. With focus on serotonin, since as it is a well characterized neurotransmitter, with multiple pharmacological tools, and well characterized downstream signaling in mammals’ species. 5-HT1A, 5-HT4, 5-HT5, 5-HT6 and 5-HT7 receptors as well as SERT (serotonin transporter seem to be useful neural markers and/or therapeutic targets. Certainly, if the mentioned evidence is replicated, then the translatability from preclinical and clinical studies to neural changes might be confirmed. Hypothesis and theories might provide appropriate limits and perspectives of evidence

Overexpression of miR‑21 promotes neural stem cell proliferation and neural differentiation via the Wnt/β‑catenin signaling pathway in vitro.

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Zhang, Wei-Min; Zhang, Zhi-Ren; Yang, Xi-Tao; Zhang, Yong-Gang; Gao, Yan-Sheng

2018-01-01

The primary aim of the present study was to examine the effects of microRNA‑21 (miR‑21) on the proliferation and differentiation of rat primary neural stem cells (NSCs) in vitro. miR‑21 was overexpressed in NSCs by transfection with a miR‑21 mimic. The effects of miR‑21 overexpression on NSC proliferation were revealed by Cell Counting kit 8 and 5‑ethynyl‑2'‑deoxyuridine incorporation assay, and miR‑21 overexpression was revealed to increase NSC proliferation. miR‑21 overexpression was confirmed using reverse transcription‑quantitative polymerase chain reaction (RT‑qPCR). mRNA and protein expression levels of key molecules (β‑catenin, cyclin D1, p21 and miR‑21) in the Wnt/β‑catenin signaling pathway were studied by RT‑qPCR and western blot analysis. RT‑qPCR and western blot analyses revealed that miR‑21 overexpression increased β‑catenin and cyclin D1 expression, and decreased p21 expression. These results suggested that miR‑21‑induced increase in proliferation was mediated by activation of the Wnt/β‑catenin signaling pathway, since overexpression of miR‑21 increased β‑catenin and cyclin D1 expression and reduced p21 expression. Furthermore, inhibition of the Wnt/β‑catenin pathway with FH535 attenuated the influence of miR‑21 overexpression on NSC proliferation, indicating that the factors activated by miR‑21 overexpression were inhibited by FH535 treatment. Furthermore, overexpression of miR‑21 enhanced the differentiation of NSCs into neurons and inhibited their differentiation into astrocytes. The present study indicated that in primary rat NSCs, overexpression of miR‑21 may promote proliferation and differentiation into neurons via the Wnt/β‑catenin signaling pathway in vitro.

Social cognition and neural substrates of face perception: implications for neurodevelopmental and neuropsychiatric disorders.

Science.gov (United States)

Lazar, Steven M; Evans, David W; Myers, Scott M; Moreno-De Luca, Andres; Moore, Gregory J

2014-04-15

Social cognition is an important aspect of social behavior in humans. Social cognitive deficits are associated with neurodevelopmental and neuropsychiatric disorders. In this study we examine the neural substrates of social cognition and face processing in a group of healthy young adults to examine the neural substrates of social cognition. Fifty-seven undergraduates completed a battery of social cognition tasks and were assessed with electroencephalography (EEG) during a face-perception task. A subset (N=22) were administered a face-perception task during functional magnetic resonance imaging. Variance in the N170 EEG was predicted by social attribution performance and by a quantitative measure of empathy. Neurally, face processing was more bilateral in females than in males. Variance in fMRI voxel count in the face-sensitive fusiform gyrus was predicted by quantitative measures of social behavior, including the Social Responsiveness Scale (SRS) and the Empathizing Quotient. When measured as a quantitative trait, social behaviors in typical and pathological populations share common neural pathways. The results highlight the importance of viewing neurodevelopmental and neuropsychiatric disorders as spectrum phenomena that may be informed by studies of the normal distribution of relevant traits in the general population. Copyright © 2014 Elsevier B.V. All rights reserved.

Brain bases of reading fluency in typical reading and impaired fluency in dyslexia.

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Joanna A Christodoulou

Full Text Available Although the neural systems supporting single word reading are well studied, there are limited direct comparisons between typical and dyslexic readers of the neural correlates of reading fluency. Reading fluency deficits are a persistent behavioral marker of dyslexia into adulthood. The current study identified the neural correlates of fluent reading in typical and dyslexic adult readers, using sentences presented in a word-by-word format in which single words were presented sequentially at fixed rates. Sentences were presented at slow, medium, and fast rates, and participants were asked to decide whether each sentence did or did not make sense semantically. As presentation rates increased, participants became less accurate and slower at making judgments, with comprehension accuracy decreasing disproportionately for dyslexic readers. In-scanner performance on the sentence task correlated significantly with standardized clinical measures of both reading fluency and phonological awareness. Both typical readers and readers with dyslexia exhibited widespread, bilateral increases in activation that corresponded to increases in presentation rate. Typical readers exhibited significantly larger gains in activation as a function of faster presentation rates than readers with dyslexia in several areas, including left prefrontal and left superior temporal regions associated with semantic retrieval and semantic and phonological representations. Group differences were more extensive when behavioral differences between conditions were equated across groups. These findings suggest a brain basis for impaired reading fluency in dyslexia, specifically a failure of brain regions involved in semantic retrieval and semantic and phonological representations to become fully engaged for comprehension at rapid reading rates.

Canonical Wnt signaling transiently stimulates proliferation and enhances neurogenesis in neonatal neural progenitor cultures

International Nuclear Information System (INIS)

Hirsch, Cordula; Campano, Louise M.; Woehrle, Simon; Hecht, Andreas

2007-01-01

Canonical Wnt signaling triggers the formation of heterodimeric transcription factor complexes consisting of β-catenin and T cell factors, and thereby controls the execution of specific genetic programs. During the expansion and neurogenic phases of embryonic neural development canonical Wnt signaling initially controls proliferation of neural progenitor cells, and later neuronal differentiation. Whether Wnt growth factors affect neural progenitor cells postnatally is not known. Therefore, we have analyzed the impact of Wnt signaling on neural progenitors isolated from cerebral cortices of newborn mice. Expression profiling of pathway components revealed that these cells are fully equipped to respond to Wnt signals. However, Wnt pathway activation affected only a subset of neonatal progenitors and elicited a limited increase in proliferation and neuronal differentiation in distinct subsets of cells. Moreover, Wnt pathway activation only transiently stimulated S-phase entry but did not support long-term proliferation of progenitor cultures. The dampened nature of the Wnt response correlates with the predominant expression of inhibitory pathway components and the rapid actuation of negative feedback mechanisms. Interestingly, in differentiating cell cultures activation of canonical Wnt signaling reduced Hes1 and Hes5 expression suggesting that during postnatal neural development, Wnt/β-catenin signaling enhances neurogenesis from progenitor cells by interfering with Notch pathway activity

Transcriptional profiling of adult neural stem-like cells from the human brain.

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Cecilie Jonsgar Sandberg

Full Text Available There is a great potential for the development of new cell replacement strategies based on adult human neural stem-like cells. However, little is known about the hierarchy of cells and the unique molecular properties of stem- and progenitor cells of the nervous system. Stem cells from the adult human brain can be propagated and expanded in vitro as free floating neurospheres that are capable of self-renewal and differentiation into all three cell types of the central nervous system. Here we report the first global gene expression study of adult human neural stem-like cells originating from five human subventricular zone biopsies (mean age 42, range 33-60. Compared to adult human brain tissue, we identified 1,189 genes that were significantly up- and down-regulated in adult human neural stem-like cells (1% false discovery rate. We found that adult human neural stem-like cells express stem cell markers and have reduced levels of markers that are typical of the mature cells in the nervous system. We report that the genes being highly expressed in adult human neural stem-like cells are associated with developmental processes and the extracellular region of the cell. The calcium signaling pathway and neuroactive ligand-receptor interactions are enriched among the most differentially regulated genes between adult human neural stem-like cells and adult human brain tissue. We confirmed the expression of 10 of the most up-regulated genes in adult human neural stem-like cells in an additional sample set that included adult human neural stem-like cells (n = 6, foetal human neural stem cells (n = 1 and human brain tissues (n = 12. The NGFR, SLITRK6 and KCNS3 receptors were further investigated by immunofluorescence and shown to be heterogeneously expressed in spheres. These receptors could potentially serve as new markers for the identification and characterisation of neural stem- and progenitor cells or as targets for manipulation of cellular

Neural networks. A new analytical tool, applicable also in nuclear technology

International Nuclear Information System (INIS)

Stritar, A.

1992-01-01

The basic concept of neural networks and back propagation learning algorithm are described. The behaviour of typical neural network is demonstrated on a simple graphical case. A short literature survey about the application of neural networks in nuclear science and engineering is made. The application of the neural network to the probability density calculation is shown. (author) [sl

Health risk assessment of various metal(loid)s via multiple exposure pathways on children living near a typical lead-acid battery plant, China

International Nuclear Information System (INIS)

Cao, Suzhen; Duan, Xiaoli; Zhao, Xiuge; Wang, Beibei; Ma, Jin; Fan, Delong; Sun, Chengye; He, Bin; Wei, Fusheng; Jiang, Guibin

2015-01-01

Manufacture of lead-acid batteries is of widespread interest because of its emissions of heavy metals and metalloids into environment, harming environmental quality and consequently causing detrimental effects on human health. In this study, exposure pathways and health risks of children to heavy metal(loid)s (Pb, Cd, As, etc) were investigated based on field sampling and questionnaire. Pb was one of the most abundant elements in children's blood, with an elevated blood lead level of 12.45 μg dL −1 . Soil/dust and food were heavily polluted by targeted metal(loid)s. Food ingestion accounted for more than 80% of the total exposure for most metal(loid)s. The non-cancer risks to children were 3–10 times higher than the acceptable level of 1, while the cancer risks were 5–200 times higher than the maximum acceptable level of 1.0 × 10 −4 . The study emphasized the significance of effective environmental management, particularly to ensure food security near battery facilities. - Highlights: • The health risks of children living around a typical lead-acid battery was analyzed. • The exposure pathways of children to 12 heavy metal(loid)s were assessed. • Courtyard soil and indoor dust and duplicate food were contaminated by metal(loid)s. • Food ingestion was the major pathway for children's exposure to most metal(loid)s. • Higher potentially non-cancer and cancer risks happened to the local children. - The children living around a typical lead-acid battery plant suffered from serious health risks, which mainly attributed to food ingestion and air inhalation exposure

Alzheimer disease: functional abnormalities in the dorsal visual pathway.

LENUS (Irish Health Repository)

Bokde, Arun L W

2012-02-01

PURPOSE: To evaluate whether patients with Alzheimer disease (AD) have altered activation compared with age-matched healthy control (HC) subjects during a task that typically recruits the dorsal visual pathway. MATERIALS AND METHODS: The study was performed in accordance with the Declaration of Helsinki, with institutional ethics committee approval, and all subjects provided written informed consent. Two tasks were performed to investigate neural function: face matching and location matching. Twelve patients with mild AD and 14 age-matched HC subjects were included. Brain activation was measured by using functional magnetic resonance imaging. Group statistical analyses were based on a mixed-effects model corrected for multiple comparisons. RESULTS: Task performance was not statistically different between the two groups, and within groups there were no differences in task performance. In the HC group, the visual perception tasks selectively activated the visual pathways. Conversely in the AD group, there was no selective activation during performance of these same tasks. Along the dorsal visual pathway, the AD group recruited additional regions, primarily in the parietal and frontal lobes, for the location-matching task. There were no differences in activation between groups during the face-matching task. CONCLUSION: The increased activation in the AD group may represent a compensatory mechanism for decreased processing effectiveness in early visual areas of patients with AD. The findings support the idea that the dorsal visual pathway is more susceptible to putative AD-related neuropathologic changes than is the ventral visual pathway.

Developing a computational tool for predicting physical parameters of a typical VVER-1000 core based on artificial neural network

International Nuclear Information System (INIS)

Mirvakili, S.M.; Faghihi, F.; Khalafi, H.

2012-01-01

Highlights: ► Thermal–hydraulics parameters of a VVER-1000 core based on neural network (ANN), are carried out. ► Required data for ANN training are found based on modified COBRA-EN code and then linked each other using MATLAB software. ► Based on ANN method, average and maximum temperature of fuel and clad as well as MDNBR of each FA are predicted. -- Abstract: The main goal of the present article is to design a computational tool to predict physical parameters of the VVER-1000 nuclear reactor core based on artificial neural network (ANN), taking into account a detailed physical model of the fuel rods and coolant channels in a fuel assembly. Predictions of thermal characteristics of fuel, clad and coolant are performed using cascade feed forward ANN based on linear fission power distribution and power peaking factors of FAs and hot channels factors (which are found based on our previous neutronic calculations). A software package has been developed to prepare the required data for ANN training which applies a modified COBRA-EN code for sub-channel analysis and links the codes using the MATLAB software. Based on the current estimation system, five main core TH parameters are predicted, which include the average and maximum temperatures of fuel and clad as well as the minimum departure from nucleate boiling ratio (MDNBR) for each FA. To get the best conditions for the considered ANNs training, a comprehensive sensitivity study has been performed to examine the effects of variation of hidden neurons, hidden layers, transfer functions, and the learning algorithms on the training and simulation results. Performance evaluation results show that the developed ANN can be trained to estimate the core TH parameters of a typical VVER-1000 reactor quickly without loss of accuracy.

Vascular Endothelial Growth Factor Receptor 3 Controls Neural Stem Cell Activation in Mice and Humans

Directory of Open Access Journals (Sweden)

Jinah Han

2015-02-01

Full Text Available Neural stem cells (NSCs continuously produce new neurons within the adult mammalian hippocampus. NSCs are typically quiescent but activated to self-renew or differentiate into neural progenitor cells. The molecular mechanisms of NSC activation remain poorly understood. Here, we show that adult hippocampal NSCs express vascular endothelial growth factor receptor (VEGFR 3 and its ligand VEGF-C, which activates quiescent NSCs to enter the cell cycle and generate progenitor cells. Hippocampal NSC activation and neurogenesis are impaired by conditional deletion of Vegfr3 in NSCs. Functionally, this is associated with compromised NSC activation in response to VEGF-C and physical activity. In NSCs derived from human embryonic stem cells (hESCs, VEGF-C/VEGFR3 mediates intracellular activation of AKT and ERK pathways that control cell fate and proliferation. These findings identify VEGF-C/VEGFR3 signaling as a specific regulator of NSC activation and neurogenesis in mammals.

The alexithymic brain: the neural pathways linking alexithymia to physical disorders

Directory of Open Access Journals (Sweden)

Kano Michiko

2013-01-01

Full Text Available Abstract Alexithymia is a personality trait characterized by difficulties in identifying and describing feelings and is associated with psychiatric and psychosomatic disorders. The mechanisms underlying the link between emotional dysregulation and psychosomatic disorders are unclear. Recent progress in neuroimaging has provided important information regarding emotional experience in alexithymia. We have conducted three brain imaging studies on alexithymia, which we describe herein. This article considers the role of emotion in the development of physical symptoms and discusses a possible pathway that we have identified in our neuroimaging studies linking alexithymia with psychosomatic disorders. In terms of socio-affective processing, alexithymics demonstrate lower reactivity in brain regions associated with emotion. Many studies have reported reduced activation in limbic areas (e.g., cingulate cortex, anterior insula, amygdala and the prefrontal cortex when alexithymics attempt to feel other people’s feelings or retrieve their own emotional episodes, compared to nonalexithymics. With respect to primitive emotional reactions such as the response to pain, alexithymics show amplified activity in areas considered to be involved in physical sensation. In addition to greater hormonal arousal responses in alexithymics during visceral pain, increased activity has been reported in the insula, anterior cingulate cortex, and midbrain. Moreover, in complex social situations, alexithymics may not be able to use feelings to guide their behavior appropriately. The Iowa gambling task (IGT was developed to assess decision-making processes based on emotion-guided evaluation. When alexithymics perform the IGT, they fail to learn an advantageous decision-making strategy and show reduced activity in the medial prefrontal cortex, a key area for successful performance of the IGT, and increased activity in the caudate, a region associated with impulsive choice. The

Suprahyoid Muscle Complex: A Reliable Neural Assessment Tool For Dysphagia?

DEFF Research Database (Denmark)

Kothari, Mohit; Stubbs, Peter William; Pedersen, Asger Roer

be a non-invasive reliable neural assessment tool for patients with dysphagia. Objective: To investigate the possibility of using the suprahyoid muscle complex (SMC) using surface electromyography (sEMG) to assess changes to neural pathways by determining the reliability of measurements in healthy...

IGF-1 Promotes Brn-4 Expression and Neuronal Differentiation of Neural Stem Cells via the PI3K/Akt Pathway

Science.gov (United States)

Zhang, Xinhua; Zhang, Lei; Cheng, Xiang; Guo, Yuxiu; Sun, Xiaohui; Chen, Geng; Li, Haoming; Li, Pengcheng; Lu, Xiaohui; Tian, Meiling; Qin, Jianbing; Zhou, Hui; Jin, Guohua

2014-01-01

Our previous studies indicated that transcription factor Brn-4 is upregulated in the surgically denervated hippocampus in vivo, promoting neuronal differentiation of hippocampal neural stem cells (NSCs) in vitro. The molecules mediating Brn-4 upregulation in the denervated hippocampus remain unknown. In this study we examined the levels of insulin-like growth factor-1 (IGF-1) in hippocampus following denervation. Surgical denervation led to a significant increase in IGF-1 expression in vivo. We also report that IGF-1 treatment on NSCs in vitro led to a marked acceleration of Brn-4 expression and cell differentiation down neuronal pathways. The promotion effects were blocked by PI3K-specific inhibitor (LY294002), but not MAPK inhibitor (PD98059); levels of phospho-Akt were increased by IGF-1 treatment. In addition, inhibition of IGF-1 receptor (AG1024) and mTOR (rapamycin) both attenuated the increased expression of Brn-4 induced by IGF-1. Together, the results demonstrated that upregulation of IGF-1 induced by hippocampal denervation injury leads to activation of the PI3K/Akt signaling pathway, which in turn gives rise to upregulation of the Brn-4 and subsequent stem cell differentiation down neuronal pathways. PMID:25474202

Optoelectronic Implementation of Neural Networks

Indian Academy of Sciences (India)

neural networks, such as learning, adapting and copying by means of parallel ... to provide robust recognition of hand-printed English text. Engine idle and misfiring .... and s represents the bounded activation function of a neuron. It is typically ...

Comparing the neural bases of self-referential processing in typically developing and 22q11.2 adolescents.

Science.gov (United States)

Schneider, Maude; Debbané, Martin; Lagioia, Annalaura; Salomon, Roy; d'Argembeau, Arnaud; Eliez, Stephan

2012-04-01

The investigation of self-reflective processing during adolescence is relevant, as this period is characterized by deep reorganization of the self-concept. It may be the case that an atypical development of brain regions underlying self-reflective processing increases the risk for psychological disorders and impaired social functioning. In this study, we investigated the neural bases of self- and other-related processing in typically developing adolescents and youths with 22q11.2 deletion syndrome (22q11DS), a rare neurogenetic condition associated with difficulties in social interactions and increased risk for schizophrenia. The fMRI paradigm consisted in judging if a series of adjectives applied to the participant himself/herself (self), to his/her best friend or to a fictional character (Harry Potter). In control adolescents, we observed that self- and other-related processing elicited strong activation in cortical midline structures (CMS) when contrasted with a semantic baseline condition. 22q11DS exhibited hypoactivation in the CMS and the striatum during the processing of self-related information when compared to the control group. Finally, the hypoactivation in the anterior cingulate cortex was associated with the severity of prodromal positive symptoms of schizophrenia. The findings are discussed in a developmental framework and in light of their implication for the development of schizophrenia in this at-risk population. Copyright © 2011 Elsevier Ltd. All rights reserved.

The neural cell adhesion molecule

DEFF Research Database (Denmark)

Berezin, V; Bock, E; Poulsen, F M

2000-01-01

During the past year, the understanding of the structure and function of neural cell adhesion has advanced considerably. The three-dimensional structures of several of the individual modules of the neural cell adhesion molecule (NCAM) have been determined, as well as the structure of the complex...... between two identical fragments of the NCAM. Also during the past year, a link between homophilic cell adhesion and several signal transduction pathways has been proposed, connecting the event of cell surface adhesion to cellular responses such as neurite outgrowth. Finally, the stimulation of neurite...

Neural measures of social attention across the first years of life: characterizing typical development and markers of autism risk.

Science.gov (United States)

Luyster, Rhiannon J; Powell, Christine; Tager-Flusberg, Helen; Nelson, Charles A

2014-04-01

Few studies employing event-related potentials (ERPs) to examine infant perception/cognition have systematically characterized age-related changes over the first few years of life. Establishing a 'normative' template of development is important in its own right, and doing so may also better highlight points of divergence for high-risk populations of infants, such as those at elevated genetic risk for autism spectrum disorder (ASD). The present investigation explores the developmental progression of the P1, N290, P400 and Nc components for a large sample of young children between 6 and 36 months of age, addressing age-related changes in amplitude, sensitivity to familiar and unfamiliar stimuli and hemispheric lateralization. Two samples of infants are included: those at low- and high-risk for ASD. The four components of interest show differential patterns of change over time and hemispheric lateralization; however, infants at low- and high-risk for ASD do not show significant differences in patterns of neural response to faces. These results will provide a useful point of reference for future developmental cognitive neuroscience research targeting both typical development and vulnerable populations. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

Protein signaling pathways in differentiation of neural stem cells

Czech Academy of Sciences Publication Activity Database

Skalníková, Helena; Vodička, Petr; Pelech, S.; Motlík, Jan; Gadher, S. J.; Kovářová, Hana

2008-01-01

Roč. 8, - (2008), s. 4547-4559 ISSN 1615-9853 R&D Projects: GA MŠk 1M0538 Institutional research plan: CEZ:AV0Z50450515 Keywords : antibody microarray * differentiation * neural stem cells Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 4.586, year: 2008

The proliferation of amplifying neural progenitor cells is impaired in the aging brain and restored by the mTOR pathway activation.

Science.gov (United States)

Romine, Jennifer; Gao, Xiang; Xu, Xiao-Ming; So, Kwok Fai; Chen, Jinhui

2015-04-01

A decrease in neurogenesis in the aged brain has been correlated with cognitive decline. The molecular signaling that regulates age-related decline in neurogenesis is still not fully understood. We found that different subtypes of neural stem cells (NSCs) in the hippocampus were differentially impaired by aging. The quiescent NSCs decreased slowly, although the active NSCs exhibited a sharp and dramatic decline from the ages of 6-9 months and became more quiescent at an early stage during the aging process. The activity of the mammalian target of rapamycin (mTOR) signal pathway is compromised in the NSCs of the aged brain. Activating the mTOR signaling pathway increased NSC proliferation and promoted neurogenesis in aged mice. In contrast, inhibiting the mTOR signaling pathway decreased NSCs proliferation. These results indicate that an age-associated decline in neurogenesis is mainly because of the reduction in proliferation of active NSCs, at least partially because of the compromise in the mTOR signaling activity. Stimulating the mTOR signaling revitalizes the NSCs, restores their proliferation, and enhances neurogenesis in the hippocampus of the aged brain. Copyright © 2015 Elsevier Inc. All rights reserved.

Excess thyroid hormone inhibits embryonic neural stem/progenitor cells proliferation and maintenance through STAT3 signalling pathway.

Science.gov (United States)

Chen, Chunhai; Zhou, Zhou; Zhong, Min; Li, Maoquan; Yang, Xuesen; Zhang, Yanwen; Wang, Yuan; Wei, Aimin; Qu, Mingyue; Zhang, Lei; Xu, Shangcheng; Chen, Shude; Yu, Zhengping

2011-07-01

Hyperthyroidism is prevalent during pregnancy, but little is known about the effects of excess thyroid hormone on the development of embryonic neural stem/progenitor cells (NSCs), and the mechanisms underlying these effects. Previous studies indicate that STAT3 plays a crucial role in determining NSC fate during neurodevelopment. In this study, we investigated the effects of a supraphysiological dose of 3,5,3'-L-triiodothyronine (T3) on the proliferation and maintenance of NSCs derived from embryonic day 13.5 mouse neocortex, and the involvement of STAT3 in this process. Our results suggest that excess T3 treatment inhibits NSC proliferation and maintenance. T3 decreased tyrosine phosphorylation of JAK1, JAK2 and STAT3, and subsequently inhibited STAT3-DNA binding activity. Furthermore, proliferation and maintenance of NSCs were decreased by inhibitors of JAKs and STAT3, indicating that the STAT3 signalling pathway is involved in the process of NSC proliferation and maintenance. Taken together, these results suggest that the STAT3 signalling pathway is involved in the process of T3-induced inhibition of embryonic NSC proliferation and maintenance. These findings provide data for understanding the effects of hyperthyroidism during pregnancy on fetal brain development, and the mechanisms underlying these effects.

Female Mice Deficient in Alpha-Fetoprotein Show Female-Typical Neural Responses to Conspecific-Derived Pheromones

NARCIS (Netherlands)

Brock, O.; Keller, M.; Douhard, Q.; Bakker, J.

2012-01-01

The neural mechanisms controlling sexual behavior are sexually differentiated by the perinatal actions of sex steroid hormones. We recently observed using female mice deficient in alpha-fetoprotein (AFP-KO) and which lack the protective actions of AFP against maternal estradiol, that exposure to

IGF-1 promotes Brn-4 expression and neuronal differentiation of neural stem cells via the PI3K/Akt pathway.

Directory of Open Access Journals (Sweden)

Xinhua Zhang

Full Text Available Our previous studies indicated that transcription factor Brn-4 is upregulated in the surgically denervated hippocampus in vivo, promoting neuronal differentiation of hippocampal neural stem cells (NSCs in vitro. The molecules mediating Brn-4 upregulation in the denervated hippocampus remain unknown. In this study we examined the levels of insulin-like growth factor-1 (IGF-1 in hippocampus following denervation. Surgical denervation led to a significant increase in IGF-1 expression in vivo. We also report that IGF-1 treatment on NSCs in vitro led to a marked acceleration of Brn-4 expression and cell differentiation down neuronal pathways. The promotion effects were blocked by PI3K-specific inhibitor (LY294002, but not MAPK inhibitor (PD98059; levels of phospho-Akt were increased by IGF-1 treatment. In addition, inhibition of IGF-1 receptor (AG1024 and mTOR (rapamycin both attenuated the increased expression of Brn-4 induced by IGF-1. Together, the results demonstrated that upregulation of IGF-1 induced by hippocampal denervation injury leads to activation of the PI3K/Akt signaling pathway, which in turn gives rise to upregulation of the Brn-4 and subsequent stem cell differentiation down neuronal pathways.

Neural circuit components of the Drosophila OFF motion vision pathway.

Science.gov (United States)

Meier, Matthias; Serbe, Etienne; Maisak, Matthew S; Haag, Jürgen; Dickson, Barry J; Borst, Alexander

2014-02-17

Detecting the direction of visual motion is an essential task of the early visual system. The Reichardt detector has been proven to be a faithful description of the underlying computation in insects. A series of recent studies addressed the neural implementation of the Reichardt detector in Drosophila revealing the overall layout in parallel ON and OFF channels, its input neurons from the lamina (L1→ON, and L2→OFF), and the respective output neurons to the lobula plate (ON→T4, and OFF→T5). While anatomical studies showed that T4 cells receive input from L1 via Mi1 and Tm3 cells, the neurons connecting L2 to T5 cells have not been identified so far. It is, however, known that L2 contacts, among others, two neurons, called Tm2 and L4, which show a pronounced directionality in their wiring. We characterized the visual response properties of both Tm2 and L4 neurons via Ca(2+) imaging. We found that Tm2 and L4 cells respond with an increase in activity to moving OFF edges in a direction-unselective manner. To investigate their participation in motion vision, we blocked their output while recording from downstream tangential cells in the lobula plate. Silencing of Tm2 and L4 completely abolishes the response to moving OFF edges. Our results demonstrate that both cell types are essential components of the Drosophila OFF motion vision pathway, prior to the computation of directionality in the dendrites of T5 cells. Copyright © 2014 Elsevier Ltd. All rights reserved.

Neural networks mediating sentence reading in the deaf

Directory of Open Access Journals (Sweden)

Elizabeth Ann Hirshorn

2014-06-01

Full Text Available The present work addresses the neural bases of sentence reading in deaf populations. To better understand the relative role of deafness and English knowledge in shaping the neural networks that mediate sentence reading, three populations with different degrees of English knowledge and depth of hearing loss were included – deaf signers, oral deaf and hearing individuals. The three groups were matched for reading comprehension and scanned while reading sentences. A similar neural network of left perisylvian areas was observed, supporting the view of a shared network of areas for reading despite differences in hearing and English knowledge. However, differences were observed, in particular in the auditory cortex, with deaf signers and oral deaf showing greatest bilateral superior temporal gyrus (STG recruitment as compared to hearing individuals. Importantly, within deaf individuals, the same STG area in the left hemisphere showed greater recruitment as hearing loss increased. To further understand the functional role of such auditory cortex re-organization after deafness, connectivity analyses were performed from the STG regions identified above. Connectivity from the left STG toward areas typically associated with semantic processing (BA45 and thalami was greater in deaf signers and in oral deaf as compared to hearing. In contrast, connectivity from left STG toward areas identified with speech-based processing was greater in hearing and in oral deaf as compared to deaf signers. These results support the growing literature indicating recruitment of auditory areas after congenital deafness for visually-mediated language functions, and establish that both auditory deprivation and language experience shape its functional reorganization. Implications for differential reliance on semantic vs. phonological pathways during reading in the three groups is discussed.

Neural network application to diesel generator diagnostics

International Nuclear Information System (INIS)

Logan, K.P.

1990-01-01

Diagnostic problems typically begin with the observation of some system behavior which is recognized as a deviation from the expected. The fundamental underlying process is one involving pattern matching cf observed symptoms to a set of compiled symptoms belonging to a fault-symptom mapping. Pattern recognition is often relied upon for initial fault detection and diagnosis. Parallel distributed processing (PDP) models employing neural network paradigms are known to be good pattern recognition devices. This paper describes the application of neural network processing techniques to the malfunction diagnosis of subsystems within a typical diesel generator configuration. Neural network models employing backpropagation learning were developed to correctly recognize fault conditions from the input diagnostic symptom patterns pertaining to various engine subsystems. The resulting network models proved to be excellent pattern recognizers for malfunction examples within the training set. The motivation for employing network models in lieu of a rule-based expert system, however, is related to the network's potential for generalizing malfunctions outside of the training set, as in the case of noisy or partial symptom patterns

Neural Networks

Directory of Open Access Journals (Sweden)

Schwindling Jerome

2010-04-01

Full Text Available This course presents an overview of the concepts of the neural networks and their aplication in the framework of High energy physics analyses. After a brief introduction on the concept of neural networks, the concept is explained in the frame of neuro-biology, introducing the concept of multi-layer perceptron, learning and their use as data classifer. The concept is then presented in a second part using in more details the mathematical approach focussing on typical use cases faced in particle physics. Finally, the last part presents the best way to use such statistical tools in view of event classifers, putting the emphasis on the setup of the multi-layer perceptron. The full article (15 p. corresponding to this lecture is written in french and is provided in the proceedings of the book SOS 2008.

Genetic tracing of the gustatory and trigeminal neural pathways originating from T1R3-expressing taste receptor cells and solitary chemoreceptor cells.

Science.gov (United States)

Ohmoto, Makoto; Matsumoto, Ichiro; Yasuoka, Akihito; Yoshihara, Yoshihiro; Abe, Keiko

2008-08-01

We established transgenic mouse lines expressing a transneuronal tracer, wheat germ agglutinin (WGA), under the control of mouse T1R3 gene promoter/enhancer. In the taste buds, WGA transgene was faithfully expressed in T1R3-positive sweet/umami taste receptor cells. WGA protein was transferred not laterally to the synapse-bearing, sour-responsive type III cells in the taste buds but directly to a subset of neurons in the geniculate and nodose/petrosal ganglia, and further conveyed to a rostro-central region of the nucleus of solitary tract. In addition, WGA was expressed in solitary chemoreceptor cells in the nasal epithelium and transferred along the trigeminal sensory pathway to the brainstem neurons. The solitary chemoreceptor cells endogenously expressed T1R3 together with bitter taste receptors T2Rs. This result shows an exceptional signature of receptor expression. Thus, the t1r3-WGA transgenic mice revealed the sweet/umami gustatory pathways from taste receptor cells and the trigeminal neural pathway from solitary chemoreceptor cells.

Prior Knowledge about Objects Determines Neural Color Representation in Human Visual Cortex.

Science.gov (United States)

Vandenbroucke, A R E; Fahrenfort, J J; Meuwese, J D I; Scholte, H S; Lamme, V A F

2016-04-01

To create subjective experience, our brain must translate physical stimulus input by incorporating prior knowledge and expectations. For example, we perceive color and not wavelength information, and this in part depends on our past experience with colored objects ( Hansen et al. 2006; Mitterer and de Ruiter 2008). Here, we investigated the influence of object knowledge on the neural substrates underlying subjective color vision. In a functional magnetic resonance imaging experiment, human subjects viewed a color that lay midway between red and green (ambiguous with respect to its distance from red and green) presented on either typical red (e.g., tomato), typical green (e.g., clover), or semantically meaningless (nonsense) objects. Using decoding techniques, we could predict whether subjects viewed the ambiguous color on typical red or typical green objects based on the neural response of veridical red and green. This shift of neural response for the ambiguous color did not occur for nonsense objects. The modulation of neural responses was observed in visual areas (V3, V4, VO1, lateral occipital complex) involved in color and object processing, as well as frontal areas. This demonstrates that object memory influences wavelength information relatively early in the human visual system to produce subjective color vision. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Magnocellular pathway for rotation invariant Neocognitron.

Science.gov (United States)

Ting, C H

1993-03-01

In the mammalian visual system, magnocellular pathway and parvocellular pathway cooperatively process visual information in parallel. The magnocellular pathway is more global and less particular about the details while the parvocellular pathway recognizes objects based on the local features. In many aspects, Neocognitron may be regarded as the artificial analogue of the parvocellular pathway. It is interesting then to model the magnocellular pathway. In order to achieve "rotation invariance" for Neocognitron, we propose a neural network model after the magnocellular pathway and expand its roles to include surmising the orientation of the input pattern prior to recognition. With the incorporation of the magnocellular pathway, a basic shift in the original paradigm has taken place. A pattern is now said to be recognized when and only when one of the winners of the magnocellular pathway is validified by the parvocellular pathway. We have implemented the magnocellular pathway coupled with Neocognitron parallel on transputers; our simulation programme is now able to recognize numerals in arbitrary orientation.

DNA topoisomerase IIβ stimulates neurite outgrowth in neural differentiated human mesenchymal stem cells through regulation of Rho-GTPases (RhoA/Rock2 pathway) and Nurr1 expression.

Science.gov (United States)

Zaim, Merve; Isik, Sevim

2018-04-25

DNA topoisomerase IIβ (topo IIβ) is known to regulate neural differentiation by inducing the neuronal genes responsible for critical neural differentiation events such as neurite outgrowth and axon guidance. However, the pathways of axon growth controlled by topo IIβ have not been clarified yet. Microarray results of our previous study have shown that topo IIβ silencing in neural differentiated primary human mesenchymal stem cells (hMSCs) significantly alters the expression pattern of genes involved in neural polarity, axonal growth, and guidance, including Rho-GTPases. This study aims to further analyze the regulatory role of topo IIβ on the process of axon growth via regulation of Rho-GTPases. For this purpose, topo IIβ was silenced in neurally differentiated hMSCs. Cells lost their morphology because of topo IIβ deficiency, becoming enlarged and flattened. Additionally, a reduction in both neural differentiation efficiency and neurite length, upregulation in RhoA and Rock2, downregulation in Cdc42 gene expression were detected. On the other hand, cells were transfected with topo IIβ gene to elucidate the possible neuroprotective effect of topo IIβ overexpression on neural-induced hMSCs. Topo IIβ overexpression prompted all the cells to exhibit neural cell morphology as characterized by longer neurites. RhoA and Rock2 expressions were downregulated, whereas Cdc42 expression was upregulated. Nurr1 expression level correlated with topo IIβ in both topo IIβ-overexpressed and -silenced cells. Furthermore, differential translocation of Rho-GTPases was detected by immunostaining in response to topo IIβ. Our results suggest that topo IIβ deficiency could give rise to neurodegeneration through dysregulation of Rho-GTPases. However, further in-vivo research is needed to demonstrate if re-regulation of Rho GTPases by topo IIβ overexpression could be a neuroprotective treatment in the case of neurodegenerative diseases.

Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream.

Science.gov (United States)

Güçlü, Umut; van Gerven, Marcel A J

2015-07-08

Converging evidence suggests that the primate ventral visual pathway encodes increasingly complex stimulus features in downstream areas. We quantitatively show that there indeed exists an explicit gradient for feature complexity in the ventral pathway of the human brain. This was achieved by mapping thousands of stimulus features of increasing complexity across the cortical sheet using a deep neural network. Our approach also revealed a fine-grained functional specialization of downstream areas of the ventral stream. Furthermore, it allowed decoding of representations from human brain activity at an unsurpassed degree of accuracy, confirming the quality of the developed approach. Stimulus features that successfully explained neural responses indicate that population receptive fields were explicitly tuned for object categorization. This provides strong support for the hypothesis that object categorization is a guiding principle in the functional organization of the primate ventral stream. Copyright © 2015 the authors 0270-6474/15/3510005-10$15.00/0.

Chaotic Hopfield Neural Network Swarm Optimization and Its Application

Directory of Open Access Journals (Sweden)

Yanxia Sun

2013-01-01

Full Text Available A new neural network based optimization algorithm is proposed. The presented model is a discrete-time, continuous-state Hopfield neural network and the states of the model are updated synchronously. The proposed algorithm combines the advantages of traditional PSO, chaos and Hopfield neural networks: particles learn from their own experience and the experiences of surrounding particles, their search behavior is ergodic, and convergence of the swarm is guaranteed. The effectiveness of the proposed approach is demonstrated using simulations and typical optimization problems.

Abnormal regional spontaneous neural activity in visual pathway in retinal detachment patients: a resting-state functional MRI study

Directory of Open Access Journals (Sweden)

Huang X

2017-11-01

Full Text Available Xin Huang,1,2,* Dan Li,3,* Hai-Jun Li,3 Yu-Lin Zhong,1 Shelby Freeberg,4 Jing Bao,1 Xian-Jun Zeng,3 Yi Shao1 1Department of Ophthalmology, The First Affiliated Hospital of Nanchang University, Jiangxi Province Clinical Ophthalmology Institute, Nanchang, Jiangxi, People’s Republic of China; 2Department of Ophthalmology, Eye Center, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, Hubei, People’s Republic of China; 3Department of Radiology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, People’s Republic of China; 4Department of Ophthalmology, University of Florida, Gainesville, FL, USA *These authors contributed equally to this work Objective: The aim of the study was to investigate changes of brain neural homogeneity in retinal detachment (RD patients using the regional homogeneity (ReHo method to understand their relationships with clinical features. Materials and methods: A total of 30 patients with RD (16 men and 14 women, and 30 healthy controls (HCs (16 men and 14 women closely matched in age and sex were recruited. Resting-state functional magnetic resonance imaging scans were performed for all subjects. The ReHo method was used to investigate the brain regional neural homogeneity. Patients with RD were distinguished from HCs by receiver operating characteristic curve. The relationships between the mean ReHo signal values in many brain regions and clinical features in RD patients were calculated by Pearson correlation analysis. Results: Compared with HCs, RD patients had significantly decreased ReHo values in the right occipital lobe, right superior temporal gyrus, bilateral cuneus and left middle frontal gyrus. Moreover, we found that the mean ReHo signal of the bilateral cuneus showed positive relationships with the duration of the RD (r=0.392, P=0.032. Conclusion: The RD patients showed brain neural homogeneity dysfunction in the visual pathway, which may underline the pathological mechanism

Affective neural response to restricted interests in autism spectrum disorders.

Science.gov (United States)

Cascio, Carissa J; Foss-Feig, Jennifer H; Heacock, Jessica; Schauder, Kimberly B; Loring, Whitney A; Rogers, Baxter P; Pryweller, Jennifer R; Newsom, Cassandra R; Cockhren, Jurnell; Cao, Aize; Bolton, Scott

2014-01-01

Restricted interests are a class of repetitive behavior in autism spectrum disorders (ASD) whose intensity and narrow focus often contribute to significant interference with daily functioning. While numerous neuroimaging studies have investigated executive circuits as putative neural substrates of repetitive behavior, recent work implicates affective neural circuits in restricted interests. We sought to explore the role of affective neural circuits and determine how restricted interests are distinguished from hobbies or interests in typical development. We compared a group of children with ASD to a typically developing (TD) group of children with strong interests or hobbies, employing parent report, an operant behavioral task, and functional imaging with personalized stimuli based on individual interests. While performance on the operant task was similar between the two groups, parent report of intensity and interference of interests was significantly higher in the ASD group. Both the ASD and TD groups showed increased BOLD response in widespread affective neural regions to the pictures of their own interest. When viewing pictures of other children's interests, the TD group showed a similar pattern, whereas BOLD response in the ASD group was much more limited. Increased BOLD response in the insula and anterior cingulate cortex distinguished the ASD from the TD group, and parent report of the intensity and interference with daily life of the child's restricted interest predicted insula response. While affective neural network response and operant behavior are comparable in typical and restricted interests, the narrowness of focus that clinically distinguishes restricted interests in ASD is reflected in more interference in daily life and aberrantly enhanced insula and anterior cingulate response to individuals' own interests in the ASD group. These results further support the involvement of affective neural networks in repetitive behaviors in ASD. © 2013 The

Neural plasticity in functional and anatomical MRI studies of children with Tourette syndrome

DEFF Research Database (Denmark)

Eichele, Heike; Plessen, Kerstin J

2012-01-01

Background: Tourette syndrome (TS) is a neuropsychiatric disorder with childhood onset characterized by chronic motor and vocal tics. The typical clinical course of an attenuation of symptoms during adolescence in parallel with the emerging self-regulatory control during development suggests...... that plastic processes may play an important role in the development of tic symptoms. Methods: We conducted a systematic search to identify existing imaging studies (both anatomical and functional magnetic resonance imaging [fMRI]) in young persons under the age of 19 years with TS. Results: The final search...... compensatory pathways in children with TS. Along with alterations in regions putatively representing the origin of tics, deviations in several other regions most likely represent an activity-dependent neural plasticity that help to modulate tic severity, such as the prefrontal cortex, but also in the corpus...

Neural reflex pathways in intestinal inflammation: hypotheses to viable therapy

NARCIS (Netherlands)

Willemze, Rose A.; Luyer, Misha D.; Buurman, Wim A.; de Jonge, Wouter J.

2015-01-01

Studies in neuroscience and immunology have clarified much of the anatomical and cellular basis for bidirectional interactions between the nervous and immune systems. As with other organs, intestinal immune responses and the development of immunity seems to be modulated by neural reflexes.

Neural Networks

International Nuclear Information System (INIS)

Smith, Patrick I.

2003-01-01

Physicists use large detectors to measure particles created in high-energy collisions at particle accelerators. These detectors typically produce signals indicating either where ionization occurs along the path of the particle, or where energy is deposited by the particle. The data produced by these signals is fed into pattern recognition programs to try to identify what particles were produced, and to measure the energy and direction of these particles. Ideally, there are many techniques used in this pattern recognition software. One technique, neural networks, is particularly suitable for identifying what type of particle caused by a set of energy deposits. Neural networks can derive meaning from complicated or imprecise data, extract patterns, and detect trends that are too complex to be noticed by either humans or other computer related processes. To assist in the advancement of this technology, Physicists use a tool kit to experiment with several neural network techniques. The goal of this research is interface a neural network tool kit into Java Analysis Studio (JAS3), an application that allows data to be analyzed from any experiment. As the final result, a physicist will have the ability to train, test, and implement a neural network with the desired output while using JAS3 to analyze the results or output. Before an implementation of a neural network can take place, a firm understanding of what a neural network is and how it works is beneficial. A neural network is an artificial representation of the human brain that tries to simulate the learning process [5]. It is also important to think of the word artificial in that definition as computer programs that use calculations during the learning process. In short, a neural network learns by representative examples. Perhaps the easiest way to describe the way neural networks learn is to explain how the human brain functions. The human brain contains billions of neural cells that are responsible for processing

The neural signature of emotional memories in serial crimes.

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Chassy, Philippe

2017-10-01

Neural plasticity is the process whereby semantic information and emotional responses are stored in neural networks. It is hypothesized that the neural networks built over time to encode the sexual fantasies that motivate serial killers to act should display a unique, detectable activation pattern. The pathological neural watermark hypothesis posits that such networks comprise activation of brain sites that reflect four cognitive components: autobiographical memory, sexual arousal, aggression, and control over aggression. The neural sites performing these cognitive functions have been successfully identified by previous research. The key findings are reviewed to hypothesise the typical pattern of activity that serial killers should display. Through the integration of biological findings into one framework, the neural approach proposed in this paper is in stark contrast with the many theories accounting for serial killers that offer non-medical taxonomies. The pathological neural watermark hypothesis offers a new framework to understand and detect deviant individuals. The technical and legal issues are briefly discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Gear Fault Diagnosis Based on BP Neural Network

Science.gov (United States)

Huang, Yongsheng; Huang, Ruoshi

2018-03-01

Gear transmission is more complex, widely used in machinery fields, which form of fault has some nonlinear characteristics. This paper uses BP neural network to train the gear of four typical failure modes, and achieves satisfactory results. Tested by using test data, test results have an agreement with the actual results. The results show that the BP neural network can effectively solve the complex state of gear fault in the gear fault diagnosis.

Dissecting the hypothalamic pathways that underlie innate behaviors.

Science.gov (United States)

Zha, Xi; Xu, Xiaohong

2015-12-01

Many complex behaviors that do not require learning are displayed and are termed innate. Although traditionally the subject matter of ethology, innate behaviors offer a unique entry point for neuroscientists to dissect the physiological mechanisms governing complex behaviors. Since the last century, converging evidence has implicated the hypothalamus as the central brain area that controls innate behaviors. Recent studies using cutting-edge tools have revealed that genetically-defined populations of neurons residing in distinct hypothalamic nuclei and their associated neural pathways regulate the initiation and maintenance of diverse behaviors including feeding, sleep, aggression, and parental care. Here, we review the newly-defined hypothalamic pathways that regulate each innate behavior. In addition, emerging general principles of the neural control of complex behaviors are discussed.

Neural networks. A new analytical tool, applicable also in nuclear technology

Energy Technology Data Exchange (ETDEWEB)

Stritar, A [Inst. Jozef Stefan, Ljubljana (Slovenia)

1992-07-01

The basic concept of neural networks and back propagation learning algorithm are described. The behaviour of typical neural network is demonstrated on a simple graphical case. A short literature survey about the application of neural networks in nuclear science and engineering is made. The application of the neural network to the probability density calculation is shown. (author) [Slovenian] Opisana je osnova nevronskih mrez in back propagation nacina njihovega ucenja. Obnasanje enostavne nevronske mreze je prikazano na graficnem primeru. Podan je kratek pregled literaure o uporabi nevronskih mrez v jedrski znanosti in tehnologiji. Prikazana je tudi uporaba nevronske mreze pri izracunu verjetnostne porazdelitve. (author)

Dynamic changes in the inner ear function and vestibular neural pathway related to the progression of labyrinthine infarction in patient with an anterior inferior cerebellar artery infarction.

Science.gov (United States)

Kim, Duk Rim; Lee, Hyo-Jeong; Kim, Hyung-Jong; Hong, Sung Kwang

2011-12-01

To describe changes in the inner ear function and the vestibular neural pathway according to the progression of a labyrinthine infarction in a patient with an anterior inferior cerebellar artery (AICA) infarction. A 58-year-old woman with hypertension who presented with isolated inner ear symptoms similar to those of endolymphatic hydrops but finally progressed to an AICA infarction. Serial neurotologic testing according to progression to an AICA infarction and antiplatelet therapy. Radiologic findings and neurotologic parameters, including pure tone audiogram thresholds, spontaneous nystagmus, summating potentials/action potentials on electrocochleography, interaural amplitude difference on the vestibular-evoked myogenic potential test, canal paresis and fixation index on the bithermal caloric test, and gain on oculomotor tests. Our patient initially presented with sudden hearing loss and was diagnosed with an acute AICA infarction on a follow up MRI. Dynamic change in neurotologic testing was observed during disease progression. The vertigo and motion intolerance improved gradually after antiplatelet therapy. Changes in the clinical profile, which were documented during a transition from isolated labyrinthine ischemia to an AICA infarction, suggest that sensitivity to an ischemic injury is variable in different components of the labyrinthine organs in addition to providing a new insight into the response of vestibular neural pathway to ischemic injury.

A population of serumdeprivation-induced bone marrow stem cells (SD-BMSC) expresses marker typical for embryonic and neural stem cells

International Nuclear Information System (INIS)

Sauerzweig, Steven; Munsch, Thomas; Lessmann, Volkmar; Reymann, Klaus G.; Braun, Holger

2009-01-01

The bone marrow represents an easy accessible source of adult stem cells suitable for various cell based therapies. Several studies in recent years suggested the existence of pluripotent stem cells within bone marrow stem cells (BMSC) expressing marker proteins of both embryonic and tissue committed stem cells. These subpopulations were referred to as MAPC, MIAMI and VSEL-cells. Here we describe SD-BMSC (serumdeprivation-induced BMSC) which are induced as a distinct subpopulation after complete serumdeprivation. SD-BMSC are generated from small-sized nestin-positive BMSC (S-BMSC) organized as round-shaped cells in the top layer of BMSC-cultures. The generation of SD-BMSC is caused by a selective proliferation of S-BMSC and accompanied by changes in both morphology and gene expression. SD-BMSC up-regulate not only markers typical for neural stem cells like nestin and GFAP, but also proteins characteristic for embryonic cells like Oct4 and SOX2. We hypothesize, that SD-BMSC like MAPC, MIAMI and VSEL-cells represent derivatives from a single pluripotent stem cell fraction within BMSC exhibiting characteristics of embryonic and tissue committed stem cells. The complete removal of serum might offer a simple way to specifically enrich this fraction of pluripotent embryonic like stem cells in BMSC cultures

Noradrenergic modulation of neural erotic stimulus perception.

Science.gov (United States)

Graf, Heiko; Wiegers, Maike; Metzger, Coraline Danielle; Walter, Martin; Grön, Georg; Abler, Birgit

2017-09-01

We recently investigated neuromodulatory effects of the noradrenergic agent reboxetine and the dopamine receptor affine amisulpride in healthy subjects on dynamic erotic stimulus processing. Whereas amisulpride left sexual functions and neural activations unimpaired, we observed detrimental activations under reboxetine within the caudate nucleus corresponding to motivational components of sexual behavior. However, broadly impaired subjective sexual functioning under reboxetine suggested effects on further neural components. We now investigated the same sample under these two agents with static erotic picture stimulation as alternative stimulus presentation mode to potentially observe further neural treatment effects of reboxetine. 19 healthy males were investigated under reboxetine, amisulpride and placebo for 7 days each within a double-blind cross-over design. During fMRI static erotic picture were presented with preceding anticipation periods. Subjective sexual functions were assessed by a self-reported questionnaire. Neural activations were attenuated within the caudate nucleus, putamen, ventral striatum, the pregenual and anterior midcingulate cortex and in the orbitofrontal cortex under reboxetine. Subjective diminished sexual arousal under reboxetine was correlated with attenuated neural reactivity within the posterior insula. Again, amisulpride left neural activations along with subjective sexual functioning unimpaired. Neither reboxetine nor amisulpride altered differential neural activations during anticipation of erotic stimuli. Our results verified detrimental effects of noradrenergic agents on neural motivational but also emotional and autonomic components of sexual behavior. Considering the overlap of neural network alterations with those evoked by serotonergic agents, our results suggest similar neuromodulatory effects of serotonergic and noradrenergic agents on common neural pathways relevant for sexual behavior. Copyright © 2017 Elsevier B.V. and

Rac1 Guides Porf-2 to Wnt Pathway to Mediate Neural Stem Cell Proliferation

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Xi-Tao Yang

2017-06-01

Full Text Available The molecular and cellular mechanisms underlying the anti-proliferative effects of preoptic regulator factor 2 (Porf-2 on neural stem cells (NSCs remain largely unknown. Here, we found that Porf-2 inhibits the activity of ras-related C3 botulinum toxin substrate 1 (Rac1 protein in hippocampus-derived rat NSCs. Reduced Rac1 activity impaired the nuclear translocation of β-catenin, ultimately causing a repression of NSCs proliferation. Porf-2 knockdown enhanced NSCs proliferation but not in the presence of small molecule inhibitors of Rac1 or Wnt. At the same time, the repression of NSCs proliferation caused by Porf-2 overexpression was counteracted by small molecule activators of Rac1 or Wnt. By using a rat optic nerve crush model, we observed that Porf-2 knockdown enhanced the recovery of visual function. In particular, optic nerve injury in rats led to increased Wnt family member 3a (Wnt3a protein expression, which we found responsible for enhancing Porf-2 knockdown-induced NSCs proliferation. These findings suggest that Porf-2 exerts its inhibitory effect on NSCs proliferation via Rac1-Wnt/β-catenin pathway. Porf-2 may therefore represent and interesting target for optic nerve injury recovery and therapy.

Explicit versus implicit neural processing of musical emotions

OpenAIRE

Bogert, Brigitte; Numminen-Kontti, Taru; Gold, Benjamin; Sams, Mikko; Numminen, Jussi; Burunat, Iballa; Lampinen, Jouko; Brattico, Elvira

2016-01-01

Music is often used to regulate emotions and mood. Typically, music conveys and induces emotions even when one does not attend to them. Studies on the neural substrates of musical emotions have, however, only examined brain activity when subjects have focused on the emotional content of the music. Here we address with functional magnetic resonance imaging (fMRI) the neural processing of happy, sad, and fearful music with a paradigm in which 56 subjects were instructed to either classify the e...

Neural network approach to time-dependent dividing surfaces in classical reaction dynamics

Science.gov (United States)

Schraft, Philippe; Junginger, Andrej; Feldmaier, Matthias; Bardakcioglu, Robin; Main, Jörg; Wunner, Günter; Hernandez, Rigoberto

2018-04-01

In a dynamical system, the transition between reactants and products is typically mediated by an energy barrier whose properties determine the corresponding pathways and rates. The latter is the flux through a dividing surface (DS) between the two corresponding regions, and it is exact only if it is free of recrossings. For time-independent barriers, the DS can be attached to the top of the corresponding saddle point of the potential energy surface, and in time-dependent systems, the DS is a moving object. The precise determination of these direct reaction rates, e.g., using transition state theory, requires the actual construction of a DS for a given saddle geometry, which is in general a demanding methodical and computational task, especially in high-dimensional systems. In this paper, we demonstrate how such time-dependent, global, and recrossing-free DSs can be constructed using neural networks. In our approach, the neural network uses the bath coordinates and time as input, and it is trained in a way that its output provides the position of the DS along the reaction coordinate. An advantage of this procedure is that, once the neural network is trained, the complete information about the dynamical phase space separation is stored in the network's parameters, and a precise distinction between reactants and products can be made for all possible system configurations, all times, and with little computational effort. We demonstrate this general method for two- and three-dimensional systems and explain its straightforward extension to even more degrees of freedom.

Distinct pathways of neural coupling for different basic emotions.

Science.gov (United States)

Tettamanti, Marco; Rognoni, Elena; Cafiero, Riccardo; Costa, Tommaso; Galati, Dario; Perani, Daniela

2012-01-16

Emotions are complex events recruiting distributed cortical and subcortical cerebral structures, where the functional integration dynamics within the involved neural circuits in relation to the nature of the different emotions are still unknown. Using fMRI, we measured the neural responses elicited by films representing basic emotions (fear, disgust, sadness, happiness). The amygdala and the associative cortex were conjointly activated by all basic emotions. Furthermore, distinct arrays of cortical and subcortical brain regions were additionally activated by each emotion, with the exception of sadness. Such findings informed the definition of three effective connectivity models, testing for the functional integration of visual cortex and amygdala, as regions processing all emotions, with domain-specific regions, namely: i) for fear, the frontoparietal system involved in preparing adaptive motor responses; ii) for disgust, the somatosensory system, reflecting protective responses against contaminating stimuli; iii) for happiness: medial prefrontal and temporoparietal cortices involved in understanding joyful interactions. Consistently with these domain-specific models, the results of the effective connectivity analysis indicate that the amygdala is involved in distinct functional integration effects with cortical networks processing sensorimotor, somatosensory, or cognitive aspects of basic emotions. The resulting effective connectivity networks may serve to regulate motor and cognitive behavior based on the quality of the induced emotional experience. Copyright © 2011. Published by Elsevier Inc.

Neural correlates of consciousness: a definition of the dorsal and ventral streams and their relation to phenomenology.

Science.gov (United States)

Vakalopoulos, Costa

2005-01-01

The paper presents a hypothesis for a neural correlate of consciousness. A proposal is made that both the dorsal and ventral streams must be concurrently active to generate conscious awareness and that V1 (striate cortex) provides a serial link between them. An argument is presented against a true extrastriate communication between the dorsal and ventral streams. Secondly, a detailed theory is developed for the structure of the visual hierarchy. Premotor theory states that each organism-object interaction can be described by the two quantitative measures of torque and change in joint position served by the basal ganglia and cerebellum, respectively. This leads to a component theory of motor efference copy providing a fundamental tool for categorizing dorsal and ventral stream networks. The rationale for this is that the dorsal stream specifies spatial coordinates of the external world, which can be coded by the reafference of changes in joint position. The ventral stream is concerned with object recognition and is coded for by forces exerted on the world during a developmental exploratory phase of the organism. The proposed pathways for a component motor efference copy from both the cerebellum and basal ganglia converge on the thalamus and modulate thalamocortical projections via the thalamic reticular nucleus. The origin of the corticopontine projections, which are a massive pathway for cortical information to reach the cerebellum, coincides with the area typically considered as part of the dorsal stream, whereas the entire cortex projects to the striatum. This adds empirical support for a new conceptualization of the visual streams. The model also presents a solution to the binding problem of a neural correlate of consciousness, that is, how a distributed neural network synchronizes its activity during a cognitive event. It represents a reinterpretation of the current status of the visual hierarchy.

Neural computational modeling reveals a major role of corticospinal gating of central oscillations in the generation of essential tremor

Directory of Open Access Journals (Sweden)

Hong-en Qu

2017-01-01

Full Text Available Essential tremor, also referred to as familial tremor, is an autosomal dominant genetic disease and the most common movement disorder. It typically involves a postural and motor tremor of the hands, head or other part of the body. Essential tremor is driven by a central oscillation signal in the brain. However, the corticospinal mechanisms involved in the generation of essential tremor are unclear. Therefore, in this study, we used a neural computational model that includes both monosynaptic and multisynaptic corticospinal pathways interacting with a propriospinal neuronal network. A virtual arm model is driven by the central oscillation signal to simulate tremor activity behavior. Cortical descending commands are classified as alpha or gamma through monosynaptic or multisynaptic corticospinal pathways, which converge respectively on alpha or gamma motoneurons in the spinal cord. Several scenarios are evaluated based on the central oscillation signal passing down to the spinal motoneurons via each descending pathway. The simulated behaviors are compared with clinical essential tremor characteristics to identify the corticospinal pathways responsible for transmitting the central oscillation signal. A propriospinal neuron with strong cortical inhibition performs a gating function in the generation of essential tremor. Our results indicate that the propriospinal neuronal network is essential for relaying the central oscillation signal and the production of essential tremor.

