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Sample records for model neuronal system

  1. A Neuron Model Based Ultralow Current Sensor System for Bioapplications

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    A. K. M. Arifuzzman

    2016-01-01

    Full Text Available An ultralow current sensor system based on the Izhikevich neuron model is presented in this paper. The Izhikevich neuron model has been used for its superior computational efficiency and greater biological plausibility over other well-known neuron spiking models. Of the many biological neuron spiking features, regular spiking, chattering, and neostriatal spiny projection spiking have been reproduced by adjusting the parameters associated with the model at hand. This paper also presents a modified interpretation of the regular spiking feature in which the firing pattern is similar to that of the regular spiking but with improved dynamic range offering. The sensor current ranges between 2 pA and 8 nA and exhibits linearity in the range of 0.9665 to 0.9989 for different spiking features. The efficacy of the sensor system in detecting low amount of current along with its high linearity attribute makes it very suitable for biomedical applications.

  2. Integration of human model neurons (NT2) into embryonic chick nervous system.

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    Podrygajlo, Grzegorz; Wiegreffe, Christoph; Scaal, Martin; Bicker, Gerd

    2010-02-01

    Postmitotic neurons were generated from the human NT2 teratocarcinoma cell line in a novel cell aggregate differentiation procedure. Approximately a third of the differentiated neurons expressed cell markers related to cholinergic neurotransmission. To examine whether this human cell model system can be directed toward a motoneuronal fate, postmitotic neurons were co-cultured with mouse myotubes. Outgrowing neuronal processes established close contact with the myotubes and formed neuromuscular junction-like structures that bound alpha-bungarotoxin. To determine how grafted precursor cells and neurons respond to embryonic nerve tissue, NT2 cells at different stages of neural development were injected into chick embryo neural tube and brain. Grafted NT2 neurons populated both parts of the nervous system, sometimes migrating away from the site of injection. The neural tube appeared to be more permissive for neurite extensions than the brain. Moreover, extending neurites of spinal grafts were approaching the ventral roots, thus resembling motoneuronal projections.

  3. Stochastic neuron models

    CERN Document Server

    Greenwood, Priscilla E

    2016-01-01

    This book describes a large number of open problems in the theory of stochastic neural systems, with the aim of enticing probabilists to work on them. This includes problems arising from stochastic models of individual neurons as well as those arising from stochastic models of the activities of small and large networks of interconnected neurons. The necessary neuroscience background to these problems is outlined within the text, so readers can grasp the context in which they arise. This book will be useful for graduate students and instructors providing material and references for applying probability to stochastic neuron modeling. Methods and results are presented, but the emphasis is on questions where additional stochastic analysis may contribute neuroscience insight. An extensive bibliography is included. Dr. Priscilla E. Greenwood is a Professor Emerita in the Department of Mathematics at the University of British Columbia. Dr. Lawrence M. Ward is a Professor in the Department of Psychology and the Brain...

  4. The fractional-order modeling and synchronization of electrically coupled neuron systems

    KAUST Repository

    Moaddy, K.

    2012-11-01

    In this paper, we generalize the integer-order cable model of the neuron system into the fractional-order domain, where the long memory dependence of the fractional derivative can be a better fit for the neuron response. Furthermore, the chaotic synchronization with a gap junction of two or multi-coupled-neurons of fractional-order are discussed. The circuit model, fractional-order state equations and the numerical technique are introduced in this paper for individual and multiple coupled neuron systems with different fractional-orders. Various examples are introduced with different fractional orders using the non-standard finite difference scheme together with the Grünwald-Letnikov discretization process which is easily implemented and reliably accurate. © 2011 Elsevier Ltd. All rights reserved.

  5. Extending the mirror neuron system model, II: what did I just do? A new role for mirror neurons.

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    Bonaiuto, James; Arbib, Michael A

    2010-04-01

    A mirror system is active both when an animal executes a class of actions (self-actions) and when it sees another execute an action of that class. Much attention has been given to the possible roles of mirror systems in responding to the actions of others but there has been little attention paid to their role in self-actions. In the companion article (Bonaiuto et al. Biol Cybern 96:9-38, 2007) we presented MNS2, an extension of the Mirror Neuron System model of the monkey mirror system trained to recognize the external appearance of its own actions as a basis for recognizing the actions of other animals when they perform similar actions. Here we further extend the study of the mirror system by introducing the novel hypotheses that a mirror system may additionally help in monitoring the success of a self-action and may also be activated by recognition of one's own apparent actions as well as efference copy from one's intended actions. The framework for this computational demonstration is a model of action sequencing, called augmented competitive queuing, in which action choice is based on the desirability of executable actions. We show how this "what did I just do?" function of mirror neurons can contribute to the learning of both executability and desirability which in certain cases supports rapid reorganization of motor programs in the face of disruptions.

  6. Information Processing and Collective Behavior in a Model Neuronal System

    Science.gov (United States)

    2014-03-28

    including   cancer,  cardiovascular   disease ,  and  possibly  even  late-­‐onset  diabetes.  Rapid   readjustment  of  our...channels, sodium channels, input signal, we simulate the classical Hodgkin -Huxley (HH) model with stochastic channel dynamics and deterministic stimuli

  7. A system for quantitative morphological measurement and electronic modelling of neurons: three-dimensional reconstruction.

    Science.gov (United States)

    Stockley, E W; Cole, H M; Brown, A D; Wheal, H V

    1993-04-01

    A system for accurately reconstructing neurones from optical sections taken at high magnification is described. Cells are digitised on a 68000-based microcomputer to form a database consisting of a series of linked nodes each consisting of x, y, z coordinates and an estimate of dendritic diameter. This database is used to generate three-dimensional (3-D) displays of the neurone and allows quantitative analysis of the cell volume, surface area and dendritic length. Images of the cell can be manipulated locally or transferred to an IBM 3090 mainframe where a wireframe model can be displayed on an IBM 5080 graphics terminal and rotated interactively in real time, allowing visualisation of the cell from all angles. Space-filling models can also be produced. Reconstructions can also provide morphological data for passive electrical simulations of hippocampal pyramidal cells.

  8. Model System for Live Imaging of Neuronal Responses to Injury and Repair

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    Mathieu Gravel

    2011-11-01

    Full Text Available Although it has been well established that induction of growth-associated protein-43 (GAP-43 during development coincides with axonal outgrowth and early synapse formation, the existence of neuronal plasticity and neurite outgrowth in the adult central nervous system after injuries is more controversial. To visualize the processes of neuronal injury and repair in living animals, we generated reporter mice for bioluminescence and fluorescence imaging bearing the luc (luciferase and gfp (green fluorescent protein reporter genes under the control of the murine GAP-43 promoter. Reporter functionality was first observed during the development of transgenic embryos. Using in vivo bioluminescence and fluorescence imaging, we visualized induction of the GAP-43 signals from live embryos starting at E10.5, as well as neuronal responses to brain and peripheral nerve injuries (the signals peaked at 14 days postinjury. Moreover, three-dimensional analysis of the GAP-43 bioluminescent signal confirmed that it originated from brain structures affected by ischemic injury. The analysis of fluorescence signal at cellular level revealed colocalization between endogenous protein and the GAP-43-driven gfp transgene. Taken together, our results suggest that the GAP-43-luc/gfp reporter mouse represents a valid model system for real-time analysis of neurite outgrowth and the capacity of the adult nervous system to regenerate after injuries.

  9. Comparative analysis of system identification techniques for nonlinear modeling of the neuron-microelectrode junction.

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    Khan, Saad Ahmad; Thakore, Vaibhav; Behal, Aman; Bölöni, Ladislau; Hickman, James J

    2013-03-01

    Applications of non-invasive neuroelectronic interfacing in the fields of whole-cell biosensing, biological computation and neural prosthetic devices depend critically on an efficient decoding and processing of information retrieved from a neuron-electrode junction. This necessitates development of mathematical models of the neuron-electrode interface that realistically represent the extracellular signals recorded at the neuroelectronic junction without being computationally expensive. Extracellular signals recorded using planar microelectrode or field effect transistor arrays have, until now, primarily been represented using linear equivalent circuit models that fail to reproduce the correct amplitude and shape of the signals recorded at the neuron-microelectrode interface. In this paper, to explore viable alternatives for a computationally inexpensive and efficient modeling of the neuron-electrode junction, input-output data from the neuron-electrode junction is modeled using a parametric Wiener model and a Nonlinear Auto-Regressive network with eXogenous input trained using a dynamic Neural Network model (NARX-NN model). Results corresponding to a validation dataset from these models are then employed to compare and contrast the computational complexity and efficiency of the aforementioned modeling techniques with the Lee-Schetzen technique of cross-correlation for estimating a nonlinear dynamic model of the neuroelectronic junction.

  10. Alterations in the cholinergic system of brain stem neurons in a mouse model of Rett syndrome.

    Science.gov (United States)

    Oginsky, Max F; Cui, Ningren; Zhong, Weiwei; Johnson, Christopher M; Jiang, Chun

    2014-09-15

    Rett syndrome is an autism-spectrum disorder resulting from mutations to the X-linked gene, methyl-CpG binding protein 2 (MeCP2), which causes abnormalities in many systems. It is possible that the body may develop certain compensatory mechanisms to alleviate the abnormalities. The norepinephrine system originating mainly in the locus coeruleus (LC) is defective in Rett syndrome and Mecp2-null mice. LC neurons are subject to modulation by GABA, glutamate, and acetylcholine (ACh), providing an ideal system to test the compensatory hypothesis. Here we show evidence for potential compensatory modulation of LC neurons by post- and presynaptic ACh inputs. We found that the postsynaptic currents of nicotinic ACh receptors (nAChR) were smaller in amplitude and longer in decay time in the Mecp2-null mice than in the wild type. Single-cell PCR analysis showed a decrease in the expression of α3-, α4-, α7-, and β3-subunits and an increase in the α5- and α6-subunits in the mutant mice. The α5-subunit was present in many of the LC neurons with slow-decay nAChR currents. The nicotinic modulation of spontaneous GABAA-ergic inhibitory postsynaptic currents in LC neurons was enhanced in Mecp2-null mice. In contrast, the nAChR manipulation of glutamatergic input to LC neurons was unaffected in both groups of mice. Our current-clamp studies showed that the modulation of LC neurons by ACh input was reduced moderately in Mecp2-null mice, despite the major decrease in nAChR currents, suggesting possible compensatory processes may take place, thus reducing the defects to a lesser extent in LC neurons.

  11. Transient exposure to ethanol during zebrafish embryogenesis results in defects in neuronal differentiation: an alternative model system to study FASD.

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    Xavier Joya

    Full Text Available The exposure of the human embryo to ethanol results in a spectrum of disorders involving multiple organ systems, including the impairment of the development of the central nervous system (CNS. In spite of the importance for human health, the molecular basis of prenatal ethanol exposure remains poorly understood, mainly to the difficulty of sample collection. Zebrafish is now emerging as a powerful organism for the modeling and the study of human diseases. In this work, we have assessed the sensitivity of specific subsets of neurons to ethanol exposure during embryogenesis and we have visualized the sensitive embryonic developmental periods for specific neuronal groups by the use of different transgenic zebrafish lines.In order to evaluate the teratogenic effects of acute ethanol exposure, we exposed zebrafish embryos to ethanol in a given time window and analyzed the effects in neurogenesis, neuronal differentiation and brain patterning. Zebrafish larvae exposed to ethanol displayed small eyes and/or a reduction of the body length, phenotypical features similar to the observed in children with prenatal exposure to ethanol. When neuronal populations were analyzed, we observed a clear reduction in the number of differentiated neurons in the spinal cord upon ethanol exposure. There was a decrease in the population of sensory neurons mainly due to a decrease in cell proliferation and subsequent apoptosis during neuronal differentiation, with no effect in motoneuron specification.Our investigation highlights that transient exposure to ethanol during early embryonic development affects neuronal differentiation although does not result in defects in early neurogenesis. These results establish the use of zebrafish embryos as an alternative research model to elucidate the molecular mechanism(s of ethanol-induced developmental toxicity at very early stages of embryonic development.

  12. Transient Exposure to Ethanol during Zebrafish Embryogenesis Results in Defects in Neuronal Differentiation: An Alternative Model System to Study FASD

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    Joya, Xavier; Garcia-Algar, Oscar; Vall, Oriol; Pujades, Cristina

    2014-01-01

    Background The exposure of the human embryo to ethanol results in a spectrum of disorders involving multiple organ systems, including the impairment of the development of the central nervous system (CNS). In spite of the importance for human health, the molecular basis of prenatal ethanol exposure remains poorly understood, mainly to the difficulty of sample collection. Zebrafish is now emerging as a powerful organism for the modeling and the study of human diseases. In this work, we have assessed the sensitivity of specific subsets of neurons to ethanol exposure during embryogenesis and we have visualized the sensitive embryonic developmental periods for specific neuronal groups by the use of different transgenic zebrafish lines. Methodology/Principal Findings In order to evaluate the teratogenic effects of acute ethanol exposure, we exposed zebrafish embryos to ethanol in a given time window and analyzed the effects in neurogenesis, neuronal differentiation and brain patterning. Zebrafish larvae exposed to ethanol displayed small eyes and/or a reduction of the body length, phenotypical features similar to the observed in children with prenatal exposure to ethanol. When neuronal populations were analyzed, we observed a clear reduction in the number of differentiated neurons in the spinal cord upon ethanol exposure. There was a decrease in the population of sensory neurons mainly due to a decrease in cell proliferation and subsequent apoptosis during neuronal differentiation, with no effect in motoneuron specification. Conclusion Our investigation highlights that transient exposure to ethanol during early embryonic development affects neuronal differentiation although does not result in defects in early neurogenesis. These results establish the use of zebrafish embryos as an alternative research model to elucidate the molecular mechanism(s) of ethanol-induced developmental toxicity at very early stages of embryonic development. PMID:25383948

  13. Conditional ablation of orexin/hypocretin neurons: a new mouse model for the study of narcolepsy and orexin system function.

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    Tabuchi, Sawako; Tsunematsu, Tomomi; Black, Sarah W; Tominaga, Makoto; Maruyama, Megumi; Takagi, Kazuyo; Minokoshi, Yasuhiko; Sakurai, Takeshi; Kilduff, Thomas S; Yamanaka, Akihiro

    2014-05-07

    The sleep disorder narcolepsy results from loss of hypothalamic orexin/hypocretin neurons. Although narcolepsy onset is usually postpubertal, current mouse models involve loss of either orexin peptides or orexin neurons from birth. To create a model of orexin/hypocretin deficiency with closer fidelity to human narcolepsy, diphtheria toxin A (DTA) was expressed in orexin neurons under control of the Tet-off system. Upon doxycycline removal from the diet of postpubertal orexin-tTA;TetO DTA mice, orexin neurodegeneration was rapid, with 80% cell loss within 7 d, and resulted in disrupted sleep architecture. Cataplexy, the pathognomic symptom of narcolepsy, occurred by 14 d when ∼5% of the orexin neurons remained. Cataplexy frequency increased for at least 11 weeks after doxycycline. Temporary doxycycline removal followed by reintroduction after several days enabled partial lesion of orexin neurons. DTA-induced orexin neurodegeneration caused a body weight increase without a change in food consumption, mimicking metabolic aspects of human narcolepsy. Because the orexin/hypocretin system has been implicated in the control of metabolism and addiction as well as sleep/wake regulation, orexin-tTA; TetO DTA mice are a novel model in which to study these functions, for pharmacological studies of cataplexy, and to study network reorganization as orexin input is lost.

  14. Efficient derivation of cortical glutamatergic neurons from human pluripotent stem cells: a model system to study neurotoxicity in Alzheimer's disease.

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    Vazin, Tandis; Ball, K Aurelia; Lu, Hui; Park, Hyungju; Ataeijannati, Yasaman; Head-Gordon, Teresa; Poo, Mu-ming; Schaffer, David V

    2014-02-01

    Alzheimer's disease (AD) is among the most prevalent forms of dementia affecting the aging population, and pharmacological therapies to date have not been successful in preventing disease progression. Future therapeutic efforts may benefit from the development of models that enable basic investigation of early disease pathology. In particular, disease-relevant models based on human pluripotent stem cells (hPSCs) may be promising approaches to assess the impact of neurotoxic agents in AD on specific neuronal populations and thereby facilitate the development of novel interventions to avert early disease mechanisms. We implemented an efficient paradigm to convert hPSCs into enriched populations of cortical glutamatergic neurons emerging from dorsal forebrain neural progenitors, aided by modulating Sonic hedgehog (Shh) signaling. Since AD is generally known to be toxic to glutamatergic circuits, we exposed glutamatergic neurons derived from hESCs to an oligomeric pre-fibrillar forms of Aβ known as "globulomers", which have shown strong correlation with the level of cognitive deficits in AD. Administration of such Aβ oligomers yielded signs of the disease, including cell culture age-dependent binding of Aβ and cell death in the glutamatergic populations. Furthermore, consistent with previous findings in postmortem human AD brain, Aβ-induced toxicity was selective for glutamatergic rather than GABAeric neurons present in our cultures. This in vitro model of cortical glutamatergic neurons thus offers a system for future mechanistic investigation and therapeutic development for AD pathology using human cell types specifically affected by this disease. © 2013.

  15. An Information Theoretic Model of Information Processing in the Drosophila Olfactory System: the Role of Inhibitory Neurons for System Efficiency

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    Faramarz eFaghihi

    2013-12-01

    Full Text Available Fruit flies (Drosophila melanogaster rely on their olfactory system to process environmental information. This information has to be transmitted without system-relevant loss by the olfactory system to deeper brain areas for learning. Here we study the role of several parameters of the fly's olfactory system and the environment and how they influence olfactory information transmission. We have designed an abstract model of the antennal lobe, the mushroom body and the inhibitory circuitry. Mutual information between the olfactory environment, simulated in terms of different odor concentrations, and a sub-population of intrinsic mushroom body neurons (Kenyon cells was calculated to quantify the efficiency of information transmission. With this method we study, on the one hand, the effect of different connectivity rates between olfactory projection neurons and firing thresholds of Kenyon cells. On the other hand, we analyze the influence of inhibition on mutual information between environment and mushroom body. Our simulations show an expected linear relation between the connectivity rate between the antennal lobe and the mushroom body and firing threshold of the Kenyon cells to obtain maximum mutual information for both low and high odor concentrations. However, contradicting all-day experiences, high odor concentrations cause a drastic, and unrealistic, decrease in mutual information for all connectivity rates compared to low concentration. But when inhibition on the mushroom body is included, mutual information remains at high levels independent of other system parameters. This finding points to a pivotal role of inhibition in fly information processing without which the system's efficiency will be substantially reduced.

  16. Fitting Neuron Models to Spike Trains

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    Rossant, Cyrille; Goodman, Dan F. M.; Fontaine, Bertrand; Platkiewicz, Jonathan; Magnusson, Anna K.; Brette, Romain

    2011-01-01

    Computational modeling is increasingly used to understand the function of neural circuits in systems neuroscience. These studies require models of individual neurons with realistic input–output properties. Recently, it was found that spiking models can accurately predict the precisely timed spike trains produced by cortical neurons in response to somatically injected currents, if properly fitted. This requires fitting techniques that are efficient and flexible enough to easily test different candidate models. We present a generic solution, based on the Brian simulator (a neural network simulator in Python), which allows the user to define and fit arbitrary neuron models to electrophysiological recordings. It relies on vectorization and parallel computing techniques to achieve efficiency. We demonstrate its use on neural recordings in the barrel cortex and in the auditory brainstem, and confirm that simple adaptive spiking models can accurately predict the response of cortical neurons. Finally, we show how a complex multicompartmental model can be reduced to a simple effective spiking model. PMID:21415925

  17. Is realistic neuronal modeling realistic?

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    Almog, Mara; Korngreen, Alon

    2016-11-01

    Scientific models are abstractions that aim to explain natural phenomena. A successful model shows how a complex phenomenon arises from relatively simple principles while preserving major physical or biological rules and predicting novel experiments. A model should not be a facsimile of reality; it is an aid for understanding it. Contrary to this basic premise, with the 21st century has come a surge in computational efforts to model biological processes in great detail. Here we discuss the oxymoronic, realistic modeling of single neurons. This rapidly advancing field is driven by the discovery that some neurons don't merely sum their inputs and fire if the sum exceeds some threshold. Thus researchers have asked what are the computational abilities of single neurons and attempted to give answers using realistic models. We briefly review the state of the art of compartmental modeling highlighting recent progress and intrinsic flaws. We then attempt to address two fundamental questions. Practically, can we realistically model single neurons? Philosophically, should we realistically model single neurons? We use layer 5 neocortical pyramidal neurons as a test case to examine these issues. We subject three publically available models of layer 5 pyramidal neurons to three simple computational challenges. Based on their performance and a partial survey of published models, we conclude that current compartmental models are ad hoc, unrealistic models functioning poorly once they are stretched beyond the specific problems for which they were designed. We then attempt to plot possible paths for generating realistic single neuron models. Copyright © 2016 the American Physiological Society.

  18. Mirror neurons: functions, mechanisms and models.

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    Oztop, Erhan; Kawato, Mitsuo; Arbib, Michael A

    2013-04-12

    Mirror neurons for manipulation fire both when the animal manipulates an object in a specific way and when it sees another animal (or the experimenter) perform an action that is more or less similar. Such neurons were originally found in macaque monkeys, in the ventral premotor cortex, area F5 and later also in the inferior parietal lobule. Recent neuroimaging data indicate that the adult human brain is endowed with a "mirror neuron system," putatively containing mirror neurons and other neurons, for matching the observation and execution of actions. Mirror neurons may serve action recognition in monkeys as well as humans, whereas their putative role in imitation and language may be realized in human but not in monkey. This article shows the important role of computational models in providing sufficient and causal explanations for the observed phenomena involving mirror systems and the learning processes which form them, and underlines the need for additional circuitry to lift up the monkey mirror neuron circuit to sustain the posited cognitive functions attributed to the human mirror neuron system. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  19. Modeling neuronal vulnerability in ALS.

    Science.gov (United States)

    Roselli, Francesco; Caroni, Pico

    2014-08-20

    Using computational models of motor neuron ion fluxes, firing properties, and energy requirements, Le Masson et al. (2014) reveal how local imbalances in energy homeostasis may self-amplify and contribute to neurodegeneration in ALS.

  20. Functional alterations of the ubiquitin-proteasome system in motor neurons of a mouse model of familial amyotrophic lateral sclerosis.

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    Cheroni, Cristina; Marino, Marianna; Tortarolo, Massimo; Veglianese, Pietro; De Biasi, Silvia; Fontana, Elena; Zuccarello, Laura Vitellaro; Maynard, Christa J; Dantuma, Nico P; Bendotti, Caterina

    2009-01-01

    In familial and sporadic amyotrophic lateral sclerosis (ALS) and in rodent models of the disease, alterations in the ubiquitin-proteasome system (UPS) may be responsible for the accumulation of potentially harmful ubiquitinated proteins, leading to motor neuron death. In the spinal cord of transgenic mice expressing the familial ALS superoxide dismutase 1 (SOD1) gene mutation G93A (SOD1G93A), we found a decrease in constitutive proteasome subunits during disease progression, as assessed by real-time PCR and immunohistochemistry. In parallel, an increased immunoproteasome expression was observed, which correlated with a local inflammatory response due to glial activation. These findings support the existence of proteasome modifications in ALS vulnerable tissues. To functionally investigate the UPS in ALS motor neurons in vivo, we crossed SOD1G93A mice with transgenic mice that express a fluorescently tagged reporter substrate of the UPS. In double-transgenic Ub(G76V)-GFP /SOD1G93A mice an increase in Ub(G76V)-GFP reporter, indicative of UPS impairment, was detectable in a few spinal motor neurons and not in reactive astrocytes or microglia, at symptomatic stage but not before symptoms onset. The levels of reporter transcript were unaltered, suggesting that the accumulation of Ub(G76V)-GFP was due to deficient reporter degradation. In some motor neurons the increase of Ub(G76V)-GFP was accompanied by the accumulation of ubiquitin and phosphorylated neurofilaments, both markers of ALS pathology. These data suggest that UPS impairment occurs in motor neurons of mutant SOD1-linked ALS mice and may play a role in the disease progression.

  1. Phospholipase A2 - nexus of aging, oxidative stress, neuronal excitability and functional decline of the aging nervous system? Insights from a snail model system of neuronal aging and age-associated memory impairment.

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    Petra Maria Hermann

    2014-12-01

    Full Text Available TThe aging brain can undergo a range of changes varying from subtle structural and physiological changes causing only minor functional decline under healthy normal aging conditions, to severe cognitive or neurological impairment associated with extensive loss of neurons and circuits due to age-associated neurodegenerative disease conditions. Understanding how biological aging processes affect the brain and how they contribute to the onset and progress of age-associated neurodegenerative diseases is a core research goal in contemporary neuroscience. This review focuses on the idea that changes in intrinsic neuronal electrical excitability associated with (peroxidation of membrane lipids and activation of phospholipase A2 (PLA2 enzymes are an important mechanism of learning and memory failure under normal aging conditions. Specifically, in the context of this special issue on the Biology of cognitive aging we (1 portray the opportunities offered by the identifiable neurons and behaviorally characterized neural circuits of the freshwater snail Lymnaea stagnalis in neuronal aging research and (2 recapitulate recent insights indicating a key role of lipid peroxidation-induced PLA2 as instruments of aging, oxidative stress and inflammation in age-associated neuronal and memory impairment in this model system. The findings are discussed in view of accumulating evidence suggesting involvement of analogous mechanisms in the etiology of age-associated dysfunction and disease of the human and mammalian brain.

  2. DYNAMICS IN A CLASS OF NEURON MODELS

    Institute of Scientific and Technical Information of China (English)

    Wang Junping; Ruan Jiong

    2009-01-01

    In this paper, we investigate the dynamics in a class of discrete-time neuron mo-dels. The neuron model we discussed, defined by such periodic input-output mapping as a sinusoidal function, has a remarkably larger memory capacity than the conven-tional association system with the monotonous function. Our results show that the orbit of the model takes a conventional bifurcation route, from stable equilibrium, to periodicity, even to chaotic region. And the theoretical analysis is verified by numerical simulations.

  3. Cultured neurons as model systems for biochemical and pharmacological studies on receptors for neurotransmitter amino acids

    DEFF Research Database (Denmark)

    Schousboe, A; Drejer, J; Hansen, Gert Helge

    1985-01-01

    By the use of primary cultures of neurons consisting of cerebral cortex interneurons or cerebellar granule cells it is possible to study biochemical and pharmacological aspects of receptors for GABA and glutamate. Cerebellar granule cells have been shown to express both high- and low-affinity GAB...

  4. Acupuncture prevents 6-hydroxydopamine-induced neuronal death in the nigrostriatal dopaminergic system in the rat Parkinson's disease model.

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    Park, Hi-Joon; Lim, Sabina; Joo, Wan-Seok; Yin, Chang-Shik; Lee, Hyang-Sook; Lee, Hye-Jung; Seo, Jung Chul; Leem, Kanghyun; Son, Yang-Sun; Kim, Youn-Jung; Kim, Chang-Ju; Kim, Yong-Sik; Chung, Joo-Ho

    2003-03-01

    Parkinson's disease (PD) is a chronic neurodegenerative disorder, and it has been suggested that treatments promoting survival and functional recovery of affected dopaminergic neurons could have a significant and long-term therapeutic value. In the present study, we investigated the neuroprotective effects of acupuncture on the nigrostriatal system in rat unilaterally lesioned with 6-hydroxydopamine (6-OHDA, 4 microg/microl, intrastriatal injection) using tyrosine hydroxylase (TH) and receptor for brain-derived neurotrophic factor, trkB, immunohistochemistries. Two weeks after the lesions were made, rats presented with asymmetry in rotational behavior (118.3 +/- 17.5 turns/h) following injection with apomorphine, a dopamine receptor agonist (0.5 mg/kg, sc). In contrast, acupunctural treatment at acupoints GB34 and LI3 was shown to significantly reduce this motor deficit (14.6 +/- 13.4 turns/h). Analysis via TH immunohistochemistry revealed a substantial loss of cell bodies in the substantia nigra (SN) (45.7% loss) and their terminals in the dorsolateral striatum ipsilateral to the 6-OHDA-induced lesion. However, acupunctural treatment resulted in the enhanced survival of dopaminergic neurons in the SN (21.4% loss) and their terminals in the dorsolateral striatum. Acupuncture also increased the expression of trkB significantly (35.6% increase) in the ipsilateral SN. In conclusion, we observed that only acupuncturing without the use of any drug has the neuroprotective effects against neuronal death in the rat PD model and these protective properties of acupuncture could be mediated by trkB.

  5. Nonsmooth dynamics in spiking neuron models

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    Coombes, S.; Thul, R.; Wedgwood, K. C. A.

    2012-11-01

    Large scale studies of spiking neural networks are a key part of modern approaches to understanding the dynamics of biological neural tissue. One approach in computational neuroscience has been to consider the detailed electrophysiological properties of neurons and build vast computational compartmental models. An alternative has been to develop minimal models of spiking neurons with a reduction in the dimensionality of both parameter and variable space that facilitates more effective simulation studies. In this latter case the single neuron model of choice is often a variant of the classic integrate-and-fire model, which is described by a nonsmooth dynamical system. In this paper we review some of the more popular spiking models of this class and describe the types of spiking pattern that they can generate (ranging from tonic to burst firing). We show that a number of techniques originally developed for the study of impact oscillators are directly relevant to their analysis, particularly those for treating grazing bifurcations. Importantly we highlight one particular single neuron model, capable of generating realistic spike trains, that is both computationally cheap and analytically tractable. This is a planar nonlinear integrate-and-fire model with a piecewise linear vector field and a state dependent reset upon spiking. We call this the PWL-IF model and analyse it at both the single neuron and network level. The techniques and terminology of nonsmooth dynamical systems are used to flesh out the bifurcation structure of the single neuron model, as well as to develop the notion of Lyapunov exponents. We also show how to construct the phase response curve for this system, emphasising that techniques in mathematical neuroscience may also translate back to the field of nonsmooth dynamical systems. The stability of periodic spiking orbits is assessed using a linear stability analysis of spiking times. At the network level we consider linear coupling between voltage

  6. Analog VLSI Models of Range-Tuned Neurons in the Bat Echolocation System

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    Horiuchi Timothy

    2003-01-01

    Full Text Available Bat echolocation is a fascinating topic of research for both neuroscientists and engineers, due to the complex and extremely time-constrained nature of the problem and its potential for application to engineered systems. In the bat's brainstem and midbrain exist neural circuits that are sensitive to the specific difference in time between the outgoing sonar vocalization and the returning echo. While some of the details of the neural mechanisms are known to be species-specific, a basic model of reafference-triggered, postinhibitory rebound timing is reasonably well supported by available data. We have designed low-power, analog VLSI circuits to mimic this mechanism and have demonstrated range-dependent outputs for use in a real-time sonar system. These circuits are being used to implement range-dependent vocalization amplitude, vocalization rate, and closest target isolation.

  7. Lemon Odor Reduces Stress-induced Neuronal Activation in the Emotion Expression System: An Animal Model Study

    Science.gov (United States)

    Sanada, Kazue; Sugimoto, Koji; Shutoh, Fumihiro; Hisano, Setsuji

    Perception of particular sensory stimuli from the surroundings can influence emotion in individuals. In an uncomfortable situation, humans protect themselves from some aversive stimulus by acutely evoking a stress response. Animal model studies have contributed to an understanding of neuronal mechanisms underlying the stress response in humans. To study a possible anti-stressful effect of lemon odor, an excitation of neurons secreting corticotropin-releasing hormone (CRH) as a primary factor of the hypothalamic-pituitary-adrenal axis (HPA) was analyzed in animal model experiments, in which rats are restrained in the presence or absence of the odor. The effect was evaluated by measuring expression of c-Fos (an excited neuron marker) in the hypothalamic paraventricular nucleus (PVN), a key structure of the HPA in the brain. We prepared 3 animal groups: Groups S, L and I. Groups S and L were restrained for 30 minutes while being blown by air and being exposed to the lemon odor, respectively. Group I was intact without any treatment. Two hours later of the onset of experiments, brains of all groups were sampled and processed for microscopic examination. Brain sections were processed for c-Fos immunostaining and/or in situ hybridization for CRH. In Group S but not in Group I, c-Fos expression was found in the PVN. A combined in situ hybridization-immunohistochemical dual labeling revealed that CRH mRNA-expressing neurons express c-Fos. In computer-assisted automatic counting, the incidence of c-Fos-expressing neurons in the entire PVN was statistically lower in Group L than in Group S. Detailed analysis of PVN subregions demonstrated that c-Fos-expressing neurons are fewer in Group L than in Group S in the dorsal part of the medial parvocellular subregion. These results may suggest that lemon odor attenuates the restraint stress-induced neuronal activation including CRH neurons, presumably mimicking an aspect of stress responses in humans.

  8. [The ontogeny of the mirror neuron system].

    Science.gov (United States)

    Myowa-Yamakoshi, Masako

    2014-06-01

    Abstract Humans utilize the mirror neuron system to understand and predict others' actions. However, the ontogeny of the mirror neuron system remains unknown. Whether mirror neuron function is an innate trait or whether mirror neurons acquire their sensorimotor matching properties ontogenetically remains to be clarified. In this paper, I review the ontogenetic theory of the mirror neuron system. I then discuss the functioning of the mirror neuron system in the context of social cognitive abilities, which are unique to humans. Recently, some researchers argue that it is too early to interpret the function of mirror neurons as an understanding of the underlying psychological states of others. They imply that such functioning would require inferential cognitive processes that are known to involve areas outside the mirror neuron system. Filling in this missing link may be the key to elucidating the unique ability of humans to understand others' actions.

  9. Novel model of neuronal bioenergetics

    DEFF Research Database (Denmark)

    Bak, Lasse Kristoffer; Obel, Linea Lykke Frimodt; Walls, Anne B

    2012-01-01

    matrix thus activating the tricarboxylic acid cycle dehydrogenases. This will lead to a lower activity of the MASH (malate-aspartate shuttle), which in turn will result in anaerobic glycolysis and lactate production rather than lactate utilization. In the present work, we have investigated the effect......We have previously investigated the relative roles of extracellular glucose and lactate as fuels for glutamatergic neurons during synaptic activity. The conclusion from these studies was that cultured glutamatergic neurons utilize glucose rather than lactate during NMDA (N......-methyl-d-aspartate)-induced synaptic activity and that lactate alone is not able to support neurotransmitter glutamate homoeostasis. Subsequently, a model was proposed to explain these results at the cellular level. In brief, the intermittent rises in intracellular Ca2+ during activation cause influx of Ca2+ into the mitochondrial...

  10. A neuron-astrocyte transistor-like model for neuromorphic dressed neurons.

    Science.gov (United States)

    Valenza, G; Pioggia, G; Armato, A; Ferro, M; Scilingo, E P; De Rossi, D

    2011-09-01

    Experimental evidences on the role of the synaptic glia as an active partner together with the bold synapse in neuronal signaling and dynamics of neural tissue strongly suggest to investigate on a more realistic neuron-glia model for better understanding human brain processing. Among the glial cells, the astrocytes play a crucial role in the tripartite synapsis, i.e. the dressed neuron. A well-known two-way astrocyte-neuron interaction can be found in the literature, completely revising the purely supportive role for the glia. The aim of this study is to provide a computationally efficient model for neuron-glia interaction. The neuron-glia interactions were simulated by implementing the Li-Rinzel model for an astrocyte and the Izhikevich model for a neuron. Assuming the dressed neuron dynamics similar to the nonlinear input-output characteristics of a bipolar junction transistor, we derived our computationally efficient model. This model may represent the fundamental computational unit for the development of real-time artificial neuron-glia networks opening new perspectives in pattern recognition systems and in brain neurophysiology.

  11. A Neuron Model for FPGA Spiking Neuronal Network Implementation

    Directory of Open Access Journals (Sweden)

    BONTEANU, G.

    2011-11-01

    Full Text Available We propose a neuron model, able to reproduce the basic elements of the neuronal dynamics, optimized for digital implementation of Spiking Neural Networks. Its architecture is structured in two major blocks, a datapath and a control unit. The datapath consists of a membrane potential circuit, which emulates the neuronal dynamics at the soma level, and a synaptic circuit used to update the synaptic weight according to the spike timing dependent plasticity (STDP mechanism. The proposed model is implemented into a Cyclone II-Altera FPGA device. Our results indicate the neuron model can be used to build up 1K Spiking Neural Networks on reconfigurable logic suport, to explore various network topologies.

  12. Neuronal Control of Swimming Behavior: Comparison of Vertebrate and Invertebrate Model Systems

    Science.gov (United States)

    Mullins, Olivia J.; Hackett, John T.; Buchanan, James T.; Friesen, W. Otto

    2010-01-01

    Swimming movements in the leech and lamprey are highly analogous, and lack homology. Thus, similarities in mechanisms must arise from convergent evolution rather than from common ancestry. Despite over forty years of parallel investigations into this annelid and primitive vertebrate, a close comparison of the approaches and results of this research is lacking. The present review evaluates the neural mechanisms underlying swimming in these two animals and describes the many similarities that provide intriguing examples of convergent evolution. Specifically, we discuss swim initiation, maintenance and termination, isolated nervous system preparations, neural-circuitry, central oscillators, intersegmental coupling, phase lags, cycle periods and sensory feedback. Comparative studies between species highlight mechanisms that optimize behavior and allow us a broader understanding of nervous system function. PMID:21093529

  13. Conditional expression of retrovirally delivered anti-MYCN shRNA as an in vitro model system to study neuronal differentiation in MYCN-amplified neuroblastoma

    Directory of Open Access Journals (Sweden)

    Tømte Ellen

    2011-01-01

    Full Text Available Abstract Background Neuroblastoma is a childhood cancer derived from immature cells of the sympathetic nervous system. The disease is clinically heterogeneous, ranging from neuronal differentiated benign ganglioneuromas to aggressive metastatic tumours with poor prognosis. Amplification of the MYCN oncogene is a well established poor prognostic factor found in up to 40% of high risk neuroblastomas. Using neuroblastoma cell lines to study neuronal differentiation in vitro is now well established. Several protocols, including exposure to various agents and growth factors, will differentiate neuroblastoma cell lines into neuron-like cells. These cells are characterized by a neuronal morphology with long extensively branched neurites and expression of several neurospecific markers. Results In this study we use retrovirally delivered inducible short-hairpin RNA (shRNA modules to knock down MYCN expression in MYCN-amplified (MNA neuroblastoma cell lines. By addition of the inducer doxycycline, we show that the Kelly and SK-N-BE(2 neuroblastoma cell lines efficiently differentiate into neuron-like cells with an extensive network of neurites. These cells are further characterized by increased expression of the neuronal differentiation markers NFL and GAP43. In addition, we show that induced expression of retrovirally delivered anti-MYCN shRNA inhibits cell proliferation by increasing the fraction of MNA neuroblastoma cells in the G1 phase of the cell cycle and that the clonogenic growth potential of these cells was also dramatically reduced. Conclusion We have developed an efficient MYCN-knockdown in vitro model system to study neuronal differentiation in MNA neuroblastomas.

  14. Multi-class oscillating systems of interacting neurons

    DEFF Research Database (Denmark)

    Ditlevsen, Susanne; Löcherbach, Eva

    2017-01-01

    We consider multi-class systems of interacting nonlinear Hawkes processes modeling several large families of neurons and study their mean field limits. As the total number of neurons goes to infinity we prove that the evolution within each class can be described by a nonlinear limit differential...

  15. Results on a Binding Neuron Model and Their Implications for Modified Hourglass Model for Neuronal Network

    Directory of Open Access Journals (Sweden)

    Viswanathan Arunachalam

    2013-01-01

    Full Text Available The classical models of single neuron like Hodgkin-Huxley point neuron or leaky integrate and fire neuron assume the influence of postsynaptic potentials to last till the neuron fires. Vidybida (2008 in a refreshing departure has proposed models for binding neurons in which the trace of an input is remembered only for a finite fixed period of time after which it is forgotten. The binding neurons conform to the behaviour of real neurons and are applicable in constructing fast recurrent networks for computer modeling. This paper develops explicitly several useful results for a binding neuron like the firing time distribution and other statistical characteristics. We also discuss the applicability of the developed results in constructing a modified hourglass network model in which there are interconnected neurons with excitatory as well as inhibitory inputs. Limited simulation results of the hourglass network are presented.

  16. Stochastic models for spike trains of single neurons

    CERN Document Server

    Sampath, G

    1977-01-01

    1 Some basic neurophysiology 4 The neuron 1. 1 4 1. 1. 1 The axon 7 1. 1. 2 The synapse 9 12 1. 1. 3 The soma 1. 1. 4 The dendrites 13 13 1. 2 Types of neurons 2 Signals in the nervous system 14 2. 1 Action potentials as point events - point processes in the nervous system 15 18 2. 2 Spontaneous activi~ in neurons 3 Stochastic modelling of single neuron spike trains 19 3. 1 Characteristics of a neuron spike train 19 3. 2 The mathematical neuron 23 4 Superposition models 26 4. 1 superposition of renewal processes 26 4. 2 Superposition of stationary point processe- limiting behaviour 34 4. 2. 1 Palm functions 35 4. 2. 2 Asymptotic behaviour of n stationary point processes superposed 36 4. 3 Superposition models of neuron spike trains 37 4. 3. 1 Model 4. 1 39 4. 3. 2 Model 4. 2 - A superposition model with 40 two input channels 40 4. 3. 3 Model 4. 3 4. 4 Discussion 41 43 5 Deletion models 5. 1 Deletion models with 1nd~endent interaction of excitatory and inhibitory sequences 44 VI 5. 1. 1 Model 5. 1 The basic de...

  17. System identification of Drosophila olfactory sensory neurons.

    Science.gov (United States)

    Kim, Anmo J; Lazar, Aurel A; Slutskiy, Yevgeniy B

    2011-02-01

    The lack of a deeper understanding of how olfactory sensory neurons (OSNs) encode odors has hindered the progress in understanding the olfactory signal processing in higher brain centers. Here we employ methods of system identification to investigate the encoding of time-varying odor stimuli and their representation for further processing in the spike domain by Drosophila OSNs. In order to apply system identification techniques, we built a novel low-turbulence odor delivery system that allowed us to deliver airborne stimuli in a precise and reproducible fashion. The system provides a 1% tolerance in stimulus reproducibility and an exact control of odor concentration and concentration gradient on a millisecond time scale. Using this novel setup, we recorded and analyzed the in-vivo response of OSNs to a wide range of time-varying odor waveforms. We report for the first time that across trials the response of OR59b OSNs is very precise and reproducible. Further, we empirically show that the response of an OSN depends not only on the concentration, but also on the rate of change of the odor concentration. Moreover, we demonstrate that a two-dimensional (2D) Encoding Manifold in a concentration-concentration gradient space provides a quantitative description of the neuron's response. We then use the white noise system identification methodology to construct one-dimensional (1D) and two-dimensional (2D) Linear-Nonlinear-Poisson (LNP) cascade models of the sensory neuron for a fixed mean odor concentration and fixed contrast. We show that in terms of predicting the intensity rate of the spike train, the 2D LNP model performs on par with the 1D LNP model, with a root mean-square error (RMSE) increase of about 5 to 10%. Surprisingly, we find that for a fixed contrast of the white noise odor waveforms, the nonlinear block of each of the two models changes with the mean input concentration. The shape of the nonlinearities of both the 1D and the 2D LNP model appears to be

  18. Hyperbolic Plykin attractor can exist in neuron models

    DEFF Research Database (Denmark)

    Belykh, V.; Belykh, I.; Mosekilde, Erik

    2005-01-01

    Strange hyperbolic attractors are hard to find in real physical systems. This paper provides the first example of a realistic system, a canonical three-dimensional (3D) model of bursting neurons, that is likely to have a strange hyperbolic attractor. Using a geometrical approach to the study...... of the neuron model, we derive a flow-defined Poincare map giving ail accurate account of the system's dynamics. In a parameter region where the neuron system undergoes bifurcations causing transitions between tonic spiking and bursting, this two-dimensional map becomes a map of a disk with several periodic...... holes. A particular case is the map of a disk with three holes, matching the Plykin example of a planar hyperbolic attractor. The corresponding attractor of the 3D neuron model appears to be hyperbolic (this property is not verified in the present paper) and arises as a result of a two-loop (secondary...

  19. Uncertainty propagation in neuronal dynamical systems

    NARCIS (Netherlands)

    Torres Valderrama, A.; Blom, J.G.

    2013-01-01

    One of the most notorious characteristics of neuronal electrical activity is its variability, whose origin is not just instrumentation noise, but mainly the intrinsically stochastic nature of neural computations. Neuronal models based on deterministic differential equations cannot account for such v

  20. Spiking Neural P Systems with Neuron Division and Dissolution

    Science.gov (United States)

    Liu, Xiyu; Wang, Wenping

    2016-01-01

    Spiking neural P systems are a new candidate in spiking neural network models. By using neuron division and budding, such systems can generate/produce exponential working space in linear computational steps, thus provide a way to solve computational hard problems in feasible (linear or polynomial) time with a “time-space trade-off” strategy. In this work, a new mechanism called neuron dissolution is introduced, by which redundant neurons produced during the computation can be removed. As applications, uniform solutions to two NP-hard problems: SAT problem and Subset Sum problem are constructed in linear time, working in a deterministic way. The neuron dissolution strategy is used to eliminate invalid solutions, and all answers to these two problems are encoded as indices of output neurons. Our results improve the one obtained in Science China Information Sciences, 2011, 1596-1607 by Pan et al. PMID:27627104

  1. Effective stimuli for constructing reliable neuron models.

    Directory of Open Access Journals (Sweden)

    Shaul Druckmann

    2011-08-01

    Full Text Available The rich dynamical nature of neurons poses major conceptual and technical challenges for unraveling their nonlinear membrane properties. Traditionally, various current waveforms have been injected at the soma to probe neuron dynamics, but the rationale for selecting specific stimuli has never been rigorously justified. The present experimental and theoretical study proposes a novel framework, inspired by learning theory, for objectively selecting the stimuli that best unravel the neuron's dynamics. The efficacy of stimuli is assessed in terms of their ability to constrain the parameter space of biophysically detailed conductance-based models that faithfully replicate the neuron's dynamics as attested by their ability to generalize well to the neuron's response to novel experimental stimuli. We used this framework to evaluate a variety of stimuli in different types of cortical neurons, ages and animals. Despite their simplicity, a set of stimuli consisting of step and ramp current pulses outperforms synaptic-like noisy stimuli in revealing the dynamics of these neurons. The general framework that we propose paves a new way for defining, evaluating and standardizing effective electrical probing of neurons and will thus lay the foundation for a much deeper understanding of the electrical nature of these highly sophisticated and non-linear devices and of the neuronal networks that they compose.

  2. A computational model of motor neuron degeneration.

    Science.gov (United States)

    Le Masson, Gwendal; Przedborski, Serge; Abbott, L F

    2014-08-20

    To explore the link between bioenergetics and motor neuron degeneration, we used a computational model in which detailed morphology and ion conductance are paired with intracellular ATP production and consumption. We found that reduced ATP availability increases the metabolic cost of a single action potential and disrupts K+/Na+ homeostasis, resulting in a chronic depolarization. The magnitude of the ATP shortage at which this ionic instability occurs depends on the morphology and intrinsic conductance characteristic of the neuron. If ATP shortage is confined to the distal part of the axon, the ensuing local ionic instability eventually spreads to the whole neuron and involves fasciculation-like spiking events. A shortage of ATP also causes a rise in intracellular calcium. Our modeling work supports the notion that mitochondrial dysfunction can account for salient features of the paralytic disorder amyotrophic lateral sclerosis, including motor neuron hyperexcitability, fasciculation, and differential vulnerability of motor neuron subpopulations.

  3. Silicon-Neuron Design: A Dynamical Systems Approach.

    Science.gov (United States)

    Arthur, John V; Boahen, Kwabena

    2011-01-01

    We present an approach to design spiking silicon neurons based on dynamical systems theory. Dynamical systems theory aids in choosing the appropriate level of abstraction, prescribing a neuron model with the desired dynamics while maintaining simplicity. Further, we provide a procedure to transform the prescribed equations into subthreshold current-mode circuits. We present a circuit design example, a positive-feedback integrate-and-fire neuron, fabricated in 0.25 μm CMOS. We analyze and characterize the circuit, and demonstrate that it can be configured to exhibit desired behaviors, including spike-frequency adaptation and two forms of bursting.

  4. Neuron Loss in Transgenic Mouse Models of Alzheimer's Disease

    Directory of Open Access Journals (Sweden)

    Oliver Wirths

    2010-01-01

    Full Text Available Since their initial generation in the mid 1990s, transgenic mouse models of Alzheimers's disease (AD have been proven to be valuable model systems which are indispensable for modern AD research. Whereas most of these models are characterized by extensive amyloid plaque pathology, inflammatory changes and often behavioral deficits, modeling of neuron loss was much less successful. The present paper discusses the current achievements of modeling neuron loss in transgenic mouse models based on APP/Aβ and Tau overexpression and provides an overview of currently available AD mouse models showing these pathological alterations.

  5. Stochastic biomathematical models with applications to neuronal modeling

    CERN Document Server

    Batzel, Jerry; Ditlevsen, Susanne

    2013-01-01

    Stochastic biomathematical models are becoming increasingly important as new light is shed on the role of noise in living systems. In certain biological systems, stochastic effects may even enhance a signal, thus providing a biological motivation for the noise observed in living systems. Recent advances in stochastic analysis and increasing computing power facilitate the analysis of more biophysically realistic models, and this book provides researchers in computational neuroscience and stochastic systems with an overview of recent developments. Key concepts are developed in chapters written by experts in their respective fields. Topics include: one-dimensional homogeneous diffusions and their boundary behavior, large deviation theory and its application in stochastic neurobiological models, a review of mathematical methods for stochastic neuronal integrate-and-fire models, stochastic partial differential equation models in neurobiology, and stochastic modeling of spreading cortical depression.

  6. A predictive in vitro model of the impact of drugs with anticholinergic properties on human neuronal and astrocytic systems.

    Directory of Open Access Journals (Sweden)

    Elizabeth K Woehrling

    Full Text Available The link between off-target anticholinergic effects of medications and acute cognitive impairment in older adults requires urgent investigation. We aimed to determine whether a relevant in vitro model may aid the identification of anticholinergic responses to drugs and the prediction of anticholinergic risk during polypharmacy. In this preliminary study we employed a co-culture of human-derived neurons and astrocytes (NT2.N/A derived from the NT2 cell line. NT2.N/A cells possess much of the functionality of mature neurons and astrocytes, key cholinergic phenotypic markers and muscarinic acetylcholine receptors (mAChRs. The cholinergic response of NT2 astrocytes to the mAChR agonist oxotremorine was examined using the fluorescent dye fluo-4 to quantitate increases in intracellular calcium [Ca2+]i. Inhibition of this response by drugs classified as severe (dicycloverine, amitriptyline, moderate (cyclobenzaprine and possible (cimetidine on the Anticholinergic Cognitive Burden (ACB scale, was examined after exposure to individual and pairs of compounds. Individually, dicycloverine had the most significant effect regarding inhibition of the astrocytic cholinergic response to oxotremorine, followed by amitriptyline then cyclobenzaprine and cimetidine, in agreement with the ACB scale. In combination, dicycloverine with cyclobenzaprine had the most significant effect, followed by dicycloverine with amitriptyline. The order of potency of the drugs in combination frequently disagreed with predicted ACB scores derived from summation of the individual drug scores, suggesting current scales may underestimate the effect of polypharmacy. Overall, this NT2.N/A model may be appropriate for further investigation of adverse anticholinergic effects of multiple medications, in order to inform clinical choices of suitable drug use in the elderly.

  7. Why is your spouse so predictable? Connecting mirror neuron system and self-expansion model of love.

    Science.gov (United States)

    Ortigue, Stephanie; Bianchi-Demicheli, Francesco

    2008-12-01

    The simulation theory assumes we understand actions and intentions of others through a direct matching process. This matching process activates a complex brain network involving the mirror neuron system (MNS), which is self-related and active when one does something or observes someone else acting. Because social psychology admits that mutual intention's understanding grows in close relationship as love grows, we hypothesize that mirror mechanisms take place in love relationships. The similarities between the mirror matching process and the mutual intention's understanding that occurs when two persons are in love suggest that exposure to love might affect functional and neural mechanisms, thus facilitating the understanding of the beloved's intentions. Congruent with our hypothesis, our preliminary results from 38 subjects strongly suggest a significant facilitation effect of love on understanding the intentions of the beloved (as opposed to control stimuli). Based on these phenomenological, and neurofunctional findings we suggest that the mirror mechanisms are involved in the facilitation effects of love for understanding intentions, and might further be extended to any types of love (e.g., passionate love, maternal love). Love experiences are important not only to the beloved himself, but also to any societal, cultural, and institutional patterns that relate to love. Yet, concerning its subjective character, love experiences are difficult to access. The modern procedures and techniques of socio-cognitive neuroscience make it possible to understand love and self-related experiences not only by the analysis of subjective self-reported questionnaires, but also by approaching the automatic (non-conscious) mirror experiences of love in healthy subjects, and neurological patients with a brain damage within the mirror neuron system. Although the psychology of love is now well admitted, the systematic study of the automatic facilitation effect of love through mirror

  8. Models of the stochastic activity of neurones

    CERN Document Server

    Holden, Arun Vivian

    1976-01-01

    These notes have grown from a series of seminars given at Leeds between 1972 and 1975. They represent an attempt to gather together the different kinds of model which have been proposed to account for the stochastic activity of neurones, and to provide an introduction to this area of mathematical biology. A striking feature of the electrical activity of the nervous system is that it appears stochastic: this is apparent at all levels of recording, ranging from intracellular recordings to the electroencephalogram. The chapters start with fluctuations in membrane potential, proceed through single unit and synaptic activity and end with the behaviour of large aggregates of neurones: L have chgaen this seque~~e\\/~~';uggest that the interesting behaviourr~f :the nervous system - its individuality, variability and dynamic forms - may in part result from the stochastic behaviour of its components. I would like to thank Dr. Julio Rubio for reading and commenting on the drafts, Mrs. Doris Beighton for producing the fin...

