WorldWideScience

Sample records for neural connections depends

  1. Activity-dependent modulation of neural circuit synaptic connectivity

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    Charles R Tessier

    2009-07-01

    Full Text Available In many nervous systems, the establishment of neural circuits is known to proceed via a two-stage process; 1 early, activity-independent wiring to produce a rough map characterized by excessive synaptic connections, and 2 subsequent, use-dependent pruning to eliminate inappropriate connections and reinforce maintained synapses. In invertebrates, however, evidence of the activity-dependent phase of synaptic refinement has been elusive, and the dogma has long been that invertebrate circuits are “hard-wired” in a purely activity-independent manner. This conclusion has been challenged recently through the use of new transgenic tools employed in the powerful Drosophila system, which have allowed unprecedented temporal control and single neuron imaging resolution. These recent studies reveal that activity-dependent mechanisms are indeed required to refine circuit maps in Drosophila during precise, restricted windows of late-phase development. Such mechanisms of circuit refinement may be key to understanding a number of human neurological diseases, including developmental disorders such as Fragile X syndrome (FXS and autism, which are hypothesized to result from defects in synaptic connectivity and activity-dependent circuit function. This review focuses on our current understanding of activity-dependent synaptic connectivity in Drosophila, primarily through analyzing the role of the fragile X mental retardation protein (FMRP in the Drosophila FXS disease model. The particular emphasis of this review is on the expanding array of new genetically-encoded tools that are allowing cellular events and molecular players to be dissected with ever greater precision and detail.

  2. On sparsely connected optimal neural networks

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    Beiu, V. [Los Alamos National Lab., NM (United States); Draghici, S. [Wayne State Univ., Detroit, MI (United States)

    1997-10-01

    This paper uses two different approaches to show that VLSI- and size-optimal discrete neural networks are obtained for small fan-in values. These have applications to hardware implementations of neural networks, but also reveal an intrinsic limitation of digital VLSI technology: its inability to cope with highly connected structures. The first approach is based on implementing F{sub n,m} functions. The authors show that this class of functions can be implemented in VLSI-optimal (i.e., minimizing AT{sup 2}) neural networks of small constant fan-ins. In order to estimate the area (A) and the delay (T) of such networks, the following cost functions will be used: (i) the connectivity and the number-of-bits for representing the weights and thresholds--for good estimates of the area; and (ii) the fan-ins and the length of the wires--for good approximates of the delay. The second approach is based on implementing Boolean functions for which the classical Shannon`s decomposition can be used. Such a solution has already been used to prove bounds on the size of fan-in 2 neural networks. They will generalize the result presented there to arbitrary fan-in, and prove that the size is minimized by small fan-in values. Finally, a size-optimal neural network of small constant fan-ins will be suggested for F{sub n,m} functions.

  3. Knowledge synthesis with maps of neural connectivity

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    Marcelo eTallis

    2011-11-01

    Full Text Available This paper describes software for neuroanatomical knowledge synthesis based on high-quality neural connectivity data. This software supports a mature neuroanatomical methodology developed since the early 1990s. Over this time, the Swanson laboratory at USC has generated an account of the neural connectivity of the sub-structures of the hypothalamus, amygdala, septum, hippocampus and bed nucleus of the stria terminalis. This is based on neuroanatomical data maps drawn into a standard brain atlas by experts. In earlier work, we presented an application for visualizing and comparing anatomical macroconnections using the Swanson 3rd edition atlas as a framework for accurate registration. Here we describe major improvements to the NeuARt application based on the incorporation of a knowledge representation of experimental design. We also present improvements in the interface and features of the neuroanatomical data mapping components within a unified web-application. As a step towards developing an accurate sub-regional account of neural connectivity, we provide navigational access between the neuroanatomical data maps and a semantic representation of area-to-area connections that they support. We do so based on an approach called ’Knowledge Engineering from Experimental Design’ (KEfED model that is based on experimental variables. We have extended the underlying KEfED representation of tract-tracing experiments by incorporating the definition of a neuronanatomical data map as a measurement variable in the study design. This paper describes the software design of a web application that allows anatomical data sets to be described within a standard experimental context and thus incorporated with non-spatial data sets.

  4. Neural network connectivity and response latency modelled by stochastic processes

    DEFF Research Database (Denmark)

    Tamborrino, Massimiliano

    is connected to thousands of other neurons. The rst question is: how to model neural networks through stochastic processes? A multivariate Ornstein-Uhlenbeck process, obtained as a diffusion approximation of a jump process, is the proposed answer. Obviously, dependencies between neurons imply dependencies......Stochastic processes and their rst passage times have been widely used to describe the membrane potential dynamics of single neurons and to reproduce neuronal spikes, respectively.However, cerebral cortex in human brains is estimated to contain 10-20 billions of neurons and each of them...... between their spike times. Therefore, the second question is: how to detect neural network connectivity from simultaneously recorded spike trains? Answering this question corresponds to investigate the joint distribution of sequences of rst passage times. A non-parametric method based on copulas...

  5. Neural network connectivity and response latency modelled by stochastic processes

    DEFF Research Database (Denmark)

    Tamborrino, Massimiliano

    is connected to thousands of other neurons. The rst question is: how to model neural networks through stochastic processes? A multivariate Ornstein-Uhlenbeck process, obtained as a diffusion approximation of a jump process, is the proposed answer. Obviously, dependencies between neurons imply dependencies...... between their spike times. Therefore, the second question is: how to detect neural network connectivity from simultaneously recorded spike trains? Answering this question corresponds to investigate the joint distribution of sequences of rst passage times. A non-parametric method based on copulas...... generation of pikes. When a stimulus is applied to the network, the spontaneous rings may prevail and hamper detection of the effects of the stimulus. Therefore, the spontaneous rings cannot be ignored and the response latency has to be detected on top of a background signal. Everything becomes more dicult...

  6. A novel method linking neural connectivity to behavioral fluctuations: Behavior-regressed connectivity.

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    Passaro, Antony D; Vettel, Jean M; McDaniel, Jonathan; Lawhern, Vernon; Franaszczuk, Piotr J; Gordon, Stephen M

    2017-03-01

    During an experimental session, behavioral performance fluctuates, yet most neuroimaging analyses of functional connectivity derive a single connectivity pattern. These conventional connectivity approaches assume that since the underlying behavior of the task remains constant, the connectivity pattern is also constant. We introduce a novel method, behavior-regressed connectivity (BRC), to directly examine behavioral fluctuations within an experimental session and capture their relationship to changes in functional connectivity. This method employs the weighted phase lag index (WPLI) applied to a window of trials with a weighting function. Using two datasets, the BRC results are compared to conventional connectivity results during two time windows: the one second before stimulus onset to identify predictive relationships, and the one second after onset to capture task-dependent relationships. In both tasks, we replicate the expected results for the conventional connectivity analysis, and extend our understanding of the brain-behavior relationship using the BRC analysis, demonstrating subject-specific BRC maps that correspond to both positive and negative relationships with behavior. Comparison with Existing Method(s): Conventional connectivity analyses assume a consistent relationship between behaviors and functional connectivity, but the BRC method examines performance variability within an experimental session to understand dynamic connectivity and transient behavior. The BRC approach examines connectivity as it covaries with behavior to complement the knowledge of underlying neural activity derived from conventional connectivity analyses. Within this framework, BRC may be implemented for the purpose of understanding performance variability both within and between participants. Published by Elsevier B.V.

  7. Entrainment of Arteriole Vasomotor Fluctuations by Neural Activity Is a Basis of Blood-Oxygenation-Level-Dependent "Resting-State" Connectivity.

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    Mateo, Celine; Knutsen, Per M; Tsai, Philbert S; Shih, Andy Y; Kleinfeld, David

    2017-11-15

    Resting-state signals in blood-oxygenation-level-dependent (BOLD) imaging are used to parcellate brain regions and define "functional connections" between regions. Yet a physiological link between fluctuations in blood oxygenation with those in neuronal signaling pathways is missing. We present evidence from studies on mouse cortex that modulation of vasomotion, i.e., intrinsic ultra-slow (0.1 Hz) fluctuations in arteriole diameter, provides this link. First, ultra-slow fluctuations in neuronal signaling, which occur as an envelope over γ-band activity, entrains vasomotion. Second, optogenetic manipulations confirm that entrainment is unidirectional. Third, co-fluctuations in the diameter of pairs of arterioles within the same hemisphere diminish to chance for separations >1.4 mm. Yet the diameters of arterioles in distant (>5 mm), mirrored transhemispheric sites strongly co-fluctuate; these correlations are diminished in acallosal mice. Fourth, fluctuations in arteriole diameter coherently drive fluctuations in blood oxygenation. Thus, entrainment of vasomotion links neuronal pathways to functional connections. Copyright © 2017. Published by Elsevier Inc.

  8. Rod-Shaped Neural Units for Aligned 3D Neural Network Connection.

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    Kato-Negishi, Midori; Onoe, Hiroaki; Ito, Akane; Takeuchi, Shoji

    2017-08-01

    This paper proposes neural tissue units with aligned nerve fibers (called rod-shaped neural units) that connect neural networks with aligned neurons. To make the proposed units, 3D fiber-shaped neural tissues covered with a calcium alginate hydrogel layer are prepared with a microfluidic system and are cut in an accurate and reproducible manner. These units have aligned nerve fibers inside the hydrogel layer and connectable points on both ends. By connecting the units with a poly(dimethylsiloxane) guide, 3D neural tissues can be constructed and maintained for more than two weeks of culture. In addition, neural networks can be formed between the different neural units via synaptic connections. Experimental results indicate that the proposed rod-shaped neural units are effective tools for the construction of spatially complex connections with aligned nerve fibers in vitro. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  9. Neural substrates of context- and person-dependent altruistic punishment.

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    Wang, Lili; Lu, Xiaping; Gu, Ruolei; Zhu, Ruida; Xu, Rui; Broster, Lucas S; Feng, Chunliang

    2017-11-01

    Human altruistic behaviors are heterogeneous across both contexts and people, whereas the neural signatures underlying the heterogeneity remain to be elucidated. To address this issue, we examined the neural signatures underlying the context- and person-dependent altruistic punishment, conjoining event-related fMRI with both task-based and resting-state functional connectivity (RSFC). Acting as an impartial third party, participants decided how to punish norm violators either alone or in the presence of putative others. We found that the presence of others decreased altruistic punishment due to diffusion of responsibility. Those behavioral effects paralleled altered neural responses in the dorsal anterior cingulate cortex (dACC) and putamen. Further, we identified modulation of responsibility diffusion on task-based functional connectivity of dACC with the brain regions implicated in reward processing (i.e., posterior cingulate cortex and amygdala/orbital frontal cortex). Finally, the RSFC results revealed that (i) increased intrinsic connectivity strengths of the putamen with temporoparietal junction and dorsolateral PFC were associated with attenuated responsibility diffusion in altruistic punishment and (ii) increased putamen-dorsomedial PFC connectivity strengths were associated with reduced responsibility diffusion in self-reported responsibility. Taken together, our findings elucidate the context- and person-dependent altruistic behaviors as well as associated neural substrates and thus provide a potential neurocognitive mechanism of heterogeneous human altruistic behaviors. Hum Brain Mapp 38:5535-5550, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  10. Adolescent nicotine induces persisting changes in development of neural connectivity.

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    Smith, Robert F; McDonald, Craig G; Bergstrom, Hadley C; Ehlinger, Daniel G; Brielmaier, Jennifer M

    2015-08-01

    Adolescent nicotine induces persisting changes in development of neural connectivity. A large number of brain changes occur during adolescence as the CNS matures. These changes suggest that the adolescent brain may still be susceptible to developmental alterations by substances which impact its growth. Here we review recent studies on adolescent nicotine which show that the adolescent brain is differentially sensitive to nicotine-induced alterations in dendritic elaboration, in several brain areas associated with processing reinforcement and emotion, specifically including nucleus accumbens, medial prefrontal cortex, basolateral amygdala, bed nucleus of the stria terminalis, and dentate gyrus. Both sensitivity to nicotine, and specific areas responding to nicotine, differ between adolescent and adult rats, and dendritic changes in response to adolescent nicotine persist into adulthood. Areas sensitive to, and not sensitive to, structural remodeling induced by adolescent nicotine suggest that the remodeling generally corresponds to the extended amygdala. Evidence suggests that dendritic remodeling is accompanied by persisting changes in synaptic connectivity. Modeling, electrophysiological, neurochemical, and behavioral data are consistent with the implication of our anatomical studies showing that adolescent nicotine induces persisting changes in neural connectivity. Emerging data thus suggest that early adolescence is a period when nicotine consumption, presumably mediated by nicotine-elicited changes in patterns of synaptic activity, can sculpt late brain development, with consequent effects on synaptic interconnection patterns and behavior regulation. Adolescent nicotine may induce a more addiction-prone phenotype, and the structures altered by nicotine also subserve some emotional and cognitive functions, which may also be altered. We suggest that dendritic elaboration and associated changes are mediated by activity-dependent synaptogenesis, acting in part

  11. Estimation of Effectivty Connectivity via Data-Driven Neural Modeling

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    Dean Robert Freestone

    2014-11-01

    Full Text Available This research introduces a new method for functional brain imaging via a process of model inversion. By estimating parameters of a computational model, we are able to track effective connectivity and mean membrane potential dynamics that cannot be directly measured using electrophysiological measurements alone. The ability to track the hidden aspects of neurophysiology will have a profound impact on the way we understand and treat epilepsy. For example, under the assumption the model captures the key features of the cortical circuits of interest, the framework will provide insights into seizure initiation and termination on a patient-specific basis. It will enable investigation into the effect a particular drug has on specific neural populations and connectivity structures using minimally invasive measurements. The method is based on approximating brain networks using an interconnected neural population model. The neural population model is based on a neural mass model that describes the functional activity of the brain, capturing the mesoscopic biophysics and anatomical structure. The model is made subject-specific by estimating the strength of intra-cortical connections within a region and inter-cortical connections between regions using a novel Kalman filtering method. We demonstrate through simulation how the framework can be used the track the mechanisms involved in seizure initiation and termination.

  12. Coherency and connectivity in oscillating neural networks: linear partialization analysis

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    Kalitzin, S.; van Dijk, B. W.; Spekreijse, H.; van Leeuwen, W. A.

    1997-01-01

    This paper studies the relation between the functional synaptic connections between two artificial neural networks and the correlation of their spiking activities. The model neurons had realistic non-oscillatory dynamic properties and the networks showed oscillatory behavior as a result of their

  13. A Bayesian compressed-sensing approach for reconstructing neural connectivity from subsampled anatomical data.

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    Mishchenko, Yuriy; Paninski, Liam

    2012-10-01

    In recent years, the problem of reconstructing the connectivity in large neural circuits ("connectomics") has re-emerged as one of the main objectives of neuroscience. Classically, reconstructions of neural connectivity have been approached anatomically, using electron or light microscopy and histological tracing methods. This paper describes a statistical approach for connectivity reconstruction that relies on relatively easy-to-obtain measurements using fluorescent probes such as synaptic markers, cytoplasmic dyes, transsynaptic tracers, or activity-dependent dyes. We describe the possible design of these experiments and develop a Bayesian framework for extracting synaptic neural connectivity from such data. We show that the statistical reconstruction problem can be formulated naturally as a tractable L₁-regularized quadratic optimization. As a concrete example, we consider a realistic hypothetical connectivity reconstruction experiment in C. elegans, a popular neuroscience model where a complete wiring diagram has been previously obtained based on long-term electron microscopy work. We show that the new statistical approach could lead to an orders of magnitude reduction in experimental effort in reconstructing the connectivity in this circuit. We further demonstrate that the spatial heterogeneity and biological variability in the connectivity matrix--not just the "average" connectivity--can also be estimated using the same method.

  14. Neuromodulatory connectivity defines the structure of a behavioral neural network.

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    Diao, Feici; Elliott, Amicia D; Diao, Fengqiu; Shah, Sarav; White, Benjamin H

    2017-11-22

    Neural networks are typically defined by their synaptic connectivity, yet synaptic wiring diagrams often provide limited insight into network function. This is due partly to the importance of non-synaptic communication by neuromodulators, which can dynamically reconfigure circuit activity to alter its output. Here, we systematically map the patterns of neuromodulatory connectivity in a network that governs a developmentally critical behavioral sequence in Drosophila. This sequence, which mediates pupal ecdysis, is governed by the serial release of several key factors, which act both somatically as hormones and within the brain as neuromodulators. By identifying and characterizing the functions of the neuronal targets of these factors, we find that they define hierarchically organized layers of the network controlling the pupal ecdysis sequence: a modular input layer, an intermediate central pattern generating layer, and a motor output layer. Mapping neuromodulatory connections in this system thus defines the functional architecture of the network.

  15. Reorganization of the Connectivity between Elementary Functions – A Model Relating Conscious States to Neural Connections

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    Jesper Mogensen

    2017-04-01

    Full Text Available In the present paper it is argued that the “neural correlate of consciousness” (NCC does not appear to be a separate “module” – but an aspect of information processing within the neural substrate of various cognitive processes. Consequently, NCC can only be addressed adequately within frameworks that model the general relationship between neural processes and mental states – and take into account the dynamic connectivity of the brain. We presently offer the REFGEN (general reorganization of elementary functions model as such a framework. This model builds upon and expands the REF (reorganization of elementary functions and REFCON (of elementary functions and consciousness models. All three models integrate the relationship between the neural and mental layers of description via the construction of an intermediate level dealing with computational states. The importance of experience based organization of neural and cognitive processes is stressed. The models assume that the mechanisms of consciousness are in principle the same as the basic mechanisms of all aspects of cognition – when information is processed to a sufficiently “high level” it becomes available to conscious experience. The NCC is within the REFGEN model seen as aspects of the dynamic and experience driven reorganizations of the synaptic connectivity between the neurocognitive “building blocks” of the model – the elementary functions.

  16. Identification of neural connectivity signatures of autism using machine learning

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    Gopikrishna eDeshpande

    2013-10-01

    Full Text Available Alterations in neural connectivity have been suggested as a signature of the pathobiology of autism. Although disrupted correlation between cortical regions observed from functional MRI is considered to be an explanatory model for autism, the directional causal influence between brain regions is a vital link missing in these studies. The current study focuses on addressing this in an fMRI study of Theory-of-Mind in 15 high-functioning adolescents and adults with autism (ASD and 15 typically developing (TD controls. Participants viewed a series of comic strip vignettes in the MRI scanner and were asked to choose the most logical end to the story from three alternatives, separately for trials involving physical and intentional causality. Causal brain connectivity obtained from a multivariate autoregressive model, along with assessment scores, functional connectivity values, and fractional anisotropy obtained from DTI data for each participant, were submitted to a recursive cluster elimination based support vector machine classifier to determine the accuracy with which the classifier can predict a novel participant’s group membership (ASD or TD. We found a maximum classification accuracy of 95.9 % with 19 features which had the highest discriminative ability between the groups. All of the 19 features were effective connectivity paths, indicating that causal information may be critical in discriminating between ASD and TD groups. These effective connectivity paths were also found to be significantly greater in controls as compared to ASD participants and consisted predominantly of outputs from the fusiform face area and middle temporal gyrus indicating impaired connectivity in ASD participants, particularly in the social brain areas. These findings collectively point towards the fact that alterations in causal brain connectivity in individuals with ASD could serve as a potential non-invasive neuroimaging signature for autism

  17. Training for Micrographia Alters Neural Connectivity in Parkinson's Disease

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    Evelien Nackaerts

    2018-01-01

    Full Text Available Despite recent advances in clarifying the neural networks underlying rehabilitation in Parkinson's disease (PD, the impact of prolonged motor learning interventions on brain connectivity in people with PD is currently unknown. Therefore, the objective of this study was to compare cortical network changes after 6 weeks of visually cued handwriting training (= experimental with a placebo intervention to address micrographia, a common problem in PD. Twenty seven early Parkinson's patients on dopaminergic medication performed a pre-writing task in both the presence and absence of visual cues during behavioral tests and during fMRI. Subsequently, patients were randomized to the experimental (N = 13 or placebo intervention (N = 14 both lasting 6 weeks, after which they underwent the same testing procedure. We used dynamic causal modeling to compare the neural network dynamics in both groups before and after training. Most importantly, intensive writing training propagated connectivity via the left hemispheric visuomotor stream to an increased coupling with the supplementary motor area, not witnessed in the placebo group. Training enhanced communication in the left visuomotor integration system in line with the learned visually steered training. Notably, this pattern was apparent irrespective of the presence of cues, suggesting transfer from cued to uncued handwriting. We conclude that in early PD intensive motor skill learning, which led to clinical improvement, alters cortical network functioning. We showed for the first time in a placebo-controlled design that it remains possible to enhance the drive to the supplementary motor area through motor learning.

  18. Alterations in neural connectivity in preterm children at school age.

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    Gozzo, Yeisid; Vohr, Betty; Lacadie, Cheryl; Hampson, Michelle; Katz, Karol H; Maller-Kesselman, Jill; Schneider, Karen C; Peterson, Bradley S; Rajeevan, Nallakkandi; Makuch, Robert W; Constable, R Todd; Ment, Laura R

    2009-11-01

    Converging data suggest recovery from injury in the preterm brain. We used functional magnetic resonance imaging (fMRI) to test the hypothesis that cerebral connectivity involving Wernicke's area and other important cortical language regions would differ between preterm (PT) and term (T) control school age children during performance of an auditory language task. Fifty-four PT children (600-1250 g birth weight) and 24 T controls were evaluated using an fMRI passive language task and neurodevelopmental assessments including: the Wechsler Intelligence Scale for Children - III (WISC-III), the Peabody Individual Achievement Test - Revised (PIAT-R) and the Peabody Picture Vocabulary Test - Revised (PPVT-R) at 8 years of age. Neural activity was assessed for language processing and the data were evaluated for connectivity and correlations to cognitive outcomes. We found that PT subjects scored significantly lower on all components of the WISC-III (planguage function at school age differently than T controls; these alterations may represent a delay in maturation of neural networks or the engagement of alternate circuits for language processing.

  19. Identification of neural connectivity signatures of autism using machine learning.

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    Deshpande, Gopikrishna; Libero, Lauren E; Sreenivasan, Karthik R; Deshpande, Hrishikesh D; Kana, Rajesh K

    2013-01-01

    Alterations in interregional neural connectivity have been suggested as a signature of the pathobiology of autism. There have been many reports of functional and anatomical connectivity being altered while individuals with autism are engaged in complex cognitive and social tasks. Although disrupted instantaneous correlation between cortical regions observed from functional MRI is considered to be an explanatory model for autism, the causal influence of a brain area on another (effective connectivity) is a vital link missing in these studies. The current study focuses on addressing this in an fMRI study of Theory-of-Mind (ToM) in 15 high-functioning adolescents and adults with autism and 15 typically developing control participants. Participants viewed a series of comic strip vignettes in the MRI scanner and were asked to choose the most logical end to the story from three alternatives, separately for trials involving physical and intentional causality. The mean time series, extracted from 18 activated regions of interest, were processed using a multivariate autoregressive model (MVAR) to obtain the causality matrices for each of the 30 participants. These causal connectivity weights, along with assessment scores, functional connectivity values, and fractional anisotropy obtained from DTI data for each participant, were submitted to a recursive cluster elimination based support vector machine classifier to determine the accuracy with which the classifier can predict a novel participant's group membership (autism or control). We found a maximum classification accuracy of 95.9% with 19 features which had the highest discriminative ability between the groups. All of the 19 features were effective connectivity paths, indicating that causal information may be critical in discriminating between autism and control groups. These effective connectivity paths were also found to be significantly greater in controls as compared to ASD participants and consisted predominantly of

  20. Dopamine-Dependent Architecture of Cortico-Subcortical Network Connectivity

    NARCIS (Netherlands)

    Cole, D.M.; Oei, N.Y.; Soeter, R.P.; Both, S.; van Gerven, J.M.; Rombouts, S.A.; Beckmann, Christian

    2013-01-01

    Maladaptive dopaminergic mediation of reward processing in humans is thought to underlie multiple neuropsychiatric disorders, including addiction, Parkinson's disease, and schizophrenia. Mechanisms responsible for the development of such disorders may depend on individual differences in neural

  1. Recurrent connections form a phase-locking neuronal tuner for frequency-dependent selective communication.

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    Shin, Dongkwan; Cho, Kwang-Hyun

    2013-01-01

    The brain requires task-dependent interregional coherence of information flow in the anatomically connected neural network. However, it is still unclear how a neuronal group can flexibly select its communication target. In this study, we revealed a hidden routing mechanism on the basis of recurrent connections. Our simulation results based on the spike response model show that recurrent connections between excitatory and inhibitory neurons modulate the resonant frequency of a local neuronal group, and that this modulation enables a neuronal group to receive selective information by filtering a preferred frequency component. We also found that the recurrent connection facilitates the successful routing of any necessary information flow between neuronal groups through frequency-dependent resonance of synchronized oscillations. Taken together, these results suggest that recurrent connections act as a phase-locking neuronal tuner which determines the resonant frequency of a local group and thereby controls the preferential routing of incoming signals.

  2. Measuring symmetry, asymmetry and randomness in neural network connectivity.

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    Umberto Esposito

    Full Text Available Cognitive functions are stored in the connectome, the wiring diagram of the brain, which exhibits non-random features, so-called motifs. In this work, we focus on bidirectional, symmetric motifs, i.e. two neurons that project to each other via connections of equal strength, and unidirectional, non-symmetric motifs, i.e. within a pair of neurons only one neuron projects to the other. We hypothesise that such motifs have been shaped via activity dependent synaptic plasticity processes. As a consequence, learning moves the distribution of the synaptic connections away from randomness. Our aim is to provide a global, macroscopic, single parameter characterisation of the statistical occurrence of bidirectional and unidirectional motifs. To this end we define a symmetry measure that does not require any a priori thresholding of the weights or knowledge of their maximal value. We calculate its mean and variance for random uniform or Gaussian distributions, which allows us to introduce a confidence measure of how significantly symmetric or asymmetric a specific configuration is, i.e. how likely it is that the configuration is the result of chance. We demonstrate the discriminatory power of our symmetry measure by inspecting the eigenvalues of different types of connectivity matrices. We show that a Gaussian weight distribution biases the connectivity motifs to more symmetric configurations than a uniform distribution and that introducing a random synaptic pruning, mimicking developmental regulation in synaptogenesis, biases the connectivity motifs to more asymmetric configurations, regardless of the distribution. We expect that our work will benefit the computational modelling community, by providing a systematic way to characterise symmetry and asymmetry in network structures. Further, our symmetry measure will be of use to electrophysiologists that investigate symmetry of network connectivity.

  3. Connectivity dependence of Fano resonances in single molecules

    OpenAIRE

    Grace, Ali K. Ismael Iain; Lambert, Colin J.

    2017-01-01

    Using a first principles approach combined with analysis of heuristic tight-binding models, we examine the connectivity dependence of two forms of quantum interference in single molecules. Based on general arguments, Fano resonances are shown to be insensitive to connectivity, while Mach-Zehnder-type interference features are shown to be connectivity dependent. This behaviour is found to occur in molecular wires containing anthraquinone units, in which the pendant carbonyl groups create Fano ...

  4. Striatal activation and frontostriatal connectivity during non-drug reward anticipation in alcohol dependence.

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    Becker, Alena; Kirsch, Martina; Gerchen, Martin Fungisai; Kiefer, Falk; Kirsch, Peter

    2017-05-01

    According to prevailing neurobiological theories of addiction, altered function in neural reward circuitry is a central mechanism of alcohol dependence. Growing evidence postulates that the ventral striatum (VS), as well as areas of the prefrontal cortex, contribute to the increased incentive salience of alcohol-associated cues, diminished motivation to pursue non-drug rewards and weakened strength of inhibitory cognitive control, which are central to addiction. The present study aims to investigate the neural response and functional connectivity underlying monetary, non-drug reward processing in alcohol dependence. We utilized a reward paradigm to investigate the anticipation of monetary reward in 32 alcohol-dependent inpatients and 35 healthy controls. Functional magnetic resonance imaging was used to measure task-related brain activation and connectivity. Alcohol-dependent patients showed increased activation of the VS during anticipation of monetary gain compared with healthy controls. Generalized psychophysiological interaction analyses revealed decreased functional connectivity between the VS and the dorsolateral prefrontal cortex in alcohol dependent patients relative to controls. Increased activation of the VS and reduced frontostriatal connectivity were associated with increased craving. These findings provide evidence that alcohol dependence is rather associated with disrupted integration of striatal and prefrontal processes than with a global reward anticipation deficit. © 2016 Society for the Study of Addiction.

  5. A closer look at the apparent correlation of structural and functional connectivity in excitable neural networks

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    Messé, Arnaud; Hütt, Marc-Thorsten; König, Peter; Hilgetag, Claus C.

    2015-01-01

    The relationship between the structural connectivity (SC) and functional connectivity (FC) of neural systems is a central focus in brain network science. It is an open question, however, how strongly the SC-FC relationship depends on specific topological features of brain networks or the models used for describing excitable dynamics. Using a basic model of discrete excitable units that follow a susceptible - excited - refractory dynamic cycle (SER model), we here analyze how functional connectivity is shaped by the topological features of a neural network, in particular its modularity. We compared the results obtained by the SER model with corresponding simulations by another well established dynamic mechanism, the Fitzhugh-Nagumo model, in order to explore general features of the SC-FC relationship. We showed that apparent discrepancies between the results produced by the two models can be resolved by adjusting the time window of integration of co-activations from which the FC is derived, providing a clearer distinction between co-activations and sequential activations. Thus, network modularity appears as an important factor shaping the FC-SC relationship across different dynamic models.

  6. Activity-dependent neural plasticity from bench to bedside.

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    Ganguly, Karunesh; Poo, Mu-Ming

    2013-10-30

    Much progress has been made in understanding how behavioral experience and neural activity can modify the structure and function of neural circuits during development and in the adult brain. Studies of physiological and molecular mechanisms underlying activity-dependent plasticity in animal models have suggested potential therapeutic approaches for a wide range of brain disorders in humans. Physiological and electrical stimulations as well as plasticity-modifying molecular agents may facilitate functional recovery by selectively enhancing existing neural circuits or promoting the formation of new functional circuits. Here, we review the advances in basic studies of neural plasticity mechanisms in developing and adult nervous systems and current clinical treatments that harness neural plasticity, and we offer perspectives on future development of plasticity-based therapy. Copyright © 2013 Elsevier Inc. All rights reserved.

  7. Synaptic organizations and dynamical properties of weakly connected neural oscillators. II. Learning phase information.

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    Hoppensteadt, F C; Izhikevich, E M

    1996-08-01

    This is the second of two articles devoted to analyzing the relationship between synaptic organizations (anatomy) and dynamical properties (function) of networks of neural oscillators near multiple supercritical Andronov-Hopf bifurcation points. Here we analyze learning processes in such networks. Regarding learning dynamics, we assume (1) learning is local (i.e. synaptic modification depends on pre- and postsynaptic neurons but not on others), (2) synapses modify slowly relative to characteristic neuron response times, (3) in the absence of either pre- or postsynaptic activity, the synapse weakens (forgets). Our major goal is to analyze all synaptic organizations of oscillatory neural networks that can memorize and retrieve phase information or time delays. We show that such network have the following attributes: (1) the rate of synaptic plasticity connected with learning is determined locally by the presynaptic neurons, (2) the excitatory neurons must be long-axon relay neurons capable of forming distant connections with other excitatory and inhibitory neurons, (3) if inhibitory neurons have long axons, then the network can learn, passively forget and actively unlearn information by adjusting synaptic plasticity rates.

  8. Connectivity dependence of Fano resonances in single molecules.

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    Ismael, Ali K; Grace, Iain; Lambert, Colin J

    2017-03-01

    Using a first principles approach combined with analysis of heuristic tight-binding models, we examine the connectivity dependence of two forms of quantum interference in single molecules. Based on general arguments, Fano resonances are shown to be insensitive to connectivity, while Mach-Zehnder-type interference features are shown to be connectivity dependent. This behaviour is found to occur in molecular wires containing anthraquinone units, in which the pendant carbonyl groups create Fano resonances, which coexist with multiple-path quantum interference features.

  9. ORBITAL CONNECTIONS FOR PERTURBATION-DEPENDENT BASIS-SETS

    DEFF Research Database (Denmark)

    Olsen, Jeppe; Bak, Keld L.; Ruud, K.

    1995-01-01

    The use of perturbation-dependent basis sets is analysed with emphasis on the connection between the basis sets at different values of the perturbation strength. A particular connection, the natural connection, that minimizes the change of the basis set orbitals is devised and the second quantiza......The use of perturbation-dependent basis sets is analysed with emphasis on the connection between the basis sets at different values of the perturbation strength. A particular connection, the natural connection, that minimizes the change of the basis set orbitals is devised and the second...... quantization realization of this connection is introduced. It is shown that the natural connection is important for the efficient evaluation of molecular properties and for the physical interpretation of the terms entering the calculated properties. For example, in molecular Hessian calculations the natural...... connection reduces the size of the relaxation term, leading to faster convergence of the response equations. The physical separation of the terms also means that first-order non-adiabatic coupling matrix elements can be obtained in a very simple way from a molecular Hessian calculation....

  10. Neural Adaptation Leads to Cognitive Ethanol Dependence

    OpenAIRE

    Robinson, Brooks G.; Khurana, Sukant; Kuperman, Anna; Atkinson, Nigel S.

    2012-01-01

    Physiological alcohol dependence is a key adaptation to chronic ethanol consumption that underlies withdrawal symptoms, is thought to directly contribute to alcohol addiction behaviors, and is associated with cognitive problems such as deficits in learning and memory [1–3]. Based on the idea that an ethanol-adapted (dependent) animal will perform better in a learning assay than an animal experiencing ethanol withdrawal will, we have used a learning paradigm to detect physiological ethanol dep...

  11. Age-related increases in long-range connectivity in fetal functional neural connectivity networks in utero

    Directory of Open Access Journals (Sweden)

    Moriah E. Thomason

    2015-02-01

    Full Text Available Formation of operational neural networks is one of the most significant accomplishments of human fetal brain growth. Recent advances in functional magnetic resonance imaging (fMRI have made it possible to obtain information about brain function during fetal development. Specifically, resting-state fMRI and novel signal covariation approaches have opened up a new avenue for non-invasive assessment of neural functional connectivity (FC before birth. Early studies in this area have unearthed new insights about principles of prenatal brain function. However, very little is known about the emergence and maturation of neural networks during fetal life. Here, we obtained cross-sectional rs-fMRI data from 39 fetuses between 24 and 38 weeks postconceptual age to examine patterns of connectivity across ten neural FC networks. We identified primitive forms of motor, visual, default mode, thalamic, and temporal networks in the human fetal brain. We discovered the first evidence of increased long-range, cerebral-cerebellar, cortical-subcortical, and intra-hemispheric FC with advancing fetal age. Continued aggregation of data about fundamental neural connectivity systems in utero is essential to establishing principles of connectomics at the beginning of human life. Normative data provides a vital context against which to compare instances of abnormal neurobiological development.

  12. Neural systems language: a formal modeling language for the systematic description, unambiguous communication, and automated digital curation of neural connectivity.

    Science.gov (United States)

    Brown, Ramsay A; Swanson, Larry W

    2013-09-01

    Systematic description and the unambiguous communication of findings and models remain among the unresolved fundamental challenges in systems neuroscience. No common descriptive frameworks exist to describe systematically the connective architecture of the nervous system, even at the grossest level of observation. Furthermore, the accelerating volume of novel data generated on neural connectivity outpaces the rate at which this data is curated into neuroinformatics databases to synthesize digitally systems-level insights from disjointed reports and observations. To help address these challenges, we propose the Neural Systems Language (NSyL). NSyL is a modeling language to be used by investigators to encode and communicate systematically reports of neural connectivity from neuroanatomy and brain imaging. NSyL engenders systematic description and communication of connectivity irrespective of the animal taxon described, experimental or observational technique implemented, or nomenclature referenced. As a language, NSyL is internally consistent, concise, and comprehensible to both humans and computers. NSyL is a promising development for systematizing the representation of neural architecture, effectively managing the increasing volume of data on neural connectivity and streamlining systems neuroscience research. Here we present similar precedent systems, how NSyL extends existing frameworks, and the reasoning behind NSyL's development. We explore NSyL's potential for balancing robustness and consistency in representation by encoding previously reported assertions of connectivity from the literature as examples. Finally, we propose and discuss the implications of a framework for how NSyL will be digitally implemented in the future to streamline curation of experimental results and bridge the gaps among anatomists, imagers, and neuroinformatics databases. Copyright © 2013 Wiley Periodicals, Inc.

  13. The necessity of connection structures in neural models of variable binding

    NARCIS (Netherlands)

    van der Velde, Frank; van der Velde, Frank; de Kamps, Marc

    2015-01-01

    In his review of neural binding problems, Feldman (Cogn Neurodyn 7:1–11, 2013) addressed two types of models as solutions of (novel) variable binding. The one type uses labels such as phase synchrony of activation. The other (‘connectivity based’) type uses dedicated connections structures to

  14. Prefrontal response and frontostriatal functional connectivity to monetary reward in abstinent alcohol-dependent young adults.

    Directory of Open Access Journals (Sweden)

    Erika E Forbes

    Full Text Available Although altered function in neural reward circuitry is widely proposed in models of addiction, more recent conceptual views have emphasized the role of disrupted response in prefrontal regions. Changes in regions such as the orbitofrontal cortex, medial prefrontal cortex, and dorsolateral prefrontal cortex are postulated to contribute to the compulsivity, impulsivity, and altered executive function that are central to addiction. In addition, few studies have examined function in these regions during young adulthood, when exposure is less chronic than in typical samples of alcohol-dependent adults. To address these issues, we examined neural response and functional connectivity during monetary reward in 24 adults with alcohol dependence and 24 psychiatrically healthy adults. Adults with alcohol dependence exhibited less response to the receipt of monetary reward in a set of prefrontal regions including the medial prefrontal cortex, lateral orbitofrontal cortex, and dorsolateral prefrontal cortex. Adults with alcohol dependence also exhibited greater negative correlation between function in each of these regions and that in the nucleus accumbens. Within the alcohol-dependent group, those with family history of alcohol dependence exhibited lower mPFC response, and those with more frequent drinking exhibited greater negative functional connectivity between the mPFC and the nucleus accumbens. These findings indicate that alcohol dependence is associated with less engagement of prefrontal cortical regions, suggesting weak or disrupted regulation of ventral striatal response. This pattern of prefrontal response and frontostriatal connectivity has consequences for the behavior patterns typical of addiction. Furthermore, brain-behavior findings indicate that the potential mechanisms of disruption in frontostriatal circuitry in alcohol dependence include family liability to alcohol use problems and more frequent use of alcohol. In all, these findings

  15. Prefrontal response and frontostriatal functional connectivity to monetary reward in abstinent alcohol-dependent young adults.

    Science.gov (United States)

    Forbes, Erika E; Rodriguez, Eric E; Musselman, Samuel; Narendran, Rajesh

    2014-01-01

    Although altered function in neural reward circuitry is widely proposed in models of addiction, more recent conceptual views have emphasized the role of disrupted response in prefrontal regions. Changes in regions such as the orbitofrontal cortex, medial prefrontal cortex, and dorsolateral prefrontal cortex are postulated to contribute to the compulsivity, impulsivity, and altered executive function that are central to addiction. In addition, few studies have examined function in these regions during young adulthood, when exposure is less chronic than in typical samples of alcohol-dependent adults. To address these issues, we examined neural response and functional connectivity during monetary reward in 24 adults with alcohol dependence and 24 psychiatrically healthy adults. Adults with alcohol dependence exhibited less response to the receipt of monetary reward in a set of prefrontal regions including the medial prefrontal cortex, lateral orbitofrontal cortex, and dorsolateral prefrontal cortex. Adults with alcohol dependence also exhibited greater negative correlation between function in each of these regions and that in the nucleus accumbens. Within the alcohol-dependent group, those with family history of alcohol dependence exhibited lower mPFC response, and those with more frequent drinking exhibited greater negative functional connectivity between the mPFC and the nucleus accumbens. These findings indicate that alcohol dependence is associated with less engagement of prefrontal cortical regions, suggesting weak or disrupted regulation of ventral striatal response. This pattern of prefrontal response and frontostriatal connectivity has consequences for the behavior patterns typical of addiction. Furthermore, brain-behavior findings indicate that the potential mechanisms of disruption in frontostriatal circuitry in alcohol dependence include family liability to alcohol use problems and more frequent use of alcohol. In all, these findings build on the extant

  16. Visual Working Memory Load-Related Changes in Neural Activity and Functional Connectivity

    Science.gov (United States)

    Li, Ling; Zhang, Jin-Xiang; Jiang, Tao

    2011-01-01

    Background Visual working memory (VWM) helps us store visual information to prepare for subsequent behavior. The neuronal mechanisms for sustaining coherent visual information and the mechanisms for limited VWM capacity have remained uncharacterized. Although numerous studies have utilized behavioral accuracy, neural activity, and connectivity to explore the mechanism of VWM retention, little is known about the load-related changes in functional connectivity for hemi-field VWM retention. Methodology/Principal Findings In this study, we recorded electroencephalography (EEG) from 14 normal young adults while they performed a bilateral visual field memory task. Subjects had more rapid and accurate responses to the left visual field (LVF) memory condition. The difference in mean amplitude between the ipsilateral and contralateral event-related potential (ERP) at parietal-occipital electrodes in retention interval period was obtained with six different memory loads. Functional connectivity between 128 scalp regions was measured by EEG phase synchronization in the theta- (4–8 Hz), alpha- (8–12 Hz), beta- (12–32 Hz), and gamma- (32–40 Hz) frequency bands. The resulting matrices were converted to graphs, and mean degree, clustering coefficient and shortest path length was computed as a function of memory load. The results showed that brain networks of theta-, alpha-, beta-, and gamma- frequency bands were load-dependent and visual-field dependent. The networks of theta- and alpha- bands phase synchrony were most predominant in retention period for right visual field (RVF) WM than for LVF WM. Furthermore, only for RVF memory condition, brain network density of theta-band during the retention interval were linked to the delay of behavior reaction time, and the topological property of alpha-band network was negative correlation with behavior accuracy. Conclusions/Significance We suggest that the differences in theta- and alpha- bands between LVF and RVF conditions in

  17. Visual working memory load-related changes in neural activity and functional connectivity.

    Directory of Open Access Journals (Sweden)

    Ling Li

    Full Text Available BACKGROUND: Visual working memory (VWM helps us store visual information to prepare for subsequent behavior. The neuronal mechanisms for sustaining coherent visual information and the mechanisms for limited VWM capacity have remained uncharacterized. Although numerous studies have utilized behavioral accuracy, neural activity, and connectivity to explore the mechanism of VWM retention, little is known about the load-related changes in functional connectivity for hemi-field VWM retention. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we recorded electroencephalography (EEG from 14 normal young adults while they performed a bilateral visual field memory task. Subjects had more rapid and accurate responses to the left visual field (LVF memory condition. The difference in mean amplitude between the ipsilateral and contralateral event-related potential (ERP at parietal-occipital electrodes in retention interval period was obtained with six different memory loads. Functional connectivity between 128 scalp regions was measured by EEG phase synchronization in the theta- (4-8 Hz, alpha- (8-12 Hz, beta- (12-32 Hz, and gamma- (32-40 Hz frequency bands. The resulting matrices were converted to graphs, and mean degree, clustering coefficient and shortest path length was computed as a function of memory load. The results showed that brain networks of theta-, alpha-, beta-, and gamma- frequency bands were load-dependent and visual-field dependent. The networks of theta- and alpha- bands phase synchrony were most predominant in retention period for right visual field (RVF WM than for LVF WM. Furthermore, only for RVF memory condition, brain network density of theta-band during the retention interval were linked to the delay of behavior reaction time, and the topological property of alpha-band network was negative correlation with behavior accuracy. CONCLUSIONS/SIGNIFICANCE: We suggest that the differences in theta- and alpha- bands between LVF and RVF

  18. Task-dependent modulation of oscillatory neural activity during movements

    DEFF Research Database (Denmark)

    Herz, D. M.; Christensen, M. S.; Reck, C.

    2011-01-01

    -dependent modulation of frequency coupling within this network. To this end we recorded 122-multichannel EEG in 13 healthy subjects while they performed three simple motor tasks. EEG data source modeling using individual MR images was carried out with a multiple source beamformer approach. A bilateral motor network...... for inferring on architecture and coupling parameters of neural networks....

  19. Stimulus-dependent maximum entropy models of neural population codes.

    Directory of Open Access Journals (Sweden)

    Einat Granot-Atedgi

    Full Text Available Neural populations encode information about their stimulus in a collective fashion, by joint activity patterns of spiking and silence. A full account of this mapping from stimulus to neural activity is given by the conditional probability distribution over neural codewords given the sensory input. For large populations, direct sampling of these distributions is impossible, and so we must rely on constructing appropriate models. We show here that in a population of 100 retinal ganglion cells in the salamander retina responding to temporal white-noise stimuli, dependencies between cells play an important encoding role. We introduce the stimulus-dependent maximum entropy (SDME model-a minimal extension of the canonical linear-nonlinear model of a single neuron, to a pairwise-coupled neural population. We find that the SDME model gives a more accurate account of single cell responses and in particular significantly outperforms uncoupled models in reproducing the distributions of population codewords emitted in response to a stimulus. We show how the SDME model, in conjunction with static maximum entropy models of population vocabulary, can be used to estimate information-theoretic quantities like average surprise and information transmission in a neural population.

  20. Altered Brain Functional Connectivity in Betel Quid-Dependent Chewers

    Directory of Open Access Journals (Sweden)

    Xiaojun Huang

    2017-11-01

    Full Text Available BackgroundBetel quid (BQ is a common psychoactive substance worldwide with particularly high usage in many Asian countries. This study aimed to explore the effect of BQ use on functional connectivity by comparing global functional brain networks and their subset between BQ chewers and healthy controls (HCs.MethodsResting-state functional magnetic resonance imaging (fMRI was obtained from 24 betel quid-dependent (BQD male chewers and 27 healthy male individuals on a 3.0T scanner. We used independent component analysis (ICA to determine components that represent the brain’s functional networks and their spatial aspects of functional connectivity. Two sample t-tests were used to identify the functional connectivity differences in each network between these two groups.ResultsSeventeen networks were identified by ICA. Nine of them showed connectivity differences between BQD and HCs (two sample t-tests, p < 0.001 uncorrected. We found increased functional connectivity in the orbitofrontal, bilateral frontoparietal, frontotemporal, occipital/parietal, frontotemporal/cerebellum, and temporal/limbic networks, and decreased connectivity in the parietal and medial frontal/anterior cingulate networks in the BQD compared to the HCs. The betel quid dependence scale scores were positively related to the increased functional connectivity in the orbitofrontal (r = 0.39, p = 0.03 while negatively related to the decreased functional connectivity in medial frontal/anterior cingulate networks (r = −0.35, p = 0.02.DiscussionOur findings provide further evidence that BQ chewing may lead to brain functional connectivity changes, which may play a key role in the psychological and physiological effects of BQ.

  1. Micromechanical modeling of rate-dependent behavior of Connective tissues.

    Science.gov (United States)

    Fallah, A; Ahmadian, M T; Firozbakhsh, K; Aghdam, M M

    2017-03-07

    In this paper, a constitutive and micromechanical model for prediction of rate-dependent behavior of connective tissues (CTs) is presented. Connective tissues are considered as nonlinear viscoelastic material. The rate-dependent behavior of CTs is incorporated into model using the well-known quasi-linear viscoelasticity (QLV) theory. A planar wavy representative volume element (RVE) is considered based on the tissue microstructure histological evidences. The presented model parameters are identified based on the available experiments in the literature. The presented constitutive model introduced to ABAQUS by means of UMAT subroutine. Results show that, monotonic uniaxial test predictions of the presented model at different strain rates for rat tail tendon (RTT) and human patellar tendon (HPT) are in good agreement with experimental data. Results of incremental stress-relaxation test are also presented to investigate both instantaneous and viscoelastic behavior of connective tissues. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. Disrupted Control Network Connectivity in Abstinent Patients with Alcohol Dependence

    OpenAIRE

    Kim, Siekyeong; Im, Sungjin; Lee, Jeonghwan; Lee, Sang-Gu

    2017-01-01

    Objective Alcohol causes damage to the brain and is associated with various functional impairments. However, much of the brain damage can be reversed by abstaining for enough time. This study aims to investigate the patterns and degrees of brain function in abstinent patients with alcohol dependence by using resting-state functional connectivity. Methods 26 male patients with alcohol dependence (alcohol group) and 28 age-matched male healthy volunteers (control group) were recruited from a me...

  3. Movement decoding using neural synchronization and inter-hemispheric connectivity from deep brain local field potentials.

    Science.gov (United States)

    Mamun, K A; Mace, M; Lutman, M E; Stein, J; Liu, X; Aziz, T; Vaidyanathan, R; Wang, S

    2015-10-01

    Correlating electrical activity within the human brain to movement is essential for developing and refining interventions (e.g. deep brain stimulation (DBS)) to treat central nervous system disorders. It also serves as a basis for next generation brain-machine interfaces (BMIs). This study highlights a new decoding strategy for capturing movement and its corresponding laterality from deep brain local field potentials (LFPs). LFPs were recorded with surgically implanted electrodes from the subthalamic nucleus or globus pallidus interna in twelve patients with Parkinson's disease or dystonia during a visually cued finger-clicking task. We introduce a method to extract frequency dependent neural synchronization and inter-hemispheric connectivity features based upon wavelet packet transform (WPT) and Granger causality approaches. A novel weighted sequential feature selection algorithm has been developed to select optimal feature subsets through a feature contribution measure. This is particularly useful when faced with limited trials of high dimensionality data as it enables estimation of feature importance during the decoding process. This novel approach was able to accurately and informatively decode movement related behaviours from the recorded LFP activity. An average accuracy of 99.8% was achieved for movement identification, whilst subsequent laterality classification was 81.5%. Feature contribution analysis highlighted stronger contralateral causal driving between the basal ganglia hemispheres compared to ipsilateral driving, with causality measures considerably improving laterality discrimination. These findings demonstrate optimally selected neural synchronization alongside causality measures related to inter-hemispheric connectivity can provide an effective control signal for augmenting adaptive BMIs. In the case of DBS patients, acquiring such signals requires no additional surgery whilst providing a relatively stable and computationally inexpensive control

  4. Frequency-difference-dependent stochastic resonance in neural systems

    Science.gov (United States)

    Guo, Daqing; Perc, Matjaž; Zhang, Yangsong; Xu, Peng; Yao, Dezhong

    2017-08-01

    Biological neurons receive multiple noisy oscillatory signals, and their dynamical response to the superposition of these signals is of fundamental importance for information processing in the brain. Here we study the response of neural systems to the weak envelope modulation signal, which is superimposed by two periodic signals with different frequencies. We show that stochastic resonance occurs at the beat frequency in neural systems at the single-neuron as well as the population level. The performance of this frequency-difference-dependent stochastic resonance is influenced by both the beat frequency and the two forcing frequencies. Compared to a single neuron, a population of neurons is more efficient in detecting the information carried by the weak envelope modulation signal at the beat frequency. Furthermore, an appropriate fine-tuning of the excitation-inhibition balance can further optimize the response of a neural ensemble to the superimposed signal. Our results thus introduce and provide insights into the generation and modulation mechanism of the frequency-difference-dependent stochastic resonance in neural systems.

  5. Visually-salient contour detection using a V1 neural model with horizontal connections

    CERN Document Server

    Loxley, P N

    2011-01-01

    A convolution model which accounts for neural activity dynamics in the primary visual cortex is derived and used to detect visually salient contours in images. Image inputs to the model are modulated by long-range horizontal connections, allowing contextual effects in the image to determine visual saliency, i.e. line segments arranged in a closed contour elicit a larger neural response than line segments forming background clutter. The model is tested on 3 types of contour, including a line, a circular closed contour, and a non-circular closed contour. Using a modified association field to describe horizontal connections the model is found to perform well for different parameter values. For each type of contour a different facilitation mechanism is found. Operating as a feed-forward network, the model assigns saliency by increasing the neural activity of line segments facilitated by the horizontal connections. Alternatively, operating as a feedback network, the model can achieve further improvement over sever...

  6. Synaptic organizations and dynamical properties of weakly connected neural oscillators. I. Analysis of a canonical model.

    Science.gov (United States)

    Hoppensteadt, F C; Izhikevich, E M

    1996-08-01

    We study weakly connected networks of neural oscillators near multiple Andronov-Hopf bifurcation points. We analyze relationships between synaptic organizations (anatomy) of the networks and their dynamical properties (function). Our principal assumptions are: (1) Each neural oscillator comprises two populations of neurons; excitatory and inhibitory ones; (2) activity of each population of neurons is described by a scalar (one-dimensional) variable; (3) each neural oscillator is near a nondegenerate supercritical Andronov-Hopf bifurcation point; (4) the synaptic connections between the neural oscillators are weak. All neural networks satisfying these hypotheses are governed by the same dynamical system, which we call the canonical model. Studying the canonical model shows that: (1) A neural oscillator can communicate only with those oscillators which have roughly the same natural frequency. That is, synaptic connections between a pair of oscillators having different natural frequencies are functionally insignificant. (2) Two neural oscillators having the same natural frequencies might not communicate if the connections between them are from among a class of pathological synaptic configurations. In both cases the anatomical presence of synaptic connections between neural oscillators does not necessarily guarantee that the connections are functionally significant. (3) There can be substantial phase differences (time delays) between the neural oscillators, which result from the synaptic organization of the network, not from the transmission delays. Using the canonical model we can illustrate self-ignition and autonomous quiescence (oscillator death) phenomena. That is, a network of passive elements can exhibit active properties and vice versa. We also study how Dale's principle affects dynamics of the networks, in particular, the phase differences that the network can reproduce. We present a complete classification of all possible synaptic organizations from this

  7. Alterations in neural connectivity in preterm children at school age

    OpenAIRE

    Gozzo, Yeisid; Vohr, Betty; Lacadie, Cheryl; Hampson, Michelle; Katz, Karol H.; Maller-Kesselman, Jill; Schneider, Karen C.; Peterson, Bradley S.; Rajeevan, Nallakkandi; Makuch, Robert W.; Constable, R. Todd; Ment, Laura R.

    2009-01-01

    Converging data suggest recovery from injury in the preterm brain. We used functional Magnetic Resonance Imaging (fMRI) to test the hypothesis that cerebral connectivity involving Wernicke’s area and other important cortical language regions would differ between preterm (PT) and term (T) control school age children during performance of an auditory language task. Fifty-four PT children (600 – 1250 g birth weight) and 24 T controls were evaluated using an fMRI passive language task and neurode...

  8. The connections between neural crest development and neuroblastoma.

    Science.gov (United States)

    Jiang, Manrong; Stanke, Jennifer; Lahti, Jill M

    2011-01-01

    Neuroblastoma (NB), the most common extracranial solid tumor in childhood, is an extremely heterogeneous disease both biologically and clinically. Although significant progress has been made in identifying molecular and genetic markers for NB, this disease remains an enigmatic challenge. Since NB is thought to be an embryonal tumor that is derived from precursor cells of the peripheral (sympathetic) nervous system, understanding the development of normal sympathetic nervous system may highlight abnormal events that contribute to NB initiation. Therefore, this review focuses on the development of the peripheral trunk neural crest, the current understanding of how developmental factors may contribute to NB and on recent advances in the identification of important genetic lesions and signaling pathways involved in NB tumorigenesis and metastasis. Finally, we discuss how future advances in identification of molecular alterations in NB may lead to more effective, less toxic therapies, and improve the prognosis for NB patients. Copyright © 2011 Elsevier Inc. All rights reserved.

  9. Visual Working Memory Load-Related Changes in Neural Activity and Functional Connectivity

    OpenAIRE

    Ling Li; Jin-Xiang Zhang; Tao Jiang

    2011-01-01

    BACKGROUND: Visual working memory (VWM) helps us store visual information to prepare for subsequent behavior. The neuronal mechanisms for sustaining coherent visual information and the mechanisms for limited VWM capacity have remained uncharacterized. Although numerous studies have utilized behavioral accuracy, neural activity, and connectivity to explore the mechanism of VWM retention, little is known about the load-related changes in functional connectivity for hemi-field VWM retention. MET...

  10. The biocultural paradigm: the neural connection between science and mysticism.

    Science.gov (United States)

    de Nicolas, A T

    1998-01-01

    New discoveries in perceptual psychology, brain chemistry, brain evolution, brain development, ethology, cultural anthropology, the more recent work of MacLean on the structure of the brains and the discovery by Gazzaniga of the role of the, so-called, "interpreter module," are the foundations of a new paradigm on human cortical information processing, called by its discoverer, Dr. M. Colavito, the "biocultural paradigm." This paradigm shows that biology and culture act on one another as the conditioning parameters of neurocultural information. Through mutual interaction biology in humans becomes culture, and vice versa, culture opens and stimulates the neural passages of the brains, accounting thus for the varieties of brains in humans, and for cultural diversity. Culture conditions and stimulates biology, while biology conditions and makes culture possible. Cultures and brains may be distinguished from one another through identification with certain functions or combination of functions that are exercised habitually, or become neural hard-wire through repetition or habit. This new model has replaced older and simpler models of the nature/ nurture controversy, such as the unextended rational substance of Descartes, the tabula rasa of Locke, the associated-matrix of Hume, the passive, reinforcement-driven animal of Skinner, and the genetically hard-wired robot of the sociobiologists. However, elements of these earlier models are included in the new one, but the conversation about human experience has changed, and, therefore, the human images of ourselves. This change was forced on scientists by the importance of the conditionality of the experience of "I" and "not-I" as described by Alex Comfort in his book I and That, and was introduced in the conversations some of us already had with each other. This article focuses on the "I" and "not-I" experiences with a description of the "not-I" or "oceanic" or "mystical" experience to clarify the new paradigm of

  11. Transcranial magnetic stimulation and connectivity mapping: tools for studying the neural bases of brain disorders.

    Directory of Open Access Journals (Sweden)

    Michelle Hampson

    2010-08-01

    Full Text Available There has been an increasing emphasis on characterizing pathophysiology underlying psychiatric and neurological disorders in terms of altered neural connectivity and network dynamics. Transcranial magnetic stimulation (TMS provides a unique opportunity for investigating connectivity in the human brain. TMS allows researchers and clinicians to directly stimulate cortical regions accessible to electromagnetic coils positioned on the scalp. The induced activation can then propagate through long-range connections to other brain areas. Thus, by identifying distal regions activated during TMS, researchers can infer connectivity patterns in the healthy human brain and can examine how those patterns may be disrupted in patients with different brain disorders. Conversely, connectivity maps derived using neuroimaging methods can identify components of a dysfunctional network. Nodes in this dysfunctional network accessible as targets for TMS by virtue of their proximity to the scalp may then permit TMS-induced alterations of components of the network not directly accessible to TMS via propagated effects. Thus TMS can provide a portal for accessing and altering neural dynamics in networks that are widely distributed anatomically. Finally, when long-term modulation of network dynamics is induced by trains of repetitive TMS, changes in functional connectivity patterns can be studied in parallel with changes in patient symptoms. These correlational data can elucidate neural mechanisms underlying illness and recovery. In this review, we focus on the application of these approaches to the study of psychiatric and neurological illnesses.

  12. Self-organized noise resistance of oscillatory neural networks with spike timing-dependent plasticity.

    Science.gov (United States)

    Popovych, Oleksandr V; Yanchuk, Serhiy; Tass, Peter A

    2013-10-11

    Intuitively one might expect independent noise to be a powerful tool for desynchronizing a population of synchronized neurons. We here show that, intriguingly, for oscillatory neural populations with adaptive synaptic weights governed by spike timing-dependent plasticity (STDP) the opposite is true. We found that the mean synaptic coupling in such systems increases dynamically in response to the increase of the noise intensity, and there is an optimal noise level, where the amount of synaptic coupling gets maximal in a resonance-like manner as found for the stochastic or coherence resonances, although the mechanism in our case is different. This constitutes a noise-induced self-organization of the synaptic connectivity, which effectively counteracts the desynchronizing impact of independent noise over a wide range of the noise intensity. Given the attempts to counteract neural synchrony underlying tinnitus with noisers and maskers, our results may be of clinical relevance.

  13. What Is Lost During Dreamless Sleep: The Relationship Between Neural Connectivity Patterns and Consciousness

    Directory of Open Access Journals (Sweden)

    Michaela Klimova

    2014-09-01

    Full Text Available Non-rapid eye movement (NREM sleep is characterised by reduced consciousness; thus, studying its neural characteristics acts as a useful indication of what is needed for conscious experience. The integrated information theory (Tononi, 2008 states that the ability of different thalamocortical regions to interact is crucial for consciousness, thereby motivating research concerning connectivity changes in the thalamocortical system that accompany changing consciousness levels. This review aims to discuss investigations of functional connectivity of resting-state and large-scale brain networks, applying correlational approaches to neuroimaging data as well as studies that used brain stimulation to investigate effective connectivity. Most findings suggest a reorganisation of functional brain networks where inter-region connectivity is reduced and intra-region connectivity is stronger in deep sleep than wakefulness.

  14. Power spectrum of the rectified EMG: when and why is rectification beneficial for identifying neural connectivity?

    Science.gov (United States)

    Negro, Francesco; Keenan, Kevin; Farina, Dario

    2015-06-01

    Objective. The identification of common oscillatory inputs to motor neurons in the electromyographic (EMG) signal power spectrum is often preceded by EMG rectification for enhancing the low-frequency oscillatory components. However, rectification is a nonlinear operator and its influence on the EMG signal spectrum is not fully understood. In this study, we aim at determining when EMG rectification is beneficial in the study of oscillatory inputs to motor neurons. Approach. We provide a full mathematical description of the power spectrum of the rectified EMG signal and the influence of the average shape of the motor unit action potentials on it. We also provide a validation of these theoretical results with both simulated and experimental EMG signals. Main results. Simulations using an advanced computational model and experimental results demonstrated the accuracy of the theoretical derivations on the effect of rectification on the EMG spectrum. These derivations proved that rectification is beneficial when assessing the strength of low-frequency (delta and alpha bands) common synaptic inputs to the motor neurons, when the duration of the action potentials is short, and when the level of cancellation is relatively low. On the other hand, rectification may distort the estimation of common synaptic inputs when studying higher frequencies (beta and gamma), in a way dependent on the duration of the action potentials, and may introduce peaks in the coherence function that do not correspond to physiological shared inputs. Significance. This study clarifies the conditions when rectifying the surface EMG is appropriate for studying neural connectivity.

  15. Effect of Explicit Evaluation on Neural Connectivity Related to Listening to Unfamiliar Music

    Science.gov (United States)

    Liu, Chao; Brattico, Elvira; Abu-jamous, Basel; Pereira, Carlos S.; Jacobsen, Thomas; Nandi, Asoke K.

    2017-01-01

    People can experience different emotions when listening to music. A growing number of studies have investigated the brain structures and neural connectivities associated with perceived emotions. However, very little is known about the effect of an explicit act of judgment on the neural processing of emotionally-valenced music. In this study, we adopted the novel consensus clustering paradigm, called binarisation of consensus partition matrices (Bi-CoPaM), to study whether and how the conscious aesthetic evaluation of the music would modulate brain connectivity networks related to emotion and reward processing. Participants listened to music under three conditions – one involving a non-evaluative judgment, one involving an explicit evaluative aesthetic judgment, and one involving no judgment at all (passive listening only). During non-evaluative attentive listening we obtained auditory-limbic connectivity whereas when participants were asked to decide explicitly whether they liked or disliked the music excerpt, only two clusters of intercommunicating brain regions were found: one including areas related to auditory processing and action observation, and the other comprising higher-order structures involved with visual processing. Results indicate that explicit evaluative judgment has an impact on the neural auditory-limbic connectivity during affective processing of music. PMID:29311874

  16. Effect of Explicit Evaluation on Neural Connectivity Related to Listening to Unfamiliar Music

    Directory of Open Access Journals (Sweden)

    Chao Liu

    2017-12-01

    Full Text Available People can experience different emotions when listening to music. A growing number of studies have investigated the brain structures and neural connectivities associated with perceived emotions. However, very little is known about the effect of an explicit act of judgment on the neural processing of emotionally-valenced music. In this study, we adopted the novel consensus clustering paradigm, called binarisation of consensus partition matrices (Bi-CoPaM, to study whether and how the conscious aesthetic evaluation of the music would modulate brain connectivity networks related to emotion and reward processing. Participants listened to music under three conditions – one involving a non-evaluative judgment, one involving an explicit evaluative aesthetic judgment, and one involving no judgment at all (passive listening only. During non-evaluative attentive listening we obtained auditory-limbic connectivity whereas when participants were asked to decide explicitly whether they liked or disliked the music excerpt, only two clusters of intercommunicating brain regions were found: one including areas related to auditory processing and action observation, and the other comprising higher-order structures involved with visual processing. Results indicate that explicit evaluative judgment has an impact on the neural auditory-limbic connectivity during affective processing of music.

  17. Outcome dependency alters the neural substrates of impression formation

    Science.gov (United States)

    Ames, Daniel L.; Fiske, Susan T.

    2015-01-01

    How do people maintain consistent impressions of other people when other people are often inconsistent? The present research addresses this question by combining recent neuroscientific insights with ecologically meaningful behavioral methods. Participants formed impressions of real people whom they met in a personally involving situation. fMRI and supporting behavioral data revealed that outcome dependency (i.e., depending on another person for a desired outcome) alters previously identified neural dynamics of impression formation. Consistent with past research, a functional localizer identified a region of dorsomedial PFC previously linked to social impression formation. In the main task, this ROI revealed the predicted patterns of activity across outcome dependency conditions: greater BOLD response when information confirmed (vs. violated) social expectations if participants were outcome-independent and the reverse pattern if participants were outcome-dependent. We suggest that, although social perceivers often discount expectancy-disconfirming information as noise, being dependent on another person for a desired outcome focuses impression-formation processing on the most diagnostic information, rather than on the most tractable information. PMID:23850465

  18. The necessity of connection structures in neural models of variable binding.

    Science.gov (United States)

    van der Velde, Frank; de Kamps, Marc

    2015-08-01

    In his review of neural binding problems, Feldman (Cogn Neurodyn 7:1-11, 2013) addressed two types of models as solutions of (novel) variable binding. The one type uses labels such as phase synchrony of activation. The other ('connectivity based') type uses dedicated connections structures to achieve novel variable binding. Feldman argued that label (synchrony) based models are the only possible candidates to handle novel variable binding, whereas connectivity based models lack the flexibility required for that. We argue and illustrate that Feldman's analysis is incorrect. Contrary to his conclusion, connectivity based models are the only viable candidates for models of novel variable binding because they are the only type of models that can produce behavior. We will show that the label (synchrony) based models analyzed by Feldman are in fact examples of connectivity based models. Feldman's analysis that novel variable binding can be achieved without existing connection structures seems to result from analyzing the binding problem in a wrong frame of reference, in particular in an outside instead of the required inside frame of reference. Connectivity based models can be models of novel variable binding when they possess a connection structure that resembles a small-world network, as found in the brain. We will illustrate binding with this type of model with episode binding and the binding of words, including novel words, in sentence structures.

  19. Effect of Explicit Evaluation on Neural Connectivity Related to Listening to Unfamiliar Music

    DEFF Research Database (Denmark)

    Liu, Chao; Brattico, Elvira; Abu-Jamous, Basel

    2017-01-01

    People can experience different emotions when listening to music. A growing number of studies have investigated the brain structures and neural connectivities associated with perceived emotions. However, very little is known about the effect of an explicit act of judgment on the neural processing...... of emotionally-valenced music. In this study, we adopted the novel consensus clustering paradigm, called binarisation of consensus partition matrices (Bi-CoPaM), to study whether and how the conscious aesthetic evaluation of the music would modulate brain connectivity networks related to emotion and reward...... processing. Participants listened to music under three conditions - one involving a non-evaluative judgment, one involving an explicit evaluative aesthetic judgment, and one involving no judgment at all (passive listening only). During non-evaluative attentive listening we obtained auditory...

  20. The neural changes in connectivity of the voice network during voice pitch perturbation.

    Science.gov (United States)

    Flagmeier, Sabina G; Ray, Kimberly L; Parkinson, Amy L; Li, Karl; Vargas, Robert; Price, Larry R; Laird, Angela R; Larson, Charles R; Robin, Donald A

    2014-05-01

    Voice control is critical to communication. To date, studies have used behavioral, electrophysiological and functional data to investigate the neural correlates of voice control using perturbation tasks, but have yet to examine the interactions of these neural regions. The goal of this study was to use structural equation modeling of functional neuroimaging data to examine network properties of voice with and without perturbation. Results showed that the presence of a pitch shift, which was processed as an error in vocalization, altered connections between right STG and left STG. Other regions that revealed differences in connectivity during error detection and correction included bilateral inferior frontal gyrus, and the primary and pre motor cortices. Results indicated that STG plays a critical role in voice control, specifically, during error detection and correction. Additionally, pitch perturbation elicits changes in the voice network that suggest the right hemisphere is critical to pitch modulation. Published by Elsevier Inc.