Neural computational modeling reveals a major role of corticospinal gating of central oscillations in the generation of essential tremor.

Science.gov (United States)

Qu, Hong-En; Niu, Chuanxin M; Li, Si; Hao, Man-Zhao; Hu, Zi-Xiang; Xie, Qing; Lan, Ning

2017-12-01

Essential tremor, also referred to as familial tremor, is an autosomal dominant genetic disease and the most common movement disorder. It typically involves a postural and motor tremor of the hands, head or other part of the body. Essential tremor is driven by a central oscillation signal in the brain. However, the corticospinal mechanisms involved in the generation of essential tremor are unclear. Therefore, in this study, we used a neural computational model that includes both monosynaptic and multisynaptic corticospinal pathways interacting with a propriospinal neuronal network. A virtual arm model is driven by the central oscillation signal to simulate tremor activity behavior. Cortical descending commands are classified as alpha or gamma through monosynaptic or multisynaptic corticospinal pathways, which converge respectively on alpha or gamma motoneurons in the spinal cord. Several scenarios are evaluated based on the central oscillation signal passing down to the spinal motoneurons via each descending pathway. The simulated behaviors are compared with clinical essential tremor characteristics to identify the corticospinal pathways responsible for transmitting the central oscillation signal. A propriospinal neuron with strong cortical inhibition performs a gating function in the generation of essential tremor. Our results indicate that the propriospinal neuronal network is essential for relaying the central oscillation signal and the production of essential tremor.

Xenopus reduced folate carrier regulates neural crest development epigenetically.

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Jiejing Li

Full Text Available Folic acid deficiency during pregnancy causes birth neurocristopathic malformations resulting from aberrant development of neural crest cells. The Reduced folate carrier (RFC is a membrane-bound receptor for facilitating transfer of reduced folate into the cells. RFC knockout mice are embryonic lethal and develop multiple malformations, including neurocristopathies. Here we show that XRFC is specifically expressed in neural crest tissues in Xenopus embryos and knockdown of XRFC by specific morpholino results in severe neurocristopathies. Inhibition of RFC blocked the expression of a series of neural crest marker genes while overexpression of RFC or injection of 5-methyltetrahydrofolate expanded the neural crest territories. In animal cap assays, knockdown of RFC dramatically reduced the mono- and trimethyl-Histone3-K4 levels and co-injection of the lysine methyltransferase hMLL1 largely rescued the XRFC morpholino phenotype. Our data revealed that the RFC mediated folate metabolic pathway likely potentiates neural crest gene expression through epigenetic modifications.

Self-reported empathy and neural activity during action imitation and observation in schizophrenia

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William P. Horan

2014-01-01

Conclusions: Although patients with schizophrenia demonstrated largely normal patterns of neural activation across the finger movement and facial expression tasks, they reported decreased self perceived empathy and failed to show the typical relationship between neural activity and self-reported empathy seen in controls. These findings suggest that patients show a disjunction between automatic neural responses to low level social cues and higher level, integrative social cognitive processes involved in self-perceived empathy.

The neural circuits that generate tics in Tourette's syndrome.

Science.gov (United States)

Wang, Zhishun; Maia, Tiago V; Marsh, Rachel; Colibazzi, Tiziano; Gerber, Andrew; Peterson, Bradley S

2011-12-01

The purpose of this study was to examine neural activity and connectivity within cortico-striato-thalamo-cortical circuits and to reveal circuit-based neural mechanisms that govern tic generation in Tourette's syndrome. Functional magnetic resonance imaging data were acquired from 13 individuals with Tourette's syndrome and 21 healthy comparison subjects during spontaneous or simulated tics. Independent component analysis with hierarchical partner matching was used to isolate neural activity within functionally distinct regions of cortico-striato-thalamo-cortical circuits. Granger causality was used to investigate causal interactions among these regions. The Tourette's syndrome group exhibited stronger neural activity and interregional causality than healthy comparison subjects throughout all portions of the motor pathway, including the sensorimotor cortex, putamen, pallidum, and substantia nigra. Activity in these areas correlated positively with the severity of tic symptoms. Activity within the Tourette's syndrome group was stronger during spontaneous tics than during voluntary tics in the somatosensory and posterior parietal cortices, putamen, and amygdala/hippocampus complex, suggesting that activity in these regions may represent features of the premonitory urges that generate spontaneous tic behaviors. In contrast, activity was weaker in the Tourette's syndrome group than in the healthy comparison group within portions of cortico-striato-thalamo-cortical circuits that exert top-down control over motor pathways (the caudate and anterior cingulate cortex), and progressively less activity in these regions accompanied more severe tic symptoms, suggesting that faulty activity in these circuits may result in their failure to control tic behaviors or the premonitory urges that generate them. Our findings, taken together, suggest that tics are caused by the combined effects of excessive activity in motor pathways and reduced activation in control portions of cortico

The Neural Correlates of Moral Thinking: A Meta-Analysis

OpenAIRE

Douglas J. Bryant; Wang F; Kelley Deardeuff; Emily Zoccoli; Chang S. Nam

2016-01-01

We conducted a meta-analysis to evaluate current research that aims to map the neural correlates of two typical conditions of moral judgment: right-wrong moral judgments and decision-making in moral dilemmas. Utilizing the activation likelihood estimation (ALE) method, we conducted a meta-analysis using neuroimaging data obtained from twenty-one previous studies that measured responses in one or the other of these conditions. We found that across the studies (n = 400), distinct neural circuit...

Hedgehog signaling pathway in neuroblastoma differentiation.

Science.gov (United States)

Souzaki, Ryota; Tajiri, Tatsuro; Souzaki, Masae; Kinoshita, Yoshiaki; Tanaka, Sakura; Kohashi, Kenichi; Oda, Yoshinao; Katano, Mitsuo; Taguchi, Tomoaki

2010-12-01

The hedgehog (Hh) signaling pathway is activated in some adult cancers. On the other hand, the Hh signaling pathway plays an important role in the development of the neural crest in embryos. The aim of this study is to show the activation of Hh signaling pathway in neuroblastoma (NB), a pediatric malignancy arising from neural crest cells, and to reveal the meaning of the Hh signaling pathway in NB development. This study analyzed the expression of Sonic hedgehog (Shh), GLI1, and Patched 1 (Ptch1), transactivators of Hh signaling pathway, by immunohistochemistry in 82 NB and 10 ganglioneuroblastoma cases. All 92 cases were evaluated for the status of MYCN amplification. Of the 92 cases, 67 (73%) were positive for Shh, 62 cases (67%) were positive for GLI1, and 73 cases (79%) were positive for Ptch1. Only 2 (10%) of the 20 cases with MYCN amplification were positive for Shh and GLI1, and 4 cases (20%) were positive for Ptch1 (MYCN amplification vs no MYCN amplification, P ≦ .01). The percentage of GLI1-positive cells in the cases with INSS stage 1 without MYCN amplification was significantly higher than that with INSS stage 4. Of 72 cases without MYCN amplification, 60 were GLI1-positive. Twelve cases were GLI1-negative, and the prognosis of the GLI1-positive cases was significantly better than that of the GLI1-negative cases (P = .015). Most of NBs without MYCN amplification were positive for Shh, GLI1, and Ptch1. In the cases without MYCN amplification, the high expression of GLI1 was significantly associated with early clinical stage and a good prognosis of the patients. In contrast to adult cancers, the activation of the Hh signaling pathway in NB may be associated with the differentiation of the NB. Copyright © 2010 Elsevier Inc. All rights reserved.

Normalization as a canonical neural computation

Science.gov (United States)

Carandini, Matteo; Heeger, David J.

2012-01-01

There is increasing evidence that the brain relies on a set of canonical neural computations, repeating them across brain regions and modalities to apply similar operations to different problems. A promising candidate for such a computation is normalization, in which the responses of neurons are divided by a common factor that typically includes the summed activity of a pool of neurons. Normalization was developed to explain responses in the primary visual cortex and is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions. Normalization may underlie operations such as the representation of odours, the modulatory effects of visual attention, the encoding of value and the integration of multisensory information. Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that it serves as a canonical neural computation. PMID:22108672

The neural subjective frame: from bodily signals to perceptual consciousness.

Science.gov (United States)

Park, Hyeong-Dong; Tallon-Baudry, Catherine

2014-05-05

The report 'I saw the stimulus' operationally defines visual consciousness, but where does the 'I' come from? To account for the subjective dimension of perceptual experience, we introduce the concept of the neural subjective frame. The neural subjective frame would be based on the constantly updated neural maps of the internal state of the body and constitute a neural referential from which first person experience can be created. We propose to root the neural subjective frame in the neural representation of visceral information which is transmitted through multiple anatomical pathways to a number of target sites, including posterior insula, ventral anterior cingulate cortex, amygdala and somatosensory cortex. We review existing experimental evidence showing that the processing of external stimuli can interact with visceral function. The neural subjective frame is a low-level building block of subjective experience which is not explicitly experienced by itself which is necessary but not sufficient for perceptual experience. It could also underlie other types of subjective experiences such as self-consciousness and emotional feelings. Because the neural subjective frame is tightly linked to homeostatic regulations involved in vigilance, it could also make a link between state and content consciousness.

Interactive extraction of neural structures with user-guided morphological diffusion

KAUST Repository

Yong Wan,; Otsuna, H.; Chi-Bin Chien,; Hansen, C.

2012-01-01

Extracting neural structures with their fine details from confocal volumes is essential to quantitative analysis in neurobiology research. Despite the abundance of various segmentation methods and tools, for complex neural structures, both manual and semi-automatic methods are ine ective either in full 3D or when user interactions are restricted to 2D slices. Novel interaction techniques and fast algorithms are demanded by neurobiologists to interactively and intuitively extract neural structures from confocal data. In this paper, we present such an algorithm-technique combination, which lets users interactively select desired structures from visualization results instead of 2D slices. By integrating the segmentation functions with a confocal visualization tool neurobiologists can easily extract complex neural structures within their typical visualization workflow.

Interactive extraction of neural structures with user-guided morphological diffusion

KAUST Repository

Yong Wan,

2012-10-01

Extracting neural structures with their fine details from confocal volumes is essential to quantitative analysis in neurobiology research. Despite the abundance of various segmentation methods and tools, for complex neural structures, both manual and semi-automatic methods are ine ective either in full 3D or when user interactions are restricted to 2D slices. Novel interaction techniques and fast algorithms are demanded by neurobiologists to interactively and intuitively extract neural structures from confocal data. In this paper, we present such an algorithm-technique combination, which lets users interactively select desired structures from visualization results instead of 2D slices. By integrating the segmentation functions with a confocal visualization tool neurobiologists can easily extract complex neural structures within their typical visualization workflow.

Artificial intelligence. Application of the Statistical Neural Networks computer program in nuclear medicine

International Nuclear Information System (INIS)

Stefaniak, B.; Cholewinski, W.; Tarkowska, A.

2005-01-01

Artificial Neural Networks (ANN) may be a tool alternative and complementary to typical statistical analysis. However, in spite of many computer application of various ANN algorithms ready for use, artificial intelligence is relatively rarely applied to data processing. In this paper practical aspects of scientific application of ANN in medicine using the Statistical Neural Networks Computer program, were presented. Several steps of data analysis with the above ANN software package were discussed shortly, from material selection and its dividing into groups to the types of obtained results. The typical problems connected with assessing scintigrams by ANN were also described. (author)

A wirelessly powered microspectrometer for neural probe-pin device

Science.gov (United States)

Choi, Sang H.; Kim, Min H.; Song, Kyo D.; Yoon, Hargsoon; Lee, Uhn

2015-12-01

Treatment of neurological anomalies, whether done invasively or not, places stringent demands on device functionality and size. We have developed a micro-spectrometer for use as an implantable neural probe to monitor neuro-chemistry in synapses. The micro-spectrometer, based on a NASA-invented miniature Fresnel grating, is capable of differentiating the emission spectra from various brain tissues. The micro-spectrometer meets the size requirements, and is able to probe the neuro-chemistry and suppression voltage typically associated with a neural anomaly. This neural probe-pin device (PPD) is equipped with wireless power technology (WPT) to enable operation in a continuous manner without requiring an implanted battery. The implanted neural PPD, together with a neural electronics interface and WPT, enable real-time measurement and control/feedback for remediation of neural anomalies. The design and performance of the combined PPD/WPT device for monitoring dopamine in a rat brain will be presented to demonstrate the current level of development. Future work on this device will involve the addition of an embedded expert system capable of performing semi-autonomous management of neural functions through a routine of sensing, processing, and control.

Neuron's eye view: Inferring features of complex stimuli from neural responses.

Directory of Open Access Journals (Sweden)

Xin Chen

2017-08-01

Full Text Available Experiments that study neural encoding of stimuli at the level of individual neurons typically choose a small set of features present in the world-contrast and luminance for vision, pitch and intensity for sound-and assemble a stimulus set that systematically varies along these dimensions. Subsequent analysis of neural responses to these stimuli typically focuses on regression models, with experimenter-controlled features as predictors and spike counts or firing rates as responses. Unfortunately, this approach requires knowledge in advance about the relevant features coded by a given population of neurons. For domains as complex as social interaction or natural movement, however, the relevant feature space is poorly understood, and an arbitrary a priori choice of features may give rise to confirmation bias. Here, we present a Bayesian model for exploratory data analysis that is capable of automatically identifying the features present in unstructured stimuli based solely on neuronal responses. Our approach is unique within the class of latent state space models of neural activity in that it assumes that firing rates of neurons are sensitive to multiple discrete time-varying features tied to the stimulus, each of which has Markov (or semi-Markov dynamics. That is, we are modeling neural activity as driven by multiple simultaneous stimulus features rather than intrinsic neural dynamics. We derive a fast variational Bayesian inference algorithm and show that it correctly recovers hidden features in synthetic data, as well as ground-truth stimulus features in a prototypical neural dataset. To demonstrate the utility of the algorithm, we also apply it to cluster neural responses and demonstrate successful recovery of features corresponding to monkeys and faces in the image set.

Liquid pathways generic studies; results, interpretation, and design implications

International Nuclear Information System (INIS)

Walker, D.H.; Nutant, J.A.

1980-01-01

Offshore Power Systems and the Nuclear Regulatory Commission have evaluated dose consequences resulting from a release of radioactivity to liquid pathways following a postulated core-melt accident. The objective of these studies was to compare the risks from postulated core-melt accidents for the Floating Nuclear Plant with those for a typical land-based nuclear plant. Offshore Power Systems concluded that the differences in liquid pathway risks between plant types are not significant when compared with the air pathways risks. Air pathways risk is similar to or significantly larger than liquid pathways risk depending on the accident scenario. The Nuclear Regulatory Commission judged the liquid pathways risks from the Floating Nuclear Plant to be significantly greater than the liquid pathway risks for the typical land-based plant. Although OPS disagrees with the NRC judgment, design changes dictated by the NRC are being implemented by OPS

Identifying Broadband Rotational Spectra with Neural Networks

Science.gov (United States)

Zaleski, Daniel P.; Prozument, Kirill

2017-06-01

A typical broadband rotational spectrum may contain several thousand observable transitions, spanning many species. Identifying the individual spectra, particularly when the dynamic range reaches 1,000:1 or even 10,000:1, can be challenging. One approach is to apply automated fitting routines. In this approach, combinations of 3 transitions can be created to form a "triple", which allows fitting of the A, B, and C rotational constants in a Watson-type Hamiltonian. On a standard desktop computer, with a target molecule of interest, a typical AUTOFIT routine takes 2-12 hours depending on the spectral density. A new approach is to utilize machine learning to train a computer to recognize the patterns (frequency spacing and relative intensities) inherit in rotational spectra and to identify the individual spectra in a raw broadband rotational spectrum. Here, recurrent neural networks have been trained to identify different types of rotational spectra and classify them accordingly. Furthermore, early results in applying convolutional neural networks for spectral object recognition in broadband rotational spectra appear promising. Perez et al. "Broadband Fourier transform rotational spectroscopy for structure determination: The water heptamer." Chem. Phys. Lett., 2013, 571, 1-15. Seifert et al. "AUTOFIT, an Automated Fitting Tool for Broadband Rotational Spectra, and Applications to 1-Hexanal." J. Mol. Spectrosc., 2015, 312, 13-21. Bishop. "Neural networks for pattern recognition." Oxford university press, 1995.

Localizing Tortoise Nests by Neural Networks.

Directory of Open Access Journals (Sweden)

Roberto Barbuti

Full Text Available The goal of this research is to recognize the nest digging activity of tortoises using a device mounted atop the tortoise carapace. The device classifies tortoise movements in order to discriminate between nest digging, and non-digging activity (specifically walking and eating. Accelerometer data was collected from devices attached to the carapace of a number of tortoises during their two-month nesting period. Our system uses an accelerometer and an activity recognition system (ARS which is modularly structured using an artificial neural network and an output filter. For the purpose of experiment and comparison, and with the aim of minimizing the computational cost, the artificial neural network has been modelled according to three different architectures based on the input delay neural network (IDNN. We show that the ARS can achieve very high accuracy on segments of data sequences, with an extremely small neural network that can be embedded in programmable low power devices. Given that digging is typically a long activity (up to two hours, the application of ARS on data segments can be repeated over time to set up a reliable and efficient system, called Tortoise@, for digging activity recognition.

Neural Differentiation of Human Adipose Tissue-Derived Stem Cells Involves Activation of the Wnt5a/JNK Signalling

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Sujeong Jang

2015-01-01

Full Text Available Stem cells are a powerful resource for cell-based transplantation therapies, but understanding of stem cell differentiation at the molecular level is not clear yet. We hypothesized that the Wnt pathway controls stem cell maintenance and neural differentiation. We have characterized the transcriptional expression of Wnt during the neural differentiation of hADSCs. After neural induction, the expressions of Wnt2, Wnt4, and Wnt11 were decreased, but the expression of Wnt5a was increased compared with primary hADSCs in RT-PCR analysis. In addition, the expression levels of most Fzds and LRP5/6 ligand were decreased, but not Fzd3 and Fzd5. Furthermore, Dvl1 and RYK expression levels were downregulated in NI-hADSCs. There were no changes in the expression of ß-catenin and GSK3ß. Interestingly, Wnt5a expression was highly increased in NI-hADSCs by real time RT-PCR analysis and western blot. Wnt5a level was upregulated after neural differentiation and Wnt3, Dvl2, and Naked1 levels were downregulated. Finally, we found that the JNK expression was increased after neural induction and ERK level was decreased. Thus, this study shows for the first time how a single Wnt5a ligand can activate the neural differentiation pathway through the activation of Wnt5a/JNK pathway by binding Fzd3 and Fzd5 and directing Axin/GSK-3ß in hADSCs.

Phase transitions in vector quantization and neural gas

NARCIS (Netherlands)

Witoelar, Aree; Biehl, Michael

The statistical physics of off-learning is applied to winner-takes-all (WTA) and rank-based vector quantization (VQ), including the neural gas (NG). The analysis is based on the limit of high training temperatures and the annealed approximation. The typical learning behavior is evaluated for systems

Mechanisms underlying metabolic and neural defects in zebrafish and human multiple acyl-CoA dehydrogenase deficiency (MADD.

Directory of Open Access Journals (Sweden)

Yuanquan Song

2009-12-01

Full Text Available In humans, mutations in electron transfer flavoprotein (ETF or electron transfer flavoprotein dehydrogenase (ETFDH lead to MADD/glutaric aciduria type II, an autosomal recessively inherited disorder characterized by a broad spectrum of devastating neurological, systemic and metabolic symptoms. We show that a zebrafish mutant in ETFDH, xavier, and fibroblast cells from MADD patients demonstrate similar mitochondrial and metabolic abnormalities, including reduced oxidative phosphorylation, increased aerobic glycolysis, and upregulation of the PPARG-ERK pathway. This metabolic dysfunction is associated with aberrant neural proliferation in xav, in addition to other neural phenotypes and paralysis. Strikingly, a PPARG antagonist attenuates aberrant neural proliferation and alleviates paralysis in xav, while PPARG agonists increase neural proliferation in wild type embryos. These results show that mitochondrial dysfunction, leading to an increase in aerobic glycolysis, affects neurogenesis through the PPARG-ERK pathway, a potential target for therapeutic intervention.

Chemically Induced Reprogramming of Somatic Cells to Pluripotent Stem Cells and Neural Cells.

Science.gov (United States)

Biswas, Dhruba; Jiang, Peng

2016-02-06

The ability to generate transplantable neural cells in a large quantity in the laboratory is a critical step in the field of developing stem cell regenerative medicine for neural repair. During the last few years, groundbreaking studies have shown that cell fate of adult somatic cells can be reprogrammed through lineage specific expression of transcription factors (TFs)-and defined culture conditions. This key concept has been used to identify a number of potent small molecules that could enhance the efficiency of reprogramming with TFs. Recently, a growing number of studies have shown that small molecules targeting specific epigenetic and signaling pathways can replace all of the reprogramming TFs. Here, we provide a detailed review of the studies reporting the generation of chemically induced pluripotent stem cells (ciPSCs), neural stem cells (ciNSCs), and neurons (ciN). We also discuss the main mechanisms of actions and the pathways that the small molecules regulate during chemical reprogramming.

ChainMail based neural dynamics modeling of soft tissue deformation for surgical simulation.

Science.gov (United States)

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.

The Neural Basis of Vocal Pitch Imitation in Humans.

Science.gov (United States)

Belyk, Michel; Pfordresher, Peter Q; Liotti, Mario; Brown, Steven

2016-04-01

Vocal imitation is a phenotype that is unique to humans among all primate species, and so an understanding of its neural basis is critical in explaining the emergence of both speech and song in human evolution. Two principal neural models of vocal imitation have emerged from a consideration of nonhuman animals. One hypothesis suggests that putative mirror neurons in the inferior frontal gyrus pars opercularis of Broca's area may be important for imitation. An alternative hypothesis derived from the study of songbirds suggests that the corticostriate motor pathway performs sensorimotor processes that are specific to vocal imitation. Using fMRI with a sparse event-related sampling design, we investigated the neural basis of vocal imitation in humans by comparing imitative vocal production of pitch sequences with both nonimitative vocal production and pitch discrimination. The strongest difference between these tasks was found in the putamen bilaterally, providing a striking parallel to the role of the analogous region in songbirds. Other areas preferentially activated during imitation included the orofacial motor cortex, Rolandic operculum, and SMA, which together outline the corticostriate motor loop. No differences were seen in the inferior frontal gyrus. The corticostriate system thus appears to be the central pathway for vocal imitation in humans, as predicted from an analogy with songbirds.

Applying neural networks as software sensors for enzyme engineering.

Science.gov (United States)

Linko, S; Zhu, Y H; Linko, P

1999-04-01

The on-line control of enzyme-production processes is difficult, owing to the uncertainties typical of biological systems and to the lack of suitable on-line sensors for key process variables. For example, intelligent methods to predict the end point of fermentation could be of great economic value. Computer-assisted control based on artificial-neural-network models offers a novel solution in such situations. Well-trained feedforward-backpropagation neural networks can be used as software sensors in enzyme-process control; their performance can be affected by a number of factors.

Epigenetic regulation of the Hedgehog and Wnt pathways in cancer

NARCIS (Netherlands)

Wils, Leon J.; Bijlsma, Maarten F.

2018-01-01

The Hedgehog (Hh) and wingless-Int1 (Wnt) pathways are important for tissue patterning in the developing embryo. In adult tissue, both pathways are typically dormant but are activated under certain conditions such as tissue damage. Aberrant activation of these pathways by mutations in key pathway

Human neural progenitors express functional lysophospholipid receptors that regulate cell growth and morphology

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Callihan Phillip

2008-12-01

Full Text Available Abstract Background Lysophospholipids regulate the morphology and growth of neurons, neural cell lines, and neural progenitors. A stable human neural progenitor cell line is not currently available in which to study the role of lysophospholipids in human neural development. We recently established a stable, adherent human embryonic stem cell-derived neuroepithelial (hES-NEP cell line which recapitulates morphological and phenotypic features of neural progenitor cells isolated from fetal tissue. The goal of this study was to determine if hES-NEP cells express functional lysophospholipid receptors, and if activation of these receptors mediates cellular responses critical for neural development. Results Our results demonstrate that Lysophosphatidic Acid (LPA and Sphingosine-1-phosphate (S1P receptors are functionally expressed in hES-NEP cells and are coupled to multiple cellular signaling pathways. We have shown that transcript levels for S1P1 receptor increased significantly in the transition from embryonic stem cell to hES-NEP. hES-NEP cells express LPA and S1P receptors coupled to Gi/o G-proteins that inhibit adenylyl cyclase and to Gq-like phospholipase C activity. LPA and S1P also induce p44/42 ERK MAP kinase phosphorylation in these cells and stimulate cell proliferation via Gi/o coupled receptors in an Epidermal Growth Factor Receptor (EGFR- and ERK-dependent pathway. In contrast, LPA and S1P stimulate transient cell rounding and aggregation that is independent of EGFR and ERK, but dependent on the Rho effector p160 ROCK. Conclusion Thus, lysophospholipids regulate neural progenitor growth and morphology through distinct mechanisms. These findings establish human ES cell-derived NEP cells as a model system for studying the role of lysophospholipids in neural progenitors.

YAP/TAZ enhance mammalian embryonic neural stem cell characteristics in a Tead-dependent manner

Energy Technology Data Exchange (ETDEWEB)

Han, Dasol; Byun, Sung-Hyun; Park, Soojeong; Kim, Juwan; Kim, Inhee; Ha, Soobong; Kwon, Mookwang; Yoon, Keejung, E-mail: keejung@skku.edu

2015-02-27

Mammalian brain development is regulated by multiple signaling pathways controlling cell proliferation, migration and differentiation. Here we show that YAP/TAZ enhance embryonic neural stem cell characteristics in a cell autonomous fashion using diverse experimental approaches. Introduction of retroviral vectors expressing YAP or TAZ into the mouse embryonic brain induced cell localization in the ventricular zone (VZ), which is the embryonic neural stem cell niche. This change in cell distribution in the cortical layer is due to the increased stemness of infected cells; YAP-expressing cells were colabeled with Sox2, a neural stem cell marker, and YAP/TAZ increased the frequency and size of neurospheres, indicating enhanced self-renewal- and proliferative ability of neural stem cells. These effects appear to be TEA domain family transcription factor (Tead)–dependent; a Tead binding-defective YAP mutant lost the ability to promote neural stem cell characteristics. Consistently, in utero gene transfer of a constitutively active form of Tead2 (Tead2-VP16) recapitulated all the features of YAP/TAZ overexpression, and dominant negative Tead2-EnR resulted in marked cell exit from the VZ toward outer cortical layers. Taken together, these results indicate that the Tead-dependent YAP/TAZ signaling pathway plays important roles in neural stem cell maintenance by enhancing stemness of neural stem cells during mammalian brain development. - Highlights: • Roles of YAP and Tead in vivo during mammalian brain development are clarified. • Expression of YAP promotes embryonic neural stem cell characteristics in vivo in a cell autonomous fashion. • Enhancement of neural stem cell characteristics by YAP depends on Tead. • Transcriptionally active form of Tead alone can recapitulate the effects of YAP. • Transcriptionally repressive form of Tead severely reduces stem cell characteristics.

YAP/TAZ enhance mammalian embryonic neural stem cell characteristics in a Tead-dependent manner

International Nuclear Information System (INIS)

Han, Dasol; Byun, Sung-Hyun; Park, Soojeong; Kim, Juwan; Kim, Inhee; Ha, Soobong; Kwon, Mookwang; Yoon, Keejung

2015-01-01

Mammalian brain development is regulated by multiple signaling pathways controlling cell proliferation, migration and differentiation. Here we show that YAP/TAZ enhance embryonic neural stem cell characteristics in a cell autonomous fashion using diverse experimental approaches. Introduction of retroviral vectors expressing YAP or TAZ into the mouse embryonic brain induced cell localization in the ventricular zone (VZ), which is the embryonic neural stem cell niche. This change in cell distribution in the cortical layer is due to the increased stemness of infected cells; YAP-expressing cells were colabeled with Sox2, a neural stem cell marker, and YAP/TAZ increased the frequency and size of neurospheres, indicating enhanced self-renewal- and proliferative ability of neural stem cells. These effects appear to be TEA domain family transcription factor (Tead)–dependent; a Tead binding-defective YAP mutant lost the ability to promote neural stem cell characteristics. Consistently, in utero gene transfer of a constitutively active form of Tead2 (Tead2-VP16) recapitulated all the features of YAP/TAZ overexpression, and dominant negative Tead2-EnR resulted in marked cell exit from the VZ toward outer cortical layers. Taken together, these results indicate that the Tead-dependent YAP/TAZ signaling pathway plays important roles in neural stem cell maintenance by enhancing stemness of neural stem cells during mammalian brain development. - Highlights: • Roles of YAP and Tead in vivo during mammalian brain development are clarified. • Expression of YAP promotes embryonic neural stem cell characteristics in vivo in a cell autonomous fashion. • Enhancement of neural stem cell characteristics by YAP depends on Tead. • Transcriptionally active form of Tead alone can recapitulate the effects of YAP. • Transcriptionally repressive form of Tead severely reduces stem cell characteristics

Andrographolide Promotes Neural Differentiation of Rat Adipose Tissue-Derived Stromal Cells through Wnt/β-Catenin Signaling Pathway

Directory of Open Access Journals (Sweden)

Yan Liang

2017-01-01

Full Text Available Adipose tissue-derived stromal cells (ADSCs are a high-yield source of pluripotent stem cells for use in cell-based therapies. We explored the effect of andrographolide (ANDRO, one of the ingredients of the medicinal herb extract on the neural differentiation of rat ADSCs and associated molecular mechanisms. We observed that rat ADSCs were small and spindle-shaped and expressed multiple stem cell markers including nestin. They were multipotent as evidenced by adipogenic, osteogenic, chondrogenic, and neural differentiation under appropriate conditions. The proportion of cells exhibiting neural-like morphology was higher, and neurites developed faster in the ANDRO group than in the control group in the same neural differentiation medium. Expression levels of the neural lineage markers MAP2, tau, GFAP, and β-tubulin III were higher in the ANDRO group. ANDRO induced a concentration-dependent increase in Wnt/β-catenin signaling as evidenced by the enhanced expression of nuclear β-catenin and the inhibited form of GSK-3β (pSer9. Thus, this study shows for the first time how by enhancing the neural differentiation of ADSCs we expect that ANDRO pretreatment may increase the efficacy of adult stem cell transplantation in nervous system diseases, but more exploration is needed.

Pattern Recognition and Classification of Fatal Traffic Accidents in Israel A Neural Network Approach

DEFF Research Database (Denmark)

Prato, Carlo Giacomo; Gitelman, Victoria; Bekhor, Shlomo

2011-01-01

on 1,793 fatal traffic accidents occurred during the period between 2003 and 2006 and applies Kohonen and feed-forward back-propagation neural networks with the objective of extracting from the data typical patterns and relevant factors. Kohonen neural networks reveal five compelling accident patterns....... Feed-forward back-propagation neural networks indicate that sociodemographic characteristics of drivers and victims, accident location, and period of the day are extremely relevant factors. Accident patterns suggest that countermeasures are necessary for identified problems concerning mainly vulnerable...

Hepatocyte growth factor/scatter factor-MET signaling in neural crest-derived melanocyte development.

Science.gov (United States)

Kos, L; Aronzon, A; Takayama, H; Maina, F; Ponzetto, C; Merlino, G; Pavan, W

1999-02-01

The mechanisms governing development of neural crest-derived melanocytes, and how alterations in these pathways lead to hypopigmentation disorders, are not completely understood. Hepatocyte growth factor/scatter factor (HGF/SF) signaling through the tyrosine-kinase receptor, MET, is capable of promoting the proliferation, increasing the motility, and maintaining high tyrosinase activity and melanin synthesis of melanocytes in vitro. In addition, transgenic mice that ubiquitously overexpress HGF/SF demonstrate hyperpigmentation in the skin and leptomenigenes and develop melanomas. To investigate whether HGF/ SF-MET signaling is involved in the development of neural crest-derived melanocytes, transgenic embryos, ubiquitously overexpressing HGF/SF, were analyzed. In HGF/SF transgenic embryos, the distribution of melanoblasts along the characteristic migratory pathway was not affected. However, additional ectopically localized melanoblasts were also observed in the dorsal root ganglia and neural tube, as early as 11.5 days post coitus (p.c.). We utilized an in vitro neural crest culture assay to further explore the role of HGF/SF-MET signaling in neural crest development. HGF/SF added to neural crest cultures increased melanoblast number, permitted differentiation into pigmented melanocytes, promoted melanoblast survival, and could replace mast-cell growth factor/Steel factor (MGF) in explant cultures. To examine whether HGF/SF-MET signaling is required for the proper development of melanocytes, embryos with a targeted Met null mutation (Met-/-) were analysed. In Met-/- embryos, melanoblast number and location were not overtly affected up to 14 days p.c. These results demonstrate that HGF/SF-MET signaling influences, but is not required for, the initial development of neural crest-derived melanocytes in vivo and in vitro.

Fractionating the Neural Substrates of Incidental Recognition Memory

Science.gov (United States)

Greene, Ciara M.; Vidaki, Kleio; Soto, David

2015-01-01

Familiar stimuli are typically accompanied by decreases in neural response relative to the presentation of novel items, but these studies often include explicit instructions to discriminate old and new items; this creates difficulties in partialling out the contribution of top-down intentional orientation to the items based on recognition goals.…

Germ layers, the neural crest and emergent organization in development and evolution.

Science.gov (United States)

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.

A Translational Approach to Vocalization Deficits and Neural Recovery after Behavioral Treatment in Parkinson Disease

Science.gov (United States)

Ciucci, Michelle R.; Vinney, Lisa; Wahoske, Emerald J.; Connor, Nadine P.

2010-01-01

Parkinson disease is characterized by a complex neuropathological profile that primarily affects dopaminergic neural pathways in the basal ganglia, including pathways that modulate cranial sensorimotor functions such as swallowing, voice and speech. Prior work from our lab has shown that the rat model of unilateral 6-hydroxydopamine infusion to…

The Neural Circuits that Generate Tics in Gilles de la Tourette Syndrome

Science.gov (United States)

Wang, Zhishun; Maia, Tiago V.; Marsh, Rachel; Colibazzi, Tiziano; Gerber, Andrew; Peterson, Bradley S.

2014-01-01

Objective To study neural activity and connectivity within cortico-striato-thalamo-cortical circuits and to reveal circuit-based neural mechanisms that govern tic generation in Tourette syndrome. Method We acquired fMRI data from 13 participants with Tourette syndrome and 21 controls during spontaneous or simulated tics. We used independent component analysis with hierarchical partner matching to isolate neural activity within functionally distinct regions of cortico-striato-thalamo-cortical circuits. We used Granger causality to investigate causal interactions among these regions. Results We found that the Tourette group exhibited stronger neural activity and interregional causality than controls throughout all portions of the motor pathway including sensorimotor cortex, putamen, pallidum, and substania nigra. Activity in these areas correlated positively with the severity of tic symptoms. Activity within the Tourette group was stronger during spontaneous tics than during voluntary tics in somatosensory and posterior parietal cortices, putamen, and amygdala/hippocampus complex, suggesting that activity in these regions may represent features of the premonitory urges that generate spontaneous tic behaviors. In contrast, activity was weaker in the Tourette group than in controls within portions of cortico-striato-thalamo-cortical circuits that exert top-down control over motor pathways (caudate and anterior cingulate cortex), and progressively less activity in these regions accompanied more severe tic symptoms, suggesting that faulty activity in these circuits may fail to control tic behaviors or the premonitory urges that generate them. Conclusions Our findings taken together suggest that tics are caused by the combined effects of excessive activity in motor pathways and reduced activation in control portions of cortico-striato-thalamo-cortical circuits. PMID:21955933

Fetal Alcohol Spectrum Disorder (FASD) Associated Neural Defects: Complex Mechanisms and Potential Therapeutic Targets.

Science.gov (United States)

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.

Fetal Alcohol Spectrum Disorder (FASD Associated Neural Defects: Complex Mechanisms and Potential Therapeutic Targets

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.

Analysis of complex systems using neural networks

International Nuclear Information System (INIS)

Uhrig, R.E.

1992-01-01

The application of neural networks, alone or in conjunction with other advanced technologies (expert systems, fuzzy logic, and/or genetic algorithms), to some of the problems of complex engineering systems has the potential to enhance the safety, reliability, and operability of these systems. Typically, the measured variables from the systems are analog variables that must be sampled and normalized to expected peak values before they are introduced into neural networks. Often data must be processed to put it into a form more acceptable to the neural network (e.g., a fast Fourier transformation of the time-series data to produce a spectral plot of the data). Specific applications described include: (1) Diagnostics: State of the Plant (2) Hybrid System for Transient Identification, (3) Sensor Validation, (4) Plant-Wide Monitoring, (5) Monitoring of Performance and Efficiency, and (6) Analysis of Vibrations. Although specific examples described deal with nuclear power plants or their subsystems, the techniques described can be applied to a wide variety of complex engineering systems

Feature to prototype transition in neural networks

Science.gov (United States)

Krotov, Dmitry; Hopfield, John

Models of associative memory with higher order (higher than quadratic) interactions, and their relationship to neural networks used in deep learning are discussed. Associative memory is conventionally described by recurrent neural networks with dynamical convergence to stable points. Deep learning typically uses feedforward neural nets without dynamics. However, a simple duality relates these two different views when applied to problems of pattern classification. From the perspective of associative memory such models deserve attention because they make it possible to store a much larger number of memories, compared to the quadratic case. In the dual description, these models correspond to feedforward neural networks with one hidden layer and unusual activation functions transmitting the activities of the visible neurons to the hidden layer. These activation functions are rectified polynomials of a higher degree rather than the rectified linear functions used in deep learning. The network learns representations of the data in terms of features for rectified linear functions, but as the power in the activation function is increased there is a gradual shift to a prototype-based representation, the two extreme regimes of pattern recognition known in cognitive psychology. Simons Center for Systems Biology.

Cell surface glycan engineering of neural stem cells augments neurotropism and improves recovery in a murine model of multiple sclerosis

KAUST Repository

Merzaban, Jasmeen; Imitola, Jaime; Starossom, Sarah C.; Zhu, Bing; Wang, Yue; Lee, Jack; Ali, Amal J.; Olah, Marta; AbuElela, Ayman; Khoury, Samia J.; Sackstein, Robert

2015-01-01

Neural stem cell (NSC)-based therapies offer potential for neural repair in central nervous system (CNS) inflammatory and degenerative disorders. Typically, these conditions present with multifocal CNS lesions making it impractical to inject NSCs

Fault diagnosis method for nuclear power plants based on neural networks and voting fusion

International Nuclear Information System (INIS)

Zhou Gang; Ge Shengqi; Yang Li

2010-01-01

A new fault diagnosis method based on multiple neural networks (ANNs) and voting fusion for nuclear power plants (NPPs) was proposed in view of the shortcoming of single neural network fault diagnosis method. In this method, multiple neural networks that the types of neural networks were different were trained for the fault diagnosis of NPP. The operation parameters of NPP, which have important affect on the safety of NPP, were selected as the input variable of neural networks. The output of neural networks is fault patterns of NPP. The last results of diagnosis for NPP were obtained by fusing the diagnosing results of different neural networks by voting fusion. The typical operation patterns of NPP were diagnosed to demonstrate the effect of the proposed method. The results show that employing the proposed diagnosing method can improve the precision and reliability of fault diagnosis results of NPPs. (authors)

Artificial neural networks in the nuclear engineering (Part 2)

International Nuclear Information System (INIS)

Baptista Filho, Benedito Dias

2002-01-01

The field of Artificial Neural Networks (ANN), one of the branches of Artificial Intelligence has been waking up a lot of interest in the Nuclear Engineering (NE). ANN can be used to solve problems of difficult modeling, when the data are fail or incomplete and in high complexity problems of control. The first part of this work began a discussion with feed-forward neural networks in back-propagation. In this part of the work, the Multi-synaptic neural networks is applied to control problems. Also, the self-organized maps is presented in a typical pattern classification problem: transients classification. The main purpose of the work is to show that ANN can be successfully used in NE if a carefully choice of its type is done: the application sets this choice. (author)

Application of improved PSO-RBF neural network in the synthetic ammonia decarbonization

Directory of Open Access Journals (Sweden)

Yongwei LI

2017-12-01

Full Text Available The synthetic ammonia decarbonization is a typical complex industrial process, which has the characteristics of time variation, nonlinearity and uncertainty, and the on-line control model is difficult to be established. An improved PSO-RBF neural network control algorithm is proposed to solve the problems of low precision and poor robustness in the complex process of the synthetic ammonia decarbonization. The particle swarm optimization algorithm and RBF neural network are combined. The improved particle swarm algorithm is used to optimize the RBF neural network's hidden layer primary function center, width and the output layer's connection value to construct the RBF neural network model optimized by the improved PSO algorithm. The improved PSO-RBF neural network control model is applied to the key carbonization process and compared with the traditional fuzzy neural network. The simulation results show that the improved PSO-RBF neural network control method used in the synthetic ammonia decarbonization process has higher control accuracy and system robustness, which provides an effective way to solve the modeling and optimization control of a complex industrial process.

Optimal Hierarchical Modular Topologies for Producing Limited Sustained Activation of Neural Networks

OpenAIRE

Kaiser, Marcus; Hilgetag, Claus C.

2010-01-01

An essential requirement for the representation of functional patterns in complex neural networks, such as the mammalian cerebral cortex, is the existence of stable regimes of network activation, typically arising from a limited parameter range. In this range of limited sustained activity (LSA), the activity of neural populations in the network persists between the extremes of either quickly dying out or activating the whole network. Hierarchical modular networks were previously found to show...

Application of a neural network for reflectance spectrum classification

Science.gov (United States)

Yang, Gefei; Gartley, Michael

2017-05-01

Traditional reflectance spectrum classification algorithms are based on comparing spectrum across the electromagnetic spectrum anywhere from the ultra-violet to the thermal infrared regions. These methods analyze reflectance on a pixel by pixel basis. Inspired by high performance that Convolution Neural Networks (CNN) have demonstrated in image classification, we applied a neural network to analyze directional reflectance pattern images. By using the bidirectional reflectance distribution function (BRDF) data, we can reformulate the 4-dimensional into 2 dimensions, namely incident direction × reflected direction × channels. Meanwhile, RIT's micro-DIRSIG model is utilized to simulate additional training samples for improving the robustness of the neural networks training. Unlike traditional classification by using hand-designed feature extraction with a trainable classifier, neural networks create several layers to learn a feature hierarchy from pixels to classifier and all layers are trained jointly. Hence, the our approach of utilizing the angular features are different to traditional methods utilizing spatial features. Although training processing typically has a large computational cost, simple classifiers work well when subsequently using neural network generated features. Currently, most popular neural networks such as VGG, GoogLeNet and AlexNet are trained based on RGB spatial image data. Our approach aims to build a directional reflectance spectrum based neural network to help us to understand from another perspective. At the end of this paper, we compare the difference among several classifiers and analyze the trade-off among neural networks parameters.

Religious beliefs influence neural substrates of self-reflection in Tibetans.

Science.gov (United States)

Wu, Yanhong; Wang, Cheng; He, Xi; Mao, Lihua; Zhang, Li

2010-06-01

Previous transcultural neuroimaging studies have shown that the neural substrates of self-reflection can be shaped by different cultures. There are few studies, however, on the neural activity of self-reflection where religion is viewed as a form of cultural expression. The present study examined the self-processing of two Chinese ethnic groups (Han and Tibetan) to investigate the significant role of religion on the functional anatomy of self-representation. We replicated the previous results in Han participants with the ventral medial prefrontal cortex and left anterior cingulate cortex showing stronger activation in self-processing when compared with other-processing conditions. However, no typical self-reference pattern was identified in Tibetan participants on behavioral or neural levels. This could be explained by the minimal subjective sense of 'I-ness' in Tibetan Buddhists. Our findings lend support to the presumed role of culture and religion in shaping the neural substrate of self.

Longitudinal Brain Development of Numerical Skills in Typically Developing Children and Children with Developmental Dyscalculia

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Ursina McCaskey

2018-01-01

Full Text Available Developmental dyscalculia (DD is a learning disability affecting the acquisition of numerical-arithmetical skills. Studies report persistent deficits in number processing and aberrant functional activation of the fronto-parietal numerical network in DD. However, the neural development of numerical abilities has been scarcely investigated. The present paper provides a first attempt to investigate behavioral and neural trajectories of numerical abilities longitudinally in typically developing (TD and DD children. During a study period of 4 years, 28 children (8–11 years were evaluated twice by means of neuropsychological tests and a numerical order fMRI paradigm. Over time, TD children improved in numerical abilities and showed a consistent and well-developed fronto-parietal network. In contrast, DD children revealed persistent deficits in number processing and arithmetic. Brain imaging results of the DD group showed an age-related activation increase in parietal regions (intraparietal sulcus, pointing to a delayed development of number processing areas. Besides, an activation increase in frontal areas was observed over time, indicating the use of compensatory mechanisms. In conclusion, results suggest a continuation in neural development of number representation in DD, whereas the neural network for simple ordinal number estimation seems to be stable or show only subtle changes in TD children over time.

Longitudinal Brain Development of Numerical Skills in Typically Developing Children and Children with Developmental Dyscalculia.

Science.gov (United States)

McCaskey, Ursina; von Aster, Michael; Maurer, Urs; Martin, Ernst; O'Gorman Tuura, Ruth; Kucian, Karin

2017-01-01

Developmental dyscalculia (DD) is a learning disability affecting the acquisition of numerical-arithmetical skills. Studies report persistent deficits in number processing and aberrant functional activation of the fronto-parietal numerical network in DD. However, the neural development of numerical abilities has been scarcely investigated. The present paper provides a first attempt to investigate behavioral and neural trajectories of numerical abilities longitudinally in typically developing (TD) and DD children. During a study period of 4 years, 28 children (8-11 years) were evaluated twice by means of neuropsychological tests and a numerical order fMRI paradigm. Over time, TD children improved in numerical abilities and showed a consistent and well-developed fronto-parietal network. In contrast, DD children revealed persistent deficits in number processing and arithmetic. Brain imaging results of the DD group showed an age-related activation increase in parietal regions (intraparietal sulcus), pointing to a delayed development of number processing areas. Besides, an activation increase in frontal areas was observed over time, indicating the use of compensatory mechanisms. In conclusion, results suggest a continuation in neural development of number representation in DD, whereas the neural network for simple ordinal number estimation seems to be stable or show only subtle changes in TD children over time.

PWR system simulation and parameter estimation with neural networks

Energy Technology Data Exchange (ETDEWEB)

Akkurt, Hatice; Colak, Uener E-mail: uc@nuke.hacettepe.edu.tr

2002-11-01

A detailed nonlinear model for a typical PWR system has been considered for the development of simulation software. Each component in the system has been represented by appropriate differential equations. The SCILAB software was used for solving nonlinear equations to simulate steady-state and transient operational conditions. Overall system has been constructed by connecting individual components to each other. The validity of models for individual components and overall system has been verified. The system response against given transients have been analyzed. A neural network has been utilized to estimate system parameters during transients. Different transients have been imposed in training and prediction stages with neural networks. Reactor power and system reactivity during the transient event have been predicted by the neural network. Results show that neural networks estimations are in good agreement with the calculated response of the reactor system. The maximum errors are within {+-}0.254% for power and between -0.146 and 0.353% for reactivity prediction cases. Steam generator parameters, pressure and water level, are also successfully predicted by the neural network employed in this study. The noise imposed on the input parameters of the neural network deteriorates the power estimation capability whereas the reactivity estimation capability is not significantly affected.

PWR system simulation and parameter estimation with neural networks

International Nuclear Information System (INIS)

Akkurt, Hatice; Colak, Uener

2002-01-01

A detailed nonlinear model for a typical PWR system has been considered for the development of simulation software. Each component in the system has been represented by appropriate differential equations. The SCILAB software was used for solving nonlinear equations to simulate steady-state and transient operational conditions. Overall system has been constructed by connecting individual components to each other. The validity of models for individual components and overall system has been verified. The system response against given transients have been analyzed. A neural network has been utilized to estimate system parameters during transients. Different transients have been imposed in training and prediction stages with neural networks. Reactor power and system reactivity during the transient event have been predicted by the neural network. Results show that neural networks estimations are in good agreement with the calculated response of the reactor system. The maximum errors are within ±0.254% for power and between -0.146 and 0.353% for reactivity prediction cases. Steam generator parameters, pressure and water level, are also successfully predicted by the neural network employed in this study. The noise imposed on the input parameters of the neural network deteriorates the power estimation capability whereas the reactivity estimation capability is not significantly affected

Damage detection in carbon composite material typical of wind turbine blades using auto-associative neural networks

Science.gov (United States)

Dervilis, N.; Barthorpe, R. J.; Antoniadou, I.; Staszewski, W. J.; Worden, K.

2012-04-01

The structure of a wind turbine blade plays a vital role in the mechanical and structural operation of the turbine. As new generations of offshore wind turbines are trying to achieve a leading role in the energy market, key challenges such as a reliable Structural Health Monitoring (SHM) of the blades is significant for the economic and structural efficiency of the wind energy. Fault diagnosis of wind turbine blades is a "grand challenge" due to their composite nature, weight and length. The damage detection procedure involves additional difficulties focused on aerodynamic loads, environmental conditions and gravitational loads. It will be shown that vibration dynamic response data combined with AANNs is a robust and powerful tool, offering on-line and real time damage prediction. In this study the features used for SHM are Frequency Response Functions (FRFs) acquired via experimental methods based on an LMS system by which identification of mode shapes and natural frequencies is accomplished. The methods used are statistical outlier analysis which allows a diagnosis of deviation from normality and an Auto-Associative Neural Network (AANN). Both of these techniques are trained by adopting the FRF data for normal and damage condition. The AANN is a method which has not yet been widely used in the condition monitoring of composite materials of blades. This paper is trying to introduce a new scheme for damage detection, localisation and severity assessment by adopting simple measurements such as FRFs and exploiting multilayer neural networks and outlier novelty detection.

Rapid and Objective Assessment of Neural Function in Autism Spectrum Disorder Using Transient Visual Evoked Potentials.

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Paige M Siper

Full Text Available There is a critical need to identify biomarkers and objective outcome measures that can be used to understand underlying neural mechanisms in autism spectrum disorder (ASD. Visual evoked potentials (VEPs offer a noninvasive technique to evaluate the functional integrity of neural mechanisms, specifically visual pathways, while probing for disease pathophysiology.Transient VEPs (tVEPs were obtained from 96 unmedicated children, including 37 children with ASD, 36 typically developing (TD children, and 23 unaffected siblings (SIBS. A conventional contrast-reversing checkerboard condition was compared to a novel short-duration condition, which was developed to enable objective data collection from severely affected populations who are often excluded from electroencephalographic (EEG studies.Children with ASD showed significantly smaller amplitudes compared to TD children at two of the earliest critical VEP components, P60-N75 and N75-P100. SIBS showed intermediate responses relative to ASD and TD groups. There were no group differences in response latency. Frequency band analyses indicated significantly weaker responses for the ASD group in bands encompassing gamma-wave activity. Ninety-two percent of children with ASD were able to complete the short-duration condition compared to 68% for the standard condition.The current study establishes the utility of a short-duration tVEP test for use in children at varying levels of functioning and describes neural abnormalities in children with idiopathic ASD. Implications for excitatory/inhibitory balance as well as the potential application of VEP for use in clinical trials are discussed.

Maternal Diabetes Alters Expression of MicroRNAs that Regulate Genes Critical for Neural Tube Development

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Seshadri Ramya

2017-07-01

Full Text Available Maternal diabetes is known to cause neural tube defects (NTDs in embryos and neuropsychological deficits in infants. Several metabolic pathways and a plethora of genes have been identified to be deregulated in developing brain of embryos by maternal diabetes, although the exact mechanism remains unknown. Recently, miRNAs have been shown to regulate genes involved in brain development and maturation. Therefore, we hypothesized that maternal diabetes alters the expression of miRNAs that regulate genes involved in biological pathways critical for neural tube development and closure during embryogenesis. To address this, high throughput miRNA expression profiling in neural stem cells (NSCs isolated from the forebrain of embryos from normal or streptozotocin-induced diabetic pregnancy was carried out. It is known that maternal diabetes results in fetal hypoglycemia/hyperglycemia or hypoxia. Hence, NSCs from embryos of control pregnant mice were exposed to low or high glucose or hypoxia in vitro. miRNA pathway analysis revealed distinct deregulation of several biological pathways, including axon guidance pathway, which are critical for brain development in NSCs exposed to different treatments. Among the differentially expressed miRNAs, the miRNA-30 family members which are predicted to target genes involved in brain development was upregulated in NSCs from embryos of diabetic pregnancy when compared to control. miRNA-30b was found to be upregulated while its target gene Sirtuin 1 (Sirt1, as revealed by luciferase assay, was down regulated in NSCs from embryos of diabetic pregnancy. Further, overexpression of miRNA-30b in NSCs, resulted in decreased expression of Sirt1 protein, and altered the neuron/glia ratio. On the other hand, siRNA mediated knockdown of Sirt1 in NSCs promoted astrogenesis, indicating that miRNA-30b alters lineage specification via Sirt1. Overall, these results suggest that maternal diabetes alters the genes involved in neural tube

Orphan nuclear receptor TLX activates Wnt/β-catenin signalling to stimulate neural stem cell proliferation and self-renewal

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Qu, Qiuhao; Sun, Guoqiang; Li, Wenwu; Yang, Su; Ye, Peng; Zhao, Chunnian; Yu, Ruth T.; Gage, Fred H.; Evans, Ronald M.; Shi, Yanhong

2010-01-01

The nuclear receptor TLX (also known as NR2E1) is essential for adult neural stem cell self-renewal; however, the molecular mechanisms involved remain elusive. Here we show that TLX activates the canonical Wnt/β-catenin pathway in adult mouse neural stem cells. Furthermore, we demonstrate that Wnt/β-catenin signalling is important in the proliferation and self-renewal of adult neural stem cells in the presence of epidermal growth factor and fibroblast growth factor. Wnt7a and active β-catenin promote neural stem cell self-renewal, whereas the deletion of Wnt7a or the lentiviral transduction of axin, a β-catenin inhibitor, led to decreased cell proliferation in adult neurogenic areas. Lentiviral transduction of active β-catenin led to increased numbers of type B neural stem cells in the subventricular zone of adult brains, whereas deletion of Wnt7a or TLX resulted in decreased numbers of neural stem cells retaining bromodeoxyuridine label in the adult brain. Both Wnt7a and active β-catenin significantly rescued a TLX (also known as Nr2e1) short interfering RNA-induced deficiency in neural stem cell proliferation. Lentiviral transduction of an active β-catenin increased cell proliferation in neurogenic areas of TLX-null adult brains markedly. These results strongly support the hypothesis that TLX acts through the Wnt/β-catenin pathway to regulate neural stem cell proliferation and self-renewal. Moreover, this study suggests that neural stem cells can promote their own self-renewal by secreting signalling molecules that act in an autocrine/paracrine mode. PMID:20010817

Orphan nuclear receptor TLX activates Wnt/beta-catenin signalling to stimulate neural stem cell proliferation and self-renewal.

Science.gov (United States)

Qu, Qiuhao; Sun, Guoqiang; Li, Wenwu; Yang, Su; Ye, Peng; Zhao, Chunnian; Yu, Ruth T; Gage, Fred H; Evans, Ronald M; Shi, Yanhong

2010-01-01

The nuclear receptor TLX (also known as NR2E1) is essential for adult neural stem cell self-renewal; however, the molecular mechanisms involved remain elusive. Here we show that TLX activates the canonical Wnt/beta-catenin pathway in adult mouse neural stem cells. Furthermore, we demonstrate that Wnt/beta-catenin signalling is important in the proliferation and self-renewal of adult neural stem cells in the presence of epidermal growth factor and fibroblast growth factor. Wnt7a and active beta-catenin promote neural stem cell self-renewal, whereas the deletion of Wnt7a or the lentiviral transduction of axin, a beta-catenin inhibitor, led to decreased cell proliferation in adult neurogenic areas. Lentiviral transduction of active beta-catenin led to increased numbers of type B neural stem cells in the subventricular zone of adult brains, whereas deletion of Wnt7a or TLX resulted in decreased numbers of neural stem cells retaining bromodeoxyuridine label in the adult brain. Both Wnt7a and active beta-catenin significantly rescued a TLX (also known as Nr2e1) short interfering RNA-induced deficiency in neural stem cell proliferation. Lentiviral transduction of an active beta-catenin increased cell proliferation in neurogenic areas of TLX-null adult brains markedly. These results strongly support the hypothesis that TLX acts through the Wnt/beta-catenin pathway to regulate neural stem cell proliferation and self-renewal. Moreover, this study suggests that neural stem cells can promote their own self-renewal by secreting signalling molecules that act in an autocrine/paracrine mode.

A Fault Diagnosis Approach for the Hydraulic System by Artificial Neural Networks

OpenAIRE

Xiangyu He; Shanghong He

2014-01-01

Based on artificial neural networks, a fault diagnosis approach for the hydraulic system was proposed in this paper. Normal state samples were used as the training data to develop a dynamic general regression neural network (DGRNN) model. The trained DGRNN model then served as the fault determinant to diagnose test faults and the work condition of the hydraulic system was identified. Several typical faults of the hydraulic system were used to verify the fault diagnosis approach. Experiment re...

Photopolymerized materials and patterning for improved performance of neural prosthetics

Science.gov (United States)

Tuft, Bradley William

Neural prosthetics are used to replace or substantially augment remaining motor and sensory functions of neural pathways that were lost or damaged due to physical trauma, disease, or genetics. However, due to poor spatial signal resolution, neural prostheses fail to recapitulate the intimate, precise interactions inherent to neural networks. Designing materials and interfaces that direct de novo nerve growth to spatially specific stimulating elements is, therefore, a promising method to enhance signal specificity and performance of prostheses such as the successful cochlear implant (CI) and the developing retinal implant. In this work, the spatial and temporal reaction control inherent to photopolymerization was used to develop methods to generate micro and nanopatterned materials that direct neurite growth from prosthesis relevant neurons. In particular, neurite growth and directionality has been investigated in response to physical, mechanical, and chemical cues on photopolymerized surfaces. Spiral ganglion neurons (SGNs) serve as the primary neuronal model as they are the principal target for CI stimulation. The objective of the research is to rationally design materials that spatially direct neurite growth and to translate fundamental understanding of nerve cell-material interactions into methods of nerve regeneration that improve neural prosthetic performance. A rapid, single-step photopolymerization method was developed to fabricate micro and nanopatterned physical cues on methacrylate surfaces by selectively blocking light with photomasks. Feature height is readily tuned by modulating parameters of the photopolymerizaiton including initiator concentration and species, light intensity, separation distance from the photomask, and radiation exposure time. Alignment of neural elements increases significantly with increasing feature amplitude and constant periodicity, as well as with decreasing periodicity and constant amplitude. SGN neurite alignment strongly

Transcriptomic Analysis Of Purified Embryonic Neural Stem Cells From Zebrafish Embryos Reveals Signalling Pathways Involved In Glycine-dependent Neurogenesis

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Eric eSAMARUT

2016-03-01

Full Text Available How is the initial set of neurons correctly established during the development of the vertebrate central nervous system? In the embryo, glycine and GABA are depolarizing due the immature chloride gradient, which is only reversed to become hyperpolarizing later in post-natal development. We previously showed that glycine regulates neurogenesis via paracrine signalling that promotes calcium transients in neural stem cells (NSCs and their differentiation into interneurons within the spinal cord of the zebrafish embryo. However, the subjacent molecular mechanisms are not yet understood. Our previous work suggests that early neuronal progenitors were not differentiating correctly in the developing spinal cord. As a result, we aimed at identifying the downstream molecular mechanisms involved specifically in NSCs during glycine-dependent embryonic neurogenesis. Using a gfap:GFP transgenic line, we successfully purified NSCs by fluorescence-activated cell sorting (FACS from whole zebrafish embryos and in embryos in which the glycine receptor was knocked down. The strength of this approach is that it focused on the NSC population while tackling the biological issue in an in vivo context in whole zebrafish embryos. After sequencing the transcriptome by RNA-sequencing, we analyzed the genes whose expression was changed upon disruption of glycine signalling and we confirmed the differential expression by independent RTqPCR assay. While over a thousand genes showed altered expression levels, through pathway analysis we identified 14 top candidate genes belonging to five different canonical signalling pathways (signalling by calcium, TGF-beta, sonic hedgehog, Wnt and p53-related apoptosis that are likely to mediate the promotion of neurogenesis by glycine.