  9. Neuronal communication through coherence in the human motor system

    NARCIS (Netherlands)

    Schoffelen, J.M.

    2007-01-01

    This thesis explores the concept of neuronal communication through oscillatory synchronization. For most of the described research, we used the human motor system as a model system, in particular the cortico spinal system, in combination with non invasive recording techniques. Oscillatory

  10. Modeling the Development of Goal-Specificity in Mirror Neurons.

    Science.gov (United States)

    Thill, Serge; Svensson, Henrik; Ziemke, Tom

    2011-12-01

    Neurophysiological studies have shown that parietal mirror neurons encode not only actions but also the goal of these actions. Although some mirror neurons will fire whenever a certain action is perceived (goal-independently), most will only fire if the motion is perceived as part of an action with a specific goal. This result is important for the action-understanding hypothesis as it provides a potential neurological basis for such a cognitive ability. It is also relevant for the design of artificial cognitive systems, in particular robotic systems that rely on computational models of the mirror system in their interaction with other agents. Yet, to date, no computational model has explicitly addressed the mechanisms that give rise to both goal-specific and goal-independent parietal mirror neurons. In the present paper, we present a computational model based on a self-organizing map, which receives artificial inputs representing information about both the observed or executed actions and the context in which they were executed. We show that the map develops a biologically plausible organization in which goal-specific mirror neurons emerge. We further show that the fundamental cause for both the appearance and the number of goal-specific neurons can be found in geometric relationships between the different inputs to the map. The results are important to the action-understanding hypothesis as they provide a mechanism for the emergence of goal-specific parietal mirror neurons and lead to a number of predictions: (1) Learning of new goals may mostly reassign existing goal-specific neurons rather than recruit new ones; (2) input differences between executed and observed actions can explain observed corresponding differences in the number of goal-specific neurons; and (3) the percentage of goal-specific neurons may differ between motion primitives.

  11. How neurons migrate: a dynamic in-silico model of neuronal migration in the developing cortex

    LENUS (Irish Health Repository)

    Setty, Yaki

    2011-09-30

    Abstract Background Neuronal migration, the process by which neurons migrate from their place of origin to their final position in the brain, is a central process for normal brain development and function. Advances in experimental techniques have revealed much about many of the molecular components involved in this process. Notwithstanding these advances, how the molecular machinery works together to govern the migration process has yet to be fully understood. Here we present a computational model of neuronal migration, in which four key molecular entities, Lis1, DCX, Reelin and GABA, form a molecular program that mediates the migration process. Results The model simulated the dynamic migration process, consistent with in-vivo observations of morphological, cellular and population-level phenomena. Specifically, the model reproduced migration phases, cellular dynamics and population distributions that concur with experimental observations in normal neuronal development. We tested the model under reduced activity of Lis1 and DCX and found an aberrant development similar to observations in Lis1 and DCX silencing expression experiments. Analysis of the model gave rise to unforeseen insights that could guide future experimental study. Specifically: (1) the model revealed the possibility that under conditions of Lis1 reduced expression, neurons experience an oscillatory neuron-glial association prior to the multipolar stage; and (2) we hypothesized that observed morphology variations in rats and mice may be explained by a single difference in the way that Lis1 and DCX stimulate bipolar motility. From this we make the following predictions: (1) under reduced Lis1 and enhanced DCX expression, we predict a reduced bipolar migration in rats, and (2) under enhanced DCX expression in mice we predict a normal or a higher bipolar migration. Conclusions We present here a system-wide computational model of neuronal migration that integrates theory and data within a precise

  12. Automatic fitting of spiking neuron models to electrophysiological recordings

    Directory of Open Access Journals (Sweden)

    Cyrille Rossant

    2010-03-01

    Full Text Available Spiking models can accurately predict the spike trains produced by cortical neurons in response to somatically injected currents. Since the specific characteristics of the model depend on the neuron, a computational method is required to fit models to electrophysiological recordings. The fitting procedure can be very time consuming both in terms of computer simulations and in terms of code writing. We present algorithms to fit spiking models to electrophysiological data (time-varying input and spike trains that can run in parallel on graphics processing units (GPUs. The model fitting library is interfaced with Brian, a neural network simulator in Python. If a GPU is present it uses just-in-time compilation to translate model equations into optimized code. Arbitrary models can then be defined at script level and run on the graphics card. This tool can be used to obtain empirically validated spiking models of neurons in various systems. We demonstrate its use on public data from the INCF Quantitative Single-Neuron Modeling 2009 competition by comparing the performance of a number of neuron spiking models.

  13. Context-aware modeling of neuronal morphologies

    Directory of Open Access Journals (Sweden)

    Benjamin eTorben-Nielsen

    2014-09-01

    Full Text Available Neuronal morphologies are pivotal for brain functioning: physical overlap between dendrites and axons constrain the circuit topology, and the precise shape and composition of dendrites determine the integration of inputs to produce an output signal. At the same time, morphologies are highly diverse and variant. The variance, presumably, originates from neurons developing in a densely packed brain substrate where they interact (e.g., repulsion or attraction with other actors in this substrate. However, when studying neurons their context is never part of the analysis and they are treated as if they existed in isolation.Here we argue that to fully understand neuronal morphology and its variance it is important to consider neurons in relation to each other and to other actors in the surrounding brain substrate, i.e., their context. We propose a context-aware computational framework, NeuroMaC, in which large numbers of neurons can be grown simultaneously according to growth rules expressed in terms of interactions between the developing neuron and the surrounding brain substrate.As a proof of principle, we demonstrate that by using NeuroMaC we can generate accurate virtual morphologies of distinct classes both in isolation and as part of neuronal forests. Accuracy is validated against population statistics of experimentally reconstructed morphologies. We show that context-aware generation of neurons can explain characteristics of variation. Indeed, plausible variation is an inherent property of the morphologies generated by context-aware rules. We speculate about the applicability of this framework to investigate morphologies and circuits, to classify healthy and pathological morphologies, and to generate large quantities of morphologies for large-scale modeling.

  14. A developmental approach to predicting neuronal connectivity from small biological datasets: a gradient-based neuron growth model.

    Science.gov (United States)

    Borisyuk, Roman; Al Azad, Abul Kalam; Conte, Deborah; Roberts, Alan; Soffe, Stephen R

    2014-01-01

    Relating structure and function of neuronal circuits is a challenging problem. It requires demonstrating how dynamical patterns of spiking activity lead to functions like cognitive behaviour and identifying the neurons and connections that lead to appropriate activity of a circuit. We apply a "developmental approach" to define the connectome of a simple nervous system, where connections between neurons are not prescribed but appear as a result of neuron growth. A gradient based mathematical model of two-dimensional axon growth from rows of undifferentiated neurons is derived for the different types of neurons in the brainstem and spinal cord of young tadpoles of the frog Xenopus. Model parameters define a two-dimensional CNS growth environment with three gradient cues and the specific responsiveness of the axons of each neuron type to these cues. The model is described by a nonlinear system of three difference equations; it includes a random variable, and takes specific neuron characteristics into account. Anatomical measurements are first used to position cell bodies in rows and define axon origins. Then a generalization procedure allows information on the axons of individual neurons from small anatomical datasets to be used to generate larger artificial datasets. To specify parameters in the axon growth model we use a stochastic optimization procedure, derive a cost function and find the optimal parameters for each type of neuron. Our biologically realistic model of axon growth starts from axon outgrowth from the cell body and generates multiple axons for each different neuron type with statistical properties matching those of real axons. We illustrate how the axon growth model works for neurons with axons which grow to the same and the opposite side of the CNS. We then show how, by adding a simple specification for dendrite morphology, our model "developmental approach" allows us to generate biologically-realistic connectomes.

  15. A developmental approach to predicting neuronal connectivity from small biological datasets: a gradient-based neuron growth model.

    Directory of Open Access Journals (Sweden)

    Roman Borisyuk

    Full Text Available Relating structure and function of neuronal circuits is a challenging problem. It requires demonstrating how dynamical patterns of spiking activity lead to functions like cognitive behaviour and identifying the neurons and connections that lead to appropriate activity of a circuit. We apply a "developmental approach" to define the connectome of a simple nervous system, where connections between neurons are not prescribed but appear as a result of neuron growth. A gradient based mathematical model of two-dimensional axon growth from rows of undifferentiated neurons is derived for the different types of neurons in the brainstem and spinal cord of young tadpoles of the frog Xenopus. Model parameters define a two-dimensional CNS growth environment with three gradient cues and the specific responsiveness of the axons of each neuron type to these cues. The model is described by a nonlinear system of three difference equations; it includes a random variable, and takes specific neuron characteristics into account. Anatomical measurements are first used to position cell bodies in rows and define axon origins. Then a generalization procedure allows information on the axons of individual neurons from small anatomical datasets to be used to generate larger artificial datasets. To specify parameters in the axon growth model we use a stochastic optimization procedure, derive a cost function and find the optimal parameters for each type of neuron. Our biologically realistic model of axon growth starts from axon outgrowth from the cell body and generates multiple axons for each different neuron type with statistical properties matching those of real axons. We illustrate how the axon growth model works for neurons with axons which grow to the same and the opposite side of the CNS. We then show how, by adding a simple specification for dendrite morphology, our model "developmental approach" allows us to generate biologically-realistic connectomes.

  16. Human motor neuron progenitor transplantation leads to endogenous neuronal sparing in 3 models of motor neuron loss.

    Science.gov (United States)

    Wyatt, Tanya J; Rossi, Sharyn L; Siegenthaler, Monica M; Frame, Jennifer; Robles, Rockelle; Nistor, Gabriel; Keirstead, Hans S

    2011-01-01

    Motor neuron loss is characteristic of many neurodegenerative disorders and results in rapid loss of muscle control, paralysis, and eventual death in severe cases. In order to investigate the neurotrophic effects of a motor neuron lineage graft, we transplanted human embryonic stem cell-derived motor neuron progenitors (hMNPs) and examined their histopathological effect in three animal models of motor neuron loss. Specifically, we transplanted hMNPs into rodent models of SMA (Δ7SMN), ALS (SOD1 G93A), and spinal cord injury (SCI). The transplanted cells survived and differentiated in all models. In addition, we have also found that hMNPs secrete physiologically active growth factors in vivo, including NGF and NT-3, which significantly enhanced the number of spared endogenous neurons in all three animal models. The ability to maintain dying motor neurons by delivering motor neuron-specific neurotrophic support represents a powerful treatment strategy for diseases characterized by motor neuron loss.

  17. An introduction to modeling neuronal dynamics

    CERN Document Server

    Börgers, Christoph

    2017-01-01

    This book is intended as a text for a one-semester course on Mathematical and Computational Neuroscience for upper-level undergraduate and beginning graduate students of mathematics, the natural sciences, engineering, or computer science. An undergraduate introduction to differential equations is more than enough mathematical background. Only a slim, high school-level background in physics is assumed, and none in biology. Topics include models of individual nerve cells and their dynamics, models of networks of neurons coupled by synapses and gap junctions, origins and functions of population rhythms in neuronal networks, and models of synaptic plasticity. An extensive online collection of Matlab programs generating the figures accompanies the book. .

  18. Modelling of the enteric nervous network: 3. Adrenergic neuron.

    Science.gov (United States)

    Miftakhov, R N; Wingate, D L

    1994-11-01

    A mathematical model is developed to investigate the coupled electrochemical processes of nerve-pulse transmission via adrenergic synapse. Based on pharmacological and morphophysiological data, the model describes the dynamics of the propagation of the electric signal along the unmyelinated geometrically non-uniform axon of the neuron and the chemical mechanisms of the transformation of the electrical signal in the synaptic zone into the post-synaptic output. The combined nonlinear system of partial and ordinary differential equations has been obtained and solved numerically. The results of computer simulation of the function of the idealized adrenergic neuron quantitatively and qualitatively describe the dynamics of Ca2+ ion influx into the terminal, noradrenaline release from the free 'releasable' store, its diffusion into the synaptic cleft, binding with the adrenoceptors on the pre- and post-synaptic structures with the generation of the inhibitory post-synaptic potential, and utilization of noradrenaline by neuronal and non-neuronal capture mechanisms.

  19. An electromechanical model of neuronal dynamics using Hamilton's principle

    Science.gov (United States)

    Drapaca, Corina S.

    2015-01-01

    Damage of the brain may be caused by mechanical loads such as penetration, blunt force, shock loading from blast, and by chemical imbalances due to neurological diseases and aging that trigger not only neuronal degeneration but also changes in the mechanical properties of brain tissue. An understanding of the interconnected nature of the electro-chemo-mechanical processes that result in brain damage and ultimately loss of functionality is currently lacking. While modern mathematical models that focus on how to link brain mechanics to its biochemistry are essential in enhancing our understanding of brain science, the lack of experimental data required by these models as well as the complexity of the corresponding computations render these models hard to use in clinical applications. In this paper we propose a unified variational framework for the modeling of neuronal electromechanics. We introduce a constrained Lagrangian formulation that takes into account Newton's law of motion of a linear viscoelastic Kelvin–Voigt solid-state neuron as well as the classic Hodgkin–Huxley equations of the electronic neuron. The system of differential equations describing neuronal electromechanics is obtained by applying Hamilton's principle. Numerical simulations of possible damage dynamics in neurons will be presented. PMID:26236195

  20. An electromechanical model of neuronal dynamics using Hamilton's principle.

    Science.gov (United States)

    Drapaca, Corina S

    2015-01-01

    Damage of the brain may be caused by mechanical loads such as penetration, blunt force, shock loading from blast, and by chemical imbalances due to neurological diseases and aging that trigger not only neuronal degeneration but also changes in the mechanical properties of brain tissue. An understanding of the interconnected nature of the electro-chemo-mechanical processes that result in brain damage and ultimately loss of functionality is currently lacking. While modern mathematical models that focus on how to link brain mechanics to its biochemistry are essential in enhancing our understanding of brain science, the lack of experimental data required by these models as well as the complexity of the corresponding computations render these models hard to use in clinical applications. In this paper we propose a unified variational framework for the modeling of neuronal electromechanics. We introduce a constrained Lagrangian formulation that takes into account Newton's law of motion of a linear viscoelastic Kelvin-Voigt solid-state neuron as well as the classic Hodgkin-Huxley equations of the electronic neuron. The system of differential equations describing neuronal electromechanics is obtained by applying Hamilton's principle. Numerical simulations of possible damage dynamics in neurons will be presented.

  1. An Electromechanical Model of Neuronal Dynamics using Hamilton's Principle

    Directory of Open Access Journals (Sweden)

    Corina Stefania Drapaca

    2015-07-01

    Full Text Available Damage of the brain may be caused by mechanical loads such as penetration, blunt force, shock loading from blast, and by chemical imbalances due to neurological diseases and aging that trigger not only neuronal degeneration but also changes in the mechanical properties of brain tissue. An understanding of the interconnected nature of the electro-chemo-mechanical processes that result in brain damage and ultimately loss of functionality is currently lacking. While modern mathematical models that focus on how to link brain mechanics to its biochemistry are essential in enhancing our understanding of brain science, the lack of experimental data required by these models as well as the complexity of the corresponding computations render these models hard to use in clinical applications. In this paper we propose a unified variational framework for the modeling of neuronal electromechanics. We introduce a constrained Lagrangian formulation that takes into account Newton's law of motion of a linear viscoelastic Kelvin-Voigt solid-state neuron as well as the classic Hodgkin-Huxley equations of the electronic neuron. The system of differential equations describing neuronal electromechanics is obtained by applying Hamilton's principle. Numerical simulations of possible damage dynamics in neurons will be presented.

  2. Reliable neuronal systems: the importance of heterogeneity.

    Directory of Open Access Journals (Sweden)

    Johannes Lengler

    Full Text Available For every engineer it goes without saying: in order to build a reliable system we need components that consistently behave precisely as they should. It is also well known that neurons, the building blocks of brains, do not satisfy this constraint. Even neurons of the same type come with huge variances in their properties and these properties also vary over time. Synapses, the connections between neurons, are highly unreliable in forwarding signals. In this paper we argue that both these fact add variance to neuronal processes, and that this variance is not a handicap of neural systems, but that instead predictable and reliable functional behavior of neural systems depends crucially on this variability. In particular, we show that higher variance allows a recurrently connected neural population to react more sensitively to incoming signals, and processes them faster and more energy efficient. This, for example, challenges the general assumption that the intrinsic variability of neurons in the brain is a defect that has to be overcome by synaptic plasticity in the process of learning.

  3. Human mirror neuron system and its plasticity

    Institute of Scientific and Technical Information of China (English)

    Wei Chen; Tifei Yuan; Yin Wang; Jun Ding

    2008-01-01

    The mirror neuron system (MNS) was first discovered in non-human primates; these neurons fire when a monkey performs an action or observes another monkey (or even some people) performing that same action. Recent findings have suggested that neural rehabilitation might be achieved through the activation of the MNS in patients after stroke. We propose two major mechanisms (one involving adult neurogenesis and another involving brain-derived neurotrophic factor) that may underlie the activation, modulation and expe-rience-dependent plasticity in the MNS, for further study on promoting central nerve functional reconstruc-tion and rehabilitation of patients with central nervous system injury.

  4. Digital hardware implementation of a stochastic two-dimensional neuron model.

    Science.gov (United States)

    Grassia, F; Kohno, T; Levi, T

    2017-02-22

    This study explores the feasibility of stochastic neuron simulation in digital systems (FPGA), which realizes an implementation of a two-dimensional neuron model. The stochasticity is added by a source of current noise in the silicon neuron using an Ornstein-Uhlenbeck process. This approach uses digital computation to emulate individual neuron behavior using fixed point arithmetic operation. The neuron model's computations are performed in arithmetic pipelines. It was designed in VHDL language and simulated prior to mapping in the FPGA. The experimental results confirmed the validity of the developed stochastic FPGA implementation, which makes the implementation of the silicon neuron more biologically plausible for future hybrid experiments.

  5. The Mirror Neuron System: A Fresh View

    Science.gov (United States)

    Casile, Antonino; Caggiano, Vittorio; Ferrari, Pier Francesco

    2013-01-01

    Mirror neurons are a class of visuomotor neurons in the monkey premotor and parietal cortices that discharge during the execution and observation of goal-directed motor acts. They are deemed to be at the basis of primates’ social abilities. In this review, the authors provide a fresh view about two still open questions about mirror neurons. The first question is their possible functional role. By reviewing recent neurophysiological data, the authors suggest that mirror neurons might represent a flexible system that encodes observed actions in terms of several behaviorally relevant features. The second question concerns the possible developmental mechanisms responsible for their initial emergence. To provide a possible answer to question, the authors review two different aspects of sensorimotor development: facial and hand movements, respectively. The authors suggest that possibly two different “mirror” systems might underlie the development of action understanding and imitative abilities in the two cases. More specifically, a possibly prewired system already present at birth but shaped by the social environment might underlie the early development of facial imitative abilities. On the contrary, an experience-dependent system might subserve perception-action couplings in the case of hand movements. The development of this latter system might be critically dependent on the observation of own movements. PMID:21467305

  6. Huperzine A provides neuroprotection against several cell death inducers using in vitro model systems of motor neuron cell death.

    Science.gov (United States)

    Hemendinger, Richelle A; Armstrong, Edward J; Persinski, Rafal; Todd, Julianne; Mougeot, Jean-Luc; Volvovitz, Franklin; Rosenfeld, Jeffrey

    2008-01-01

    Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease resulting from the progressive loss of motor neurons in the spinal cord and brain. To date, clinically effective neuroprotective agents have not been available. The current study demonstrates for the first time that huperzine A, a potential neuroprotective agent, has the ability to protect a motor neuron-like cell line and motor neurons in spinal cord organotypic cultures from toxin-induced cell death. The neuroblastoma-spinal motor neuron fusion cell line, NSC34 and rat spinal cord organotypic cultures (OTC) were exposed to cell death inducers for 24 h or 14 d, respectively, with and without pre-treatment with huperzine A. The inducers used here include: staurosporine, thapsigargin, hydrogen peroxide (H2O2), carbonyl cyanide m-chlorophenyl hydrazone (CCCP) and L-(-)-threo-3-hydroxyaspartic acid (THA). These agents were selected as they induce apoptosis/necrosis via mechanisms implicated in patients with generalized motor neuron disease. Cell death was determined in NSC34 cells by metabolic activity, caspase activity/expression and by nuclear morphology and in the OTCs, using immunohistochemistry and Western blot analysis. Nuclear staining of NSC34 cells revealed cell death induced by staurosporine, thapsigargin, H2O2 and CCCP. This induction was significantly reduced with 2 h pre-treatment with 10 microM huperzine A (maximum, 35% rescue; p 0.05) following exposure to staurosporine, thapsigargin and H2O2 but not with CCCP. These data were supported by the metabolic assays and caspase activity. In addition, pre-treatment with huperzine A dramatically improved motor neuron survival, based on choline acetyltransferase (ChAT) expression analysis in OTCs following exposure to THA, and compared to THA-treated control cultures. These studies are currently being extended to include other inducers and with additional compounds as potential drug therapies that could be used in combination for the treatment of

  7. Towards reproducible descriptions of neuronal network models.

    Directory of Open Access Journals (Sweden)

    Eilen Nordlie

    2009-08-01

    Full Text Available Progress in science depends on the effective exchange of ideas among scientists. New ideas can be assessed and criticized in a meaningful manner only if they are formulated precisely. This applies to simulation studies as well as to experiments and theories. But after more than 50 years of neuronal network simulations, we still lack a clear and common understanding of the role of computational models in neuroscience as well as established practices for describing network models in publications. This hinders the critical evaluation of network models as well as their re-use. We analyze here 14 research papers proposing neuronal network models of different complexity and find widely varying approaches to model descriptions, with regard to both the means of description and the ordering and placement of material. We further observe great variation in the graphical representation of networks and the notation used in equations. Based on our observations, we propose a good model description practice, composed of guidelines for the organization of publications, a checklist for model descriptions, templates for tables presenting model structure, and guidelines for diagrams of networks. The main purpose of this good practice is to trigger a debate about the communication of neuronal network models in a manner comprehensible to humans, as opposed to machine-readable model description languages. We believe that the good model description practice proposed here, together with a number of other recent initiatives on data-, model-, and software-sharing, may lead to a deeper and more fruitful exchange of ideas among computational neuroscientists in years to come. We further hope that work on standardized ways of describing--and thinking about--complex neuronal networks will lead the scientific community to a clearer understanding of high-level concepts in network dynamics, and will thus lead to deeper insights into the function of the brain.

  8. The mirror neuron system : New frontiers

    NARCIS (Netherlands)

    Keysers, Christian; Fadiga, Luciano

    2008-01-01

    Since the discovery of mirror neurons, much effort has been invested into Studying their location and properties in the human brain. Here we review these original findings and introduce the Main topics of this special issue of Social Neuroscience. What does the mirror system code? How is the mirror

  9. Laser Acupuncture at HT7 Acupoint Improves Cognitive Deficit, Neuronal Loss, Oxidative Stress, and Functions of Cholinergic and Dopaminergic Systems in Animal Model of Parkinson's Disease.

    Science.gov (United States)

    Wattanathorn, Jintanaporn; Sutalangka, Chatchada

    2014-01-01

    To date, the therapeutic strategy against cognitive impairment in Parkinson's disease (PD) is still not in satisfaction level and requires novel effective intervention. Based the oxidative stress reduction and cognitive enhancement induced by laser acupuncture at HT7, the beneficial effect of laser acupuncture at HT7 against cognitive impairment in PD has been focused. In this study, we aimed to determine the effect of laser acupuncture at HT7 on memory impairment, oxidative stress status, and the functions of both cholinergic and dopaminergic systems in hippocampus of animal model of PD. Male Wistar rats, weighing 180-220 g, were induced unilateral lesion at right substantianigra by 6-OHDA and were treated with laser acupuncture continuously at a period of 14 days. The results showed that laser acupuncture at HT7 enhanced memory and neuron density in CA3 and dentate gyrus. The decreased AChE, MAO-B, and MDA together with increased GSH-Px in hippocampus of a 6-OHDA lesion rats were also observed. In conclusion, laser acupuncture at HT7 can improve neuron degeneration and memory impairment in animal model of PD partly via the decreased oxidative stress and the improved cholinergic and dopaminergic functions. More researches concerning effect of treatment duration are still required.

  10. Avalanches in a stochastic model of spiking neurons.

    Directory of Open Access Journals (Sweden)

    Marc Benayoun

    Full Text Available Neuronal avalanches are a form of spontaneous activity widely observed in cortical slices and other types of nervous tissue, both in vivo and in vitro. They are characterized by irregular, isolated population bursts when many neurons fire together, where the number of spikes per burst obeys a power law distribution. We simulate, using the Gillespie algorithm, a model of neuronal avalanches based on stochastic single neurons. The network consists of excitatory and inhibitory neurons, first with all-to-all connectivity and later with random sparse connectivity. Analyzing our model using the system size expansion, we show that the model obeys the standard Wilson-Cowan equations for large network sizes ( neurons. When excitation and inhibition are closely balanced, networks of thousands of neurons exhibit irregular synchronous activity, including the characteristic power law distribution of avalanche size. We show that these avalanches are due to the balanced network having weakly stable functionally feedforward dynamics, which amplifies some small fluctuations into the large population bursts. Balanced networks are thought to underlie a variety of observed network behaviours and have useful computational properties, such as responding quickly to changes in input. Thus, the appearance of avalanches in such functionally feedforward networks indicates that avalanches may be a simple consequence of a widely present network structure, when neuron dynamics are noisy. An important implication is that a network need not be "critical" for the production of avalanches, so experimentally observed power laws in burst size may be a signature of noisy functionally feedforward structure rather than of, for example, self-organized criticality.

  11. Avalanches in a stochastic model of spiking neurons.

    Science.gov (United States)

    Benayoun, Marc; Cowan, Jack D; van Drongelen, Wim; Wallace, Edward

    2010-07-08

    Neuronal avalanches are a form of spontaneous activity widely observed in cortical slices and other types of nervous tissue, both in vivo and in vitro. They are characterized by irregular, isolated population bursts when many neurons fire together, where the number of spikes per burst obeys a power law distribution. We simulate, using the Gillespie algorithm, a model of neuronal avalanches based on stochastic single neurons. The network consists of excitatory and inhibitory neurons, first with all-to-all connectivity and later with random sparse connectivity. Analyzing our model using the system size expansion, we show that the model obeys the standard Wilson-Cowan equations for large network sizes ( neurons). When excitation and inhibition are closely balanced, networks of thousands of neurons exhibit irregular synchronous activity, including the characteristic power law distribution of avalanche size. We show that these avalanches are due to the balanced network having weakly stable functionally feedforward dynamics, which amplifies some small fluctuations into the large population bursts. Balanced networks are thought to underlie a variety of observed network behaviours and have useful computational properties, such as responding quickly to changes in input. Thus, the appearance of avalanches in such functionally feedforward networks indicates that avalanches may be a simple consequence of a widely present network structure, when neuron dynamics are noisy. An important implication is that a network need not be "critical" for the production of avalanches, so experimentally observed power laws in burst size may be a signature of noisy functionally feedforward structure rather than of, for example, self-organized criticality.

  12. A Radio Communication System for Neuronal Signals

    Institute of Scientific and Technical Information of China (English)

    Wang Min; Yang Maoquan; Wang Xiaojun; Guang Kui; Zhang Xiao

    2012-01-01

    To collect neuronal activity data from awake, freely behaving animals, we developed miniature telemetry recording system. The integrated system consists of four major components: l) Microelectrodes and micro-driver assembly, 2) analog front end (AFE), 3) programmable system on chip (PSoC), and 4) ra- dio transceiver and the LabVIEW were used as a platform for the graphic user interface. The result showed the system was able to record and analyze neuronal recordings in freely moving animals and lasted continuously for a time period of a week or more. This is very useful for the study of the interdisciplinary research of neu- roscience and information engineering techniques. The circuits and architecture of the devices can be adapted for neurobiology and research with other small animals.

  13. Neuronal integrative analysis of the "Dumbbell" model for passive neurons.

    Science.gov (United States)

    Krzyzanski, Wojciech; Bell, Jonathan; Poznanski, Roman R

    2002-12-01

    We analyze the so called "Dumbbell" model of Jackson (J. Neurophysiol. 69 (1993) pp. 464) for a single neuron consisting of a patch-clamped cell body attached to dendritic cable of finite length terminating in an oblique derivative ("natural termination") boundary condition representing a dendritic swelling or a natural ending sealed by a continuous surface of the cell membrane. The model is solved analytically via the Green's function method. Large and small time asymptotic behavior of the membrane potential is developed when there is a somatic voltage-clamp imposed. We discuss the difference in the voltage distribution if a sealed-end (Neumann) termination is used instead of the natural termination boundary condition. If the access resistance is large the differences between the potentials corresponding to the two boundary conditions are small at the soma, but can vary significantly near the dendritic termination. This discrepancy is amplified at the soma if there is a synaptic stimulus introduced between the soma and dendritic tip.

  14. Model reduction of strong-weak neurons

    OpenAIRE

    Steven James Cox; Bosen eDu; Danny eSorensen

    2014-01-01

    We consider neurons with large dendritic trees that are weakly excitable in the sense that back propagating action potentials are severly attenuated as they travel from the small, strongly excitable, spike initiation zone. In previous work we have shown that the computational size of weakly excitable cell models may be reduced by two or more orders of magnitude, and that the size of strongly excitable models may be reduced by at least one order of magnitude, without sacrificing the spatio–tem...

  15. Model reduction of strong-weak neurons.

    Science.gov (United States)

    Du, Bosen; Sorensen, Danny; Cox, Steven J

    2014-01-01

    We consider neurons with large dendritic trees that are weakly excitable in the sense that back propagating action potentials are severly attenuated as they travel from the small, strongly excitable, spike initiation zone. In previous work we have shown that the computational size of weakly excitable cell models may be reduced by two or more orders of magnitude, and that the size of strongly excitable models may be reduced by at least one order of magnitude, without sacrificing the spatio-temporal nature of its inputs (in the sense we reproduce the cell's precise mapping of inputs to outputs). We combine the best of these two strategies via a predictor-corrector decomposition scheme and achieve a drastically reduced highly accurate model of a caricature of the neuron responsible for collision detection in the locust.

  16. Edge detection based on Hodgkin-Huxley neuron model simulation.

    Science.gov (United States)

    Yedjour, Hayat; Meftah, Boudjelal; Lézoray, Olivier; Benyettou, Abdelkader

    2017-04-03

    In this paper, we propose a spiking neural network model for edge detection in images. The proposed model is biologically inspired by the mechanisms employed by natural vision systems, more specifically by the biologically fulfilled function of simple cells of the human primary visual cortex that are selective for orientation. Several aspects are studied in this model according to three characteristics: feedforward spiking neural structure; conductance-based model of the Hodgkin-Huxley neuron and Gabor receptive fields structure. A visualized map is generated using the firing rate of neurons representing the orientation map of the visual cortex area. We have simulated the proposed model on different images. Successful computer simulation results are obtained. For comparison, we have chosen five methods for edge detection. We finally evaluate and compare the performances of our model toward contour detection using a public dataset of natural images with associated contour ground truths. Experimental results show the ability and high performance of the proposed network model.

  17. Identification of determinism in noisy neuronal systems.

    Science.gov (United States)

    Slutzky, Marc W; Cvitanovic, Predrag; Mogul, David J

    2002-08-30

    Most neuronal ensembles are nonlinear excitable systems. Thus it is becoming common to apply principles derived from nonlinear dynamics to characterize neuronal systems. One important characterization is whether such systems contain deterministic behavior or are purely stochastic. Unfortunately, many methods used to make this distinction do not perform well when both determinism and high-amplitude noise are present which is often the case in physiological systems. Therefore, we propose two novel techniques for identifying determinism in experimental systems. The first, called short-time expansion analysis, examines the expansion rate of small groups of points in state space. The second, called state point forcing, derives from the technique of chaos control. The system state is forced onto a fixed point, and the subsequent behavior is analyzed. This technique can be used to verify the presence of fixed points (or unstable periodic orbits) and to assess stationarity. If these are present, it implies that the system contains determinism. We demonstrate the use and possible limitations of these two techniques in two systems: the Hénon map, a classic example of a chaotic system, and spontaneous epileptiform bursting in the rat hippocampal slice. Identifying the presence of determinism in a physiological system assists in the understanding of the system's dynamics and provides a mechanism for manipulating this behavior.

  18. Real-time Algorithms for Sparse Neuronal System Identification.

    Science.gov (United States)

    Sheikhattar, Alireza; Babadi, Behtash

    2016-08-01

    We consider the problem of sparse adaptive neuronal system identification, where the goal is to estimate the sparse time-varying neuronal model parameters in an online fashion from neural spiking observations. We develop two adaptive filters based on greedy estimation techniques and regularized log-likelihood maximization. We apply the proposed algorithms to simulated spiking data as well as experimentally recorded data from the ferret's primary auditory cortex during performance of auditory tasks. Our results reveal significant performance gains achieved by the proposed algorithms in terms of sparse identification and trackability, compared to existing algorithms.

  19. Model Reduction of Strong-Weak Neurons

    Directory of Open Access Journals (Sweden)

    Steven James Cox

    2014-12-01

    Full Text Available We consider neurons with large dendritic trees that are weakly excitable in the sense that back propagating action potentials are severly attenuated as they travelfrom the small, strongly excitable, spike initiation zone. In previous workwe have shown that the computational size of weakly excitable cell modelsmay be reduced by two or more orders of magnitude, and that the size of stronglyexcitable models may be reduced by at least one order of magnitude,without sacrificing thespatio-temporal nature of its inputs (in the sense we reproduce the cell's precise mapping of inputs to outputs. We combine the best of these twostrategies via a predictor--corrector decomposition scheme andachieve a drastically reduced highly accurate model of a caricature of the neuron responsible for collision detection in the locust.

  20. Reconstruction of neuronal input through modeling single-neuron dynamics and computations

    Energy Technology Data Exchange (ETDEWEB)

    Qin, Qing; Wang, Jiang; Yu, Haitao; Deng, Bin, E-mail: dengbin@tju.edu.cn; Chan, Wai-lok [School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China)

    2016-06-15

    Mathematical models provide a mathematical description of neuron activity, which can better understand and quantify neural computations and corresponding biophysical mechanisms evoked by stimulus. In this paper, based on the output spike train evoked by the acupuncture mechanical stimulus, we present two different levels of models to describe the input-output system to achieve the reconstruction of neuronal input. The reconstruction process is divided into two steps: First, considering the neuronal spiking event as a Gamma stochastic process. The scale parameter and the shape parameter of Gamma process are, respectively, defined as two spiking characteristics, which are estimated by a state-space method. Then, leaky integrate-and-fire (LIF) model is used to mimic the response system and the estimated spiking characteristics are transformed into two temporal input parameters of LIF model, through two conversion formulas. We test this reconstruction method by three different groups of simulation data. All three groups of estimates reconstruct input parameters with fairly high accuracy. We then use this reconstruction method to estimate the non-measurable acupuncture input parameters. Results show that under three different frequencies of acupuncture stimulus conditions, estimated input parameters have an obvious difference. The higher the frequency of the acupuncture stimulus is, the higher the accuracy of reconstruction is.

  1. Reconstruction of neuronal input through modeling single-neuron dynamics and computations

    Science.gov (United States)

    Qin, Qing; Wang, Jiang; Yu, Haitao; Deng, Bin; Chan, Wai-lok

    2016-06-01

    Mathematical models provide a mathematical description of neuron activity, which can better understand and quantify neural computations and corresponding biophysical mechanisms evoked by stimulus. In this paper, based on the output spike train evoked by the acupuncture mechanical stimulus, we present two different levels of models to describe the input-output system to achieve the reconstruction of neuronal input. The reconstruction process is divided into two steps: First, considering the neuronal spiking event as a Gamma stochastic process. The scale parameter and the shape parameter of Gamma process are, respectively, defined as two spiking characteristics, which are estimated by a state-space method. Then, leaky integrate-and-fire (LIF) model is used to mimic the response system and the estimated spiking characteristics are transformed into two temporal input parameters of LIF model, through two conversion formulas. We test this reconstruction method by three different groups of simulation data. All three groups of estimates reconstruct input parameters with fairly high accuracy. We then use this reconstruction method to estimate the non-measurable acupuncture input parameters. Results show that under three different frequencies of acupuncture stimulus conditions, estimated input parameters have an obvious difference. The higher the frequency of the acupuncture stimulus is, the higher the accuracy of reconstruction is.

  2. Computational modeling of optogenetic neuronal excitation under complex illumination conditions using a Matlab-Neuron interface (Conference Presentation)

    Science.gov (United States)

    Yona, Guy; Weissler, Yonatan; Meitav, Nizan; Guzi, Eliran; Rifold, Dafna D.; Kahn, Itamar; Shoham, Shy

    2016-03-01

    Optogenetics has in recent years become a central tool in neuroscience research. Creating a realistic model of optogenetic neuronal excitation is of crucial importance for controlling the activation levels of various neuronal populations in different depths, predicting experimental results and designing the optical systems. However, current approaches to modeling light propagation through rodents' brain tissue suffer from major shortcomings and comprehensive modeling of local illumination levels together with other important factors governing excitation (i.e., cellular morphology, channel dynamics and expression), are still lacking. To address this challenge we introduce a new simulation tool for optogenetic neuronal excitation under complex and realistic illumination conditions that implements a detailed physical model for light scattering (in MATLAB) together with neuron morphology and channelrhodopsin-2 model (in NEURON). These two disparate simulation environments were interconnected using a newly developed generic interface termed 'NeuroLab'. Applying this method, we show that in a layer-V cortical neuron, the relative contribution of the apical dendrites to neuronal excitation is considerably greater than that of the soma or basal dendrites, when illuminated from the surface.

  3. Biophysically realistic minimal model of dopamine neuron

    Science.gov (United States)

    Oprisan, Sorinel

    2008-03-01

    We proposed and studied a new biophysically relevant computational model of dopaminergic neurons. Midbrain dopamine neurons are involved in motivation and the control of movement, and have been implicated in various pathologies such as Parkinson's disease, schizophrenia, and drug abuse. The model we developed is a single-compartment Hodgkin-Huxley (HH)-type parallel conductance membrane model. The model captures the essential mechanisms underlying the slow oscillatory potentials and plateau potential oscillations. The main currents involved are: 1) a voltage-dependent fast calcium current, 2) a small conductance potassium current that is modulated by the cytosolic concentration of calcium, and 3) a slow voltage-activated potassium current. We developed multidimensional bifurcation diagrams and extracted the effective domains of sustained oscillations. The model includes a calcium balance due to the fundamental importance of calcium influx as proved by simultaneous electrophysiological and calcium imaging procedure. Although there are significant evidences to suggest a partially electrogenic calcium pump, all previous models considered only elecrtogenic pumps. We investigated the effect of the electrogenic calcium pump on the bifurcation diagram of the model and compared our findings against the experimental results.

  4. Qualitative-Modeling-Based Silicon Neurons and Their Networks

    Science.gov (United States)

    Kohno, Takashi; Sekikawa, Munehisa; Li, Jing; Nanami, Takuya; Aihara, Kazuyuki

    2016-01-01

    The ionic conductance models of neuronal cells can finely reproduce a wide variety of complex neuronal activities. However, the complexity of these models has prompted the development of qualitative neuron models. They are described by differential equations with a reduced number of variables and their low-dimensional polynomials, which retain the core mathematical structures. Such simple models form the foundation of a bottom-up approach in computational and theoretical neuroscience. We proposed a qualitative-modeling-based approach for designing silicon neuron circuits, in which the mathematical structures in the polynomial-based qualitative models are reproduced by differential equations with silicon-native expressions. This approach can realize low-power-consuming circuits that can be configured to realize various classes of neuronal cells. In this article, our qualitative-modeling-based silicon neuron circuits for analog and digital implementations are quickly reviewed. One of our CMOS analog silicon neuron circuits can realize a variety of neuronal activities with a power consumption less than 72 nW. The square-wave bursting mode of this circuit is explained. Another circuit can realize Class I and II neuronal activities with about 3 nW. Our digital silicon neuron circuit can also realize these classes. An auto-associative memory realized on an all-to-all connected network of these silicon neurons is also reviewed, in which the neuron class plays important roles in its performance. PMID:27378842

  5. Human Motor Neuron Progenitor Transplantation Leads to Endogenous Neuronal Sparing in 3 Models of Motor Neuron Loss

    Directory of Open Access Journals (Sweden)

    Tanya J. Wyatt

    2011-01-01

    Full Text Available Motor neuron loss is characteristic of many neurodegenerative disorders and results in rapid loss of muscle control, paralysis, and eventual death in severe cases. In order to investigate the neurotrophic effects of a motor neuron lineage graft, we transplanted human embryonic stem cell-derived motor neuron progenitors (hMNPs and examined their histopathological effect in three animal models of motor neuron loss. Specifically, we transplanted hMNPs into rodent models of SMA (Δ7SMN, ALS (SOD1 G93A, and spinal cord injury (SCI. The transplanted cells survived and differentiated in all models. In addition, we have also found that hMNPs secrete physiologically active growth factors in vivo, including NGF and NT-3, which significantly enhanced the number of spared endogenous neurons in all three animal models. The ability to maintain dying motor neurons by delivering motor neuron-specific neurotrophic support represents a powerful treatment strategy for diseases characterized by motor neuron loss.

  6. Linear and Nonlinear Electrical Models of Neurons for Hopfield Neural Network

    Science.gov (United States)

    Sarwar, Farah; Iqbal, Shaukat; Hussain, Muhammad Waqar

    2016-11-01

    A novel electrical model of neuron is proposed in this presentation. The suggested neural network model has linear/nonlinear input-output characteristics. This new deterministic model has joint biological properties in excellent agreement with the earlier deterministic neuron model of Hopfield and Tank and to the stochastic neuron model of McCulloch and Pitts. It is an accurate portrayal of differential equation presented by Hopfield and Tank to mimic neurons. Operational amplifiers, resistances, capacitor, and diodes are used to design this system. The presented biological model of neurons remains to be advantageous for simulations. Impulse response is studied and conferred to certify the stability and strength of this innovative model. A simple illustration is mapped to demonstrate the exactness of the intended system. Precisely mapped illustration exhibits 100 % accurate results.

  7. Neuronal and brain morphological changes in animal models of schizophrenia.

    Science.gov (United States)

    Flores, Gonzalo; Morales-Medina, Julio César; Diaz, Alfonso

    2016-03-15

    Schizophrenia, a severe and debilitating disorder with a high social burden, affects 1% of the adult world population. Available therapies are unable to treat all the symptoms, and result in strong side effects. For this reason, numerous animal models have been generated to elucidate the pathophysiology of this disorder. All these models present neuronal remodeling and abnormalities in spine stability. It is well known that the complexity in dendritic arborization determines the number of receptive synaptic contacts. Also the loss of dendritic spines and arbor stability are strongly associated with schizophrenia. This review evaluates changes in spine density and dendritic arborization in animal models of schizophrenia. By understanding these changes, pharmacological treatments can be designed to target specific neural systems to attenuate neuronal remodeling and associated behavioral deficits.

  8. Chimera in a neuronal network model of the cat brain

    OpenAIRE

    Santos, M. S.; Szezech Jr., J. D.; Borges, F. S.; Iarosz, K. C.; Caldas, I. L.; Batista, A. M.; Viana, R. L.; Kurths, J.

    2016-01-01

    Neuronal systems have been modeled by complex networks in different description levels. Recently, it has been verified that networks can simultaneously exhibit one coherent and other incoherent domain, known as chimera states. In this work, we study the existence of chimera states in a network considering the connectivity matrix based on the cat cerebral cortex. The cerebral cortex of the cat can be separated in 65 cortical areas organised into the four cognitive regions: visual, auditory, so...

  9. Analysis of Chaotic Resonance in Izhikevich Neuron Model.

    Science.gov (United States)

    Nobukawa, Sou; Nishimura, Haruhiko; Yamanishi, Teruya; Liu, Jian-Qin

    2015-01-01

    In stochastic resonance (SR), the presence of noise helps a nonlinear system amplify a weak (sub-threshold) signal. Chaotic resonance (CR) is a phenomenon similar to SR but without stochastic noise, which has been observed in neural systems. However, no study to date has investigated and compared the characteristics and performance of the signal responses of a spiking neural system in some chaotic states in CR. In this paper, we focus on the Izhikevich neuron model, which can reproduce major spike patterns that have been experimentally observed. We examine and classify the chaotic characteristics of this model by using Lyapunov exponents with a saltation matrix and Poincaré section methods in order to address the measurement challenge posed by the state-dependent jump in the resetting process. We found the existence of two distinctive states, a chaotic state involving primarily turbulent movement and an intermittent chaotic state. In order to assess the signal responses of CR in these classified states, we introduced an extended Izhikevich neuron model by considering weak periodic signals, and defined the cycle histogram of neuron spikes as well as the corresponding mutual correlation and information. Through computer simulations, we confirmed that both chaotic states in CR can sensitively respond to weak signals. Moreover, we found that the intermittent chaotic state exhibited a prompter response than the chaotic state with primarily turbulent movement.

  10. Chaos and stability in a model of inhibitory neuronal network

    CERN Document Server

    Catsigeras, Eleonora

    2011-01-01

    We analyze the dynamics of a deterministic model of inhibitory neuronal networks proving that the discontinuities of the Poincare map produce a never empty chaotic set, while its continuity pieces produce stable orbits. We classify the systems in three types: the almost everywhere (a.e.) chaotic, the a.e. stable, and the combined systems. The a.e. stable are periodic and chaos appears as bifurcations. We prove that a.e. stable systems exhibit limit cycles, attracting a.e. the orbits.

  11. Mathematical modelling of the enteric nervous network. 1: Cholinergic neuron.

    Science.gov (United States)

    Miftakhov, R N; Wingate, D L

    1994-01-01

    A mathematical model is proposed to describe the coupled electrochemical mechanisms of nerve-pulse transmission via cholinergic synapse. Based on pharmacological and morphophysiological data, the model describes the dynamics of the propagation of the electric signal along the unmyelinated geometrically non-uniform axon of the neuron and the chemical mechanisms of the transformation of the electrical signal in the synaptic zone into the postsynaptic output. The combined nonlinear system of partial and ordinary differential equations has been obtained and solved numerically. The results of numerical simulation of the function of the cholinergic neuron quantitatively and qualitatively describe the dynamics of Ca2+ ions influx into the terminal, acetylcholine release from the vesicles, accumulation of its free fraction, diffusion into the synaptic cleft, and binding with the receptors on the postsynaptic structures with the generation of the fast excitatory postsynaptic potential. They are in good agreement with the observed experimental findings.

  12. Intrinsic regenerative mechanisms of central nervous system neurons.

    Science.gov (United States)

    Muramatsu, Rieko; Ueno, Masaki; Yamashita, Toshihide

    2009-10-01

    Injuries to the adult central nervous system (CNS), such as spinal cord injury and brain contusion, can cause permanent functional deficits if axonal connections are broken. Spontaneous functional recovery rarely occurs. It has been widely accepted that the extracellular environment of the CNS inhibits neuronal regeneration. However, it should be noted that another reason for injured neurons failing to regenerate is their weak intrinsic ability to do so. The regeneration of injured neurons is a process involving many intracellular phenomena, including cytoskeletal changes, gene and protein expression, and changes in the responsiveness to extracellular cues. The capacity of injured neurons to regenerate is modulated to some extent by changes in the expression of intracellular signaling molecules such as glycogen synthase kinase-3beta and cyclic adenosine 3',5'-monophosphate. Knowledge of these effects has guided the development of animal models for regenerative therapies of CNS injury. Enhancing the intrinsic regenerative machinery of injured axons in the adult CNS is a potentially powerful strategy for treating patients with a CNS injury.

  13. Functionalized anatomical models for EM-neuron Interaction modeling

    Science.gov (United States)

    Neufeld, Esra; Cassará, Antonino Mario; Montanaro, Hazael; Kuster, Niels; Kainz, Wolfgang

    2016-06-01

    The understanding of interactions between electromagnetic (EM) fields and nerves are crucial in contexts ranging from therapeutic neurostimulation to low frequency EM exposure safety. To properly consider the impact of in vivo induced field inhomogeneity on non-linear neuronal dynamics, coupled EM-neuronal dynamics modeling is required. For that purpose, novel functionalized computable human phantoms have been developed. Their implementation and the systematic verification of the integrated anisotropic quasi-static EM solver and neuronal dynamics modeling functionality, based on the method of manufactured solutions and numerical reference data, is described. Electric and magnetic stimulation of the ulnar and sciatic nerve were modeled to help understanding a range of controversial issues related to the magnitude and optimal determination of strength-duration (SD) time constants. The results indicate the importance of considering the stimulation-specific inhomogeneous field distributions (especially at tissue interfaces), realistic models of non-linear neuronal dynamics, very short pulses, and suitable SD extrapolation models. These results and the functionalized computable phantom will influence and support the development of safe and effective neuroprosthetic devices and novel electroceuticals. Furthermore they will assist the evaluation of existing low frequency exposure standards for the entire population under all exposure conditions.

  14. The Application of Big-Neuron Theory in Expert Systems

    Institute of Scientific and Technical Information of China (English)

    李涛

    2001-01-01

    With a new way of knowledge representation and acquirement, inference, and building an expert system based on big-neurons composed of different field expert knowledge presented, the fundamental theory and architecture of expert system based upon big-neuron theory has thus been built. It is unnecessary to organize a large number of production rules when using big-neurons to build an expert system. The facts and rules of an expert system have already been hidden in big-neurons. And also, it is unnecessary to do a great quantity of tree searching when using this method to do logic reasoning. Machine can do self-organizing and self-learning.

  15. A primal analysis system of brain neurons data.

    Science.gov (United States)

    Pu, Dong-Mei; Gao, Da-Qi; Yuan, Yu-Bo

    2014-01-01

    It is a very challenging work to classify the 86 billions of neurons in the human brain. The most important step is to get the features of these neurons. In this paper, we present a primal system to analyze and extract features from brain neurons. First, we make analysis on the original data of neurons in which one neuron contains six parameters: room type, X, Y, Z coordinate range, total number of leaf nodes, and fuzzy volume of neurons. Then, we extract three important geometry features including rooms type, number of leaf nodes, and fuzzy volume. As application, we employ the feature database to fit the basic procedure of neuron growth. The result shows that the proposed system is effective.

  16. Language comprehension warps the mirror neuron system.

    Science.gov (United States)

    Zarr, Noah; Ferguson, Ryan; Glenberg, Arthur M

    2013-01-01

    Is the mirror neuron system (MNS) used in language understanding? According to embodied accounts of language comprehension, understanding sentences describing actions makes use of neural mechanisms of action control, including the MNS. Consequently, repeatedly comprehending sentences describing similar actions should induce adaptation of the MNS thereby warping its use in other cognitive processes such as action recognition and prediction. To test this prediction, participants read blocks of multiple sentences where each sentence in the block described transfer of objects in a direction away or toward the reader. Following each block, adaptation was measured by having participants predict the end-point of videotaped actions. The adapting sentences disrupted prediction of actions in the same direction, but (a) only for videos of biological motion, and (b) only when the effector implied by the language (e.g., the hand) matched the videos. These findings are signatures of the MNS.

  17. A distance constrained synaptic plasticity model of C. elegans neuronal network

    Science.gov (United States)

    Badhwar, Rahul; Bagler, Ganesh

    2017-03-01

    Brain research has been driven by enquiry for principles of brain structure organization and its control mechanisms. The neuronal wiring map of C. elegans, the only complete connectome available till date, presents an incredible opportunity to learn basic governing principles that drive structure and function of its neuronal architecture. Despite its apparently simple nervous system, C. elegans is known to possess complex functions. The nervous system forms an important underlying framework which specifies phenotypic features associated to sensation, movement, conditioning and memory. In this study, with the help of graph theoretical models, we investigated the C. elegans neuronal network to identify network features that are critical for its control. The 'driver neurons' are associated with important biological functions such as reproduction, signalling processes and anatomical structural development. We created 1D and 2D network models of C. elegans neuronal system to probe the role of features that confer controllability and small world nature. The simple 1D ring model is critically poised for the number of feed forward motifs, neuronal clustering and characteristic path-length in response to synaptic rewiring, indicating optimal rewiring. Using empirically observed distance constraint in the neuronal network as a guiding principle, we created a distance constrained synaptic plasticity model that simultaneously explains small world nature, saturation of feed forward motifs as well as observed number of driver neurons. The distance constrained model suggests optimum long distance synaptic connections as a key feature specifying control of the network.

  18. From spiking neuron models to linear-nonlinear models.

    Directory of Open Access Journals (Sweden)

    Srdjan Ostojic

    Full Text Available Neurons transform time-varying inputs into action potentials emitted stochastically at a time dependent rate. The mapping from current input to output firing rate is often represented with the help of phenomenological models such as the linear-nonlinear (LN cascade, in which the output firing rate is estimated by applying to the input successively a linear temporal filter and a static non-linear transformation. These simplified models leave out the biophysical details of action potential generation. It is not a priori clear to which extent the input-output mapping of biophysically more realistic, spiking neuron models can be reduced to a simple linear-nonlinear cascade. Here we investigate this question for the leaky integrate-and-fire (LIF, exponential integrate-and-fire (EIF and conductance-based Wang-Buzsáki models in presence of background synaptic activity. We exploit available analytic results for these models to determine the corresponding linear filter and static non-linearity in a parameter-free form. We show that the obtained functions are identical to the linear filter and static non-linearity determined using standard reverse correlation analysis. We then quantitatively compare the output of the corresponding linear-nonlinear cascade with numerical simulations of spiking neurons, systematically varying the parameters of input signal and background noise. We find that the LN cascade provides accurate estimates of the firing rates of spiking neurons in most of parameter space. For the EIF and Wang-Buzsáki models, we show that the LN cascade can be reduced to a firing rate model, the timescale of which we determine analytically. Finally we introduce an adaptive timescale rate model in which the timescale of the linear filter depends on the instantaneous firing rate. This model leads to highly accurate estimates of instantaneous firing rates.