  1. Reward-related neural responses are dependent on the beneficiary.

    Science.gov (United States)

    Braams, Barbara R; Güroğlu, Berna; de Water, Erik; Meuwese, Rosa; Koolschijn, P Cédric; Peper, Jiska S; Crone, Eveline A

    2014-07-01

    Prior studies have suggested that positive social interactions are experienced as rewarding. Yet, it is not well understood how social relationships influence neural responses to other persons' gains. In this study, we investigated neural responses during a gambling task in which healthy participants (N = 31; 18 females) could win or lose money for themselves, their best friend or a disliked other (antagonist). At the moment of receiving outcome, person-related activity was observed in the dorsal medial prefrontal cortex (dmPFC), precuneus and temporal parietal junction (TPJ), showing higher activity for friends and antagonists than for self, and this activity was independent of outcome. The only region showing an interaction between the person-participants played for and outcome was the ventral striatum. Specifically, the striatum was more active following gains than losses for self and friends, whereas for the antagonist this pattern was reversed. Together, these results show that, in a context with social and reward information, social aspects are processed in brain regions associated with social cognition (mPFC, TPJ), and reward aspects are processed in primary reward areas (striatum). Furthermore, there is an interaction of social and reward information in the striatum, such that reward-related activity was dependent on social relationship. © The Author (2013). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  2. An optimally evolved connective ratio of neural networks that maximizes the occurrence of synchronized bursting behavior

    Science.gov (United States)

    2012-01-01

    Background Synchronized bursting activity (SBA) is a remarkable dynamical behavior in both ex vivo and in vivo neural networks. Investigations of the underlying structural characteristics associated with SBA are crucial to understanding the system-level regulatory mechanism of neural network behaviors. Results In this study, artificial pulsed neural networks were established using spike response models to capture fundamental dynamics of large scale ex vivo cortical networks. Network simulations with synaptic parameter perturbations showed the following two findings. (i) In a network with an excitatory ratio (ER) of 80-90%, its connective ratio (CR) was within a range of 10-30% when the occurrence of SBA reached the highest expectation. This result was consistent with the experimental observation in ex vivo neuronal networks, which were reported to possess a matured inhibitory synaptic ratio of 10-20% and a CR of 10-30%. (ii) No SBA occurred when a network does not contain any all-positive-interaction feedback loop (APFL) motif. In a neural network containing APFLs, the number of APFLs presented an optimal range corresponding to the maximal occurrence of SBA, which was very similar to the optimal CR. Conclusions In a neural network, the evolutionarily selected CR (10-30%) optimizes the occurrence of SBA, and APFL serves a pivotal network motif required to maximize the occurrence of SBA. PMID:22462685

  3. The process of learning in neural net models with Poisson and Gauss connectivities.

    Science.gov (United States)

    Sivridis, L; Kotini, A; Anninos, P

    2008-01-01

    In this study we examined the dynamic behavior of isolated and non-isolated neural networks with chemical markers that follow a Poisson or Gauss distribution of connectivity. The Poisson distribution shows higher activity in comparison to the Gauss distribution although the latter has more connections that obliterated due to randomness. We examined 57 hematoxylin and eosin stained sections from an equal number of autopsy specimens with a diagnosis of "cerebral matter within normal limits". Neural counting was carried out in 5 continuous optic fields, with the use of a simple optical microscope connected to a computer (software programmer Nikon Act-1 vers-2). The number of neurons that corresponded to a surface was equal to 0.15 mm(2). There was a gradual reduction in the number of neurons as age increased. A mean value of 45.8 neurons /0.15 mm(2) was observed within the age range 21-25, 33 neurons /0.15 mm(2) within the age range 41-45, 19.3 neurons /0.15 mm(2) within the age range 56-60 years. After the age of 60 it was observed that the number of neurons per unit area stopped decreasing. A correlation was observed between these experimental findings and the theoretical neural model developed by professor Anninos and his colleagues. Equivalence between the mean numbers of neurons of the above mentioned age groups and the highest possible number of synaptic connections per neuron (highest number of synaptic connections corresponded to the age group 21-25) was created. We then used both inhibitory and excitatory post-synaptic potentials and applied these values to the Poisson and Gauss distributions, whereas the neuron threshold was varied between 3 and 5. According to the obtained phase diagrams, the hysteresis loops decrease as age increases. These findings were significant as the hysteresis loops can be regarded as the basis for short-term memory.

  4. Knowledge engineering tools for reasoning with scientific observations and interpretations: a neural connectivity use case.

    Science.gov (United States)

    Russ, Thomas A; Ramakrishnan, Cartic; Hovy, Eduard H; Bota, Mihail; Burns, Gully A P C

    2011-08-22

    We address the goal of curating observations from published experiments in a generalizable form; reasoning over these observations to generate interpretations and then querying this interpreted knowledge to supply the supporting evidence. We present web-application software as part of the 'BioScholar' project (R01-GM083871) that fully instantiates this process for a well-defined domain: using tract-tracing experiments to study the neural connectivity of the rat brain. The main contribution of this work is to provide the first instantiation of a knowledge representation for experimental observations called 'Knowledge Engineering from Experimental Design' (KEfED) based on experimental variables and their interdependencies. The software has three parts: (a) the KEfED model editor - a design editor for creating KEfED models by drawing a flow diagram of an experimental protocol; (b) the KEfED data interface - a spreadsheet-like tool that permits users to enter experimental data pertaining to a specific model; (c) a 'neural connection matrix' interface that presents neural connectivity as a table of ordinal connection strengths representing the interpretations of tract-tracing data. This tool also allows the user to view experimental evidence pertaining to a specific connection. BioScholar is built in Flex 3.5. It uses Persevere (a noSQL database) as a flexible data store and PowerLoom® (a mature First Order Logic reasoning system) to execute queries using spatial reasoning over the BAMS neuroanatomical ontology. We first introduce the KEfED approach as a general approach and describe its possible role as a way of introducing structured reasoning into models of argumentation within new models of scientific publication. We then describe the design and implementation of our example application: the BioScholar software. This is presented as a possible biocuration interface and supplementary reasoning toolkit for a larger, more specialized bioinformatics system: the Brain

  5. Knowledge engineering tools for reasoning with scientific observations and interpretations: a neural connectivity use case

    Directory of Open Access Journals (Sweden)

    Bota Mihail

    2011-08-01

    Full Text Available Abstract Background We address the goal of curating observations from published experiments in a generalizable form; reasoning over these observations to generate interpretations and then querying this interpreted knowledge to supply the supporting evidence. We present web-application software as part of the 'BioScholar' project (R01-GM083871 that fully instantiates this process for a well-defined domain: using tract-tracing experiments to study the neural connectivity of the rat brain. Results The main contribution of this work is to provide the first instantiation of a knowledge representation for experimental observations called 'Knowledge Engineering from Experimental Design' (KEfED based on experimental variables and their interdependencies. The software has three parts: (a the KEfED model editor - a design editor for creating KEfED models by drawing a flow diagram of an experimental protocol; (b the KEfED data interface - a spreadsheet-like tool that permits users to enter experimental data pertaining to a specific model; (c a 'neural connection matrix' interface that presents neural connectivity as a table of ordinal connection strengths representing the interpretations of tract-tracing data. This tool also allows the user to view experimental evidence pertaining to a specific connection. BioScholar is built in Flex 3.5. It uses Persevere (a noSQL database as a flexible data store and PowerLoom® (a mature First Order Logic reasoning system to execute queries using spatial reasoning over the BAMS neuroanatomical ontology. Conclusions We first introduce the KEfED approach as a general approach and describe its possible role as a way of introducing structured reasoning into models of argumentation within new models of scientific publication. We then describe the design and implementation of our example application: the BioScholar software. This is presented as a possible biocuration interface and supplementary reasoning toolkit for a larger

  6. A realistic neural mass model of the cortex with laminar-specific connections and synaptic plasticity - evaluation with auditory habituation.

    Directory of Open Access Journals (Sweden)

    Peng Wang

    Full Text Available In this work we propose a biologically realistic local cortical circuit model (LCCM, based on neural masses, that incorporates important aspects of the functional organization of the brain that have not been covered by previous models: (1 activity dependent plasticity of excitatory synaptic couplings via depleting and recycling of neurotransmitters and (2 realistic inter-laminar dynamics via laminar-specific distribution of and connections between neural populations. The potential of the LCCM was demonstrated by accounting for the process of auditory habituation. The model parameters were specified using Bayesian inference. It was found that: (1 besides the major serial excitatory information pathway (layer 4 to layer 2/3 to layer 5/6, there exists a parallel "short-cut" pathway (layer 4 to layer 5/6, (2 the excitatory signal flow from the pyramidal cells to the inhibitory interneurons seems to be more intra-laminar while, in contrast, the inhibitory signal flow from inhibitory interneurons to the pyramidal cells seems to be both intra- and inter-laminar, and (3 the habituation rates of the connections are unsymmetrical: forward connections (from layer 4 to layer 2/3 are more strongly habituated than backward connections (from Layer 5/6 to layer 4. Our evaluation demonstrates that the novel features of the LCCM are of crucial importance for mechanistic explanations of brain function. The incorporation of these features into a mass model makes them applicable to modeling based on macroscopic data (like EEG or MEG, which are usually available in human experiments. Our LCCM is therefore a valuable building block for future realistic models of human cognitive function.

  7. Speed hysteresis and noise shaping of traveling fronts in neural fields: role of local circuitry and nonlocal connectivity

    Science.gov (United States)

    Capone, Cristiano; Mattia, Maurizio

    2017-01-01

    Neural field models are powerful tools to investigate the richness of spatiotemporal activity patterns like waves and bumps, emerging from the cerebral cortex. Understanding how spontaneous and evoked activity is related to the structure of underlying networks is of central interest to unfold how information is processed by these systems. Here we focus on the interplay between local properties like input-output gain function and recurrent synaptic self-excitation of cortical modules, and nonlocal intermodular synaptic couplings yielding to define a multiscale neural field. In this framework, we work out analytic expressions for the wave speed and the stochastic diffusion of propagating fronts uncovering the existence of an optimal balance between local and nonlocal connectivity which minimizes the fluctuations of the activation front propagation. Incorporating an activity-dependent adaptation of local excitability further highlights the independent role that local and nonlocal connectivity play in modulating the speed of propagation of the activation and silencing wavefronts, respectively. Inhomogeneities in space of local excitability give raise to a novel hysteresis phenomenon such that the speed of waves traveling in opposite directions display different velocities in the same location. Taken together these results provide insights on the multiscale organization of brain slow-waves measured during deep sleep and anesthesia.

  8. Increased functional connectivity in intrinsic neural networks in individuals with aniridia

    Science.gov (United States)

    Pierce, Jordan E.; Krafft, Cynthia E.; Rodrigue, Amanda L.; Bobilev, Anastasia M.; Lauderdale, James D.; McDowell, Jennifer E.

    2014-01-01

    Mutations affecting the PAX6 gene result in aniridia, a condition characterized by the lack of an iris and other panocular defects. Among humans with aniridia, structural abnormalities also have been reported within the brain. The current study examined the functional implications of these deficits through “resting state” or task-free functional magnetic resonance imaging (fMRI) in 12 individuals with aniridia and 12 healthy age- and gender-matched controls. Using independent components analysis (ICA) and dual regression, individual patterns of functional connectivity associated with three intrinsic connectivity networks (ICNs; executive control, primary visual, and default mode) were compared across groups. In all three analyses, the aniridia group exhibited regions of greater connectivity correlated with the network, while the controls did not show any such regions. These differences suggest that individuals with aniridia recruit additional neural regions to supplement function in critical intrinsic networks, possibly due to inherent structural or sensory abnormalities related to the disorder. PMID:25566032

  9. Increased functional connectivity in intrinsic neural networks in individuals with aniridia

    Directory of Open Access Journals (Sweden)

    Jordan Elisabeth Pierce

    2014-12-01

    Full Text Available Mutations affecting the PAX6 gene result in aniridia, a condition characterized by the lack of an iris and other panocular defects. Among humans with aniridia, structural abnormalities also have been reported within the brain. The current study examined the functional implications of these deficits through resting state or task-free functional magnetic resonance imaging in 12 individuals with aniridia and 12 healthy age- and gender-matched controls. Using independent components analysis and dual regression, individual patterns of functional connectivity associated with three intrinsic connectivity networks (executive control, primary visual, and default mode were compared across groups. In all three analyses, the aniridia group exhibited regions of greater connectivity correlated with the network, while the controls did not show any such regions. These differences suggest that individuals with aniridia recruit additional neural regions to supplement function in critical intrinsic networks, possibly due to inherent structural or sensory abnormalities related to the disorder.

  10. Increased corticolimbic connectivity in cocaine dependence versus pathological gambling is associated with drug severity and emotion-related impulsivity.

    Science.gov (United States)

    Contreras-Rodríguez, Oren; Albein-Urios, Natalia; Vilar-López, Raquel; Perales, Jose C; Martínez-Gonzalez, Jose M; Fernández-Serrano, Maria J; Lozano-Rojas, Oscar; Clark, Luke; Verdejo-García, Antonio

    2016-05-01

    Neural biomarkers for the active detrimental effects of cocaine dependence (CD) are lacking. Direct comparisons of brain connectivity in cocaine-targeted networks between CD and behavioural addictions (i.e. pathological gambling, PG) may be informative. This study therefore contrasted the resting-state functional connectivity networks of 20 individuals with CD, 19 individuals with PG and 21 healthy individuals (controls). Study groups were assessed to rule out psychiatric co-morbidities (except alcohol abuse and nicotine dependence) and current substance use or gambling (except PG). We first examined global connectivity differences in the corticolimbic reward network and then utilized seed-based analyses to characterize the connectivity of regions displaying between-group differences. We examined the relationships between seed-based connectivity and trait impulsivity and cocaine severity. CD compared with PG displayed increased global functional connectivity in a large-scale ventral corticostriatal network involving the orbitofrontal cortex, caudate, thalamus and amygdala. Seed-based analyses showed that CD compared with PG exhibited enhanced connectivity between the orbitofrontal and subgenual cingulate cortices and between caudate and lateral prefrontal cortex, which are involved in representing the value of decision-making feedback. CD and PG compared with controls showed overlapping connectivity changes between the orbitofrontal and dorsomedial prefrontal cortices and between amygdala and insula, which are involved in stimulus-outcome learning. Orbitofrontal-subgenual cingulate cortical connectivity correlated with impulsivity and caudate/amygdala connectivity correlated with cocaine severity. We conclude that CD is linked to enhanced connectivity in a large-scale ventral corticostriatal-amygdala network that is relevant to decision making and likely to reflect an active cocaine detrimental effect. © 2015 Society for the Study of Addiction.

  11. Connectivity strategies for higher-order neural networks applied to pattern recognition

    Science.gov (United States)

    Spirkovska, Lilly; Reid, Max B.

    1990-01-01

    Different strategies for non-fully connected HONNs (higher-order neural networks) are discussed, showing that by using such strategies an input field of 128 x 128 pixels can be attained while still achieving in-plane rotation and translation-invariant recognition. These techniques allow HONNs to be used with the larger input scenes required for practical pattern-recognition applications. The number of interconnections that must be stored has been reduced by a factor of approximately 200,000 in a T/C case and about 2000 in a Space Shuttle/F-18 case by using regional connectivity. Third-order networks have been simulated using several connection strategies. The method found to work best is regional connectivity. The main advantages of this strategy are the following: (1) it considers features of various scales within the image and thus gets a better sample of what the image looks like; (2) it is invariant to shape-preserving geometric transformations, such as translation and rotation; (3) the connections are predetermined so that no extra computations are necessary during run time; and (4) it does not require any extra storage for recording which connections were formed.

  12. Joint multiple fully connected convolutional neural network with extreme learning machine for hepatocellular carcinoma nuclei grading.

    Science.gov (United States)

    Li, Siqi; Jiang, Huiyan; Pang, Wenbo

    2017-05-01

    Accurate cell grading of cancerous tissue pathological image is of great importance in medical diagnosis and treatment. This paper proposes a joint multiple fully connected convolutional neural network with extreme learning machine (MFC-CNN-ELM) architecture for hepatocellular carcinoma (HCC) nuclei grading. First, in preprocessing stage, each grayscale image patch with the fixed size is obtained using center-proliferation segmentation (CPS) method and the corresponding labels are marked under the guidance of three pathologists. Next, a multiple fully connected convolutional neural network (MFC-CNN) is designed to extract the multi-form feature vectors of each input image automatically, which considers multi-scale contextual information of deep layer maps sufficiently. After that, a convolutional neural network extreme learning machine (CNN-ELM) model is proposed to grade HCC nuclei. Finally, a back propagation (BP) algorithm, which contains a new up-sample method, is utilized to train MFC-CNN-ELM architecture. The experiment comparison results demonstrate that our proposed MFC-CNN-ELM has superior performance compared with related works for HCC nuclei grading. Meanwhile, external validation using ICPR 2014 HEp-2 cell dataset shows the good generalization of our MFC-CNN-ELM architecture. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. Impaired activity-dependent neural circuit assembly and refinement in autism spectrum disorder genetic models

    Directory of Open Access Journals (Sweden)

    Caleb Andrew Doll

    2014-02-01

    Full Text Available Early-use activity during circuit-specific critical periods refines brain circuitry by the coupled processes of eliminating inappropriate synapses and strengthening maintained synapses. We theorize these activity-dependent developmental processes are specifically impaired in autism spectrum disorders (ASDs. ASD genetic models in both mouse and Drosophila have pioneered our insights into normal activity-dependent neural circuit assembly and consolidation, and how these developmental mechanisms go awry in specific genetic conditions. The monogenic Fragile X syndrome (FXS, a common cause of heritable ASD and intellectual disability, has been particularly well linked to defects in activity-dependent critical period processes. The Fragile X Mental Retardation Protein (FMRP is positively activity-regulated in expression and function, in turn regulates excitability and activity in a negative feedback loop, and appears to be required for the activity-dependent remodeling of synaptic connectivity during early-use critical periods. The Drosophila FXS model has been shown to functionally conserve the roles of human FMRP in synaptogenesis, and has been centrally important in generating our current mechanistic understanding of the FXS disease state. Recent advances in Drosophila optogenetics, transgenic calcium reporters, highly-targeted transgenic drivers for individually-identified neurons, and a vastly improved connectome of the brain are now being combined to provide unparalleled opportunities to both manipulate and monitor activity-dependent processes during critical period brain development in defined neural circuits. The field is now poised to exploit this new Drosophila transgenic toolbox for the systematic dissection of activity-dependent mechanisms in normal versus ASD brain development, particularly utilizing the well-established Drosophila FXS disease model.

  14. Application of viral vectors to the study of neural connectivities and neural circuits in the marmoset brain.

    Science.gov (United States)

    Watakabe, Akiya; Sadakane, Osamu; Hata, Katsusuke; Ohtsuka, Masanari; Takaji, Masafumi; Yamamori, Tetsuo

    2017-03-01

    It is important to study the neural connectivities and functions in primates. For this purpose, it is critical to be able to transfer genes to certain neurons in the primate brain so that we can image the neuronal signals and analyze the function of the transferred gene. Toward this end, our team has been developing gene transfer systems using viral vectors. In this review, we summarize our current achievements as follows. 1) We compared the features of gene transfer using five different AAV serotypes in combination with three different promoters, namely, CMV, mouse CaMKII (CaMKII), and human synapsin 1 (hSyn1), in the marmoset cortex with those in the mouse and macaque cortices. 2) We used target-specific double-infection techniques in combination with TET-ON and TET-OFF using lentiviral retrograde vectors for enhanced visualization of neural connections. 3) We used an AAV-mediated gene transfer method to study the transcriptional control for amplifying fluorescent signals using the TET/TRE system in the primate neocortex. We also established systems for shRNA mediated gene targeting in a neocortical region where a gene is significantly expressed and for expressing the gene using the CMV promoter for an unexpressed neocortical area in the primate cortex using AAV vectors to understand the regulation of downstream genes. Our findings have demonstrated the feasibility of using viral vector mediated gene transfer systems for the study of primate cortical circuits using the marmoset as an animal model. © 2016 Wiley Periodicals, Inc. Develop Neurobiol 77: 354-372, 2017. © 2016 The Authors. Developmental Neurobiology Published by Wiley Periodicals, Inc.

  15. Processing of different types of social threat in shyness: Preliminary findings of distinct functional neural connectivity.

    Science.gov (United States)

    Tang, Alva; Beaton, Elliott A; Tatham, Erica; Schulkin, Jay; Hall, Geoffrey B; Schmidt, Louis A

    2016-01-01

    Current theory suggests that the processing of different types of threat is supported by distinct neural networks. Here we tested whether there are distinct neural correlates associated with different types of threat processing in shyness. Using fMRI and multivariate techniques, we compared neural responses and functional connectivity during the processing of imminent (i.e., congruent angry/angry face pairs) and ambiguous (i.e., incongruent angry/neutral face pairs) social threat in young adults selected for high and low shyness. To both types of threat processing, non-shy adults recruited a right medial prefrontal cortex (mPFC) network encompassing nodes of the default mode network involved in automatic emotion regulation, whereas shy adults recruited a right dorsal anterior cingulate cortex (dACC) network encompassing nodes of the frontoparietal network that instantiate active attentional and cognitive control. Furthermore, in shy adults, the mPFC interacted with the dACC network for ambiguous threat, but with a distinct network encompassing nodes of the salience network for imminent threat. These preliminary results expand our understanding of right mPFC function associated with temperamental shyness. They also provide initial evidence for differential neural networks associated with shy and non-shy profiles in the context of different types of social threat processing.

  16. Sustained enhancements in inhibitory control depend primarily on the reinforcement of fronto-basal anatomical connectivity.

    Science.gov (United States)

    Chavan, Camille; Mouthon, Michael; Simonet, Marie; Hoogewoud, Henri-Marcel; Draganski, Bogdan; van der Zwaag, Wietske; Spierer, Lucas

    2017-01-01

    What are the neurophysiological determinants of sustained supra-normal inhibitory control performance? We addressed this question by coupling multimodal neuroimaging and behavioral investigations of experts in fencing who underwent more than 20,000 h of inhibitory control training over 15 years. The superior control of the experts manifested behaviorally as a speeding-up of inhibition processes during a Go/NoGo task and was accompanied by changes in bilateral inferior frontal white matter microstructure. In the expert group, inhibition performance correlated positively with the fractional anisotropy (FA) of white matter tracts projecting to the basal ganglia, and the total training load with the FA in supplementary motor areas. Critically, the experts showed no changes in grey matter volume or in the functional organization of the fronto-basal inhibitory control network. The fencers' performance and neural activity during a 2-back working memory task did not differ from those of the controls, ensuring that their expertise was specific to inhibitory control. Our results indicate that while phasic changes in the patterns of neural activity and grey matter architecture accompany inhibitory control improvement after short- to medium- term training, long-lasting inhibitory control improvements primarily depend on the reinforcement of fronto-basal structural connectivity.

  17. On the connection between level of education and the neural circuitry of emotion perception

    Directory of Open Access Journals (Sweden)

    Liliana Ramona Demenescu

    2014-10-01

    Full Text Available Through education, a social group transmits accumulated knowledge, skills, customs, and values to its members. So far, to the best of our knowledge, the association between educational attainment and neural correlates of emotion processing has been left unexplored. In a retrospective analysis of the NESDA fMRI study, we compared two groups of fourteen healthy volunteers with intermediate and high educational attainment, matched for age and gender. The data concerned event-related functional magnetic resonance imaging of brain activation during perception of facial emotional expressions. The region of interest analysis showed stronger right amygdala activation to facial expressions in participants with lower relative to higher educational attainment. The psychophysiological interaction analysis revealed that participants with higher educational attainment exhibited stronger right amygdala – right insula connectivity during perception of emotional and neutral facial expressions. This exploratory study suggests the relevance of educational attainment on the neural mechanism of facial expression processing.

  18. Abnormal Resting-State Neural Activity and Connectivity of Fatigue in Parkinson's Disease.

    Science.gov (United States)

    Zhang, Jie-Jin; Ding, Jian; Li, Jun-Yi; Wang, Min; Yuan, Yong-Sheng; Zhang, Li; Jiang, Si-Ming; Wang, Xi-Xi; Zhu, Lin; Zhang, Ke-Zhong

    2017-03-01

    Fatigue is a common burdensome problem in patients with Parkinson's disease (PD), but its pathophysiological mechanisms are poorly understood. This study aimed at investigating the neural substrates of fatigue in patients with PD. A total of 17 PD patients with fatigue, 32 PD patients without fatigue, and 25 matched healthy controls were recruited. The 9-item fatigue severity scale (FSS) was used for fatigue screening and severity rating. Resting-state functional magnetic resonance imaging (RS-fMRI) data were obtained from all subjects. Amplitude of low-frequency fluctuations (ALFF) was used to measure regional brain activity, and functional connectivity (FC) was applied to investigate functional connectivity at a network level. PD-related fatigue was associated with ALFF changes in right middle frontal gyrus within the attention network and in left insula as well as right midcingulate cortex within the salience network. FC analysis revealed that above three regions showing ALFF differences had altered functional connectivity mainly in the temporal, parietal, and motor cortices. Our findings do reveal that abnormal regional brain activity within attention and salience network and altered FC of above abnormal regions are involved in neural mechanism of fatigue in patients with PD. © 2017 John Wiley & Sons Ltd.

  19. Estimating time-dependent connectivity in marine systems

    Science.gov (United States)

    Defne, Zafer; Ganju, Neil K.; Aretxabaleta, Alfredo

    2016-01-01

    Hydrodynamic connectivity describes the sources and destinations of water parcels within a domain over a given time. When combined with biological models, it can be a powerful concept to explain the patterns of constituent dispersal within marine ecosystems. However, providing connectivity metrics for a given domain is a three-dimensional problem: two dimensions in space to define the sources and destinations and a time dimension to evaluate connectivity at varying temporal scales. If the time scale of interest is not predefined, then a general approach is required to describe connectivity over different time scales. For this purpose, we have introduced the concept of a “retention clock” that highlights the change in connectivity through time. Using the example of connectivity between protected areas within Barnegat Bay, New Jersey, we show that a retention clock matrix is an informative tool for multitemporal analysis of connectivity.

  20. Effects of mindfulness based stress reduction therapy on subjective bother and neural connectivity in chronic tinnitus.

    Science.gov (United States)

    Roland, Lauren T; Lenze, Eric J; Hardin, Frances Mei; Kallogjeri, Dorina; Nicklaus, Joyce; Wineland, Andre M; Fendell, Ginny; Peelle, Jonathan E; Piccirillo, Jay F

    2015-05-01

    To evaluate the impact of a Mindfulness Based Stress Reduction (MBSR) program in patients with chronic bothersome tinnitus on the (1) severity of symptoms of tinnitus and (2) functional connectivity in neural attention networks. Open-label interventional pilot study. Outpatient academic medical center. A total of 13 adult participants with a median age of 55 years, suffering from bothersome tinnitus. An 8-week MBSR program was conducted by a trained MBSR instructor. The primary outcome measure was the difference in patient-reported tinnitus symptoms using the Tinnitus Handicap Index (THI) and Tinnitus Functional Index (TFI) between pre-intervention, post-MBSR, and 4-week post-MBSR assessments. Secondary outcomes included change in measurements of depression, anxiety, mindfulness, and cognitive abilities. Functional connectivity magnetic resonance imaging (MRI) was performed at pre- and post-MBSR intervention time points to serve as a neuroimaging biomarker of critical cortical networks. Scores on the THI and TFI showed statistically significant and clinically meaningful improvement over the course of the study with a median ΔTHI of -16 and median ΔTFI of -14.8 between baseline and 4-week follow-up scores. Except for depression, there was no significant change in any of the secondary outcome measures. Analysis of the resting state functional connectivity MRI (rs-fcMRI) data showed increased connectivity in the post-MBSR group in attention networks but not the default network. Participation in an MBSR program is associated with decreased severity in tinnitus symptoms and depression and connectivity changes in neural attention networks. MBSR is a promising treatment option for chronic bothersome tinnitus that is both noninvasive and inexpensive. © American Academy of Otolaryngology-Head and Neck Surgery Foundation 2015.

  1. Aberrant Spontaneous and Task-Dependent Functional Connections in the Anxious Brain.

    Science.gov (United States)

    MacNamara, Annmarie; DiGangi, Julia; Phan, K Luan

    2016-05-01

    A number of brain regions have been implicated in the anxiety disorders, yet none of these regions in isolation has been distinguished as the sole or discrete site responsible for anxiety disorder pathology. Therefore, the identification of dysfunctional neural networks as represented by alterations in the temporal correlation of blood-oxygen level dependent (BOLD) signal across several brain regions in anxiety disorders has been increasingly pursued in the past decade. Here, we review task-independent (e.g., resting state) and task-induced functional connectivity magnetic resonance imaging (fcMRI) studies in the adult anxiety disorders (including trauma- and stressor-related and obsessive compulsive disorders). The results of this review suggest that anxiety disorder pathophysiology involves aberrant connectivity between amygdala-frontal and frontal-striatal regions, as well as within and between canonical "intrinsic" brain networks - the default mode and salience networks, and that evidence of these aberrations may help inform findings of regional activation abnormalities observed in the anxiety disorders. Nonetheless, significant challenges remain, including the need to better understand mixed findings observed using different methods (e.g., resting state and task-based approaches); the need for more developmental work; the need to delineate disorder-specific and transdiagnostic fcMRI aberrations in the anxiety disorders; and the need to better understand the clinical significance of fcMRI abnormalities. In meeting these challenges, future work has the potential to elucidate aberrant neural networks as intermediate, brain-based phenotypes to predict disease onset and progression, refine diagnostic nosology, and ascertain treatment mechanisms and predictors of treatment response across anxiety, trauma-related and obsessive compulsive disorders.

  2. Cell biology in neuroscience: Architects in neural circuit design: glia control neuron numbers and connectivity.

    Science.gov (United States)

    Corty, Megan M; Freeman, Marc R

    2013-11-11

    Glia serve many important functions in the mature nervous system. In addition, these diverse cells have emerged as essential participants in nearly all aspects of neural development. Improved techniques to study neurons in the absence of glia, and to visualize and manipulate glia in vivo, have greatly expanded our knowledge of glial biology and neuron-glia interactions during development. Exciting studies in the last decade have begun to identify the cellular and molecular mechanisms by which glia exert control over neuronal circuit formation. Recent findings illustrate the importance of glial cells in shaping the nervous system by controlling the number and connectivity of neurons.

  3. Effect of brain structure, brain function, and brain connectivity on relapse in alcohol-dependent patients.

    Science.gov (United States)

    Beck, Anne; Wüstenberg, Torsten; Genauck, Alexander; Wrase, Jana; Schlagenhauf, Florian; Smolka, Michael N; Mann, Karl; Heinz, Andreas

    2012-08-01

    In alcohol-dependent patients, brain atrophy and functional brain activation elicited by alcohol-associated stimuli may predict relapse. However, to date, the interaction between both factors has not been studied. To determine whether results from structural and functional magnetic resonance imaging are associated with relapse in detoxified alcohol-dependent patients. A cue-reactivity functional magnetic resonance experiment with alcohol-associated and neutral stimuli. After a follow-up period of 3 months, the group of 46 detoxified alcohol-dependent patients was subdivided into 16 abstainers and 30 relapsers. Faculty for Clinical Medicine Mannheim at the University of Heidelberg, Germany. A total of 46 detoxified alcohol-dependent patients and 46 age- and sex-matched healthy control subjects Local gray matter volume, local stimulus-related functional magnetic resonance imaging activation, joint analyses of structural and functional data with Biological Parametric Mapping, and connectivity analyses adopting the psychophysiological interaction approach. Subsequent relapsers showed pronounced atrophy in the bilateral orbitofrontal cortex and in the right medial prefrontal and anterior cingulate cortex, compared with healthy controls and patients who remained abstinent. The local gray matter volume-corrected brain response elicited by alcohol-associated vs neutral stimuli in the left medial prefrontal cortex was enhanced for subsequent relapsers, whereas abstainers displayed an increased neural response in the midbrain (the ventral tegmental area extending into the subthalamic nucleus) and ventral striatum. For alcohol-associated vs neutral stimuli in abstainers compared with relapsers, the analyses of the psychophysiological interaction showed a stronger functional connectivity between the midbrain and the left amygdala and between the midbrain and the left orbitofrontal cortex. Subsequent relapsers displayed increased brain atrophy in brain areas associated with

  4. Loss in Connectivity (LoCo) among regions of the brain reward system in alcohol dependence

    OpenAIRE

    Kuceyeski, Amy; Meyerhoff, Dieter J.; Durazzo, Timothy C.; Raj, Ashish

    2012-01-01

    A recently developed measure of structural brain connectivity disruption, the Loss in Connectivity (LoCo), is adapted for studies in alcohol dependence. LoCo uses independent tractography information from young healthy controls to project the location of white matter microstructure abnormalities in alcohol dependent vs. non-dependent individuals onto connected gray matter regions. The LoCo scores are computed from white matter abnormality masks derived at two levels: 1) group-wise differences...

  5. Altered neural connectivity in adult female rats exposed to early life social stress.

    Science.gov (United States)

    Nephew, Benjamin C; Huang, Wei; Poirier, Guillaume L; Payne, Laurellee; King, Jean A

    2017-01-01

    The use of a variety of neuroanatomical techniques has led to a greater understanding of the adverse effects of stress on psychiatric health. One recent advance that has been particularly valuable is the development of resting state functional connectivity (RSFC) in clinical studies. The current study investigates changes in RSFC in F1 adult female rats exposed to the early life chronic social stress (ECSS) of the daily introduction of a novel male intruder to the cage of their F0 mothers while the F1 pups are in the cage. This ECSS for the F1 animals consists of depressed maternal care from their F0 mothers and exposure to conflict between their F0 mothers and intruder males. Analyses of the functional connectivity data in ECSS exposed adult females versus control females reveal broad changes in the limbic and reward systems, the salience and introspective socioaffective networks, and several additional stress and social behavior associated nuclei. Substantial changes in connectivity were found in the prefrontal cortex, nucleus accumbens, hippocampus, and somatosensory cortex. The current rodent RSFC data support the hypothesis that the exposure to early life social stress has long term effects on neural connectivity in numerous social behavior, stress, and depression relevant brain nuclei. Future conscious rodent RSFC studies can build on the wealth of data generated from previous neuroanatomical studies of early life stress and enhance translational connectivity between animal and human fMRI studies in the development of novel preventative measures and treatments. Copyright © 2016 Elsevier B.V. All rights reserved.

  6. Neural connectivity moderates the association between sleep and impulsivity in adolescents

    Directory of Open Access Journals (Sweden)

    Sarah M. Tashjian

    2017-10-01

    Full Text Available Adolescence is characterized by chronic insufficient sleep and extensive brain development, but the relation between adolescent sleep and brain function remains unclear. We report the first functional magnetic resonance imaging study to investigate functional connectivity as a moderator between sleep and impulsivity, a problematic behavior during this developmental period. Naturalistic differences in sleep have not yet been explored as treatable contributors to adolescent impulsivity. Although public and scientific attention focuses on sleep duration, we report individual differences in sleep quality, not duration, in fifty-five adolescents (ages 14–18 yielded significant differences in functional connectivity between the prefrontal cortex and default mode network. Poor sleep quality was related to greater affect-related impulsivity among adolescents with low, but not high, connectivity, suggesting neural functioning relates to individual differences linking sleep quality and impulsivity. Response inhibition and cognitive impulsivity were not related to sleep quality, suggesting that sleep has a greater impact on affect-related impulsivity. Exploring environmental contributors of poor sleep quality, we demonstrated pillow comfort was uniquely related to sleep quality over age, sex, and income, a promising advance ripe for intervention.

  7. Backward renormalization-group inference of cortical dipole sources and neural connectivity efficacy

    Science.gov (United States)

    Amaral, Selene da Rocha; Baccalá, Luiz A.; Barbosa, Leonardo S.; Caticha, Nestor

    2017-06-01

    Proper neural connectivity inference has become essential for understanding cognitive processes associated with human brain function. Its efficacy is often hampered by the curse of dimensionality. In the electroencephalogram case, which is a noninvasive electrophysiological monitoring technique to record electrical activity of the brain, a possible way around this is to replace multichannel electrode information with dipole reconstructed data. We use a method based on maximum entropy and the renormalization group to infer the position of the sources, whose success hinges on transmitting information from low- to high-resolution representations of the cortex. The performance of this method compares favorably to other available source inference algorithms, which are ranked here in terms of their performance with respect to directed connectivity inference by using artificially generated dynamic data. We examine some representative scenarios comprising different numbers of dynamically connected dipoles over distinct cortical surface positions and under different sensor noise impairment levels. The overall conclusion is that inverse problem solutions do not affect the correct inference of the direction of the flow of information as long as the equivalent dipole sources are correctly found.

  8. Tracting the neural basis of music: Deficient structural connectivity underlying acquired amusia.

    Science.gov (United States)

    Sihvonen, Aleksi J; Ripollés, Pablo; Särkämö, Teppo; Leo, Vera; Rodríguez-Fornells, Antoni; Saunavaara, Jani; Parkkola, Riitta; Soinila, Seppo

    2017-12-01

    Acquired amusia provides a unique opportunity to investigate the fundamental neural architectures of musical processing due to the transition from a functioning to defective music processing system. Yet, the white matter (WM) deficits in amusia remain systematically unexplored. To evaluate which WM structures form the neural basis for acquired amusia and its recovery, we studied 42 stroke patients longitudinally at acute, 3-month, and 6-month post-stroke stages using DTI [tract-based spatial statistics (TBSS) and deterministic tractography (DT)] and the Scale and Rhythm subtests of the Montreal Battery of Evaluation of Amusia (MBEA). Non-recovered amusia was associated with structural damage and subsequent degeneration in multiple WM tracts including the right inferior fronto-occipital fasciculus (IFOF), arcuate fasciculus (AF), inferior longitudinal fasciculus (ILF), uncinate fasciculus (UF), and frontal aslant tract (FAT), as well as in the corpus callosum (CC) and its posterior part (tapetum). In a linear regression analysis, the volume of the right IFOF was the main predictor of MBEA performance across time. Overall, our results provide a comprehensive picture of the large-scale deficits in intra- and interhemispheric structural connectivity underlying amusia, and conversely highlight which pathways are crucial for normal music perception. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Context-dependent neural modulations in the perception of duration

    Directory of Open Access Journals (Sweden)

    Yuki eMurai

    2016-03-01

    Full Text Available Recent neuroimaging studies have revealed that distinct brain networks are recruited in the perception of sub- and supra-second timescales, whereas psychophysical studies have suggested that there are common or continuous mechanisms for perceiving these two durations. The present study aimed to elucidate the neural implementation of such continuity by examining the neural correlates of peri-second timing.We measured neural activity during a duration reproduction task using fMRI. Our results replicate the findings of previous studies in showing that separate neural networks are recruited for sub- versus supra-second time perception: motor systems including the motor cortex and the supplementary motor area for sub-second perception, and the frontal, parietal, and auditory cortical areas for supra-second perception. We further found that the peri-second perception activated both the sub- and supra-second networks, and that the timing system that processed duration perception in previous trials was more involved in subsequent peri-second processing. These results indicate that the sub- and supra-second timing systems overlap at around 1 second, and cooperate to optimally encode duration based on the hysteresis of previous trials.

  10. Altered neural connectivity in excitatory and inhibitory cortical circuits in autism

    Directory of Open Access Journals (Sweden)

    Basilis eZikopoulos

    2013-09-01

    Full Text Available Converging evidence from diverse studies suggests that atypical brain connectivity in autism affects in distinct ways short- and long-range cortical pathways, disrupting neural communication and the balance of excitation and inhibition. This hypothesis is based mostly on functional non-invasive studies that show atypical synchronization and connectivity patterns between cortical areas in children and adults with autism. Indirect methods to study the course and integrity of major brain pathways at low resolution show changes in fractional anisotropy or diffusivity of the white matter in autism. Findings in post-mortem brains of adults with autism provide evidence of changes in the fine structure of axons below prefrontal cortices, which communicate over short- or long-range pathways with other cortices and subcortical structures. Here we focus on evidence of cellular and axon features that likely underlie the changes in short- and long-range communication in autism. We review recent findings of changes in the shape, thickness, and volume of brain areas, cytoarchitecture, neuronal morphology, cellular elements, and structural and neurochemical features of individual axons in the white matter, where pathology is evident even in gross images. We relate cellular and molecular features to imaging and genetic studies that highlight a variety of polymorphisms and epigenetic factors that primarily affect neurite growth and synapse formation and function in autism. We report preliminary findings of changes in autism in the ratio of distinct types of inhibitory neurons in prefrontal cortex, known to shape network dynamics and the balance of excitation and inhibition. Finally we present a model that synthesizes diverse findings by relating them to developmental events, with a goal to identify common processes that perturb development in autism and affect neural communication, reflected in altered patterns of attention, social interactions, and language.

  11. Task-dependent reorganization of functional connectivity networks during visual semantic decision making.

    Science.gov (United States)

    DeSalvo, Matthew N; Douw, Linda; Takaya, Shigetoshi; Liu, Hesheng; Stufflebeam, Steven M

    2014-01-01

    Functional MRI is widely used to study task-related changes in neuronal activity as well as resting-state functional connectivity. In this study, we explore task-related changes in functional connectivity networks using fMRI. Dynamic connectivity may represent a new measure of neural network robustness that would impact both clinical and research efforts. However, prior studies of task-related changes in functional connectivity have shown apparently conflicting results, leading to several competing hypotheses regarding the relationship between task-related and resting-state brain networks. We used a graph theory-based network approach to compare functional connectivity in healthy subjects between the resting state and when performing a clinically used semantic decision task. We analyzed fMRI data from 21 healthy, right-handed subjects. While three nonoverlapping, highly intraconnected functional modules were observed in the resting state, an additional language-related module emerged during the semantic decision task. Both overall and within-module connectivity were greater in default mode network (DMN) and classical language areas during semantic decision making compared to rest, while between-module connectivity was diffusely greater at rest, revealing a more widely distributed pattern of functional connectivity at rest. The results of this study suggest that there are differences in network topology between resting and task states. Specifically, semantic decision making is associated with a reduction in distributed connectivity through hub areas of the DMN as well as an increase in connectivity within both default and language networks.

  12. Sleep as a window into early neural development: Shifts in sleep-dependent learning effects across early childhood.

    Science.gov (United States)

    Gómez, Rebecca L; Edgin, Jamie O

    2015-09-01

    Sleep is an important physiological state for the consolidation and generalization of new learning in children and adults. We review the literature on sleep-dependent memory consolidation and generalization in infants and preschool children and place the findings in the context of the development of the neural systems underlying memory (hippocampus and its connections to cortex). Based on the extended trajectory of hippocampal development, transitions in the nature of sleep-dependent learning are expected. The studies reviewed here show shifts in the nature of sleep-dependent learning across early childhood, with sleep facilitating generalization in infants but enhancing precise memory after 18-24 months of age. Future studies on sleep-dependent learning in infants and young children must take these transitions in early brain development into account.

  13. Neural traces of stress: cortisol related sustained enhancement of amygdala-hippocampal functional connectivity

    Directory of Open Access Journals (Sweden)

    Sharon eVaisvaser

    2013-07-01

    Full Text Available Stressful experiences modulate neuro-circuitry function, and the temporal trajectory of these alterations, elapsing from early disturbances to late recovery, heavily influences resilience and vulnerability to stress. Such effects of stress may depend on processes that are engaged during resting-state, through active recollection of past experiences and anticipation of future events, all known to involve the default mode network (DMN. By inducing social stress and acquiring resting-state fMRI before stress, immediately following it, and two hours later, we expanded the time-window for examining the trajectory of the stress response. Throughout the study repeated cortisol samplings and self-reports of stress levels were obtained from 51 healthy young males. Post-stress alterations were investigated by whole brain resting-state functional connectivity of two central hubs of the DMN: the posterior cingulate cortex and hippocampus. Results indicate a 'recovery' pattern of DMN connectivity, in which all alterations, ascribed to the intervening stress, returned to pre-stress levels. The only exception to this pattern was a stress-induced rise in amygdala-hippocampal connectivity, which was sustained for as long as two hours following stress induction. Furthermore, this sustained enhancement of limbic connectivity was inversely correlated to individual stress-induced cortisol responsiveness (AUCi and characterized only the group lacking such increased cortisol (i.e., non-responders. Our observations provide evidence of a prolonged post-stress response profile, characterized by both the comprehensive balance of most DMN functional connections and the distinct time and cortisol dependent ascent of intra-limbic connectivity. These novel insights into neuro-endocrine relations are another milestone in the ongoing search for individual markers in stress-related psychopathologies.

  14. Polygenic risk for five psychiatric disorders and cross-disorder and disorder-specific neural connectivity in two independent populations

    Directory of Open Access Journals (Sweden)

    Tianqi Wang

    2017-01-01

    Full Text Available Major psychiatric disorders, including attention deficit hyperactivity disorder (ADHD, autism (AUT, bipolar disorder (BD, major depressive disorder (MDD, and schizophrenia (SZ, are highly heritable and polygenic. Evidence suggests that these five disorders have both shared and distinct genetic risks and neural connectivity abnormalities. To measure aggregate genetic risks, the polygenic risk score (PGRS was computed. Two independent general populations (N = 360 and N = 323 were separately examined to investigate whether the cross-disorder PGRS and PGRS for a specific disorder were associated with individual variability in functional connectivity. Consistent altered functional connectivity was found with the bilateral insula: for the left supplementary motor area and the left superior temporal gyrus with the cross-disorder PGRS, for the left insula and right middle and superior temporal lobe associated with the PGRS for autism, for the bilateral midbrain, posterior cingulate, cuneus, and precuneus associated with the PGRS for BD, and for the left angular gyrus and the left dorsolateral prefrontal cortex associated with the PGRS for schizophrenia. No significant functional connectivity was found associated with the PGRS for ADHD and MDD. Our findings indicated that genetic effects on the cross-disorder and disorder-specific neural connectivity of common genetic risk loci are detectable in the general population. Our findings also indicated that polygenic risk contributes to the main neurobiological phenotypes of psychiatric disorders and that identifying cross-disorder and specific functional connectivity related to polygenic risks may elucidate the neural pathways for these disorders.

  15. Delay-dependent asymptotic stability for neural networks with time-varying delays

    Directory of Open Access Journals (Sweden)

    Xiaofeng Liao

    2006-01-01

    ensure local and global asymptotic stability of the equilibrium of the neural network. Our results are applied to a two-neuron system with delayed connections between neurons, and some novel asymptotic stability criteria are also derived. The obtained conditions are shown to be less conservative and restrictive than those reported in the known literature. Some numerical examples are included to demonstrate our results.

  16. Adults with high social anhedonia have altered neural connectivity with ventral lateral prefrontal cortex when processing positive social signals

    Directory of Open Access Journals (Sweden)

    Hong eYin

    2015-08-01

    Full Text Available Social anhedonia (SA is a debilitating characteristic of schizophrenia and a vulnerability for developing schizophrenia among people at risk. Prior work (Hooker et al, 2014 has revealed neural deficits in ventral lateral prefrontal cortex (VLPFC during processing of positive emotion in a community sample of people with high social anhedonia. Deficits in VLPFC neural activity are related to worse self-reported schizophrenia-spectrum symptoms and worse mood and behavior after social stress. In the current study, psychophysiological interaction (PPI analysis was applied to investigate the neural mechanisms mediated by VLPFC during emotion processing. PPI analysis revealed that, compared to low SA controls, participants with high SA displayed reduced VLPFC integration, specifically reduced connectivity between VLPFC and premotor cortex, inferior parietal and posterior temporal regions when viewing positive relative to neutral emotion. Across all participants, connectivity between VLPFC and inferior parietal region when viewing positive (versus neutral emotion was significantly correlated with measures of emotion management and attentional control. Additionally connectivity between VLPFC and superior temporal sulcus was related to reward and pleasure anticipation, and connectivity between VLPFC and inferior temporal sulcus correlated with attentional control measure. Our results suggest that impairments to VLPFC mediated neural circuitry underlie the cognitive and emotional deficits.

  17. Exponential distance distribution of connected neurons in simulations of two-dimensional in vitro neural network development

    Science.gov (United States)

    Lv, Zhi-Song; Zhu, Chen-Ping; Nie, Pei; Zhao, Jing; Yang, Hui-Jie; Wang, Yan-Jun; Hu, Chin-Kun

    2017-06-01

    The distribution of the geometric distances of connected neurons is a practical factor underlying neural networks in the brain. It can affect the brain's dynamic properties at the ground level. Karbowski derived a power-law decay distribution that has not yet been verified by experiment. In this work, we check its validity using simulations with a phenomenological model. Based on the in vitro two-dimensional development of neural networks in culture vessels by Ito, we match the synapse number saturation time to obtain suitable parameters for the development process, then determine the distribution of distances between connected neurons under such conditions. Our simulations obtain a clear exponential distribution instead of a power-law one, which indicates that Karbowski's conclusion is invalid, at least for the case of in vitro neural network development in two-dimensional culture vessels.

  18. Identification of Sparse Neural Functional Connectivity using Penalized Likelihood Estimation and Basis Functions

    Science.gov (United States)

    Song, Dong; Wang, Haonan; Tu, Catherine Y.; Marmarelis, Vasilis Z.; Hampson, Robert E.; Deadwyler, Sam A.; Berger, Theodore W.

    2013-01-01

    One key problem in computational neuroscience and neural engineering is the identification and modeling of functional connectivity in the brain using spike train data. To reduce model complexity, alleviate overfitting, and thus facilitate model interpretation, sparse representation and estimation of functional connectivity is needed. Sparsities include global sparsity, which captures the sparse connectivities between neurons, and local sparsity, which reflects the active temporal ranges of the input-output dynamical interactions. In this paper, we formulate a generalized functional additive model (GFAM) and develop the associated penalized likelihood estimation methods for such a modeling problem. A GFAM consists of a set of basis functions convolving the input signals, and a link function generating the firing probability of the output neuron from the summation of the convolutions weighted by the sought model coefficients. Model sparsities are achieved by using various penalized likelihood estimations and basis functions. Specifically, we introduce two variations of the GFAM using a global basis (e.g., Laguerre basis) and group LASSO estimation, and a local basis (e.g., B-spline basis) and group bridge estimation, respectively. We further develop an optimization method based on quadratic approximation of the likelihood function for the estimation of these models. Simulation and experimental results show that both group-LASSO-Laguerre and group-bridge-B-spline can capture faithfully the global sparsities, while the latter can replicate accurately and simultaneously both global and local sparsities. The sparse models outperform the full models estimated with the standard maximum likelihood method in out-of-sample predictions. PMID:23674048

  19. Rules of engagement: factors that regulate activity-dependent synaptic plasticity during neural network development.

    Science.gov (United States)

    Stoneham, Emily T; Sanders, Erin M; Sanyal, Mohima; Dumas, Theodore C

    2010-10-01

    Overproduction and pruning during development is a phenomenon that can be observed in the number of organisms in a population, the number of cells in many tissue types, and even the number of synapses on individual neurons. The sculpting of synaptic connections in the brain of a developing organism is guided by its personal experience, which on a neural level translates to specific patterns of activity. Activity-dependent plasticity at glutamatergic synapses is an integral part of neuronal network formation and maturation in developing vertebrate and invertebrate brains. As development of the rodent forebrain transitions away from an over-proliferative state, synaptic plasticity undergoes modification. Late developmental changes in synaptic plasticity signal the establishment of a more stable network and relate to pronounced perceptual and cognitive abilities. In large part, activation of glutamate-sensitive N-methyl-d-aspartate (NMDA) receptors regulates synaptic stabilization during development and is a necessary step in memory formation processes that occur in the forebrain. A developmental change in the subunits that compose NMDA receptors coincides with developmental modifications in synaptic plasticity and cognition, and thus much research in this area focuses on NMDA receptor composition. We propose that there are additional, equally important developmental processes that influence synaptic plasticity, including mechanisms that are upstream (factors that influence NMDA receptors) and downstream (intracellular processes regulated by NMDA receptors) from NMDA receptor activation. The goal of this review is to summarize what is known and what is not well understood about developmental changes in functional plasticity at glutamatergic synapses, and in the end, attempt to relate these changes to maturation of neural networks.

  20. Neural substrates of impulsive decision making modulated by modafinil in alcohol-dependent patients.

    Science.gov (United States)

    Schmaal, L; Goudriaan, A E; Joos, L; Dom, G; Pattij, T; van den Brink, W; Veltman, D J

    2014-10-01

    Impulsive decision making is a hallmark of frequently occurring addiction disorders including alcohol dependence (AD). Therefore, ameliorating impulsive decision making is a promising target for the treatment of AD. Previous studies have shown that modafinil enhances cognitive control functions in various psychiatric disorders. However, the effects of modafinil on delay discounting and its underlying neural correlates have not been investigated as yet. The aim of the current study was to investigate the effects of modafinil on neural correlates of impulsive decision making in abstinent AD patients and healthy control (HC) subjects. A randomized, double-blind, placebo-controlled, within-subjects cross-over study using functional magnetic resonance imaging (fMRI) was conducted in 14 AD patients and 16 HC subjects. All subjects participated in two fMRI sessions in which they either received a single dose of placebo or 200 mg of modafinil 2 h before the session. During fMRI, subjects completed a delay-discounting task to measure impulsive decision making. Modafinil improved impulsive decision making in AD pateints, which was accompanied by enhanced recruitment of frontoparietal regions and reduced activation of the ventromedial prefrontal cortex. Moreover, modafinil-induced enhancement of functional connectivity between the superior frontal gyrus and ventral striatum was specifically associated with improvement in impulsive decision making. These findings indicate that modafinil can improve impulsive decision making in AD patients through an enhanced coupling of prefrontal control regions and brain regions coding the subjective value of rewards. Therefore, the current study supports the implementation of modafinil in future clinical trials for AD.

  1. Estuarine and coastal connectivity of an estuarine-dependent fishery ...

    African Journals Online (AJOL)

    This study used acoustic telemetry to assess the usage of multiple estuaries and coastal waters by the estuarine-dependent spotted grunter Pomadasys commersonnii. Twenty-six adult fish were tagged with acoustic transmitters in the Kariega and Bushmans estuaries, South Africa, and their movements along a 300-km ...

  2. Re-appraisal of negative emotions in cocaine dependence: dysfunctional corticolimbic activation and connectivity.

    Science.gov (United States)

    Albein-Urios, Natalia; Verdejo-Román, Juan; Asensio, Samuel; Soriano-Mas, Carles; Martínez-González, José M; Verdejo-García, Antonio

    2014-05-01

    Cocaine dependence is associated with pronounced elevations of negative affect and deficient regulation of negative emotions. We aimed to investigate the neural substrates of negative emotion regulation in cocaine-dependent individuals (CDI), as compared to non-drug-using controls, using functional magnetic resonance imaging (fMRI) during a re-appraisal task. Seventeen CDI abstinent for at least 15 days and without other psychiatric co-morbidities and 18 intelligence quotient-matched non-drug-using controls participated in the study. Participants performed the re-appraisal task during fMRI scanning: they were exposed to 24 blocks of negative affective or neutral pictures that they should Observe (neutral pictures), Maintain (sustain the emotion elicited by negative pictures) or Suppress (regulate the emotion elicited by negative pictures through previously trained re-appraisal techniques). Task-related activations during two conditions of interest (Maintain>Observe and Suppress>Maintain) were analyzed using the general linear model in SPM8 software. We also performed psychophysiological interaction (PPI) seed-based analyses based on one region from each condition: the dorsolateral prefrontal cortex (dlPFC-Maintain>Observe) and the inferior frontal gyrus (IFG-Suppress>Maintain). Results showed that cocaine users had increased right dlPFC and bilateral temporoparietal junction activations during Maintain>Observe, whereas they showed decreased right IFG, posterior cingulate cortex, insula and fusiform gyrus activations during Suppress>Maintain. PPI analyses showed that cocaine users had increased functional coupling between the dlPFC and emotion-related regions during Maintain>Observe, whereas they showed decreased functional coupling between the right IFG and the amygdala during Suppress>Maintain. These findings indicate that CDI have dysfunctional corticolimbic activation and connectivity during negative emotion experience and re-appraisal. © 2012 The Authors

  3. Identifying functional connectivity in large-scale neural ensemble recordings: a multiscale data mining approach.

    Science.gov (United States)

    Eldawlatly, Seif; Jin, Rong; Oweiss, Karim G

    2009-02-01

    Identifying functional connectivity between neuronal elements is an essential first step toward understanding how the brain orchestrates information processing at the single-cell and population levels to carry out biological computations. This letter suggests a new approach to identify functional connectivity between neuronal elements from their simultaneously recorded spike trains. In particular, we identify clusters of neurons that exhibit functional interdependency over variable spatial and temporal patterns of interaction. We represent neurons as objects in a graph and connect them using arbitrarily defined similarity measures calculated across multiple timescales. We then use a probabilistic spectral clustering algorithm to cluster the neurons in the graph by solving a minimum graph cut optimization problem. Using point process theory to model population activity, we demonstrate the robustness of the approach in tracking a broad spectrum of neuronal interaction, from synchrony to rate co-modulation, by systematically varying the length of the firing history interval and the strength of the connecting synapses that govern the discharge pattern of each neuron. We also demonstrate how activity-dependent plasticity can be tracked and quantified in multiple network topologies built to mimic distinct behavioral contexts. We compare the performance to classical approaches to illustrate the substantial gain in performance.

  4. The relation between structural and functional connectivity depends on age and on task goals

    Directory of Open Access Journals (Sweden)

    Jaclyn Hennessey Ford

    2014-05-01

    Full Text Available The last decade has seen an increase in neuroimaging studies examining structural (i.e., structural integrity of white matter tracts and functional connectivity (e.g., correlations in neural activity throughout the brain. Although structural and functional connectivity changes have often been measured independently, examining the relation between these two measures is critical to understanding the specific function of neural networks and the ways they may differ across tasks and individuals. The current study addressed this question by examining the effect of age (treated as a continuous variable and emotional valence on the relation between functional and structural connectivity. As prior studies have suggested that prefrontal regions may guide and regulate emotional memory search via functional connections with the amygdala, the current analysis focused on functional connectivity between the left amygdala and the left prefrontal cortex, and structural integrity of the uncinate fasciculus, a white matter tract connecting prefrontal and temporal regions.Participants took part in a scanned retrieval task in which they recalled positive, negative, and neutral images associated with neutral titles. Aging was associated with a significant increase in the relation between measures of structural integrity (specifically, fractional anisotropy, or FA along the uncinate fasciculus and functional connectivity between the left ventral prefrontal cortex and amygdala during positive event retrieval, but not negative or neutral retrieval. Notably, during negative event retrieval, age was linked to stronger structure-function relations between the amygdala and the dorsal anterior cingulate cortex, such that increased structural integrity predicted strong negative functional connectivity in older adults only. These findings are consistent with theories that older adults may engage regulatory strategies if they have the structural pathways to allow them to do so.

  5. Refinement and Pattern Formation in Neural Circuits by the Interaction of Traveling Waves with Spike-Timing Dependent Plasticity

    Science.gov (United States)

    Bennett, James E. M.; Bair, Wyeth

    2015-01-01

    Traveling waves in the developing brain are a prominent source of highly correlated spiking activity that may instruct the refinement of neural circuits. A candidate mechanism for mediating such refinement is spike-timing dependent plasticity (STDP), which translates correlated activity patterns into changes in synaptic strength. To assess the potential of these phenomena to build useful structure in developing neural circuits, we examined the interaction of wave activity with STDP rules in simple, biologically plausible models of spiking neurons. We derive an expression for the synaptic strength dynamics showing that, by mapping the time dependence of STDP into spatial interactions, traveling waves can build periodic synaptic connectivity patterns into feedforward circuits with a broad class of experimentally observed STDP rules. The spatial scale of the connectivity patterns increases with wave speed and STDP time constants. We verify these results with simulations and demonstrate their robustness to likely sources of noise. We show how this pattern formation ability, which is analogous to solutions of reaction-diffusion systems that have been widely applied to biological pattern formation, can be harnessed to instruct the refinement of postsynaptic receptive fields. Our results hold for rich, complex wave patterns in two dimensions and over several orders of magnitude in wave speeds and STDP time constants, and they provide predictions that can be tested under existing experimental paradigms. Our model generalizes across brain areas and STDP rules, allowing broad application to the ubiquitous occurrence of traveling waves and to wave-like activity patterns induced by moving stimuli. PMID:26308406

  6. 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.

  7. Topological dynamics in spike-timing dependent plastic model neural networks

    Directory of Open Access Journals (Sweden)

    David B. Stone

    2013-04-01

    Full Text Available Spike-timing dependent plasticity (STDP is a biologically constrained unsupervised form of learning that potentiates or depresses synaptic connections based on the precise timing of pre-synaptic and post-synaptic firings. The effects of on-going STDP on the topology of evolving model neural networks were assessed in 50 unique simulations which modeled two hours of activity. After a period of stabilization, a number of global and local topological features were monitored periodically to quantify on-going changes in network structure. Global topological features included the total number of remaining synapses, average synaptic strengths, and average number of synapses per neuron (degree. Under a range of different input regimes and initial network configurations, each network maintained a robust and highly stable global structure across time. Local topology was monitored by assessing state changes of all three-neuron subgraphs (triads present in the networks. Overall counts and the range of triad configurations varied little across the simulations; however, a substantial set of individual triads continued to undergo rapid state changes and revealed a dynamic local topology. In addition, specific small-world properties also fluctuated across time. These findings suggest that on-going STDP provides an efficient means of selecting and maintaining a stable yet flexible network organization.

  8. Time dependent evaluation of the lightning upward connecting leader inception

    Energy Technology Data Exchange (ETDEWEB)

    Becerra, Marley; Cooray, Vernon [Division for Electricity and Lightning Research, Uppsala University (Sweden) and Angstroem Laboratory, Box 534, SE 751 21, Uppsala (Sweden)

    2006-11-07

    The evaluation of the upward connecting leader inception from a grounded structure has generally been performed neglecting the effect of the propagation of the downward stepped leader. Nevertheless, field observations suggest that the space charge produced by streamer corona and aborted upward leaders during the approach of the downward lightning leader can influence significantly the initiation of stable upward positive leaders. Thus, a physical leader inception model is developed, which takes into account the electric field variations produced by the descending leader during the process of inception. Also, it accounts for the shielding effect produced by streamer corona and unstable leaders formed before the stable leader inception takes place. The model is validated by comparing its predictions with the results obtained in long gap experiments and in an altitude triggered lightning experiment. The model is then used to estimate the leader inception conditions for free standing rods as a function of tip radius and height. It is found that the rod radius slightly affects the height of the downward leader tip necessary to initiate upward leaders. Only an improvement of about 10% on the lightning attractiveness can be reached by using lightning rods with an optimum radius. Based on the obtained results, the field observations of competing lightning rods are explained. Furthermore, the influence of the average stepped leader velocity on the inception of positive upward leaders is evaluated. The results obtained show that the rate of change of the background electric field produced by a downward leader descent largely influences the conditions necessary for upward leader initiation. Estimations of the leader inception conditions for the upper and lower limit of the measured values of the average downward lightning leader velocity differ by more than 80%. In addition, the striking distances calculated taking into account the temporal change of the background field are

  9. Time dependent evaluation of the lightning upward connecting leader inception

    Science.gov (United States)

    Becerra, Marley; Cooray, Vernon

    2006-11-01

    The evaluation of the upward connecting leader inception from a grounded structure has generally been performed neglecting the effect of the propagation of the downward stepped leader. Nevertheless, field observations suggest that the space charge produced by streamer corona and aborted upward leaders during the approach of the downward lightning leader can influence significantly the initiation of stable upward positive leaders. Thus, a physical leader inception model is developed, which takes into account the electric field variations produced by the descending leader during the process of inception. Also, it accounts for the shielding effect produced by streamer corona and unstable leaders formed before the stable leader inception takes place. The model is validated by comparing its predictions with the results obtained in long gap experiments and in an altitude triggered lightning experiment. The model is then used to estimate the leader inception conditions for free standing rods as a function of tip radius and height. It is found that the rod radius slightly affects the height of the downward leader tip necessary to initiate upward leaders. Only an improvement of about 10% on the lightning attractiveness can be reached by using lightning rods with an optimum radius. Based on the obtained results, the field observations of competing lightning rods are explained. Furthermore, the influence of the average stepped leader velocity on the inception of positive upward leaders is evaluated. The results obtained show that the rate of change of the background electric field produced by a downward leader descent largely influences the conditions necessary for upward leader initiation. Estimations of the leader inception conditions for the upper and lower limit of the measured values of the average downward lightning leader velocity differ by more than 80%. In addition, the striking distances calculated taking into account the temporal change of the background field are

  10. In search of neural mechanisms of mirror neuron dysfunction in schizophrenia: resting state functional connectivity approach.

    Science.gov (United States)

    Zaytseva, Yuliya; Bendova, Marie; Garakh, Zhanna; Tintera, Jaroslav; Rydlo, Jan; Spaniel, Filip; Horacek, Jiri

    2015-09-01

    It has been repeatedly shown that schizophrenia patients have immense alterations in goal-directed behaviour, social cognition, and social interactions, cognitive abilities that are presumably driven by the mirror neurons system (MNS). However, the neural bases of these deficits still remain unclear. Along with the task-related fMRI and EEG research tapping into the mirror neuron system, the characteristics of the resting state activity in the particular areas that encompass mirror neurons might be of interest as they obviously determine the baseline of the neuronal activity. Using resting state fMRI, we investigated resting state functional connectivity (FC) in four predefined brain structures, ROIs (inferior frontal gyrus, superior parietal lobule, premotor cortex and superior temporal gyrus), known for their mirror neurons activity, in 12 patients with first psychotic episode and 12 matched healthy individuals. As a specific hypothesis, based on the knowledge of the anatomical inputs of thalamus to all preselected ROIs, we have investigated the FC between thalamus and the ROIs. Of all ROIs included, seed-to-voxel connectivity analysis revealed significantly decreased FC only in left posterior superior temporal gyrus (STG) and the areas in visual cortex and cerebellum in patients as compared to controls. Using ROI-to-ROI analysis (thalamus and selected ROIs), we have found an increased FC of STG and bilateral thalamus whereas the FC of these areas was decreased in controls. Our results suggest that: (1) schizophrenia patients exhibit FC of STG which corresponds to the previously reported changes of superior temporal gyrus in schizophrenia and might contribute to the disturbances of specific functions, such as emotional processing or spatial awareness; (2) as the thalamus plays a pivotal role in the sensory gating, providing the filtering of the redundant stimulation, the observed hyperconnectivity between the thalami and the STGs in patients with schizophrenia

  11. Augmented Nonlinear Controller for Maximum Power-Point Tracking with Artificial Neural Network in Grid-Connected Photovoltaic Systems

    Directory of Open Access Journals (Sweden)

    Suliang Ma

    2016-11-01

    Full Text Available Photovoltaic (PV systems have non-linear characteristics that generate maximum power at one particular operating point. Environmental factors such as irradiance and temperature variations greatly affect the maximum power point (MPP. Diverse offline and online techniques have been introduced for tracking the MPP. Here, to track the MPP, an augmented-state feedback linearized (AFL non-linear controller combined with an artificial neural network (ANN is proposed. This approach linearizes the non-linear characteristics in PV systems and DC/DC converters, for tracking and optimizing the PV system operation. It also reduces the dependency of the designed controller on linearized models, to provide global stability. A complete model of the PV system is simulated. The existing maximum power-point tracking (MPPT and DC/DC boost-converter controller techniques are compared with the proposed ANN method. Two case studies, which simulate realistic circumstances, are presented to demonstrate the effectiveness and superiority of the proposed method. The AFL with ANN controller can provide good dynamic operation, faster convergence speed, and fewer operating-point oscillations around the MPP. It also tracks the global maxima under different conditions, especially irradiance-mutating situations, more effectively than the conventional methods. Detailed mathematical models and a control approach for a three-phase grid-connected intelligent hybrid system are proposed using MATLAB/Simulink.

  12. Llgl1 Connects Cell Polarity with Cell-Cell Adhesion in Embryonic Neural Stem Cells.

    Science.gov (United States)

    Jossin, Yves; Lee, Minhui; Klezovitch, Olga; Kon, Elif; Cossard, Alexia; Lien, Wen-Hui; Fernandez, Tania E; Cooper, Jonathan A; Vasioukhin, Valera

    2017-06-05

    Malformations of the cerebral cortex (MCCs) are devastating developmental disorders. We report here that mice with embryonic neural stem-cell-specific deletion of Llgl1 (Nestin-Cre/Llgl1fl/fl), a mammalian ortholog of the Drosophila cell polarity gene lgl, exhibit MCCs resembling severe periventricular heterotopia (PH). Immunohistochemical analyses and live cortical imaging of PH formation revealed that disruption of apical junctional complexes (AJCs) was responsible for PH in Nestin-Cre/Llgl1fl/fl brains. While it is well known that cell polarity proteins govern the formation of AJCs, the exact mechanisms remain unclear. We show that LLGL1 directly binds to and promotes internalization of N-cadherin, and N-cadherin/LLGL1 interaction is inhibited by atypical protein kinase C-mediated phosphorylation of LLGL1, restricting the accumulation of AJCs to the basolateral-apical boundary. Disruption of the N-cadherin-LLGL1 interaction during cortical development in vivo is sufficient for PH. These findings reveal a mechanism responsible for the physical and functional connection between cell polarity and cell-cell adhesion machineries in mammalian cells. Copyright © 2017 Elsevier Inc. All rights reserved.