Harmonics added to a flickering light can upset the balance between ON and OFF pathways to produce illusory colors.

Science.gov (United States)

Rider, Andrew T; Henning, G Bruce; Eskew, Rhea T; Stockman, Andrew

2018-04-24

The neural signals generated by the light-sensitive photoreceptors in the human eye are substantially processed and recoded in the retina before being transmitted to the brain via the optic nerve. A key aspect of this recoding is the splitting of the signals within the two major cone-driven visual pathways into distinct ON and OFF branches that transmit information about increases and decreases in the neural signal around its mean level. While this separation is clearly important physiologically, its effect on perception is unclear. We have developed a model of the ON and OFF pathways in early color processing. Using this model as a guide, we can produce imbalances in the ON and OFF pathways by changing the shapes of time-varying stimulus waveforms and thus make reliable and predictable alterations to the perceived average color of the stimulus-although the physical mean of the waveforms does not change. The key components in the model are the early half-wave rectifying synapses that split retinal photoreceptor outputs into the ON and OFF pathways and later sigmoidal nonlinearities in each pathway. The ability to systematically vary the waveforms to change a perceptual quality by changing the balance of signals between the ON and OFF visual pathways provides a powerful psychophysical tool for disentangling and investigating the neural workings of human vision. Copyright © 2018 the Author(s). Published by PNAS.

Application of neural network technology to setpoint control of a simulated reactor experiment loop

International Nuclear Information System (INIS)

Cordes, G.A.; Bryan, S.R.; Powell, R.H.; Chick, D.R.

1991-01-01

This paper describes the design, implementation, and application of artificial neural networks to achieve temperature and flow rate control for a simulation of a typical experiment loop in the Advanced Test Reactor (ATR) located at the Idaho National Engineering Laboratory (INEL). The goal of the project was to research multivariate, nonlinear control using neural networks. A loop simulation code was adapted for the project and used to create a training set and test the neural network controller for comparison with the existing loop controllers. The results for the best neural network design are documented and compared with existing loop controller action. The neural network was shown to be as accurate at loop control as the classical controllers in the operating region represented by the training set. 5 refs., 8 figs., 3 tabs

Neural pathways in processing of sexual arousal: a dynamic causal modeling study.

Science.gov (United States)

Seok, J-W; Park, M-S; Sohn, J-H

2016-09-01

Three decades of research have investigated brain processing of visual sexual stimuli with neuroimaging methods. These researchers have found that sexual arousal stimuli elicit activity in a broad neural network of cortical and subcortical brain areas that are known to be associated with cognitive, emotional, motivational and physiological components. However, it is not completely understood how these neural systems integrate and modulated incoming information. Therefore, we identify cerebral areas whose activations were correlated with sexual arousal using event-related functional magnetic resonance imaging and used the dynamic causal modeling method for searching the effective connectivity about the sexual arousal processing network. Thirteen heterosexual males were scanned while they passively viewed alternating short trials of erotic and neutral pictures on a monitor. We created a subset of seven models based on our results and previous studies and selected a dominant connectivity model. Consequently, we suggest a dynamic causal model of the brain processes mediating the cognitive, emotional, motivational and physiological factors of human male sexual arousal. These findings are significant implications for the neuropsychology of male sexuality.

[Folic acid: Primary prevention of neural tube defects. Literature Review].

Science.gov (United States)

Llamas Centeno, M J; Miguélez Lago, C

2016-03-01

Neural tube defects (NTD) are the most common congenital malformations of the nervous system, they have a multifactorial etiology, are caused by exposure to chemical, physical or biological toxic agents, factors deficiency, diabetes, obesity, hyperthermia, genetic alterations and unknown causes. Some of these factors are associated with malnutrition by interfering with the folic acid metabolic pathway, the vitamin responsible for neural tube closure. Its deficit produce anomalies that can cause abortions, stillbirths or newborn serious injuries that cause disability, impaired quality of life and require expensive treatments to try to alleviate in some way the alterations produced in the embryo. Folic acid deficiency is considered the ultimate cause of the production of neural tube defects, it is clear the reduction in the incidence of Espina Bifida after administration of folic acid before conception, this leads us to want to further study the action of folic acid and its application in the primary prevention of neural tube defects. More than 40 countries have made the fortification of flour with folate, achieving encouraging data of decrease in the prevalence of neural tube defects. This paper attempts to make a literature review, which clarify the current situation and future of the prevention of neural tube defects.

Rare Neural Correlations Implement Robotic Conditioning with Delayed Rewards and Disturbances

Science.gov (United States)

Soltoggio, Andrea; Lemme, Andre; Reinhart, Felix; Steil, Jochen J.

2013-01-01

Neural conditioning associates cues and actions with following rewards. The environments in which robots operate, however, are pervaded by a variety of disturbing stimuli and uncertain timing. In particular, variable reward delays make it difficult to reconstruct which previous actions are responsible for following rewards. Such an uncertainty is handled by biological neural networks, but represents a challenge for computational models, suggesting the lack of a satisfactory theory for robotic neural conditioning. The present study demonstrates the use of rare neural correlations in making correct associations between rewards and previous cues or actions. Rare correlations are functional in selecting sparse synapses to be eligible for later weight updates if a reward occurs. The repetition of this process singles out the associating and reward-triggering pathways, and thereby copes with distal rewards. The neural network displays macro-level classical and operant conditioning, which is demonstrated in an interactive real-life human-robot interaction. The proposed mechanism models realistic conditioning in humans and animals and implements similar behaviors in neuro-robotic platforms. PMID:23565092

Neural Tube Defects, Folic Acid and Methylation

Science.gov (United States)

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

Molecular target discovery for neural repair in the functional genomics era

NARCIS (Netherlands)

Verhaagen, J.; van Kesteren, R.E.; Bossers, K.A.; Mac Gillavry, H.D.; Mason, M.R.; Smit, A.B.

2012-01-01

A comprehensive understanding of the molecular pathways activated by traumatic neural injury is of major importance for the development of treatments for spinal cord injury (SCI). High-throughput gene expression profiling is a powerful approach to reveal genome-wide changes in gene expression during

Statistical Physics of Neural Systems with Nonadditive Dendritic Coupling

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David Breuer

2014-03-01

Full Text Available How neurons process their inputs crucially determines the dynamics of biological and artificial neural networks. In such neural and neural-like systems, synaptic input is typically considered to be merely transmitted linearly or sublinearly by the dendritic compartments. Yet, single-neuron experiments report pronounced supralinear dendritic summation of sufficiently synchronous and spatially close-by inputs. Here, we provide a statistical physics approach to study the impact of such nonadditive dendritic processing on single-neuron responses and the performance of associative-memory tasks in artificial neural networks. First, we compute the effect of random input to a neuron incorporating nonlinear dendrites. This approach is independent of the details of the neuronal dynamics. Second, we use those results to study the impact of dendritic nonlinearities on the network dynamics in a paradigmatic model for associative memory, both numerically and analytically. We find that dendritic nonlinearities maintain network convergence and increase the robustness of memory performance against noise. Interestingly, an intermediate number of dendritic branches is optimal for memory functionality.

Wire Finishing Mill Rolling Bearing Fault Diagnosis Based on Feature Extraction and BP Neural Network

Directory of Open Access Journals (Sweden)

Hong-Yu LIU

2014-10-01

Full Text Available Rolling bearing is main part of rotary machine. It is frail section of rotary machine. Its running status affects entire mechanical equipment system performance directly. Vibration acceleration signals of the third finishing mill of Anshan Steel and Iron Group wire plant were collected in this paper. Fourier analysis, power spectrum analysis and wavelet transform were made on collected signals. Frequency domain feature extraction and wavelet transform feature extraction were made on collected signals. BP neural network fault diagnosis model was adopted. Frequency domain feature values and wavelet transform feature values were treated as neural network input values. Various typical fault models were treated as neural network output values. Corresponding relations between feature vector and fault omen were utilized. BP neural network model of typical wire plant finishing mill rolling bearing fault was constructed by training many groups sample data. After inputting sample needed to be diagnosed, wire plant finishing mill rolling bearing fault can be diagnosed. This research has important practical significance on enhancing rolling bearing fault diagnosis precision, repairing rolling bearing duly, decreasing stop time, enhancing equipment running efficiency and enhancing economic benefits.

Neurotrophin-3 promotes proliferation and cholinergic neuronal differentiation of bone marrow- derived neural stem cells via notch signaling pathway.

Science.gov (United States)

Yan, Yu-Hui; Li, Shao-Heng; Gao, Zhong; Zou, Sa-Feng; Li, Hong-Yan; Tao, Zhen-Yu; Song, Jie; Yang, Jing-Xian

2016-12-01

Recently, the potential for neural stem cells (NSCs) to be used in the treatment of Alzheimer's disease (AD) has been reported; however, the therapeutic effects are modest by virtue of the low neural differentiation rate. In our study, we transfected bone marrow-derived NSCs (BM-NSCs) with Neurotrophin-3 (NT-3), a superactive neurotrophic factor that promotes neuronal survival, differentiation, and migration of neuronal cells, to investigate the effects of NT-3 gene overexpression on the proliferation and differentiation into cholinergic neuron of BM-NSCs in vitro and its possible molecular mechanism. BM-NSCs were generated from BM mesenchymal cells of adult C57BL/6 mice and cultured in vitro. After transfected with NT-3 gene, immunofluorescence and RT-PCR method were used to determine the ability of BM-NSCs on proliferation and differentiation into cholinergic neuron; Acetylcholine Assay Kit was used for acetylcholine (Ach). RT-PCR and WB analysis were used to characterize mRNA and protein level related to the Notch signaling pathway. We found that NT-3 can promote the proliferation and differentiation of BM-NSCs into cholinergic neurons and elevate the levels of acetylcholine (ACh) in the supernatant. Furthermore, NT-3 gene overexpression increase the expression of Hes1, decreased the expression of Mash1 and Ngn1 during proliferation of BM-NSCs. Whereas, the expression of Hes1 was down-regulated, and Mash1 and Ngn1 expression were up-regulated during differentiation of BM-NSCs. Our findings support the prospect of using NT-3-transduced BM-NSCs in developing therapies for AD due to their equivalent therapeutic potential as subventricular zone-derived NSCs (SVZ-NSCs), greater accessibility, and autogenous attributes. Copyright © 2016 Elsevier Inc. All rights reserved.

Study of the neural basis of striatal modulation of the jaw-opening reflex.

Science.gov (United States)

Barceló, Ana C; Fillipini, B; Pazo, Jorge Horacio

2010-02-01

Previous experimental data from this laboratory demonstrated the participation of the striatum and dopaminergic pathways in central nociceptive processing. The objective of this study was to examine the possible pathways and neural structures associated with the analgesic action of the striatum. The experiments were carried out in rats anesthetized with urethane. The jaw-opening reflex (JOR) was evoked by electrical stimulation of the tooth pulp of lower incisors and recorded in the anterior belly of the digastric muscles. Intrastriatal microinjection of apomorphine, a nonspecific dopamine agonist, reduced or abolished the JOR amplitude. Electrolytic or kainic acid lesions, unilateral to the apomorphine-injected striatum, of the globus pallidus, substantia nigra pars reticulata, subthalamic nucleus and bilateral lesion the rostroventromedial medulla (RVM), blocked the inhibition of the JOR by striatal stimulation. These findings suggest that the main output nuclei of the striatum and the RVM may be critical elements in the neural pathways mediating the inhibition of the reflex response, evoked in jaw muscles by noxious stimulation of dental pulp.

Optimization of composite panels using neural networks and genetic algorithms

NARCIS (Netherlands)

Ruijter, W.; Spallino, R.; Warnet, Laurent; de Boer, Andries

2003-01-01

The objective of this paper is to present first results of a running study on optimization of aircraft components (composite panels of a typical vertical tail plane) by using Genetic Algorithms (GA) and Neural Networks (NN). The panels considered are standardized to some extent but still there is a

Polarity-specific high-level information propagation in neural networks.

Science.gov (United States)

Lin, Yen-Nan; Chang, Po-Yen; Hsiao, Pao-Yueh; Lo, Chung-Chuan

2014-01-01

Analyzing the connectome of a nervous system provides valuable information about the functions of its subsystems. Although much has been learned about the architectures of neural networks in various organisms by applying analytical tools developed for general networks, two distinct and functionally important properties of neural networks are often overlooked. First, neural networks are endowed with polarity at the circuit level: Information enters a neural network at input neurons, propagates through interneurons, and leaves via output neurons. Second, many functions of nervous systems are implemented by signal propagation through high-level pathways involving multiple and often recurrent connections rather than by the shortest paths between nodes. In the present study, we analyzed two neural networks: the somatic nervous system of Caenorhabditis elegans (C. elegans) and the partial central complex network of Drosophila, in light of these properties. Specifically, we quantified high-level propagation in the vertical and horizontal directions: the former characterizes how signals propagate from specific input nodes to specific output nodes and the latter characterizes how a signal from a specific input node is shared by all output nodes. We found that the two neural networks are characterized by very efficient vertical and horizontal propagation. In comparison, classic small-world networks show a trade-off between vertical and horizontal propagation; increasing the rewiring probability improves the efficiency of horizontal propagation but worsens the efficiency of vertical propagation. Our result provides insights into how the complex functions of natural neural networks may arise from a design that allows them to efficiently transform and combine input signals.

Spatial vision in older adults: perceptual changes and neural bases.

Science.gov (United States)

McKendrick, Allison M; Chan, Yu Man; Nguyen, Bao N

2018-05-17

The number of older adults is rapidly increasing internationally, leading to a significant increase in research on how healthy ageing impacts vision. Most clinical assessments of spatial vision involve simple detection (letter acuity, grating contrast sensitivity, perimetry). However, most natural visual environments are more spatially complicated, requiring contrast discrimination, and the delineation of object boundaries and contours, which are typically present on non-uniform backgrounds. In this review we discuss recent research that reports on the effects of normal ageing on these more complex visual functions, specifically in the context of recent neurophysiological studies. Recent research has concentrated on understanding the effects of healthy ageing on neural responses within the visual pathway in animal models. Such neurophysiological research has led to numerous, subsequently tested, hypotheses regarding the likely impact of healthy human ageing on specific aspects of spatial vision. Healthy normal ageing impacts significantly on spatial visual information processing from the retina through to visual cortex. Some human data validates that obtained from studies of animal physiology, however some findings indicate that rethinking of presumed neural substrates is required. Notably, not all spatial visual processes are altered by age. Healthy normal ageing impacts significantly on some spatial visual processes (in particular centre-surround tasks), but leaves contrast discrimination, contrast adaptation, and orientation discrimination relatively intact. The study of older adult vision contributes to knowledge of the brain mechanisms altered by the ageing process, can provide practical information regarding visual environments that older adults may find challenging, and may lead to new methods of assessing visual performance in clinical environments. © 2018 The Authors Ophthalmic & Physiological Optics © 2018 The College of Optometrists.

Human Embryonic Stem Cells: A Model for the Study of Neural Development and Neurological Diseases

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Piya Prajumwongs

2016-01-01

Full Text Available Although the mechanism of neurogenesis has been well documented in other organisms, there might be fundamental differences between human and those species referring to species-specific context. Based on principles learned from other systems, it is found that the signaling pathways required for neural induction and specification of human embryonic stem cells (hESCs recapitulated those in the early embryo development in vivo at certain degree. This underscores the usefulness of hESCs in understanding early human neural development and reinforces the need to integrate the principles of developmental biology and hESC biology for an efficient neural differentiation.

Astrocytes mediate synapse elimination through MEGF10 and MERTK pathways

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Chung, Won-Suk; Clarke, Laura E.; Wang, Gordon X.; Stafford, Benjamin K.; Sher, Alexander; Chakraborty, Chandrani; Joung, Julia; Foo, Lynette C.; Thompson, Andrew; Chen, Chinfei; Smith, Stephen J.; Barres, Ben A.

2013-12-01

To achieve its precise neural connectivity, the developing mammalian nervous system undergoes extensive activity-dependent synapse remodelling. Recently, microglial cells have been shown to be responsible for a portion of synaptic pruning, but the remaining mechanisms remain unknown. Here we report a new role for astrocytes in actively engulfing central nervous system synapses. This process helps to mediate synapse elimination, requires the MEGF10 and MERTK phagocytic pathways, and is strongly dependent on neuronal activity. Developing mice deficient in both astrocyte pathways fail to refine their retinogeniculate connections normally and retain excess functional synapses. Finally, we show that in the adult mouse brain, astrocytes continuously engulf both excitatory and inhibitory synapses. These studies reveal a novel role for astrocytes in mediating synapse elimination in the developing and adult brain, identify MEGF10 and MERTK as critical proteins in the synapse remodelling underlying neural circuit refinement, and have important implications for understanding learning and memory as well as neurological disease processes.

Innervation of Extrahepatic Biliary Tract, With Special Reference to the Direct Bidirectional Neural Connections of the Gall Bladder, Sphincter of Oddi and Duodenum in Suncus murinus, in Whole-Mount Immunohistochemical Study.

Science.gov (United States)

Yi, S-Q; Ren, K; Kinoshita, M; Takano, N; Itoh, M; Ozaki, N

2016-06-01

Sphincter of Oddi dysfunction is one of the most important symptoms in post-cholecystectomy syndrome. Using either electrical or mechanical stimulation and retrogradely transported neuronal dyes, it has been demonstrated that there are direct neural pathways connecting gall bladder and the sphincter of Oddi in the Australian opossum and the golden hamster. In the present study, we employed whole-mount immunohistochemistry staining to observe and verify that there are two different plexuses of the extrahepatic biliary tract in Suncus murinus. One, named Pathway One, showed a fine, irregular but dense network plexus that ran adhesively and resided on/in the extrahepatic biliary tract wall, and the plexus extended into the intrahepatic area. On the other hand, named Pathway Two, exhibiting simple, thicker and straight neural bundles, ran parallel to the surface of the extrahepatic biliary tract and passed between the gall bladder and duodenum, but did not give off any branches to the liver. Pathway Two was considered to involve direct bidirectional neural connections between the duodenum and the biliary tract system. For the first time, morphologically, we demonstrated direct neural connections between gall bladder and duodenum in S. murinus. Malfunction of the sphincter of Oddi may be caused by injury of the direct neural pathways between gall bladder and duodenum by cholecystectomy. From the viewpoint of preserving the function of the major duodenal papilla and common bile duct, we emphasize the importance of avoiding kocherization of the common bile duct so as to preserve the direct neural connections between gall bladder and sphincter of Oddi. © 2015 Blackwell Verlag GmbH.

Neural mechanisms of individual and sexual recognition in Syrian hamsters (Mesocricetus auratus).

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Petrulis, Aras

2009-06-25

Recognizing the individual and sexual identities of conspecifics is critical for adaptive social behavior and, in most mammals this information is communicated primarily by chemosensory cues. Due to its heavy reliance on odor cues, we have used the Syrian hamster as our model species for investigating the neural regulation of social recognition. Using lesion, electrophysiological and immunocytochemical techniques, separate neural pathways underlying recognition of individual odors and guidance of sex-typical responses to opposite-sex odors have been identified in both male and female hamsters. Specifically, we have found that recognition of individual odor identity requires olfactory bulb connections to entorhinal cortex (ENT) rather than other chemoreceptive brain regions. This kind of social memory does not appear to require the hippocampus and may, instead, depend on ENT connections with piriform cortex. In contrast, sexual recognition, through either differential investigation or scent marking toward opposite-sex odors, depends on both olfactory and vomeronasal system input to the corticomedial amygdala. Preference for investigating opposite-sex odors requires primarily olfactory input to the medial amygdala (ME) whereas appropriately targeted scent marking responses require vomeronasal input to ME as well as to other structures. Within the ME, the anterior section (MEa) appears important for evaluating or classifying social odors whereas the posterodorsal region (MEpd) may be more involved in generating approach to social odors. Evidence is presented that analysis of social odors may initially be done in MEa and then communicated to MEpd, perhaps through micro-circuits that separately process male and female odors.

Aβ-Induced Insulin Resistance and the Effects of Insulin on the Cholesterol Synthesis Pathway and Aβ Secretion in Neural Cells.

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Najem, Dema; Bamji-Mirza, Michelle; Yang, Ze; Zhang, Wandong

2016-06-01

Alzheimer's disease (AD) is characterized by amyloid-β (Aβ) toxicity, tau pathology, insulin resistance, neuroinflammation, and dysregulation of cholesterol homeostasis, all of which play roles in neurodegeneration. Insulin has polytrophic effects on neurons and may be at the center of these pathophysiological changes. In this study, we investigated possible relationships among insulin signaling and cholesterol biosynthesis, along with the effects of Aβ42 on these pathways in vitro. We found that neuroblastoma 2a (N2a) cells transfected with the human gene encoding amyloid-β protein precursor (AβPP) (N2a-AβPP) produced Aβ and exhibited insulin resistance by reduced p-Akt and a suppressed cholesterol-synthesis pathway following insulin treatment, and by increased phosphorylation of insulin receptor subunit-1 at serine 612 (p-IRS-S612) as compared to parental N2a cells. Treatment of human neuroblastoma SH-SY5Y cells with Aβ42 also increased p-IRS-S612, suggesting that Aβ42 is responsible for insulin resistance. The insulin resistance was alleviated when N2a-AβPP cells were treated with higher insulin concentrations. Insulin increased Aβ release from N2a-AβPP cells, by which it may promote Aβ clearance. Insulin increased cholesterol-synthesis gene expression in SH-SY5Y and N2a cells, including 24-dehydrocholesterol reductase (DHCR24) and 3-hydroxy-3-methyl-glutaryl-CoA reductase (HMGCR) through sterol-regulatory element-binding protein-2 (SREBP2). While Aβ42-treated SH-SY5Y cells exhibited increased HMGCR expression and c-Jun phosphorylation as pro-inflammatory responses, they also showed down-regulation of neuro-protective/anti-inflammatory DHCR24. These results suggest that Aβ42 may cause insulin resistance, activate JNK for c-Jun phosphorylation, and lead to dysregulation of cholesterol homeostasis, and that enhancing insulin signaling may relieve the insulin-resistant phenotype and the dysregulated cholesterol-synthesis pathway to promote A�

Neural network classifier of attacks in IP telephony

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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.

Uncinate fasciculus fractional anisotropy correlates with typical use of reappraisal in women but not men.

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Zuurbier, Lisette A; Nikolova, Yuliya S; Ahs, Fredrik; Hariri, Ahmad R

2013-06-01

Emotion regulation refers to strategies through which individuals influence their experience and expression of emotions. Two typical strategies are reappraisal, a cognitive strategy for reframing the context of an emotional experience, and suppression, a behavioral strategy for inhibiting emotional responses. Functional neuroimaging studies have revealed that regions of the prefrontal cortex modulate amygdala reactivity during both strategies, but relatively greater downregulation of the amygdala occurs during reappraisal. Moreover, these studies demonstrated that engagement of this modulatory circuitry varies as a function of gender. The uncinate fasciculus is a major structural pathway connecting regions of the anterior temporal lobe, including the amygdala to inferior frontal regions, especially the orbitofrontal cortex. The objective of the current study was to map variability in the structural integrity of the uncinate fasciculus onto individual differences in self-reported typical use of reappraisal and suppression. Diffusion tensor imaging was used in 194 young adults to derive regional fractional anisotropy values for the right and left uncinate fasciculus. All participants also completed the Emotion Regulation Questionnaire. In women but not men, self-reported typical reappraisal use was positively correlated with fractional anisotropy values in a region of the left uncinate fasciculus within the orbitofrontal cortex. In contrast, typical use of suppression was not significantly correlated with fractional anisotropy in any region of the uncinate fasciculus in either men or women. Our data suggest that in women typical reappraisal use is specifically related to the integrity of white matter pathways linking the amygdala and prefrontal cortex.

Bridging the Gaps in the Study of Typical and Atypical Cognitive Development: A Commentary

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Graham, Susan A.; Madigan, Sheri

2016-01-01

The articles in this special issue of the "Journal of Cognition and Development" examine the cognitive development of children who are following typical and atypical developmental pathways. The articles offer a mixture of theory-based considerations, reviews of the literature, and new empirical data addressing fundamental aspects of…

Developmental Pathway Genes and Neural Plasticity Underlying Emotional Learning and Stress-Related Disorders

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Maheau, Marissa E.; Ressler, Kerry J.

2017-01-01

The manipulation of neural plasticity as a means of intervening in the onset and progression of stress-related disorders retains its appeal for many researchers, despite our limited success in translating such interventions from the laboratory to the clinic. Given the challenges of identifying individual genetic variants that confer increased risk…

Association of Low Ficolin-Lectin Pathway Parameters with Cardiac Syndrome X

DEFF Research Database (Denmark)

Horváth, Z; Csuka, Dorottya; Vargova, K

2016-01-01

In patients with typical angina pectoris, inducible myocardial ischaemia and macroscopically normal coronaries (cardiac syndrome X (CSX)), a significantly elevated plasma level of terminal complement complex (TCC), the common end product of complement activation, has been observed without.......003). In conclusion, in patients with typical angina and myocardial ischaemia despite macroscopically normal coronary arteries, low levels of several lectin pathway parameters were observed, indicating complement activation and consumption. Complement activation through the ficolin-lectin pathway might play a role...

Robust synchronization of delayed neural networks based on adaptive control and parameters identification

International Nuclear Information System (INIS)

Zhou Jin; Chen Tianping; Xiang Lan

2006-01-01

This paper investigates synchronization dynamics of delayed neural networks with all the parameters unknown. By combining the adaptive control and linear feedback with the updated law, some simple yet generic criteria for determining the robust synchronization based on the parameters identification of uncertain chaotic delayed neural networks are derived by using the invariance principle of functional differential equations. It is shown that the approaches developed here further extend the ideas and techniques presented in recent literature, and they are also simple to implement in practice. Furthermore, the theoretical results are applied to a typical chaotic delayed Hopfied neural networks, and numerical simulation also demonstrate the effectiveness and feasibility of the proposed technique

Murine dishevelled 3 functions in redundant pathways with dishevelled 1 and 2 in normal cardiac outflow tract, cochlea, and neural tube development.

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Etheridge, S Leah; Ray, Saugata; Li, Shuangding; Hamblet, Natasha S; Lijam, Nardos; Tsang, Michael; Greer, Joy; Kardos, Natalie; Wang, Jianbo; Sussman, Daniel J; Chen, Ping; Wynshaw-Boris, Anthony

2008-11-01

Dishevelled (Dvl) proteins are important signaling components of both the canonical beta-catenin/Wnt pathway, which controls cell proliferation and patterning, and the planar cell polarity (PCP) pathway, which coordinates cell polarity within a sheet of cells and also directs convergent extension cell (CE) movements that produce narrowing and elongation of the tissue. Three mammalian Dvl genes have been identified and the developmental roles of Dvl1 and Dvl2 were previously determined. Here, we identify the functions of Dvl3 in development and provide evidence of functional redundancy among the three murine Dvls. Dvl3(-/-) mice died perinatally with cardiac outflow tract abnormalities, including double outlet right ventricle and persistent truncus arteriosis. These mutants also displayed a misorientated stereocilia in the organ of Corti, a phenotype that was enhanced with the additional loss of a single allele of the PCP component Vangl2/Ltap (LtapLp/+). Although neurulation appeared normal in both Dvl3(-/-) and LtapLp/+ mutants, Dvl3(+/-);LtapLp/+ combined mutants displayed incomplete neural tube closure. Importantly, we show that many of the roles of Dvl3 are also shared by Dvl1 and Dvl2. More severe phenotypes were observed in Dvl3 mutants with the deficiency of another Dvl, and increasing Dvl dosage genetically with Dvl transgenes demonstrated the ability of Dvls to compensate for each other to enable normal development. Interestingly, global canonical Wnt signaling appeared largely unaffected in the double Dvl mutants, suggesting that low Dvl levels are sufficient for functional canonical Wnt signals. In summary, we demonstrate that Dvl3 is required for cardiac outflow tract development and describe its importance in the PCP pathway during neurulation and cochlea development. Finally, we establish several developmental processes in which the three Dvls are functionally redundant.

Murine dishevelled 3 functions in redundant pathways with dishevelled 1 and 2 in normal cardiac outflow tract, cochlea, and neural tube development.

Directory of Open Access Journals (Sweden)

S Leah Etheridge

2008-11-01

Full Text Available Dishevelled (Dvl proteins are important signaling components of both the canonical beta-catenin/Wnt pathway, which controls cell proliferation and patterning, and the planar cell polarity (PCP pathway, which coordinates cell polarity within a sheet of cells and also directs convergent extension cell (CE movements that produce narrowing and elongation of the tissue. Three mammalian Dvl genes have been identified and the developmental roles of Dvl1 and Dvl2 were previously determined. Here, we identify the functions of Dvl3 in development and provide evidence of functional redundancy among the three murine Dvls. Dvl3(-/- mice died perinatally with cardiac outflow tract abnormalities, including double outlet right ventricle and persistent truncus arteriosis. These mutants also displayed a misorientated stereocilia in the organ of Corti, a phenotype that was enhanced with the additional loss of a single allele of the PCP component Vangl2/Ltap (LtapLp/+. Although neurulation appeared normal in both Dvl3(-/- and LtapLp/+ mutants, Dvl3(+/-;LtapLp/+ combined mutants displayed incomplete neural tube closure. Importantly, we show that many of the roles of Dvl3 are also shared by Dvl1 and Dvl2. More severe phenotypes were observed in Dvl3 mutants with the deficiency of another Dvl, and increasing Dvl dosage genetically with Dvl transgenes demonstrated the ability of Dvls to compensate for each other to enable normal development. Interestingly, global canonical Wnt signaling appeared largely unaffected in the double Dvl mutants, suggesting that low Dvl levels are sufficient for functional canonical Wnt signals. In summary, we demonstrate that Dvl3 is required for cardiac outflow tract development and describe its importance in the PCP pathway during neurulation and cochlea development. Finally, we establish several developmental processes in which the three Dvls are functionally redundant.

Cognon Neural Model Software Verification and Hardware Implementation Design

Science.gov (United States)

Haro Negre, Pau

Little is known yet about how the brain can recognize arbitrary sensory patterns within milliseconds using neural spikes to communicate information between neurons. In a typical brain there are several layers of neurons, with each neuron axon connecting to ˜104 synapses of neurons in an adjacent layer. The information necessary for cognition is contained in theses synapses, which strengthen during the learning phase in response to newly presented spike patterns. Continuing on the model proposed in "Models for Neural Spike Computation and Cognition" by David H. Staelin and Carl H. Staelin, this study seeks to understand cognition from an information theoretic perspective and develop potential models for artificial implementation of cognition based on neuronal models. To do so we focus on the mathematical properties and limitations of spike-based cognition consistent with existing neurological observations. We validate the cognon model through software simulation and develop concepts for an optical hardware implementation of a network of artificial neural cognons.

The neural basis of loss aversion in decision-making under risk.

Science.gov (United States)

Tom, Sabrina M; Fox, Craig R; Trepel, Christopher; Poldrack, Russell A

2007-01-26

People typically exhibit greater sensitivity to losses than to equivalent gains when making decisions. We investigated neural correlates of loss aversion while individuals decided whether to accept or reject gambles that offered a 50/50 chance of gaining or losing money. A broad set of areas (including midbrain dopaminergic regions and their targets) showed increasing activity as potential gains increased. Potential losses were represented by decreasing activity in several of these same gain-sensitive areas. Finally, individual differences in behavioral loss aversion were predicted by a measure of neural loss aversion in several regions, including the ventral striatum and prefrontal cortex.

Differentiating neural reward responsiveness in autism versus ADHD

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Gregor Kohls

2014-10-01

Full Text Available Although attention deficit hyperactivity disorders (ADHD and autism spectrum disorders (ASD share certain neurocognitive characteristics, it has been hypothesized to differentiate the two disorders based on their brain's reward responsiveness to either social or monetary reward. Thus, the present fMRI study investigated neural activation in response to both reward types in age and IQ-matched boys with ADHD versus ASD relative to typically controls (TDC. A significant group by reward type interaction effect emerged in the ventral striatum with greater activation to monetary versus social reward only in TDC, whereas subjects with ADHD responded equally strong to both reward types, and subjects with ASD showed low striatal reactivity across both reward conditions. Moreover, disorder-specific neural abnormalities were revealed, including medial prefrontal hyperactivation in response to social reward in ADHD versus ventral striatal hypoactivation in response to monetary reward in ASD. Shared dysfunction was characterized by fronto-striato-parietal hypoactivation in both clinical groups when money was at stake. Interestingly, lower neural activation within parietal circuitry was associated with higher autistic traits across the entire study sample. In sum, the present findings concur with the assumption that both ASD and ADHD display distinct and shared neural dysfunction in response to reward.

Neural precursors of future liking and affective reciprocity.

Science.gov (United States)

Zerubavel, Noam; Hoffman, Mark Anthony; Reich, Adam; Ochsner, Kevin N; Bearman, Peter

2018-04-24

Why do certain group members end up liking each other more than others? How does affective reciprocity arise in human groups? The prediction of interpersonal sentiment has been a long-standing pursuit in the social sciences. We combined fMRI and longitudinal social network data to test whether newly acquainted group members' reward-related neural responses to images of one another's faces predict their future interpersonal sentiment, even many months later. Specifically, we analyze associations between relationship-specific valuation activity and relationship-specific future liking. We found that one's own future (T2) liking of a particular group member is predicted jointly by actor's initial (T1) neural valuation of partner and by that partner's initial (T1) neural valuation of actor. These actor and partner effects exhibited equivalent predictive strength and were robust when statistically controlling for each other, both individuals' initial liking, and other potential drivers of liking. Behavioral findings indicated that liking was initially unreciprocated at T1 yet became strongly reciprocated by T2. The emergence of affective reciprocity was partly explained by the reciprocal pathways linking dyad members' T1 neural data both to their own and to each other's T2 liking outcomes. These findings elucidate interpersonal brain mechanisms that define how we ultimately end up liking particular interaction partners, how group members' initially idiosyncratic sentiments become reciprocated, and more broadly, how dyads evolve. This study advances a flexible framework for researching the neural foundations of interpersonal sentiments and social relations that-conceptually, methodologically, and statistically-emphasizes group members' neural interdependence. Copyright © 2018 the Author(s). Published by PNAS.

ADAM13 Induces Cranial Neural Crest by Cleaving Class B Ephrins and Regulating Wnt Signaling

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Wei, Shuo; Xu, Guofeng; Bridges, Lance C.; Williams, Phoebe; White, Judith M.; DeSimone, Douglas W.

2010-01-01

SUMMARY The cranial neural crest (CNC) are multipotent embryonic cells that contribute to craniofacial structures and other cells and tissues of the vertebrate head. During embryogenesis, CNC is induced at the neural plate boundary through the interplay of several major signaling pathways. Here we report that the metalloproteinase activity of ADAM13 is required for early induction of CNC in Xenopus. In both cultured cells and X. tropicalis embryos, membrane-bound Ephrins (Efns) B1 and B2 were identified as substrates for ADAM13. ADAM13 upregulates canonical Wnt signaling and early expression of the transcription factor snail2, whereas EfnB1 inhibits the canonical Wnt pathway and snail2 expression. We propose that by cleaving class B Efns, ADAM13 promotes canonical Wnt signaling and early CNC induction. PMID:20708595

Impaired neuronal maturation of hippocampal neural progenitor cells in mice lacking CRAF.

Science.gov (United States)

Pfeiffer, Verena; Götz, Rudolf; Camarero, Guadelupe; Heinsen, Helmut; Blum, Robert; Rapp, Ulf Rüdiger

2018-01-01

RAF kinases are major constituents of the mitogen activated signaling pathway, regulating cell proliferation, differentiation and cell survival of many cell types, including neurons. In mammals, the family of RAF proteins consists of three members, ARAF, BRAF, and CRAF. Ablation of CRAF kinase in inbred mouse strains causes major developmental defects during fetal growth and embryonic or perinatal lethality. Heterozygous germline mutations in CRAF result in Noonan syndrome, which is characterized by neurocognitive impairment that may involve hippocampal physiology. The role of CRAF signaling during hippocampal development and generation of new postnatal hippocampal granule neurons has not been examined and may provide novel insight into the cause of hippocampal dysfunction in Noonan syndrome. In this study, by crossing CRAF-deficiency to CD-1 outbred mice, a CRAF mouse model was established which enabled us to investigate the interplay of neural progenitor proliferation and postmitotic differentiation during adult neurogenesis in the hippocampus. Albeit the general morphology of the hippocampus was unchanged, CRAF-deficient mice displayed smaller granule cell layer (GCL) volume at postnatal day 30 (P30). In CRAF-deficient mice a substantial number of abnormal, chromophilic, fast dividing cells were found in the subgranular zone (SGZ) and hilus of the dentate gyrus (DG), indicating that CRAF signaling contributes to hippocampal neural progenitor proliferation. CRAF-deficient neural progenitor cells showed an increased cell death rate and reduced neuronal maturation. These results indicate that CRAF function affects postmitotic neural cell differentiation and points to a critical role of CRAF-dependent growth factor signaling pathway in the postmitotic development of adult-born neurons.

Neural correlates of eating disorders: translational potential

Directory of Open Access Journals (Sweden)

McAdams CJ

2015-09-01

Full Text Available Carrie J McAdams,1,2 Whitney Smith1 1University of Texas at Southwestern Medical Center, 2Department of Psychiatry, Texas Health Presbyterian Hospital of Dallas, Dallas, TX, USA Abstract: Eating disorders are complex and serious psychiatric illnesses whose etiology includes psychological, biological, and social factors. Treatment of eating disorders is challenging as there are few evidence-based treatments and limited understanding of the mechanisms that result in sustained recovery. In the last 20 years, we have begun to identify neural pathways that are altered in eating disorders. Consideration of how these pathways may contribute to an eating disorder can provide an understanding of expected responses to treatments. Eating disorder behaviors include restrictive eating, compulsive overeating, and purging behaviors after eating. Eating disorders are associated with changes in many neural systems. In this targeted review, we focus on three cognitive processes associated with neurocircuitry differences in subjects with eating disorders such as reward, decision-making, and social behavior. We briefly examine how each of these systems function in healthy people, using Neurosynth meta-analysis to identify key regions commonly implicated in these circuits. We review the evidence for disruptions of these regions and systems in eating disorders. Finally, we describe psychiatric and psychological treatments that are likely to function by impacting these regions. Keywords: anorexia nervosa, bulimia nervosa, social cognition, reward processing, decision-making

ADAM13 Induces Cranial Neural Crest by Cleaving Class B Ephrins and Regulating Wnt Signaling

OpenAIRE

Wei, Shuo; Xu, Guofeng; Bridges, Lance C.; Williams, Phoebe; White, Judith M.; DeSimone, Douglas W.

2010-01-01

The cranial neural crest (CNC) are multipotent embryonic cells that contribute to craniofacial structures and other cells and tissues of the vertebrate head. During embryogenesis, CNC is induced at the neural plate boundary through the interplay of several major signaling pathways. Here we report that the metalloproteinase activity of ADAM13 is required for early induction of CNC in Xenopus. In both cultured cells and X. tropicalis embryos, membrane-bound Ephrins (Efns) B1 and B2 were identif...

Field-theoretic approach to fluctuation effects in neural networks

International Nuclear Information System (INIS)

Buice, Michael A.; Cowan, Jack D.

2007-01-01

A well-defined stochastic theory for neural activity, which permits the calculation of arbitrary statistical moments and equations governing them, is a potentially valuable tool for theoretical neuroscience. We produce such a theory by analyzing the dynamics of neural activity using field theoretic methods for nonequilibrium statistical processes. Assuming that neural network activity is Markovian, we construct the effective spike model, which describes both neural fluctuations and response. This analysis leads to a systematic expansion of corrections to mean field theory, which for the effective spike model is a simple version of the Wilson-Cowan equation. We argue that neural activity governed by this model exhibits a dynamical phase transition which is in the universality class of directed percolation. More general models (which may incorporate refractoriness) can exhibit other universality classes, such as dynamic isotropic percolation. Because of the extremely high connectivity in typical networks, it is expected that higher-order terms in the systematic expansion are small for experimentally accessible measurements, and thus, consistent with measurements in neocortical slice preparations, we expect mean field exponents for the transition. We provide a quantitative criterion for the relative magnitude of each term in the systematic expansion, analogous to the Ginsburg criterion. Experimental identification of dynamic universality classes in vivo is an outstanding and important question for neuroscience

A Computational Model of a Descending Mechanosensory Pathway Involved in Active Tactile Sensing.

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Jan M Ache

2015-07-01

Full Text Available Many animals, including humans, rely on active tactile sensing to explore the environment and negotiate obstacles, especially in the dark. Here, we model a descending neural pathway that mediates short-latency proprioceptive information from a tactile sensor on the head to thoracic neural networks. We studied the nocturnal stick insect Carausius morosus, a model organism for the study of adaptive locomotion, including tactually mediated reaching movements. Like mammals, insects need to move their tactile sensors for probing the environment. Cues about sensor position and motion are therefore crucial for the spatial localization of tactile contacts and the coordination of fast, adaptive motor responses. Our model explains how proprioceptive information about motion and position of the antennae, the main tactile sensors in insects, can be encoded by a single type of mechanosensory afferents. Moreover, it explains how this information is integrated and mediated to thoracic neural networks by a diverse population of descending interneurons (DINs. First, we quantified responses of a DIN population to changes in antennal position, motion and direction of movement. Using principal component (PC analysis, we find that only two PCs account for a large fraction of the variance in the DIN response properties. We call the two-dimensional space spanned by these PCs 'coding-space' because it captures essential features of the entire DIN population. Second, we model the mechanoreceptive input elements of this descending pathway, a population of proprioceptive mechanosensory hairs monitoring deflection of the antennal joints. Finally, we propose a computational framework that can model the response properties of all important DIN types, using the hair field model as its only input. This DIN model is validated by comparison of tuning characteristics, and by mapping the modelled neurons into the two-dimensional coding-space of the real DIN population. This

The role of the amygdala in naturalistic mentalising in typical development and in autism spectrum disorder.

Science.gov (United States)

Rosenblau, Gabriela; Kliemann, Dorit; Lemme, Benjamin; Walter, Henrik; Heekeren, Hauke R; Dziobek, Isabel

2016-06-01

The substantial discrepancy between mentalising in experimental settings v. real-life social interactions hinders the understanding of the neural basis of real-life social cognition and of social impairments in psychiatric disorders. To determine the neural mechanisms underlying naturalistic mentalising in individuals with and without autism spectrum disorder. We investigated mentalising with a new video-based functional magnetic resonance imaging task in 20 individuals with autism spectrum disorder and 22 matched healthy controls. Naturalistic mentalising implicated regions of the traditional mentalising network (medial prefrontal cortex, temporoparietal junction), and additionally the insula and amygdala. Moreover, amygdala activity predicted implicit mentalising performance on an independent behavioural task. Compared with controls, the autism spectrum disorder group did not show differences in neural activity within classical mentalising regions. They did, however, show reduced amygdala activity and a reduced correlation between amygdala activity and mentalising accuracy on the behavioural task, compared with controls. These findings highlight the crucial role of the amygdala in making accurate implicit mental state inferences in typical development and in the social cognitive impairments of individuals with autism spectrum disorder. © The Royal College of Psychiatrists 2016.

Maximum solid concentrations of coal water slurries predicted by neural network models

Energy Technology Data Exchange (ETDEWEB)

Cheng, Jun; Li, Yanchang; Zhou, Junhu; Liu, Jianzhong; Cen, Kefa

2010-12-15

The nonlinear back-propagation (BP) neural network models were developed to predict the maximum solid concentration of coal water slurry (CWS) which is a substitute for oil fuel, based on physicochemical properties of 37 typical Chinese coals. The Levenberg-Marquardt algorithm was used to train five BP neural network models with different input factors. The data pretreatment method, learning rate and hidden neuron number were optimized by training models. It is found that the Hardgrove grindability index (HGI), moisture and coalification degree of parent coal are 3 indispensable factors for the prediction of CWS maximum solid concentration. Each BP neural network model gives a more accurate prediction result than the traditional polynomial regression equation. The BP neural network model with 3 input factors of HGI, moisture and oxygen/carbon ratio gives the smallest mean absolute error of 0.40%, which is much lower than that of 1.15% given by the traditional polynomial regression equation. (author)

Neural-network-designed pulse sequences for robust control of singlet-triplet qubits

Science.gov (United States)

Yang, Xu-Chen; Yung, Man-Hong; Wang, Xin

2018-04-01

Composite pulses are essential for universal manipulation of singlet-triplet spin qubits. In the absence of noise, they are required to perform arbitrary single-qubit operations due to the special control constraint of a singlet-triplet qubit, while in a noisy environment, more complicated sequences have been developed to dynamically correct the error. Tailoring these sequences typically requires numerically solving a set of nonlinear equations. Here we demonstrate that these pulse sequences can be generated by a well-trained, double-layer neural network. For sequences designed for the noise-free case, the trained neural network is capable of producing almost exactly the same pulses known in the literature. For more complicated noise-correcting sequences, the neural network produces pulses with slightly different line shapes, but the robustness against noises remains comparable. These results indicate that the neural network can be a judicious and powerful alternative to existing techniques in developing pulse sequences for universal fault-tolerant quantum computation.

Cornelia de Lange Syndrome: NIPBL haploinsufficiency downregulates canonical Wnt pathway in zebrafish embryos and patients fibroblasts.

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Pistocchi, A; Fazio, G; Cereda, A; Ferrari, L; Bettini, L R; Messina, G; Cotelli, F; Biondi, A; Selicorni, A; Massa, V

2013-10-17

Cornelia de Lange Syndrome is a severe genetic disorder characterized by malformations affecting multiple systems, with a common feature of severe mental retardation. Genetic variants within four genes (NIPBL (Nipped-B-like), SMC1A, SMC3, and HDAC8) are believed to be responsible for the majority of cases; all these genes encode proteins that are part of the 'cohesin complex'. Cohesins exhibit two temporally separated major roles in cells: one controlling the cell cycle and the other involved in regulating the gene expression. The present study focuses on the role of the zebrafish nipblb paralog during neural development, examining its expression in the central nervous system, and analyzing the consequences of nipblb loss of function. Neural development was impaired by the knockdown of nipblb in zebrafish. nipblb-loss-of-function embryos presented with increased apoptosis in the developing neural tissues, downregulation of canonical Wnt pathway genes, and subsequent decreased Cyclin D1 (Ccnd1) levels. Importantly, the same pattern of canonical WNT pathway and CCND1 downregulation was observed in NIPBL-mutated patient-specific fibroblasts. Finally, chemical activation of the pathway in nipblb-loss-of-function embryos rescued the adverse phenotype and restored the physiological levels of cell death.

Neural mechanisms of oculomotor abnormalities in the infantile strabismus syndrome.

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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.

Neural plasticity in functional and anatomical MRI studies of children with Tourette syndrome.

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Eichele, Heike; Plessen, Kerstin J

2013-01-01

Tourette syndrome (TS) is a neuropsychiatric disorder with childhood onset characterized by chronic motor and vocal tics. The typical clinical course of an attenuation of symptoms during adolescence in parallel with the emerging self-regulatory control during development suggests that plastic processes may play an important role in the development of tic symptoms. We conducted a systematic search to identify existing imaging studies (both anatomical and functional magnetic resonance imaging [fMRI]) in young persons under the age of 19 years with TS. The final search resulted in 13 original studies, which were reviewed with a focus on findings suggesting adaptive processes (using fMRI) and plasticity (using anatomical MRI). Differences in brain activation compared to healthy controls during tasks that require overriding of prepotent responses help to understand compensatory pathways in children with TS. Along with alterations in regions putatively representing the origin of tics, deviations in several other regions most likely represent an activity-dependent neural plasticity that help to modulate tic severity, such as the prefrontal cortex, but also in the corpus callosum and the limbic system. Factors that potentially influence the development of adaptive changes in the brain of children with TS are age, comorbidity with other developmental disorders, medication use, IQ along with study-design or MRI techniques for acquisition, and analysis of data. The most prominent limitation of all studies is their cross-sectional design. Longitudinal studies extending to younger age groups and to children at risk for developing TS hopefully will confirm findings of neural plasticity in future investigations.

[Comprehensive regulation effect of traditional Chinese medicine on proliferation and differentiation of neural stem cells].

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Wang, Hong-Jin; Li, Jing-Jing; Ke, Hui; Xu, Xiao-Yu

2017-11-01

Since the discovery of neural stem cells(NSCs) in embryonic and adult mammalian central nervous systems, new approaches for proliferation and differentiation of NSCs have been put forward. One of the approaches to promote the clinical application of NSCs is to search effective methods to regulate the proliferation and differentiation. This problem is urgently to be solved in the medical field. Previous studies have shown that traditional Chinese medicine could promote the proliferation and differentiation of NSCs by regulating the relevant signaling pathway in vivo and in vitro. Domestic and foreign literatures for regulating the proliferation and differentiation of neural stem cells in recent 10 years and the reports for their target and signaling pathways were analyzed in this paper. Traditional Chinese medicine could regulate the proliferation and differentiation of NSCs through signaling pathways of Notch, PI3K/Akt, Wnt/β-catenin and GFs. However, studies about NSCs and traditional Chinese medicine should be further deepened; the mechanism of multiple targets and the comprehensive regulation function of traditional Chinese medicine should be clarified. Copyright© by the Chinese Pharmaceutical Association.

A stochastic learning algorithm for layered neural networks

International Nuclear Information System (INIS)

Bartlett, E.B.; Uhrig, R.E.

1992-01-01

The random optimization method typically uses a Gaussian probability density function (PDF) to generate a random search vector. In this paper the random search technique is applied to the neural network training problem and is modified to dynamically seek out the optimal probability density function (OPDF) from which to select the search vector. The dynamic OPDF search process, combined with an auto-adaptive stratified sampling technique and a dynamic node architecture (DNA) learning scheme, completes the modifications of the basic method. The DNA technique determines the appropriate number of hidden nodes needed for a given training problem. By using DNA, researchers do not have to set the neural network architectures before training is initiated. The approach is applied to networks of generalized, fully interconnected, continuous perceptions. Computer simulation results are given

Exploration of molecular pathways mediating electric field-directed Schwann cell migration by RNA-Seq

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Yao, Li; Li, Yongchao; Knapp, Jennifer; Smith, Peter

2015-01-01

In peripheral nervous systems, Schwann cells wrap around axons of motor and sensory neurons to form the myelin sheath. Following spinal cord injury, Schwann cells regenerate and migrate to the lesion and are involved in the spinal cord regeneration process. Transplantation of Schwann cells into injured neural tissue results in enhanced spinal axonal regeneration. Effective directional migration of Schwann cells is critical in the neural regeneration process. In this study, we report that Schwann cells migrate anodally in an applied electric field (EF). The directedness and displacement of anodal migration increased significantly when the strength of the EF increased from 50 mV/mm to 200 mV/mm. The EF did not significantly affect the cell migration speed. To explore the genes and signaling pathways that regulate cell migration in EFs, we performed a comparative analysis of differential gene expression between cells stimulated with an EF (100 mV/mm) and those without using next-generation RNA sequencing, verified by RT-qPCR. Based on the cut-off criteria (FC > 1.2, q cells versus EF-stimulated cells. A Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis found that compared to the control group, 21 pathways are down-regulated, while 10 pathways are up-regulated. Differentially expressed genes participate in multiple cellular signaling pathways involved in the regulation of cell migration, including pathways of regulation of actin cytoskeleton, focal adhesion, and PI3K-Akt. PMID:25557037

Stephen L. Gans Distinguished Overseas Lecture. The neural crest in pediatric surgery.

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Tovar, Juan A

2007-06-01

This review highlights the relevance of the neural crest (NC) as a developmental control mechanism involved in several pediatric surgical conditions and the investigative interest of following some of its known signaling pathways. The participation of the NC in facial clefts, ear defects, branchial fistulae and cysts, heart outflow tract and aortic arch anomalies, pigmentary disorders, abnormal enteric innervation, neural tumors, hemangiomas, and vascular anomalies is briefly reviewed. Then, the literature on clinical and experimental esophageal atresia-tracheoesophageal fistula (EA-TEF) and congenital diaphragmatic hernia (CDH) is reviewed for the presence of associated NC defects. Finally, some of the molecular signaling pathways involved in both conditions (sonic hedgehog, Hox genes, and retinoids) are summarized. The association of facial, cardiovascular, thymic, parathyroid, and C-cell defects together with anomalies of extrinsic and intrinsic esophageal innervation in babies and/or animals with both EA-TEF and CDH strongly supports the hypothesis that NC is involved in the pathogenesis of these malformative clusters. On the other hand, both EA-TEF and CDH are observed in mice mutant for genes involved in the previously mentioned signaling pathways. The investigation of NC-related molecular pathogenic pathways involved in malformative associations like EA-TEF and CDH that are induced by chromosomal anomalies, chemical teratogens, and engineered mutations is a promising way of clarifying why and how some pediatric surgical conditions occur. Pediatric surgeons should be actively involved in these investigations.

Re-evaluation of the AASHTO-flexible pavement design equation with neural network modeling.

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Tiğdemir, Mesut

2014-01-01

Here we establish that equivalent single-axle loads values can be estimated using artificial neural networks without the complex design equality of American Association of State Highway and Transportation Officials (AASHTO). More importantly, we find that the neural network model gives the coefficients to be able to obtain the actual load values using the AASHTO design values. Thus, those design traffic values that might result in deterioration can be better calculated using the neural networks model than with the AASHTO design equation. The artificial neural network method is used for this purpose. The existing AASHTO flexible pavement design equation does not currently predict the pavement performance of the strategic highway research program (Long Term Pavement Performance studies) test sections very accurately, and typically over-estimates the number of equivalent single axle loads needed to cause a measured loss of the present serviceability index. Here we aimed to demonstrate that the proposed neural network model can more accurately represent the loads values data, compared against the performance of the AASHTO formula. It is concluded that the neural network may be an appropriate tool for the development of databased-nonparametric models of pavement performance.

Deep Recurrent Neural Networks for Human Activity Recognition

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Abdulmajid Murad

2017-11-01

Full Text Available Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM and k-nearest neighbors (KNN. Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs and CNNs.

Deep Recurrent Neural Networks for Human Activity Recognition.

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Murad, Abdulmajid; Pyun, Jae-Young

2017-11-06

Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs) address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs) for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM) DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM) and k-nearest neighbors (KNN). Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs) and CNNs.

Autism as an adaptive common variant pathway for human brain development

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Mark H. Johnson

2017-06-01

Full Text Available While research on focal perinatal lesions has provided evidence for recovery of function, much less is known about processes of brain adaptation resulting from mild but widespread disturbances to neural processing over the early years (such as alterations in synaptic efficiency. Rather than being viewed as a direct behavioral consequence of life-long neural dysfunction, I propose that autism is best viewed as the end result of engaging adaptive processes during a sensitive period. From this perspective, autism is not appropriately described as a disorder of neurodevelopment, but rather as an adaptive common variant pathway of human functional brain development.

Fault Diagnosis of Hydraulic Servo Valve Based on Genetic Optimization RBF-BP Neural Network

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Li-Ping FAN

2014-04-01

Full Text Available Electro-hydraulic servo valves are core components of the hydraulic servo system of rolling mills. It is necessary to adopt an effective fault diagnosis method to keep the hydraulic servo valve in a good work state. In this paper, RBF and BP neural network are integrated effectively to build a double hidden layers RBF-BP neural network for fault diagnosis. In the process of training the neural network, genetic algorithm (GA is used to initialize and optimize the connection weights and thresholds of the network. Several typical fault states are detected by the constructed GA-optimized fault diagnosis scheme. Simulation results shown that the proposed fault diagnosis scheme can give satisfactory effect.

Inwardly Rectifying Potassium (Kir) Channels Represent a Critical Ion Conductance Pathway in the Nervous Systems of Insects.

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Chen, Rui; Swale, Daniel R

2018-01-25

A complete understanding of the physiological pathways critical for proper function of the insect nervous system is still lacking. The recent development of potent and selective small-molecule modulators of insect inward rectifier potassium (Kir) channels has enabled the interrogation of the physiological role and toxicological potential of Kir channels within various insect tissue systems. Therefore, we aimed to highlight the physiological and functional role of neural Kir channels the central nervous system, muscular system, and neuromuscular system through pharmacological and genetic manipulations. Our data provide significant evidence that Drosophila neural systems rely on the inward conductance of K + ions for proper function since pharmacological inhibition and genetic ablation of neural Kir channels yielded dramatic alterations of the CNS spike discharge frequency and broadening and reduced amplitude of the evoked EPSP at the neuromuscular junction. Based on these data, we conclude that neural Kir channels in insects (1) are critical for proper function of the insect nervous system, (2) represents an unexplored physiological pathway that is likely to shape the understanding of neuronal signaling, maintenance of membrane potentials, and maintenance of the ionic balance of insects, and (3) are capable of inducing acute toxicity to insects through neurological poisoning.

Non-Viral Generation of Neural Precursor-like Cells from Adult Human Fibroblasts

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Maucksch C

2012-01-01

Full Text Available Recent studies have reported direct reprogramming of human fibroblasts to mature neurons by the introduction of defined neural genes. This technology has potential use in the areas of neurological disease modeling and drug development. However, use of induced neurons for large-scale drug screening and cell-based replacement strategies is limited due to their inability to expand once reprogrammed. We propose it would be more desirable to induce expandable neural precursor cells directly from human fibroblasts. To date several pluripotent and neural transcription factors have been shown to be capable of converting mouse fibroblasts to neural stem/precursor-like cells when delivered by viral vectors. Here we extend these findings and demonstrate that transient ectopic insertion of the transcription factors SOX2 and PAX6 to adult human fibroblasts through use of non-viral plasmid transfection or protein transduction allows the generation of induced neural precursor (iNP colonies expressing a range of neural stem and pro-neural genes. Upon differentiation, iNP cells give rise to neurons exhibiting typical neuronal morphologies and expressing multiple neuronal markers including tyrosine hydroxylase and GAD65/67. Importantly, iNP-derived neurons demonstrate electrophysiological properties of functionally mature neurons with the capacity to generate action potentials. In addition, iNP cells are capable of differentiating into glial fibrillary acidic protein (GFAP-expressing astrocytes. This study represents a novel virus-free approach for direct reprogramming of human fibroblasts to a neural precursor fate.

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.)