  19. Modelling small-patterned neuronal networks coupled to microelectrode arrays

    Science.gov (United States)

    Massobrio, Paolo; Martinoia, Sergio

    2008-09-01

    Cultured neurons coupled to planar substrates which exhibit 'well-defined' two-dimensional network architectures can provide valuable insights into cell-to-cell communication, network dynamics versus topology, and basic mechanisms of synaptic plasticity and learning. In the literature several approaches were presented to drive neuronal growth, such as surface modification by silane chemistry, photolithographic techniques, microcontact printing, microfluidic channel flow patterning, microdrop patterning, etc. This work presents a computational model fit for reproducing and explaining the dynamics exhibited by small-patterned neuronal networks coupled to microelectrode arrays (MEAs). The model is based on the concept of meta-neuron, i.e., a small spatially confined number of actual neurons which perform single macroscopic functions. Each meta-neuron is characterized by a detailed morphology, and the membrane channels are modelled by simple Hodgkin-Huxley and passive kinetics. The two main findings that emerge from the simulations can be summarized as follows: (i) the increasing complexity of meta-neuron morphology reflects the variations of the network dynamics as a function of network development; (ii) the dynamics displayed by the patterned neuronal networks considered can be explained by hypothesizing the presence of several short- and a few long-term distance interactions among small assemblies of neurons (i.e., meta-neurons).

  20. Types of neurons in the enteric nervous system.

    Science.gov (United States)

    Furness, J B

    2000-07-01

    This paper, written for the symposium in honour of more than 40 years' contribution to autonomic research by Professor Geoffrey Burnstock, highlights the progress made in understanding the organisation of the enteric nervous system over this time. Forty years ago, the prevailing view was that the neurons within the gut wall were post-ganglionic neurons of parasympathetic pathways. This view was replaced as evidence accrued that the neurons are part of the enteric nervous system and are involved in reflex and integrative activities that can occur even in the absence of neuronal influence from extrinsic sources. Work in Burnstock's laboratory led to the discovery of intrinsic inhibitory neurons with then novel pharmacology of transmission, and precipitated investigation of neuron types in the enteric nervous system. All the types of neurons in the enteric nervous system of the small intestine of the guinea-pig have now been identified in terms of their morphologies, projections, primary neurotransmitters and physiological identification. In this region there are 14 functionally defined neuron types, each with a characteristic combination of morphological, neurochemical and biophysical properties. The nerve circuits underlying effects on motility, blood flow and secretion that are mediated through the enteric nervous system are constructed from these neurons. The circuits for simple motility reflexes are now known, and progress has been made in analysing those involved in local control of blood flow and transmucosal fluid movement in the small intestine.

  1. Parameter estimation in neuronal stochastic differential equation models from intracellular recordings of membrane potentials in single neurons

    DEFF Research Database (Denmark)

    Ditlevsen, Susanne; Samson, Adeline

    2016-01-01

    evolution. One-dimensional models are the stochastic integrate-and-fire neuronal diffusion models. Biophysical neuronal models take into account the dynamics of ion channels or synaptic activity, leading to multidimensional diffusion models. Since only the membrane potential can be measured......Dynamics of the membrane potential in a single neuron can be studied by estimating biophysical parameters from intracellular recordings. Diffusion processes, given as continuous solutions to stochastic differential equations, are widely applied as models for the neuronal membrane potential...

  2. The Mirror Neuron System and Action Recognition

    Science.gov (United States)

    Buccino, Giovanni; Binkofski, Ferdinand; Riggio, Lucia

    2004-01-01

    Mirror neurons, first described in the rostral part of monkey ventral premotor cortex (area F5), discharge both when the animal performs a goal-directed hand action and when it observes another individual performing the same or a similar action. More recently, in the same area mirror neurons responding to the observation of mouth actions have been…

  3. The Mirror Neuron System and Action Recognition

    Science.gov (United States)

    Buccino, Giovanni; Binkofski, Ferdinand; Riggio, Lucia

    2004-01-01

    Mirror neurons, first described in the rostral part of monkey ventral premotor cortex (area F5), discharge both when the animal performs a goal-directed hand action and when it observes another individual performing the same or a similar action. More recently, in the same area mirror neurons responding to the observation of mouth actions have been…

  4. Chaos control and synchronization in a fractional neuron network system

    Energy Technology Data Exchange (ETDEWEB)

    Zhou Shangbo [Computer Department of Chongqing University, Chongqing 400044 (China); Li Hua [Department of Mathematics and Computer Science, University of Lethbridge, T1K 3M4 (Canada)], E-mail: hua.li@uleth.ca; Zhu Zhengzhou [Computer Department of Chongqing University, Chongqing 400044 (China)

    2008-05-15

    In this paper, an algorithm of numerical solution for fractional differential equations is presented. Chaos in a neuron network system is also illustrated. Moreover, chaos feedback control and synchronization systems are constructed. The study and experiment indicate that the chaos in fractional order neuron networks could be controlled and synchronized.

  5. Mimicking human neuronal pathways in silico: an emergent model on the effective connectivity.

    Science.gov (United States)

    Gürcan, Önder; Türker, Kemal S; Mano, Jean-Pierre; Bernon, Carole; Dikenelli, Oğuz; Glize, Pierre

    2014-04-01

    We present a novel computational model that detects temporal configurations of a given human neuronal pathway and constructs its artificial replication. This poses a great challenge since direct recordings from individual neurons are impossible in the human central nervous system and therefore the underlying neuronal pathway has to be considered as a black box. For tackling this challenge, we used a branch of complex systems modeling called artificial self-organization in which large sets of software entities interacting locally give rise to bottom-up collective behaviors. The result is an emergent model where each software entity represents an integrate-and-fire neuron. We then applied the model to the reflex responses of single motor units obtained from conscious human subjects. Experimental results show that the model recovers functionality of real human neuronal pathways by comparing it to appropriate surrogate data. What makes the model promising is the fact that, to the best of our knowledge, it is the first realistic model to self-wire an artificial neuronal network by efficiently combining neuroscience with artificial self-organization. Although there is no evidence yet of the model's connectivity mapping onto the human connectivity, we anticipate this model will help neuroscientists to learn much more about human neuronal networks, and could also be used for predicting hypotheses to lead future experiments.

  6. Realistic modeling of neurons and networks: towards brain simulation.

    Science.gov (United States)

    D'Angelo, Egidio; Solinas, Sergio; Garrido, Jesus; Casellato, Claudia; Pedrocchi, Alessandra; Mapelli, Jonathan; Gandolfi, Daniela; Prestori, Francesca

    2013-01-01

    Realistic modeling is a new advanced methodology for investigating brain functions. Realistic modeling is based on a detailed biophysical description of neurons and synapses, which can be integrated into microcircuits. The latter can, in turn, be further integrated to form large-scale brain networks and eventually to reconstruct complex brain systems. Here we provide a review of the realistic simulation strategy and use the cerebellar network as an example. This network has been carefully investigated at molecular and cellular level and has been the object of intense theoretical investigation. The cerebellum is thought to lie at the core of the forward controller operations of the brain and to implement timing and sensory prediction functions. The cerebellum is well described and provides a challenging field in which one of the most advanced realistic microcircuit models has been generated. We illustrate how these models can be elaborated and embedded into robotic control systems to gain insight into how the cellular properties of cerebellar neurons emerge in integrated behaviors. Realistic network modeling opens up new perspectives for the investigation of brain pathologies and for the neurorobotic field.

  7. Direct Neuronal Reprogramming for Disease Modeling Studies Using Patient-Derived Neurons: What Have We Learned?

    Directory of Open Access Journals (Sweden)

    Janelle Drouin-Ouellet

    2017-09-01

    Full Text Available Direct neuronal reprogramming, by which a neuron is formed via direct conversion from a somatic cell without going through a pluripotent intermediate stage, allows for the possibility of generating patient-derived neurons. A unique feature of these so-called induced neurons (iNs is the potential to maintain aging and epigenetic signatures of the donor, which is critical given that many diseases of the CNS are age related. Here, we review the published literature on the work that has been undertaken using iNs to model human brain disorders. Furthermore, as disease-modeling studies using this direct neuronal reprogramming approach are becoming more widely adopted, it is important to assess the criteria that are used to characterize the iNs, especially in relation to the extent to which they are mature adult neurons. In particular: i what constitutes an iN cell, ii which stages of conversion offer the earliest/optimal time to assess features that are specific to neurons and/or a disorder and iii whether generating subtype-specific iNs is critical to the disease-related features that iNs express. Finally, we discuss the range of potential biomedical applications that can be explored using patient-specific models of neurological disorders with iNs, and the challenges that will need to be overcome in order to realize these applications.

  8. Mathematical modeling of the neuron morphology using two dimensional images.

    Science.gov (United States)

    Rajković, Katarina; Marić, Dušica L; Milošević, Nebojša T; Jeremic, Sanja; Arsenijević, Valentina Arsić; Rajković, Nemanja

    2016-02-01

    In this study mathematical analyses such as the analysis of area and length, fractal analysis and modified Sholl analysis were applied on two dimensional (2D) images of neurons from adult human dentate nucleus (DN). Using mathematical analyses main morphological properties were obtained including the size of neuron and soma, the length of all dendrites, the density of dendritic arborization, the position of the maximum density and the irregularity of dendrites. Response surface methodology (RSM) was used for modeling the size of neurons and the length of all dendrites. However, the RSM model based on the second-order polynomial equation was only possible to apply to correlate changes in the size of the neuron with other properties of its morphology. Modeling data provided evidence that the size of DN neurons statistically depended on the size of the soma, the density of dendritic arborization and the irregularity of dendrites. The low value of mean relative percent deviation (MRPD) between the experimental data and the predicted neuron size obtained by RSM model showed that model was suitable for modeling the size of DN neurons. Therefore, RSM can be generally used for modeling neuron size from 2D images.

  9. Self-organization model on receptive field of neuron with asymmetric time window of synaptic modification

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    The spatial-temporal response properties of some simple neurons in visual pathway arise basically prior to birth. In the absence of visual experience, how do these neurons develop in visual system? Based on Wimbauer network with delay, a four-layer feed-forward network model is proposed, which is characterized by modifying the Hebb learning rule through introducing the asymmetric time window of synaptic modification found recently in neurobiology. The model can not only generate by self-organization more diversified spatial-temporal response characteristics of neuronal receptive field than earlier models but also provide some explanations for the possible mechanism underlying the development of receptive fields of contrast polarity sensitive neurons found in visual system of vertebrate. Thus the proposed model may be more widely applicable than Linsker model and Wimbauer model.

  10. Phase-flip bifurcation in a coupled Josephson junction neuron system

    Energy Technology Data Exchange (ETDEWEB)

    Segall, Kenneth, E-mail: ksegall@colgate.edu [Department of Physics and Astronomy, Colgate University, Hamilton, NY 13346 (United States); Guo, Siyang; Crotty, Patrick [Department of Physics and Astronomy, Colgate University, Hamilton, NY 13346 (United States); Schult, Dan [Department of Mathematics, Colgate University, Hamilton, NY 13346 (United States); Miller, Max [Department of Physics and Astronomy, Colgate University, Hamilton, NY 13346 (United States)

    2014-12-15

    Aiming to understand group behaviors and dynamics of neural networks, we have previously proposed the Josephson junction neuron (JJ neuron) as a fast analog model that mimics a biological neuron using superconducting Josephson junctions. In this study, we further analyze the dynamics of the JJ neuron numerically by coupling one JJ neuron to another. In this coupled system we observe a phase-flip bifurcation, where the neurons synchronize out-of-phase at weak coupling and in-phase at strong coupling. We verify this by simulation of the circuit equations and construct a bifurcation diagram for varying coupling strength using the phase response curve and spike phase difference map. The phase-flip bifurcation could be observed experimentally using standard digital superconducting circuitry.

  11. Optimizing neuronal differentiation from induced pluripotent stem cells to model ASD

    Directory of Open Access Journals (Sweden)

    Dae-Sung eKim

    2014-04-01

    Full Text Available Autism spectrum disorder (ASD is an early-onset neurodevelopmental disorder characterized by deficits in social communication, and restricted and repetitive patterns of behavior. Despite its high prevalence, discovery of pathophysiological mechanisms underlying ASD has lagged due to a lack of appropriate model systems. Recent advances in induced pluripotent stem cell (iPSC technology and neural differentiation techniques allow for detailed functional analyses of neurons generated from living individuals with ASD. Refinement of cortical neuron differentiation methods from iPSCs will enable mechanistic studies of specific neuronal subpopulations that may be preferentially impaired in ASD. In this review, we summarize recent accomplishments in differentiation of cortical neurons from human pluripotent stems cells and efforts to establish in vitro model systems to study ASD using personalized neurons.

  12. Parametric Anatomical Modeling: a method for modeling the anatomical layout of neurons and their projections.

    Science.gov (United States)

    Pyka, Martin; Klatt, Sebastian; Cheng, Sen

    2014-01-01

    Computational models of neural networks can be based on a variety of different parameters. These parameters include, for example, the 3d shape of neuron layers, the neurons' spatial projection patterns, spiking dynamics and neurotransmitter systems. While many well-developed approaches are available to model, for example, the spiking dynamics, there is a lack of approaches for modeling the anatomical layout of neurons and their projections. We present a new method, called Parametric Anatomical Modeling (PAM), to fill this gap. PAM can be used to derive network connectivities and conduction delays from anatomical data, such as the position and shape of the neuronal layers and the dendritic and axonal projection patterns. Within the PAM framework, several mapping techniques between layers can account for a large variety of connection properties between pre- and post-synaptic neuron layers. PAM is implemented as a Python tool and integrated in the 3d modeling software Blender. We demonstrate on a 3d model of the hippocampal formation how PAM can help reveal complex properties of the synaptic connectivity and conduction delays, properties that might be relevant to uncover the function of the hippocampus. Based on these analyses, two experimentally testable predictions arose: (i) the number of neurons and the spread of connections is heterogeneously distributed across the main anatomical axes, (ii) the distribution of connection lengths in CA3-CA1 differ qualitatively from those between DG-CA3 and CA3-CA3. Models created by PAM can also serve as an educational tool to visualize the 3d connectivity of brain regions. The low-dimensional, but yet biologically plausible, parameter space renders PAM suitable to analyse allometric and evolutionary factors in networks and to model the complexity of real networks with comparatively little effort.

  13. Flybrain neuron database: a comprehensive database system of the Drosophila brain neurons.

    Science.gov (United States)

    Shinomiya, Kazunori; Matsuda, Keiji; Oishi, Takao; Otsuna, Hideo; Ito, Kei

    2011-04-01

    The long history of neuroscience has accumulated information about numerous types of neurons in the brain of various organisms. Because such neurons have been reported in diverse publications without controlled format, it is not easy to keep track of all the known neurons in a particular nervous system. To address this issue we constructed an online database called Flybrain Neuron Database (Flybrain NDB), which serves as a platform to collect and provide information about all the types of neurons published so far in the brain of Drosophila melanogaster. Projection patterns of the identified neurons in diverse areas of the brain were recorded in a unified format, with text-based descriptions as well as images and movies wherever possible. In some cases projection sites and the distribution of the post- and presynaptic sites were determined with greater detail than described in the original publication. Information about the labeling patterns of various antibodies and expression driver strains to visualize identified neurons are provided as a separate sub-database. We also implemented a novel visualization tool with which users can interactively examine three-dimensional reconstruction of the confocal serial section images with desired viewing angles and cross sections. Comprehensive collection and versatile search function of the anatomical information reported in diverse publications make it possible to analyze possible connectivity between different brain regions. We analyzed the preferential connectivity among optic lobe layers and the plausible olfactory sensory map in the lateral horn to show the usefulness of such a database.

  14. A Phase-Locking Analysis of Neuronal Firing Rhythms with Transcranial Magneto-Acoustical Stimulation Based on the Hodgkin-Huxley Neuron Model.

    Science.gov (United States)

    Yuan, Yi; Pang, Na; Chen, Yudong; Wang, Yi; Li, Xiaoli

    2017-01-01

    Transcranial magneto-acoustical stimulation (TMAS) uses ultrasonic waves and a static magnetic field to generate electric current in nerve tissues for the purpose of modulating neuronal activities. It has the advantage of high spatial resolution and penetration depth. Neuronal firing rhythms carry and transmit nerve information in neural systems. In this study, we investigated the phase-locking characteristics of neuronal firing rhythms with TMAS based on the Hodgkin-Huxley neuron model. The simulation results indicate that the modulation frequency of ultrasound can affect the phase-locking behaviors. The results of this study may help us to explain the potential firing mechanism of TMAS.

  15. SIMPEL: Circuit model for photonic spike processing laser neurons

    CERN Document Server

    Shastri, Bhavin J; Tait, Alexander N; Wu, Ben; Prucnal, Paul R

    2014-01-01

    We propose an equivalent circuit model for photonic spike processing laser neurons with an embedded saturable absorber---a simulation model for photonic excitable lasers (SIMPEL). We show that by mapping the laser neuron rate equations into a circuit model, SPICE analysis can be used as an efficient and accurate engine for numerical calculations, capable of generalization to a variety of different laser neuron types found in literature. The development of this model parallels the Hodgkin--Huxley model of neuron biophysics, a circuit framework which brought efficiency, modularity, and generalizability to the study of neural dynamics. We employ the model to study various signal-processing effects such as excitability with excitatory and inhibitory pulses, binary all-or-nothing response, and bistable dynamics.

  16. Probing the dynamics of identified neurons with a data-driven modeling approach.

    Directory of Open Access Journals (Sweden)

    Thomas Nowotny

    Full Text Available In controlling animal behavior the nervous system has to perform within the operational limits set by the requirements of each specific behavior. The implications for the corresponding range of suitable network, single neuron, and ion channel properties have remained elusive. In this article we approach the question of how well-constrained properties of neuronal systems may be on the neuronal level. We used large data sets of the activity of isolated invertebrate identified cells and built an accurate conductance-based model for this cell type using customized automated parameter estimation techniques. By direct inspection of the data we found that the variability of the neurons is larger when they are isolated from the circuit than when in the intact system. Furthermore, the responses of the neurons to perturbations appear to be more consistent than their autonomous behavior under stationary conditions. In the developed model, the constraints on different parameters that enforce appropriate model dynamics vary widely from some very tightly controlled parameters to others that are almost arbitrary. The model also allows predictions for the effect of blocking selected ionic currents and to prove that the origin of irregular dynamics in the neuron model is proper chaoticity and that this chaoticity is typical in an appropriate sense. Our results indicate that data driven models are useful tools for the in-depth analysis of neuronal dynamics. The better consistency of responses to perturbations, in the real neurons as well as in the model, suggests a paradigm shift away from measuring autonomous dynamics alone towards protocols of controlled perturbations. Our predictions for the impact of channel blockers on the neuronal dynamics and the proof of chaoticity underscore the wide scope of our approach.

  17. [Mirror neuron system dysfunction in schizophrenia and its clinical implication].

    Science.gov (United States)

    Kato, Motoichiro; Kato, Yutaka

    2014-06-01

    Since the discovery of mirror neuron system, several neurophysiological and neuroimaging studies showed that the mirror neuron system might have a role in understanding other people's actions and intentions with automatic simulation of their actions. Moreover, some studies suggested that mirror neurons have a broader role in social cognition including understanding others' emotions and empathy. It has not been proved, however, whether the mirror neuron system is necessarily involved in empathy processes. In the domain of social cognition deficits, it is important to investigate the involvement of mirror neuron system dysfunction in psychosis such as schizophrenia. Using magnetoencephalography, we examined whether antipsychotic-free schizophrenia patients displayed mirror neuron system dysfunction during observation of biological motion (jaw movement). Compared with normal controls, the patients with schizophrenia had fewer components of both the waveform and equivalent current dipole, suggesting aberrant brain activity resulting from dysfunction of the right inferior parietal cortex. They also lacked the changes of alpha band and gamma band oscillation seen in normal controls, and had weaker phase locking factors and gamma-synchronization predominantly in right parietal cortex. This finding demonstrated that untreated patients with schizophrenia exhibited aberrant mirror neuron system function based on the right inferior parietal cortex, which is characterized by dysfunction of gamma-synchronization.

  18. Basal Forebrain Cholinergic System and Orexin Neurons: Effects on Attention

    Science.gov (United States)

    Villano, Ines; Messina, Antonietta; Valenzano, Anna; Moscatelli, Fiorenzo; Esposito, Teresa; Monda, Vincenzo; Esposito, Maria; Precenzano, Francesco; Carotenuto, Marco; Viggiano, Andrea; Chieffi, Sergio; Cibelli, Giuseppe; Monda, Marcellino; Messina, Giovanni

    2017-01-01

    The basal forebrain (BF) cholinergic system has an important role in attentive functions. The cholinergic system can be activated by different inputs, and in particular, by orexin neurons, whose cell bodies are located within the postero-lateral hypothalamus. Recently the orexin-producing neurons have been proved to promote arousal and attention through their projections to the BF. The aim of this review article is to summarize the evidence showing that the orexin system contributes to attentional processing by an increase in cortical acetylcholine release and in cortical neurons activity. PMID:28197081

  19. Multiscale modeling of brain dynamics: from single neurons and networks to mathematical tools.

    Science.gov (United States)

    Siettos, Constantinos; Starke, Jens

    2016-09-01

    The extreme complexity of the brain naturally requires mathematical modeling approaches on a large variety of scales; the spectrum ranges from single neuron dynamics over the behavior of groups of neurons to neuronal network activity. Thus, the connection between the microscopic scale (single neuron activity) to macroscopic behavior (emergent behavior of the collective dynamics) and vice versa is a key to understand the brain in its complexity. In this work, we attempt a review of a wide range of approaches, ranging from the modeling of single neuron dynamics to machine learning. The models include biophysical as well as data-driven phenomenological models. The discussed models include Hodgkin-Huxley, FitzHugh-Nagumo, coupled oscillators (Kuramoto oscillators, Rössler oscillators, and the Hindmarsh-Rose neuron), Integrate and Fire, networks of neurons, and neural field equations. In addition to the mathematical models, important mathematical methods in multiscale modeling and reconstruction of the causal connectivity are sketched. The methods include linear and nonlinear tools from statistics, data analysis, and time series analysis up to differential equations, dynamical systems, and bifurcation theory, including Granger causal connectivity analysis, phase synchronization connectivity analysis, principal component analysis (PCA), independent component analysis (ICA), and manifold learning algorithms such as ISOMAP, and diffusion maps and equation-free techniques. WIREs Syst Biol Med 2016, 8:438-458. doi: 10.1002/wsbm.1348 For further resources related to this article, please visit the WIREs website.

  20. Reorganization of neuronal circuits of the central olfactory system during postprandial sleep.

    Science.gov (United States)

    Yamaguchi, Masahiro; Manabe, Hiroyuki; Murata, Koshi; Mori, Kensaku

    2013-01-01

    Plastic changes in neuronal circuits often occur in association with specific behavioral states. In this review, we focus on an emerging view that neuronal circuits in the olfactory system are reorganized along the wake-sleep cycle. Olfaction is crucial to sustaining the animals' life, and odor-guided behaviors have to be newly acquired or updated to successfully cope with a changing odor world. It is therefore likely that neuronal circuits in the olfactory system are highly plastic and undergo repeated reorganization in daily life. A remarkably plastic feature of the olfactory system is that newly generated neurons are continually integrated into neuronal circuits of the olfactory bulb (OB) throughout life. New neurons in the OB undergo an extensive selection process, during which many are eliminated by apoptosis for the fine tuning of neuronal circuits. The life and death decision of new neurons occurs extensively during a short time window of sleep after food consumption (postprandial sleep), a typical daily olfactory behavior. We review recent studies that explain how olfactory information is transferred between the OB and the olfactory cortex (OC) along the course of the wake-sleep cycle. Olfactory sensory input is effectively transferred from the OB to the OC during waking, while synchronized top-down inputs from the OC to the OB are promoted during the slow-wave sleep. We discuss possible neuronal circuit mechanisms for the selection of new neurons in the OB, which involves the encoding of olfactory sensory inputs and memory trace formation during waking and internally generated activities in the OC and OB during subsequent sleep. The plastic changes in the OB and OC are well coordinated along the course of olfactory behavior during wakefulness and postbehavioral rest and sleep. We therefore propose that the olfactory system provides an excellent model in which to understand behavioral state-dependent plastic mechanisms of the neuronal circuits in the brain.

  1. Reorganization of neuronal circuits of the central olfactory system during postprandial sleep

    Directory of Open Access Journals (Sweden)

    Masahiro eYamaguchi

    2013-08-01

    Full Text Available Plastic changes in neuronal circuits often occur in association with specific behavioral states. In this review, we focus on an emerging view that neuronal circuits in the olfactory system are reorganized along the wake-sleep cycle. Olfaction is crucial to sustaining the animals’ life, and odor-guided behaviors have to be newly acquired or updated to successfully cope with a changing odor world. It is therefore likely that neuronal circuits in the olfactory system are highly plastic and undergo repeated reorganization in daily life. A remarkably plastic feature of the olfactory system is that newly generated neurons are continually integrated into neuronal circuits of the olfactory bulb (OB throughout life. New neurons in the OB undergo an extensive selection process, during which many are eliminated by apoptosis for the fine tuning of neuronal circuits. The life and death decision of new neurons occurs extensively during a short time window of sleep after food consumption (postprandial sleep, a typical daily olfactory behavior. We review recent studies that explain how olfactory information is transferred between the OB and the olfactory cortex (OC along the course of the wake-sleep cycle. Olfactory sensory input is effectively transferred from the OB to the OC during waking, while synchronized top-down inputs from the OC to the OB are promoted during the slow-wave sleep. We discuss possible neuronal circuit mechanisms for the selection of new neurons in the OB, which involves the encoding of olfactory sensory inputs and memory trace formation during waking and internally generated activities in the OC and OB during subsequent sleep. The plastic changes in the OB and OC are well coordinated along the course of olfactory behavior during wakefulness and postbehavioral rest and sleep. We therefore propose that the olfactory system provides an excellent model in which to understand behavioral state-dependent plastic mechanisms of the neuronal

  2. Modanifil activates the histaminergic system through the orexinergic neurons.

    Science.gov (United States)

    Ishizuka, Tomoko; Murotani, Tomotaka; Yamatodani, Atsushi

    2010-10-15

    Modafinil is a drug used to treat hypersomnolence of narcolepsy. We previously reported that modafinil increases hypothalamic histamine release in rats but did not increase locomotor activity in histamine-depleted mice, suggesting that modafinil-induced locomotor activity involves the histaminergic system. Modafinil is also thought to express its effect through the orexinergic neurons, and orexin increases hypothalamic histamine release. These findings led us to investigate whether modafinil activates the histaminergic system via the orexinergic system. In the present study, we performed in vivo microdialysis and c-Fos immunohistochemistry to investigate whether the orexinergic system mediates the activation of the histaminergic system by modafinil using orexin neuron-deficient mice. Two hours after the injection, modafinil (150 mg/kg) caused a significant increase of histamine release compared to the basal release in wild type mice. However, modafinil had no effect on the histamine release in orexin neuron-deficient mice. By immunohistochemical study, we found that there was no neuronal activation in the tuberomammillary nucleus where the cell bodies of the histaminergic neurons exclusively exist in orexin neuron-deficient mice. These findings indicate that modafinil-induced increment of histamine release requires intact orexinergic neurons.

  3. Small is beautiful: models of small neuronal networks.

    Science.gov (United States)

    Lamb, Damon G; Calabrese, Ronald L

    2012-08-01

    Modeling has contributed a great deal to our understanding of how individual neurons and neuronal networks function. In this review, we focus on models of the small neuronal networks of invertebrates, especially rhythmically active CPG networks. Models have elucidated many aspects of these networks, from identifying key interacting membrane properties to pointing out gaps in our understanding, for example missing neurons. Even the complex CPGs of vertebrates, such as those that underlie respiration, have been reduced to small network models to great effect. Modeling of these networks spans from simplified models, which are amenable to mathematical analyses, to very complicated biophysical models. Some researchers have now adopted a population approach, where they generate and analyze many related models that differ in a few to several judiciously chosen free parameters; often these parameters show variability across animals and thus justify the approach. Models of small neuronal networks will continue to expand and refine our understanding of how neuronal networks in all animals program motor output, process sensory information and learn.

  4. Dynamic Behavior of Artificial Hodgkin-Huxley Neuron Model Subject to Additive Noise.

    Science.gov (United States)

    Kang, Qi; Huang, BingYao; Zhou, MengChu

    2016-09-01

    Motivated by neuroscience discoveries during the last few years, many studies consider pulse-coupled neural networks with spike-timing as an essential component in information processing by the brain. There also exists some technical challenges while simulating the networks of artificial spiking neurons. The existing studies use a Hodgkin-Huxley (H-H) model to describe spiking dynamics and neuro-computational properties of each neuron. But they fail to address the effect of specific non-Gaussian noise on an artificial H-H neuron system. This paper aims to analyze how an artificial H-H neuron responds to add different types of noise using an electrical current and subunit noise model. The spiking and bursting behavior of this neuron is also investigated through numerical simulations. In addition, through statistic analysis, the intensity of different kinds of noise distributions is discussed to obtain their relationship with the mean firing rate, interspike intervals, and stochastic resonance.

  5. Multi-Scale Molecular Deconstruction of the Serotonin Neuron System.

    Science.gov (United States)

    Okaty, Benjamin W; Freret, Morgan E; Rood, Benjamin D; Brust, Rachael D; Hennessy, Morgan L; deBairos, Danielle; Kim, Jun Chul; Cook, Melloni N; Dymecki, Susan M

    2015-11-18

    Serotonergic (5HT) neurons modulate diverse behaviors and physiology and are implicated in distinct clinical disorders. Corresponding diversity in 5HT neuronal phenotypes is becoming apparent and is likely rooted in molecular differences, yet a comprehensive approach characterizing molecular variation across the 5HT system is lacking, as is concomitant linkage to cellular phenotypes. Here we combine intersectional fate mapping, neuron sorting, and genome-wide RNA-seq to deconstruct the mouse 5HT system at multiple levels of granularity-from anatomy, to genetic sublineages, to single neurons. Our unbiased analyses reveal principles underlying system organization, 5HT neuron subtypes, constellations of differentially expressed genes distinguishing subtypes, and predictions of subtype-specific functions. Using electrophysiology, subtype-specific neuron silencing, and conditional gene knockout, we show that these molecularly defined 5HT neuron subtypes are functionally distinct. Collectively, this resource classifies molecular diversity across the 5HT system and discovers sertonergic subtypes, markers, organizing principles, and subtype-specific functions with potential disease relevance.

  6. On learning time delays between the spikes from different input neurons in a biophysical model of a pyramidal neuron.

    Science.gov (United States)

    Koutsou, Achilleas; Bugmann, Guido; Christodoulou, Chris

    2015-10-01

    Biological systems are able to recognise temporal sequences of stimuli or compute in the temporal domain. In this paper we are exploring whether a biophysical model of a pyramidal neuron can detect and learn systematic time delays between the spikes from different input neurons. In particular, we investigate whether it is possible to reinforce pairs of synapses separated by a dendritic propagation time delay corresponding to the arrival time difference of two spikes from two different input neurons. We examine two subthreshold learning approaches where the first relies on the backpropagation of EPSPs (excitatory postsynaptic potentials) and the second on the backpropagation of a somatic action potential, whose production is supported by a learning-enabling background current. The first approach does not provide a learning signal that sufficiently differentiates between synapses at different locations, while in the second approach, somatic spikes do not provide a reliable signal distinguishing arrival time differences of the order of the dendritic propagation time. It appears that the firing of pyramidal neurons shows little sensitivity to heterosynaptic spike arrival time differences of several milliseconds. This neuron is therefore unlikely to be able to learn to detect such differences.

  7. Linking Memories across Time via Neuronal and Dendritic Overlaps in Model Neurons with Active Dendrites

    Directory of Open Access Journals (Sweden)

    George Kastellakis

    2016-11-01

    Full Text Available Memories are believed to be stored in distributed neuronal assemblies through activity-induced changes in synaptic and intrinsic properties. However, the specific mechanisms by which different memories become associated or linked remain a mystery. Here, we develop a simplified, biophysically inspired network model that incorporates multiple plasticity processes and explains linking of information at three different levels: (1 learning of a single associative memory, (2 rescuing of a weak memory when paired with a strong one, and (3 linking of multiple memories across time. By dissecting synaptic from intrinsic plasticity and neuron-wide from dendritically restricted protein capture, the model reveals a simple, unifying principle: linked memories share synaptic clusters within the dendrites of overlapping populations of neurons. The model generates numerous experimentally testable predictions regarding the cellular and sub-cellular properties of memory engrams as well as their spatiotemporal interactions.

  8. Spiking Neural P Systems with Neuron Division and Budding

    OpenAIRE

    Pan, Linqiang; Paun, Gheorghe; Pérez Jiménez, Mario de Jesús

    2009-01-01

    In order to enhance the e±ciency of spiking neural P systems, we introduce the features of neuron division and neuron budding, which are processes inspired by neural stem cell division. As expected (as it is the case for P systems with active membranes), in this way we get the possibility to solve computationally hard problems in polynomial time. We illustrate this possibility with SAT problem.

  9. A Neuron-Based Model of Sleep-Wake Cycles

    Science.gov (United States)

    Postnova, Svetlana; Peters, Achim; Braun, Hans

    2008-03-01

    In recent years it was discovered that a neuropeptide orexin/hypocretin plays a main role in sleep processes. This peptide is produced by the neurons in the lateral hypothalamus, which project to almost all brain areas. We present a computational model of sleep-wake cycles, which is based on the Hodgkin-Huxley type neurons and considers reciprocal glutaminergic projections between the lateral hypothalamus and the prefrontal cortex. Orexin is released as a neuromodulator and is required to keep the neurons firing, which corresponds to the wake state. When orexin is depleted the neurons are getting silent as observed in the sleep state. They can be reactivated by the circadian signal from the suprachiasmatic nucleus and/or external stimuli (alarm clock). Orexin projections to the thalamocortical neurons also can account for their transition from tonic firing activity during wakefulness to synchronized burst discharges during sleep.

  10. A Statistical Model for In Vivo Neuronal Dynamics.

    Directory of Open Access Journals (Sweden)

    Simone Carlo Surace

    Full Text Available Single neuron models have a long tradition in computational neuroscience. Detailed biophysical models such as the Hodgkin-Huxley model as well as simplified neuron models such as the class of integrate-and-fire models relate the input current to the membrane potential of the neuron. Those types of models have been extensively fitted to in vitro data where the input current is controlled. Those models are however of little use when it comes to characterize intracellular in vivo recordings since the input to the neuron is not known. Here we propose a novel single neuron model that characterizes the statistical properties of in vivo recordings. More specifically, we propose a stochastic process where the subthreshold membrane potential follows a Gaussian process and the spike emission intensity depends nonlinearly on the membrane potential as well as the spiking history. We first show that the model has a rich dynamical repertoire since it can capture arbitrary subthreshold autocovariance functions, firing-rate adaptations as well as arbitrary shapes of the action potential. We then show that this model can be efficiently fitted to data without overfitting. We finally show that this model can be used to characterize and therefore precisely compare various intracellular in vivo recordings from different animals and experimental conditions.

  11. Parameter estimation in neuronal stochastic differential equation models from intracellular recordings of membrane potentials in single neurons

    DEFF Research Database (Denmark)

    Ditlevsen, Susanne; Samson, Adeline

    2016-01-01

    Dynamics of the membrane potential in a single neuron can be studied by estimating biophysical parameters from intracellular recordings. Diffusion processes, given as continuous solutions to stochastic differential equations, are widely applied as models for the neuronal membrane potential...... evolution. One-dimensional models are the stochastic integrate-and-fire neuronal diffusion models. Biophysical neuronal models take into account the dynamics of ion channels or synaptic activity, leading to multidimensional diffusion models. Since only the membrane potential can be measured......, this complicates the statistical inference and parameter estimation from these partially observed detailed models. This paper reviews parameter estimation techniques from intracellular recordings in these diffusion models....

  12. Mapping Generative Models onto a Network of Digital Spiking Neurons.

    Science.gov (United States)

    Pedroni, Bruno U; Das, Srinjoy; Arthur, John V; Merolla, Paul A; Jackson, Bryan L; Modha, Dharmendra S; Kreutz-Delgado, Kenneth; Cauwenberghs, Gert

    2016-08-01

    Stochastic neural networks such as Restricted Boltzmann Machines (RBMs) have been successfully used in applications ranging from speech recognition to image classification, and are particularly interesting because of their potential for generative tasks. Inference and learning in these algorithms use a Markov Chain Monte Carlo procedure called Gibbs sampling, where a logistic function forms the kernel of this sampler. On the other side of the spectrum, neuromorphic systems have shown great promise for low-power and parallelized cognitive computing, but lack well-suited applications and automation procedures. In this work, we propose a systematic method for bridging the RBM algorithm and digital neuromorphic systems, with a generative pattern completion task as proof of concept. For this, we first propose a method of producing the Gibbs sampler using bio-inspired digital noisy integrate-and-fire neurons. Next, we describe the process of mapping generative RBMs trained offline onto the IBM TrueNorth neurosynaptic processor-a low-power digital neuromorphic VLSI substrate. Mapping these algorithms onto neuromorphic hardware presents unique challenges in network connectivity and weight and bias quantization, which, in turn, require architectural and design strategies for the physical realization. Generative performance is analyzed to validate the neuromorphic requirements and to best select the neuron parameters for the model. Lastly, we describe a design automation procedure which achieves optimal resource usage, accounting for the novel hardware adaptations. This work represents the first implementation of generative RBM inference on a neuromorphic VLSI substrate.

  13. Iterative learning control algorithm for spiking behavior of neuron model

    Science.gov (United States)

    Li, Shunan; Li, Donghui; Wang, Jiang; Yu, Haitao

    2016-11-01

    Controlling neurons to generate a desired or normal spiking behavior is the fundamental building block of the treatment of many neurologic diseases. The objective of this work is to develop a novel control method-closed-loop proportional integral (PI)-type iterative learning control (ILC) algorithm to control the spiking behavior in model neurons. In order to verify the feasibility and effectiveness of the proposed method, two single-compartment standard models of different neuronal excitability are specifically considered: Hodgkin-Huxley (HH) model for class 1 neural excitability and Morris-Lecar (ML) model for class 2 neural excitability. ILC has remarkable advantages for the repetitive processes in nature. To further highlight the superiority of the proposed method, the performances of the iterative learning controller are compared to those of classical PI controller. Either in the classical PI control or in the PI control combined with ILC, appropriate background noises are added in neuron models to approach the problem under more realistic biophysical conditions. Simulation results show that the controller performances are more favorable when ILC is considered, no matter which neuronal excitability the neuron belongs to and no matter what kind of firing pattern the desired trajectory belongs to. The error between real and desired output is much smaller under ILC control signal, which suggests ILC of neuron’s spiking behavior is more accurate.

  14. 3D-printer visualization of neuron models

    Directory of Open Access Journals (Sweden)

    Robert A McDougal

    2015-06-01

    Full Text Available Neurons come in a wide variety of shapes and sizes. In a quest to understand this neuronal diversity, researchers have three-dimensionally traced tens of thousands of neurons; many of these tracings are freely available through online repositories like NeuroMorpho.Org and ModelDB. Tracings can be visualized on the computer screen, used for statistical analysis of the properties of different cell types, used to simulate neuronal behavior, and more. We introduce the use of 3D printing as a technique for visualizing traced morphologies. Our method for generating printable versions of a cell or group of cells is to expand dendrite and axon diameters and then to transform the wireframe tracing into a 3D object with a neuronal surface generating algorithm like Constructive Tessellated Neuronal Geometry (CTNG. We show that 3D printed cells can be readily examined, manipulated, and compared with other neurons to gain insight into both the biology and the reconstruction process. We share our printable models in a new database, 3DModelDB, and encourage others to do the same with cells that they generate using our code or other methods. To provide additional context, 3DModelDB provides a simulatable version of each cell, links to papers that use or describe it, and links to associated entries in other databases.

  15. 3D-printer visualization of neuron models.

    Science.gov (United States)

    McDougal, Robert A; Shepherd, Gordon M

    2015-01-01

    Neurons come in a wide variety of shapes and sizes. In a quest to understand this neuronal diversity, researchers have three-dimensionally traced tens of thousands of neurons; many of these tracings are freely available through online repositories like NeuroMorpho.Org and ModelDB. Tracings can be visualized on the computer screen, used for statistical analysis of the properties of different cell types, used to simulate neuronal behavior, and more. We introduce the use of 3D printing as a technique for visualizing traced morphologies. Our method for generating printable versions of a cell or group of cells is to expand dendrite and axon diameters and then to transform the tracing into a 3D object with a neuronal surface generating algorithm like Constructive Tessellated Neuronal Geometry (CTNG). We show that 3D printed cells can be readily examined, manipulated, and compared with other neurons to gain insight into both the biology and the reconstruction process. We share our printable models in a new database, 3DModelDB, and encourage others to do the same with cells that they generate using our code or other methods. To provide additional context, 3DModelDB provides a simulatable version of each cell, links to papers that use or describe it, and links to associated entries in other databases.

  16. Spiking neuron model for temporal sequence recognition.

    Science.gov (United States)

    Byrnes, Sean; Burkitt, Anthony N; Grayden, David B; Meffin, Hamish

    2010-01-01

    A biologically inspired neuronal network that stores and recognizes temporal sequences of symbols is described. Each symbol is represented by excitatory input to distinct groups of neurons (symbol pools). Unambiguous storage of multiple sequences with common subsequences is ensured by partitioning each symbol pool into subpools that respond only when the current symbol has been preceded by a particular sequence of symbols. We describe synaptic structure and neural dynamics that permit the selective activation of subpools by the correct sequence. Symbols may have varying durations of the order of hundreds of milliseconds. Physiologically plausible plasticity mechanisms operate on a time scale of tens of milliseconds; an interaction of the excitatory input with periodic global inhibition bridges this gap so that neural events representing successive symbols occur on this much faster timescale. The network is shown to store multiple overlapping sequences of events. It is robust to variation in symbol duration, it is scalable, and its performance degrades gracefully with perturbation of its parameters.

  17. An experimental electronic model for a neuronal cell

    Science.gov (United States)

    Campos-Cantón, I.; Rangel-López, A.; Martel-Gallegos, G.; Zarazúa, S.; Vertiz-Hérnandez, A.

    2014-04-01

    Over the last two decades, the study of information transmission in living beings has acquired great relevance, because it regulates and conducts the functioning of all of the organs in the body. In information transmission pathways, the neuron plays an important role in that it receives, transmits, and processes electrical signals from different parts of the human body; these signals are transmitted as electrical impulses called action potentials, and they transmit information from one neuron to another. In this work, and with the aim of developing experiments for teaching biological processes, we implemented an electronic circuit of the neuron cell device and its mathematical model based on piecewise linear functions.

  18. Interactions of the orexin/hypocretin neurones and the histaminergic system.

    Science.gov (United States)

    Sundvik, M; Panula, P

    2015-02-01

    Histaminergic and orexin/hypocretin systems are components in the brain wake-promoting system. Both are affected in the sleep disorder narcolepsy, but the role of histamine in narcolepsy is unclear. The histaminergic neurones are activated by the orexin/hypocretin system in rodents, and the development of the orexin/hypocretin neurones is bidirectionally regulated by the histaminergic system in zebrafish. This review summarizes the current knowledge of the interactions of these two systems in normal and pathological conditions in humans and different animal models.

  19. FGF-2 induces neuronal death through upregulation of system xc-.

    Science.gov (United States)

    Liu, Xiaoqian; Albano, Rebecca; Lobner, Doug

    2014-02-14

    The cystine/glutamate antiporter (system xc-) transports cystine into cell in exchange for glutamate. Fibroblast growth factor-2 (FGF-2) upregulates system xc- selectively on astrocytes, which leads to increased cystine uptake, the substrate for glutathione production, and increased glutamate release. While increased intracellular glutathione can limit oxidative stress, the increased glutamate release can potentially lead to excitotoxicity to neurons. To test this hypothesis, mixed neuronal and glial cortical cultures were treated with FGF-2. Treatment with FGF-2 for 48 h caused a significant neuronal death in these cultures. Cell death was not observed in neuronal-enriched cultures, or astrocyte-enriched cultures, suggesting the toxicity was the result of neuron-glia interaction. Blocking system xc- eliminated the neuronal death as did the AMPA/kainate receptor antagonist 2,3-dihydroxy-6-nitro-7-sulfamoyl-benzo[f]quinoxaline-2,3-dione (NBQX), but not the NMDA receptor antagonist memantine. When cultures were exposed directly to glutamate, both NBQX and memantine blocked the neuronal toxicity. The mechanism of this altered profile of glutamate receptor mediated toxicity by FGF-2 is unclear. The selective calcium permeable AMPA receptor antagonist 1-naphthyl acetyl spermine (NASPM) failed to offer protection. The most likely explanation for the results is that 48 h FGF-2 treatment induces AMPA/kainate receptor toxicity through increased system xc- function resulting in increased release of glutamate. At the same time, FGF-2 alters the sensitivity of the neurons to glutamate toxicity in a manner that promotes selective AMPA/kainate receptor mediated toxicity.

  20. Restoring the encoding properties of a stochastic neuron model by an exogenous noise

    Directory of Open Access Journals (Sweden)

    Alessandra ePaffi

    2015-05-01

    Full Text Available Here we evaluate the possibility of improving the encoding properties of an impaired neuronal system by superimposing an exogenous noise to an external electric stimulation signal. The approach is based on the use of mathematical neuron models consisting of stochastic HH-like circuit, where the impairment of the endogenous presynaptic inputs is described as a subthreshold injected current and the exogenous stimulation signal is a sinusoidal voltage perturbation across the membrane. Our results indicate that a correlated Gaussian noise, added to the sinusoidal signal can significantly increase the encoding properties of the impaired system, through the Stochastic Resonance (SR phenomenon. These results suggest that an exogenous noise, suitably tailored, could improve the efficacy of those stimulation techniques used in neuronal systems, where the presynaptic sensory neurons are impaired and have to be artificially bypassed.

  1. Restoring the encoding properties of a stochastic neuron model by an exogenous noise.

    Science.gov (United States)

    Paffi, Alessandra; Camera, Francesca; Apollonio, Francesca; d'Inzeo, Guglielmo; Liberti, Micaela

    2015-01-01

    Here we evaluate the possibility of improving the encoding properties of an impaired neuronal system by superimposing an exogenous noise to an external electric stimulation signal. The approach is based on the use of mathematical neuron models consisting of stochastic HH-like circuit, where the impairment of the endogenous presynaptic inputs is described as a subthreshold injected current and the exogenous stimulation signal is a sinusoidal voltage perturbation across the membrane. Our results indicate that a correlated Gaussian noise, added to the sinusoidal signal can significantly increase the encoding properties of the impaired system, through the Stochastic Resonance (SR) phenomenon. These results suggest that an exogenous noise, suitably tailored, could improve the efficacy of those stimulation techniques used in neuronal systems, where the presynaptic sensory neurons are impaired and have to be artificially bypassed.

  2. Astrocyte and Neuronal Plasticity in the Somatosensory System.

    Science.gov (United States)

    Sims, Robert E; Butcher, John B; Parri, H Rheinallt; Glazewski, Stanislaw

    2015-01-01

    Changing the whisker complement on a rodent's snout can lead to two forms of experience-dependent plasticity (EDP) in the neurons of the barrel cortex, where whiskers are somatotopically represented. One form, termed coding plasticity, concerns changes in synaptic transmission and connectivity between neurons. This is thought to underlie learning and memory processes and so adaptation to a changing environment. The second, called homeostatic plasticity, serves to maintain a restricted dynamic range of neuronal activity thus preventing its saturation or total downregulation. Current explanatory models of cortical EDP are almost exclusively neurocentric. However, in recent years, increasing evidence has emerged on the role of astrocytes in brain function, including plasticity. Indeed, astrocytes appear as necessary partners of neurons at the core of the mechanisms of coding and homeostatic plasticity recorded in neurons. In addition to neuronal plasticity, several different forms of astrocytic plasticity have recently been discovered. They extend from changes in receptor expression and dynamic changes in morphology to alteration in gliotransmitter release. It is however unclear how astrocytic plasticity contributes to the neuronal EDP. Here, we review the known and possible roles for astrocytes in the barrel cortex, including its plasticity.

  3. Mathematical Modeling of Subthreshold Resonant Properties in Pyloric Dilator Neurons

    OpenAIRE

    Vazifehkhah Ghaffari, Babak; Kouhnavard, Mojgan; Aihara, Takeshi; Kitajima, Tatsuo

    2015-01-01

    Various types of neurons exhibit subthreshold resonance oscillation (preferred frequency response) to fluctuating sinusoidal input currents. This phenomenon is well known to influence the synaptic plasticity and frequency of neural network oscillation. This study evaluates the resonant properties of pacemaker pyloric dilator (PD) neurons in the central pattern generator network through mathematical modeling. From the pharmacological point of view, calcium currents cannot be blocked in PD neur...

  4. A Neuronal Culture System to Detect Prion Synaptotoxicity.

    Directory of Open Access Journals (Sweden)

    Cheng Fang

    2016-05-01

    Full Text Available Synaptic pathology is an early feature of prion as well as other neurodegenerative diseases. Although the self-templating process by which prions propagate is well established, the mechanisms by which prions cause synaptotoxicity are poorly understood, due largely to the absence of experimentally tractable cell culture models. Here, we report that exposure of cultured hippocampal neurons to PrPSc, the infectious isoform of the prion protein, results in rapid retraction of dendritic spines. This effect is entirely dependent on expression of the cellular prion protein, PrPC, by target neurons, and on the presence of a nine-amino acid, polybasic region at the N-terminus of the PrPC molecule. Both protease-resistant and protease-sensitive forms of PrPSc cause dendritic loss. This system provides new insights into the mechanisms responsible for prion neurotoxicity, and it provides a platform for characterizing different pathogenic forms of PrPSc and testing potential therapeutic agents.

  5. Selective loss of alpha motor neurons with sparing of gamma motor neurons and spinal cord cholinergic neurons in a mouse model of spinal muscular atrophy.

    Science.gov (United States)

    Powis, Rachael A; Gillingwater, Thomas H

    2016-03-01

    Spinal muscular atrophy (SMA) is a neuromuscular disease characterised primarily by loss of lower motor neurons from the ventral grey horn of the spinal cord and proximal muscle atrophy. Recent experiments utilising mouse models of SMA have demonstrated that not all motor neurons are equally susceptible to the disease, revealing that other populations of neurons can also be affected. Here, we have extended investigations of selective vulnerability of neuronal populations in the spinal cord of SMA mice to include comparative assessments of alpha motor neuron (α-MN) and gamma motor neuron (γ-MN) pools, as well as other populations of cholinergic neurons. Immunohistochemical analyses of late-symptomatic SMA mouse spinal cord revealed that numbers of α-MNs were significantly reduced at all levels of the spinal cord compared with controls, whereas numbers of γ-MNs remained stable. Likewise, the average size of α-MN cell somata was decreased in SMA mice with no change occurring in γ-MNs. Evaluation of other pools of spinal cord cholinergic neurons revealed that pre-ganglionic sympathetic neurons, central canal cluster interneurons, partition interneurons and preganglionic autonomic dorsal commissural nucleus neuron numbers all remained unaffected in SMA mice. Taken together, these findings indicate that α-MNs are uniquely vulnerable among cholinergic neuron populations in the SMA mouse spinal cord, with γ-MNs and other cholinergic neuronal populations being largely spared.

  6. An optogenetic mouse model of rett syndrome targeting on catecholaminergic neurons.

    Science.gov (United States)

    Zhang, Shuang; Johnson, Christopher M; Cui, Ningren; Xing, Hao; Zhong, Weiwei; Wu, Yang; Jiang, Chun

    2016-10-01

    Rett syndrome (RTT) is a neurodevelopmental disorder affecting multiple functions, including the norepinephrine (NE) system. In the CNS, NE is produced mostly by neurons in the locus coeruleus (LC), where defects in intrinsic neuronal properties, NE biosynthetic enzymes, neuronal CO2 sensitivity, and synaptic currents have been reported in mouse models of RTT. LC neurons in methyl-CpG-binding protein 2 gene (Mecp2) null mice show a high rate of spontaneous firing, although whether such hyperexcitability might increase or decrease the NE release from synapses is unknown. To activate the NEergic axonal terminals selectively, we generated an optogenetic mouse model of RTT in which NEergic neuronal excitability can be manipulated with light. Using commercially available mouse breeders, we produced a new strain of double-transgenic mice with Mecp2 knockout and channelrhodopsin (ChR) knockin in catecholaminergic neurons. Several RTT-like phenotypes were found in the tyrosine hydroxylase (TH)-ChR-Mecp2(-/Y) mice, including hypoactivity, low body weight, hindlimb clasping, and breathing disorders. In brain slices, optostimulation produced depolarization and an increase in the firing rate of LC neurons from TH-ChR control mice. In TH-ChR control mice, optostimulation of presynaptic NEergic neurons augmented the firing rate of hypoglossal neurons (HNs), which was blocked by the α-adrenoceptor antagonist phentolamine. Such optostimulation of NEergic terminals had almost no effect on HNs from two or three TH-ChR-Mecp2(-/Y) mice, indicating that excessive excitation of presynaptic neurons does not benefit NEergic modulation in mice with Mecp2 disruption. These results also demonstrate the feasibility of generating double-transgenic mice for studies of RTT with commercially available mice, which are inexpensive, labor/time efficient, and promising for cell-specific stimulation. © 2016 Wiley Periodicals, Inc.