  13. Functional connectivity of primary motor cortex is dependent on genetic burden in prodromal Huntington disease.

    Science.gov (United States)

    Koenig, Katherine A; Lowe, Mark J; Harrington, Deborah L; Lin, Jian; Durgerian, Sally; Mourany, Lyla; Paulsen, Jane S; Rao, Stephen M

    2014-09-01

    Subtle changes in motor function have been observed in individuals with prodromal Huntington disease (prHD), but the underlying neural mechanisms are not well understood nor is the cumulative effect of the disease (disease burden) on functional connectivity. The present study examined the resting-state functional magnetic resonance imaging (rs-fMRI) connectivity of the primary motor cortex (M1) in 16 gene-negative (NEG) controls and 48 gene-positive prHD participants with various levels of disease burden. The results showed that the strength of the left M1 connectivity with the ipsilateral M1 and somatosensory areas decreased as disease burden increased and correlated with motor symptoms. Weakened M1 connectivity within the motor areas was also associated with abnormalities in long-range connections that evolved with disease burden. In this study, M1 connectivity was decreased with visual centers (bilateral cuneus), but increased with a hub of the default mode network (DMN; posterior cingulate cortex). Changes in connectivity measures were associated with worse performance on measures of cognitive-motor functioning. Short- and long-range functional connectivity disturbances were also associated with volume loss in the basal ganglia, suggesting that weakened M1 connectivity is partly a manifestation of striatal atrophy. Altogether, the results indicate that the prodromal phase of HD is associated with abnormal interhemispheric interactions among motor areas and disturbances in the connectivity of M1 with visual centers and the DMN. These changes may, respectively, contribute to increased motor symptoms, visuomotor integration problems, and deficits in the executive control of movement as individuals approach a manifest diagnosis.

  14. Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule.

    Science.gov (United States)

    Liu, Hui; Song, Yongduan; Xue, Fangzheng; Li, Xiumin

    2015-11-01

    In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than the SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing.

  15. Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Hui; Song, Yongduan; Xue, Fangzheng; Li, Xiumin, E-mail: xmli@cqu.edu.cn [Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education, Chongqing University, Chongqing 400044 (China); College of Automation, Chongqing University, Chongqing 400044 (China)

    2015-11-15

    In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than the SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing.

  16. Time- and task-dependent non-neural effects of real and sham TMS.

    Directory of Open Access Journals (Sweden)

    Felix Duecker

    Full Text Available Transcranial magnetic stimulation (TMS is widely used in experimental brain research to manipulate brain activity in humans. Next to the intended neural effects, every TMS pulse produces a distinct clicking sound and sensation on the head which can also influence task performance. This necessitates careful consideration of control conditions in order to ensure that behavioral effects of interest can be attributed to the neural consequences of TMS and not to non-neural effects of a TMS pulse. Surprisingly, even though these non-neural effects of TMS are largely unknown, they are often assumed to be unspecific, i.e. not dependent on TMS parameters. This assumption is inherent to many control strategies in TMS research but has recently been challenged on empirical grounds. Here, we further develop the empirical basis of control strategies in TMS research. We investigated the time-dependence and task-dependence of the non-neural effects of TMS and compared real and sham TMS over vertex. Critically, we show that non-neural TMS effects depend on a complex interplay of these factors. Although TMS had no direct neural effects, both pre- and post-stimulus TMS time windows modulated task performance on both a sensory detection task and a cognitive angle judgment task. For the most part, these effects were quantitatively similar across tasks but effect sizes were clearly different. Moreover, the effects of real and sham TMS were almost identical with interesting exceptions that shed light on the relative contribution of auditory and somato-sensory aspects of a TMS pulse. Knowledge of such effects is of critical importance for the interpretation of TMS experiments and helps deciding what constitutes an appropriate control condition. Our results broaden the empirical basis of control strategies in TMS research and point at potential pitfalls that should be avoided.

  17. Functional connectivity analysis of resting-state fMRI networks in nicotine dependent patients

    Science.gov (United States)

    Smith, Aria; Ehtemami, Anahid; Fratte, Daniel; Meyer-Baese, Anke; Zavala-Romero, Olmo; Goudriaan, Anna E.; Schmaal, Lianne; Schulte, Mieke H. J.

    2016-03-01

    Brain imaging studies identified brain networks that play a key role in nicotine dependence-related behavior. Functional connectivity of the brain is dynamic; it changes over time due to different causes such as learning, or quitting a habit. Functional connectivity analysis is useful in discovering and comparing patterns between functional magnetic resonance imaging (fMRI) scans of patients' brains. In the resting state, the patient is asked to remain calm and not do any task to minimize the contribution of external stimuli. The study of resting-state fMRI networks have shown functionally connected brain regions that have a high level of activity during this state. In this project, we are interested in the relationship between these functionally connected brain regions to identify nicotine dependent patients, who underwent a smoking cessation treatment. Our approach is on the comparison of the set of connections between the fMRI scans before and after treatment. We applied support vector machines, a machine learning technique, to classify patients based on receiving the treatment or the placebo. Using the functional connectivity (CONN) toolbox, we were able to form a correlation matrix based on the functional connectivity between different regions of the brain. The experimental results show that there is inadequate predictive information to classify nicotine dependent patients using the SVM classifier. We propose other classification methods be explored to better classify the nicotine dependent patients.

  18. [Robustness analysis of adaptive neural network model based on spike timing-dependent plasticity].

    Science.gov (United States)

    Chen, Yunzhi; Xu, Guizhi; Zhou, Qian; Guo, Miaomiao; Guo, Lei; Wan, Xiaowei

    2015-02-01

    To explore the self-organization robustness of the biological neural network, and thus to provide new ideas and methods for the electromagnetic bionic protection, we studied both the information transmission mechanism of neural network and spike timing-dependent plasticity (STDP) mechanism, and then investigated the relationship between synaptic plastic and adaptive characteristic of biology. Then a feedforward neural network with the Izhikevich model and the STDP mechanism was constructed, and the adaptive robust capacity of the network was analyzed. Simulation results showed that the neural network based on STDP mechanism had good rubustness capacity, and this characteristics is closely related to the STDP mechanisms. Based on this simulation work, the cell circuit with neurons and synaptic circuit which can simulate the information processing mechanisms of biological nervous system will be further built, then the electronic circuits with adaptive robustness will be designed based on the cell circuit.

  19. Dissociated neural effects of cortisol depending on threat escapability

    NARCIS (Netherlands)

    Montoya, Estrella R; van Honk, Jack; Bos, Peter A; Terburg, David

    2015-01-01

    Evolution has provided us with a highly flexible neuroendocrine threat system which, depending on threat imminence, switches between active escape and passive freezing. Cortisol, the "stress-hormone", is thought to play an important role in both fear behaviors, but the exact mechanisms are not

  20. A Novel Neural Network Vector Control for Single-Phase Grid-Connected Converters with L, LC and LCL Filters

    Directory of Open Access Journals (Sweden)

    Xingang Fu

    2016-04-01

    Full Text Available This paper investigates a novel recurrent neural network (NN-based vector control approach for single-phase grid-connected converters (GCCs with L (inductor, LC (inductor-capacitor and LCL (inductor-capacitor-inductor filters and provides their comparison study with the conventional standard vector control method. A single neural network controller replaces two current-loop PI controllers, and the NN training approximates the optimal control for the single-phase GCC system. The Levenberg–Marquardt (LM algorithm was used to train the NN controller based on the complete system equations without any decoupling policies. The proposed NN approach can solve the decoupling problem associated with the conventional vector control methods for L, LC and LCL-filter-based single-phase GCCs. Both simulation study and hardware experiments demonstrate that the neural network vector controller shows much more improved performance than that of conventional vector controllers, including faster response speed and lower overshoot. Especially, NN vector control could achieve very good performance using low switch frequency. More importantly, the neural network vector controller is a damping free controller, which is generally required by a conventional vector controller for an LCL-filter-based single-phase grid-connected converter and, therefore, can overcome the inefficiency problem caused by damping policies.

  1. Class 1 neural excitability, conventional synapses, weakly connected networks, and mathematical foundations of pulse-coupled models.

    Science.gov (United States)

    Izhikevich, E M

    1999-01-01

    Many scientists believe that all pulse-coupled neural networks are toy models that are far away from the biological reality. We show here, however, that a huge class of biophysically detailed and biologically plausible neural-network models can be transformed into a canonical pulse-coupled form by a piece-wise continuous, possibly noninvertible, change of variables. Such transformations exist when a network satisfies a number of conditions; e.g., it is weakly connected; the neurons are Class 1 excitable (i.e., they can generate action potentials with an arbitrary small frequency); and the synapses between neurons are conventional (i.e., axo-dendritic and axo-somatic). Thus, the difference between studying the pulse-coupled model and Hodgkin-Huxley-type neural networks is just a matter of a coordinate change. Therefore, any piece of information about the pulse-coupled model is valuable since it tells something about all weakly connected networks of Class 1 neurons. For example, we show that the pulse-coupled network of identical neurons does not synchronize in-phase. This confirms Ermentrout's result that weakly connected Class 1 neurons are difficult to synchronize, regardless of the equations that describe dynamics of each cell.

  2. Connectivity in the yeast cell cycle transcription network: inferences from neural networks.

    Directory of Open Access Journals (Sweden)

    Christopher E Hart

    2006-12-01

    Full Text Available A current challenge is to develop computational approaches to infer gene network regulatory relationships based on multiple types of large-scale functional genomic data. We find that single-layer feed-forward artificial neural network (ANN models can effectively discover gene network structure by integrating global in vivo protein:DNA interaction data (ChIP/Array with genome-wide microarray RNA data. We test this on the yeast cell cycle transcription network, which is composed of several hundred genes with phase-specific RNA outputs. These ANNs were robust to noise in data and to a variety of perturbations. They reliably identified and ranked 10 of 12 known major cell cycle factors at the top of a set of 204, based on a sum-of-squared weights metric. Comparative analysis of motif occurrences among multiple yeast species independently confirmed relationships inferred from ANN weights analysis. ANN models can capitalize on properties of biological gene networks that other kinds of models do not. ANNs naturally take advantage of patterns of absence, as well as presence, of factor binding associated with specific expression output; they are easily subjected to in silico "mutation" to uncover biological redundancies; and they can use the full range of factor binding values. A prominent feature of cell cycle ANNs suggested an analogous property might exist in the biological network. This postulated that "network-local discrimination" occurs when regulatory connections (here between MBF and target genes are explicitly disfavored in one network module (G2, relative to others and to the class of genes outside the mitotic network. If correct, this predicts that MBF motifs will be significantly depleted from the discriminated class and that the discrimination will persist through evolution. Analysis of distantly related Schizosaccharomyces pombe confirmed this, suggesting that network-local discrimination is real and complements well-known enrichment of

  3. Principles of Experience-Dependent Neural Plasticity: Implications for Rehabilitation after Brain Damage

    Science.gov (United States)

    Kleim, Jeffrey A.; Jones, Theresa A.

    2008-01-01

    Purpose: This paper reviews 10 principles of experience-dependent neural plasticity and considerations in applying them to the damaged brain. Method: Neuroscience research using a variety of models of learning, neurological disease, and trauma are reviewed from the perspective of basic neuroscientists but in a manner intended to be useful for the…

  4. Brief Report: Anomalous Neural Deactivations and Functional Connectivity during Receptive Language in Autism Spectrum Disorder--A Functional MRI Study

    Science.gov (United States)

    Karten, Ariel; Hirsch, Joy

    2015-01-01

    Neural mechanisms that underlie language disability in autism spectrum disorder (ASD) have been associated with reduced excitatory processes observed as positive blood oxygen level dependent (BOLD) responses. However, negative BOLD responses (NBR) associated with language and inhibitory processes have been less studied in ASD. In this study,…

  5. Mutual connectivity analysis (MCA) using generalized radial basis function neural networks for nonlinear functional connectivity network recovery in resting-state functional MRI

    Science.gov (United States)

    D'Souza, Adora M.; Abidin, Anas Zainul; Nagarajan, Mahesh B.; Wismüller, Axel

    2016-03-01

    We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 +/- 0.037) as well as the underlying network structure (Rand index = 0.87 +/- 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.

  6. On the Nature of the Intrinsic Connectivity of the Cat Motor Cortex: Evidence for a Recurrent Neural Network Topology

    DEFF Research Database (Denmark)

    Capaday, Charles; Ethier, C; Brizzi, L

    2009-01-01

    Capaday C, Ethier C, Brizzi L, Sik A, van Vreeswijk C, Gingras D. On the nature of the intrinsic connectivity of the cat motor cortex: evidence for a recurrent neural network topology. J Neurophysiol 102: 2131-2141, 2009. First published July 22, 2009; doi: 10.1152/jn.91319.2008. The details...... and functional significance of the intrinsic horizontal connections between neurons in the motor cortex (MCx) remain to be clarified. To further elucidate the nature of this intracortical connectivity pattern, experiments were done on the MCx of three cats. The anterograde tracer biocytin was ejected...... iontophoretically in layers II, III, and V. Some 30-50 neurons within a radius of similar to 250 mu m were thus stained. The functional output of the motor cortical point at which biocytin was injected, and of the surrounding points, was identified by microstimulation and electromyographic recordings. The axonal...

  7. Attenuated neural response to emotional cues in cocaine-dependence: a preliminary analysis of gender differences.

    Science.gov (United States)

    Canterberry, Melanie; Peltier, MacKenzie R; Brady, Kathleen T; Hanlon, Colleen A

    2016-09-01

    Cocaine users often report a loss of arousal for nondrug-related stimuli, which may contribute to their response to drug-related rewards. However, little is known about users' neural reactivity to emotional nondrug-related stimuli and the potential influence of gender. Test the hypotheses that cocaine-dependent individuals have an attenuated neural response to arousing stimuli relative to controls and that this difference is amplified in women. The brain response to typically arousing positive and negative images as well as neutral images from the International Affective Picture System was measured in 40 individuals (20 non-treatment seeking cocaine-dependent and 20 age- and gender-matched control participants; 50% of whom were women). Images were displayed for 4 s each in blocks of five across two 270-second runs. General linear models assessed within and between group activation differences for the emotional images. Cocaine-dependent individuals had a significantly lower response to typically arousing positive and negative images than controls, with attenuated neural activity present in the medial prefrontal cortex (mPFC) and anterior cingulate cortex (ACC). Analyses by gender revealed less mPFC/ACC activation among female users, but not males, for both positive and negative images. The dampened neural response to typically arousing stimuli among cocaine-dependent polydrug users suggests decreased salience processing for nondrug stimuli, particularly among female users. This decreased responding is consistent with data from other substance using populations and suggests that this may be a general feature of addiction. Amplifying the neural response to naturally arousing nondrug-related reinforcers may present an opportunity for unique behavioral and brain stimulation therapies.

  8. Bias-dependent hybrid PKI empirical-neural model of microwave FETs

    Science.gov (United States)

    Marinković, Zlatica; Pronić-Rančić, Olivera; Marković, Vera

    2011-10-01

    Empirical models of microwave transistors based on an equivalent circuit are valid for only one bias point. Bias-dependent analysis requires repeated extractions of the model parameters for each bias point. In order to make model bias-dependent, a new hybrid empirical-neural model of microwave field-effect transistors is proposed in this article. The model is a combination of an equivalent circuit model including noise developed for one bias point and two prior knowledge input artificial neural networks (PKI ANNs) aimed at introducing bias dependency of scattering (S) and noise parameters, respectively. The prior knowledge of the proposed ANNs involves the values of the S- and noise parameters obtained by the empirical model. The proposed hybrid model is valid in the whole range of bias conditions. Moreover, the proposed model provides better accuracy than the empirical model, which is illustrated by an appropriate modelling example of a pseudomorphic high-electron mobility transistor device.

  9. The neural changes in connectivity of the voice network during voice pitch perturbation

    OpenAIRE

    Flagmeier, Sabina G.; Ray, Kimberly L.; Parkinson, Amy L.; Li, Karl; Vargas, Robert; Price, Larry R.; Laird, Angela R.; Charles R Larson; Robin, Donald A.

    2014-01-01

    Voice control is critical to communication. To date, studies have used behavioral, electrophysiological and functional data to investigate the neural correlates of voice control using perturbation tasks, but have yet to examine the interactions of these neural regions. The goal of this study was to use structural equation modeling of functional neuroimaging data to examine network properties of voice with and without perturbation. Results showed that the presence of a pitch shift, which was p...

  10. Aberrant default-mode functional and structural connectivity in heroin-dependent individuals.

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    Xiaofen Ma

    Full Text Available Little is known about connectivity within the default mode network (DMN in heroin-dependent individuals (HDIs. In the current study, diffusion-tensor imaging (DTI and resting-state functional MRI (rs-fMRI were combined to investigate both structural and functional connectivity within the DMN in HDIs.Fourteen HDIs and 14 controls participated in the study. Structural (path length, tracts count, (fractional anisotropy FA and (mean diffusivity MD derived from DTI tractographyand functional (temporal correlation coefficient derived from rs-fMRI DMN connectivity changes were examined in HDIs. Pearson correlation analysis was performed to compare the structural/functional indices and duration of heroin use/Iowa gambling task(IGT performance in HDIs.HDIs had lower FA and higher MD in the tract connecting the posterior cingulate cortex/precuneus (PCC/PCUN to right parahippocampal gyrus (PHG, compared to the controls. HDIs also had decreased FA and track count in the tract connecting the PCC/PCUN and medial prefrontal cortex (MPFC, as well as decreased functional connectivity between the PCC/PCUN and bilateral PHG and MPFC, compared to controls. FA values for the tract connecting PCC/PCUN to the right PHG and connecting PCC/PCUN to the MPFC were negatively correlated to the duration of heroin use. The temporal correlation coefficients between the PCC/PCUN and the MPFC, and the FA values for the tract connecting the PCC/PCUN to the MPFC were positively correlated to IGT performance in HDIs.Structural and functional connectivity within the DMN are both disturbed in HDIs. This disturbance progresses as duration of heroin use increases and is related to deficits in decision making in HDIs.

  11. Differences in functional connectivity between alcohol dependence and internet gaming disorder.

    Science.gov (United States)

    Han, Ji Won; Han, Doug Hyun; Bolo, Nicolas; Kim, BoAh; Kim, Boong Nyun; Renshaw, Perry F

    2015-02-01

    Internet gaming disorder (IGD) and alcohol dependence (AD) have been reported to share clinical characteristics including craving and over-engagement despite negative consequences. However, there are also clinical factors that differ between individuals with IGD and those with AD in terms of chemical intoxication, prevalence age, and visual and auditory stimulation. We assessed brain functional connectivity within the prefrontal, striatum, and temporal lobe in 15 patients with IGD and in 16 patients with AD. Symptoms of depression, anxiety, and the attention deficit hyperactivity disorder were assessed in patients with IGD and in patients with AD. Both AD and IGD subjects have positive functional connectivity between the dorsolateral prefrontal cortex (DLPFC), cingulate, and cerebellum. In addition, both groups have negative functional connectivity between the DLPFC and the orbitofrontal cortex. However, the AD subjects have positive functional connectivity between the DLPFC, temporal lobe and striatal areas while IGD subjects have negative functional connectivity between the DLPFC, temporal lobe and striatal areas. AD and IGD subjects may share deficits in executive function, including problems with self-control and adaptive responding. However, the negative connectivity between the DLPFC and the striatal areas in IGD subjects, different from the connectivity observed in AD subjects, may be due to the earlier prevalence age, different comorbid diseases as well as visual and auditory stimulation. Copyright © 2014 Elsevier Ltd. All rights reserved.

  12. Cingulate cortex functional connectivity predicts future relapse in alcohol dependent individuals.

    Science.gov (United States)

    Zakiniaeiz, Yasmin; Scheinost, Dustin; Seo, Dongju; Sinha, Rajita; Constable, R Todd

    2017-01-01

    Alcohol dependence is a chronic relapsing illness. Alcohol and stress cues have consistently been shown to increase craving and relapse risk in recovering alcohol dependent (AUD) patients. However, differences in functional connectivity in response to these cues have not been studied using data-driven approaches. Here, voxel-wise connectivity is used in a whole-brain investigation of functional connectivity differences associated with alcohol and stress cues and to examine whether these differences are related to subsequent relapse. In Study 1, 45, 4- to 8-week abstinent, recovering AUD patients underwent functional magnetic resonance imaging during individualized imagery of alcohol, stress, and neutral cues. Relapse measures were collected prospectively for 90 days post-discharge from inpatient treatment. AUD patients showed blunted anterior (ACC), mid (MCC) and posterior cingulate cortex (PCC), voxel-wise connectivity responses to stress compared to neutral cues and blunted PCC response to alcohol compared to neutral cues. Using Cox proportional hazard regression, weaker connectivity in ACC and MCC during neutral exposure was associated with longer time to relapse (better recovery outcome). Similarly, greater connectivity in PCC during alcohol-cue compared to stress cue was associated with longer time to relapse. In Study 2, a sub-group of 30 AUD patients were demographically-matched to 30 healthy control (HC) participants for group comparisons. AUD compared to HC participants showed reduced cingulate connectivity during alcohol and stress cues. Using novel data-driven approaches, the cingulate cortex emerged as a key region in the disruption of functional connectivity during alcohol and stress-cue processing in AUD patients and as a marker of subsequent alcohol relapse.

  13. Cingulate cortex functional connectivity predicts future relapse in alcohol dependent individuals

    Directory of Open Access Journals (Sweden)

    Yasmin Zakiniaeiz

    2017-01-01

    Full Text Available Alcohol dependence is a chronic relapsing illness. Alcohol and stress cues have consistently been shown to increase craving and relapse risk in recovering alcohol dependent (AUD patients. However, differences in functional connectivity in response to these cues have not been studied using data-driven approaches. Here, voxel-wise connectivity is used in a whole-brain investigation of functional connectivity differences associated with alcohol and stress cues and to examine whether these differences are related to subsequent relapse. In Study 1, 45, 4- to 8-week abstinent, recovering AUD patients underwent functional magnetic resonance imaging during individualized imagery of alcohol, stress, and neutral cues. Relapse measures were collected prospectively for 90 days post-discharge from inpatient treatment. AUD patients showed blunted anterior (ACC, mid (MCC and posterior cingulate cortex (PCC, voxel-wise connectivity responses to stress compared to neutral cues and blunted PCC response to alcohol compared to neutral cues. Using Cox proportional hazard regression, weaker connectivity in ACC and MCC during neutral exposure was associated with longer time to relapse (better recovery outcome. Similarly, greater connectivity in PCC during alcohol-cue compared to stress cue was associated with longer time to relapse. In Study 2, a sub-group of 30 AUD patients were demographically-matched to 30 healthy control (HC participants for group comparisons. AUD compared to HC participants showed reduced cingulate connectivity during alcohol and stress cues. Using novel data-driven approaches, the cingulate cortex emerged as a key region in the disruption of functional connectivity during alcohol and stress-cue processing in AUD patients and as a marker of subsequent alcohol relapse.

  14. Determination of relaxation modulus of time-dependent materials using neural networks

    Science.gov (United States)

    Aulova, Alexandra; Govekar, Edvard; Emri, Igor

    2017-08-01

    Health monitoring systems for plastic based structures require the capability of real time tracking of changes in response to the time-dependent behavior of polymer based structures. The paper proposes artificial neural networks as a tool of solving inverse problem appearing within time-dependent material characterization, since the conventional methods are computationally demanding and cannot operate in the real time mode. Abilities of a Multilayer Perceptron (MLP) and a Radial Basis Function Neural Network (RBFN) to solve ill-posed inverse problems on an example of determination of a time-dependent relaxation modulus curve segment from constant strain rate tensile test data are investigated. The required modeling data composed of strain rate, tensile and related relaxation modulus were generated using existing closed-form solution. Several neural networks topologies were tested with respect to the structure of input data, and their performance was compared to an exponential fitting technique. Selected optimal topologies of MLP and RBFN were tested for generalization and robustness on noisy data; performance of all the modeling methods with respect to the number of data points in the input vector was analyzed as well. It was shown that MLP and RBFN are capable of solving inverse problems related to the determination of a time dependent relaxation modulus curve segment. Particular topologies demonstrate good generalization and robustness capabilities, where the topology of RBFN with data provided in parallel proved to be superior compared to other methods.

  15. Functional connectivity among spike trains in neural assemblies during rat working memory task.

    Science.gov (United States)

    Xie, Jiacun; Bai, Wenwen; Liu, Tiaotiao; Tian, Xin

    2014-11-01

    Working memory refers to a brain system that provides temporary storage to manipulate information for complex cognitive tasks. As the brain is a more complex, dynamic and interwoven network of connections and interactions, the questions raised here: how to investigate the mechanism of working memory from the view of functional connectivity in brain network? How to present most characteristic features of functional connectivity in a low-dimensional network? To address these questions, we recorded the spike trains in prefrontal cortex with multi-electrodes when rats performed a working memory task in Y-maze. The functional connectivity matrix among spike trains was calculated via maximum likelihood estimation (MLE). The average connectivity value Cc, mean of the matrix, was calculated and used to describe connectivity strength quantitatively. The spike network was constructed by the functional connectivity matrix. The information transfer efficiency Eglob was calculated and used to present the features of the network. In order to establish a low-dimensional spike network, the active neurons with higher firing rates than average rate were selected based on sparse coding. The results show that the connectivity Cc and the network transfer efficiency Eglob vaired with time during the task. The maximum values of Cc and Eglob were prior to the working memory behavior reference point. Comparing with the results in the original network, the feature network could present more characteristic features of functional connectivity. Copyright © 2014 Elsevier B.V. All rights reserved.

  16. Neural Correlates of Impulsive Aggressive Behavior in Subjects With a History of Alcohol Dependence

    OpenAIRE

    Kose,Samet; Steinberg, Joel L.; Moeller, F. Gerard; Gowin, Joshua L.; Zuniga, Edward; Kamdar, Zahra N.; Schmitz, Joy M.; Scott D. Lane

    2015-01-01

    Alcohol-related aggression is a complex and problematic phenomenon with profound public health consequences. We examined neural correlates potentially moderating the relationship between human aggressive behavior and chronic alcohol use. Thirteen subjects meeting DSM–IV criteria for past alcohol-dependence in remission (AD) and 13 matched healthy controls (CONT) participated in an fMRI study adapted from a laboratory model of human aggressive behavior (Point Subtraction Aggression Paradigm, o...

  17. Delay-Dependent Stability Criteria of Uncertain Periodic Switched Recurrent Neural Networks with Time-Varying Delays

    Directory of Open Access Journals (Sweden)

    Xing Yin

    2011-01-01

    uncertain periodic switched recurrent neural networks with time-varying delays. When uncertain discrete-time recurrent neural network is a periodic system, it is expressed as switched neural network for the finite switching state. Based on the switched quadratic Lyapunov functional approach (SQLF and free-weighting matrix approach (FWM, some linear matrix inequality criteria are found to guarantee the delay-dependent asymptotical stability of these systems. Two examples illustrate the exactness of the proposed criteria.

  18. Loss in Connectivity (LoCo) among regions of the brain reward system in alcohol dependence

    Science.gov (United States)

    Kuceyeski, Amy; Meyerhoff, Dieter J.; Durazzo, Timothy C.; Raj, Ashish

    2014-01-01

    A recently developed measure of structural brain connectivity disruption, the Loss in Connectivity (LoCo), is adapted for studies in alcohol dependence. LoCo uses independent tractography information from young healthy controls to project the location of white matter microstructure abnormalities in alcohol dependent vs. non-dependent individuals onto connected gray matter regions. The LoCo scores are computed from white matter abnormality masks derived at two levels: 1) group-wise differences of alcohol dependent individuals versus light drinking controls and 2) differences of the alcohol dependent individual versus the light drinking control group. LoCo scores based on group-wise white matter differences show that gray matter regions belonging to the extended brain reward system-network (BRS) have significantly higher LoCo (i.e., disconnectivity) than those not in this network (t = 2.18, p = 0.016). LoCo scores based on individuals’ white matter differences are also higher in BRS vs. non-BRS (t = 5.26, p = 3.92×10−6) of alcohol dependent individuals. These results suggest that white matter alterations in alcohol dependence, although subtle and spatially heterogeneous across the population, are nonetheless preferentially localized to the BRS. LoCo is shown to provide a more sensitive estimate of gray matter involvement than conventional volumetric gray matter measures, by differentiating better between brains of alcohol dependent individuals and non-alcoholic controls (rates of 89.3% versus 69.6%). However, just as volumetric measures, LoCo is not significantly correlated with standard drinking severity measures. LoCo is a sensitive white matter measure of regional cortical disconnectivity that uniquely characterizes anatomical network disruptions in alcohol dependence. PMID:22815206

  19. Enhancement of Spike-Timing-Dependent Plasticity in Spiking Neural Systems with Noise.

    Science.gov (United States)

    Nobukawa, Sou; Nishimura, Haruhiko

    2016-08-01

    Synaptic plasticity is widely recognized to support adaptable information processing in the brain. Spike-timing-dependent plasticity, one subtype of plasticity, can lead to synchronous spike propagation with temporal spiking coding information. Recently, it was reported that in a noisy environment, like the actual brain, the spike-timing-dependent plasticity may be made efficient by the effect of stochastic resonance. In the stochastic resonance, the presence of noise helps a nonlinear system in amplifying a weak (under barrier) signal. However, previous studies have ignored the full variety of spiking patterns and many relevant factors in neural dynamics. Thus, in order to prove the physiological possibility for the enhancement of spike-timing-dependent plasticity by stochastic resonance, it is necessary to demonstrate that this stochastic resonance arises in realistic cortical neural systems. In this study, we evaluate this stochastic resonance phenomenon in the realistic cortical neural system described by the Izhikevich neuron model and compare the characteristics of typical spiking patterns of regular spiking, intrinsically bursting and chattering experimentally observed in the cortex.

  20. On the connection between level of education and the neural circuitry of emotion perception

    NARCIS (Netherlands)

    Demenescu, L.R.; Stan, A.; Kortekaas, R.; van der Wee, N.J.A.; Veltman, D.J.; Aleman, A.

    2014-01-01

    Through education, a social group transmits accumulated knowledge, skills, customs, and values to its members. So far, to the best of our knowledge, the association between educational attainment and neural correlates of emotion processing has been left unexplored. In a retrospective analysis of The

  1. Folate-dependent methylation of septins governs ciliogenesis during neural tube closure.

    Science.gov (United States)

    Toriyama, Manami; Toriyama, Michinori; Wallingford, John B; Finnell, Richard H

    2017-08-01

    Periconception maternal folic acid (vitamin B9) supplementation can reduce the prevalence of neural tube defects (NTDs), although just how folates benefit the developing embryo and promote closing of the neural tube and other morphologic processes during development remains unknown. Folate contributes to a 1-carbon metabolism, which is essential for purine biosynthesis and methionine recycling and affects methylation of DNA, histones, and nonhistone proteins. Herein, we used animal models and cultured mammalian cells to demonstrate that disruption of the methylation pathway mediated by folate compromises normal neural tube closure (NTC) and ciliogenesis. We demonstrate that the embryos with NTD failed to adequately methylate septin2, a key regulator of cilium structure and function. We report that methylation of septin2 affected its GTP binding activity and formation of the septin2-6-7 complex. We propose that folic acid promotes normal NTC in some embryos by regulating the methylation of septin2, which is critical for normal cilium formation during early embryonic development.-Toriyama, M., Toriyama, M., Wallingford, J. B., Finnell, R. H. Folate-dependent methylation of septins governs ciliogenesis during neural tube closure. © FASEB.

  2. Neural Correlates of Math Gains Vary Depending on Parental Socioeconomic Status (SES).

    Science.gov (United States)

    Demir-Lira, Özlem Ece; Prado, Jérôme; Booth, James R

    2016-01-01

    We used functional magnetic resonance imaging (fMRI) to examine the neural predictors of math development, and asked whether these predictors vary as a function of parental socioeconomic status (SES) in children ranging in age from 8 to 13 years. We independently localized brain regions subserving verbal versus spatial processing in order to characterize relations between activation in these regions during an arithmetic task and long-term change in math skill (up to 3 years). Neural predictors of math gains encompassed brain regions subserving both verbal and spatial processing, but the relation between relative reliance on these regions and math skill growth varied depending on parental SES. Activity in an area of the left inferior frontal gyrus (IFG) identified by the verbal localizer was related to greater growth in math skill at the higher end of the SES continuum, but lesser improvements at the lower end. Activity in an area of the right superior parietal cortex identified by the spatial localizer was related to greater growth in math skill at the lower end of the SES continuum, but lesser improvements at the higher end. Results highlight early neural mechanisms as possible neuromarkers of long-term arithmetic learning and suggest that neural predictors of math gains vary with parental SES.

  3. Mode of Effective Connectivity within a Putative Neural Network Differentiates Moral Cognitions Related to Care and Justice Ethics

    Science.gov (United States)

    Cáceda, Ricardo; James, G. Andrew; Ely, Timothy D.; Snarey, John; Kilts, Clinton D.

    2011-01-01

    Background Moral sensitivity refers to the interpretive awareness of moral conflict and can be justice or care oriented. Justice ethics is associated primarily with human rights and the application of moral rules, whereas care ethics is related to human needs and a situational approach involving social emotions. Among the core brain regions involved in moral issue processing are: medial prefrontal cortex, anterior (ACC) and posterior (PCC) cingulate cortex, posterior superior temporal sulcus (pSTS), insula and amygdala. This study sought to inform the long standing debate of whether care and justice moral ethics represent one or two different forms of cognition. Methodology/Principal Findings Model-free and model-based connectivity analysis were used to identify functional neural networks underlying care and justice ethics for a moral sensitivity task. In addition to modest differences in patterns of associated neural activity, distinct modes of functional and effective connectivity were observed for moral sensitivity for care and justice issues that were modulated by individual variation in moral ability. Conclusions/Significance These results support a neurobiological differentiation between care and justice ethics and suggest that human moral behavior reflects the outcome of integrating opposing rule-based, self-other perspectives, and emotional responses. PMID:21364916

  4. Mode of effective connectivity within a putative neural network differentiates moral cognitions related to care and justice ethics.

    Directory of Open Access Journals (Sweden)

    Ricardo Cáceda

    Full Text Available BACKGROUND: Moral sensitivity refers to the interpretive awareness of moral conflict and can be justice or care oriented. Justice ethics is associated primarily with human rights and the application of moral rules, whereas care ethics is related to human needs and a situational approach involving social emotions. Among the core brain regions involved in moral issue processing are: medial prefrontal cortex, anterior (ACC and posterior (PCC cingulate cortex, posterior superior temporal sulcus (pSTS, insula and amygdala. This study sought to inform the long standing debate of whether care and justice moral ethics represent one or two different forms of cognition. METHODOLOGY/PRINCIPAL FINDINGS: Model-free and model-based connectivity analysis were used to identify functional neural networks underlying care and justice ethics for a moral sensitivity task. In addition to modest differences in patterns of associated neural activity, distinct modes of functional and effective connectivity were observed for moral sensitivity for care and justice issues that were modulated by individual variation in moral ability. CONCLUSIONS/SIGNIFICANCE: These results support a neurobiological differentiation between care and justice ethics and suggest that human moral behavior reflects the outcome of integrating opposing rule-based, self-other perspectives, and emotional responses.

  5. A Neural Model of Distance-Dependent Percept of Object Size Constancy.

    Directory of Open Access Journals (Sweden)

    Jiehui Qian

    Full Text Available Size constancy is one of the well-known visual phenomena that demonstrates perceptual stability to account for the effect of viewing distance on retinal image size. Although theories involving distance scaling to achieve size constancy have flourished based on psychophysical studies, its underlying neural mechanisms remain unknown. Single cell recordings show that distance-dependent size tuned cells are common along the ventral stream, originating from V1, V2, and V4 leading to IT. In addition, recent research employing fMRI demonstrates that an object's perceived size, associated with its perceived egocentric distance, modulates its retinotopic representation in V1. These results suggest that V1 contributes to size constancy, and its activity is possibly regulated by feedback of distance information from other brain areas. Here, we propose a neural model based on these findings. First, we construct an egocentric distance map in LIP by integrating horizontal disparity and vergence through gain-modulated MT neurons. Second, LIP neurons send modulatory feedback of distance information to size tuned cells in V1, resulting in a spread of V1 cortical activity. This process provides V1 with distance-dependent size representations. The model supports that size constancy is preserved by scaling retinal image size to compensate for changes in perceived distance, and suggests a possible neural circuit capable of implementing this process.

  6. Stochastic dynamic causal modeling of working memory connections in cocaine dependence.

    Science.gov (United States)

    Ma, Liangsuo; Steinberg, Joel L; Hasan, Khader M; Narayana, Ponnada A; Kramer, Larry A; Moeller, F Gerard

    2014-03-01

    Although reduced working memory brain activation has been reported in several brain regions of cocaine-dependent subjects compared with controls, very little is known about whether there is altered connectivity of working memory pathways in cocaine dependence. This study addresses this issue by using functional magnetic resonance imaging-based stochastic dynamic causal modeling (DCM) analysis to study the effective connectivity of 19 cocaine-dependent subjects and 14 healthy controls while performing a working memory task. Stochastic DCM is an advanced method that has recently been implemented in SPM8 that can obtain improved estimates, relative to deterministic DCM, of hidden neuronal causes before convolution with the hemodynamic response. Thus, stochastic DCM may be less influenced by the confounding effects of variations in blood oxygen level-dependent response caused by disease or drugs. Based on the significant regional activation common to both groups and consistent with previous working memory activation studies, seven regions of interest were chosen as nodes for DCM analyses. Bayesian family level inference, Bayesian model selection analyses, and Bayesian model averaging (BMA) were conducted. BMA showed that the cocaine-dependent subjects had large differences compared with the control subjects in the strengths of prefrontal-striatal modulatory (B matrix) DCM parameters. These findings are consistent with altered cortical-striatal networks that may be related to reduced dopamine function in cocaine dependence. As far as we are aware, this is the first between-group DCM study using stochastic methodology. Copyright © 2012 Wiley Periodicals, Inc.

  7. Differentiation-Dependent Motility-Responses of Developing Neural Progenitors to Optogenetic Stimulation

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    Tímea Köhidi

    2017-12-01

    Full Text Available During neural tissue genesis, neural stem/progenitor cells are exposed to bioelectric stimuli well before synaptogenesis and neural circuit formation. Fluctuations in the electrochemical potential in the vicinity of developing cells influence the genesis, migration and maturation of neuronal precursors. The complexity of the in vivo environment and the coexistence of various progenitor populations hinder the understanding of the significance of ionic/bioelectric stimuli in the early phases of neuronal differentiation. Using optogenetic stimulation, we investigated the in vitro motility responses of radial glia-like neural stem/progenitor populations to ionic stimuli. Radial glia-like neural stem cells were isolated from CAGloxpStoploxpChR2(H134-eYFP transgenic mouse embryos. After transfection with Cre-recombinase, ChR2(channelrhodopsin-2-expressing and non-expressing cells were separated by eYFP fluorescence. Expression of light-gated ion channels were checked by patch clamp and fluorescence intensity assays. Neurogenesis by ChR2-expressing and non-expressing cells was induced by withdrawal of EGF from the medium. Cells in different (stem cell, migrating progenitor and maturing precursor stages of development were illuminated with laser light (λ = 488 nm; 1.3 mW/mm2; 300 ms in every 5 min for 12 h. The displacement of the cells was analyzed on images taken at the end of each light pulse. Results demonstrated that the migratory activity decreased with the advancement of neuronal differentiation regardless of stimulation. Light-sensitive cells, however, responded on a differentiation-dependent way. In non-differentiated ChR2-expressing stem cell populations, the motility did not change significantly in response to light-stimulation. The displacement activity of migrating progenitors was enhanced, while the motility of differentiating neuronal precursors was markedly reduced by illumination.

  8. Error-related functional connectivity of the thalamus in cocaine dependence

    Directory of Open Access Journals (Sweden)

    Sheng Zhang

    2014-01-01

    Full Text Available Error processing is a critical component of cognitive control, an executive function that has been widely implicated in substance misuse. In previous studies we showed that error related activations of the thalamus predicted relapse to drug use in cocaine addicted individuals (Luo et al., 2013. Here, we investigated whether the error-related functional connectivity of the thalamus is altered in cocaine dependent patients (PCD, n = 54 as compared to demographically matched healthy individuals (HC, n = 54. The results of a generalized psychophysiological interaction analysis showed negative thalamic connectivity with the ventral medial prefrontal cortex (vmPFC, in the area of perigenual and subgenual anterior cingulate cortex, in HC but not PCD (p < 0.05, corrected, two-sample t test. This difference in functional connectivity was not observed for task-residual signals, suggesting that it is specific to task-related processes during cognitive control. Further, the thalamic-vmPFC connectivity is positively correlated with the amount of cocaine use in the prior month for female but not for male PCD. These findings add to recent literature and provide additional evidence for circuit-level biomarkers of cocaine dependence.

  9. Distinct Neural Signatures Detected for ADHD Subtypes After Controlling for Micro-Movements in Resting State Functional Connectivity MRI Data

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    Damien eFair

    2013-02-01

    Full Text Available In recent years, there has been growing enthusiasm that functional MRI could achieve clinical utility for a broad range of neuropsychiatric disorders. However, several barriers remain. For example, the acquisition of large-scale datasets capable of clarifying the marked heterogeneity that exists in psychiatric illnesses will need to be realized. In addition, there continues to be a need for the development of image processing and analysis methods capable of separating signal from artifact. As a prototypical hyperkinetic disorder, and movement related artifact being a significant confound in functional imaging studies, ADHD offers a unique challenge. As part of the ADHD-200 Global Competition and this special edition of Frontiers, the ADHD-200 Consortium demonstrates the utility of an aggregate dataset pooled across five institutions in addressing these challenges. The work aimed to A examine the impact of emerging techniques for controlling for micro-movements, and B provide novel insights into the neural correlates of ADHD subtypes. Using SVM based MVPA we show that functional connectivity patterns in individuals are capable of differentiating the two most prominent ADHD subtypes. The application of graph-theory revealed that the Combined (ADHD-C and Inattentive (ADHD-I subtypes demonstrated some overlapping (particularly sensorimotor systems, but unique patterns of atypical connectivity. For ADHD-C, atypical connectivity was prominent in midline default network components, as well as insular cortex; in contrast, the ADHD-I group exhibited atypical patterns within the dlPFC regions and cerebellum. Systematic motion-related artifact was noted, and highlighted the need for stringent motion correction. Findings reported were robust to the specific motion correction strategy employed. These data suggest that rs-fcMRI data can be used to characterize individual patients with ADHD and to identify neural distinctions underlying the clinical

  10. [Progress in activity-dependent structural plasticity of neural circuits in cortex].

    Science.gov (United States)

    Rao, Xiao-Ping; Xu, Zhi-Xiang; Xu, Fu-Qiang

    2012-10-01

    Neural circuits of mammalian cerebral cortex have exhibited amazing abilities of structural and functional plasticity in development, learning and memory, neurological and psychiatric diseases. With the new imaging techniques and the application of molecular biology methods, observation neural circuits' structural dynamics within the cortex in vivo at the cellular and synaptic level was possible, so there were many great progresses in the field of the activity-dependent structural plasticity over the past decade. This paper reviewed some of the aspects of the experimental results, focused on the characteristics of dendritic structural plasticity in individual growth and development, rich environment, sensory deprivation, and pathological conditions, as well as learning and memory, especially the dynamics of dendritic spines on morphology and quantity; after that, we introduced axonal structural plasticity, the molecular and cellular mechanisms of structural plasticity, and proposed some future problems to be solved at last.

  11. Task-dependent neural and behavioral effects of verb argument structure features.

    Science.gov (United States)

    Malyutina, Svetlana; den Ouden, Dirk-Bart

    2017-05-01

    Understanding which verb argument structure (VAS) features (if any) are part of verbs' lexical entries and under which conditions they are accessed provides information on the nature of lexical representations and sentence construction. We investigated neural and behavioral effects of three understudied VAS characteristics (number of subcategorization options, number of thematic options and overall number of valency frames) in lexical decision and sentence well-formedness judgment in healthy adults. VAS effects showed strong dependency on processing conditions. As reflected by behavioral performance and neural recruitment patterns, increased VAS complexity in terms of subcategorization options and thematic options had a detrimental effect on sentence processing, but facilitated lexical access to single words, possibly by providing more lexico-semantic associations and access routes (facilitation through complexity). Effects of the number of valency frames are equivocal. We suggest that VAS effects may be mediated semantically rather than by a dedicated VAS module in verbs' representations. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. A time-delay neural network for solving time-dependent shortest path problem.

    Science.gov (United States)

    Huang, Wei; Yan, Chunwang; Wang, Jinsong; Wang, Wei

    2017-06-01

    This paper concerns the time-dependent shortest path problem, which is difficult to come up with global optimal solution by means of classical shortest path approaches such as Dijkstra, and pulse-coupled neural network (PCNN). In this study, we propose a time-delay neural network (TDNN) framework that comes with the globally optimal solution when solving the time-dependent shortest path problem. The underlying idea of TDNN comes from the following mechanism: the shortest path depends on the earliest auto-wave (from start node) that arrives at the destination node. In the design of TDNN, each node on a network is considered as a neuron, which comes in the form of two units: time-window unit and auto-wave unit. Time-window unit is used to generate auto-wave in each time window, while auto-wave unit is exploited here to update the state of auto-wave. Whether or not an auto-wave leaves a node (neuron) depends on the state of auto-wave. The evaluation of the performance of the proposed approach was carried out based on online public Cordeau instances and New York Road instances. The proposed TDNN was also compared with the quality of classical approaches such as Dijkstra and PCNN. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. Neural correlates of verbal creativity: Differences in resting-state functional connectivity associated with expertise in creative writing

    Directory of Open Access Journals (Sweden)

    Martin eLotze

    2014-07-01

    Full Text Available Neural characteristics of verbal creativity as assessed by word generation tasks have been recently identified, but differences in resting-state functional connectivity (rFC between experts and non-experts in creative writing have not been reported yet. Previous electroencephalography (EEG coherence measures during rest demonstrated a decreased cooperation between brain areas in association with creative thinking ability. Here, we used resting-state functional magnetic resonance imaging to compare 20 experts in creative writing and 23 age-matched non-experts with respect to rFC strengths within a brain network previously found to be associated with creative writing. Decreased rFC for experts was found between areas 44 of both hemispheres. Increased rFC for experts was observed between right hemispheric caudate and intraparietal sulcus. Correlation analysis of verbal creativity indices with rFC values in the expert group revealed predominantly negative associations, particularly of rFC between left area 44 and left temporal pole. Overall, our data support previous findings on reduced connectivity between interhemispheric areas and increased right-hemispheric connectivity during rest in highly verbally creative individuals.

  14. Neural correlates of verbal creativity: differences in resting-state functional connectivity associated with expertise in creative writing.

    Science.gov (United States)

    Lotze, Martin; Erhard, Katharina; Neumann, Nicola; Eickhoff, Simon B; Langner, Robert

    2014-01-01

    Neural characteristics of verbal creativity as assessed by word generation tasks have been recently identified, but differences in resting-state functional connectivity (rFC) between experts and non-experts in creative writing have not been reported yet. Previous electroencephalography (EEG) coherence measures during rest demonstrated a decreased cooperation between brain areas in association with creative thinking ability. Here, we used resting-state functional magnetic resonance imaging to compare 20 experts in creative writing and 23 age-matched non-experts with respect to rFC strengths within a brain network previously found to be associated with creative writing. Decreased rFC for experts was found between areas 44 of both hemispheres. Increased rFC for experts was observed between right hemispheric caudate and intraparietal sulcus. Correlation analysis of verbal creativity indices (VCIs) with rFC values in the expert group revealed predominantly negative associations, particularly of rFC between left area 44 and left temporal pole. Overall, our data support previous findings of reduced connectivity between interhemispheric areas and increased right-hemispheric connectivity during rest in highly verbally creative individuals.

  15. When the Sense of Smell Meets Emotion: Anxiety-State-Dependent Olfactory Processing and Neural Circuitry Adaptation

    Science.gov (United States)

    Novak, Lucas R.; Gitelman, Darren R.

    2013-01-01

    Phylogenetically the most ancient sense, olfaction is characterized by a unique intimacy with the emotion system. However, mechanisms underlying olfaction–emotion interaction remain unclear, especially in an ever-changing environment and dynamic internal milieu. Perturbing the internal state with anxiety induction in human subjects, we interrogated emotion-state-dependent olfactory processing in a functional magnetic resonance imaging (fMRI) study. Following anxiety induction, initially neutral odors become unpleasant and take longer to detect, accompanied by augmented response to these odors in the olfactory (anterior piriform and orbitofrontal) cortices and emotion-relevant pregenual anterior cingulate cortex. In parallel, the olfactory sensory relay adapts with increased anxiety, incorporating amygdala as an integral step via strengthened (afferent or efferent) connections between amygdala and all levels of the olfactory cortical hierarchy. This anxiety-state-dependent neural circuitry thus enables cumulative infusion of limbic affective information throughout the olfactory sensory progression, thereby driving affectively charged olfactory perception. These findings could constitute an olfactory etiology model of emotional disorders, as exaggerated emotion–olfaction interaction in negative mood states turns innocuous odors aversive, fueling anxiety and depression with rising ambient sensory stress. PMID:24068799

  16. Alterations in brain structure and functional connectivity in prescription opioid-dependent patients

    Science.gov (United States)

    Upadhyay, Jaymin; Maleki, Nasim; Potter, Jennifer; Elman, Igor; Rudrauf, David; Knudsen, Jaime; Wallin, Diana; Pendse, Gautam; McDonald, Leah; Griffin, Margaret; Anderson, Julie; Nutile, Lauren; Renshaw, Perry; Weiss, Roger; Becerra, Lino

    2010-01-01

    A dramatic increase in the use and dependence of prescription opioids has occurred within the last 10 years. The consequences of long-term prescription opioid use and dependence on the brain are largely unknown, and any speculation is inferred from heroin and methadone studies. Thus, no data have directly demonstrated the effects of prescription opioid use on brain structure and function in humans. To pursue this issue, we used structural magnetic resonance imaging, diffusion tensor imaging and resting-state functional magnetic resonance imaging in a highly enriched group of prescription opioid-dependent patients [(n =  10); from a larger study on prescription opioid dependent patients (n =  133)] and matched healthy individuals (n =  10) to characterize possible brain alterations that may be caused by long-term prescription opioid use. Criteria for patient selection included: (i) no dependence on alcohol or other drugs; (ii) no comorbid psychiatric or neurological disease; and (iii) no medical conditions, including pain. In comparison to control subjects, individuals with opioid dependence displayed bilateral volumetric loss in the amygdala. Prescription opioid-dependent subjects had significantly decreased anisotropy in axonal pathways specific to the amygdala (i.e. stria terminalis, ventral amygdalofugal pathway and uncinate fasciculus) as well as the internal and external capsules. In the patient group, significant decreases in functional connectivity were observed for seed regions that included the anterior insula, nucleus accumbens and amygdala subdivisions. Correlation analyses revealed that longer duration of prescription opioid exposure was associated with greater changes in functional connectivity. Finally, changes in amygdala functional connectivity were observed to have a significant dependence on amygdala volume and white matter anisotropy of efferent and afferent pathways of the amygdala. These findings suggest that prescription

  17. How Do Efficient Coding Strategies Depend on Origins of Noise in Neural Circuits?

    Science.gov (United States)

    Brinkman, Braden A W; Weber, Alison I; Rieke, Fred; Shea-Brown, Eric

    2016-10-01

    Neural circuits reliably encode and transmit signals despite the presence of noise at multiple stages of processing. The efficient coding hypothesis, a guiding principle in computational neuroscience, suggests that a neuron or population of neurons allocates its limited range of responses as efficiently as possible to best encode inputs while mitigating the effects of noise. Previous work on this question relies on specific assumptions about where noise enters a circuit, limiting the generality of the resulting conclusions. Here we systematically investigate how noise introduced at different stages of neural processing impacts optimal coding strategies. Using simulations and a flexible analytical approach, we show how these strategies depend on the strength of each noise source, revealing under what conditions the different noise sources have competing or complementary effects. We draw two primary conclusions: (1) differences in encoding strategies between sensory systems-or even adaptational changes in encoding properties within a given system-may be produced by changes in the structure or location of neural noise, and (2) characterization of both circuit nonlinearities as well as noise are necessary to evaluate whether a circuit is performing efficiently.

  18. Could LC-NE-Dependent Adjustment of Neural Gain Drive Functional Brain Network Reorganization?

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    Carole Guedj

    2017-01-01

    Full Text Available The locus coeruleus-norepinephrine (LC-NE system is thought to act at synaptic, cellular, microcircuit, and network levels to facilitate cognitive functions through at least two different processes, not mutually exclusive. Accordingly, as a reset signal, the LC-NE system could trigger brain network reorganizations in response to salient information in the environment and/or adjust the neural gain within its target regions to optimize behavioral responses. Here, we provide evidence of the co-occurrence of these two mechanisms at the whole-brain level, in resting-state conditions following a pharmacological stimulation of the LC-NE system. We propose that these two mechanisms are interdependent such that the LC-NE-dependent adjustment of the neural gain inferred from the clustering coefficient could drive functional brain network reorganizations through coherence in the gamma rhythm. Via the temporal dynamic of gamma-range band-limited power, the release of NE could adjust the neural gain, promoting interactions only within the neuronal populations whose amplitude envelopes are correlated, thus making it possible to reorganize neuronal ensembles, functional networks, and ultimately, behavioral responses. Thus, our proposal offers a unified framework integrating the putative influence of the LC-NE system on both local- and long-range adjustments of brain dynamics underlying behavioral flexibility.

  19. How Do Efficient Coding Strategies Depend on Origins of Noise in Neural Circuits?

    Directory of Open Access Journals (Sweden)

    Braden A W Brinkman

    2016-10-01

    Full Text Available Neural circuits reliably encode and transmit signals despite the presence of noise at multiple stages of processing. The efficient coding hypothesis, a guiding principle in computational neuroscience, suggests that a neuron or population of neurons allocates its limited range of responses as efficiently as possible to best encode inputs while mitigating the effects of noise. Previous work on this question relies on specific assumptions about where noise enters a circuit, limiting the generality of the resulting conclusions. Here we systematically investigate how noise introduced at different stages of neural processing impacts optimal coding strategies. Using simulations and a flexible analytical approach, we show how these strategies depend on the strength of each noise source, revealing under what conditions the different noise sources have competing or complementary effects. We draw two primary conclusions: (1 differences in encoding strategies between sensory systems-or even adaptational changes in encoding properties within a given system-may be produced by changes in the structure or location of neural noise, and (2 characterization of both circuit nonlinearities as well as noise are necessary to evaluate whether a circuit is performing efficiently.

  20. Calcium dependent plasticity applied to repetitive transcranial magnetic stimulation with a neural field model.

    Science.gov (United States)

    Wilson, M T; Fung, P K; Robinson, P A; Shemmell, J; Reynolds, J N J

    2016-08-01

    The calcium dependent plasticity (CaDP) approach to the modeling of synaptic weight change is applied using a neural field approach to realistic repetitive transcranial magnetic stimulation (rTMS) protocols. A spatially-symmetric nonlinear neural field model consisting of populations of excitatory and inhibitory neurons is used. The plasticity between excitatory cell populations is then evaluated using a CaDP approach that incorporates metaplasticity. The direction and size of the plasticity (potentiation or depression) depends on both the amplitude of stimulation and duration of the protocol. The breaks in the inhibitory theta-burst stimulation protocol are crucial to ensuring that the stimulation bursts are potentiating in nature. Tuning the parameters of a spike-timing dependent plasticity (STDP) window with a Monte Carlo approach to maximize agreement between STDP predictions and the CaDP results reproduces a realistically-shaped window with two regions of depression in agreement with the existing literature. Developing understanding of how TMS interacts with cells at a network level may be important for future investigation.

  1. Impact of acoustic coordinated reset neuromodulation on effective connectivity in a neural network of phantom sound.

    Science.gov (United States)

    Silchenko, Alexander N; Adamchic, Ilya; Hauptmann, Christian; Tass, Peter A

    2013-08-15

    Chronic subjective tinnitus is an auditory phantom phenomenon characterized by abnormal neuronal synchrony in the central auditory system. As recently shown in a proof of concept clinical trial, acoustic coordinated reset (CR) neuromodulation causes a significant relief of tinnitus symptoms combined with a significant decrease of pathological oscillatory activity in a network comprising auditory and non-auditory brain areas. The objective of the present study was to analyze whether CR therapy caused an alteration of the effective connectivity in a tinnitus related network of localized EEG brain sources. To determine which connections matter, in a first step, we considered a larger network of brain sources previously associated with tinnitus. To that network we applied a data-driven approach, combining empirical mode decomposition and partial directed coherence analysis, in patients with bilateral tinnitus before and after 12 weeks of CR therapy as well as in healthy controls. To increase the signal-to-noise ratio, we focused on the good responders, classified by a reliable-change-index (RCI). Prior to CR therapy and compared to the healthy controls, the good responders showed a significantly increased connectivity between the left primary cortex auditory cortex and the posterior cingulate cortex in the gamma and delta bands together with a significantly decreased effective connectivity between the right primary auditory cortex and the dorsolateral prefrontal cortex in the alpha band. Intriguingly, after 12 weeks of CR therapy most of the pathological interactions were gone, so that the connectivity patterns of good responders and healthy controls became statistically indistinguishable. In addition, we used dynamic causal modeling (DCM) to examine the types of interactions which were altered by CR therapy. Our DCM results show that CR therapy specifically counteracted the imbalance of excitation and inhibition. CR significantly weakened the excitatory connection

  2. Implications of the Dependence of Neuronal Activity on Neural Network States for the Design of Brain-Machine Interfaces.

    Science.gov (United States)

    Panzeri, Stefano; Safaai, Houman; De Feo, Vito; Vato, Alessandro

    2016-01-01

    Brain-machine interfaces (BMIs) can improve the quality of life of patients with sensory and motor disabilities by both decoding motor intentions expressed by neural activity, and by encoding artificially sensed information into patterns of neural activity elicited by causal interventions on the neural tissue. Yet, current BMIs can exchange relatively small amounts of information with the brain. This problem has proved difficult to overcome by simply increasing the number of recording or stimulating electrodes, because trial-to-trial variability of neural activity partly arises from intrinsic factors (collectively known as the network state) that include ongoing spontaneous activity and neuromodulation, and so is shared among neurons. Here we review recent progress in characterizing the state dependence of neural responses, and in particular of how neural responses depend on endogenous slow fluctuations of network excitability. We then elaborate on how this knowledge may be used to increase the amount of information that BMIs exchange with brain. Knowledge of network state can be used to fine-tune the stimulation pattern that should reliably elicit a target neural response used to encode information in the brain, and to discount part of the trial-by-trial variability of neural responses, so that they can be decoded more accurately.

  3. Implications of the dependence of neuronal activity on neural network states for the design of brain-machine interfaces

    Directory of Open Access Journals (Sweden)

    Stefano ePanzeri

    2016-04-01

    Full Text Available Brain-machine interfaces (BMIs can improve the quality of life of patients with sensory and motor disabilities by both decoding motor intentions expressed by neural activity, and by encoding artificially sensed information into patterns of neural activity elicited by causal interventions on the neural tissue. Yet, current BMIs can exchange relatively small amounts of information with the brain. This problem has proved difficult to overcome by simply increasing the number of recording or stimulating electrodes, because trial-to-trial variability of neural activity partly arises from intrinsic factors (collectively known as the network state that include ongoing spontaneous activity and neuromodulation, and so is shared among neurons. Here we review recent progress in characterizing the state dependence of neural responses, and in particular of how neural responses depend on endogenous slow fluctuations of network excitability. We then elaborate on how this knowledge may be used to increase the amount of information that BMIs exchange with brains. Knowledge of network state can be used to fine-tune the stimulation pattern that should reliably elicit a target neural response used to encode information in the brain, and to discount part of the trial-by-trial variability of neural responses, so that they can be decoded more accurately.

  4. Connecting Neurons to a Mobile Robot: An In Vitro Bidirectional Neural Interface

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    A. Novellino

    2007-01-01

    Full Text Available One of the key properties of intelligent behaviors is the capability to learn and adapt to changing environmental conditions. These features are the result of the continuous and intense interaction of the brain with the external world, mediated by the body. For this reason x201C;embodiment” represents an innovative and very suitable experimental paradigm when studying the neural processes underlying learning new behaviors and adapting to unpredicted situations. To this purpose, we developed a novel bidirectional neural interface. We interconnected in vitro neurons, extracted from rat embryos and plated on a microelectrode array (MEA, to external devices, thus allowing real-time closed-loop interaction. The novelty of this experimental approach entails the necessity to explore different computational schemes and experimental hypotheses. In this paper, we present an open, scalable architecture, which allows fast prototyping of different modules and where coding and decoding schemes and different experimental configurations can be tested. This hybrid system can be used for studying the computational properties and information coding in biological neuronal networks with far-reaching implications for the future development of advanced neuroprostheses.

  5. State-dependent modulation of functional connectivity in early blind individuals.

    Science.gov (United States)

    Pelland, Maxime; Orban, Pierre; Dansereau, Christian; Lepore, Franco; Bellec, Pierre; Collignon, Olivier

    2017-02-15

    Resting-state functional connectivity (RSFC) studies have provided strong evidences that visual deprivation influences the brain's functional architecture. In particular, reduced RSFC coupling between occipital (visual) and temporal (auditory) regions has been reliably observed in early blind individuals (EB) at rest. In contrast, task-dependent activation studies have repeatedly demonstrated enhanced co-activation and connectivity of occipital and temporal regions during auditory processing in EB. To investigate this apparent discrepancy, the functional coupling between temporal and occipital networks at rest was directly compared to that of an auditory task in both EB and sighted controls (SC). Functional brain clusters shared across groups and cognitive states (rest and auditory task) were defined. In EBs, we observed higher occipito-temporal correlations in activity during the task than at rest. The reverse pattern was observed in SC. We also observed higher temporal variability of occipito-temporal RSFC in EB suggesting that occipital regions in this population may play the role of a multiple demand system. Our study reveals how the connectivity profile of sighted and early blind people is differentially influenced by their cognitive state, bridging the gap between previous task-dependent and RSFC studies. Our results also highlight how inferring group-differences in functional brain architecture solely based on resting-state acquisition has to be considered with caution. Copyright © 2016 Elsevier Inc. All rights reserved.

  6. A stimulus-dependent spike threshold is an optimal neural coder

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    Douglas L Jones

    2015-06-01

    Full Text Available A neural code based on sequences of spikes can consume a significant portion of the brain’s energy budget. Thus, energy considerations would dictate that spiking activity be kept as low as possible. However, a high spike-rate improves the coding and representation of signals in spike trains, particularly in sensory systems. These are competing demands, and selective pressure has presumably worked to optimize coding by apportioning a minimum number of spikes so as to maximize coding fidelity. The mechanisms by which a neuron generates spikes while maintaining a fidelity criterion are not known. Here, we show that a signal-dependent neural threshold, similar to a dynamic or adapting threshold, optimizes the trade-off between spike generation (encoding and fidelity (decoding. The threshold mimics a post-synaptic membrane (a low-pass filter and serves as an internal decoder. Further, it sets the average firing rate (the energy constraint. The decoding process provides an internal copy of the coding error to the spike-generator which emits a spike when the error equals or exceeds a spike threshold. When optimized, the trade-off leads to a deterministic spike firing-rule that generates optimally timed spikes so as to maximize fidelity. The optimal coder is derived in closed-form in the limit of high spike-rates, when the signal can be approximated as a piece-wise constant signal. The predicted spike-times are close to those obtained experimentally in the primary electrosensory afferent neurons of weakly electric fish (Apteronotus leptorhynchus and pyramidal neurons from the somatosensory cortex of the rat. We suggest that KCNQ/Kv7 channels (underlying the M-current are good candidates for the decoder. They are widely coupled to metabolic processes and do not inactivate. We conclude that the neural threshold is optimized to generate an energy-efficient and high-fidelity neural code.

  7. Theory of Mind and the Whole Brain Functional Connectivity: Behavioral and Neural Evidences with the Amsterdam Resting State Questionnaire.

    Science.gov (United States)

    Marchetti, Antonella; Baglio, Francesca; Costantini, Isa; Dipasquale, Ottavia; Savazzi, Federica; Nemni, Raffaello; Sangiuliano Intra, Francesca; Tagliabue, Semira; Valle, Annalisa; Massaro, Davide; Castelli, Ilaria

    2015-01-01

    A topic of common interest to psychologists and philosophers is the spontaneous flow of thoughts when the individual is awake but not involved in cognitive demands. This argument, classically referred to as the "stream of consciousness" of James, is now known in the psychological literature as "Mind-Wandering." Although of great interest, this construct has been scarcely investigated so far. Diaz et al. (2013) created the Amsterdam Resting State Questionnaire (ARSQ), composed of 27 items, distributed in seven factors: discontinuity of mind, theory of mind (ToM), self, planning, sleepiness, comfort, and somatic awareness. The present study aims at: testing psychometric properties of the ARSQ in a sample of 670 Italian subjects; exploring the neural correlates of a subsample of participants (N = 28) divided into two groups on the basis of the scores obtained in the ToM factor. Results show a satisfactory reliability of the original factional structure in the Italian sample. In the subjects with a high mean in the ToM factor compared to low mean subjects, functional MRI revealed: a network (48 nodes) with higher functional connectivity (FC) with a dominance of the left hemisphere; an increased within-lobe FC in frontal and insular lobes. In both neural and behavioral terms, our results support the idea that the mind, which does not rest even when explicitly asked to do so, has various and interesting mentalistic-like contents.

  8. Delay-distribution-dependent H∞ state estimation for delayed neural networks with (x,v)-dependent noises and fading channels.

    Science.gov (United States)

    Sheng, Li; Wang, Zidong; Tian, Engang; Alsaadi, Fuad E

    2016-12-01

    This paper deals with the H∞ state estimation problem for a class of discrete-time neural networks with stochastic delays subject to state- and disturbance-dependent noises (also called (x,v)-dependent noises) and fading channels. The time-varying stochastic delay takes values on certain intervals with known probability distributions. The system measurement is transmitted through fading channels described by the Rice fading model. The aim of the addressed problem is to design a state estimator such that the estimation performance is guaranteed in the mean-square sense against admissible stochastic time-delays, stochastic noises as well as stochastic fading signals. By employing the stochastic analysis approach combined with the Kronecker product, several delay-distribution-dependent conditions are derived to ensure that the error dynamics of the neuron states is stochastically stable with prescribed H∞ performance. Finally, a numerical example is provided to illustrate the effectiveness of the obtained results. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. Neural signature of coma revealed by posteromedial cortex connection density analysis

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    Briguita Malagurski

    2017-01-01

    A complex pattern of decreased and increased connections was observed, suggesting a network imbalance between internal/external processing systems, within PMC during coma. The number of PMC voxels with hypo-CD positive correlation showed a significant negative association with the CRS-R score, notwithstanding aetiology. Traumatic injury specifically appeared to be associated with a greater prevalence of hyper-connected (negative correlation voxels, which was inversely associated with patient neurological outcome. A logistic regression model using the number of hypo-CD positive and hyper-CD negative correlations, accurately permitted patient's outcome prediction (AUC = 0.906, 95%IC = 0.795–1. These points might reflect adaptive plasticity mechanism and pave the way for innovative prognosis and therapeutics methods.

  10. Neural connectivity moderates the association between sleep and impulsivity in adolescents

    OpenAIRE

    Sarah M. Tashjian; Diane Goldenberg; Adriana Galván

    2017-01-01

    Adolescence is characterized by chronic insufficient sleep and extensive brain development, but the relation between adolescent sleep and brain function remains unclear. We report the first functional magnetic resonance imaging study to investigate functional connectivity as a moderator between sleep and impulsivity, a problematic behavior during this developmental period. Naturalistic differences in sleep have not yet been explored as treatable contributors to adolescent impulsivity. Althoug...