Perlecan is required for FGF-2 signaling in the neural stem cell niche

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Aurelien Kerever

2014-03-01

Full Text Available In the adult subventricular zone (neurogenic niche, neural stem cells double-positive for two markers of subsets of neural stem cells in the adult central nervous system, glial fibrillary acidic protein and CD133, lie in proximity to fractones and to blood vessel basement membranes, which contain the heparan sulfate proteoglycan perlecan. Here, we demonstrate that perlecan deficiency reduces the number of both GFAP/CD133-positive neural stem cells in the subventricular zone and new neurons integrating into the olfactory bulb. We also show that FGF-2 treatment induces the expression of cyclin D2 through the activation of the Akt and Erk1/2 pathways and promotes neurosphere formation in vitro. However, in the absence of perlecan, FGF-2 fails to promote neurosphere formation. These results suggest that perlecan is a component of the neurogenic niche that regulates FGF-2 signaling and acts by promoting neural stem cell self-renewal and neurogenesis.

Fgf8-related secondary organizers exert different polarizing planar instructions along the mouse anterior neural tube.

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Crespo-Enriquez, Ivan; Partanen, Juha; Martinez, Salvador; Echevarria, Diego

2012-01-01

Early brain patterning depends on proper arrangement of positional information. This information is given by gradients of secreted signaling molecules (morphogens) detected by individual cells within the responding tissue, leading to specific fate decisions. Here we report that the morphogen FGF8 exerts initially a differential signal activity along the E9.5 mouse neural tube. We demonstrate that this polarizing activity codes by RAS-regulated ERK1/2 signaling and depends on the topographical location of the secondary organizers: the isthmic organizer (IsO) and the anterior neural ridge (anr) but not on zona limitans intrathalamica (zli). Our results suggest that Sprouty2, a negative modulator of RAS/ERK pathway, is important for regulating Fgf8 morphogenetic signal activity by controlling Fgf8-induced signaling pathways and positional information during early brain development.

Anatomical pathways involved in generating and sensing rhythmic whisker movements

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Laurens W.J. Bosman

2011-10-01

Full Text Available The rodent whisker system is widely used as a model system for investigating sensorimotor integration, neural mechanisms of complex cognitive tasks, neural development, and robotics. The whisker pathways to the barrel cortex have received considerable attention. However, many subcortical structures are paramount to the whisker system. They contribute to important processes, like filtering out salient features, integration with other senses and adaptation of the whisker system to the general behavioral state of the animal. We present here an overview of the brain regions and their connections involved in the whisker system. We do not only describe the anatomy and functional roles of the cerebral cortex, but also those of subcortical structures like the striatum, superior colliculus, cerebellum, pontomedullary reticular formation, zona incerta and anterior pretectal nucleus as well as those of level setting systems like the cholinergic, histaminergic, serotonergic and noradrenergic pathways. We conclude by discussing how these brain regions may affect each other and how they together may control the precise timing of whisker movements and coordinate whisker perception.

Quantitative Analysis of Human Pluripotency and Neural Specification by In-Depth (PhosphoProteomic Profiling

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Ilyas Singec

2016-09-01

Full Text Available Controlled differentiation of human embryonic stem cells (hESCs can be utilized for precise analysis of cell type identities during early development. We established a highly efficient neural induction strategy and an improved analytical platform, and determined proteomic and phosphoproteomic profiles of hESCs and their specified multipotent neural stem cell derivatives (hNSCs. This quantitative dataset (nearly 13,000 proteins and 60,000 phosphorylation sites provides unique molecular insights into pluripotency and neural lineage entry. Systems-level comparative analysis of proteins (e.g., transcription factors, epigenetic regulators, kinase families, phosphorylation sites, and numerous biological pathways allowed the identification of distinct signatures in pluripotent and multipotent cells. Furthermore, as predicted by the dataset, we functionally validated an autocrine/paracrine mechanism by demonstrating that the secreted protein midkine is a regulator of neural specification. This resource is freely available to the scientific community, including a searchable website, PluriProt.

Compositionality in Neural Control:An Interdisciplinary Study of Scribbling Movements in Primates

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Moshe eAbeles

2013-09-01

Full Text Available This article discusses the compositional structure of hand movements by analyzing and modeling neural and behavioral data obtained from experiments where a monkey (Macaca fascicularis performed scribbling movements induced by a search task. Using geometrically based approaches to movement segmentation, it is shown that the hand trajectories are composed of elementary segments that are primarily parabolic in shape. The segments could be categorized into a small number of classes on the basis of decreasing intra-class variance over the course of training. A separate classification of the neural data employing a hidden Markov model showed a coincidence of the neural states with the behavioral categories. An additional analysis of both types of data by a data mining method provided evidence that the neural activity patterns underlying the behavioral primitives were formed by sets of specific and precise spike patterns. A geometric description of the movement trajectories, together with precise neural timing data indicates a compositional variant of a realistic synfire chain model. This model reproduces the typical shapes and temporal properties of the trajectories; hence the structure and composition of the primitives may reflect meaningful behavior.

Hybrid discrete-time neural networks.

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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.

Neural crest stem cell population in craniomaxillofacial development and tissue repair

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M La Noce

2014-10-01

Full Text Available Neural crest cells, delaminating from the neural tube during migration, undergo an epithelial-mesenchymal transition and differentiate into several cell types strongly reinforcing the mesoderm of the craniofacial body area – giving rise to bone, cartilage and other tissues and cells of this human body area. Recent studies on craniomaxillofacial neural crest-derived cells have provided evidence for the tremendous plasticity of these cells. Actually, neural crest cells can respond and adapt to the environment in which they migrate and the cranial mesoderm plays an important role toward patterning the identity of the migrating neural crest cells. In our experience, neural crest-derived stem cells, such as dental pulp stem cells, can actively proliferate, repair bone and give rise to other tissues and cytotypes, including blood vessels, smooth muscle, adipocytes and melanocytes, highlighting that their use in tissue engineering is successful. In this review, we provide an overview of the main pathways involved in neural crest formation, delamination, migration and differentiation; and, in particular, we concentrate our attention on the translatability of the latest scientific progress. Here we try to suggest new ideas and strategies that are needed to fully develop the clinical use of these cells. This effort should involve both researchers/clinicians and improvements in good manufacturing practice procedures. It is important to address studies towards clinical application or take into consideration that studies must have an effective therapeutic prospect for humans. New approaches and ideas must be concentrated also toward stem cell recruitment and activation within the human body, overcoming the classical grafting.

Epidermal wound repair is regulated by the planar cell polarity signaling pathway.

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Caddy, Jacinta; Wilanowski, Tomasz; Darido, Charbel; Dworkin, Sebastian; Ting, Stephen B; Zhao, Quan; Rank, Gerhard; Auden, Alana; Srivastava, Seema; Papenfuss, Tony A; Murdoch, Jennifer N; Humbert, Patrick O; Parekh, Vishwas; Boulos, Nidal; Weber, Thomas; Zuo, Jian; Cunningham, John M; Jane, Stephen M

2010-07-20

The mammalian PCP pathway regulates diverse developmental processes requiring coordinated cellular movement, including neural tube closure and cochlear stereociliary orientation. Here, we show that epidermal wound repair is regulated by PCP signaling. Mice carrying mutant alleles of PCP genes Vangl2, Celsr1, PTK7, and Scrb1, and the transcription factor Grhl3, interact genetically, exhibiting failed wound healing, neural tube defects, and disordered cochlear polarity. Using phylogenetic analysis, ChIP, and gene expression in Grhl3(-)(/-) mice, we identified RhoGEF19, a homolog of a RhoA activator involved in PCP signaling in Xenopus, as a direct target of GRHL3. Knockdown of Grhl3 or RhoGEF19 in keratinocytes induced defects in actin polymerization, cellular polarity, and wound healing, and re-expression of RhoGEF19 rescued these defects in Grhl3-kd cells. These results define a role for Grhl3 in PCP signaling and broadly implicate this pathway in epidermal repair. (c) 2010 Elsevier Inc. All rights reserved.

Cracking the neural code, treating paralysis and the future of bioelectronic medicine.

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Bouton, C

2017-07-01

The human nervous system is a vast network carrying not only sensory and movement information, but also information to and from our organs, intimately linking it to our overall health. Scientists and engineers have been working for decades to tap into this network and 'crack the neural code' by decoding neural signals and learning how to 'speak' the language of the nervous system. Progress has been made in developing neural decoding methods to decipher brain activity and bioelectronic technologies to treat rheumatoid arthritis, paralysis, epilepsy and for diagnosing brain-related diseases such as Parkinson's and Alzheimer's disease. In a recent first-in-human study involving paralysis, a paralysed male study participant regained movement in his hand, years after his injury, through the use of a bioelectronic neural bypass. This work combined neural decoding and neurostimulation methods to translate and re-route signals around damaged neural pathways within the central nervous system. By extending these methods to decipher neural messages in the peripheral nervous system, status information from our bodily functions and specific organs could be gained. This, one day, could allow real-time diagnostics to be performed to give us a deeper insight into a patient's condition, or potentially even predict disease or allow early diagnosis. The future of bioelectronic medicine is extremely bright and is wide open as new diagnostic and treatment options are developed for patients around the world. © 2017 The Association for the Publication of the Journal of Internal Medicine.

Influence of neural adaptation on dynamics and equilibrium state of neural activities in a ring neural network

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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.

Use of neural networks in the analysis of complex systems

International Nuclear Information System (INIS)

Uhrig, R.E.

1992-01-01

The application of neural networks, alone or in conjunction with other advanced technologies (expert systems, fuzzy logic, and/or genetic algorithms) to some of the problems of complex engineering systems has the potential to enhance the safety reliability and operability of these systems. The work described here deals with complex systems or parts of such systems that can be isolated from the total system. Typically, the measured variables from the systems are analog variables that must be sampled and normalized to expected peak values before they are introduced into neural networks. Often data must be processed to put it into a form more acceptable to the neural network. The neural networks are usually simulated on modern high-speed computers that carry out the calculations serially. However, it is possible to implement neural networks using specially designed microchips where the network calculations are truly carried out in parallel, thereby providing virtually instantaneous outputs for each set of inputs. Specific applications described include: Diagnostics: State of the Plant; Hybrid System for Transient Identification; Detection of Change of Mode in Complex Systems; Sensor Validation; Plant-Wide Monitoring; Monitoring of Performance and Efficiency; and Analysis of Vibrations. Although the specific examples described deal with nuclear power plants or their subsystems, the techniques described can be applied to a wide variety of complex engineering systems

Behavioral and Physiological Neural Network Analyses: A Common Pathway toward Pattern Recognition and Prediction

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Ninness, Chris; Lauter, Judy L.; Coffee, Michael; Clary, Logan; Kelly, Elizabeth; Rumph, Marilyn; Rumph, Robin; Kyle, Betty; Ninness, Sharon K.

2012-01-01

Using 3 diversified datasets, we explored the pattern-recognition ability of the Self-Organizing Map (SOM) artificial neural network as applied to diversified nonlinear data distributions in the areas of behavioral and physiological research. Experiment 1 employed a dataset obtained from the UCI Machine Learning Repository. Data for this study…

Novel Hedgehog pathway targets against basal cell carcinoma

International Nuclear Information System (INIS)

Tang, Jean Y.; So, P.-L.; Epstein, Ervin H.

2007-01-01

The Hedgehog signaling pathway plays a key role in directing growth and patterning during embryonic development and is required in vertebrates for the normal development of many structures, including the neural tube, axial skeleton, skin, and hair. Aberrant activation of the Hedgehog (Hh) pathway in adult tissue is associated with the development of basal cell carcinoma (BCC), medulloblastoma, and a subset of pancreatic, gastrointestinal, and other cancers. This review will provide an overview of what is known about the mechanisms by which activation of Hedgehog signaling leads to the development of BCCs and will review two recent papers suggesting that agents that modulate sterol levels might influence the Hh pathway. Thus, sterols may be a new therapeutic target for the treatment of BCCs, and readily available agents such as statins (HMG-CoA reductase inhibitors) or vitamin D might be helpful in reducing BCC incidence

Fast and automatic activation of an abstract representation of money in the human ventral visual pathway.

Directory of Open Access Journals (Sweden)

Catherine Tallon-Baudry

Full Text Available Money, when used as an incentive, activates the same neural circuits as rewards associated with physiological needs. However, unlike physiological rewards, monetary stimuli are cultural artifacts: how are monetary stimuli identified in the first place? How and when does the brain identify a valid coin, i.e. a disc of metal that is, by social agreement, endowed with monetary properties? We took advantage of the changes in the Euro area in 2002 to compare neural responses to valid coins (Euros, Australian Dollars with neural responses to invalid coins that have lost all monetary properties (French Francs, Finnish Marks. We show in magneto-encephalographic recordings, that the ventral visual pathway automatically distinguishes between valid and invalid coins, within only ∼150 ms. This automatic categorization operates as well on coins subjects were familiar with as on unfamiliar coins. No difference between neural responses to scrambled controls could be detected. These results could suggest the existence of a generic, all-purpose neural representation of money that is independent of experience. This finding is reminiscent of a central assumption in economics, money fungibility, or the fact that a unit of money is substitutable to another. From a neural point of view, our findings may indicate that the ventral visual pathway, a system previously thought to analyze visual features such as shape or color and to be influenced by daily experience, could also able to use conceptual attributes such as monetary validity to categorize familiar as well as unfamiliar visual objects. The symbolic abilities of the posterior fusiform region suggested here could constitute an efficient neural substrate to deal with culturally defined symbols, independently of experience, which probably fostered money's cultural emergence and success.

Structural Covariance of the Prefrontal-Amygdala Pathways Associated with Heart Rate Variability.

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Wei, Luqing; Chen, Hong; Wu, Guo-Rong

2018-01-01

The neurovisceral integration model has shown a key role of the amygdala in neural circuits underlying heart rate variability (HRV) modulation, and suggested that reciprocal connections from amygdala to brain regions centered on the central autonomic network (CAN) are associated with HRV. To provide neuroanatomical evidence for these theoretical perspectives, the current study used covariance analysis of MRI-based gray matter volume (GMV) to map structural covariance network of the amygdala, and then determined whether the interregional structural correlations related to individual differences in HRV. The results showed that covariance patterns of the amygdala encompassed large portions of cortical (e.g., prefrontal, cingulate, and insula) and subcortical (e.g., striatum, hippocampus, and midbrain) regions, lending evidence from structural covariance analysis to the notion that the amygdala was a pivotal node in neural pathways for HRV modulation. Importantly, participants with higher resting HRV showed increased covariance of amygdala to dorsal medial prefrontal cortex and anterior cingulate cortex (dmPFC/dACC) extending into adjacent medial motor regions [i.e., pre-supplementary motor area (pre-SMA)/SMA], demonstrating structural covariance of the prefrontal-amygdala pathways implicated in HRV, and also implying that resting HRV may reflect the function of neural circuits underlying cognitive regulation of emotion as well as facilitation of adaptive behaviors to emotion. Our results, thus, provide anatomical substrates for the neurovisceral integration model that resting HRV may index an integrative neural network which effectively organizes emotional, cognitive, physiological and behavioral responses in the service of goal-directed behavior and adaptability.

Chondroitin sulfate proteoglycans regulate the growth, differentiation and migration of multipotent neural precursor cells through the integrin signaling pathway

Directory of Open Access Journals (Sweden)

Lü He-Zuo

2009-10-01

Full Text Available Abstract Background Neural precursor cells (NPCs are defined by their ability to proliferate, self-renew, and retain the potential to differentiate into neurons and glia. Deciphering the factors that regulate their behaviors will greatly aid in their use as potential therapeutic agents or targets. Chondroitin sulfate proteoglycans (CSPGs are prominent components of the extracellular matrix (ECM in the central nervous system (CNS and are assumed to play important roles in controlling neuronal differentiation and development. Results In the present study, we demonstrated that CSPGs were constitutively expressed on the NPCs isolated from the E16 rat embryonic brain. When chondroitinase ABC was used to abolish the function of endogenous CSPGs on NPCs, it induced a series of biological responses including the proliferation, differentiation and migration of NPCs, indicating that CSPGs may play a critical role in NPC development and differentiation. Finally, we provided evidence suggesting that integrin signaling pathway may be involved in the effects of CSPGs on NPCs. Conclusion The present study investigating the influence and mechanisms of CSPGs on the differentiation and migration of NPCs should help us to understand the basic biology of NPCs during CNS development and provide new insights into developing new strategies for the treatment of the neurological disorders in the CNS.

The artist emerges: visual art learning alters neural structure and function.

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Schlegel, Alexander; Alexander, Prescott; Fogelson, Sergey V; Li, Xueting; Lu, Zhengang; Kohler, Peter J; Riley, Enrico; Tse, Peter U; Meng, Ming

2015-01-15

How does the brain mediate visual artistic creativity? Here we studied behavioral and neural changes in drawing and painting students compared to students who did not study art. We investigated three aspects of cognition vital to many visual artists: creative cognition, perception, and perception-to-action. We found that the art students became more creative via the reorganization of prefrontal white matter but did not find any significant changes in perceptual ability or related neural activity in the art students relative to the control group. Moreover, the art students improved in their ability to sketch human figures from observation, and multivariate patterns of cortical and cerebellar activity evoked by this drawing task became increasingly separable between art and non-art students. Our findings suggest that the emergence of visual artistic skills is supported by plasticity in neural pathways that enable creative cognition and mediate perceptuomotor integration. Copyright © 2014 Elsevier Inc. All rights reserved.

[Algorithms of artificial neural networks--practical application in medical science].

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Stefaniak, Bogusław; Cholewiński, Witold; Tarkowska, Anna

2005-12-01

Artificial Neural Networks (ANN) may be a tool alternative and complementary to typical statistical analysis. However, in spite of many computer applications of various ANN algorithms ready for use, artificial intelligence is relatively rarely applied to data processing. This paper presents practical aspects of scientific application of ANN in medicine using widely available algorithms. Several main steps of analysis with ANN were discussed starting from material selection and dividing it into groups, to the quality assessment of obtained results at the end. The most frequent, typical reasons for errors as well as the comparison of ANN method to the modeling by regression analysis were also described.

Neural Control of the Lower Urinary Tract

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de Groat, William C.; Griffiths, Derek; Yoshimura, Naoki

2015-01-01

This article summarizes anatomical, neurophysiological, pharmacological, and brain imaging studies in humans and animals that have provided insights into the neural circuitry and neurotransmitter mechanisms controlling the lower urinary tract. The functions of the lower urinary tract to store and periodically eliminate urine are regulated by a complex neural control system in the brain, spinal cord, and peripheral autonomic ganglia that coordinates the activity of smooth and striated muscles of the bladder and urethral outlet. The neural control of micturition is organized as a hierarchical system in which spinal storage mechanisms are in turn regulated by circuitry in the rostral brain stem that initiates reflex voiding. Input from the forebrain triggers voluntary voiding by modulating the brain stem circuitry. Many neural circuits controlling the lower urinary tract exhibit switch-like patterns of activity that turn on and off in an all-or-none manner. The major component of the micturition switching circuit is a spinobulbospinal parasympathetic reflex pathway that has essential connections in the periaqueductal gray and pontine micturition center. A computer model of this circuit that mimics the switching functions of the bladder and urethra at the onset of micturition is described. Micturition occurs involuntarily in infants and young children until the age of 3 to 5 years, after which it is regulated voluntarily. Diseases or injuries of the nervous system in adults can cause the re-emergence of involuntary micturition, leading to urinary incontinence. Neuroplasticity underlying these developmental and pathological changes in voiding function is discussed. PMID:25589273

Neural Mechanisms of Interference Control and Time Discrimination in Attention-Deficit/Hyperactivity Disorder

Science.gov (United States)

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…

A novel application of artificial neural network for wind speed estimation

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Fang, Da; Wang, Jianzhou

2017-05-01

Providing accurate multi-steps wind speed estimation models has increasing significance, because of the important technical and economic impacts of wind speed on power grid security and environment benefits. In this study, the combined strategies for wind speed forecasting are proposed based on an intelligent data processing system using artificial neural network (ANN). Generalized regression neural network and Elman neural network are employed to form two hybrid models. The approach employs one of ANN to model the samples achieving data denoising and assimilation and apply the other to predict wind speed using the pre-processed samples. The proposed method is demonstrated in terms of the predicting improvements of the hybrid models compared with single ANN and the typical forecasting method. To give sufficient cases for the study, four observation sites with monthly average wind speed of four given years in Western China were used to test the models. Multiple evaluation methods demonstrated that the proposed method provides a promising alternative technique in monthly average wind speed estimation.

A central neural circuit for itch sensation.

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Mu, Di; Deng, Juan; Liu, Ke-Fei; Wu, Zhen-Yu; Shi, Yu-Feng; Guo, Wei-Min; Mao, Qun-Quan; Liu, Xing-Jun; Li, Hui; Sun, Yan-Gang

2017-08-18

Although itch sensation is an important protective mechanism for animals, chronic itch remains a challenging clinical problem. Itch processing has been studied extensively at the spinal level. However, how itch information is transmitted to the brain and what central circuits underlie the itch-induced scratching behavior remain largely unknown. We found that the spinoparabrachial pathway was activated during itch processing and that optogenetic suppression of this pathway impaired itch-induced scratching behaviors. Itch-mediating spinal neurons, which express the gastrin-releasing peptide receptor, are disynaptically connected to the parabrachial nucleus via glutamatergic spinal projection neurons. Blockade of synaptic output of glutamatergic neurons in the parabrachial nucleus suppressed pruritogen-induced scratching behavior. Thus, our studies reveal a central neural circuit that is critical for itch signal processing. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Fast Automatic Airport Detection in Remote Sensing Images Using Convolutional Neural Networks

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Fen Chen

2018-03-01

Full Text Available Fast and automatic detection of airports from remote sensing images is useful for many military and civilian applications. In this paper, a fast automatic detection method is proposed to detect airports from remote sensing images based on convolutional neural networks using the Faster R-CNN algorithm. This method first applies a convolutional neural network to generate candidate airport regions. Based on the features extracted from these proposals, it then uses another convolutional neural network to perform airport detection. By taking the typical elongated linear geometric shape of airports into consideration, some specific improvements to the method are proposed. These approaches successfully improve the quality of positive samples and achieve a better accuracy in the final detection results. Experimental results on an airport dataset, Landsat 8 images, and a Gaofen-1 satellite scene demonstrate the effectiveness and efficiency of the proposed method.

Neural Computations in a Dynamical System with Multiple Time Scales.

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Mi, Yuanyuan; Lin, Xiaohan; Wu, Si

2016-01-01

Neural systems display rich short-term dynamics at various levels, e.g., spike-frequency adaptation (SFA) at the single-neuron level, and short-term facilitation (STF) and depression (STD) at the synapse level. These dynamical features typically cover a broad range of time scales and exhibit large diversity in different brain regions. It remains unclear what is the computational benefit for the brain to have such variability in short-term dynamics. In this study, we propose that the brain can exploit such dynamical features to implement multiple seemingly contradictory computations in a single neural circuit. To demonstrate this idea, we use continuous attractor neural network (CANN) as a working model and include STF, SFA and STD with increasing time constants in its dynamics. Three computational tasks are considered, which are persistent activity, adaptation, and anticipative tracking. These tasks require conflicting neural mechanisms, and hence cannot be implemented by a single dynamical feature or any combination with similar time constants. However, with properly coordinated STF, SFA and STD, we show that the network is able to implement the three computational tasks concurrently. We hope this study will shed light on the understanding of how the brain orchestrates its rich dynamics at various levels to realize diverse cognitive functions.

Lukasiewicz-Topos Models of Neural Networks, Cell Genome and Interactome Nonlinear Dynamic Models

CERN Document Server

Baianu, I C

2004-01-01

A categorical and Lukasiewicz-Topos framework for Lukasiewicz Algebraic Logic models of nonlinear dynamics in complex functional systems such as neural networks, genomes and cell interactomes is proposed. Lukasiewicz Algebraic Logic models of genetic networks and signaling pathways in cells are formulated in terms of nonlinear dynamic systems with n-state components that allow for the generalization of previous logical models of both genetic activities and neural networks. An algebraic formulation of variable 'next-state functions' is extended to a Lukasiewicz Topos with an n-valued Lukasiewicz Algebraic Logic subobject classifier description that represents non-random and nonlinear network activities as well as their transformations in developmental processes and carcinogenesis.

Neural tube defects – disorders of neurulation and related embryonic processes

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Copp, Andrew J.; Greene, Nicholas D. E.

2014-01-01

Neural tube defects (NTDs) are severe congenital malformations affecting 1 in every 1000 pregnancies. ‘Open’ NTDs result from failure of primary neurulation as seen in anencephaly, myelomeningocele (open spina bifida) and craniorachischisis. Degeneration of the persistently open neural tube in utero leads to loss of neurological function below the lesion level. ‘Closed’ NTDs are skin-covered disorders of spinal cord structure, ranging from asymptomatic spina bifida occulta to severe spinal cord tethering, and usually traceable to disruption of secondary neurulation. ‘Herniation’ NTDs are those in which meninges, with or without brain or spinal cord tissue, become exteriorised through a pathological opening in the skull or vertebral column (e.g. encephalocele and meningocele). NTDs have multifactorial etiology, with genes and environmental factors interacting to determine individual risk of malformation. While over 200 mutant genes cause open NTDs in mice, much less is known about the genetic causation of human NTDs. Recent evidence has implicated genes of the planar cell polarity signalling pathway in a proportion of cases. The embryonic development of NTDs is complex, with diverse cellular and molecular mechanisms operating at different levels of the body axis. Molecular regulatory events include the BMP and Sonic hedgehog pathways which have been implicated in control of neural plate bending. Primary prevention of NTDs has been implemented clinically following the demonstration that folic acid, when taken as a peri-conceptional supplement, can prevent many cases. Not all NTDs respond to folic acid, however, and adjunct therapies are required for prevention of this folic acid-resistant category. PMID:24009034

A case of typical atrioventricular nodal (AVN) reentrant tachycardia confined to the compact AV node, showing a variety of rare electrophysiological findings, including eccentric AVN echoes

OpenAIRE

Tanaka, Kazushi; Shiotani, Shinji; Fukuda, Keisuke; Fujihara, Masahiko; Higashimori, Akihiro; Morioka, Nobuyuki; Yokoi, Yoshiaki; Fujimura, Osamu

2014-01-01

Herein, we report the case of a 49-year-old woman with typical atrioventricular nodal (AVN) reentrant tachycardia, confined to the compact atrioventricular node, showing numerous rare electrophysiological findings such as unique AVN reentrant echoes, double ventricular responses, latent retrograde dual AVN pathways, antegrade triple AVN pathways, and longitudinal dissociation within the lower final common pathway.

A case of typical atrioventricular nodal (AVN reentrant tachycardia confined to the compact AV node, showing a variety of rare electrophysiological findings, including eccentric AVN echoes

Directory of Open Access Journals (Sweden)

Kazushi Tanaka, M.D., Ph.D.

2014-12-01

Full Text Available Herein, we report the case of a 49-year-old woman with typical atrioventricular nodal (AVN reentrant tachycardia, confined to the compact atrioventricular node, showing numerous rare electrophysiological findings such as unique AVN reentrant echoes, double ventricular responses, latent retrograde dual AVN pathways, antegrade triple AVN pathways, and longitudinal dissociation within the lower final common pathway.

Decoding Visual Location From Neural Patterns in the Auditory Cortex of the Congenitally Deaf

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Almeida, Jorge; He, Dongjun; Chen, Quanjing; Mahon, Bradford Z.; Zhang, Fan; Gonçalves, Óscar F.; Fang, Fang; Bi, Yanchao

2016-01-01

Sensory cortices of individuals who are congenitally deprived of a sense can exhibit considerable plasticity and be recruited to process information from the senses that remain intact. Here, we explored whether the auditory cortex of congenitally deaf individuals represents visual field location of a stimulus—a dimension that is represented in early visual areas. We used functional MRI to measure neural activity in auditory and visual cortices of congenitally deaf and hearing humans while they observed stimuli typically used for mapping visual field preferences in visual cortex. We found that the location of a visual stimulus can be successfully decoded from the patterns of neural activity in auditory cortex of congenitally deaf but not hearing individuals. This is particularly true for locations within the horizontal plane and within peripheral vision. These data show that the representations stored within neuroplastically changed auditory cortex can align with dimensions that are typically represented in visual cortex. PMID:26423461

Qualitative analysis of the maintenance politics of the systems of a typical PWR by artificial neural networks; Analise qualitativa da politica de manutencoes dos sistemas de um PWR tipico por redes neurais artificiais

Energy Technology Data Exchange (ETDEWEB)

Lourenco, Victor Hugo Moreno

2010-02-15

Proceedings and techniques in order to maximize the reliability and the availability of industrial plants have been used along the last decades by specialists and professionals of maintenance. However, the modem industrial systems' sizing, and the increasing complexity and interdependence among its components have become this activity's planning a more and more difficult task. Considering this scenario, the objective of the present work is to provide a computational tool which is able to help about the taking decision's task, and about planning policies of maintenance practiced in thermonuclear plants. The tool developed is based on the artificial neural networks (ANN) for the recognition of standards and establishment of correlations among events occurred in the components of pressurized water reactor (PWR) typical systems. The ANN work as miners of database of failure events, and are able to identify connections and to establish imperceptible inferences even for the most experienced specialists in maintenance of nuclear systems. The results were attained from realistic data and are confronted against the maintenance's classic policies which are practiced nowadays on PWR thermonuclear plants. These results show the solidity of the technique in valuing and predicting failures in a real power plant, and is able to be used as a tool for supporting decisions about planning maintenance policies on a typical PWR. (author)

Prolonged Expansion Induces Spontaneous Neural Progenitor Differentiation from Human Gingiva-Derived Mesenchymal Stem Cells.

Science.gov (United States)

Rajan, Thangavelu Soundara; Scionti, Domenico; Diomede, Francesca; Piattelli, Adriano; Bramanti, Placido; Mazzon, Emanuela; Trubiani, Oriana

2017-12-01

Neural crest-derived mesenchymal stem cells (MSCs) obtained from dental tissues received considerable interest in regenerative medicine, particularly in nerve regeneration owing to their embryonic origin and ease of harvest. Proliferation efficacy and differentiation capacity into diverse cell lineages propose dental MSCs as an in vitro tool for disease modeling. In this study, we investigated the spontaneous differentiation efficiency of dental MSCs obtained from human gingiva tissue (hGMSCs) into neural progenitor cells after extended passaging. At passage 41, the morphology of hGMSCs changed from typical fibroblast-like shape into sphere-shaped cells with extending processes. Next-generation transcriptomics sequencing showed increased expression of neural progenitor markers such as NES, MEIS2, and MEST. In addition, de novo expression of neural precursor genes, such as NRN1, PHOX2B, VANGL2, and NTRK3, was noticed in passage 41. Immunocytochemistry results showed suppression of neurogenesis repressors TP53 and p21, whereas Western blot results revealed the expression of neurotrophic factors BDNF and NT3 at passage 41. Our results showed the spontaneous efficacy of hGMSCs to differentiate into neural precursor cells over prolonged passages and that these cells may assist in producing novel in vitro disease models that are associated with neural development.

The Typicality Ranking Task: A New Method to Derive Typicality Judgments from Children

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Ameel, Eef; Storms, Gert

2016-01-01

An alternative method for deriving typicality judgments, applicable in young children that are not familiar with numerical values yet, is introduced, allowing researchers to study gradedness at younger ages in concept development. Contrary to the long tradition of using rating-based procedures to derive typicality judgments, we propose a method that is based on typicality ranking rather than rating, in which items are gradually sorted according to their typicality, and that requires a minimum of linguistic knowledge. The validity of the method is investigated and the method is compared to the traditional typicality rating measurement in a large empirical study with eight different semantic concepts. The results show that the typicality ranking task can be used to assess children’s category knowledge and to evaluate how this knowledge evolves over time. Contrary to earlier held assumptions in studies on typicality in young children, our results also show that preference is not so much a confounding variable to be avoided, but that both variables are often significantly correlated in older children and even in adults. PMID:27322371

Evolvable synthetic neural system

Science.gov (United States)

Curtis, Steven A. (Inventor)

2009-01-01

An evolvable synthetic neural system includes an evolvable neural interface operably coupled to at least one neural basis function. Each neural basis function includes an evolvable neural interface operably coupled to a heuristic neural system to perform high-level functions and an autonomic neural system to perform low-level functions. In some embodiments, the evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy.

An integrative neural model of social perception, action observation, and theory of mind

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Yang, Daniel Y.-J.; Rosenblau, Gabriela; Keifer, Cara; Pelphrey, Kevin A.

2016-01-01

In the field of social neuroscience, major branches of research have been instrumental in describing independent components of typical and aberrant social information processing, but the field as a whole lacks a comprehensive model that integrates different branches. We review existing research related to the neural basis of three key neural systems underlying social information processing: social perception, action observation, and theory of mind. We propose an integrative model that unites these three processes and highlights the posterior superior temporal sulcus (pSTS), which plays a central role in all three systems. Furthermore, we integrate these neural systems with the dual system account of implicit and explicit social information processing. Large-scale meta-analyses based on Neurosynth confirmed that the pSTS is at the intersection of the three neural systems. Resting-state functional connectivity analysis with 1000 subjects confirmed that the pSTS is connected to all other regions in these systems. The findings presented in this review are specifically relevant for psychiatric research especially disorders characterized by social deficits such as autism spectrum disorder. PMID:25660957

Aberrant signaling pathways in medulloblastomas: a stem cell connection

Directory of Open Access Journals (Sweden)

Carolina Oliveira Rodini

2010-12-01

Full Text Available Medulloblastoma is a highly malignant primary tumor of the central nervous system. It represents the most frequent type of solid tumor and the leading cause of death related to cancer in early childhood. Current treatment includes surgery, chemotherapy and radiotherapy which may lead to severe cognitive impairment and secondary brain tumors. New perspectives for therapeutic development have emerged with the identification of stem-like cells displaying high tumorigenic potential and increased radio- and chemo-resistance in gliomas. Under the cancer stem cell hypothesis, transformation of neural stem cells and/or granular neuron progenitors of the cerebellum are though to be involved in medulloblastoma development. Dissecting the genetic and molecular alterations associated with this process should significantly impact both basic and applied cancer research. Based on cumulative evidences in the fields of genetics and molecular biology of medulloblastomas, we discuss the possible involvement of developmental signaling pathways as critical biochemical switches determining normal neurogenesis or tumorigenesis. From the clinical viewpoint, modulation of signaling pathways such as TGFβ, regulating neural stem cell proliferation and tumor development, might be attempted as an alternative strategy for future drug development aiming at more efficient therapies and improved clinical outcome of patients with pediatric brain cancers.

Symmetries of a generic utricular projection: neural connectivity and the distribution of utricular information.

Science.gov (United States)

Chartrand, Thomas; McCollum, Gin; Hanes, Douglas A; Boyle, Richard D

2016-02-01

Sensory contribution to perception and action depends on both sensory receptors and the organization of pathways (or projections) reaching the central nervous system. Unlike the semicircular canals that are divided into three discrete sensitivity directions, the utricle has a relatively complicated anatomical structure, including sensitivity directions over essentially 360° of a curved, two-dimensional disk. The utricle is not flat, and we do not assume it to be. Directional sensitivity of individual utricular afferents decreases in a cosine-like fashion from peak excitation for movement in one direction to a null or near null response for a movement in an orthogonal direction. Directional sensitivity varies slowly between neighboring cells except within the striolar region that separates the medial from the lateral zone, where the directional selectivity abruptly reverses along the reversal line. Utricular primary afferent pathways reach the vestibular nuclei and cerebellum and, in many cases, converge on target cells with semicircular canal primary afferents and afference from other sources. Mathematically, some canal pathways are known to be characterized by symmetry groups related to physical space. These groups structure rotational information and movement. They divide the target neural center into distinct populations according to the innervation patterns they receive. Like canal pathways, utricular pathways combine symmetries from the utricle with those from target neural centers. This study presents a generic set of transformations drawn from the known structure of the utricle and therefore likely to be found in utricular pathways, but not exhaustive of utricular pathway symmetries. This generic set of transformations forms a 32-element group that is a semi-direct product of two simple abelian groups. Subgroups of the group include order-four elements corresponding to discrete rotations. Evaluation of subgroups allows us to functionally identify the

Autism as an adaptive common variant pathway for human brain development.

Science.gov (United States)

Johnson, Mark H

2017-06-01

While research on focal perinatal lesions has provided evidence for recovery of function, much less is known about processes of brain adaptation resulting from mild but widespread disturbances to neural processing over the early years (such as alterations in synaptic efficiency). Rather than being viewed as a direct behavioral consequence of life-long neural dysfunction, I propose that autism is best viewed as the end result of engaging adaptive processes during a sensitive period. From this perspective, autism is not appropriately described as a disorder of neurodevelopment, but rather as an adaptive common variant pathway of human functional brain development. Copyright © 2017 The Author. Published by Elsevier Ltd.. All rights reserved.

Age-related difference in the effective neural connectivity associated with probabilistic category learning

International Nuclear Information System (INIS)

Yoon, Eun Jin; Cho, Sang Soo; Kim, Hee Jung; Bang, Seong Ae; Park, Hyun Soo; Kim, Yu Kyeong; Kim, Sang Eun

2007-01-01

Although it is well known that explicit memory is affected by the deleterious changes in brain with aging, but effect of aging in implicit memory such as probabilistic category learning (PCL) is not clear. To identify the effect of aging on the neural interaction for successful PCL, we investigated the neural substrates of PCL and the age-related changes of the neural network between these brain regions. 23 young (age, 252 y; 11 males) and 14 elderly (673 y; 7 males) healthy subjects underwent FDG PET during a resting state and 150-trial weather prediction (WP) task. Correlations between the WP hit rates and regional glucose metabolism were assessed using SPM2 (P diff (37) = 142.47, P<0.005), Systematic comparisons of each path revealed that frontal crosscallosal and the frontal to parahippocampal connection were most responsible for the model differences (P<0.05). For the successful PCL, the elderly recruits the basal ganglia implicit memory system but MTL recruitment differs from the young. The inadequate MTL correlation pattern in the elderly is may be caused by the changes of the neural pathway related with explicit memory. These neural changes can explain the decreased performance of PCL in elderly subjects

Neural circuitry and immunity

Science.gov (United States)

Pavlov, Valentin A.; Tracey, Kevin J.

2015-01-01

Research during the last decade has significantly advanced our understanding of the molecular mechanisms at the interface between the nervous system and the immune system. Insight into bidirectional neuroimmune communication has characterized the nervous system as an important partner of the immune system in the regulation of inflammation. Neuronal pathways, including the vagus nerve-based inflammatory reflex are physiological regulators of immune function and inflammation. In parallel, neuronal function is altered in conditions characterized by immune dysregulation and inflammation. Here, we review these regulatory mechanisms and describe the neural circuitry modulating immunity. Understanding these mechanisms reveals possibilities to use targeted neuromodulation as a therapeutic approach for inflammatory and autoimmune disorders. These findings and current clinical exploration of neuromodulation in the treatment of inflammatory diseases defines the emerging field of Bioelectronic Medicine. PMID:26512000

Review On Applications Of Neural Network To Computer Vision

Science.gov (United States)

Li, Wei; Nasrabadi, Nasser M.

1989-03-01

Neural network models have many potential applications to computer vision due to their parallel structures, learnability, implicit representation of domain knowledge, fault tolerance, and ability of handling statistical data. This paper demonstrates the basic principles, typical models and their applications in this field. Variety of neural models, such as associative memory, multilayer back-propagation perceptron, self-stabilized adaptive resonance network, hierarchical structured neocognitron, high order correlator, network with gating control and other models, can be applied to visual signal recognition, reinforcement, recall, stereo vision, motion, object tracking and other vision processes. Most of the algorithms have been simulated on com-puters. Some have been implemented with special hardware. Some systems use features, such as edges and profiles, of images as the data form for input. Other systems use raw data as input signals to the networks. We will present some novel ideas contained in these approaches and provide a comparison of these methods. Some unsolved problems are mentioned, such as extracting the intrinsic properties of the input information, integrating those low level functions to a high-level cognitive system, achieving invariances and other problems. Perspectives of applications of some human vision models and neural network models are analyzed.

A novel method for extraction of neural response from single channel cochlear implant auditory evoked potentials.

Science.gov (United States)

Sinkiewicz, Daniel; Friesen, Lendra; Ghoraani, Behnaz

2017-02-01

Cortical auditory evoked potentials (CAEP) are used to evaluate cochlear implant (CI) patient auditory pathways, but the CI device produces an electrical artifact, which obscures the relevant information in the neural response. Currently there are multiple methods, which attempt to recover the neural response from the contaminated CAEP, but there is no gold standard, which can quantitatively confirm the effectiveness of these methods. To address this crucial shortcoming, we develop a wavelet-based method to quantify the amount of artifact energy in the neural response. In addition, a novel technique for extracting the neural response from single channel CAEPs is proposed. The new method uses matching pursuit (MP) based feature extraction to represent the contaminated CAEP in a feature space, and support vector machines (SVM) to classify the components as normal hearing (NH) or artifact. The NH components are combined to recover the neural response without artifact energy, as verified using the evaluation tool. Although it needs some further evaluation, this approach is a promising method of electrical artifact removal from CAEPs. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

What is typical is good: The influence of face typicality on perceived trustworthiness

NARCIS (Netherlands)

Sofer, C.; Dotsch, R.; Wigboldus, D.H.J.; Todorov, A.T.

2015-01-01

The role of face typicality in face recognition is well established, but it is unclear whether face typicality is important for face evaluation. Prior studies have focused mainly on typicality's influence on attractiveness, although recent studies have cast doubt on its importance for attractiveness

Effect of electrical stimulation on neural regeneration via the p38-RhoA and ERK1/2-Bcl-2 pathways in spinal cord-injured rats.

Science.gov (United States)

Joo, Min Cheol; Jang, Chul Hwan; Park, Jong Tae; Choi, Seung Won; Ro, Seungil; Kim, Min Seob; Lee, Moon Young

2018-02-01

Although electrical stimulation is therapeutically applied for neural regeneration in patients, it remains unclear how electrical stimulation exerts its effects at the molecular level on spinal cord injury (SCI). To identify the signaling pathway involved in electrical stimulation improving the function of injured spinal cord, 21 female Sprague-Dawley rats were randomly assigned to three groups: control (no surgical intervention, n = 6), SCI (SCI only, n = 5), and electrical simulation (ES; SCI induction followed by ES treatment, n = 10). A complete spinal cord transection was performed at the 10 th thoracic level. Electrical stimulation of the injured spinal cord region was applied for 4 hours per day for 7 days. On days 2 and 7 post SCI, the Touch-Test Sensory Evaluators and the Basso-Beattie-Bresnahan locomotor scale were used to evaluate rat sensory and motor function. Somatosensory-evoked potentials of the tibial nerve of a hind paw of the rat were measured to evaluate the electrophysiological function of injured spinal cord. Western blot analysis was performed to measure p38-RhoA and ERK1/2-Bcl-2 pathways related protein levels in the injured spinal cord. Rat sensory and motor functions were similar between SCI and ES groups. Compared with the SCI group, in the ES group, the latencies of the somatosensory-evoked potential of the tibial nerve of rats were significantly shortened, the amplitudes were significantly increased, RhoA protein level was significantly decreased, protein gene product 9.5 expression, ERK1/2, p38, and Bcl-2 protein levels in the spinal cord were significantly increased. These data suggest that ES can promote the recovery of electrophysiological function of the injured spinal cord through regulating p38-RhoA and ERK1/2-Bcl-2 pathway-related protein levels in the injured spinal cord.

Effect of electrical stimulation on neural regeneration via the p38-RhoA and ERK1/2-Bcl-2 pathways in spinal cord-injured rats

Science.gov (United States)

Joo, Min Cheol; Jang, Chul Hwan; Park, Jong Tae; Choi, Seung Won; Ro, Seungil; Kim, Min Seob; Lee, Moon Young

2018-01-01

Although electrical stimulation is therapeutically applied for neural regeneration in patients, it remains unclear how electrical stimulation exerts its effects at the molecular level on spinal cord injury (SCI). To identify the signaling pathway involved in electrical stimulation improving the function of injured spinal cord, 21 female Sprague-Dawley rats were randomly assigned to three groups: control (no surgical intervention, n = 6), SCI (SCI only, n = 5), and electrical simulation (ES; SCI induction followed by ES treatment, n = 10). A complete spinal cord transection was performed at the 10th thoracic level. Electrical stimulation of the injured spinal cord region was applied for 4 hours per day for 7 days. On days 2 and 7 post SCI, the Touch-Test Sensory Evaluators and the Basso-Beattie-Bresnahan locomotor scale were used to evaluate rat sensory and motor function. Somatosensory-evoked potentials of the tibial nerve of a hind paw of the rat were measured to evaluate the electrophysiological function of injured spinal cord. Western blot analysis was performed to measure p38-RhoA and ERK1/2-Bcl-2 pathways related protein levels in the injured spinal cord. Rat sensory and motor functions were similar between SCI and ES groups. Compared with the SCI group, in the ES group, the latencies of the somatosensory-evoked potential of the tibial nerve of rats were significantly shortened, the amplitudes were significantly increased, RhoA protein level was significantly decreased, protein gene product 9.5 expression, ERK1/2, p38, and Bcl-2 protein levels in the spinal cord were significantly increased. These data suggest that ES can promote the recovery of electrophysiological function of the injured spinal cord through regulating p38-RhoA and ERK1/2-Bcl-2 pathway-related protein levels in the injured spinal cord. PMID:29557386

White matter pathways in persistent developmental stuttering: Lessons from tractography.

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Kronfeld-Duenias, Vered; Civier, Oren; Amir, Ofer; Ezrati-Vinacour, Ruth; Ben-Shachar, Michal

2018-03-01

Fluent speech production relies on the coordinated processing of multiple brain regions. This highlights the role of neural pathways that connect distinct brain regions in producing fluent speech. Here, we aim to investigate the role of the white matter pathways in persistent developmental stuttering (PDS), where speech fluency is disrupted. We use diffusion weighted imaging and tractography to compare the white matter properties between adults who do and do not stutter. We compare the diffusion properties along 18 major cerebral white matter pathways. We complement the analysis with an overview of the methodology and a roadmap of the pathways implicated in PDS according to the existing literature. We report differences in the microstructural properties of the anterior callosum, the right inferior longitudinal fasciculus and the right cingulum in people who stutter compared with fluent controls. Persistent developmental stuttering is consistently associated with differences in bilateral distributed networks. We review evidence showing that PDS involves differences in bilateral dorsal fronto-temporal and fronto-parietal pathways, in callosal pathways, in several motor pathways and in basal ganglia connections. This entails an important role for long range white matter pathways in this disorder. Using a wide-lens analysis, we demonstrate differences in additional, right hemispheric pathways, which go beyond the replicable findings in the literature. This suggests that the affected circuits may extend beyond the known language and motor pathways. Copyright © 2017 Elsevier Inc. All rights reserved.

Neural Tuning to Low-Level Features of Speech throughout the Perisylvian Cortex.

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Berezutskaya, Julia; Freudenburg, Zachary V; Güçlü, Umut; van Gerven, Marcel A J; Ramsey, Nick F

2017-08-16

Despite a large body of research, we continue to lack a detailed account of how auditory processing of continuous speech unfolds in the human brain. Previous research showed the propagation of low-level acoustic features of speech from posterior superior temporal gyrus toward anterior superior temporal gyrus in the human brain (Hullett et al., 2016). In this study, we investigate what happens to these neural representations past the superior temporal gyrus and how they engage higher-level language processing areas such as inferior frontal gyrus. We used low-level sound features to model neural responses to speech outside of the primary auditory cortex. Two complementary imaging techniques were used with human participants (both males and females): electrocorticography (ECoG) and fMRI. Both imaging techniques showed tuning of the perisylvian cortex to low-level speech features. With ECoG, we found evidence of propagation of the temporal features of speech sounds along the ventral pathway of language processing in the brain toward inferior frontal gyrus. Increasingly coarse temporal features of speech spreading from posterior superior temporal cortex toward inferior frontal gyrus were associated with linguistic features such as voice onset time, duration of the formant transitions, and phoneme, syllable, and word boundaries. The present findings provide the groundwork for a comprehensive bottom-up account of speech comprehension in the human brain. SIGNIFICANCE STATEMENT We know that, during natural speech comprehension, a broad network of perisylvian cortical regions is involved in sound and language processing. Here, we investigated the tuning to low-level sound features within these regions using neural responses to a short feature film. We also looked at whether the tuning organization along these brain regions showed any parallel to the hierarchy of language structures in continuous speech. Our results show that low-level speech features propagate throughout the

Similar patterns of neural activity predict memory function during encoding and retrieval.

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Kragel, James E; Ezzyat, Youssef; Sperling, Michael R; Gorniak, Richard; Worrell, Gregory A; Berry, Brent M; Inman, Cory; Lin, Jui-Jui; Davis, Kathryn A; Das, Sandhitsu R; Stein, Joel M; Jobst, Barbara C; Zaghloul, Kareem A; Sheth, Sameer A; Rizzuto, Daniel S; Kahana, Michael J

2017-07-15

Neural networks that span the medial temporal lobe (MTL), prefrontal cortex, and posterior cortical regions are essential to episodic memory function in humans. Encoding and retrieval are supported by the engagement of both distinct neural pathways across the cortex and common structures within the medial temporal lobes. However, the degree to which memory performance can be determined by neural processing that is common to encoding and retrieval remains to be determined. To identify neural signatures of successful memory function, we administered a delayed free-recall task to 187 neurosurgical patients implanted with subdural or intraparenchymal depth electrodes. We developed multivariate classifiers to identify patterns of spectral power across the brain that independently predicted successful episodic encoding and retrieval. During encoding and retrieval, patterns of increased high frequency activity in prefrontal, MTL, and inferior parietal cortices, accompanied by widespread decreases in low frequency power across the brain predicted successful memory function. Using a cross-decoding approach, we demonstrate the ability to predict memory function across distinct phases of the free-recall task. Furthermore, we demonstrate that classifiers that combine information from both encoding and retrieval states can outperform task-independent models. These findings suggest that the engagement of a core memory network during either encoding or retrieval shapes the ability to remember the past, despite distinct neural interactions that facilitate encoding and retrieval. Copyright © 2017 Elsevier Inc. All rights reserved.

Assessing Basal and Acute Autophagic Responses in the Adult Drosophila Nervous System: The Impact of Gender, Genetics and Diet on Endogenous Pathway Profiles.

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Eric P Ratliff

Full Text Available The autophagy pathway is critical for the long-term homeostasis of cells and adult organisms and is often activated during periods of stress. Reduced pathway efficacy plays a central role in several progressive neurological disorders that are associated with the accumulation of cytotoxic peptides and protein aggregates. Previous studies have shown that genetic and transgenic alterations to the autophagy pathway impacts longevity and neural aggregate profiles of adult Drosophila. In this study, we have identified methods to measure the acute in vivo induction of the autophagy pathway in the adult fly CNS. Our findings indicate that the genotype, age, and gender of adult flies can influence pathway responses. Further, we demonstrate that middle-aged male flies exposed to intermittent fasting (IF had improved neuronal autophagic profiles. IF-treated flies also had lower neural aggregate profiles, maintained more youthful behaviors and longer lifespans, when compared to ad libitum controls. In summary, we present methodology to detect dynamic in vivo changes that occur to the autophagic profiles in the adult Drosophila CNS and that a novel IF-treatment protocol improves pathway response in the aging nervous system.

Intranasal oxytocin enhances neural processing of monetary reward and loss in post-traumatic stress disorder and traumatized controls.

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Nawijn, Laura; van Zuiden, Mirjam; Koch, Saskia B J; Frijling, Jessie L; Veltman, Dick J; Olff, Miranda

2016-04-01

Anhedonia is a significant clinical problem in post-traumatic stress disorder (PTSD). PTSD patients show reduced motivational approach behavior, which may underlie anhedonic symptoms. Oxytocin administration is known to increase reward sensitivity and approach behavior. We therefore investigated whether oxytocin administration affected neural responses during motivational processing in PTSD patients and trauma-exposed controls. 35 police officers with PTSD (21 males) and 37 trauma-exposed police officers without PTSD (19 males) were included in a within-subjects, randomized, placebo-controlled fMRI study. Neural responses during anticipation of monetary reward and loss were investigated with a monetary incentive delay task (MID) after placebo and oxytocin (40 IU) administration. Oxytocin increased neural responses during reward and loss anticipation in PTSD patients and controls in the striatum, dorsal anterior cingulate cortex and insula, key regions in the reward pathway. Although PTSD patients did not differ from controls in motivational processing under placebo, anhedonia severity in PTSD patients was negatively related to reward responsiveness in the ventral striatum. Furthermore, oxytocin effects on reward processing in the ventral striatum were positively associated with anhedonia. Oxytocin administration increased reward pathway sensitivity during reward and loss anticipation in PTSD patients and trauma-exposed controls. Thus, oxytocin administration may increase motivation for goal-directed approach behavior in PTSD patients and controls, providing evidence for a neurobiological pathway through which oxytocin could potentially increase motivation and reward sensitivity in PTSD patients. Copyright © 2016 Elsevier Ltd. All rights reserved.

Computer simulations of neural mechanisms explaining upper and lower limb excitatory neural coupling

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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

Social behaviour shapes hypothalamic neural ensemble representations of conspecific sex

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Remedios, Ryan; Kennedy, Ann; Zelikowsky, Moriel; Grewe, Benjamin F.; Schnitzer, Mark J.; Anderson, David J.

2017-10-01

All animals possess a repertoire of innate (or instinctive) behaviours, which can be performed without training. Whether such behaviours are mediated by anatomically distinct and/or genetically specified neural pathways remains unknown. Here we report that neural representations within the mouse hypothalamus, that underlie innate social behaviours, are shaped by social experience. Oestrogen receptor 1-expressing (Esr1+) neurons in the ventrolateral subdivision of the ventromedial hypothalamus (VMHvl) control mating and fighting in rodents. We used microendoscopy to image Esr1+ neuronal activity in the VMHvl of male mice engaged in these social behaviours. In sexually and socially experienced adult males, divergent and characteristic neural ensembles represented male versus female conspecifics. However, in inexperienced adult males, male and female intruders activated overlapping neuronal populations. Sex-specific neuronal ensembles gradually separated as the mice acquired social and sexual experience. In mice permitted to investigate but not to mount or attack conspecifics, ensemble divergence did not occur. However, 30 minutes of sexual experience with a female was sufficient to promote the separation of male and female ensembles and to induce an attack response 24 h later. These observations uncover an unexpected social experience-dependent component to the formation of hypothalamic neural assemblies controlling innate social behaviours. More generally, they reveal plasticity and dynamic coding in an evolutionarily ancient deep subcortical structure that is traditionally viewed as a ‘hard-wired’ system.

Brain-Derived Neurotrophic Factor Increases Synaptic Protein Levels via the MAPK/Erk Signaling Pathway and Nrf2/Trx Axis Following the Transplantation of Neural Stem Cells in a Rat Model of Traumatic Brain Injury.

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Chen, Tao; Wu, Yu; Wang, Yuzi; Zhu, Jigao; Chu, Haiying; Kong, Li; Yin, Liangwei; Ma, Haiying

2017-11-01

Brain-derived neurotrophic factor (BDNF) plays an important role in promoting the growth, differentiation, survival and synaptic stability of neurons. Presently, the transplantation of neural stem cells (NSCs) is known to induce neural repair to some extent after injury or disease. In this study, to investigate whether NSCs genetically modified to encode the BDNF gene (BDNF/NSCs) would further enhance synaptogenesis, BDNF/NSCs or naive NSCs were directly engrafted into lesions in a rat model of traumatic brain injury (TBI). Immunohistochemistry, western blotting and RT-PCR were performed to detect synaptic proteins, BDNF-TrkB and its downstream signaling pathways, at 1, 2, 3 or 4 weeks after transplantation. Our results showed that BDNF significantly increased the expression levels of the TrkB receptor gene and the phosphorylation of the TrkB protein in the lesions. The expression levels of Ras, phosphorylated Erk1/2 and postsynaptic density protein-95 were elevated in the BDNF/NSCs-transplanted groups compared with those in the NSCs-transplanted groups throughout the experimental period. Moreover, the nuclear factor (erythroid-derived 2)-like 2/Thioredoxin (Nrf2/Trx) axis, which is a specific therapeutic target for the treatment of injury or cell death, was upregulated by BDNF overexpression. Therefore, we determined that the increased synaptic proteins level implicated in synaptogenesis might be associated with the activation of the MAPK/Erk1/2 signaling pathway and the upregulation of the antioxidant agent Trx modified by BDNF-TrkB following the BDNF/NSCs transplantation after TBI.

Synergic Functions of miRNAs Determine Neuronal Fate of Adult Neural Stem Cells

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Meritxell Pons-Espinal

2017-04-01

Full Text Available Summary: Adult neurogenesis requires the precise control of neuronal versus astrocyte lineage determination in neural stem cells. While microRNAs (miRNAs are critically involved in this step during development, their actions in adult hippocampal neural stem cells (aNSCs has been unclear. As entry point to address that question we chose DICER, an endoribonuclease essential for miRNA biogenesis and other RNAi-related processes. By specific ablation of Dicer in aNSCs in vivo and in vitro, we demonstrate that miRNAs are required for the generation of new neurons, but not astrocytes, in the adult murine hippocampus. Moreover, we identify 11 miRNAs, of which 9 have not been previously characterized in neurogenesis, that determine neurogenic lineage fate choice of aNSCs at the expense of astrogliogenesis. Finally, we propose that the 11 miRNAs sustain adult hippocampal neurogenesis through synergistic modulation of 26 putative targets from different pathways. : In this article, the authors demonstrate that Dicer-dependent miRNAs are required for the generation of new neurons, but not astrocytes, in the adult hippocampus in vivo and in vitro. The authors identify a new set of 11 miRNAs that synergistically converge on multiple targets in different pathways to sustain neurogenic lineage fate commitment in aNSCs. Keywords: mouse, hippocampus, neural stem cells, fate choice, adult neurogenesis, astrogliogenesis, DICER, microRNAs, synergy

Melatonin prevents neural tube defects in the offspring of diabetic pregnancy.

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Liu, Shangming; Guo, Yuji; Yuan, Qiuhuan; Pan, Yan; Wang, Liyan; Liu, Qian; Wang, Fuwu; Wang, Jingjing; Hao, Aijun

2015-11-01

Melatonin, an endogenous neurohormone secreted by the pineal gland, has a variety of physiological functions and neuroprotective effects. However, its protective role on the neural tube defects (NTDs) was not very clear. The aim of this study was to investigate the effects of melatonin on the incidence of NTDs (including anencephaly, encephalocele, and spina bifida) of offspring from diabetic pregnant mice as well as its underlying mechanisms. Pregnant mice were given 10 mg/kg melatonin by daily i.p. injection from embryonic day (E) 0.5 until being killed on E11.5. Here, we showed that melatonin decreased the NTDs (especially exencephaly) rate of embryos exposed to maternal diabetes. Melatonin stimulated proliferation of neural stem cells (NSCs) under hyperglycemic condition through the extracellular regulated protein kinases (ERK) pathway. Furthermore, as a direct free radical scavenger, melatonin decreased apoptosis of NSCs exposed to hyperglycemia. In the light of these findings, it suggests that melatonin supplementation may play an important role in the prevention of neural malformations in diabetic pregnancy. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Variety in emotional life: within-category typicality of emotional experiences is associated with neural activity in large-scale brain networks

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Wilson-Mendenhall, Christine D.; Barrett, Lisa Feldman; Barsalou, Lawrence W.