  7. Pituitary Adenylate cyclase-activating polypeptide orchestrates neuronal regulation of the astrocytic glutamate-releasing mechanism system xc (.).

    Science.gov (United States)

    Kong, Linghai; Albano, Rebecca; Madayag, Aric; Raddatz, Nicholas; Mantsch, John R; Choi, SuJean; Lobner, Doug; Baker, David A

    2016-05-01

    Glutamate signaling is achieved by an elaborate network involving neurons and astrocytes. Hence, it is critical to better understand how neurons and astrocytes interact to coordinate the cellular regulation of glutamate signaling. In these studies, we used rat cortical cell cultures to examine whether neurons or releasable neuronal factors were capable of regulating system xc (-) (Sxc), a glutamate-releasing mechanism that is expressed primarily by astrocytes and has been shown to regulate synaptic transmission. We found that astrocytes cultured with neurons or exposed to neuronal-conditioned media displayed significantly higher levels of Sxc activity. Next, we demonstrated that the pituitary adenylate cyclase-activating polypeptide (PACAP) may be a neuronal factor capable of regulating astrocytes. In support, we found that PACAP expression was restricted to neurons, and that PACAP receptors were expressed in astrocytes. Interestingly, blockade of PACAP receptors in cultures comprised of astrocytes and neurons significantly decreased Sxc activity to the level observed in purified astrocytes, whereas application of PACAP to purified astrocytes increased Sxc activity to the level observed in cultures comprised of neurons and astrocytes. Collectively, these data reveal that neurons coordinate the actions of glutamate-related mechanisms expressed by astrocytes, such as Sxc, a process that likely involves PACAP. A critical gap in modeling excitatory signaling is how distinct components of the glutamate system expressed by neurons and astrocytes are coordinated. In these studies, we found that system xc (-) (Sxc), a glutamate release mechanism expressed by astrocytes, is regulated by releasable neuronal factors including PACAP. This represents a novel form of neuron-astrocyte communication, and highlights the possibility that pathological changes involving astrocytic Sxc may stem from altered neuronal activity.

  8. Mathematical Modeling of Subthreshold Resonant Properties in Pyloric Dilator Neurons

    Directory of Open Access Journals (Sweden)

    Babak Vazifehkhah Ghaffari

    2015-01-01

    Full Text Available Various types of neurons exhibit subthreshold resonance oscillation (preferred frequency response to fluctuating sinusoidal input currents. This phenomenon is well known to influence the synaptic plasticity and frequency of neural network oscillation. This study evaluates the resonant properties of pacemaker pyloric dilator (PD neurons in the central pattern generator network through mathematical modeling. From the pharmacological point of view, calcium currents cannot be blocked in PD neurons without removing the calcium-dependent potassium current. Thus, the effects of calcium ICa and calcium-dependent potassium IKCa currents on resonant properties remain unclear. By taking advantage of Hodgkin-Huxley-type model of neuron and its equivalent RLC circuit, we examine the effects of changing resting membrane potential and those ionic currents on the resonance. Results show that changing the resting membrane potential influences the amplitude and frequency of resonance so that the strength of resonance (Q-value increases by both depolarization and hyperpolarization of the resting membrane potential. Moreover, hyperpolarization-activated inward current Ih and ICa (in association with IKCa are dominant factors on resonant properties at hyperpolarized and depolarized potentials, respectively. Through mathematical analysis, results indicate that Ih and IKCa affect the resonant properties of PD neurons. However, ICa only has an amplifying effect on the resonance amplitude of these neurons.

  9. Mathematical modeling of subthreshold resonant properties in pyloric dilator neurons.

    Science.gov (United States)

    Vazifehkhah Ghaffari, Babak; Kouhnavard, Mojgan; Aihara, Takeshi; Kitajima, Tatsuo

    2015-01-01

    Various types of neurons exhibit subthreshold resonance oscillation (preferred frequency response) to fluctuating sinusoidal input currents. This phenomenon is well known to influence the synaptic plasticity and frequency of neural network oscillation. This study evaluates the resonant properties of pacemaker pyloric dilator (PD) neurons in the central pattern generator network through mathematical modeling. From the pharmacological point of view, calcium currents cannot be blocked in PD neurons without removing the calcium-dependent potassium current. Thus, the effects of calcium (I(Ca)) and calcium-dependent potassium (I(KCa)) currents on resonant properties remain unclear. By taking advantage of Hodgkin-Huxley-type model of neuron and its equivalent RLC circuit, we examine the effects of changing resting membrane potential and those ionic currents on the resonance. Results show that changing the resting membrane potential influences the amplitude and frequency of resonance so that the strength of resonance (Q-value) increases by both depolarization and hyperpolarization of the resting membrane potential. Moreover, hyperpolarization-activated inward current (I(h)) and I(Ca) (in association with I(KCa)) are dominant factors on resonant properties at hyperpolarized and depolarized potentials, respectively. Through mathematical analysis, results indicate that I h and I(KCa) affect the resonant properties of PD neurons. However, I(Ca) only has an amplifying effect on the resonance amplitude of these neurons.

  10. Computational modeling of memory allocation in neuronal and dendritic populations

    Directory of Open Access Journals (Sweden)

    George I Kastellakis

    2014-03-01

    Full Text Available Recent studies using molecular and cellular approaches have established that memory is supported by distributed and sparse populations of neurons. The allocation of neurons and synapses to store a long term memory engram is not random, but depends on properties such as neuronal excitability and CREB activation. The consolidation of synaptic plasticity, which is believed to serve long-term memory storage, is dependent on protein availability, and shaped by the mechanism of synaptic tagging and capture. In addition, dendritic protein synthesis allows for compartmentalized plasticity and synapse clustering. The implications of the rules governing long-term memory allocation in neurons and their dendrites are not yet known. To this aim, we present a model that incorporates multiple plasticity-related mechanisms which are known to be active during memory allocation and consolidation. Using this model, we show that memory allocation in neurons and their dendrites is affected by dendritic protein synthesis, and that the late-LTP associativity mechanisms allow related memories to be stored in overlapping populations of neurons.

  11. Modeling ALS and FTD with iPSC-derived neurons.

    Science.gov (United States)

    Lee, Sebum; Huang, Eric J

    2017-02-01

    Recent advances in genetics and neuropathology support the idea that amyotrophic lateral sclerosis (ALS) and frontotemporal lobar dementia (FTD) are two ends of a disease spectrum. Although several animal models have been developed to investigate the pathogenesis and disease progression in ALS and FTD, there are significant limitations that hamper our ability to connect these models with the neurodegenerative processes in human diseases. With the technical breakthrough in reprogramming biology, it is now possible to generate patient-specific induced pluripotent stem cells (iPSCs) and disease-relevant neuron subtypes. This review provides a comprehensive summary of studies that use iPSC-derived neurons to model ALS and FTD. We discuss the unique capabilities of iPSC-derived neurons that capture some key features of ALS and FTD, and underscore their potential roles in drug discovery. There are, however, several critical caveats that require improvements before iPSC-derived neurons can become highly effective disease models. This article is part of a Special Issue entitled SI: Exploiting human neurons.

  12. Sensory neurons do not induce motor neuron loss in a human stem cell model of spinal muscular atrophy.

    Science.gov (United States)

    Schwab, Andrew J; Ebert, Allison D

    2014-01-01

    Spinal muscular atrophy (SMA) is an autosomal recessive disorder leading to paralysis and early death due to reduced SMN protein. It is unclear why there is such a profound motor neuron loss, but recent evidence from fly and mouse studies indicate that cells comprising the whole sensory-motor circuit may contribute to motor neuron dysfunction and loss. Here, we used induced pluripotent stem cells derived from SMA patients to test whether sensory neurons directly contribute to motor neuron loss. We generated sensory neurons from SMA induced pluripotent stem cells and found no difference in neuron generation or survival, although there was a reduced calcium response to depolarizing stimuli. Using co-culture of SMA induced pluripotent stem cell derived sensory neurons with control induced pluripotent stem cell derived motor neurons, we found no significant reduction in motor neuron number or glutamate transporter boutons on motor neuron cell bodies or neurites. We conclude that SMA sensory neurons do not overtly contribute to motor neuron loss in this human stem cell system.

  13. Mixed-mode oscillations in a three time-scale model for the dopaminergic neuron.

    NARCIS (Netherlands)

    Krupa, M.; Popovic, N.; Kopell, N.; Rotstein, H.G.

    2008-01-01

    Mixed-mode dynamics is a complex type of dynamical behavior that has been observed both numerically and experimentally in numerous prototypical systems in the natural sciences. The compartmental Wilson-Callaway model for the dopaminergic neuron is an example of a system that exhibits a wide variety

  14. Single Neuron PID Control of Aircraft Deicing Fluids Rapid Heating System

    Directory of Open Access Journals (Sweden)

    Bin Chen

    2013-02-01

    Full Text Available Aircraft deicing fluids rapid heating system is widely used in aircraft ground deicing to ensure that the operation of flights can be safe and efficient. Aiming at the temperature turbulence problem of aircraft deicing system, this paper presents the single neuron PID control strategy which combine the advantage of conventional PID control with artificial neuron control. The aircraft deicing fluids rapid heating system and the scheme and working principle of the system is introduced. Simulation is executed on the basis of the mathematical model of aircraft deicing fluids rapid heating system, which is built in this paper, according to a number of data collected by experiments which are operated on the experimental platform of deicing fluids rapid heating system. The simulation results show that the single neuron PID control strategy perform effectively on the temperature turbulence problem of aircraft deicing fluids rapid heating system. Experiments are conducted to vertify the single neuron PID control strategy, the results of which show that the single neuron PID control strategy can achieve the request in practical application of the aircraft deicing fluids rapid heating system.

  15. Spider Silk as Guiding Biomaterial for Human Model Neurons

    Directory of Open Access Journals (Sweden)

    Frank Roloff

    2014-01-01

    Full Text Available Over the last years, a number of therapeutic strategies have emerged to promote axonal regeneration. An attractive strategy is the implantation of biodegradable and nonimmunogenic artificial scaffolds into injured peripheral nerves. In previous studies, transplantation of decellularized veins filled with spider silk for bridging critical size nerve defects resulted in axonal regeneration and remyelination by invading endogenous Schwann cells. Detailed interaction of elongating neurons and the spider silk as guidance material is unknown. To visualize direct cellular interactions between spider silk and neurons in vitro, we developed an in vitro crossed silk fiber array. Here, we describe in detail for the first time that human (NT2 model neurons attach to silk scaffolds. Extending neurites can bridge gaps between single silk fibers and elongate afterwards on the neighboring fiber. Culturing human neurons on the silk arrays led to an increasing migration and adhesion of neuronal cell bodies to the spider silk fibers. Within three to four weeks, clustered somata and extending neurites formed ganglion-like cell structures. Microscopic imaging of human neurons on the crossed fiber arrays in vitro will allow for a more efficient development of methods to maximize cell adhesion and neurite growth on spider silk prior to transplantation studies.

  16. Spider silk as guiding biomaterial for human model neurons.

    Science.gov (United States)

    Roloff, Frank; Strauß, Sarah; Vogt, Peter M; Bicker, Gerd; Radtke, Christine

    2014-01-01

    Over the last years, a number of therapeutic strategies have emerged to promote axonal regeneration. An attractive strategy is the implantation of biodegradable and nonimmunogenic artificial scaffolds into injured peripheral nerves. In previous studies, transplantation of decellularized veins filled with spider silk for bridging critical size nerve defects resulted in axonal regeneration and remyelination by invading endogenous Schwann cells. Detailed interaction of elongating neurons and the spider silk as guidance material is unknown. To visualize direct cellular interactions between spider silk and neurons in vitro, we developed an in vitro crossed silk fiber array. Here, we describe in detail for the first time that human (NT2) model neurons attach to silk scaffolds. Extending neurites can bridge gaps between single silk fibers and elongate afterwards on the neighboring fiber. Culturing human neurons on the silk arrays led to an increasing migration and adhesion of neuronal cell bodies to the spider silk fibers. Within three to four weeks, clustered somata and extending neurites formed ganglion-like cell structures. Microscopic imaging of human neurons on the crossed fiber arrays in vitro will allow for a more efficient development of methods to maximize cell adhesion and neurite growth on spider silk prior to transplantation studies.

  17. Leaders of neuronal cultures in a quorum percolation model

    Directory of Open Access Journals (Sweden)

    Jean-Pierre Eckmann

    2010-09-01

    Full Text Available We present a theoretical framework using quorum-percolation for describing the initiation of activity in a neural culture. The cultures are modeled as random graphs, whose nodes are neurons with $kin$ inputs and $kout$ outputs, and whose input degrees $kin=k$ obey given distribution functions $p_k$. We examine the firing activity of the population of neurons according to their input degree ($k$ classes and calculate for each class its firing probability $Phi_k(t$ as a function of $t$. The probability of a node to fire is found to be determined by its in-degree $k$, and the first-to-fire neurons are those that have a high $k$. A small minority of high-$k$ classes may be called ``Leaders,'' as they form an inter-connected subnetwork that consistently fires much before the rest of the culture. Once initiated, the activity spreads from the Leaders to the less connected majority of the culture. We then use the distribution of in-degree of the Leaders to study the growth rate of the number of neurons active in a burst, which was experimentally measured to be initially exponential. We find that this kind of growth rate is best described by a population that has an in-degree distribution that is a Gaussian centered around $k=75$ with width $sigma=31$ for the majority of the neurons, but also has a power law tail with exponent $-2$ for ten percent of the population. Neurons in the tail may have as many as $k=4,700$ inputs. We explore and discuss the correspondence between the degree distribution and a dynamic neuronal threshold, showing that from the functional point of view, structure and elementary dynamics are interchangeable. We discuss possible geometric origins of this distribution, and comment on the importance of size, or of having a large number of neurons, in the culture.

  18. Dissecting the Phase Response of a Model Bursting Neuron

    CERN Document Server

    Sherwood, William Erik

    2009-01-01

    We investigate the phase response properties of the Hindmarsh-Rose model of neuronal bursting using burst phase response curves (BPRCs) computed with an infinitesimal perturbation approximation and by direct simulation of synaptic input. The resulting BPRCs have a significantly more complicated structure than the usual Type I and Type II PRCs of spiking neuronal models, and they exhibit highly timing-sensitive changes in the number of spikes per burst that lead to large magnitude phase responses. We use fast-slow dissection and isochron calculations to analyze the phase response dynamics in both weak and strong perturbation regimes.

  19. Optimizing NEURON Simulation Environment Using Remote Memory Access with Recursive Doubling on Distributed Memory Systems

    Directory of Open Access Journals (Sweden)

    Danish Shehzad

    2016-01-01

    Full Text Available Increase in complexity of neuronal network models escalated the efforts to make NEURON simulation environment efficient. The computational neuroscientists divided the equations into subnets amongst multiple processors for achieving better hardware performance. On parallel machines for neuronal networks, interprocessor spikes exchange consumes large section of overall simulation time. In NEURON for communication between processors Message Passing Interface (MPI is used. MPI_Allgather collective is exercised for spikes exchange after each interval across distributed memory systems. The increase in number of processors though results in achieving concurrency and better performance but it inversely affects MPI_Allgather which increases communication time between processors. This necessitates improving communication methodology to decrease the spikes exchange time over distributed memory systems. This work has improved MPI_Allgather method using Remote Memory Access (RMA by moving two-sided communication to one-sided communication, and use of recursive doubling mechanism facilitates achieving efficient communication between the processors in precise steps. This approach enhanced communication concurrency and has improved overall runtime making NEURON more efficient for simulation of large neuronal network models.

  20. Optimizing NEURON Simulation Environment Using Remote Memory Access with Recursive Doubling on Distributed Memory Systems.

    Science.gov (United States)

    Shehzad, Danish; Bozkuş, Zeki

    2016-01-01

    Increase in complexity of neuronal network models escalated the efforts to make NEURON simulation environment efficient. The computational neuroscientists divided the equations into subnets amongst multiple processors for achieving better hardware performance. On parallel machines for neuronal networks, interprocessor spikes exchange consumes large section of overall simulation time. In NEURON for communication between processors Message Passing Interface (MPI) is used. MPI_Allgather collective is exercised for spikes exchange after each interval across distributed memory systems. The increase in number of processors though results in achieving concurrency and better performance but it inversely affects MPI_Allgather which increases communication time between processors. This necessitates improving communication methodology to decrease the spikes exchange time over distributed memory systems. This work has improved MPI_Allgather method using Remote Memory Access (RMA) by moving two-sided communication to one-sided communication, and use of recursive doubling mechanism facilitates achieving efficient communication between the processors in precise steps. This approach enhanced communication concurrency and has improved overall runtime making NEURON more efficient for simulation of large neuronal network models.

  1. [Development of intellect, emotion, and intentions, and their neuronal systems].

    Science.gov (United States)

    Segawa, Masaya

    2008-09-01

    Intellect, emotion and intentions, the major components of the human mentality, are neurologically correlated to memory and sensorimotor integration, the neuronal system consisting of the amygdale and hypothalamus, and motivation and learning, respectively. Development of these neuronal processes was evaluated by correlating the pathophysiologies of idiopathic developmental neuropsychiatric disorders and developmental courses of sleep parameters, sleep-wake rhythm (SWR), and locomotion. The memory system and sensory pathways develop by the 9th gestational months. Habituation or dorsal bundle extinction (DBE) develop after the 34th gestational week. In the first 4 months after birth, DBE is consolidated and fine tuning of the primary sensory cortex and its neuronal connection to the unimodal sensory association area along with functional lateralization of the cortex are accomplished. After 4 months, restriction of atonia in the REM stage enables the integrative function of the brain and induces synaptogenesis of the cortex around 6 months and locomotion in late infancy by activating the dopaminergic (DA) neurons induces synaptogenesis of the frontal cortex. Locomotion in early infancy involves functional specialization of the cortex and in childhood with development of biphasic SWR activation of the areas of the prefrontal cortex. Development of emotions reflects in the development of personal communication and the arousal function of the hypothalamus. The former is shown in the mother-child relationship in the first 4 months, in communication with adults and playmates in late infancy to early childhood, and in development of social relationships with sympathy by the early school age with functional maturation of the orbitofrontal cortex. The latter is demonstrated in the secretion of melatonin during night time by 4 months, in the circadian rhythm of body temperature by 8 months, and in the secretion of the growth hormone by 4-5 years with synchronization to the

  2. Lateral information processing by spiking neurons: a theoretical model of the neural correlate of consciousness.

    Science.gov (United States)

    Ebner, Marc; Hameroff, Stuart

    2011-01-01

    Cognitive brain functions, for example, sensory perception, motor control and learning, are understood as computation by axonal-dendritic chemical synapses in networks of integrate-and-fire neurons. Cognitive brain functions may occur either consciously or nonconsciously (on "autopilot"). Conscious cognition is marked by gamma synchrony EEG, mediated largely by dendritic-dendritic gap junctions, sideways connections in input/integration layers. Gap-junction-connected neurons define a sub-network within a larger neural network. A theoretical model (the "conscious pilot") suggests that as gap junctions open and close, a gamma-synchronized subnetwork, or zone moves through the brain as an executive agent, converting nonconscious "auto-pilot" cognition to consciousness, and enhancing computation by coherent processing and collective integration. In this study we implemented sideways "gap junctions" in a single-layer artificial neural network to perform figure/ground separation. The set of neurons connected through gap junctions form a reconfigurable resistive grid or sub-network zone. In the model, outgoing spikes are temporally integrated and spatially averaged using the fixed resistive grid set up by neurons of similar function which are connected through gap-junctions. This spatial average, essentially a feedback signal from the neuron's output, determines whether particular gap junctions between neurons will open or close. Neurons connected through open gap junctions synchronize their output spikes. We have tested our gap-junction-defined sub-network in a one-layer neural network on artificial retinal inputs using real-world images. Our system is able to perform figure/ground separation where the laterally connected sub-network of neurons represents a perceived object. Even though we only show results for visual stimuli, our approach should generalize to other modalities. The system demonstrates a moving sub-network zone of synchrony, within which the contents of

  3. The mirror-neuron system: a Bayesian perspective

    DEFF Research Database (Denmark)

    Kilner, James; Friston, Karl; Frith, Christopher

    2007-01-01

    Is it possible to understand the intentions of other peopleby simply observing their movements? Many neuroscientists believe that this ability depends on the brain’s mirror-neuron system, which provides a direct link between action and observation. Precisely how intentions can be inferred through...... movement-observation, however, has provoked much debate. One problem in inferring the cause of an observed action, is that the problem is ill-posed because identical movements can be made when performing different actions with different goals. Here we suggest that this problem is solved by the mirror-neuron...... identifies a precise role for the mirror-neuron system in our ability to infer intentions from observed movement and outlines possible computational mechanisms....

  4. From neural plate to cortical arousal-a neuronal network theory of sleep derived from in vitro "model" systems for primordial patterns of spontaneous bioelectric activity in the vertebrate central nervous system.

    Science.gov (United States)

    Corner, Michael A

    2013-05-22

    In the early 1960s intrinsically generated widespread neuronal discharges were discovered to be the basis for the earliest motor behavior throughout the animal kingdom. The pattern generating system is in fact programmed into the developing nervous system, in a regionally specific manner, already at the early neural plate stage. Such rhythmically modulated phasic bursts were next discovered to be a general feature of developing neural networks and, largely on the basis of experimental interventions in cultured neural tissues, to contribute significantly to their morpho-physiological maturation. In particular, the level of spontaneous synchronized bursting is homeostatically regulated, and has the effect of constraining the development of excessive network excitability. After birth or hatching, this "slow-wave" activity pattern becomes sporadically suppressed in favor of sensory oriented "waking" behaviors better adapted to dealing with environmental contingencies. It nevertheless reappears periodically as "sleep" at several species-specific points in the diurnal/nocturnal cycle. Although this "default" behavior pattern evolves with development, its essential features are preserved throughout the life cycle, and are based upon a few simple mechanisms which can be both experimentally demonstrated and simulated by computer modeling. In contrast, a late onto- and phylogenetic aspect of sleep, viz., the intermittent "paradoxical" activation of the forebrain so as to mimic waking activity, is much less well understood as regards its contribution to brain development. Some recent findings dealing with this question by means of cholinergically induced "aroused" firing patterns in developing neocortical cell cultures, followed by quantitative electrophysiological assays of immediate and longterm sequelae, will be discussed in connection with their putative implications for sleep ontogeny.

  5. A Neuron-Oriented Programming System

    Institute of Scientific and Technical Information of China (English)

    李涛

    2001-01-01

    A neruonoriented programming system based on parallel neural informati o n processing has been presented. With the neural programming system built upon 4~8 process elements(TMS C30), the system has thus provided users high speed, g e neral purpose and large scale neural network application development platforms e tc.

  6. On Empathy: The Mirror Neuron System and Art Education

    Science.gov (United States)

    Jeffers, Carol S.

    2009-01-01

    This paper re/considers empathy and its implications for learning in the art classroom, particularly in light of relevant neuroscientific investigations of the mirror neuron system recently discovered in the human brain. These investigations reinterpret the meaning of perception, resonance, and connection, and point to the fundamental importance…

  7. The Mirror Neuron System: Grasping Others' Actions from Birth?

    Science.gov (United States)

    Lepage, Jean-Francois; Theoret, Hugo

    2007-01-01

    In the adult human brain, the presence of a system matching the observation and the execution of actions is well established. This mechanism is thought to rely primarily on the contribution of so-called "mirror neurons", cells that are active when a specific gesture is executed as well as when it is seen or heard. Despite the wealth of evidence…

  8. Acting together in and beyond the mirror neuron system

    NARCIS (Netherlands)

    Kokal, Idil; Gazzola, Valeria; Keysers, Christian

    2009-01-01

    Moving a set dinner table often takes two people, and doing so without spilling the glasses requires the close coordination of the two agents' actions. It has been argued that the mirror neuron system may be the key neural locus of such coordination. Instead, here we show that such coordination recr

  9. The Mirror Neuron System: Grasping Others' Actions from Birth?

    Science.gov (United States)

    Lepage, Jean-Francois; Theoret, Hugo

    2007-01-01

    In the adult human brain, the presence of a system matching the observation and the execution of actions is well established. This mechanism is thought to rely primarily on the contribution of so-called "mirror neurons", cells that are active when a specific gesture is executed as well as when it is seen or heard. Despite the wealth of evidence…

  10. Neocortical Neuronal Loss in Patients with Multiple System Atrophy

    DEFF Research Database (Denmark)

    Salvesen, Lisette; Winge, Kristian; Brudek, Tomasz

    2016-01-01

    To determine the extent of neocortical involvement in multiple system atrophy (MSA), we used design-based stereological methods to estimate the total numbers of neurons, oligodendrocytes, astrocytes, and microglia in the frontal, parietal, temporal, and occipital cortex of brains from 11 patients...... with MSA and 11 age- and gender-matched control subjects. The stereological data were supported by cell marker expression analyses in tissue samples from the prefrontal cortex. We found significantly fewer neurons in the frontal and parietal cortex of MSA brains compared with control brains. Significantly...... more astrocytes and microglia were observed in the frontal, parietal, and temporal cortex of MSA brains, whereas no change in the total number of oligodendrocytes was seen in any of the neocortical regions. There were significantly fewer neurons in the frontal cortex of MSA patients with impaired...

  11. Modeling of Auditory Neuron Response Thresholds with Cochlear Implants

    Directory of Open Access Journals (Sweden)

    Frederic Venail

    2015-01-01

    Full Text Available The quality of the prosthetic-neural interface is a critical point for cochlear implant efficiency. It depends not only on technical and anatomical factors such as electrode position into the cochlea (depth and scalar placement, electrode impedance, and distance between the electrode and the stimulated auditory neurons, but also on the number of functional auditory neurons. The efficiency of electrical stimulation can be assessed by the measurement of e-CAP in cochlear implant users. In the present study, we modeled the activation of auditory neurons in cochlear implant recipients (nucleus device. The electrical response, measured using auto-NRT (neural responses telemetry algorithm, has been analyzed using multivariate regression with cubic splines in order to take into account the variations of insertion depth of electrodes amongst subjects as well as the other technical and anatomical factors listed above. NRT thresholds depend on the electrode squared impedance (β = −0.11 ± 0.02, P<0.01, the scalar placement of the electrodes (β = −8.50 ± 1.97, P<0.01, and the depth of insertion calculated as the characteristic frequency of auditory neurons (CNF. Distribution of NRT residues according to CNF could provide a proxy of auditory neurons functioning in implanted cochleas.

  12. Modeling of Auditory Neuron Response Thresholds with Cochlear Implants.

    Science.gov (United States)

    Venail, Frederic; Mura, Thibault; Akkari, Mohamed; Mathiolon, Caroline; Menjot de Champfleur, Sophie; Piron, Jean Pierre; Sicard, Marielle; Sterkers-Artieres, Françoise; Mondain, Michel; Uziel, Alain

    2015-01-01

    The quality of the prosthetic-neural interface is a critical point for cochlear implant efficiency. It depends not only on technical and anatomical factors such as electrode position into the cochlea (depth and scalar placement), electrode impedance, and distance between the electrode and the stimulated auditory neurons, but also on the number of functional auditory neurons. The efficiency of electrical stimulation can be assessed by the measurement of e-CAP in cochlear implant users. In the present study, we modeled the activation of auditory neurons in cochlear implant recipients (nucleus device). The electrical response, measured using auto-NRT (neural responses telemetry) algorithm, has been analyzed using multivariate regression with cubic splines in order to take into account the variations of insertion depth of electrodes amongst subjects as well as the other technical and anatomical factors listed above. NRT thresholds depend on the electrode squared impedance (β = -0.11 ± 0.02, P < 0.01), the scalar placement of the electrodes (β = -8.50 ± 1.97, P < 0.01), and the depth of insertion calculated as the characteristic frequency of auditory neurons (CNF). Distribution of NRT residues according to CNF could provide a proxy of auditory neurons functioning in implanted cochleas.

  13. Aberrant neuronal activity-induced signaling and gene expression in a mouse model of RASopathy

    Science.gov (United States)

    Nakhaei-Rad, Saeideh; Montenegro-Venegas, Carolina; Pina-Fernández, Eneko; Marini, Claudia; Santos, Monica; Ahmadian, Mohammad R.; Stork, Oliver; Zenker, Martin

    2017-01-01

    Noonan syndrome (NS) is characterized by reduced growth, craniofacial abnormalities, congenital heart defects, and variable cognitive deficits. NS belongs to the RASopathies, genetic conditions linked to mutations in components and regulators of the Ras signaling pathway. Approximately 50% of NS cases are caused by mutations in PTPN11. However, the molecular mechanisms underlying cognitive impairments in NS patients are still poorly understood. Here, we report the generation and characterization of a new conditional mouse strain that expresses the overactive Ptpn11D61Y allele only in the forebrain. Unlike mice with a global expression of this mutation, this strain is viable and without severe systemic phenotype, but shows lower exploratory activity and reduced memory specificity, which is in line with a causal role of disturbed neuronal Ptpn11 signaling in the development of NS-linked cognitive deficits. To explore the underlying mechanisms we investigated the neuronal activity-regulated Ras signaling in brains and neuronal cultures derived from this model. We observed an altered surface expression and trafficking of synaptic glutamate receptors, which are crucial for hippocampal neuronal plasticity. Furthermore, we show that the neuronal activity-induced ERK signaling, as well as the consecutive regulation of gene expression are strongly perturbed. Microarray-based hippocampal gene expression profiling revealed profound differences in the basal state and upon stimulation of neuronal activity. The neuronal activity-dependent gene regulation was strongly attenuated in Ptpn11D61Y neurons. In silico analysis of functional networks revealed changes in the cellular signaling beyond the dysregulation of Ras/MAPK signaling that is nearly exclusively discussed in the context of NS at present. Importantly, changes in PI3K/AKT/mTOR and JAK/STAT signaling were experimentally confirmed. In summary, this study uncovers aberrant neuronal activity-induced signaling and regulation

  14. Reevaluating Metabolism in Alzheimer's Disease from the Perspective of the Astrocyte-Neuron Lactate Shuttle Model

    Directory of Open Access Journals (Sweden)

    Jordan T. Newington

    2013-01-01

    Full Text Available The conventional view of central nervous system (CNS metabolism is based on the assumption that glucose is the main fuel source for active neurons and is processed in an oxidative manner. However, since the early 1990s research has challenged the idea that the energy needs of nerve cells are met exclusively by glucose and oxidative metabolism. This alternative view of glucose utilization contends that astrocytes metabolize glucose to lactate, which is then released and taken up by nearby neurons and used as a fuel source, commonly known as the astrocyte-neuron lactate shuttle (ANLS model. Once thought of as a waste metabolite, lactate has emerged as a central player in the maintenance of neuronal function and long-term memory. Decreased neuronal metabolism has traditionally been viewed as a hallmark feature of Alzheimer's disease (AD. However, a more complex picture of CNS metabolism is emerging that may provide valuable insight into the pathophysiological changes that occur during AD and other neurodegenerative diseases. This review will examine the ANLS model and present recent evidence highlighting the critical role that lactate plays in neuronal survival and memory. Moreover, the role of glucose and lactate metabolism in AD will be re-evaluated from the perspective of the ANLS.

  15. Pharmacological activation/inhibition of the cannabinoid system affects alcohol withdrawal-induced neuronal hypersensitivity to excitotoxic insults.

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    Marina Rubio

    Full Text Available Cessation of chronic ethanol consumption can increase the sensitivity of the brain to excitotoxic damages. Cannabinoids have been proposed as neuroprotectants in different models of neuronal injury, but their effect have never been investigated in a context of excitotoxicity after alcohol cessation. Here we examined the effects of the pharmacological activation/inhibition of the endocannabinoid system in an in vitro model of chronic ethanol exposure and withdrawal followed by an excitotoxic challenge. Ethanol withdrawal increased N-methyl-D-aspartate (NMDA-evoked neuronal death, probably by altering the ratio between GluN2A and GluN2B NMDA receptor subunits. The stimulation of the endocannabinoid system with the cannabinoid agonist HU-210 decreased NMDA-induced neuronal death exclusively in ethanol-withdrawn neurons. This neuroprotection could be explained by a decrease in NMDA-stimulated calcium influx after the administration of HU-210, found exclusively in ethanol-withdrawn neurons. By contrast, the inhibition of the cannabinoid system with the CB1 receptor antagonist rimonabant (SR141716 during ethanol withdrawal increased death of ethanol-withdrawn neurons without any modification of NMDA-stimulated calcium influx. Moreover, chronic administration of rimonabant increased NMDA-stimulated toxicity not only in withdrawn neurons, but also in control neurons. In summary, we show for the first time that the stimulation of the endocannabinoid system is protective against the hyperexcitability developed during alcohol withdrawal. By contrast, the blockade of the endocannabinoid system is highly counterproductive during alcohol withdrawal.

  16. Neuronal modelling of baroreflex response to orthostatic stress

    Science.gov (United States)

    Samin, Azfar

    The accelerations experienced in aerial combat can cause pilot loss of consciousness (GLOC) due to a critical reduction in cerebral blood circulation. The development of smart protective equipment requires understanding of how the brain processes blood pressure (BP) information in response to acceleration. We present a biologically plausible model of the Baroreflex to investigate the neural correlates of short-term BP control under acceleration or orthostatic stress. The neuronal network model, which employs an integrate-and-fire representation of a biological neuron, comprises the sensory, motor, and the central neural processing areas that form the Baroreflex. Our modelling strategy is to test hypotheses relating to the encoding mechanisms of multiple sensory inputs to the nucleus tractus solitarius (NTS), the site of central neural processing. The goal is to run simulations and reproduce model responses that are consistent with the variety of available experimental data. Model construction and connectivity are inspired by the available anatomical and neurophysiological evidence that points to a barotopic organization in the NTS, and the presence of frequency-dependent synaptic depression, which provides a mechanism for generating non-linear local responses in NTS neurons that result in quantifiable dynamic global baroreflex responses. The entire physiological range of BP and rate of change of BP variables is encoded in a palisade of NTS neurons in that the spike responses approximate Gaussian 'tuning' curves. An adapting weighted-average decoding scheme computes the motor responses and a compensatory signal regulates the heart rate (HR). Model simulations suggest that: (1) the NTS neurons can encode the hydrostatic pressure difference between two vertically separated sensory receptor regions at +Gz, and use changes in that difference for the regulation of HR; (2) even though NTS neurons do not fire with a cardiac rhythm seen in the afferents, pulse

  17. The digital bee brain: integrating and managing neurons in a common 3D reference system

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    Jürgen Rybak

    2010-07-01

    Full Text Available The honeybee standard brain (HSB serves as an interactive tool for relating morphologies of bee brain neurons and provides a reference system for functional and bibliographical properties (http://www.neurobiologie.fu-berlin.de/beebrain/. The ultimate goal is to document not only the morphological network properties of neurons collected from separate brains, but also to establish a graphical user interface for a neuron-related data base. Here, we review the current methods and protocols used to incorporate neuronal reconstructions into the HSB. Our registration protocol consists of two separate steps applied to imaging data from two-channel confocal microscopy scans: (1 The reconstruction of the neuron, facilitated by an automatic extraction of the neuron’s skeleton based on threshold segmentation, and (2 the semi-automatic 3D segmentation of the neuropils and their registration with the HSB. The integration of neurons in the HSB is performed by applying the transformation computed in step (2 to the reconstructed neurons of step (1. The most critical issue of this protocol in terms of user interaction time – the segmentation process – is drastically improved by the use of a model-based segmentation process. Furthermore, the underlying statistical shape models (SSM allow the visualization and analysis of characteristic variations in large sets of bee brain data. The anatomy of neural networks composed of multiple neurons that are registered into the HSB are visualized by depicting the 3D reconstructions together with semantic information with the objective to integrate data from multiple sources (electrophysiology, imaging, immunocytochemistry, molecular biology. Ultimately, this will allow the user to specify cell types and retrieve their morphologies along with physiological characterizations.

  18. Appliance of Neuron Networks in Cryptographic Systems

    Directory of Open Access Journals (Sweden)

    Mohammed Al-Maitah

    2014-01-01

    Full Text Available This study is dedicated to the examination of a problem of postquantum encryption algorithms which are connected with a potential crisis in modern cryptography that is caused by appearance of quantum computers. General problem formulation is given as well as an example of danger from the quantum algorithms against classical cryptosystems. Existing postquantum systems are analyzed and the complication of their realization and cryptosecurity are estimated. Among the others algorithms on the basis of neural networks are chosen as a starting point. The study demonstrates neuro cryptographic protocol based on a three-level neural network of the direct propagation. There was evaluated it’s cryptosecurity and analyzed three types of this algorithm attack to show the reality of the hypothesis that neuro cryptography is currently one of the most promising post quantum cryptographic systems.

  19. Transport of BMAA into Neurons and Astrocytes by System xc.

    Science.gov (United States)

    Albano, Rebecca; Lobner, Doug

    2017-05-03

    The study of the mechanism of β-N-methylamino-L-alanine (BMAA) neurotoxicity originally focused on its effects at the N-methyl-D-aspartate (NMDA) receptor. In recent years, it has become clear that its mechanism of action is more complicated. First, there are certain cell types, such as motor neurons and cholinergic neurons, where the dominate mechanism of toxicity is through action at AMPA receptors. Second, even in cortical neurons where the primary mechanism of toxicity appears to be activation of NMDA receptors, there are other mechanisms involved. We found that along with NMDA receptors, activation of mGLuR5 receptors and effects on the cystine/glutamate antiporter (system xc-) were involved in the toxicity. The effects on system xc- are of particular interest. System xc- mediates the transport of cystine into the cell in exchange for releasing glutamate into the extracellular fluid. By releasing glutamate, system xc- can potentially cause excitotoxicity. However, through providing cystine to the cell, it regulates the levels of cellular glutathione (GSH), the main endogenous intracellular antioxidant, and in this way may protect cells against oxidative stress. We have previously published that BMAA inhibits cystine uptake leading to GSH depletion and had indirect evidence that BMAA is transported into the cells by system xc-. We now present direct evidence that BMAA is transported into both astrocytes and neurons through system xc-. The fact that BMAA is transported by system xc- also provides a mechanism for BMAA to enter brain cells potentially leading to misincorporation into proteins and protein misfolding.

  20. Reverse stochastic resonance in a hippocampal CA1 neuron model.

    Science.gov (United States)

    Durand, Dominique M; Kawaguchi, Minato; Mino, Hiroyuki

    2013-01-01

    Stochastic resonance (SR) is a ubiquitous and counter- intuitive phenomenon whereby the addition of noise to a non-linear system can improve the detection of sub-threshold signals. The "signal" is normally periodic or deterministic whereas the "noise" is normally stochastic. However, in neural systems, signals are often stochastic. Moreover, periodic signals are applied near neurons to control neural excitability (i.e. deep brain stimulation). We therefore tested the hypothesis that a quasi-periodic signal applied to a neural network could enhance the detection of a stochastic neural signal (reverse stochastic resonance). Using computational methods, a CA1 hippocampal neuron was simulated and a Poisson distributed subthreshold synaptic input ("signal") was applied to the synaptic terminals. A periodic or quasi periodic pulse train at various frequencies ("noise") was applied to an extracellular electrode located near the neuron. The mutual information and information transfer rate between the output and input of the neuron were calculated. The results display the signature of stochastic resonance with information transfer reaching a maximum value for increasing power (or frequency) of the "noise". This result shows that periodic signals applied extracellularly can improve the detection of subthreshold stochastic neural signals. The optimum frequency (110 Hz) is similar to that used in patients with Parkinson's suggesting that this phenomenon could play a role in the therapeutic effect of high frequency stimulation.

  1. Study on dynamic characteristics' change of hippocampal neuron reduced models caused by the Alzheimer's disease.

    Science.gov (United States)

    Peng, Yueping; Wang, Jue; Zheng, Chongxun

    2016-01-01

    In the paper, based on the electrophysiological experimental data, the Hippocampal neuron reduced model under the pathology condition of Alzheimer's disease (AD) has been built by modifying parameters' values. The reduced neuron model's dynamic characteristics under effect of AD are comparatively studied. Under direct current stimulation, compared with the normal neuron model, the AD neuron model's dynamic characteristics have obviously been changed. The neuron model under the AD condition undergoes supercritical Andronov-Hopf bifurcation from the rest state to the continuous discharge state. It is different from the neuron model under the normal condition, which undergoes saddle-node bifurcation. So, the neuron model changes into a resonator with monostable state from an integrator with bistable state under AD's action. The research reveals the neuron model's dynamic characteristics' changing under effect of AD, and provides some theoretic basis for AD research by neurodynamics theory.

  2. Pipe-cleaner Model of Neuronal Network Dynamics

    CERN Document Server

    Armstrong, Eve

    2016-01-01

    We present a functional model of neuronal network connectivity in which the single architectural element is the object commonly known in handicraft circles as a pipe cleaner. We argue that the dual nature of a neuronal circuit - that it be at times highly robust to external manipulation and yet sufficiently flexible to allow for learning and adaptation - is embodied in the pipe cleaner, and thus that a pipe cleaner framework serves as an instructive scaffold in which to examine network dynamics. Regarding the dynamics themselves: as pipe cleaners possess no intrinsic dynamics, in our model we attribute the emergent circuit dynamics to magic. Magic is a strategy that has been largely neglected in the neuroscience community, and may serve as an illuminating comparison to the common physics-based approaches. This model makes predictions that it would be really awesome to test experimentally. Moreover, the relative simplicity of the pipe cleaner - setting aside the fact that it comes in an overwhelming variety of...

  3. Integrate-and-fire neurons with threshold noise: A tractable model of how interspike interval correlations affect neuronal signal transmission

    Science.gov (United States)

    Lindner, Benjamin; Chacron, Maurice J.; Longtin, André

    2017-01-01

    Many neurons exhibit interval correlations in the absence of input signals. We study the influence of these intrinsic interval correlations of model neurons on their signal transmission properties. For this purpose, we employ two simple firing models, one of which generates a renewal process, while the other leads to a nonrenewal process with negative interval correlations. Different methods to solve for spectral statistics in the presence of a weak stimulus (spike train power spectra, cross spectra, and coherence functions) are presented, and their range of validity is discussed. Using these analytical results, we explore a lower bound on the mutual information rate between output spike train and input stimulus as a function of the system’s parameters. We demonstrate that negative correlations in the baseline activity can lead to enhanced information transfer of a weak signal by means of noise shaping of the background noise spectrum. We also show that an enhancement is not compulsory—for a stimulus with power exclusively at high frequencies, the renewal model can transfer more information than the nonrenewal model does. We discuss the application of our analytical results to other problems in neuroscience. Our results are also relevant to the general problem of how a signal affects the power spectrum of a nonlinear stochastic system. PMID:16196608

  4. Study on the Hippocampal Neuron's Minimal Models' Discharge Patterns

    Directory of Open Access Journals (Sweden)

    Yueping Peng

    2011-06-01

    Full Text Available The hippocampal CA1 pyramid neuron has plenty of discharge actions. The one-compartment model of CA1 pyramid neuron developed by David is a nine-dimension complex dynamic model. In the thesis, the currents related to the nine-dimension complex model are analyzed and classified by the model’s reduction theory and methods based on neurodynamics, and four minimal models are gotten: (I_Na+I_Kdr-minimal model, (I_Na+I_M-minimal model, (I_Na+I_Ca+I_y-minimal model, and (I_Na+I_Ca+I_sAHP-minimal model. These minimal models have plenty of dynamic actions, and under the current’s stimulation, they can all generate regular discharge and have period discharge pattern, bursting pattern, the chaos discharge pattern, and so on. Compared with the initial nine-dimension complex model, these minimal models’ dimension are much reduced, and are more convenient to numerical simulation, calculating, and analyzing. In addition, these minimal models provide a simpler and flexible method to discuss the specific currents’ dynamic characteristics and functions of the initial nine-dimension complex model by the theory of neurodynamics.

  5. Neuron-specific antioxidant OXR1 extends survival of a mouse model of amyotrophic lateral sclerosis.

    Science.gov (United States)

    Liu, Kevin X; Edwards, Benjamin; Lee, Sheena; Finelli, Mattéa J; Davies, Ben; Davies, Kay E; Oliver, Peter L

    2015-05-01

    Amyotrophic lateral sclerosis is a devastating neurodegenerative disorder characterized by the progressive loss of spinal motor neurons. While the aetiological mechanisms underlying the disease remain poorly understood, oxidative stress is a central component of amyotrophic lateral sclerosis and contributes to motor neuron injury. Recently, oxidation resistance 1 (OXR1) has emerged as a critical regulator of neuronal survival in response to oxidative stress, and is upregulated in the spinal cord of patients with amyotrophic lateral sclerosis. Here, we tested the hypothesis that OXR1 is a key neuroprotective factor during amyotrophic lateral sclerosis pathogenesis by crossing a new transgenic mouse line that overexpresses OXR1 in neurons with the SOD1(G93A) mouse model of amyotrophic lateral sclerosis. Interestingly, we report that overexpression of OXR1 significantly extends survival, improves motor deficits, and delays pathology in the spinal cord and in muscles of SOD1(G93A) mice. Furthermore, we find that overexpression of OXR1 in neurons significantly delays non-cell-autonomous neuroinflammatory response, classic complement system activation, and STAT3 activation through transcriptomic analysis of spinal cords of SOD1(G93A) mice. Taken together, these data identify OXR1 as the first neuron-specific antioxidant modulator of pathogenesis and disease progression in SOD1-mediated amyotrophic lateral sclerosis, and suggest that OXR1 may serve as a novel target for future therapeutic strategies. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain.

  6. Theoretical analysis of transcranial magneto-acoustical stimulation with Hodgkin–Huxley neuron model

    Directory of Open Access Journals (Sweden)

    Yi eYuan

    2016-04-01

    Full Text Available Transcranial magneto-acoustical stimulation (TMAS is a novel stimulation technology in which an ultrasonic wave within a magnetostatic field generates an electric current in an area of interest in the brain to modulate neuronal activities. As a key part of the neural network, neurons transmit information in the nervous system. However, the effect of TMAS on the neuronal firing rhythm remains unknown. To address this problem, we investigated the stimulatory mechanism of TMAS on neurons with a Hodgkin-Huxley neuron model. The simulation results indicate that the magnetostatic field intensity and ultrasonic power can affect the amplitude and interspike interval of neuronal action potential under continuous wave ultrasound. The simulation results also show that the ultrasonic power, duty cycle and repetition frequency can alter the firing rhythm of neural action potential under pulsed ultrasound. This study can help to reveal and explain the biological mechanism of TMAS and to provide a theoretical basis for TMAS in the treatment or rehabilitation of neuropsychiatric disorders.

  7. Theoretical Analysis of Transcranial Magneto-Acoustical Stimulation with Hodgkin-Huxley Neuron Model.

    Science.gov (United States)

    Yuan, Yi; Chen, Yudong; Li, Xiaoli

    2016-01-01

    Transcranial magneto-acoustical stimulation (TMAS) is a novel stimulation technology in which an ultrasonic wave within a magnetostatic field generates an electric current in an area of interest in the brain to modulate neuronal activities. As a key part of the neural network, neurons transmit information in the nervous system. However, the effect of TMAS on the neuronal firing pattern remains unknown. To address this problem, we investigated the stimulatory mechanism of TMAS on neurons, by using a Hodgkin-Huxley neuron model. The simulation results indicated that the magnetostatic field intensity and ultrasonic power affect the amplitude and interspike interval of neuronal action potential under a continuous wave ultrasound. The simulation results also showed that the ultrasonic power, duty cycle and repetition frequency can alter the firing pattern of neural action potential under pulsed wave ultrasound. This study may help to reveal and explain the biological mechanism of TMAS and to provide a theoretical basis for TMAS in the treatment or rehabilitation of neuropsychiatric disorders.

  8. Decoupling kinematics and mechanics reveals coding properties of trigeminal ganglion neurons in the rat vibrissal system.

    Science.gov (United States)

    Bush, Nicholas E; Schroeder, Christopher L; Hobbs, Jennifer A; Yang, Anne Et; Huet, Lucie A; Solla, Sara A; Hartmann, Mitra Jz

    2016-06-27

    Tactile information available to the rat vibrissal system begins as external forces that cause whisker deformations, which in turn excite mechanoreceptors in the follicle. Despite the fundamental mechanical origin of tactile information, primary sensory neurons in the trigeminal ganglion (Vg) have often been described as encoding the kinematics (geometry) of object contact. Here we aimed to determine the extent to which Vg neurons encode the kinematics vs. mechanics of contact. We used models of whisker bending to quantify mechanical signals (forces and moments) at the whisker base while simultaneously monitoring whisker kinematics and recording single Vg units in both anesthetized rats and awake, body restrained rats. We employed a novel manual stimulation technique to deflect whiskers in a way that decouples kinematics from mechanics, and used Generalized Linear Models (GLMs) to show that Vg neurons more directly encode mechanical signals when the whisker is deflected in this decoupled stimulus space.

  9. A robust cellular associative memory for pattern recognitions using composite trigonometric chaotic neuron models

    Directory of Open Access Journals (Sweden)

    Wimol San-Um

    2015-12-01

    Full Text Available This paper presents a robust cellular associative memory for pattern recognitions using composite trigonometric chaotic neuron models. Robust chaotic neurons are designed through a scan of positive Lyapunov Exponent (LE bifurcation structures, which indicate the quantitative measure of chaoticity for one-dimensional discrete-time dynamical systems. The proposed chaotic neuron model is a composite of sine and cosine chaotic maps, which are independent from the output activation function. Dynamics behaviors are demonstrated through bifurcation diagrams and LE-based bifurcation structures. An application to associative memories of binary patterns in Cellular Neural Networks (CNN topology is demonstrated using a signum output activation function. Examples of English alphabets are stored using symmetric auto-associative matrix of n-binary patterns. Simulation results have demonstrated that the cellular neural network can quickly and effectively restore the distorted pattern to expected information.

  10. Epileptic syndrome in systemic lupus erythematosus and neuronal autoantibody associations.

    Science.gov (United States)

    Kampylafka, E I; Alexopoulos, H; Fouka, P; Moutsopoulos, H M; Dalakas, M C; Tzioufas, A G

    2016-10-01

    We investigated systemic lupus erythematosus (SLE) patients with epilepsy, a major and organic neurological symptom. Our aim was to test patients for the autoimmune epilepsy-associated antibodies anti-GAD, anti-NMDAR, anti-AMPAR1/2, anti-GABABR and anti-VGKC. We tested sera from ten SLE patients with current or previous episodes of epileptic seizures. In addition, sera were tested for staining on primary hippocampal neurons. The patients' clinical and neuroimaging profile, disease activity and accumulated damage scores and therapeutic regimens administered were recorded, and correlations were evaluated. Patients were negative for all anti-neuronal autoantibodies tested, and showed no staining on primary hippocampal cells, which suggests the absence of autoantibodies against neuronal cell surface antigens. Epileptic seizures were all tonic-clonic, and all patients had high disease activity (mean SLE Damage Acticity Index score 19.3 ± 7.3). Six patients had minor or no brain magnetic resonance imaging findings, and three had major findings. 9/10 patients received immunosuppression for 5 ± 4 months, while anti-convulsive treatment was administered to all patients (4.2 ± 3 years). Our results suggest that the majority of SLE-related epileptic seizures cannot be attributed to the action of a single antibody against neuronal antigens. Studies with larger neuropsychiatric SLE populations and stricter inclusion criteria are necessary to verify these findings. © The Author(s) 2016.

  11. Isotocin neuronal phenotypes differ among social systems in cichlid fishes

    Science.gov (United States)

    O'Connor, Constance M.; Nesjan, Erin; Cameron, Jason; Hellmann, Jennifer K.; Ligocki, Isaac Y.; Marsh-Rollo, Susan E.; Hamilton, Ian M.; Wylie, Douglas R.; Hurd, Peter L.; Balshine, Sigal

    2017-01-01

    Social living has evolved numerous times across a diverse array of animal taxa. An open question is how the transition to a social lifestyle has shaped, and been shaped by, the underlying neurohormonal machinery of social behaviour. The nonapeptide neurohormones, implicated in the regulation of social behaviours, are prime candidates for the neuroendocrine substrates of social evolution. Here, we examined the brains of eight cichlid fish species with divergent social systems, comparing the number and size of preoptic neurons that express the nonapeptides isotocin and vasotocin. While controlling for the influence of phylogeny and body size, we found that the highly social cooperatively breeding species (n = 4) had fewer parvocellular isotocin neurons than the less social independently breeding species (n = 4), suggesting that the evolutionary transition to group living and cooperative breeding was associated with a reduction in the number of these neurons. In a complementary analysis, we found that the size and number of isotocin neurons significantly differentiated the cooperatively breeding from the independently breeding species. Our results suggest that isotocin is related to sociality in cichlids and may provide a mechanistic substrate for the evolution of sociality. PMID:28573041

  12. A neuron model of stochastic resonance using rectangular pulse trains.

    Science.gov (United States)

    Danziger, Zachary; Grill, Warren M

    2015-02-01

    Stochastic resonance (SR) is the enhanced representation of a weak input signal by the addition of an optimal level of broadband noise to a nonlinear (threshold) system. Since its discovery in the 1980s the domain of input signals shown to be applicable to SR has greatly expanded, from strictly periodic inputs to now nearly any aperiodic forcing function. The perturbations (noise) used to generate SR have also expanded, from white noise to now colored noise or vibrational forcing. This study demonstrates that a new class of perturbations can achieve SR, namely, series of stochastically generated biphasic pulse trains. Using these pulse trains as 'noise' we show that a Hodgkin Huxley model neuron exhibits SR behavior when detecting weak input signals. This result is of particular interest to neuroscience because nearly all artificial neural stimulation is implemented with square current or voltage pulses rather than broadband noise, and this new method may facilitate the translation of the performance gains achievable through SR to neural prosthetics.