  11. Resilience and cross-network connectivity: A neural model for post-trauma survival.

    Science.gov (United States)

    Brunetti, Marcella; Marzetti, Laura; Sepede, Gianna; Zappasodi, Filippo; Pizzella, Vittorio; Sarchione, Fabiola; Vellante, Federica; Martinotti, Giovanni; Di Giannantonio, Massimo

    2017-07-03

    Literature on the neurobiological bases of Post-Traumatic Stress Disorder (PTSD) considers medial Prefrontal cortex (mPFC), a core region of the Default Mode Network (DMN), as a region involved in response regulation to stressors. Disrupted functioning of the DMN has been recognized at the basis of the pathophysiology of a number of mental disorders. Furthermore, in the evaluation of the protective factors to trauma consequence, an important role has been assigned to resilience. Our aim was to investigate the specific relation of resilience and PTSD symptoms severity with resting state brain connectivity in a traumatized population using magnetoencephalography (MEG), a non-invasive imaging technique with high temporal resolution and documented advantages in clinical applications. Nineteen Trauma Exposed non-PTSD (TENP) and 19 PTSD patients participated to a resting state MEG session. MEG functional connectivity of mPFC seed to the whole brain was calculated. Correlation between mPFC functional connectivity and Clinician Administered PTSD Scale (CAPS) or Connor-Davidson Resilience Scale (CD-RISC) total score was also assessed. In the whole group, it has been evidenced that the higher was the resilience, the lower was the cross-network connectivity between DMN and Salience Network (SN) nodes. Contrarily, in the TENP group, the negative correlation between resilience and DMN-SN cross-interaction disappeared, suggesting a protective role of resilience for brain functioning. Regarding our findings as a continuum between healthy and pathological after trauma outcomes, we could suggest a link between resilience and the good dialogue between the networks needed to face a traumatic event and its long-term consequence on individuals' lives. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. Determination of the Most Important Soil Parameters Affecting the Availability of Phosphorus in Sistan Plain, Using Connection Weight Method in Neural Networks

    Directory of Open Access Journals (Sweden)

    H. Mir

    2016-09-01

    Full Text Available Introduction: Phosphorus is important as an essential element in the production of agricultural products. On the other hand, its ability to induce essential micronutrient deficiency and its negative effects on the environment, have attracted more attention to this element. The knowledge of phosphorus availability conditions in the soil and consequently the accurate management of fertilizer consumption has a key role in the environmental protection. The degree of phosphorus absorption in the soil depends on the environmental factors, soil characteristics and compositions, and phosphorus fertilizer which have been used. The amount of available phosphorus in the soil has relationship with some of the physical and chemical properties of the soil. Since, the soil characteristics are important factors in the reaction of phosphorus in the soil, the present study aimed to investigate and determine the most important soil characteristics affecting the availability of phosphorus using regression and artificial neural network techniques, in the soils of Sistan plain. Materials and Methods: Soil sampling was done in 1.5×1.5 km intervals, from 0-30 cm depth, and 200 soil samples were taken. The amounts of available phosphorus and the soil properties including the percentages of clay , organic matter, calcium carbonate and the amount of pH were measured. Then, stepwise multivariate linear regression analysis was performed to determine linear relation between available phosphorus and the soil properties. In order to model and validate the regression model, respectively 80 and 20% of data were selected and entered into SPSS software. To train the neural network, multilayer perceptron (MLP network was used by MATLAB 7.6 package. In this type of network, 70% of data is selected for training, 15% for validation and 15% for testing the model. Levenberg-Marquardt algorithm and hyperbolic tangent (as a transfer function were used to train the network. The numbers of

  13. Reduced Neural Recruitment for Bayesian Adjustment of Inhibitory Control in Methamphetamine Dependence.

    Science.gov (United States)

    Harlé, Katia M; Zhang, Shunan; Ma, Ning; Yu, Angela J; Paulus, Martin P

    2016-09-01

    Delineating the processes that contribute to the progression and maintenance of substance dependence is critical to understanding and preventing addiction. Several previous studies have shown inhibitory control deficits in individuals with stimulant use disorder. We used a Bayesian computational approach to examine potential neural deficiencies in the dynamic predictive processing underlying inhibitory function among recently abstinent methamphetamine-dependent individuals (MDIs), a population at high risk of relapse. Sixty-two MDIs were recruited from a 28-day inpatient treatment program at the San Diego Veterans Affairs Medical Center and compared with 34 healthy control subjects. They completed a stop-signal task during functional magnetic resonance imaging. A Bayesian ideal observer model was used to predict individuals' trial-to-trial probabilistic expectations of inhibitory response, P(stop), to identify group differences specific to Bayesian expectation and prediction error computation. Relative to control subjects, MDIs were more likely to make stop errors on difficult trials and had attenuated slowing following stop errors. MDIs further exhibited reduced sensitivity as measured by the neural tracking of a Bayesian measure of surprise (unsigned prediction error), which was evident across all trials in the left posterior caudate and orbitofrontal cortex (Brodmann area 11), and selectively on stop error trials in the right thalamus and inferior parietal lobule. MDIs are less sensitive to surprising task events, both across trials and upon making commission errors, which may help explain why these individuals may not engage in switching strategy when the environment changes, leading to adverse consequences.

  14. Static stretch affects neural stem cell differentiation in an extracellular matrix-dependent manner.

    Science.gov (United States)

    Arulmoli, Janahan; Pathak, Medha M; McDonnell, Lisa P; Nourse, Jamison L; Tombola, Francesco; Earthman, James C; Flanagan, Lisa A

    2015-02-17

    Neural stem and progenitor cell (NSPC) fate is strongly influenced by mechanotransduction as modulation of substrate stiffness affects lineage choice. Other types of mechanical stimuli, such as stretch (tensile strain), occur during CNS development and trauma, but their consequences for NSPC differentiation have not been reported. We delivered a 10% static equibiaxial stretch to NSPCs and examined effects on differentiation. We found static stretch specifically impacts NSPC differentiation into oligodendrocytes, but not neurons or astrocytes, and this effect is dependent on particular extracellular matrix (ECM)-integrin linkages. Generation of oligodendrocytes from NSPCs was reduced on laminin, an outcome likely mediated by the α6 laminin-binding integrin, whereas similar effects were not observed for NSPCs on fibronectin. Our data demonstrate a direct role for tensile strain in dictating the lineage choice of NSPCs and indicate the dependence of this phenomenon on specific substrate materials, which should be taken into account for the design of biomaterials for NSPC transplantation.

  15. New Delay-Dependent Exponential Stability Criteria for Neural Networks with Mixed Time-Varying Delays

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    Wu Wen

    2015-01-01

    Full Text Available This study is concerned with the problem of new delay-dependent exponential stability criteria for neural networks (NNs with mixed time-varying delays via introducing a novel integral inequality approach. Specifically, first, by taking fully the relationship between the terms in the Leibniz-Newton formula into account, several improved delay-dependent exponential stability criteria are obtained in terms of linear matrix inequalities (LMIs. Second, together with some effective mathematical techniques and a convex optimization approach, less conservative conditions are derived by constructing an appropriate Lyapunov-Krasovskii functional (LKF. Third, the proposed methods include the least numbers of decision variables while keeping the validity of the obtained results. Finally, three numerical examples with simulations are presented to illustrate the validity and advantages of the theoretical results.

  16. Time-dependent prediction degredation assessment of neural-networks-based TEC forecasting models

    Directory of Open Access Journals (Sweden)

    Th. D. Xenos

    2003-01-01

    Full Text Available An estimation of the difference in TEC prediction accuracy achieved when the prediction varies from 1 h to 7 days in advance is described using classical neural networks. Hourly-daily Faraday-rotation derived TEC measurements from Florence are used. It is shown that the prediction accuracy for the examined dataset, though degrading when time span increases, is always high. In fact, when a relative prediction error margin of ± 10% is considered, the population percentage included therein is almost always well above the 55%. It is found that the results are highly dependent on season and the dataset wealth, whereas they highly depend on the foF2 - TEC variability difference and on hysteresis-like effect between these two ionospheric characteristics.

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

    Science.gov (United States)

    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.

  18. L2-Proficiency-Dependent Laterality Shift in Structural Connectivity of Brain Language Pathways.

    Science.gov (United States)

    Xiang, Huadong; van Leeuwen, Tessa Marije; Dediu, Dan; Roberts, Leah; Norris, David G; Hagoort, Peter

    2015-08-01

    Diffusion tensor imaging (DTI) and a longitudinal language learning approach were applied to investigate the relationship between the achieved second language (L2) proficiency during L2 learning and the reorganization of structural connectivity between core language areas. Language proficiency tests and DTI scans were obtained from German students before and after they completed an intensive 6-week course of the Dutch language. In the initial learning stage, with increasing L2 proficiency, the hemispheric dominance of the Brodmann area (BA) 6-temporal pathway (mainly along the arcuate fasciculus) shifted from the left to the right hemisphere. With further increased proficiency, however, lateralization dominance was again found in the left BA6-temporal pathway. This result is consistent with reports in the literature that imply a stronger involvement of the right hemisphere in L2 processing especially for less proficient L2 speakers. This is the first time that an L2 proficiency-dependent laterality shift in the structural connectivity of language pathways during L2 acquisition has been observed to shift from left to right and back to left hemisphere dominance with increasing L2 proficiency. The authors additionally find that changes in fractional anisotropy values after the course are related to the time elapsed between the two scans. The results suggest that structural connectivity in (at least part of) the perisylvian language network may be subject to fast dynamic changes following language learning.

  19. Control of species-dependent cortico-motoneuronal connections underlying manual dexterity.

    Science.gov (United States)

    Gu, Zirong; Kalambogias, John; Yoshioka, Shin; Han, Wenqi; Li, Zhuo; Kawasawa, Yuka Imamura; Pochareddy, Sirisha; Li, Zhen; Liu, Fuchen; Xu, Xuming; Wijeratne, H. R. Sagara; Ueno, Masaki; Blatz, Emily; Salomone, Joseph; Kumanogoh, Atsushi; Rasin, Mladen-Roko; Gebelein, Brian; Weirauch, Matthew T; Sestan, Nenad; Martin, John H; Yoshida, Yutaka

    2017-07-28

    Superior manual dexterity in higher primates emerged together with the appearance of cortico-motoneuronal (CM) connections during the evolution of the mammalian corticospinal (CS) system. Previously thought to be specific to higher primates, we identified transient CM connections in early postnatal mice, which are eventually eliminated by Sema6D-PlexA1 signaling. PlexA1 mutant mice maintain CM connections into adulthood and exhibit superior manual dexterity as compared with that of controls. Last, differing PlexA1 expression in layer 5 of the motor cortex, which is strong in wild-type mice but weak in humans, may be explained by FEZF2-mediated cis-regulatory elements that are found only in higher primates. Thus, species-dependent regulation of PlexA1 expression may have been crucial in the evolution of mammalian CS systems that improved fine motor control in higher primates. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

  20. A neural measure of behavioral engagement: Task-residual low frequency blood oxygenation level dependent activity in the precuneus

    OpenAIRE

    Zhang, Sheng; Li, Chiang-shan Ray

    2009-01-01

    Brain imaging has provided a useful tool to examine the neural processes underlying human cognition. A critical question is whether and how task engagement influences the observed regional brain activations. Here we highlighted this issue and derived a neural measure of task engagement from the task-residual low frequency blood oxygenation level dependent (BOLD) activity in the precuneus. Using independent component analysis, we identified brain regions in the default circuit – including the ...

  1. The Combined Effect of Connectivity and Dependency Links on Percolation of Networks

    Science.gov (United States)

    Bashan, Amir; Havlin, Shlomo

    2011-11-01

    Percolation theory is extensively studied in statistical physics and mathematics with applications in diverse fields. However, the research is focused on systems with only one type of links, connectivity links. We review a recently developed mathematical framework for analyzing percolation properties of realistic scenarios of networks having links of two types, connectivity and dependency links. This formalism was applied to study Erdős-Rényi (ER) networks that include also dependency links. For an ER network with average degree bar{k} that is composed of dependency clusters of size s, the fraction of nodes that belong to the giant component, P ∞, is given by P_{infty}=p^{s-1}[1-exp{(-bar{k}pP_{infty})} ]s where 1- p is the initial fraction of randomly removed nodes. Here, we apply the formalism to the study of random-regular (RR) networks and find a formula for the size of the giant component in the percolation process: P ∞= p s-1(1- r k ) s where r is the solution of r= p s ( r k-1-1)(1- r k )+1, and k is the degree of the nodes. These general results coincide, for s=1, with the known equations for percolation in ER and RR networks respectively without dependency links. In contrast to s=1, where the percolation transition is second order, for s>1 it is of first order. Comparing the percolation behavior of ER and RR networks we find a remarkable difference regarding their resilience. We show, analytically and numerically, that in ER networks with low connectivity degree or large dependency clusters, removal of even a finite number (zero fraction) of the infinite network nodes will trigger a cascade of failures that fragments the whole network. Specifically, for any given s there exists a critical degree value, bar{k}_{min}, such that an ER network with bar{k}≤ bar{k}_{min} is unstable and collapse when removing even a single node. This result is in contrast to RR networks where such cascades and full fragmentation can be triggered only by removal of a

  2. Attenuated Neural Processing of Risk in Young Adults at Risk for Stimulant Dependence.

    Directory of Open Access Journals (Sweden)

    Martina Reske

    Full Text Available Approximately 10% of young adults report non-medical use of stimulants (cocaine, amphetamine, methylphenidate, which puts them at risk for the development of dependence. This fMRI study investigates whether subjects at early stages of stimulant use show altered decision making processing.158 occasional stimulants users (OSU and 50 comparison subjects (CS performed a "risky gains" decision making task during which they could select safe options (cash in 20 cents or gamble them for double or nothing in two consecutive gambles (win or lose 40 or 80 cents, "risky decisions". The primary analysis focused on risky versus safe decisions. Three secondary analyses were conducted: First, a robust regression examined the effect of lifetime exposure to stimulants and marijuana; second, subgroups of OSU with >1000 (n = 42, or <50 lifetime marijuana uses (n = 32, were compared to CS with <50 lifetime uses (n = 46 to examine potential marijuana effects; third, brain activation associated with behavioral adjustment following monetary losses was probed.There were no behavioral differences between groups. OSU showed attenuated activation across risky and safe decisions in prefrontal cortex, insula, and dorsal striatum, exhibited lower anterior cingulate cortex (ACC and dorsal striatum activation for risky decisions and greater inferior frontal gyrus activation for safe decisions. Those OSU with relatively more stimulant use showed greater dorsal ACC and posterior insula attenuation. In comparison, greater lifetime marijuana use was associated with less neural differentiation between risky and safe decisions. OSU who chose more safe responses after losses exhibited similarities with CS relative to those preferring risky options.Individuals at risk for the development of stimulant use disorders presented less differentiated neural processing of risky and safe options. Specifically, OSU show attenuated brain response in regions critical for performance monitoring

  3. Dynamic emotional and neural responses to music depend on performance expression and listener experience.

    Science.gov (United States)

    Chapin, Heather; Jantzen, Kelly; Kelso, J A Scott; Steinberg, Fred; Large, Edward

    2010-12-16

    Apart from its natural relevance to cognition, music provides a window into the intimate relationships between production, perception, experience, and emotion. Here, emotional responses and neural activity were observed as they evolved together with stimulus parameters over several minutes. Participants listened to a skilled music performance that included the natural fluctuations in timing and sound intensity that musicians use to evoke emotional responses. A mechanical performance of the same piece served as a control. Before and after fMRI scanning, participants reported real-time emotional responses on a 2-dimensional rating scale (arousal and valence) as they listened to each performance. During fMRI scanning, participants listened without reporting emotional responses. Limbic and paralimbic brain areas responded to the expressive dynamics of human music performance, and both emotion and reward related activations during music listening were dependent upon musical training. Moreover, dynamic changes in timing predicted ratings of emotional arousal, as well as real-time changes in neural activity. BOLD signal changes correlated with expressive timing fluctuations in cortical and subcortical motor areas consistent with pulse perception, and in a network consistent with the human mirror neuron system. These findings show that expressive music performance evokes emotion and reward related neural activations, and that music's affective impact on the brains of listeners is altered by musical training. Our observations are consistent with the idea that music performance evokes an emotional response through a form of empathy that is based, at least in part, on the perception of movement and on violations of pulse-based temporal expectancies.

  4. Dynamic emotional and neural responses to music depend on performance expression and listener experience.

    Directory of Open Access Journals (Sweden)

    Heather Chapin

    2010-12-01

    Full Text Available Apart from its natural relevance to cognition, music provides a window into the intimate relationships between production, perception, experience, and emotion. Here, emotional responses and neural activity were observed as they evolved together with stimulus parameters over several minutes. Participants listened to a skilled music performance that included the natural fluctuations in timing and sound intensity that musicians use to evoke emotional responses. A mechanical performance of the same piece served as a control. Before and after fMRI scanning, participants reported real-time emotional responses on a 2-dimensional rating scale (arousal and valence as they listened to each performance. During fMRI scanning, participants listened without reporting emotional responses. Limbic and paralimbic brain areas responded to the expressive dynamics of human music performance, and both emotion and reward related activations during music listening were dependent upon musical training. Moreover, dynamic changes in timing predicted ratings of emotional arousal, as well as real-time changes in neural activity. BOLD signal changes correlated with expressive timing fluctuations in cortical and subcortical motor areas consistent with pulse perception, and in a network consistent with the human mirror neuron system. These findings show that expressive music performance evokes emotion and reward related neural activations, and that music's affective impact on the brains of listeners is altered by musical training. Our observations are consistent with the idea that music performance evokes an emotional response through a form of empathy that is based, at least in part, on the perception of movement and on violations of pulse-based temporal expectancies.

  5. Preterm birth results in alterations in neural connectivity at age 16 years.

    Science.gov (United States)

    Mullen, Katherine M; Vohr, Betty R; Katz, Karol H; Schneider, Karen C; Lacadie, Cheryl; Hampson, Michelle; Makuch, Robert W; Reiss, Allan L; Constable, R Todd; Ment, Laura R

    2011-02-14

    Very low birth weight preterm (PT) children are at high risk for brain injury. Employing diffusion tensor imaging (DTI), we tested the hypothesis that PT adolescents would demonstrate microstructural white matter disorganization relative to term controls at 16 years of age. Forty-four PT subjects (600-1250 g birth weight) without neonatal brain injury and 41 term controls were evaluated at age 16 years with DTI, the Wechsler Intelligence Scale for Children-III (WISC), the Peabody Picture Vocabulary Test-Revised (PPVT), and the Comprehensive Test of Phonological Processing (CTOPP). PT subjects scored lower than term subjects on WISC full scale (p=0.003), verbal (p=0.043), and performance IQ tests (p=0.001), as well as CTOPP phonological awareness (p=0.004), but scored comparably to term subjects on PPVT and CTOPP Rapid Naming tests. PT subjects had lower fractional anisotropy (FA) values in multiple regions including bilateral uncinate fasciculi (left: p=0.01; right: p=0.004), bilateral external capsules (left: planguage task) in the PT subjects (left: r=0.314, p=0.038; right: r=0.336, p=0.026). FA values in the left and right arcuate fasciculi correlated with CTOPP Rapid Naming scores (a phonologic task) in the PT subjects (left: r=0.424, p=0.004; right: r=0.301, p=0.047). These data support for the first time that dual pathways underlying language function are present in PT adolescents. The striking bilateral dorsal correlations for the PT group suggest that prematurely born subjects rely more heavily on the right hemisphere than typically developing adults for performance of phonological language tasks. These findings may represent either a delay in maturation or the engagement of alternative neural pathways for language in the developing PT brain. Copyright © 2010 Elsevier Inc. All rights reserved.

  6. Voxel Scale Complex Networks of Functional Connectivity in the Rat Brain: Neurochemical State Dependence of Global and Local Topological Properties

    Directory of Open Access Journals (Sweden)

    Adam J. Schwarz

    2012-01-01

    Full Text Available Network analysis of functional imaging data reveals emergent features of the brain as a function of its topological properties. However, the brain is not a homogeneous network, and the dependence of functional connectivity parameters on neuroanatomical substrate and parcellation scale is a key issue. Moreover, the extent to which these topological properties depend on underlying neurochemical changes remains unclear. In the present study, we investigated both global statistical properties and the local, voxel-scale distribution of connectivity parameters of the rat brain. Different neurotransmitter systems were stimulated by pharmacological challenge (d-amphetamine, fluoxetine, and nicotine to discriminate between stimulus-specific functional connectivity and more general features of the rat brain architecture. Although global connectivity parameters were similar, mapping of local connectivity parameters at high spatial resolution revealed strong neuroanatomical dependence of functional connectivity in the rat brain, with clear differentiation between the neocortex and older brain regions. Localized foci of high functional connectivity independent of drug challenge were found in the sensorimotor cortices, consistent with the high neuronal connectivity in these regions. Conversely, the topological properties and node roles in subcortical regions varied with neurochemical state and were dependent on the specific dynamics of the different functional processes elicited.

  7. STABILITY OF LINEAR MULTIAGENT SCALAR SYSTEMS AND ITS DEPENDENCE ON CONNECTIVITY GRAPH

    Directory of Open Access Journals (Sweden)

    S. I. Tomashevich

    2014-03-01

    Full Text Available Multiagent systems are now finding increasingly wide applications in various engineering fields such as energy, transportation, robotics, aviation and others. There are two main aspects to be focused on when organizing multiagent systems: the dynamics of the agents themselves and the ways of their interaction. This interaction is determined by the structure of information connections between agents. Thus, there are several key points of multiagent systems study: the dynamics of individual agents and shape of the information graph. Formation dynamics, in general, is determined by a set of properties of agents and connectivity graph. The paper deals with the relationship between dynamics of agents and Laplace matrix, which is used to set the graph connections. The present research is based on the results given in the known paper by A. Fax and R. Murray (IEEE Trans. AC, 2004. An illustrative example is given, and the application problem of studying the formation dynamics consisting of the group of quadrocopters is presented. Information exchange between agents is determined in the paper by means of the conventional set of graphs. The paper presents an interpretation of the stability conditions and the method of system performance improvement based on these conditions. Motion of quadrocopters group along the flight height is used as an example for methodology application. The simulation results demonstrate the basic dependencies between the information graph shape (and, consequently, the eigenvalues of the Laplacian, which describes this graph and formation stability. Simulation and consideration of Nyquist diagram connection with the key points give an indication of the system stability and take steps to change the control laws. Necessary conditions for the formation stability are obtained on the basis of this research method. Research result makes it possible to create local control laws for agents to ensure the stability of motion in the selected

  8. Effects of gratitude meditation on neural network functional connectivity and brain-heart coupling.

    Science.gov (United States)

    Kyeong, Sunghyon; Kim, Joohan; Kim, Dae Jin; Kim, Hesun Erin; Kim, Jae-Jin

    2017-07-11

    A sense of gratitude is a powerful and positive experience that can promote a happier life, whereas resentment is associated with life dissatisfaction. To explore the effects of gratitude and resentment on mental well-being, we acquired functional magnetic resonance imaging and heart rate (HR) data before, during, and after the gratitude and resentment interventions. Functional connectivity (FC) analysis was conducted to identify the modulatory effects of gratitude on the default mode, emotion, and reward-motivation networks. The average HR was significantly lower during the gratitude intervention than during the resentment intervention. Temporostriatal FC showed a positive correlation with HR during the gratitude intervention, but not during the resentment intervention. Temporostriatal resting-state FC was significantly decreased after the gratitude intervention compared to the resentment intervention. After the gratitude intervention, resting-state FC of the amygdala with the right dorsomedial prefrontal cortex and left dorsal anterior cingulate cortex were positively correlated with anxiety scale and depression scale, respectively. Taken together, our findings shed light on the effect of gratitude meditation on an individual's mental well-being, and indicate that it may be a means of improving both emotion regulation and self-motivation by modulating resting-state FC in emotion and motivation-related brain regions.

  9. Stability analysis of switched cellular neural networks: A mode-dependent average dwell time approach.

    Science.gov (United States)

    Huang, Chuangxia; Cao, Jie; Cao, Jinde

    2016-10-01

    This paper addresses the exponential stability of switched cellular neural networks by using the mode-dependent average dwell time (MDADT) approach. This method is quite different from the traditional average dwell time (ADT) method in permitting each subsystem to have its own average dwell time. Detailed investigations have been carried out for two cases. One is that all subsystems are stable and the other is that stable subsystems coexist with unstable subsystems. By employing Lyapunov functionals, linear matrix inequalities (LMIs), Jessen-type inequality, Wirtinger-based inequality, reciprocally convex approach, we derived some novel and less conservative conditions on exponential stability of the networks. Comparing to ADT, the proposed MDADT show that the minimal dwell time of each subsystem is smaller and the switched system stabilizes faster. The obtained results extend and improve some existing ones. Moreover, the validness and effectiveness of these results are demonstrated through numerical simulations. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Learning and retrieval behavior in recurrent neural networks with pre-synaptic dependent homeostatic plasticity

    Science.gov (United States)

    Mizusaki, Beatriz E. P.; Agnes, Everton J.; Erichsen, Rubem; Brunnet, Leonardo G.

    2017-08-01

    The plastic character of brain synapses is considered to be one of the foundations for the formation of memories. There are numerous kinds of such phenomenon currently described in the literature, but their role in the development of information pathways in neural networks with recurrent architectures is still not completely clear. In this paper we study the role of an activity-based process, called pre-synaptic dependent homeostatic scaling, in the organization of networks that yield precise-timed spiking patterns. It encodes spatio-temporal information in the synaptic weights as it associates a learned input with a specific response. We introduce a correlation measure to evaluate the precision of the spiking patterns and explore the effects of different inhibitory interactions and learning parameters. We find that large learning periods are important in order to improve the network learning capacity and discuss this ability in the presence of distinct inhibitory currents.

  11. Indoor/outdoor connections exemplified by processes that depend on an organic compound's saturation vapor pressure

    DEFF Research Database (Denmark)

    Weschler, Charles J.

    2003-01-01

    Outdoor and indoor environments are profitably viewed as parts of a whole connected through various physical and chemical interactions. This paper examines four phenomena that share a dependence on vapor pressure-the extent to which an organic compound in the gas phase sorbs on airborne particles...... first estimates of the above processes. For typical indoor conditions, only larger compounds with lower-saturation vapor pressures (e.g., tetracosane, pentacosane, or di-2-ethylhexyl phthalate) have airborne particle concentrations comparable to or larger than gas phase concentrations. Regardless......'s saturation vapor pressure correlates in a linear fashion with the logarithms of equilibrium coefficients characteristic of each of these four phenomena. Since, to a rough approximation, the log of an organic compound's vapor pressure scales with its molecular weight, molecular weight can be used to make...

  12. Neural Signatures of the Reading-Writing Connection: Greater Involvement of Writing in Chinese Reading than English Reading.

    Science.gov (United States)

    Cao, Fan; Perfetti, Charles A

    2016-01-01

    Research on cross-linguistic comparisons of the neural correlates of reading has consistently found that the left middle frontal gyrus (MFG) is more involved in Chinese than in English. However, there is a lack of consensus on the interpretation of the language difference. Because this region has been found to be involved in writing, we hypothesize that reading Chinese characters involves this writing region to a greater degree because Chinese speakers learn to read by repeatedly writing the characters. To test this hypothesis, we recruited English L1 learners of Chinese, who performed a reading task and a writing task in each language. The English L1 sample had learned some Chinese characters through character-writing and others through phonological learning, allowing a test of writing-on-reading effect. We found that the left MFG was more activated in Chinese than English regardless of task, and more activated in writing than in reading regardless of language. Furthermore, we found that this region was more activated for reading Chinese characters learned by character-writing than those learned by phonological learning. A major conclusion is that writing regions are also activated in reading, and that this reading-writing connection is modulated by the learning experience. We replicated the main findings in a group of native Chinese speakers, which excluded the possibility that the language differences observed in the English L1 participants were due to different language proficiency level.

  13. Neural Signatures of the Reading-Writing Connection: Greater Involvement of Writing in Chinese Reading than English Reading.

    Directory of Open Access Journals (Sweden)

    Fan Cao

    Full Text Available Research on cross-linguistic comparisons of the neural correlates of reading has consistently found that the left middle frontal gyrus (MFG is more involved in Chinese than in English. However, there is a lack of consensus on the interpretation of the language difference. Because this region has been found to be involved in writing, we hypothesize that reading Chinese characters involves this writing region to a greater degree because Chinese speakers learn to read by repeatedly writing the characters. To test this hypothesis, we recruited English L1 learners of Chinese, who performed a reading task and a writing task in each language. The English L1 sample had learned some Chinese characters through character-writing and others through phonological learning, allowing a test of writing-on-reading effect. We found that the left MFG was more activated in Chinese than English regardless of task, and more activated in writing than in reading regardless of language. Furthermore, we found that this region was more activated for reading Chinese characters learned by character-writing than those learned by phonological learning. A major conclusion is that writing regions are also activated in reading, and that this reading-writing connection is modulated by the learning experience. We replicated the main findings in a group of native Chinese speakers, which excluded the possibility that the language differences observed in the English L1 participants were due to different language proficiency level.

  14. Training Recurrent Neural Networks With the Levenberg-Marquardt Algorithm for Optimal Control of a Grid-Connected Converter.

    Science.gov (United States)

    Fu, Xingang; Li, Shuhui; Fairbank, Michael; Wunsch, Donald C; Alonso, Eduardo

    2015-09-01

    This paper investigates how to train a recurrent neural network (RNN) using the Levenberg-Marquardt (LM) algorithm as well as how to implement optimal control of a grid-connected converter (GCC) using an RNN. To successfully and efficiently train an RNN using the LM algorithm, a new forward accumulation through time (FATT) algorithm is proposed to calculate the Jacobian matrix required by the LM algorithm. This paper explores how to incorporate FATT into the LM algorithm. The results show that the combination of the LM and FATT algorithms trains RNNs better than the conventional backpropagation through time algorithm. This paper presents an analytical study on the optimal control of GCCs, including theoretically ideal optimal and suboptimal controllers. To overcome the inapplicability of the optimal GCC controller under practical conditions, a new RNN controller with an improved input structure is proposed to approximate the ideal optimal controller. The performance of an ideal optimal controller and a well-trained RNN controller was compared in close to real-life power converter switching environments, demonstrating that the proposed RNN controller can achieve close to ideal optimal control performance even under low sampling rate conditions. The excellent performance of the proposed RNN controller under challenging and distorted system conditions further indicates the feasibility of using an RNN to approximate optimal control in practical applications.

  15. Mdm2 mediates FMRP- and Gp1 mGluR-dependent protein translation and neural network activity.

    Science.gov (United States)

    Liu, Dai-Chi; Seimetz, Joseph; Lee, Kwan Young; Kalsotra, Auinash; Chung, Hee Jung; Lu, Hua; Tsai, Nien-Pei

    2017-10-15

    Activating Group 1 (Gp1) metabotropic glutamate receptors (mGluRs), including mGluR1 and mGluR5, elicits translation-dependent neural plasticity mechanisms that are crucial to animal behavior and circuit development. Dysregulated Gp1 mGluR signaling has been observed in numerous neurological and psychiatric disorders. However, the molecular pathways underlying Gp1 mGluR-dependent plasticity mechanisms are complex and have been elusive. In this study, we identified a novel mechanism through which Gp1 mGluR mediates protein translation and neural plasticity. Using a multi-electrode array (MEA) recording system, we showed that activating Gp1 mGluR elevates neural network activity, as demonstrated by increased spontaneous spike frequency and burst activity. Importantly, we validated that elevating neural network activity requires protein translation and is dependent on fragile X mental retardation protein (FMRP), the protein that is deficient in the most common inherited form of mental retardation and autism, fragile X syndrome (FXS). In an effort to determine the mechanism by which FMRP mediates protein translation and neural network activity, we demonstrated that a ubiquitin E3 ligase, murine double minute-2 (Mdm2), is required for Gp1 mGluR-induced translation and neural network activity. Our data showed that Mdm2 acts as a translation suppressor, and FMRP is required for its ubiquitination and down-regulation upon Gp1 mGluR activation. These data revealed a novel mechanism by which Gp1 mGluR and FMRP mediate protein translation and neural network activity, potentially through de-repressing Mdm2. Our results also introduce an alternative way for understanding altered protein translation and brain circuit excitability associated with Gp1 mGluR in neurological diseases such as FXS. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  16. Kcnip1 a Ca²⁺-dependent transcriptional repressor regulates the size of the neural plate in Xenopus.

    Science.gov (United States)

    Néant, Isabelle; Mellström, Britt; Gonzalez, Paz; Naranjo, Jose R; Moreau, Marc; Leclerc, Catherine

    2015-09-01

    In amphibian embryos, our previous work has demonstrated that calcium transients occurring in the dorsal ectoderm at the onset of gastrulation are necessary and sufficient to engage the ectodermal cells into a neural fate by inducing neural specific genes. Some of these genes are direct targets of calcium. Here we search for a direct transcriptional mechanism by which calcium signals are acting. The only known mechanism responsible for a direct action of calcium on gene transcription involves an EF-hand Ca²⁺ binding protein which belongs to a group of four proteins (Kcnip1 to 4). Kcnip protein can act in a Ca²⁺-dependent manner as a transcriptional repressor by binding to a specific DNA sequence, the Downstream Regulatory Element (DRE) site. In Xenopus, among the four kcnips, we show that only kcnip1 is timely and spatially present in the presumptive neural territories and is able to bind DRE sites in a Ca²⁺-dependent manner. The loss of function of kcnip1 results in the expansion of the neural plate through an increased proliferation of neural progenitors. Later on, this leads to an impairment in the development of anterior neural structures. We propose that, in the embryo, at the onset of neurogenesis Kcnip1 is the Ca²⁺-dependent transcriptional repressor that controls the size of the neural plate. This article is part of a Special Issue entitled: 13th European Symposium on Calcium. Copyright © 2014. Published by Elsevier B.V.

  17. NMDA Receptors Mediate Stimulus-Timing-Dependent Plasticity and Neural Synchrony in the Dorsal Cochlear Nucleus.

    Science.gov (United States)

    Stefanescu, Roxana A; Shore, Susan E

    2015-01-01

    Auditory information relayed by auditory nerve fibers and somatosensory information relayed by granule cell parallel fibers converge on the fusiform cells (FCs) of the dorsal cochlear nucleus, the first brain station of the auditory pathway. In vitro, parallel fiber synapses on FCs exhibit spike-timing-dependent plasticity with Hebbian learning rules, partially mediated by the NMDA receptor (NMDAr). Well-timed bimodal auditory-somatosensory stimulation, in vivo equivalent of spike-timing-dependent plasticity, can induce stimulus-timing-dependent plasticity (StTDP) of the FCs spontaneous and tone-evoked firing rates. In healthy guinea pigs, the resulting distribution of StTDP learning rules across a FC neural population is dominated by a Hebbian profile while anti-Hebbian, suppressive and enhancing LRs are less frequent. In this study, we investigate in vivo, the NMDAr contribution to FC baseline activity and long term plasticity. We find that blocking the NMDAr decreases the synchronization of FC- spontaneous activity and mediates differential modulation of FC rate-level functions such that low, and high threshold units are more likely to increase, and decrease, respectively, their maximum amplitudes. Three significant alterations in mean learning-rule profiles were identified: transitions from an initial Hebbian profile towards (1) an anti-Hebbian; (2) a suppressive profile; and (3) transitions from an anti-Hebbian to a Hebbian profile. FC units preserving their learning rules showed instead, NMDAr-dependent plasticity to unimodal acoustic stimulation, with persistent depression of tone-evoked responses changing to persistent enhancement following the NMDAr antagonist. These results reveal a crucial role of the NMDAr in mediating FC baseline activity and long-term plasticity which have important implications for signal processing and auditory pathologies related to maladaptive plasticity of dorsal cochlear nucleus circuitry.

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

    Directory of Open Access Journals (Sweden)

    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.

  19. Phase-dependent stimulation effects on bursting activity in a neural network cortical simulation.

    Science.gov (United States)

    Anderson, William S; Kudela, Pawel; Weinberg, Seth; Bergey, Gregory K; Franaszczuk, Piotr J

    2009-03-01

    A neural network simulation with realistic cortical architecture has been used to study synchronized bursting as a seizure representation. This model has the property that bursting epochs arise and cease spontaneously, and bursting epochs can be induced by external stimulation. We have used this simulation to study the time-frequency properties of the evolving bursting activity, as well as effects due to network stimulation. The model represents a cortical region of 1.6 mm x 1.6mm, and includes seven neuron classes organized by cortical layer, inhibitory or excitatory properties, and electrophysiological characteristics. There are a total of 65,536 modeled single compartment neurons that operate according to a version of Hodgkin-Huxley dynamics. The intercellular wiring is based on histological studies and our previous modeling efforts. The bursting phase is characterized by a flat frequency spectrum. Stimulation pulses are applied to this modeled network, with an electric field provided by a 1mm radius circular electrode represented mathematically in the simulation. A phase dependence to the post-stimulation quiescence is demonstrated, with local relative maxima in efficacy occurring before or during the network depolarization phase in the underlying activity. Brief periods of network insensitivity to stimulation are also demonstrated. The phase dependence was irregular and did not reach statistical significance when averaged over the full 2.5s of simulated bursting investigated. This result provides comparison with previous in vivo studies which have also demonstrated increased efficacy of stimulation when pulses are applied at the peak of the local field potential during cortical after discharges. The network bursting is synchronous when comparing the different neuron classes represented up to an uncertainty of 10 ms. Studies performed with an excitatory chandelier cell component demonstrated increased synchronous bursting in the model, as predicted from

  20. Eveningness among late adolescent males predicts neural reactivity to reward and alcohol dependence 2 years later.

    Science.gov (United States)

    Hasler, Brant P; Casement, Melynda D; Sitnick, Stephanie L; Shaw, Daniel S; Forbes, Erika E

    2017-06-01

    Eveningness, a preference for later sleep-wake timing, is linked to altered reward function, which may explain a consistent association with substance abuse. Notably, the extant literature rests largely on cross-sectional data, yet both eveningness and reward function show developmental changes. We examined whether circadian preference during late adolescence predicted the neural response to reward 2 years later. A sample of 93 males reported circadian preference and completed a monetary reward fMRI paradigm at ages 20 and 22. Primary analyses examined longitudinal paths from circadian preference to medial prefrontal cortex (mPFC) and ventral striatal (VS) reward responses. We also explored whether reward responses mediated longitudinal associations between circadian preference and alcohol dependence, frequency of alcohol use, and/or frequency of cannabis use. Age 20 eveningness was positively associated with age 22 mPFC and VS responses to win, but not associated with age 22 reactivity to reward anticipation. Age 20 eveningness was indirectly related to age 22 alcohol dependence via age 22 mPFC response to win. Our findings provide novel evidence that altered reward-related brain function could underlie associations between eveningness and alcohol use problems. Eveningness may be an under-recognized but modifiable risk factor for reward-related problems such as mood and substance use disorders. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Neural Plasticity in Human Brain Connectivity: The Effects of Long Term Deep Brain Stimulation of the Subthalamic Nucleus in Parkinson’s Disease

    Science.gov (United States)

    van Hartevelt, Tim J.; Cabral, Joana; Deco, Gustavo; Møller, Arne; Green, Alexander L.; Aziz, Tipu Z.; Kringelbach, Morten L.

    2014-01-01

    Background Positive clinical outcomes are now well established for deep brain stimulation, but little is known about the effects of long-term deep brain stimulation on brain structural and functional connectivity. Here, we used the rare opportunity to acquire pre- and postoperative diffusion tensor imaging in a patient undergoing deep brain stimulation in bilateral subthalamic nuclei for Parkinson’s Disease. This allowed us to analyse the differences in structural connectivity before and after deep brain stimulation. Further, a computational model of spontaneous brain activity was used to estimate the changes in functional connectivity arising from the specific changes in structural connectivity. Results We found significant localised structural changes as a result of long-term deep brain stimulation. These changes were found in sensory-motor, prefrontal/limbic, and olfactory brain regions which are known to be affected in Parkinson’s Disease. The nature of these changes was an increase of nodal efficiency in most areas and a decrease of nodal efficiency in the precentral sensory-motor area. Importantly, the computational model clearly shows the impact of deep brain stimulation-induced structural alterations on functional brain changes, which is to shift the neural dynamics back towards a healthy regime. The results demonstrate that deep brain stimulation in Parkinson’s Disease leads to a topological reorganisation towards healthy bifurcation of the functional networks measured in controls, which suggests a potential neural mechanism for the alleviation of symptoms. Conclusions The findings suggest that long-term deep brain stimulation has not only restorative effects on the structural connectivity, but also affects the functional connectivity at a global level. Overall, our results support causal changes in human neural plasticity after long-term deep brain stimulation and may help to identify the underlying mechanisms of deep brain stimulation. PMID

  2. Neural plasticity in human brain connectivity: the effects of long term deep brain stimulation of the subthalamic nucleus in Parkinson's disease.

    Science.gov (United States)

    van Hartevelt, Tim J; Cabral, Joana; Deco, Gustavo; Møller, Arne; Green, Alexander L; Aziz, Tipu Z; Kringelbach, Morten L

    2014-01-01

    Positive clinical outcomes are now well established for deep brain stimulation, but little is known about the effects of long-term deep brain stimulation on brain structural and functional connectivity. Here, we used the rare opportunity to acquire pre- and postoperative diffusion tensor imaging in a patient undergoing deep brain stimulation in bilateral subthalamic nuclei for Parkinson's Disease. This allowed us to analyse the differences in structural connectivity before and after deep brain stimulation. Further, a computational model of spontaneous brain activity was used to estimate the changes in functional connectivity arising from the specific changes in structural connectivity. We found significant localised structural changes as a result of long-term deep brain stimulation. These changes were found in sensory-motor, prefrontal/limbic, and olfactory brain regions which are known to be affected in Parkinson's Disease. The nature of these changes was an increase of nodal efficiency in most areas and a decrease of nodal efficiency in the precentral sensory-motor area. Importantly, the computational model clearly shows the impact of deep brain stimulation-induced structural alterations on functional brain changes, which is to shift the neural dynamics back towards a healthy regime. The results demonstrate that deep brain stimulation in Parkinson's Disease leads to a topological reorganisation towards healthy bifurcation of the functional networks measured in controls, which suggests a potential neural mechanism for the alleviation of symptoms. The findings suggest that long-term deep brain stimulation has not only restorative effects on the structural connectivity, but also affects the functional connectivity at a global level. Overall, our results support causal changes in human neural plasticity after long-term deep brain stimulation and may help to identify the underlying mechanisms of deep brain stimulation.

  3. State-Dependent Differences in Functional Connectivity in Young Children With Autism Spectrum Disorder

    Directory of Open Access Journals (Sweden)

    Ashura W. Buckley

    2015-12-01

    Interpretation: Functional connectivity is distinctly different in children with autism compared to samples with typical development and developmental delay without autism. Differences in connectivity in autism are state and region related. In this study, children with autism were characterized by a dynamically evolving pattern of altered connectivity.

  4. Delay-Dependent Exponential Stability for Discrete-Time BAM Neural Networks with Time-Varying Delays

    Directory of Open Access Journals (Sweden)

    Yonggang Chen

    2008-01-01

    Full Text Available This paper considers the delay-dependent exponential stability for discrete-time BAM neural networks with time-varying delays. By constructing the new Lyapunov functional, the improved delay-dependent exponential stability criterion is derived in terms of linear matrix inequality (LMI. Moreover, in order to reduce the conservativeness, some slack matrices are introduced in this paper. Two numerical examples are presented to show the effectiveness and less conservativeness of the proposed method.

  5. Energy-based stochastic control of neural mass models suggests time-varying effective connectivity in the resting state.

    Science.gov (United States)

    Sotero, Roberto C; Shmuel, Amir

    2012-06-01

    Several studies posit energy as a constraint on the coding and processing of information in the brain due to the high cost of resting and evoked cortical activity. This suggestion has been addressed theoretically with models of a single neuron and two coupled neurons. Neural mass models (NMMs) address mean-field based modeling of the activity and interactions between populations of neurons rather than a few neurons. NMMs have been widely employed for studying the generation of EEG rhythms, and more recently as frameworks for integrated models of neurophysiology and functional MRI (fMRI) responses. To date, the consequences of energy constraints on the activity and interactions of ensembles of neurons have not been addressed. Here we aim to study the impact of constraining energy consumption during the resting-state on NMM parameters. To this end, we first linearized the model, then used stochastic control theory by introducing a quadratic cost function, which transforms the NMM into a stochastic linear quadratic regulator (LQR). Solving the LQR problem introduces a regime in which the NMM parameters, specifically the effective connectivities between neuronal populations, must vary with time. This is in contrast to current NMMs, which assume a constant parameter set for a given condition or task. We further simulated energy-constrained stochastic control of a specific NMM, the Wilson and Cowan model of two coupled neuronal populations, one of which is excitatory and the other inhibitory. These simulations demonstrate that with varying weights of the energy-cost function, the NMM parameters show different time-varying behavior. We conclude that constraining NMMs according to energy consumption may create more realistic models. We further propose to employ linear NMMs with time-varying parameters as an alternative to traditional nonlinear NMMs with constant parameters.

  6. Spectral signatures of activity-dependent neural feedback in the corticothalamic system

    Science.gov (United States)

    Roy, N.; Sanz-Leon, P.; Robinson, P. A.

    2017-11-01

    The modulation of neural quantities by presynaptic and postsynaptic activities via local feedback processes is investigated by incorporating nonlinear phenomena such as relative refractory period, synaptic enhancement, synaptic depression, and habituation. This is done by introducing susceptibilities, which quantify the response in either firing threshold or synaptic strength to unit change in either presynaptic or postsynaptic activity. Effects on the power spectra are then analyzed for a realistic corticothalamic model to determine the spectral signatures of various nonlinear processes and to what extent these are distinct. Depending on the feedback processes, there can be enhancements or reductions in low-frequency and/or alpha power, splitting of the alpha resonance, and/or appearance of new resonances at high frequencies. These features in the power spectra allow processes to be fully distinguished where they are unique, or partly distinguished if they are common to only a subset of feedbacks, and can potentially be used to constrain the types, strengths, and dynamics of feedbacks present.

  7. Cell density-dependent differential proliferation of neural stem cells on omnidirectional nanopore-arrayed surface.

    Science.gov (United States)

    Cha, Kyoung Je; Kong, Sun-Young; Lee, Ji Soo; Kim, Hyung Woo; Shin, Jae-Yeon; La, Moonwoo; Han, Byung Woo; Kim, Dong Sung; Kim, Hyun-Jung

    2017-10-12

    Recently, the importance of surface nanotopography in the determination of stem cell fate and behavior has been revealed. In the current study, we generated polystyrene cell-culture dishes with an omnidirectional nanopore arrayed surface (ONAS) (diameter: 200 nm, depth: 500 nm, center-to-center distance: 500 nm) and investigated the effects of nanotopography on rat neural stem cells (NSCs). NSCs cultured on ONAS proliferated better than those on the flat surface when cell density was low and showed less spontaneous differentiation during proliferation in the presence of mitogens. Interestingly, NSCs cultured on ONAS at clonal density demonstrated a propensity to generate neurospheres, whereas those on the flat surface migrated out, proliferated as individuals, and spread out to attach to the surface. However, the differential patterns of proliferation were cell density-dependent since the distinct phenomena were lost when cell density was increased. ONAS modulated cytoskeletal reorganization and inhibited formation of focal adhesion, which is generally observed in NSCs grown on flat surfaces. ONAS appeared to reinforce NSC-NSC interaction, restricted individual cell migration and prohibited NSC attachment to the nanopore surface. These data demonstrate that ONAS maintains NSCs as undifferentiated while retaining multipotency and is a better topography for culturing low density NSCs.

  8. Construction of high-dimensional neural network potentials using environment-dependent atom pairs.

    Science.gov (United States)

    Jose, K V Jovan; Artrith, Nongnuch; Behler, Jörg

    2012-05-21

    An accurate determination of the potential energy is the crucial step in computer simulations of chemical processes, but using electronic structure methods on-the-fly in molecular dynamics (MD) is computationally too demanding for many systems. Constructing more efficient interatomic potentials becomes intricate with increasing dimensionality of the potential-energy surface (PES), and for numerous systems the accuracy that can be achieved is still not satisfying and far from the reliability of first-principles calculations. Feed-forward neural networks (NNs) have a very flexible functional form, and in recent years they have been shown to be an accurate tool to construct efficient PESs. High-dimensional NN potentials based on environment-dependent atomic energy contributions have been presented for a number of materials. Still, these potentials may be improved by a more detailed structural description, e.g., in form of atom pairs, which directly reflect the atomic interactions and take the chemical environment into account. We present an implementation of an NN method based on atom pairs, and its accuracy and performance are compared to the atom-based NN approach using two very different systems, the methanol molecule and metallic copper. We find that both types of NN potentials provide an excellent description of both PESs, with the pair-based method yielding a slightly higher accuracy making it a competitive alternative for addressing complex systems in MD simulations.

  9. Construction of high-dimensional neural network potentials using environment-dependent atom pairs

    Science.gov (United States)

    Jose, K. V. Jovan; Artrith, Nongnuch; Behler, Jörg

    2012-05-01

    An accurate determination of the potential energy is the crucial step in computer simulations of chemical processes, but using electronic structure methods on-the-fly in molecular dynamics (MD) is computationally too demanding for many systems. Constructing more efficient interatomic potentials becomes intricate with increasing dimensionality of the potential-energy surface (PES), and for numerous systems the accuracy that can be achieved is still not satisfying and far from the reliability of first-principles calculations. Feed-forward neural networks (NNs) have a very flexible functional form, and in recent years they have been shown to be an accurate tool to construct efficient PESs. High-dimensional NN potentials based on environment-dependent atomic energy contributions have been presented for a number of materials. Still, these potentials may be improved by a more detailed structural description, e.g., in form of atom pairs, which directly reflect the atomic interactions and take the chemical environment into account. We present an implementation of an NN method based on atom pairs, and its accuracy and performance are compared to the atom-based NN approach using two very different systems, the methanol molecule and metallic copper. We find that both types of NN potentials provide an excellent description of both PESs, with the pair-based method yielding a slightly higher accuracy making it a competitive alternative for addressing complex systems in MD simulations.

  10. Experience-dependent plasticity in white matter microstructure: Reasoning training alters structural connectivity

    Directory of Open Access Journals (Sweden)

    Allyson P Mackey

    2012-08-01

    Full Text Available Diffusion tensor imaging (DTI techniques have made it possible to investigate white matter plasticity in humans. Changes in DTI measures, principally increases in fractional anisotropy (FA, have been observed following training programs as diverse as juggling, meditation, and working memory. Here, we sought to test whether three months of reasoning training could alter white matter microstructure. We recruited participants (n=23 who were enrolled in a course to prepare for the Law School Admission Test (LSAT, a test that places strong demands on reasoning skills, as well as age- and IQ-matched controls planning to take the LSAT in the future (n=22. DTI data were collected at two scan sessions scheduled three months apart. In trained participants but not controls, we observed decreases in radial diffusivity (RD in white matter connecting frontal cortices, and in mean diffusivity (MD within frontal and parietal lobe white matter. Further, participants exhibiting larger gains on the LSAT exhibited greater decreases in MD in the right internal capsule. In summary, reasoning training altered multiple measures of white matter structure in young adults. While the cellular underpinnings are unknown, these results provide evidence of experience-dependent white matter changes that may not be limited to myelination.

  11. Altered Long- and Short-Range Functional Connectivity in Patients with Betel Quid Dependence: A Resting-State Functional MRI Study

    Directory of Open Access Journals (Sweden)

    Tao Liu

    2016-12-01

    Full Text Available Objective: Addiction is a chronic relapsing brain disease. Brain structural abnormalities may constitute an abnormal neural network that underlies the risk of drug dependence. We hypothesized that individuals with Betel Quid Dependence (BQD have functional connectivity alterations that can be described by long- and short-range functional connectivity density(FCD maps. Methods: We tested this hypothesis using functional magnetic resonance imaging (fMRI data from subjects of the Han ethnic group in Hainan, China. Here, we examined BQD individuals (n = 33 and age-, sex-, and education-matched healthy controls (HCs (n = 32 in a rs-fMRI study to observe FCD alterations associated with the severity of BQD. Results: Compared with HCs, long-range FCD was decreased in the right anterior cingulate cortex (ACC and increased in the left cerebellum posterior lobe (CPL and bilateral inferior parietal lobule (IPL in the BQD group. Short-range FCD was reduced in the right ACC and left dorsolateral prefrontal cortex (dlPFC, and increased in the left CPL. The short-range FCD alteration in the right ACC displayed a negative correlation with the Betel Quid Dependence Scale (BQDS (r=-0.432, P=0.012, and the long-range FCD alteration of left IPL showed a positive correlation with the duration of BQD(r=0.519, P=0.002 in BQD individuals. Conclusions: fMRI revealed differences in long- and short- range FCD in BQD individuals, and these alterations might be due to BQ chewing, BQ dependency, or risk factors for developing BQD.

  12. Neural correlates of impulsive aggressive behavior in subjects with a history of alcohol dependence.

    Science.gov (United States)

    Kose, Samet; Steinberg, Joel L; Moeller, F Gerard; Gowin, Joshua L; Zuniga, Edward; Kamdar, Zahra N; Schmitz, Joy M; Lane, Scott D

    2015-04-01

    Alcohol-related aggression is a complex and problematic phenomenon with profound public health consequences. We examined neural correlates potentially moderating the relationship between human aggressive behavior and chronic alcohol use. Thirteen subjects meeting DSM-IV criteria for past alcohol-dependence in remission (AD) and 13 matched healthy controls (CONT) participated in an fMRI study adapted from a laboratory model of human aggressive behavior (Point Subtraction Aggression Paradigm, or PSAP). Blood oxygen level dependent (BOLD) activation was measured during bouts of operationally defined aggressive behavior, during postprovocation periods, and during monetary-reinforced behavior. Whole brain voxelwise random-effects analyses found group differences in brain regions relevant to chronic alcohol use and aggressive behavior (e.g., emotional and behavioral control). Behaviorally, AD subjects responded on both the aggressive response and monetary response options at significantly higher rates than CONT. Whole brain voxelwise random-effects analyses revealed significant group differences in response to provocation (monetary subtractions), with CONT subjects showing greater activation in frontal and prefrontal cortex, thalamus, and hippocampus. Collapsing data across all subjects, regression analyses of postprovocation brain activation on aggressive response rate revealed significant positive regression slopes in precentral gyrus and parietal cortex; and significant negative regression slopes in orbitofrontal cortex, prefrontal cortex, caudate, thalamus, and middle temporal gyrus. In these collapsed analyses, response to provocation and aggressive behavior were associated with activation in brain regions subserving inhibitory and emotional control, sensorimotor integration, and goal directed motor activity. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

  13. A novel Fizzy/Cdc20-dependent mechanism suppresses necrosis in neural stem cells

    Science.gov (United States)

    Kuang, Chaoyuan; Golden, Krista L.; Simon, Claudio R.; Damrath, John; Buttitta, Laura; Gamble, Caitlin E.; Lee, Cheng-Yu

    2014-01-01

    Cancer stem cells likely survive chemotherapy or radiotherapy by acquiring mutations that inactivate the endogenous apoptotic machinery or by cycling slowly. Thus, knowledge about the mechanisms linking the activation of an alternative cell death modality and the cell cycle machinery could have a transformative impact on the development of new cancer therapies, but the mechanisms remain completely unknown. We investigated the regulation of alternative cell death in Drosophila larval brain neural stem cells (neuroblasts) in which apoptosis is normally repressed. From a screen, we identified two novel loss-of-function alleles of the Cdc20/fizzy (fzy) gene that lead to premature brain neuroblast loss without perturbing cell proliferation in other diploid cell types. Fzy is an evolutionarily conserved regulator of anaphase promoting complex/cyclosome (APC/C). Neuroblasts carrying the novel fzy allele or exhibiting reduced APC/C function display hallmarks of necrosis. By contrast, neuroblasts overexpressing the non-degradable form of canonical APC/C substrates required for cell cycle progression undergo mitotic catastrophe. These data strongly suggest that Fzy can elicit a novel pro-survival function of APC/C by suppressing necrosis. Neuroblasts experiencing catastrophic cellular stress, or overexpressing p53, lose Fzy expression and undergo necrosis. Co-expression of fzy suppresses the death of these neuroblasts. Consequently, attenuation of the Fzy-dependent survival mechanism functions downstream of catastrophic cellular stress and p53 to eliminate neuroblasts by necrosis. Strategies that target the Fzy-dependent survival mechanism might lead to the discovery of new treatments or complement the pre-existing therapies to eliminate apoptosis-resistant cancer stem cells by necrosis. PMID:24598157

  14. Alcohol Dependence and Altered Engagement of Neural Networks in Risky Decisions

    Directory of Open Access Journals (Sweden)

    Xi eZhu

    2016-03-01

    Full Text Available Alcohol dependence is associated with heightened risk tolerance and altered decision- making. This raises the question as to whether alcohol dependent patients (ADP are incapable of proper risk assessment. We investigated how healthy controls (HC and ADP engage neural networks to cope with the increased cognitive demands of risky decisions. We collected fMRI data while 34 HC and 16 ADP played a game that included safe and risky trials. In safe trials, participants accrued money at no risk of a penalty. In risky trials, reward and risk simultaneously increased as participants were instructed to decide when to stop a reward accrual period. If the participant failed to stop before an undisclosed time, the trial would bust and participants would not earn the money from that trial. Independent Component Analysis was used to identify networks engaged during the anticipation and the decision execution of risky compared with safe trials. Like HC, ADP demonstrated distinct network engagement for safe and risky trials at anticipation. However, at decision execution, ADP exhibited severely reduced discrimination in network engagement between safe and risky trials. Although ADP behaviorally responded to risk they failed to appropriately modify network engagement as the decision continued, leading ADP to assume similar network engagement regardless of risk prospects. This may reflect disorganized network switching and a facile response strategy uniformly adopted by ADP across risk conditions. We propose that aberrant salience network (SN engagement in ADP might contribute to ineffective network switching and that the role of the SN in risky decisions warrants further investigation.

  15. Light evokes melanopsin-dependent vocalization and neural activation associated with aversive experience in neonatal mice.

    Directory of Open Access Journals (Sweden)

    Anton Delwig

    Full Text Available Melanopsin-expressing intrinsically photosensitive retinal ganglion cells (ipRGCs are the only functional photoreceptive cells in the eye of newborn mice. Through postnatal day 9, in the absence of functional rods and cones, these ipRGCs mediate a robust avoidance behavior to a light source, termed negative phototaxis. To determine whether this behavior is associated with an aversive experience in neonatal mice, we characterized light-induced vocalizations and patterns of neuronal activation in regions of the brain involved in the processing of aversive and painful stimuli. Light evoked distinct melanopsin-dependent ultrasonic vocalizations identical to those emitted under stressful conditions, such as isolation from the litter. In contrast, light did not evoke the broad-spectrum calls elicited by acute mechanical pain. Using markers of neuronal activation, we found that light induced the immediate-early gene product Fos in the posterior thalamus, a brain region associated with the enhancement of responses to mechanical stimulation of the dura by light, and thought to be the basis for migrainous photophobia. Additionally, light induced the phosphorylation of extracellular-related kinase (pERK in neurons of the central amygdala, an intracellular signal associated with the processing of the aversive aspects of pain. However, light did not activate Fos expression in the spinal trigeminal nucleus caudalis, the primary receptive field for painful stimulation to the head. We conclude that these light-evoked vocalizations and the distinct pattern of brain activation in neonatal mice are consistent with a melanopsin-dependent neural pathway involved in processing light as an aversive but not acutely painful stimulus.

  16. Whole-brain functional connectivity during acquisition of novel grammar: Distinct functional networks depend on language learning abilities.

    Science.gov (United States)

    Kepinska, Olga; de Rover, Mischa; Caspers, Johanneke; Schiller, Niels O

    2017-03-01

    In an effort to advance the understanding of brain function and organisation accompanying second language learning, we investigate the neural substrates of novel grammar learning in a group of healthy adults, consisting of participants with high and average language analytical abilities (LAA). By means of an Independent Components Analysis, a data-driven approach to functional connectivity of the brain, the fMRI data collected during a grammar-learning task were decomposed into maps representing separate cognitive processes. These included the default mode, task-positive, working memory, visual, cerebellar and emotional networks. We further tested for differences within the components, representing individual differences between the High and Average LAA learners. We found high analytical abilities to be coupled with stronger contributions to the task-positive network from areas adjacent to bilateral Broca's region, stronger connectivity within the working memory network and within the emotional network. Average LAA participants displayed stronger engagement within the task-positive network from areas adjacent to the right-hemisphere homologue of Broca's region and typical to lower level processing (visual word recognition), and increased connectivity within the default mode network. The significance of each of the identified networks for the grammar learning process is presented next to a discussion on the established markers of inter-individual learners' differences. We conclude that in terms of functional connectivity, the engagement of brain's networks during grammar acquisition is coupled with one's language learning abilities. Copyright © 2016 Elsevier B.V. All rights reserved.

  17. Input specificity and dependence of spike timing-dependent plasticity on preceding postsynaptic activity at unitary connections between neocortical layer 2/3 pyramidal cells

    NARCIS (Netherlands)

    Zilberter, M.; Holmgren, C.D.; Shemer, I.; Silberberg, G.; Grillner, S.; Harkany, T.; Zilberter, Y.

    2009-01-01

    Layer 2/3 (L2/3) pyramidal cells receive excitatory afferent input both from neighbouring pyramidal cells and from cortical and subcortical regions. The efficacy of these excitatory synaptic inputs is modulated by spike timing-dependent plasticity (STDP). Here we report that synaptic connections

  18. Sampled-Data Synchronization of Markovian Coupled Neural Networks With Mode Delays Based on Mode-Dependent LKF.

    Science.gov (United States)

    Wang, Junyi; Zhang, Huaguang; Wang, Zhanshan; Liu, Zhenwei

    This paper investigates sampled-data synchronization problem of Markovian coupled neural networks with mode-dependent interval time-varying delays and aperiodic sampling intervals based on an enhanced input delay approach. A mode-dependent augmented Lyapunov-Krasovskii functional (LKF) is utilized, which makes the LKF matrices mode-dependent as much as possible. By applying an extended Jensen's integral inequality and Wirtinger's inequality, new delay-dependent synchronization criteria are obtained, which fully utilizes the upper bound on variable sampling interval and the sawtooth structure information of varying input delay. In addition, the desired stochastic sampled-data controllers can be obtained by solving a set of linear matrix inequalities. Finally, two examples are provided to demonstrate the feasibility of the proposed method.This paper investigates sampled-data synchronization problem of Markovian coupled neural networks with mode-dependent interval time-varying delays and aperiodic sampling intervals based on an enhanced input delay approach. A mode-dependent augmented Lyapunov-Krasovskii functional (LKF) is utilized, which makes the LKF matrices mode-dependent as much as possible. By applying an extended Jensen's integral inequality and Wirtinger's inequality, new delay-dependent synchronization criteria are obtained, which fully utilizes the upper bound on variable sampling interval and the sawtooth structure information of varying input delay. In addition, the desired stochastic sampled-data controllers can be obtained by solving a set of linear matrix inequalities. Finally, two examples are provided to demonstrate the feasibility of the proposed method.

  19. Difference in the functional connectivity of the dorsolateral prefrontal cortex between smokers with nicotine dependence and individuals with internet gaming disorder.

    Science.gov (United States)

    Ge, Xin; Sun, Yawen; Han, Xu; Wang, Yao; Ding, Weina; Cao, Mengqiu; Du, Yasong; Xu, Jianrong; Zhou, Yan

    2017-07-27

    It has been reported that internet gaming disorder (IGD) and smokers with nicotine dependence (SND) share clinical characteristics, such as over-engagement despite negative consequences and cravings. This study is to investigate the alterations in the resting-state functional connectivity (rsFC) of the dorsolateral prefrontal cortex (DLPFC) observed in SND and IGD. In this study, 27 IGD, 29 SND, and 33 healthy controls (HC) underwent a resting-state functional magnetic resonance imaging (rs-fMRI) scan. DLPFC connectivity was determined in all participates by investigating the synchronized low-frequency fMRI signal fluctuations using a temporal seed-based correlation method. Compared with the HC group, the IGD and SND groups showed decreased rsFC with DLPFC in the right insula and left inferior frontal gyrus with DLPFC. Compared with SND group, the IGD subjects exhibited increased rsFC in the left inferior temporal gyrus and right inferior orbital frontal gyrus and decreased rsFC in the right middle occipital gyrus, supramarginal gyrus, and cuneus with DLPFC. Our results confirmed that SND and IGD share similar neural mechanisms related to craving and impulsive inhibitions. The significant difference in rsFC with DLPFC between the IGD and SND subjects may be attributed to the visual and auditory stimulation generated by long-term internet gaming.

  20. Method of Creation of “Core-Gisseismic Attributes” Dependences With Use of Trainable Neural Networks

    Directory of Open Access Journals (Sweden)

    Gafurov Denis

    2016-01-01

    Full Text Available The study describes methodological techniques and results of geophysical well logging and seismic data interpretation by means of trainable neural networks. Objects of research are wells and seismic materials of Talakan field. The article also presents forecast of construction and reservoir properties of Osa horizon. The paper gives an example of creation of geological (lithological -facial model of the field based on developed methodical techniques of complex interpretation of geologicgeophysical data by trainable neural network. The constructed lithological -facial model allows specifying a geological structure of the field. The developed methodical techniques and the trained neural networks may be applied to adjacent sites for research of carbonate horizons.

  1. Differential functional connectivity within an emotion regulation neural network among individuals resilient and susceptible to the depressogenic effects of early life stress.

    Science.gov (United States)

    Cisler, J M; James, G A; Tripathi, S; Mletzko, T; Heim, C; Hu, X P; Mayberg, H S; Nemeroff, C B; Kilts, C D

    2013-03-01

    Early life stress (ELS) is a significant risk factor for depression. The effects of ELS exposure on neural network organization have not been differentiated from the effect of depression. Furthermore, many individuals exposed to ELS do not develop depression, yet the network organization patterns differentiating resiliency versus susceptibility to the depressogenic effects of ELS are not clear. Women aged 18-44 years with either a history of ELS and no history of depression (n = 7), a history of ELS and current or past depression (n = 19), or a history of neither ELS nor depression (n = 12) underwent a resting-state 3-T functional magnetic resonance imaging (fMRI) scan. An emotion regulation brain network consisting of 21 nodes was described using graph analyses and compared between groups. Group differences in network topology involved decreased global connectivity and hub-like properties for the right ventrolateral prefrontal cortex (vlPFC) and decreased local network connectivity for the dorsal anterior cingulate cortex (dACC) among resilient individuals. Decreased local connectivity and increased hub-like properties of the left amygdala, decreased hub-like properties of the dACC and decreased local connectivity of the left vlPFC were observed among susceptible individuals. Regression analyses suggested that the severity of ELS (measured by self-report) correlated negatively with global connectivity and hub-like qualities for the left dorsolateral PFC (dlPFC). These preliminary results suggest functional neural connectivity patterns specific to ELS exposure and resiliency versus susceptibility to the depressogenic effects of ELS exposure.

  2. State-Dependent Changes of Connectivity Patterns and Functional Brain Network Topology in Autism Spectrum Disorder

    Science.gov (United States)

    Barttfeld, Pablo; Wicker, Bruno; Cukier, Sebastian; Navarta, Silvana; Lew, Sergio; Leiguarda, Ramon; Sigman, Mariano

    2012-01-01

    Anatomical and functional brain studies have converged to the hypothesis that autism spectrum disorders (ASD) are associated with atypical connectivity. Using a modified resting-state paradigm to drive subjects' attention, we provide evidence of a very marked interaction between ASD brain functional connectivity and cognitive state. We show that…

  3. Matriptase activation connects tissue factor-dependent coagulation initiation to epithelial proteolysis and signaling.

    Science.gov (United States)

    Le Gall, Sylvain M; Szabo, Roman; Lee, Melody; Kirchhofer, Daniel; Craik, Charles S; Bugge, Thomas H; Camerer, Eric

    2016-06-23

    The coagulation cascade is designed to sense tissue injury by physical separation of the membrane-anchored cofactor tissue factor (TF) from inactive precursors of coagulation proteases circulating in plasma. Once TF on epithelial and other extravascular cells is exposed to plasma, sequential activation of coagulation proteases coordinates hemostasis and contributes to host defense and tissue repair. Membrane-anchored serine proteases (MASPs) play critical roles in the development and homeostasis of epithelial barrier tissues; how MASPs are activated in mature epithelia is unknown. We here report that proteases of the extrinsic pathway of blood coagulation transactivate the MASP matriptase, thus connecting coagulation initiation to epithelial proteolysis and signaling. Exposure of TF-expressing cells to factors (F) VIIa and Xa triggered the conversion of latent pro-matriptase to an active protease, which in turn cleaved the pericellular substrates protease-activated receptor-2 (PAR2) and pro-urokinase. An activation pathway-selective PAR2 mutant resistant to direct cleavage by TF:FVIIa and FXa was activated by these proteases when cells co-expressed pro-matriptase, and matriptase transactivation was necessary for efficient cleavage and activation of wild-type PAR2 by physiological concentrations of TF:FVIIa and FXa. The coagulation initiation complex induced rapid and prolonged enhancement of the barrier function of epithelial monolayers that was dependent on matriptase transactivation and PAR2 signaling. These observations suggest that the coagulation cascade engages matriptase to help coordinate epithelial defense and repair programs after injury or infection, and that matriptase may contribute to TF-driven pathogenesis in cancer and inflammation.

  4. Connective-Tissue Growth Factor (CTGF/CCN2 Induces Astrogenesis and Fibronectin Expression of Embryonic Neural Cells In Vitro.

    Directory of Open Access Journals (Sweden)

    Fabio A Mendes

    Full Text Available Connective-tissue growth factor (CTGF is a modular secreted protein implicated in multiple cellular events such as chondrogenesis, skeletogenesis, angiogenesis and wound healing. CTGF contains four different structural modules. This modular organization is characteristic of members of the CCN family. The acronym was derived from the first three members discovered, cysteine-rich 61 (CYR61, CTGF and nephroblastoma overexpressed (NOV. CTGF is implicated as a mediator of important cell processes such as adhesion, migration, proliferation and differentiation. Extensive data have shown that CTGF interacts particularly with the TGFβ, WNT and MAPK signaling pathways. The capacity of CTGF to interact with different growth factors lends it an important role during early and late development, especially in the anterior region of the embryo. ctgf knockout mice have several cranio-facial defects, and the skeletal system is also greatly affected due to an impairment of the vascular-system development during chondrogenesis. This study, for the first time, indicated that CTGF is a potent inductor of gliogenesis during development. Our results showed that in vitro addition of recombinant CTGF protein to an embryonic mouse neural precursor cell culture increased the number of GFAP- and GFAP/Nestin-positive cells. Surprisingly, CTGF also increased the number of Sox2-positive cells. Moreover, this induction seemed not to involve cell proliferation. In addition, exogenous CTGF activated p44/42 but not p38 or JNK MAPK signaling, and increased the expression and deposition of the fibronectin extracellular matrix protein. Finally, CTGF was also able to induce GFAP as well as Nestin expression in a human malignant glioma stem cell line, suggesting a possible role in the differentiation process of gliomas. These results implicate ctgf as a key gene for astrogenesis during development, and suggest that its mechanism may involve activation of p44/42 MAPK signaling

  5. On the numerical solution of the time-dependent Ginzburg-Landau equations in multiply connected domains

    Energy Technology Data Exchange (ETDEWEB)

    Buscaglia, G.C.; Lopez, A. [Centro Atomico Bariloche and Inst. Balseiro, Bariloche (Argentina); Bolech, C. [Rutgers - the State Univ., Piscataway, NJ (United States). Dept. of Physics and Astronomy

    2000-07-01

    A numerical method for the solution of the time-dependent Ginzburg-Landau equations is detailed. The method is based on the popular technique of gauge invariant variables. Extension of the method to multiply connected domains is addressed. An implementation of the method is made available through the Web. (orig.)