2014-01-01

The tremendous variability within categories of human emotional experience receives little empirical attention. We hypothesized that atypical instances of emotion categories (e.g. pleasant fear of thrill-seeking) would be processed less efficiently than typical instances of emotion categories (e.g. unpleasant fear of violent threat) in large-scale brain networks. During a novel fMRI paradigm, participants immersed themselves in scenarios designed to induce atypical and typical experiences of ...

Altered topology of neural circuits in congenital prosopagnosia.

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Rosenthal, Gideon; Tanzer, Michal; Simony, Erez; Hasson, Uri; Behrmann, Marlene; Avidan, Galia

2017-08-21

Using a novel, fMRI-based inter-subject functional correlation (ISFC) approach, which isolates stimulus-locked inter-regional correlation patterns, we compared the cortical topology of the neural circuit for face processing in participants with an impairment in face recognition, congenital prosopagnosia (CP), and matched controls. Whereas the anterior temporal lobe served as the major network hub for face processing in controls, this was not the case for the CPs. Instead, this group evinced hyper-connectivity in posterior regions of the visual cortex, mostly associated with the lateral occipital and the inferior temporal cortices. Moreover, the extent of this hyper-connectivity was correlated with the face recognition deficit. These results offer new insights into the perturbed cortical topology in CP, which may serve as the underlying neural basis of the behavioral deficits typical of this disorder. The approach adopted here has the potential to uncover altered topologies in other neurodevelopmental disorders, as well.

Challenges to the Use of Artificial Neural Networks for Diagnostic Classifications with Student Test Data

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Briggs, Derek C.; Circi, Ruhan

2017-01-01

Artificial Neural Networks (ANNs) have been proposed as a promising approach for the classification of students into different levels of a psychological attribute hierarchy. Unfortunately, because such classifications typically rely upon internally produced item response patterns that have not been externally validated, the instability of ANN…

Associations between proprioceptive neural pathway structural connectivity and balance in people with multiple sclerosis

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Brett W Fling

2014-10-01

Full Text Available Mobility and balance impairments are a hallmark of multiple sclerosis (MS, affecting nearly half of patients at presentation and resulting in decreased activity and participation, falls, injuries, and reduced quality of life. A growing body of work suggests that balance impairments in people with mild MS are primarily the result of deficits in proprioception, the ability to determine body position in space in the absence of vision. A better understanding of the pathophysiology of balance disturbances in MS is needed to develop evidence-based rehabilitation approaches. The purpose of the current study was to 1 map the cortical proprioceptive pathway in-vivo using diffusion weighted imaging and 2 assess associations between proprioceptive pathway white matter microstructural integrity and performance on clinical and behavioral balance tasks. We hypothesized that people with MS (PwMS would have reduced integrity of cerebral proprioceptive pathways, and that reduced white matter microstructure within these tracts would be strongly related to proprioceptive-based balance deficits. We found poorer balance control on proprioceptive-based tasks and reduced white matter microstructural integrity of the cortical proprioceptive tracts in PwMS compared with age-matched healthy controls. Microstructural integrity of this pathway in the right hemisphere was also strongly associated with proprioceptive-based balance control in PwMS and controls. Conversely, while white matter integrity of the right hemisphere’s proprioceptive pathway was significantly correlated with overall balance performance in healthy controls, there was no such relationship in PwMS. These results augment existing literature suggesting that balance control in PwMS may become more dependent upon 1 cerebellar-regulated proprioceptive control, 2 the vestibular system, and/or 3 the visual system.

The neural basis of learning to spell again: An fMRI study of spelling training in acquired dysgraphia.

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Jeremy Purcell

2015-05-01

1 For all participants we identified brain areas associated with a normalized response for the TRAINING words at the post-training time point. 2 For all participants we identified an up-regulation of the TRAINING response (i.e., the TRAINING neural response was initially low and then increased post-training; whereas in only one participant did we also observe a down-regulation of the training response (i.e., the TRAINING neural response was initially high, but then decreased post-training. 3 Although the areas associated with the normalized TRAINING response were different in each individual, they all include areas typically associated with the spelling system (Purcell et al. 2011, including the right homologues of typically left hemisphere spelling regions. Across the participants, the following areas of normalization were observed: bilateral superior temporal gyrus, inferior frontal gyrus, and the bilateral inferior temporal/fusiform gyrus. Discussion: We found that the predominant BOLD response to training involved an up-regulation of the neural response to spelling the TRAINING items. In addition, we found individual differences in the neurotopography of the normalization response patterns although all were with within brain areas that form a part of the spelling network(Purcell et al. 2011. This work provides evidence regarding one aspect of the multiplicity of neural responses associated with recovery of spelling in individuals with acquired dysgraphia.

Neural stem cells in the adult ciliary epithelium express GFAP and are regulated by Wnt signaling

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Das, Ani V.; Zhao Xing; James, Jackson; Kim, Min; Cowan, Kenneth H.; Ahmad, Iqbal

2006-01-01

The identification of neural stem cells with retinal potential in the ciliary epithelium (CE) of the adult mammals is of considerable interest because of their potential for replacing or rescuing degenerating retinal neurons in disease or injury. The evaluation of such a potential requires characterization of these cells with regard to their phenotypic properties, potential, and regulatory mechanisms. Here, we demonstrate that rat CE stem cells/progenitors in neurosphere culture display astrocytic nature in terms of expressing glial intermediate neurofilament protein, GFAP. The GFAP-expressing CE stem cells/progenitors form neurospheres in proliferating conditions and generate neurons when shifted to differentiating conditions. These cells express components of the canonical Wnt pathway and its activation promotes their proliferation. Furthermore, we demonstrate that the activation of the canonical Wnt pathway influences neuronal differentiation of CE stem cells/progenitors in a context dependent manner. Our observations suggest that CE stem cells/progenitors share phenotypic properties and regulatory mechanism(s) with neural stem cells elsewhere in the adult CNS

Morphological neural networks

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Ritter, G.X.; Sussner, P. [Univ. of Florida, Gainesville, FL (United States)

1996-12-31

The theory of artificial neural networks has been successfully applied to a wide variety of pattern recognition problems. In this theory, the first step in computing the next state of a neuron or in performing the next layer neural network computation involves the linear operation of multiplying neural values by their synaptic strengths and adding the results. Thresholding usually follows the linear operation in order to provide for nonlinearity of the network. In this paper we introduce a novel class of neural networks, called morphological neural networks, in which the operations of multiplication and addition are replaced by addition and maximum (or minimum), respectively. By taking the maximum (or minimum) of sums instead of the sum of products, morphological network computation is nonlinear before thresholding. As a consequence, the properties of morphological neural networks are drastically different than those of traditional neural network models. In this paper we consider some of these differences and provide some particular examples of morphological neural network.

Epigenetic Regulation of the Neural Transcriptome and Alcohol Interference During Development

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Marisol eResendiz

2014-08-01

Full Text Available Alcohol intoxicated cells broadly alter their metabolites–– among them methyl and acetic acid can alter the DNA and histone epigenetic codes. Together with the promiscuous effect of alcohol on enzyme activities (including DNA methyltransferases and the downstream effect on microRNA and transposable elements, alcohol is well placed to affect intrinsic transcriptional programs of developing cells. Considering that the developmental consequences of early alcohol exposure so profoundly affect neural systems, it is not unfounded to reason that alcohol exploits transcriptional regulators to challenge canonical gene expression and in effect, intrinsic developmental pathways to achieve widespread damage in the developing nervous system. To fully evaluate the role of epigenetic regulation in alcohol-related developmental disease, it is important to first gather the targets of epigenetic players in neurodevelopmental models. Here, we attempt to review the cellular and genomic windows of opportunity for alcohol to act on intrinsic neurodevelopmental programs. We also discuss some established targets of fetal alcohol exposure and propose pathways for future study. Overall, this review hopes to illustrate the known epigenetic program and its alterations in normal neural stem cell development and further, aims to depict how alcohol, through neuroepigenetics, may lead to neurodevelopmental deficits observed in fetal alcohol spectrum disorders.

Epigenetic regulation of the neural transcriptome and alcohol interference during development.

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Resendiz, Marisol; Mason, Stephen; Lo, Chiao-Ling; Zhou, Feng C

2014-01-01

Alcohol intoxicated cells broadly alter their metabolites - among them methyl and acetic acid can alter the DNA and histone epigenetic codes. Together with the promiscuous effect of alcohol on enzyme activities (including DNA methyltransferases) and the downstream effect on microRNA and transposable elements, alcohol is well placed to affect intrinsic transcriptional programs of developing cells. Considering that the developmental consequences of early alcohol exposure so profoundly affect neural systems, it is not unfounded to reason that alcohol exploits transcriptional regulators to challenge canonical gene expression and in effect, intrinsic developmental pathways to achieve widespread damage in the developing nervous system. To fully evaluate the role of epigenetic regulation in alcohol-related developmental disease, it is important to first gather the targets of epigenetic players in neurodevelopmental models. Here, we attempt to review the cellular and genomic windows of opportunity for alcohol to act on intrinsic neurodevelopmental programs. We also discuss some established targets of fetal alcohol exposure and propose pathways for future study. Overall, this review hopes to illustrate the known epigenetic program and its alterations in normal neural stem cell development and further, aims to depict how alcohol, through neuroepigenetics, may lead to neurodevelopmental deficits observed in fetal alcohol spectrum disorders.

Neural circuits involved in the renewal of extinguished fear.

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Chen, Weihai; Wang, Yan; Wang, Xiaqing; Li, Hong

2017-07-01

The last 10 years have witnessed a substantial progress in understanding the neural mechanisms for the renewal of the extinguished fear memory. Based on the theory of fear extinction, exposure therapy has been developed as a typical cognitive behavioral therapy for posttraumatic stress disorder. Although the fear memory can be extinguished by repeated presentation of conditioned stimulus without unconditioned stimulus, the fear memory is not erased and tends to relapse outside of extinction context, which is referred to as renewal. Therefore, the renewal is regarded as a great obstruction interfering with the effect of exposure therapy. In recent years, there has been a great deal of studies in understanding the neurobiological underpinnings of fear renewal. These offer a foundation upon which novel therapeutic interventions for the renewal may be built. This review focuses on behavioral, anatomical and electrophysiological studies that interpret roles of the hippocampus, prelimbic cortex and amygdala as well as the connections between them for the renewal of the extinguished fear. Additionally, this review suggests the possible pathways for the renewal: (1) the prelimbic cortex may integrate contextual information from hippocampal inputs and project to the basolateral amygdala to mediate the renewal of extinguished fear memory; the ventral hippocampus may innervate the activities of the basolateral amygdala or the central amygdala directly for the renewal. © 2017 IUBMB Life, 69(7):470-478, 2017. © 2017 International Union of Biochemistry and Molecular Biology.

Emotional facial expressions reduce neural adaptation to face identity.

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Gerlicher, Anna M V; van Loon, Anouk M; Scholte, H Steven; Lamme, Victor A F; van der Leij, Andries R

2014-05-01

In human social interactions, facial emotional expressions are a crucial source of information. Repeatedly presented information typically leads to an adaptation of neural responses. However, processing seems sustained with emotional facial expressions. Therefore, we tested whether sustained processing of emotional expressions, especially threat-related expressions, would attenuate neural adaptation. Neutral and emotional expressions (happy, mixed and fearful) of same and different identity were presented at 3 Hz. We used electroencephalography to record the evoked steady-state visual potentials (ssVEP) and tested to what extent the ssVEP amplitude adapts to the same when compared with different face identities. We found adaptation to the identity of a neutral face. However, for emotional faces, adaptation was reduced, decreasing linearly with negative valence, with the least adaptation to fearful expressions. This short and straightforward method may prove to be a valuable new tool in the study of emotional processing.

Effects and mechanisms of melatonin on neural differentiation of induced pluripotent stem cells.

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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.

Optic pathway glioma associated with orbital rhabdomyosarcoma and bilateral optic nerve sheath dural ectasia in a child with neurofibromatosis-1

International Nuclear Information System (INIS)

Nikas, Ioannis; Theofanopoulou, Maria; Lampropoulou, Penelope; Hadjigeorgi, Christiana; Pourtsidis, Apostolos; Kosmidis, Helen

2006-01-01

Neurofibromatosis-1 (NF-1) is a multisystem disorder presenting with a variety of clinical and imaging manifestations. Neural and non-neural tumours, and unusual benign miscellaneous conditions, separately or combined, are encountered in variable locations. We present a 21/2-year-old boy with NF-1 who demonstrated coexisting optic pathway glioma with involvement of the chiasm and optic nerve, orbital alveolar rhabdomyosarcoma and bilateral optic nerve sheath dural ectasia. (orig.)

Lunar Circular Structure Classification from Chang 'e 2 High Resolution Lunar Images with Convolutional Neural Network

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Zeng, X. G.; Liu, J. J.; Zuo, W.; Chen, W. L.; Liu, Y. X.

2018-04-01

Circular structures are widely distributed around the lunar surface. The most typical of them could be lunar impact crater, lunar dome, et.al. In this approach, we are trying to use the Convolutional Neural Network to classify the lunar circular structures from the lunar images.

Genetic deletion of Rnd3 in neural stem cells promotes proliferation via upregulation of Notch signaling.

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Dong, Huimin; Lin, Xi; Li, Yuntao; Hu, Ronghua; Xu, Yang; Guo, Xiaojie; La, Qiong; Wang, Shun; Fang, Congcong; Guo, Junli; Li, Qi; Mao, Shanping; Liu, Baohui

2017-10-31

Rnd3, a Rho GTPase, is involved in the inhibition of actin cytoskeleton dynamics through the Rho kinase-dependent signaling pathway. We previously demonstrated that mice with genetic deletion of Rnd3 developed a markedly larger brain compared with wild-type mice. Here, we demonstrate that Rnd3 knockout mice developed an enlarged subventricular zone, and we identify a novel role for Rnd3 as an inhibitor of Notch signaling in neural stem cells. Rnd3 deficiency, both in vivo and in vitro , resulted in increased levels of Notch intracellular domain protein. This led to enhanced Notch signaling and promotion of aberrant neural stem cell growth, thereby resulting in a larger subventricular zone and a markedly larger brain. Inhibition of Notch activity abrogated this aberrant neural stem cell growth.

Expression of p53/HGF/c-met/STAT3 signal in fetuses with neural tube defects.

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Trovato, Maria; D'Armiento, Maria; Lavra, Luca; Ulivieri, Alessandra; Dominici, Roberto; Vitarelli, Enrica; Grosso, Maddalena; Vecchione, Raffaella; Barresi, Gaetano; Sciacchitano, Salvatore

2007-02-01

Neural tube defects (NTD) are morphogenetic alterations due to a defective closure of neural tube. Hepatocyte growth factor (HGF)/c-met system plays a role in morphogenesis of nervous system, lung, and kidney. HGF/c-met morphogenetic effects are mediated by signal transducers and activators of transcription (STAT)3 and both HGF and c-met genes are regulated from p53. The aim of our study was to analyze mRNA and protein expressions of p53, HGF, c-met, and STAT3 in fetuses with NTD. By reverse transcriptase-polymerase chain reaction and immunohistochemistry, we analyzed neural tissues from four NTD fetuses and the corresponding non-malformed lungs, kidneys and placentas. We found a reduced mRNA expression of HGF/c-met/STAT3 pathway, in the malformed nervous systems and placentas. The reduced expression of this pathway correlated with the absence of p53 in all these samples. On the contrary, detectable expression levels of p53, HGF, c-met, and STAT3 were observed in non-malformed lungs and kidneys obtained from the same fetuses. Comparable results were obtained by immunohistochemistry, with the exception of p53, which was undetected in all fetal tissues. In conclusion, in NTD fetuses, both the defective neural tube tissue and the placenta have a reduction in all components of the p53/HGF/c-met/STAT3 cascade. This raises the possibility of using the suppression of these genes for early diagnosis of NTD especially on chorionic villus sampling.

Supervised learning of probability distributions by neural networks

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Baum, Eric B.; Wilczek, Frank

1988-01-01

Supervised learning algorithms for feedforward neural networks are investigated analytically. The back-propagation algorithm described by Werbos (1974), Parker (1985), and Rumelhart et al. (1986) is generalized by redefining the values of the input and output neurons as probabilities. The synaptic weights are then varied to follow gradients in the logarithm of likelihood rather than in the error. This modification is shown to provide a more rigorous theoretical basis for the algorithm and to permit more accurate predictions. A typical application involving a medical-diagnosis expert system is discussed.

L-3-n-Butylphthalide Regulates Proliferation, Migration, and Differentiation of Neural Stem Cell In Vitro and Promotes Neurogenesis in APP/PS1 Mouse Model by Regulating BDNF/TrkB/CREB/Akt Pathway.

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Lei, Hui; Zhang, Yu; Huang, Longjian; Xu, Shaofeng; Li, Jiang; Yang, Lichao; Wang, Ling; Xing, Changhong; Wang, Xiaoliang; Peng, Ying

2018-05-04

Alzheimer's disease (AD) is characterized by extracellular accumulation of β-amyloid peptides (Aβ) and intracellular neurofibrillary tangles, along with cognitive decline and neurodegeneration. The cognitive deficit is considered to be due to the dysfunction of hippocampal neurogenesis. Although L-3-n-butylphthalide (L-NBP) has been shown beneficial effects in multiple AD animal models, the underlying molecular mechanisms are still elusive. In this study, we investigated the effects of L-NBP on neurogenesis both in vitro and in vivo. L-NBP promoted proliferation and migration of neural stem cells and induced neuronal differentiation in vitro. In APP/PS1 mice, L-NBP induced neurogenesis in the dentate gyrus and improved cognitive functions. In addition, L-NBP significantly increased the expressions of BDNF and NGF, tyrosine phosphorylation of its cognate receptor, and phosphorylation of Akt as well as CREB at Ser133 in the hippocampus of APP/PS1 mice. These results indicated that L-NBP might stimulate the proliferation, migration, and differentiation of hippocampal neural stem cells and reversed cognitive deficits in APP/PS1 mice. BDNF/TrkB/CREB/Akt signaling pathway might be involved.

Biophysical Neural Spiking, Bursting, and Excitability Dynamics in Reconfigurable Analog VLSI.

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Yu, T; Sejnowski, T J; Cauwenberghs, G

2011-10-01

We study a range of neural dynamics under variations in biophysical parameters underlying extended Morris-Lecar and Hodgkin-Huxley models in three gating variables. The extended models are implemented in NeuroDyn, a four neuron, twelve synapse continuous-time analog VLSI programmable neural emulation platform with generalized channel kinetics and biophysical membrane dynamics. The dynamics exhibit a wide range of time scales extending beyond 100 ms neglected in typical silicon models of tonic spiking neurons. Circuit simulations and measurements show transition from tonic spiking to tonic bursting dynamics through variation of a single conductance parameter governing calcium recovery. We similarly demonstrate transition from graded to all-or-none neural excitability in the onset of spiking dynamics through the variation of channel kinetic parameters governing the speed of potassium activation. Other combinations of variations in conductance and channel kinetic parameters give rise to phasic spiking and spike frequency adaptation dynamics. The NeuroDyn chip consumes 1.29 mW and occupies 3 mm × 3 mm in 0.5 μm CMOS, supporting emerging developments in neuromorphic silicon-neuron interfaces.

Taurine Induces Proliferation of Neural Stem Cells and Synapse Development in the Developing Mouse Brain

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Shivaraj, Mattu Chetana; Marcy, Guillaume; Low, Guoliang; Ryu, Jae Ryun; Zhao, Xianfeng; Rosales, Francisco J.; Goh, Eyleen L. K.

2012-01-01

Taurine is a sulfur-containing amino acid present in high concentrations in mammalian tissues. It has been implicated in several processes involving brain development and neurotransmission. However, the role of taurine in hippocampal neurogenesis during brain development is still unknown. Here we show that taurine regulates neural progenitor cell (NPC) proliferation in the dentate gyrus of the developing brain as well as in cultured early postnatal (P5) hippocampal progenitor cells and hippocampal slices derived from P5 mice brains. Taurine increased cell proliferation without having a significant effect on neural differentiation both in cultured P5 NPCs as well as cultured hippocampal slices and in vivo. Expression level analysis of synaptic proteins revealed that taurine increases the expression of Synapsin 1 and PSD 95. We also found that taurine stimulates the phosphorylation of ERK1/2 indicating a possible role of the ERK pathway in mediating the changes that we observed, especially in proliferation. Taken together, our results demonstrate a role for taurine in neural stem/progenitor cell proliferation in developing brain and suggest the involvement of the ERK1/2 pathways in mediating these actions. Our study also shows that taurine influences the levels of proteins associated with synapse development. This is the first evidence showing the effect of taurine on early postnatal neuronal development using a combination of in vitro, ex-vivo and in vivo systems. PMID:22916184

Effects of Methylphenidate on Resting-State Functional Connectivity of the Mesocorticolimbic Dopamine Pathways in Cocaine Addiction

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Konova, Anna B.; Moeller, Scott J.; Tomasi, Dardo; Volkow, Nora D.; Goldstein, Rita Z.

2013-08-01

Cocaine addiction is associated with altered resting-state functional connectivity among regions of the mesocorticolimbic dopamine pathways. Methylphenidate hydrochloride, an indirect dopamine agonist, normalizes task-related regional brain activity and associated behavior in cocaine users; however, the neural systems–level effects of methylphenidate in this population have not yet been described. To use resting-state functional magnetic resonance imaging to examine changes in mesocorticolimbic connectivity with methylphenidate and how connectivity of affected pathways relates to severity of cocaine addiction.

Variety in emotional life: within-category typicality of emotional experiences is associated with neural activity in large-scale brain networks.

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Wilson-Mendenhall, Christine D; Barrett, Lisa Feldman; Barsalou, Lawrence W

2015-01-01

The tremendous variability within categories of human emotional experience receives little empirical attention. We hypothesized that atypical instances of emotion categories (e.g. pleasant fear of thrill-seeking) would be processed less efficiently than typical instances of emotion categories (e.g. unpleasant fear of violent threat) in large-scale brain networks. During a novel fMRI paradigm, participants immersed themselves in scenarios designed to induce atypical and typical experiences of fear, sadness or happiness (scenario immersion), and then focused on and rated the pleasant or unpleasant feeling that emerged (valence focus) in most trials. As predicted, reliably greater activity in the 'default mode' network (including medial prefrontal cortex and posterior cingulate) was observed for atypical (vs typical) emotional experiences during scenario immersion, suggesting atypical instances require greater conceptual processing to situate the socio-emotional experience. During valence focus, reliably greater activity was observed for atypical (vs typical) emotional experiences in the 'salience' network (including anterior insula and anterior cingulate), suggesting atypical instances place greater demands on integrating shifting body signals with the sensory and social context. Consistent with emerging psychological construction approaches to emotion, these findings demonstrate that is it important to study the variability within common categories of emotional experience. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Differential coding of reward and movement information in the dorsomedial striatal direct and indirect pathways.

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Shin, Jung Hwan; Kim, Dohoung; Jung, Min Whan

2018-01-26

The direct and indirect pathways of the basal ganglia have long been thought to mediate behavioral promotion and inhibition, respectively. However, this classic dichotomous model has been recently challenged. To better understand neural processes underlying reward-based learning and movement control, we recorded from direct (dSPNs) and indirect (iSPNs) pathway spiny projection neurons in the dorsomedial striatum of D1-Cre and D2-Cre mice performing a probabilistic Pavlovian conditioning task. dSPNs tend to increase activity while iSPNs decrease activity as a function of reward value, suggesting the striatum represents value in the relative activity levels of dSPNs versus iSPNs. Lick offset-related activity increase is largely dSPN selective, suggesting dSPN involvement in suppressing ongoing licking behavior. Rapid responses to negative outcome and previous reward-related responses are more frequent among iSPNs than dSPNs, suggesting stronger contributions of iSPNs to outcome-dependent behavioral adjustment. These findings provide new insights into striatal neural circuit operations.

Demodex canis regulates cholinergic system mediated immunosuppressive pathways in canine demodicosis.

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Kumari, P; Nigam, R; Singh, A; Nakade, U P; Sharma, A; Garg, S K; Singh, S K

2017-09-01

Demodex canis infestation in dogs remains one of the main challenges in veterinary dermatology. The exact pathogenesis of canine demodicosis is unknown but an aberration in immune status is considered very significant. No studies have underpinned the nexus between induction of demodicosis and neural immunosuppressive pathways so far. We have evaluated the involvement of cholinergic pathways in association with cytokines regulation as an insight into the immuno-pathogenesis of canine demodicosis in the present study. Remarkable elevations in circulatory immunosuppressive cytokine interleukin-10 and cholinesterase activity were observed in dogs with demodicosis. Simultaneously, remarkable reduction in circulatory pro-inflammatory cytokine tumour necrosis factor-alpha level was observed in dogs with demodicosis. Findings of the present study evidently suggest that Demodex mites might be affecting the cholinergic pathways to induce immunosuppression in their host and then proliferate incessantly in skin microenvironment to cause demodicosis.

Neural Based Orthogonal Data Fitting The EXIN Neural Networks

CERN Document Server

Cirrincione, Giansalvo

2008-01-01

Written by three leaders in the field of neural based algorithms, Neural Based Orthogonal Data Fitting proposes several neural networks, all endowed with a complete theory which not only explains their behavior, but also compares them with the existing neural and traditional algorithms. The algorithms are studied from different points of view, including: as a differential geometry problem, as a dynamic problem, as a stochastic problem, and as a numerical problem. All algorithms have also been analyzed on real time problems (large dimensional data matrices) and have shown accurate solutions. Wh

Self-reported empathy and neural activity during action imitation and observation in schizophrenia.

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Horan, William P; Iacoboni, Marco; Cross, Katy A; Korb, Alex; Lee, Junghee; Nori, Poorang; Quintana, Javier; Wynn, Jonathan K; Green, Michael F

2014-01-01

Although social cognitive impairments are key determinants of functional outcome in schizophrenia their neural bases are poorly understood. This study investigated neural activity during imitation and observation of finger movements and facial expressions in schizophrenia, and their correlates with self-reported empathy. 23 schizophrenia outpatients and 23 healthy controls were studied with functional magnetic resonance imaging (fMRI) while they imitated, executed, or simply observed finger movements and facial emotional expressions. Between-group activation differences, as well as relationships between activation and self-reported empathy, were evaluated. Both patients and controls similarly activated neural systems previously associated with these tasks. We found no significant between-group differences in task-related activations. There were, however, between-group differences in the correlation between self-reported empathy and right inferior frontal (pars opercularis) activity during observation of facial emotional expressions. As in previous studies, controls demonstrated a positive association between brain activity and empathy scores. In contrast, the pattern in the patient group reflected a negative association between brain activity and empathy. Although patients with schizophrenia demonstrated largely normal patterns of neural activation across the finger movement and facial expression tasks, they reported decreased self perceived empathy and failed to show the typical relationship between neural activity and self-reported empathy seen in controls. These findings suggest that patients show a disjunction between automatic neural responses to low level social cues and higher level, integrative social cognitive processes involved in self-perceived empathy.

Multimodal imaging of temporal processing in typical and atypical language development.

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Kovelman, Ioulia; Wagley, Neelima; Hay, Jessica S F; Ugolini, Margaret; Bowyer, Susan M; Lajiness-O'Neill, Renee; Brennan, Jonathan

2015-03-01

New approaches to understanding language and reading acquisition propose that the human brain's ability to synchronize its neural firing rate to syllable-length linguistic units may be important to children's ability to acquire human language. Yet, little evidence from brain imaging studies has been available to support this proposal. Here, we summarize three recent brain imaging (functional near-infrared spectroscopy (fNIRS), functional magnetic resonance imaging (fMRI), and magnetoencephalography (MEG)) studies from our laboratories with young English-speaking children (aged 6-12 years). In the first study (fNIRS), we used an auditory beat perception task to show that, in children, the left superior temporal gyrus (STG) responds preferentially to rhythmic beats at 1.5 Hz. In the second study (fMRI), we found correlations between children's amplitude rise-time sensitivity, phonological awareness, and brain activation in the left STG. In the third study (MEG), typically developing children outperformed children with autism spectrum disorder in extracting words from rhythmically rich foreign speech and displayed different brain activation during the learning phase. The overall findings suggest that the efficiency with which left temporal regions process slow temporal (rhythmic) information may be important for gains in language and reading proficiency. These findings carry implications for better understanding of the brain's mechanisms that support language and reading acquisition during both typical and atypical development. © 2014 New York Academy of Sciences.

Biosynthetic Pathway and Metabolic Engineering of Plant Dihydrochalcones.

Science.gov (United States)

Ibdah, Mwafaq; Martens, Stefan; Gang, David R

2018-03-14

Dihydrochalcones are plant natural products containing the phenylpropanoid backbone and derived from the plant-specific phenylpropanoid pathway. Dihydrochalcone compounds are important in plant growth and response to stresses and, thus, can have large impacts on agricultural activity. In recent years, these compounds have also received increased attention from the biomedical community for their potential as anticancer treatments and other benefits for human health. However, they are typically produced at relatively low levels in plants. Therefore, an attractive alternative is to express the plant biosynthetic pathway genes in microbial hosts and to engineer the metabolic pathway/host to improve the production of these metabolites. In the present review, we discuss in detail the functions of genes and enzymes involved in the biosynthetic pathway of the dihydrochalcones and the recent strategies and achievements used in the reconstruction of multi-enzyme pathways in microorganisms in efforts to be able to attain higher amounts of desired dihydrochalcones.

Effect of short-term escitalopram treatment on neural activation during emotional processing.

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Maron, Eduard; Wall, Matt; Norbury, Ray; Godlewska, Beata; Terbeck, Sylvia; Cowen, Philip; Matthews, Paul; Nutt, David J

2016-01-01

Recent functional magnetic resonance (fMRI) imaging studies have revealed that subchronic medication with escitalopram leads to significant reduction in both amygdala and medial frontal gyrus reactivity during processing of emotional faces, suggesting that escitalopram may have a distinguishable modulatory effect on neural activation as compared with other serotonin-selective antidepressants. In this fMRI study we aimed to explore whether short-term medication with escitalopram in healthy volunteers is associated with reduced neural response to emotional processing, and whether this effect is predicted by drug plasma concentration. The neural response to fearful and happy faces was measured before and on day 7 of treatment with escitalopram (10mg) in 15 healthy volunteers and compared with those in a control unmedicated group (n=14). Significantly reduced activation to fearful, but not to happy facial expressions was observed in the bilateral amygdala, cingulate and right medial frontal gyrus following escitalopram medication. This effect was not correlated with plasma drug concentration. In accordance with previous data, we showed that escitalopram exerts its rapid direct effect on emotional processing via attenuation of neural activation in pathways involving medial frontal gyrus and amygdala, an effect that seems to be distinguishable from that of other SSRIs. © The Author(s) 2015.

SoxB1-driven transcriptional network underlies neural-specific interpretation of morphogen signals.

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Oosterveen, Tony; Kurdija, Sanja; Ensterö, Mats; Uhde, Christopher W; Bergsland, Maria; Sandberg, Magnus; Sandberg, Rickard; Muhr, Jonas; Ericson, Johan

2013-04-30

The reiterative deployment of a small cadre of morphogen signals underlies patterning and growth of most tissues during embyogenesis, but how such inductive events result in tissue-specific responses remains poorly understood. By characterizing cis-regulatory modules (CRMs) associated with genes regulated by Sonic hedgehog (Shh), retinoids, or bone morphogenetic proteins in the CNS, we provide evidence that the neural-specific interpretation of morphogen signaling reflects a direct integration of these pathways with SoxB1 proteins at the CRM level. Moreover, expression of SoxB1 proteins in the limb bud confers on mesodermal cells the potential to activate neural-specific target genes upon Shh, retinoid, or bone morphogenetic protein signaling, and the collocation of binding sites for SoxB1 and morphogen-mediatory transcription factors in CRMs faithfully predicts neural-specific gene activity. Thus, an unexpectedly simple transcriptional paradigm appears to conceptually explain the neural-specific interpretation of pleiotropic signaling during vertebrate development. Importantly, genes induced in a SoxB1-dependent manner appear to constitute repressive gene regulatory networks that are directly interlinked at the CRM level to constrain the regional expression of patterning genes. Accordingly, not only does the topology of SoxB1-driven gene regulatory networks provide a tissue-specific mode of gene activation, but it also determines the spatial expression pattern of target genes within the developing neural tube.

Neural Computations in a Dynamical System with Multiple Time Scales

Directory of Open Access Journals (Sweden)

Yuanyuan Mi

2016-09-01

Full Text Available Neural systems display rich short-term dynamics at various levels, e.g., spike-frequencyadaptation (SFA at single neurons, and short-term facilitation (STF and depression (STDat neuronal synapses. These dynamical features typically covers a broad range of time scalesand exhibit large diversity in different brain regions. It remains unclear what the computationalbenefit for the brain to have such variability in short-term dynamics is. In this study, we proposethat the brain can exploit such dynamical features to implement multiple seemingly contradictorycomputations in a single neural circuit. To demonstrate this idea, we use continuous attractorneural network (CANN as a working model and include STF, SFA and STD with increasing timeconstants in their dynamics. Three computational tasks are considered, which are persistent activity,adaptation, and anticipative tracking. These tasks require conflicting neural mechanisms, andhence cannot be implemented by a single dynamical feature or any combination with similar timeconstants. However, with properly coordinated STF, SFA and STD, we show that the network isable to implement the three computational tasks concurrently. We hope this study will shed lighton the understanding of how the brain orchestrates its rich dynamics at various levels to realizediverse cognitive functions.

A scale out approach towards neural induction of human induced pluripotent stem cells for neurodevelopmental toxicity studies.

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Miranda, Cláudia C; Fernandes, Tiago G; Pinto, Sandra N; Prieto, Manuel; Diogo, M Margarida; Cabral, Joaquim M S

2018-05-21

Stem cell's unique properties confer them a multitude of potential applications in the fields of cellular therapy, disease modelling and drug screening fields. In particular, the ability to differentiate neural progenitors (NP) from human induced pluripotent stem cells (hiPSCs) using chemically-defined conditions provides an opportunity to create a simple and straightforward culture platform for application in these fields. Here, we demonstrated that hiPSCs are capable of undergoing neural commitment inside microwells, forming characteristic neural structures resembling neural rosettes and further give rise to glial and neuronal cells. Furthermore, this platform can be applied towards the study of the effect of neurotoxic molecules that impair normal embryonic development. As a proof of concept, the neural teratogenic potential of the antiepileptic drug valproic acid (VPA) was analyzed. It was verified that exposure to VPA, close to typical dosage values (0.3 to 0.75 mM), led to a prevalence of NP structures over neuronal differentiation, as confirmed by analysis of the expression of neural cell adhesion molecule, as well as neural rosette number and morphology assessment. The methodology proposed herein for the generation and neural differentiation of hiPSC aggregates can potentially complement current toxicity tests such as the humanized embryonic stem cell test for the detection of teratogenic compounds that can interfere with normal embryonic development. Copyright © 2018 Elsevier B.V. All rights reserved.

Process for forming synapses in neural networks and resistor therefor

Science.gov (United States)

Fu, Chi Y.

1996-01-01

Customizable neural network in which one or more resistors form each synapse. All the resistors in the synaptic array are identical, thus simplifying the processing issues. Highly doped, amorphous silicon is used as the resistor material, to create extremely high resistances occupying very small spaces. Connected in series with each resistor in the array is at least one severable conductor whose uppermost layer has a lower reflectivity of laser energy than typical metal conductors at a desired laser wavelength.

Influences of social reward experience on behavioral responses to drugs of abuse: Review of shared and divergent neural plasticity mechanisms for sexual reward and drugs of abuse.

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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.

An integrative neural model of social perception, action observation, and theory of mind.

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Yang, Daniel Y-J; Rosenblau, Gabriela; Keifer, Cara; Pelphrey, Kevin A

2015-04-01

In the field of social neuroscience, major branches of research have been instrumental in describing independent components of typical and aberrant social information processing, but the field as a whole lacks a comprehensive model that integrates different branches. We review existing research related to the neural basis of three key neural systems underlying social information processing: social perception, action observation, and theory of mind. We propose an integrative model that unites these three processes and highlights the posterior superior temporal sulcus (pSTS), which plays a central role in all three systems. Furthermore, we integrate these neural systems with the dual system account of implicit and explicit social information processing. Large-scale meta-analyses based on Neurosynth confirmed that the pSTS is at the intersection of the three neural systems. Resting-state functional connectivity analysis with 1000 subjects confirmed that the pSTS is connected to all other regions in these systems. The findings presented in this review are specifically relevant for psychiatric research especially disorders characterized by social deficits such as autism spectrum disorder. Copyright © 2015 Elsevier Ltd. All rights reserved.

Neural reflex pathways in intestinal inflammation: hypotheses to viable therapy.

Science.gov (United States)

Willemze, Rose A; Luyer, Misha D; Buurman, Wim A; de Jonge, Wouter J

2015-06-01

Studies in neuroscience and immunology have clarified much of the anatomical and cellular basis for bidirectional interactions between the nervous and immune systems. As with other organs, intestinal immune responses and the development of immunity seems to be modulated by neural reflexes. Sympathetic immune modulation and reflexes are well described, and in the past decade the parasympathetic efferent vagus nerve has been added to this immune-regulation network. This system, designated 'the inflammatory reflex', comprises an afferent arm that senses inflammation and an efferent arm that inhibits innate immune responses. Intervention in this system as an innovative principle is currently being tested in pioneering trials of vagus nerve stimulation using implantable devices to treat IBD. Patients benefit from this treatment, but some of the working mechanisms remain to be established, for instance, treatment is effective despite the vagus nerve not always directly innervating the inflamed tissue. In this Review, we will focus on the direct neuronal regulatory mechanisms of immunity in the intestine, taking into account current advances regarding the innervation of the spleen and lymphoid organs, with a focus on the potential for treatment in IBD and other gastrointestinal pathologies.

Association of main folate metabolic pathway gene polymorphisms with neural tube defects in Han population of Northern China.

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Fang, Yulian; Zhang, Ruiping; Zhi, Xiufang; Zhao, Linsheng; Cao, Lirong; Wang, Yizheng; Cai, Chunquan

2018-04-01

Neural tube defects (NTDs) are one of the most prevalent and the most severe congenital malformations worldwide. Studies have confirmed that folic acid supplementation could effectively reduce NTDs risk, but the genetic mechanism remains unclear. In this study, we explored association of single nucleotide polymorphisms (SNP) within folate metabolic pathway genes with NTDs in Han population of Northern China. We performed a case-control study to compare genotype and allele distributions of SNPs in 152 patients with NTDs and 169 controls. A total of 16 SNPs within five genes were genotyped by the Sequenom MassARRAY assay. Our results indicated that three SNPs associated significantly with NTDs (P<0.05). For rs2236225 within MTHFD1, children with allele A or genotype AA had a high NTDs risk (OR=1.500, 95%CI=1.061~2.120; OR=2.862, 95%CI=1.022~8.015, respectively). For rs1801133 within MTHFR, NTDs risk markedly increased in patients with allele T or genotype TT (OR=1.552, 95%CI=1.130~2.131; OR=2.344, 95%CI=1.233~4.457, respectively). For rs1801394 within MTRR, children carrying allele G and genotype GG had a higher NTDs risk (OR=1.533, 95%CI=1.102~2.188; OR=2.355, 95%CI=1.044~5.312, respectively). Our results suggest that rs2236225 of MTHFD1 gene, rs1801133 of MTHFR gene and rs1801394 of MTRR gene were associated with NTDs in Han population of Northern China.

The Neural Correlates Underlying Belief Reasoning for Self and for Others: Evidence from ERPs.

Science.gov (United States)

Jiang, Qin; Wang, Qi; Li, Peng; Li, Hong

2016-01-01

Belief reasoning is typical mental state reasoning in theory of mind (ToM). Although previous studies have explored the neural bases of belief reasoning, the neural correlates of belief reasoning for self and for others are rarely addressed. The decoupling mechanism of distinguishing the mental state of others from one's own is essential for ToM processing. To address the electrophysiological bases underlying the decoupling mechanism, the present event-related potential study compared the time course of neural activities associated with belief reasoning for self and for others when the belief belonging to self was consistent or inconsistent with others. Results showed that during a 450-600 ms period, belief reasoning for self elicited a larger late positive component (LPC) than for others when beliefs were inconsistent with each other. The LPC divergence is assumed to reflect the categorization of agencies in ToM processes.

Neural Mechanisms Underlying Risk and Ambiguity Attitudes.

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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.

Neural Sequence Generation Using Spatiotemporal Patterns of Inhibition.

Directory of Open Access Journals (Sweden)

Jonathan Cannon

2015-11-01

Full Text Available Stereotyped sequences of neural activity are thought to underlie reproducible behaviors and cognitive processes ranging from memory recall to arm movement. One of the most prominent theoretical models of neural sequence generation is the synfire chain, in which pulses of synchronized spiking activity propagate robustly along a chain of cells connected by highly redundant feedforward excitation. But recent experimental observations in the avian song production pathway during song generation have shown excitatory activity interacting strongly with the firing patterns of inhibitory neurons, suggesting a process of sequence generation more complex than feedforward excitation. Here we propose a model of sequence generation inspired by these observations in which a pulse travels along a spatially recurrent excitatory chain, passing repeatedly through zones of local feedback inhibition. In this model, synchrony and robust timing are maintained not through redundant excitatory connections, but rather through the interaction between the pulse and the spatiotemporal pattern of inhibition that it creates as it circulates the network. These results suggest that spatially and temporally structured inhibition may play a key role in sequence generation.

Neural Sequence Generation Using Spatiotemporal Patterns of Inhibition.

Science.gov (United States)

Cannon, Jonathan; Kopell, Nancy; Gardner, Timothy; Markowitz, Jeffrey

2015-11-01

Stereotyped sequences of neural activity are thought to underlie reproducible behaviors and cognitive processes ranging from memory recall to arm movement. One of the most prominent theoretical models of neural sequence generation is the synfire chain, in which pulses of synchronized spiking activity propagate robustly along a chain of cells connected by highly redundant feedforward excitation. But recent experimental observations in the avian song production pathway during song generation have shown excitatory activity interacting strongly with the firing patterns of inhibitory neurons, suggesting a process of sequence generation more complex than feedforward excitation. Here we propose a model of sequence generation inspired by these observations in which a pulse travels along a spatially recurrent excitatory chain, passing repeatedly through zones of local feedback inhibition. In this model, synchrony and robust timing are maintained not through redundant excitatory connections, but rather through the interaction between the pulse and the spatiotemporal pattern of inhibition that it creates as it circulates the network. These results suggest that spatially and temporally structured inhibition may play a key role in sequence generation.

Neural networks

International Nuclear Information System (INIS)

Denby, Bruce; Lindsey, Clark; Lyons, Louis

1992-01-01

The 1980s saw a tremendous renewal of interest in 'neural' information processing systems, or 'artificial neural networks', among computer scientists and computational biologists studying cognition. Since then, the growth of interest in neural networks in high energy physics, fueled by the need for new information processing technologies for the next generation of high energy proton colliders, can only be described as explosive

Nuclear power plant fault-diagnosis using artificial neural networks

International Nuclear Information System (INIS)

Kim, Keehoon; Aljundi, T.L.; Bartlett, E.B.

1992-01-01

Artificial neural networks (ANNs) have been applied to various fields due to their fault and noise tolerance and generalization characteristics. As an application to nuclear engineering, we apply neural networks to the early recognition of nuclear power plant operational transients. If a transient or accident occurs, the network will advise the plant operators in a timely manner. More importantly, we investigate the ability of the network to provide a measure of the confidence level in its diagnosis. In this research an ANN is trained to diagnose the status of the San Onofre Nuclear Generation Station using data obtained from the plant's training simulator. Stacked generalization is then applied to predict the error in the ANN diagnosis. The data used consisted of 10 scenarios that include typical design basis accidents as well as less severe transients. The results show that the trained network is capable of diagnosing all 10 instabilities as well as providing a measure of the level of confidence in its diagnoses

Electro-acupuncture exerts beneficial effects against cerebral ischemia and promotes the proliferation of neural progenitor cells in the cortical peri-infarct area through the Wnt/β-catenin signaling pathway

Science.gov (United States)

CHEN, BIN; TAO, JING; LIN, YUKUN; LIN, RUHUI; LIU, WEILIN; CHEN, LIDIAN

2015-01-01

Electro-acupuncture (EA) is a novel therapy based on combining traditional acupuncture with modern electrotherapy, and it is currently being investigated as a treatment for ischemic stroke. In the present study, we aimed to investigate the mechanisms through which EA regulates the proliferation of neural progenitor cells (NPCs) in the cortical peri-infarct area after stroke. The neuroprotective effects of EA on ischemic rats were evaluated by determining the neurological deficit scores and cerebral infarct volumes. The proliferation of the NPCs and the activation of the Wnt/β-catenin signaling pathway in the cortical peri-infarct area were examined. Our results revealed that EA significantly alleviated neurological deficits, reduced the infarct volume and enhanced NPC proliferation [nestin/glial fibrillary acidic protein (GFAP)-double positive] in the cortex of rats subjected to middle cerebral artery occlusion (MCAO). Moreover, the Wnt1 and β-catenin mRNA and protein levels were increased, while glycogen synthase kinase-3 (GSK3) transcription was suppressed by EA. These results suggest that the upregulatory effects of EA on the Wnt/β-catenin signaling pathway may promote NPC proliferation in the cortical peri-infarct area after stroke, consequently providing a therapeutic effect against cerebral ischemia. PMID:26329606

Burst firing in a motion-sensitive neural pathway correlates with expansion properties of looming objects that evoke avoidance behaviours

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Glyn Allan McMillan

2015-12-01

Full Text Available The locust visual system contains a well-defined motion-sensitive pathway that transfers visual input to motor centers involved in predator evasion and collision avoidance. One interneuron in this pathway, the descending contralateral movement detector (DCMD, is typically described as using rate coding; edge expansion of approaching objects causes an increased rate of neuronal firing that peaks after a certain retinal threshold angle is exceeded. However, evidence of intrinsic DCMD bursting properties combined with observable oscillations in mean firing rates and tight clustering of spikes in raw traces, suggest that bursting may be important for motion detection. Sensory neuron bursting provides important timing information about dynamic stimuli in many model systems, yet no studies have rigorously investigated if bursting occurs in the locust DCMD during object approach. We presented repetitions of 30 looming stimuli known to generate behavioural responses to each of 20 locusts in order to identify and quantify putative bursting activity in the DCMD. Overall, we found a bimodal distribution of inter-spike intervals (ISI with peaks of more frequent and shorter ISIs occurring from 1-8 ms and longer less frequent ISIs occurring from 40-50 ms. Subsequent analysis identified bursts and isolated single spikes from the responses. Bursting frequency increased in the latter phase of an approach and peaked at the time of collision, while isolated spiking was predominant during the beginning of stimulus approach. We also found that the majority of inter-burst intervals occurred at 40-50 ms (or 20-25 bursts/s. Bursting also occurred across varied stimulus parameters and suggests that burst timing may be a key component of looming detection. Our findings suggest that the DCMD uses two modes of coding to transmit information about looming stimuli and that these modes change dynamically with a changing stimulus at a behaviourally-relevant time.

Neuromechanism study of insect-machine interface: flight control by neural electrical stimulation.

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Huixia Zhao

Full Text Available The insect-machine interface (IMI is a novel approach developed for man-made air vehicles, which directly controls insect flight by either neuromuscular or neural stimulation. In our previous study of IMI, we induced flight initiation and cessation reproducibly in restrained honeybees (Apis mellifera L. via electrical stimulation of the bilateral optic lobes. To explore the neuromechanism underlying IMI, we applied electrical stimulation to seven subregions of the honeybee brain with the aid of a new method for localizing brain regions. Results showed that the success rate for initiating honeybee flight decreased in the order: α-lobe (or β-lobe, ellipsoid body, lobula, medulla and antennal lobe. Based on a comparison with other neurobiological studies in honeybees, we propose that there is a cluster of descending neurons in the honeybee brain that transmits neural excitation from stimulated brain areas to the thoracic ganglia, leading to flight behavior. This neural circuit may involve the higher-order integration center, the primary visual processing center and the suboesophageal ganglion, which is also associated with a possible learning and memory pathway. By pharmacologically manipulating the electrically stimulated honeybee brain, we have shown that octopamine, rather than dopamine, serotonin and acetylcholine, plays a part in the circuit underlying electrically elicited honeybee flight. Our study presents a new brain stimulation protocol for the honeybee-machine interface and has solved one of the questions with regard to understanding which functional divisions of the insect brain participate in flight control. It will support further studies to uncover the involved neurons inside specific brain areas and to test the hypothesized involvement of a visual learning and memory pathway in IMI flight control.

Neuromechanism study of insect-machine interface: flight control by neural electrical stimulation.

Science.gov (United States)

Zhao, Huixia; Zheng, Nenggan; Ribi, Willi A; Zheng, Huoqing; Xue, Lei; Gong, Fan; Zheng, Xiaoxiang; Hu, Fuliang

2014-01-01

The insect-machine interface (IMI) is a novel approach developed for man-made air vehicles, which directly controls insect flight by either neuromuscular or neural stimulation. In our previous study of IMI, we induced flight initiation and cessation reproducibly in restrained honeybees (Apis mellifera L.) via electrical stimulation of the bilateral optic lobes. To explore the neuromechanism underlying IMI, we applied electrical stimulation to seven subregions of the honeybee brain with the aid of a new method for localizing brain regions. Results showed that the success rate for initiating honeybee flight decreased in the order: α-lobe (or β-lobe), ellipsoid body, lobula, medulla and antennal lobe. Based on a comparison with other neurobiological studies in honeybees, we propose that there is a cluster of descending neurons in the honeybee brain that transmits neural excitation from stimulated brain areas to the thoracic ganglia, leading to flight behavior. This neural circuit may involve the higher-order integration center, the primary visual processing center and the suboesophageal ganglion, which is also associated with a possible learning and memory pathway. By pharmacologically manipulating the electrically stimulated honeybee brain, we have shown that octopamine, rather than dopamine, serotonin and acetylcholine, plays a part in the circuit underlying electrically elicited honeybee flight. Our study presents a new brain stimulation protocol for the honeybee-machine interface and has solved one of the questions with regard to understanding which functional divisions of the insect brain participate in flight control. It will support further studies to uncover the involved neurons inside specific brain areas and to test the hypothesized involvement of a visual learning and memory pathway in IMI flight control.

Neuromechanism Study of Insect–Machine Interface: Flight Control by Neural Electrical Stimulation

Science.gov (United States)

Zhao, Huixia; Zheng, Nenggan; Ribi, Willi A.; Zheng, Huoqing; Xue, Lei; Gong, Fan; Zheng, Xiaoxiang; Hu, Fuliang

2014-01-01

The insect–machine interface (IMI) is a novel approach developed for man-made air vehicles, which directly controls insect flight by either neuromuscular or neural stimulation. In our previous study of IMI, we induced flight initiation and cessation reproducibly in restrained honeybees (Apis mellifera L.) via electrical stimulation of the bilateral optic lobes. To explore the neuromechanism underlying IMI, we applied electrical stimulation to seven subregions of the honeybee brain with the aid of a new method for localizing brain regions. Results showed that the success rate for initiating honeybee flight decreased in the order: α-lobe (or β-lobe), ellipsoid body, lobula, medulla and antennal lobe. Based on a comparison with other neurobiological studies in honeybees, we propose that there is a cluster of descending neurons in the honeybee brain that transmits neural excitation from stimulated brain areas to the thoracic ganglia, leading to flight behavior. This neural circuit may involve the higher-order integration center, the primary visual processing center and the suboesophageal ganglion, which is also associated with a possible learning and memory pathway. By pharmacologically manipulating the electrically stimulated honeybee brain, we have shown that octopamine, rather than dopamine, serotonin and acetylcholine, plays a part in the circuit underlying electrically elicited honeybee flight. Our study presents a new brain stimulation protocol for the honeybee–machine interface and has solved one of the questions with regard to understanding which functional divisions of the insect brain participate in flight control. It will support further studies to uncover the involved neurons inside specific brain areas and to test the hypothesized involvement of a visual learning and memory pathway in IMI flight control. PMID:25409523

Low-level neural auditory discrimination dysfunctions in specific language impairment—A review on mismatch negativity findings

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Teija Kujala

2017-12-01

Full Text Available In specific language impairment (SLI, there is a delay in the child’s oral language skills when compared with nonverbal cognitive abilities. The problems typically relate to phonological and morphological processing and word learning. This article reviews studies which have used mismatch negativity (MMN in investigating low-level neural auditory dysfunctions in this disorder. With MMN, it is possible to tap the accuracy of neural sound discrimination and sensory memory functions. These studies have found smaller response amplitudes and longer latencies for speech and non-speech sound changes in children with SLI than in typically developing children, suggesting impaired and slow auditory discrimination in SLI. Furthermore, they suggest shortened sensory memory duration and vulnerability of the sensory memory to masking effects. Importantly, some studies reported associations between MMN parameters and language test measures. In addition, it was found that language intervention can influence the abnormal MMN in children with SLI, enhancing its amplitude. These results suggest that the MMN can shed light on the neural basis of various auditory and memory impairments in SLI, which are likely to influence speech perception. Keywords: Specific language impairment, Auditory processing, Mismatch negativity (MMN

Endoplasmic reticulum stress pathway required for immune homeostasis is neurally controlled by arrestin-1.

Science.gov (United States)

Singh, Varsha; Aballay, Alejandro

2012-09-28

In response to pathogen infection, the host innate immune system activates microbial killing pathways and cellular stress pathways that need to be balanced because insufficient or excessive immune responses have deleterious consequences. Recent studies demonstrate that two G protein-coupled receptors (GPCRs) in the nervous system of Caenorhabditis elegans control immune homeostasis. To investigate further how GPCR signaling controls immune homeostasis at the organismal level, we studied arrestin-1 (ARR-1), which is the only GPCR adaptor protein in C. elegans. The results indicate that ARR-1 is required for GPCR signaling in ASH, ASI, AQR, PQR, and URX neurons, which control the unfolded protein response and a p38 mitogen-activated protein kinase signaling pathway required for innate immunity. ARR-1 activity also controlled immunity through ADF chemosensory and AFD thermosensory neurons that regulate longevity. Furthermore, we found that although ARR-1 played a key role in the control of immunity by AFD thermosensory neurons, it did not control longevity through these cells. However, ARR-1 partially controlled longevity through ADF neurons.

Transcriptional Profiling of Hypoxic Neural Stem Cells Identifies Calcineurin-NFATc4 Signaling as a Major Regulator of Neural Stem Cell Biology

Science.gov (United States)

Moreno, Marta; Fernández, Virginia; Monllau, Josep M.; Borrell, Víctor; Lerin, Carles; de la Iglesia, Núria

2015-01-01

Summary Neural stem cells (NSCs) reside in a hypoxic microenvironment within the brain. However, the crucial transcription factors (TFs) that regulate NSC biology under physiologic hypoxia are poorly understood. Here we have performed gene set enrichment analysis (GSEA) of microarray datasets from hypoxic versus normoxic NSCs with the aim of identifying pathways and TFs that are activated under oxygen concentrations mimicking normal brain tissue microenvironment. Integration of TF target (TFT) and pathway enrichment analysis identified the calcium-regulated TF NFATc4 as a major candidate to regulate hypoxic NSC functions. Nfatc4 expression was coordinately upregulated by top hypoxia-activated TFs, while NFATc4 target genes were enriched in hypoxic NSCs. Loss-of-function analyses further revealed that the calcineurin-NFATc4 signaling axis acts as a major regulator of NSC self-renewal and proliferation in vitro and in vivo by promoting the expression of TFs, including Id2, that contribute to the maintenance of the NSC state. PMID:26235896

Stochastic Oscillation in Self-Organized Critical States of Small Systems: Sensitive Resting State in Neural Systems.

Science.gov (United States)

Wang, Sheng-Jun; Ouyang, Guang; Guang, Jing; Zhang, Mingsha; Wong, K Y Michael; Zhou, Changsong

2016-01-08

Self-organized critical states (SOCs) and stochastic oscillations (SOs) are simultaneously observed in neural systems, which appears to be theoretically contradictory since SOCs are characterized by scale-free avalanche sizes but oscillations indicate typical scales. Here, we show that SOs can emerge in SOCs of small size systems due to temporal correlation between large avalanches at the finite-size cutoff, resulting from the accumulation-release process in SOCs. In contrast, the critical branching process without accumulation-release dynamics cannot exhibit oscillations. The reconciliation of SOCs and SOs is demonstrated both in the sandpile model and robustly in biologically plausible neuronal networks. The oscillations can be suppressed if external inputs eliminate the prominent slow accumulation process, providing a potential explanation of the widely studied Berger effect or event-related desynchronization in neural response. The features of neural oscillations and suppression are confirmed during task processing in monkey eye-movement experiments. Our results suggest that finite-size, columnar neural circuits may play an important role in generating neural oscillations around the critical states, potentially enabling functional advantages of both SOCs and oscillations for sensitive response to transient stimuli.

Peak alpha frequency is a neural marker of cognitive function across the autism spectrum.

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Dickinson, Abigail; DiStefano, Charlotte; Senturk, Damla; Jeste, Shafali Spurling

2018-03-01

Cognitive function varies substantially and serves as a key predictor of outcome and response to intervention in autism spectrum disorder (ASD), yet we know little about the neurobiological mechanisms that underlie cognitive function in children with ASD. The dynamics of neuronal oscillations in the alpha range (6-12 Hz) are associated with cognition in typical development. Peak alpha frequency is also highly sensitive to developmental changes in neural networks, which underlie cognitive function, and therefore, it holds promise as a developmentally sensitive neural marker of cognitive function in ASD. Here, we measured peak alpha band frequency under a task-free condition in a heterogeneous sample of children with ASD (N = 59) and age-matched typically developing (TD) children (N = 38). At a group level, peak alpha frequency was decreased in ASD compared to TD children. Moreover, within the ASD group, peak alpha frequency correlated strongly with non-verbal cognition. As peak alpha frequency reflects the integrity of neural networks, our results suggest that deviations in network development may underlie cognitive function in individuals with ASD. By shedding light on the neurobiological correlates of cognitive function in ASD, our findings lay the groundwork for considering peak alpha frequency as a useful biomarker of cognitive function within this population which, in turn, will facilitate investigations of early markers of cognitive impairment and predictors of outcome in high risk infants. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Fragile X mental retardation protein participates in non-coding RNA pathways.

Science.gov (United States)

Li, En-Hui; Zhao, Xin; Zhang, Ce; Liu, Wei

2018-02-20

Fragile X syndrome is one of the most common forms of inherited intellectual disability. It is caused by mutations of the Fragile X mental retardation 1(FMR1) gene, resulting in either the loss or abnormal expression of the Fragile X mental retardation protein (FMRP). Recent research showed that FMRP participates in non-coding RNA pathways and plays various important roles in physiology, thereby extending our knowledge of the pathogenesis of the Fragile X syndrome. Initial studies showed that the Drosophila FMRP participates in siRNA and miRNA pathways by interacting with Dicer, Ago1 and Ago2, involved in neural activity and the fate determination of the germline stem cells. Subsequent studies showed that the Drosophila FMRP participates in piRNA pathway by interacting with Aub, Ago1 and Piwi in the maintenance of normal chromatin structures and genomic stability. More recent studies showed that FMRP is associated with lncRNA pathway, suggesting a potential role for the involvement in the clinical manifestations. In this review, we summarize the novel findings and explore the relationship between FMRP and non-coding RNA pathways, particularly the piRNA pathway, thereby providing critical insights on the molecular pathogenesis of Fragile X syndrome, and potential translational applications in clinical management of the disease.