  13. Improvement and Realization of Neuron PSD Control in Servo-Control System

    Institute of Scientific and Technical Information of China (English)

    JIAO Bin; GU Xin-sheng

    2005-01-01

    Neuron PSD (proportion, sum and differentiation) controller has the ability of on-line change of weights to reach the purpose of regulating parameters of PID using neuron's self-studying and self-organization and the change of controlled plant, which overcomes the disadvantages of affecting a conventional PID's accurate regulation because of the change of load, model and non-linearity. LF2407 DSP can reach the purpose of parallel running by using multi-sets of bus. So it can greatly increase operation speed and offer a set of flexible instruction system.The realization of PSD control on DSP can build an ideal electrical machine controller.

  14. Identification of neuronal and angiogenic growth factors in an in vitro blood-brain barrier model system: Relevance in barrier integrity and tight junction formation and complexity.

    Science.gov (United States)

    Freese, Christian; Hanada, Sanshiro; Fallier-Becker, Petra; Kirkpatrick, C James; Unger, Ronald E

    2017-05-01

    We previously demonstrated that the co-cultivation of endothelial cells with neural cells resulted in an improved integrity of the in vitro blood-brain barrier (BBB), and that this model could be useful to evaluate the transport properties of potential central nervous system disease drugs through the microvascular brain endothelial. In this study we have used real-time PCR, fluorescent microscopy, protein arrays and enzyme-linked immunosorbent assays to determine which neural- and endothelial cell-derived factors are produced in the co-culture and improve the integrity of the BBB. In addition, a further improvement of the BBB integrity was achieved by adjusting serum concentrations and growth factors or by the addition of brain pericytes. Under specific conditions expression of angiogenic, angiostatic and neurotrophic factors such as endostatin, pigment epithelium derived factor (PEDF/serpins-F1), tissue inhibitor of metalloproteinases (TIMP-1), and vascular endothelial cell growth factor (VEGF) closely mimicked the in vivo situation. Freeze-fracture analysis of these cultures demonstrated the quality and organization of the endothelial tight junction structures and their association to the two different lipidic leaflets of the membrane. Finally, a multi-cell culture model of the BBB with a transendothelial electrical resistance up to 371 (±15) Ω×cm(2) was developed, which may be useful for preliminary screening of drug transport across the BBB and to evaluate cellular crosstalk of cells involved in the neurovascular unit.

  15. Six types of multistability in a neuronal model based on slow calcium current.

    Directory of Open Access Journals (Sweden)

    Tatiana Malashchenko

    Full Text Available BACKGROUND: Multistability of oscillatory and silent regimes is a ubiquitous phenomenon exhibited by excitable systems such as neurons and cardiac cells. Multistability can play functional roles in short-term memory and maintaining posture. It seems to pose an evolutionary advantage for neurons which are part of multifunctional Central Pattern Generators to possess multistability. The mechanisms supporting multistability of bursting regimes are not well understood or classified. METHODOLOGY/PRINCIPAL FINDINGS: Our study is focused on determining the bio-physical mechanisms underlying different types of co-existence of the oscillatory and silent regimes observed in a neuronal model. We develop a low-dimensional model typifying the dynamics of a single leech heart interneuron. We carry out a bifurcation analysis of the model and show that it possesses six different types of multistability of dynamical regimes. These types are the co-existence of 1 bursting and silence, 2 tonic spiking and silence, 3 tonic spiking and subthreshold oscillations, 4 bursting and subthreshold oscillations, 5 bursting, subthreshold oscillations and silence, and 6 bursting and tonic spiking. These first five types of multistability occur due to the presence of a separating regime that is either a saddle periodic orbit or a saddle equilibrium. We found that the parameter range wherein multistability is observed is limited by the parameter values at which the separating regimes emerge and terminate. CONCLUSIONS: We developed a neuronal model which exhibits a rich variety of different types of multistability. We described a novel mechanism supporting the bistability of bursting and silence. This neuronal model provides a unique opportunity to study the dynamics of networks with neurons possessing different types of multistability.

  16. Estimation of the input parameters in the Feller neuronal model

    Science.gov (United States)

    Ditlevsen, Susanne; Lansky, Petr

    2006-06-01

    The stochastic Feller neuronal model is studied, and estimators of the model input parameters, depending on the firing regime of the process, are derived. Closed expressions for the first two moments of functionals of the first-passage time (FTP) through a constant boundary in the suprathreshold regime are derived, which are used to calculate moment estimators. In the subthreshold regime, the exponentiality of the FTP is utilized to characterize the input parameters. The methods are illustrated on simulated data. Finally, approximations of the first-passage-time moments are suggested, and biological interpretations and comparisons of the parameters in the Feller and the Ornstein-Uhlenbeck models are discussed.

  17. Silencing neuronal mutant androgen receptor in a mouse model of spinal and bulbar muscular atrophy.

    Science.gov (United States)

    Sahashi, Kentaro; Katsuno, Masahisa; Hung, Gene; Adachi, Hiroaki; Kondo, Naohide; Nakatsuji, Hideaki; Tohnai, Genki; Iida, Madoka; Bennett, C Frank; Sobue, Gen

    2015-11-01

    Spinal and bulbar muscular atrophy (SBMA), an adult-onset neurodegenerative disease that affects males, results from a CAG triplet repeat/polyglutamine expansions in the androgen receptor (AR) gene. Patients develop progressive muscular weakness and atrophy, and no effective therapy is currently available. The tissue-specific pathogenesis, especially relative pathological contributions between degenerative motor neurons and muscles, remains inconclusive. Though peripheral pathology in skeletal muscle caused by toxic AR protein has been recently reported to play a pivotal role in the pathogenesis of SBMA using mouse models, the role of motor neuron degeneration in SBMA has not been rigorously investigated. Here, we exploited synthetic antisense oligonucleotides to inhibit the RNA levels of mutant AR in the central nervous system (CNS) and explore its therapeutic effects in our SBMA mouse model that harbors a mutant AR gene with 97 CAG expansions and characteristic SBMA-like neurogenic phenotypes. A single intracerebroventricular administration of the antisense oligonucleotides in the presymptomatic phase efficiently suppressed the mutant gene expression in the CNS, and delayed the onset and progression of motor dysfunction, improved body weight gain and survival with the amelioration of neuronal histopathology in motor units such as spinal motor neurons, neuromuscular junctions and skeletal muscle. These findings highlight the importance of the neurotoxicity of mutant AR protein in motor neurons as a therapeutic target.

  18. Hopf bifurcation of an (n + 1) -neuron bidirectional associative memory neural network model with delays.

    Science.gov (United States)

    Xiao, Min; Zheng, Wei Xing; Cao, Jinde

    2013-01-01

    Recent studies on Hopf bifurcations of neural networks with delays are confined to simplified neural network models consisting of only two, three, four, five, or six neurons. It is well known that neural networks are complex and large-scale nonlinear dynamical systems, so the dynamics of the delayed neural networks are very rich and complicated. Although discussing the dynamics of networks with a few neurons may help us to understand large-scale networks, there are inevitably some complicated problems that may be overlooked if simplified networks are carried over to large-scale networks. In this paper, a general delayed bidirectional associative memory neural network model with n + 1 neurons is considered. By analyzing the associated characteristic equation, the local stability of the trivial steady state is examined, and then the existence of the Hopf bifurcation at the trivial steady state is established. By applying the normal form theory and the center manifold reduction, explicit formulae are derived to determine the direction and stability of the bifurcating periodic solution. Furthermore, the paper highlights situations where the Hopf bifurcations are particularly critical, in the sense that the amplitude and the period of oscillations are very sensitive to errors due to tolerances in the implementation of neuron interconnections. It is shown that the sensitivity is crucially dependent on the delay and also significantly influenced by the feature of the number of neurons. Numerical simulations are carried out to illustrate the main results.

  19. Bursting and Synchrony in Networks of Model Neurons

    CERN Document Server

    Geier, Christian; Elger, Christian E; Lehnertz, Klaus

    2016-01-01

    Bursting neurons are considered to be a potential cause of over-excitability and seizure susceptibility. The functional influence of these neurons in extended epileptic networks is still poorly understood. There is mounting evidence that the dynamics of neuronal networks is influenced not only by neuronal and synaptic properties but also by network topology. We investigate numerically the influence of different neuron dynamics on global synchrony in neuronal networks with complex connection topologies.

  20. Neuronal histaminergic system in aging and age-related neurodegenerative disorders.

    Science.gov (United States)

    Shan, Ling; Swaab, Dick F; Bao, Ai-Min

    2013-07-01

    The neuronal histaminergic system is involved in many physiological functions and is severely affected in age-related neurodegenerative diseases such as Parkinson's disease (PD) and Alzheimer's disease (AD). The properties of the neuronal histaminergic system in experimental animals and the alterations observed in postmortem brain material of PD or AD patients are reviewed. The production of neuronal histamine shows diurnal fluctuations in control subjects who had no neuropsychiatric disorders, while this fluctuation was strongly altered in patients with neurodegenerative diseases, including PD and AD. In addition, different alterations shown as expression levels of histidine decarboxylase (the key enzyme for histamine production), histamine-methyltransferase (the histamine deactivating enzyme), and histamine receptors (H(1-4)R) were found in various neurodegenerative disorders. Discrepancies between results from animal models and postmortem human brain material studies have made clear that the validation of animal models is absolutely necessary and that studies on patients and human postmortem material are essential to understand the changes of neuronal histaminergic system occurring in neuropsychiatric disorders.

  1. Statistics of a neuron model driven by asymmetric colored noise.

    Science.gov (United States)

    Müller-Hansen, Finn; Droste, Felix; Lindner, Benjamin

    2015-02-01

    Irregular firing of neurons can be modeled as a stochastic process. Here we study the perfect integrate-and-fire neuron driven by dichotomous noise, a Markovian process that jumps between two states (i.e., possesses a non-Gaussian statistics) and exhibits nonvanishing temporal correlations (i.e., represents a colored noise). Specifically, we consider asymmetric dichotomous noise with two different transition rates. Using a first-passage-time formulation, we derive exact expressions for the probability density and the serial correlation coefficient of the interspike interval (time interval between two subsequent neural action potentials) and the power spectrum of the spike train. Furthermore, we extend the model by including additional Gaussian white noise, and we give approximations for the interspike interval (ISI) statistics in this case. Numerical simulations are used to validate the exact analytical results for pure dichotomous noise, and to test the approximations of the ISI statistics when Gaussian white noise is included. The results may help to understand how correlations and asymmetry of noise and signals in nerve cells shape neuronal firing statistics.

  2. Modeling the Influence of Ion Channels on Neuron Dynamics in Drosophila

    Directory of Open Access Journals (Sweden)

    Sandra eBerger

    2015-11-01

    Full Text Available Voltage gated ion channels play a major role in determining a neuron's firing behavior, resulting in the specific processing of synaptic input patterns. Drosophila and other invertebrates provide valuable model systems for investigating ion channel kinetics and their impact on firing properties. Despite the increasing importance of Drosophila as a model system, few computational models of its ion channel kinetics have been developed. In this study, experimentally observed biophysical properties of voltage gated ion channels from the fruitfly Drosophila melanogaster are used to develop a minimal, conductance based neuron model. We investigate the impact of the densities of these channels on the excitability of the model neuron. Changing the channel densities reproduces different in situ observed firing patterns and induces a switch from integrator to resonator properties. Further, we analyze the preference to input frequency and how it depends on the channel densities and the resulting bifurcation type the system undergoes. An extension to a three dimensional model demonstrates that the inactivation kinetics of the sodium channels play an important role, allowing for firing patterns with a delayed first spike and subsequent high frequency firing as often observed in invertebrates, without altering the delayed rectifier current.

  3. Human Brain Networks: Spiking Neuron Models, Multistability, Synchronization, Thermodynamics, Maximum Entropy Production, and Anesthetic Cascade Mechanisms

    Directory of Open Access Journals (Sweden)

    Wassim M. Haddad

    2014-07-01

    Full Text Available Advances in neuroscience have been closely linked to mathematical modeling beginning with the integrate-and-fire model of Lapicque and proceeding through the modeling of the action potential by Hodgkin and Huxley to the current era. The fundamental building block of the central nervous system, the neuron, may be thought of as a dynamic element that is “excitable”, and can generate a pulse or spike whenever the electrochemical potential across the cell membrane of the neuron exceeds a threshold. A key application of nonlinear dynamical systems theory to the neurosciences is to study phenomena of the central nervous system that exhibit nearly discontinuous transitions between macroscopic states. A very challenging and clinically important problem exhibiting this phenomenon is the induction of general anesthesia. In any specific patient, the transition from consciousness to unconsciousness as the concentration of anesthetic drugs increases is very sharp, resembling a thermodynamic phase transition. This paper focuses on multistability theory for continuous and discontinuous dynamical systems having a set of multiple isolated equilibria and/or a continuum of equilibria. Multistability is the property whereby the solutions of a dynamical system can alternate between two or more mutually exclusive Lyapunov stable and convergent equilibrium states under asymptotically slowly changing inputs or system parameters. In this paper, we extend the theory of multistability to continuous, discontinuous, and stochastic nonlinear dynamical systems. In particular, Lyapunov-based tests for multistability and synchronization of dynamical systems with continuously differentiable and absolutely continuous flows are established. The results are then applied to excitatory and inhibitory biological neuronal networks to explain the underlying mechanism of action for anesthesia and consciousness from a multistable dynamical system perspective, thereby providing a

  4. Recombinant AAV-mediated Expression of Human BDNF Protects Neurons against Cell Apoptosis in Aβ-induced Neuronal Damage Model

    Institute of Scientific and Technical Information of China (English)

    LIU Zhaohui; MA Dongliang; FENG Gaifeng; MA Yanbing; HU Haitao

    2007-01-01

    The human brain-derived neurotrophic factor (hBDNF) gene was cloned by polymerase chain reaction and the recombinant adeno-associated viral vector inserted with hBDNF gene (AAV-hBDNF) was constructed. Cultured rat hippocampal neurons were treated with Aβ25-35 and serued as the experimental Aβ-induced neuronal damage model (AD model), and the AD model was infected with AAV-hBDNF to explore neuroprotective effects of expression of BDNF. Cell viability was assayed by MTT. The expression of bcl-2 anti-apoptosis protein was detected by immunocytochemical staining. The change of intracellular free Ca ion ([Ca2+]i) was measured by laser scanning confocal microscopy. The results showed that BDNF had protective effects against Aβ-induced neuronal damage. The expression of the bcl-2 anti-apoptosis protein was raised significantly and the balance of [Ca2+]i was maintained in the AAV-hBDNF treatment group as compared with AD model group. These data suggested that recombinant AAV mediated a stable expression of hBDNF in cultured hippocampal neurons and resulted in significant neuron protective effects in AD model. The BDNF may reduce neuron apoptosis through increasing the expression of the bcl-2 anti-apoptosis protein and inhibiting intracellular calcium overload. The viral vector-mediated gene expression of BDNF may pave the way of a novel therapeutic strategy for the treatment of neurodegenerative diseases such as Alzheimer's disease.

  5. A hierarchical model for structure learning based on the physiological characteristics of neurons

    Institute of Scientific and Technical Information of China (English)

    WEI Hui

    2007-01-01

    Almost all applications of Artificial Neural Networks (ANNs) depend mainly on their memory ability.The characteristics of typical ANN models are fixed connections,with evolved weights,globalized representations,and globalized optimizations,all based on a mathematical approach.This makes those models to be deficient in robustness,efficiency of learning,capacity,anti-jamming between training sets,and correlativity of samples,etc.In this paper,we attempt to address these problems by adopting the characteristics of biological neurons in morphology and signal processing.A hierarchical neural network was designed and realized to implement structure learning and representations based on connected structures.The basic characteristics of this model are localized and random connections,field limitations of neuron fan-in and fan-out,dynamic behavior of neurons,and samples represented through different sub-circuits of neurons specialized into different response patterns.At the end of this paper,some important aspects of error correction,capacity,learning efficiency,and soundness of structural representation are analyzed theoretically.This paper has demonstrated the feasibility and advantages of structure learning and representation.This model can serve as a fundamental element of cognitive systems such as perception and associative memory.Key-words structure learning,representation,associative memory,computational neuroscience

  6. Optimal size of stochastic Hodgkin-Huxley neuronal systems for maximal energy efficiency in coding pulse signals

    Science.gov (United States)

    Yu, Lianchun; Liu, Liwei

    2014-03-01

    The generation and conduction of action potentials (APs) represents a fundamental means of communication in the nervous system and is a metabolically expensive process. In this paper, we investigate the energy efficiency of neural systems in transferring pulse signals with APs. By analytically solving a bistable neuron model that mimics the AP generation with a particle crossing the barrier of a double well, we find the optimal number of ion channels that maximizes the energy efficiency of a neuron. We also investigate the energy efficiency of a neuron population in which the input pulse signals are represented with synchronized spikes and read out with a downstream coincidence detector neuron. We find an optimal number of neurons in neuron population, as well as the number of ion channels in each neuron that maximizes the energy efficiency. The energy efficiency also depends on the characters of the input signals, e.g., the pulse strength and the interpulse intervals. These results are confirmed by computer simulation of the stochastic Hodgkin-Huxley model with a detailed description of the ion channel random gating. We argue that the tradeoff between signal transmission reliability and energy cost may influence the size of the neural systems when energy use is constrained.

  7. Breaking It Down: The Ubiquitin Proteasome System in Neuronal Morphogenesis

    Directory of Open Access Journals (Sweden)

    Andrew M. Hamilton

    2013-01-01

    Full Text Available The ubiquitin-proteasome system (UPS is most widely known for its role in intracellular protein degradation; however, in the decades since its discovery, ubiquitination has been associated with the regulation of a wide variety of cellular processes. The addition of ubiquitin tags, either as single moieties or as polyubiquitin chains, has been shown not only to mediate degradation by the proteasome and the lysosome, but also to modulate protein function, localization, and endocytosis. The UPS plays a particularly important role in neurons, where local synthesis and degradation work to balance synaptic protein levels at synapses distant from the cell body. In recent years, the UPS has come under increasing scrutiny in neurons, as elements of the UPS have been found to regulate such diverse neuronal functions as synaptic strength, homeostatic plasticity, axon guidance, and neurite outgrowth. Here we focus on recent advances detailing the roles of the UPS in regulating the morphogenesis of axons, dendrites, and dendritic spines, with an emphasis on E3 ubiquitin ligases and their identified regulatory targets.

  8. Application of Artificial Neuron Network in Modeling Thermal Crystallization Kinetics of Multi - solvent System%人工神经网络在多元溶剂体系结晶热力学建模中的应用

    Institute of Scientific and Technical Information of China (English)

    朱亮; 袁建军; 沙作良; 王彦飞; 杨立斌; 贺华

    2011-01-01

    以磷酸二氢钾在水和丙酮二元溶剂中的溶解度数据为基础,采用人工神经网络建立了一个多元溶剂体系的结晶热力学模型.结果表明:用此技术建立的模型克服了传统结晶热力学模型只能预测溶解度随单一影响因素变化趋势的缺点,能直接精确预测溶解度随温度和溶剂比等影响因素同时变化时的数据.%A neuron network model was developed to predict thermal crystallization kinetics of multi - solvent system, based on the solubility data of potassium dihydrogen phosphate in dual solvents of water and-acetone. The results indicate that this model is able to predict the thermal crystallization kinetics data of multi - solvent directly with high accuracy, overcome the weakness of traditional thermal kinetics methods.

  9. Ablation of sensory neurons in a genetic model of pancreatic ductal adenocarcinoma slows initiation and progression of cancer.

    Science.gov (United States)

    Saloman, Jami L; Albers, Kathryn M; Li, Dongjun; Hartman, Douglas J; Crawford, Howard C; Muha, Emily A; Rhim, Andrew D; Davis, Brian M

    2016-03-15

    Pancreatic ductal adenocarcinoma (PDAC) is characterized by an exuberant inflammatory desmoplastic response. The PDAC microenvironment is complex, containing both pro- and antitumorigenic elements, and remains to be fully characterized. Here, we show that sensory neurons, an under-studied cohort of the pancreas tumor stroma, play a significant role in the initiation and progression of the early stages of PDAC. Using a well-established autochthonous model of PDAC (PKC), we show that inflammation and neuronal damage in the peripheral and central nervous system (CNS) occurs as early as the pancreatic intraepithelial neoplasia (PanIN) 2 stage. Also at the PanIN2 stage, pancreas acinar-derived cells frequently invade along sensory neurons into the spinal cord and migrate caudally to the lower thoracic and upper lumbar regions. Sensory neuron ablation by neonatal capsaicin injection prevented perineural invasion (PNI), astrocyte activation, and neuronal damage, suggesting that sensory neurons convey inflammatory signals from Kras-induced pancreatic neoplasia to the CNS. Neuron ablation in PKC mice also significantly delayed PanIN formation and ultimately prolonged survival compared with vehicle-treated controls (median survival, 7.8 vs. 4.5 mo; P = 0.001). These data establish a reciprocal signaling loop between the pancreas and nervous system, including the CNS, that supports inflammation associated with oncogenic Kras-induced neoplasia. Thus, pancreatic sensory neurons comprise an important stromal cell population that supports the initiation and progression of PDAC and may represent a potential target for prevention in high-risk populations.

  10. Micro fluidic System for Culturing and Monitoring of Neuronal Cells and Tissue

    DEFF Research Database (Denmark)

    Bakmand, Tanya; Waagepetersen, Helle S.

    . Tests show that the function of neurons cultured on PNWs lies closer to neurons in vivo than neurons cultured on conventional plastic substrates. The second part of the thesis describes a fluidic system for culturing of brain slices. It describes the fabrication and use of the system as well as results...... for culturing of brain tissue. The second goal was to develop a sensor system with the potential for incorporation into both conventional culture systems and fluidic culturing systems. The third and final goal of this project was to develop a system for culturing of neuronal cells with the possibility...... neuronal cells on a Peptide Nano Wires (PNW) modified substrate aiming to bring conventional neuronal cultures closer to mimic the in vivo situation. The work describes both the fabrication of the culture substrates and results comparing the performance of PNWcultured neurons and conventional cultures...

  11. The dynamical analysis of modified two-compartment neuron model and FPGA implementation

    Science.gov (United States)

    Lin, Qianjin; Wang, Jiang; Yang, Shuangming; Yi, Guosheng; Deng, Bin; Wei, Xile; Yu, Haitao

    2017-10-01

    The complexity of neural models is increasing with the investigation of larger biological neural network, more various ionic channels and more detailed morphologies, and the implementation of biological neural network is a task with huge computational complexity and power consumption. This paper presents an efficient digital design using piecewise linearization on field programmable gate array (FPGA), to succinctly implement the reduced two-compartment model which retains essential features of more complicated models. The design proposes an approximate neuron model which is composed of a set of piecewise linear equations, and it can reproduce different dynamical behaviors to depict the mechanisms of a single neuron model. The consistency of hardware implementation is verified in terms of dynamical behaviors and bifurcation analysis, and the simulation results including varied ion channel characteristics coincide with the biological neuron model with a high accuracy. Hardware synthesis on FPGA demonstrates that the proposed model has reliable performance and lower hardware resource compared with the original two-compartment model. These investigations are conducive to scalability of biological neural network in reconfigurable large-scale neuromorphic system.

  12. Lateral Information Processing by Spiking Neurons: A Theoretical Model of the Neural Correlate of Consciousness

    Directory of Open Access Journals (Sweden)

    Marc Ebner

    2011-01-01

    Full Text Available Cognitive brain functions, for example, sensory perception, motor control and learning, are understood as computation by axonal-dendritic chemical synapses in networks of integrate-and-fire neurons. Cognitive brain functions may occur either consciously or nonconsciously (on “autopilot”. Conscious cognition is marked by gamma synchrony EEG, mediated largely by dendritic-dendritic gap junctions, sideways connections in input/integration layers. Gap-junction-connected neurons define a sub-network within a larger neural network. A theoretical model (the “conscious pilot” suggests that as gap junctions open and close, a gamma-synchronized subnetwork, or zone moves through the brain as an executive agent, converting nonconscious “auto-pilot” cognition to consciousness, and enhancing computation by coherent processing and collective integration. In this study we implemented sideways “gap junctions” in a single-layer artificial neural network to perform figure/ground separation. The set of neurons connected through gap junctions form a reconfigurable resistive grid or sub-network zone. In the model, outgoing spikes are temporally integrated and spatially averaged using the fixed resistive grid set up by neurons of similar function which are connected through gap-junctions. This spatial average, essentially a feedback signal from the neuron's output, determines whether particular gap junctions between neurons will open or close. Neurons connected through open gap junctions synchronize their output spikes. We have tested our gap-junction-defined sub-network in a one-layer neural network on artificial retinal inputs using real-world images. Our system is able to perform figure/ground separation where the laterally connected sub-network of neurons represents a perceived object. Even though we only show results for visual stimuli, our approach should generalize to other modalities. The system demonstrates a moving sub-network zone of

  13. Single Gaussian Chaotic Neuron: Numerical Study and Implementation in an Embedded System

    Directory of Open Access Journals (Sweden)

    Luis M. Torres-Treviño

    2013-01-01

    Full Text Available Artificial Gaussian neurons are very common structures of artificial neural networks like radial basis function. These artificial neurons use a Gaussian activation function that includes two parameters called the center of mass (cm and sensibility factor (λ. Changes on these parameters determine the behavior of the neuron. When the neuron has a feedback output, complex chaotic behavior is displayed. This paper presents a study and implementation of this particular neuron. Stability of fixed points, bifurcation diagrams, and Lyapunov exponents help to determine the dynamical nature of the neuron, and its implementation on embedded system illustrates preliminary results toward embedded chaos computation.

  14. Dynamical System Approach for Edge Detection Using Coupled FitzHugh-Nagumo Neurons.

    Science.gov (United States)

    Li, Shaobai; Dasmahapatra, Srinandan; Maharatna, Koushik

    2015-12-01

    The prospect of emulating the impressive computational capabilities of biological systems has led to considerable interest in the design of analog circuits that are potentially implementable in very large scale integration CMOS technology and are guided by biologically motivated models. For example, simple image processing tasks, such as the detection of edges in binary and grayscale images, have been performed by networks of FitzHugh-Nagumo-type neurons using the reaction-diffusion models. However, in these studies, the one-to-one mapping of image pixels to component neurons makes the size of the network a critical factor in any such implementation. In this paper, we develop a simplified version of the employed reaction-diffusion model in three steps. In the first step, we perform a detailed study to locate this threshold using continuous Lyapunov exponents from dynamical system theory. Furthermore, we render the diffusion in the system to be anisotropic, with the degree of anisotropy being set by the gradients of grayscale values in each image. The final step involves a simplification of the model that is achieved by eliminating the terms that couple the membrane potentials of adjacent neurons. We apply our technique to detect edges in data sets of artificially generated and real images, and we demonstrate that the performance is as good if not better than that of the previous methods without increasing the size of the network.

  15. Chimera-like states in a neuronal network model of the cat brain

    Science.gov (United States)

    Santos, M. S.; Szezech, J. D.; Borges, F. S.; Iarosz, K. C.; Caldas, I. L.; Batista, A. M.; Viana, R. L.; Kurths, J.

    2017-08-01

    Neuronal systems have been modeled by complex networks in different description levels. Recently, it has been verified that networks can simultaneously exhibit one coherent and other incoherent domain, known as chimera states. In this work, we study the existence of chimera states in a network considering the connectivity matrix based on the cat cerebral cortex. The cerebral cortex of the cat can be separated in 65 cortical areas organised into the four cognitive regions: visual, auditory, somatosensory-motor and frontolimbic. We consider a network where the local dynamics is given by the Hindmarsh-Rose model. The Hindmarsh-Rose equations are a well known model of neuronal activity that has been considered to simulate membrane potential in neuron. Here, we analyse under which conditions chimera states are present, as well as the affects induced by intensity of coupling on them. We observe the existence of chimera states in that incoherent structure can be composed of desynchronised spikes or desynchronised bursts. Moreover, we find that chimera states with desynchronised bursts are more robust to neuronal noise than with desynchronised spikes.

  16. View-Invariant Visuomotor Processing in Computational Mirror Neuron System for Humanoid.

    Science.gov (United States)

    Dawood, Farhan; Loo, Chu Kiong

    2016-01-01

    Mirror neurons are visuo-motor neurons found in primates and thought to be significant for imitation learning. The proposition that mirror neurons result from associative learning while the neonate observes his own actions has received noteworthy empirical support. Self-exploration is regarded as a procedure by which infants become perceptually observant to their own body and engage in a perceptual communication with themselves. We assume that crude sense of self is the prerequisite for social interaction. However, the contribution of mirror neurons in encoding the perspective from which the motor acts of others are seen have not been addressed in relation to humanoid robots. In this paper we present a computational model for development of mirror neuron system for humanoid based on the hypothesis that infants acquire MNS by sensorimotor associative learning through self-exploration capable of sustaining early imitation skills. The purpose of our proposed model is to take into account the view-dependency of neurons as a probable outcome of the associative connectivity between motor and visual information. In our experiment, a humanoid robot stands in front of a mirror (represented through self-image using camera) in order to obtain the associative relationship between his own motor generated actions and his own visual body-image. In the learning process the network first forms mapping from each motor representation onto visual representation from the self-exploratory perspective. Afterwards, the representation of the motor commands is learned to be associated with all possible visual perspectives. The complete architecture was evaluated by simulation experiments performed on DARwIn-OP humanoid robot.

  17. View-Invariant Visuomotor Processing in Computational Mirror Neuron System for Humanoid.

    Directory of Open Access Journals (Sweden)

    Farhan Dawood

    Full Text Available Mirror neurons are visuo-motor neurons found in primates and thought to be significant for imitation learning. The proposition that mirror neurons result from associative learning while the neonate observes his own actions has received noteworthy empirical support. Self-exploration is regarded as a procedure by which infants become perceptually observant to their own body and engage in a perceptual communication with themselves. We assume that crude sense of self is the prerequisite for social interaction. However, the contribution of mirror neurons in encoding the perspective from which the motor acts of others are seen have not been addressed in relation to humanoid robots. In this paper we present a computational model for development of mirror neuron system for humanoid based on the hypothesis that infants acquire MNS by sensorimotor associative learning through self-exploration capable of sustaining early imitation skills. The purpose of our proposed model is to take into account the view-dependency of neurons as a probable outcome of the associative connectivity between motor and visual information. In our experiment, a humanoid robot stands in front of a mirror (represented through self-image using camera in order to obtain the associative relationship between his own motor generated actions and his own visual body-image. In the learning process the network first forms mapping from each motor representation onto visual representation from the self-exploratory perspective. Afterwards, the representation of the motor commands is learned to be associated with all possible visual perspectives. The complete architecture was evaluated by simulation experiments performed on DARwIn-OP humanoid robot.

  18. Mirror neuron system based therapy for emotional disorders.

    Science.gov (United States)

    Yuan, Ti-Fei; Hoff, Robert

    2008-11-01

    Mirror neuron system (MNS) represents one of the most important discoveries in the area of neuropsychology of past decades. More than 500 papers have been published in this area (PubMed), and the major functions of MNS include action understanding, imitation, empathy, all of which are critical for an individual to be social. Recent studies suggested that MNS can modulate emotion states possibly through the empathy mechanism. Here we propose that MNS-based therapies provide a non-invasive approach in treatments to emotional disorders that were observed in autism patients, post-stroke patients with depression as well as other mood dysregulation conditions.

  19. Computational modeling of seizure dynamics using coupled neuronal networks: factors shaping epileptiform activity.

    Directory of Open Access Journals (Sweden)

    Sebastien Naze

    2015-05-01

    Full Text Available Epileptic seizure dynamics span multiple scales in space and time. Understanding seizure mechanisms requires identifying the relations between seizure components within and across these scales, together with the analysis of their dynamical repertoire. Mathematical models have been developed to reproduce seizure dynamics across scales ranging from the single neuron to the neural population. In this study, we develop a network model of spiking neurons and systematically investigate the conditions, under which the network displays the emergent dynamic behaviors known from the Epileptor, which is a well-investigated abstract model of epileptic neural activity. This approach allows us to study the biophysical parameters and variables leading to epileptiform discharges at cellular and network levels. Our network model is composed of two neuronal populations, characterized by fast excitatory bursting neurons and regular spiking inhibitory neurons, embedded in a common extracellular environment represented by a slow variable. By systematically analyzing the parameter landscape offered by the simulation framework, we reproduce typical sequences of neural activity observed during status epilepticus. We find that exogenous fluctuations from extracellular environment and electro-tonic couplings play a major role in the progression of the seizure, which supports previous studies and further validates our model. We also investigate the influence of chemical synaptic coupling in the generation of spontaneous seizure-like events. Our results argue towards a temporal shift of typical spike waves with fast discharges as synaptic strengths are varied. We demonstrate that spike waves, including interictal spikes, are generated primarily by inhibitory neurons, whereas fast discharges during the wave part are due to excitatory neurons. Simulated traces are compared with in vivo experimental data from rodents at different stages of the disorder. We draw the conclusion

  20. A statistical method of identifying interactions in neuron-glia systems based on functional multicell Ca2+ imaging.

    Directory of Open Access Journals (Sweden)

    Ken Nakae

    2014-11-01

    Full Text Available Crosstalk between neurons and glia may constitute a significant part of information processing in the brain. We present a novel method of statistically identifying interactions in a neuron-glia network. We attempted to identify neuron-glia interactions from neuronal and glial activities via maximum-a-posteriori (MAP-based parameter estimation by developing a generalized linear model (GLM of a neuron-glia network. The interactions in our interest included functional connectivity and response functions. We evaluated the cross-validated likelihood of GLMs that resulted from the addition or removal of connections to confirm the existence of specific neuron-to-glia or glia-to-neuron connections. We only accepted addition or removal when the modification improved the cross-validated likelihood. We applied the method to a high-throughput, multicellular in vitro Ca2+ imaging dataset obtained from the CA3 region of a rat hippocampus, and then evaluated the reliability of connectivity estimates using a statistical test based on a surrogate method. Our findings based on the estimated connectivity were in good agreement with currently available physiological knowledge, suggesting our method can elucidate undiscovered functions of neuron-glia systems.

  1. Calcium, synaptic plasticity and intrinsic homeostasis in Purkinje neuron models

    Directory of Open Access Journals (Sweden)

    Pablo Achard

    2008-12-01

    Full Text Available We recently reproduced the complex electrical activity of a Purkinje cell (PC with very different combinations of ionic channel maximum conductances, suggesting that a large parameter space is available to homeostatic mechanisms. It has been hypothesized that cytoplasmic calcium concentrations control the homeostatic activity sensors. This raises many questions for PCs since in these neurons calcium plays an important role in the induction of synaptic plasticity. To address this question, we generated 148 new PC models. In these models the somatic membrane voltages are stable, but the somatic calcium dynamics are very variable, in agreement with experimental results. Conversely, the calcium signal in spiny dendrites shows only small variability. We demonstrate that this localized control of calcium conductances preserves the induction of long-term depression for all models. We conclude that calcium is unlikely to be the sole activity-sensor in this cell but that there is a strong relationship between activity homeostasis and synaptic plasticity.

  2. Neurokinin B and reproductive functions: "KNDy neuron" model in mammals and the emerging story in fish.

    Science.gov (United States)

    Hu, Guangfu; Lin, Chengyuan; He, Mulan; Wong, Anderson O L

    2014-11-01

    In mammals, neurokinin B (NKB), the gene product of the tachykinin family member TAC3, is known to be a key regulator for episodic release of luteinizing hormone (LH). Its regulatory actions are mediated by a subpopulation of kisspeptin neurons within the arcuate nucleus with co-expression of NKB and dynorphin A (commonly called the "KNDy neurons"). By forming an "autosynaptic feedback loop" within the hypothalamus, the KNDy neurons can modulate gonadotropin-releasing hormone (GnRH) pulsatility and subsequent LH release in the pituitary. NKB regulation of LH secretion has been recently demonstrated in zebrafish, suggesting that the reproductive functions of NKB may be conserved from fish to mammals. Interestingly, the TAC3 genes in fish not only encode the mature peptide of NKB but also a novel tachykinin-like peptide, namely NKB-related peptide (or neurokinin F). Recent studies in zebrafish also reveal that the neuroanatomy of TAC3/kisspeptin system within the fish brain is quite different from that of mammals. In this article, the current ideas of "KNDy neuron" model for GnRH regulation and steroid feedback, other reproductive functions of NKB including its local actions in the gonad and placenta, the revised model of tachykinin evolution from invertebrates to vertebrates, as well as the emerging story of the two TAC3 gene products in fish, NKB and NKB-related peptide, will be reviewed with stress on the areas with interesting questions for future investigations.

  3. Modeling the electric potential across neuronal membranes: the effect of fixed charges on spinal ganglion neurons and neuroblastoma cells.

    Directory of Open Access Journals (Sweden)

    Thiago M Pinto

    Full Text Available We present a model for the electric potential profile across the membranes of neuronal cells. We considered the resting and action potential states, and analyzed the influence of fixed charges of the membrane on its electric potential, based on experimental values of membrane properties of the spinal ganglion neuron and the neuroblastoma cell. The spinal ganglion neuron represents a healthy neuron, and the neuroblastoma cell, which is tumorous, represents a pathological neuron. We numerically solved the non-linear Poisson-Boltzmann equation for the regions of the membrane model we have adopted, by considering the densities of charges dissolved in an electrolytic solution and fixed on both glycocalyx and cytoplasmic proteins. Our model predicts that there is a difference in the behavior of the electric potential profiles of the two types of cells, in response to changes in charge concentrations in the membrane. Our results also describe an insensitivity of the neuroblastoma cell membrane, as observed in some biological experiments. This electrical property may be responsible for the low pharmacological response of the neuroblastoma to certain chemotherapeutic treatments.

  4. Modeling the electric potential across neuronal membranes: the effect of fixed charges on spinal ganglion neurons and neuroblastoma cells.

    Science.gov (United States)

    Pinto, Thiago M; Wedemann, Roseli S; Cortez, Célia M

    2014-01-01

    We present a model for the electric potential profile across the membranes of neuronal cells. We considered the resting and action potential states, and analyzed the influence of fixed charges of the membrane on its electric potential, based on experimental values of membrane properties of the spinal ganglion neuron and the neuroblastoma cell. The spinal ganglion neuron represents a healthy neuron, and the neuroblastoma cell, which is tumorous, represents a pathological neuron. We numerically solved the non-linear Poisson-Boltzmann equation for the regions of the membrane model we have adopted, by considering the densities of charges dissolved in an electrolytic solution and fixed on both glycocalyx and cytoplasmic proteins. Our model predicts that there is a difference in the behavior of the electric potential profiles of the two types of cells, in response to changes in charge concentrations in the membrane. Our results also describe an insensitivity of the neuroblastoma cell membrane, as observed in some biological experiments. This electrical property may be responsible for the low pharmacological response of the neuroblastoma to certain chemotherapeutic treatments.

  5. Programming and reprogramming neuronal subtypes in the central nervous system.

    Science.gov (United States)

    Rouaux, Caroline; Bhai, Salman; Arlotta, Paola

    2012-07-01

    Recent discoveries in nuclear reprogramming have challenged the dogma that the identity of terminally differentiated cells cannot be changed. The identification of molecular mechanisms that reprogram differentiated cells to a new identity carries profound implications for regenerative medicine across organ systems. The central nervous system (CNS) has historically been considered to be largely immutable. However, recent studies indicate that even the adult CNS is imparted with the potential to change under the appropriate stimuli. Here, we review current knowledge regarding the capability of distinct cells within the CNS to reprogram their identity and consider the role of developmental signals in directing these cell fate decisions. Finally, we discuss the progress and current challenges of using developmental signals to precisely direct the generation of individual neuronal subtypes in the postnatal CNS and in the dish.

  6. Dynamic neuronal ensembles: Issues in representing structure change in object-oriented, biologically-based brain models

    Energy Technology Data Exchange (ETDEWEB)

    Vahie, S.; Zeigler, B.P.; Cho, H. [Univ. of Arizona, Tucson, AZ (United States)

    1996-12-31

    This paper describes the structure of dynamic neuronal ensembles (DNEs). DNEs represent a new paradigm for learning, based on biological neural networks that use variable structures. We present a computational neural element that demonstrates biological neuron functionality such as neurotransmitter feedback absolute refractory period and multiple output potentials. More specifically, we will develop a network of neural elements that have the ability to dynamically strengthen, weaken, add and remove interconnections. We demonstrate that the DNE is capable of performing dynamic modifications to neuron connections and exhibiting biological neuron functionality. In addition to its applications for learning, DNEs provide an excellent environment for testing and analysis of biological neural systems. An example of habituation and hyper-sensitization in biological systems, using a neural circuit from a snail is presented and discussed. This paper provides an insight into the DNE paradigm using models developed and simulated in DEVS.

  7. Complementary processing of haptic information by slowly and rapidly adapting neurons in the trigeminothalamic pathway. Electrophysiology, mathematical modeling and simulations of vibrissae-related neurons.

    Directory of Open Access Journals (Sweden)

    Abel eSanchez-Jimenez

    2013-06-01

    Full Text Available Tonic (slowly adapting and phasic (rapidly adapting primary afferents convey complementary aspects of haptic information to the central nervous system: object location and texture the former, shape the latter. Tonic and phasic neural responses are also recorded in all relay stations of the somatosensory pathway, yet it is unknown their role in both, information processing and information transmission to the cortex: we don’t know if tonic and phasic neurons process complementary aspects of haptic information and/or if these two types constitute two separate channels that convey complementary aspects of tactile information to the cortex. Here we propose to elucidate these two questions in the fast trigeminal pathway of the rat (PrV-VPM: principal trigeminal nucleus-ventroposteromedial thalamic nucleus. We analyze early and global behavior, latencies and stability of the responses of individual cells in PrV and medial lemniscus under 1-40 Hz stimulation of the whiskers in control and decorticated animals and we use stochastic spiking models and extensive simulations. Our results strongly suggest that in the first relay station of the somatosensory system (PrV: 1 tonic and phasic neurons process complementary aspects of whisker-related tactile information 2 tonic and phasic responses are not originated from two different types of neurons 3 the two responses are generated by the differential action of the somatosensory cortex on a unique type of PrV cell 4 tonic and phasic neurons do not belong to two different channels for the transmission of tactile information to the thalamus 5 trigeminothalamic transmission is exclusively performed by tonically firing neurons and 6 all aspects of haptic information are coded into low-pass, band-pass and high-pass filtering profiles of tonically firing neurons. Our results are important for both, basic research on neural circuits and information processing, and development of sensory neuroprostheses.

  8. Complementary processing of haptic information by slowly and rapidly adapting neurons in the trigeminothalamic pathway. Electrophysiology, mathematical modeling and simulations of vibrissae-related neurons.

    Science.gov (United States)

    Sanchez-Jimenez, Abel; Torets, Carlos; Panetsos, Fivos

    2013-01-01

    TONIC (SLOWLY ADAPTING) AND PHASIC (RAPIDLY ADAPTING) PRIMARY AFFERENTS CONVEY COMPLEMENTARY ASPECTS OF HAPTIC INFORMATION TO THE CENTRAL NERVOUS SYSTEM: object location and texture the former, shape the latter. Tonic and phasic neural responses are also recorded in all relay stations of the somatosensory pathway, yet it is unknown their role in both, information processing and information transmission to the cortex: we don't know if tonic and phasic neurons process complementary aspects of haptic information and/or if these two types constitute two separate channels that convey complementary aspects of tactile information to the cortex. Here we propose to elucidate these two questions in the fast trigeminal pathway of the rat (PrV-VPM: principal trigeminal nucleus-ventroposteromedial thalamic nucleus). We analyze early and global behavior, latencies and stability of the responses of individual cells in PrV and medial lemniscus under 1-40 Hz stimulation of the whiskers in control and decorticated animals and we use stochastic spiking models and extensive simulations. Our results strongly suggest that in the first relay station of the somatosensory system (PrV): (1) tonic and phasic neurons process complementary aspects of whisker-related tactile information (2) tonic and phasic responses are not originated from two different types of neurons (3) the two responses are generated by the differential action of the somatosensory cortex on a unique type of PrV cell (4) tonic and phasic neurons do not belong to two different channels for the transmission of tactile information to the thalamus (5) trigeminothalamic transmission is exclusively performed by tonically firing neurons and (6) all aspects of haptic information are coded into low-pass, band-pass, and high-pass filtering profiles of tonically firing neurons. Our results are important for both, basic research on neural circuits and information processing, and development of sensory neuroprostheses.

  9. Modeling neuron selectivity over simple midlevel features for image classification.

    Science.gov (United States)

    Shu Kong; Zhuolin Jiang; Qiang Yang

    2015-08-01

    We now know that good mid-level features can greatly enhance the performance of image classification, but how to efficiently learn the image features is still an open question. In this paper, we present an efficient unsupervised midlevel feature learning approach (MidFea), which only involves simple operations, such as k-means clustering, convolution, pooling, vector quantization, and random projection. We show this simple feature can also achieve good performance in traditional classification task. To further boost the performance, we model the neuron selectivity (NS) principle by building an additional layer over the midlevel features prior to the classifier. The NS-layer learns category-specific neurons in a supervised manner with both bottom-up inference and top-down analysis, and thus supports fast inference for a query image. Through extensive experiments, we demonstrate that this higher level NS-layer notably improves the classification accuracy with our simple MidFea, achieving comparable performances for face recognition, gender classification, age estimation, and object categorization. In particular, our approach runs faster in inference by an order of magnitude than sparse coding-based feature learning methods. As a conclusion, we argue that not only do carefully learned features (MidFea) bring improved performance, but also a sophisticated mechanism (NS-layer) at higher level boosts the performance further.

  10. Complex Behavior in a Selective Aging Neuron Model Based on Small World Networks

    Institute of Scientific and Technical Information of China (English)

    LUO Min-Jie; ZHANG Gui-Qing; LIU Qiu-Yu; CHEN Tian-Lun

    2008-01-01

    Complex behavior in a selective aging simple neuron model based on small world networks is investigated. The basic elements of the model are endowed with the main features of a neuron function. The structure of the selective aging neuron model is discussed. We also give some properties of the new network and find that the neuron model displays a power-law behavior. If the brain network is small world-like network, the mean avalanche size is almost the same unless the aging parameter is big enough.

  11. Role of Dicer and the miRNA system in neuronal plasticity and brain function.

    Science.gov (United States)

    Fiorenza, Anna; Barco, Angel

    2016-11-01

    MicroRNAs (miRNAs) are small regulatory non-coding RNAs that contribute to fine-tuning regulation of gene expression by mRNA destabilization and/or translational repression. Their abundance in the nervous system, their temporally and spatially regulated expression and their ability to respond in an activity-dependent manner make miRNAs ideal candidates for the regulation of complex processes in the brain, including neuronal plasticity, memory formation and neural development. The conditional ablation of the RNase III Dicer, which is essential for the maturation of most miRNAs, is a useful model to investigate the effect of the loss of the miRNA system, as a whole, in different tissues and cellular types. In this review, we first provide an overview of Dicer function and structure, and discuss outstanding questions concerning the role of miRNAs in the regulation of gene expression and neuronal function, to later focus on the insight derived from studies in which the genetic ablation of Dicer was used to determine the role of the miRNA system in the nervous system. In particular, we highlight the collective role of miRNAs fine-tuning plasticity-related gene expression and providing robustness to neuronal gene expression networks. Copyright © 2016 Elsevier Inc. All rights reserved.

  12. Deterministic and stochastic bifurcations in the Hindmarsh-Rose neuronal model.

    Science.gov (United States)

    Dtchetgnia Djeundam, S R; Yamapi, R; Kofane, T C; Aziz-Alaoui, M A

    2013-09-01

    We analyze the bifurcations occurring in the 3D Hindmarsh-Rose neuronal model with and without random signal. When under a sufficient stimulus, the neuron activity takes place; we observe various types of bifurcations that lead to chaotic transitions. Beside the equilibrium solutions and their stability, we also investigate the deterministic bifurcation. It appears that the neuronal activity consists of chaotic transitions between two periodic phases called bursting and spiking solutions. The stochastic bifurcation, defined as a sudden change in character of a stochastic attractor when the bifurcation parameter of the system passes through a critical value, or under certain condition as the collision of a stochastic attractor with a stochastic saddle, occurs when a random Gaussian signal is added. Our study reveals two kinds of stochastic bifurcation: the phenomenological bifurcation (P-bifurcations) and the dynamical bifurcation (D-bifurcations). The asymptotical method is used to analyze phenomenological bifurcation. We find that the neuronal activity of spiking and bursting chaos remains for finite values of the noise intensity.

  13. Ataxia Jackson (ax(J)): a genetic model for apoptotic neuronal cell death.

    Science.gov (United States)

    Ohgoh, Makoto; Yamazaki, Kazuto

    2003-01-01

    Programmed cell death or apoptosis is an important process to form normal adult cytoarchitecture. But in vivo analysis of neuronal apoptosis has not been well advanced. Therefore, apoptotic cell death of a particular neuronal system or anatomical part in a mutant is an invaluable target to learn about a link between a gene and neuronal apoptosis. Ataxia (ax) is an autosomal recessive neurological mutant mouse. We recently investigated brains of homozygotes for ataxia Jackson (ax(J)), an allele of ax, using TUNEL method. A few TUNEL-positive cells were observed in the granular cell layer of the cerebellum, the dentate gyrus, and the olfactory bulb of phenotypically normal littermates (ax(J)/+ or +/+) aged at 23-38 days. In affected ax(J)/ax(J) mice, however, the number of TUNEL-positive cells was significantly increased in the cerebellum, particularly in the granular cell layer (p ax(J) mouse will be an in vivo unique model for studies on the genetic basis of apoptotic neuronal cell death, and identification of the ax gene is desired to elucidate molecular basis of the apoptosis.

  14. Bistable dynamics underlying excitability of ion homeostasis in neuron models.

    Directory of Open Access Journals (Sweden)

    Niklas Hübel

    2014-05-01

    Full Text Available When neurons fire action potentials, dissipation of free energy is usually not directly considered, because the change in free energy is often negligible compared to the immense reservoir stored in neural transmembrane ion gradients and the long-term energy requirements are met through chemical energy, i.e., metabolism. However, these gradients can temporarily nearly vanish in neurological diseases, such as migraine and stroke, and in traumatic brain injury from concussions to severe injuries. We study biophysical neuron models based on the Hodgkin-Huxley (HH formalism extended to include time-dependent ion concentrations inside and outside the cell and metabolic energy-driven pumps. We reveal the basic mechanism of a state of free energy-starvation (FES with bifurcation analyses showing that ion dynamics is for a large range of pump rates bistable without contact to an ion bath. This is interpreted as a threshold reduction of a new fundamental mechanism of ionic excitability that causes a long-lasting but transient FES as observed in pathological states. We can in particular conclude that a coupling of extracellular ion concentrations to a large glial-vascular bath can take a role as an inhibitory mechanism crucial in ion homeostasis, while the Na⁺/K⁺ pumps alone are insufficient to recover from FES. Our results provide the missing link between the HH formalism and activator-inhibitor models that have been successfully used for modeling migraine phenotypes, and therefore will allow us to validate the hypothesis that migraine symptoms are explained by disturbed function in ion channel subunits, Na⁺/K⁺ pumps, and other proteins that regulate ion homeostasis.

  15. Mathematical modelling and numerical simulation of the morphological development of neurons.

    Science.gov (United States)

    Graham, Bruce P; van Ooyen, Arjen

    2006-10-30

    The morphological development of neurons is a very complex process involving both genetic and environmental components. Mathematical modelling and numerical simulation are valuable tools in helping us unravel particular aspects of how individual neurons grow their characteristic morphologies and eventually form appropriate networks with each other. A variety of mathematical models that consider (1) neurite initiation (2) neurite elongation (3) axon pathfinding, and (4) neurite branching and dendritic shape formation are reviewed. The different mathematical techniques employed are also described. Some comparison of modelling results with experimental data is made. A critique of different modelling techniques is given, leading to a proposal for a unified modelling environment for models of neuronal development. A unified mathematical and numerical simulation framework should lead to an expansion of work on models of neuronal development, as has occurred with compartmental models of neuronal electrical activity.

  16. Antioxidant activity of X-34 in synaptosomal and neuronal systems.

    Science.gov (United States)

    Kanski, Jaroslaw; Sultana, Rukhsana; Klunk, William; Butterfield, D Allan

    2003-10-24

    Inhibiting aggregation and deposition of amyloid beta-peptide (Abeta) in brain is a therapeutic strategy for Alzheimer's disease (AD). A Congo-red-like molecule, X-34, is reported to bind to Abeta deposits. Oxidative stress associated with Abeta is hypothesized to be critical for the neurotoxic properties of this peptide. The present study was undertaken to test the hypothesis that X-34, with its salicylate groups, would act as an antioxidant. When challenged by hydroxyl or peroxyl free radicals or Abeta(1-42), oxidative stress and neurotoxicity occurred in neural systems as assessed by several indices. However, pretreatment of synaptosomes and primary neuronal cell culture with X-34 greatly ameliorated lipid peroxidation induced by these free radicals and Abeta(1-42). Protein oxidation was not prevented by X-34. These results are discussed in terms of potential therapeutic use of X-34 and related compounds in AD.