  6. Concentration-dependent effect of nerve growth factor on cell fate determination of neural progenitors.

    Science.gov (United States)

    Zhang, Lei; Jiang, Hui; Hu, Zhengqing

    2011-10-01

    Stem cell-based spiral ganglion neuron (SGN) replacement therapy has been proposed to be a promising strategy to restore hearing either via replacing degenerated neurons or by improving the efficacy of cochlear implants which rely on functional neurons. However, lack of suitable donor cells and low survival rate of implanted cells are the major obstacles to successful implementation of therapeutic transplantation. The present study investigated the potential of mouse inner ear statoacoustic ganglion (SAG)-derived neural progenitors (NPs) to differentiate toward SGN-like glutamatergic cells and the influence to cell survival and differentiation when nerve growth factor (NGF) was supplied. We found that SAG-NPs could form neurospheres, proliferate, and differentiate into cells expressing neuronal protein neurofilament and β-III tubulin. NGF affected the cell fate of SAG-NP in a concentration-dependent manner in vitro. Low concentration of NGF (2-5 ng/mL) promoted cell proliferation. Medium concentration of NGF (20-40 ng/mL) stimulated cells to differentiate into bi-polar SGN-like cells expressing glutamatergic proteins. High concentration of NGF (100 ng/mL) could rescue cells from induced apoptosis. In the in vivo study, NGF (100 ng/mL) dramatically enhanced SAG-NP survival rate after implantation into adult mammalian inner ear. This finding raises the possibility to further induce these NPs to differentiate into SGN-like neurons in future in vivo study. In conclusion, given the capability of proliferation and differentiation into SGN-like cells with the supplement of NGF in vitro, SAG-NPs can serve as donor cells in stem cell-based SGN replacement therapy. NGF improved the survival of SAG-NPs not only in vitro but also in vivo.

  7. Neural correlates of reward-based spatial learning in persons with cocaine dependence.

    Science.gov (United States)

    Tau, Gregory Z; Marsh, Rachel; Wang, Zhishun; Torres-Sanchez, Tania; Graniello, Barbara; Hao, Xuejun; Xu, Dongrong; Packard, Mark G; Duan, Yunsuo; Kangarlu, Alayar; Martinez, Diana; Peterson, Bradley S

    2014-02-01

    Dysfunctional learning systems are thought to be central to the pathogenesis of and impair recovery from addictions. The functioning of the brain circuits for episodic memory or learning that support goal-directed behavior has not been studied previously in persons with cocaine dependence (CD). Thirteen abstinent CD and 13 healthy participants underwent MRI scanning while performing a task that requires the use of spatial cues to navigate a virtual-reality environment and find monetary rewards, allowing the functional assessment of the brain systems for spatial learning, a form of episodic memory. Whereas both groups performed similarly on the reward-based spatial learning task, we identified disturbances in brain regions involved in learning and reward in CD participants. In particular, CD was associated with impaired functioning of medial temporal lobe (MTL), a brain region that is crucial for spatial learning (and episodic memory) with concomitant recruitment of striatum (which normally participates in stimulus-response, or habit, learning), and prefrontal cortex. CD was also associated with enhanced sensitivity of the ventral striatum to unexpected rewards but not to expected rewards earned during spatial learning. We provide evidence that spatial learning in CD is characterized by disturbances in functioning of an MTL-based system for episodic memory and a striatum-based system for stimulus-response learning and reward. We have found additional abnormalities in distributed cortical regions. Consistent with findings from animal studies, we provide the first evidence in humans describing the disruptive effects of cocaine on the coordinated functioning of multiple neural systems for learning and memory.

  8. Niche-dependent development of functional neuronal networks from embryonic stem cell-derived neural populations

    Directory of Open Access Journals (Sweden)

    Siebler Mario

    2009-08-01

    Full Text Available Abstract Background The present work was performed to investigate the ability of two different embryonic stem (ES cell-derived neural precursor populations to generate functional neuronal networks in vitro. The first ES cell-derived neural precursor population was cultivated as free-floating neural aggregates which are known to form a developmental niche comprising different types of neural cells, including neural precursor cells (NPCs, progenitor cells and even further matured cells. This niche provides by itself a variety of different growth factors and extracellular matrix proteins that influence the proliferation and differentiation of neural precursor and progenitor cells. The second population was cultivated adherently in monolayer cultures to control most stringently the extracellular environment. This population comprises highly homogeneous NPCs which are supposed to represent an attractive way to provide well-defined neuronal progeny. However, the ability of these different ES cell-derived immature neural cell populations to generate functional neuronal networks has not been assessed so far. Results While both precursor populations were shown to differentiate into sufficient quantities of mature NeuN+ neurons that also express GABA or vesicular-glutamate-transporter-2 (vGlut2, only aggregate-derived neuronal populations exhibited a synchronously oscillating network activity 2–4 weeks after initiating the differentiation as detected by the microelectrode array technology. Neurons derived from homogeneous NPCs within monolayer cultures did merely show uncorrelated spiking activity even when differentiated for up to 12 weeks. We demonstrated that these neurons exhibited sparsely ramified neurites and an embryonic vGlut2 distribution suggesting an inhibited terminal neuronal maturation. In comparison, neurons derived from heterogeneous populations within neural aggregates appeared as fully mature with a dense neurite network and punctuated

  9. Task-dependent modulation of effective connectivity within the default mode network

    Directory of Open Access Journals (Sweden)

    Baojuan eLi

    2012-06-01

    Full Text Available The default mode network (DMN has recently attracted widespread interest. Previous studies have found that task related processing can induce deactivation and changes in the functional connectivity of this network. However, it remains unclear how tasks modulate the underlying effective connectivity within the DMN. Using recent advances in Dynamic Causal Modeling (DCM, we study the effective connectivity of resting state networks. The current fMRI study investigated the modulatory effect of (gender judgment task performance on directed connectivity within the DMN. Sixteen healthy subjects were scanned twice: at rest and while performing a gender judgment task. Group independent component analysis was used to decompose the functional images into spatial independent components. Four subject-specific regions of interest (ROIs were defined according to the ensuing default mode component: the posterior cingulate cortex, the left lateral parietal cortex, the right lateral parietal cortex and the medial prefrontal cortex. Effective connectivity among these regions was then characterized with stochastic DCM, revealing enhanced (extrinsic between region connectivity within the DMN during task sessions – and a universal decrease in (intrinsic self inhibition – relative to resting sessions. These results suggest a distributed but systematic modulatory effect of cognitive and attentional set on the effective connectivity subtending the DMN: an effect that increases its sensitivity to inputs and may optimize distributed processing during task performance.

  10. Neural connectivity during reward expectation dissociates psychopathic criminals from non-criminal individuals with high impulsive/antisocial psychopathic traits

    NARCIS (Netherlands)

    Geurts, D.E.; Borries, K. von; Volman, I.; Bulten, B.H.; Cools, R.; Verkes, R.J.

    2016-01-01

    Criminal behaviour poses a big challenge for society. A thorough understanding of the neurobiological mechanisms underlying criminality could optimize its prevention and management. Specifically,elucidating the neural mechanisms underpinning reward expectation might be pivotal to understanding

  11. Task-Dependent Modulation of Effective Connectivity within the Default Mode Network.

    Science.gov (United States)

    Li, Baojuan; Wang, Xiang; Yao, Shuqiao; Hu, Dewen; Friston, Karl

    2012-01-01

    The default mode network (DMN) has recently attracted widespread interest. Previous studies have found that task-related processing can induce deactivation and changes in the functional connectivity of this network. However, it remains unclear how tasks modulate the underlying effective connectivity within the DMN. Using recent advances in dynamic causal modeling (DCM), we investigated the modulatory effect of (gender judgment) task performance on directed connectivity within the DMN. Sixteen healthy subjects were scanned twice: at rest and while performing a gender judgment task. Group independent component analysis was used to identify independent spatial components. Four subject-specific regions of interest (ROIs) were defined according to the ensuing default mode component: the posterior cingulate cortex, the left lateral parietal cortex, the right lateral parietal cortex, and the medial prefrontal cortex. Effective connectivity among these regions was then characterized with stochastic DCM, revealing enhanced (extrinsic) between region connectivity within the DMN during task sessions - and a universal decrease in (intrinsic) self-inhibition - relative to resting sessions. These results suggest a distributed but systematic modulatory effect of cognitive and attentional set on the effective connectivity subtending the DMN: an effect that increases its sensitivity to inputs and may optimize distributed processing during task performance.

  12. Thermo-elastic plane deformations in doubly-connected domains with temperature and pressure which depend of the thermal conductivity

    Directory of Open Access Journals (Sweden)

    Giovanni Cimatti

    2014-05-01

    Full Text Available We propose a new weak formulation for the plane problem of thermoelastic theory in multiply-connected domains. This permits to avoid the difficulties connected with the Cesaro-Volterra boundary conditions in the related elliptic boundary-value problem. In the second part we consider a nonlinear version of the problem assuming that the thermal conductivity depends not only on the temperature but also on the pressure. Recent studies reveals that this situation can occur in practice. A theorem of existence and uniqueness is proved for this problem.

  13. Neural mechanisms of interstimulus interval-dependent responses in the primary auditory cortex of awake cats

    Directory of Open Access Journals (Sweden)

    Qin Ling

    2009-02-01

    recovery time course of excitability suggested the involvement of short-term plasticity. The observed phenomena were well captured by a single cell model which incorporated AMPA, GABAA, NMDA and GABAB receptors as well as short-term plasticity of thalamocortical synaptic connections. Conclusion Overall, it was suggested that ISI-dependent responses of the majority of AI neurons are configured through the temporal interplay of excitation and suppression (inhibition along with short-term plasticity.

  14. Data-driven inference of network connectivity for modeling the dynamics of neural codes in the insect antennal lobe

    Directory of Open Access Journals (Sweden)

    Eli eShlizerman

    2014-08-01

    Full Text Available The antennal lobe (AL, olfactory processing center in insects, is able to process stimuli into distinct neural activity patterns, called olfactory neural codes. To model their dynamics we perform multichannel recordings from the projection neurons in the AL driven by different odorants. We then derive a dynamic neuronal network from the electrophysiological data. The network consists of lateral-inhibitory neurons and excitatory neurons (modeled as firing-rate units, and is capable of producing unique olfactory neural codes for the tested odorants. To construct the network, we (i design a projection, an odor space, for the neural recording from the AL, which discriminates between distinct odorants trajectories (ii characterize scent recognition, i.e., decision-making based on olfactory signals and (iii infer the wiring of the neural circuit, the connectome of the AL. We show that the constructed model is consistent with biological observations, such as contrast enhancement and robustness to noise. The study suggests a data-driven approach to answer a key biological question in identifying how lateral inhibitory neurons can be wired to excitatory neurons to permit robust activity patterns.

  15. Data-driven inference of network connectivity for modeling the dynamics of neural codes in the insect antennal lobe.

    Science.gov (United States)

    Shlizerman, Eli; Riffell, Jeffrey A; Kutz, J Nathan

    2014-01-01

    The antennal lobe (AL), olfactory processing center in insects, is able to process stimuli into distinct neural activity patterns, called olfactory neural codes. To model their dynamics we perform multichannel recordings from the projection neurons in the AL driven by different odorants. We then derive a dynamic neuronal network from the electrophysiological data. The network consists of lateral-inhibitory neurons and excitatory neurons (modeled as firing-rate units), and is capable of producing unique olfactory neural codes for the tested odorants. To construct the network, we (1) design a projection, an odor space, for the neural recording from the AL, which discriminates between distinct odorants trajectories (2) characterize scent recognition, i.e., decision-making based on olfactory signals and (3) infer the wiring of the neural circuit, the connectome of the AL. We show that the constructed model is consistent with biological observations, such as contrast enhancement and robustness to noise. The study suggests a data-driven approach to answer a key biological question in identifying how lateral inhibitory neurons can be wired to excitatory neurons to permit robust activity patterns.

  16. Neural song preference during vocal learning in the zebra finch depends on age and state.

    Science.gov (United States)

    Nick, Teresa A; Konishi, Masakazu

    2005-02-05

    The zebra finch acquires its song by first memorizing a model song from a tutor and then matching its own vocalizations to the memory trace of the tutor song, called a template. Neural mechanisms underlying this process require a link between the neural memory trace and the premotor song circuitry, which drives singing. We now report that a premotor song nucleus responds more to the tutor song model than to every other stimulus examined, including the bird's own song (BOS). Neural tuning to the song model occurred only during waking and peaked during the template-matching period of development, when the vocal motor output is sculpted to match the tutor song. During the same developmental phase, the BOS was the most effective excitatory stimulus during sleep. The preference for BOS compared to tutor song inverted with sleep/wake state. Thus, song preference shifts with development and state. 2004 Wiley Periodicals, Inc.

  17. Neural correlates of effort-dependent and effort-independent cognitive fatigue components in patients with multiple sclerosis.

    Science.gov (United States)

    Spiteri, Stefan; Hassa, Thomas; Claros-Salinas, Dolores; Dettmers, Christian; Schoenfeld, Mircea Ariel

    2017-11-01

    Among patients with multiple sclerosis (MS), fatigue is the most commonly reported symptom. It can be subdivided into an effort-dependent (fatigability) and an effort-independent component (trait-fatigue). The objective was to disentangle activity changes associated with effort-independent "trait-fatigue" from those associated with effort-dependent fatigability in MS patients. This study employed behavioral measures and functional magnetic imaging to investigate neural changes in MS patients associated with fatigue. A total of 40 MS patients and 22 age-matched healthy controls performed in a fatigue-inducing N-back task. Effort-independent fatigue was assessed using the Fatigue Scale of Motor and Cognition (FSMC) questionnaire. Effort-independent fatigue was observed to be reflected by activity increases in fronto-striatal-subcortical networks primarily involved in the maintenance of homeostatic processes and in motor and cognitive control. Effort-dependent fatigue (fatigability) leads to activity decreases in attention-related cortical and subcortical networks. These results indicate that effort-independent (fatigue) and effort-dependent fatigue (fatigability) in MS patients have functionally related but fundamentally different neural correlates. Fatigue in MS as a general phenomenon is reflected by complex interactions of activity increases in control networks (effort-independent component) and activity reductions in executive networks (effort-dependent component) of brain areas.

  18. Neural network activation during a stop-signal task discriminates cocaine-dependent from non-drug-abusing men.

    Science.gov (United States)

    Elton, Amanda; Young, Jonathan; Smitherman, Sonet; Gross, Robin E; Mletzko, Tanja; Kilts, Clinton D

    2014-05-01

    Cocaine dependence is defined by a loss of inhibitory control over drug-use behaviors, mirrored by measurable impairments in laboratory tasks of inhibitory control. The current study tested the hypothesis that deficits in multiple subprocesses of behavioral control are associated with reliable neural-processing alterations that define cocaine addiction. While undergoing functional magnetic resonance imaging (fMRI), 38 cocaine-dependent men and 27 healthy control men performed a stop-signal task of motor inhibition. An independent component analysis on fMRI time courses identified task-related neural networks attributed to motor, visual, cognitive and affective processes. The statistical associations of these components with five different stop-signal task conditions were selected for use in a linear discriminant analysis to define a classifier for cocaine addiction from a subsample of 26 cocaine-dependent men and 18 controls. Leave-one-out cross-validation accurately classified 89.5% (39/44; chance accuracy = 26/44 = 59.1%) of subjects with 84.6% (22/26) sensitivity and 94.4% (17/18) specificity. The remaining 12 cocaine-dependent and 9 control men formed an independent test sample, for which accuracy of the classifier was 81.9% (17/21; chance accuracy = 12/21 = 57.1%) with 75% (9/12) sensitivity and 88.9% (8/9) specificity. The cocaine addiction classification score was significantly correlated with a measure of impulsiveness as well as the duration of cocaine use for cocaine-dependent men. The results of this study support the ability of a pattern of multiple neural network alterations associated with inhibitory motor control to define a binary classifier for cocaine addiction. © 2012 The Authors, Addiction Biology © 2012 Society for the Study of Addiction.

  19. Hippocampal Adult Neurogenesis Is Maintained by Neil3-Dependent Repair of Oxidative DNA Lesions in Neural Progenitor Cells

    Directory of Open Access Journals (Sweden)

    Christine Elisabeth Regnell

    2012-09-01

    Full Text Available Accumulation of oxidative DNA damage has been proposed as a potential cause of age-related cognitive decline. The major pathway for removal of oxidative DNA base lesions is base excision repair, which is initiated by DNA glycosylases. In mice, Neil3 is the main DNA glycosylase for repair of hydantoin lesions in single-stranded DNA of neural stem/progenitor cells, promoting neurogenesis. Adult neurogenesis is crucial for maintenance of hippocampus-dependent functions involved in behavior. Herein, behavioral studies reveal learning and memory deficits and reduced anxiety-like behavior in Neil3−/− mice. Neural stem/progenitor cells from aged Neil3−/− mice show impaired proliferative capacity and reduced DNA repair activity. Furthermore, hippocampal neurons in Neil3−/− mice display synaptic irregularities. It appears that Neil3-dependent repair of oxidative DNA damage in neural stem/progenitor cells is required for maintenance of adult neurogenesis to counteract the age-associated deterioration of cognitive performance.

  20. Multiple tooth-losses during development suppress age-dependent emergence of oscillatory neural activities in the oral somatosensory cortex.

    Science.gov (United States)

    Yoshimura, Hiroshi; Honjo, Makoto; Mashiyama, Yuichi; Kaneyama, Keiseki; Segami, Natsuki; Sato, Jun; Sugai, Tokio; Kato, Nobuo; Onoda, Norihiko

    2008-08-11

    Tooth and tooth-related organs play important roles in not only mastication, but also sensory perception in the oral region. In general, sensory neural inputs during the developmental period are required for the maturation of functions in the sensory cortex. However, whether maturations of oral somatosensory cortex (OSC) require certain levels of sensory input from oral regions has been unclear. The present study investigated the influence of multiple tooth-losses during the developmental period on age-dependent emergence of rhythmic activities of population neurons in the OSC. Low-frequency electrical stimulation was delivered to layer IV and field potentials were recorded from layer II/III in the OSC of rat brain slices. In control rats, N-methyl-d-aspartate (NMDA) receptor-dependent oscillation at 8-10 Hz appeared during postnatal weeks 2-3. In rats with extraction of multiple teeth at 17-18 days old, oscillation did not appear even at maturity, whereas in rats with multiple teeth extracted at 37-38 days old, oscillation appearances were maintained in maturity. Thus, emergence of oscillation in the OSC was suppressed by multiple tooth-losses during postnatal 2-3 weeks. These results suggest that sufficient neural inputs from the teeth and tooth-related organs during developmental periods are essential for maturation of neural functions in the OSC.

  1. Numerical bifurcation analysis of distance-dependent on-center off-surround shunting neural networks.

    NARCIS (Netherlands)

    Molenaar, P.C.M.; Raijmakers, M.E.J.; van der Maas, H.L.J.

    1996-01-01

    On-center off-surround shunting neural networks are often applied as models for content-addressable memory (CAM), the equilibria being the stored memories. One important demand of biological plausible CAMs is that they function under a broad range of parameters, since several parameters vary due to

  2. Distinct neural pathways mediate alpha7 nicotinic acetylcholine receptor-dependent activation of the forebrain

    DEFF Research Database (Denmark)

    Thomsen, Morten S; Hay-Schmidt, Anders; Hansen, Henrik H

    2010-01-01

    important for cognitive function. However, the neural substrates involved in these effects remain elusive. Here we identify cortically projecting cholinergic neurons in the horizontal limb of the diagonal band of Broca (HDB) in the basal forebrain (BF) as important targets for alpha(7) nAChR activation...

  3. Functional dissociations in top-down control dependent neural repetition priming.

    NARCIS (Netherlands)

    Klaver, P.; Schnaidt, M.; Fell, J.; Ruhlmann, J.; Elger, C.E.; Fernandez, G.

    2007-01-01

    Little is known about the neural mechanisms underlying top-down control of repetition priming. Here, we use functional brain imaging to investigate these mechanisms. Study and repetition tasks used a natural/man-made forced choice task. In the study phase subjects were required to respond to either

  4. Neural Differences in Bilingual Children's Arithmetic Processing Depending on Language of Instruction

    NARCIS (Netherlands)

    Mondt, K.; Struys, E.; Noort, M.W.M.L. van den; Balériaux, D.; Metens, T.; Paquier, P.; Craen, P. van de; Bosch, M.P.C.; Denolin, V.

    2011-01-01

    Many children in bilingual regions follow lessons in a language at school (school-language) that they hardly ever speak at home or in other informal settings. What are the neural effects of this phenomenon? This functional magnetic resonance imaging (fMRI) study investigates the effects of using

  5. Altered neural connectivity during response inhibition in adolescents with attention-deficit/hyperactivity disorder and their unaffected siblings

    Directory of Open Access Journals (Sweden)

    Daan van Rooij

    2015-01-01

    Discussion: Subjects with ADHD fail to integrate activation within the response inhibition network and to inhibit connectivity with task-irrelevant regions. Unaffected siblings show similar alterations only during failed stop trials, as well as unique suppression of motor areas, suggesting compensatory strategies. These findings support the role of altered functional connectivity in understanding the neurobiology and familial transmission of ADHD.

  6. Neural mechanism of activity spread in the cat motor cortex and its relation to the intrinsic connectivity

    DEFF Research Database (Denmark)

    Capaday, Charles; van Vreeswijk, Carl; Ethier, Christian

    2011-01-01

    NON TECHNICAL SUMMARY{NBSP}: The motor cortex (MCx) is an important brain region that initiates and controls voluntary movements. Neurons in MCx are anatomically connected by recurrent (feedback) networks. This connectivity pattern allows neurons to communicate reciprocally with each other potent...

  7. Richness in Functional Connectivity Depends on the Neuronal Integrity within the Posterior Cingulate Cortex

    NARCIS (Netherlands)

    Lord, Anton R; Li, Meng; Demenescu, Liliana R; Van der Meer, J.; Borchardt, Viola; Krause, Anna Linda; Heinze, Hans-Jochen; Breakspear, Michael; Walter, Martin

    2017-01-01

    The brain's connectivity skeleton-a rich club of strongly interconnected members-was initially shown to exist in human structural networks, but recent evidence suggests a functional counterpart. This rich club typically includes key regions (or hubs) from multiple canonical networks, reducing the

  8. Experience-dependent rewiring of specific inhibitory connections in adult neocortex.

    Directory of Open Access Journals (Sweden)

    Dennis Kätzel

    2014-02-01

    Full Text Available Although neocortical connectivity is remarkably stereotyped, the abundance of some wiring motifs varies greatly between cortical areas. To examine if regional wiring differences represent functional adaptations, we have used optogenetic raster stimulation to map the laminar distribution of GABAergic interneurons providing inhibition to pyramidal cells in layer 2/3 (L2/3 of adult mouse barrel cortex during sensory deprivation and recovery. Whisker trimming caused large, motif-specific changes in inhibitory synaptic connectivity: ascending inhibition from deep layers 4 and 5 was attenuated to 20%-45% of baseline, whereas inhibition from superficial layers remained stable (L2/3 or increased moderately (L1. The principal mechanism of deprivation-induced plasticity was motif-specific changes in inhibitory-to-excitatory connection probabilities; the strengths of extant connections were left unaltered. Whisker regrowth restored the original balance of inhibition from deep and superficial layers. Targeted, reversible modifications of specific inhibitory wiring motifs thus contribute to the adaptive remodeling of cortical circuits.

  9. Which Bulb Is Brighter? It Depends on Connection! Strategies for Illuminating Electrical Concepts Using Light Bulbs

    Science.gov (United States)

    Wong, Darren; Lee, Paul; Foong, See Kit

    2017-01-01

    In this paper, we examined teachers' understanding of electrical concepts such as power, current and potential difference based on how these concepts were applied to understand the relative brightness seen in bulbs of different wattage under different connections--series or parallel. From the responses of teachers to a concept question, we…

  10. Time-dependence of graph theory metrics in functional connectivity analysis.

    Science.gov (United States)

    Chiang, Sharon; Cassese, Alberto; Guindani, Michele; Vannucci, Marina; Yeh, Hsiang J; Haneef, Zulfi; Stern, John M

    2016-01-15

    Brain graphs provide a useful way to computationally model the network structure of the connectome, and this has led to increasing interest in the use of graph theory to quantitate and investigate the topological characteristics of the healthy brain and brain disorders on the network level. The majority of graph theory investigations of functional connectivity have relied on the assumption of temporal stationarity. However, recent evidence increasingly suggests that functional connectivity fluctuates over the length of the scan. In this study, we investigate the stationarity of brain network topology using a Bayesian hidden Markov model (HMM) approach that estimates the dynamic structure of graph theoretical measures of whole-brain functional connectivity. In addition to extracting the stationary distribution and transition probabilities of commonly employed graph theory measures, we propose two estimators of temporal stationarity: the S-index and N-index. These indexes can be used to quantify different aspects of the temporal stationarity of graph theory measures. We apply the method and proposed estimators to resting-state functional MRI data from healthy controls and patients with temporal lobe epilepsy. Our analysis shows that several graph theory measures, including small-world index, global integration measures, and betweenness centrality, may exhibit greater stationarity over time and therefore be more robust. Additionally, we demonstrate that accounting for subject-level differences in the level of temporal stationarity of network topology may increase discriminatory power in discriminating between disease states. Our results confirm and extend findings from other studies regarding the dynamic nature of functional connectivity, and suggest that using statistical models which explicitly account for the dynamic nature of functional connectivity in graph theory analyses may improve the sensitivity of investigations and consistency across investigations

  11. Memristor-based neural networks

    Science.gov (United States)

    Thomas, Andy

    2013-03-01

    The synapse is a crucial element in biological neural networks, but a simple electronic equivalent has been absent. This complicates the development of hardware that imitates biological architectures in the nervous system. Now, the recent progress in the experimental realization of memristive devices has renewed interest in artificial neural networks. The resistance of a memristive system depends on its past states and exactly this functionality can be used to mimic the synaptic connections in a (human) brain. After a short introduction to memristors, we present and explain the relevant mechanisms in a biological neural network, such as long-term potentiation and spike time-dependent plasticity, and determine the minimal requirements for an artificial neural network. We review the implementations of these processes using basic electric circuits and more complex mechanisms that either imitate biological systems or could act as a model system for them.

  12. 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.

    2015-01-01

    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. PMID:25673781

  13. The neural basis of trait self-esteem revealed by the amplitude of low-frequency fluctuations and resting state functional connectivity.

    Science.gov (United States)

    Pan, Weigang; Liu, Congcong; Yang, Qian; Gu, Yan; Yin, Shouhang; Chen, Antao

    2016-03-01

    Self-esteem is an affective, self-evaluation of oneself and has a significant effect on mental and behavioral health. Although research has focused on the neural substrates of self-esteem, little is known about the spontaneous brain activity that is associated with trait self-esteem (TSE) during the resting state. In this study, we used the resting-state functional magnetic resonance imaging (fMRI) signal of the amplitude of low-frequency fluctuations (ALFFs) and resting state functional connectivity (RSFC) to identify TSE-related regions and networks. We found that a higher level of TSE was associated with higher ALFFs in the left ventral medial prefrontal cortex (vmPFC) and lower ALFFs in the left cuneus/lingual gyrus and right lingual gyrus. RSFC analyses revealed that the strengths of functional connectivity between the left vmPFC and bilateral hippocampus were positively correlated with TSE; however, the connections between the left vmPFC and right inferior frontal gyrus and posterior superior temporal sulcus were negatively associated with TSE. Furthermore, the strengths of functional connectivity between the left cuneus/lingual gyrus and right dorsolateral prefrontal cortex and anterior cingulate cortex were positively related to TSE. These findings indicate that TSE is linked to core regions in the default mode network and social cognition network, which is involved in self-referential processing, autobiographical memory and social cognition. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  14. Relative Composition of Fibrous Connective and Fatty/Glandular Tissue in Connective Tissue Grafts Depends on the Harvesting Technique but not the Donor Site of the Hard Palate.

    Science.gov (United States)

    Bertl, Kristina; Pifl, Markus; Hirtler, Lena; Rendl, Barbara; Nürnberger, Sylvia; Stavropoulos, Andreas; Ulm, Christian

    2015-12-01

    Whether the composition of palatal connective tissue grafts (CTGs) varies depending on donor site or harvesting technique in terms of relative amounts of fibrous connective tissue (CT) and fatty/glandular tissue (FGT) is currently unknown and is histologically assessed in the present study. In 10 fresh human cadavers, tissue samples were harvested in the anterior and posterior palate and in areas close to (marginal) and distant from (apical) the mucosal margin. Mucosal thickness, lamina propria thickness (defined as the extent of subepithelial portion of the biopsy containing ≤25% or ≤50% FGT), and proportions of CT and FGT were semi-automatically estimated for the entire mucosa and for CTGs virtually harvested by split-flap (SF) preparation minimum 1 mm deep or after deepithelialization (DE). Palatal mucosal thickness, ranging from 2.35 to 6.89 mm, and histologic composition showed high interindividual variability. Lamina propria thickness (P >0.21) and proportions of CT (P = 0.48) and FGT (P = 0.15) did not differ significantly among the donor sites (anterior, posterior, marginal, apical). However, thicker palatal tissue was associated with higher FGT content (P tissue composition in the hard palate, DE-harvested CTG contains much larger amounts of CT and much lower amounts of FGT than SF-harvested CTG, irrespective of the harvesting site.

  15. Altered Effective Connectivity of Hippocampus-Dependent Episodic Memory Network in mTBI Survivors

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    Hao Yan

    2016-01-01

    Full Text Available Traumatic brain injuries (TBIs are generally recognized to affect episodic memory. However, less is known regarding how external force altered the way functionally connected brain structures of the episodic memory system interact. To address this issue, we adopted an effective connectivity based analysis, namely, multivariate Granger causality approach, to explore causal interactions within the brain network of interest. Results presented that TBI induced increased bilateral and decreased ipsilateral effective connectivity in the episodic memory network in comparison with that of normal controls. Moreover, the left anterior superior temporal gyrus (aSTG, the concept forming hub, left hippocampus (the personal experience binding hub, and left parahippocampal gyrus (the contextual association hub were no longer network hubs in TBI survivors, who compensated for hippocampal deficits by relying more on the right hippocampus (underlying perceptual memory and the right medial frontal gyrus (MeFG in the anterior prefrontal cortex (PFC. We postulated that the overrecruitment of the right anterior PFC caused dysfunction of the strategic component of episodic memory, which caused deteriorating episodic memory in mTBI survivors. Our findings also suggested that the pattern of brain network changes in TBI survivors presented similar functional consequences to normal aging.

  16. Neural substrates involved in anger induced by audio-visual film clips among patients with alcohol dependency.

    Science.gov (United States)

    Park, Mi-Sook; Lee, Bae Hwan; Sohn, Jin-Hun

    2016-07-08

    Very little is known about the neural circuitry underlying anger processing among alcoholics. The purpose of this study was to examine the altered brain activity of alcoholic individuals during transient anger emotion. Using functional magnetic resonance imaging (fMRI), 18 male patients diagnosed with alcohol dependence in an inpatient alcohol treatment facility and 16 social drinkers with similar demographics were scanned during the viewing of anger-provoking film clips. While there was no significant difference in the level of experienced anger between alcohol-dependent patients and non-alcoholic controls, significantly greater activation was observed in the bilateral dorsal anterior cingulate cortex (dACC) and the right precentral gyrus among alcoholic patients compared to the normal controls. In summary, specific brain regions were identified that are associated with anger among patients with alcohol dependency.

  17. Experience-dependent neural plasticity, learning, and memory in the era of epitranscriptomics.

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    Leighton, L J; Ke, K; Zajaczkowski, E L; Edmunds, J; Spitale, R C; Bredy, T W

    2017-09-19

    In this short review, we highlight recent findings in the emerging field of epitranscriptomic mechanisms and discuss their potential role in neural plasticity, learning and memory. These include the influence of RNA modifications on activity-induced RNA structure states, RNA editing and RNA localization, and how qualitative state changes in RNA increase the functional diversity and information-carrying capacity of RNA molecules. We predict that RNA modifications may be just as important for synaptic plasticity and memory as quantitative changes in transcript and protein abundance, but with the added advantage of not being required to signal back to the nucleus, and therefore better suited to be coordinated with the temporal dynamics of learning. © 2017 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

  18. Changes in the spinal neural circuits are dependent on the movement speed of the visuomotor task

    Directory of Open Access Journals (Sweden)

    Shinji eKubota

    2015-12-01

    Full Text Available Previous studies have shown that spinal neural circuits are modulated by motor skill training. However, the effects of task movement speed on changes in spinal neural circuits have not been clarified. The aim of this research was to investigate whether spinal neural circuits were affected by task movement speed. Thirty-eight healthy subjects participated in this study. In experiment 1, the effects of task movement speed on the spinal neural circuits were examined. 18 subjects performed a visuomotor task involving ankle muscle slow (9 subjects or fast (9 subjects movement speed. Another 9 subjects performed a non-visuomotor task (controls in fast movement speed. The motor task training lasted for 20 min. The amounts of D1 inhibition and reciprocal Ia inhibition were measured using H-relfex condition-test paradigm and recorded before, and at 5, 15, and 30 min after the training session. In experiment 2, using transcranial magnetic stimulation (TMS, the effects of corticospinal descending inputs on the presynaptic inhibitory pathway were examined before and after performing either a visuomotor (8 subjects or a control task (8 subjects. All measurements were taken under resting conditions. The amount of D1 inhibition increased after the visuomotor task irrespective of movement speed (P < 0.01. The amount of reciprocal Ia inhibition increased with fast movement speed conditioning (P < 0.01, but was unchanged by slow movement speed conditioning. These changes lasted up to 15 min in D1 inhibition and 5 min in reciprocal Ia inhibition after the training session. The control task did not induce changes in D1 inhibition and reciprocal Ia inhibition. The TMS conditioned inhibitory effects of presynaptic inhibitory pathways decreased following visuomotor tasks (P < 0.01. The size of test H-reflex was almost the same size throughout experiments. The results suggest that supraspinal descending inputs for controlling joint movement are responsible for changes

  19. Dopamine-dependent changes in the functional connectivity between basal ganglia and cerebral cortex in humans

    NARCIS (Netherlands)

    Williams, D; Tijssen, M; van Bruggen, G; Bosch, A; Insola, A; Di Lazzaro, V; Mazzone, P; Oliviero, A; Quartarone, A; Speelman, H; Brown, P

    2002-01-01

    We test the hypothesis that interaction between the human basal ganglia and cerebral cortex involves activity in multiple functional circuits characterized by their frequency of oscillation, phase characteristics, dopamine dependency and topography. To this end we took recordings from

  20. Acute D3 Antagonist GSK598809 Selectively Enhances Neural Response During Monetary Reward Anticipation in Drug and Alcohol Dependence.

    Science.gov (United States)

    Murphy, Anna; Nestor, Liam J; McGonigle, John; Paterson, Louise; Boyapati, Venkataramana; Ersche, Karen D; Flechais, Remy; Kuchibatla, Shankar; Metastasio, Antonio; Orban, Csaba; Passetti, Filippo; Reed, Laurence; Smith, Dana; Suckling, John; Taylor, Eleanor; Robbins, Trevor W; Lingford-Hughes, Anne; Nutt, David J; Deakin, John Fw; Elliott, Rebecca

    2017-04-01

    Evidence suggests that disturbances in neurobiological mechanisms of reward and inhibitory control maintain addiction and provoke relapse during abstinence. Abnormalities within the dopamine system may contribute to these disturbances and pharmacologically targeting the D3 dopamine receptor (DRD3) is therefore of significant clinical interest. We used functional magnetic resonance imaging to investigate the acute effects of the DRD3 antagonist GSK598809 on anticipatory reward processing, using the monetary incentive delay task (MIDT), and response inhibition using the Go/No-Go task (GNGT). A double-blind, placebo-controlled, crossover design approach was used in abstinent alcohol dependent, abstinent poly-drug dependent and healthy control volunteers. For the MIDT, there was evidence of blunted ventral striatal response to reward in the poly-drug-dependent group under placebo. GSK598809 normalized ventral striatal reward response and enhanced response in the DRD3-rich regions of the ventral pallidum and substantia nigra. Exploratory investigations suggested that the effects of GSK598809 were mainly driven by those with primary dependence on alcohol but not on opiates. Taken together, these findings suggest that GSK598809 may remediate reward deficits in substance dependence. For the GNGT, enhanced response in the inferior frontal cortex of the poly-drug group was found. However, there were no effects of GSK598809 on the neural network underlying response inhibition nor were there any behavioral drug effects on response inhibition. GSK598809 modulated the neural network underlying reward anticipation but not response inhibition, suggesting that DRD3 antagonists may restore reward deficits in addiction.

  1. The neural code for auditory space depends on sound frequency and head size in an optimal manner.

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    Nicol S Harper

    Full Text Available A major cue to the location of a sound source is the interaural time difference (ITD-the difference in sound arrival time at the two ears. The neural representation of this auditory cue is unresolved. The classic model of ITD coding, dominant for a half-century, posits that the distribution of best ITDs (the ITD evoking a neuron's maximal response is unimodal and largely within the range of ITDs permitted by head-size. This is often interpreted as a place code for source location. An alternative model, based on neurophysiology in small mammals, posits a bimodal distribution of best ITDs with exquisite sensitivity to ITDs generated by means of relative firing rates between the distributions. Recently, an optimal-coding model was proposed, unifying the disparate features of these two models under the framework of efficient coding by neural populations. The optimal-coding model predicts that distributions of best ITDs depend on head size and sound frequency: for high frequencies and large heads it resembles the classic model, for low frequencies and small head sizes it resembles the bimodal model. The optimal-coding model makes key, yet unobserved, predictions: for many species, including humans, both forms of neural representation are employed, depending on sound frequency. Furthermore, novel representations are predicted for intermediate frequencies. Here, we examine these predictions in neurophysiological data from five mammalian species: macaque, guinea pig, cat, gerbil and kangaroo rat. We present the first evidence supporting these untested predictions, and demonstrate that different representations appear to be employed at different sound frequencies in the same species.

  2. Design porosity osmotic tablet for delivering low and pH-dependent soluble drug using an artificial neural network.

    Science.gov (United States)

    Patel, Alpesh; Mehta, Tarak; Patel, Mukesh; Patel, Kanu; Patel, Natvarlal

    2012-09-01

    In this paper formulation of porosity osmotic tablet containing isradipine (model drug) as a low and pH dependent solubility was optimized based on the simultaneous optimization technique in which an artificial neural network (ANN) was incorporated. Nonlinear relationships between the causal factors and the response variables were represented well with the response surface predicted by ANN. Three causal factors, i.e., drug, osmotic pressure promoting agent rate (Lactose: Fructose), PEG400 content in coating solution and coating weight, were evaluated based on their effects on drug release rate. In vitro dissolution profile time profiles at four different sampling times (1, 12, 20 and 24h) were chosen as output variables. Commercially available STATISTICA 7 (Stat soft, USA) was used throughout the study. The optimize values for the factors X1-X3 were 1.25:0.75, 22% and 2.5% respectively. Calculated difference (f1 = 11.19) and similarity (f2 = 70.07) factors indicate that there is no difference between predicted and experimental observed drug release profile. Artificial neural network technique can be particularly suitable in the pharmaceutical technology of controlled release dosage forms where systems are complex and nonlinear relationships between independent and dependent variables often exist.

  3. Temperature-dependent magnetism in artificial honeycomb lattice of connected elements

    Science.gov (United States)

    Summers, B.; Debeer-Schmitt, L.; Dahal, A.; Glavic, A.; Kampschroeder, P.; Gunasekera, J.; Singh, D. K.

    2018-01-01

    Artificial magnetic honeycomb lattices are expected to exhibit a broad and tunable range of novel magnetic phenomena that would be difficult to achieve in natural materials, such as long-range spin ice, entropy-driven magnetic charge-ordered states, and spin order due to the spin chirality. Eventually, the spin correlation is expected to develop into a unique spin-solid-state-density ground state, manifested by the distribution of the pairs of vortex states of opposite chirality. Here we report the creation of an artificial permalloy honeycomb lattice of ultrasmall connecting bonds, with a typical size of ≃12 nm. Detailed magnetic and neutron-scattering measurements on the newly fabricated honeycomb lattice demonstrate the evolution of magnetic correlation as a function of temperature. At low enough temperature, neutron-scattering measurements and micromagnetic simulation suggest the development of a loop state of vortex configuration in this system.

  4. Dopaminergic drug effects during reversal learning depend on anatomical connections between the orbitofrontal cortex and the amygdala.

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    Marieke E. van der Schaaf

    2013-08-01

    Full Text Available Dopamine in the striatum is known to be important for reversal learning. However, the striatum does not act in isolation and reversal learning is also well accepted to depend on the orbitofrontal cortex (OFC and the amygdala. Here we assessed whether dopaminergic drug effects on human striatal BOLD signalling during reversal learning is associated with anatomical connectivity in an orbitofrontal-limbic-striatal network, as measured with diffusion tensor imaging. By using a fibre-based approach, we demonstrate that dopaminergic drug effects on striatal BOLD signal varied as a function of fractional anisotropy (FA in a pathway connecting the OFC with the amygdala. Moreover, our experimental design allowed us to establish that these white-matter dependent drug effects were mediated via D2 receptors. Thus, white matter dependent effects of the D2 receptor agonist bromocriptine on striatal BOLD signal were abolished by co-administration with the D2 receptor antagonist sulpiride. These data provide fundamental insight into the mechanism of action of dopaminergic drug effects during reversal learning. In addition, they may have important clinical implications by suggesting that white matter integrity can help predict dopaminergic drug effects on brain function, ultimately contributing to individual tailoring of dopaminergic drug treatment strategies in psychiatry.

  5. Brightness in human rod vision depends on slow neural adaptation to quantum statistics of light.

    Science.gov (United States)

    Rudd, Michael E; Rieke, Fred

    2016-11-01

    In human rod-mediated vision, threshold for small, brief flashes rises in proportion to the square root of adapting luminance at all but the lowest and highest adapting intensities. A classical signal detection theory from Rose (1942, 1948) and de Vries (1943) attributed this rise to the perceptual masking of weak flashes by Poisson fluctuations in photon absorptions from the adapting field. However, previous work by Brown and Rudd (1998) demonstrated that the square-root law also holds for suprathreshold brightness judgments, a finding that supports an alternative explanation of the square-root sensitivity changes as a consequence of physiological adaptation (i.e., neural gain control). Here, we employ a dichoptic matching technique to investigate the properties of this brightness gain control. We show that the brightness gain control: 1) affects the brightness of high-intensity suprathreshold flashes for which assumptions of the de Vries-Rose theory are strongly violated; 2) exhibits a long time course of 100-200 s; and 3) is subject to modulation by temporal contrast noise when the mean adapting luminance is held constant. These findings are consistent with the hypothesis that the square-root law results from a slow neural adaptation to statistical noise in the rod pool. We suggest that such adaptation may function to reduce the probability of spurious ganglion cell spiking activity due to photon fluctuation noise as the ambient illumination level is increased.

  6. Neural response in obsessive-compulsive washers depends on individual fit of triggers

    Directory of Open Access Journals (Sweden)

    Ali eBaioui

    2013-04-01

    Full Text Available BackgroundPatients with obsessive-compulsive disorder (OCD have highly idiosyncratic triggers. To fully understand which role this idiosyncrasy plays in the neurobiological mechanisms behind OCD, it is necessary to elucidate the impact of individualization regarding the applied investigation methods.This functional magnetic resonance imaging (fMRI study explores the neural correlates of contamination/washing-related OCD with a highly individualized symptom provocation paradigm. Additionally, it is the first study to directly compare individualized and standardized symptom provocation. MethodsNineteen patients with washing compulsions created individual OCD hierarchies, which later served as instructions to photograph their own individualized stimulus sets. The patients and 19 case-by-case matched healthy controls participated in a symptom provocation fMRI experiment with individualized and standardized stimulus sets created for each patient. ResultsOCD patients compared to healthy controls displayed stronger activation in the basal ganglia (nucleus accumbens, nucleus caudatus, pallidum for individualized symptom provocation. Using standardized symptom provocation, this group comparison led to stronger activation in the nucleus caudatus. The direct comparison of between-group effects for both symptom provocation approaches revealed stronger activation of the orbitofronto-striatal network for individualized symptom provocation.ConclusionsThe present study provides insight into the differential impact of individualized and standardized symptom provocation on the orbitofronto-striatal network of OCD washers. Behavioral and neural responses imply a higher symptom-specificity of individualized symptom provocation.

  7. Neural mechanisms underlying contextual dependency of subjective values: converging evidence from monkeys and humans.

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    Abitbol, Raphaëlle; Lebreton, Maël; Hollard, Guillaume; Richmond, Barry J; Bouret, Sébastien; Pessiglione, Mathias

    2015-02-04

    A major challenge for decision theory is to account for the instability of expressed preferences across time and context. Such variability could arise from specific properties of the brain system used to assign subjective values. Growing evidence has identified the ventromedial prefrontal cortex (VMPFC) as a key node of the human brain valuation system. Here, we first replicate this observation with an fMRI study in humans showing that subjective values of painting pictures, as expressed in explicit pleasantness ratings, are specifically encoded in the VMPFC. We then establish a bridge with monkey electrophysiology, by comparing single-unit activity evoked by visual cues between the VMPFC and the orbitofrontal cortex. At the neural population level, expected reward magnitude was only encoded in the VMPFC, which also reflected subjective cue values, as expressed in Pavlovian appetitive responses. In addition, we demonstrate in both species that the additive effect of prestimulus activity on evoked activity has a significant impact on subjective values. In monkeys, the factor dominating prestimulus VMPFC activity was trial number, which likely indexed variations in internal dispositions related to fatigue or satiety. In humans, prestimulus VMPFC activity was externally manipulated through changes in the musical context, which induced a systematic bias in subjective values. Thus, the apparent stochasticity of preferences might relate to the VMPFC automatically aggregating the values of contextual features, which would bias subsequent valuation because of temporal autocorrelation in neural activity. Copyright © 2015 the authors 0270-6474/15/352308-13$15.00/0.

  8. Neural basis of stimulus-angle-dependent motor control of wind-elicited walking behavior in the cricket Gryllus bimaculatus.

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    Momoko Oe

    Full Text Available Crickets exhibit oriented walking behavior in response to air-current stimuli. Because crickets move in the opposite direction from the stimulus source, this behavior is considered to represent 'escape behavior' from an approaching predator. However, details of the stimulus-angle-dependent control of locomotion during the immediate phase, and the neural basis underlying the directional motor control of this behavior remain unclear. In this study, we used a spherical-treadmill system to measure locomotory parameters including trajectory, turn angle and velocity during the immediate phase of responses to air-puff stimuli applied from various angles. Both walking direction and turn angle were correlated with stimulus angle, but their relationships followed different rules. A shorter stimulus also induced directionally-controlled walking, but reduced the yaw rotation in stimulus-angle-dependent turning. These results suggest that neural control of the turn angle requires different sensory information than that required for oriented walking. Hemi-severance of the ventral nerve cords containing descending axons from the cephalic to the prothoracic ganglion abolished stimulus-angle-dependent control, indicating that this control required descending signals from the brain. Furthermore, we selectively ablated identified ascending giant interneurons (GIs in vivo to examine their functional roles in wind-elicited walking. Ablation of GI8-1 diminished control of the turn angle and decreased walking distance in the initial response. Meanwhile, GI9-1b ablation had no discernible effect on stimulus-angle-dependent control or walking distance, but delayed the reaction time. These results suggest that the ascending signals conveyed by GI8-1 are required for turn-angle control and maintenance of walking behavior, and that GI9-1b is responsible for rapid initiation of walking. It is possible that individual types of GIs separately supply the sensory signals

  9. Reduced neural connectivity but increased task-related activity during working memory in de novo Parkinson patients

    NARCIS (Netherlands)

    Trujillo, James P; Gerrits, Niels J H M; Veltman, Dick J; Berendse, Henk W; van der Werf, Ysbrand D; van den Heuvel, Odile A

    OBJECTIVE: Patients with Parkinson's disease (PD) often suffer from impairments in executive functions, such as working memory deficits. It is widely held that dopamine depletion in the striatum contributes to these impairments through decreased activity and connectivity between task-related brain

  10. Launch light dependency of step-index multimode fiber connections analyzed by modal power distribution using encircled angular flux.

    Science.gov (United States)

    Kobayashi, Shigeru; Yasukawa, Manabu; Sugihara, Okihiro

    2017-02-01

    The propagating modal power distribution (MPD) of step-index multimode fibers (SI-MMFs), which strongly influences the performance of systems and components composed of these fibers, has not often been discussed, because, until recently, there has been no definition to show the MPD. Encircled angular flux (EAF) is a newly developed metric for defining the MPD in step-index multimode waveguides including fibers standardized by the International Electrotechnical Commission. Using the combined analysis of EAF and insertion loss, we studied the launch light dependency of SI-MMF connections. Our studies contribute to enhancing both current applications and future higher data rate communications using SI-MMFs.

  11. The Circadian Clock Gene Period1 Connects the Molecular Clock to Neural Activity in the Suprachiasmatic Nucleus.

    Science.gov (United States)

    Kudo, Takashi; Block, Gene D; Colwell, Christopher S

    2015-01-01

    The neural activity patterns of suprachiasmatic nucleus (SCN) neurons are dynamically regulated throughout the circadian cycle with highest levels of spontaneous action potentials during the day. These rhythms in electrical activity are critical for the function of the circadian timing system and yet the mechanisms by which the molecular clockwork drives changes in the membrane are not well understood. In this study, we sought to examine how the clock gene Period1 (Per1) regulates the electrical activity in the mouse SCN by transiently and selectively decreasing levels of PER1 through use of an antisense oligodeoxynucleotide. We found that this treatment effectively reduced SCN neural activity. Direct current injection to restore the normal membrane potential partially, but not completely, returned firing rate to normal levels. The antisense treatment also reduced baseline [Ca(2+)]i levels as measured by Fura2 imaging technique. Whole cell patch clamp recording techniques were used to examine which specific potassium currents were altered by the treatment. These recordings revealed that the large conductance [Ca(2+)]i-activated potassium currents were reduced in antisense-treated neurons and that blocking this current mimicked the effects of the anti-sense on SCN firing rate. These results indicate that the circadian clock gene Per1 alters firing rate in SCN neurons and raise the possibility that the large conductance [Ca(2+)]i-activated channel is one of the targets. © The Author(s) 2015.

  12. Antagonistic Serotonergic and Octopaminergic Neural Circuits Mediate Food-Dependent Locomotory Behavior in Caenorhabditis elegans.

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    Churgin, Matthew A; McCloskey, Richard J; Peters, Emily; Fang-Yen, Christopher

    2017-08-16

    Biogenic amines are conserved signaling molecules that link food cues to behavior and metabolism in a wide variety of organisms. In the nematode Caenorhabditis elegans, the biogenic amines serotonin (5-HT) and octopamine regulate a number of food-related behaviors. Using a novel method for long-term quantitative behavioral imaging, we show that 5-HT and octopamine jointly influence locomotor activity and quiescence in feeding and fasting hermaphrodites, and we define the neural circuits through which this modulation occurs. We show that 5-HT produced by the ADF neurons acts via the SER-5 receptor in muscles and neurons to suppress quiescent behavior and promote roaming in fasting worms, whereas 5-HT produced by the NSM neurons acts on the MOD-1 receptor in AIY neurons to promote low-amplitude locomotor behavior characteristic of well fed animals. Octopamine, produced by the RIC neurons, acts via SER-3 and SER-6 receptors in SIA neurons to promote roaming behaviors characteristic of fasting animals. We find that 5-HT signaling is required for animals to assume food-appropriate behavior, whereas octopamine signaling is required for animals to assume fasting-appropriate behavior. The requirement for both neurotransmitters in both the feeding and fasting states enables increased behavioral adaptability. Our results define the molecular and neural pathways through which parallel biogenic amine signaling tunes behavior appropriately to nutrient conditions.SIGNIFICANCE STATEMENT Animals adjust behavior in response to environmental changes, such as fluctuations in food abundance, to maximize survival and reproduction. Biogenic amines, such as like serotonin, are conserved neurotransmitters that regulate behavior and metabolism in relation to energy status. Disruptions of biogenic amine signaling contribute to human neurological diseases of mood, appetite, and movement. In this study, we investigated the roles of the biogenic amines serotonin and octopamine in regulating

  13. Neural Architecture of Hunger-Dependent Multisensory Decision Making in C. elegans.

    Science.gov (United States)

    Ghosh, D Dipon; Sanders, Tom; Hong, Soonwook; McCurdy, Li Yan; Chase, Daniel L; Cohen, Netta; Koelle, Michael R; Nitabach, Michael N

    2016-12-07

    Little is known about how animals integrate multiple sensory inputs in natural environments to balance avoidance of danger with approach to things of value. Furthermore, the mechanistic link between internal physiological state and threat-reward decision making remains poorly understood. Here we confronted C. elegans worms with the decision whether to cross a hyperosmotic barrier presenting the threat of desiccation to reach a source of food odor. We identified a specific interneuron that controls this decision via top-down extrasynaptic aminergic potentiation of the primary osmosensory neurons to increase their sensitivity to the barrier. We also establish that food deprivation increases the worm's willingness to cross the dangerous barrier by suppressing this pathway. These studies reveal a potentially general neural circuit architecture for internal state control of threat-reward decision making. Copyright © 2016 Elsevier Inc. All rights reserved.

  14. Neural evidence for description dependent reward processing in the framing effect

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    Rongjun eYu

    2014-03-01

    Full Text Available Human decision making can be influenced by emotionally valenced contexts, known as the framing effect. We used event-related brain potentials to investigate how framing influences the encoding of reward. We found that the feedback related negativity (FRN, which indexes the worse than expected negative prediction error in the anterior cingulate cortex, was more negative for the negative frame than for the positive frame in the win domain. Consistent with previous findings that the FRN is not sensitive to better than expected positive prediction error, the FRN did not differentiate the positive and negative frame in the loss domain. Our results provide neural evidence that the description invariance principle which states that reward representation and decision making are not influenced by how options are presented is violated in the framing effect.

  15. Multisensory Bayesian Inference Depends on Synapse Maturation during Training: Theoretical Analysis and Neural Modeling Implementation.

    Science.gov (United States)

    Ursino, Mauro; Cuppini, Cristiano; Magosso, Elisa

    2017-03-01

    Recent theoretical and experimental studies suggest that in multisensory conditions, the brain performs a near-optimal Bayesian estimate of external events, giving more weight to the more reliable stimuli. However, the neural mechanisms responsible for this behavior, and its progressive maturation in a multisensory environment, are still insufficiently understood. The aim of this letter is to analyze this problem with a neural network model of audiovisual integration, based on probabilistic population coding-the idea that a population of neurons can encode probability functions to perform Bayesian inference. The model consists of two chains of unisensory neurons (auditory and visual) topologically organized. They receive the corresponding input through a plastic receptive field and reciprocally exchange plastic cross-modal synapses, which encode the spatial co-occurrence of visual-auditory inputs. A third chain of multisensory neurons performs a simple sum of auditory and visual excitations. The work includes a theoretical part and a computer simulation study. We show how a simple rule for synapse learning (consisting of Hebbian reinforcement and a decay term) can be used during training to shrink the receptive fields and encode the unisensory likelihood functions. Hence, after training, each unisensory area realizes a maximum likelihood estimate of stimulus position (auditory or visual). In cross-modal conditions, the same learning rule can encode information on prior probability into the cross-modal synapses. Computer simulations confirm the theoretical results and show that the proposed network can realize a maximum likelihood estimate of auditory (or visual) positions in unimodal conditions and a Bayesian estimate, with moderate deviations from optimality, in cross-modal conditions. Furthermore, the model explains the ventriloquism illusion and, looking at the activity in the multimodal neurons, explains the automatic reweighting of auditory and visual inputs

  16. Uncertainty-Dependent Extinction of Fear Memory in an Amygdala-mPFC Neural Circuit Model

    Science.gov (United States)

    Li, Yuzhe; Nakae, Ken; Ishii, Shin; Naoki, Honda

    2016-01-01

    Uncertainty of fear conditioning is crucial for the acquisition and extinction of fear memory. Fear memory acquired through partial pairings of a conditioned stimulus (CS) and an unconditioned stimulus (US) is more resistant to extinction than that acquired through full pairings; this effect is known as the partial reinforcement extinction effect (PREE). Although the PREE has been explained by psychological theories, the neural mechanisms underlying the PREE remain largely unclear. Here, we developed a neural circuit model based on three distinct types of neurons (fear, persistent and extinction neurons) in the amygdala and medial prefrontal cortex (mPFC). In the model, the fear, persistent and extinction neurons encode predictions of net severity, of unconditioned stimulus (US) intensity, and of net safety, respectively. Our simulation successfully reproduces the PREE. We revealed that unpredictability of the US during extinction was represented by the combined responses of the three types of neurons, which are critical for the PREE. In addition, we extended the model to include amygdala subregions and the mPFC to address a recent finding that the ventral mPFC (vmPFC) is required for consolidating extinction memory but not for memory retrieval. Furthermore, model simulations led us to propose a novel procedure to enhance extinction learning through re-conditioning with a stronger US; strengthened fear memory up-regulates the extinction neuron, which, in turn, further inhibits the fear neuron during re-extinction. Thus, our models increased the understanding of the functional roles of the amygdala and vmPFC in the processing of uncertainty in fear conditioning and extinction. PMID:27617747

  17. Effects of Modafinil on Neural Correlates of Response Inhibition in Alcohol-Dependent Patients

    NARCIS (Netherlands)

    Schmaal, L.; Joos, L.; Koeleman, M.; Veltman, D.J.; van den Brink, W.; Goudriaan, A.E.

    2013-01-01

    Background: Impaired response inhibition is a key feature of patients with alcohol dependence. Improving impulse control is a promising target for the treatment of alcohol dependence. The pharmacologic agent modafinil enhances cognitive control functions in both healthy subjects and in patients with

  18. Effects of modafinil on neural correlates of response inhibition in alcohol-dependent patients

    NARCIS (Netherlands)

    Schmaal, Lianne; Joos, Leen; Koeleman, Marte; Veltman, Dick J.; van den Brink, Wim; Goudriaan, Anna E.

    2013-01-01

    Impaired response inhibition is a key feature of patients with alcohol dependence. Improving impulse control is a promising target for the treatment of alcohol dependence. The pharmacologic agent modafinil enhances cognitive control functions in both healthy subjects and in patients with various

  19. Ketamine modulates subgenual cingulate connectivity with the memory-related neural circuit—a mechanism of relevance to resistant depression?

    Directory of Open Access Journals (Sweden)

    Jing J. Wong

    2016-02-01

    Full Text Available Background. Ketamine has been reported to have efficacy as an antidepressant in several studies of treatment-resistant depression. In this study, we investigate whether an acute administration of ketamine leads to reductions in the functional connectivity of subgenual anterior cingulate cortex (sgACC with other brain regions. Methods. Thirteen right-handed healthy male subjects underwent a 15 min resting state fMRI with an infusion of intravenous ketamine (target blood level = 150 ng/ml starting at 5 min. We used a seed region centred on the sgACC and assessed functional connectivity before and during ketamine administration. Results. Before ketamine administration, positive coupling with the sgACC seed region was observed in a large cluster encompassing the anterior cingulate and negative coupling was observed with the anterior cerebellum. Following ketamine administration, sgACC activity became negatively correlated with the brainstem, hippocampus, parahippocampal gyrus, retrosplenial cortex, and thalamus. Discussion. Ketamine reduced functional connectivity of the sgACC with brain regions implicated in emotion, memory and mind wandering. It is possible the therapeutic effects of ketamine may be mediated via this mechanism, although further work is required to test this hypothesis.

  20. Part 2-The firings of many neurons and their density; the neural network its connections and field of firings.

    Science.gov (United States)

    Saaty, Thomas

    2017-02-01

    This paper is concerned with the firing of many neurons and the synthesis of these firings to develop functions and their transforms which relate chemical and electrical phenomena to the physical world. The density of such functions in the most general spaces that we encounter allows us to use linear combinations of them to approximate arbitrarily close to any phenomenon we encounter, imagine or think about. Absence of the technology needed to represent all the senses and the mathematical difficulty of making geometric representations of functions of a complex and of more general division algebra variables make it difficult to validate the mathematical outcome of this approach to neural firings. But we think that this problem will be solved in the not-too-distant future when at least the senses of smell, taste and touch would have been so mathematized that it is possible to instill these qualities in robots in some fashion. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. A re-assessment of long distance growth and connectivity of neural stem cells after severe spinal cord injury

    Science.gov (United States)

    Sharp, Kelli G.; Yee, Kelly Matsudaira; Steward, Oswald

    2014-01-01

    As part of the NIH “Facilities of Research Excellence—Spinal Cord Injury” project to support independent replication, we repeated key parts of a study reporting robust engraftment of neural stem cells (NSCs) treated with growth factors after complete spinal cord transection in rats. Rats (n = 20) received complete transections at thoracic level 3 (T3) and 2 weeks later received NSC transplants in a fibrin matrix with a growth factor cocktail using 2 different transplantation methods (with and without removal of scar tissue). Control rats (n = 9) received transections only. Hindlimb locomotor function was assessed with the BBB scale. Nine weeks post injury, reticulospinal tract axons were traced in 6 rats by injecting BDA into the reticular formation. Transplants grew to fill the lesion cavity in most rats although grafts made with scar tissue removal had large central cavities. Grafts blended extensively with host tissue obliterating the astroglial boundary at the cut ends, but in most cases there was a well-defined partition within the graft that separated rostral and caudal parts of the graft. In some cases, the partition contained non-neuronal scar tissue. There was extensive outgrowth of GFP labeled axons from the graft, but there was minimal ingrowth of host axons into the graft revealed by tract tracing and immunocy-tochemistry for 5HT. There were no statistically significant differences between transplant and control groups in the degree of locomotor recovery. Our results confirm the previous report that NSC transplants can fill lesion cavities and robustly extend axons, but reveal that most grafts do not create a continuous bridge of neural tissue between rostral and caudal segments. PMID:24747827

  2. Large-scale directional connections among multi resting-state neural networks in human brain: a functional MRI and Bayesian network modeling study.

    Science.gov (United States)

    Li, Rui; Chen, Kewei; Fleisher, Adam S; Reiman, Eric M; Yao, Li; Wu, Xia

    2011-06-01

    This study examined the large-scale connectivity among multiple resting-state networks (RSNs) in the human brain. Independent component analysis was first applied to the resting-state functional MRI (fMRI) data acquired from 12 healthy young subjects for the separation of RSNs. Four sensory (lateral and medial visual, auditory, and sensory-motor) RSNs and four cognitive (default-mode, self-referential, dorsal and ventral attention) RSNs were identified. Gaussian Bayesian network (BN) learning approach was then used for the examination of the conditional dependencies among these RSNs and the construction of the network-to-network directional connectivity patterns. The BN based results demonstrated that sensory networks and cognitive networks were hierarchically organized. Specially, we found the sensory networks were highly intra-dependent and the cognitive networks were strongly intra-influenced. In addition, the results depicted dominant bottom-up connectivity from sensory networks to cognitive networks in which the self-referential and the default-mode networks might play respectively important roles in the process of resting-state information transfer and integration. The present study characterized the global connectivity relations among RSNs and delineated more characteristics of spontaneous activity dynamics. Copyright © 2011 Elsevier Inc. All rights reserved.

  3. Natural variation in the thermotolerance of neural function and behavior due to a cGMP-dependent protein kinase.

    Directory of Open Access Journals (Sweden)

    Ken Dawson-Scully

    Full Text Available Although it is acknowledged that genetic variation contributes to individual differences in thermotolerance, the specific genes and pathways involved and how they are modulated by the environment remain poorly understood. We link natural variation in the thermotolerance of neural function and behavior in Drosophila melanogaster to the foraging gene (for, which encodes a cGMP-dependent protein kinase (PKG as well as to its downstream target, protein phosphatase 2A (PP2A. Genetic and pharmacological manipulations revealed that reduced PKG (or PP2A activity caused increased thermotolerance of synaptic transmission at the larval neuromuscular junction. Like synaptic transmission, feeding movements were preserved at higher temperatures in larvae with lower PKG levels. In a comparative assay, pharmacological manipulations altering thermotolerance in a central circuit of Locusta migratoria demonstrated conservation of this neuroprotective pathway. In this circuit, either the inhibition of PKG or PP2A induced robust thermotolerance of neural function. We suggest that PKG and therefore the polymorphism associated with the allelic variation in for may provide populations with natural variation in heat stress tolerance. for's function in behavior is conserved across most organisms, including ants, bees, nematodes, and mammals. PKG's role in thermotolerance may also apply to these and other species. Natural variation in thermotolerance arising from genes involved in the PKG pathway could impact the evolution of thermotolerance in natural populations.

  4. Neural substrates of impulsive decision making modulated by modafinil in alcohol-dependent patients

    NARCIS (Netherlands)

    Schmaal, L.; Goudriaan, A.E.; Joos, L.; Dom, G.; Pattij, T.; van den Brink, W.; Veltman, D.J.

    2014-01-01

    Background Impulsive decision making is a hallmark of frequently occurring addiction disorders including alcohol dependence (AD). Therefore, ameliorating impulsive decision making is a promising target for the treatment of AD. Previous studies have shown that modafinil enhances cognitive control

  5. Neural substrates of impulsive decision making modulated by modafinil in alcohol-dependent patients

    NARCIS (Netherlands)

    Schmaal, L.; Goudriaan, A. E.; Joos, L.; Dom, G.; Pattij, T.; van den Brink, W.; Veltman, D. J.

    2014-01-01

    Impulsive decision making is a hallmark of frequently occurring addiction disorders including alcohol dependence (AD). Therefore, ameliorating impulsive decision making is a promising target for the treatment of AD. Previous studies have shown that modafinil enhances cognitive control functions in

  6. Which bulb is brighter? It depends on connection! Strategies for illuminating electrical concepts using light bulbs

    Science.gov (United States)

    Wong, Darren; Lee, Paul; Foong, S. K.

    2017-11-01

    In this paper, we examined teachers’ understanding of electrical concepts such as power, current and potential difference based on how these concepts were applied to understand the relative brightness seen in bulbs of different wattage under different connections—series or parallel. From the responses of teachers to a concept question, we identified common lines of reasoning and the associated conceptual difficulties. To support the explanation of the concept question, we set up relevant circuits and made measurements of the circuits. We discuss the temperature dependence of the resistance of the light bulb which although critical for in depth understanding of the relative brightness, was often omitted in the teacher responses. Lastly, we share insights and strategies to elicit and confront students' thinking and to help them resolve, extend and apply their thinking with regard to the related electrical concepts using various light bulb activities.

  7. Neural responses to unfairness and fairness depend on self-contribution to the income

    Science.gov (United States)

    Guo, Xiuyan; Zheng, Li; Cheng, Xuemei; Chen, Menghe; Li, Jianqi; Chen, Luguang; Yang, Zhiliang

    2014-01-01

    Self-contribution to the income (individual achievement) was an important factor which needs to be taken into individual’s fairness considerations. This study aimed at elucidating the modulation of self-contribution to the income, on recipient’s responses to unfairness in the Ultimatum Game. Eighteen participants were scanned while they were playing an adapted version of the Ultimatum Game as responders. Before splitting money, the proposer and the participant (responder) played the ball-guessing game. The responder’s contribution to the income was manipulated by both the participant’s and the proposer’s accuracy in the ball-guessing game. It turned out that the participants more often rejected unfair offers and gave lower fairness ratings when they played a more important part in the earnings. At the neural level, anterior insula, anterior cingulate cortex, dorsolateral prefrontal cortex and temporoparietal junction showed greater activities to unfairness when self-contribution increased, whereas ventral striatum and medial orbitofrontal gyrus showed higher activations to fair (vs unfair) offers in the other-contributed condition relative to the other two. Besides, the activations of right dorsolateral prefrontal cortex during unfair offers showed positive correlation with rejection rates in the self-contributed condition. These findings shed light on the significance of self-contribution in fairness-related social decision-making processes. PMID:23946001

  8. Experience dependence of neural responses to different classes of male songs in the primary auditory forebrain of female songbirds.