Adult ADHD and working memory: neural evidence of impaired encoding.

Science.gov (United States)

Kim, Soyeon; Liu, Zhongxu; Glizer, Daniel; Tannock, Rosemary; Woltering, Steven

2014-08-01

To investigate neural and behavioural correlates of visual encoding during a working memory (WM) task in young adults with and without Attention-Deficit/Hyperactivity Disorder (ADHD). A sample of 30 college students currently meeting a diagnosis of ADHD and 25 typically developing students, matched on age and gender, performed a delayed match-to-sample task with low and high memory load conditions. Dense-array electroencephalography was recorded. Specifically, the P3, an event related potential (ERP) associated with WM, was examined because of its relation with attentional allocation during WM. Task performance (accuracy, reaction time) as well as performance on other neuropsychological tasks of WM was analyzed. Neural differences were found between the groups. Specifically, the P3 amplitude was smaller in the ADHD group compared to the comparison group for both load conditions at parietal-occipital sites. Lower scores on behavioural working memory tasks were suggestive of impaired behavioural WM performance in the ADHD group. Findings from this study provide the first evidence of neural differences in the encoding stage of WM in young adults with ADHD, suggesting ineffective allocation of attentional resources involved in encoding of information in WM. These findings, reflecting alternate neural functioning of WM, may explain some of the difficulties related to WM functioning that college students with ADHD report in their every day cognitive functioning. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Intermittent reductions in respiratory neural activity elicit spinal TNF-α-independent, atypical PKC-dependent inactivity-induced phrenic motor facilitation.

Science.gov (United States)

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.

Alcohol resistance in Drosophila is modulated by the Toll innate immune pathway.

Science.gov (United States)

Troutwine, B R; Ghezzi, A; Pietrzykowski, A Z; Atkinson, N S

2016-04-01

A growing body of evidence has shown that alcohol alters the activity of the innate immune system and that changes in innate immune system activity can influence alcohol-related behaviors. Here, we show that the Toll innate immune signaling pathway modulates the level of alcohol resistance in Drosophila. In humans, a low level of response to alcohol is correlated with increased risk of developing an alcohol use disorder. The Toll signaling pathway was originally discovered in, and has been extensively studied in Drosophila. The Toll pathway is a major regulator of innate immunity in Drosophila, and mammalian Toll-like receptor signaling has been implicated in alcohol responses. Here, we use Drosophila-specific genetic tools to test eight genes in the Toll signaling pathway for effects on the level of response to ethanol. We show that increasing the activity of the pathway increases ethanol resistance whereas decreasing the pathway activity reduces ethanol resistance. Furthermore, we show that gene products known to be outputs of innate immune signaling are rapidly induced following ethanol exposure. The interaction between the Toll signaling pathway and ethanol is rooted in the natural history of Drosophila melanogaster. © 2016 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

Beta1 integrins activate a MAPK signalling pathway in neural stem cells that contributes to their maintenance

DEFF Research Database (Denmark)

Campos, Lia S; Leone, Dino P; Relvas, Joao B

2004-01-01

, signalling is required for neural stem cell maintenance, as assessed by neurosphere formation, and inhibition or genetic ablation of beta1 integrin using cre/lox technology reduces the level of MAPK activity. We conclude that integrins are therefore an important part of the signalling mechanisms that control......The emerging evidence that stem cells develop in specialised niches highlights the potential role of environmental factors in their regulation. Here we examine the role of beta1 integrin/extracellular matrix interactions in neural stem cells. We find high levels of beta1 integrin expression...... in the stem-cell containing regions of the embryonic CNS, with associated expression of the laminin alpha2 chain. Expression levels of laminin alpha2 are reduced in the postnatal CNS, but a population of cells expressing high levels of beta1 remains. Using neurospheres - aggregate cultures, derived from...

The role of phosphatidylinositol 3-kinase in neural cell adhesion molecule-mediated neuronal differentiation and survival

DEFF Research Database (Denmark)

Ditlevsen, Dorte K; Køhler, Lene B; Pedersen, Martin Volmer

2003-01-01

The neural cell adhesion molecule, NCAM, is known to stimulate neurite outgrowth from primary neurones and PC12 cells presumably through signalling pathways involving the fibroblast growth factor receptor (FGFR), protein kinase A (PKA), protein kinase C (PKC), the Ras-mitogen activated protein...... kinase (MAPK) pathway and an increase in intracellular Ca2+ levels. Stimulation of neurones with the synthetic NCAM-ligand, C3, induces neurite outgrowth through signalling pathways similar to the pathways activated through physiological, homophilic NCAM-stimulation. We present here data indicating...... that phosphatidylinositol 3-kinase (PI3K) is required for NCAM-mediated neurite outgrowth from PC12-E2 cells and from cerebellar and dopaminergic neurones in primary culture, and that the thr/ser kinase Akt/protein kinase B (PKB) is phosphorylated downstream of PI3K after stimulation with C3. Moreover, we present data...

Identifying Tmem59 related gene regulatory network of mouse neural stem cell from a compendium of expression profiles

Directory of Open Access Journals (Sweden)

Guo Xiuyun

2011-09-01

Full Text Available Abstract Background Neural stem cells offer potential treatment for neurodegenerative disorders, such like Alzheimer's disease (AD. While much progress has been made in understanding neural stem cell function, a precise description of the molecular mechanisms regulating neural stem cells is not yet established. This lack of knowledge is a major barrier holding back the discovery of therapeutic uses of neural stem cells. In this paper, the regulatory mechanism of mouse neural stem cell (NSC differentiation by tmem59 is explored on the genome-level. Results We identified regulators of tmem59 during the differentiation of mouse NSCs from a compendium of expression profiles. Based on the microarray experiment, we developed the parallelized SWNI algorithm to reconstruct gene regulatory networks of mouse neural stem cells. From the inferred tmem59 related gene network including 36 genes, pou6f1 was identified to regulate tmem59 significantly and might play an important role in the differentiation of NSCs in mouse brain. There are four pathways shown in the gene network, indicating that tmem59 locates in the downstream of the signalling pathway. The real-time RT-PCR results shown that the over-expression of pou6f1 could significantly up-regulate tmem59 expression in C17.2 NSC line. 16 out of 36 predicted genes in our constructed network have been reported to be AD-related, including Ace, aqp1, arrdc3, cd14, cd59a, cds1, cldn1, cox8b, defb11, folr1, gdi2, mmp3, mgp, myrip, Ripk4, rnd3, and sncg. The localization of tmem59 related genes and functional-related gene groups based on the Gene Ontology (GO annotation was also identified. Conclusions Our findings suggest that the expression of tmem59 is an important factor contributing to AD. The parallelized SWNI algorithm increased the efficiency of network reconstruction significantly. This study enables us to highlight novel genes that may be involved in NSC differentiation and provides a shortcut to

Statistical physics, neural networks, brain studies

International Nuclear Information System (INIS)

Toulouse, G.

1999-01-01

An overview of some aspects of a vast domain, located at the crossroads of physics, biology and computer science is presented: (1) During the last fifteen years, physicists advancing along various pathways have come into contact with biology (computational neurosciences) and engineering (formal neural nets). (2) This move may actually be viewed as one component in a larger picture. A prominent trend of recent years, observable over many countries, has been the establishment of interdisciplinary centers devoted to the study of: cognitive sciences; natural and artificial intelligence; brain, mind and behaviour; perception and action; learning and memory; robotics; man-machine communication, etc. What are the promising lines of development? What opportunities for physicists? An attempt will be made to address such questions and related issues

Neural control of phrenic motoneuron discharge

Science.gov (United States)

Lee, Kun-Ze; Fuller, David D.

2011-01-01

Phrenic motoneurons (PMNs) provide a synaptic relay between bulbospinal respiratory pathways and the diaphragm muscle. PMNs also receive propriospinal inputs, although the functional role of these interneuronal projections has not been established. Here we review the literature regarding PMN discharge patterns during breathing and the potential mechanisms that underlie PMN recruitment. Anatomical and neurophysiological studies indicate that PMNs form a heterogeneous pool, with respiratory-related PMN discharge and recruitment patterns likely determined by a balance between intrinsic MN properties and extrinsic synaptic inputs. We also review the limited literature regarding PMN bursting during respiratory plasticity. Differential recruitment or rate modulation of PMN subtypes may underlie phrenic motor plasticity following neural injury and/or respiratory stimulation; however this possibility remains relatively unexplored. PMID:21376841

How typical are 'typical' tremor characteristics? : Sensitivity and specificity of five tremor phenomena

NARCIS (Netherlands)

van der Stouwe, A. M. M.; Elting, J. W.; van der Hoeven, J. H.; van Laar, T.; Leenders, K. L.; Maurits, N. M.; Tijssen, M. Aj.

Introduction: Distinguishing between different tremor disorders can be challenging. Some tremor disorders are thought to have typical tremor characteristics: the current study aims to provide sensitivity and specificity for five 'typical' tremor phenomena. Methods: Retrospectively, we examined 210

Single-Cell Memory Regulates a Neural Circuit for Sensory Behavior.

Science.gov (United States)

Kobayashi, Kyogo; Nakano, Shunji; Amano, Mutsuki; Tsuboi, Daisuke; Nishioka, Tomoki; Ikeda, Shingo; Yokoyama, Genta; Kaibuchi, Kozo; Mori, Ikue

2016-01-05

Unveiling the molecular and cellular mechanisms underlying memory has been a challenge for the past few decades. Although synaptic plasticity is proven to be essential for memory formation, the significance of "single-cell memory" still remains elusive. Here, we exploited a primary culture system for the analysis of C. elegans neurons and show that a single thermosensory neuron has an ability to form, retain, and reset a temperature memory. Genetic and proteomic analyses found that the expression of the single-cell memory exhibits inter-individual variability, which is controlled by the evolutionarily conserved CaMKI/IV and Raf pathway. The variable responses of a sensory neuron influenced the neural activity of downstream interneurons, suggesting that modulation of the sensory neurons ultimately determines the behavioral output in C. elegans. Our results provide proof of single-cell memory and suggest that the individual differences in neural responses at the single-cell level can confer individuality. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Evolvable Neural Software System

Science.gov (United States)

Curtis, Steven A.

2009-01-01

The Evolvable Neural Software System (ENSS) is composed of sets of Neural Basis Functions (NBFs), which can be totally autonomously created and removed according to the changing needs and requirements of the software system. The resulting structure is both hierarchical and self-similar in that a given set of NBFs may have a ruler NBF, which in turn communicates with other sets of NBFs. These sets of NBFs may function as nodes to a ruler node, which are also NBF constructs. In this manner, the synthetic neural system can exhibit the complexity, three-dimensional connectivity, and adaptability of biological neural systems. An added advantage of ENSS over a natural neural system is its ability to modify its core genetic code in response to environmental changes as reflected in needs and requirements. The neural system is fully adaptive and evolvable and is trainable before release. It continues to rewire itself while on the job. The NBF is a unique, bilevel intelligence neural system composed of a higher-level heuristic neural system (HNS) and a lower-level, autonomic neural system (ANS). Taken together, the HNS and the ANS give each NBF the complete capabilities of a biological neural system to match sensory inputs to actions. Another feature of the NBF is the Evolvable Neural Interface (ENI), which links the HNS and ANS. The ENI solves the interface problem between these two systems by actively adapting and evolving from a primitive initial state (a Neural Thread) to a complicated, operational ENI and successfully adapting to a training sequence of sensory input. This simulates the adaptation of a biological neural system in a developmental phase. Within the greater multi-NBF and multi-node ENSS, self-similar ENI s provide the basis for inter-NBF and inter-node connectivity.

Investigating the Influence of Biological Sex on the Behavioral and Neural Basis of Face Recognition.

Science.gov (United States)

Scherf, K Suzanne; Elbich, Daniel B; Motta-Mena, Natalie V

2017-01-01

There is interest in understanding the influence of biological factors, like sex, on the organization of brain function. We investigated the influence of biological sex on the behavioral and neural basis of face recognition in healthy, young adults. In behavior, there were no sex differences on the male Cambridge Face Memory Test (CFMT)+ or the female CFMT+ (that we created) and no own-gender bias (OGB) in either group. We evaluated the functional topography of ventral stream organization by measuring the magnitude and functional neural size of 16 individually defined face-, two object-, and two place-related regions bilaterally. There were no sex differences in any of these measures of neural function in any of the regions of interest (ROIs) or in group level comparisons. These findings reveal that men and women have similar category-selective topographic organization in the ventral visual pathway. Next, in a separate task, we measured activation within the 16 face-processing ROIs specifically during recognition of target male and female faces. There were no sex differences in the magnitude of the neural responses in any face-processing region. Furthermore, there was no OGB in the neural responses of either the male or female participants. Our findings suggest that face recognition behavior, including the OGB, is not inherently sexually dimorphic. Face recognition is an essential skill for navigating human social interactions, which is reflected equally in the behavior and neural architecture of men and women.

Investigating the Influence of Biological Sex on the Behavioral and Neural Basis of Face Recognition

Science.gov (United States)

2017-01-01

Abstract There is interest in understanding the influence of biological factors, like sex, on the organization of brain function. We investigated the influence of biological sex on the behavioral and neural basis of face recognition in healthy, young adults. In behavior, there were no sex differences on the male Cambridge Face Memory Test (CFMT)+ or the female CFMT+ (that we created) and no own-gender bias (OGB) in either group. We evaluated the functional topography of ventral stream organization by measuring the magnitude and functional neural size of 16 individually defined face-, two object-, and two place-related regions bilaterally. There were no sex differences in any of these measures of neural function in any of the regions of interest (ROIs) or in group level comparisons. These findings reveal that men and women have similar category-selective topographic organization in the ventral visual pathway. Next, in a separate task, we measured activation within the 16 face-processing ROIs specifically during recognition of target male and female faces. There were no sex differences in the magnitude of the neural responses in any face-processing region. Furthermore, there was no OGB in the neural responses of either the male or female participants. Our findings suggest that face recognition behavior, including the OGB, is not inherently sexually dimorphic. Face recognition is an essential skill for navigating human social interactions, which is reflected equally in the behavior and neural architecture of men and women. PMID:28497111

A new potential secretion pathway for recombinant proteins in Bacillus subtilis.

Science.gov (United States)

Wang, Guangqiang; Xia, Yongjun; Gu, Zhennan; Zhang, Hao; Chen, Yong Q; Chen, Haiqin; Ai, Lianzhong; Chen, Wei

2015-11-10

Secretion of cytoplasmic expressed proteins into growth media has significant advantages. Due to the lack of an outer membrane, Bacillus subtilis is considered as a desirable 'cell factory' for the secretion of recombinant proteins. However, bottlenecks in the classical pathway for the secretion of recombinant proteins limit its use on a wide scale. In this study, we attempted to use four typical non-classically secreted proteins as signals to export three recombinant model proteins to the culture medium. All four non-classically secreted proteins can direct the export of the intrinsically disordered nucleoskeletal-like protein (Nsp). Two of them can guide the secretion of alkaline phosphatase (PhoA). One can lead the secretion of the thermostable β-galactosidase BgaB, which cannot be secreted with the aid of typical Sec-dependent signal peptides. Our results show that the non-classically secreted proteins lead the recombinant proteins to the culture medium, and thus non-classical protein secretion pathways can be exploited as a novel secretion pathway for recombinant proteins.

EDITORIAL: Commercial opportunities for neural engineers

Science.gov (United States)

Cavuoto, James

2008-03-01

of the device in 2000. Anthony Ignagni, who worked with Mortimer and Onders as project director and chief biomedical engineer, became a co-founder of Synapse and is currently president and CEO. Afferent Corp., Providence, RI, a manufacturer of sensory stimulation systems based on research at Boston University, Afferent's technology is based on work by James Collins, professor of biomedical engineering at Boston University, who showed that low-level stochastic, or random, vibrations improved sense of touch. Collins went on to demonstrate that generating a subthreshold noise in the sensory pathways with a random electrical stimulation improves detectability of weak mechanical stimuli. In 1999 entrepreneur Jason Harry licensed the stochastic resonance technology from Boston University and received help from the Community Technology Fund-the university's technology transfer incubator. NeuroNexus Technologies, Inc., Ann Arbor, MI, a manufacturer of implanted neural probes, based on a program at the University of Michigan. NeuroNexus was spun out of UM's Center for Neural Communications Technology. Daryl Kipke, head of the Neural Engineering Laboratory at the university, started up NeuroNexus with several colleagues and currently serves as president and CEO. Commercialization issues were discussed recently at a preconference workshop at the 2007 meeting of the International Neuromodulation Society in Acapulco, Mexico. In the session, which was chaired by Chris Coburn of the Cleveland Clinic, neurotech entrepreneurs John Bowers from Northstar Neuroscience and Ben Pless, formerly of NeuroPace, shared their experiences bringing neuromodulation therapies to market. Coburn related his observations from the Cleveland Clinic, which has spun off 22 companies over the last five years. He cited several factors that would influence a neurotech startup's market potential, such as identifying the regulatory pathway, any predicate devices that exist, and the revenue potential for

Stochastic Spiking Neural Networks Enabled by Magnetic Tunnel Junctions: From Nontelegraphic to Telegraphic Switching Regimes

Science.gov (United States)

Liyanagedera, Chamika M.; Sengupta, Abhronil; Jaiswal, Akhilesh; Roy, Kaushik

2017-12-01

Stochastic spiking neural networks based on nanoelectronic spin devices can be a possible pathway to achieving "brainlike" compact and energy-efficient cognitive intelligence. The computational model attempt to exploit the intrinsic device stochasticity of nanoelectronic synaptic or neural components to perform learning or inference. However, there has been limited analysis on the scaling effect of stochastic spin devices and its impact on the operation of such stochastic networks at the system level. This work attempts to explore the design space and analyze the performance of nanomagnet-based stochastic neuromorphic computing architectures for magnets with different barrier heights. We illustrate how the underlying network architecture must be modified to account for the random telegraphic switching behavior displayed by magnets with low barrier heights as they are scaled into the superparamagnetic regime. We perform a device-to-system-level analysis on a deep neural-network architecture for a digit-recognition problem on the MNIST data set.

A new method to estimate parameters of linear compartmental models using artificial neural networks

International Nuclear Information System (INIS)

Gambhir, Sanjiv S.; Keppenne, Christian L.; Phelps, Michael E.; Banerjee, Pranab K.

1998-01-01

At present, the preferred tool for parameter estimation in compartmental analysis is an iterative procedure; weighted nonlinear regression. For a large number of applications, observed data can be fitted to sums of exponentials whose parameters are directly related to the rate constants/coefficients of the compartmental models. Since weighted nonlinear regression often has to be repeated for many different data sets, the process of fitting data from compartmental systems can be very time consuming. Furthermore the minimization routine often converges to a local (as opposed to global) minimum. In this paper, we examine the possibility of using artificial neural networks instead of weighted nonlinear regression in order to estimate model parameters. We train simple feed-forward neural networks to produce as outputs the parameter values of a given model when kinetic data are fed to the networks' input layer. The artificial neural networks produce unbiased estimates and are orders of magnitude faster than regression algorithms. At noise levels typical of many real applications, the neural networks are found to produce lower variance estimates than weighted nonlinear regression in the estimation of parameters from mono- and biexponential models. These results are primarily due to the inability of weighted nonlinear regression to converge. These results establish that artificial neural networks are powerful tools for estimating parameters for simple compartmental models. (author)

Differences between otolith- and semicircular canal-activated neural circuitry in the vestibular system.

Science.gov (United States)

Uchino, Yoshio; Kushiro, Keisuke

2011-12-01

In the last two decades, we have focused on establishing a reliable technique for focal stimulation of vestibular receptors to evaluate neural connectivity. Here, we summarize the vestibular-related neuronal circuits for the vestibulo-ocular reflex, vestibulocollic reflex, and vestibulospinal reflex arcs. The focal stimulating technique also uncovered some hidden neural mechanisms. In the otolith system, we identified two hidden neural mechanisms that enhance otolith receptor sensitivity. The first is commissural inhibition, which boosts sensitivity by incorporating inputs from bilateral otolith receptors, the existence of which was in contradiction to the classical understanding of the otolith system but was observed in the utricular system. The second mechanism, cross-striolar inhibition, intensifies the sensitivity of inputs from both sides of receptive cells across the striola in a single otolith sensor. This was an entirely novel finding and is typically observed in the saccular system. We discuss the possible functional meaning of commissural and cross-striolar inhibition. Finally, our focal stimulating technique was applied to elucidate the different constructions of axonal projections from each vestibular receptor to the spinal cord. We also discuss the possible function of the unique neural connectivity observed in each vestibular receptor system. Copyright © 2011 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

Recurrent Convolutional Neural Networks: A Better Model of Biological Object Recognition.

Science.gov (United States)

Spoerer, Courtney J; McClure, Patrick; Kriegeskorte, Nikolaus

2017-01-01

Feedforward neural networks provide the dominant model of how the brain performs visual object recognition. However, these networks lack the lateral and feedback connections, and the resulting recurrent neuronal dynamics, of the ventral visual pathway in the human and non-human primate brain. Here we investigate recurrent convolutional neural networks with bottom-up (B), lateral (L), and top-down (T) connections. Combining these types of connections yields four architectures (B, BT, BL, and BLT), which we systematically test and compare. We hypothesized that recurrent dynamics might improve recognition performance in the challenging scenario of partial occlusion. We introduce two novel occluded object recognition tasks to test the efficacy of the models, digit clutter (where multiple target digits occlude one another) and digit debris (where target digits are occluded by digit fragments). We find that recurrent neural networks outperform feedforward control models (approximately matched in parametric complexity) at recognizing objects, both in the absence of occlusion and in all occlusion conditions. Recurrent networks were also found to be more robust to the inclusion of additive Gaussian noise. Recurrent neural networks are better in two respects: (1) they are more neurobiologically realistic than their feedforward counterparts; (2) they are better in terms of their ability to recognize objects, especially under challenging conditions. This work shows that computer vision can benefit from using recurrent convolutional architectures and suggests that the ubiquitous recurrent connections in biological brains are essential for task performance.

Cramp-fasciculation syndrome in patients with and without neural autoantibodies.

Science.gov (United States)

Liewluck, Teerin; Klein, Christopher J; Jones, Lyell K

2014-03-01

We investigated the clinical, electrophysiological and neural autoantibody characteristics in cramp-fasciculation syndrome (CFS) patients. We reviewed Mayo Clinic records from 2000 to 2011 to identify clinically defined CFS patients who underwent neural autoantibody testing. Stored sera of patients who tested positive for antibodies to voltage-gated potassium channel complex (VGKC complex) were analyzed further for leucine-rich glioma-inactivated 1 (LGI1) or contactin-associated protein-2 immunoglobulin G (CASPR2-IgG) antibodies. Thirty-seven patients were identified. Twelve were seropositive for neural autoantibodies. Clinical manifestations were similar in seropositive and seronegative patients, although central and autonomic neuronal hyperexcitability symptoms were more common in seropositive cases. No patients had a malignancy. Repetitive tibial nerve stimulation at 10 Hz revealed longer afterdischarges in seropositive patients. Two of 7 patients with VGKC-complex autoimmunity demonstrated LGI1 or CASPR2-IgG antibodies. Only 2 of 12 seropositive patients required immunotherapy. VGKC-complex autoimmunity occurs in a minority of CFS patients. Antibody positivity was associated with extramuscular manifestations, typically without malignancy. Target antigens within the VGKC complex remain unknown in most patients. Published 2013 by Wiley Periodicals, Inc. This article is a US Government work and, as such, is in the public domain in the United States of America.

Artificial neural network-based exploration of gene-nutrient interactions in folate and xenobiotic metabolic pathways that modulate susceptibility to breast cancer.

Science.gov (United States)

Naushad, Shaik Mohammad; Ramaiah, M Janaki; Pavithrakumari, Manickam; Jayapriya, Jaganathan; Hussain, Tajamul; Alrokayan, Salman A; Gottumukkala, Suryanarayana Raju; Digumarti, Raghunadharao; Kutala, Vijay Kumar

2016-04-15

In the current study, an artificial neural network (ANN)-based breast cancer prediction model was developed from the data of folate and xenobiotic pathway genetic polymorphisms along with the nutritional and demographic variables to investigate how micronutrients modulate susceptibility to breast cancer. The developed ANN model explained 94.2% variability in breast cancer prediction. Fixed effect models of folate (400 μg/day) and B12 (6 μg/day) showed 33.3% and 11.3% risk reduction, respectively. Multifactor dimensionality reduction analysis showed the following interactions in responders to folate: RFC1 G80A × MTHFR C677T (primary), COMT H108L × CYP1A1 m2 (secondary), MTR A2756G (tertiary). The interactions among responders to B12 were RFC1G80A × cSHMT C1420T and CYP1A1 m2 × CYP1A1 m4. ANN simulations revealed that increased folate might restore ER and PR expression and reduce the promoter CpG island methylation of extra cellular superoxide dismutase and BRCA1. Dietary intake of folate appears to confer protection against breast cancer through its modulating effects on ER and PR expression and methylation of EC-SOD and BRCA1. Copyright © 2016 Elsevier B.V. All rights reserved.

Selenomethionine promoted hippocampal neurogenesis via the PI3K-Akt-GSK3β-Wnt pathway in a mouse model of Alzheimer's disease

International Nuclear Information System (INIS)

Zheng, Rui; Zhang, Zhong-Hao; Chen, Chen; Chen, Yao; Jia, Shi-Zheng; Liu, Qiong; Ni, Jia-Zuan; Song, Guo-Li

2017-01-01

The maintenance of neural system integrity and function is the ultimate goal for the treatment of neurodegenerative disease such as Alzheimer's disease (AD). Neurogenesis plays an integral role in the maintenance of neural and cognitive functions, and its dysfunction is regarded as a major cause of cognitive impairment in AD. Moreover, the induction of neurogenesis by targeting endogenous neural stem cells (NSCs) is considered as one of the most promising treatment strategies. Our previous studies demonstrated that selenomethionine (Se-Met) was able to reduce β-amyloid peptide (Aβ) deposition, decrease Tau protein hyperphosphorylation and markedly improve cognitive functions in triple transgenic (3xTg) AD mice. In this study, we reported that the therapeutic effect of Se-Met on AD could also be due to neurogenesis modulation. By using the cultured hippocampal NSCs from 3xTg AD mice, we discovered that Se-Met (1–10 μM) with low concentration could promote NSC proliferation, while the one with a high concentration (50,100 μM) inhibiting proliferation. In subsequent studies, we also found that Se-Met activated the signaling pathway of PI3K/Akt, and thereby inhibited the GSK3β activity, which would further activated the β-catenin/Cyclin-D signaling pathway and promote NSC proliferation. Besides, after the induction of Se-Met, the number of neurons differentiated from NSCs significantly increased, and the number of astrocytes decreased. After a 90-day treatment with Se-Met (6 μg/mL), the number of hippocampal neurons in 4-month-old AD mice increased significantly, while the one of astrocyte saw a sharp drop. Thus, Se-Met treatment promoted NSCs differentiation into neurons, and subsequently repaired damaged neural systems in AD mice. Being consistent with our in vitro studies, Se-Met acts through the PI3K-Akt- GSK3β-Wnt signaling pathway in vivo. This study provides an unparalleled evidence that selenium (Se) compounds are, to some extent, effective

Neural modularity helps organisms evolve to learn new skills without forgetting old skills.

Science.gov (United States)

Ellefsen, Kai Olav; Mouret, Jean-Baptiste; Clune, Jeff

2015-04-01

A long-standing goal in artificial intelligence is creating agents that can learn a variety of different skills for different problems. In the artificial intelligence subfield of neural networks, a barrier to that goal is that when agents learn a new skill they typically do so by losing previously acquired skills, a problem called catastrophic forgetting. That occurs because, to learn the new task, neural learning algorithms change connections that encode previously acquired skills. How networks are organized critically affects their learning dynamics. In this paper, we test whether catastrophic forgetting can be reduced by evolving modular neural networks. Modularity intuitively should reduce learning interference between tasks by separating functionality into physically distinct modules in which learning can be selectively turned on or off. Modularity can further improve learning by having a reinforcement learning module separate from sensory processing modules, allowing learning to happen only in response to a positive or negative reward. In this paper, learning takes place via neuromodulation, which allows agents to selectively change the rate of learning for each neural connection based on environmental stimuli (e.g. to alter learning in specific locations based on the task at hand). To produce modularity, we evolve neural networks with a cost for neural connections. We show that this connection cost technique causes modularity, confirming a previous result, and that such sparsely connected, modular networks have higher overall performance because they learn new skills faster while retaining old skills more and because they have a separate reinforcement learning module. Our results suggest (1) that encouraging modularity in neural networks may help us overcome the long-standing barrier of networks that cannot learn new skills without forgetting old ones, and (2) that one benefit of the modularity ubiquitous in the brains of natural animals might be to

Neural modularity helps organisms evolve to learn new skills without forgetting old skills.

Directory of Open Access Journals (Sweden)

Kai Olav Ellefsen

2015-04-01

Full Text Available A long-standing goal in artificial intelligence is creating agents that can learn a variety of different skills for different problems. In the artificial intelligence subfield of neural networks, a barrier to that goal is that when agents learn a new skill they typically do so by losing previously acquired skills, a problem called catastrophic forgetting. That occurs because, to learn the new task, neural learning algorithms change connections that encode previously acquired skills. How networks are organized critically affects their learning dynamics. In this paper, we test whether catastrophic forgetting can be reduced by evolving modular neural networks. Modularity intuitively should reduce learning interference between tasks by separating functionality into physically distinct modules in which learning can be selectively turned on or off. Modularity can further improve learning by having a reinforcement learning module separate from sensory processing modules, allowing learning to happen only in response to a positive or negative reward. In this paper, learning takes place via neuromodulation, which allows agents to selectively change the rate of learning for each neural connection based on environmental stimuli (e.g. to alter learning in specific locations based on the task at hand. To produce modularity, we evolve neural networks with a cost for neural connections. We show that this connection cost technique causes modularity, confirming a previous result, and that such sparsely connected, modular networks have higher overall performance because they learn new skills faster while retaining old skills more and because they have a separate reinforcement learning module. Our results suggest (1 that encouraging modularity in neural networks may help us overcome the long-standing barrier of networks that cannot learn new skills without forgetting old ones, and (2 that one benefit of the modularity ubiquitous in the brains of natural animals

Surface electromyographic amplitude does not identify differences in neural drive to synergistic muscles.

Science.gov (United States)

Martinez-Valdes, Eduardo; Negro, Francesco; Falla, Deborah; De Nunzio, Alessandro Marco; Farina, Dario

2018-04-01

Surface electromyographic (EMG) signal amplitude is typically used to compare the neural drive to muscles. We experimentally investigated this association by studying the motor unit (MU) behavior and action potentials in the vastus medialis (VM) and vastus lateralis (VL) muscles. Eighteen participants performed isometric knee extensions at four target torques [10, 30, 50, and 70% of the maximum torque (MVC)] while high-density EMG signals were recorded from the VM and VL. The absolute EMG amplitude was greater for VM than VL ( P differences in EMG amplitude can be due to both differences in the neural drive and in the size of the MU action potentials, we indirectly inferred the neural drives received by the two muscles by estimating the synaptic inputs received by the corresponding motor neuron pools. For this purpose, we analyzed the increase in discharge rate from recruitment to target torque for motor units matched by recruitment threshold in the two muscles. This analysis indicated that the two muscles received similar levels of neural drive. Nonetheless, the size of the MU action potentials was greater for VM than VL ( P difference explained most of the differences in EMG amplitude between the two muscles (~63% of explained variance). These results indicate that EMG amplitude, even following normalization, does not reflect the neural drive to synergistic muscles. Moreover, absolute EMG amplitude is mainly explained by the size of MU action potentials. NEW & NOTEWORTHY Electromyographic (EMG) amplitude is widely used to compare indirectly the strength of neural drive received by synergistic muscles. However, there are no studies validating this approach with motor unit data. Here, we compared between-muscles differences in surface EMG amplitude and motor unit behavior. The results clarify the limitations of surface EMG to interpret differences in neural drive between muscles.

Neural Modularity Helps Organisms Evolve to Learn New Skills without Forgetting Old Skills

Science.gov (United States)

Ellefsen, Kai Olav; Mouret, Jean-Baptiste; Clune, Jeff

2015-01-01

A long-standing goal in artificial intelligence is creating agents that can learn a variety of different skills for different problems. In the artificial intelligence subfield of neural networks, a barrier to that goal is that when agents learn a new skill they typically do so by losing previously acquired skills, a problem called catastrophic forgetting. That occurs because, to learn the new task, neural learning algorithms change connections that encode previously acquired skills. How networks are organized critically affects their learning dynamics. In this paper, we test whether catastrophic forgetting can be reduced by evolving modular neural networks. Modularity intuitively should reduce learning interference between tasks by separating functionality into physically distinct modules in which learning can be selectively turned on or off. Modularity can further improve learning by having a reinforcement learning module separate from sensory processing modules, allowing learning to happen only in response to a positive or negative reward. In this paper, learning takes place via neuromodulation, which allows agents to selectively change the rate of learning for each neural connection based on environmental stimuli (e.g. to alter learning in specific locations based on the task at hand). To produce modularity, we evolve neural networks with a cost for neural connections. We show that this connection cost technique causes modularity, confirming a previous result, and that such sparsely connected, modular networks have higher overall performance because they learn new skills faster while retaining old skills more and because they have a separate reinforcement learning module. Our results suggest (1) that encouraging modularity in neural networks may help us overcome the long-standing barrier of networks that cannot learn new skills without forgetting old ones, and (2) that one benefit of the modularity ubiquitous in the brains of natural animals might be to

Chaotic diagonal recurrent neural network

International Nuclear Information System (INIS)

Wang Xing-Yuan; Zhang Yi

2012-01-01

We propose a novel neural network based on a diagonal recurrent neural network and chaos, and its structure and learning algorithm are designed. The multilayer feedforward neural network, diagonal recurrent neural network, and chaotic diagonal recurrent neural network are used to approach the cubic symmetry map. The simulation results show that the approximation capability of the chaotic diagonal recurrent neural network is better than the other two neural networks. (interdisciplinary physics and related areas of science and technology)

Computational modeling of neural plasticity for self-organization of neural networks.

Science.gov (United States)

Chrol-Cannon, Joseph; Jin, Yaochu

2014-11-01

Self-organization in biological nervous systems during the lifetime is known to largely occur through a process of plasticity that is dependent upon the spike-timing activity in connected neurons. In the field of computational neuroscience, much effort has been dedicated to building up computational models of neural plasticity to replicate experimental data. Most recently, increasing attention has been paid to understanding the role of neural plasticity in functional and structural neural self-organization, as well as its influence on the learning performance of neural networks for accomplishing machine learning tasks such as classification and regression. Although many ideas and hypothesis have been suggested, the relationship between the structure, dynamics and learning performance of neural networks remains elusive. The purpose of this article is to review the most important computational models for neural plasticity and discuss various ideas about neural plasticity's role. Finally, we suggest a few promising research directions, in particular those along the line that combines findings in computational neuroscience and systems biology, and their synergetic roles in understanding learning, memory and cognition, thereby bridging the gap between computational neuroscience, systems biology and computational intelligence. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

What Is Typical Is Good : The Influence of Face Typicality on Perceived Trustworthiness

NARCIS (Netherlands)

Sofer, Carmel; Dotsch, Ron; Wigboldus, Daniel H J; Todorov, Alexander

2015-01-01

The role of face typicality in face recognition is well established, but it is unclear whether face typicality is important for face evaluation. Prior studies have focused mainly on typicality’s influence on attractiveness, although recent studies have cast doubt on its importance for attractiveness

Logical knowledge representation of regulatory relations in biomedical pathways

DEFF Research Database (Denmark)

Zambach, Sine; Hansen, Jens Ulrik

2010-01-01

Knowledge on regulatory relations, in for example regulatory pathways in biology, is used widely in experiment design by biomedical researchers and in systems biology. The knowledge has typically either been represented through simple graphs or through very expressive differential equation...... simulations of smaller parts of a pathway. In this work we suggest a knowledge representation of the most basic relations in regulatory processes regulates, positively regulates and negatively regulates in logics based on a semantic analysis. We discuss the usage of these relations in biology and in articial...... intelligence for hypothesis development in drug discovery....

Induction of apoptotic death and retardation of neuronal differentiation of human neural stem cells by sodium arsenite treatment

Energy Technology Data Exchange (ETDEWEB)

Ivanov, Vladimir N., E-mail: vni3@columbia.edu [Center for Radiological Research, Department of Radiation Oncology, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, NY 10032 (United States); Hei, Tom K. [Center for Radiological Research, Department of Radiation Oncology, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, NY 10032 (United States)

2013-04-01

Chronic arsenic toxicity is a global health problem that affects more than 100 million people worldwide. Long-term health effects of inorganic sodium arsenite in drinking water may result in skin, lung and liver cancers and in severe neurological abnormalities. We investigated in the present study whether sodium arsenite affects signaling pathways that control cell survival, proliferation and neuronal differentiation of human neural stem cells (NSC). We demonstrated that the critical signaling pathway, which was suppressed by sodium arsenite in NSC, was the protective PI3K–AKT pathway. Sodium arsenite (2–4 μM) also caused down-regulation of Nanog, one of the key transcription factors that control pluripotency and self-renewal of stem cells. Mitochondrial damage and cytochrome-c release induced by sodium arsenite exposure was followed by initiation of the mitochondrial apoptotic pathway in NSC. Beside caspase-9 and caspase-3 inhibitors, suppression of JNK activity decreased levels of arsenite-induced apoptosis in NSC. Neuronal differentiation of NSC was substantially inhibited by sodium arsenite exposure. Overactivation of JNK1 and ERK1/2 and down-regulation of PI3K–AKT activity induced by sodium arsenite were critical factors that strongly affected neuronal differentiation. In conclusion, sodium arsenite exposure of human NSC induces the mitochondrial apoptotic pathway, which is substantially accelerated due to the simultaneous suppression of PI3K–AKT. Sodium arsenite also negatively affects neuronal differentiation of NSC through overactivation of MEK–ERK and suppression of PI3K–AKT. - Highlights: ► Arsenite induces the mitochondrial apoptotic pathway in human neural stem cells. ► Arsenite-induced apoptosis is strongly upregulated by suppression of PI3K–AKT. ► Arsenite-induced apoptosis is strongly down-regulated by inhibition of JNK–cJun. ► Arsenite negatively affects neuronal differentiation by inhibition of PI3K–AKT.

Induction of apoptotic death and retardation of neuronal differentiation of human neural stem cells by sodium arsenite treatment

International Nuclear Information System (INIS)

Ivanov, Vladimir N.; Hei, Tom K.

2013-01-01

Chronic arsenic toxicity is a global health problem that affects more than 100 million people worldwide. Long-term health effects of inorganic sodium arsenite in drinking water may result in skin, lung and liver cancers and in severe neurological abnormalities. We investigated in the present study whether sodium arsenite affects signaling pathways that control cell survival, proliferation and neuronal differentiation of human neural stem cells (NSC). We demonstrated that the critical signaling pathway, which was suppressed by sodium arsenite in NSC, was the protective PI3K–AKT pathway. Sodium arsenite (2–4 μM) also caused down-regulation of Nanog, one of the key transcription factors that control pluripotency and self-renewal of stem cells. Mitochondrial damage and cytochrome-c release induced by sodium arsenite exposure was followed by initiation of the mitochondrial apoptotic pathway in NSC. Beside caspase-9 and caspase-3 inhibitors, suppression of JNK activity decreased levels of arsenite-induced apoptosis in NSC. Neuronal differentiation of NSC was substantially inhibited by sodium arsenite exposure. Overactivation of JNK1 and ERK1/2 and down-regulation of PI3K–AKT activity induced by sodium arsenite were critical factors that strongly affected neuronal differentiation. In conclusion, sodium arsenite exposure of human NSC induces the mitochondrial apoptotic pathway, which is substantially accelerated due to the simultaneous suppression of PI3K–AKT. Sodium arsenite also negatively affects neuronal differentiation of NSC through overactivation of MEK–ERK and suppression of PI3K–AKT. - Highlights: ► Arsenite induces the mitochondrial apoptotic pathway in human neural stem cells. ► Arsenite-induced apoptosis is strongly upregulated by suppression of PI3K–AKT. ► Arsenite-induced apoptosis is strongly down-regulated by inhibition of JNK–cJun. ► Arsenite negatively affects neuronal differentiation by inhibition of PI3K–AKT

Crosstalk of Autophagy and the Secretory Pathway and Its Role in Diseases.

Science.gov (United States)

Zahoor, Muhammad; Farhan, Hesso

2018-01-01

The secretory and autophagic pathways are two fundamental, evolutionary highly conserved endomembrane processes. Typically, secretion is associated with biosynthesis and delivery of proteins. In contrast, autophagy is usually considered as a degradative pathway. Thus, an analogy to metabolic pathways is evident. Anabolic (biosynthetic) and catabolic (degradative) pathways are usually intimately linked and intertwined, and likewise, the secretory and autophagy pathways are intertwined. Investigation of this link is an emerging area of research, and we will provide an overview of some of the major advances that have been made to contribute to understanding of how secretion regulates autophagy and vice versa. Finally, we will highlight evidence that supports a potential involvement of the autophagy-secretion crosstalk in human diseases. © 2018 Elsevier Inc. All rights reserved.

Using deep neural networks to augment NIF post-shot analysis

Science.gov (United States)

Humbird, Kelli; Peterson, Luc; McClarren, Ryan; Field, John; Gaffney, Jim; Kruse, Michael; Nora, Ryan; Spears, Brian

2017-10-01

Post-shot analysis of National Ignition Facility (NIF) experiments is the process of determining which simulation inputs yield results consistent with experimental observations. This analysis is typically accomplished by running suites of manually adjusted simulations, or Monte Carlo sampling surrogate models that approximate the response surfaces of the physics code. These approaches are expensive and often find simulations that match only a small subset of observables simultaneously. We demonstrate an alternative method for performing post-shot analysis using inverse models, which map directly from experimental observables to simulation inputs with quantified uncertainties. The models are created using a novel machine learning algorithm which automates the construction and initialization of deep neural networks to optimize predictive accuracy. We show how these neural networks, trained on large databases of post-shot simulations, can rigorously quantify the agreement between simulation and experiment. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Developing a hippocampal neural prosthetic to facilitate human memory encoding and recall

Science.gov (United States)

Hampson, Robert E.; Song, Dong; Robinson, Brian S.; Fetterhoff, Dustin; Dakos, Alexander S.; Roeder, Brent M.; She, Xiwei; Wicks, Robert T.; Witcher, Mark R.; Couture, Daniel E.; Laxton, Adrian W.; Munger-Clary, Heidi; Popli, Gautam; Sollman, Myriam J.; Whitlow, Christopher T.; Marmarelis, Vasilis Z.; Berger, Theodore W.; Deadwyler, Sam A.

2018-06-01

Objective. We demonstrate here the first successful implementation in humans of a proof-of-concept system for restoring and improving memory function via facilitation of memory encoding using the patient’s own hippocampal spatiotemporal neural codes for memory. Memory in humans is subject to disruption by drugs, disease and brain injury, yet previous attempts to restore or rescue memory function in humans typically involved only nonspecific, modulation of brain areas and neural systems related to memory retrieval. Approach. We have constructed a model of processes by which the hippocampus encodes memory items via spatiotemporal firing of neural ensembles that underlie the successful encoding of short-term memory. A nonlinear multi-input, multi-output (MIMO) model of hippocampal CA3 and CA1 neural firing is computed that predicts activation patterns of CA1 neurons during the encoding (sample) phase of a delayed match-to-sample (DMS) human short-term memory task. Main results. MIMO model-derived electrical stimulation delivered to the same CA1 locations during the sample phase of DMS trials facilitated short-term/working memory by 37% during the task. Longer term memory retention was also tested in the same human subjects with a delayed recognition (DR) task that utilized images from the DMS task, along with images that were not from the task. Across the subjects, the stimulated trials exhibited significant improvement (35%) in both short-term and long-term retention of visual information. Significance. These results demonstrate the facilitation of memory encoding which is an important feature for the construction of an implantable neural prosthetic to improve human memory.

Using deep recurrent neural network for direct beam solar irradiance cloud screening

Science.gov (United States)

Chen, Maosi; Davis, John M.; Liu, Chaoshun; Sun, Zhibin; Zempila, Melina Maria; Gao, Wei

2017-09-01

Cloud screening is an essential procedure for in-situ calibration and atmospheric properties retrieval on (UV-)MultiFilter Rotating Shadowband Radiometer [(UV-)MFRSR]. Previous study has explored a cloud screening algorithm for direct-beam (UV-)MFRSR voltage measurements based on the stability assumption on a long time period (typically a half day or a whole day). To design such an algorithm requires in-depth understanding of radiative transfer and delicate data manipulation. Recent rapid developments on deep neural network and computation hardware have opened a window for modeling complicated End-to-End systems with a standardized strategy. In this study, a multi-layer dynamic bidirectional recurrent neural network is built for determining the cloudiness on each time point with a 17-year training dataset and tested with another 1-year dataset. The dataset is the daily 3-minute cosine corrected voltages, airmasses, and the corresponding cloud/clear-sky labels at two stations of the USDA UV-B Monitoring and Research Program. The results show that the optimized neural network model (3-layer, 250 hidden units, and 80 epochs of training) has an overall test accuracy of 97.87% (97.56% for the Oklahoma site and 98.16% for the Hawaii site). Generally, the neural network model grasps the key concept of the original model to use data in the entire day rather than short nearby measurements to perform cloud screening. A scrutiny of the logits layer suggests that the neural network model automatically learns a way to calculate a quantity similar to total optical depth and finds an appropriate threshold for cloud screening.

Epigenetics and Neural developmental disorders: Washington DC, September 18 and 19, 2006.

Science.gov (United States)

Zhao, Xinyu; Pak, ChangHui; Smrt, Richard D; Jin, Peng

2007-01-01

Neural developmental disorders, such as autism, Rett Syndrome, Fragile X syndrome, and Angelman syndrome manifest during early postnatal neural development. Although the genes responsible for some of these disorders have been identified, how the mutations of these genes affect neural development is currently unclear. Emerging evidence suggest that these disorders share common underlying defects in neuronal morphology, synaptic connectivity and brain plasticity. In particular, alterations in dendritic branching and spine morphology play a central role in the pathophysiology of most mental retardation disorders, suggesting that common pathways regulating neuronal function may be affected. Epigenetic modulations, mediated by DNA methylation, RNA-associated silencing, and histone modification, can serve as an intermediate process that imprints dynamic environmental experiences on the "fixed" genome, resulting in stable alterations in phenotypes. Disturbance in epigenetic regulations can lead to inappropriate expression or silencing of genes, causing an array of multi-system disorders and neoplasias. Rett syndrome, the most common form of mental retardation in young girls, is due to l mutation of MECP2, encoding a methylated DNA binding protein that translates DNA methylation into gene repression. Angelman syndrome is due to faulty genomic imprinting or maternal mutations in UBE3A. Fragile X Syndrome, in most cases, results from the hypermethylation of FMR1 promoter, hence the loss of expression of functional FMRP protein. Autism, with its complex etiology, may have strong epigenetic link. Together, these observations strongly suggest that epigenetic mechanisms may play a critical role in brain development and etiology of related disorders. This report summarizes the scientific discussions and major conclusions from a recent conference that aimed to gain insight into the common molecular pathways affected among these disorders and discover potential therapeutic targets

Neural Parallel Engine: A toolbox for massively parallel neural signal processing.

Science.gov (United States)

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.

A hybrid model based on neural networks for biomedical relation extraction.

Science.gov (United States)

Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian; Zhang, Shaowu; Sun, Yuanyuan; Yang, Liang

2018-05-01

Biomedical relation extraction can automatically extract high-quality biomedical relations from biomedical texts, which is a vital step for the mining of biomedical knowledge hidden in the literature. Recurrent neural networks (RNNs) and convolutional neural networks (CNNs) are two major neural network models for biomedical relation extraction. Neural network-based methods for biomedical relation extraction typically focus on the sentence sequence and employ RNNs or CNNs to learn the latent features from sentence sequences separately. However, RNNs and CNNs have their own advantages for biomedical relation extraction. Combining RNNs and CNNs may improve biomedical relation extraction. In this paper, we present a hybrid model for the extraction of biomedical relations that combines RNNs and CNNs. First, the shortest dependency path (SDP) is generated based on the dependency graph of the candidate sentence. To make full use of the SDP, we divide the SDP into a dependency word sequence and a relation sequence. Then, RNNs and CNNs are employed to automatically learn the features from the sentence sequence and the dependency sequences, respectively. Finally, the output features of the RNNs and CNNs are combined to detect and extract biomedical relations. We evaluate our hybrid model using five public (protein-protein interaction) PPI corpora and a (drug-drug interaction) DDI corpus. The experimental results suggest that the advantages of RNNs and CNNs in biomedical relation extraction are complementary. Combining RNNs and CNNs can effectively boost biomedical relation extraction performance. Copyright © 2018 Elsevier Inc. All rights reserved.

Discrimination of ex-core neutron noise signatures using artificial neural networks

International Nuclear Information System (INIS)

Alguindigue, I.E.; Uhrig, R.E.; Cai, M.; Trenty, A.

1993-01-01

The vibratory behavior of the internals in a Pressurized Water Reactor, PWR, can be identified and monitored using ex-core neutron noise data from power detectors located at ionization chambers outside the vessel. The signatures collected from these sensors provide information regarding presence of contacts between the core barrel and the pressure vessel, and more importantly, a means of verifying the integrity of components in the system. This report describes a neural-network-based methodology for identifying the vibration mode of the core barrel, and for detecting a particular family of mechanical failures. Features are extracted from the neutron noise spectra and used for training neural network models to identify the different states of vibratory behavior typically exhibited by PWR'S. The technique was tested on data from twenty eight 900MW pressurized water reactors in France, and the results achieved are over 98% accurate

Shindigs, brunches, and rodeos: the neural basis of event words.

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Bedny, Marina; Dravida, Swethasri; Saxe, Rebecca

2014-09-01

Events (e.g., "running" or "eating") constitute a basic type within human cognition and human language. We asked whether thinking about events, as compared to other conceptual categories, depends on partially independent neural circuits. Indirect evidence for this hypothesis comes from previous studies showing elevated posterior temporal responses to verbs, which typically label events. Neural responses to verbs could, however, be driven either by their grammatical or by their semantic properties. In the present experiment, we separated the effects of grammatical class (verb vs. noun) and semantic category (event vs. object) by measuring neural responses to event nouns (e.g., "the hurricane"). Participants rated the semantic relatedness of event nouns, as well as of two categories of object nouns-animals (e.g., "the alligator") and plants (e.g., "the acorn")-and three categories of verbs-manner of motion (e.g., "to roll"), emission (e.g., "to sparkle"), and perception (e.g., "to gaze"). As has previously been observed, we found larger responses to verbs than to object nouns in the left posterior middle (LMTG) and superior (LSTG) temporal gyri. Crucially, we also found that the LMTG responds more to event than to object nouns. These data suggest that part of the posterior lateral temporal response to verbs is driven by their semantic properties. By contrast, a more superior region, at the junction of the temporal and parietal cortices, responded more to verbs than to all nouns, irrespective of their semantic category. We concluded that the neural mechanisms engaged when thinking about event and object categories are partially dissociable.

Neuronal spike sorting based on radial basis function neural networks

Directory of Open Access Journals (Sweden)

Taghavi Kani M

2011-02-01

Full Text Available "nBackground: Studying the behavior of a society of neurons, extracting the communication mechanisms of brain with other tissues, finding treatment for some nervous system diseases and designing neuroprosthetic devices, require an algorithm to sort neuralspikes automatically. However, sorting neural spikes is a challenging task because of the low signal to noise ratio (SNR of the spikes. The main purpose of this study was to design an automatic algorithm for classifying neuronal spikes that are emitted from a specific region of the nervous system."n "nMethods: The spike sorting process usually consists of three stages: detection, feature extraction and sorting. We initially used signal statistics to detect neural spikes. Then, we chose a limited number of typical spikes as features and finally used them to train a radial basis function (RBF neural network to sort the spikes. In most spike sorting devices, these signals are not linearly discriminative. In order to solve this problem, the aforesaid RBF neural network was used."n "nResults: After the learning process, our proposed algorithm classified any arbitrary spike. The obtained results showed that even though the proposed Radial Basis Spike Sorter (RBSS reached to the same error as the previous methods, however, the computational costs were much lower compared to other algorithms. Moreover, the competitive points of the proposed algorithm were its good speed and low computational complexity."n "nConclusion: Regarding the results of this study, the proposed algorithm seems to serve the purpose of procedures that require real-time processing and spike sorting.

Neural chips, neural computers and application in high and superhigh energy physics experiments

International Nuclear Information System (INIS)

Nikityuk, N.M.; )

2001-01-01

Architecture peculiarity and characteristics of series of neural chips and neural computes used in scientific instruments are considered. Tendency of development and use of them in high energy and superhigh energy physics experiments are described. Comparative data which characterize the efficient use of neural chips for useful event selection, classification elementary particles, reconstruction of tracks of charged particles and for search of hypothesis Higgs particles are given. The characteristics of native neural chips and accelerated neural boards are considered [ru

Dynamic neural networking as a basis for plasticity in the control of heart rate.

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Kember, G; Armour, J A; Zamir, M

2013-01-21

A model is proposed in which the relationship between individual neurons within a neural network is dynamically changing to the effect of providing a measure of "plasticity" in the control of heart rate. The neural network on which the model is based consists of three populations of neurons residing in the central nervous system, the intrathoracic extracardiac nervous system, and the intrinsic cardiac nervous system. This hierarchy of neural centers is used to challenge the classical view that the control of heart rate, a key clinical index, resides entirely in central neuronal command (spinal cord, medulla oblongata, and higher centers). Our results indicate that dynamic networking allows for the possibility of an interplay among the three populations of neurons to the effect of altering the order of control of heart rate among them. This interplay among the three levels of control allows for different neural pathways for the control of heart rate to emerge under different blood flow demands or disease conditions and, as such, it has significant clinical implications because current understanding and treatment of heart rate anomalies are based largely on a single level of control and on neurons acting in unison as a single entity rather than individually within a (plastically) interconnected network. Copyright © 2012 Elsevier Ltd. All rights reserved.

A Feasibility Study for Perioperative Ventricular Tachycardia Prognosis and Detection and Noise Detection Using a Neural Network and Predictive Linear Operators

Science.gov (United States)

Moebes, T. A.

1994-01-01

To locate the accessory pathway(s) in preexicitation syndromes, epicardial and endocardial ventricular mapping is performed during anterograde ventricular activation via accessory pathway(s) from data originally received in signal form. As the number of channels increases, it is pertinent that more automated detection of coherent/incoherent signals is achieved as well as the prediction and prognosis of ventricular tachywardia (VT). Today's computers and computer program algorithms are not good in simple perceptual tasks such as recognizing a pattern or identifying a sound. This discrepancy, among other things, has been a major motivating factor in developing brain-based, massively parallel computing architectures. Neural net paradigms have proven to be effective at pattern recognition tasks. In signal processing, the picking of coherent/incoherent signals represents a pattern recognition task for computer systems. The picking of signals representing the onset ot VT also represents such a computer task. We attacked this problem by defining four signal attributes for each potential first maximal arrival peak and one signal attribute over the entire signal as input to a back propagation neural network. One attribute was the predicted amplitude value after the maximum amplitude over a data window. Then, by using a set of known (user selected) coherent/incoherent signals, and signals representing the onset of VT, we trained the back propagation network to recognize coherent/incoherent signals, and signals indicating the onset of VT. Since our output scheme involves a true or false decision, and since the output unit computes values between 0 and 1, we used a Fuzzy Arithmetic approach to classify data as coherent/incoherent signals. Furthermore, a Mean-Square Error Analysis was used to determine system stability. The neural net based picking coherent/incoherent signal system achieved high accuracy on picking coherent/incoherent signals on different patients. The system

Autism spectrum disorders and drug addiction: Common pathways, common molecules, distinct disorders?

Directory of Open Access Journals (Sweden)

Patrick E. Rothwell

2016-02-01

Full Text Available Autism spectrum disorders (ASDs and drug addiction do not share substantial comorbidity or obvious similarities in etiology or symptomatology. It is thus surprising that a number of recent studies implicate overlapping neural circuits and molecular signaling pathways in both disorders. The purpose of this review is to highlight this emerging intersection and consider implications for understanding the pathophysiology of these seemingly distinct disorders. One area of overlap involves neural circuits and neuromodulatory systems in the striatum and basal ganglia, which play an established role in addiction and reward but are increasingly implicated in clinical and preclinical studies of ASDs. A second area of overlap relates to molecules like Fragile X mental retardation protein (FMRP and methyl CpG-binding protein-2 (MECP2, which are best known for their contribution to the pathogenesis of syndromic ASDs, but have recently been shown to regulate behavioral and neurobiological responses to addictive drug exposure. These shared pathways and molecules point to common dimensions of behavioral dysfunction, including the repetition of behavioral patterns and aberrant reward processing. The synthesis of knowledge gained through parallel investigations of ASDs and addiction may inspire the design of new therapeutic interventions to correct common elements of striatal dysfunction.

Autism Spectrum Disorders and Drug Addiction: Common Pathways, Common Molecules, Distinct Disorders?

Science.gov (United States)

Rothwell, Patrick E

2016-01-01

Autism spectrum disorders (ASDs) and drug addiction do not share substantial comorbidity or obvious similarities in etiology or symptomatology. It is thus surprising that a number of recent studies implicate overlapping neural circuits and molecular signaling pathways in both disorders. The purpose of this review is to highlight this emerging intersection and consider implications for understanding the pathophysiology of these seemingly distinct disorders. One area of overlap involves neural circuits and neuromodulatory systems in the striatum and basal ganglia, which play an established role in addiction and reward but are increasingly implicated in clinical and preclinical studies of ASDs. A second area of overlap relates to molecules like Fragile X mental retardation protein (FMRP) and methyl CpG-binding protein-2 (MECP2), which are best known for their contribution to the pathogenesis of syndromic ASDs, but have recently been shown to regulate behavioral and neurobiological responses to addictive drug exposure. These shared pathways and molecules point to common dimensions of behavioral dysfunction, including the repetition of behavioral patterns and aberrant reward processing. The synthesis of knowledge gained through parallel investigations of ASDs and addiction may inspire the design of new therapeutic interventions to correct common elements of striatal dysfunction.

Neural tissue-spheres

DEFF Research Database (Denmark)

Andersen, Rikke K; Johansen, Mathias; Blaabjerg, Morten

2007-01-01

By combining new and established protocols we have developed a procedure for isolation and propagation of neural precursor cells from the forebrain subventricular zone (SVZ) of newborn rats. Small tissue blocks of the SVZ were dissected and propagated en bloc as free-floating neural tissue...... content, thus allowing experimental studies of neural precursor cells and their niche...

The nucleus accumbens 5-HTR₄-CART pathway ties anorexia to hyperactivity.