  17. Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks

    DEFF Research Database (Denmark)

    Hagen, Espen; Dahmen, David; Stavrinou, Maria L

    2016-01-01

    and electrophysiological features of neurons near the recording electrode, as well as synaptic inputs from the entire network. Here we propose a hybrid modeling scheme combining efficient point-neuron network models with biophysical principles underlying LFP generation by real neurons. The LFP predictions rely...... on populations of network-equivalent multicompartment neuron models with layer-specific synaptic connectivity, can be used with an arbitrary number of point-neuron network populations, and allows for a full separation of simulated network dynamics and LFPs. We apply the scheme to a full-scale cortical network...... model for a ∼1 mm(2) patch of primary visual cortex, predict laminar LFPs for different network states, assess the relative LFP contribution from different laminar populations, and investigate effects of input correlations and neuron density on the LFP. The generic nature of the hybrid scheme and its...

  18. Rescue of neuronal migration deficits in a mouse model of fetal Minamata disease by increasing neuronal Ca2+ spike frequency.

    Science.gov (United States)

    Fahrion, Jennifer K; Komuro, Yutaro; Li, Ying; Ohno, Nobuhiko; Littner, Yoav; Raoult, Emilie; Galas, Ludovic; Vaudry, David; Komuro, Hitoshi

    2012-03-27

    In the brains of patients with fetal Minamata disease (FMD), which is caused by exposure to methylmercury (MeHg) during development, many neurons are hypoplastic, ectopic, and disoriented, indicating disrupted migration, maturation, and growth. MeHg affects a myriad of signaling molecules, but little is known about which signals are primary targets for MeHg-induced deficits in neuronal development. In this study, using a mouse model of FMD, we examined how MeHg affects the migration of cerebellar granule cells during early postnatal development. The cerebellum is one of the most susceptible brain regions to MeHg exposure, and profound loss of cerebellar granule cells is detected in the brains of patients with FMD. We show that MeHg inhibits granule cell migration by reducing the frequency of somal Ca(2+) spikes through alterations in Ca(2+), cAMP, and insulin-like growth factor 1 (IGF1) signaling. First, MeHg slows the speed of granule cell migration in a dose-dependent manner, independent of the mode of migration. Second, MeHg reduces the frequency of spontaneous Ca(2+) spikes in granule cell somata in a dose-dependent manner. Third, a unique in vivo live-imaging system for cell migration reveals that reducing the inhibitory effects of MeHg on somal Ca(2+) spike frequency by stimulating internal Ca(2+) release and Ca(2+) influxes, inhibiting cAMP activity, or activating IGF1 receptors ameliorates the inhibitory effects of MeHg on granule cell migration. These results suggest that alteration of Ca(2+) spike frequency and Ca(2+), cAMP, and IGF1 signaling could be potential therapeutic targets for infants with MeHg intoxication.

  19. Neuronal cell death, nerve growth factor and neurotrophic models: 50 years on.

    Science.gov (United States)

    Bennet, M R; Gibson, W G; Lemon, G

    2002-01-10

    Viktor Hamburger has just died at the age of 100. It is 50 years since he and Rita Levi-Montalcini laid the foundations for the study of naturally occurring cell death and of neurotrophic factors in the nervous system. In a period of less than 10 years, from 1949 to 1958, Hamburger and Levi-Montalcini made the following seminal discoveries: that neuron cell death occurs in dorsal root ganglia, sympathetic ganglia and the cervical column of motoneurons; that the predictions arising from this observation, namely that survival is dependent on the supply of a trophic factor, could be substantiated by studying the effects of a sarcoma on the proliferation of ganglionic processes both in vivo and in vitro; and that the proliferation of these processes could be used as an assay system to isolate the factor. This work provides a short review mostly of the early history of this subject in the context of the Hamburger/Levi-Montalcini paradigm. This acts as an introduction to a consideration of models that have been proposed to account for how the different sources of growth factors provide for the survival of neurons during development. It is suggested that what has been called the 'social-control' model provides the most parsimonious quantitative description of the contribution of trophic factors to neuronal survival, a concept for which we are in debt to Viktor Hamburger and Rita Levi-Montalcini.

  20. Dynamic State Transitions in the Nervous System: From Ion Channels to Neurons to Networks

    Science.gov (United States)

    Århem, Peter; Braun, Hans A.; Huber, Martin T.; Liljenström, Hans

    The following sections are included: * Introduction * Ion channels: The microscopic scale * The variety of ion channels * Channel kinetics * Neurons: The mesoscopic scale * The feedback loops between membrane potential and ion currents * Neuron models: Concepts and examples * Impulse pattern modulation by ion channel densities * Oscillatory patterns * Irregular patterns * Impulse pattern modulation by subthreshold oscillations * The cold receptor model * Deterministic patterns and noise induced state-transitions on temperature scaling * Neuronal networks: The oscopic scale * Random channel events cause network state transitions * A hippocampal neural network model * Simulating noise-induced state transitions * Functional significance of oscopic neurodynamics * Conclusions * Appendix A: Computation of the neuron models * Hippocampal neuron model * The cold receptor model * Appendix B: Neural network model * References

  1. Electrophysiological properties of inferior olive neurons: A compartmental model.

    Science.gov (United States)

    Schweighofer, N; Doya, K; Kawato, M

    1999-08-01

    As a step in exploring the functions of the inferior olive, we constructed a biophysical model of the olivary neurons to examine their unique electrophysiological properties. The model consists of two compartments to represent the known distribution of ionic currents across the cell membrane, as well as the dendritic location of the gap junctions and synaptic inputs. The somatic compartment includes a low-threshold calcium current (I(Ca_l)), an anomalous inward rectifier current (I(h)), a sodium current (I(Na)), and a delayed rectifier potassium current (I(K_dr)). The dendritic compartment contains a high-threshold calcium current (I(Ca_h)), a calcium-dependent potassium current (I(K_Ca)), and a current flowing into other cells through electrical coupling (I(c)). First, kinetic parameters for these currents were set according to previously reported experimental data. Next, the remaining free parameters were determined to account for both static and spiking properties of single olivary neurons in vitro. We then performed a series of simulated pharmacological experiments using bifurcation analysis and extensive two-parameter searches. Consistent with previous studies, we quantitatively demonstrated the major role of I(Ca_l) in spiking excitability. In addition, I(h) had an important modulatory role in the spike generation and period of oscillations, as previously suggested by Bal and McCormick. Finally, we investigated the role of electrical coupling in two coupled spiking cells. Depending on the coupling strength, the hyperpolarization level, and the I(Ca_l) and I(h) modulation, the coupled cells had four different synchronization modes: the cells could be in-phase, phase-shifted, or anti-phase or could exhibit a complex desynchronized spiking mode. Hence these simulation results support the counterintuitive hypothesis that electrical coupling can desynchronize coupled inferior olive cells.

  2. Neuronal changes caused by Trypanosoma cruzi: an experimental model

    Directory of Open Access Journals (Sweden)

    Neide M Moreira

    2011-06-01

    Full Text Available Define an experimental model by evaluating quantitative and morphometric changes in myenteric neurons of the colon of mice infected with Trypanosoma cruzi. Twenty-eight Swiss male mice were distributed into groups: control (CG, n=9 and inoculated with 100 (IG100, n=9 and 1000 (IG1000, n=10 blood trypomastigotes, Y strain-T. cruzi II. Parasitemia was evaluated from 3-25 days post inoculation (dpi with parasites peak of 7.7 × 10(6 and 8.4 × 10(6 trypomastigotes/mL at 8th dpi (p>0.05 in IG100 and IG1000, respectively. Chronic phase of the infection was obtained with two doses of 100mg/Kg/weight and one dose of 250mg/Kg/weight of Benznidazole on 11, 16 and 18 dpi. Three animals from each group were euthanized at 18, 30 and 75 dpi. The colon was stained with Giemsa. The quantitative and morphometric analysis of neurons revealed that the infection caused a decrease of neuronal density on 30th dpi (pDefinir um modelo experimental de avaliação de alterações quantitativas e morfométricas nos neurônios mientéricos do cólon de camundongos infectados pelo Trypanosoma cruzi. Vinte e oito camundongos Swiss machos foram distribuídos nos grupos: controle (GC, n=9 e infectados com 100 (IG100, n=9 e 1000 (IG1000, n=10 tripomastigotas sanguíneos, cepa Y-T. cruzi II. A parasitemia foi avaliada 3-25 dias pós inoculação (dpi, com pico de parasitos de 7,7 × 10(6 e 8,4 × 10(6 tripomastigotas/mL no 8º dpi (p>0,05 em IG100 e IG1000, respectivamente. A fase crônica da infecção foi obtida com duas doses de 100mg/Kg/weight e uma dose de 250mg/Kg/ weight do benznidazol, em 11, 16 e 18 dpi. Três animais de cada grupo foram sacrificados aos 18, 30 e 75 dpi. O cólon foi corado com Giemsa. A análise quantitativa e morfométrica de neurônios revelou que a infecção causou uma diminuição da densidade neuronal no 30º dpi (p<0,05 e 75 dpi (p<0,05 em IG100 e IG1000. A infecção causou morte e hipertrofia neuronal no 75º dpi em IG100 e IG1000 (p<0,05, p

  3. A neuron model with trainable activation function (TAF) and its MFNN supervised learning

    Institute of Scientific and Technical Information of China (English)

    吴佑寿; 赵明生

    2001-01-01

    This paper addresses a new kind of neuron model, which has trainable activation function (TAF) in addition to only trainable weights in the conventional M-P model. The final neuron activation function can be derived from a primitive neuron activation function by training. The BP like learning algorithm has been presented for MFNN constructed by neurons of TAF model. Several simulation examples are given to show the network capacity and performance advantages of the new MFNN in comparison with that of conventional sigmoid MFNN.

  4. Phase Locking Phenomena and Electroencephalogram-Like Activities in Dynamic Neuronal Systems

    Institute of Scientific and Technical Information of China (English)

    XU Xin-Jian; WANG Sheng-Jun; TANG Wei; WANG Ying-Hai

    2005-01-01

    @@ We study signal detection and transduction of dynamic neuronal systems under the influence of external noise,white and coloured. Based on simulations, we show explicitly phase locking phenomena between the output and the input of a single neuron and Electroencephalogram-like activities on neural networks with small-world connectivity. The numerical results prove that the dynamic neuronal system can be adjusted to an optimal sensitive state for signal processing in the presence of additive noise.

  5. NeuronBank: A Tool for Cataloging Neuronal Circuitry.

    Science.gov (United States)

    Katz, Paul S; Calin-Jageman, Robert; Dhawan, Akshaye; Frederick, Chad; Guo, Shuman; Dissanayaka, Rasanjalee; Hiremath, Naveen; Ma, Wenjun; Shen, Xiuyn; Wang, Hsui C; Yang, Hong; Prasad, Sushil; Sunderraman, Rajshekhar; Zhu, Ying

    2010-01-01

    The basic unit of any nervous system is the neuron. Therefore, understanding the operation of nervous systems ultimately requires an inventory of their constituent neurons and synaptic connectivity, which form neural circuits. The presence of uniquely identifiable neurons or classes of neurons in many invertebrates has facilitated the construction of cellular-level connectivity diagrams that can be generalized across individuals within a species. Homologous neurons can also be recognized across species. Here we describe NeuronBank.org, a web-based tool that we are developing for cataloging, searching, and analyzing neuronal circuitry within and across species. Information from a single species is represented in an individual branch of NeuronBank. Users can search within a branch or perform queries across branches to look for similarities in neuronal circuits across species. The branches allow for an extensible ontology so that additional characteristics can be added as knowledge grows. Each entry in NeuronBank generates a unique accession ID, allowing it to be easily cited. There is also an automatic link to a Wiki page allowing an encyclopedic explanation of the entry. All of the 44 previously published neurons plus one previously unpublished neuron from the mollusc, Tritonia diomedea, have been entered into a branch of NeuronBank as have 4 previously published neurons from the mollusc, Melibe leonina. The ability to organize information about neuronal circuits will make this information more accessible, ultimately aiding research on these important models.

  6. NeuronBank: a tool for cataloging neuronal circuitry

    Directory of Open Access Journals (Sweden)

    Paul S Katz

    2010-04-01

    Full Text Available The basic unit of any nervous system is the neuron. Therefore, understanding the operation of nervous systems ultimately requires an inventory of their constituent neurons and synaptic connectivity, which form neural circuits. The presence of uniquely identifiable neurons or classes of neurons in many invertebrates has facilitated the construction of cellular-level connectivity diagrams that can be generalized across individuals within a species. Homologous neurons can also be recognized across species. Here we describe NeuronBank.org, a web-based tool that we are developing for cataloging, searching, and analyzing neuronal circuitry within and across species. Information from a single species is represented in an individual branch of NeuronBank. Users can search within a branch or perform queries across branches to look for similarities in neuronal circuits across species. The branches allow for an extensible ontology so that additional characteristics can be added as knowledge grows. Each entry in NeuronBank generates a unique accession ID, allowing it to be easily cited. There is also an automatic link to a Wiki page allowing an encyclopedic explanation of the entry. All of the 44 previously published neurons plus one previously unpublished neuron from the mollusc, Tritonia diomedea, have been entered into a branch of NeuronBank as have 4 previously published neurons from the mollusc, Melibe leonina. The ability to organize information about neuronal circuits will make this information more accessible, ultimately aiding research on these important models.

  7. NeuronBank: A Tool for Cataloging Neuronal Circuitry

    Science.gov (United States)

    Katz, Paul S.; Calin-Jageman, Robert; Dhawan, Akshaye; Frederick, Chad; Guo, Shuman; Dissanayaka, Rasanjalee; Hiremath, Naveen; Ma, Wenjun; Shen, Xiuyn; Wang, Hsui C.; Yang, Hong; Prasad, Sushil; Sunderraman, Rajshekhar; Zhu, Ying

    2010-01-01

    The basic unit of any nervous system is the neuron. Therefore, understanding the operation of nervous systems ultimately requires an inventory of their constituent neurons and synaptic connectivity, which form neural circuits. The presence of uniquely identifiable neurons or classes of neurons in many invertebrates has facilitated the construction of cellular-level connectivity diagrams that can be generalized across individuals within a species. Homologous neurons can also be recognized across species. Here we describe NeuronBank.org, a web-based tool that we are developing for cataloging, searching, and analyzing neuronal circuitry within and across species. Information from a single species is represented in an individual branch of NeuronBank. Users can search within a branch or perform queries across branches to look for similarities in neuronal circuits across species. The branches allow for an extensible ontology so that additional characteristics can be added as knowledge grows. Each entry in NeuronBank generates a unique accession ID, allowing it to be easily cited. There is also an automatic link to a Wiki page allowing an encyclopedic explanation of the entry. All of the 44 previously published neurons plus one previously unpublished neuron from the mollusc, Tritonia diomedea, have been entered into a branch of NeuronBank as have 4 previously published neurons from the mollusc, Melibe leonina. The ability to organize information about neuronal circuits will make this information more accessible, ultimately aiding research on these important models. PMID:20428500

  8. Mirror neurons and mirror systems in monkeys and humans.

    Science.gov (United States)

    Fabbri-Destro, Maddalena; Rizzolatti, Giacomo

    2008-06-01

    Mirror neurons are a distinct class of neurons that transform specific sensory information into a motor format. Mirror neurons have been originally discovered in the premotor and parietal cortex of the monkey. Subsequent neurophysiological (TMS, EEG, MEG) and brain imaging studies have shown that a mirror mechanism is also present in humans. According to its anatomical locations, mirror mechanism plays a role in action and intention understanding, imitation, speech, and emotion feeling.

  9. A hierarchical neuronal model for generation and online recognition of birdsongs.

    Directory of Open Access Journals (Sweden)

    Izzet B Yildiz

    2011-12-01

    Full Text Available The neuronal system underlying learning, generation and recognition of song in birds is one of the best-studied systems in the neurosciences. Here, we use these experimental findings to derive a neurobiologically plausible, dynamic, hierarchical model of birdsong generation and transform it into a functional model of birdsong recognition. The generation model consists of neuronal rate models and includes critical anatomical components like the premotor song-control nucleus HVC (proper name, the premotor nucleus RA (robust nucleus of the arcopallium, and a model of the syringeal and respiratory organs. We use Bayesian inference of this dynamical system to derive a possible mechanism for how birds can efficiently and robustly recognize the songs of their conspecifics in an online fashion. Our results indicate that the specific way birdsong is generated enables a listening bird to robustly and rapidly perceive embedded information at multiple time scales of a song. The resulting mechanism can be useful for investigating the functional roles of auditory recognition areas and providing predictions for future birdsong experiments.

  10. Temporal structure of neuronal population oscillations with empirical model decomposition

    Science.gov (United States)

    Li, Xiaoli

    2006-08-01

    Frequency analysis of neuronal oscillation is very important for understanding the neural information processing and mechanism of disorder in the brain. This Letter addresses a new method to analyze the neuronal population oscillations with empirical mode decomposition (EMD). Following EMD of neuronal oscillation, a series of intrinsic mode functions (IMFs) are obtained, then Hilbert transform of IMFs can be used to extract the instantaneous time frequency structure of neuronal oscillation. The method is applied to analyze the neuronal oscillation in the hippocampus of epileptic rats in vivo, the results show the neuronal oscillations have different descriptions during the pre-ictal, seizure onset and ictal periods of the epileptic EEG at the different frequency band. This new method is very helpful to provide a view for the temporal structure of neural oscillation.

  11. A First-Order Non-Homogeneous Markov Model for the Response of Spiking Neurons Stimulated by Small Phase-Continuous Signals

    CERN Document Server

    Tapson, J; van Schaik, A; Etienne-Cummings, R

    2008-01-01

    We present a first-order non-homogeneous Markov model for the interspike-interval density of a continuously stimulated spiking neuron. The model allows the conditional interspike-interval density and the stationary interspike-interval density to be expressed as products of two separate functions, one of which describes only the neuron characteristics, and the other of which describes only the signal characteristics. This allows the use of this model to predict the response when the underlying neuron model is not known or well determined. The approximation shows particularly clearly that signal autocorrelations and cross-correlations arise as natural features of the interspike-interval density, and are particularly clear for small signals and moderate noise. We show that this model simplifies the design of spiking neuron cross-correlation systems, and describe a four-neuron mutual inhibition network that generates a cross-correlation output for two input signals.

  12. Neuronal expression of glucosylceramide synthase in central nervous system regulates body weight and energy homeostasis.

    Directory of Open Access Journals (Sweden)

    Viola Nordström

    Full Text Available Hypothalamic neurons are main regulators of energy homeostasis. Neuronal function essentially depends on plasma membrane-located gangliosides. The present work demonstrates that hypothalamic integration of metabolic signals requires neuronal expression of glucosylceramide synthase (GCS; UDP-glucose:ceramide glucosyltransferase. As a major mechanism of central nervous system (CNS metabolic control, we demonstrate that GCS-derived gangliosides interacting with leptin receptors (ObR in the neuronal membrane modulate leptin-stimulated formation of signaling metabolites in hypothalamic neurons. Furthermore, ganglioside-depleted hypothalamic neurons fail to adapt their activity (c-Fos in response to alterations in peripheral energy signals. Consequently, mice with inducible forebrain neuron-specific deletion of the UDP-glucose:ceramide glucosyltransferase gene (Ugcg display obesity, hypothermia, and lower sympathetic activity. Recombinant adeno-associated virus (rAAV-mediated Ugcg delivery to the arcuate nucleus (Arc significantly ameliorated obesity, specifying gangliosides as seminal components for hypothalamic regulation of body energy homeostasis.

  13. Developing Itô stochastic differential equation models for neuronal signal transduction pathways.

    Science.gov (United States)

    Manninen, Tiina; Linne, Marja-Leena; Ruohonen, Keijo

    2006-08-01

    Mathematical modeling and simulation of dynamic biochemical systems are receiving considerable attention due to the increasing availability of experimental knowledge of complex intracellular functions. In addition to deterministic approaches, several stochastic approaches have been developed for simulating the time-series behavior of biochemical systems. The problem with stochastic approaches, however, is the larger computational time compared to deterministic approaches. It is therefore necessary to study alternative ways to incorporate stochasticity and to seek approaches that reduce the computational time needed for simulations, yet preserve the characteristic behavior of the system in question. In this work, we develop a computational framework based on the Itô stochastic differential equations for neuronal signal transduction networks. There are several different ways to incorporate stochasticity into deterministic differential equation models and to obtain Itô stochastic differential equations. Two of the developed models are found most suitable for stochastic modeling of neuronal signal transduction. The best models give stable responses which means that the variances of the responses with time are not increasing and negative concentrations are avoided. We also make a comparative analysis of different kinds of stochastic approaches, that is the Itô stochastic differential equations, the chemical Langevin equation, and the Gillespie stochastic simulation algorithm. Different kinds of stochastic approaches can be used to produce similar responses for the neuronal protein kinase C signal transduction pathway. The fine details of the responses vary slightly, depending on the approach and the parameter values. However, when simulating great numbers of chemical species, the Gillespie algorithm is computationally several orders of magnitude slower than the Itô stochastic differential equations and the chemical Langevin equation. Furthermore, the chemical

  14. Mirror neuron system based therapy for aphasia rehabilitation.

    Science.gov (United States)

    Chen, Wenli; Ye, Qian; Ji, Xiangtong; Zhang, Sicong; Yang, Xi; Zhou, Qiumin; Cong, Fang; Chen, Wei; Zhang, Xin; Zhang, Bing; Xia, Yang; Yuan, Ti-Fei; Shan, Chunlei

    2015-01-01

    To investigate the effect of hand action observation training, i.e., mirror neuron system (MNS) based training, on language function of aphasic patients after stroke. In addition, to reveal the tentative mechanism underlying this effect. Six aphasic patients after stroke, meeting the criteria, undergo 3 weeks' training protocol (30 min per day, 6 days per week). Among them, four patients accepted an ABA training design, i.e., they implemented Protocol A (hand action observation combined with repetition) in the first and third weeks and carried out Protocol B (static object observation combined with repetition) in the second week. Conversely, for the other two patients, BAB training design was adopted, i.e., patients took Protocol B in the first and third weeks and accepted Protocol A in the second week. Picture naming test, western aphasia battery (WAB) and Token Test were applied to evaluate the changes of language function before and after each week's training. Furthermore, two subjects (one aphasic patient and one healthy volunteer) attended a functional MRI (fMRI) experiment, by which we tried to reveal the mechanism underlying possible language function changes after training. Compared with static object observation and repetition training (Protocol B), hand action observation and repetition training (Protocol A) effectively improved most aspects of the language function in all six patients, as demonstrated in the picture naming test, subtests of oral language and aphasia quotient (AQ) of WAB. In addition, the fMRI experiment showed that Protocol A induced more activations in the MNS of one patient and one healthy control when compared to Protocol B. The mirror neuron based therapy may facilitate the language recovery for aphasic patients and this, to some extent, provides a novel direction of rehabilitation for aphasia patients.

  15. Are neuronal networks that vicious ? Or only their models ?

    CERN Document Server

    Cessac, B

    2007-01-01

    We present a mathematical analysis of a network with integrate and fire neurons, taking into account the realistic fact that the spike time is only known within some \\textit{finite} precision. This leads us to propose a model where spikes are effective at times multiple of a characteristic time scale $\\delta$, where $\\delta$ can be mathematically arbitrary small. We make a complete mathematical characterization of the model-dynamics for conductance based integrate and fire models. We obtain the following results. The asymptotic dynamics is composed by finitely many periodic orbits, whose number and period can be arbitrary large and diverge in a region of the parameters space, traditionally called the ``edge of chaos'', a notion mathematically well defined in the present paper. Furthermore, except at the edge of chaos, there is a one-to-one correspondence between the membrane potential trajectories and the spikes raster plot. This shows that the neural code is entirely ``in the spikes'' in this case. As a key ...

  16. Dynamical patterns of calcium signaling in a functional model of neuron-astrocyte networks

    DEFF Research Database (Denmark)

    Postnov, D.E.; Koreshkov, R.N.; Brazhe, N.A.

    2009-01-01

    We propose a functional mathematical model for neuron-astrocyte networks. The model incorporates elements of the tripartite synapse and the spatial branching structure of coupled astrocytes. We consider glutamate-induced calcium signaling as a specific mode of excitability and transmission...... in astrocytic-neuronal networks. We reproduce local and global dynamical patterns observed experimentally....

  17. Distribution of SMI-32-immunoreactive neurons in the central auditory system of the rat.

    Science.gov (United States)

    Ouda, Ladislav; Druga, Rastislav; Syka, Josef

    2012-01-01

    SMI-32 antibody recognizes a non-phosphorylated epitope of neurofilament proteins, which are thought to be necessary for the maintenance of large neurons with highly myelinated processes. We investigated the distribution and quantity of SMI-32-immunoreactive(-ir) neurons in individual parts of the rat auditory system. SMI-32-ir neurons were present in all auditory structures; however, in most regions they constituted only a minority of all neurons (10-30%). In the cochlear nuclei, a higher occurrence of SMI-32-ir neurons was found in the ventral cochlear nucleus. Within the superior olivary complex, SMI-32-ir cells were particularly abundant in the medial nucleus of the trapezoid body (MNTB), the only auditory region where SMI-32-ir neurons constituted an absolute majority of all neurons. In the inferior colliculus, a region with the highest total number of neurons among the rat auditory subcortical structures, the percentage of SMI-32-ir cells was, in contrast to the MNTB, very low. In the medial geniculate body, SMI-32-ir neurons were prevalent in the ventral division. At the cortical level, SMI-32-ir neurons were found mainly in layers III, V and VI. Within the auditory cortex, it was possible to distinguish the Te1, Te2 and Te3 areas on the basis of the variable numerical density and volumes of SMI-32-ir neurons, especially when the pyramidal cells of layer V were taken into account. SMI-32-ir neurons apparently form a representative subpopulation of neurons in all parts of the rat central auditory system and may belong to both the inhibitory and excitatory systems, depending on the particular brain region.

  18. Protein aggregation in association with delayed neuronal death in rat model of brain ischemia

    Institute of Scientific and Technical Information of China (English)

    Pengfei GE; Tianfei LUG; Shuanglin FU; Wenchen LI; Chonghao WANG; Chuibing ZHOU; Yinan LUO

    2008-01-01

    To investigate the relationship between protein aggregation and delayed neuronal death, we adopted rat models of 20 min ischemia. Brain ischemia was produced using the 2-vessel occlusion (2VO) model in rats Light microscopy, transmission electronic microscopy and Western blot analysis were performed for morphological analysis of neurons, and protein detection. The results showed delayed neuronal death took place at 72 h after ischemia-reperfusion, protein aggregates formed at 4 h after reperfusion and reached the peak at 24 h after reper-fusion, and Western blot analysis was consistent with transmission electronic microscopy. We conclude that protein aggregation is one of the important factors leading to delayed neuronal death.

  19. A Computational Model to Investigate Astrocytic Glutamate Uptake Influence on Synaptic Transmission and Neuronal Spiking

    Directory of Open Access Journals (Sweden)

    Sushmita Lakshmi Allam

    2012-10-01

    Full Text Available Over the past decades, our view of astrocytes has switched from passive support cells to active processing elements in the brain. The current view is that astrocytes shape neuronal communication and also play an important role in many neurodegenerative diseases. Despite the growing awareness of the importance of astrocytes, the exact mechanisms underlying neuron-astrocyte communication and the physiological consequences of astrocytic-neuronal interactions remain largely unclear. In this work, we define a modeling framework that will permit to address unanswered questions regarding the role of astrocytes. Our computational model of a detailed glutamatergic synapse facilitates the analysis of neural system responses to various stimuli and conditions that are otherwise difficult to obtain experimentally, in particular the readouts at the sub-cellular level. In this paper, we extend a detailed glutamatergic synaptic model, to include astrocytic glutamate transporters. We demonstrate how these glial transporters, responsible for the majority of glutamate uptake, modulate synaptic transmission mediated by ionotropic AMPA and NMDA receptors at glutamatergic synapses. Furthermore, we investigate how these local signaling effects at the synaptic level are translated into varying spatio-temporal patterns of neuron firing. Paired pulse stimulation results reveal that the effect of astrocytic glutamate uptake is more apparent when the input inter-spike interval is sufficiently long to allow the receptors to recover from desensitization. These results suggest an important functional role of astrocytes in spike timing dependent processes and demand further investigation of the molecular basis of certain neurological diseases specifically related to alterations in astrocytic glutamate uptake, such as epilepsy.

  20. Mapping the flow of information within the putative mirror neuron system during gesture observation.

    Science.gov (United States)

    Schippers, Marleen B; Keysers, Christian

    2011-07-01

    The putative mirror neuron system may either function as a strict feed-forward system or as a dynamic control system. A strict feed-forward system would predict that action observation leads to a predominantly temporal→parietal→premotor flow of information in which a visual representation is transformed into motor-programs which contribute to action understanding. Instead, a dynamic feedback control system would predict that the reverse direction of information flow predominates because of a combination of inhibitory forward and excitatory inverse models. Here we test which of these conflicting predictions best matches the information flow within the putative mirror neuron system (pMNS) and between the pMNS and the rest of the brain during the observation of comparatively long naturalistic stretches of communicative gestures. We used Granger causality to test the dominant direction of influence. Our results fit the predictions of the dynamic feedback control system: we found predominantly an information flow within the pMNS from premotor to parietal and middle temporal cortices. This is more pronounced during an active guessing task than while passively reviewing the same gestures. In particular, the ventral premotor cortex sends significantly more information to other pMNS areas than it receives during active guessing than during passive observation.

  1. Neurodynamics of biased competition and cooperation for attention: a model with spiking neurons.

    Science.gov (United States)

    Deco, Gustavo; Rolls, Edmund T

    2005-07-01

    Recent neurophysiological experiments have led to a promising "biased competition hypothesis" of the neural basis of attention. According to this hypothesis, attention appears as a sometimes nonlinear property that results from a top-down biasing effect that influences the competitive and cooperative interactions that work both within cortical areas and between cortical areas. In this paper we describe a detailed dynamical analysis of the synaptic and neuronal spiking mechanisms underlying biased competition. We perform a detailed analysis of the dynamical capabilities of the system by exploring the stationary attractors in the parameter space by a mean-field reduction consistent with the underlying synaptic and spiking dynamics. The nonstationary dynamical behavior, as measured in neuronal recording experiments, is studied by an integrate-and-fire model with realistic dynamics. This elucidates the role of cooperation and competition in the dynamics of biased competition and shows why feedback connections between cortical areas need optimally to be weaker by a factor of about 2.5 than the feedforward connections in an attentional network. We modeled the interaction between top-down attention and bottom-up stimulus contrast effects found neurophysiologically and showed that top-down attentional effects can be explained by external attention inputs biasing neurons to move to different parts of their nonlinear activation functions. Further, it is shown that, although NMDA nonlinear effects may be useful in attention, they are not necessary, with nonlinear effects (which may appear multiplicative) being produced in the way just described.

  2. Dynamical responses in a new neuron model subjected to electromagnetic induction and phase noise

    Science.gov (United States)

    Wu, Fuqiang; Wang, Chunni; Jin, Wuyin; Ma, Jun

    2017-03-01

    Complex electrical activities in neuron can induce time-varying electromagnetic field and the effect of various electromagnetic inductions should be considered in dealing with electrical activities of neuron. Based on an improved neuron model, the effect of electromagnetic induction is described by using magnetic flux, and the modulation of magnetic flux on membrane potential is realized by using memristor coupling. Furthermore, additive phase noise is imposed on the neuron to detect the dynamical response of neuron and phase transition in modes. The dynamical properties of electrical activities are detected and discussed, and double coherence resonance behavior is observed, respectively. Furthermore, multiple modes of electrical activities can be observed in the sampled time series for membrane potential of the neuron model.

  3. The Morris-Lecar neuron model embeds a leaky integrate-and-fire model

    DEFF Research Database (Denmark)

    Ditlevsen, Susanne; Greenwood, Priscilla

    2013-01-01

    We showthat the stochastic Morris–Lecar neuron, in a neighborhood of its stable point, can be approximated by a two-dimensional Ornstein Uhlenbeck (OU) modulation of a constant circular motion. The associated radial OU process is an example of a leaky integrate-and-fire (LIF) model prior to firing...

  4. A modeling approach on why simple central pattern generators are built of irregular neurons.

    Science.gov (United States)

    Reyes, Marcelo Bussotti; Carelli, Pedro Valadão; Sartorelli, José Carlos; Pinto, Reynaldo Daniel

    2015-01-01

    The crustacean pyloric Central Pattern Generator (CPG) is a nervous circuit that endogenously provides periodic motor patterns. Even after about 40 years of intensive studies, the rhythm genesis is still not rigorously understood in this CPG, mainly because it is made of neurons with irregular intrinsic activity. Using mathematical models we addressed the question of using a network of irregularly behaving elements to generate periodic oscillations, and we show some advantages of using non-periodic neurons with intrinsic behavior in the transition from bursting to tonic spiking (as found in biological pyloric CPGs) as building components. We studied two- and three-neuron model CPGs built either with Hindmarsh-Rose or with conductance-based Hodgkin-Huxley-like model neurons. By changing a model's parameter we could span the neuron's intrinsic dynamical behavior from slow periodic bursting to fast tonic spiking, passing through a transition where irregular bursting was observed. Two-neuron CPG, half center oscillator (HCO), was obtained for each intrinsic behavior of the neurons by coupling them with mutual symmetric synaptic inhibition. Most of these HCOs presented regular antiphasic bursting activity and the changes of the bursting frequencies was studied as a function of the inhibitory synaptic strength. Among all HCOs, those made of intrinsic irregular neurons presented a wider burst frequency range while keeping a reliable regular oscillatory (bursting) behavior. HCOs of periodic neurons tended to be either hard to change their behavior with synaptic strength variations (slow periodic burster neurons) or unable to perform a physiologically meaningful rhythm (fast tonic spiking neurons). Moreover, 3-neuron CPGs with connectivity and output similar to those of the pyloric CPG presented the same results.

  5. The primary locus of motor neuron death in an ALS–PDC mouse model

    OpenAIRE

    2009-01-01

    A mouse model of amyotrophic lateral sclerosis–parkinsonism–dementia complex based on the consumption of cycad seed flour was used to determine whether the observed pathology of motor neuron loss begins in the distal axons or the spinal cord. Assessments of neuromuscular junction integrity and motor neurons were performed at multiple time points. Mice fed cycad pellets performed worse on the wire hang than controls. Microglial activation in cycad-fed mice was observed with motor neuron degene...

  6. A modeling approach on why simple central pattern generators are built of irregular neurons.

    Directory of Open Access Journals (Sweden)

    Marcelo Bussotti Reyes

    Full Text Available The crustacean pyloric Central Pattern Generator (CPG is a nervous circuit that endogenously provides periodic motor patterns. Even after about 40 years of intensive studies, the rhythm genesis is still not rigorously understood in this CPG, mainly because it is made of neurons with irregular intrinsic activity. Using mathematical models we addressed the question of using a network of irregularly behaving elements to generate periodic oscillations, and we show some advantages of using non-periodic neurons with intrinsic behavior in the transition from bursting to tonic spiking (as found in biological pyloric CPGs as building components. We studied two- and three-neuron model CPGs built either with Hindmarsh-Rose or with conductance-based Hodgkin-Huxley-like model neurons. By changing a model's parameter we could span the neuron's intrinsic dynamical behavior from slow periodic bursting to fast tonic spiking, passing through a transition where irregular bursting was observed. Two-neuron CPG, half center oscillator (HCO, was obtained for each intrinsic behavior of the neurons by coupling them with mutual symmetric synaptic inhibition. Most of these HCOs presented regular antiphasic bursting activity and the changes of the bursting frequencies was studied as a function of the inhibitory synaptic strength. Among all HCOs, those made of intrinsic irregular neurons presented a wider burst frequency range while keeping a reliable regular oscillatory (bursting behavior. HCOs of periodic neurons tended to be either hard to change their behavior with synaptic strength variations (slow periodic burster neurons or unable to perform a physiologically meaningful rhythm (fast tonic spiking neurons. Moreover, 3-neuron CPGs with connectivity and output similar to those of the pyloric CPG presented the same results.

  7. A Hebbian learning rule gives rise to mirror neurons and links them to control theoretic inverse models.

    Science.gov (United States)

    Hanuschkin, A; Ganguli, S; Hahnloser, R H R

    2013-01-01

    Mirror neurons are neurons whose responses to the observation of a motor act resemble responses measured during production of that act. Computationally, mirror neurons have been viewed as evidence for the existence of internal inverse models. Such models, rooted within control theory, map-desired sensory targets onto the motor commands required to generate those targets. To jointly explore both the formation of mirrored responses and their functional contribution to inverse models, we develop a correlation-based theory of interactions between a sensory and a motor area. We show that a simple eligibility-weighted Hebbian learning rule, operating within a sensorimotor loop during motor explorations and stabilized by heterosynaptic competition, naturally gives rise to mirror neurons as well as control theoretic inverse models encoded in the synaptic weights from sensory to motor neurons. Crucially, we find that the correlational structure or stereotypy of the neural code underlying motor explorations determines the nature of the learned inverse model: random motor codes lead to causal inverses that map sensory activity patterns to their motor causes; such inverses are maximally useful, by allowing the imitation of arbitrary sensory target sequences. By contrast, stereotyped motor codes lead to less useful predictive inverses that map sensory activity to future motor actions. Our theory generalizes previous work on inverse models by showing that such models can be learned in a simple Hebbian framework without the need for error signals or backpropagation, and it makes new conceptual connections between the causal nature of inverse models, the statistical structure of motor variability, and the time-lag between sensory and motor responses of mirror neurons. Applied to bird song learning, our theory can account for puzzling aspects of the song system, including necessity of sensorimotor gating and selectivity of auditory responses to bird's own song (BOS) stimuli.

  8. A Hebbian learning rule gives rise to mirror neurons and links them to control theoretic inverse models

    Directory of Open Access Journals (Sweden)

    Alexander eHanuschkin

    2013-06-01

    Full Text Available Mirror neurons are neurons whose responses to the observation of a motor act resemble responses measured during production of that act. Computationally, mirror neurons have been viewed as evidence for the existence of internal inverse models. Such models, rooted within control theory, map desired sensory targets onto the motor commands required to generate those targets. To jointly explore both the formation of mirrored responses and their functional contribution to inverse models, we develop a correlation-based theory of interactions between a sensory and a motor area. We show that a simple eligibility-weighted Hebbian learning rule, operating within a sensorimotor loop during motor explorations and stabilized by heterosynaptic competition, naturally gives rise to mirror neurons as well as control theoretic inverse models encoded in the synaptic weights from sensory to motor neurons. Crucially, we find that the correlational structure or stereotypy of the neural code underlying motor explorations determines the nature of the learned inverse model: Random motor codes lead to causal inverses that map sensory activity patterns to their motor causes; such inverses are maximally useful, they allow for imitating arbitrary sensory target sequences. By contrast, stereotyped motor codes lead to less useful predictive inverses that map sensory activity to future motor actions.Our theory generalizes previous work on inverse models by showing that such models can be learned in a simple Hebbian framework without the need for error signals or backpropagation, and it makes new conceptual connections between the causal nature of inverse models, the statistical structure of motor variability, and the time-lag between sensory and motor responses of mirror neurons. Applied to bird song learning, our theory can account for puzzling aspects of the song system, including necessity of sensorimotor gating and selectivity of auditory responses to bird’s own song

  9. Th17 Cells Induce Dopaminergic Neuronal Death via LFA-1/ICAM-1 Interaction in a Mouse Model of Parkinson's Disease.

    Science.gov (United States)

    Liu, Zhan; Huang, Yan; Cao, Bei-Bei; Qiu, Yi-Hua; Peng, Yu-Ping

    2016-11-14

    T helper (Th)17 cells, a subset of CD4(+) T lymphocytes, have strong pro-inflammatory property and appear to be essential in the pathogenesis of many inflammatory diseases. However, the involvement of Th17 cells in Parkinson's disease (PD) that is characterized by a progressive degeneration of dopaminergic (DAergic) neurons in the nigrostriatal system is unclear. Here, we aimed to demonstrate that Th17 cells infiltrate into the brain parenchyma and induce neuroinflammation and DAergic neuronal death in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)- or 1-methyl-4-phenylpyridinium (MPP(+))-induced PD models. Blood-brain barrier (BBB) disruption in the substantia nigra (SN) was assessed by the signal of FITC-labeled albumin that was injected into blood circulation via the ascending aorta. Live cell imaging system was used to observe a direct contact of Th17 cells with neurons by staining these cells using the two adhesion molecules, leukocyte function-associated antigen (LFA)-1 and intercellular adhesion molecule (ICAM)-1, respectively. Th17 cells invaded into the SN where BBB was disrupted in MPTP-induced PD mice. Th17 cells exacerbated DAergic neuronal loss and pro-inflammatory/neurotrophic factor disorders in MPP(+)-treated ventral mesencephalic (VM) cell cultures. A direct contact of LFA-1-stained Th17 cells with ICAM-1-stained VM neurons was dynamically captured. Either blocking LFA-1 in Th17 cells or blocking ICAM-1 in VM neurons with neutralizing antibodies abolished Th17-induced DAergic neuronal death. These results establish that Th17 cells infiltrate into the brain parenchyma of PD mice through lesioned BBB and exert neurotoxic property by promoting glial activation and importantly by a direct damage to neurons depending on LFA-1/ICAM-1 interaction.

  10. Model Systems

    Directory of Open Access Journals (Sweden)

    Francisco Rodríguez-Trelles

    1998-12-01

    Full Text Available Current efforts to study the biological effects of global change have focused on ecological responses, particularly shifts in species ranges. Mostly ignored are microevolutionary changes. Genetic changes may be at least as important as ecological ones in determining species' responses. In addition, such changes may be a sensitive indicator of global changes that will provide different information than that provided by range shifts. We discuss potential candidate systems to use in such monitoring programs. Studies of Drosophila subobscura suggest that its chromosomal inversion polymorphisms are responding to global warming. Drosophila inversion polymorphisms can be useful indicators of the effects of climate change on populations and ecosystems. Other species also hold the potential to become important indicators of global change. Such studies might significantly influence ecosystem conservation policies and research priorities.

  11. Simulation of Networked Control System based on Smith Compensator and Single Neuron Incomplete Differential Forward PID

    Directory of Open Access Journals (Sweden)

    Haitao Zhang

    2011-12-01

    Full Text Available In the networked control system with random time delay in forward and feedback channels, a kind of controller based on Smith compensator and signal neuron incomplete differential forward PID is presented. First, using root locus method and simulink simulation software, the influences of network’s time delay on the system stability and dynamic performance are analyzed. Then, combined with incomplete differential forward PID control algorithm, Smith compensation model is established. Compared with existing Smith compensator, the proposed control model is easy to be implemented, and can also get better control performance in the case of miss-matching compensator model. Finally, the simulation research on a DC motor is done, and the simulation results show the effectiveness of the proposed method.

  12. Mathematical models for sleep-wake dynamics: comparison of the two-process model and a mutual inhibition neuronal model.

    Directory of Open Access Journals (Sweden)

    Anne C Skeldon

    Full Text Available Sleep is essential for the maintenance of the brain and the body, yet many features of sleep are poorly understood and mathematical models are an important tool for probing proposed biological mechanisms. The most well-known mathematical model of sleep regulation, the two-process model, models the sleep-wake cycle by two oscillators: a circadian oscillator and a homeostatic oscillator. An alternative, more recent, model considers the mutual inhibition of sleep promoting neurons and the ascending arousal system regulated by homeostatic and circadian processes. Here we show there are fundamental similarities between these two models. The implications are illustrated with two important sleep-wake phenomena. Firstly, we show that in the two-process model, transitions between different numbers of daily sleep episodes can be classified as grazing bifurcations. This provides the theoretical underpinning for numerical results showing that the sleep patterns of many mammals can be explained by the mutual inhibition model. Secondly, we show that when sleep deprivation disrupts the sleep-wake cycle, ostensibly different measures of sleepiness in the two models are closely related. The demonstration of the mathematical similarities of the two models is valuable because not only does it allow some features of the two-process model to be interpreted physiologically but it also means that knowledge gained from study of the two-process model can be used to inform understanding of the behaviour of the mutual inhibition model. This is important because the mutual inhibition model and its extensions are increasingly being used as a tool to understand a diverse range of sleep-wake phenomena such as the design of optimal shift-patterns, yet the values it uses for parameters associated with the circadian and homeostatic processes are very different from those that have been experimentally measured in the context of the two-process model.

  13. Mathematical models for sleep-wake dynamics: comparison of the two-process model and a mutual inhibition neuronal model.

    Science.gov (United States)

    Skeldon, Anne C; Dijk, Derk-Jan; Derks, Gianne

    2014-01-01

    Sleep is essential for the maintenance of the brain and the body, yet many features of sleep are poorly understood and mathematical models are an important tool for probing proposed biological mechanisms. The most well-known mathematical model of sleep regulation, the two-process model, models the sleep-wake cycle by two oscillators: a circadian oscillator and a homeostatic oscillator. An alternative, more recent, model considers the mutual inhibition of sleep promoting neurons and the ascending arousal system regulated by homeostatic and circadian processes. Here we show there are fundamental similarities between these two models. The implications are illustrated with two important sleep-wake phenomena. Firstly, we show that in the two-process model, transitions between different numbers of daily sleep episodes can be classified as grazing bifurcations. This provides the theoretical underpinning for numerical results showing that the sleep patterns of many mammals can be explained by the mutual inhibition model. Secondly, we show that when sleep deprivation disrupts the sleep-wake cycle, ostensibly different measures of sleepiness in the two models are closely related. The demonstration of the mathematical similarities of the two models is valuable because not only does it allow some features of the two-process model to be interpreted physiologically but it also means that knowledge gained from study of the two-process model can be used to inform understanding of the behaviour of the mutual inhibition model. This is important because the mutual inhibition model and its extensions are increasingly being used as a tool to understand a diverse range of sleep-wake phenomena such as the design of optimal shift-patterns, yet the values it uses for parameters associated with the circadian and homeostatic processes are very different from those that have been experimentally measured in the context of the two-process model.

  14. A novel method for three-dimensional culture of central nervous system neurons.

    Science.gov (United States)

    Puschmann, Till B; de Pablo, Yolanda; Zandén, Carl; Liu, Johan; Pekny, Milos

    2014-06-01

    Neuronal signal transduction and communication in vivo is based on highly complex and dynamic networks among neurons expanding in a three-dimensional (3D) manner. Studies of cell-cell communication, synaptogenesis, and neural network plasticity constitute major research areas for understanding the involvement of neurons in neurodegenerative diseases, such as Huntington's, Alzheimer's, and Parkinson's disease, and in regenerative neural plasticity responses in situations, such as neurotrauma or stroke. Various cell culture systems constitute important experimental platforms to study neuronal functions in health and disease. A major downside of the existing cell culture systems is that the alienating planar cell environment leads to aberrant cell-cell contacts and network formation and increased reactivity of cell culture-contaminating glial cells. To mimic a suitable 3D environment for the growth and investigation of neuronal networks in vitro has posed an insurmountable challenge. Here, we report the development of a novel electrospun, polyurethane nanofiber-based 3D cell culture system for the in vitro support of neuronal networks, in which neurons can grow freely in all directions and form network structures more complex than any culture system has so far been able to support. In this 3D system, neurons extend processes from their cell bodies as a function of the nanofiber diameter. The nanofiber scaffold also minimizes the reactive state of contaminating glial cells.

  15. Adaptive Neuron Model: An architecture for the rapid learning of nonlinear topological transformations

    Science.gov (United States)

    Tawel, Raoul (Inventor)

    1994-01-01

    A method for the rapid learning of nonlinear mappings and topological transformations using a dynamically reconfigurable artificial neural network is presented. This fully-recurrent Adaptive Neuron Model (ANM) network was applied to the highly degenerate inverse kinematics problem in robotics, and its performance evaluation is bench-marked. Once trained, the resulting neuromorphic architecture was implemented in custom analog neural network hardware and the parameters capturing the functional transformation downloaded onto the system. This neuroprocessor, capable of 10(exp 9) ops/sec, was interfaced directly to a three degree of freedom Heathkit robotic manipulator. Calculation of the hardware feed-forward pass for this mapping was benchmarked at approximately 10 microsec.

  16. Bacterial Toxins and the Nervous System: Neurotoxins and Multipotential Toxins Interacting with Neuronal Cells

    Science.gov (United States)

    Popoff, Michel R.; Poulain, Bernard

    2010-01-01

    Toxins are potent molecules used by various bacteria to interact with a host organism. Some of them specifically act on neuronal cells (clostridial neurotoxins) leading to characteristics neurological affections. But many other toxins are multifunctional and recognize a wider range of cell types including neuronal cells. Various enterotoxins interact with the enteric nervous system, for example by stimulating afferent neurons or inducing neurotransmitter release from enterochromaffin cells which result either in vomiting, in amplification of the diarrhea, or in intestinal inflammation process. Other toxins can pass the blood brain barrier and directly act on specific neurons. PMID:22069606

  17. Bacterial toxins and the nervous system: neurotoxins and multipotential toxins interacting with neuronal cells.

    Science.gov (United States)

    Popoff, Michel R; Poulain, Bernard

    2010-04-01

    Toxins are potent molecules used by various bacteria to interact with a host organism. Some of them specifically act on neuronal cells (clostridial neurotoxins) leading to characteristics neurological affections. But many other toxins are multifunctional and recognize a wider range of cell types including neuronal cells. Various enterotoxins interact with the enteric nervous system, for example by stimulating afferent neurons or inducing neurotransmitter release from enterochromaffin cells which result either in vomiting, in amplification of the diarrhea, or in intestinal inflammation process. Other toxins can pass the blood brain barrier and directly act on specific neurons.

  18. Astrocyte and Neuronal Plasticity in the Somatosensory System

    OpenAIRE

    Sims, Robert E.; Butcher, John B.; Parri, H. Rheinallt; Glazewski, Stanislaw

    2015-01-01

    Changing the whisker complement on a rodent's snout can lead to two forms of experience-dependent plasticity (EDP) in the neurons of the barrel cortex, where whiskers are somatotopically represented. One form, termed coding plasticity, concerns changes in synaptic transmission and connectivity between neurons. This is thought to underlie learning and memory processes and so adaptation to a changing environment. The second, called homeostatic plasticity, serves to maintain a restricted dynamic...

  19. Experimentally determined chaotic phase synchronization in a neuronal system

    Science.gov (United States)

    Makarenko, Vladimir; Llinás, Rodolfo

    1998-01-01

    Mathematical analysis of the subthreshold oscillatory properties of inferior olivary neurons in vitro indicates that the oscillation is nonlinear and supports low dimensional chaotic dynamics. This property leads to the generation of complex functional states that can be attained rapidly via phase coherence that conform to the category of “generalized synchronization.” Functionally, this translates into neuronal ensemble properties that can support maximum functional permissiveness and that rapidly can transform into robustly determined multicellular coherence. PMID:9861041

  20. Myelination and node of Ranvier formation on sensory neurons in a defined in vitro system.

    Science.gov (United States)

    Rumsey, John W; McAleer, Christopher; Das, Mainak; Bhalkikar, Abhijeet; Wilson, Kerry; Stancescu, Maria; Lambert, Stephen; Hickman, James J

    2013-09-01

    One of the most important developmental modifications of the nervous system is Schwann cell myelination of axons. Schwann cells ensheath axons to create myelin segments to provide protection to the axon as well as increase the conduction of action potentials. In vitro neuronal systems provide a unique modality to study a variety of factors influencing myelination as well as diseases associated with myelin sheath degradation. This work details the development of a patterned in vitro myelinating dorsal root ganglion culture. This defined system utilized a serum-free medium in combination with a patterned substrate, utilizing the cytophobic and cytophilic molecules (poly)ethylene glycol (PEG) and N-1[3 (trimethoxysilyl) propyl] diethylenetriamine (DETA), respectively. Directional outgrowth of the neurites and subsequent myelination was controlled by surface modifications, and conformity to the pattern was measured over the duration of the experiments. The myelinated segments and nodal proteins were visualized and quantified using confocal microscopy. This tissue-engineered system provides a highly controlled, reproducible model for studying Schwann cell interactions with sensory neurons, as well as the myelination process, and its effect on neuronal plasticity and peripheral nerve regeneration. It is also compatible for use in bio-hybrid constructs to reproduce the stretch reflex arc on a chip because the media combination used is the same that we have used previously for motoneurons, muscle, and for neuromuscular junction (NMJ) formation. This work could have application for the study of demyelinating diseases such as diabetes induced peripheral neuropathy and could rapidly translate to a role in the discovery of drugs promoting enhanced peripheral nervous system (PNS) remyelination.

  1. Single Neuron PID Control of Aircraft Deicing Fluids Rapid Heating System

    OpenAIRE

    2013-01-01

    Aircraft deicing fluids rapid heating system is widely used in aircraft ground deicing to ensure that the operation of flights can be safe and efficient. Aiming at the temperature turbulence problem of aircraft deicing system, this paper presents the single neuron PID control strategy which combine the advantage of conventional PID control with artificial neuron control. The aircraft deicing fluids rapid heating system and the scheme and working principle of the system is introduced. Simulati...

  2. Inhibitory synapse formation in a co-culture model incorporating GABAergic medium spiny neurons and HEK293 cells stably expressing GABAA receptors.