    Science.gov (United States)

    Hauber, Mark E; Woolley, Sarah M N; Cassey, Phillip; Theunissen, Frédéric E

    2013-04-15

    There is both extensive species-specificity and critical experience-dependence in the recognition of own species songs in many songbird species. For example, female zebra finches Taeniopygia guttata raised by their parents show behavioral preferences for the songs of the father over unfamiliar conspecific males and for unfamiliar songs of conspecifics over heterospecifics. Behavioral discrimination between different species' songs is also displayed by females raised without exposure to any male songs but it is diminished in females raised by heterospecific foster parents. We tested whether neural responses in the female auditory forebrain paralleled each of these known behavioral patterns in song-class discrimination. We analyzed spike rates, above background levels, recorded from single units in the L2a subregion of the field L complex of female zebra finches. In subjects raised by genetic parents, spike rates were similar to songs of fathers and unfamiliar male zebra finches, and higher to unfamiliar conspecific over unfamiliar heterospecific songs. In females raised in isolation from male songs, we also found higher spike rates to unfamiliar conspecific over heterospecific songs. In females raised by heterospecific foster parents, spike rates were similar in response to songs of the foster father and unfamiliar males of the foster species, similar between unfamiliar songs of conspecifics and the heterospecific foster species, and higher to unfamiliar songs of the foster species over a third finch species. Thus, in parallel to the experience-dependence of females' behaviors in response to different male song classes, differences in social experiences can also alter neural response patterns to male song classes in the auditory forebrain of female zebra finches. Copyright © 2013 Elsevier B.V. All rights reserved.

  9. Decreased functional connectivity and disrupted neural network in the prefrontal cortex of affective disorders: A resting-state fNIRS study.

    Science.gov (United States)

    Zhu, Huilin; Xu, Jie; Li, Jiangxue; Peng, Hongjun; Cai, Tingting; Li, Xinge; Wu, Shijing; Cao, Wei; He, Sailing

    2017-10-15

    Affective disorders (AD) have been conceptualized as neural network-level diseases. In this study, we utilized functional near infrared spectroscopy (fNIRS) to investigate the spontaneous hemodynamic activities in the prefrontal cortex (PFC) of the AD patients with or without medications. 42 optical channels were applied to cover the superior frontal gyrus (SFG), middle frontal gyrus (MFG), and inferior frontal gyrus (IFG), which constitute one of the most important affective networks of the brain. We performed resting-state measurements on 28 patients who were diagnosed as having AD and 30 healthy controls (HC). Raw fNIRS data were preprocessed with independent component analysis (ICA) and a band-pass filter to remove artifacts and physiological noise. By systematically analyzing the intra-regional, intrahemispheric, and interhemispheric connectivities based on the spontaneous oscillations of Δ[HbO], our results indicated that patients with AD exhibited significantly reduced intra-regional and symmetrically interhemispheric connectivities in the PFC when compared to HC. More specifically, relative to HC, AD patients showed significantly lower locally functional connectivity in the right IFG, and poor long-distance connectivity between bilateral IFG. In addition, AD patients without medication presented more disrupted cortical organizations in the PFC, and the severity of self-reported symptoms of depression was negatively correlated with the strength of intra-regional and symmetrically interhemispheric connectivity in the PFC. Regarding the measuring technique, fNIRS has restricted measurement depth and spatial resolution. During the study, the subgroups of AD, such as major depressive disorder, bipolar, comorbidity, or non-comorbidity, dosage of psychotropic drugs, as well as different types of pharmacological responses were not distinguished and systematically compared. Furthermore, due to the limitation of the research design, it was still not very clear how

  10. Effects of cognitive bias modification training on neural alcohol cue reactivity in alcohol dependence

    NARCIS (Netherlands)

    Wiers, C.E.; Stelzel, C.; Gladwin, T.E.; Park, S.Q.; Pawelczack, S.; Gawron, C.K.; Stuke, H.; Heinz, A.; Wiers, R.W.; Rinck, M.; Lindenmeyer, J.; Walter, H.; Bermpohl, F.

    2015-01-01

    Objective: In alcohol-dependent patients, alcohol cues evoke increased activation in mesolimbic brain areas, such as the nucleus accumbens and the amygdala. Moreover, patients show an alcohol approach bias, a tendency to more quickly approach than avoid alcohol cues. Cognitive bias modification

  11. Effects of cognitive bias modification training on neural alcohol cue reactivity in alcohol dependence

    NARCIS (Netherlands)

    Wiers, C.E.; Stelzel, C.; Gladwin, T.E.; Park, S.Q.; Pawelczack, S.; Gawron, C.K.; Stuke, H.; Heinz, A.; Wiers, R.W.H.J.; Rinck, M.; Lindenmeyer, J.; Walter, H.; Bermpohl, F.

    2015-01-01

    OBJECTIVE: In alcohol-dependent patients, alcohol cues evoke increased activation in mesolimbic brain areas, such as the nucleus accumbens and the amygdala. Moreover, patients show an alcohol approach bias, a tendency to more quickly approach than avoid alcohol cues. Cognitive bias modification

  12. Neural bases of pharmacological treatment of nicotine dependence - insights from functional brain imaging: a systematic review

    NARCIS (Netherlands)

    Menossi, Henrique Soila; Goudriaan, Anna E.; de Azevedo-Marques Périco, Cintia; Nicastri, Sérgio; de Andrade, Arthur Guerra; D'Elia, Gilberto; Li, Chiang-Shan R.; Castaldelli-Maia, João Mauricio

    2013-01-01

    Nicotine dependence is difficult to treat, and the biological mechanisms that are involved are not entirely clear. There is an urgent need to develop better drugs and more effective treatments for clinical practice. A critical step towards accelerating progress in medication development is to

  13. Emergence of slow collective oscillations in neural networks with spike-timing dependent plasticity

    DEFF Research Database (Denmark)

    Mikkelsen, Kaare; Imparato, Alberto; Torcini, Alessandro

    2013-01-01

    The collective dynamics of excitatory pulse coupled neurons with spike timing dependent plasticity (STDP) is studied. The introduction of STDP induces persistent irregular oscillations between strongly and weakly synchronized states, reminiscent of brain activity during slow-wave sleep. We explain...

  14. Cell-Type-Specific Circuit Connectivity of Hippocampal CA1 Revealed through Cre-Dependent Rabies Tracing

    Directory of Open Access Journals (Sweden)

    Yanjun Sun

    2014-04-01

    Full Text Available We developed and applied a Cre-dependent, genetically modified rabies-based tracing system to map direct synaptic connections to specific CA1 neuron types in the mouse hippocampus. We found common inputs to excitatory and inhibitory CA1 neurons from CA3, CA2, the entorhinal cortex (EC, the medial septum (MS, and, unexpectedly, the subiculum. Excitatory CA1 neurons receive inputs from both cholinergic and GABAergic MS neurons, whereas inhibitory neurons receive a great majority of inputs from GABAergic MS neurons. Both cell types also receive weaker input from glutamatergic MS neurons. Comparisons of inputs to CA1 PV+ interneurons versus SOM+ interneurons showed similar strengths of input from the subiculum, but PV+ interneurons received much stronger input than SOM+ neurons from CA3, the EC, and the MS. Thus, rabies tracing identifies hippocampal circuit connections and maps how the different input sources to CA1 are distributed with different strengths on each of its constituent cell types.

  15. Neural development of binaural tuning through Hebbian learning predicts frequency-dependent best delays.

    Science.gov (United States)

    Fontaine, Bertrand; Brette, Romain

    2011-08-10

    Birds use microsecond differences in the arrival times of the sounds at the two ears to infer the location of a sound source in the horizontal plane. These interaural time differences (ITDs) are encoded by binaural neurons which fire more when the ITD matches their "best delay." In the textbook model of sound localization, the best delays of binaural neurons reflect the differences in axonal delays of their monaural inputs, but recent observations have cast doubts on this classical view because best delays were found to depend on preferred frequency. Here, we show that these observations are in fact consistent with the notion that best delays are created by differences in axonal delays, provided ITD tuning is created during development through spike-timing-dependent plasticity: basilar membrane filtering results in correlations between inputs to binaural neurons, which impact the selection of synapses during development, leading to the observed distribution of best delays.

  16. The ciliary proteins Meckelin and Jouberin are required for retinoic acid-dependent neural differentiation of mouse embryonic stem cells.

    Science.gov (United States)

    Romani, Sveva; Illi, Barbara; De Mori, Roberta; Savino, Mauro; Gleeson, Joseph G; Valente, Enza Maria

    2014-01-01

    The dysfunction of the primary cilium, a complex, evolutionarily conserved, organelle playing an important role in sensing and transducing cell signals, is the unifying pathogenetic mechanism of a growing number of diseases collectively termed "ciliopathies", typically characterized by multiorgan involvement. Developmental defects of the central nervous system (CNS) characterize a subset of ciliopathies showing clinical and genetic overlap, such as Joubert syndrome (JS) and Meckel syndrome (MS). Although several knock-out mice lacking a variety of ciliary proteins have shown the importance of primary cilia in the development of the brain and CNS-derived structures, developmental in vitro studies, extremely useful to unravel the role of primary cilia along the course of neural differentiation, are still missing. Mouse embryonic stem cells (mESCs) have been recently proven to mimic brain development, giving the unique opportunity to dissect the CNS differentiation process along its sequential steps. In the present study we show that mESCs express the ciliary proteins Meckelin and Jouberin in a developmentally-regulated manner, and that these proteins co-localize with acetylated tubulin labeled cilia located at the outer embryonic layer. Further, mESCs differentiating along the neuronal lineage activate the cilia-dependent sonic hedgehog signaling machinery, which is impaired in Meckelin knock-out cells but results unaffected in Jouberin-deficient mESCs. However, both lose the ability to acquire a neuronal phenotype. Altogether, these results demonstrate a pivotal role of Meckelin and Jouberin during embryonic neural specification and indicate mESCs as a suitable tool to investigate the developmental impact of ciliary proteins dysfunction. Copyright © 2014 International Society of Differentiation. Published by Elsevier B.V. All rights reserved.

  17. PARP inhibitors protect against sex- and AAG-dependent alkylation-induced neural degeneration.

    Science.gov (United States)

    Allocca, Mariacarmela; Corrigan, Joshua J; Fake, Kimberly R; Calvo, Jennifer A; Samson, Leona D

    2017-09-15

    Alkylating agents are commonly used to treat cancer. Although base excision repair (BER) is a major pathway for repairing DNA alkylation damage, under certain conditions, the initiation of BER produces toxic repair intermediates that damage healthy tissues. The initiation of BER by the alkyladenine DNA glycosylase (AAG, a.k.a. MPG) can mediate alkylation-induced cytotoxicity in specific cells in the retina and cerebellum of male mice. Cytotoxicity in both wild-type and Aag-transgenic (AagTg) mice is abrogated in the absence of Poly(ADP-ribose) polymerase-1 (PARP1). Here, we tested whether PARP inhibitors can also prevent alkylation-induced retinal and cerebellar degeneration in male and female WT and AagTg mice. Importantly, we found that WT mice display sex-dependent alkylation-induced retinal damage (but not cerebellar damage), with WT males being more sensitive than females. Accordingly, estradiol treatment protects males against alkylation-induced retinal degeneration. In AagTg male and female mice, the alkylation-induced tissue damage in both the retina and cerebellum is exacerbated and the sex difference in the retina is abolished. PARP inhibitors, much like Parp1 gene deletion, protect against alkylation-induced AAG-dependent neuronal degeneration in WT and AagTg mice, regardless of the gender, but their efficacy in preventing alkylation-induced neuronal degeneration depends on PARP inhibitor characteristics and doses. The recent surge in the use of PARP inhibitors in combination with cancer chemotherapeutic alkylating agents might represent a powerful tool for obtaining increased therapeutic efficacy while avoiding the collateral effects of alkylating agents in healthy tissues.

  18. Time dependent neural network models for detecting changes of state in complex processes: applications in earth sciences and astronomy.

    Science.gov (United States)

    Valdés, Julio J; Bonham-Carter, Graeme

    2006-03-01

    A computational intelligence approach is used to explore the problem of detecting internal state changes in time dependent processes; described by heterogeneous, multivariate time series with imprecise data and missing values. Such processes are approximated by collections of time dependent non-linear autoregressive models represented by a special kind of neuro-fuzzy neural network. Grid and high throughput computing model mining procedures based on neuro-fuzzy networks and genetic algorithms, generate: (i) collections of models composed of sets of time lag terms from the time series, and (ii) prediction functions represented by neuro-fuzzy networks. The composition of the models and their prediction capabilities, allows the identification of changes in the internal structure of the process. These changes are associated with the alternation of steady and transient states, zones with abnormal behavior, instability, and other situations. This approach is general, and its sensitivity for detecting subtle changes of state is revealed by simulation experiments. Its potential in the study of complex processes in earth sciences and astrophysics is illustrated with applications using paleoclimate and solar data.

  19. A neural network potential-energy surface for the water dimer based on environment-dependent atomic energies and charges

    Science.gov (United States)

    Morawietz, Tobias; Sharma, Vikas; Behler, Jörg

    2012-02-01

    Understanding the unique properties of water still represents a significant challenge for theory and experiment. Computer simulations by molecular dynamics require a reliable description of the atomic interactions, and in recent decades countless water potentials have been reported in the literature. Still, most of these potentials contain significant approximations, for instance a frozen internal structure of the individual water monomers. Artificial neural networks (NNs) offer a promising way for the construction of very accurate potential-energy surfaces taking all degrees of freedom explicitly into account. These potentials are based on electronic structure calculations for representative configurations, which are then interpolated to a continuous energy surface that can be evaluated many orders of magnitude faster. We present a full-dimensional NN potential for the water dimer as a first step towards the construction of a NN potential for liquid water. This many-body potential is based on environment-dependent atomic energy contributions, and long-range electrostatic interactions are incorporated employing environment-dependent atomic charges. We show that the potential and derived properties like vibrational frequencies are in excellent agreement with the underlying reference density-functional theory calculations.

  20. Origin-Dependent Neural Cell Identities in Differentiated Human iPSCs In Vitro and after Transplantation into the Mouse Brain

    Directory of Open Access Journals (Sweden)

    Gunnar Hargus

    2014-09-01

    Full Text Available The differentiation capability of induced pluripotent stem cells (iPSCs toward certain cell types for disease modeling and drug screening assays might be influenced by their somatic cell of origin. Here, we have compared the neural induction of human iPSCs generated from fetal neural stem cells (fNSCs, dermal fibroblasts, or cord blood CD34+ hematopoietic progenitor cells. Neural progenitor cells (NPCs and neurons could be generated at similar efficiencies from all iPSCs. Transcriptomics analysis of the whole genome and of neural genes revealed a separation of neuroectoderm-derived iPSC-NPCs from mesoderm-derived iPSC-NPCs. Furthermore, we found genes that were similarly expressed in fNSCs and neuroectoderm, but not in mesoderm-derived iPSC-NPCs. Notably, these neural signatures were retained after transplantation into the cortex of mice and paralleled with increased survival of neuroectoderm-derived cells in vivo. These results indicate distinct origin-dependent neural cell identities in differentiated human iPSCs both in vitro and in vivo.

  1. Neuroadaptive changes associated with smoking: structural and functional neural changes in nicotine dependence.

    Science.gov (United States)

    Martin-Soelch, Chantal

    2013-02-15

    Tobacco smoking is the most frequent form of substance abuse. We provide a review of the neuroadaptive changes evidenced in human smokers with regard to the current neurobiological models of addiction. Addiction is thought to result from an interplay between positive and negative reinforcement. Positive reinforcing effects of the drugs are mediated by striatal dopamine release, while negative reinforcement involves the relief of withdrawal symptoms and neurobiological stress systems. In addition, drug-related stimuli are attributed with excessive motivational value and are thought to exert a control on the behavior. This mechanism plays a central role in drug maintenance and relapse. Further neuroadaptive changes associated with chronic use of the drug consist of reduced responses to natural rewards and in the activation of an antireward system, related to neurobiological stress systems. Reduced inhibitory cognitive control is believed to support the development and the maintenance of addiction. The findings observed in human nicotine dependence are generally in line with these models. The current state of the research indicates specific neuroadaptive changes associated with nicotine addiction that need to be further elucidated with regard to their role in the treatment of nicotine dependence.

  2. Neuroadaptive Changes Associated with Smoking: Structural and Functional Neural Changes in Nicotine Dependence

    Directory of Open Access Journals (Sweden)

    Chantal Martin-Soelch

    2013-02-01

    Full Text Available Tobacco smoking is the most frequent form of substance abuse. We provide a review of the neuroadaptive changes evidenced in human smokers with regard to the current neurobiological models of addiction. Addiction is thought to result from an interplay between positive and negative reinforcement. Positive reinforcing effects of the drugs are mediated by striatal dopamine release, while negative reinforcement involves the relief of withdrawal symptoms and neurobiological stress systems. In addition, drug-related stimuli are attributed with excessive motivational value and are thought to exert a control on the behavior. This mechanism plays a central role in drug maintenance and relapse. Further neuroadaptive changes associated with chronic use of the drug consist of reduced responses to natural rewards and in the activation of an antireward system, related to neurobiological stress systems. Reduced inhibitory cognitive control is believed to support the development and the maintenance of addiction. The findings observed in human nicotine dependence are generally in line with these models. The current state of the research indicates specific neuroadaptive changes associated with nicotine addiction that need to be further elucidated with regard to their role in the treatment of nicotine dependence.

  3. Stochastic spike synchronization in a small-world neural network with spike-timing-dependent plasticity.

    Science.gov (United States)

    Kim, Sang-Yoon; Lim, Woochang

    2018-01-01

    We consider the Watts-Strogatz small-world network (SWN) consisting of subthreshold neurons which exhibit noise-induced spikings. This neuronal network has adaptive dynamic synaptic strengths governed by the spike-timing-dependent plasticity (STDP). In previous works without STDP, stochastic spike synchronization (SSS) between noise-induced spikings of subthreshold neurons was found to occur in a range of intermediate noise intensities. Here, we investigate the effect of additive STDP on the SSS by varying the noise intensity. Occurrence of a "Matthew" effect in synaptic plasticity is found due to a positive feedback process. As a result, good synchronization gets better via long-term potentiation of synaptic strengths, while bad synchronization gets worse via long-term depression. Emergences of long-term potentiation and long-term depression of synaptic strengths are intensively investigated via microscopic studies based on the pair-correlations between the pre- and the post-synaptic IISRs (instantaneous individual spike rates) as well as the distributions of time delays between the pre- and the post-synaptic spike times. Furthermore, the effects of multiplicative STDP (which depends on states) on the SSS are studied and discussed in comparison with the case of additive STDP (independent of states). These effects of STDP on the SSS in the SWN are also compared with those in the regular lattice and the random graph. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. A newly identified mouse hypothalamic area having bidirectional neural connections with the lateral septum: the perifornical area of the anterior hypothalamus rich in chondroitin sulfate proteoglycans.

    Science.gov (United States)

    Horii-Hayashi, Noriko; Sasagawa, Takayo; Hashimoto, Takashi; Kaneko, Takeshi; Takeuchi, Kosei; Nishi, Mayumi

    2015-09-01

    While previous studies and brain atlases divide the hypothalamus into many nuclei and areas, uncharacterised regions remain. Here, we report a new region in the mouse anterior hypothalamus (AH), a triangular-shaped perifornical area of the anterior hypothalamus (PeFAH) between the paraventricular hypothalamic nucleus and fornix, that abundantly expresses chondroitin sulfate proteoglycans (CSPGs). The PeFAH strongly stained with markers for chondroitin sulfate/CSPGs such as Wisteria floribunda agglutinin and antibodies against aggrecan and chondroitin 6 sulfate. Nissl-stained sections of the PeFAH clearly distinguished it as a region of comparatively low density compared to neighboring regions, the paraventricular nucleus and central division of the anterior hypothalamic area. Immunohistochemical and DNA microarray analyses suggested that PeFAH contains sparsely distributed calretinin-positive neurons and a compact cluster of enkephalinergic neurons. Neuronal tract tracing revealed that both enkephalin- and calretinin-positive neurons project to the lateral septum (LS), while the PeFAH receives input from calbindin-positive LS neurons. These results suggest bidirectional connections between the PeFAH and LS. Considering neuronal subtype and projection, part of PeFAH that includes a cluster of enkephalinergic neurons is similar to the rat perifornical nucleus and guinea pig magnocellular dorsal nucleus. Finally, we examined c-Fos expression after several types of stimuli and found that PeFAH neuronal activity was increased by psychological but not homeostatic stressors. These findings suggest that the PeFAH is a source of enkephalin peptides in the LS and indicate that bidirectional neural connections between these regions may participate in controlling responses to psychological stressors. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  5. Self-Tuning Fully-Connected PID Neural Network System for Distributed Temperature Sensing and Control of Instrument with Multi-Modules.

    Science.gov (United States)

    Zhang, Zhen; Ma, Cheng; Zhu, Rong

    2016-10-14

    High integration of multi-functional instruments raises a critical issue in temperature control that is challenging due to its spatial-temporal complexity. This paper presents a multi-input multi-output (MIMO) self-tuning temperature sensing and control system for efficiently modulating the temperature environment within a multi-module instrument. The smart system ensures that the internal temperature of the instrument converges to a target without the need of a system model, thus making the control robust. The system consists of a fully-connected proportional-integral-derivative (PID) neural network (FCPIDNN) and an on-line self-tuning module. The experimental results show that the presented system can effectively control the internal temperature under various mission scenarios, in particular, it is able to self-reconfigure upon actuator failure. The system provides a new scheme for a complex and time-variant MIMO control system which can be widely applied for the distributed measurement and control of the environment in instruments, integration electronics, and house constructions.

  6. Dynamic dependence on ATR and ATM for double-strand break repair in human embryonic stem cells and neural descendants.

    Directory of Open Access Journals (Sweden)

    Bret R Adams

    2010-04-01

    Full Text Available The DNA double-strand break (DSB is the most toxic form of DNA damage. Studies aimed at characterizing DNA repair during development suggest that homologous recombination repair (HRR is more critical in pluripotent cells compared to differentiated somatic cells in which nonhomologous end joining (NHEJ is dominant. We have characterized the DNA damage response (DDR and quality of DNA double-strand break (DSB repair in human embryonic stem cells (hESCs, and in vitro-derived neural cells. Resolution of ionizing radiation-induced foci (IRIF was used as a surrogate for DSB repair. The resolution of gamma-H2AX foci occurred at a slower rate in hESCs compared to neural progenitors (NPs and astrocytes perhaps reflective of more complex DSB repair in hESCs. In addition, the resolution of RAD51 foci, indicative of active homologous recombination repair (HRR, showed that hESCs as well as NPs have high capacity for HRR, whereas astrocytes do not. Importantly, the ATM kinase was shown to be critical for foci formation in astrocytes, but not in hESCs, suggesting that the DDR is different in these cells. Blocking the ATM kinase in astrocytes not only prevented the formation but also completely disassembled preformed repair foci. The ability of hESCs to form IRIF was abrogated with caffeine and siRNAs targeted against ATR, implicating that hESCs rely on ATR, rather than ATM for regulating DSB repair. This relationship dynamically changed as cells differentiated. Interestingly, while the inhibition of the DNA-PKcs kinase (and presumably non-homologous endjoining [NHEJ] in astrocytes slowed IRIF resolution it did not in hESCs, suggesting that repair in hESCs does not utilize DNA-PKcs. Altogether, our results show that hESCs have efficient DSB repair that is largely ATR-dependent HRR, whereas astrocytes critically depend on ATM for NHEJ, which, in part, is DNA-PKcs-independent.

  7. A Gustatory Neural Circuit of Caenorhabditis elegans Generates Memory-Dependent Behaviors in Na(+) Chemotaxis.

    Science.gov (United States)

    Wang, Lifang; Sato, Hirofumi; Satoh, Yohsuke; Tomioka, Masahiro; Kunitomo, Hirofumi; Iino, Yuichi

    2017-02-22

    Animals show various behaviors in response to environmental chemicals. These behaviors are often plastic depending on previous experiences. Caenorhabditis elegans, which has highly developed chemosensory system with a limited number of sensory neurons, is an ideal model for analyzing the role of each neuron in innate and learned behaviors. Here, we report a new type of memory-dependent behavioral plasticity in Na(+) chemotaxis generated by the left member of bilateral gustatory neuron pair ASE (ASEL neuron). When worms were cultivated in the presence of Na(+), they showed positive chemotaxis toward Na(+), but when cultivated under Na(+)-free conditions, they showed no preference regarding Na(+) concentration. Both channelrhodopsin-2 (ChR2) activation with blue light and up-steps of Na(+) concentration activated ASEL only after cultivation with Na(+), as judged by increase in intracellular Ca(2+) Under cultivation conditions with Na(+), photoactivation of ASEL caused activation of its downstream interneurons AIY and AIA, which stimulate forward locomotion, and inhibition of its downstream interneuron AIB, which inhibits the turning/reversal behavior, and overall drove worms toward higher Na(+) concentrations. We also found that the Gq signaling pathway and the neurotransmitter glutamate are both involved in the behavioral response generated by ASEL.SIGNIFICANCE STATEMENT Animals have acquired various types of behavioral plasticity during their long evolutionary history. Caenorhabditis elegans prefers odors associated with food, but plastically changes its behavioral response according to previous experience. Here, we report a new type of behavioral response generated by a single gustatory sensory neuron, the ASE-left (ASEL) neuron. ASEL did not respond to photostimulation or upsteps of Na(+) concentration when worms were cultivated in Na(+)-free conditions; however, when worms were cultivated with Na(+), ASEL responded and inhibited AIB to avoid turning and

  8. Genome-Enabled Modeling of Biogeochemical Processes Predicts Metabolic Dependencies that Connect the Relative Fitness of Microbial Functional Guilds

    Science.gov (United States)

    Brodie, E.; King, E.; Molins, S.; Karaoz, U.; Steefel, C. I.; Banfield, J. F.; Beller, H. R.; Anantharaman, K.; Ligocki, T. J.; Trebotich, D.

    2015-12-01

    Pore-scale processes mediated by microorganisms underlie a range of critical ecosystem services, regulating carbon stability, nutrient flux, and the purification of water. Advances in cultivation-independent approaches now provide us with the ability to reconstruct thousands of genomes from microbial populations from which functional roles may be assigned. With this capability to reveal microbial metabolic potential, the next step is to put these microbes back where they belong to interact with their natural environment, i.e. the pore scale. At this scale, microorganisms communicate, cooperate and compete across their fitness landscapes with communities emerging that feedback on the physical and chemical properties of their environment, ultimately altering the fitness landscape and selecting for new microbial communities with new properties and so on. We have developed a trait-based model of microbial activity that simulates coupled functional guilds that are parameterized with unique combinations of traits that govern fitness under dynamic conditions. Using a reactive transport framework, we simulate the thermodynamics of coupled electron donor-acceptor reactions to predict energy available for cellular maintenance, respiration, biomass development, and enzyme production. From metagenomics, we directly estimate some trait values related to growth and identify the linkage of key traits associated with respiration and fermentation, macromolecule depolymerizing enzymes, and other key functions such as nitrogen fixation. Our simulations were carried out to explore abiotic controls on community emergence such as seasonally fluctuating water table regimes across floodplain organic matter hotspots. Simulations and metagenomic/metatranscriptomic observations highlighted the many dependencies connecting the relative fitness of functional guilds and the importance of chemolithoautotrophic lifestyles. Using an X-Ray microCT-derived soil microaggregate physical model combined

  9. Assembly of 4-, 6- and 8-connected Cd(II) pseudo-polymorphic coordination polymers: Synthesis, solvent-dependent structural variation and properties

    Energy Technology Data Exchange (ETDEWEB)

    Li, Zhao-Hao [College of Chemistry and Chemical Engineering, and Henan Key Laboratory of Function-Oriented Porous Materials, Luoyang Normal University, Luoyang 471934 (China); Xue, Li-Ping, E-mail: lpxue@163.com [College of Food and Drug, Luoyang Normal University, Luoyang 471934 (China); Miao, Shao-Bin [College of Chemistry and Chemical Engineering, and Henan Key Laboratory of Function-Oriented Porous Materials, Luoyang Normal University, Luoyang 471934 (China); Zhao, Bang-Tun, E-mail: zbt@lynu.edu.cn [College of Chemistry and Chemical Engineering, and Henan Key Laboratory of Function-Oriented Porous Materials, Luoyang Normal University, Luoyang 471934 (China)

    2016-08-15

    The reaction of Cd(NO{sub 3}){sub 2}·4H{sub 2}O, 2,5-thiophenedicarboxylic acid (H{sub 2}tdc) and 1,2-bis(imidazol-1′-yl)methane (bimm) by modulating solvent systems yielded three highly connected pseudo-polymorphic coordination polymers based on different dinuclear [Cd{sub 2}(CO{sub 2}){sub 2}] subunits bridged by carboxylate groups. Single crystal structural analyses reveal structural variation from 4-connected 2D sql layer, 6-connected 2-fold interpenetrated 3D pcu to 8-connected 3D bcu-type network in compounds 1–3. The structural dissimilarity in the structures dependent on the coordination environments of Cd(II) ions and linking modes of mixed ligand influenced by different solvent systems during the synthesis process. Moreover, thermogravimetric and photoluminescence behaviors of 1–3 were also investigated for the first time, and all the complexes emit blue luminescence in the solid state. - Graphical abstract: Key Topic. Different solvent systems modulated three Cd(II) pseudo-polymorphic coordination polymers based on thiophene-2,5-dicarboxylate and 1,2-bis(imidazol-1′-yl)methane mixed ligands. Display Omitted - Highlights: • Three solvent-dependent Cd(II) pseudo-polymorphic coordination polymers have been synthesized. • Structural variation from 4-connected 2D layer, 6-connected 2-fold interpenetrated 3D net to 8-connected 3D net. • All complexes emit blue luminescence.

  10. Diagnosing Autism Spectrum Disorder from Brain Resting-State Functional Connectivity Patterns Using a Deep Neural Network with a Novel Feature Selection Method.

    Science.gov (United States)

    Guo, Xinyu; Dominick, Kelli C; Minai, Ali A; Li, Hailong; Erickson, Craig A; Lu, Long J

    2017-01-01

    The whole-brain functional connectivity (FC) pattern obtained from resting-state functional magnetic resonance imaging data are commonly applied to study neuropsychiatric conditions such as autism spectrum disorder (ASD) by using different machine learning models. Recent studies indicate that both hyper- and hypo- aberrant ASD-associated FCs were widely distributed throughout the entire brain rather than only in some specific brain regions. Deep neural networks (DNN) with multiple hidden layers have shown the ability to systematically extract lower-to-higher level information from high dimensional data across a series of neural hidden layers, significantly improving classification accuracy for such data. In this study, a DNN with a novel feature selection method (DNN-FS) is developed for the high dimensional whole-brain resting-state FC pattern classification of ASD patients vs. typical development (TD) controls. The feature selection method is able to help the DNN generate low dimensional high-quality representations of the whole-brain FC patterns by selecting features with high discriminating power from multiple trained sparse auto-encoders. For the comparison, a DNN without the feature selection method (DNN-woFS) is developed, and both of them are tested with different architectures (i.e., with different numbers of hidden layers/nodes). Results show that the best classification accuracy of 86.36% is generated by the DNN-FS approach with 3 hidden layers and 150 hidden nodes (3/150). Remarkably, DNN-FS outperforms DNN-woFS for all architectures studied. The most significant accuracy improvement was 9.09% with the 3/150 architecture. The method also outperforms other feature selection methods, e.g., two sample t-test and elastic net. In addition to improving the classification accuracy, a Fisher's score-based biomarker identification method based on the DNN is also developed, and used to identify 32 FCs related to ASD. These FCs come from or cross different pre

  11. Diagnosing Autism Spectrum Disorder from Brain Resting-State Functional Connectivity Patterns Using a Deep Neural Network with a Novel Feature Selection Method

    Directory of Open Access Journals (Sweden)

    Xinyu Guo

    2017-08-01

    Full Text Available The whole-brain functional connectivity (FC pattern obtained from resting-state functional magnetic resonance imaging data are commonly applied to study neuropsychiatric conditions such as autism spectrum disorder (ASD by using different machine learning models. Recent studies indicate that both hyper- and hypo- aberrant ASD-associated FCs were widely distributed throughout the entire brain rather than only in some specific brain regions. Deep neural networks (DNN with multiple hidden layers have shown the ability to systematically extract lower-to-higher level information from high dimensional data across a series of neural hidden layers, significantly improving classification accuracy for such data. In this study, a DNN with a novel feature selection method (DNN-FS is developed for the high dimensional whole-brain resting-state FC pattern classification of ASD patients vs. typical development (TD controls. The feature selection method is able to help the DNN generate low dimensional high-quality representations of the whole-brain FC patterns by selecting features with high discriminating power from multiple trained sparse auto-encoders. For the comparison, a DNN without the feature selection method (DNN-woFS is developed, and both of them are tested with different architectures (i.e., with different numbers of hidden layers/nodes. Results show that the best classification accuracy of 86.36% is generated by the DNN-FS approach with 3 hidden layers and 150 hidden nodes (3/150. Remarkably, DNN-FS outperforms DNN-woFS for all architectures studied. The most significant accuracy improvement was 9.09% with the 3/150 architecture. The method also outperforms other feature selection methods, e.g., two sample t-test and elastic net. In addition to improving the classification accuracy, a Fisher's score-based biomarker identification method based on the DNN is also developed, and used to identify 32 FCs related to ASD. These FCs come from or cross

  12. An efficient neural network approach to dynamic robot motion planning.

    Science.gov (United States)

    Yang, S X; Meng, M

    2000-03-01

    In this paper, a biologically inspired neural network approach to real-time collision-free motion planning of mobile robots or robot manipulators in a nonstationary environment is proposed. Each neuron in the topologically organized neural network has only local connections, whose neural dynamics is characterized by a shunting equation. Thus the computational complexity linearly depends on the neural network size. The real-time robot motion is planned through the dynamic activity landscape of the neural network without any prior knowledge of the dynamic environment, without explicitly searching over the free workspace or the collision paths, and without any learning procedures. Therefore it is computationally efficient. The global stability of the neural network is guaranteed by qualitative analysis and the Lyapunov stability theory. The effectiveness and efficiency of the proposed approach are demonstrated through simulation studies.

  13. [Glutamate signaling and neural plasticity].

    Science.gov (United States)

    Watanabe, Masahiko

    2013-07-01

    Proper functioning of the nervous system relies on the precise formation of neural circuits during development. At birth, neurons have redundant synaptic connections not only to their proper targets but also to other neighboring cells. Then, functional neural circuits are formed during early postnatal development by the selective strengthening of necessary synapses and weakening of surplus connections. Synaptic connections are also modified so that projection fields of active afferents expand at the expense of lesser ones. We have studied the molecular mechanisms underlying these activity-dependent prunings and the plasticity of synaptic circuitry using gene-engineered mice defective in the glutamatergic signaling system. NMDA-type glutamate receptors are critically involved in the establishment of the somatosensory pathway ascending from the brainstem trigeminal nucleus to the somatosensory cortex. Without NMDA receptors, whisker-related patterning fails to develop, whereas lesion-induced plasticity occurs normally during the critical period. In contrast, mice lacking the glutamate transporters GLAST or GLT1 are selectively impaired in the lesion-induced critical plasticity of cortical barrels, although whisker-related patterning itself develops normally. In the developing cerebellum, multiple climbing fibers initially innervating given Purkinje cells are eliminated one by one until mono-innervation is achieved. In this pruning process, P/Q-type Ca2+ channels expressed on Purkinje cells are critically involved by the selective strengthening of single main climbing fibers against other lesser afferents. Therefore, the activation of glutamate receptors that leads to an activity-dependent increase in the intracellular Ca2+ concentration plays a key role in the pruning of immature synaptic circuits into functional circuits. On the other hand, glutamate transporters appear to control activity-dependent plasticity among afferent fields, presumably through adjusting

  14. Menstrual cycle-dependent neural plasticity in the adult human brain is hormone, task, and region specific.

    NARCIS (Netherlands)

    Fernandez, G.S.E.; Weis, S.; Stoffel-Wagner, B.; Tendolkar, I.; Reuber, M.; Beyenburg, S.; Klaver, P.; Fell, J.; Greiff, A. de; Ruhlmann, J.; Reul, J.; Elger, C.E.

    2003-01-01

    In rodents, cyclically fluctuating levels of gonadal steroid hormones modulate neural plasticity by altering synaptic transmission and synaptogenesis. Alterations of mood and cognition observed during the menstrual cycle suggest that steroid-related plasticity also occurs in humans. Cycle

  15. The relationship between the neural computations for speech and music perception is context-dependent: an activation likelihood estimate study

    Directory of Open Access Journals (Sweden)

    Arianna eLaCroix

    2015-08-01

    Full Text Available The relationship between the neurobiology of speech and music has been investigated for more than a century. There remains no widespread agreement regarding how (or to what extent music perception utilizes the neural circuitry that is engaged in speech processing, particularly at the cortical level. Prominent models such as Patel’s Shared Syntactic Integration Resource Hypothesis (SSIRH and Koelsch’s neurocognitive model of music perception suggest a high degree of overlap, particularly in the frontal lobe, but also perhaps more distinct representations in the temporal lobe with hemispheric asymmetries. The present meta-analysis study used activation likelihood estimate analyses to identify the brain regions consistently activated for music as compared to speech across the functional neuroimaging (fMRI and PET literature. Eighty music and 91 speech neuroimaging studies of healthy adult control subjects were analyzed. Peak activations reported in the music and speech studies were divided into four paradigm categories: passive listening, discrimination tasks, error/anomaly detection tasks and memory-related tasks. We then compared activation likelihood estimates within each category for music versus speech, and each music condition with passive listening. We found that listening to music and to speech preferentially activate distinct temporo-parietal bilateral cortical networks. We also found music and speech to have shared resources in the left pars opercularis but speech-specific resources in the left pars triangularis. The extent to which music recruited speech-activated frontal resources was modulated by task. While there are certainly limitations to meta-analysis techniques particularly regarding sensitivity, this work suggests that the extent of shared resources between speech and music may be task-dependent and highlights the need to consider how task effects may be affecting conclusions regarding the neurobiology of speech and music.

  16. The relationship between the neural computations for speech and music perception is context-dependent: an activation likelihood estimate study

    Science.gov (United States)

    LaCroix, Arianna N.; Diaz, Alvaro F.; Rogalsky, Corianne

    2015-01-01

    The relationship between the neurobiology of speech and music has been investigated for more than a century. There remains no widespread agreement regarding how (or to what extent) music perception utilizes the neural circuitry that is engaged in speech processing, particularly at the cortical level. Prominent models such as Patel's Shared Syntactic Integration Resource Hypothesis (SSIRH) and Koelsch's neurocognitive model of music perception suggest a high degree of overlap, particularly in the frontal lobe, but also perhaps more distinct representations in the temporal lobe with hemispheric asymmetries. The present meta-analysis study used activation likelihood estimate analyses to identify the brain regions consistently activated for music as compared to speech across the functional neuroimaging (fMRI and PET) literature. Eighty music and 91 speech neuroimaging studies of healthy adult control subjects were analyzed. Peak activations reported in the music and speech studies were divided into four paradigm categories: passive listening, discrimination tasks, error/anomaly detection tasks and memory-related tasks. We then compared activation likelihood estimates within each category for music vs. speech, and each music condition with passive listening. We found that listening to music and to speech preferentially activate distinct temporo-parietal bilateral cortical networks. We also found music and speech to have shared resources in the left pars opercularis but speech-specific resources in the left pars triangularis. The extent to which music recruited speech-activated frontal resources was modulated by task. While there are certainly limitations to meta-analysis techniques particularly regarding sensitivity, this work suggests that the extent of shared resources between speech and music may be task-dependent and highlights the need to consider how task effects may be affecting conclusions regarding the neurobiology of speech and music. PMID:26321976

  17. Constructive autoassociative neural network for facial recognition.

    Directory of Open Access Journals (Sweden)

    Bruno J T Fernandes

    Full Text Available Autoassociative artificial neural networks have been used in many different computer vision applications. However, it is difficult to define the most suitable neural network architecture because this definition is based on previous knowledge and depends on the problem domain. To address this problem, we propose a constructive autoassociative neural network called CANet (Constructive Autoassociative Neural Network. CANet integrates the concepts of receptive fields and autoassociative memory in a dynamic architecture that changes the configuration of the receptive fields by adding new neurons in the hidden layer, while a pruning algorithm removes neurons from the output layer. Neurons in the CANet output layer present lateral inhibitory connections that improve the recognition rate. Experiments in face recognition and facial expression recognition show that the CANet outperforms other methods presented in the literature.

  18. Ascorbic acid alters cell fate commitment of human neural progenitors in a WNT/β-catenin/ROS signaling dependent manner.

    Science.gov (United States)

    Rharass, Tareck; Lantow, Margareta; Gbankoto, Adam; Weiss, Dieter G; Panáková, Daniela; Lucas, Stéphanie

    2017-10-16

    Improving the neuronal yield from in vitro cultivated neural progenitor cells (NPCs) is an essential challenge in transplantation therapy in neurological disorders. In this regard, Ascorbic acid (AA) is widely used to expand neurogenesis from NPCs in cultures although the mechanisms of its action remain unclear. Neurogenesis from NPCs is regulated by the redox-sensitive WNT/β-catenin signaling pathway. We therefore aimed to investigate how AA interacts with this pathway and potentiates neurogenesis. Effects of 200 μM AA were compared with the pro-neurogenic reagent and WNT/β-catenin signaling agonist lithium chloride (LiCl), and molecules with antioxidant activities i.e. N-acetyl-L-cysteine (NAC) and ruthenium red (RuR), in differentiating neural progenitor ReNcell VM cells. Cells were supplemented with reagents for two periods of treatment: a full period encompassing the whole differentiation process versus an early short period that is restricted to the cell fate commitment stage. Intracellular redox balance and reactive oxygen species (ROS) metabolism were examined by flow cytometry using redox and ROS sensors. Confocal microscopy was performed to assess cell viability, neuronal yield, and levels of two proteins: Nucleoredoxin (NXN) and the WNT/β-catenin signaling component Dishevelled 2 (DVL2). TUBB3 and MYC gene responses were evaluated by quantitative real-time PCR. DVL2-NXN complex dissociation was measured by fluorescence resonance energy transfer (FRET). In contrast to NAC which predictably exhibited an antioxidant effect, AA treatment enhanced ROS metabolism with no cytotoxic induction. Both drugs altered ROS levels only at the early stage of the differentiation as no changes were held beyond the neuronal fate commitment stage. FRET studies showed that AA treatment accelerated the redox-dependent release of the initial pool of DVL2 from its sequestration by NXN, while RuR treatment hampered the dissociation of the two proteins. Accordingly, AA

  19. Kif11 dependent cell cycle progression in radial glial cells is required for proper neurogenesis in the zebrafish neural tube.

    Science.gov (United States)

    Johnson, Kimberly; Moriarty, Chelsea; Tania, Nessy; Ortman, Alissa; DiPietrantonio, Kristina; Edens, Brittany; Eisenman, Jean; Ok, Deborah; Krikorian, Sarah; Barragan, Jessica; Golé, Christophe; Barresi, Michael J F

    2014-03-01

    Radial glia serve as the resident neural stem cells in the embryonic vertebrate nervous system, and their proliferation must be tightly regulated to generate the correct number of neuronal and glial cell progeny in the neural tube. During a forward genetic screen, we recently identified a zebrafish mutant in the kif11 loci that displayed a significant increase in radial glial cell bodies at the ventricular zone of the spinal cord. Kif11, also known as Eg5, is a kinesin-related, plus-end directed motor protein responsible for stabilizing and separating the bipolar mitotic spindle. We show here that Gfap+ radial glial cells express kif11 in the ventricular zone and floor plate. Loss of Kif11 by mutation or pharmacological inhibition with S-trityl-L-cysteine (STLC) results in monoastral spindle formation in radial glial cells, which is characteristic of mitotic arrest. We show that M-phase radial glia accumulate over time at the ventricular zone in kif11 mutants and STLC treated embryos. Mathematical modeling of the radial glial accumulation in kif11 mutants not only confirmed an ~226× delay in mitotic exit (likely a mitotic arrest), but also predicted two modes of increased cell death. These modeling predictions were supported by an increase in the apoptosis marker, anti-activated Caspase-3, which was also found to be inversely proportional to a decrease in cell proliferation. In addition, treatment with STLC at different stages of neural development uncovered two critical periods that most significantly require Kif11 function for stem cell progression through mitosis. We also show that loss of Kif11 function causes specific reductions in oligodendroglia and secondary interneurons and motorneurons, suggesting these later born populations require proper radial glia division. Despite these alterations to cell cycle dynamics, survival, and neurogenesis, we document unchanged cell densities within the neural tube in kif11 mutants, suggesting that a mechanism of

  20. Altered orbitofrontal activity and dorsal striatal connectivity during emotion processing in dependent marijuana users after 28 days of abstinence.

    Science.gov (United States)

    Zimmermann, Kaeli; Yao, Shuxia; Heinz, Marcel; Zhou, Feng; Dau, Wolfgang; Banger, Markus; Weber, Bernd; Hurlemann, René; Becker, Benjamin

    2017-12-02

    Intact cognitive and emotional functioning is vital for the long-term success of addiction treatment strategies. Accumulating evidence suggests an association between chronic marijuana use and lasting alterations in cognitive brain function. Despite initial evidence for altered emotion processing in dependent marijuana users after short abstinence periods, adaptations in the domain of emotion processing after longer abstinence remain to be determined. Using task-based and resting state fMRI, the present study investigated emotion processing in 19 dependent marijuana users and 18 matched non-using controls after an abstinence period of > 28 days. Relative to the control subjects, negative emotional stimuli elicited increased medial orbitofrontal cortex (mOFC) activity and stronger mOFC-dorsal striatal and mOFC-amygdala functional coupling in dependent marijuana users (p evidence for persisting emotion processing alterations in dependent marijuana users. Alterations might reflect long-term neural adaptations as a consequence of chronic marijuana use or predisposing risk factors for the development of marijuana dependence.

  1. HDAC6 maintains mitochondrial connectivity under hypoxic stress by suppressing MARCH5/MITOL dependent MFN2 degradation

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Hak-June [Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon, 305-764 (Korea, Republic of); Nagano, Yoshito [Department of Clinical Neuroscience and Therapeutics, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, 734-8551 (Japan); Choi, Su Jin; Park, Song Yi [Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon, 305-764 (Korea, Republic of); Kim, Hongtae [Department of Biological Sciences, Sungkyunkwan University (SKKU), Suwon, 440-746 (Korea, Republic of); Yao, Tso-Pang, E-mail: tsopang.yao@duke.edu [Department of Pharmacology and Cancer Biology, Duke University, Durham, NC 27710 (United States); Lee, Joo-Yong, E-mail: leejooyong@cnu.ac.kr [Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon, 305-764 (Korea, Republic of)

    2015-09-04

    Mitochondria undergo fusion and fission in response to various metabolic stresses. Growing evidences have suggested that the morphological change of mitochondria by fusion and fission plays a critical role in protecting mitochondria from metabolic stresses. Here, we showed that hypoxia treatment could induce interaction between HDAC6 and MFN2, thus protecting mitochondrial connectivity. Mechanistically, we demonstrated that a mitochondrial ubiquitin ligase MARCH5/MITOL was responsible for hypoxia-induced MFN2 degradation in HDAC6 deficient cells. Notably, genetic abolition of HDAC6 in amyotrophic lateral sclerosis model mice showed MFN2 degradation with MARCH5 induction. Our results indicate that HDAC6 is a critical regulator of MFN2 degradation by MARCH5, thus protecting mitochondrial connectivity from hypoxic stress. - Highlights: • Hypoxic stress induces the interaction between HDAC6 and MFN2. • Hypoxic stress activates MARCH5 in HDAC6 deficient cells to degrade MFN2. • HDAC6 is required to maintain mitochondrial connectivity under hypoxia. • MARCH5 is increased and promotes the degradation of MFN2 in HDAC6 KO ALS mice.

  2. Synapses of horizontal connections in adult rat somatosensory cortex have different properties depending on the source of their axons.

    Science.gov (United States)

    Hickmott, Peter W

    2010-03-01

    In somatosensory cortex (S1) tactile stimulation activates specific regions. The borders between representations of different body parts constrain the spread of excitation and inhibition: connections that cross from one representation to another (cross-border, CB) are weaker than those remaining within the representation (noncross border, NCB). Thus, physiological properties of CB and NCB synapses onto layer 2/3 pyramidal neurons were compared using whole-cell recordings in layer 2/3 neurons close to the border between the forepaw and lower jaw representations. Electrical stimulation of CB and NCB connections was used to activate synaptic potentials. Properties of excitatory (EPSPs) and inhibitory (IPSPs) postsynaptic potentials (PSP) were determined using 3 methods: 1) minimal stimulation to elicit single-fiber responses; 2) stimulation in the presence of extracellular Sr(2+) to elicit asynchronous quantal responses; 3) short trains of stimulation at various frequencies to examine postsynaptic potential (PSP) dynamics. Both minimal and asynchronous quantal EPSPs were smaller when evoked by CB than NCB stimulation. However, the dynamics of EPSP and IPSP trains were not different between CB and NCB stimulation. These data suggest that individual excitatory synapses from connections that cross a border (CB) have smaller amplitudes than those that come from within a representation (NCB), and suggest a postsynaptic locus for the difference.

  3. Exponential Antisynchronization Control of Stochastic Memristive Neural Networks with Mixed Time-Varying Delays Based on Novel Delay-Dependent or Delay-Independent Adaptive Controller

    Directory of Open Access Journals (Sweden)

    Minghui Yu

    2017-01-01

    Full Text Available The global exponential antisynchronization in mean square of memristive neural networks with stochastic perturbation and mixed time-varying delays is studied in this paper. Then, two kinds of novel delay-dependent and delay-independent adaptive controllers are designed. With the ability of adapting to environment changes, the proposed controllers can modify their behaviors to achieve the best performance. In particular, on the basis of the differential inclusions theory, inequality theory, and stochastic analysis techniques, several sufficient conditions are obtained to guarantee the exponential antisynchronization between the drive system and response system. Furthermore, two numerical simulation examples are provided to the validity of the derived criteria.

  4. 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.

  5. Longitudinal functional connectivity changes correlate with mood improvement after regular exercise in a dose-dependent fashion.

    Science.gov (United States)

    Tozzi, Leonardo; Carballedo, Angela; Lavelle, Grace; Doolin, Kelly; Doyle, Myles; Amico, Francesco; McCarthy, Hazel; Gormley, John; Lord, Anton; O'Keane, Veronica; Frodl, Thomas

    2016-04-01

    Exercise increases wellbeing and improves mood. It is however unclear how these mood changes relate to brain function. We conducted a randomized controlled trial investigating resting-state modifications in healthy adults after an extended period of aerobic physical exercise and their relationship with mood improvements. We aimed to identify novel functional networks whose activity could provide a physiological counterpart to the mood-related benefits of exercise. Thirty-eight healthy sedentary volunteers were randomised to either the aerobic exercise group of the study or a control group. Participants in the exercise group attended aerobic sessions with a physiotherapist twice a week for 16 weeks. Resting-state modifications using magnetic resonance imaging were assessed before and after the programme and related to mood changes. An unbiased approach using graph metrics and network-based statistics was adopted. Exercise reduced mood disturbance and improved emotional wellbeing. It also induced a decrease in local efficiency in the parahippocampal lobe through strengthening of the functional connections from this structure to the supramarginal gyrus, precentral area, superior temporal gyrus and temporal pole. Changes in mood disturbance following exercise were correlated with those in connectivity between parahippocampal gyrus and superior temporal gyrus as well as with the amount of training. No changes were detected in the control group. In conclusion, connectivity from the parahippocampal gyrus to motor, sensory integration and mood regulation areas was strengthened through exercise. These functional changes might be related to the benefits of regular physical activity on mood. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  6. The matrix metalloproteinase inhibitor marimastat promotes neural progenitor cell differentiation into neurons by gelatinase-independent TIMP-2-dependent mechanisms.

    Science.gov (United States)

    Sinno, Maddalena; Biagioni, Stefano; Ajmone-Cat, Maria Antonietta; Pafumi, Irene; Caramanica, Pasquale; Medda, Virginia; Tonti, Gaetana; Minghetti, Luisa; Mannello, Ferdinando; Cacci, Emanuele

    2013-02-01

    Metalloproteinases (MMPs) and their endogenous inhibitors (TIMPs), produced in the brain by cells of non-neural and neural origin, including neural progenitors (NPs), are emerging as regulators of nervous system development and adult brain functions. In the present study, we explored whether MMP-2, MMP-9, and TIMP-2, abundantly produced in the brain, modulate NP developmental properties. We found that treatment of NPs, isolated from the murine fetal cerebral cortex or adult subventricular zone, with the clinically tested broad-spectrum MMP inhibitor Marimastat profoundly affected the NP differentiation fate. Marimastat treatment allowed for an enrichment of our cultures in neuronal cells, inducing NPs to generate higher percentage of neurons and a lower percentage of astrocytes, possibly affecting NP commitment. Consistently with its proneurogenic effect, Marimastat early downregulated the expression of Notch target genes, such as Hes1 and Hes5. MMP-2 and MMP-9 profiling on proliferating and differentiating NPs revealed that MMP-9 was not expressed under these conditions, whereas MMP-2 increased in the medium as pro-MMP-2 (72 kDa) during differentiation; its active form (62 kDa) was not detectable by gel zymography. MMP-2 silencing or administration of recombinant active MMP-2 demonstrated that MMP-2 does not affect NP neuronal differentiation, nor it is involved in the Marimastat proneurogenic effect. We also found that TIMP-2 is expressed in NPs and increases during late differentiation, mainly as a consequence of astrocyte generation. Endogenous TIMP-2 did not modulate NP neurogenic potential; however, the proneurogenic action of Marimastat was mediated by TIMP-2, as demonstrated by silencing experiments. In conclusion, our data exclude a major involvement of MMP-2 and MMP-9 in the regulation of basal NP differentiation, but highlight the ability of TIMP-2 to act as key effector of the proneurogenic response to an inducing stimulus such as Marimastat.

  7. Context-dependent neural activation: internally and externally guided rhythmic lower limb movement in individuals with and without neurodegenerative disease

    Directory of Open Access Journals (Sweden)

    Madeleine Eve Hackney

    2015-12-01

    Full Text Available Parkinson’s Disease (PD is a neurodegenerative disorder that has received considerable attention in allopathic medicine over the past decades. However, it is clear that, to date, pharmacological and surgical interventions do not fully address symptoms of PD and patients’ quality of life. As both an alternative therapy and as an adjuvant to conventional approaches, several types of rhythmic movement (e.g., movement strategies, dance, tandem biking, tai chi have shown improvements to motor symptoms, lower limb control and postural stability in people with PD (Amano, Nocera, Vallabhajosula, Juncos, Gregor, Waddell et al., 2013; Earhart, 2009; M. E. Hackney & Earhart, 2008; Kadivar, Corcos, Foto, & Hondzinski, 2011; Morris, Iansek, & Kirkwood, 2009; Ridgel, Vitek, & Alberts, 2009. However, while these programs are increasing in number, still little is known about the neural mechanisms underlying motor improvements attained with such interventions. Studying limb motor control under task specific contexts can help determine the mechanisms of rehabilitation effectiveness. Both internally guided (IG and externally guided (EG movement strategies have evidence to support their use in rehabilitative programs. However, there appears to be a degree of differentiation in the neural substrates involved in IG versus EG designs. Because of the potential task specific benefits of rhythmic training within a rehabilitative context, this report will consider the use of IG and EG movement strategies, and observations produced by functional magnetic resonance imaging (fMRI and other imaging techniques. This review will present findings from lower limb imaging studies, under IG and EG conditions for populations with and without movement disorders. We will discuss how these studies might inform movement disorders rehabilitation (in the form of rhythmic, music-based movement training and highlight research gaps. We believe better understanding of lower limb neural

  8. The positional identity of iPSC-derived neural progenitor cells along the anterior-posterior axis is controlled in a dosage-dependent manner by bFGF and EGF

    DEFF Research Database (Denmark)

    Zhou, Shuling; Ochalek, Anna; Szczesna, Karolina

    2016-01-01

    Neural rosettes derived from human induced pluripotent stem cells (iPSCs) have been claimed to be a highly robust in vitro cellular model for biomedical application. They are able to propagate in vitro in the presence of mitogens, including basic fibroblast growth factor (bFGF) and epidermal growth...... factor (EGF). However, these two mitogens are also involved in anterior-posterior patterning in a gradient dependent manner along the neural tube axis. Here, we compared the regional identity of neural rosette cells and specific neural subtypes of their progeny propagated with low and high concentrations...... of bFGF and EGF. We observed that low concentrations of bFGF and EGF in the culturing system were able to induce forebrain identity of the neural rosettes and promote subsequent cortical neuronal differentiation. On the contrary, high concentrations of these mitogens stimulate a mid-hindbrain fate...

  9. Changes in pitch height elicit both language-universal and language-dependent changes in neural representation of pitch in the brainstem and auditory cortex.

    Science.gov (United States)

    Krishnan, Ananthanarayan; Suresh, Chandan H; Gandour, Jackson T

    2017-03-27

    Language experience shapes encoding of pitch-relevant information at both brainstem and cortical levels of processing. Pitch height is a salient dimension that orders pitch from low to high. Herein we investigate the effects of language experience (Chinese, English) in the brainstem and cortex on (i) neural responses to variations in pitch height, (ii) presence of asymmetry in cortical pitch representation, and (iii) patterns of relative changes in magnitude of pitch height between these two levels of brain structure. Stimuli were three nonspeech homologs of Mandarin Tone 2 varying in pitch height only. The frequency-following response (FFR) and the cortical pitch-specific response (CPR) were recorded concurrently. At the Fz-linked T7/T8 site, peak latency of Na, Pb, and Nb decreased with increasing pitch height for both groups. Peak-to-peak amplitude of Na-Pb and Pb-Nb increased with increasing pitch height across groups. A language-dependent effect was restricted to Na-Pb; the Chinese had larger amplitude than the English group. At temporal sites (T7/T8), the Chinese group had larger amplitude, as compared to English, across stimuli, but also limited to the Na-Pb component and right temporal site. In the brainstem, F0 magnitude decreased with increasing pitch height; Chinese had larger magnitude across stimuli. A comparison of CPR and FFR responses revealed distinct patterns of relative changes in magnitude common to both groups. CPR amplitude increased and FFR amplitude decreased with increasing pitch height. Experience-dependent effects on CPR components vary as a function of neural sensitivity to pitch height within a particular temporal window (Na-Pb). Differences between the auditory brainstem and cortex imply distinct neural mechanisms for pitch extraction at both levels of brain structure. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

  10. 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.

  11. Boys vs. girls: Gender differences in the neural development of trust and reciprocity depend on social context.

    Science.gov (United States)

    Lemmers-Jansen, Imke L J; Krabbendam, Lydia; Veltman, Dick J; Fett, Anne-Kathrin J

    2017-06-01

    Trust and cooperation increase from adolescence to adulthood, but studies on gender differences in this development are rare. We investigated gender and age-related differences in trust and reciprocity and associated neural mechanisms in 43 individuals (16-27 years, 22 male). Participants played two multi-round trust games with a cooperative and an unfair partner. Males showed more basic trust towards unknown others than females. Both genders increased trust during cooperative interactions, with no differences in average trust. Age was unrelated to trust during cooperation. During unfair interactions males decreased their trust more with age than females. ROI analysis showed age-related increases in activation in the temporo-parietal junction (TPJ) and dorsolateral prefrontal cortex (dlPFC) during cooperative investments, and increased age-related caudate activation during both cooperative and unfair repayments. Gender differences in brain activation were only observed during cooperative repayments, with males activating the TPJ more than females, and females activating the caudate more. The findings suggest relatively mature processes of trust and reciprocity in the investigated age range. Gender differences only occur in unfair contexts, becoming more pronounced with age. Largely similar neural activation in males and females and few age effects suggest that similar, mature cognitive strategies are employed. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  12. Evidence of adaptations of locomotor neural drive in response to enhanced intermuscular connectivity between the triceps surae muscles of the rat

    OpenAIRE

    Bernabei, Michel; van Dieën, Jaap H.; Maas, Huub

    2017-01-01

    The aims of this study were to investigate changes 1) in the coordination of activation of the triceps surae muscle group, and 2) in muscle belly length of soleus (SO) and lateral gastrocnemius (LG) during locomotion (trotting) in response to increased stiffness of intermuscular connective tissues in the rat. We measured muscle activation and muscle belly lengths, as well as hindlimb kinematics, before and after an artificial enhancement of the connectivity between SO and LG muscles obtained ...

  13. Evidence of adaptations of locomotor neural drive in response to enhanced intermuscular connectivity between the triceps surae muscles of the rat.

    Science.gov (United States)

    Bernabei, Michel; van Dieën, Jaap H; Maas, Huub

    2017-09-01

    The aims of this study were to investigate changes 1) in the coordination of activation of the triceps surae muscle group, and 2) in muscle belly length of soleus (SO) and lateral gastrocnemius (LG) during locomotion (trotting) in response to increased stiffness of intermuscular connective tissues in the rat. We measured muscle activation and muscle belly lengths, as well as hindlimb kinematics, before and after an artificial enhancement of the connectivity between SO and LG muscles obtained by implanting a tissue-integrating surgical mesh at the muscles' interface. We found that SO muscle activation decreased to 62%, while activation of LG and medial gastrocnemius muscles increased to 134 and 125%, respectively, compared with the levels measured preintervention. Although secondary additional or amplified activation bursts were observed with enhanced connectivity, the primary pattern of activation over the stride and the burst duration were not affected by the intervention. Similar muscle length changes after manipulation were observed, suggesting that length feedback from spindle receptors within SO and LG was not affected by the connectivity enhancement. We conclude that peripheral mechanical constraints given by morphological (re)organization of connective tissues linking synergists are taken into account by the central nervous system. The observed shift in activity toward the gastrocnemius muscles after the intervention suggests that these larger muscles are preferentially recruited when the soleus has a similar mechanical disadvantage in that it produces an unwanted flexion moment around the knee.NEW & NOTEWORTHY Connective tissue linkages between muscle-tendon units may act as an additional mechanical constraint on the musculoskeletal system, thereby reducing the spectrum of solutions for performing a motor task. We found that intermuscular coordination changes following intermuscular connectivity enhancement. Besides showing that the extent of such

  14. Neural Plasticity in Human Brain Connectivity: The Effects of Long Term Deep Brain Stimulation of the Subthalamic Nucleus in Parkinson's Disease

    OpenAIRE

    van Hartevelt, Tim J; Joana Cabral; Gustavo Deco; Arne Møller; Green, Alexander L.; Aziz, Tipu Z.; Morten L Kringelbach

    2014-01-01

    Background: Positive clinical outcomes are now well established for deep brain stimulation, but little is known about the effects of long-term deep brain stimulation on brain structural and functional connectivity. Here, we used the rare opportunity to acquire pre- and postoperative diffusion tensor imaging in a patient undergoing deep brain stimulation in bilateral subthalamic nuclei for Parkinson’s Disease. This allowed us to analyse the differences in structural connectivity before and aft...

  15. A gradual depth-dependent change in connectivity features of supragranular pyramidal cells in rat barrel cortex.

    Science.gov (United States)

    Staiger, Jochen F; Bojak, Ingo; Miceli, Stéphanie; Schubert, Dirk

    2015-01-01

    Recent experimental evidence suggests a finer genetic, structural and functional subdivision of the layers which form a cortical column. The classical layer II/III (LII/III) of rodent neocortex integrates ascending sensory information with contextual cortical information for behavioral read-out. We systematically investigated to which extent regular-spiking supragranular pyramidal neurons, located at different depths within the cortex, show different input-output connectivity patterns. Combining glutamate uncaging with whole-cell recordings and biocytin filling, we revealed a novel cellular organization of LII/III: (1) "Lower LII/III" pyramidal cells receive a very strong excitatory input from lemniscal LIV and much fewer inputs from paralemniscal LVa. They project to all layers of the home column, including a feedback projection to LIV, whereas transcolumnar projections are relatively sparse. (2) "Upper LII/III" pyramidal cells also receive their strongest input from LIV, but in addition, a very strong and dense excitatory input from LVa. They project extensively to LII/III as well as LVa and Vb of their home and neighboring columns. (3) "Middle LII/III" pyramidal cell shows an intermediate connectivity phenotype that stands in many ways in between the features described for lower versus upper LII/III. "Lower LII/III" intracolumnarly segregates and transcolumnarly integrates lemniscal information, whereas "upper LII/III" seems to integrate lemniscal with paralemniscal information. This suggests a fine-grained functional subdivision of the supragranular compartment containing multiple circuits without any obvious cytoarchitectonic, other structural or functional correlate of a laminar border in rodent barrel cortex.

  16. The nonlinear heat equation with state–dependent parameters and its connection to the Burgers’ and the potential Burgers’ equation

    DEFF Research Database (Denmark)

    Backi, Christoph Josef; Bendtsen, Jan Dimon; Leth, John-Josef

    2014-01-01

    In this work the stability properties of a nonlinear partial differential equation (PDE) with state–dependent parameters is investigated. Among other things, the PDE describes freezing of foodstuff, and is closely related to the (Potential) Burgers’ Equation. We show that for certain forms...

  17. Dopaminergic drug effects during reversal learning depend on anatomical connections between the orbitofrontal cortex and the amygdala

    NARCIS (Netherlands)

    Schaaf, Marieke van der; Zwiers, M.P.; Schouwenburg, M.R. van; Geurts, D.E.M.; Schellekens, A.F.A.; Buitelaar, J.; Verkes, R.J.; Cools, R.

    2013-01-01

    Dopamine in the striatum is known to be important for reversal learning. However, the striatum does not act in isolation and reversal learning is also well accepted to depend on the orbitofrontal cortex (OFC) and the amygdala. Here we assessed whether dopaminergic drug effects on human striatal BOLD

  18. Dopaminergic drug effects during reversal learning depend on anatomical connections between the orbitofrontal cortex and the amygdala

    NARCIS (Netherlands)

    Schaaf, M.E. van der; Zwiers, M.P.; Schouwenburg, M.R. van; Geurts, D.E.M.; Schellekens, A.F.A.; Buitelaar, J.K.; Verkes, R.J.; Cools, R.

    2013-01-01

    Dopamine in the striatum is known to be important for reversal learning. However, the striatum does not act in isolation and reversal learning is also well-accepted to depend on the orbitofrontal cortex (OFC) and the amygdala. Here we assessed whether dopaminergic drug effects on human striatal BOLD

  19. Frequency-dependent functional connectivity within resting-state networks: An atlas-based MEG beamformer solution

    NARCIS (Netherlands)

    Hillebrand, A.; Barnes, G.R.; Bosboom, J.L.; Berendse, H.W.; Stam, C.J.

    2012-01-01

    The brain consists of functional units with more-or-less specific information processing capabilities, yet cognitive functions require the co-ordinated activity of these spatially separated units. Magnetoencephalography (MEG) has the temporal resolution to capture these frequency-dependent

  20. A Laboratory Study on Stress Dependency of Joint Transmissivity and its Modeling with Neural Networks, Fuzzy Method and Regression Analysis

    Directory of Open Access Journals (Sweden)

    Amin Moori Roozali

    2014-08-01

    Full Text Available Correct estimation of water inflow into underground excavations can decrease safety risks and associated costs. Researchers have proposed different methods to asses this value. It has been proved that water transmissivity of a rock joint is a function of factors, such as normal stress, joint roughness and its size and water pressure therefore, a laboratory setup was proposed to quantitatively measure the flow as a function of mentioned parameters. Among these, normal stress has proved to be the most influential parameter. With increasing joint roughness and rock sample size, water flow has decreased while increasing water pressure has a direct increasing effect on the flow. To simulate the complex interaction of these parameters, neural networks and Fuzzy method together with regression analysis have been utilized. Correlation factors between laboratory results and obtained numerical ones show good agreement which proves usefulness of these methods for assessment of water inflow.

  1. Auto-Associative Recurrent Neural Networks and Long Term Dependencies in Novelty Detection for Audio Surveillance Applications

    Science.gov (United States)

    Rossi, A.; Montefoschi, F.; Rizzo, A.; Diligenti, M.; Festucci, C.

    2017-10-01

    Machine Learning applied to Automatic Audio Surveillance has been attracting increasing attention in recent years. In spite of several investigations based on a large number of different approaches, little attention had been paid to the environmental temporal evolution of the input signal. In this work, we propose an exploration in this direction comparing the temporal correlations extracted at the feature level with the one learned by a representational structure. To this aim we analysed the prediction performances of a Recurrent Neural Network architecture varying the length of the processed input sequence and the size of the time window used in the feature extraction. Results corroborated the hypothesis that sequential models work better when dealing with data characterized by temporal order. However, so far the optimization of the temporal dimension remains an open issue.

  2. Activity-dependent plasticity in the isolated embryonic avian brainstem following manipulations of rhythmic spontaneous neural activity.