Science.gov (United States)

Jean, A; Laurent, L; Bockaert, J; Charnay, Y; Dusticier, N; Nieoullon, A; Barrot, M; Neve, R; Compan, V

2012-12-11

In mental diseases, the brain does not systematically adjust motor activity to feeding. Probably, the most outlined example is the association between hyperactivity and anorexia in Anorexia nervosa. The neural underpinnings of this 'paradox', however, are poorly elucidated. Although anorexia and hyperactivity prevail over self-preservation, both symptoms rarely exist independently, suggesting commonalities in neural pathways, most likely in the reward system. We previously discovered an addictive molecular facet of anorexia, involving production, in the nucleus accumbens (NAc), of the same transcripts stimulated in response to cocaine and amphetamine (CART) upon stimulation of the 5-HT(4) receptors (5-HTR(4)) or MDMA (ecstasy). Here, we tested whether this pathway predisposes not only to anorexia but also to hyperactivity. Following food restriction, mice are expected to overeat. However, selecting hyperactive and addiction-related animal models, we observed that mice lacking 5-HTR(1B) self-imposed food restriction after deprivation and still displayed anorexia and hyperactivity after ecstasy. Decryption of the mechanisms showed a gain-of-function of 5-HTR(4) in the absence of 5-HTR(1B), associated with CART surplus in the NAc and not in other brain areas. NAc-5-HTR(4) overexpression upregulated NAc-CART, provoked anorexia and hyperactivity. NAc-5-HTR(4) knockdown or blockade reduced ecstasy-induced hyperactivity. Finally, NAc-CART knockdown suppressed hyperactivity upon stimulation of the NAc-5-HTR(4). Additionally, inactivating NAc-5-HTR(4) suppressed ecstasy's preference, strengthening the rewarding facet of anorexia. In conclusion, the NAc-5-HTR(4)/CART pathway establishes a 'tight-junction' between anorexia and hyperactivity, suggesting the existence of a primary functional unit susceptible to limit overeating associated with resting following homeostasis rules.

Tactile spatial working memory activates the dorsal extrastriate cortical pathway in congenitally blind individuals.

Science.gov (United States)

Bonino, D; Ricciardi, E; Sani, L; Gentili, C; Vanello, N; Guazzelli, M; Vecchi, T; Pietrini, P

2008-09-01

In sighted individuals, both the visual and tactile version of the same spatial working memory task elicited neural responses in the dorsal "where" cortical pathway (Ricciardi et al., 2006). Whether the neural response during the tactile working memory task is due to visually-based spatial imagery or rather reflects a more abstract, supramodal organization of the dorsal cortical pathway remains to be determined. To understand the role of visual experience on the functional organization of the dorsal cortical stream, using functional magnetic resonance imaging (fMRI) here we examined brain response in four individuals with congenital or early blindness and no visual recollection, while they performed the same tactile spatial working memory task, a one-back recognition of 2D and 3D matrices. The blind subjects showed a significant activation in bilateral posterior parietal cortex, dorsolateral and inferior prefrontal areas, precuneus, lateral occipital cortex, and cerebellum. Thus, dorsal occipito-parietal areas are involved in mental imagery dealing with spatial components in subjects without prior visual experience and in response to a non-visual task. These data indicate that recruitment of the dorsal cortical pathway in response to the tactile spatial working memory task is not mediated by visually-based imagery and that visual experience is not a prerequisite for the development of a more abstract functional organization of the dorsal stream. These findings, along with previous data indicating a similar supramodal functional organization within the ventral cortical pathway and the motion processing brain regions, may contribute to explain how individuals who are born deprived of sight are able to interact effectively with the surrounding world.

Regulation of Msx genes by a Bmp gradient is essential for neural crest specification.

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Tribulo, Celeste; Aybar, Manuel J; Nguyen, Vu H; Mullins, Mary C; Mayor, Roberto

2003-12-01

There is evidence in Xenopus and zebrafish embryos that the neural crest/neural folds are specified at the border of the neural plate by a precise threshold concentration of a Bmp gradient. In order to understand the molecular mechanism by which a gradient of Bmp is able to specify the neural crest, we analyzed how the expression of Bmp targets, the Msx genes, is regulated and the role that Msx genes has in neural crest specification. As Msx genes are directly downstream of Bmp, we analyzed Msx gene expression after experimental modification in the level of Bmp activity by grafting a bead soaked with noggin into Xenopus embryos, by expressing in the ectoderm a dominant-negative Bmp4 or Bmp receptor in Xenopus and zebrafish embryos, and also through Bmp pathway component mutants in the zebrafish. All the results show that a reduction in the level of Bmp activity leads to an increase in the expression of Msx genes in the neural plate border. Interestingly, by reaching different levels of Bmp activity in animal cap ectoderm, we show that a specific concentration of Bmp induces msx1 expression to a level similar to that required to induce neural crest. Our results indicate that an intermediate level of Bmp activity specifies the expression of Msx genes in the neural fold region. In addition, we have analyzed the role that msx1 plays on neural crest specification. As msx1 has a role in dorsoventral pattering, we have carried out conditional gain- and loss-of-function experiments using different msx1 constructs fused to a glucocorticoid receptor element to avoid an early effect of this factor. We show that msx1 expression is able to induce all other early neural crest markers tested (snail, slug, foxd3) at the time of neural crest specification. Furthermore, the expression of a dominant negative of Msx genes leads to the inhibition of all the neural crest markers analyzed. It has been previously shown that snail is one of the earliest genes acting in the neural crest

Effects of Chronic Low-Dose Radiation on Human Neural Progenitor Cells

Science.gov (United States)

Katsura, Mari; Cyou-Nakamine, Hiromasa; Zen, Qin; Zen, Yang; Nansai, Hiroko; Amagasa, Shota; Kanki, Yasuharu; Inoue, Tsuyoshi; Kaneki, Kiyomi; Taguchi, Akashi; Kobayashi, Mika; Kaji, Toshiyuki; Kodama, Tatsuhiko; Miyagawa, Kiyoshi; Wada, Youichiro; Akimitsu, Nobuyoshi; Sone, Hideko

2016-01-01

The effects of chronic low-dose radiation on human health have not been well established. Recent studies have revealed that neural progenitor cells are present not only in the fetal brain but also in the adult brain. Since immature cells are generally more radiosensitive, here we investigated the effects of chronic low-dose radiation on cultured human neural progenitor cells (hNPCs) derived from embryonic stem cells. Radiation at low doses of 31, 124 and 496 mGy per 72 h was administered to hNPCs. The effects were estimated by gene expression profiling with microarray analysis as well as morphological analysis. Gene expression was dose-dependently changed by radiation. By thirty-one mGy of radiation, inflammatory pathways involving interferon signaling and cell junctions were altered. DNA repair and cell adhesion molecules were affected by 124 mGy of radiation while DNA synthesis, apoptosis, metabolism, and neural differentiation were all affected by 496 mGy of radiation. These in vitro results suggest that 496 mGy radiation affects the development of neuronal progenitor cells while altered gene expression was observed at a radiation dose lower than 100 mGy. This study would contribute to the elucidation of the clinical and subclinical phenotypes of impaired neuronal development induced by chronic low-dose radiation.

Fast analysis of spectral data using neural networks

International Nuclear Information System (INIS)

Roach, C.M.

1992-01-01

Fast analysis techniques are highly desirable in experiments where measurements are recorded at high rates. In fusion experiments the processing required to obtain plasma parameters is usually orders of magnitude slower than the data acquisition. Spectroscopic diagnostics suffer greatly from this problem. The extraction of plasma parameters from a measured spectrum typically corresponds to a nonlinear mapping between distinct multi-dimensional spaces. Where no analytic expression for the mapping exists, conventional analysis methods (e.g. least squares) are usually iterative and therefore slow. With this concern in mind a fast spectral analysis method involving neural networks has been investigated. (author) 6 refs., 3 figs

An improved genetic algorithm for designing optimal temporal patterns of neural stimulation

Science.gov (United States)

Cassar, Isaac R.; Titus, Nathan D.; Grill, Warren M.

2017-12-01

Objective. Electrical neuromodulation therapies typically apply constant frequency stimulation, but non-regular temporal patterns of stimulation may be more effective and more efficient. However, the design space for temporal patterns is exceedingly large, and model-based optimization is required for pattern design. We designed and implemented a modified genetic algorithm (GA) intended for design optimal temporal patterns of electrical neuromodulation. Approach. We tested and modified standard GA methods for application to designing temporal patterns of neural stimulation. We evaluated each modification individually and all modifications collectively by comparing performance to the standard GA across three test functions and two biophysically-based models of neural stimulation. Main results. The proposed modifications of the GA significantly improved performance across the test functions and performed best when all were used collectively. The standard GA found patterns that outperformed fixed-frequency, clinically-standard patterns in biophysically-based models of neural stimulation, but the modified GA, in many fewer iterations, consistently converged to higher-scoring, non-regular patterns of stimulation. Significance. The proposed improvements to standard GA methodology reduced the number of iterations required for convergence and identified superior solutions.

Exploring the role of neural mirroring in children with autism spectrum disorder.

Science.gov (United States)

Ruysschaert, Lieselot; Warreyn, Petra; Wiersema, Jan R; Oostra, Ann; Roeyers, Herbert

2014-04-01

Investigating the underlying neural mechanisms of autism spectrum disorder (ASD) has recently been influenced by the discovery of mirror neurons. These neurons, active during both observation and execution of actions, are thought to play a crucial role in imitation and other social-communicative skills that are often impaired in ASD. In the current electroencephalographic study, we investigated mu suppression, indicating neural mirroring in children with ASD between the ages of 24 and 48 months and age-matched typically developing children, during observation of goal-directed actions and non-goal-directed mimicked hand movements, as well as during action execution. Results revealed no significant group differences with significant central mu suppression in the ASD children and control children during both execution and observation of goal-directed actions and during observation of hand movements. Furthermore, no significant correlations between mu suppression on one hand and quality of imitation, age, and social communication questionnaire scores on the other hand were found. These findings challenge the "broken mirror" hypothesis of ASD, suggesting that impaired neural mirroring is not a distinctive feature of ASD. © 2014 International Society for Autism Research, Wiley Periodicals, Inc.

A neural network driving curve generation method for the heavy-haul train

Directory of Open Access Journals (Sweden)

Youneng Huang

2016-05-01

Full Text Available The heavy-haul train has a series of characteristics, such as the locomotive traction properties, the longer length of train, and the nonlinear train pipe pressure during train braking. When the train is running on a continuous long and steep downgrade railway line, the safety of the train is ensured by cycle braking, which puts high demands on the driving skills of the driver. In this article, a driving curve generation method for the heavy-haul train based on a neural network is proposed. First, in order to describe the nonlinear characteristics of train braking, the neural network model is constructed and trained by practical driving data. In the neural network model, various nonlinear neurons are interconnected to work for information processing and transmission. The target value of train braking pressure reduction and release time is achieved by modeling the braking process. The equation of train motion is computed to obtain the driving curve. Finally, in four typical operation scenarios, comparing the curve data generated by the method with corresponding practical data of the Shuohuang heavy-haul railway line, the results show that the method is effective.

White matter integrity deficits in prefrontal-amygdala pathways in Williams syndrome.

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Avery, Suzanne N; Thornton-Wells, Tricia A; Anderson, Adam W; Blackford, Jennifer Urbano

2012-01-16

Williams syndrome is a neurodevelopmental disorder associated with significant non-social fears. Consistent with this elevated non-social fear, individuals with Williams syndrome have an abnormally elevated amygdala response when viewing threatening non-social stimuli. In typically-developing individuals, amygdala activity is inhibited through dense, reciprocal white matter connections with the prefrontal cortex. Neuroimaging studies suggest a functional uncoupling of normal prefrontal-amygdala inhibition in individuals with Williams syndrome, which might underlie both the extreme amygdala activity and non-social fears. This functional uncoupling might be caused by structural deficits in underlying white matter pathways; however, prefrontal-amygdala white matter deficits have yet to be explored in Williams syndrome. We used diffusion tensor imaging to investigate prefrontal-amygdala white matter integrity differences in individuals with Williams syndrome and typically-developing controls with high levels of non-social fear. White matter pathways between the amygdala and several prefrontal regions were isolated using probabilistic tractography. Within each pathway, we tested for between-group differences in three measures of white matter integrity: fractional anisotropy (FA), radial diffusivity (RD), and parallel diffusivity (λ(1)). Individuals with Williams syndrome had lower FA, compared to controls, in several of the prefrontal-amygdala pathways investigated, indicating a reduction in white matter integrity. Lower FA in Williams syndrome was explained by significantly higher RD, with no differences in λ(1), suggestive of lower fiber density or axon myelination in prefrontal-amygdala pathways. These results suggest that deficits in the structural integrity of prefrontal-amygdala white matter pathways might underlie the increased amygdala activity and extreme non-social fears observed in Williams syndrome. Copyright © 2011 Elsevier Inc. All rights reserved.

Early brain response to low-dose radiation exposure involves molecular networks and pathways associated with cognitive functions, advanced aging and Alzheimer's disease.

Science.gov (United States)

Lowe, Xiu R; Bhattacharya, Sanchita; Marchetti, Francesco; Wyrobek, Andrew J

2009-01-01

Understanding the cognitive and behavioral consequences of brain exposures to low-dose ionizing radiation has broad relevance for health risks from medical radiation diagnostic procedures, radiotherapy and environmental nuclear contamination as well as for Earth-orbit and space missions. Analyses of transcriptome profiles of mouse brain tissue after whole-body irradiation showed that low-dose exposures (10 cGy) induced genes not affected by high-dose radiation (2 Gy) and that low-dose genes were associated with unique pathways and functions. The low-dose response had two major components: pathways that are consistently seen across tissues and pathways that were specific for brain tissue. Low-dose genes clustered into a saturated network (P < 10(-53)) containing mostly down-regulated genes involving ion channels, long-term potentiation and depression, vascular damage, etc. We identified nine neural signaling pathways that showed a high degree of concordance in their transcriptional response in mouse brain tissue after low-dose irradiation, in the aging human brain (unirradiated), and in brain tissue from patients with Alzheimer's disease. Mice exposed to high-dose radiation did not show these effects and associations. Our findings indicate that the molecular response of the mouse brain within a few hours after low-dose irradiation involves the down-regulation of neural pathways associated with cognitive dysfunctions that are also down-regulated in normal human aging and Alzheimer's disease.

Early Brain Response to Low-Dose Radiation Exposure Involves Molecular Networks and Pathways Associated with Cognitive Functions, Advanced Aging and Alzheimer's Disease

International Nuclear Information System (INIS)

Lowe, Xiu R.; Bhattacharya, Sanchita; Marchetti, Francesco; Wyrobek, Andrew J.

2008-01-01

Understanding the cognitive and behavioral consequences of brain exposures to low-dose ionizing radiation has broad relevance for health risks from medical radiation diagnostic procedures, radiotherapy, environmental nuclear contamination, as well as earth orbit and space missions. Analyses of transcriptome profiles of murine brain tissue after whole-body radiation showed that low-dose exposures (10 cGy) induced genes not affected by high dose (2 Gy), and low-dose genes were associated with unique pathways and functions. The low-dose response had two major components: pathways that are consistently seen across tissues, and pathways that were brain tissue specific. Low-dose genes clustered into a saturated network (p -53 ) containing mostly down-regulated genes involving ion channels, long-term potentiation and depression, vascular damage, etc. We identified 9 neural signaling pathways that showed a high degree of concordance in their transcriptional response in mouse brain tissue after low-dose radiation, in the aging human brain (unirradiated), and in brain tissue from patients with Alzheimer's disease. Mice exposed to high-dose radiation did not show these effects and associations. Our findings indicate that the molecular response of the mouse brain within a few hours after low-dose irradiation involves the down-regulation of neural pathways associated with cognitive dysfunctions that are also down regulated in normal human aging and Alzheimer's disease

Leptin-dependent neurotoxicity via induction of apoptosis in adult rat neural stem cells

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Stéphanie eSEGURA

2015-09-01

Full Text Available Adipocyte-derived hormone leptin has been recently implicated in the control of neuronal plasticity. To explore whether modulation of adult neurogenesis may contribute to leptin control of neuronal plasticity, we used the neurosphere assay of neural stem cells derived from the adult rat subventricular zone (SVZ. Endogenous expression of specific leptin receptor (ObRb transcripts, as revealed by RT-PCR, is associated with activation of both ERK and STAT-3 pathways via phosphorylation of the critical ERK/STAT-3 amino acid residues upon addition of leptin to neurospheres. Furthermore, leptin triggered withdrawal of neural stem cells from the cell cycle as monitored by Ki67 labelling. This effect was blocked by pharmacological inhibition of ERK activation thus demonstrating that ERK mediates leptin effects on neural stem cell expansion. Leptin-dependent withdrawal of neural stem cells from the cell cycle was associated with increased apoptosis, as detected by TUNEL, which was preceded by cyclin D1 induction. Cyclin D1 was indeed extensively colocalized with TUNEL-positive apoptotic cells. Cyclin-D1 silencing by specific shRNA prevented leptin-induced decrease of the cell number per neurosphere thus pointing to the causal relationship between leptin actions on apoptosis and cyclin D1 induction. Leptin target cells in SVZ neurospheres were identified by double TUNEL/phenotypic marker immunocytofluorescence as differentiating neurons mostly. The inhibition of neural stem cell expansion via ERK/cyclin D1-triggered apoptosis defines novel biological action of leptin which may be involved in adiposity-dependent neurotoxicity.

ETOH inhibits embryonic neural stem/precursor cell proliferation via PLD signaling

International Nuclear Information System (INIS)

Fujita, Yuko; Hiroyama, Masami; Sanbe, Atsushi; Yamauchi, Junji; Murase, Shoko; Tanoue, Akito

2008-01-01

While a mother's excessive alcohol consumption during pregnancy is known to have adverse effects on fetal neural development, little is known about the underlying mechanism of these effects. In order to investigate these mechanisms, we investigated the toxic effect of ethanol (ETOH) on neural stem/precursor cell (NSC) proliferation. In cultures of NSCs, phospholipase D (PLD) is activated following stimulation with epidermal growth factor (EGF) and fibroblast growth factor 2 (FGF2). Exposure of NSCs to ETOH suppresses cell proliferation, while it has no effect on cell death. Phosphatidic acid (PA), which is a signaling messenger produced by PLD, reverses ETOH inhibition of NSC proliferation. Blocking the PLD signal by 1-butanol suppresses the proliferation. ETOH-induced suppression of NSC proliferation and the protective effect of PA for ETOH-induced suppression are mediated through extracellular signal-regulated kinase signaling. These results indicate that exposure to ETOH impairs NSC proliferation by altering the PLD signaling pathway

PLZF regulates fibroblast growth factor responsiveness and maintenance of neural progenitors.

Science.gov (United States)

Gaber, Zachary B; Butler, Samantha J; Novitch, Bennett G

2013-10-01

Distinct classes of neurons and glial cells in the developing spinal cord arise at specific times and in specific quantities from spatially discrete neural progenitor domains. Thus, adjacent domains can exhibit marked differences in their proliferative potential and timing of differentiation. However, remarkably little is known about the mechanisms that account for this regional control. Here, we show that the transcription factor Promyelocytic Leukemia Zinc Finger (PLZF) plays a critical role shaping patterns of neuronal differentiation by gating the expression of Fibroblast Growth Factor (FGF) Receptor 3 and responsiveness of progenitors to FGFs. PLZF elevation increases FGFR3 expression and STAT3 pathway activity, suppresses neurogenesis, and biases progenitors towards glial cell production. In contrast, PLZF loss reduces FGFR3 levels, leading to premature neuronal differentiation. Together, these findings reveal a novel transcriptional strategy for spatially tuning the responsiveness of distinct neural progenitor groups to broadly distributed mitogenic signals in the embryonic environment.

A mutation in the tuft mouse disrupts TET1 activity and alters the expression of genes that are crucial for neural tube closure

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Keith S. K. Fong

2016-05-01

Full Text Available Genetic variations affecting neural tube closure along the head result in malformations of the face and brain. Neural tube defects (NTDs are among the most common birth defects in humans. We previously reported a mouse mutant called tuft that arose spontaneously in our wild-type 3H1 colony. Adult tuft mice present midline craniofacial malformations with or without an anterior cephalocele. In addition, affected embryos presented neural tube closure defects resulting in insufficient closure of the anterior neuropore or exencephaly. Here, through whole-genome sequencing, we identified a nonsense mutation in the Tet1 gene, which encodes a methylcytosine dioxygenase (TET1, co-segregating with the tuft phenotype. This mutation resulted in premature termination that disrupts the catalytic domain that is involved in the demethylation of cytosine. We detected a significant loss of TET enzyme activity in the heads of tuft embryos that were homozygous for the mutation and had NTDs. RNA-Seq transcriptome analysis indicated that multiple gene pathways associated with neural tube closure were dysregulated in tuft embryo heads. Among them, the expressions of Cecr2, Epha7 and Grhl2 were significantly reduced in some embryos presenting neural tube closure defects, whereas one or more components of the non-canonical WNT signaling pathway mediating planar cell polarity and convergent extension were affected in others. We further show that the recombinant mutant TET1 protein was capable of entering the nucleus and affected the expression of endogenous Grhl2 in IMCD-3 (inner medullary collecting duct cells. These results indicate that TET1 is an epigenetic determinant for regulating genes that are crucial to closure of the anterior neural tube and its mutation has implications to craniofacial development, as presented by the tuft mouse.

Is our Universe typical?

International Nuclear Information System (INIS)

Gurzadyan, V.G.

1988-01-01

The problem of typicalness of the Universe - as a dynamical system possessing both regular and chaotic regions of positive measure of phase space, is raised and discussed. Two dynamical systems are considered: 1) The observed Universe as a hierarchy of systems of N graviting bodies; 2) (3+1)-manifold with matter evolving to Wheeler-DeWitt equation in superspace with Hawking boundary condition of compact metrics. It is shown that the observed Universe is typical. There is no unambiguous answer for the second system yet. If it is typical too then the same present state of the Universe could have been originated from an infinite number of different initial conditions the restoration of which is practically impossible at present. 35 refs.; 2 refs

Neural systems underlying aversive conditioning in humans with primary and secondary reinforcers

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Mauricio R Delgado

2011-05-01

Full Text Available Money is a secondary reinforcer commonly used across a range of disciplines in experimental paradigms investigating reward learning and decision-making. The effectiveness of monetary reinforcers during aversive learning and its neural basis, however, remains a topic of debate. Specifically, it is unclear if the initial acquisition of aversive representations of monetary losses depends on similar neural systems as more traditional aversive conditioning that involves primary reinforcers. This study contrasts the efficacy of a biologically defined primary reinforcer (shock and a socially defined secondary reinforcer (money during aversive learning and its associated neural circuitry. During a two-part experiment, participants first played a gambling game where wins and losses were based on performance to gain an experimental bank. Participants were then exposed to two separate aversive conditioning sessions. In one session, a primary reinforcer (mild shock served as an unconditioned stimulus (US and was paired with one of two colored squares, the conditioned stimuli (CS+ and CS-, respectively. In another session, a secondary reinforcer (loss of money served as the US and was paired with one of two different CS. Skin conductance responses were greater for CS+ compared to CS- trials irrespective of type of reinforcer. Neuroimaging results revealed that the striatum, a region typically linked with reward-related processing, was found to be involved in the acquisition of aversive conditioned response irrespective of reinforcer type. In contrast, the amygdala was involved during aversive conditioning with primary reinforcers, as suggested by both an exploratory fMRI analysis and a follow-up case study with a patient with bilateral amygdala damage. Taken together, these results suggest that learning about potential monetary losses may depend on reinforcement learning related systems, rather than on typical structures involved in more biologically based

Microglia modulate hippocampal neural precursor activity in response to exercise and aging.

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Vukovic, Jana; Colditz, Michael J; Blackmore, Daniel G; Ruitenberg, Marc J; Bartlett, Perry F

2012-05-09

Exercise has been shown to positively augment adult hippocampal neurogenesis; however, the cellular and molecular pathways mediating this effect remain largely unknown. Previous studies have suggested that microglia may have the ability to differentially instruct neurogenesis in the adult brain. Here, we used transgenic Csf1r-GFP mice to investigate whether hippocampal microglia directly influence the activation of neural precursor cells. Our results revealed that an exercise-induced increase in neural precursor cell activity was mediated via endogenous microglia and abolished when these cells were selectively removed from hippocampal cultures. Conversely, microglia from the hippocampi of animals that had exercised were able to activate latent neural precursor cells when added to neurosphere preparations from sedentary mice. We also investigated the role of CX(3)CL1, a chemokine that is known to provide a more neuroprotective microglial phenotype. Intraparenchymal infusion of a blocking antibody against the CX(3)CL1 receptor, CX(3)CR1, but not control IgG, dramatically reduced the neurosphere formation frequency in mice that had exercised. While an increase in soluble CX(3)CL1 was observed following running, reduced levels of this chemokine were found in the aged brain. Lower levels of CX(3)CL1 with advancing age correlated with the natural decline in neural precursor cell activity, a state that could be partially alleviated through removal of microglia. These findings provide the first direct evidence that endogenous microglia can exert a dual and opposing influence on neural precursor cell activity within the hippocampus, and that signaling through the CX(3)CL1-CX(3)CR1 axis critically contributes toward this process.

Integrating the behavioral and neural dynamics of response selection in a dual-task paradigm: a dynamic neural field model of Dux et al. (2009).

Science.gov (United States)

Buss, Aaron T; Wifall, Tim; Hazeltine, Eliot; Spencer, John P

2014-02-01

People are typically slower when executing two tasks than when only performing a single task. These dual-task costs are initially robust but are reduced with practice. Dux et al. (2009) explored the neural basis of dual-task costs and learning using fMRI. Inferior frontal junction (IFJ) showed a larger hemodynamic response on dual-task trials compared with single-task trial early in learning. As dual-task costs were eliminated, dual-task hemodynamics in IFJ reduced to single-task levels. Dux and colleagues concluded that the reduction of dual-task costs is accomplished through increased efficiency of information processing in IFJ. We present a dynamic field theory of response selection that addresses two questions regarding these results. First, what mechanism leads to the reduction of dual-task costs and associated changes in hemodynamics? We show that a simple Hebbian learning mechanism is able to capture the quantitative details of learning at both the behavioral and neural levels. Second, is efficiency isolated to cognitive control areas such as IFJ, or is it also evident in sensory motor areas? To investigate this, we restrict Hebbian learning to different parts of the neural model. None of the restricted learning models showed the same reductions in dual-task costs as the unrestricted learning model, suggesting that efficiency is distributed across cognitive control and sensory motor processing systems.

DANoC: An Efficient Algorithm and Hardware Codesign of Deep Neural Networks on Chip.

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Zhou, Xichuan; Li, Shengli; Tang, Fang; Hu, Shengdong; Lin, Zhi; Zhang, Lei

2017-07-18

Deep neural networks (NNs) are the state-of-the-art models for understanding the content of images and videos. However, implementing deep NNs in embedded systems is a challenging task, e.g., a typical deep belief network could exhaust gigabytes of memory and result in bandwidth and computational bottlenecks. To address this challenge, this paper presents an algorithm and hardware codesign for efficient deep neural computation. A hardware-oriented deep learning algorithm, named the deep adaptive network, is proposed to explore the sparsity of neural connections. By adaptively removing the majority of neural connections and robustly representing the reserved connections using binary integers, the proposed algorithm could save up to 99.9% memory utility and computational resources without undermining classification accuracy. An efficient sparse-mapping-memory-based hardware architecture is proposed to fully take advantage of the algorithmic optimization. Different from traditional Von Neumann architecture, the deep-adaptive network on chip (DANoC) brings communication and computation in close proximity to avoid power-hungry parameter transfers between on-board memory and on-chip computational units. Experiments over different image classification benchmarks show that the DANoC system achieves competitively high accuracy and efficiency comparing with the state-of-the-art approaches.

Typicals/Típicos

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Silvia Vélez

2004-01-01

Full Text Available Typicals is a series of 12 colour photographs digitally created from photojournalistic images from Colombia combined with "typical" craft textiles and text from guest writers. Typicals was first exhibited as photographs 50cm x 75cm in size, each with their own magnifying glass, at the Contemporary Art Space at Gorman House in Canberra, Australia, in 2000. It was then exhibited in "Feedback: Art Social Consciousness and Resistance" at Monash University Museum of Art in Melbourne, Australia, from March to May 2003. From May to June 2003 it was exhibited at the Museo de Arte de la Universidad Nacional de Colombia Santa Fé Bogotá, Colombia. In its current manifestation the artwork has been adapted from the catalogue of the museum exhibitions. It is broken up into eight pieces corresponding to the contributions of the writers. The introduction by Sylvia Vélez is the PDF file accessible via a link below this abstract. The other seven PDF files are accessible via the 'Supplementary Files' section to the left of your screen. Please note that these files are around 4 megabytes each, so it may be difficult to access them from a dial-up connection.

Understanding the role of speech production in reading: Evidence for a print-to-speech neural network using graphical analysis.

Science.gov (United States)

Cummine, Jacqueline; Cribben, Ivor; Luu, Connie; Kim, Esther; Bahktiari, Reyhaneh; Georgiou, George; Boliek, Carol A

2016-05-01

The neural circuitry associated with language processing is complex and dynamic. Graphical models are useful for studying complex neural networks as this method provides information about unique connectivity between regions within the context of the entire network of interest. Here, the authors explored the neural networks during covert reading to determine the role of feedforward and feedback loops in covert speech production. Brain activity of skilled adult readers was assessed in real word and pseudoword reading tasks with functional MRI (fMRI). The authors provide evidence for activity coherence in the feedforward system (inferior frontal gyrus-supplementary motor area) during real word reading and in the feedback system (supramarginal gyrus-precentral gyrus) during pseudoword reading. Graphical models provided evidence of an extensive, highly connected, neural network when individuals read real words that relied on coordination of the feedforward system. In contrast, when individuals read pseudowords the authors found a limited/restricted network that relied on coordination of the feedback system. Together, these results underscore the importance of considering multiple pathways and articulatory loops during language tasks and provide evidence for a print-to-speech neural network. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A multi-pathway model for photosynthetic reaction center

International Nuclear Information System (INIS)

Qin, M.; Shen, H. Z.; Yi, X. X.

2016-01-01

Charge separation occurs in a pair of tightly coupled chlorophylls at the heart of photosynthetic reaction centers of both plants and bacteria. Recently it has been shown that quantum coherence can, in principle, enhance the efficiency of a solar cell, working like a quantum heat engine. Here, we propose a biological quantum heat engine (BQHE) motivated by Photosystem II reaction center (PSII RC) to describe the charge separation. Our model mainly considers two charge-separation pathways which is more than that typically considered in the published literature. We explore how these cross-couplings increase the current and power of the charge separation and discuss the effects of multiple pathways in terms of current and power. The robustness of the BQHE against the charge recombination in natural PSII RC and dephasing induced by environments is also explored, and extension from two pathways to multiple pathways is made. These results suggest that noise-induced quantum coherence helps to suppress the influence of acceptor-to-donor charge recombination, and besides, nature-mimicking architectures with engineered multiple pathways for charge separations might be better for artificial solar energy devices considering the influence of environments.

The evolution of the pathway and its role in improving patient care.

Science.gov (United States)

Mould, G; Bowers, J; Ghattas, M

2010-10-01

Redesign in healthcare has increased the focus on the needs of the patient. The redesign process typically involves a review of current practice using the patient pathway before considering possible improvements. The patient pathway can serve various roles, and it may be mapped in different ways using a variety of media. This paper reviews the evolution of the patient pathway comparing the merits of different media. Simple approaches to mapping pathways can be most useful. However, experience in the redesign of Unscheduled Care in NHS Fife suggests that computer-based, hierarchical pathway models using stylised icons offer many advantages. Such approaches can increase the effectiveness of pathways in the redesign process, providing both the detail and the system view in an accessible graphical form. This enhanced capability helps staff analyse current practice and visualise and assess redesign options. In addition, the pathway can fulfil new roles as a training tool and an effective basis for organising knowledge about patient care.

Medical Concept Normalization in Social Media Posts with Recurrent Neural Networks.

Science.gov (United States)

Tutubalina, Elena; Miftahutdinov, Zulfat; Nikolenko, Sergey; Malykh, Valentin

2018-06-12

Text mining of scientific libraries and social media has already proven itself as a reliable tool for drug repurposing and hypothesis generation. The task of mapping a disease mention to a concept in a controlled vocabulary, typically to the standard thesaurus in the Unified Medical Language System (UMLS), is known as medical concept normalization. This task is challenging due to the differences in the use of medical terminology between health care professionals and social media texts coming from the lay public. To bridge this gap, we use sequence learning with recurrent neural networks and semantic representation of one- or multi-word expressions: we develop end-to-end architectures directly tailored to the task, including bidirectional Long Short-Term Memory, Gated Recurrent Units with an attention mechanism, and additional semantic similarity features based on UMLS. Our evaluation against a standard benchmark shows that recurrent neural networks improve results over an effective baseline for classification based on convolutional neural networks. A qualitative examination of mentions discovered in a dataset of user reviews collected from popular online health information platforms as well as a quantitative evaluation both show improvements in the semantic representation of health-related expressions in social media. Copyright © 2018. Published by Elsevier Inc.

Inferring the functional effect of gene expression changes in signaling pathways

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Sebastián-León, Patricia; Carbonell, José; Salavert, Francisco; Sanchez, Rubén; Medina, Ignacio; Dopazo, Joaquín

2013-01-01

Signaling pathways constitute a valuable source of information that allows interpreting the way in which alterations in gene activities affect to particular cell functionalities. There are web tools available that allow viewing and editing pathways, as well as representing experimental data on them. However, few methods aimed to identify the signaling circuits, within a pathway, associated to the biological problem studied exist and none of them provide a convenient graphical web interface. We present PATHiWAYS, a web-based signaling pathway visualization system that infers changes in signaling that affect cell functionality from the measurements of gene expression values in typical expression microarray case–control experiments. A simple probabilistic model of the pathway is used to estimate the probabilities for signal transmission from any receptor to any final effector molecule (taking into account the pathway topology) using for this the individual probabilities of gene product presence/absence inferred from gene expression values. Significant changes in these probabilities allow linking different cell functionalities triggered by the pathway to the biological problem studied. PATHiWAYS is available at: http://pathiways.babelomics.org/. PMID:23748960

NEURAL PAIN PATHWAY TRACING OF RABBIT ISCHEMIC HEART BY DOUBLE-RETROGRADE NEUROTRACING

OpenAIRE

Theodorus Dapamede; Obed Trinurcahyo Kinantyo Paundralingga; Masruroh Rahayu; Bambang Soemantri

2015-01-01

Background. Myocardial ischaemia occurs due to inadequate supply of oxygen to fulfill the myocardial tissue oxygen demand. This leads to angina pectoris or referred pain, whichhappens because of the inability of the brain to distinguish the visceral afferent inputs from the somatic afferent inputs since they run along a common pathway via the dorsal root ganglia. Aims. This study aims to distinguish specific areas of the rabbit heart that are projected to specific dorsal root ganglia, whic...

Neural networks for aircraft control

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Linse, Dennis

1990-01-01

Current research in Artificial Neural Networks indicates that networks offer some potential advantages in adaptation and fault tolerance. This research is directed at determining the possible applicability of neural networks to aircraft control. The first application will be to aircraft trim. Neural network node characteristics, network topology and operation, neural network learning and example histories using neighboring optimal control with a neural net are discussed.

Brain acetylcholinesterase activity controls systemic cytokine levels through the cholinergic anti-inflammatory pathway

Science.gov (United States)

Pavlov, Valentin A.; Parrish, William R.; Rosas-Ballina, Mauricio; Ochani, Mahendar; Puerta, Margot; Ochani, Kanta; Chavan, Sangeeta; Al-Abed, Yousef; Tracey, Kevin J.

2015-01-01

The excessive release of cytokines by the immune system contributes importantly to the pathogenesis of inflammatory diseases. Recent advances in understanding the biology of cytokine toxicity led to the discovery of the “cholinergic anti-inflammatory pathway,” defined as neural signals transmitted via the vagus nerve that inhibit cytokine release through a mechanism that requires the alpha7 subunit-containing nicotinic acetylcholine receptor (α7nAChR). Vagus nerve regulation of peripheral functions is controlled by brain nuclei and neural networks, but despite considerable importance, little is known about the molecular basis for central regulation of the vagus nerve-based cholinergic anti-inflammatory pathway. Here we report that brain acetylcholinesterase activity controls systemic and organ specific TNF production during endotoxemia. Peripheral administration of the acetylcholinesterase inhibitor galantamine significantly reduced serum TNF levels through vagus nerve signaling, and protected against lethality during murine endotoxemia. Administration of a centrally-acting muscarinic receptor antagonist abolished the suppression of TNF by galantamine, indicating that suppressing acetylcholinesterase activity, coupled with central muscarinic receptors, controls peripheral cytokine responses. Administration of galantamine to α7nAChR knockout mice failed to suppress TNF levels, indicating that the α7nAChR-mediated cholinergic anti-inflammatory pathway is required for the anti-inflammatory effect of galantamine. These findings show that inhibition of brain acetylcholinesterase suppresses systemic inflammation through a central muscarinic receptor-mediated and vagal- and α7nAChR-dependent mechanism. Our data also indicate that a clinically used centrally-acting acetylcholinesterase inhibitor can be utilized to suppress abnormal inflammation to therapeutic advantage. PMID:18639629

Pupillary Response and Phenotype in ASD: Latency to Constriction Discriminates ASD from Typically Developing Adolescents.

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Lynch, Georgina T F; James, Stephen M; VanDam, Mark

2018-02-01

Brain imaging data describe differences in the ASD brain, including amygdala overgrowth, neural interconnectivity, and a three-phase model of neuroanatomical changes from early post-natal development through late adolescence. The pupil reflex test (PRT), a noninvasive measure of brain function, may help improve early diagnosis and elucidate underlying physiology in expression of ASD endophenotype. Commonly observed characteristics of ASD include normal visual acuity but difficulty with eye gaze and photosensitivity, suggesting deficient neuromodulation of cranial nerves. Aims of this study were to confirm sensitivity of the PRT for identifying adolescents with ASD, determine if a phenotype for a subtype of ASD marked by pupil response is present in adolescence, and determine whether differences could be observed on a neurologic exam testing cranial nerves II and III (CNII; CNIII). Using pupillometry, constriction latency was measured serving as a proxy for recording neuromodulation of cranial nerves underlying the pupillary reflex. The swinging flashlight method, used to perform the PRT for measuring constriction latency and return to baseline, discriminated ASD participants from typically developing adolescents on 72.2% of trials. Results further confirmed this measure's sensitivity within a subtype of ASD in later stages of development, serving as a correlate of neural activity within the locus-coeruleus norepinephrine (LC-NE) system. A brainstem model of atypical PRT in ASD is examined in relation to modulation of cranial nerves and atypical arousal levels subserving the atypical pupillary reflex. Autism Res 2018, 11: 364-375. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. Milder forms of autism spectrum disorder (ASD) can be difficult to diagnose based on behavioral testing alone. This study used eye-tracking equipment and a hand-held penlight to measure the pupil reflex in adolescents with "high functioning" ASD and in adolescents

The Neural Border: Induction, Specification and Maturation of the territory that generates Neural Crest cells.

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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.

Artificial neural networks for control of a grid-connected rectifier/inverter under disturbance, dynamic and power converter switching conditions.

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Li, Shuhui; Fairbank, Michael; Johnson, Cameron; Wunsch, Donald C; Alonso, Eduardo; Proaño, Julio L

2014-04-01

Three-phase grid-connected converters are widely used in renewable and electric power system applications. Traditionally, grid-connected converters are controlled with standard decoupled d-q vector control mechanisms. However, recent studies indicate that such mechanisms show limitations in their applicability to dynamic systems. This paper investigates how to mitigate such restrictions using a neural network to control a grid-connected rectifier/inverter. The neural network implements a dynamic programming algorithm and is trained by using back-propagation through time. To enhance performance and stability under disturbance, additional strategies are adopted, including the use of integrals of error signals to the network inputs and the introduction of grid disturbance voltage to the outputs of a well-trained network. The performance of the neural-network controller is studied under typical vector control conditions and compared against conventional vector control methods, which demonstrates that the neural vector control strategy proposed in this paper is effective. Even in dynamic and power converter switching environments, the neural vector controller shows strong ability to trace rapidly changing reference commands, tolerate system disturbances, and satisfy control requirements for a faulted power system.

Neural correlates of socioeconomic status in the developing human brain.

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Noble, Kimberly G; Houston, Suzanne M; Kan, Eric; Sowell, Elizabeth R

2012-07-01

Socioeconomic disparities in childhood are associated with remarkable differences in cognitive and socio-emotional development during a time when dramatic changes are occurring in the brain. Yet, the neurobiological pathways through which socioeconomic status (SES) shapes development remain poorly understood. Behavioral evidence suggests that language, memory, social-emotional processing, and cognitive control exhibit relatively large differences across SES. Here we investigated whether volumetric differences could be observed across SES in several neural regions that support these skills. In a sample of 60 socioeconomically diverse children, highly significant SES differences in regional brain volume were observed in the hippocampus and the amygdala. In addition, SES × age interactions were observed in the left superior temporal gyrus and left inferior frontal gyrus, suggesting increasing SES differences with age in these regions. These results were not explained by differences in gender, race or IQ. Likely mechanisms include differences in the home linguistic environment and exposure to stress, which may serve as targets for intervention at a time of high neural plasticity. © 2012 Blackwell Publishing Ltd.

The Orphan Nuclear Receptor TLX/NR2E1 in Neural Stem Cells and Diseases

OpenAIRE

Wang, Tao; Xiong, Jian-Qiong

2016-01-01

The human TLX gene encodes an orphan nuclear receptor predominantly expressed in the central nervous system. Tailess and Tlx, the TLX homologues in Drosophila and mouse, play essential roles in body-pattern formation and neurogenesis during early embryogenesis and perform crucial functions in maintaining stemness and controlling the differentiation of adult neural stem cells in the central nervous system, especially the visual system. Multiple target genes and signaling pathways are regulated...

Neural network regulation driven by autonomous neural firings

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Cho, Myoung Won

2016-07-01

Biological neurons naturally fire spontaneously due to the existence of a noisy current. Such autonomous firings may provide a driving force for network formation because synaptic connections can be modified due to neural firings. Here, we study the effect of autonomous firings on network formation. For the temporally asymmetric Hebbian learning, bidirectional connections lose their balance easily and become unidirectional ones. Defining the difference between reciprocal connections as new variables, we could express the learning dynamics as if Ising model spins interact with each other in magnetism. We present a theoretical method to estimate the interaction between the new variables in a neural system. We apply the method to some network systems and find some tendencies of autonomous neural network regulation.

Why we can talk, debate, and change our minds: neural circuits, basal ganglia operations, and transcriptional factors.

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Lieberman, Philip

2014-12-01

Ackermann et al. disregard attested knowledge concerning aphasia, Parkinson disease, cortical-to-striatal circuits, basal ganglia, laryngeal phonation, and other matters. Their dual-pathway model cannot account for "what is special about the human brain." Their human cortical-to-laryngeal neural circuit does not exist. Basal ganglia operations, enhanced by mutations on FOXP2, confer human motor-control, linguistic, and cognitive capabilities.

Brief Report: Robo1 Regulates the Migration of Human Subventricular Zone Neural Progenitor Cells During Development.

Science.gov (United States)

Guerrero-Cazares, Hugo; Lavell, Emily; Chen, Linda; Schiapparelli, Paula; Lara-Velazquez, Montserrat; Capilla-Gonzalez, Vivian; Clements, Anna Christina; Drummond, Gabrielle; Noiman, Liron; Thaler, Katrina; Burke, Anne; Quiñones-Hinojosa, Alfredo

2017-07-01

Human neural progenitor cell (NPC) migration within the subventricular zone (SVZ) of the lateral ganglionic eminence is an active process throughout early brain development. The migration of human NPCs from the SVZ to the olfactory bulb during fetal stages resembles what occurs in adult rodents. As the human brain develops during infancy, this migratory stream is drastically reduced in cell number and becomes barely evident in adults. The mechanisms regulating human NPC migration are unknown. The Slit-Robo signaling pathway has been defined as a chemorepulsive cue involved in axon guidance and neuroblast migration in rodents. Slit and Robo proteins expressed in the rodent brain help guide neuroblast migration from the SVZ through the rostral migratory stream to the olfactory bulb. Here, we present the first study on the role that Slit and Robo proteins play in human-derived fetal neural progenitor cell migration (hfNPC). We describe that Robo1 and Robo2 isoforms are expressed in the human fetal SVZ. Furthermore, we demonstrate that Slit2 is able to induce a chemorepellent effect on the migration of hfNPCs derived from the human fetal SVZ. In addition, when Robo1 expression is inhibited, hfNPCs are unable to migrate to the olfactory bulb of mice when injected in the anterior SVZ. Our findings indicate that the migration of human NPCs from the SVZ is partially regulated by the Slit-Robo axis. This pathway could be regulated to direct the migration of NPCs in human endogenous neural cell therapy. Stem Cells 2017;35:1860-1865. © 2017 AlphaMed Press.

Growth of the Developing Cerebral Cortex Is Controlled by MicroRNA-7 through the p53 Pathway

Directory of Open Access Journals (Sweden)

Andrew Pollock

2014-05-01

Full Text Available Proper growth of the mammalian cerebral cortex is crucial for normal brain functions and is controlled by precise gene-expression regulation. Here, we show that microRNA-7 (miR-7 is highly expressed in cortical neural progenitors and describe miR-7 sponge transgenic mice in which miR-7-silencing activity is specifically knocked down in the embryonic cortex. Blocking miR-7 function causes microcephaly-like brain defects due to reduced intermediate progenitor (IP production and apoptosis. Upregulation of miR-7 target genes, including those implicated in the p53 pathway, such as Ak1 and Cdkn1a (p21, is responsible for abnormalities in neural progenitors. Furthermore, ectopic expression of Ak1 or p21 and specific blockade of miR-7 binding sites in target genes using protectors in vivo induce similarly reduced IP production. Using conditional miRNA sponge transgenic approaches, we uncovered an unexpected role for miR-7 in cortical growth through its interactions with genes in the p53 pathway.

MicroRNA let-7d regulates the TLX/microRNA-9 cascade to control neural cell fate and neurogenesis.

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Zhao, Chunnian; Sun, GuoQiang; Ye, Peng; Li, Shengxiu; Shi, Yanhong

2013-01-01

MicroRNAs have important functions in the nervous system through post-transcriptional regulation of neurogenesis genes. Here we show that microRNA let-7d, which has been implicated in cocaine addiction and other neurological disorders, targets the neural stem cell regulator TLX. Overexpression of let-7d in vivo reduced neural stem cell proliferation and promoted premature neuronal differentiation and migration, a phenotype similar to those induced by TLX knockdown or overexpression of its negatively-regulated target, microRNA-9. We found a let-7d binding sequence in the tlx 3' UTR and demonstrated that let-7d reduced TLX expression levels in neural stem cells, which in turn, up-regulated miR-9 expression. Moreover, co-expression of let-7d and TLX lacking its 3' UTR in vivo restored neural stem cell proliferation and reversed the premature neuronal differentiation and migration. Therefore, manipulating let-7d and its downstream targets could be a novel strategy to unravel neurogenic signaling pathways and identify potential interventions for relevant neurological disorders.

Dynamics of neural cryptography.

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Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido

2007-05-01

Synchronization of neural networks has been used for public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchronization and unidirectional learning is driven by attractive and repulsive stochastic forces. Thus it can be described well by a random walk model for the overlap between participating neural networks. For that purpose transition probabilities and scaling laws for the step sizes are derived analytically. Both these calculations as well as numerical simulations show that bidirectional interaction leads to full synchronization on average. In contrast, successful learning is only possible by means of fluctuations. Consequently, synchronization is much faster than learning, which is essential for the security of the neural key-exchange protocol. However, this qualitative difference between bidirectional and unidirectional interaction vanishes if tree parity machines with more than three hidden units are used, so that those neural networks are not suitable for neural cryptography. In addition, the effective number of keys which can be generated by the neural key-exchange protocol is calculated using the entropy of the weight distribution. As this quantity increases exponentially with the system size, brute-force attacks on neural cryptography can easily be made unfeasible.

Dynamics of neural cryptography

International Nuclear Information System (INIS)

Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido

2007-01-01

Synchronization of neural networks has been used for public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchronization and unidirectional learning is driven by attractive and repulsive stochastic forces. Thus it can be described well by a random walk model for the overlap between participating neural networks. For that purpose transition probabilities and scaling laws for the step sizes are derived analytically. Both these calculations as well as numerical simulations show that bidirectional interaction leads to full synchronization on average. In contrast, successful learning is only possible by means of fluctuations. Consequently, synchronization is much faster than learning, which is essential for the security of the neural key-exchange protocol. However, this qualitative difference between bidirectional and unidirectional interaction vanishes if tree parity machines with more than three hidden units are used, so that those neural networks are not suitable for neural cryptography. In addition, the effective number of keys which can be generated by the neural key-exchange protocol is calculated using the entropy of the weight distribution. As this quantity increases exponentially with the system size, brute-force attacks on neural cryptography can easily be made unfeasible

Dynamics of neural cryptography

Science.gov (United States)

Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido

2007-05-01

Synchronization of neural networks has been used for public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchronization and unidirectional learning is driven by attractive and repulsive stochastic forces. Thus it can be described well by a random walk model for the overlap between participating neural networks. For that purpose transition probabilities and scaling laws for the step sizes are derived analytically. Both these calculations as well as numerical simulations show that bidirectional interaction leads to full synchronization on average. In contrast, successful learning is only possible by means of fluctuations. Consequently, synchronization is much faster than learning, which is essential for the security of the neural key-exchange protocol. However, this qualitative difference between bidirectional and unidirectional interaction vanishes if tree parity machines with more than three hidden units are used, so that those neural networks are not suitable for neural cryptography. In addition, the effective number of keys which can be generated by the neural key-exchange protocol is calculated using the entropy of the weight distribution. As this quantity increases exponentially with the system size, brute-force attacks on neural cryptography can easily be made unfeasible.

Bioprinting for Neural Tissue Engineering.

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Knowlton, Stephanie; Anand, Shivesh; Shah, Twisha; Tasoglu, Savas

2018-01-01

Bioprinting is a method by which a cell-encapsulating bioink is patterned to create complex tissue architectures. Given the potential impact of this technology on neural research, we review the current state-of-the-art approaches for bioprinting neural tissues. While 2D neural cultures are ubiquitous for studying neural cells, 3D cultures can more accurately replicate the microenvironment of neural tissues. By bioprinting neuronal constructs, one can precisely control the microenvironment by specifically formulating the bioink for neural tissues, and by spatially patterning cell types and scaffold properties in three dimensions. We review a range of bioprinted neural tissue models and discuss how they can be used to observe how neurons behave, understand disease processes, develop new therapies and, ultimately, design replacement tissues. Copyright © 2017 Elsevier Ltd. All rights reserved.

Neural correlates of the difference between working memory speed and simple sensorimotor speed: an fMRI study.

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Hikaru Takeuchi

Full Text Available The difference between the speed of simple cognitive processes and the speed of complex cognitive processes has various psychological correlates. However, the neural correlates of this difference have not yet been investigated. In this study, we focused on working memory (WM for typical complex cognitive processes. Functional magnetic resonance imaging data were acquired during the performance of an N-back task, which is a measure of WM for typical complex cognitive processes. In our N-back task, task speed and memory load were varied to identify the neural correlates responsible for the difference between the speed of simple cognitive processes (estimated from the 0-back task and the speed of WM. Our findings showed that this difference was characterized by the increased activation in the right dorsolateral prefrontal cortex (DLPFC and the increased functional interaction between the right DLPFC and right superior parietal lobe. Furthermore, the local gray matter volume of the right DLPFC was correlated with participants' accuracy during fast WM tasks, which in turn correlated with a psychometric measure of participants' intelligence. Our findings indicate that the right DLPFC and its related network are responsible for the execution of the fast cognitive processes involved in WM. Identified neural bases may underlie the psychometric differences between the speed with which subjects perform simple cognitive tasks and the speed with which subjects perform more complex cognitive tasks, and explain the previous traditional psychological findings.

Adolescence and Reward: Making Sense of Neural and Behavioral Changes Amid the Chaos.

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Walker, Deena M; Bell, Margaret R; Flores, Cecilia; Gulley, Joshua M; Willing, Jari; Paul, Matthew J

2017-11-08

Adolescence is a time of significant neural and behavioral change with remarkable development in social, emotional, and cognitive skills. It is also a time of increased exploration and risk-taking (e.g., drug use). Many of these changes are thought to be the result of increased reward-value coupled with an underdeveloped inhibitory control, and thus a hypersensitivity to reward. Perturbations during adolescence can alter the developmental trajectory of the brain, resulting in long-term alterations in reward-associated behaviors. This review highlights recent developments in our understanding of how neural circuits, pubertal hormones, and environmental factors contribute to adolescent-typical reward-associated behaviors with a particular focus on sex differences, the medial prefrontal cortex, social reward, social isolation, and drug use. We then introduce a new approach that makes use of natural adaptations of seasonally breeding species to investigate the role of pubertal hormones in adolescent development. This research has only begun to parse out contributions of the many neural, endocrine, and environmental changes to the heightened reward sensitivity and increased vulnerability to mental health disorders that characterize this life stage. Copyright © 2017 the authors 0270-6474/17/3710855-12$15.00/0.

Modeling of chemical exergy of agricultural biomass using improved general regression neural network

International Nuclear Information System (INIS)

Huang, Y.W.; Chen, M.Q.; Li, Y.; Guo, J.

2016-01-01

A comprehensive evaluation for energy potential contained in agricultural biomass was a vital step for energy utilization of agricultural biomass. The chemical exergy of typical agricultural biomass was evaluated based on the second law of thermodynamics. The chemical exergy was significantly influenced by C and O elements rather than H element. The standard entropy of the samples also was examined based on their element compositions. Two predicted models of the chemical exergy were developed, which referred to a general regression neural network model based upon the element composition, and a linear model based upon the high heat value. An auto-refinement algorithm was firstly developed to improve the performance of regression neural network model. The developed general regression neural network model with K-fold cross-validation had a better ability for predicting the chemical exergy than the linear model, which had lower predicted errors (±1.5%). - Highlights: • Chemical exergies of agricultural biomass were evaluated based upon fifty samples. • Values for the standard entropy of agricultural biomass samples were calculated. • A linear relationship between chemical exergy and HHV of samples was detected. • An improved GRNN prediction model for the chemical exergy of biomass was developed.

Reorganization of Functional Brain Maps After Exercise Training: Importance of Cerebellar-Thalamic-Cortical Pathway

OpenAIRE

Holschneider, DP; Yang, J; Guo, Y; Maarek, J-M I

2007-01-01

Exercise training (ET) causes functional and morphologic changes in normal and injured brain. While studies have examined effects of short-term (same day) training on functional brain activation, less work has evaluated effects of long-term training, in particular treadmill running. An improved understanding is relevant as changes in neural reorganization typically require days to weeks, and treadmill training is a component of many neurorehabilitation programs.

Early Brain Response to Low-Dose Radiation Exposure Involves Molecular Networks and Pathways Associated with Cognitive Functions, Advanced Aging and Alzheimer's Disease

Energy Technology Data Exchange (ETDEWEB)

Lowe, Xiu R; Bhattacharya, Sanchita; Marchetti, Francesco; Wyrobek, Andrew J.

2008-06-06

Understanding the cognitive and behavioral consequences of brain exposures to low-dose ionizing radiation has broad relevance for health risks from medical radiation diagnostic procedures, radiotherapy, environmental nuclear contamination, as well as earth orbit and space missions. Analyses of transcriptome profiles of murine brain tissue after whole-body radiation showed that low-dose exposures (10 cGy) induced genes not affected by high dose (2 Gy), and low-dose genes were associated with unique pathways and functions. The low-dose response had two major components: pathways that are consistently seen across tissues, and pathways that were brain tissue specific. Low-dose genes clustered into a saturated network (p < 10{sup -53}) containing mostly down-regulated genes involving ion channels, long-term potentiation and depression, vascular damage, etc. We identified 9 neural signaling pathways that showed a high degree of concordance in their transcriptional response in mouse brain tissue after low-dose radiation, in the aging human brain (unirradiated), and in brain tissue from patients with Alzheimer's disease. Mice exposed to high-dose radiation did not show these effects and associations. Our findings indicate that the molecular response of the mouse brain within a few hours after low-dose irradiation involves the down-regulation of neural pathways associated with cognitive dysfunctions that are also down regulated in normal human aging and Alzheimer's disease.

NAD+ salvage pathway in cancer metabolism and therapy.

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Kennedy, Barry E; Sharif, Tanveer; Martell, Emma; Dai, Cathleen; Kim, Youra; Lee, Patrick W K; Gujar, Shashi A

2016-12-01

Nicotinamide adenine dinucleotide (NAD + ) is an essential coenzyme for various physiological processes including energy metabolism, DNA repair, cell growth, and cell death. Many of these pathways are typically dysregulated in cancer cells, making NAD + an intriguing target for cancer therapeutics. NAD + is mainly synthesized by the NAD + salvage pathway in cancer cells, and not surprisingly, the pharmacological targeting of the NAD + salvage pathway causes cancer cell cytotoxicity in vitro and in vivo. Several studies have described the precise consequences of NAD + depletion on cancer biology, and have demonstrated that NAD+ depletion results in depletion of energy levels through lowered rates of glycolysis, reduced citric acid cycle activity, and decreased oxidative phosphorylation. Additionally, depletion of NAD + causes sensitization of cancer cells to oxidative damage by disruption of the anti-oxidant defense system, decreased cell proliferation, and initiation of cell death through manipulation of cell signaling pathways (e.g., SIRT1 and p53). Recently, studies have explored the effect of well-known cancer therapeutics in combination with pharmacological depletion of NAD + levels, and found in many cases a synergistic effect on cancer cell cytotoxicity. In this context, we will discuss the effects of NAD + salvage pathway inhibition on cancer cell biology and provide insight on this pathway as a novel anti-cancer therapeutic target. Copyright © 2016 Elsevier Ltd. All rights reserved.

Time Multiplexed Active Neural Probe with 1356 Parallel Recording Sites

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Bogdan C. Raducanu

2017-10-01

Full Text Available We present a high electrode density and high channel count CMOS (complementary metal-oxide-semiconductor active neural probe containing 1344 neuron sized recording pixels (20 µm × 20 µm and 12 reference pixels (20 µm × 80 µm, densely packed on a 50 µm thick, 100 µm wide, and 8 mm long shank. The active electrodes or pixels consist of dedicated in-situ circuits for signal source amplification, which are directly located under each electrode. The probe supports the simultaneous recording of all 1356 electrodes with sufficient signal to noise ratio for typical neuroscience applications. For enhanced performance, further noise reduction can be achieved while using half of the electrodes (678. Both of these numbers considerably surpass the state-of-the art active neural probes in both electrode count and number of recording channels. The measured input referred noise in the action potential band is 12.4 µVrms, while using 678 electrodes, with just 3 µW power dissipation per pixel and 45 µW per read-out channel (including data transmission.

Deep Convolutional Neural Networks: Structure, Feature Extraction and Training

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Namatēvs Ivars

2017-12-01

Full Text Available Deep convolutional neural networks (CNNs are aimed at processing data that have a known network like topology. They are widely used to recognise objects in images and diagnose patterns in time series data as well as in sensor data classification. The aim of the paper is to present theoretical and practical aspects of deep CNNs in terms of convolution operation, typical layers and basic methods to be used for training and learning. Some practical applications are included for signal and image classification. Finally, the present paper describes the proposed block structure of CNN for classifying crucial features from 3D sensor data.