    Science.gov (United States)

    Brown, Laura E; Fuchs, Celine; Nicholson, Martin W; Stephenson, F Anne; Thomson, Alex M; Jovanovic, Jasmina N

    2014-11-14

    Inhibitory neurons act in the central nervous system to regulate the dynamics and spatio-temporal co-ordination of neuronal networks. GABA (γ-aminobutyric acid) is the predominant inhibitory neurotransmitter in the brain. It is released from the presynaptic terminals of inhibitory neurons within highly specialized intercellular junctions known as synapses, where it binds to GABAA receptors (GABAARs) present at the plasma membrane of the synapse-receiving, postsynaptic neurons. Activation of these GABA-gated ion channels leads to influx of chloride resulting in postsynaptic potential changes that decrease the probability that these neurons will generate action potentials. During development, diverse types of inhibitory neurons with distinct morphological, electrophysiological and neurochemical characteristics have the ability to recognize their target neurons and form synapses which incorporate specific GABAARs subtypes. This principle of selective innervation of neuronal targets raises the question as to how the appropriate synaptic partners identify each other. To elucidate the underlying molecular mechanisms, a novel in vitro co-culture model system was established, in which medium spiny GABAergic neurons, a highly homogenous population of neurons isolated from the embryonic striatum, were cultured with stably transfected HEK293 cell lines that express different GABAAR subtypes. Synapses form rapidly, efficiently and selectively in this system, and are easily accessible for quantification. Our results indicate that various GABAAR subtypes differ in their ability to promote synapse formation, suggesting that this reduced in vitro model system can be used to reproduce, at least in part, the in vivo conditions required for the recognition of the appropriate synaptic partners and formation of specific synapses. Here the protocols for culturing the medium spiny neurons and generating HEK293 cells lines expressing GABAARs are first described, followed by detailed

  3. Non-cell autonomous influence of the astrocyte system xc− on hypoglycaemic neuronal cell death

    Directory of Open Access Journals (Sweden)

    Sandra J Hewett

    2012-02-01

    Full Text Available Despite longstanding evidence that hypoglycaemic neuronal injury is mediated by glutamate excitotoxicity, the cellular and molecular mechanisms involved remain incompletely defined. Here, we demonstrate that the excitotoxic neuronal death that follows GD (glucose deprivation is initiated by glutamate extruded from astrocytes via system xc− – an amino acid transporter that imports l-cystine and exports l-glutamate. Specifically, we find that depriving mixed cortical cell cultures of glucose for up to 8 h injures neurons, but not astrocytes. Neuronal death is prevented by ionotropic glutamate receptor antagonism and is partially sensitive to tetanus toxin. Removal of amino acids during the deprivation period prevents – whereas addition of l-cystine restores – GD-induced neuronal death, implicating the cystine/glutamate antiporter, system xc−. Indeed, drugs known to inhibit system xc− ameliorate GD-induced neuronal death. Further, a dramatic reduction in neuronal death is observed in chimaeric cultures consisting of neurons derived from WT (wild-type mice plated on top of astrocytes derived from sut mice, which harbour a naturally occurring null mutation in the gene (Slc7a11 that encodes the substrate-specific light chain of system xc− (xCT. Finally, enhancement of astrocytic system xc− expression and function via IL-1β (interleukin-1β exposure potentiates hypoglycaemic neuronal death, the process of which is prevented by removal of l-cystine and/or addition of system xc− inhibitors. Thus, under the conditions of GD, our studies demonstrate that astrocytes, via system xc−, have a direct, non-cell autonomous effect on cortical neuron survival.

  4. Non-cell autonomous influence of the astrocyte system xc- on hypoglycaemic neuronal cell death.

    Science.gov (United States)

    Jackman, Nicole A; Melchior, Shannon E; Hewett, James A; Hewett, Sandra J

    2012-02-08

    Despite longstanding evidence that hypoglycaemic neuronal injury is mediated by glutamate excitotoxicity, the cellular and molecular mechanisms involved remain incompletely defined. Here, we demonstrate that the excitotoxic neuronal death that follows GD (glucose deprivation) is initiated by glutamate extruded from astrocytes via system xc---an amino acid transporter that imports L-cystine and exports L-glutamate. Specifically, we find that depriving mixed cortical cell cultures of glucose for up to 8 h injures neurons, but not astrocytes. Neuronal death is prevented by ionotropic glutamate receptor antagonism and is partially sensitive to tetanus toxin. Removal of amino acids during the deprivation period prevents--whereas addition of L-cystine restores--GD-induced neuronal death, implicating the cystine/glutamate antiporter, system xc-. Indeed, drugs known to inhibit system xc- ameliorate GD-induced neuronal death. Further, a dramatic reduction in neuronal death is observed in chimaeric cultures consisting of neurons derived from WT (wild-type) mice plated on top of astrocytes derived from sut mice, which harbour a naturally occurring null mutation in the gene (Slc7a11) that encodes the substrate-specific light chain of system xc- (xCT). Finally, enhancement of astrocytic system xc- expression and function via IL-1β (interleukin-1β) exposure potentiates hypoglycaemic neuronal death, the process of which is prevented by removal of l-cystine and/or addition of system xc- inhibitors. Thus, under the conditions of GD, our studies demonstrate that astrocytes, via system xc-, have a direct, non-cell autonomous effect on cortical neuron survival.

  5. Non-Cell Autonomous Influence of the Astrocyte System xc − on Hypoglycaemic Neuronal Cell Death

    Directory of Open Access Journals (Sweden)

    Nicole A Jackman

    2012-01-01

    Full Text Available Despite longstanding evidence that hypoglycaemic neuronal injury is mediated by glutamate excitotoxicity, the cellular and molecular mechanisms involved remain incompletely defined. Here, we demonstrate that the excitotoxic neuronal death that follows GD (glucose deprivation is initiated by glutamate extruded from astrocytes via system xc −– – an amino acid transporter that imports L-cystine and exports L-glutamate. Specifically, we find that depriving mixed cortical cell cultures of glucose for up to 8 h injures neurons, but not astrocytes. Neuronal death is prevented by ionotropic glutamate receptor antagonism and is partially sensitive to tetanus toxin. Removal of amino acids during the deprivation period prevents – whereas addition of L-cystine restores – GD-induced neuronal death, implicating the cystine/glutamate antiporter, system xc−–. Indeed, drugs known to inhibit system xc −– ameliorate GD-induced neuronal death. Further, a dramatic reduction in neuronal death is observed in chimaeric cultures consisting of neurons derived from WT (wild-type mice plated on top of astrocytes derived from sut mice, which harbour a naturally occurring null mutation in the gene (Slc7a11 that encodes the substrate-specific light chain of system xc −– (xCT. Finally, enhancement of astrocytic system xc −– expression and function via IL-1β (interleukin-1β exposure potentiates hypoglycaemic neuronal death, the process of which is prevented by removal of L-cystine and/or addition of system xc −– inhibitors. Thus, under the conditions of GD, our studies demonstrate that astrocytes, via system xc −–, have a direct, non-cell autonomous effect on cortical neuron survival.

  6. Establishment of a mechanical injury model of rat hippocampal neurons in vitro

    Institute of Scientific and Technical Information of China (English)

    YANG Xiao-feng; CAO Fei; PAN De-sheng; LIU Wei-guo; HU Wei-wei; ZHENG Xiu-jue; ZHAO Xue-qun; L(U) Shi-ting

    2006-01-01

    Objective:To establish a simple, reproducible, and practical mechanical injury model of hippocampal neurons of Sprague-Dawley rats in vitro.Methods: Hippocampal neurons isolated from1-2-day old rats were cultured in vitro. Mild, moderate and severe mechanical injuries were delivered to the neurons by syringe needle tearing, respectively. The control neurons were treated identically with the exception of trauma. Cell damage was assessed by measuring the Propidium Iodide(PI) uptaking at different time points (0.5, 1, 6, 12 and24 hours) after injury. The concentration of neuron specific enolase was also measured at some time points.Results: Pathological examination showed that degeneration, degradation and necrosis occurred in the injured cultured neurons. Compared with the control group, the ratio of PI-positive cells in the injured groups increased significantly after 30 minutes of injury (P <0.05). More severe the damage was, more PI-positive neurons were detected. Compared with the control group,the concentration of neuron specific enolase in the injured culture increased significantly after 1 hour of injury (P <0.05).Conclusions: The established model of hippocampal neuron injury in vitro can be repeated easily and can simulate the damage mechanism of traumatic brain injury,which can be used in the future research of traumatic brain injury.

  7. Non-Neuronal Cells Are Required to Mediate the Effects of Neuroinflammation: Results from a Neuron-Enriched Culture System.

    Directory of Open Access Journals (Sweden)

    Chin Wai Hui

    Full Text Available Chronic inflammation is associated with activated microglia and reactive astrocytes and plays an important role in the pathogenesis of neurodegenerative diseases such as Alzheimer's. Both in vivo and in vitro studies have demonstrated that inflammatory cytokine responses to immune challenges contribute to neuronal death during neurodegeneration. In order to investigate the role of glial cells in this phenomenon, we developed a modified method to remove the non-neuronal cells in primary cultures of E16.5 mouse cortex. We modified previously reported methods as we found that a brief treatment with the thymidine analog, 5-fluorodeoxyuridine (FdU, is sufficient to substantially deplete dividing non-neuronal cells in primary cultures. Cell cycle and glial markers confirm the loss of ~99% of all microglia, astrocytes and oligodendrocyte precursor cells (OPCs. More importantly, under this milder treatment, the neurons suffered neither cell loss nor any morphological defects up to 2.5 weeks later; both pre- and post-synaptic markers were retained. Further, neurons in FdU-treated cultures remained responsive to excitotoxicity induced by glutamate application. The immunobiology of the FdU culture, however, was significantly changed. Compared with mixed culture, the protein levels of NFκB p65 and the gene expression of several cytokine receptors were altered. Individual cytokines or conditioned medium from β-amyloid-stimulated THP-1 cells that were, potent neurotoxins in normal, mixed cultures, were virtually inactive in the absence of glial cells. The results highlight the importance of our glial-depleted culture system and identifies and offer unexpected insights into the complexity of -brain neuroinflammation.

  8. Simple cortical and thalamic neuron models for digital arithmetic circuit implementation

    Directory of Open Access Journals (Sweden)

    Takuya eNanami

    2016-05-01

    Full Text Available Trade-off between reproducibility of neuronal activities and computational efficiency is one ofcrucial subjects in computational neuroscience and neuromorphic engineering. A wide variety ofneuronal models have been studied from different viewpoints. The digital spiking silicon neuron(DSSN model is a qualitative model that focuses on efficient implementation by digital arithmeticcircuits. We expanded the DSSN model and found appropriate parameter sets with which itreproduces the dynamical behaviors of the ionic-conductance models of four classes of corticaland thalamic neurons. We first developed a 4-variable model by reducing the number of variablesin the ionic-conductance models and elucidated its mathematical structures using bifurcationanalysis. Then, expanded DSSN models were constructed that reproduce these mathematicalstructures and capture the characteristic behavior of each neuron class. We confirmed thatstatistics of the neuronal spike sequences are similar in the DSSN and the ionic-conductancemodels. Computational cost of the DSSN model is larger than that of the recent sophisticatedIntegrate-and-Fire-based models, but smaller than the ionic-conductance models. This modelis intended to provide another meeting point for above trade-off that satisfies the demand forlarge-scale neuronal network simulation with closer-to-biology models.

  9. The impact of neuronal Notch-1/JNK pathway on intracerebral hemorrhage-induced neuronal injury of rat model.

    Science.gov (United States)

    Chen, Maohua; Sun, Jun; Lu, Chuan; Chen, Xiandong; Ba, Huajun; Lin, Qun; Cai, Jianyong; Dai, Junxia

    2016-11-08

    Notch signaling is a highly conserved pathway that regulates cell fate decisions during embryonic development. Notch activation endangers neurons by modulating NF-κB and HIF-1α pathways, however, the role of Notch signaling in activating JNK/c-Jun following intracerebral hemorrhage (ICH) has not been investigated. In this study, we used rat ICH models and thrombin-induced cell models to investigate the potential role of Notch-1/JNK signals. Our findings revealed that Notch-1 and JNK increased in hematoma-surrounding neurons tissues following ICH during ischemic conditions (all pNotch-1, p-JNK, and active caspase-3 were all up-regulated in cell viability-decreasing ICH cell models (all pNotch-1 or JNK suppressed the phosphorylation of JNK and the expression of active caspase-3, and cell viability was obviously ameliorated. In conclusion, this work suggested Notch-1 activates JNK pathway to induce the active caspase-3, leading to neuronal injury when intracerebral hemorrhage or ischemia occurred. Thus the Notch-1/JNK signal pathway has an important role in ICH process, and may be a therapeutic target to prevent brain injury.

  10. Sprouty2 and -4 hypomorphism promotes neuronal survival and astrocytosis in a mouse model of kainic acid induced neuronal damage.

    Science.gov (United States)

    Thongrong, Sitthisak; Hausott, Barbara; Marvaldi, Letizia; Agostinho, Alexandra S; Zangrandi, Luca; Burtscher, Johannes; Fogli, Barbara; Schwarzer, Christoph; Klimaschewski, Lars

    2016-05-01

    Sprouty (Spry) proteins play a key role as negative feedback inhibitors of the Ras/Raf/MAPK/ERK pathway downstream of various receptor tyrosine kinases. Among the four Sprouty isoforms, Spry2 and Spry4 are expressed in the hippocampus. In this study, possible effects of Spry2 and Spry4 hypomorphism on neurodegeneration and seizure thresholds in a mouse model of epileptogenesis was analyzed. The Spry2/4 hypomorphs exhibited stronger ERK activation which was limited to the CA3 pyramidal cell layer and to the hilar region. The seizure threshold of Spry2/4(+/-) mice was significantly reduced at naive state but no difference to wildtype mice was observed 1 month following KA treatment. Histomorphological analysis revealed that dentate granule cell dispersion (GCD) was diminished in Spry2/4(+/-) mice in the subchronic phase after KA injection. Neuronal degeneration was reduced in CA1 and CA3 principal neuron layers as well as in scattered neurons of the contralateral CA1 and hilar regions. Moreover, Spry2/4 reduction resulted in enhanced survival of somatostatin and neuropeptide Y expressing interneurons. GFAP staining intensity and number of reactive astrocytes markedly increased in lesioned areas of Spry2/4(+/-) mice as compared with wildtype mice. Taken together, although the seizure threshold is reduced in naive Spry2/4(+/-) mice, neurodegeneration and GCD is mitigated following KA induced hippocampal lesions, identifying Spry proteins as possible pharmacological targets in brain injuries resulting in neurodegeneration. The present data are consistent with the established functions of the ERK pathway in astrocyte proliferation as well as protection from neuronal cell death and suggest a novel role of Spry proteins in the migration of differentiated neurons.

  11. A model explaining synchronization of neuron bioelectric frequency under weak alternating low frequency magnetic field

    Energy Technology Data Exchange (ETDEWEB)

    Moral, A. del, E-mail: delmoral@unizar.es [Laboratorio de Magnetismo, Departamento de Física de Materia Condensada and Instituto de Ciencia de Materiales, Universidad de Zaragoza and Consejo Superior de Investigaciones Científicas, 50009 Zaragoza (Spain); Laboratorio de Magnetobiología, Departamento de Anatomía e Histología, Facultad de Medicina, Universidad de Zaragoza, 50009 Zaragoza (Spain); Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, 28223 Madrid (Spain); Azanza, María J., E-mail: mjazanza@unizar.es [Laboratorio de Magnetobiología, Departamento de Anatomía e Histología, Facultad de Medicina, Universidad de Zaragoza, 50009 Zaragoza (Spain); Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, 28223 Madrid (Spain)

    2015-03-01

    A biomagnetic-electrical model is presented that explains rather well the experimentally observed synchronization of the bioelectric potential firing rate (“frequency”), f, of single unit neurons of Helix aspersa mollusc under the application of extremely low frequency (ELF) weak alternating (AC) magnetic fields (MF). The proposed model incorporates to our widely experimentally tested model of superdiamagnetism (SD) and Ca{sup 2+} Coulomb explosion (CE) from lipid (LP) bilayer membrane (SD–CE model), the electrical quadrupolar long range interaction between the bilayer LP membranes of synchronized neuron pairs, not considered before. The quadrupolar interaction is capable of explaining well the observed synchronization. Actual extension of our SD–CE-model shows that the neuron firing frequency field, B, dependence becomes not modified, but the bioelectric frequency is decreased and its spontaneous temperature, T, dependence is modified. A comparison of the model with synchronization experimental results of pair of neurons under weak (B{sub 0}≅0.2–15 mT) AC-MF of frequency f{sub M}=50 Hz is reported. From the deduced size of synchronized LP clusters under B, is suggested the formation of small neuron networks via the membrane lipid correlation. - Highlights: • Neuron pair synchronization under low frequency alternating (AC) magnetic field (MF). • Superdiamagnetism and Ca{sup 2+} Coulomb explosion for AC MF effect in synchronized frequency. • Membrane lipid electrical quadrupolar pair interaction as synchronization mechamism. • Good agreement of model with electrophysiological experiments on mollusc Helix neurons.

  12. Novel human neuronal tau model exhibiting neurofibrillary tangles and transcellular propagation.

    Science.gov (United States)

    Reilly, Patrick; Winston, Charisse N; Baron, Kelsey R; Trejo, Margarita; Rockenstein, Edward M; Akers, Johnny C; Kfoury, Najla; Diamond, Marc; Masliah, Eliezer; Rissman, Robert A; Yuan, Shauna H

    2017-10-01

    Tauopathies are a class of neurodegenerative diseases, including Alzheimer's disease, frontotemporal dementia and progressive supranuclear palsy, which are associated with the pathological aggregation of tau protein into neurofibrillary tangles (NFT). Studies have characterized tau as a "prion-like" protein given its ability to form distinct, stable amyloid conformations capable of transcellular and multigenerational propagation in clonal fashion. It has been proposed that progression of tauopathy could be due to the prion-like propagation of tau, suggesting the possibility that end-stage pathologies, like NFT formation, may require an instigating event such as tau seeding. To investigate this, we applied a novel human induced pluripotent stem cell (hiPSC) system we have developed to serve as a human neuronal model. We introduced the tau repeat domain (tau-RD) with P301L and V337M (tau-RD-LM) mutations into hiPSC-derived neurons and observed expression of tau-RD at levels similar to total tau in postmortem AD brains. Tau aggregation occurred without the addition of recombinant tau fibrils. The conditioned media from tau-RD cultures contained tau-RD seeds, which were capable of inducing aggregate formation in homotypic mode in non-transduced recipient neuronal cultures. The resultant NFTs were thioflavin-positive, silver stain-positive, and assumed fibrillary appearance on transmission electron microscopy (TEM) with immunogold, which revealed paired helical filament 1 (PHF1)-positive NFTs, representing possible recruitment of endogenous tau in the aggregates. Functionally, expression of tau-RD caused neurotoxicity that manifested as axon retraction, synaptic density reduction, and enlargement of lysosomes. The results of our hiPSC study were reinforced by the observation that Tau-RD-LM is excreted in exosomes, which mediated the transfer of human tau to wild-type mouse neurons in vivo. Our hiPSC human neuronal system provides a model for further studies of tau

  13. Inefficient constitutive inhibition of P2X3 receptors by brain natriuretic peptide system contributes to sensitization of trigeminal sensory neurons in a genetic mouse model of familial hemiplegic migraine.

    Science.gov (United States)

    Marchenkova, Anna; Vilotti, Sandra; Ntamati, Niels; van den Maagdenberg, Arn Mjm; Nistri, Andrea

    2016-01-01

    On trigeminal ganglion neurons, pain-sensing P2X3 receptors are constitutively inhibited by brain natriuretic peptide via its natriuretic peptide receptor-A. This inhibition is associated with increased P2X3 serine phosphorylation and receptor redistribution to non-lipid raft membrane compartments. The natriuretic peptide receptor-A antagonist anantin reverses these effects. We studied whether P2X3 inhibition is dysfunctional in a genetic familial hemiplegic migraine type-1 model produced by introduction of the human pathogenic R192Q missense mutation into the mouse CACNA1A gene (knock-in phenotype). This model faithfully replicates several properties of familial hemiplegic migraine type-1, with gain-of-function of CaV2.1 Ca(2+) channels, raised levels of the algogenic peptide calcitonin gene-related peptide, and enhanced activity of P2X3 receptors in trigeminal ganglia. In knock-in neurons, anantin did not affect P2X3 receptor activity, membrane distribution, or serine phosphorylation level, implying ineffective inhibition by the constitutive brain natriuretic peptide/natriuretic peptide receptor-A pathway. However, expression and functional properties of this pathway remained intact together with its ability to downregulate TRPV1 channels. Reversing the familial hemiplegic migraine type-1 phenotype with the CaV2.1-specific antagonist, ω-agatoxin IVA restored P2X3 activity to wild-type level and enabled the potentiating effects of anantin again. After blocking calcitonin gene-related peptide receptors, P2X3 receptors exhibited wild-type properties and were again potentiated by anantin. P2X3 receptors on mouse trigeminal ganglion neurons are subjected to contrasting modulation by inhibitory brain natriuretic peptide and facilitatory calcitonin gene-related peptide that both operate via complex intracellular signaling. In the familial hemiplegic migraine type-1 migraine model, the action of calcitonin gene-related peptide appears to prevail over brain natriuretic

  14. Nonlinear Statistical Data Assimilation for HVC RA Neurons in the Avian Song System

    CERN Document Server

    Kadakia, Nirag; Breen, Daniel; Morone, Uriel; Daou, Arij; Margoliash, Daniel; DI Abarbanel, Henry

    2016-01-01

    With the goal of building a model of the HVC nucleus in the avian song system, we discuss in detail a model of HVC\\textsubscript{RA} projection neurons comprised of a somatic compartment with fast Na$^+$ and K$^+$ currents and a dendritic compartment with slower Ca$^{2+}$ dynamics. We show this model qualitatively exhibits many observed electrophysiological behaviors. We then show in numerical procedures how one can design and analyze feasible laboratory experiments that allow the estimation of all of the many parameters and unmeasured dynamical variables, give observations of the somatic voltage $V_s(t)$ alone. A key to this procedure is to initially estimate the slow dynamics associated with Ca, blocking the fast Na and K variations, and then with the Ca parameters fixed, estimate the fast Na and K dynamics. This separation of time scales provides a numerically robust method for completing the full neuron model, and the efficacy of the method is tested by prediction when observations are complete. The simul...

  15. Developmental transcriptional networks are required to maintain neuronal subtype identity in the mature nervous system.

    Directory of Open Access Journals (Sweden)

    Kevin T Eade

    Full Text Available During neurogenesis, transcription factors combinatorially specify neuronal fates and then differentiate subtype identities by inducing subtype-specific gene expression profiles. But how is neuronal subtype identity maintained in mature neurons? Modeling this question in two Drosophila neuronal subtypes (Tv1 and Tv4, we test whether the subtype transcription factor networks that direct differentiation during development are required persistently for long-term maintenance of subtype identity. By conditional transcription factor knockdown in adult Tv neurons after normal development, we find that most transcription factors within the Tv1/Tv4 subtype transcription networks are indeed required to maintain Tv1/Tv4 subtype-specific gene expression in adults. Thus, gene expression profiles are not simply "locked-in," but must be actively maintained by persistent developmental transcription factor networks. We also examined the cross-regulatory relationships between all transcription factors that persisted in adult Tv1/Tv4 neurons. We show that certain critical cross-regulatory relationships that had existed between these transcription factors during development were no longer present in the mature adult neuron. This points to key differences between developmental and maintenance transcriptional regulatory networks in individual neurons. Together, our results provide novel insight showing that the maintenance of subtype identity is an active process underpinned by persistently active, combinatorially-acting, developmental transcription factors. These findings have implications for understanding the maintenance of all long-lived cell types and the functional degeneration of neurons in the aging brain.

  16. VTA GABA neurons modulate specific learning behaviours through the control of dopamine and cholinergic systems

    Directory of Open Access Journals (Sweden)

    Meaghan C Creed

    2014-01-01

    Full Text Available The mesolimbic reward system is primarily comprised of the ventral tegmental area (VTA and the nucleus accumbens (NAc as well as their afferent and efferent connections. This circuitry is essential for learning about stimuli associated with motivationally-relevant outcomes. Moreover, addictive drugs affect and remodel this system, which may underlie their addictive properties. In addition to DA neurons, the VTA also contains approximately 30% ɣ-aminobutyric acid (GABA neurons. The task of signalling both rewarding and aversive events from the VTA to the NAc has mostly been ascribed to DA neurons and the role of GABA neurons has been largely neglected until recently. GABA neurons provide local inhibition of DA neurons and also long-range inhibition of projection regions, including the NAc. Here we review studies using a combination of in vivo and ex vivo electrophysiology, pharmacogenetic and optogenetic manipulations that have characterized the functional neuroanatomy of inhibitory circuits in the mesolimbic system, and describe how GABA neurons of the VTA regulate reward and aversion-related learning. We also discuss pharmacogenetic manipulation of this system with benzodiazepines (BDZs, a class of addictive drugs, which act directly on GABAA receptors located on GABA neurons of the VTA. The results gathered with each of these approaches suggest that VTA GABA neurons bi-directionally modulate activity of local DA neurons, underlying reward or aversion at the behavioural level. Conversely, long-range GABA projections from the VTA to the NAc selectively target cholinergic interneurons (CINs to pause their firing and temporarily reduce cholinergic tone in the NAc, which modulates associative learning. Further characterization of inhibitory circuit function within and beyond the VTA is needed in order to fully understand the function of the mesolimbic system under normal and pathological conditions.

  17. Behavioral constraints in the development of neuronal properties: a cortical model embedded in a real-world device.

    Science.gov (United States)

    Almássy, N; Edelman, G M; Sporns, O

    1998-06-01

    The ability of organisms to categorize diverse and often novel stimuli depends on ongoing interactions with their environment. In a modality such as vision, categorization requires the generation of both selective and invariant responses of cortical neurons to complex visual stimuli. How does behavior contribute to shaping the responses of these neurons? Analysis of this question is made difficult by the complex multilevel interactions between many neural and behavioral variables. To mitigate this difficulty, we studied the development and ongoing plasticity of pattern-selective neuronal responses by means of synthetic neural modeling. For this purpose, we constructed Darwin V, which consists of a simulated neuronal model embedded in a real-world device that is capable of motion and autonomous behavior. The neuronal model consists of four major components: a visual system (containing cortical and subcortical networks); a taste system based on conductance; sets of motor neurons capable of triggering behavior; and a diffuse ascending (value) system. The modeled visual cortex consists of two areas: a topographic map responsive to elementary features connected to a higher-order map composed of initially non-selective neuronal units. During behavior over time in its environment, Darwin V encounters numerous objects consisting of black metal cubes displaying different patterns of white blobs and stripes. Initially, the lack of specific higher-order visual responses does not allow visual pattern discrimination, and appetitive and aversive behaviors are triggered by the 'taste' (surface conductivity of objects) alone. In the course of sensory experience, however, changes occur in visual and sensorimotor connection strengths, with two major consequences. First, units within the higher visual area acquire responses that are both pattern selective and translation invariant. Second, as a result of the operation of the value system, these responses become linked to appropriate

  18. Self-Organized Criticality in a Simple Neuron Model Based on Scale-Free Networks

    Institute of Scientific and Technical Information of China (English)

    LIN Min; WANG Gang; CHEN Tian-Lun

    2006-01-01

    A simple model for a set of interacting idealized neurons in scale-free networks is introduced. The basic elements of the model are endowed with the main features of a neuron function. We find that our model displays powerlaw behavior of avalanche sizes and generates long-range temporal correlation. More importantly, we find different dynamical behavior for nodes with different connectivity in the scale-free networks.

  19. Nonlinear Maps for Design of Discrete-Time Models of Neuronal Network Dynamics

    Science.gov (United States)

    2016-03-31

    responsive tiring patterns . We propose to use modern DSP ideas to develop new efficient approaches to the design of such discrete-time models for...2016 Performance/Technic~ 03-01-2016- 03-31-2016 4. TITLE AND SUBTITLE Sa. CONTRACT NUMBER Nonlinear Maps for Design of Discrete-Time Models of...simulations is to design a neuronal model in the form of difference equations that generates neuronal states in discrete moments of time. In this

  20. A Neuronal Model of Predictive Coding Accounting for the Mismatch Negativity

    OpenAIRE

    Wacongne, Catherine; Changeux, Jean-Pierre; Dehaene, Stanislas

    2012-01-01

    International audience; The mismatch negativity (MMN) is thought to index the activation of specialized neural networks for active prediction and deviance detection. However, a detailed neuronal model of the neurobiological mechanisms underlying the MMN is still lacking, and its computational foundations remain debated. We propose here a detailed neuronal model of auditory cortex, based on predictive coding, that accounts for the critical features of MMN. The model is entirely composed of spi...

  1. Modeling ALS with motor neurons derived from human induced pluripotent stem cells.

    Science.gov (United States)

    Sances, Samuel; Bruijn, Lucie I; Chandran, Siddharthan; Eggan, Kevin; Ho, Ritchie; Klim, Joseph R; Livesey, Matt R; Lowry, Emily; Macklis, Jeffrey D; Rushton, David; Sadegh, Cameron; Sareen, Dhruv; Wichterle, Hynek; Zhang, Su-Chun; Svendsen, Clive N

    2016-04-01

    Directing the differentiation of induced pluripotent stem cells into motor neurons has allowed investigators to develop new models of amyotrophic lateral sclerosis (ALS). However, techniques vary between laboratories and the cells do not appear to mature into fully functional adult motor neurons. Here we discuss common developmental principles of both lower and upper motor neuron development that have led to specific derivation techniques. We then suggest how these motor neurons may be matured further either through direct expression or administration of specific factors or coculture approaches with other tissues. Ultimately, through a greater understanding of motor neuron biology, it will be possible to establish more reliable models of ALS. These in turn will have a greater chance of validating new drugs that may be effective for the disease.

  2. A Millimetre-sized Robot Realized by a Piezoelectric Impact-type Rotary Actuator and a Hardware Neuron Model

    Directory of Open Access Journals (Sweden)

    Minami Takato

    2014-07-01

    Full Text Available Micro-robotic systems are increasingly used in medicine and other fields requiring precision engineering. This paper proposes a piezoelectric impact- type rotary actuator and applies it to a millimetre-size robot controlled by a hardware neuron model. The rotary actuator and robot are fabricated by micro-electro- mechanical systems (MEMS technology. The actuator is composed of multilayer piezoelectric elements. The rotational motion of the rotor is generated by the impact head attached to the piezoelectric element. The millimetre-size robot is fitted with six legs, three on either side of the developed actuator, and can walk on uneven surfaces like an insect. The three leg parts on each side are connected by a linking mechanism. The control system is a hardware neuron model constructed from analogue electronic circuits that mimic the behaviour of biological neurons. The output signal ports of the controller are connected to the multilayer piezoelectric element. This robot system requires no specialized software programs or A/D converters. The rotation speed of the rotary actuator reaches 60 rpm at an applied neuron frequency of 25 kHz during the walking motion. The width, length and height of the robot are 4.0, 4.6 and 3.6 mm, respectively. The motion speed is 180 mm/min.

  3. The Emergence of Synaesthesia in a Neuronal Network Model via Changes in Perceptual Sensitivity and Plasticity

    Science.gov (United States)

    Ward, Jamie

    2016-01-01

    Synaesthesia is an unusual perceptual experience in which an inducer stimulus triggers a percept in a different domain in addition to its own. To explore the conditions under which synaesthesia evolves, we studied a neuronal network model that represents two recurrently connected neural systems. The interactions in the network evolve according to learning rules that optimize sensory sensitivity. We demonstrate several scenarios, such as sensory deprivation or heightened plasticity, under which synaesthesia can evolve even though the inputs to the two systems are statistically independent and the initial cross-talk interactions are zero. Sensory deprivation is the known causal mechanism for acquired synaesthesia and increased plasticity is implicated in developmental synaesthesia. The model unifies different causes of synaesthesia within a single theoretical framework and repositions synaesthesia not as some quirk of aberrant connectivity, but rather as a functional brain state that can emerge as a consequence of optimising sensory information processing. PMID:27392215

  4. The Emergence of Synaesthesia in a Neuronal Network Model via Changes in Perceptual Sensitivity and Plasticity.

    Science.gov (United States)

    Shriki, Oren; Sadeh, Yaniv; Ward, Jamie

    2016-07-01

    Synaesthesia is an unusual perceptual experience in which an inducer stimulus triggers a percept in a different domain in addition to its own. To explore the conditions under which synaesthesia evolves, we studied a neuronal network model that represents two recurrently connected neural systems. The interactions in the network evolve according to learning rules that optimize sensory sensitivity. We demonstrate several scenarios, such as sensory deprivation or heightened plasticity, under which synaesthesia can evolve even though the inputs to the two systems are statistically independent and the initial cross-talk interactions are zero. Sensory deprivation is the known causal mechanism for acquired synaesthesia and increased plasticity is implicated in developmental synaesthesia. The model unifies different causes of synaesthesia within a single theoretical framework and repositions synaesthesia not as some quirk of aberrant connectivity, but rather as a functional brain state that can emerge as a consequence of optimising sensory information processing.

  5. The Emergence of Synaesthesia in a Neuronal Network Model via Changes in Perceptual Sensitivity and Plasticity.

    Directory of Open Access Journals (Sweden)

    Oren Shriki

    2016-07-01

    Full Text Available Synaesthesia is an unusual perceptual experience in which an inducer stimulus triggers a percept in a different domain in addition to its own. To explore the conditions under which synaesthesia evolves, we studied a neuronal network model that represents two recurrently connected neural systems. The interactions in the network evolve according to learning rules that optimize sensory sensitivity. We demonstrate several scenarios, such as sensory deprivation or heightened plasticity, under which synaesthesia can evolve even though the inputs to the two systems are statistically independent and the initial cross-talk interactions are zero. Sensory deprivation is the known causal mechanism for acquired synaesthesia and increased plasticity is implicated in developmental synaesthesia. The model unifies different causes of synaesthesia within a single theoretical framework and repositions synaesthesia not as some quirk of aberrant connectivity, but rather as a functional brain state that can emerge as a consequence of optimising sensory information processing.

  6. Effect of deep brain stimulation on substantia nigra neurons in a rat model of Parkinson's disease

    Institute of Scientific and Technical Information of China (English)

    WU Sheng-tian; MA Yu; ZHANG Kai; ZHANG Jian-guo

    2012-01-01

    Background Parkinson's disease(PD)is a common neurodegenerative disease,which occurs mainly in the elderly.Recent studies have demonstrated that apoptosis plays an important role in the occurrence and development of PD.Subthalamic nucleus deep brain stimulation(STN-DBS)has been recognized as an effective treatment for PD.Recent clinical observations have shown that STN-DBS was able to delay early PD progression,and experiments in animal models have also demonstrated a protective effect of STN-DBS on neurons.However,the correlation between the neuron-protective effect of STN-DBS and the progression of substantia nigra pars compacta(SNc)neuronal apoptosis is still unknown.The aim of this study was to investigate the protective effect and potential mechanism of STN-DBS on SNc neurons in PD rats.Methods After the establishment of a PD rat model by unilateral/2-point injection of 6-hydroxydopamine in the medial forebrain bundle of the brain,DBS by implanting electrodes in the STN was administered.Behavioral changes were observed,and morphological changes of SNc neurons were analyzed by Nissl staining and DNA in situ end-labeling.Through extracellular recording of single neuron discharges and microelectrophoresis,the causes of and changes in SNc excitability during STN-DBS were analyzed,and the protective effect and potential mechanism of action of STN-DBS on SNc neurons in PD rats was investigated.Results SNc neuron apoptosis was significantly decreased(P<0.05)in the stimulation group,compared with the sham stimulation PD group.Spontaneous discharges of SNc neurons were observed in normal rats and PD model rats,and the mean frequency of spontaneous discharges of SNc neurons in normal rats((40.65±11.08)Hz)was higher than that of residual SNc neurons in PD rats((36.71±9.23)Hz).Electrical stimulation of the STN in rats was associated with elevated excitation in unilateral SNc neurons.However,administering the gamma-aminobutyric acid receptor blocker

  7. The mirror neuron system in post-stroke rehabilitation

    Science.gov (United States)

    2013-01-01

    Different treatments for stroke patients have been proposed; among them the mirror therapy and motion imagery lead to functional recovery by providing a cortical reorganization. Up today the basic concepts of the current literature on mirror neurons and the major findings regarding the use of mirror therapy and motor imagery as potential tools to promote reorganization and functional recovery in post-stroke patients. Bibliographic research was conducted based on publications over the past thirteen years written in English in the databases Scielo, Pubmed/MEDLINE, ISI Web of Knowledge. The studies showed how the interaction among vision, proprioception and motor commands promotes the recruitment of mirror neurons, thus providing cortical reorganization and functional recovery of post-stroke patients. We conclude that the experimental advances on Mirror Neurons will bring new rational therapeutic approaches to post-stroke rehabilitation. PMID:24134862

  8. AAV Vector-Mediated Gene Delivery to Substantia Nigra Dopamine Neurons: Implications for Gene Therapy and Disease Models

    Directory of Open Access Journals (Sweden)

    Katrina Albert

    2017-02-01

    Full Text Available Gene delivery using adeno-associated virus (AAV vectors is a widely used method to transduce neurons in the brain, especially due to its safety, efficacy, and long-lasting expression. In addition, by varying AAV serotype, promotor, and titer, it is possible to affect the cell specificity of expression or the expression levels of the protein of interest. Dopamine neurons in the substantia nigra projecting to the striatum, comprising the nigrostriatal pathway, are involved in movement control and degenerate in Parkinson′s disease. AAV-based gene targeting to the projection area of these neurons in the striatum has been studied extensively to induce the production of neurotrophic factors for disease-modifying therapies for Parkinson′s disease. Much less emphasis has been put on AAV-based gene therapy targeting dopamine neurons in substantia nigra. We will review the literature related to targeting striatum and/or substantia nigra dopamine neurons using AAVs in order to express neuroprotective and neurorestorative molecules, as well as produce animal disease models of Parkinson′s disease. We discuss difficulties in targeting substantia nigra dopamine neurons and their vulnerability to stress in general. Therefore, choosing a proper control for experimental work is not trivial. Since the axons along the nigrostriatal tract are the first to degenerate in Parkinson′s disease, the location to deliver the therapy must be carefully considered. We also review studies using AAV-a-synuclein (a-syn to target substantia nigra dopamine neurons to produce an α-syn overexpression disease model in rats. Though these studies are able to produce mild dopamine system degeneration in the striatum and substantia nigra and some behavioural effects, there are studies pointing to the toxicity of AAV-carrying green fluorescent protein (GFP, which is often used as a control. Therefore, we discuss the potential difficulties in overexpressing proteins in general in

  9. Implementation of an integrated op-amp based chaotic neuron model and observation of its chaotic dynamics.

    Science.gov (United States)

    Jung, Jinwoo; Lee, Jewon; Song, Hanjung

    2011-03-01

    This paper presents a fully integrated circuit implementation of an operational amplifier (op-amp) based chaotic neuron model with a bipolar output function, experimental measurements, and analyses of its chaotic behavior. The proposed chaotic neuron model integrated circuit consists of several op-amps, sample and hold circuits, a nonlinear function block for chaotic signal generation, a clock generator, a nonlinear output function, etc. Based on the HSPICE (circuit program) simulation results, approximated empirical equations for analyses were formulated. Then, the chaotic dynamical responses such as bifurcation diagrams, time series, and Lyapunov exponent were calculated using these empirical equations. In addition, we performed simulations about two chaotic neuron systems with four synapses to confirm neural network connections and got normal behavior of the chaotic neuron such as internal state bifurcation diagram according to the synaptic weight variation. The proposed circuit was fabricated using a 0.8-μm single poly complementary metal-oxide semiconductor technology. Measurements of the fabricated single chaotic neuron with ± 2.5 V power supplies and a 10 kHz sampling clock frequency were carried out and compared with the simulated results.

  10. Interplay between inflammation, immune system and neuronal pathways: effect on gastrointestinal motility.

    Science.gov (United States)

    De Winter, Benedicte-Y; De Man, Joris-G

    2010-11-28

    Sepsis is a systemic inflammatory response representing the leading cause of death in critically ill patients, mostly due to multiple organ failure. The gastrointestinal tract plays a pivotal role in the pathogenesis of sepsis-induced multiple organ failure through intestinal barrier dysfunction, bacterial translocation and ileus. In this review we address the role of the gastrointestinal tract, the mediators, cell types and transduction pathways involved, based on experimental data obtained from models of inflammation-induced ileus and (preliminary) clinical data. The complex interplay within the gastrointestinal wall between mast cells, residential macrophages and glial cells on the one hand, and neurons and smooth muscle cells on the other hand, involves intracellular signaling pathways, Toll-like receptors and a plethora of neuroactive substances such as nitric oxide, prostaglandins, cytokines, chemokines, growth factors, tryptases and hormones. Multidirectional signaling between the different components in the gastrointestinal wall, the spinal cord and central nervous system impacts inflammation and its consequences. We propose that novel therapeutic strategies should target inflammation on the one hand and gastrointestinal motility, gastrointestinal sensitivity and even pain signaling on the other hand, for instance by impeding afferent neuronal signaling, by activation of the vagal anti-inflammatory pathway or by the use of pharmacological agents such as ghrelin and ghrelin agonists or drugs interfering with the endocannabinoid system.

  11. Low-Gain, Low-Noise Integrated Neuronal Amplifier for Implantable Artifact-Reduction Recording System

    Directory of Open Access Journals (Sweden)

    Abdelhamid Benazzouz

    2013-09-01

    Full Text Available Brain neuroprostheses for neuromodulation are being designed to monitor the neural activity of the brain in the vicinity of the region being stimulated using a single macro-electrode. Using a single macro-electrode, recent neuromodulation studies show that recording systems with a low gain neuronal amplifier and successive amplifier stages can reduce or reject stimulation artifacts. These systems were made with off-the-shelf components that are not amendable for future implant design. A low-gain, low-noise integrated neuronal amplifier (NA with the capability of recording local field potentials (LFP and spike activity is presented. In vitro and in vivo characterizations of the tissue/electrode interface, with equivalent impedance as an electrical model for recording in the LFP band using macro-electrodes for rodents, contribute to the NA design constraints. The NA occupies 0.15 mm2 and dissipates 6.73 µW, and was fabricated using a 0.35 µm CMOS process. Test-bench validation indicates that the NA provides a mid-band gain of 20 dB and achieves a low input-referred noise of 4 µVRMS. Ability of the NA to perform spike recording in test-bench experiments is presented. Additionally, an awake and freely moving rodent setup was used to illustrate the integrated NA ability to record LFPs, paving the pathway for future implantable systems for neuromodulation.

  12. Quantitative 3D investigation of Neuronal network in mouse spinal cord model

    Science.gov (United States)

    Bukreeva, I.; Campi, G.; Fratini, M.; Spanò, R.; Bucci, D.; Battaglia, G.; Giove, F.; Bravin, A.; Uccelli, A.; Venturi, C.; Mastrogiacomo, M.; Cedola, A.

    2017-01-01

    The investigation of the neuronal network in mouse spinal cord models represents the basis for the research on neurodegenerative diseases. In this framework, the quantitative analysis of the single elements in different districts is a crucial task. However, conventional 3D imaging techniques do not have enough spatial resolution and contrast to allow for a quantitative investigation of the neuronal network. Exploiting the high coherence and the high flux of synchrotron sources, X-ray Phase-Contrast multiscale-Tomography allows for the 3D investigation of the neuronal microanatomy without any aggressive sample preparation or sectioning. We investigated healthy-mouse neuronal architecture by imaging the 3D distribution of the neuronal-network with a spatial resolution of 640 nm. The high quality of the obtained images enables a quantitative study of the neuronal structure on a subject-by-subject basis. We developed and applied a spatial statistical analysis on the motor neurons to obtain quantitative information on their 3D arrangement in the healthy-mice spinal cord. Then, we compared the obtained results with a mouse model of multiple sclerosis. Our approach paves the way to the creation of a “database” for the characterization of the neuronal network main features for a comparative investigation of neurodegenerative diseases and therapies.

  13. The angiotensin converting enzyme inhibitor captopril protects nigrostriatal dopamine neurons in animal models of parkinsonism.

    Science.gov (United States)

    Sonsalla, Patricia K; Coleman, Christal; Wong, Lai-Yoong; Harris, Suzan L; Richardson, Jason R; Gadad, Bharathi S; Li, Wenhao; German, Dwight C

    2013-12-01

    Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by a prominent loss of nigrostriatal dopamine (DA) neurons with an accompanying neuroinflammation. The peptide angiotensin II (AngII) plays a role in oxidative-stress induced disorders and is thought to mediate its detrimental actions via activation of AngII AT1 receptors. The brain renin-angiotensin system is implicated in neurodegenerative disorders including PD. Blockade of the angiotensin converting enzyme or AT1 receptors provides protection in acute animal models of parkinsonism. We demonstrate here that treatment of mice with the angiotensin converting enzyme inhibitor captopril protects the striatum from acutely administered 1-methyl-4-phenyl-1,2,3,6-tetrahydropyrine (MPTP), and that chronic captopril protects the nigral DA cell bodies from degeneration in a progressive rat model of parkinsonism created by the chronic intracerebral infusion of 1-methyl-4-phenylpyridinium (MPP+). The accompanying activation of microglia in the substantia nigra of MPP+-treated rats was reduced by the chronic captopril treatment. These findings indicate that captopril is neuroprotective for nigrostriatal DA neurons in both acute and chronic rodent PD models. Targeting the brain AngII pathway may be a feasible approach to slowing neurodegeneration in PD. © 2013.

  14. The tumor suppressor HHEX inhibits axon growth when prematurely expressed in developing central nervous system neurons.

    Science.gov (United States)

    Simpson, Matthew T; Venkatesh, Ishwariya; Callif, Ben L; Thiel, Laura K; Coley, Denise M; Winsor, Kristen N; Wang, Zimei; Kramer, Audra A; Lerch, Jessica K; Blackmore, Murray G

    2015-09-01

    Neurons in the embryonic and peripheral nervous system respond to injury by activating transcriptional programs supportive of axon growth, ultimately resulting in functional recovery. In contrast, neurons in the adult central nervous system (CNS) possess a limited capacity to regenerate axons after injury, fundamentally constraining repair. Activating pro-regenerative gene expression in CNS neurons is a promising therapeutic approach, but progress is hampered by incomplete knowledge of the relevant transcription factors. An emerging hypothesis is that factors implicated in cellular growth and motility outside the nervous system may also control axon growth in neurons. We therefore tested sixty-nine transcription factors, previously identified as possessing tumor suppressive or oncogenic properties in non-neuronal cells, in assays of neurite outgrowth. This screen identified YAP1 and E2F1 as enhancers of neurite outgrowth, and PITX1, RBM14, ZBTB16, and HHEX as inhibitors. Follow-up experiments are focused on the tumor suppressor HHEX, one of the strongest growth inhibitors. HHEX is widely expressed in adult CNS neurons, including corticospinal tract neurons after spinal injury, but is present only in trace amounts in immature cortical neurons and adult peripheral neurons. HHEX overexpression in early postnatal cortical neurons reduced both initial axonogenesis and the rate of axon elongation, and domain deletion analysis strongly implicated transcriptional repression as the underlying mechanism. These findings suggest a role for HHEX in restricting axon growth in the developing CNS, and substantiate the hypothesis that previously identified oncogenes and tumor suppressors can play conserved roles in axon extension. Copyright © 2015 Elsevier Inc. All rights reserved.

  15. Modeling and analysis of the molecular basis of pain in sensory neurons.

    Directory of Open Access Journals (Sweden)

    Sang Ok Song

    Full Text Available Intracellular calcium dynamics are critical to cellular functions like pain transmission. Extracellular ATP plays an important role in modulating intracellular calcium levels by interacting with the P2 family of surface receptors. In this study, we developed a mechanistic mathematical model of ATP-induced P2 mediated calcium signaling in archetype sensory neurons. The model architecture, which described 90 species connected by 162 interactions, was formulated by aggregating disparate molecular modules from literature. Unlike previous models, only mass action kinetics were used to describe the rate of molecular interactions. Thus, the majority of the 252 unknown model parameters were either association, dissociation or catalytic rate constants. Model parameters were estimated from nine independent data sets taken from multiple laboratories. The training data consisted of both dynamic and steady-state measurements. However, because of the complexity of the calcium network, we were unable to estimate unique model parameters. Instead, we estimated a family or ensemble of probable parameter sets using a multi-objective thermal ensemble method. Each member of the ensemble met an error criterion and was located along or near the optimal trade-off surface between the individual training data sets. The model quantitatively reproduced experimental measurements from dorsal root ganglion neurons as a function of extracellular ATP forcing. Hypothesized architecture linking phosphoinositide regulation with P2X receptor activity explained the inhibition of P2X-mediated current flow by activated metabotropic P2Y receptors. Sensitivity analysis using individual and the whole system outputs suggested which molecular subsystems were most important following P2 activation. Taken together, modeling and analysis of ATP-induced P2 mediated calcium signaling generated qualitative insight into the critical interactions controlling ATP induced calcium dynamics

  16. A model of biological neuron with terminal chaos and quantum-like features

    Energy Technology Data Exchange (ETDEWEB)

    Conte, Elio [Department of Neuroscience, Psychiatric Clinic L. Bini, Bari University, 70100 Bari (Italy); Department of Pharmacology and Human Physiology, TIRES-Center for Innovative Technology for Signal Detection and Processing, Bari University, 70100 Bari (Italy); Pierri, GianPaolo [Department of Neuroscience, Psychiatric Clinic L. Bini, Bari University, 70100 Bari (Italy); Federici, Antonio [Department of Pharmacology and Human Physiology, TIRES-Center for Innovative Technology for Signal Detection and Processing, Bari University, 70100 Bari (Italy); Mendolicchio, Leonardo [Department of Neuroscience, Psychiatric Clinic L. Bini, Bari University, 70100 Bari (Italy); Zbilut, Joseph P. [Department of Molecular Biophysics and Physiology, Rush University, Chicago, IL 60612 (United States)

    2006-11-15

    A model of biological neuron is proposed combining terminal dynamics with quantum-like mechanical features, assuming the spin to be an important entity in neurodynamics, and, in particular, in synaptic transmission.

  17. Orexin Receptor Activation Generates Gamma Band Input to Cholinergic and Serotonergic Arousal System Neurons and Drives an Intrinsic Ca2+-Dependent Resonance in LDT and PPT Cholinergic Neurons

    Science.gov (United States)

    Ishibashi, Masaru; Gumenchuk, Iryna; Kang, Bryan; Steger, Catherine; Lynn, Elizabeth; Molina, Nancy E.; Eisenberg, Leonard M.; Leonard, Christopher S.

    2015-01-01

    A hallmark of the waking state is a shift in EEG power to higher frequencies with epochs of synchronized intracortical gamma activity (30–60 Hz) – a process associated with high-level cognitive functions. The ascending arousal system, including cholinergic laterodorsal (LDT) and pedunculopontine (PPT) tegmental neurons and serotonergic dorsal raphe (DR) neurons, promotes this state. Recently, this system has been proposed as a gamma wave generator, in part, because some neurons produce high-threshold, Ca2+-dependent oscillations at gamma frequencies. However, it is not known whether arousal-related inputs to these neurons generate such oscillations, or whether such oscillations are ever transmitted to neuronal targets. Since key arousal input arises from hypothalamic orexin (hypocretin) neurons, we investigated whether the unusually noisy, depolarizing orexin current could provide significant gamma input to cholinergic and serotonergic neurons, and whether such input could drive Ca2+-dependent oscillations. Whole-cell recordings in brain slices were obtained from mice expressing Cre-induced fluorescence in cholinergic LDT and PPT, and serotonergic DR neurons. After first quantifying reporter expression accuracy in cholinergic and serotonergic neurons, we found that the orexin current produced significant high frequency, including gamma, input to both cholinergic and serotonergic neurons. Then, by using a dynamic clamp, we found that adding a noisy orexin conductance to cholinergic neurons induced a Ca2+-dependent resonance that peaked in the theta and alpha frequency range (4–14 Hz) and extended up to 100 Hz. We propose that this orexin current noise and the Ca2+ dependent resonance work synergistically to boost the encoding of high-frequency synaptic inputs into action potentials and to help ensure cholinergic neurons fire during EEG activation. This activity could reinforce thalamocortical states supporting arousal, REM sleep, and intracortical gamma. PMID

  18. Orexin Receptor Activation Generates Gamma Band Input to Cholinergic and Serotonergic Arousal System Neurons and Drives an Intrinsic Ca(2+)-Dependent Resonance in LDT and PPT Cholinergic Neurons.

    Science.gov (United States)

    Ishibashi, Masaru; Gumenchuk, Iryna; Kang, Bryan; Steger, Catherine; Lynn, Elizabeth; Molina, Nancy E; Eisenberg, Leonard M; Leonard, Christopher S

    2015-01-01

    A hallmark of the waking state is a shift in EEG power to higher frequencies with epochs of synchronized intracortical gamma activity (30-60 Hz) - a process associated with high-level cognitive functions. The ascending arousal system, including cholinergic laterodorsal (LDT) and pedunculopontine (PPT) tegmental neurons and serotonergic dorsal raphe (DR) neurons, promotes this state. Recently, this system has been proposed as a gamma wave generator, in part, because some neurons produce high-threshold, Ca(2+)-dependent oscillations at gamma frequencies. However, it is not known whether arousal-related inputs to these neurons generate such oscillations, or whether such oscillations are ever transmitted to neuronal targets. Since key arousal input arises from hypothalamic orexin (hypocretin) neurons, we investigated whether the unusually noisy, depolarizing orexin current could provide significant gamma input to cholinergic and serotonergic neurons, and whether such input could drive Ca(2+)-dependent oscillations. Whole-cell recordings in brain slices were obtained from mice expressing Cre-induced fluorescence in cholinergic LDT and PPT, and serotonergic DR neurons. After first quantifying reporter expression accuracy in cholinergic and serotonergic neurons, we found that the orexin current produced significant high frequency, including gamma, input to both cholinergic and serotonergic neurons. Then, by using a dynamic clamp, we found that adding a noisy orexin conductance to cholinergic neurons induced a Ca(2+)-dependent resonance that peaked in the theta and alpha frequency range (4-14 Hz) and extended up to 100 Hz. We propose that this orexin current noise and the Ca(2+) dependent resonance work synergistically to boost the encoding of high-frequency synaptic inputs into action potentials and to help ensure cholinergic neurons fire during EEG activation. This activity could reinforce thalamocortical states supporting arousal, REM sleep, and intracortical gamma.