    Science.gov (United States)

    Vincen-Brown, Michael A; Revill, Ann L; Pilarski, Jason Q

    2016-07-15

    When rhythmic spontaneous neural activity (rSNA) first appears in the embryonic chick brainstem and cranial nerve motor axons it is principally driven by nicotinic neurotransmission (NT). At this early age, the nicotinic acetylcholine receptor (nAChR) agonist nicotine is known to critically disrupt rSNA at low concentrations (0.1-0.5μM), which are levels that mimic the blood plasma levels of a fetus following maternal cigarette smoking. Thus, we quantified the effect of persistent exposure to exogenous nicotine on rSNA using an in vitro developmental model. We found that rSNA was eliminated by continuous bath application of exogenous nicotine, but rSNA recovered activity within 6-12h despite the persistent activation and desensitization of nAChRs. During the recovery period rSNA was critically driven by chloride-mediated membrane depolarization instead of nicotinic NT. To test whether this observed compensation was unique to the antagonism of nicotinic NT or whether the loss of spiking behavior also played a role, we eliminated rSNA by lowering overall excitatory drive with a low [K(+)]o superfusate. In this context, rSNA again recovered, although the recovery time was much quicker, and exhibited a lower frequency, higher duration, and an increase in the number of bursts per episode when compared to control embryos. Importantly, we show that the main compensatory response to lower overall excitatory drive, similar to nicotinergic block, is a result of potentiated chloride mediated membrane depolarization. These results support increasing evidence that early neural circuits sense spiking behavior to maintain primordial bioelectric rhythms. Understanding the nature of developmental plasticity in the nervous system, especially versions that preserve rhythmic behaviors following clinically meaningful environmental stimuli, both normal and pathological, will require similar studies to determine the consequences of feedback compensation at more mature chronological ages

  3. Dynamic culture induces a cell type-dependent response impacting on the thickness of engineered connective tissues.

    Science.gov (United States)

    Fortier, Guillaume Marceau; Gauvin, Robert; Proulx, Maryse; Vallée, Maud; Fradette, Julie

    2013-04-01

    Mesenchymal cells are central to connective tissue homeostasis and are widely used for tissue-engineering applications. Dermal fibroblasts and adipose-derived stromal cells (ASCs) allow successful tissue reconstruction by the self-assembly approach of tissue engineering. This method leads to the production of multilayered tissues, devoid of exogenous biomaterials, that can be used as stromal compartments for skin or vesical reconstruction. These tissues are formed by combining cell sheets, generated through cell stimulation with ascorbic acid, which favours the cell-derived production/organization of matrix components. Since media motion can impact on cell behaviour, we investigated the effect of dynamic culture on mesenchymal cells during tissue reconstruction, using the self-assembly method. Tissues produced using ASCs in the presence of a wave-like movement were nearly twice thicker than under standard conditions, while no difference was observed for tissues produced from dermal fibroblasts. The increased matrix deposition was not correlated with an increased proliferation of ASCs, or by higher transcript levels of fibronectin or collagens I and III. A 30% increase of type V collagen mRNA was observed. Interestingly, tissues engineered from dermal fibroblasts featured a four-fold higher level of MMP-1 transcripts under dynamic conditions. Mechanical properties were similar for tissues reconstructed using dynamic or static conditions. Finally, cell sheets produced using ASCs under dynamic conditions could readily be manipulated, resulting in a 2 week reduction of the production time (from 5 to 3 weeks). Our results describe a distinctive property of ASCs' response to media motion, indicating that their culture under dynamic conditions leads to optimized tissue engineering. Copyright © 2011 John Wiley & Sons, Ltd.

  4. The SPF27 homologue Num1 connects splicing and kinesin 1-dependent cytoplasmic trafficking in Ustilago maydis.

    Science.gov (United States)

    Kellner, Nikola; Heimel, Kai; Obhof, Theresa; Finkernagel, Florian; Kämper, Jörg

    2014-01-01

    The conserved NineTeen protein complex (NTC) is an integral subunit of the spliceosome and required for intron removal during pre-mRNA splicing. The complex associates with the spliceosome and participates in the regulation of conformational changes of core spliceosomal components, stabilizing RNA-RNA- as well as RNA-protein interactions. In addition, the NTC is involved in cell cycle checkpoint control, response to DNA damage, as well as formation and export of mRNP-particles. We have identified the Num1 protein as the homologue of SPF27, one of NTC core components, in the basidiomycetous fungus Ustilago maydis. Num1 is required for polarized growth of the fungal hyphae, and, in line with the described NTC functions, the num1 mutation affects the cell cycle and cell division. The num1 deletion influences splicing in U. maydis on a global scale, as RNA-Seq analysis revealed increased intron retention rates. Surprisingly, we identified in a screen for Num1 interacting proteins not only NTC core components as Prp19 and Cef1, but several proteins with putative functions during vesicle-mediated transport processes. Among others, Num1 interacts with the motor protein Kin1 in the cytoplasm. Similar phenotypes with respect to filamentous and polar growth, vacuolar morphology, as well as the motility of early endosomes corroborate the genetic interaction between Num1 and Kin1. Our data implicate a previously unidentified connection between a component of the splicing machinery and cytoplasmic transport processes. As the num1 deletion also affects cytoplasmic mRNA transport, the protein may constitute a novel functional interconnection between the two disparate processes of splicing and trafficking.

  5. The SPF27 homologue Num1 connects splicing and kinesin 1-dependent cytoplasmic trafficking in Ustilago maydis.

    Directory of Open Access Journals (Sweden)

    Nikola Kellner

    2014-01-01

    Full Text Available The conserved NineTeen protein complex (NTC is an integral subunit of the spliceosome and required for intron removal during pre-mRNA splicing. The complex associates with the spliceosome and participates in the regulation of conformational changes of core spliceosomal components, stabilizing RNA-RNA- as well as RNA-protein interactions. In addition, the NTC is involved in cell cycle checkpoint control, response to DNA damage, as well as formation and export of mRNP-particles. We have identified the Num1 protein as the homologue of SPF27, one of NTC core components, in the basidiomycetous fungus Ustilago maydis. Num1 is required for polarized growth of the fungal hyphae, and, in line with the described NTC functions, the num1 mutation affects the cell cycle and cell division. The num1 deletion influences splicing in U. maydis on a global scale, as RNA-Seq analysis revealed increased intron retention rates. Surprisingly, we identified in a screen for Num1 interacting proteins not only NTC core components as Prp19 and Cef1, but several proteins with putative functions during vesicle-mediated transport processes. Among others, Num1 interacts with the motor protein Kin1 in the cytoplasm. Similar phenotypes with respect to filamentous and polar growth, vacuolar morphology, as well as the motility of early endosomes corroborate the genetic interaction between Num1 and Kin1. Our data implicate a previously unidentified connection between a component of the splicing machinery and cytoplasmic transport processes. As the num1 deletion also affects cytoplasmic mRNA transport, the protein may constitute a novel functional interconnection between the two disparate processes of splicing and trafficking.

  6. Evolutionary connection between the catalytic subunits of DNA-dependent RNA polymerases and eukaryotic RNA-dependent RNA polymerases and the origin of RNA polymerases

    Directory of Open Access Journals (Sweden)

    Aravind L

    2003-01-01

    Full Text Available Abstract Background The eukaryotic RNA-dependent RNA polymerase (RDRP is involved in the amplification of regulatory microRNAs during post-transcriptional gene silencing. This enzyme is highly conserved in most eukaryotes but is missing in archaea and bacteria. No evolutionary relationship between RDRP and other polymerases has been reported so far, hence the origin of this eukaryote-specific polymerase remains a mystery. Results Using extensive sequence profile searches, we identified bacteriophage homologs of the eukaryotic RDRP. The comparison of the eukaryotic RDRP and their homologs from bacteriophages led to the delineation of the conserved portion of these enzymes, which is predicted to harbor the catalytic site. Further, detailed sequence comparison, aided by examination of the crystal structure of the DNA-dependent RNA polymerase (DDRP, showed that the RDRP and the β' subunit of DDRP (and its orthologs in archaea and eukaryotes contain a conserved double-psi β-barrel (DPBB domain. This DPBB domain contains the signature motif DbDGD (b is a bulky residue, which is conserved in all RDRPs and DDRPs and contributes to catalysis via a coordinated divalent cation. Apart from the DPBB domain, no similarity was detected between RDRP and DDRP, which leaves open two scenarios for the origin of RDRP: i RDRP evolved at the onset of the evolution of eukaryotes via a duplication of the DDRP β' subunit followed by dramatic divergence that obliterated the sequence similarity outside the core catalytic domain and ii the primordial RDRP, which consisted primarily of the DPBB domain, evolved from a common ancestor with the DDRP at a very early stage of evolution, during the RNA world era. The latter hypothesis implies that RDRP had been subsequently eliminated from cellular life forms and might have been reintroduced into the eukaryotic genomes through a bacteriophage. Sequence and structure analysis of the DDRP led to further insights into the

  7. Intramolecular activation of a Ca(2+)-dependent protein kinase is disrupted by insertions in the tether that connects the calmodulin-like domain to the kinase

    Science.gov (United States)

    Vitart, V.; Christodoulou, J.; Huang, J. F.; Chazin, W. J.; Harper, J. F.; Evans, M. L. (Principal Investigator)

    2000-01-01

    Ca(2+)-dependent protein kinases (CDPK) have a calmodulin-like domain (CaM-LD) tethered to the C-terminal end of the kinase. Activation is proposed to involve intramolecular binding of the CaM-LD to a junction sequence that connects the CaM-LD to the kinase domain. Consistent with this model, a truncated CDPK (DeltaNC) in which the CaM-LD has been deleted can be activated in a bimolecular interaction with an isolated CaM-LD or calmodulin, similar to the activation of a calmodulin-dependent protein kinase (CaMK) by calmodulin. Here we provide genetic evidence that this bimolecular activation requires a nine-residue binding segment from F436 to I444 (numbers correspond to CPK-1 accession number L14771). Two mutations at either end of this core segment (F436/A and VI444/AA) severely disrupted bimolecular activation, whereas flanking mutations had only minor effects. Intramolecular activation of a full-length kinase was also disrupted by a VI444/AA mutation, but surprisingly not by a F436/A mutation (at the N-terminal end of the binding site). Interestingly, intramolecular but not bimolecular activation was disrupted by insertion mutations placed immediately downstream of I444. To show that mutant enzymes were not misfolded, latent kinase activity was stimulated through binding of an antijunction antibody. Results here support a model of intramolecular activation in which the tether (A445 to G455) that connects the CaM-LD to the kinase provides an important structural constraint and is not just a simple flexible connection.

  8. Evidence of adaptations of locomotor neural drive in response to enhanced intermuscular connectivity between the triceps surae muscles of the rat

    NARCIS (Netherlands)

    Bernabei, Michel; van Dieën, Jaap H.; Maas, Huub

    2017-01-01

    The aims of this study were to investigate changes 1) in the coordination of activation of the triceps surae muscle group, and 2) in muscle belly length of soleus (SO) and lateral gastrocnemius (LG) during locomotion (trotting) in response to increased stiffness of intermuscular connective tissues

  9. Oxygen-dependent acetylation and dimerization of the corepressor CtBP2 in neural stem cells

    Energy Technology Data Exchange (ETDEWEB)

    Karaca, Esra; Lewicki, Jakub; Hermanson, Ola, E-mail: Ola.Hermanson@ki.se

    2015-03-01

    The transcriptional corepressor CtBP2 is essential for proper development of the nervous system. The factor exerts its repression by interacting in complexes with chromatin-modifying factors such as histone deacetylases (HDAC) 1/2 and the histone demethylase LSD1/KDM1. Notably, the histone acetyl transferase p300 acetylates CtBP2 and this is an important regulatory event of the activity and subcellular localization of the protein. We recently demonstrated an essential role for CtBPs as sensors of microenvironmental oxygen levels influencing the differentiation potential of neural stem cells (NSCs), but it is not known whether oxygen levels influence the acetylation levels of CtBP factors. Here we show by using proximity ligation assay (PLA) that CtBP2 acetylation levels increased significantly in undifferentiated, proliferating NSCs under hypoxic conditions. CtBP2 interacted with the class III HDAC Sirt1 but this interaction was unaltered in hypoxic conditions, and treatment with the Sirt1 inhibitor Ex527 did not result in any significant change in total CtBP2 acetylation levels. Instead, we revealed a significant decrease in PLA signal representing CtBP2 dimerization in NSCs under hypoxic conditions, negatively correlating with the acetylation levels. Our results suggest that microenvironmental oxygen levels influence the dimerization and acetylation levels, and thereby the activity, of CtBP2 in proliferating NSCs.

  10. Neural cell adhesion molecule-stimulated neurite outgrowth depends on activation of protein kinase C and the Ras-mitogen-activated protein kinase pathway

    DEFF Research Database (Denmark)

    Kolkova, K; Novitskaya, V; Pedersen, N

    2000-01-01

    The signal transduction pathways associated with neural cell adhesion molecule (NCAM)-induced neuritogenesis are only partially characterized. We here demonstrate that NCAM-induced neurite outgrowth depends on activation of p59(fyn), focal adhesion kinase (FAK), phospholipase Cgamma (PLCgamma......), protein kinase C (PKC), and the Ras-mitogen-activated protein (MAP) kinase pathway. This was done using a coculture system consisting of PC12-E2 cells grown on fibroblasts, with or without NCAM expression, allowing NCAM-NCAM interactions resulting in neurite outgrowth. PC12-E2 cells were transiently...... propose a model of NCAM signaling involving two pathways: NCAM-Ras-MAP kinase and NCAM-FGF receptor-PLCgamma-PKC, and we propose that PKC serves as the link between the two pathways activating Raf and thereby creating the sustained activity of the MAP kinases necessary for neuronal differentiation....

  11. Dynamic Effective Connectivity of Inter-Areal Brain Circuits

    Science.gov (United States)

    Battaglia, Demian; Witt, Annette; Wolf, Fred; Geisel, Theo

    2012-01-01

    Anatomic connections between brain areas affect information flow between neuronal circuits and the synchronization of neuronal activity. However, such structural connectivity does not coincide with effective connectivity (or, more precisely, causal connectivity), related to the elusive question “Which areas cause the present activity of which others?”. Effective connectivity is directed and depends flexibly on contexts and tasks. Here we show that dynamic effective connectivity can emerge from transitions in the collective organization of coherent neural activity. Integrating simulation and semi-analytic approaches, we study mesoscale network motifs of interacting cortical areas, modeled as large random networks of spiking neurons or as simple rate units. Through a causal analysis of time-series of model neural activity, we show that different dynamical states generated by a same structural connectivity motif correspond to distinct effective connectivity motifs. Such effective motifs can display a dominant directionality, due to spontaneous symmetry breaking and effective entrainment between local brain rhythms, although all connections in the considered structural motifs are reciprocal. We show then that transitions between effective connectivity configurations (like, for instance, reversal in the direction of inter-areal interactions) can be triggered reliably by brief perturbation inputs, properly timed with respect to an ongoing local oscillation, without the need for plastic synaptic changes. Finally, we analyze how the information encoded in spiking patterns of a local neuronal population is propagated across a fixed structural connectivity motif, demonstrating that changes in the active effective connectivity regulate both the efficiency and the directionality of information transfer. Previous studies stressed the role played by coherent oscillations in establishing efficient communication between distant areas. Going beyond these early proposals, we

  12. Dynamic effective connectivity of inter-areal brain circuits.

    Directory of Open Access Journals (Sweden)

    Demian Battaglia

    Full Text Available Anatomic connections between brain areas affect information flow between neuronal circuits and the synchronization of neuronal activity. However, such structural connectivity does not coincide with effective connectivity (or, more precisely, causal connectivity, related to the elusive question "Which areas cause the present activity of which others?". Effective connectivity is directed and depends flexibly on contexts and tasks. Here we show that dynamic effective connectivity can emerge from transitions in the collective organization of coherent neural activity. Integrating simulation and semi-analytic approaches, we study mesoscale network motifs of interacting cortical areas, modeled as large random networks of spiking neurons or as simple rate units. Through a causal analysis of time-series of model neural activity, we show that different dynamical states generated by a same structural connectivity motif correspond to distinct effective connectivity motifs. Such effective motifs can display a dominant directionality, due to spontaneous symmetry breaking and effective entrainment between local brain rhythms, although all connections in the considered structural motifs are reciprocal. We show then that transitions between effective connectivity configurations (like, for instance, reversal in the direction of inter-areal interactions can be triggered reliably by brief perturbation inputs, properly timed with respect to an ongoing local oscillation, without the need for plastic synaptic changes. Finally, we analyze how the information encoded in spiking patterns of a local neuronal population is propagated across a fixed structural connectivity motif, demonstrating that changes in the active effective connectivity regulate both the efficiency and the directionality of information transfer. Previous studies stressed the role played by coherent oscillations in establishing efficient communication between distant areas. Going beyond these early

  13. Differentiation-Dependent Energy Production and Metabolite Utilization: A Comparative Study on Neural Stem Cells, Neurons, and Astrocytes.

    Science.gov (United States)

    Jády, Attila Gy; Nagy, Ádám M; Kőhidi, Tímea; Ferenczi, Szilamér; Tretter, László; Madarász, Emília

    2016-07-01

    While it is evident that the metabolic machinery of stem cells should be fairly different from that of differentiated neurons, the basic energy production pathways in neural stem cells (NSCs) or in neurons are far from clear. Using the model of in vitro neuron production by NE-4C NSCs, this study focused on the metabolic changes taking place during the in vitro neuronal differentiation. O2 consumption, H(+) production, and metabolic responses to single metabolites were measured in cultures of NSCs and in their neuronal derivatives, as well as in primary neuronal and astroglial cultures. In metabolite-free solutions, NSCs consumed little O2 and displayed a higher level of mitochondrial proton leak than neurons. In stem cells, glycolysis was the main source of energy for the survival of a 2.5-h period of metabolite deprivation. In contrast, stem cell-derived or primary neurons sustained a high-level oxidative phosphorylation during metabolite deprivation, indicating the consumption of own cellular material for energy production. The stem cells increased O2 consumption and mitochondrial ATP production in response to single metabolites (with the exception of glucose), showing rapid adaptation of the metabolic machinery to the available resources. In contrast, single metabolites did not increase the O2 consumption of neurons or astrocytes. In "starving" neurons, neither lactate nor pyruvate was utilized for mitochondrial ATP production. Gene expression studies also suggested that aerobic glycolysis and rapid metabolic adaptation characterize the NE-4C NSCs, while autophagy and alternative glucose utilization play important roles in the metabolism of stem cell-derived neurons.

  14. Effects of cognitive bias modification training on neural signatures of alcohol approach tendencies in male alcohol-dependent patients

    NARCIS (Netherlands)

    Wiers, C.E.; Ludwig, V.U.; Gladwin, T.E.; Park, S.Q.; Heinz, A.; Wiers, R.W.; Rinck, M.; Lindenmeyer, J.; Walter, H.; Bermpohl, F.

    2015-01-01

    Alcohol-dependent patients have been shown to faster approach than avoid alcohol stimuli on the Approach Avoidance Task (AAT). This so-called alcohol approach bias has been associated with increased brain activation in the medial prefrontal cortex and nucleus accumbens. Cognitive bias modification

  15. Integrating Fisheries Dependent and Independent Approaches to assess Fisheries, Abundance, Diversity, Distribution and Genetic Connectivity of Red Sea Elasmobranch Populations

    KAUST Repository

    Spaet, Julia L.

    2014-05-01

    The Red Sea has long been recognized as a global hotspot of marine biodiversity. Ongoing overfishing, however, is threatening this unique ecosystem, recently leading to the identification of the Red Sea as one of three major hotspots of extinction risk for sharks and rays worldwide. Elasmobranch catches in Saudi Arabian Red Sea waters are unregulated, often misidentified and unrecorded, resulting in a lack of species-specific landings information, which would be vital for the formulation of effective management strategies. Here we employed an integrated approach of fisheries dependent and independent survey methods combined with molecular tools to provide biological, ecological and fisheries data to aid in the assessment of the status of elasmobranch populations in the Red Sea. Over the course of two years, we conducted market surveys at the biggest Saudi Arabian fish market in Jeddah. Market landings were dominated by, mostly immature individuals - implying both recruitment and growth overfishing. Additionally, we employed baited remote underwater video (BRUVS) and longline surveys along almost the entire length of the Red Sea coast of Saudi Arabia as well as at selected reef systems in Sudan. The comparison of catch per unit effort (CPUE) data for Saudi Arabian Red Sea BRUVS and longline surveys to published data originating from non-Red Sea ocean systems revealed CPUE values several orders of magnitude lower for both survey methods in the Red Sea compared to other locations around the world. Finally, we infered the regional population structure of four commercially important shark species between the Red Sea and the Western Indian Ocean.We genotyped nearly 2000 individuals at the mitochondrial control region as well as a total of 20 microsatellite loci. Genetic homogeneity could not be rejected for any of the four species across the spatial comparison. Based on high levels of region-wide exploitation, we suggest that, for management purposes, the population

  16. A functional clustering algorithm for the analysis of neural relationships

    CERN Document Server

    Feldt, S; Hetrick, V L; Berke, J D; Zochowski, M

    2008-01-01

    We formulate a novel technique for the detection of functional clusters in neural data. In contrast to prior network clustering algorithms, our procedure progressively combines spike trains and derives the optimal clustering cutoff in a simple and intuitive manner. To demonstrate the power of this algorithm to detect changes in network dynamics and connectivity, we apply it to both simulated data and real neural data obtained from the mouse hippocampus during exploration and slow-wave sleep. We observe state-dependent clustering patterns consistent with known neurophysiological processes involved in memory consolidation.

  17. Modeling electrocortical activity through improved local approximations of integral neural field equations.

    NARCIS (Netherlands)

    Coombes, S.; Venkov, N.A.; Shiau, L.; Bojak, I.; Liley, D.T.; Laing, C.R.

    2007-01-01

    Neural field models of firing rate activity typically take the form of integral equations with space-dependent axonal delays. Under natural assumptions on the synaptic connectivity we show how one can derive an equivalent partial differential equation (PDE) model that properly treats the axonal

  18. Artificial Neural Networks·

    Indian Academy of Sciences (India)

    differences between biological neural networks (BNNs) of the brain and ANN s. A thorough understanding of ... neurons. Artificial neural models are loosely based on biology since a complete understanding of the .... A learning scheme for updating a neuron's connections (weights) was proposed by Donald Hebb in 1949.

  19. Handbook of Brain Connectivity

    CERN Document Server

    Jirsa, Viktor K

    2007-01-01

    Our contemporary understanding of brain function is deeply rooted in the ideas of the nonlinear dynamics of distributed networks. Cognition and motor coordination seem to arise from the interactions of local neuronal networks, which themselves are connected in large scales across the entire brain. The spatial architectures between various scales inevitably influence the dynamics of the brain and thereby its function. But how can we integrate brain connectivity amongst these structural and functional domains? Our Handbook provides an account of the current knowledge on the measurement, analysis and theory of the anatomical and functional connectivity of the brain. All contributors are leading experts in various fields concerning structural and functional brain connectivity. In the first part of the Handbook, the chapters focus on an introduction and discussion of the principles underlying connected neural systems. The second part introduces the currently available non-invasive technologies for measuring struct...

  20. Real-time collision-free motion planning of a mobile robot using a Neural Dynamics-based approach.

    Science.gov (United States)

    Yang, S X; Meng, M H

    2003-01-01

    A neural dynamics based approach is proposed for real-time motion planning with obstacle avoidance of a mobile robot in a nonstationary environment. The dynamics of each neuron in the topologically organized neural network is characterized by a shunting equation or an additive equation. The real-time collision-free robot motion is planned through the dynamic neural activity landscape of the neural network without any learning procedures and without any local collision-checking procedures at each step of the robot movement. Therefore the model algorithm is computationally simple. There are only local connections among neurons. The computational complexity linearly depends on the neural network size. The stability of the proposed neural network system is proved by qualitative analysis and a Lyapunov stability theory. The effectiveness and efficiency of the proposed approach are demonstrated through simulation studies.

  1. Receptance coupling of multi-subsystem connected via a wedge mechanism with application in the position-dependent dynamics of ballscrew drives

    Science.gov (United States)

    Liu, Hui; Lu, Dun; Zhang, Jun; Zhao, Wanhua

    2016-08-01

    An accurate model of the feed drive's high-order position-dependent dynamics is crucial for the analysis and controller design of a high-performance machine tool. In this paper, a new dynamic substructuring condition-multi-subsystem connected via a wedge mechanism is introduced, which is originated from the ballscrew-nut dynamic coupling interface. Receptance coupling equations were derived for the condition, and a dynamic modeling approach is developed for the ballscrew drive system based on the equations. The developed model accounts for the ballscrew's rotational and axial flexibilities and the dynamic couplings among these flexibilities and that of the sliding component. The model explicitly describes the dynamics variation with respect to the table position, and is particularly suitable for sensitivity based analysis. Based on the model, the position-dependent dynamics of an example ballscrew drive was analyzed, by using the frequencies distribution, the modal shape, and especially the sensitivity of the frequency response functions with respect to the table position.

  2. High serotonin levels during brain development alter the structural input-output connectivity of neural networks in the rat somatosensory layer IV

    Directory of Open Access Journals (Sweden)

    Stéphanie eMiceli

    2013-06-01

    Full Text Available Homeostatic regulation of serotonin (5-HT concentration is critical for normal topographical organization and development of thalamocortical (TC afferent circuits. Down-regulation of the serotonin transporter (SERT and the consequent impaired reuptake of 5-HT at the synapse, results in a reduced terminal branching of developing TC afferents within the primary somatosensory cortex (S1. Despite the presence of multiple genetic models, the effect of high extracellular 5-HT levels on the structure and function of developing intracortical neural networks is far from being understood. Here, using juvenile SERT knockout (SERT-/- rats we investigated, in vitro, the effect of increased 5-HT levels on the structural organization of (i the thalamocortical projections of the ventroposteromedial thalamic nucleus towards S1, (ii the general barrel-field pattern and (iii the electrophysiological and morphological properties of the excitatory cell population in layer IV of S1 (spiny stellate and pyramidal cells. Our results confirmed previous findings that high levels of 5-HT during development lead to a reduction of the topographical precision of TCA projections towards the barrel cortex. Also, the barrel pattern was altered but not abolished in SERT-/- rats. In layer IV, both excitatory spiny stellate and pyramidal cells showed a significantly reduced intracolumnar organization of their axonal projections. In addition, the layer IV spiny stellate cells gave rise to a prominent projection towards the infragranular layer Vb. Our findings point to a structural and functional reorganization, of TCAs, as well as early stage intracortical microcircuitry, following the disruption of 5-HT reuptake during critical developmental periods. The increased projection pattern of the layer IV neurons suggests that the intracortical network changes are not limited to the main entry layer IV but may also affect the subsequent stages of the canonical circuits of the barrel

  3. A new class of methods for functional connectivity estimation

    Science.gov (United States)

    Lin, Wutu

    Measuring functional connectivity from neural recordings is important in understanding processing in cortical networks. The covariance-based methods are the current golden standard for functional connectivity estimation. However, the link between the pair-wise correlations and the physiological connections inside the neural network is unclear. Therefore, the power of inferring physiological basis from functional connectivity estimation is limited. To build a stronger tie and better understand the relationship between functional connectivity and physiological neural network, we need (1) a realistic model to simulate different types of neural recordings with known ground truth for benchmarking; (2) a new functional connectivity method that produce estimations closely reflecting the physiological basis. In this thesis, (1) I tune a spiking neural network model to match with human sleep EEG data, (2) introduce a new class of methods for estimating connectivity from different kinds of neural signals and provide theory proof for its superiority, (3) apply it to simulated fMRI data as an application.

  4. Müller glial cell‐dependent regeneration of the neural retina: An overview across vertebrate model systems

    Science.gov (United States)

    Hamon, Annaïg; Roger, Jérôme E.; Yang, Xian‐Jie

    2016-01-01

    Retinal dystrophies are a major cause of blindness for which there are currently no curative treatments. Transplantation of stem cell‐derived neuronal progenitors to replace lost cells has been widely investigated as a therapeutic option. Another promising strategy would be to trigger self‐repair mechanisms in patients, through the recruitment of endogenous cells with stemness properties. Accumulating evidence in the past 15 year0s has revealed that several retinal cell types possess neurogenic potential, thus opening new avenues for regenerative medicine. Among them, Müller glial cells have been shown to be able to undergo a reprogramming process to re‐acquire a stem/progenitor state, allowing them to proliferate and generate new neurons for repair following retinal damages. Although Müller cell–dependent spontaneous regeneration is remarkable in some species such as the fish, it is extremely limited and ineffective in mammals. Understanding the cellular events and molecular mechanisms underlying Müller cell activities in species endowed with regenerative capacities could provide knowledge to unlock the restricted potential of their mammalian counterparts. In this context, the present review provides an overview of Müller cell responses to injury across vertebrate model systems and summarizes recent advances in this rapidly evolving field. Developmental Dynamics 245:727–738, 2016. © 2015 The Authors. Developmental Dynamics published by Wiley Periodicals, Inc. PMID:26661417

  5. PCB 136 atropselectively alters morphometric and functional parameters of neuronal connectivity in cultured rat hippocampal neurons via ryanodine receptor-dependent mechanisms.

    Science.gov (United States)

    Yang, Dongren; Kania-Korwel, Izabela; Ghogha, Atefeh; Chen, Hao; Stamou, Marianna; Bose, Diptiman D; Pessah, Isaac N; Lehmler, Hans-Joachim; Lein, Pamela J

    2014-04-01

    We recently demonstrated that polychlorinated biphenyl (PCB) congeners with multiple ortho chlorine substitutions sensitize ryanodine receptors (RyRs), and this activity promotes Ca²⁺-dependent dendritic growth in cultured neurons. Many ortho-substituted congeners display axial chirality, and we previously reported that the chiral congener PCB 136 (2,2',3,3',6,6'-hexachlorobiphenyl) atropselectively sensitizes RyRs. Here, we test the hypothesis that PCB 136 atropisomers differentially alter dendritic growth and other parameters of neuronal connectivity influenced by RyR activity. (-)-PCB 136, which potently sensitizes RyRs, enhances dendritic growth in primary cultures of rat hippocampal neurons, whereas (+)-PCB 136, which lacks RyR activity, has no effect on dendritic growth. The dendrite-promoting activity of (-)-PCB 136 is observed at concentrations ranging from 0.1 to 100 nM and is blocked by pharmacologic RyR antagonism. Neither atropisomer alters axonal growth or cell viability. Quantification of PCB 136 atropisomers in hippocampal cultures indicates that atropselective effects on dendritic growth are not due to differential partitioning of atropisomers into cultured cells. Imaging of hippocampal neurons loaded with Ca²⁺-sensitive dye demonstrates that (-)-PCB 136 but not (+)-PCB 136 increases the frequency of spontaneous Ca²⁺ oscillations. Similarly, (-)-PCB 136 but not (+)-PCB 136 increases the activity of hippocampal neurons plated on microelectrode arrays. These data support the hypothesis that atropselective effects on RyR activity translate into atropselective effects of PCB 136 atropisomers on neuronal connectivity, and suggest that the variable atropisomeric enrichment of chiral PCBs observed in the human population may be a significant determinant of individual susceptibility for adverse neurodevelopmental outcomes following PCB exposure.

  6. Searching for learning-dependent changes in the antennal lobe: simultaneous recording of neural activity and aversive olfactory learning in honeybees

    Directory of Open Access Journals (Sweden)

    Edith Roussel

    2010-09-01

    Full Text Available Plasticity in the honeybee brain has been studied using the appetitive olfactory conditioning of the proboscis extension reflex, in which a bee learns the association between an odor and a sucrose reward. In this framework, coupling behavioral measurements of proboscis extension and invasive recordings of neural activity has been difficult because proboscis movements usually introduce brain movements that affect physiological preparations. Here we took advantage of a new conditioning protocol, the aversive olfactory conditioning of the sting extension reflex, which does not generate this problem. We achieved the first simultaneous recordings of conditioned sting extension responses and calcium imaging of antennal lobe activity, thus revealing on-line processing of olfactory information during conditioning trials. Based on behavioral output we distinguished learners and non-learners and analyzed possible learning-dependent changes in antennal lobe activity. We did not find differences between glomerular responses to the CS+ and the CS- in learners. Unexpectedly, we found that during conditioning trials non-learners exhibited a progressive decrease in physiological responses to odors, irrespective of their valence. This effect could neither be attributed to a fitness problem nor to abnormal dye bleaching. We discuss the absence of learning-induced changes in the antennal lobe of learners and the decrease in calcium responses found in non-learners. Further studies will have to extend the search for functional plasticity related to aversive learning to other brain areas and to look on a broader range of temporal scales

  7. [Neural codes for perception].

    Science.gov (United States)

    Romo, R; Salinas, E; Hernández, A; Zainos, A; Lemus, L; de Lafuente, V; Luna, R

    This article describes experiments designed to show the neural codes associated with the perception and processing of tactile information. The results of these experiments have shown the neural activity correlated with tactile perception. The neurones of the primary somatosensory cortex (S1) represent the physical attributes of tactile perception. We found that these representations correlated with tactile perception. By means of intracortical microstimulation we demonstrated the causal relationship between S1 activity and tactile perception. In the motor areas of the frontal lobe is to be found the connection between sensorial and motor representation whilst decisions are being taken. S1 generates neural representations of the somatosensory stimuli which seen to be sufficient for tactile perception. These neural representations are subsequently processed by central areas to S1 and seem useful in perception, memory and decision making.

  8. Computational modeling of spiking neural network with learning rules from STDP and intrinsic plasticity

    Science.gov (United States)

    Li, Xiumin; Wang, Wei; Xue, Fangzheng; Song, Yongduan

    2018-02-01

    Recently there has been continuously increasing interest in building up computational models of spiking neural networks (SNN), such as the Liquid State Machine (LSM). The biologically inspired self-organized neural networks with neural plasticity can enhance the capability of computational performance, with the characteristic features of dynamical memory and recurrent connection cycles which distinguish them from the more widely used feedforward neural networks. Despite a variety of computational models for brain-like learning and information processing have been proposed, the modeling of self-organized neural networks with multi-neural plasticity is still an important open challenge. The main difficulties lie in the interplay among different forms of neural plasticity rules and understanding how structures and dynamics of neural networks shape the computational performance. In this paper, we propose a novel approach to develop the models of LSM with a biologically inspired self-organizing network based on two neural plasticity learning rules. The connectivity among excitatory neurons is adapted by spike-timing-dependent plasticity (STDP) learning; meanwhile, the degrees of neuronal excitability are regulated to maintain a moderate average activity level by another learning rule: intrinsic plasticity (IP). Our study shows that LSM with STDP+IP performs better than LSM with a random SNN or SNN obtained by STDP alone. The noticeable improvement with the proposed method is due to the better reflected competition among different neurons in the developed SNN model, as well as the more effectively encoded and processed relevant dynamic information with its learning and self-organizing mechanism. This result gives insights to the optimization of computational models of spiking neural networks with neural plasticity.

  9. Stressor and glucocorticoid-dependent induction of the immediate early gene kruppel-like factor 9: implications for neural development and plasticity.

    Science.gov (United States)

    Bonett, Ronald M; Hu, Fang; Bagamasbad, Pia; Denver, Robert J

    2009-04-01

    Krüppel-like factor 9 (KLF9) is a thyroid hormone-induced, immediate early gene implicated in neural development in vertebrates. We analyzed stressor and glucocorticoid (GC)-dependent regulation of KLF9 expression in the brain of the frog Xenopus laevis, and investigated a possible role for KLF9 in neuronal differentiation. Exposure to shaking/confinement stressor increased plasma corticosterone (CORT) concentration, and KLF9 immunoreactivity in several brain regions, which included the medial amygdala and bed nucleus of the stria terminalis, anterior preoptic area (homologous to the mammalian paraventricular nucleus), and optic tectum (homologous to the mammalian superior colliculus). The stressor-induced KLF9 mRNA expression in the brain was blocked by pretreatment with the GC receptor antagonist RU486, or mimicked by injection of CORT. Treatment with CORT also caused a rapid and dose-dependent increase in KLF9 mRNA in X. laevis XTC-2 cells that was resistant to inhibition of protein synthesis. The action of CORT on KLF9 expression in XTC-2 cells was blocked by RU486, but not by the mineralocorticoid receptor antagonist spironolactone. To test for functional consequences of up-regulation of KLF9, we introduced a KLF9 expression plasmid into living tadpole brain by electroporation-mediated gene transfer. Forced expression of KLF9 in tadpole brain caused an increase in Golgi-stained cells, reflective of neuronal differentiation/maturation. Our results support that KLF9 is a direct, GC receptor target gene that is induced by stress, and functions as an intermediary in the actions of GCs on brain gene expression and neuronal structure.

  10. Stressor and Glucocorticoid-Dependent Induction of the Immediate Early Gene Krüppel-Like Factor 9: Implications for Neural Development and Plasticity

    Science.gov (United States)

    Bonett, Ronald M.; Hu, Fang; Bagamasbad, Pia; Denver, Robert J.

    2009-01-01

    Krüppel-like factor 9 (KLF9) is a thyroid hormone-induced, immediate early gene implicated in neural development in vertebrates. We analyzed stressor and glucocorticoid (GC)-dependent regulation of KLF9 expression in the brain of the frog Xenopus laevis, and investigated a possible role for KLF9 in neuronal differentiation. Exposure to shaking/confinement stressor increased plasma corticosterone (CORT) concentration, and KLF9 immunoreactivity in several brain regions, which included the medial amygdala and bed nucleus of the stria terminalis, anterior preoptic area (homologous to the mammalian paraventricular nucleus), and optic tectum (homologous to the mammalian superior colliculus). The stressor-induced KLF9 mRNA expression in the brain was blocked by pretreatment with the GC receptor antagonist RU486, or mimicked by injection of CORT. Treatment with CORT also caused a rapid and dose-dependent increase in KLF9 mRNA in X. laevis XTC-2 cells that was resistant to inhibition of protein synthesis. The action of CORT on KLF9 expression in XTC-2 cells was blocked by RU486, but not by the mineralocorticoid receptor antagonist spironolactone. To test for functional consequences of up-regulation of KLF9, we introduced a KLF9 expression plasmid into living tadpole brain by electroporation-mediated gene transfer. Forced expression of KLF9 in tadpole brain caused an increase in Golgi-stained cells, reflective of neuronal differentiation/maturation. Our results support that KLF9 is a direct, GC receptor target gene that is induced by stress, and functions as an intermediary in the actions of GCs on brain gene expression and neuronal structure. PMID:19036875

  11. Emergence of modular structure in a large-scale brain network with interactions between dynamics and connectivity

    Directory of Open Access Journals (Sweden)

    Cornelis Jan Stam

    2010-09-01

    Full Text Available A network of 32 or 64 connected neural masses, each representing a large population of interacting excitatory and inhibitory neurons and generating an EEG / MEG like output signal, was used to demonstrate how an interaction between dynamics and connectivity might explain the emergence of complex network features, in particular modularity. Network evolution was modeled by two processes: (i synchronization dependent plasticity (SDP and (ii growth dependent plasticity (GDP. In the case of SDP, connections between neural masses were strengthened when they were strongly synchronized, and were weakened when they were not. GDP was modeled as a homeostatic process with random, distance dependent outgrowth of new connections between neural masses. GDP alone resulted in stable networks with distance dependent connection strengths, typical small-world features, but no degree correlations and only weak modularity. SDP applied to random networks induced clustering, but no clear modules. Stronger modularity evolved only through an interaction of SDP and GDP, with the number and size of the modules depending on the relative strength of both processes, as well as on the size of the network. Lesioning part of the network, after a stable state was achieved, resulted in a temporary disruption of the network structure. The model gives a possible scenario to explain how modularity can arise in developing brain networks, and makes predictions about the time course of network changes during development and following acute lesions.

  12. Emergence of Modular Structure in a Large-Scale Brain Network with Interactions between Dynamics and Connectivity.

    Science.gov (United States)

    Stam, Cornelis J; Hillebrand, Arjan; Wang, Huijuan; Van Mieghem, Piet

    2010-01-01

    A network of 32 or 64 connected neural masses, each representing a large population of interacting excitatory and inhibitory neurons and generating an electroencephalography/magnetoencephalography like output signal, was used to demonstrate how an interaction between dynamics and connectivity might explain the emergence of complex network features, in particular modularity. Network evolution was modeled by two processes: (i) synchronization dependent plasticity (SDP) and (ii) growth dependent plasticity (GDP). In the case of SDP, connections between neural masses were strengthened when they were strongly synchronized, and were weakened when they were not. GDP was modeled as a homeostatic process with random, distance dependent outgrowth of new connections between neural masses. GDP alone resulted in stable networks with distance dependent connection strengths, typical small-world features, but no degree correlations and only weak modularity. SDP applied to random networks induced clustering, but no clear modules. Stronger modularity evolved only through an interaction of SDP and GDP, with the number and size of the modules depending on the relative strength of both processes, as well as on the size of the network. Lesioning part of the network, after a stable state was achieved, resulted in a temporary disruption of the network structure. The model gives a possible scenario to explain how modularity can arise in developing brain networks, and makes predictions about the time course of network changes during development and following acute lesions.

  13. Synchronization and long-time memory in neural networks with inhibitory hubs and synaptic plasticity

    Science.gov (United States)

    Bertolotti, Elena; Burioni, Raffaella; di Volo, Matteo; Vezzani, Alessandro

    2017-01-01

    We investigate the dynamical role of inhibitory and highly connected nodes (hub) in synchronization and input processing of leaky-integrate-and-fire neural networks with short term synaptic plasticity. We take advantage of a heterogeneous mean-field approximation to encode the role of network structure and we tune the fraction of inhibitory neurons fI and their connectivity level to investigate the cooperation between hub features and inhibition. We show that, depending on fI, highly connected inhibitory nodes strongly drive the synchronization properties of the overall network through dynamical transitions from synchronous to asynchronous regimes. Furthermore, a metastable regime with long memory of external inputs emerges for a specific fraction of hub inhibitory neurons, underlining the role of inhibition and connectivity also for input processing in neural networks.

  14. Evolving neural networks using a genetic algorithm for heartbeat classification.

    Science.gov (United States)

    Sekkal, Mansouria; Chikh, Mohamed Amine; Settouti, Nesma

    2011-07-01

    This study investigates the effectiveness of a genetic algorithm (GA) evolved neural network (NN) classifier and its application to the classification of premature ventricular contraction (PVC) beats. As there is no standard procedure to determine the network structure for complicated cases, generally the design of the NN would be dependent on the user's experience. To prevent this problem, we propose a neural classifier that uses a GA for the determination of optimal connections between neurons for better recognition. The MIT-BIH arrhythmia database is employed to evaluate its accuracy. First, the topology of the NN was determined using the trial and error method. Second, the genetic operators were carefully designed to optimize the neural network structure. Performance and accuracy of the two techniques are presented and compared. Copyright © 2011 Informa UK, Ltd.

  15. Internal representation of task rules by recurrent dynamics: the importance of the diversity of neural responses

    Directory of Open Access Journals (Sweden)

    Mattia Rigotti

    2010-10-01

    Full Text Available Neural activity of behaving animals, especially in the prefrontal cortex, is highly heterogeneous, with selective responses to diverse aspects of the executed task. We propose a general model of recurrent neural networks that perform complex rule-based tasks, and we show that the diversity of neuronal responses plays a fundamental role when the behavioral responses are context dependent. Specifically, we found that when the inner mental states encoding the task rules are represented by stable patterns of neural activity (attractors of the neural dynamics, the neurons must be selective for combinations of sensory stimuli and inner mental states. Such mixed selectivity is easily obtained by neurons that connect with random synaptic strengths both to the recurrent network and to neurons encoding sensory inputs. The number of randomly connected neurons needed to solve a task is on average only three times as large as the number of neurons needed in a network designed ad hoc. Moreover, the number of needed neurons grows only linearly with the number of task-relevant events and mental states, provided that each neuron responds to a large proportion of events (dense/distributed coding. A biologically realistic implementation of the model captures several aspects of the activity recorded from monkeys performing context dependent tasks. Our findings explain the importance of the diversity of neural responses and provide us with simple and general principles for designing attractor neural networks that perform complex computation.

  16. OTX2 exhibits cell-context-dependent effects on cellular and molecular properties of human embryonic neural precursors and medulloblastoma cells

    Directory of Open Access Journals (Sweden)

    Ravinder Kaur

    2015-10-01

    Full Text Available Medulloblastoma (MB is the most common malignant primary pediatric brain tumor and is currently divided into four subtypes based on different genomic alterations, gene expression profiles and response to treatment: WNT, Sonic Hedgehog (SHH, Group 3 and Group 4. This extensive heterogeneity has made it difficult to assess the functional relevance of genes to malignant progression. For example, expression of the transcription factor Orthodenticle homeobox2 (OTX2 is frequently dysregulated in multiple MB variants; however, its role may be subtype specific. We recently demonstrated that neural precursors derived from transformed human embryonic stem cells (trans-hENs, but not their normal counterparts (hENs, resemble Groups 3 and 4 MB in vitro and in vivo. Here, we tested the utility of this model system as a means of dissecting the role of OTX2 in MB using gain- and loss-of-function studies in hENs and trans-hENs, respectively. Parallel experiments with MB cells revealed that OTX2 exerts inhibitory effects on hEN and SHH MB cells by regulating growth, self-renewal and migration in vitro and tumor growth in vivo. This was accompanied by decreased expression of pluripotent genes, such as SOX2, and was supported by overexpression of SOX2 in OTX2+ SHH MB and hENs that resulted in significant rescue of self-renewal and cell migration. By contrast, OTX2 is oncogenic and promotes self-renewal of trans-hENs and Groups 3 and 4 MB independent of pluripotent gene expression. Our results demonstrate a novel role for OTX2 in self-renewal and migration of hENs and MB cells and reveal a cell-context-dependent link between OTX2 and pluripotent genes. Our study underscores the value of human embryonic stem cell derivatives as alternatives to cell lines and heterogeneous patient samples for investigating the contribution of key developmental regulators to MB progression.

  17. Persistent activity in neural networks with dynamic synapses.

    Directory of Open Access Journals (Sweden)

    Omri Barak

    2007-02-01

    Full Text Available Persistent activity states (attractors, observed in several neocortical areas after the removal of a sensory stimulus, are believed to be the neuronal basis of working memory. One of the possible mechanisms that can underlie persistent activity is recurrent excitation mediated by intracortical synaptic connections. A recent experimental study revealed that connections between pyramidal cells in prefrontal cortex exhibit various degrees of synaptic depression and facilitation. Here we analyze the effect of synaptic dynamics on the emergence and persistence of attractor states in interconnected neural networks. We show that different combinations of synaptic depression and facilitation result in qualitatively different network dynamics with respect to the emergence of the attractor states. This analysis raises the possibility that the framework of attractor neural networks can be extended to represent time-dependent stimuli.

  18. Connected Traveler

    Energy Technology Data Exchange (ETDEWEB)

    Schroeder, Alex

    2015-11-01

    The Connected Traveler project is a multi-disciplinary undertaking that seeks to validate potential for transformative transportation system energy savings by incentivizing efficient traveler behavior. This poster outlines various aspects of the Connected Traveler project, including market opportunity, understanding traveler behavior and decision-making, automation and connectivity, and a projected timeline for Connected Traveler's key milestones.

  19. Investigation of possible neural architectures underlying information-geometric measures.

    Science.gov (United States)

    Tatsuno, Masami; Okada, Masato

    2004-04-01

    A novel analytical method based on information geometry was recently proposed, and this method may provide useful insights into the statistical interactions within neural groups. The link between informationgeometric measures and the structure of neural interactions has not yet been elucidated, however, because of the ill-posed nature of the problem. Here, possible neural architectures underlying information-geometric measures are investigated using an isolated pair and an isolated triplet of model neurons. By assuming the existence of equilibrium states, we derive analytically the relationship between the information-geometric parameters and these simple neural architectures. For symmetric networks, the first- and second-order information-geometric parameters represent, respectively, the external input and the underlying connections between the neurons provided that the number of neurons used in the parameter estimation in the log-linear model and the number of neurons in the network are the same. For asymmetric networks, however, these parameters are dependent on both the intrinsic connections and the external inputs to each neuron. In addition, we derive the relation between the information-geometric parameter corresponding to the two-neuron interaction and a conventional cross-correlation measure. We also show that the information-geometric parameters vary depending on the number of neurons assumed for parameter estimation in the log-linear model. This finding suggests a need to examine the information-geometric method carefully. A possible criterion for choosing an appropriate orthogonal coordinate is also discussed. This article points out the importance of a model-based approach and sheds light on the possible neural structure underlying the application of information geometry to neural network analysis.

  20. Neural Manifolds for the Control of Movement.

    Science.gov (United States)

    Gallego, Juan A; Perich, Matthew G; Miller, Lee E; Solla, Sara A

    2017-06-07

    The analysis of neural dynamics in several brain cortices has consistently uncovered low-dimensional manifolds that capture a significant fraction of neural variability. These neural manifolds are spanned by specific patterns of correlated neural activity, the "neural modes." We discuss a model for neural control of movement in which the time-dependent activation of these neural modes is the generator of motor behavior. This manifold-based view of motor cortex may lead to a better understanding of how the brain controls movement. Copyright © 2017 Elsevier Inc. All rights reserved.

  1. Optogenetics in Silicon: A Neural Processor for Predicting Optically Active Neural Networks.

    Science.gov (United States)

    Junwen Luo; Nikolic, Konstantin; Evans, Benjamin D; Na Dong; Xiaohan Sun; Andras, Peter; Yakovlev, Alex; Degenaar, Patrick

    2017-02-01

    We present a reconfigurable neural processor for real-time simulation and prediction of opto-neural behaviour. We combined a detailed Hodgkin-Huxley CA3 neuron integrated with a four-state Channelrhodopsin-2 (ChR2) model into reconfigurable silicon hardware. Our architecture consists of a Field Programmable Gated Array (FPGA) with a custom-built computing data-path, a separate data management system and a memory approach based router. Advancements over previous work include the incorporation of short and long-term calcium and light-dependent ion channels in reconfigurable hardware. Also, the developed processor is computationally efficient, requiring only 0.03 ms processing time per sub-frame for a single neuron and 9.7 ms for a fully connected network of 500 neurons with a given FPGA frequency of 56.7 MHz. It can therefore be utilized for exploration of closed loop processing and tuning of biologically realistic optogenetic circuitry.

  2. Density dependent neurodynamics.

    Science.gov (United States)

    Halnes, Geir; Liljenström, Hans; Arhem, Peter

    2007-01-01

    The dynamics of a neural network depends on density parameters at (at least) two different levels: the subcellular density of ion channels in single neurons, and the density of cells and synapses at a network level. For the Frankenhaeuser-Huxley (FH) neural model, the density of sodium (Na) and potassium (K) channels determines the behaviour of a single neuron when exposed to an external stimulus. The features of the onset of single neuron oscillations vary qualitatively among different regions in the channel density plane. At a network level, the density of neurons is reflected in the global connectivity. We study the relation between the two density levels in a network of oscillatory FH neurons, by qualitatively distinguishing between three regions, where the mean network activity is (1) spiking, (2) oscillating with enveloped frequencies, and (3) bursting, respectively. We demonstrate that the global activity can be shifted between regions by changing either the density of ion channels at the subcellular level, or the connectivity at the network level, suggesting that different underlying mechanisms can explain similar global phenomena. Finally, we model a possible effect of anaesthesia by blocking specific inhibitory ion channels.

  3. Information-geometric measures estimate neural interactions during oscillatory brain states.

    Science.gov (United States)

    Nie, Yimin; Fellous, Jean-Marc; Tatsuno, Masami

    2014-01-01

    The characterization of functional network structures among multiple neurons is essential to understanding neural information processing. Information geometry (IG), a theory developed for investigating a space of probability distributions has recently been applied to spike-train analysis and has provided robust estimations of neural interactions. Although neural firing in the equilibrium state is often assumed in these studies, in reality, neural activity is non-stationary. The brain exhibits various oscillations depending on cognitive demands or when an animal is asleep. Therefore, the investigation of the IG measures during oscillatory network states is important for testing how the IG method can be applied to real neural data. Using model networks of binary neurons or more realistic spiking neurons, we studied how the single- and pairwise-IG measures were influenced by oscillatory neural activity. Two general oscillatory mechanisms, externally driven oscillations and internally induced oscillations, were considered. In both mechanisms, we found that the single-IG measure was linearly related to the magnitude of the external input, and that the pairwise-IG measure was linearly related to the sum of connection strengths between two neurons. We also observed that the pairwise-IG measure was not dependent on the oscillation frequency. These results are consistent with the previous findings that were obtained under the equilibrium conditions. Therefore, we demonstrate that the IG method provides useful insights into neural interactions under the oscillatory condition that can often be observed in the real brain.

  4. Information-geometric measures estimate neural interactions during oscillatory brain states

    Directory of Open Access Journals (Sweden)

    Yimin eNie

    2014-02-01

    Full Text Available The characterization of functional network structures among multiple neurons is essential to understanding neural information processing. Information geometry (IG, a theory developed for investigating a space of probability distributions has recently been applied to spike-train analysis and has provided robust estimations of neural interactions. Although neural firing in the equilibrium state is often assumed in these studies, in reality, neural activity is non-stationary. The brain exhibits various oscillations depending on cognitive demands or when an animal is asleep. Therefore, the investigation of the IG measures during oscillatory network states is important for testing how the IG method can be applied to real neural data. Using model networks of binary neurons or more realistic spiking neurons, we studied how the single- and pairwise-IG measures were influenced by oscillatory neural activity. Two general oscillatory mechanisms, externally driven oscillations and internally induced oscillations, were considered. In both mechanisms, we found that the single-IG measure was linearly related to the magnitude of the external input, and that the pairwise-IG measure was linearly related to the sum of connection strengths between two neurons. We also observed that the pairwise-IG measure was not dependent on the oscillation frequency. These results are consistent with the previous findings that were obtained under the equilibrium conditions. Therefore, we demonstrate that the IG method provides useful insights into neural interactions under the oscillatory condition that can often be observed in the real brain.

  5. Neural Correlates of Stimulus Reportability

    OpenAIRE

    Hulme, Oliver J.; Friston, Karl F.; Zeki, Semir

    2009-01-01

    Most experiments on the “neural correlates of consciousness” employ stimulus reportability as an operational definition of what is consciously perceived. The interpretation of such experiments therefore depends critically on understanding the neural basis of stimulus reportability. Using a high volume of fMRI data, we investigated the neural correlates of stimulus reportability using a partial report object detection paradigm. Subjects were presented with a random array of circularly arranged...

  6. Neural connections between antrum and duodenum

    DEFF Research Database (Denmark)

    Kraglund, K; Schrøder, H D; Stødkilde-Jørgensen, H

    1983-01-01

    Postprandial coordination of antroduodenal motility partly takes place via intrinsic mural pathways. The nature and origin of these nerve fibers have not yet been clarified. In this investigation using fluorochromic substances injected into the antrum and duodenum it was demonstrated that common...

  7. The neural basis of unwanted thoughts during resting state.

    Science.gov (United States)

    Kühn, Simone; Vanderhasselt, Marie-Anne; De Raedt, Rudi; Gallinat, Jürgen

    2014-09-01

    Human beings are constantly engaged in thought. Sometimes thoughts occur repetitively and can become distressing. Up to now the neural bases of these intrusive or unwanted thoughts is largely unexplored. To study the neural correlates of unwanted thoughts, we acquired resting-state fMRI data of 41 female healthy subjects and assessed the self-reported amount of unwanted thoughts during measurement. We analyzed local connectivity by means of regional homogeneity (ReHo) and functional connectivity of a seed region. More unwanted thoughts (state) were associated with lower ReHo in right dorsolateral prefrontal cortex (DLPFC) and higher ReHo in left striatum (putamen). Additional seed-based analysis revealed higher functional connectivity of the left striatum with left inferior frontal gyrus (IFG) in participants reporting more unwanted thoughts. The state-dependent higher connectivty in left striatum was positively correlated with rumination assessed with a dedicated questionnaire focussing on trait aspects. Unwanted thoughts are associated with activity in the fronto-striatal brain circuitry. The reduction of local connectivity in DLPFC could reflect deficiencies in thought suppression processes, whereas the hightened activity in left striatum could imply an imbalance of gating mechanisms housed in basal ganglia. Its functional connectivity to left IFG is discussed as the result of thought-related speech processes. © The Author (2013). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  8. An FPGA Implementation of a Polychronous Spiking Neural Network with Delay Adaptation

    Science.gov (United States)

    Wang, Runchun; Cohen, Gregory; Stiefel, Klaus M.; Hamilton, Tara Julia; Tapson, Jonathan; van Schaik, André

    2013-01-01

    We present an FPGA implementation of a re-configurable, polychronous spiking neural network with a large capacity for spatial-temporal patterns. The proposed neural network generates delay paths de novo, so that only connections that actually appear in the training patterns will be created. This allows the proposed network to use all the axons (variables) to store information. Spike Timing Dependent Delay Plasticity is used to fine-tune and add dynamics to the network. We use a time multiplexing approach allowing us to achieve 4096 (4k) neurons and up to 1.15 million programmable delay axons on a Virtex 6 FPGA. Test results show that the proposed neural network is capable of successfully recalling more than 95% of all spikes for 96% of the stored patterns. The tests also show that the neural network is robust to noise from random input spikes. PMID:23408739

  9. Structures of Neural Correlation and How They Favor Coding

    Science.gov (United States)

    Franke, Felix; Fiscella, Michele; Sevelev, Maksim; Roska, Botond; Hierlemann, Andreas; da Silveira, Rava Azeredo

    2017-01-01

    Summary The neural representation of information suffers from “noise”—the trial-to-trial variability in the response of neurons. The impact of correlated noise upon population coding has been debated, but a direct connection between theory and experiment remains tenuous. Here, we substantiate this connection and propose a refined theoretical picture. Using simultaneous recordings from a population of direction-selective retinal ganglion cells, we demonstrate that coding benefits from noise correlations. The effect is appreciable already in small populations, yet it is a collective phenomenon. Furthermore, the stimulus-dependent structure of correlation is key. We develop simple functional models that capture the stimulus-dependent statistics. We then use them to quantify the performance of population coding, which depends upon interplays of feature sensitivities and noise correlations in the population. Because favorable structures of correlation emerge robustly in circuits with noisy, nonlinear elements, they will arise and benefit coding beyond the confines of retina. PMID:26796692

  10. Demonstration of a neural circuit critical for imprinting behavior in chicks.

    Science.gov (United States)

    Nakamori, Tomoharu; Sato, Katsushige; Atoji, Yasuro; Kanamatsu, Tomoyuki; Tanaka, Kohichi; Ohki-Hamazaki, Hiroko

    2010-03-24

    Imprinting behavior in birds is elicited by visual and/or auditory cues. It has been demonstrated previously that visual cues are recognized and processed in the visual Wulst (VW), and imprinting memory is stored in the intermediate medial mesopallium (IMM) of the telencephalon. Alteration of neural responses in these two regions according to imprinting has been reported, yet direct evidence of the neural circuit linking these two regions is lacking. Thus, it remains unclear how memory is formed and expressed in this circuit. Here, we present anatomical as well as physiological evidence of the neural circuit connecting the VW and IMM and show that imprinting training during the critical period strengthens and refines this circuit. A functional connection established by imprint training resulted in an imprinting behavior. After the closure of the critical period, training could not activate this circuit nor induce the imprinting behavior. Glutamatergic neurons in the ventroposterior region of the VW, the core region of the hyperpallium densocellulare (HDCo), sent their axons to the periventricular part of the HD, just dorsal and afferent to the IMM. We found that the HDCo is important in imprinting behavior. The refinement and/or enhancement of this neural circuit are attributed to increased activity of HDCo cells, and the activity depended on NR2B-containing NMDA receptors. These findings show a neural connection in the telencephalon in Aves and demonstrate that NR2B function is indispensable for the plasticity of HDCo cells, which are key mediators of imprinting.

  11. Micro- and Nanotechnologies for Optical Neural Interfaces

    Science.gov (United States)

    Pisanello, Ferruccio; Sileo, Leonardo; De Vittorio, Massimo

    2016-01-01

    In last decade, the possibility to optically interface with the mammalian brain in vivo has allowed unprecedented investigation of functional connectivity of neural circuitry. Together with new genetic and molecular techniques to optically trigger and monitor neural activity, a new generation of optical neural interfaces is being developed, mainly thanks to the exploitation of both bottom-up and top-down nanofabrication approaches. This review highlights the role of nanotechnologies for optical neural interfaces, with particular emphasis on new devices and methodologies for optogenetic control of neural activity and unconventional methods for detection and triggering of action potentials using optically-active colloidal nanoparticles. PMID:27013939

  12. Neural-like growing networks

    Science.gov (United States)

    Yashchenko, Vitaliy A.

    2000-03-01

    On the basis of the analysis of scientific ideas reflecting the law in the structure and functioning the biological structures of a brain, and analysis and synthesis of knowledge, developed by various directions in Computer Science, also there were developed the bases of the theory of a new class neural-like growing networks, not having the analogue in world practice. In a base of neural-like growing networks the synthesis of knowledge developed by classical theories - semantic and neural of networks is. The first of them enable to form sense, as objects and connections between them in accordance with construction of the network. With thus each sense gets a separate a component of a network as top, connected to other tops. In common it quite corresponds to structure reflected in a brain, where each obvious concept is presented by certain structure and has designating symbol. Secondly, this network gets increased semantic clearness at the expense owing to formation not only connections between neural by elements, but also themselves of elements as such, i.e. here has a place not simply construction of a network by accommodation sense structures in environment neural of elements, and purely creation of most this environment, as of an equivalent of environment of memory. Thus neural-like growing networks are represented by the convenient apparatus for modeling of mechanisms of teleological thinking, as a fulfillment of certain psychophysiological of functions.

  13. Developmental plasticity in neural circuits for a learned behavior.

    Science.gov (United States)

    Bottjer, S W; Arnold, A P

    1997-01-01

    The neural substrate underlying learned vocal behavior in songbirds provides a textbook illustration of anatomical localization of function for a complex learned behavior in vertebrates. The song-control system has become an important model for studying neural systems related to learning, behavior, and development. The song system of zebra finches is characterized by a heightened capacity for both neural and behavioral change during development and has taught us valuable information regarding sensitive periods, rearrangement of synaptic connections, topographic specificity, cell death and neurogenesis, experience-dependent neural plasticity, and sexual differentiation. The song system differs in some interesting ways from some well-studied mammalian model systems and thus offers fresh perspectives on specific theoretical issues. In this highly selective review, we concentrate on two major questions: What are the developmental changes in the song system responsible for song learning and the restriction of learning to a sensitive period, and what factors explain the highly sexually dimorphic development of this system? We discuss the important role of sex steroid hormones and of neurotrophins in creating a male-typical neural song circuit (which can learn to produce complex vocalizations) instead of a reduced, female-typical song circuit that does not produce learned song.

  14. Neural networks within multi-core optic fibers.

    Science.gov (United States)

    Cohen, Eyal; Malka, Dror; Shemer, Amir; Shahmoon, Asaf; Zalevsky, Zeev; London, Michael

    2016-07-07

    Hardware implementation of artificial neural networks facilitates real-time parallel processing of massive data sets. Optical neural networks offer low-volume 3D connectivity together with large bandwidth and minimal heat production in contrast to electronic implementation. Here, we present a conceptual design for in-fiber optical neural networks. Neurons and synapses are realized as individual silica cores in a multi-core fiber. Optical signals are transferred transversely between cores by means of optical coupling. Pump driven amplification in erbium-doped cores mimics synaptic interactions. We simulated three-layered feed-forward neural networks and explored their capabilities. Simulations suggest that networks can differentiate between given inputs depending on specific configurations of amplification; this implies classification and learning capabilities. Finally, we tested experimentally our basic neuronal elements using fibers, couplers, and amplifiers, and demonstrated that this configuration implements a neuron-like function. Therefore, devices similar to our proposed multi-core fiber could potentially serve as building blocks for future large-scale small-volume optical artificial neural networks.

  15. Perineuronal net, CSPG receptor and their regulation of neural plasticity.

    Science.gov (United States)

    Miao, Qing-Long; Ye, Qian; Zhang, Xiao-Hui

    2014-08-25

    Perineuronal nets (PNNs) are reticular structures resulting from the aggregation of extracellular matrix (ECM) molecules around the cell body and proximal neurite of specific population of neurons in the central nervous system (CNS). Since the first description of PNNs by Camillo Golgi in 1883, the molecular composition, developmental formation and potential functions of these specialized extracellular matrix structures have only been intensively studied over the last few decades. The main components of PNNs are hyaluronan (HA), chondroitin sulfate proteoglycans (CSPGs) of the lectican family, link proteins and tenascin-R. PNNs appear late in neural development, inversely correlating with the level of neural plasticity. PNNs have long been hypothesized to play a role in stabilizing the extracellular milieu, which secures the characteristic features of enveloped neurons and protects them from the influence of malicious agents. Aberrant PNN signaling can lead to CNS dysfunctions like epilepsy, stroke and Alzheimer's disease. On the other hand, PNNs create a barrier which constrains the neural plasticity and counteracts the regeneration after nerve injury. Digestion of PNNs with chondroitinase ABC accelerates functional recovery from the spinal cord injury and restores activity-dependent mechanisms for modifying neuronal connections in the adult animals, indicating that PNN is an important regulator of neural plasticity. Here, we review recent progress in the studies on the formation of PNNs during early development and the identification of CSPG receptor - an essential molecular component of PNN signaling, along with a discussion on their unique regulatory roles in neural plasticity.

  16. Neural networks within multi-core optic fibers

    Science.gov (United States)

    Cohen, Eyal; Malka, Dror; Shemer, Amir; Shahmoon, Asaf; Zalevsky, Zeev; London, Michael

    2016-07-01

    Hardware implementation of artificial neural networks facilitates real-time parallel processing of massive data sets. Optical neural networks offer low-volume 3D connectivity together with large bandwidth and minimal heat production in contrast to electronic implementation. Here, we present a conceptual design for in-fiber optical neural networks. Neurons and synapses are realized as individual silica cores in a multi-core fiber. Optical signals are transferred transversely between cores by means of optical coupling. Pump driven amplification in erbium-doped cores mimics synaptic interactions. We simulated three-layered feed-forward neural networks and explored their capabilities. Simulations suggest that networks can differentiate between given inputs depending on specific configurations of amplification; this implies classification and learning capabilities. Finally, we tested experimentally our basic neuronal elements using fibers, couplers, and amplifiers, and demonstrated that this configuration implements a neuron-like function. Therefore, devices similar to our proposed multi-core fiber could potentially serve as building blocks for future large-scale small-volume optical artificial neural networks.

  17. Enhancement of signal sensitivity in a heterogeneous neural network refined from synaptic plasticity

    Energy Technology Data Exchange (ETDEWEB)

    Li Xiumin; Small, Michael, E-mail: ensmall@polyu.edu.h, E-mail: 07901216r@eie.polyu.edu.h [Department of Electronic and Information Engineering, Hong Kong Polytechnic University, Hung Hom, Kowloon (Hong Kong)

    2010-08-15

    Long-term synaptic plasticity induced by neural activity is of great importance in informing the formation of neural connectivity and the development of the nervous system. It is reasonable to consider self-organized neural networks instead of prior imposition of a specific topology. In this paper, we propose a novel network evolved from two stages of the learning process, which are respectively guided by two experimentally observed synaptic plasticity rules, i.e. the spike-timing-dependent plasticity (STDP) mechanism and the burst-timing-dependent plasticity (BTDP) mechanism. Due to the existence of heterogeneity in neurons that exhibit different degrees of excitability, a two-level hierarchical structure is obtained after the synaptic refinement. This self-organized network shows higher sensitivity to afferent current injection compared with alternative archetypal networks with different neural connectivity. Statistical analysis also demonstrates that it has the small-world properties of small shortest path length and high clustering coefficients. Thus the selectively refined connectivity enhances the ability of neuronal communications and improves the efficiency of signal transmission in the network.

  18. Deep neural network with weight sparsity control and pre-training extracts hierarchical features and enhances classification performance: Evidence from whole-brain resting-state functional connectivity patterns of schizophrenia.

    Science.gov (United States)

    Kim, Junghoe; Calhoun, Vince D; Shim, Eunsoo; Lee, Jong-Hwan

    2016-01-01

    Functional connectivity (FC) patterns obtained from resting-state functional magnetic resonance imaging data are commonly employed to study neuropsychiatric conditions by using pattern classifiers such as the support vector machine (SVM). Meanwhile, a deep neural network (DNN) with multiple hidden layers has shown its ability to systematically extract lower-to-higher level information of image and speech data from lower-to-higher hidden layers, markedly enhancing classification accuracy. The objective of this study was to adopt the DNN for whole-brain resting-state FC pattern classification of schizophrenia (SZ) patients vs. healthy controls (HCs) and identification of aberrant FC patterns associated with SZ. We hypothesized that the lower-to-higher level features learned via the DNN would significantly enhance the classification accuracy, and proposed an adaptive learning algorithm to explicitly control the weight sparsity in each hidden layer via L1-norm regularization. Furthermore, the weights were initialized via stacked autoencoder based pre-training to further improve the classification performance. Classification accuracy was systematically evaluated as a function of (1) the number of hidden layers/nodes, (2) the use of L1-norm regularization, (3) the use of the pre-training, (4) the use of framewise displacement (FD) removal, and (5) the use of anatomical/functional parcellation. Using FC patterns from anatomically parcellated regions without FD removal, an error rate of 14.2% was achieved by employing three hidden layers and 50 hidden nodes with both L1-norm regularization and pre-training, which was substantially lower than the error rate from the SVM (22.3%). Moreover, the trained DNN weights (i.e., the learned features) were found to represent the hierarchical organization of aberrant FC patterns in SZ compared with HC. Specifically, pairs of nodes extracted from the lower hidden layer represented sparse FC patterns implicated in SZ, which was

  19. Deep neural network with weight sparsity control and pre-training extracts hierarchical features and enhances classification performance: Evidence from whole-brain resting-state functional connectivity patterns of schizophrenia

    Science.gov (United States)

    Kim, Junghoe; Calhoun, Vince D.; Shim, Eunsoo; Lee, Jong-Hwan

    2015-01-01

    Functional connectivity (FC) patterns obtained from resting-state functional magnetic resonance imaging data are commonly employed to study neuropsychiatric conditions by using pattern classifiers such as the support vector machine (SVM). Meanwhile, a deep neural network (DNN) with multiple hidden layers has shown its ability to systematically extract lower-to-higher level information of image and speech data from lower-to-higher hidden layers, markedly enhancing classification accuracy. The objective of this study was to adopt the DNN for whole-brain resting-state FC pattern classification of schizophrenia (SZ) patients vs. healthy controls (HCs) and identification of aberrant FC patterns associated with SZ. We hypothesized that the lower-to-higher level features learned via the DNN would significantly enhance the classification accuracy, and proposed an adaptive learning algorithm to explicitly control the weight sparsity in each hidden layer via L1-norm regularization. Furthermore, the weights were initialized via stacked autoencoder based pre-training to further improve the classification performance. Classification accuracy was systematically evaluated as a function of (1) the number of hidden layers/nodes, (2) the use of L1-norm regularization, (3) the use of the pre-training, (4) the use of framewise displacement (FD) removal, and (5) the use of anatomical/functional parcellation. Using FC patterns from anatomically parcellated regions without FD removal, an error rate of 14.2% was achieved by employing three hidden layers and 50 hidden nodes with both L1-norm regularization and pre-training, which was substantially lower than the error rate from the SVM (22.3%). Moreover, the trained DNN weights (i.e., the learned features) were found to represent the hierarchical organization of aberrant FC patterns in SZ compared with HC. Specifically, pairs of nodes extracted from the lower hidden layer represented sparse FC patterns implicated in SZ, which was

  20. Marginalization in Random Nonlinear Neural Networks

    Science.gov (United States)

    Vasudeva Raju, Rajkumar; Pitkow, Xaq

    2015-03-01

    Computations involved in tasks like causal reasoning in the brain require a type of probabilistic inference known as marginalization. Marginalization corresponds to averaging over irrelevant variables to obtain the probability of the variables of interest. This is a fundamental operation that arises whenever input stimuli depend on several variables, but only some are task-relevant. Animals often exhibit behavior consistent with marginalizing over some variables, but the neural substrate of this computation is unknown. It has been previously shown (Beck et al. 2011) that marginalization can be performed optimally by a deterministic nonlinear network that implements a quadratic interaction of neural activity with divisive normalization. We show that a simpler network can perform essentially the same computation. These Random Nonlinear Networks (RNN) are feedforward networks with one hidden layer, sigmoidal activation functions, and normally-distributed weights connecting the input and hidden layers. We train the output weights connecting the hidden units to an output population, such that the output model accurately represents a desired marginal probability distribution without significant information loss compared to optimal marginalization. Simulations for the case of linear coordinate transformations show that the RNN model has good marginalization performance, except for highly uncertain inputs that have low amplitude population responses. Behavioral experiments, based on these results, could then be used to identify if this model does indeed explain how the brain performs marginalization.