Testing typicality in multiverse cosmology

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Azhar, Feraz

2015-05-01

In extracting predictions from theories that describe a multiverse, we face the difficulty that we must assess probability distributions over possible observations prescribed not just by an underlying theory, but by a theory together with a conditionalization scheme that allows for (anthropic) selection effects. This means we usually need to compare distributions that are consistent with a broad range of possible observations with actual experimental data. One controversial means of making this comparison is by invoking the "principle of mediocrity": that is, the principle that we are typical of the reference class implicit in the conjunction of the theory and the conditionalization scheme. In this paper, we quantitatively assess the principle of mediocrity in a range of cosmological settings, employing "xerographic distributions" to impose a variety of assumptions regarding typicality. We find that for a fixed theory, the assumption that we are typical gives rise to higher likelihoods for our observations. If, however, one allows both the underlying theory and the assumption of typicality to vary, then the assumption of typicality does not always provide the highest likelihoods. Interpreted from a Bayesian perspective, these results support the claim that when one has the freedom to consider different combinations of theories and xerographic distributions (or different "frameworks"), one should favor the framework that has the highest posterior probability; and then from this framework one can infer, in particular, how typical we are. In this way, the invocation of the principle of mediocrity is more questionable than has been recently claimed.

Neural correlates and neural computations in posterior parietal cortex during perceptual decision-making

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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.

Neural mechanisms linking social status and inflammatory responses to social stress.

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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.

Fault Diagnosis Method of Polymerization Kettle Equipment Based on Rough Sets and BP Neural Network

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Shu-zhi Gao

2013-01-01

Full Text Available Polyvinyl chloride (PVC polymerizing production process is a typical complex controlled object, with complexity features, such as nonlinear, multivariable, strong coupling, and large time-delay. Aiming at the real-time fault diagnosis and optimized monitoring requirements of the large-scale key polymerization equipment of PVC production process, a real-time fault diagnosis strategy is proposed based on rough sets theory with the improved discernibility matrix and BP neural networks. The improved discernibility matrix is adopted to reduct the attributes of rough sets in order to decrease the input dimensionality of fault characteristics effectively. Levenberg-Marquardt BP neural network is trained to diagnose the polymerize faults according to the reducted decision table, which realizes the nonlinear mapping from fault symptom set to polymerize fault set. Simulation experiments are carried out combining with the industry history datum to show the effectiveness of the proposed rough set neural networks fault diagnosis method. The proposed strategy greatly increased the accuracy rate and efficiency of the polymerization fault diagnosis system.

Equivalent neural responses in children and adolescents with and without autism during judgments of affect

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Brent C. Vander Wyk

2014-04-01

Full Text Available Previous research has noted disrupted patterns of neural activation during emotion, processing in individuals with autism spectrum disorders (ASD. However, prior research relied on, designs that may place greater cognitive load on individuals with ASD. In order to address this issue, we adapted the fMRI task of Ochsner et al. (2004a for children by, presenting fewer stimuli, with fewer valence levels, and longer stimuli duration. A localizer sample of, typically developing children (n = 26 was used to construct regions of interest involved in emotional, processing. Activations in these regions during self- and other-referential emotion processing was, compared in age, IQ, gender matched groups (n = 17 ASD, n = 16 TD. Matched samples replicate, condition contrasts of the localizer, but no group differences were found in behavior measures or, neural activation. An exploratory functional connectivity analysis in a subset of the matched groups, also did not detect striking differences between the groups. These findings suggest that disruptions in activation in emotion processing neural networks in ASD is partially a function of task related cognitive load.

Deep Learning Neural Networks and Bayesian Neural Networks in Data Analysis

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Chernoded Andrey

2017-01-01

Full Text Available Most of the modern analyses in high energy physics use signal-versus-background classification techniques of machine learning methods and neural networks in particular. Deep learning neural network is the most promising modern technique to separate signal and background and now days can be widely and successfully implemented as a part of physical analysis. In this article we compare Deep learning and Bayesian neural networks application as a classifiers in an instance of top quark analysis.

Neural Tube Defects

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Neural tube defects are birth defects of the brain, spine, or spinal cord. They happen in the ... that she is pregnant. The two most common neural tube defects are spina bifida and anencephaly. In ...

Neural stem cell-derived exosomes mediate viral entry

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Sims B

2014-10-01

Full Text Available Brian Sims,1,2,* Linlin Gu,3,* Alexandre Krendelchtchikov,3 Qiana L Matthews3,4 1Division of Neonatology, Department of Pediatrics, 2Department of Cell, Developmental, and Integrative Biology, 3Division of Infectious Diseases, Department of Medicine, 4Center for AIDS Research, University of Alabama at Birmingham, Birmingham, AL, USA *These authors contributed equally to this work Background: Viruses enter host cells through interactions of viral ligands with cellular receptors. Viruses can also enter cells in a receptor-independent fashion. Mechanisms regarding the receptor-independent viral entry into cells have not been fully elucidated. Exosomal trafficking between cells may offer a mechanism by which viruses can enter cells.Methods: To investigate the role of exosomes on cellular viral entry, we employed neural stem cell-derived exosomes and adenovirus type 5 (Ad5 for the proof-of-principle study. Results: Exosomes significantly enhanced Ad5 entry in Coxsackie virus and adenovirus receptor (CAR-deficient cells, in which Ad5 only had very limited entry. The exosomes were shown to contain T-cell immunoglobulin mucin protein 4 (TIM-4, which binds phosphatidylserine. Treatment with anti-TIM-4 antibody significantly blocked the exosome-mediated Ad5 entry.Conclusion: Neural stem cell-derived exosomes mediated significant cellular entry of Ad5 in a receptor-independent fashion. This mediation may be hampered by an antibody specifically targeting TIM-4 on exosomes. This set of results will benefit further elucidation of virus/exosome pathways, which would contribute to reducing natural viral infection by developing therapeutic agents or vaccines. Keywords: neural stem cell-derived exosomes, adenovirus type 5, TIM-4, viral entry, phospholipids

Transcriptional and Genomic Targets of Neural Stem Cells for Functional Recovery after Hemorrhagic Stroke

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Le Zhang

2017-01-01

Full Text Available Hemorrhagic stroke is a life-threatening disease characterized by a sudden rupture of cerebral blood vessels, and it is widely believed that neural cell death occurs after exposure to blood metabolites or subsequently damaged cells. Neural stem cells (NSCs, which maintain neurogenesis and are found in subgranular zone and subventricular zone, are thought to be an endogenous neuroprotective mechanism for these brain injuries. However, due to the complexity of NSCs and their microenvironment, current strategies cannot satisfactorily enhance functional recovery after hemorrhagic stroke. It is well known that transcriptional and genomic pathways play important roles in ensuring the normal functions of NSCs, including proliferation, migration, differentiation, and neural reconnection. Recently, emerging evidence from the use of new technologies such as next-generation sequencing and transcriptome profiling has provided insight into our understanding of genomic function and regulation of NSCs. In the present article, we summarize and present the current data on the control of NSCs at both the transcriptional and genomic levels. Using bioinformatics methods, we sought to predict novel therapeutic targets of endogenous neurogenesis and exogenous NSC transplantation for functional recovery after hemorrhagic stroke, which could also advance our understanding of its pathophysiology.

Functional magnetic resonance imaging of facial information processing in children with autistic disorder, attention deficit hyperactivity disorder and typically developing controls.

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Malisza, Krisztina L; Clancy, Christine; Shiloff, Deborah; Holden, Jeanette; Jones, Cheryl; Paulson, Kristjan; Yu, Dickie C T; Summers, Randy; Chudley, Albert E

2011-01-01

The present study used functional magnetic resonance imaging (fMRI) to compare the neural activation patterns of children diagnosed with autistic disorder (AD), attention deficit hyperactivity disorder (ADHD), and typically developing controls (TCs) in response to a task involving evaluation of facial expressions. Substantially greater functional activity was noted in TCs compared to both subjects diagnosed with AD and ADHD. Consistent with previous studies, differences in functional activation of the amygdala, fusiform gyrus, cerebellum, mesolimbic, and temporal lobe cortical regions of the brain during a task evaluating facial expressions were noted in AD compared to TCs. Differences in the neural activity in these brain regions were also observed in children diagnosed with AD compared to those diagnosed with ADHD. Overall decreased neural activity was observed during the faces task performance in the AD group compared to the other two groups, a finding consistent with studies using adults. Both TC and ADHD control groups showed increased inferior frontal cortex activity compared to the AD group. Significant activity was present in both TC and ADHD control groups in the insula which was absent in the AD group; this is consistent with other studies showing dysfunction of the mesolimbic system in children with AD. Although frontostriatal and mesolimbic systems appear to be affected in AD, these deficits were not in the same attentional networks which are dysfunctional in children diagnosed with ADHD.

Adolescent transformations of behavioral and neural processes as potential targets for prevention.

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Eldreth, Dana; Hardin, Michael G; Pavletic, Nevia; Ernst, Monique

2013-06-01

Adolescence is a transitional period in development that is marked by a distinct, typical behavioral profile of high rates of exploration, novelty-seeking, and emotional lability. While these behaviors generally assist the adolescent transition to independence, they can also confer vulnerability for excessive risk-taking and psychopathology, particularly in the context of specific environmental or genetic influences. As prevention research depends on the identification of targets of vulnerability, the following review will discuss the interplay among motivational systems including reward-related, avoidance-related, and regulatory processes in typical and atypical adolescent development. Each set of processes will be discussed in relation to their underlying neural correlates and distinct developmental trajectories. Evidence suggests that typical adolescent behavior and the risk for atypical development are mediated by heightened adolescent responsiveness of reward-related and avoidance-related systems under specific conditions, concurrent with poor modulation by immature regulatory processes. Finally, we will propose strategies to exploit heightened reward processing to reinforce inhibitory control, which is an essential component of regulatory processes in prevention interventions.

Cleanup standards and pathways analysis methods

International Nuclear Information System (INIS)

Devgun, J.S.

1993-01-01

Remediation of a radioactively contaminated site requires that certain regulatory criteria be met before the site can be released for unrestricted future use. Since the ultimate objective of remediation is to protect the public health and safety, residual radioactivity levels remaining at a site after cleanup must be below certain preset limits or meet acceptable dose or risk criteria. Release of a decontaminated site requires proof that the radiological data obtained from the site meet the regulatory criteria for such a release. Typically release criteria consist of a composite of acceptance limits that depend on the radionuclides, the media in which they are present, and federal and local regulations. In recent years, the US Department of Energy (DOE) has developed a pathways analysis model to determine site-specific soil activity concentration guidelines for radionuclides that do not have established generic acceptance limits. The DOE pathways analysis computer code (developed by Argonne National Laboratory for the DOE) is called RESRAD (Gilbert et al. 1989). Similar efforts have been initiated by the US Nuclear Regulatory Commission (NRC) to develop and use dose-related criteria based on genetic pathways analyses rather than simplistic numerical limits on residual radioactivity. The focus of this paper is radionuclide contaminated soil. Cleanup standards are reviewed, pathways analysis methods are described, and an example is presented in which RESRAD was used to derive cleanup guidelines

Roles of db-cAMP, IBMX and RA in aspects of neural differentiation of cord blood derived mesenchymal-like stem cells.

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Murni Tio

Full Text Available Mesenchymal stem cells (MSCs have multilineage differentiation potential which includes cell lineages of the central nervous system; hence MSCs might be useful in the treatment of neurodegenerative diseases such as Parkinson's disease. Although mesenchymal stem cells have been shown to differentiate into the neural lineage, there is still little knowledge about the underlying mechanisms of differentiation particularly towards specialized neurons such as dopaminergic neurons. Here, we show that MSCs derived from human umbilical cord blood (MSC(hUCBs are capable of expressing tyrosine hydroxylase (TH and Nurr1, markers typically associated with DA neurons. We also found differential phosphorylation of TH isoforms indicating the presence of post-translational mechanisms possibly activating and modifying TH in MSC(hUCB. Furthermore, functional dissection of components in the differentiation medium revealed that dibutyryl-cAMP (db-cAMP, 3-isobutyl-1-methylxanthine (IBMX and retinoic acid (RA are involved in the regulation of Nurr1 and Neurofilament-L expression as well as in the differential phosphorylation of TH. We also demonstrate a possible inhibitory role of the protein kinase A signaling pathway in the phosphorylation of specific TH isoforms.

Evaluation of the cranial base in amnion rupture sequence involving the anterior neural tube: implications regarding recurrence risk.

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Jones, Kenneth Lyons; Robinson, Luther K; Benirschke, Kurt

2006-09-01

Amniotic bands can cause disruption of the cranial end of the developing fetus, leading in some cases to a neural tube closure defect. Although recurrence for unaffected parents of an affected child with a defect in which the neural tube closed normally but was subsequently disrupted by amniotic bands is negligible; for a primary defect in closure of the neural tube to which amnion has subsequently adhered, recurrence risk is 1.7%. In that primary defects of neural tube closure are characterized by typical abnormalities of the base of the skull, evaluation of the cranial base in such fetuses provides an approach for making a distinction between these 2 mechanisms. This distinction has implications regarding recurrence risk. The skull base of 2 fetuses with amnion rupture sequence involving the cranial end of the neural tube were compared to that of 1 fetus with anencephaly as well as that of a structurally normal fetus. The skulls were cleaned, fixed in 10% formalin, recleaned, and then exposed to 10% KOH solution. After washing and recleaning, the skulls were exposed to hydrogen peroxide for bleaching and photography. Despite involvement of the anterior neural tube in both fetuses with amnion rupture sequence, in Case 3 the cranial base was normal while in Case 4 the cranial base was similar to that seen in anencephaly. This technique provides a method for determining the developmental pathogenesis of anterior neural tube defects in cases of amnion rupture sequence. As such, it provides information that can be used to counsel parents of affected children with respect to recurrence risk.

Effects of chronic REM sleep restriction on D1 receptor and related signal pathways in rat prefrontal cortex.

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Han, Yan; Wen, Xiaosa; Rong, Fei; Chen, Xinmin; Ouyang, Ruying; Wu, Shuai; Nian, Hua; Ma, Wenling

2015-01-01

The prefrontal cortex (PFC) mediates cognitive function that is sensitive to disruption by sleep loss, and molecular mechanisms regulating neural dysfunction induced by chronic sleep restriction (CSR), particularly in the PFC, have yet to be completely understood. The aim of the present study was to investigate the effect of chronic REM sleep restriction (REM-CSR) on the D1 receptor (D1R) and key molecules in D1R' signal pathways in PFC. We employed the modified multiple platform method to create the REM-CSR rat model. The ultrastructure of PFC was observed by electron microscopy. HPLC was performed to measure the DA level in PFC. The expressions of genes and proteins of related molecules were assayed by real-time PCR and Western blot, respectively. The general state and morphology of PFC in rats were changed by CSR, and DA level and the expression of D1R in PFC were markedly decreased (P CSR rats (P CSR induced cognitive dysfunction, and the PKA pathway of D1R may play an important role in the impairment of advanced neural function.

New Solutions to the Firing Squad Synchronization Problems for Neural and Hyperdag P Systems

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Michael J. Dinneen

2009-11-01

Full Text Available We propose two uniform solutions to an open question: the Firing Squad Synchronization Problem (FSSP, for hyperdag and symmetric neural P systems, with anonymous cells. Our solutions take e_c+5 and 6e_c+7 steps, respectively, where e_c is the eccentricity of the commander cell of the dag or digraph underlying these P systems. The first and fast solution is based on a novel proposal, which dynamically extends P systems with mobile channels. The second solution is substantially longer, but is solely based on classical rules and static channels. In contrast to the previous solutions, which work for tree-based P systems, our solutions synchronize to any subset of the underlying digraph; and do not require membrane polarizations or conditional rules, but require states, as typically used in hyperdag and neural P systems.

A neural flow estimator

DEFF Research Database (Denmark)

Jørgensen, Ivan Harald Holger; Bogason, Gudmundur; Bruun, Erik

1995-01-01

This paper proposes a new way to estimate the flow in a micromechanical flow channel. A neural network is used to estimate the delay of random temperature fluctuations induced in a fluid. The design and implementation of a hardware efficient neural flow estimator is described. The system...... is implemented using switched-current technique and is capable of estimating flow in the μl/s range. The neural estimator is built around a multiplierless neural network, containing 96 synaptic weights which are updated using the LMS1-algorithm. An experimental chip has been designed that operates at 5 V...

Hidden neural networks

DEFF Research Database (Denmark)

Krogh, Anders Stærmose; Riis, Søren Kamaric

1999-01-01

A general framework for hybrids of hidden Markov models (HMMs) and neural networks (NNs) called hidden neural networks (HNNs) is described. The article begins by reviewing standard HMMs and estimation by conditional maximum likelihood, which is used by the HNN. In the HNN, the usual HMM probability...... parameters are replaced by the outputs of state-specific neural networks. As opposed to many other hybrids, the HNN is normalized globally and therefore has a valid probabilistic interpretation. All parameters in the HNN are estimated simultaneously according to the discriminative conditional maximum...... likelihood criterion. The HNN can be viewed as an undirected probabilistic independence network (a graphical model), where the neural networks provide a compact representation of the clique functions. An evaluation of the HNN on the task of recognizing broad phoneme classes in the TIMIT database shows clear...

NeuroMEMS: Neural Probe Microtechnologies

Directory of Open Access Journals (Sweden)

Sam Musallam

2008-10-01

Full Text Available Neural probe technologies have already had a significant positive effect on our understanding of the brain by revealing the functioning of networks of biological neurons. Probes are implanted in different areas of the brain to record and/or stimulate specific sites in the brain. Neural probes are currently used in many clinical settings for diagnosis of brain diseases such as seizers, epilepsy, migraine, Alzheimer’s, and dementia. We find these devices assisting paralyzed patients by allowing them to operate computers or robots using their neural activity. In recent years, probe technologies were assisted by rapid advancements in microfabrication and microelectronic technologies and thus are enabling highly functional and robust neural probes which are opening new and exciting avenues in neural sciences and brain machine interfaces. With a wide variety of probes that have been designed, fabricated, and tested to date, this review aims to provide an overview of the advances and recent progress in the microfabrication techniques of neural probes. In addition, we aim to highlight the challenges faced in developing and implementing ultralong multi-site recording probes that are needed to monitor neural activity from deeper regions in the brain. Finally, we review techniques that can improve the biocompatibility of the neural probes to minimize the immune response and encourage neural growth around the electrodes for long term implantation studies.

Online neural monitoring of statistical learning.

Science.gov (United States)

Batterink, Laura J; Paller, Ken A

2017-05-01

The extraction of patterns in the environment plays a critical role in many types of human learning, from motor skills to language acquisition. This process is known as statistical learning. Here we propose that statistical learning has two dissociable components: (1) perceptual binding of individual stimulus units into integrated composites and (2) storing those integrated representations for later use. Statistical learning is typically assessed using post-learning tasks, such that the two components are conflated. Our goal was to characterize the online perceptual component of statistical learning. Participants were exposed to a structured stream of repeating trisyllabic nonsense words and a random syllable stream. Online learning was indexed by an EEG-based measure that quantified neural entrainment at the frequency of the repeating words relative to that of individual syllables. Statistical learning was subsequently assessed using conventional measures in an explicit rating task and a reaction-time task. In the structured stream, neural entrainment to trisyllabic words was higher than in the random stream, increased as a function of exposure to track the progression of learning, and predicted performance on the reaction time (RT) task. These results demonstrate that monitoring this critical component of learning via rhythmic EEG entrainment reveals a gradual acquisition of knowledge whereby novel stimulus sequences are transformed into familiar composites. This online perceptual transformation is a critical component of learning. Copyright © 2017 Elsevier Ltd. All rights reserved.

The functional and structural neural basis of individual differences in loss aversion.

Science.gov (United States)

Canessa, Nicola; Crespi, Chiara; Motterlini, Matteo; Baud-Bovy, Gabriel; Chierchia, Gabriele; Pantaleo, Giuseppe; Tettamanti, Marco; Cappa, Stefano F

2013-09-04

Decision making under risk entails the anticipation of prospective outcomes, typically leading to the greater sensitivity to losses than gains known as loss aversion. Previous studies on the neural bases of choice-outcome anticipation and loss aversion provided inconsistent results, showing either bidirectional mesolimbic responses of activation for gains and deactivation for losses, or a specific amygdala involvement in processing losses. Here we focused on loss aversion with the aim to address interindividual differences in the neural bases of choice-outcome anticipation. Fifty-six healthy human participants accepted or rejected 104 mixed gambles offering equal (50%) chances of gaining or losing different amounts of money while their brain activity was measured with functional magnetic resonance imaging (fMRI). We report both bidirectional and gain/loss-specific responses while evaluating risky gambles, with amygdala and posterior insula specifically tracking the magnitude of potential losses. At the individual level, loss aversion was reflected both in limbic fMRI responses and in gray matter volume in a structural amygdala-thalamus-striatum network, in which the volume of the "output" centromedial amygdala nuclei mediating avoidance behavior was negatively correlated with monetary performance. We conclude that outcome anticipation and ensuing loss aversion involve multiple neural systems, showing functional and structural individual variability directly related to the actual financial outcomes of choices. By supporting the simultaneous involvement of both appetitive and aversive processing in economic decision making, these results contribute to the interpretation of existing inconsistencies on the neural bases of anticipating choice outcomes.

Neural Mechanisms of Episodic Retrieval Support Divergent Creative Thinking.

Science.gov (United States)

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.

VoIP attacks detection engine based on neural network

Science.gov (United States)

Safarik, Jakub; Slachta, Jiri

2015-05-01

The security is crucial for any system nowadays, especially communications. One of the most successful protocols in the field of communication over IP networks is Session Initiation Protocol. It is an open-source project used by different kinds of applications, both open-source and proprietary. High penetration and text-based principle made SIP number one target in IP telephony infrastructure, so security of SIP server is essential. To keep up with hackers and to detect potential malicious attacks, security administrator needs to monitor and evaluate SIP traffic in the network. But monitoring and following evaluation could easily overwhelm the security administrator in networks, typically in networks with a number of SIP servers, users and logically or geographically separated networks. The proposed solution lies in automatic attack detection systems. The article covers detection of VoIP attacks through a distributed network of nodes. Then the gathered data analyze aggregation server with artificial neural network. Artificial neural network means multilayer perceptron network trained with a set of collected attacks. Attack data could also be preprocessed and verified with a self-organizing map. The source data is detected by distributed network of detection nodes. Each node contains a honeypot application and traffic monitoring mechanism. Aggregation of data from each node creates an input for neural networks. The automatic classification on a centralized server with low false positive detection reduce the cost of attack detection resources. The detection system uses modular design for easy deployment in final infrastructure. The centralized server collects and process detected traffic. It also maintains all detection nodes.

Planning music-based amelioration and training in infancy and childhood based on neural evidence.

Science.gov (United States)

Huotilainen, Minna; Tervaniemi, Mari

2018-05-04

Music-based amelioration and training of the developing auditory system has a long tradition, and recent neuroscientific evidence supports using music in this manner. Here, we present the available evidence showing that various music-related activities result in positive changes in brain structure and function, becoming helpful for auditory cognitive processes in everyday life situations for individuals with typical neural development and especially for individuals with hearing, learning, attention, or other deficits that may compromise auditory processing. We also compare different types of music-based training and show how their effects have been investigated with neural methods. Finally, we take a critical position on the multitude of error sources found in amelioration and training studies and on publication bias in the field. We discuss some future improvements of these issues in the field of music-based training and their potential results at the neural and behavioral levels in infants and children for the advancement of the field and for a more complete understanding of the possibilities and significance of the training. © 2018 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals, Inc. on behalf of New York Academy of Sciences.

A novel neural substrate for the transformation of olfactory inputs into motor output.

Directory of Open Access Journals (Sweden)

Dominique Derjean

2010-12-01

Full Text Available It is widely recognized that animals respond to odors by generating or modulating specific motor behaviors. These reactions are important for daily activities, reproduction, and survival. In the sea lamprey, mating occurs after ovulated females are attracted to spawning sites by male sex pheromones. The ubiquity and reliability of olfactory-motor behavioral responses in vertebrates suggest tight coupling between the olfactory system and brain areas controlling movements. However, the circuitry and the underlying cellular neural mechanisms remain largely unknown. Using lamprey brain preparations, and electrophysiology, calcium imaging, and tract tracing experiments, we describe the neural substrate responsible for transforming an olfactory input into a locomotor output. We found that olfactory stimulation with naturally occurring odors and pheromones induced large excitatory responses in reticulospinal cells, the command neurons for locomotion. We have also identified the anatomy and physiology of this circuit. The olfactory input was relayed in the medial part of the olfactory bulb, in the posterior tuberculum, in the mesencephalic locomotor region, to finally reach reticulospinal cells in the hindbrain. Activation of this olfactory-motor pathway generated rhythmic ventral root discharges and swimming movements. Our study bridges the gap between behavior and cellular neural mechanisms in vertebrates, identifying a specific subsystem within the CNS, dedicated to producing motor responses to olfactory inputs.

The nucleus accumbens 5-HTR4-CART pathway ties anorexia to hyperactivity

Science.gov (United States)

Jean, A; Laurent, L; Bockaert, J; Charnay, Y; Dusticier, N; Nieoullon, A; Barrot, M; Neve, R; Compan, V

2012-01-01

In mental diseases, the brain does not systematically adjust motor activity to feeding. Probably, the most outlined example is the association between hyperactivity and anorexia in Anorexia nervosa. The neural underpinnings of this ‘paradox', however, are poorly elucidated. Although anorexia and hyperactivity prevail over self-preservation, both symptoms rarely exist independently, suggesting commonalities in neural pathways, most likely in the reward system. We previously discovered an addictive molecular facet of anorexia, involving production, in the nucleus accumbens (NAc), of the same transcripts stimulated in response to cocaine and amphetamine (CART) upon stimulation of the 5-HT4 receptors (5-HTR4) or MDMA (ecstasy). Here, we tested whether this pathway predisposes not only to anorexia but also to hyperactivity. Following food restriction, mice are expected to overeat. However, selecting hyperactive and addiction-related animal models, we observed that mice lacking 5-HTR1B self-imposed food restriction after deprivation and still displayed anorexia and hyperactivity after ecstasy. Decryption of the mechanisms showed a gain-of-function of 5-HTR4 in the absence of 5-HTR1B, associated with CART surplus in the NAc and not in other brain areas. NAc-5-HTR4 overexpression upregulated NAc-CART, provoked anorexia and hyperactivity. NAc-5-HTR4 knockdown or blockade reduced ecstasy-induced hyperactivity. Finally, NAc-CART knockdown suppressed hyperactivity upon stimulation of the NAc-5-HTR4. Additionally, inactivating NAc-5-HTR4 suppressed ecstasy's preference, strengthening the rewarding facet of anorexia. In conclusion, the NAc-5-HTR4/CART pathway establishes a ‘tight-junction' between anorexia and hyperactivity, suggesting the existence of a primary functional unit susceptible to limit overeating associated with resting following homeostasis rules. PMID:23233022

Pathway Distiller - multisource biological pathway consolidation.

Science.gov (United States)

Doderer, Mark S; Anguiano, Zachry; Suresh, Uthra; Dashnamoorthy, Ravi; Bishop, Alexander J R; Chen, Yidong

2012-01-01

One method to understand and evaluate an experiment that produces a large set of genes, such as a gene expression microarray analysis, is to identify overrepresentation or enrichment for biological pathways. Because pathways are able to functionally describe the set of genes, much effort has been made to collect curated biological pathways into publicly accessible databases. When combining disparate databases, highly related or redundant pathways exist, making their consolidation into pathway concepts essential. This will facilitate unbiased, comprehensive yet streamlined analysis of experiments that result in large gene sets. After gene set enrichment finds representative pathways for large gene sets, pathways are consolidated into representative pathway concepts. Three complementary, but different methods of pathway consolidation are explored. Enrichment Consolidation combines the set of the pathways enriched for the signature gene list through iterative combining of enriched pathways with other pathways with similar signature gene sets; Weighted Consolidation utilizes a Protein-Protein Interaction network based gene-weighting approach that finds clusters of both enriched and non-enriched pathways limited to the experiments' resultant gene list; and finally the de novo Consolidation method uses several measurements of pathway similarity, that finds static pathway clusters independent of any given experiment. We demonstrate that the three consolidation methods provide unified yet different functional insights of a resultant gene set derived from a genome-wide profiling experiment. Results from the methods are presented, demonstrating their applications in biological studies and comparing with a pathway web-based framework that also combines several pathway databases. Additionally a web-based consolidation framework that encompasses all three methods discussed in this paper, Pathway Distiller (http://cbbiweb.uthscsa.edu/PathwayDistiller), is established to allow

Prediction of Negative Conversion Days of Childhood Nephrotic Syndrome Based on the Improved Backpropagation Neural Network with Momentum

Directory of Open Access Journals (Sweden)

Yi-jun Liu

2015-12-01

Full Text Available Childhood nephrotic syndrome is a chronic disease harmful to growth of children. Scientific and accurate prediction of negative conversion days for children with nephrotic syndrome offers potential benefits for treatment of patients and helps achieve better cure effect. In this study, the improved backpropagation neural network with momentum is used for prediction. Momentum speeds up convergence and maintains the generalization performance of the neural network, and therefore overcomes weaknesses of the standard backpropagation algorithm. The three-tier network structure is constructed. Eight indicators including age, lgG, lgA and lgM, etc. are selected for network inputs. The scientific computing software of MATLAB and its neural network tools are used to create model and predict. The training sample of twenty-eight cases is used to train the neural network. The test sample of six typical cases belonging to six different age groups respectively is used to test the predictive model. The low mean absolute error of predictive results is achieved at 0.83. The experimental results of the small-size sample show that the proposed approach is to some degree applicable for the prediction of negative conversion days of childhood nephrotic syndrome.

twzPEA: A Topology and Working Zone Based Pathway Enrichment Analysis Framework

Science.gov (United States)

Sensitive detection of involvement and adaptation of key signaling, regulatory, and metabolic pathways holds the key to deciphering molecular mechanisms such as those in the biomass-to-biofuel conversion process in yeast. Typical gene set enrichment analyses often do not use topology information in...

Brain-Heart Pathways to Blood Pressure-Related Hypoalgesia.

Science.gov (United States)

Ottaviani, Cristina; Fagioli, Sabrina; Mattei, Eugenio; Censi, Federica; Edwards, Louisa; Macaluso, Emiliano; Bozzali, Marco; Critchley, Hugo; Calcagnini, Giovanni

2018-03-28

High blood pressure (BP) is associated with reduced pain sensitivity, known as BP-related hypoalgesia. The underlying neural mechanisms remain uncertain, yet arterial baroreceptor signaling, occurring at cardiac systole, is implicated. We examined normotensives using functional neuroimaging (fMRI) and pain stimulation during distinct phases of the cardiac cycle to test the hypothesized neural mediation of baroreceptor-induced attenuation of pain. Eighteen participants (10 women; 32.7 ± 6.5 years) underwent BP monitoring over one week at home, and individual pain thresholds were determined in the lab. Subsequently, participants were administered unpredictable painful and non-painful electrocutaneous shocks (stimulus type), timed to occur either at systole or diastole (cardiac phase) in an event-related design. After each trial, participants evaluated their subjective experience. Subjective pain was lower for painful stimuli administered at systole compared to diastole, F1, 2283 = 4.82; p = 0.03. Individuals with higher baseline BP demonstrated overall lower pain perception, F1, 2164 = 10.47; p < 0.0001. Within the brain, painful stimulation activated somatosensory areas, prefrontal cortex, cingulate cortex, posterior insula, amygdala, and the thalamus. Stimuli delivered during systole (concurrent with baroreceptor discharge) activated areas associated with heightened parasympathetic drive. No stimulus type x cardiac phase interaction emerged except for a small cluster located in the right parietal cortex. We confirm the negative associations between BP and pain, highlighting the antinociceptive impact of baroreceptor discharge. Neural substrates associated with baroreceptor/BP-related hypoalgesia include superior parietal lobule, precentral and lingual gyrus, regions typically involved in the cognitive aspects of pain experience.

Prediction and typicality in multiverse cosmology

International Nuclear Information System (INIS)

Azhar, Feraz

2014-01-01

In the absence of a fundamental theory that precisely predicts values for observable parameters, anthropic reasoning attempts to constrain probability distributions over those parameters in order to facilitate the extraction of testable predictions. The utility of this approach has been vigorously debated of late, particularly in light of theories that claim we live in a multiverse, where parameters may take differing values in regions lying outside our observable horizon. Within this cosmological framework, we investigate the efficacy of top-down anthropic reasoning based on the weak anthropic principle. We argue contrary to recent claims that it is not clear one can either dispense with notions of typicality altogether or presume typicality, in comparing resulting probability distributions with observations. We show in a concrete, top-down setting related to dark matter, that assumptions about typicality can dramatically affect predictions, thereby providing a guide to how errors in reasoning regarding typicality translate to errors in the assessment of predictive power. We conjecture that this dependence on typicality is an integral feature of anthropic reasoning in broader cosmological contexts, and argue in favour of the explicit inclusion of measures of typicality in schemes invoking anthropic reasoning, with a view to extracting predictions from multiverse scenarios. (paper)

Prediction and typicality in multiverse cosmology

Science.gov (United States)

Azhar, Feraz

2014-02-01

In the absence of a fundamental theory that precisely predicts values for observable parameters, anthropic reasoning attempts to constrain probability distributions over those parameters in order to facilitate the extraction of testable predictions. The utility of this approach has been vigorously debated of late, particularly in light of theories that claim we live in a multiverse, where parameters may take differing values in regions lying outside our observable horizon. Within this cosmological framework, we investigate the efficacy of top-down anthropic reasoning based on the weak anthropic principle. We argue contrary to recent claims that it is not clear one can either dispense with notions of typicality altogether or presume typicality, in comparing resulting probability distributions with observations. We show in a concrete, top-down setting related to dark matter, that assumptions about typicality can dramatically affect predictions, thereby providing a guide to how errors in reasoning regarding typicality translate to errors in the assessment of predictive power. We conjecture that this dependence on typicality is an integral feature of anthropic reasoning in broader cosmological contexts, and argue in favour of the explicit inclusion of measures of typicality in schemes invoking anthropic reasoning, with a view to extracting predictions from multiverse scenarios.

Neural Networks: Implementations and Applications

OpenAIRE

Vonk, E.; Veelenturf, L.P.J.; Jain, L.C.

1996-01-01

Artificial neural networks, also called neural networks, have been used successfully in many fields including engineering, science and business. This paper presents the implementation of several neural network simulators and their applications in character recognition and other engineering areas

New roles for Nanos in neural cell fate determination revealed by studies in a cnidarian.

Science.gov (United States)

Kanska, Justyna; Frank, Uri

2013-07-15

Nanos is a pan-metazoan germline marker, important for germ cell development and maintenance. In flies, Nanos also acts in posterior and neural development, but these functions have not been demonstrated experimentally in other animals. Using the cnidarian Hydractinia we have uncovered novel roles for Nanos in neural cell fate determination. Ectopic expression of Nanos2 increased the numbers of embryonic stinging cell progenitors, but decreased the numbers of neurons. Downregulation of Nanos2 had the opposite effect. Furthermore, Nanos2 blocked maturation of committed, post-mitotic nematoblasts. Hence, Nanos2 acts as a switch between two differentiation pathways, increasing the numbers of nematoblasts at the expense of neuroblasts, but preventing nematocyte maturation. Nanos2 ectopic expression also caused patterning defects, but these were not associated with deregulation of Wnt signaling, showing that the basic anterior-posterior polarity remained intact, and suggesting that numerical imbalance between nematocytes and neurons might have caused these defects, affecting axial patterning only indirectly. We propose that the functions of Nanos in germ cells and in neural development are evolutionarily conserved, but its role in posterior patterning is an insect or arthropod innovation.

Transformation-invariant visual representations in self-organizing spiking neural networks.

Science.gov (United States)

Evans, Benjamin D; Stringer, Simon M

2012-01-01

The ventral visual pathway achieves object and face recognition by building transformation-invariant representations from elementary visual features. In previous computer simulation studies with rate-coded neural networks, the development of transformation-invariant representations has been demonstrated using either of two biologically plausible learning mechanisms, Trace learning and Continuous Transformation (CT) learning. However, it has not previously been investigated how transformation-invariant representations may be learned in a more biologically accurate spiking neural network. A key issue is how the synaptic connection strengths in such a spiking network might self-organize through Spike-Time Dependent Plasticity (STDP) where the change in synaptic strength is dependent on the relative times of the spikes emitted by the presynaptic and postsynaptic neurons rather than simply correlated activity driving changes in synaptic efficacy. Here we present simulations with conductance-based integrate-and-fire (IF) neurons using a STDP learning rule to address these gaps in our understanding. It is demonstrated that with the appropriate selection of model parameters and training regime, the spiking network model can utilize either Trace-like or CT-like learning mechanisms to achieve transform-invariant representations.

Transform-invariant visual representations in self-organizing spiking neural networks

Directory of Open Access Journals (Sweden)

Benjamin eEvans

2012-07-01

Full Text Available The ventral visual pathway achieves object and face recognition by building transform-invariant representations from elementary visual features. In previous computer simulation studies with rate-coded neural networks, the development of transform invariant representations has been demonstrated using either of two biologically plausible learning mechanisms, Trace learning and Continuous Transformation (CT learning. However, it has not previously been investigated how transform invariant representations may be learned in a more biologically accurate spiking neural network. A key issue is how the synaptic connection strengths in such a spiking network might self-organize through Spike-Time Dependent Plasticity (STDP where the change in synaptic strength is dependent on the relative times of the spikes emitted by the pre- and postsynaptic neurons rather than simply correlated activity driving changes in synaptic efficacy. Here we present simulations with conductance-based integrate-and-fire (IF neurons using a STDP learning rule to address these gaps in our understanding. It is demonstrated that with the appropriate selection of model pa- rameters and training regime, the spiking network model can utilize either Trace-like or CT-like learning mechanisms to achieve transform-invariant representations.

Neuroprotective effect of rapamycin on spinal cord injury via activation of the Wnt/β-catenin signaling pathway

Directory of Open Access Journals (Sweden)

Kai Gao

2015-01-01

Full Text Available The Wnt/β-catenin signaling pathway plays a crucial role in neural development, axonal guidance, neuropathic pain remission and neuronal survival. In this study, we initially examined the effect of rapamycin on the Wnt/β-catenin signaling pathway after spinal cord injury, by intraperitoneally injecting spinal cord injured rats with rapamycin over 2 days. Western blot analysis and immunofluorescence staining were used to detect the expression levels of β-catenin protein, ca-spase-3 protein and brain-derived neurotrophic factor protein, components of the Wnt/β-catenin signaling pathway. Rapamycin increased the levels of β-catenin and brain-derived neurotrophic factor in the injured spinal cord, improved the pathological morphology at the injury site, reduced the loss of motor neurons, and promoted motor functional recovery in rats after spinal cord injury. Our experimental findings suggest that the neuroprotective effect of rapamycin intervention is mediated through activation of the Wnt/β-catenin signaling pathway after spinal cord injury.

Nonassociative learning as gated neural integrator and differentiator in stimulus-response pathways

Directory of Open Access Journals (Sweden)

Young Daniel L

2006-08-01

Full Text Available Abstract Nonassociative learning is a basic neuroadaptive behavior exhibited across animal phyla and sensory modalities but its role in brain intelligence is unclear. Current literature on habituation and sensitization, the classic "dual process" of nonassociative learning, gives highly incongruous accounts between varying experimental paradigms. Here we propose a general theory of nonassociative learning featuring four base modes: habituation/primary sensitization in primary stimulus-response pathways, and desensitization/secondary sensitization in secondary stimulus-response pathways. Primary and secondary modes of nonassociative learning are distinguished by corresponding activity-dependent recall, or nonassociative gating, of neurotransmission memory. From the perspective of brain computation, nonassociative learning is a form of integral-differential calculus whereas nonassociative gating is a form of Boolean logic operator – both dynamically transforming the stimulus-response relationship. From the perspective of sensory integration, nonassociative gating provides temporal filtering whereas nonassociative learning affords low-pass, high-pass or band-pass/band-stop frequency filtering – effectively creating an intelligent sensory firewall that screens all stimuli for attention and resultant internal model adaptation and reaction. This unified framework ties together many salient characteristics of nonassociative learning and nonassociative gating and suggests a common kernel that correlates with a wide variety of sensorimotor integration behaviors such as central resetting and self-organization of sensory inputs, fail-safe sensorimotor compensation, integral-differential and gated modulation of sensorimotor feedbacks, alarm reaction, novelty detection and selective attention, as well as a variety of mental and neurological disorders such as sensorimotor instability, attention deficit hyperactivity, sensory defensiveness, autism

Neural activation associated with the cognitive emotion regulation of sadness in healthy children

Directory of Open Access Journals (Sweden)

Andy C. Belden

2014-07-01

Full Text Available When used effectively, cognitive reappraisal of distressing events is a highly adaptive cognitive emotion regulation (CER strategy, with impairments in cognitive reappraisal associated with greater risk for psychopathology. Despite extensive literature examining the neural correlates of cognitive reappraisal in healthy and psychiatrically ill adults, there is a dearth of data to inform the neural bases of CER in children, a key gap in the literature necessary to map the developmental trajectory of cognitive reappraisal. In this fMRI study, psychiatrically healthy schoolchildren were instructed to use cognitive reappraisal to modulate their emotional reactions and responses of negative affect after viewing sad photos. Consistent with the adult literature, when actively engaged in reappraisal compared to passively viewing sad photos, children showed increased activation in the vlPFC, dlPFC, and dmPFC as well as in parietal and temporal lobe regions. When children used cognitive reappraisal to minimize their experience of negative affect after viewing sad stimuli they exhibited dampened amygdala responses. Results are discussed in relation to the importance of identifying and characterizing neural processes underlying adaptive CER strategies in typically developing children in order to understand how these systems go awry and relate to the risk and occurrence of affective disorders.

Brain substrates of implicit and explicit memory: the importance of concurrently acquired neural signals of both memory types.

Science.gov (United States)

Voss, Joel L; Paller, Ken A

2008-11-01

A comprehensive understanding of human memory requires cognitive and neural descriptions of memory processes along with a conception of how memory processing drives behavioral responses and subjective experiences. One serious challenge to this endeavor is that an individual memory process is typically operative within a mix of other contemporaneous memory processes. This challenge is particularly disquieting in the context of implicit memory, which, unlike explicit memory, transpires without the subject necessarily being aware of memory retrieval. Neural correlates of implicit memory and neural correlates of explicit memory are often investigated in different experiments using very different memory tests and procedures. This strategy poses difficulties for elucidating the interactions between the two types of memory process that may result in explicit remembering, and for determining the extent to which certain neural processing events uniquely contribute to only one type of memory. We review recent studies that have succeeded in separately assessing neural correlates of both implicit memory and explicit memory within the same paradigm using event-related brain potentials (ERPs) and functional magnetic resonance imaging (fMRI), with an emphasis on studies from our laboratory. The strategies we describe provide a methodological framework for achieving valid assessments of memory processing, and the findings support an emerging conceptualization of the distinct neurocognitive events responsible for implicit and explicit memory.

Neurophysiology and neural engineering: a review.

Science.gov (United States)

Prochazka, Arthur

2017-08-01

Neurophysiology is the branch of physiology concerned with understanding the function of neural systems. Neural engineering (also known as neuroengineering) is a discipline within biomedical engineering that uses engineering techniques to understand, repair, replace, enhance, or otherwise exploit the properties and functions of neural systems. In most cases neural engineering involves the development of an interface between electronic devices and living neural tissue. This review describes the origins of neural engineering, the explosive development of methods and devices commencing in the late 1950s, and the present-day devices that have resulted. The barriers to interfacing electronic devices with living neural tissues are many and varied, and consequently there have been numerous stops and starts along the way. Representative examples are discussed. None of this could have happened without a basic understanding of the relevant neurophysiology. I also consider examples of how neural engineering is repaying the debt to basic neurophysiology with new knowledge and insight. Copyright © 2017 the American Physiological Society.

Fast and Efficient Asynchronous Neural Computation with Adapting Spiking Neural Networks

NARCIS (Netherlands)

D. Zambrano (Davide); S.M. Bohte (Sander)

2016-01-01

textabstractBiological neurons communicate with a sparing exchange of pulses - spikes. It is an open question how real spiking neurons produce the kind of powerful neural computation that is possible with deep artificial neural networks, using only so very few spikes to communicate. Building on

Chitosan scaffolds induce human dental pulp stem cells to neural differentiation: potential roles for spinal cord injury therapy.

Science.gov (United States)

Zhang, Jinlong; Lu, Xiaohui; Feng, Guijuan; Gu, Zhifeng; Sun, Yuyu; Bao, Guofeng; Xu, Guanhua; Lu, Yuanzhou; Chen, Jiajia; Xu, Lingfeng; Feng, Xingmei; Cui, Zhiming

2016-10-01

Cell-based transplantation strategies hold great potential for spinal cord injury (SCI) repair. Chitosan scaffolds have therapeutic benefits for spinal cord regeneration. Human dental pulp stem cells (DPSCs) are abundant available stem cells with low immunological incompatibility and can be considered for cell replacement therapy. The purpose of this study is to investigate the role of chitosan scaffolds in the neural differentiation of DPSCs in vitro and to assess the supportive effects of chitosan scaffolds in an animal model of SCI. DPSCs were incubated with chitosan scaffolds. Cell viability and the secretion of neurotrophic factors were analyzed. DPSCs incubated with chitosan scaffolds were treated with neural differentiation medium for 14 days and then neural genes and protein markers were analyzed by Western blot and reverse transcription plus the polymerase chain reaction. Our study revealed a higher cell viability and neural differentiation in the DPSC/chitosan-scaffold group. Compared with the control group, the levels of BDNF, GDNF, b-NGF, and NT-3 were significantly increased in the DPSC/chitosan-scaffold group. The Wnt/β-catenin signaling pathway played a key role in the neural differentiation of DPSCs combined with chitosan scaffolds. Transplantation of DPSCs together with chitosan scaffolds into an SCI rat model resulted in the marked recovery of hind limb locomotor functions. Thus, chitosan scaffolds were non-cytotoxic and provided a conducive and favorable microenvironment for the survival and neural differentiation of DPSCs. Transplantation of DPSCs might therefore be a suitable candidate for treating SCI and other neuronal degenerative diseases.

Endolysosomal pathway activity protects cells from neurotoxic TDP-43

Directory of Open Access Journals (Sweden)

Christine Leibiger

2018-03-01

Full Text Available The accumulation of protein aggregates in neurons is a typical pathological hallmark of the motor neuron disease amyotrophic lateral sclerosis (ALS and of frontotemporal dementia (FTD. In many cases, these aggregates are composed of the 43 kDa TAR DNA-binding protein (TDP‑43. Using a yeast model for TDP‑43 proteinopathies, we observed that the vacuole (the yeast equivalent of lysosomes markedly contributed to the degradation of TDP‑43. This clearance occurred via TDP‑43-containing vesicles fusing with the vacuole through the concerted action of the endosomal-vacuolar (or endolysosomal pathway and autophagy. In line with its dominant role in the clearance of TDP‑43, endosomal-vacuolar pathway activity protected cells from the detrimental effects of TDP‑43. In contrast, enhanced autophagy contributed to TDP‑43 cytotoxicity, despite being involved in TDP‑43 degradation. TDP‑43’s interference with endosomal-vacuolar pathway activity may have two deleterious consequences. First, it interferes with its own degradation via this pathway, resulting in TDP‑43 accumulation. Second, it affects vacuolar proteolytic activity, which requires endosomal-vacuolar trafficking. We speculate that the latter contributes to aberrant autophagy. In sum, we propose that ameliorating endolysosomal pathway activity enhances cell survival in TDP‑43-associated diseases.

Oxytocin and vasopressin neural networks: Implications for social behavioral diversity and translational neuroscience.

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Johnson, Zachary V; Young, Larry J

2017-05-01

Oxytocin- and vasopressin-related systems are present in invertebrate and vertebrate bilaterian animals, including humans, and exhibit conserved neuroanatomical and functional properties. In vertebrates, these systems innervate conserved neural networks that regulate social learning and behavior, including conspecific recognition, social attachment, and parental behavior. Individual and species-level variation in central organization of oxytocin and vasopressin systems has been linked to individual and species variation in social learning and behavior. In humans, genetic polymorphisms in the genes encoding oxytocin and vasopressin peptides and/or their respective target receptors have been associated with individual variation in social recognition, social attachment phenotypes, parental behavior, and psychiatric phenotypes such as autism. Here we describe both conserved and variable features of central oxytocin and vasopressin systems in the context of social behavioral diversity, with a particular focus on neural networks that modulate social learning, behavior, and salience of sociosensory stimuli during species-typical social contexts. Published by Elsevier Ltd.

Fractional Hopfield Neural Networks: Fractional Dynamic Associative Recurrent Neural Networks.

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Pu, Yi-Fei; Yi, Zhang; Zhou, Ji-Liu

2017-10-01

This paper mainly discusses a novel conceptual framework: fractional Hopfield neural networks (FHNN). As is commonly known, fractional calculus has been incorporated into artificial neural networks, mainly because of its long-term memory and nonlocality. Some researchers have made interesting attempts at fractional neural networks and gained competitive advantages over integer-order neural networks. Therefore, it is naturally makes one ponder how to generalize the first-order Hopfield neural networks to the fractional-order ones, and how to implement FHNN by means of fractional calculus. We propose to introduce a novel mathematical method: fractional calculus to implement FHNN. First, we implement fractor in the form of an analog circuit. Second, we implement FHNN by utilizing fractor and the fractional steepest descent approach, construct its Lyapunov function, and further analyze its attractors. Third, we perform experiments to analyze the stability and convergence of FHNN, and further discuss its applications to the defense against chip cloning attacks for anticounterfeiting. The main contribution of our work is to propose FHNN in the form of an analog circuit by utilizing a fractor and the fractional steepest descent approach, construct its Lyapunov function, prove its Lyapunov stability, analyze its attractors, and apply FHNN to the defense against chip cloning attacks for anticounterfeiting. A significant advantage of FHNN is that its attractors essentially relate to the neuron's fractional order. FHNN possesses the fractional-order-stability and fractional-order-sensitivity characteristics.

Typicality and reasoning fallacies.

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Shafir, E B; Smith, E E; Osherson, D N

1990-05-01

The work of Tversky and Kahneman on intuitive probability judgment leads to the following prediction: The judged probability that an instance belongs to a category is an increasing function of the typicality of the instance in the category. To test this prediction, subjects in Experiment 1 read a description of a person (e.g., "Linda is 31, bright, ... outspoken") followed by a category. Some subjects rated how typical the person was of the category, while others rated the probability that the person belonged to that category. For categories like bank teller and feminist bank teller: (1) subjects rated the person as more typical of the conjunctive category (a conjunction effect); (2) subjects rated it more probable that the person belonged to the conjunctive category (a conjunction fallacy); and (3) the magnitudes of the conjunction effect and fallacy were highly correlated. Experiment 2 documents an inclusion fallacy, wherein subjects judge, for example, "All bank tellers are conservative" to be more probable than "All feminist bank tellers are conservative." In Experiment 3, results parallel to those of Experiment 1 were obtained with respect to the inclusion fallacy.

Atrial activation during atrioventricular nodal reentrant tachycardia: studies on retrograde fast pathway conduction

NARCIS (Netherlands)

Katritsis, Demosthenes G.; Ellenbogen, Kenneth A.; Becker, Anton E.

2006-01-01

Detailed right and left septal mapping of retrograde atrial activation during typical atrioventricular nodal reentrant tachycardia (AVNRT) has not been undertaken and may provide insight into the complex physiology of AVNRT, especially the anatomic localization of the fast and slow pathways. The

Self-stimulation in the rat: quantitative characteristics of the reward pathway.

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Gallistel, C R

1978-12-01

Quantitative characteristics of the neural pathway that carries the reinforcing signal in electrical self-stimulation of the brain were established by finding which combinations of stimulation parameters give the same performance in a runway. The reward for each run was a train of evenly spaced monophasic cathodal pulses from a monopolar electrode. With train duration and pulse frequency held constant, the required current was a hyperbolic function of pulse duration, with chronaxie c approximately 1.5 msec. With pulse duration held constant, the required strength of the train (the charge delivered per second) was a hyperbolic function of train duration, with chronaxie C approximately 500 msec. To a first approximation, the values of c and C were independent of the choice either of train duration and pulse frequency or of pulse duration, respectively. Hence, the current intensity required by any choice of train duration, pulse frequency, and pulse duration dependent on only two basic parameters, c and C, and one quantity, Qi, the required impulse charge. These may reflect, respectively, current integration by directly excited neurons; temporal integration of neural activity by synaptic processes in a neural network; and the peak of the impulse response of the network, assuming that the network has linear dynamics and that the reward depends on the peak of the output of the network.

Bidirectional neural interface: Closed-loop feedback control for hybrid neural systems.

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Chou, Zane; Lim, Jeffrey; Brown, Sophie; Keller, Melissa; Bugbee, Joseph; Broccard, Frédéric D; Khraiche, Massoud L; Silva, Gabriel A; Cauwenberghs, Gert

2015-01-01

Closed-loop neural prostheses enable bidirectional communication between the biological and artificial components of a hybrid system. However, a major challenge in this field is the limited understanding of how these components, the two separate neural networks, interact with each other. In this paper, we propose an in vitro model of a closed-loop system that allows for easy experimental testing and modification of both biological and artificial network parameters. The interface closes the system loop in real time by stimulating each network based on recorded activity of the other network, within preset parameters. As a proof of concept we demonstrate that the bidirectional interface is able to establish and control network properties, such as synchrony, in a hybrid system of two neural networks more significantly more effectively than the same system without the interface or with unidirectional alternatives. This success holds promise for the application of closed-loop systems in neural prostheses, brain-machine interfaces, and drug testing.

Typicality and misinformation: Two sources of distortion

Directory of Open Access Journals (Sweden)

Malen Migueles

2008-01-01

Full Text Available This study examined the effect of two sources of memory error: exposure to post-event information and extracting typical contents from schemata. Participants were shown a video of a bank robbery and presented with highand low-typicality misinformation extracted from two normative studies. The misleading suggestions consisted of either changes in the original video information or additions of completely new contents. In the subsequent recognition task the post-event misinformation produced memory impairment. The participants used the underlying schema of the event to extract high-typicality information which had become integrated with episodic information, thus giving rise to more hits and false alarms for these items. However, the effect of exposure to misinformation was greater on low-typicality items. There were no differences between changed or added information, but there were more false alarms when a low-typicality item was changed to a high-typicality item

A new perspective on behavioral inconsistency and neural noise in aging: Compensatory speeding of neural communication

Directory of Open Access Journals (Sweden)

S. Lee Hong

2012-09-01

Full Text Available This paper seeks to present a new perspective on the aging brain. Here, we make connections between two key phenomena of brain aging: 1 increased neural noise or random background activity; and 2 slowing of brain activity. Our perspective proposes the possibility that the slowing of neural processing due to decreasing nerve conduction velocities leads to a compensatory speeding of neuron firing rates. These increased firing rates lead to a broader distribution of power in the frequency spectrum of neural oscillations, which we propose, can just as easily be interpreted as neural noise. Compensatory speeding of neural activity, as we present, is constrained by the: A availability of metabolic energy sources; and B competition for frequency bandwidth needed for neural communication. We propose that these constraints lead to the eventual inability to compensate for age-related declines in neural function that are manifested clinically as deficits in cognition, affect, and motor behavior.

cables1 Is Required for Embryonic Neural Development: Molecular, Cellular, and Behavioral Evidence From the Zebrafish

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GROENEWEG, JOLIJN W.; WHITE, YVONNE A.R.; KOKEL, DAVID; PETERSON, RANDALL T.; ZUKERBERG, LAWRENCE R.; BERIN, INNA; RUEDA, BO R.; WOOD, ANTONY W.

2014-01-01

SUMMARY In vitro studies have suggested that the Cables1 gene regulates epithelial cell proliferation, whereas other studies suggest a role in promoting neural differentiation. In efforts to clarify the functions of Cables1 in vivo, we conducted gain- and loss-of-function studies targeting its ortholog (cables1) in the zebrafish embryo. Similar to rodents, zebrafish cables1 mRNA expression is detected most robustly in embryonic neural tissues. Antisense knockdown of cables1 leads to increased numbers of apoptotic cells, particularly in brain tissue, in addition to a distinct behavioral phenotype, characterized by hyperactivity in response to stimulation. Apoptosis and the behavioral abnormality could be rescued by co-expression of a morpholino-resistant cables1 construct. Suppression of p53 expression in cables1 morphants partially rescued both apoptosis and the behavioral phenotype, suggesting that the phenotype of cables1 morphants is due in part to p53-dependent apoptosis. Alterations in the expression patterns of several neural transcription factors were observed in cables1 morphants during early neurulation, suggesting that cables1 is required for early neural differentiation. Ectopic overexpression of cables1 strongly disrupted embryonic morphogenesis, while overexpression of a cables1 mutant lacking the C-terminal cyclin box had little effect, suggesting functional importance of the cyclin box. Lastly, marked reductions in p35, but not Cdk5, were observed in cables1 morphants. Collectively, these data suggest that cables1 is important for neural differentiation during embryogenesis, in a mechanism that likely involves interactions with the Cdk5/p35 kinase pathway. PMID:21268180

Volumetric multimodality neural network for brain tumor segmentation

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Silvana Castillo, Laura; Alexandra Daza, Laura; Carlos Rivera, Luis; Arbeláez, Pablo

2017-11-01

Brain lesion segmentation is one of the hardest tasks to be solved in computer vision with an emphasis on the medical field. We present a convolutional neural network that produces a semantic segmentation of brain tumors, capable of processing volumetric data along with information from multiple MRI modalities at the same time. This results in the ability to learn from small training datasets and highly imbalanced data. Our method is based on DeepMedic, the state of the art in brain lesion segmentation. We develop a new architecture with more convolutional layers, organized in three parallel pathways with different input resolution, and additional fully connected layers. We tested our method over the 2015 BraTS Challenge dataset, reaching an average dice coefficient of 84%, while the standard DeepMedic implementation reached 74%.

Sequential neural models with stochastic layers

DEFF Research Database (Denmark)

Fraccaro, Marco; Sønderby, Søren Kaae; Paquet, Ulrich

2016-01-01

How can we efficiently propagate uncertainty in a latent state representation with recurrent neural networks? This paper introduces stochastic recurrent neural networks which glue a deterministic recurrent neural network and a state space model together to form a stochastic and sequential neural...... generative model. The clear separation of deterministic and stochastic layers allows a structured variational inference network to track the factorization of the model's posterior distribution. By retaining both the nonlinear recursive structure of a recurrent neural network and averaging over...

Lifelong bilingualism maintains neural efficiency for cognitive control in aging.

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Gold, Brian T; Kim, Chobok; Johnson, Nathan F; Kryscio, Richard J; Smith, Charles D

2013-01-09

Recent behavioral data have shown that lifelong bilingualism can maintain youthful cognitive control abilities in aging. Here, we provide the first direct evidence of a neural basis for the bilingual cognitive control boost in aging. Two experiments were conducted, using a perceptual task-switching paradigm, including a total of 110 participants. In Experiment 1, older adult bilinguals showed better perceptual switching performance than their monolingual peers. In Experiment 2, younger and older adult monolinguals and bilinguals completed the same perceptual task-switching experiment while functional magnetic resonance imaging (fMRI) was performed. Typical age-related performance reductions and fMRI activation increases were observed. However, like younger adults, bilingual older adults outperformed their monolingual peers while displaying decreased activation in left lateral frontal cortex and cingulate cortex. Critically, this attenuation of age-related over-recruitment associated with bilingualism was directly correlated with better task-switching performance. In addition, the lower blood oxygenation level-dependent response in frontal regions accounted for 82% of the variance in the bilingual task-switching reaction time advantage. These results suggest that lifelong bilingualism offsets age-related declines in the neural efficiency for cognitive control processes.