  1. A neural network model for texture discrimination.

    Science.gov (United States)

    Xing, J; Gerstein, G L

    1993-01-01

    A model of texture discrimination in visual cortex was built using a feedforward network with lateral interactions among relatively realistic spiking neural elements. The elements have various membrane currents, equilibrium potentials and time constants, with action potentials and synapses. The model is derived from the modified programs of MacGregor (1987). Gabor-like filters are applied to overlapping regions in the original image; the neural network with lateral excitatory and inhibitory interactions then compares and adjusts the Gabor amplitudes in order to produce the actual texture discrimination. Finally, a combination layer selects and groups various representations in the output of the network to form the final transformed image material. We show that both texture segmentation and detection of texture boundaries can be represented in the firing activity of such a network for a wide variety of synthetic to natural images. Performance details depend most strongly on the global balance of strengths of the excitatory and inhibitory lateral interconnections. The spatial distribution of lateral connective strengths has relatively little effect. Detailed temporal firing activities of single elements in the lateral connected network were examined under various stimulus conditions. Results show (as in area 17 of cortex) that a single element's response to image features local to its receptive field can be altered by changes in the global context.

  2. Self-organization of neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Clark, J.W.; Winston, J.V.; Rafelski, J.

    1984-05-14

    The plastic development of a neural-network model operating autonomously in discrete time is described by the temporal modification of interneuronal coupling strengths according to momentary neural activity. A simple algorithm (brainwashing) is found which, applied to nets with initially quasirandom connectivity, leads to model networks with properties conducive to the simulation of memory and learning phenomena. 18 references, 2 figures.

  3. Adaptive Neurons For Artificial Neural Networks

    Science.gov (United States)

    Tawel, Raoul

    1990-01-01

    Training time decreases dramatically. In improved mathematical model of neural-network processor, temperature of neurons (in addition to connection strengths, also called weights, of synapses) varied during supervised-learning phase of operation according to mathematical formalism and not heuristic rule. Evidence that biological neural networks also process information at neuronal level.

  4. Implementing Signature Neural Networks with Spiking Neurons.

    Science.gov (United States)

    Carrillo-Medina, José Luis; Latorre, Roberto

    2016-01-01

    of inhibitory connections. These parameters also modulate the memory capabilities of the network. The dynamical modes observed in the different informational dimensions in a given moment are independent and they only depend on the parameters shaping the information processing in this dimension. In view of these results, we argue that plasticity mechanisms inside individual cells and multicoding strategies can provide additional computational properties to spiking neural networks, which could enhance their capacity and performance in a wide variety of real-world tasks.

  5. Implementing Signature Neural Networks with Spiking Neurons

    Science.gov (United States)

    Carrillo-Medina, José Luis; Latorre, Roberto

    2016-01-01

    absence of inhibitory connections. These parameters also modulate the memory capabilities of the network. The dynamical modes observed in the different informational dimensions in a given moment are independent and they only depend on the parameters shaping the information processing in this dimension. In view of these results, we argue that plasticity mechanisms inside individual cells and multicoding strategies can provide additional computational properties to spiking neural networks, which could enhance their capacity and performance in a wide variety of real-world tasks. PMID:28066221

  6. Nonequilibrium landscape theory of neural networks

    Science.gov (United States)

    Yan, Han; Zhao, Lei; Hu, Liang; Wang, Xidi; Wang, Erkang; Wang, Jin

    2013-01-01

    The brain map project aims to map out the neuron connections of the human brain. Even with all of the wirings mapped out, the global and physical understandings of the function and behavior are still challenging. Hopfield quantified the learning and memory process of symmetrically connected neural networks globally through equilibrium energy. The energy basins of attractions represent memories, and the memory retrieval dynamics is determined by the energy gradient. However, the realistic neural networks are asymmetrically connected, and oscillations cannot emerge from symmetric neural networks. Here, we developed a nonequilibrium landscape–flux theory for realistic asymmetrically connected neural networks. We uncovered the underlying potential landscape and the associated Lyapunov function for quantifying the global stability and function. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. We applied our theory to rapid-eye movement sleep cycle. We identified the key regulation factors for function through global sensitivity analysis of landscape topography against wirings, which are in good agreements with experiments. PMID:24145451

  7. Neural substrates of reliability-weighted visual-tactile multisensory integration

    Directory of Open Access Journals (Sweden)

    Michael S Beauchamp

    2010-06-01

    Full Text Available As sensory systems deteriorate in aging or disease, the brain must relearn the appropriate weights to assign each modality during multisensory integration. Using blood-oxygen level dependent functional magnetic resonance imaging (BOLD fMRI of human subjects, we tested a model for the neural mechanisms of sensory weighting, termed “weighted connections”. This model holds that the connection weights between early and late areas vary depending on the reliability of the modality, independent of the level of early sensory cortex activity. When subjects detected viewed and felt touches to the hand, a network of brain areas was active, including visual areas in lateral occipital cortex, somatosensory areas in inferior parietal lobe, and multisensory areas in the intraparietal sulcus (IPS. In agreement with the weighted connection model, the connection weight measured with structural equation modeling between somatosensory cortex and IPS increased for somatosensory-reliable stimuli, and the connection weight between visual cortex and IPS increased for visual-reliable stimuli. This double dissociation of connection strengths was similar to the pattern of behavioral responses during incongruent multisensory stimulation, suggesting that weighted connections may be a neural mechanism for behavioral reliability weighting.for behavioral reliability weighting.

  8. Thermal Stimulation Alters Cervical Spinal Cord Functional Connectivity in Humans.

    Science.gov (United States)

    Weber, Kenneth A; Sentis, Amy I; Bernadel-Huey, Olivia N; Chen, Yufen; Wang, Xue; Parrish, Todd B; Mackey, Sean

    2018-01-15

    The spinal cord has an active role in the modulation and transmission of the neural signals traveling between the body and the brain. Recent advancements in functional magnetic resonance imaging (fMRI) have made the in vivo examination of spinal cord function in humans now possible. This technology has been recently extended to the investigation of resting state functional networks in the spinal cord, leading to the identification of distinct patterns of spinal cord functional connectivity. In this study, we expand on the previous work and further investigate resting state cervical spinal cord functional connectivity in healthy participants (n = 15) using high resolution imaging coupled with both seed-based functional connectivity analyses and graph theory-based metrics. Within spinal cord segment functional connectivity was present between the left and right ventral horns (bilateral motor network), left and right dorsal horns (bilateral sensory network), and the ipsilateral ventral and dorsal horns (unilateral sensory-motor network). Functional connectivity between the spinal cord segments was less apparent with the connectivity centered at the region of interest and spanning spinal cord functional network was demonstrated to be state-dependent as thermal stimulation of the right ventrolateral forearm resulted in significant disruption of the bilateral sensory network, increased network global efficiency, and decreased network modularity. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

  9. Atypical network connectivity for imitation in autism spectrum disorder.

    Science.gov (United States)

    Shih, Patricia; Shen, Mark; Ottl, Birgit; Keehn, Brandon; Gaffrey, Michael S; Müller, Ralph-Axel

    2010-08-01

    Imitation has been considered as one of the precursors for sociocommunicative development. Impairments of imitation in autism spectrum disorder (ASD) could be indicative of dysfunctional underlying neural processes. Neuroimaging studies have found reduced activation in areas associated with imitation, but a functional connectivity MRI network perspective of these regions in autism is unavailable. Functional and effective connectivity was examined in 14 male participants with ASD and 14 matched typically developing (TD) participants. We analyzed intrinsic, low-frequency blood oxygen level dependent (BOLD) fluctuations of three regions in literature found to be associated with imitation (inferior frontal gyrus [IFG], inferior parietal lobule [IPL], superior temporal sulcus [STS]). Direct group comparisons did not show significantly reduced functional connectivity within the imitation network in ASD. Conversely, we observed greater connectivity with frontal regions, particularly superior frontal and anterior cingulate gyri, in the ASD compared to TD group. Structural equation modeling of effective connectivity revealed a significantly reduced effect of IPL on IFG together with an increased influence of a region in dorsal prefrontal cortex (dPFC) on IFG in the ASD group. Our results suggest atypical connectivity of the imitation network with an enhanced role of dPFC, which may relate to behavioral impairments. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

  10. Gendered Connections

    DEFF Research Database (Denmark)

    Jensen, Steffen Bo

    2009-01-01

    This article explores the gendered nature of urban politics in Cape Town by focusing on a group of female, township politicians. Employing the Deleuzian concept of `wild connectivity', it argues that these politically entrepreneurial women were able to negotiate a highly volatile urban landscape ...... of connectivity might endure, as Capetonian politics assumes a post-apartheid structure....

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

    Science.gov (United States)

    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.

  12. Multiprocessor Neural Network in Healthcare.

    Science.gov (United States)

    Godó, Zoltán Attila; Kiss, Gábor; Kocsis, Dénes

    2015-01-01

    A possible way of creating a multiprocessor artificial neural network is by the use of microcontrollers. The RISC processors' high performance and the large number of I/O ports mean they are greatly suitable for creating such a system. During our research, we wanted to see if it is possible to efficiently create interaction between the artifical neural network and the natural nervous system. To achieve as much analogy to the living nervous system as possible, we created a frequency-modulated analog connection between the units. Our system is connected to the living nervous system through 128 microelectrodes. Two-way communication is provided through A/D transformation, which is even capable of testing psychopharmacons. The microcontroller-based analog artificial neural network can play a great role in medical singal processing, such as ECG, EEG etc.

  13. About connections.

    Science.gov (United States)

    Rockland, Kathleen S

    2015-01-01

    Despite the attention attracted by "connectomics", one can lose sight of the very real questions concerning "What are connections?" In the neuroimaging community, "structural" connectivity is ground truth and underlying constraint on "functional" or "effective" connectivity. It is referenced to underlying anatomy; but, as increasingly remarked, there is a large gap between the wealth of human brain mapping and the relatively scant data on actual anatomical connectivity. Moreover, connections have typically been discussed as "pairwise", point x projecting to point y (or: to points y and z), or more recently, in graph theoretical terms, as "nodes" or regions and the interconnecting "edges". This is a convenient shorthand, but tends not to capture the richness and nuance of basic anatomical properties as identified in the classic tradition of tracer studies. The present short review accordingly revisits connectional weights, heterogeneity, reciprocity, topography, and hierarchical organization, drawing on concrete examples. The emphasis is on presynaptic long-distance connections, motivated by the intention to probe current assumptions and promote discussions about further progress and synthesis.

  14. About Connections

    Directory of Open Access Journals (Sweden)

    Kathleen S Rockland

    2015-05-01

    Full Text Available Despite the attention attracted by connectomics, one can lose sight of the very real questions concerning What are connections? In the neuroimaging community, structural connectivity is ground truth and underlying constraint on functional or effective connectivity. It is referenced to underlying anatomy; but, as increasingly remarked, there is a large gap between the wealth of human brain mapping and the relatively scant data on actual anatomical connectivity. Moreover, connections have typically been discussed as pairwise, point x projecting to point y (or: to points y and z, or more recently, in graph theoretical terms, as nodes or regions and the interconnecting edges. This is a convenient shorthand, but tends not to capture the richness and nuance of basic anatomical properties as identified in the classic tradition of tracer studies. The present short review accordingly revisits connectional weights, heterogeneity, reciprocity, topography, and hierarchical organization, drawing on concrete examples. The emphasis is on presynaptic long-distance connections, motivated by the intention to probe current assumptions and promote discussions about further progress and synthesis.

  15. Joint brain connectivity estimation from diffusion and functional MRI data

    Science.gov (United States)

    Chu, Shu-Hsien; Lenglet, Christophe; Parhi, Keshab K.

    2015-03-01

    Estimating brain wiring patterns is critical to better understand the brain organization and function. Anatomical brain connectivity models axonal pathways, while the functional brain connectivity characterizes the statistical dependencies and correlation between the activities of various brain regions. The synchronization of brain activity can be inferred through the variation of blood-oxygen-level dependent (BOLD) signal from functional MRI (fMRI) and the neural connections can be estimated using tractography from diffusion MRI (dMRI). Functional connections between brain regions are supported by anatomical connections, and the synchronization of brain activities arises through sharing of information in the form of electro-chemical signals on axon pathways. Jointly modeling fMRI and dMRI data may improve the accuracy in constructing anatomical connectivity as well as functional connectivity. Such an approach may lead to novel multimodal biomarkers potentially able to better capture functional and anatomical connectivity variations. We present a novel brain network model which jointly models the dMRI and fMRI data to improve the anatomical connectivity estimation and extract the anatomical subnetworks associated with specific functional modes by constraining the anatomical connections as structural supports to the functional connections. The key idea is similar to a multi-commodity flow optimization problem that minimizes the cost or maximizes the efficiency for flow configuration and simultaneously fulfills the supply-demand constraint for each commodity. In the proposed network, the nodes represent the grey matter (GM) regions providing brain functionality, and the links represent white matter (WM) fiber bundles connecting those regions and delivering information. The commodities can be thought of as the information corresponding to brain activity patterns as obtained for instance by independent component analysis (ICA) of fMRI data. The concept of information

  16. Quantifying hydrologic connectivity with measures from the brain neurosciences - a feasibility study

    Science.gov (United States)

    Rinderer, Michael; Ali, Genevieve; Larsen, Laurel

    2017-04-01

    While the concept of connectivity is increasingly applied in hydrology and ecology, little agreement exists on its definition and quantification approaches. In contrast, the neurosciences have developed a systematic conceptualization of connectivity and methods to quantify it. In particular, neuroscientists make a clear distinction between: 1) structural connectivity, which is determined by the anatomy of the brain neural network, 2) functional connectivity, that is based on statistical dependencies between neural signals, and 3) effective connectivity, that allows to infer causal relations based on the assumption that "true" interactions occur with a certain time delay. In a similar vein, in hydrology, structural connectivity can be defined as the physical adjacency of landscape elements that are seen as a prerequisite of material transfer, while functional or process connectivity would rather describe interactions or causal relations between spatial adjacency characteristics and temporally varying factors. While hydrologists have suggested methods to derive structural connectivity (SC), the quantification of functional (FC) or effective connectivity (EC) has remained elusive. The goal of the current study was therefore to apply timeseries analysis methods from brain neuroscience to quantify EC and FC among groundwater (n = 34) and stream discharge (n = 1) monitoring sites in a 20-ha Swiss catchment where topography is assumed to be a major driver of connectivity. SC was assessed through influence maps that quantify the percentage of flow from an upslope site to a downslope site by applying a multiple flow direction algorithm. FC was assessed by cross-correlation, total and partial mutual information while EC was quantified via total and partial entropy, Granger causality and a phase slope index. Our results showed that many structural connections were also expressed as functional or effective connections, which is reasonable in a catchment with shallow perched

  17. The neural correlates of temporal reward discounting.

    Science.gov (United States)

    Scheres, Anouk; de Water, Erik; Mies, Gabry W

    2013-09-01

    Temporal reward discounting (TD) refers to the decrease in subjective value of a reward when the delay to that reward increases. In recent years, a growing number of studies on the neural correlates of temporal reward discounting have been conducted. This article focuses on functional magnetic resonance imaging (fMRI) studies on TD in humans. First, we describe the different types of tasks (also from behavioral studies) and the dependent variables. Subsequently, we discuss the evidence for three neurobiological models of TD: the dual-systems model, the single-system model and the self-control model. Further, studies in which nontraditional tasks (e.g., with nonmonetary rewards) were used to study TD are reviewed. Finally, we discuss the neural correlates of individual differences in discounting, and its development across the lifespan. We conclude that the evidence for each of the three neurobiological models of TD is mixed, in that all models receive (partial) support, and several studies provide support for multiple models. Because of large differences between studies in task design and analytical approach, it is difficult to draw a firm conclusion regarding which model provides the best explanation of the neural correlates of temporal discounting. We propose that some components of these models can complement each other, and future studies should test the predictions offered by different models against each other. Several future research directions are suggested, including studying the connectivity between brain regions in relation to discounting, and directly comparing the neural mechanisms involved in discounting of monetary and primary rewards. WIREs Cogn Sci 2013, 4:523-545. doi: 10.1002/wcs.1246 CONFLICT OF INTEREST: The authors have declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website. © 2013 John Wiley & Sons, Ltd.

  18. HR Connect

    Data.gov (United States)

    US Agency for International Development — HR Connect is the USAID HR personnel system which allows HR professionals to process HR actions related to employee's personal and position information. This system...

  19. Mathematics Connection

    African Journals Online (AJOL)

    MATHEMATICS CONNECTION aims at providing a forum topromote the development of Mathematics Education in Ghana. Articles that seekto enhance the teaching and/or learning of mathematics at all levels of theeducational system are welcome.

  20. Exploring connections between statistical mechanics and Green's functions for realistic systems. Temperature dependent entropy and internal energy from a self-consistent second-order Green's function

    CERN Document Server

    Welden, Alicia Rae; Zgid, Dominika

    2016-01-01

    Including finite-temperature effects into electronic structure calculations of semiconductors and metals is frequently necessary, but can become cumbersome using zero-temperature methods, which require an explicit evaluation of excited states to extend the approach to finite-temperature. Using a Matsubara Green's function formalism, it is easy to include the effects of temperature and to connect dynamic quantities such as the self-energy with static thermodynamic quantities such as the Helmholtz energy, entropy, and internal energy. We evaluate the thermodynamic quantities with a self-consistent Green's function where the self-energy is approximated to second-order (GF2). To validate our method, we benchmark it against finite temperature full configuration interaction (FCI) calculations for a hydrogen fluoride (HF) molecule and find excellent agreement at high temperatures and very good agreement at low temperatures. Then, we proceed to evaluate thermodynamic quantities for a one-dimension hydrogen solid at v...

  1. Silencer-delimited transgenesis: NRSE/RE1 sequences promote neural-specific transgene expression in a NRSF/REST-dependent manner

    Directory of Open Access Journals (Sweden)

    Xie Xiayang

    2012-11-01

    Full Text Available Abstract Background We have investigated a simple strategy for enhancing transgene expression specificity by leveraging genetic silencer elements. The approach serves to restrict transgene expression to a tissue of interest - the nervous system in the example provided here - thereby promoting specific/exclusive targeting of discrete cellular subtypes. Recent innovations are bringing us closer to understanding how the brain is organized, how neural circuits function, and how neurons can be regenerated. Fluorescent proteins enable mapping of the 'connectome', optogenetic tools allow excitable cells to be short-circuited or hyperactivated, and targeted ablation of neuronal subtypes facilitates investigations of circuit function and neuronal regeneration. Optimally, such toolsets need to be expressed solely within the cell types of interest as off-site expression makes establishing causal relationships difficult. To address this, we have exploited a gene 'silencing' system that promotes neuronal specificity by repressing expression in non-neural tissues. This methodology solves non-specific background issues that plague large-scale enhancer trap efforts and may provide a means of leveraging promoters/enhancers that otherwise express too broadly to be of value for in vivo manipulations. Results We show that a conserved neuron-restrictive silencer element (NRSE can function to restrict transgene expression to the nervous system. The neuron-restrictive silencing factor/repressor element 1 silencing transcription factor (NRSF/REST transcriptional repressor binds NRSE/repressor element 1 (RE1 sites and silences gene expression in non-neuronal cells. Inserting NRSE sites into transgenes strongly biased expression to neural tissues. NRSE sequences were effective in restricting expression of bipartite Gal4-based 'driver' transgenes within the context of an enhancer trap and when associated with a defined promoter and enhancer. However, NRSE sequences did

  2. 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.

  3. Stress dependent dispersion relations of acoustic waves travelling on a chain of point masses connected by anharmonic linear and torsional springs

    Science.gov (United States)

    Pluta, Mieczysław; Amjad, Umar; Klinghammer, Hermann; Jha, Diwaker; Tarar, Khurram; Grill, Wolfgang

    2012-05-01

    The propagation of a deformation along a flexural beam or plate depends on material properties, geometrical conditions like the beam cross-section, effects of stiffening or softening due to external stress, and last but not least the mode of the wave including its polarization. The time-of-flight (TOF) of acoustic waves is influenced by any of the above listed parameters. This effect is utilized in ultrasonic NDE and structural health monitoring applications. It was shown in earlier publications that the solutions of wave equations for a linear chain model consisting of identical mass points, subject to a direction and distance dependent potential, show the dispersion properties and dependencies on externally applied stress of the lowest longitudinal and transversal plate modes. In the model presented here anharmonic potentials are introduced. The potentials are represented by torsional springs at each mass point and linear springs between them. Dynamic equations are derived, based on interactions with next and second next neighbors. The results obtained with the developed model are compared with experimental observations concerning the reaction of the TOF for the lowest Lamb modes in an aluminum plate under variable in plane stress. The developed models are capable to demonstrate general aspects of the mode and frequency dependence of the acousto-elastic coefficients for the lowest symmetric and antisymmetric Lamb waves. The introduced anharmonicities allow furthermore for a close approximation of the experimental findings.

  4. BOLD signal and functional connectivity associated with loving kindness meditation

    Science.gov (United States)

    Garrison, Kathleen A; Scheinost, Dustin; Constable, R Todd; Brewer, Judson A

    2014-01-01

    Loving kindness is a form of meditation involving directed well-wishing, typically supported by the silent repetition of phrases such as “may all beings be happy,” to foster a feeling of selfless love. Here we used functional magnetic resonance imaging to assess the neural substrate of loving kindness meditation in experienced meditators and novices. We first assessed group differences in blood oxygen level-dependent (BOLD) signal during loving kindness meditation. We next used a relatively novel approach, the intrinsic connectivity distribution of functional connectivity, to identify regions that differ in intrinsic connectivity between groups, and then used a data-driven approach to seed-based connectivity analysis to identify which connections differ between groups. Our findings suggest group differences in brain regions involved in self-related processing and mind wandering, emotional processing, inner speech, and memory. Meditators showed overall reduced BOLD signal and intrinsic connectivity during loving kindness as compared to novices, more specifically in the posterior cingulate cortex/precuneus (PCC/PCu), a finding that is consistent with our prior work and other recent neuroimaging studies of meditation. Furthermore, meditators showed greater functional connectivity during loving kindness between the PCC/PCu and the left inferior frontal gyrus, whereas novices showed greater functional connectivity during loving kindness between the PCC/PCu and other cortical midline regions of the default mode network, the bilateral posterior insula lobe, and the bilateral parahippocampus/hippocampus. These novel findings suggest that loving kindness meditation involves a present-centered, selfless focus for meditators as compared to novices. PMID:24944863

  5. BOLD signal and functional connectivity associated with loving kindness meditation.

    Science.gov (United States)

    Garrison, Kathleen A; Scheinost, Dustin; Constable, R Todd; Brewer, Judson A

    2014-05-01

    Loving kindness is a form of meditation involving directed well-wishing, typically supported by the silent repetition of phrases such as "may all beings be happy," to foster a feeling of selfless love. Here we used functional magnetic resonance imaging to assess the neural substrate of loving kindness meditation in experienced meditators and novices. We first assessed group differences in blood oxygen level-dependent (BOLD) signal during loving kindness meditation. We next used a relatively novel approach, the intrinsic connectivity distribution of functional connectivity, to identify regions that differ in intrinsic connectivity between groups, and then used a data-driven approach to seed-based connectivity analysis to identify which connections differ between groups. Our findings suggest group differences in brain regions involved in self-related processing and mind wandering, emotional processing, inner speech, and memory. Meditators showed overall reduced BOLD signal and intrinsic connectivity during loving kindness as compared to novices, more specifically in the posterior cingulate cortex/precuneus (PCC/PCu), a finding that is consistent with our prior work and other recent neuroimaging studies of meditation. Furthermore, meditators showed greater functional connectivity during loving kindness between the PCC/PCu and the left inferior frontal gyrus, whereas novices showed greater functional connectivity during loving kindness between the PCC/PCu and other cortical midline regions of the default mode network, the bilateral posterior insula lobe, and the bilateral parahippocampus/hippocampus. These novel findings suggest that loving kindness meditation involves a present-centered, selfless focus for meditators as compared to novices.

  6. Hypothesis for the pathophysiology of delirium: role of baseline brain network connectivity and changes in inhibitory tone.

    Science.gov (United States)

    Sanders, Robert D

    2011-07-01

    Normal brain function is facilitated by a highly organized and interconnected structure allowing complex integration of sensory information and motor responses. The acute confusional state of delirium is characterized by a fluctuating disturbance in consciousness, arousal level and cognition-memory; as such, delirium represents a failure in the integration and appropriate processing of information. The pathogenesis of this cognitive disintegration is unclear; herein a hypothesis is proposed that delirium results from an acute breakdown in network connectivity within the brain. The hypothesis predicts that the extent to which the network connectivity breaks down is dependent on two factors: (i) the baseline connectivity within the brain and (ii) the level of inhibitory tone. Baseline connectivity is the connectivity of neural networks within the brain before the precipitating insult provoking delirium. Many non-modifiable risk factors for delirium influence baseline connectivity such as age, cognitive impairment, dementia and depression. Precipitant events that provoke delirium (modifiable risk factors) are hypothesized to further, and acutely, breakdown network connectivity by increasing inhibitory tone within the brain. Modifiable risk factors include inflammation, metabolic abnormalities, sleep deprivation and medication such as benzodiazepines. An important role for GABAergic neurotransmission is implicated in increasing the inhibitory tone to produce delirium. This theory accounts for the various forms of delirium, hypoactive, hyperactive and mixed. The form of delirium that ensues will depend upon how and which networks breakdown (dependent on both the individual's baseline network connectivity and the degree change in inhibitory tone produced). Copyright © 2011 Elsevier Ltd. All rights reserved.

  7. Natural language acquisition in large scale neural semantic networks

    Science.gov (United States)

    Ealey, Douglas

    This thesis puts forward the view that a purely signal- based approach to natural language processing is both plausible and desirable. By questioning the veracity of symbolic representations of meaning, it argues for a unified, non-symbolic model of knowledge representation that is both biologically plausible and, potentially, highly efficient. Processes to generate a grounded, neural form of this model-dubbed the semantic filter-are discussed. The combined effects of local neural organisation, coincident with perceptual maturation, are used to hypothesise its nature. This theoretical model is then validated in light of a number of fundamental neurological constraints and milestones. The mechanisms of semantic and episodic development that the model predicts are then used to explain linguistic properties, such as propositions and verbs, syntax and scripting. To mimic the growth of locally densely connected structures upon an unbounded neural substrate, a system is developed that can grow arbitrarily large, data- dependant structures composed of individual self- organising neural networks. The maturational nature of the data used results in a structure in which the perception of concepts is refined by the networks, but demarcated by subsequent structure. As a consequence, the overall structure shows significant memory and computational benefits, as predicted by the cognitive and neural models. Furthermore, the localised nature of the neural architecture also avoids the increasing error sensitivity and redundancy of traditional systems as the training domain grows. The semantic and episodic filters have been demonstrated to perform as well, or better, than more specialist networks, whilst using significantly larger vocabularies, more complex sentence forms and more natural corpora.

  8. How the importance of survival estimates in estimating Whinchat population dynamics depends on the scale of migratory connectivity and site fidelity

    OpenAIRE

    Cresswell, Will

    2015-01-01

    Accurate monitoring of whinchat population dynamics requires accurate estimates of breeding season survival and productivity, non-breeding survival and site fidelity (dispersal, immigration and emmigration). But monitoring of non-breeding survival between breeding seasons is confounded by the scale of site fidelity resulting in low estimates, and this will vary dependent on breeding success. Only one study (in progress) has measured true survival of whinchats on the wintering grounds (in Nige...

  9. 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.

  10. Connected Traveler

    Energy Technology Data Exchange (ETDEWEB)

    2016-06-01

    The Connected Traveler framework seeks to boost the energy efficiency of personal travel and the overall transportation system by maximizing the accuracy of predicted traveler behavior in response to real-time feedback and incentives. It is anticipated that this approach will establish a feedback loop that 'learns' traveler preferences and customizes incentives to meet or exceed energy efficiency targets by empowering individual travelers with information needed to make energy-efficient choices and reducing the complexity required to validate transportation system energy savings. This handout provides an overview of NREL's Connected Traveler project, including graphics, milestones, and contact information.

  11. Predispositions and plasticity in music and speech learning: neural correlates and implications.

    Science.gov (United States)

    Zatorre, Robert J

    2013-11-01

    Speech and music are remarkable aspects of human cognition and sensory-motor processing. Cognitive neuroscience has focused on them to understand how brain function and structure are modified by learning. Recent evidence indicates that individual differences in anatomical and functional properties of the neural architecture also affect learning and performance in these domains. Here, neuroimaging findings are reviewed that reiterate evidence of experience-dependent brain plasticity, but also point to the predictive validity of such data in relation to new learning in speech and music domains. Indices of neural sensitivity to certain stimulus features have been shown to predict individual rates of learning; individual network properties of brain activity are especially relevant in this regard, as they may reflect anatomical connectivity. Similarly, numerous studies have shown that anatomical features of auditory cortex and other structures, and their anatomical connectivity, are predictive of new sensory-motor learning ability. Implications of this growing body of literature are discussed.

  12. Exploring connections between statistical mechanics and Green's functions for realistic systems: Temperature dependent electronic entropy and internal energy from a self-consistent second-order Green's function

    Science.gov (United States)

    Welden, Alicia Rae; Rusakov, Alexander A.; Zgid, Dominika

    2016-11-01

    Including finite-temperature effects from the electronic degrees of freedom in electronic structure calculations of semiconductors and metals is desired; however, in practice it remains exceedingly difficult when using zero-temperature methods, since these methods require an explicit evaluation of multiple excited states in order to account for any finite-temperature effects. Using a Matsubara Green's function formalism remains a viable alternative, since in this formalism it is easier to include thermal effects and to connect the dynamic quantities such as the self-energy with static thermodynamic quantities such as the Helmholtz energy, entropy, and internal energy. However, despite the promising properties of this formalism, little is known about the multiple solutions of the non-linear equations present in the self-consistent Matsubara formalism and only a few cases involving a full Coulomb Hamiltonian were investigated in the past. Here, to shed some light onto the iterative nature of the Green's function solutions, we self-consistently evaluate the thermodynamic quantities for a one-dimensional (1D) hydrogen solid at various interatomic separations and temperatures using the self-energy approximated to second-order (GF2). At many points in the phase diagram of this system, multiple phases such as a metal and an insulator exist, and we are able to determine the most stable phase from the analysis of Helmholtz energies. Additionally, we show the evolution of the spectrum of 1D boron nitride to demonstrate that GF2 is capable of qualitatively describing the temperature effects influencing the size of the band gap.

  13. Exploring connections between statistical mechanics and Green's functions for realistic systems: Temperature dependent electronic entropy and internal energy from a self-consistent second-order Green's function.

    Science.gov (United States)

    Welden, Alicia Rae; Rusakov, Alexander A; Zgid, Dominika

    2016-11-28

    Including finite-temperature effects from the electronic degrees of freedom in electronic structure calculations of semiconductors and metals is desired; however, in practice it remains exceedingly difficult when using zero-temperature methods, since these methods require an explicit evaluation of multiple excited states in order to account for any finite-temperature effects. Using a Matsubara Green's function formalism remains a viable alternative, since in this formalism it is easier to include thermal effects and to connect the dynamic quantities such as the self-energy with static thermodynamic quantities such as the Helmholtz energy, entropy, and internal energy. However, despite the promising properties of this formalism, little is known about the multiple solutions of the non-linear equations present in the self-consistent Matsubara formalism and only a few cases involving a full Coulomb Hamiltonian were investigated in the past. Here, to shed some light onto the iterative nature of the Green's function solutions, we self-consistently evaluate the thermodynamic quantities for a one-dimensional (1D) hydrogen solid at various interatomic separations and temperatures using the self-energy approximated to second-order (GF2). At many points in the phase diagram of this system, multiple phases such as a metal and an insulator exist, and we are able to determine the most stable phase from the analysis of Helmholtz energies. Additionally, we show the evolution of the spectrum of 1D boron nitride to demonstrate that GF2 is capable of qualitatively describing the temperature effects influencing the size of the band gap.

  14. 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...

  15. Making connections

    NARCIS (Netherlands)

    Marion Duimel

    2007-01-01

    Original title: Verbinding maken; senioren en internet. More and more older people are finding their way to the Internet. Many people aged over 50 who have only recently gone online say that a new world has opened up for them. By connecting to the Internet they have the feeling that they

  16. CMS Connect

    Science.gov (United States)

    Balcas, J.; Bockelman, B.; Gardner, R., Jr.; Hurtado Anampa, K.; Jayatilaka, B.; Aftab Khan, F.; Lannon, K.; Larson, K.; Letts, J.; Marra Da Silva, J.; Mascheroni, M.; Mason, D.; Perez-Calero Yzquierdo, A.; Tiradani, A.

    2017-10-01

    The CMS experiment collects and analyzes large amounts of data coming from high energy particle collisions produced by the Large Hadron Collider (LHC) at CERN. This involves a huge amount of real and simulated data processing that needs to be handled in batch-oriented platforms. The CMS Global Pool of computing resources provide +100K dedicated CPU cores and another 50K to 100K CPU cores from opportunistic resources for these kind of tasks and even though production and event processing analysis workflows are already managed by existing tools, there is still a lack of support to submit final stage condor-like analysis jobs familiar to Tier-3 or local Computing Facilities users into these distributed resources in an integrated (with other CMS services) and friendly way. CMS Connect is a set of computing tools and services designed to augment existing services in the CMS Physics community focusing on these kind of condor analysis jobs. It is based on the CI-Connect platform developed by the Open Science Grid and uses the CMS GlideInWMS infrastructure to transparently plug CMS global grid resources into a virtual pool accessed via a single submission machine. This paper describes the specific developments and deployment of CMS Connect beyond the CI-Connect platform in order to integrate the service with CMS specific needs, including specific Site submission, accounting of jobs and automated reporting to standard CMS monitoring resources in an effortless way to their users.

  17. Neural crest cell survival is dependent on Rho kinase and is required for development of the mid face in mouse embryos.

    Directory of Open Access Journals (Sweden)

    Helen M Phillips

    Full Text Available Neural crest cells (NCC give rise to much of the tissue that forms the vertebrate head and face, including cartilage and bone, cranial ganglia and teeth. In this study we show that conditional expression of a dominant-negative (DN form of Rho kinase (Rock in mouse NCC results in severe hypoplasia of the frontonasal processes and first pharyngeal arch, ultimately resulting in reduction of the maxilla and nasal bones and severe craniofacial clefting affecting the nose, palate and lip. These defects resemble frontonasal dysplasia in humans. Disruption of the actin cytoskeleton, which leads to abnormalities in cell-matrix attachment, is seen in the RockDN;Wnt1-cre mutant embryos. This leads to elevated cell death, resulting in NCC deficiency and hypoplastic NCC-derived craniofacial structures. Rock is thus essential for survival of NCC that form the craniofacial region. We propose that reduced NCC numbers in the frontonasal processes and first pharyngeal arch, resulting from exacerbated cell death, may be the common mechanism underlying frontonasal dysplasia.

  18. Neural Stem Cells Rescue Cognitive and Motor Dysfunction in a Transgenic Model of Dementia with Lewy Bodies through a BDNF-Dependent Mechanism

    Directory of Open Access Journals (Sweden)

    Natalie R.S. Goldberg

    2015-11-01

    Full Text Available Accumulation of α-synuclein (α-syn into insoluble aggregates occurs in several related disorders collectively referred to as synucleinopathies. To date, studies have used neural stem cells (NSCs to examine questions about α-syn propagation, but have overlooked the therapeutic potential of NSC transplantation to modulate cognition in disorders such as dementia with Lewy bodies or Parkinson’s disease dementia. Here, we show that striatal transplantation of NSCs into aged α-syn transgenic mice significantly improves performance in multiple cognitive and motor domains. This recovery is associated with NSC expression of brain-derived neurotrophic factor (BDNF, which restores depleted levels and modulates dopaminergic and glutamatergic systems. Most importantly, transplantation of BDNF-depleted NSCs fails to improve behavior, whereas AAV-mediated BDNF delivery mimics the benefits of NSC transplantation, supporting a critical role for this neurotrophin in functional improvement. Thus, NSC transplantation could offer a promising approach to treat the understudied yet devastating cognitive components of many synucleinopathies.

  19. Neural Stem Cells Rescue Cognitive and Motor Dysfunction in a Transgenic Model of Dementia with Lewy Bodies through a BDNF-Dependent Mechanism.

    Science.gov (United States)

    Goldberg, Natalie R S; Caesar, Jacqueline; Park, Ashley; Sedgh, Shawn; Finogenov, Gilana; Masliah, Eliezer; Davis, Joy; Blurton-Jones, Mathew

    2015-11-10

    Accumulation of α-synuclein (α-syn) into insoluble aggregates occurs in several related disorders collectively referred to as synucleinopathies. To date, studies have used neural stem cells (NSCs) to examine questions about α-syn propagation, but have overlooked the therapeutic potential of NSC transplantation to modulate cognition in disorders such as dementia with Lewy bodies or Parkinson's disease dementia. Here, we show that striatal transplantation of NSCs into aged α-syn transgenic mice significantly improves performance in multiple cognitive and motor domains. This recovery is associated with NSC expression of brain-derived neurotrophic factor (BDNF), which restores depleted levels and modulates dopaminergic and glutamatergic systems. Most importantly, transplantation of BDNF-depleted NSCs fails to improve behavior, whereas AAV-mediated BDNF delivery mimics the benefits of NSC transplantation, supporting a critical role for this neurotrophin in functional improvement. Thus, NSC transplantation could offer a promising approach to treat the understudied yet devastating cognitive components of many synucleinopathies. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  20. Fuzzy neural networks: theory and applications

    Science.gov (United States)

    Gupta, Madan M.

    1994-10-01

    During recent years, significant advances have been made in two distinct technological areas: fuzzy logic and computational neural networks. The theory of fuzzy logic provides a mathematical framework to capture the uncertainties associated with human cognitive processes, such as thinking and reasoning. It also provides a mathematical morphology to emulate certain perceptual and linguistic attributes associated with human cognition. On the other hand, the computational neural network paradigms have evolved in the process of understanding the incredible learning and adaptive features of neuronal mechanisms inherent in certain biological species. Computational neural networks replicate, on a small scale, some of the computational operations observed in biological learning and adaptation. The integration of these two fields, fuzzy logic and neural networks, have given birth to an emerging technological field -- fuzzy neural networks. Fuzzy neural networks, have the potential to capture the benefits of these two fascinating fields, fuzzy logic and neural networks, into a single framework. The intent of this tutorial paper is to describe the basic notions of biological and computational neuronal morphologies, and to describe the principles and architectures of fuzzy neural networks. Towards this goal, we develop a fuzzy neural architecture based upon the notion of T-norm and T-conorm connectives. An error-based learning scheme is described for this neural structure.

  1. Cognitive control network connectivity in adolescent women with and without a parental history of depression

    Directory of Open Access Journals (Sweden)

    Peter C. Clasen

    2014-01-01

    Conclusions: Depressed parents may transmit depression vulnerability to their adolescent daughters via alterations in functional connectivity within neural circuits that underlie cognitive control of emotional information.

  2. Z(2) gauge neural network and its phase structure

    Science.gov (United States)

    Takafuji, Yusuke; Nakano, Yuki; Matsui, Tetsuo

    2012-11-01

    We study general phase structures of neural-network models that have Z(2) local gauge symmetry. The Z(2) spin variable Si=±1 on the i-th site describes a neuron state as in the Hopfield model, and the Z(2) gauge variable J=±1 describes a state of the synaptic connection between j-th and i-th neurons. The gauge symmetry allows for a self-coupling energy among J’s such as JJJ, which describes reverberation of signals. Explicitly, we consider the three models; (I) an annealed model with full and partial connections of J, (II) a quenched model with full connections where J is treated as a slow quenched variable, and (III) a quenched three-dimensional lattice model with the nearest-neighbor connections. By numerical simulations, we examine their phase structures paying attention to the effect of the reverberation term, and compare them with each other and with the annealed 3D lattice model which has been studied beforehand. By noting the dependence of thermodynamic quantities upon the total number of sites and the connectivity among sites, we obtain a coherent interpretation to understand these results. Among other things, we find that the Higgs phase of the annealed model is separated into two stable spin-glass phases in the quenched models (II) and (III).

  3. 78 FR 55684 - ConnectED Workshop

    Science.gov (United States)

    2013-09-11

    ... National Telecommunications and Information Administration ConnectED Workshop AGENCY: National... in the United States to next- generation broadband. This Notice announces that the ConnectED Workshop... ConnectED Workshop will discuss the growing bandwidth needs of K-12 schools as more schools use mobile...

  4. The Psychoactive Designer Drug and Bath Salt Constituent MDPV Causes Widespread Disruption of Brain Functional Connectivity.

    Science.gov (United States)

    Colon-Perez, Luis M; Tran, Kelvin; Thompson, Khalil; Pace, Michael C; Blum, Kenneth; Goldberger, Bruce A; Gold, Mark S; Bruijnzeel, Adriaan W; Setlow, Barry; Febo, Marcelo

    2016-08-01

    The abuse of 'bath salts' has raised concerns because of their adverse effects, which include delirium, violent behavior, and suicide ideation in severe cases. The bath salt constituent 3,4-methylenedioxypyrovalerone (MDPV) has been closely linked to these and other adverse effects. The abnormal behavioral pattern produced by acute high-dose MDPV intake suggests possible disruptions of neural communication between brain regions. Therefore, we determined if MDPV exerts disruptive effects on brain functional connectivity, particularly in areas of the prefrontal cortex. Male rats were imaged following administration of a single dose of MDPV (0.3, 1.0, or 3.0 mg/kg) or saline. Resting state brain blood oxygenation level-dependent (BOLD) images were acquired at 4.7 T. To determine the role of dopamine transmission in MDPV-induced changes in functional connectivity, a group of rats received the dopamine D1/D2 receptor antagonist cis-flupenthixol (0.5 mg/kg) 30 min before MDPV. MDPV dose-dependently reduced functional connectivity. Detailed analysis of its effects revealed that connectivity between frontal cortical and striatal areas was reduced. This included connectivity between the prelimbic prefrontal cortex and other areas of the frontal cortex and the insular cortex with hypothalamic, ventral, and dorsal striatal areas. Although the reduced connectivity appeared widespread, connectivity between these regions and somatosensory cortex was not as severely affected. Dopamine receptor blockade did not prevent the MDPV-induced decrease in functional connectivity. The results provide a novel signature of MDPV's in vivo mechanism of action. Reduced brain functional connectivity has been reported in patients suffering from psychosis and has been linked to cognitive dysfunction, audiovisual hallucinations, and negative affective states akin to those reported for MDPV-induced intoxication. The present results suggest that disruption of functional connectivity networks

  5. Resting network is composed of more than one neural pattern: an fMRI study.

    Science.gov (United States)

    Lee, T-W; Northoff, G; Wu, Y-T

    2014-08-22

    In resting state, the dynamics of blood oxygen level-dependent signals recorded by functional magnetic resonance imaging (fMRI) showed reliable modular structures. To explore the network property, previous research used to construct an adjacency matrix by Pearson's correlation and prune it using stringent statistical threshold. However, traditional analyses may lose useful information at middle to moderate high correlation level. This resting fMRI study adopted full connection as a criterion to partition the adjacency matrix into composite sub-matrices (neural patterns) and investigated the associated community organization and network features. Modular consistency across subjects was assessed using scaled inclusivity index. Our results disclosed two neural patterns with reliable modular structures. Concordant with the results of traditional intervention, community detection analysis showed that neural pattern 1, the sub-matrix at highest correlation level, was composed of sensory-motor, visual associative, default mode/midline, temporal limbic and basal ganglia structures. The neural pattern 2 was situated at middle to moderate high correlation level and comprised two larger modules, possibly associated with mental processing of outer world (such as visuo-associative, auditory and sensory-motor networks) and inner homeostasis (such as default-mode, midline and limbic systems). Graph theoretical analyses further demonstrated that the network feature of neural pattern 1 was more local and segregate, whereas that of neural pattern 2 was more global and integrative. Our results suggest that future resting fMRI research may take the neural pattern at middle to moderate high correlation range into consideration, which has long been ignored in extant literature. The variation of neural pattern 2 could be relevant to individual characteristics of self-regulatory functions, and the disruption in its topology may underlie the pathology of several neuropsychiatric illnesses

  6. Caveolin-1 plays a crucial role in inhibiting neuronal differentiation of neural stem/progenitor cells via VEGF signaling-dependent pathway.

    Directory of Open Access Journals (Sweden)

    Yue Li

    Full Text Available In the present study, we aim to elucidate the roles of caveolin-1(Cav-1, a 22 kDa protein in plasma membrane invaginations, in modulating neuronal differentiation of neural progenitor cells (NPCs. In the hippocampal dentate gyrus, we found that Cav-1 knockout mice revealed remarkably higher levels of vascular endothelial growth factor (VEGF and the more abundant formation of newborn neurons than wild type mice. We then studied the potential mechanisms of Cav-1 in modulating VEGF signaling and neuronal differentiation in isolated cultured NPCs under normoxic and hypoxic conditions. Hypoxic embryonic rat NPCs were exposed to 1% O₂ for 24 h and then switched to 21% O₂ for 1, 3, 7 and 14 days whereas normoxic NPCs were continuously cultured with 21% O₂. Compared with normoxic NPCs, hypoxic NPCs had down-regulated expression of Cav-1 and up-regulated VEGF expression and p44/42MAPK phosphorylation, and enhanced neuronal differentiation. We further studied the roles of Cav-1 in inhibiting neuronal differentiation by using Cav-1 scaffolding domain peptide and Cav-1-specific small interfering RNA. In both normoxic and hypoxic NPCs, Cav-1 peptide markedly down-regulated the expressions of VEGF and flk1, decreased the phosphorylations of p44/42MAPK, Akt and Stat3, and inhibited neuronal differentiation, whereas the knockdown of Cav-1 promoted the expression of VEGF, phosphorylations of p44/42MAPK, Akt and Stat3, and stimulated neuronal differentiation. Moreover, the enhanced phosphorylations of p44/42MAPK, Akt and Stat3, and neuronal differentiation were abolished by co-treatment of VEGF inhibitor V1. These results provide strong evidence to prove that Cav-1 can inhibit neuronal differentiation via down-regulations of VEGF, p44/42MAPK, Akt and Stat3 signaling pathways, and that VEGF signaling is a crucial target of Cav-1. The hypoxia-induced down-regulation of Cav-1 contributes to enhanced neuronal differentiation in NPCs.

  7. Focal adhesion kinase protein regulates Wnt3a gene expression to control cell fate specification in the developing neural plate

    Science.gov (United States)

    Fonar, Yuri; Gutkovich, Yoni E.; Root, Heather; Malyarova, Anastasia; Aamar, Emil; Golubovskaya, Vita M.; Elias, Sarah; Elkouby, Yaniv M.; Frank, Dale

    2011-01-01

    Focal adhesion kinase (FAK) is a cytoplasmic tyrosine kinase protein localized to regions called focal adhesions, which are contact points between cells and the extracellular matrix. FAK protein acts as a scaffold to transfer adhesion-dependent and growth factor signals into the cell. Increased FAK expression is linked to aggressive metastatic and invasive tumors. However, little is known about its normal embryonic function. FAK protein knockdown during early Xenopus laevis development anteriorizes the embryo. Morphant embryos express increased levels of anterior neural markers, with reciprocally reduced posterior neural marker expression. Posterior neural plate folding and convergence-extension is also inhibited. This anteriorized phenotype resembles that of embryos knocked down zygotically for canonical Wnt signaling. FAK and Wnt3a genes are both expressed in the neural plate, and Wnt3a expression is FAK dependent. Ectopic Wnt expression rescues this FAK morphant anteriorized phenotype. Wnt3a thus acts downstream of FAK to balance anterior–posterior cell fate specification in the developing neural plate. Wnt3a gene expression is also FAK dependent in human breast cancer cells, suggesting that this FAK–Wnt linkage is highly conserved. This unique observation connects the FAK- and Wnt-signaling pathways, both of which act to promote cancer when aberrantly activated in mammalian cells. PMID:21551070

  8. CDMA and TDMA based neural nets.

    Science.gov (United States)

    Herrero, J C

    2001-06-01

    CDMA and TDMA telecommunication techniques were established long time ago, but they have acquired a renewed presence due to the rapidly increasing mobile phones demand. In this paper, we are going to see they are suitable for neural nets, if we leave the concept "connection" between processing units and we adopt the concept "messages" exchanged between them. This may open the door to neural nets with a higher number of processing units and flexible configuration.

  9. 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.

  10. A neural population model incorporating dopaminergic neurotransmission during complex voluntary behaviors.

    Directory of Open Access Journals (Sweden)

    Stefan Fürtinger

    2014-11-01

    Full Text Available Assessing brain activity during complex voluntary motor behaviors that require the recruitment of multiple neural sites is a field of active research. Our current knowledge is primarily based on human brain imaging studies that have clear limitations in terms of temporal and spatial resolution. We developed a physiologically informed non-linear multi-compartment stochastic neural model to simulate functional brain activity coupled with neurotransmitter release during complex voluntary behavior, such as speech production. Due to its state-dependent modulation of neural firing, dopaminergic neurotransmission plays a key role in the organization of functional brain circuits controlling speech and language and thus has been incorporated in our neural population model. A rigorous mathematical proof establishing existence and uniqueness of solutions to the proposed model as well as a computationally efficient strategy to numerically approximate these solutions are presented. Simulated brain activity during the resting state and sentence production was analyzed using functional network connectivity, and graph theoretical techniques were employed to highlight differences between the two conditions. We demonstrate that our model successfully reproduces characteristic changes seen in empirical data between the resting state and speech production, and dopaminergic neurotransmission evokes pronounced changes in modeled functional connectivity by acting on the underlying biological stochastic neural model. Specifically, model and data networks in both speech and rest conditions share task-specific network features: both the simulated and empirical functional connectivity networks show an increase in nodal influence and segregation in speech over the resting state. These commonalities confirm that dopamine is a key neuromodulator of the functional connectome of speech control. Based on reproducible characteristic aspects of empirical data, we suggest a number

  11. Neural recording and modulation technologies

    Science.gov (United States)

    Chen, Ritchie; Canales, Andres; Anikeeva, Polina

    2017-01-01

    In the mammalian nervous system, billions of neurons connected by quadrillions of synapses exchange electrical, chemical and mechanical signals. Disruptions to this network manifest as neurological or psychiatric conditions. Despite decades of neuroscience research, our ability to treat or even to understand these conditions is limited by the capability of tools to probe the signalling complexity of the nervous system. Although orders of magnitude smaller and computationally faster than neurons, conventional substrate-bound electronics do not recapitulate the chemical and mechanical properties of neural tissue. This mismatch results in a foreign-body response and the encapsulation of devices by glial scars, suggesting that the design of an interface between the nervous system and a synthetic sensor requires additional materials innovation. Advances in genetic tools for manipulating neural activity have fuelled the demand for devices that are capable of simultaneously recording and controlling individual neurons at unprecedented scales. Recently, flexible organic electronics and bio- and nanomaterials have been developed for multifunctional and minimally invasive probes for long-term interaction with the nervous system. In this Review, we discuss the design lessons from the quarter-century-old field of neural engineering, highlight recent materials-driven progress in neural probes and look at emergent directions inspired by the principles of neural transduction.

  12. Connecting dots

    DEFF Research Database (Denmark)

    Murakami, Kyoko; Jacobs, Rachel L.

    2017-01-01

    and Middleton, 1995). A reminiscence conversation is a dynamic talk-in-interaction, which can produce valuable learning experience for the participants involved. Reminiscence talk contains rich, personal, historic data that can reveal and inform family members of an unknown past. In this seminar/chapter, we......Reminiscence is a self-reflecting process on past events and experiences. Not only does it enable past experiences to be brought to light through talk, but it also creates an affective environment, which allows participants to explore and construct a representation of the self (Buchanan...... of connecting the dots of recalled moments of individual family members lives and is geared towards building a family’s shared future for posterity. Lastly, we consider a wider implication of family reminiscence in terms of human development. http://www.infoagepub.com/products/Memory-Practices-and-Learning...

  13. Dynamic changes in superior temporal sulcus connectivity during perception of noisy audiovisual speech.

    Science.gov (United States)

    Nath, Audrey R; Beauchamp, Michael S

    2011-02-02

    Humans are remarkably adept at understanding speech, even when it is contaminated by noise. Multisensory integration may explain some of this ability: combining independent information from the auditory modality (vocalizations) and the visual modality (mouth movements) reduces noise and increases accuracy. Converging evidence suggests that the superior temporal sulcus (STS) is a critical brain area for multisensory integration, but little is known about its role in the perception of noisy speech. Behavioral studies have shown that perceptual judgments are weighted by the reliability of the sensory modality: more reliable modalities are weighted more strongly, even if the reliability changes rapidly. We hypothesized that changes in the functional connectivity of STS with auditory and visual cortex could provide a neural mechanism for perceptual reliability weighting. To test this idea, we performed five blood oxygenation level-dependent functional magnetic resonance imaging and behavioral experiments in 34 healthy subjects. We found increased functional connectivity between the STS and auditory cortex when the auditory modality was more reliable (less noisy) and increased functional connectivity between the STS and visual cortex when the visual modality was more reliable, even when the reliability changed rapidly during presentation of successive words. This finding matched the results of a behavioral experiment in which the perception of incongruent audiovisual syllables was biased toward the more reliable modality, even with rapidly changing reliability. Changes in STS functional connectivity may be an important neural mechanism underlying the perception of noisy speech.

  14. Interhemispheric connectivity influences the degree of modulation of TMS-induced effects during auditory processing

    Directory of Open Access Journals (Sweden)

    Jamila eAndoh

    2011-07-01

    Full Text Available Repetitive TMS (rTMS has been shown to interfere with many components of language processing, including semantic, syntactic and phonologic. However, not much is known about its effects on primary auditory processing, especially its action on Heschl’s gyrus (HG. We aimed to investigate the behavioural and neural basis of rTMS during a melody processing task, while targeting the left HG, the right HG and the Vertex as a control site. Response Times (RT were normalized relative to the baseline-rTMS (Vertex and expressed as percentage change from baseline (%RT change. We also looked at sex differences in rTMS-induced response as well as in functional connectivity during melody processing using rTMS and functional Magnetic Resonance Imaging (fMRI.Functional MRI results showed an increase in the right HG compared with the left HG during the melody task, as well as sex differences in functional connectivity indicating a greater interhemispheric connectivity between left and right HG in females compared with males. TMS results showed that 10Hz-rTMS targeting the right HG induced differential effects according to sex, with a facilitation of performance in females and an impairment of performance in males. We also found a differential correlation between the %RT change after 10Hz-rTMS targeting the right HG and the interhemispheric functional connectivity between right and left HG, indicating that an increase in interhemispheric functional connectivity was associated with a facilitation of performance. This is the first study to report a differential rTMS-induced interference with melody processing depending on sex. In addition, we showed a relationship between the interference induced by rTMS on behavioral performance and the neural activity in the network connecting left and right HG, suggesting that the interhemispheric functional connectivity could determine the degree of modulation of behavioral performance.

  15. Functional connectivity of the rodent brain using optical imaging

    Science.gov (United States)

    Guevara Codina, Edgar

    The aim of this thesis is to apply functional connectivity in a variety of animal models, using several optical imaging modalities. Even at rest, the brain shows high metabolic activity: the correlation in slow spontaneous fluctuations identifies remotely connected areas of the brain; hence the term "functional connectivity". Ongoing changes in spontaneous activity may provide insight into the neural processing that takes most of the brain metabolic activity, and so may provide a vast source of disease related changes. Brain hemodynamics may be modified during disease and affect resting-state activity. The thesis aims to better understand these changes in functional connectivity due to disease, using functional optical imaging. The optical imaging techniques explored in the first two contributions of this thesis are Optical Imaging of Intrinsic Signals and Laser Speckle Contrast Imaging, together they can estimate the metabolic rate of oxygen consumption, that closely parallels neural activity. They both have adequate spatial and temporal resolution and are well adapted to image the convexity of the mouse cortex. In the last article, a depth-sensitive modality called photoacoustic tomography was used in the newborn rat. Optical coherence tomography and laminar optical tomography were also part of the array of imaging techniques developed and applied in other collaborations. The first article of this work shows the changes in functional connectivity in an acute murine model of epileptiform activity. Homologous correlations are both increased and decreased with a small dependence on seizure duration. These changes suggest a potential decoupling between the hemodynamic parameters in resting-state networks, underlining the importance to investigate epileptic networks with several independent hemodynamic measures. The second study examines a novel murine model of arterial stiffness: the unilateral calcification of the right carotid. Seed-based connectivity analysis

  16. Physical activity and environmental enrichment regulate the generation of neural precursors in the adult mouse substantia nigra in a dopamine-dependent manner

    Directory of Open Access Journals (Sweden)

    Klaissle Philipp

    2012-10-01

    Full Text Available Abstract Background Parkinson’s disease is characterized by a continuous loss of neurons within the substantia nigra (SN leading to a depletion of dopamine. Within the adult SN as a non-neurogenic region, cells with mainly oligodendrocytic precursor characteristics, expressing the neuro-glial antigen-2 (NG2 are continuously generated. Proliferation of these cells is altered in animal models of Parkinson’s disease (PD. Exercise and environmental enrichment re-increase proliferation of NG2+ cells in PD models, however, a possible mechanistic role of dopamine for this increase is not completely understood. NG2+ cells can differentiate into oligodendrocytes but also into microglia and neurons as observed in vitro suggesting a possible hint for endogenous regenerative capacity of the SN. We investigated the role of dopamine in NG2-generation and differentiation in the adult SN stimulated by physical activity and environmental enrichment. Results We used the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP-model for dopamine depletion and analysed newborn cells in the SN at different maturation stages and time points depending on voluntary physical activity, enriched environment and levodopa-treatment. We describe an activity- induced increase of new NG2-positive cells and also mature oligodendrocytes in the SN of healthy mice. Running and enriched environment refused to stimulate NG2-generation and oligodendrogenesis in MPTP-mice, an effect which could be reversed by pharmacological levodopa-induced rescue. Conclusion We suggest dopamine being a key regulator for activity-induced generation of NG2-cells and oliogodendrocytes in the SN as a potentially relevant mechanism in endogenous nigral cellular plasticity.

  17. How T-cell-dependent and -independent challenges access the brain: vascular and neural responses to bacterial lipopolysaccharide and staphylococcal enterotoxin B.

    Science.gov (United States)

    Serrats, Jordi; Sawchenko, Paul E

    2009-10-01

    Bacterial lipopolysaccharide (LPS) is widely used to study immune influences on the CNS, and cerebrovascular prostaglandin (PG) synthesis is implicated in mediating LPS influences on some acute phase responses. Other bacterial products, such as staphylococcal enterotoxin B (SEB), impact target tissues differently in that their effects are T-lymphocyte-dependent, yet both LPS and SEB recruit a partially overlapping set of subcortical central autonomic cell groups. We sought to compare neurovascular responses to the two pathogens, and the mechanisms by which they may access the brain. Rats received iv injections of LPS (2 microg/kg), SEB (1mg/kg) or vehicle and were sacrificed 0.5-3h later. Both challenges engaged vascular cells as early 0.5h, as evidenced by induced expression of the vascular early response gene (Verge), and the immediate-early gene, NGFI-B. Cyclooxygenase-2 (COX-2) expression was detected in both endothelial and perivascular cells (PVCs) in response to LPS, but only in PVCs of SEB-challenged animals. The non-selective COX inhibitor, indomethacin (1mg/kg, iv), blocked LPS-induced activation in a subset of central autonomic structures, but failed to alter SEB-driven responses. Liposome mediated ablation of PVCs modulated the CNS response to LPS, did not affect the SEB-induced activational profile. By contrast, disruptions of interoceptive signaling by area postrema lesions or vagotomy (complete or hepatic) markedly attenuated SEB-, but not LPS-, stimulated central activational responses. Despite partial overlap in their neuronal and vascular response profiles, LPS and SEB appear to use distinct mechanisms to access the brain.

  18. Neural Tube Defects

    Science.gov (United States)

    ... vitamin, before and during pregnancy prevents most neural tube defects. Neural tube defects are usually diagnosed before the infant is ... or imaging tests. There is no cure for neural tube defects. The nerve damage and loss of function ...

  19. An intrinsic connectivity network approach to insula-derived dysfunctions among cocaine users.

    Science.gov (United States)

    Wisner, Krista M; Patzelt, Edward H; Lim, Kelvin O; MacDonald, Angus W

    2013-11-01

    Addiction is a complex phenotype, though it consistently includes characteristics of impulsivity. A number of brain regions are suggested to be involved in cocaine addiction, including the insula, which serves diverse functions including interoceptive awareness and integration of neural signals from sensory, subcortical and frontal regions. Malfunction of this integration links impulsive behavior to the insula. This study examines intrinsic connectivity of the insula in chronic cocaine users to investigate abnormal insular circuitry, its role in cocaine addiction, and relationships to measure of impulsivity. Cocaine-dependent individuals (n = 33) and healthy controls (n = 32) completed a resting-state fMRI scan. An intrinsic connectivity network (ICN) approach generated metrics of mean network connectivity and inter-network connectivity from fMRI data. Metrics pertaining to ICNs involving insula and other structures repeatedly involved in addiction (e.g. striatum) were selected for analysis, which included the capacity to discriminate groups. Relationships between group discriminating connectivity metrics and behavioral impulsivity were examined. Models demonstrated group prediction accuracy up to 75%. Accuracy of 69% was obtained by a parsimonious model of six inter-network connectivity metrics. The inter-network connectivity between an ICN involving the anterior insula and ACC, and an ICN involving the striatum, was significantly weaker in cocaine users relative to controls. The degree of reduced inter-network connectivity was significantly related to greater non-planning impulsivity in cocaine users. Aberrant insula-derived intrinsic connectivity patterns are observed in cocaine users and include dysfunctions in insula to striatal connectivity, which is furthermore linked to increased impulsivity pertaining to forethought.

  20. Classification of behavior using unsupervised temporal neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Adair, K.L. [Florida State Univ., Tallahassee, FL (United States). Dept. of Computer Science; Argo, P. [Los Alamos National Lab., NM (United States)

    1998-03-01

    Adding recurrent connections to unsupervised neural networks used for clustering creates a temporal neural network which clusters a sequence of inputs as they appear over time. The model presented combines the Jordan architecture with the unsupervised learning technique Adaptive Resonance Theory, Fuzzy ART. The combination yields a neural network capable of quickly clustering sequential pattern sequences as the sequences are generated. The applicability of the architecture is illustrated through a facility monitoring problem.

  1. 38 CFR 17.149 - Sensori-neural aids.

    Science.gov (United States)

    2010-07-01

    ... medical treatment. (c) VA will furnish needed hearing aids to those veterans who have service-connected... 38 Pensions, Bonuses, and Veterans' Relief 1 2010-07-01 2010-07-01 false Sensori-neural aids. 17... Prosthetic, Sensory, and Rehabilitative Aids § 17.149 Sensori-neural aids. (a) Notwithstanding any other...

  2. Synchronization and Inter-Layer Interactions of Noise-Driven Neural Networks.

    Science.gov (United States)

    Yuniati, Anis; Mai, Te-Lun; Chen, Chi-Ming

    2017-01-01

    In this study, we used the Hodgkin-Huxley (HH) model of neurons to investigate the phase diagram of a developing single-layer neural network and that of a network consisting of two weakly coupled neural layers. These networks are noise driven and learn through the spike-timing-dependent plasticity (STDP) or the inverse STDP rules. We described how these networks transited from a non-synchronous background activity state (BAS) to a synchronous firing state (SFS) by varying the network connectivity and the learning efficacy. In particular, we studied the interaction between a SFS layer and a BAS layer, and investigated how synchronous firing dynamics was induced in the BAS layer. We further investigated the effect of the inter-layer interaction on a BAS to SFS repair mechanism by considering three types of neuron positioning (random, grid, and lognormal distributions) and two types of inter-layer connections (random and preferential connections). Among these scenarios, we concluded that the repair mechanism has the largest effect for a network with the lognormal neuron positioning and the preferential inter-layer connections.

  3. A posteriori model validation for the temporal order of directed functional connectivity maps

    Science.gov (United States)

    Beltz, Adriene M.; Molenaar, Peter C. M.

    2015-01-01

    A posteriori model validation for the temporal order of neural directed functional connectivity maps is rare. This is striking because models that require sequential independence among residuals are regularly implemented. The aim of the current study was (a) to apply to directed functional connectivity maps of functional magnetic resonance imaging data an a posteriori model validation procedure (i.e., white noise tests of one-step-ahead prediction errors combined with decision criteria for revising the maps based upon Lagrange Multiplier tests), and (b) to demonstrate how the procedure applies to single-subject simulated, single-subject task-related, and multi-subject resting state data. Directed functional connectivity was determined by the unified structural equation model family of approaches in order to map contemporaneous and first order lagged connections among brain regions at the group- and individual-levels while incorporating external input, then white noise tests were run. Findings revealed that the validation procedure successfully detected unmodeled sequential dependencies among residuals and recovered higher order (greater than one) simulated connections, and that the procedure can accommodate task-related input. Findings also revealed that lags greater than one were present in resting state data: With a group-level network that contained only contemporaneous and first order connections, 44% of subjects required second order, individual-level connections in order to obtain maps with white noise residuals. Results have broad methodological relevance (e.g., temporal validation is necessary after directed functional connectivity analyses because the presence of unmodeled higher order sequential dependencies may bias parameter estimates) and substantive implications (e.g., higher order lags may be common in resting state data). PMID:26379489

  4. Experience-dependent emergence of beta and gamma band oscillations in the primary visual cortex during the critical period.

    Science.gov (United States)

    Chen, Guang; Rasch, Malte J; Wang, Ran; Zhang, Xiao-hui

    2015-12-09

    Neural oscillatory activities have been shown to play important roles in neural information processing and the shaping of circuit connections during development. However, it remains unknown whether and how specific neural oscillations emerge during a postnatal critical period (CP), in which neuronal connections are most substantially modified by neural activity and experience. By recording local field potentials (LFPs) and single unit activity in developing primary visual cortex (V1) of head-fixed awake mice, we here demonstrate an emergence of characteristic oscillatory activities during the CP. From the pre-CP to CP, the peak frequency of spontaneous fast oscillatory activities shifts from the beta band (15-35 Hz) to the gamma band (40-70 Hz), accompanied by a decrease of cross-frequency coupling (CFC) and broadband spike-field coherence (SFC). Moreover, visual stimulation induced a large increase of beta-band activity but a reduction of gamma-band activity specifically from the CP onwards. Dark rearing of animals from the birth delayed this emergence of oscillatory activities during the CP, suggesting its dependence on early visual experience. These findings suggest that the characteristic neuronal oscillatory activities emerged specifically during the CP may represent as neural activity trait markers for the experience-dependent maturation of developing visual cortical circuits.

  5. [Neural repair].

    Science.gov (United States)

    Kitada, Masaaki; Dezawa, Mari

    2008-05-01

    Recent progress of stem cell biology gives us the hope for neural repair. We have established methods to specifically induce functional Schwann cells and neurons from bone marro