  19. Orexin receptor activation generates gamma band input to cholinergic and serotonergic arousal system neurons and drives an intrinsic Ca2+-dependent resonance in LDT and PPT cholinergic neurons.

    Directory of Open Access Journals (Sweden)

    Masaru eIshibashi

    2015-06-01

    Full Text Available A hallmark of the waking state is a shift in EEG power to higher frequencies with epochs of synchronized intracortical gamma activity (30-60 Hz - a process associated with high-level cognitive functions. The ascending arousal system, including cholinergic laterodorsal (LDT and pedunculopontine (PPT tegmental neurons and serotonergic dorsal raphe (DR neurons, promotes this state. Recently, this system has been proposed as a gamma wave generator, in part, because some neurons produce high-threshold, Ca2+-dependent oscillations at gamma frequencies. However, it is not known whether arousal-related inputs to these neurons generate such oscillations, or whether such oscillations are ever transmitted to neuronal targets. Since key arousal input arises from hypothalamic orexin (hypocretin neurons, we investigated whether the unusually noisy, depolarizing orexin current could provide significant gamma input to cholinergic and serotonergic neurons, and whether such input could drive Ca2+-dependent oscillations. Whole-cell recordings in brain slices were obtained from mice expressing Cre-induced fluorescence in cholinergic LDT and PPT, and serotonergic DR neurons. After first quantifying reporter expression accuracy in cholinergic and serotonergic neurons, we found that the orexin current produced significant high frequency, including gamma, input to both cholinergic and serotonergic neurons. Then, by using a dynamic clamp, we found that adding a noisy orexin conductance to cholinergic neurons induced a Ca2+-dependent resonance that peaked in the theta and alpha frequency range (4 - 14 Hz and extended up to 100 Hz. We propose that this orexin current noise and the Ca2+ dependent resonance work synergistically to boost the encoding of high-frequency synaptic inputs into action potentials and to help ensure cholinergic neurons fire during EEG activation. This activity could reinforce thalamocortical states supporting arousal, REM sleep and intracortical

  20. Predictive features of persistent activity emergence in regular spiking and intrinsic bursting model neurons.

    Science.gov (United States)

    Sidiropoulou, Kyriaki; Poirazi, Panayiota

    2012-01-01

    Proper functioning of working memory involves the expression of stimulus-selective persistent activity in pyramidal neurons of the prefrontal cortex (PFC), which refers to neural activity that persists for seconds beyond the end of the stimulus. The mechanisms which PFC pyramidal neurons use to discriminate between preferred vs. neutral inputs at the cellular level are largely unknown. Moreover, the presence of pyramidal cell subtypes with different firing patterns, such as regular spiking and intrinsic bursting, raises the question as to what their distinct role might be in persistent firing in the PFC. Here, we use a compartmental modeling approach to search for discriminatory features in the properties of incoming stimuli to a PFC pyramidal neuron and/or its response that signal which of these stimuli will result in persistent activity emergence. Furthermore, we use our modeling approach to study cell-type specific differences in persistent activity properties, via implementing a regular spiking (RS) and an intrinsic bursting (IB) model neuron. We identify synaptic location within the basal dendrites as a feature of stimulus selectivity. Specifically, persistent activity-inducing stimuli consist of activated synapses that are located more distally from the soma compared to non-inducing stimuli, in both model cells. In addition, the action potential (AP) latency and the first few inter-spike-intervals of the neuronal response can be used to reliably detect inducing vs. non-inducing inputs, suggesting a potential mechanism by which downstream neurons can rapidly decode the upcoming emergence of persistent activity. While the two model neurons did not differ in the coding features of persistent activity emergence, the properties of persistent activity, such as the firing pattern and the duration of temporally-restricted persistent activity were distinct. Collectively, our results pinpoint to specific features of the neuronal response to a given stimulus that code

  1. Predictive features of persistent activity emergence in regular spiking and intrinsic bursting model neurons.

    Directory of Open Access Journals (Sweden)

    Kyriaki Sidiropoulou

    Full Text Available Proper functioning of working memory involves the expression of stimulus-selective persistent activity in pyramidal neurons of the prefrontal cortex (PFC, which refers to neural activity that persists for seconds beyond the end of the stimulus. The mechanisms which PFC pyramidal neurons use to discriminate between preferred vs. neutral inputs at the cellular level are largely unknown. Moreover, the presence of pyramidal cell subtypes with different firing patterns, such as regular spiking and intrinsic bursting, raises the question as to what their distinct role might be in persistent firing in the PFC. Here, we use a compartmental modeling approach to search for discriminatory features in the properties of incoming stimuli to a PFC pyramidal neuron and/or its response that signal which of these stimuli will result in persistent activity emergence. Furthermore, we use our modeling approach to study cell-type specific differences in persistent activity properties, via implementing a regular spiking (RS and an intrinsic bursting (IB model neuron. We identify synaptic location within the basal dendrites as a feature of stimulus selectivity. Specifically, persistent activity-inducing stimuli consist of activated synapses that are located more distally from the soma compared to non-inducing stimuli, in both model cells. In addition, the action potential (AP latency and the first few inter-spike-intervals of the neuronal response can be used to reliably detect inducing vs. non-inducing inputs, suggesting a potential mechanism by which downstream neurons can rapidly decode the upcoming emergence of persistent activity. While the two model neurons did not differ in the coding features of persistent activity emergence, the properties of persistent activity, such as the firing pattern and the duration of temporally-restricted persistent activity were distinct. Collectively, our results pinpoint to specific features of the neuronal response to a given

  2. Neuronal types and their specification dynamics in the autonomic nervous system

    OpenAIRE

    2016-01-01

    The autonomic nervous system is formed by a sympathetic and a parasympathetic division that have complementary roles in the maintenance of body homeostasis. Autonomic neurons, also known as visceral motor neurons, are tonically active and innervate virtually every organ in our body. For instance, cardiac outflow, thermoregulation and even the focusing of our eyes are just some of the plethora of physiological functions under the control of this system. Consequently, perturbatio...

  3. Modeling motor neuron disease : the matter of time

    NARCIS (Netherlands)

    Arbab, Mandana; Baars, Susanne; Geijsen, Niels

    2014-01-01

    Stem cell technologies have created new opportunities to generate unlimited numbers of human neurons in the lab and study neurodegenerative disorders such as amyotrophic lateral sclerosis (ALS) and spinal muscular atrophy (SMA). Although some disease hallmarks have been reported in patient-derived s

  4. Stochastic resonance in neuron models : Endogenous stimulation revisited

    NARCIS (Netherlands)

    Plesser, HE; Geisel, T

    2001-01-01

    The paradigm of stochastic resonance (SR)-the idea that signal detection and transmission may benefit from noise-has met with great interest in both physics and the neurosciences. We investigate here the consequences of reducing the dynamics of a periodically driven neuron to a renewal process (stim

  5. Histologic assessment of neurons in rat models of cerebral ischemia.

    Science.gov (United States)

    Eke, A; Conger, K A; Anderson, M; Garcia, J H

    1990-02-01

    We describe a method for typing neurons into four progressive stages of ischemic deterioration based on visual characterization of the nucleus in terms of its optical contrast, delineation along the nuclear-cytoplasmic interface, and its shape. Difficulty in assessing nuclear shape required the introduction of an angularity comparator chart to improve the investigator's accuracy. Three investigators typed neurons obtained from normal, ischemic, and ischemic-reperfused rat brains. Accuracy and reproducibility of the investigators' typing decisions with and without the angularity comparator charts were evaluated. The accuracy of subjective shape assessment was compared with objective digitizer measurements of the same. The angularity comparator charts reduced subjective shape classification error by two thirds, and group error (overall performance expressed by the coefficient of variance) decreased from 15.9% to 4.7% for Type I (normal cells), from 33.9% to 17.3% for Type II (cells with angular nuclei), from 15.5% to 14.1% for Type III (cells with smeared nuclei), and from 3.2% to 5.5% for Type IV (dead cells). Thus, Type I and IV neurons can be assessed at a higher reproducibility than the intermediate Types II and III. Our typing method can also be used to evaluate the effect of treatment regimes on ischemic neuronal damage.

  6. Neuronal population dynamic model:An analytic approach

    Institute of Scientific and Technical Information of China (English)

    Wentao Huang; Licheng Jiao; Yuelei Xu; Shiping Ma; Jianhua Jia

    2009-01-01

    rom this,the stationary solution and the firing rate of the stationary states are given.Last,by the Fourier transform,the time dependent solution is also obtained.This method can be used to analyze the various dynamic behaviors of neuronal populations.

  7. Simulation study on dynamics transition in neuronal activity during sleep cycle by using asynchronous and symmetry neural network model.

    Science.gov (United States)

    Nakao, M; Takahashi, T; Mizutani, Y; Yamamoto, M

    1990-01-01

    We have found that single neuronal activities in different regions in the brain commonly exhibit the distinct dynamics transition during sleep-waking cycle in cats. Especially, power spectral densities of single neuronal activities change their profiles from the white to the 1/f along with sleep cycle from slow wave sleep (SWS) to paradoxical sleep (PS). Each region has different neural network structure and physiological function. This suggests a globally working mechanism may be underlying the dynamics transition we concern. Pharmacological studies have shown that a change in a wide-spread serotonergic input to these regions possibly causes the neuronal dynamics transition during sleep cycle. In this paper, based on these experimental results, an asynchronous and symmetry neural network model including inhibitory input, which represents the role of the serotonergic system, is utilized to examine the reality of our idea that the inhibitory input level varying during sleep cycle induce that transition. Simulation results show that the globally applied inhibitory input can control the dynamics of single neuronal state evolution in the artificial neural network: 1/f-like power spectral density profiles result under weak inhibition, which possibly corresponds to PS, and white profiles under strong inhibition, which possibly corresponds to SWS. An asynchronous neural network is known to change its state according to its energy function. The geometrical structure of network energy function is thought to vary along with the change in inhibitory level, which is expected to cause the dynamics transition of neuronal state evolution in the network model. These simulation results support the possibility that the serotonergic system is essential for the dynamics transition of single neuronal activities during sleep cycle.

  8. A biological plausible Generalized Leaky Integrate-and-Fire neuron model.

    Science.gov (United States)

    Wang, Zhenzhong; Guo, Lilin; Adjouadi, Malek

    2014-01-01

    This study introduces a new Generalized Leaky Integrate-and-Fire (GLIF) neuron model. Unlike Normal Leaky Integrate-and-Fire (NLIF) models, the leaking resistor in the GLIF model equation is assumed to be variable, and an additional term would have the bias current added to the model equation in order to improve the accuracy. Adjusting the parameters defined for the leaking resistor and bias current, a GLIF model could be accurately matched to any Hodgkin-Huxley (HH) model and be able to reproduce plausible biological neuron behaviors.

  9. Intrinsic up-regulation of 2-AG favors an area specific neuronal survival in different in vitro models of neuronal damage.

    Directory of Open Access Journals (Sweden)

    Sonja Kallendrusch

    Full Text Available BACKGROUND: The endocannabinoid 2-arachidonoyl glycerol (2-AG acts as a retrograde messenger and modulates synaptic signaling e. g. in the hippocampus. 2-AG also exerts neuroprotective effects under pathological situations. To better understand the mechanism beyond physiological signaling we used Organotypic Entorhino-Hippocampal Slice Cultures (OHSC and investigated the temporal regulation of 2-AG in different cell subsets during excitotoxic lesion and dendritic lesion of long range projections in the enthorhinal cortex (EC, dentate gyrus (DG and the cornu ammonis region 1 (CA1. RESULTS: 2-AG levels were elevated 24 h after excitotoxic lesion in CA1 and DG (but not EC and 24 h after perforant pathway transection (PPT in the DG only. After PPT diacylglycerol lipase alpha (DAGL protein, the synthesizing enzyme of 2-AG was decreased when Dagl mRNA expression and 2-AG levels were enhanced. In contrast to DAGL, the 2-AG hydrolyzing enzyme monoacylglycerol lipase (MAGL showed no alterations in total protein and mRNA expression after PPT in OHSC. MAGL immunoreaction underwent a redistribution after PPT and excitotoxic lesion since MAGL IR disappeared in astrocytes of lesioned OHSC. DAGL and MAGL immunoreactions were not detectable in microglia at all investigated time points. Thus, induction of the neuroprotective endocannabinoid 2-AG might be generally accomplished by down-regulation of MAGL in astrocytes after neuronal lesions. CONCLUSION: Increase in 2-AG levels during secondary neuronal damage reflects a general neuroprotective mechanism since it occurred independently in both different lesion models. This intrinsic up-regulation of 2-AG is synergistically controlled by DAGL and MAGL in neurons and astrocytes and thus represents a protective system for neurons that is involved in dendritic reorganisation.

  10. Neuronal Entropy-Rate Feature of Entopeduncular Nucleus in Rat Model of Parkinson's Disease.

    Science.gov (United States)

    Darbin, Olivier; Jin, Xingxing; Von Wrangel, Christof; Schwabe, Kerstin; Nambu, Atsushi; Naritoku, Dean K; Krauss, Joachim K; Alam, Mesbah

    2016-03-01

    The function of the nigro-striatal pathway on neuronal entropy in the basal ganglia (BG) output nucleus, i.e. the entopeduncular nucleus (EPN) was investigated in the unilaterally 6-hyroxydopamine (6-OHDA)-lesioned rat model of Parkinson's disease (PD). In both control subjects and subjects with 6-OHDA lesion of dopamine (DA) the nigro-striatal pathway, a histological hallmark for parkinsonism, neuronal entropy in EPN was maximal in neurons with firing rates ranging between 15 and 25 Hz. In 6-OHDA lesioned rats, neuronal entropy in the EPN was specifically higher in neurons with firing rates above 25 Hz. Our data establishes that the nigro-striatal pathway controls neuronal entropy in motor circuitry and that the parkinsonian condition is associated with abnormal relationship between firing rate and neuronal entropy in BG output nuclei. The neuronal firing rates and entropy relationship provide putative relevant electrophysiological information to investigate the sensory-motor processing in normal condition and conditions such as movement disorders.

  11. Noninvasive blood glucose sensing using near infra-red spectroscopy and artificial neural networks based on inverse delayed function model of neuron.

    Science.gov (United States)

    Ramasahayam, Swathi; Koppuravuri, Sri Haindavi; Arora, Lavanya; Chowdhury, Shubhajit Roy

    2015-01-01

    In this paper, a non-invasive blood glucose sensing system is presented using near infra-red(NIR) spectroscopy. The signal from the NIR optodes is processed using artificial neural networks (ANN) to estimate the glucose level in blood. In order to obtain accurate values of the synaptic weights of the ANN, inverse delayed (ID) function model of neuron has been used. The ANN model has been implemented on field programmable gate array (FPGA). Error in estimating glucose levels using ANN based on ID function model of neuron implemented on FPGA, came out to be 1.02 mg/dl using 15 hidden neurons in the hidden layer as against 5.48 mg/dl using ANN based on conventional neuron model.

  12. Numerical simulation of neuronal spike patterns in a retinal network model

    Institute of Scientific and Technical Information of China (English)

    Lei Wang; Shenquan Liu; Shanxing Ou

    2011-01-01

    This study utilized a neuronal compartment model and NEURON software to study the effects of external light stimulation on retinal photoreceptors and spike patterns of neurons in a retinal network. Following light stimulation of different shapes and sizes, changes in the spike features of ganglion cells indicated that different shapes of light stimulation elicited different retinal responses. By manipulating the shape of light stimulation, we investigated the effects of the large number of electrical synapses existing between retinal neurons. Model simulation and analysis suggested that interplexiform cells play an important role in visual signal information processing in the retina, and the findings indicated that our constructed retinal network model was reliable and feasible. In addition, the simulation results demonstrated that ganglion cells exhibited a variety of spike patterns under different light stimulation sizes and different stimulation shapes, which reflect the functions of the retina in signal transmission and processing.

  13. A learning-enabled neuron array IC based upon transistor channel models of biological phenomena.

    Science.gov (United States)

    Brink, S; Nease, S; Hasler, P; Ramakrishnan, S; Wunderlich, R; Basu, A; Degnan, B

    2013-02-01

    We present a single-chip array of 100 biologically-based electronic neuron models interconnected to each other and the outside environment through 30,000 synapses. The chip was fabricated in a standard 350 nm CMOS IC process. Our approach used dense circuit models of synaptic behavior, including biological computation and learning, as well as transistor channel models. We use Address-Event Representation (AER) spike communication for inputs and outputs to this IC. We present the IC architecture and infrastructure, including IC chip, configuration tools, and testing platform. We present measurement of small network of neurons, measurement of STDP neuron dynamics, and measurement from a compiled spiking neuron WTA topology, all compiled into this IC.

  14. Relaxation and self-sustained oscillations in the time elapsed neuron network model

    CERN Document Server

    Pakdaman, Khashayar; Salort, Delphine

    2011-01-01

    The time elapsed model describes the firing activity of an homogeneous assembly of neurons thanks to the distribution of times elapsed since the last discharge. It gives a mathematical description of the probability density of neurons structured by this time. In an earlier work, based on generalized relative entropy methods, it is proved that for highly or weakly connected networks the model exhibits relaxation to the steady state and for moderately connected networks it is obtained numerical evidence of appearance of self-sustained periodic solutions. Here, we go further and, using the particular form of the model, we quantify the regime where relaxation to a stationary state occurs in terms of the network connectivity. To introduce our methodology, we first consider the case where the neurons are not connected and we give a new statement showing that total asynchronous firing of neurons appears asymptotically. In a second step, we consider the case with connections and give a low connectivity condition that...

  15. Neuromorphic silicon neuron circuits

    Directory of Open Access Journals (Sweden)

    Giacomo eIndiveri

    2011-05-01

    Full Text Available Hardware implementations of spiking neurons can be extremely useful for a large variety of applications, ranging from high-speed modeling of large-scale neural systems to real-time behaving systems, to bidirectional brain-machine interfaces. The specific circuit solutions used to implement silicon neurons depend on the application requirements. In this paper we describe the most common building blocks and techniques used to implement these circuits, and present an overview of a wide range of neuromorphic silicon neurons, which implement different computational models, ranging from biophysically realistic and conductance based Hodgkin-Huxley models to bi-dimensional generalized adaptive Integrate and Fire models. We compare the different design methodologies used for each silicon neuron design described, and demonstrate their features with experimental results, measured from a wide range of fabricated VLSI chips.

  16. Assessment of primary neuronal culture as a model for soman-induced neurotoxicity and effectiveness of nemantine as a neuroprotective drug

    Energy Technology Data Exchange (ETDEWEB)

    Deshpande, S.S.; Smith, C.D.; Filbert, M.G.

    1995-12-31

    An in vitro mammalian model neuronal system to evaluate the intrinsic toxicity of soman and other neurotoxicants as well as the efficacy of potential countermeasures was investigated. The link between soman toxicity glutamate hyperactivity and neuronal death in the central nervous system was investigated in primary dissociated cell cultures from rat hippocampus and cerebral neocortex. Exposure of cortical or hippocampal neurons to glutamate for 30 min produced neuronal death in almost 80% of the cells examined at 24 h. Hippocampal neurons exposed to soman for 15-12Omin at 0.1 %M concentration caused almost complete inhibition ( > 90%) of acetylcholinesterase but failed to show any evidence of effects on cell viability, indicating a lack of direct cytotoxicity by this agent. Acetylcholine (ACh, 0.1 mM), alone or in combination with soman, did not potentiate glutamate toxicity in hippocampal neurons. Memantine, a drug used for the therapy of Parkinson`s disease, spasticity and other brain disorders, significantly protected hippocampal and cortical neurons in culture against glutamate and N-methyl-D- aspartate (NN4DA) excitotoxicity. In rats a single dose of memantine (18 mg/kg) administered 1 h prior to a s.c. injection of a 0.9 LD50 dose of soman reduced the severity of convulsions and increased survival. Survival. however, was accompanied by neuronal loss in the frontal cortex, piriform cortex and hippocampus.

  17. Assessment of primary neuronal culture as a model for soman-induced neurotoxicity and effectiveness of memantine as a neuroprotective drug

    Energy Technology Data Exchange (ETDEWEB)

    Deshpande, S.S.; Smith, C.D.; Filbert, M.G.

    1995-12-31

    An in vitro mammalian model neuronal system to evaluate the intrinsic toxicity of soman and other neurotoxicants as well as the efficacy of potential countermeasures was investigated. The link between soman toxicity, glutamate hyperactivity and neuronal death in the central nervous system was investigated in primary dissociated cell cultures from rat hippocampus and cerebral neocortex. Exposure of cortical or hippocampal neurons to glutamate for 30 min produced neuronal death in almost 800/0 of the cells examined at 24 h. Hippocampal neurons exposed to soman for 15-120 min at 0.1 ptN,concentration caused almost complete inhibition > 90% of acetylcholinesterase but failed to show any evidence of effects on cell viability, indicating a lack of direct cytotoxicity by this agent. Acetylcholine (ACh, 0.1 mNI). alone or in combination with soman. did not potentiate glutamate toxicity in hippocampal neurons. Memantine, a drug used for the therapy of Parkinson`s disease, spasticity and other brain disorders. significantly protected hippocampal and cortical neurons in culture against glutamate and N-methyl-D- aspartate (NNIDA) excitotoxicity. In rats a single dose of memantine (18 mg kg) administered 1 h prior to a s.c. injection of a 0.9 LD50 dose of soman reduced the severity of convulsions and increased survival. Survival. however, was accompanied by neuronal loss in the frontal cortex, piriform cortex and hippocampus.

  18. Chimera states in a Hodgkin-Huxley model of thermally sensitive neurons

    Science.gov (United States)

    Glaze, Tera A.; Lewis, Scott; Bahar, Sonya

    2016-08-01

    Chimera states occur when identically coupled groups of nonlinear oscillators exhibit radically different dynamics, with one group exhibiting synchronized oscillations and the other desynchronized behavior. This dynamical phenomenon has recently been studied in computational models and demonstrated experimentally in mechanical, optical, and chemical systems. The theoretical basis of these states is currently under active investigation. Chimera behavior is of particular relevance in the context of neural synchronization, given the phenomenon of unihemispheric sleep and the recent observation of asymmetric sleep in human patients with sleep apnea. The similarity of neural chimera states to neural "bump" states, which have been suggested as a model for working memory and visual orientation tuning in the cortex, adds to their interest as objects of study. Chimera states have been demonstrated in the FitzHugh-Nagumo model of excitable cells and in the Hindmarsh-Rose neural model. Here, we demonstrate chimera states and chimera-like behaviors in a Hodgkin-Huxley-type model of thermally sensitive neurons both in a system with Abrams-Strogatz (mean field) coupling and in a system with Kuramoto (distance-dependent) coupling. We map the regions of parameter space for which chimera behavior occurs in each of the two coupling schemes.

  19. Evaluation of the importance of astrocytes when screening for acute toxicity in neuronal cell systems.

    Science.gov (United States)

    Woehrling, E K; Hill, E J; Coleman, M D

    2010-02-01

    Reliable, high throughput, in vitro preliminary screening batteries have the potential to greatly accelerate the rate at which regulatory neurotoxicity data is generated. This study evaluated the importance of astrocytes when predicting acute toxic potential using a neuronal screening battery of pure neuronal (NT2.N) and astrocytic (NT2.A) and integrated neuronal/astrocytic (NT2.N/A) cell systems derived from the human NT2.D1 cell line, using biochemical endpoints (mitochondrial membrane potential (MMP) depolarisation and ATP and GSH depletion). Following exposure for 72 h, the known acute human neurotoxicants trimethyltin-chloride, chloroquine and 6-hydroxydopamine were frequently capable of disrupting biochemical processes in all of the cell systems at non-cytotoxic concentrations. Astrocytes provide key metabolic and protective support to neurons during toxic challenge in vivo and generally the astrocyte containing cell systems showed increased tolerance to toxicant insult compared with the NT2.N mono-culture in vitro. Whilst there was no consistent relationship between MMP, ATP and GSH log IC(50) values for the NT2.N/A and NT2.A cell systems, these data did provide preliminary evidence of modulation of the acute neuronal toxic response by astrocytes. In conclusion, the suitability of NT2 neurons and astrocytes as cell systems for acute toxicity screening deserves further investigation.

  20. Modelling spatiotemporal olfactory data in two steps: from binary to Hodgkin-Huxley neurones.

    Science.gov (United States)

    Quenet, Brigitte; Dubois, Rémi; Sirapian, Sevan; Dreyfus, Gérard; Horn, David

    2002-01-01

    Network models of synchronously updated McCulloch-Pitts neurones exhibit complex spatiotemporal patterns that are similar to activities of biological neurones in phase with a periodic local field potential, such as those observed experimentally by Wehr and Laurent (1996, Nature 384, 162-166) in the locust olfactory pathway. Modelling biological neural nets with networks of simple formal units makes the dynamics of the model analytically tractable. It is thus possible to determine the constraints that must be satisfied by its connection matrix in order to make its neurones exhibit a given sequence of activity (see, for instance, Quenet et al., 2001, Neurocomputing 38-40, 831-836). In the present paper, we address the following question: how can one construct a formal network of Hodgkin-Huxley (HH) type neurones that reproduces experimentally observed neuronal codes? A two-step strategy is suggested in the present paper: first, a simple network of binary units is designed, whose activity reproduces the binary experimental codes; second, this model is used as a guide to design a network of more realistic formal HH neurones. We show that such a strategy is indeed fruitful: it allowed us to design a model that reproduces the Wehr-Laurent olfactory codes, and to investigate the robustness of these codes to synaptic noise.

  1. Mapping the flow of information within the putative mirror neuron system during gesture observation

    NARCIS (Netherlands)

    Schippers, Marleen B.; Keysers, Christian

    2011-01-01

    The putative mirror neuron system may either function as a strict feed-forward system or as a dynamic control system. A strict feed-forward system would predict that action observation leads to a predominantly temporal -> parietal -> premotor flow of information in which a visual representation is t

  2. Peripheral Nervous System Genes Expressed in Central Neurons Induce Growth on Inhibitory Substrates

    Science.gov (United States)

    Buchser, William J.; Smith, Robin P.; Pardinas, Jose R.; Haddox, Candace L.; Hutson, Thomas; Moon, Lawrence; Hoffman, Stanley R.; Bixby, John L.; Lemmon, Vance P.

    2012-01-01

    Trauma to the spinal cord and brain can result in irreparable loss of function. This failure of recovery is in part due to inhibition of axon regeneration by myelin and chondroitin sulfate proteoglycans (CSPGs). Peripheral nervous system (PNS) neurons exhibit increased regenerative ability compared to central nervous system neurons, even in the presence of inhibitory environments. Previously, we identified over a thousand genes differentially expressed in PNS neurons relative to CNS neurons. These genes represent intrinsic differences that may account for the PNS’s enhanced regenerative ability. Cerebellar neurons were transfected with cDNAs for each of these PNS genes to assess their ability to enhance neurite growth on inhibitory (CSPG) or permissive (laminin) substrates. Using high content analysis, we evaluated the phenotypic profile of each neuron to extract meaningful data for over 1100 genes. Several known growth associated proteins potentiated neurite growth on laminin. Most interestingly, novel genes were identified that promoted neurite growth on CSPGs (GPX3, EIF2B5, RBMX). Bioinformatic approaches also uncovered a number of novel gene families that altered neurite growth of CNS neurons. PMID:22701605

  3. A mammalian nervous-system-specific plasma membrane proteasome complex that modulates neuronal function.

    Science.gov (United States)

    Ramachandran, Kapil V; Margolis, Seth S

    2017-04-01

    In the nervous system, rapidly occurring processes such as neuronal transmission and calcium signaling are affected by short-term inhibition of proteasome function. It is unclear how proteasomes are able to acutely regulate such processes, as this action is inconsistent with their canonical role in proteostasis. Here we describe a mammalian nervous-system-specific membrane proteasome complex that directly and rapidly modulates neuronal function by degrading intracellular proteins into extracellular peptides that can stimulate neuronal signaling. This proteasome complex is closely associated with neuronal plasma membranes, exposed to the extracellular space, and catalytically active. Selective inhibition of the membrane proteasome complex by a cell-impermeable proteasome inhibitor blocked the production of extracellular peptides and attenuated neuronal-activity-induced calcium signaling. Moreover, we observed that membrane-proteasome-derived peptides were sufficient to induce neuronal calcium signaling. Our discoveries challenge the prevailing notion that proteasomes function primarily to maintain proteostasis, and highlight a form of neuronal communication that takes place through a membrane proteasome complex.

  4. Peripheral nervous system genes expressed in central neurons induce growth on inhibitory substrates.

    Directory of Open Access Journals (Sweden)

    William J Buchser

    Full Text Available Trauma to the spinal cord and brain can result in irreparable loss of function. This failure of recovery is in part due to inhibition of axon regeneration by myelin and chondroitin sulfate proteoglycans (CSPGs. Peripheral nervous system (PNS neurons exhibit increased regenerative ability compared to central nervous system neurons, even in the presence of inhibitory environments. Previously, we identified over a thousand genes differentially expressed in PNS neurons relative to CNS neurons. These genes represent intrinsic differences that may account for the PNS's enhanced regenerative ability. Cerebellar neurons were transfected with cDNAs for each of these PNS genes to assess their ability to enhance neurite growth on inhibitory (CSPG or permissive (laminin substrates. Using high content analysis, we evaluated the phenotypic profile of each neuron to extract meaningful data for over 1100 genes. Several known growth associated proteins potentiated neurite growth on laminin. Most interestingly, novel genes were identified that promoted neurite growth on CSPGs (GPX3, EIF2B5, RBMX. Bioinformatic approaches also uncovered a number of novel gene families that altered neurite growth of CNS neurons.

  5. Peripheral nervous system genes expressed in central neurons induce growth on inhibitory substrates.

    Science.gov (United States)

    Buchser, William J; Smith, Robin P; Pardinas, Jose R; Haddox, Candace L; Hutson, Thomas; Moon, Lawrence; Hoffman, Stanley R; Bixby, John L; Lemmon, Vance P

    2012-01-01

    Trauma to the spinal cord and brain can result in irreparable loss of function. This failure of recovery is in part due to inhibition of axon regeneration by myelin and chondroitin sulfate proteoglycans (CSPGs). Peripheral nervous system (PNS) neurons exhibit increased regenerative ability compared to central nervous system neurons, even in the presence of inhibitory environments. Previously, we identified over a thousand genes differentially expressed in PNS neurons relative to CNS neurons. These genes represent intrinsic differences that may account for the PNS's enhanced regenerative ability. Cerebellar neurons were transfected with cDNAs for each of these PNS genes to assess their ability to enhance neurite growth on inhibitory (CSPG) or permissive (laminin) substrates. Using high content analysis, we evaluated the phenotypic profile of each neuron to extract meaningful data for over 1100 genes. Several known growth associated proteins potentiated neurite growth on laminin. Most interestingly, novel genes were identified that promoted neurite growth on CSPGs (GPX3, EIF2B5, RBMX). Bioinformatic approaches also uncovered a number of novel gene families that altered neurite growth of CNS neurons.

  6. Hippocampal adaptive response following extensive neuronal loss in an inducible transgenic mouse model.

    Directory of Open Access Journals (Sweden)

    Kristoffer Myczek

    Full Text Available Neuronal loss is a common component of a variety of neurodegenerative disorders (including Alzheimer's, Parkinson's, and Huntington's disease and brain traumas (stroke, epilepsy, and traumatic brain injury. One brain region that commonly exhibits neuronal loss in several neurodegenerative disorders is the hippocampus, an area of the brain critical for the formation and retrieval of memories. Long-lasting and sometimes unrecoverable deficits caused by neuronal loss present a unique challenge for clinicians and for researchers who attempt to model these traumas in animals. Can these deficits be recovered, and if so, is the brain capable of regeneration following neuronal loss? To address this significant question, we utilized the innovative CaM/Tet-DT(A mouse model that selectively induces neuronal ablation. We found that we are able to inflict a consistent and significant lesion to the hippocampus, resulting in hippocampally-dependent behavioral deficits and a long-lasting upregulation in neurogenesis, suggesting that this process might be a critical part of hippocampal recovery. In addition, we provide novel evidence of angiogenic and vasculature changes following hippocampal neuronal loss in CaM/Tet-DTA mice. We posit that angiogenesis may be an important factor that promotes neurogenic upregulation following hippocampal neuronal loss, and both factors, angiogenesis and neurogenesis, can contribute to the adaptive response of the brain for behavioral recovery.

  7. Neuronally-directed effects of RXR activation in a mouse model of Alzheimer’s disease

    Science.gov (United States)

    Mariani, M. M.; Malm, T.; Lamb, R.; Jay, T. R.; Neilson, L.; Casali, B.; Medarametla, L.; Landreth, G. E.

    2017-01-01

    Alzheimer’s disease (AD) is characterized by extensive neuron loss that accompanies profound impairments in memory and cognition. We examined the neuronally directed effects of the retinoid X receptor agonist bexarotene in an aggressive model of AD. We report that a two week treatment of 3.5 month old 5XFAD mice with bexarotene resulted in the clearance of intraneuronal amyloid deposits. Importantly, neuronal loss was attenuated by 44% in the subiculum in mice 4 months of age and 18% in layer V of the cortex in mice 8 months of age. Moreover, bexarotene treatment improved remote memory stabilization in fear conditioned mice and improved olfactory cross habituation. These improvements in neuron viability and function were correlated with significant increases in the levels of post-synaptic marker PSD95 and the pre-synaptic marker synaptophysin. Moreover, bexarotene pretreatment improved neuron survival in primary 5XFAD neurons in vitro in response to glutamate-induced excitotoxicity. The salutary effects of bexarotene were accompanied by reduced plaque burden, decreased astrogliosis, and suppression of inflammatory gene expression. Collectively, these data provide evidence that bexarotene treatment reduced neuron loss, elevated levels of markers of synaptic integrity that was linked to improved cognition and in an aggressive model of AD. PMID:28205585

  8. Xenopus laevis neuronal cell adhesion molecule (nrcam): plasticity of a CAM in the developing nervous system.

    Science.gov (United States)

    Lokapally, Ashwin; Metikala, Sanjeeva; Hollemann, Thomas

    2017-01-01

    Neuron-glial-related cell adhesion molecule (NRCAM) is a neuronal cell adhesion molecule of the L1 immunoglobulin superfamily, which plays diverse roles during nervous system development including axon growth and guidance, synapse formation, and formation of the myelinated nerve. Perturbations in NRCAM function cause a wide variety of disorders, which can affect wiring and targeting of neurons, or cause psychiatric disorders as well as cancers through abnormal modulation of signaling events. In the present study, we characterize the Xenopus laevis homolog of nrcam. Expression of Xenopus nrcam is most abundant along the dorsal midline throughout the developing brain and in the outer nuclear layer of the retina.

  9. Dorsal root ganglia neurons and differentiated adipose-derived stem cells: an in vitro co-culture model to study peripheral nerve regeneration.

    Science.gov (United States)

    de Luca, Alba C; Faroni, Alessandro; Reid, Adam J

    2015-02-26

    Dorsal root ganglia (DRG) neurons, located in the intervertebral foramina of the spinal column, can be used to create an in vitro system facilitating the study of nerve regeneration and myelination. The glial cells of the peripheral nervous system, Schwann cells (SC), are key facilitators of these processes; it is therefore crucial that the interactions of these cellular components are studied together. Direct contact between DRG neurons and glial cells provides additional stimuli sensed by specific membrane receptors, further improving the neuronal response. SC release growth factors and proteins in the culture medium, which enhance neuron survival and stimulate neurite sprouting and extension. However, SC require long proliferation time to be used for tissue engineering applications and the sacrifice of an healthy nerve for their sourcing. Adipose-derived stem cells (ASC) differentiated into SC phenotype are a valid alternative to SC for the set-up of a co-culture model with DRG neurons to study nerve regeneration. The present work presents a detailed and reproducible step-by-step protocol to harvest both DRG neurons and ASC from adult rats; to differentiate ASC towards a SC phenotype; and combines the two cell types in a direct co-culture system to investigate the interplay between neurons and SC in the peripheral nervous system. This tool has great potential in the optimization of tissue-engineered constructs for peripheral nerve repair.

  10. Neuronal chains for actions in the parietal lobe: a computational model.

    Directory of Open Access Journals (Sweden)

    Fabian Chersi

    Full Text Available The inferior part of the parietal lobe (IPL is known to play a very important role in sensorimotor integration. Neurons in this region code goal-related motor acts performed with the mouth, with the hand and with the arm. It has been demonstrated that most IPL motor neurons coding a specific motor act (e.g., grasping show markedly different activation patterns according to the final goal of the action sequence in which the act is embedded (grasping for eating or grasping for placing. Some of these neurons (parietal mirror neurons show a similar selectivity also during the observation of the same action sequences when executed by others. Thus, it appears that the neuronal response occurring during the execution and the observation of a specific grasping act codes not only the executed motor act, but also the agent's final goal (intention.In this work we present a biologically inspired neural network architecture that models mechanisms of motor sequences execution and recognition. In this network, pools composed of motor and mirror neurons that encode motor acts of a sequence are arranged in form of action goal-specific neuronal chains. The execution and the recognition of actions is achieved through the propagation of activity bursts along specific chains modulated by visual and somatosensory inputs.The implemented spiking neuron network is able to reproduce the results found in neurophysiological recordings of parietal neurons during task performance and provides a biologically plausible implementation of the action selection and recognition process.Finally, the present paper proposes a mechanism for the formation of new neural chains by linking together in a sequential manner neurons that represent subsequent motor acts, thus producing goal-directed sequences.

  11. Continuous system modeling

    Science.gov (United States)

    Cellier, Francois E.

    1991-01-01

    A comprehensive and systematic introduction is presented for the concepts associated with 'modeling', involving the transition from a physical system down to an abstract description of that system in the form of a set of differential and/or difference equations, and basing its treatment of modeling on the mathematics of dynamical systems. Attention is given to the principles of passive electrical circuit modeling, planar mechanical systems modeling, hierarchical modular modeling of continuous systems, and bond-graph modeling. Also discussed are modeling in equilibrium thermodynamics, population dynamics, and system dynamics, inductive reasoning, artificial neural networks, and automated model synthesis.

  12. A synaptic input portal for a mapped clock oscillator model of neuronal electrical rhythmic activity

    Science.gov (United States)

    Zariffa, José; Ebden, Mark; Bardakjian, Berj L.

    2004-09-01

    Neuronal electrical oscillations play a central role in a variety of situations, such as epilepsy and learning. The mapped clock oscillator (MCO) model is a general model of transmembrane voltage oscillations in excitable cells. In order to be able to investigate the behaviour of neuronal oscillator populations, we present a neuronal version of the model. The neuronal MCO includes an extra input portal, the synaptic portal, which can reflect the biological relationships in a chemical synapse between the frequency of the presynaptic action potentials and the postsynaptic resting level, which in turn affects the frequency of the postsynaptic potentials. We propose that the synaptic input-output relationship must include a power function in order to be able to reproduce physiological behaviour such as resting level saturation. One linear and two power functions (Butterworth and sigmoidal) are investigated, using the case of an inhibitory synapse. The linear relation was not able to produce physiologically plausible behaviour, whereas both the power function examples were appropriate. The resulting neuronal MCO model can be tailored to a variety of neuronal cell types, and can be used to investigate complex population behaviour, such as the influence of network topology and stochastic resonance.

  13. Immunohistochemical visualization of hippocampal neuron activity after spatial learning in a mouse model of neurodevelopmental disorders.

    Science.gov (United States)

    Provenzano, Giovanni; Pangrazzi, Luca; Poli, Andrea; Berardi, Nicoletta; Bozzi, Yuri

    2015-05-12

    Induction of phosphorylated extracellular-regulated kinase (pERK) is a reliable molecular readout of learning-dependent neuronal activation. Here, we describe a pERK immunohistochemistry protocol to study the profile of hippocampal neuron activation following exposure to a spatial learning task in a mouse model characterized by cognitive deficits of neurodevelopmental origin. Specifically, we used pERK immunostaining to study neuronal activation following Morris water maze (MWM, a classical hippocampal-dependent learning task) in Engrailed-2 knockout (En2(-/-)) mice, a model of autism spectrum disorders (ASD). As compared to wild-type (WT) controls, En2(-/-) mice showed significant spatial learning deficits in the MWM. After MWM, significant differences in the number of pERK-positive neurons were detected in specific hippocampal subfields of En2(-/-) mice, as compared to WT animals. Thus, our protocol can robustly detect differences in pERK-positive neurons associated to hippocampal-dependent learning impairment in a mouse model of ASD. More generally, our protocol can be applied to investigate the profile of hippocampal neuron activation in both genetic or pharmacological mouse models characterized by cognitive deficits.

  14. Effects of Fluvastatin on Characteristics of Stellate Ganglion Neurons in a Rabbit Model of Myocardial Ischemia

    Institute of Scientific and Technical Information of China (English)

    Li-Jun Cheng; Guang-Ping Li; Jian Li; Yan Chen; Xing-Hua Wang

    2016-01-01

    Background:Stellate ganglion (SG) plays an important role in cardiovascular diseases.The electrical activity of SG neurons is involved in the regulation of the autonomic nervous system.The aim of this research was to evaluate the effects offluvastatin on the electrophysiological characteristics of SG neurons in a rabbit model of myocardial ischemia (MI).Methods:The MI model was induced by abdominal subcutaneous injections of isoproterenol in rabbits.Using whole-cell patch clamp technique,we studied the characteristic changes of ion channels and action potentials (APs) in isolated SG neurons in control group (n =20),MI group (n =20) and fluvastatin pretreated group (fluvastatin group,n =20),respectively.The protein expression of sodium channel in SG was determined by immunohistochemical analysis.Results:MI and the intervention of fluvastatin did not have significantly influence on the characteristics of delayed rectifier potassium channel currents.The maximal peak current density of sodium channel currents in SG neurons along with the characteristics of activation curves,inactivation curves,and recovery curves after inactivation were changed in the MI group.The peak current densities of control group,MI group,and fluvastatin group (n =10 in each group) were-71.77 ± 23.22 pA/pF,-126.75 ± 18.90 pA/pF,and-86.42 ± 28.30 pA/pF,respectively (F=4.862,P =0.008).Fluvastatin can decrease the current amplitude which has been increased by MI.Moreover,fluvastatin induced the inactivation curves and post-inactive recovery curves moving to the position of the control group.But the expression of sodium channel-associated protein (Nav 1.7) had no significantly statistical difference among the three groups.The percentages of Nav 1.7 protein in control group,MI group,and fluvastatin group (n =5 in each group) were 21.49 ± 7.33%,28.53 ± 8.26%,and 21.64 ± 2.78%,respectively (F =1.495,P =0.275).Moreover,MI reduced the electrical activity of AP and increased amplitude of AP

  15. Arnold tongues and the Devil's Staircase in a discrete-time Hindmarsh–Rose neuron model

    Energy Technology Data Exchange (ETDEWEB)

    Felicio, Carolini C., E-mail: carolini.cf@gmail.com; Rech, Paulo C., E-mail: paulo.rech@udesc.br

    2015-11-06

    We investigate a three-dimensional discrete-time dynamical system, described by a three-dimensional map derived from a continuous-time Hindmarsh–Rose neuron model by the forward Euler method. For a fixed integration step size, we report a two-dimensional parameter-space for this system, where periodic structures, the so-called Arnold tongues, can be seen with periods organized in a Farey tree sequence. We also report possible modifications in this parameter-space, as a function of the integration step size. - Highlights: • We investigate the parameter-space of a particular 3D map. • Periodic structures, namely Arnold tongues, can be seen there. • They are organized in a Farey tree sequence. • The map was derived from a continuous-time Hindmarsh–Rose neuron model. • The forward Euler method was used for such purpose.

  16. A multidisciplinary approach to study the functional properties of neuron-like cell models constituting a living bio-hybrid system: SH-SY5Y cells adhering to PANI substrate

    Directory of Open Access Journals (Sweden)

    S. Caponi

    2016-11-01

    Full Text Available A living bio-hybrid system has been successfully implemented. It is constituted by neuroblastic cells, the SH-SY5Y human neuroblastoma cells, adhering to a poly-anyline (PANI a semiconductor polymer with memristive properties. By a multidisciplinary approach, the biocompatibility of the substrate has been analyzed and the functionality of the adhering cells has been investigated. We found that the PANI films can support the cell adhesion. Moreover, the SH-SY5Y cells were successfully differentiated into neuron-like cells for in vitro applications demonstrating that PANI can also promote cell differentiation. In order to deeply characterize the modifications of the bio-functionality induced by the cell-substrate interaction, the functional properties of the cells have been characterized by electrophysiology and Raman spectroscopy. Our results confirm that the PANI films do not strongly affect the general properties of the cells, ensuring their viability without toxic effects on their physiology. Ascribed to the adhesion process, however, a slight increase of the markers of the cell suffering has been evidenced by Raman spectroscopy and accordingly the electrophysiology shows a reduction at positive stimulations in the cells excitability.

  17. A flexible, interactive software tool for fitting the parameters of neuronal models

    Directory of Open Access Journals (Sweden)

    Péter eFriedrich

    2014-07-01

    Full Text Available The construction of biologically relevant neuronal models as well as model-based analysis of experimental data often requires the simultaneous fitting of multiple model parameters, so that the behavior of the model in a certain paradigm matches (as closely as possible the corresponding output of a real neuron according to some predefined criterion. Although the task of model optimization is often computationally hard, and the quality of the results depends heavily on technical issues such as the appropriate choice (and implementation of cost functions and optimization algorithms, no existing program provides access to the best available methods while also guiding the user through the process effectively. Our software, called Optimizer, implements a modular and extensible framework for the optimization of neuronal models, and also features a graphical interface which makes it easy for even non-expert users to handle many commonly occurring scenarios. Meanwhile, educated users can extend the capabilities of the program and customize it according to their needs with relatively little effort. Optimizer has been developed in Python, takes advantage of open-source Python modules for nonlinear optimization, and interfaces directly with the NEURON simulator to run the models. Other simulators are supported through an external interface. We have tested the program on several different types of problem of varying complexity, using different model classes. As targets, we used simulated traces from the same or a more complex model class, as well as experimental data. We successfully used Optimizer to determine passive parameters and conductance densities in compartmental models, and to fit simple (adaptive exponential integrate-and-fire neuronal models to complex biological data. Our detailed comparisons show that Optimizer can handle a wider range of problems, and delivers equally good or better performance than any other existing neuronal model fitting

  18. Reflecting on the mirror neuron system in autism: a systematic review of current theories.

    Science.gov (United States)

    Hamilton, Antonia F de C

    2013-01-01

    There is much interest in the claim that dysfunction of the mirror neuron system in individuals with autism spectrum condition causes difficulties in social interaction and communication. This paper systematically reviews all published studies using neuroscience methods (EEG/MEG/TMS/eyetracking/EMG/fMRI) to examine the integrity of the mirror system in autism. 25 suitable papers are reviewed. The review shows that current data are very mixed and that studies using weakly localised measures of the integrity of the mirror system are hard to interpret. The only well localised measure of mirror system function is fMRI. In fMRI studies, those using emotional stimuli have reported group differences, but studies using non-emotional hand action stimuli do not. Overall, there is little evidence for a global dysfunction of the mirror system in autism. Current data can be better understood under an alternative model in which social top-down response modulation is abnormal in autism. The implications of this model and future research directions are discussed.

  19. Seizure-Induced Neuronal Injury: Vulnerability to Febrile Seizures in an Immature Rat Model

    OpenAIRE

    Toth, Zsolt; Yan, Xiao-Xin; Haftoglou, Suzie; Ribak, Charles E.; Tallie Z. Baram

    1998-01-01

    Febrile seizures are the most common seizure type in young children. Whether they induce death of hippocampal and amygdala neurons and consequent limbic (temporal lobe) epilepsy has remained controversial, with conflicting data from prospective and retrospective studies. Using an appropriate-age rat model of febrile seizures, we investigated the acute and chronic effects of hyperthermic seizures on neuronal integrity and survival in the hippocampus and amygdala via molecular and neuroanatomic...

  20. Irradiation of Neurons with High-Energy Charged Particles: An In Silico Modeling Approach.

    Directory of Open Access Journals (Sweden)

    Murat Alp

    2015-08-01

    Full Text Available In this work, a stochastic computational model of microscopic energy deposition events is used to study for the first time damage to irradiated neuronal cells of the mouse hippocampus. An extensive library of radiation tracks for different particle types is created to score energy deposition in small voxels and volume segments describing a neuron's morphology that later are sampled for given particle fluence or dose. Methods included the construction of in silico mouse hippocampal granule cells from neuromorpho.org with spine and filopodia segments stochastically distributed along the dendritic branches. The model is tested with high-energy (56Fe, (12C, and (1H particles and electrons. Results indicate that the tree-like structure of the neuronal morphology and the microscopic dose deposition of distinct particles may lead to different outcomes when cellular injury is assessed, leading to differences in structural damage for the same absorbed dose. The significance of the microscopic dose in neuron components is to introduce specific local and global modes of cellular injury that likely contribute to spine, filopodia, and dendrite pruning, impacting cognition and possibly the collapse of the neuron. Results show that the heterogeneity of heavy particle tracks at low doses, compared to the more uniform dose distribution of electrons, juxtaposed with neuron morphology make it necessary to model the spatial dose painting for specific neuronal components. Going forward, this work can directly support the development of biophysical models of the modifications of spine and dendritic morphology observed after low dose charged particle irradiation by providing accurate descriptions of the underlying physical insults to complex neuron structures at the nano-meter scale.

  1. FPGA implementation of a biological neural network based on the Hodgkin-Huxley neuron model.

    Science.gov (United States)

    Yaghini Bonabi, Safa; Asgharian, Hassan; Safari, Saeed; Nili Ahmadabadi, Majid

    2014-01-01

    A set of techniques for efficient implementation of Hodgkin-Huxley-based (H-H) model of a neural network on FPGA (Field Programmable Gate Array) is presented. The central implementation challenge is H-H model complexity that puts limits on the network size and on the execution speed. However, basics of the original model cannot be compromised when effect of synaptic specifications on the network behavior is the subject of study. To solve the problem, we used computational techniques such as CORDIC (Coordinate Rotation Digital Computer) algorithm and step-by-step integration in the implementation of arithmetic circuits. In addition, we employed different techniques such as sharing resources to preserve the details of model as well as increasing the network size in addition to keeping the network execution speed close to real time while having high precision. Implementation of a two mini-columns network with 120/30 excitatory/inhibitory neurons is provided to investigate the characteristic of our method in practice. The implementation techniques provide an opportunity to construct large FPGA-based network models to investigate the effect of different neurophysiological mechanisms, like voltage-gated channels and synaptic activities, on the behavior of a neural network in an appropriate execution time. Additional to inherent properties of FPGA, like parallelism and re-configurability, our approach makes the FPGA-based system a proper candidate for study on neural control of cognitive robots and systems as well.

  2. Thalamic neuron models encode stimulus information by burst-size modulation

    Directory of Open Access Journals (Sweden)

    Daniel Henry Elijah

    2015-09-01

    Full Text Available Thalamic neurons have been long assumed to fire in tonic mode during perceptive states, and in burst mode during sleep and unconsciousness. However, recent evidence suggests that bursts may also be relevant in the encoding of sensory information. Here we explore the neural code of such thalamic bursts. In order to assess whether the burst code is generic or whether it depends on the detailed properties of each bursting neuron, we analyzed two neuron models incorporating different levels of biological detail. One of the models contained no information of the biophysical processes entailed in spike generation, and described neuron activity at a phenomenological level. The second model represented the evolution of the individual ionic conductances involved in spiking and bursting, and required a large number of parameters. We analyzed the models' input selectivity using reverse correlation methods and information theory. We found that n-spike bursts from both models transmit information by modulating their spike count in response to changes to instantaneous input features, such as slope, phase, amplitude, etc. The stimulus feature that is most efficiently encoded by bursts, however, need not coincide with one of such classical features. We therefore searched for the optimal feature among all those that could be expressed as a linear transformation of the time-dependent input current. We found that bursting neurons transmitted 6 times more information about such more general features. The relevant events in the stimulus were located in a time window spanning ~100 ms before and ~20 ms after burst onset. Most importantly, the neural code employed by the simple and the biologically realistic models was largely the same, implying that the simple thalamic neuron model contains the essential ingredients that account for the computational properties of the thalamic burst code. Thus, our results suggest the n-spike burst code is a general property of

  3. Thalamic neuron models encode stimulus information by burst-size modulation.

    Science.gov (United States)

    Elijah, Daniel H; Samengo, Inés; Montemurro, Marcelo A

    2015-01-01

    Thalamic neurons have been long assumed to fire in tonic mode during perceptive states, and in burst mode during sleep and unconsciousness. However, recent evidence suggests that bursts may also be relevant in the encoding of sensory information. Here, we explore the neural code of such thalamic bursts. In order to assess whether the burst code is generic or whether it depends on the detailed properties of each bursting neuron, we analyzed two neuron models incorporating different levels of biological detail. One of the models contained no information of the biophysical processes entailed in spike generation, and described neuron activity at a phenomenological level. The second model represented the evolution of the individual ionic conductances involved in spiking and bursting, and required a large number of parameters. We analyzed the models' input selectivity using reverse correlation methods and information theory. We found that n-spike bursts from both models transmit information by modulating their spike count in response to changes to instantaneous input features, such as slope, phase, amplitude, etc. The stimulus feature that is most efficiently encoded by bursts, however, need not coincide with one of such classical features. We therefore searched for the optimal feature among all those that could be expressed as a linear transformation of the time-dependent input current. We found that bursting neurons transmitted 6 times more information about such more general features. The relevant events in the stimulus were located in a time window spanning ~100 ms before and ~20 ms after burst onset. Most importantly, the neural code employed by the simple and the biologically realistic models was largely the same, implying that the simple thalamic neuron model contains the essential ingredients that account for the computational properties of the thalamic burst code. Thus, our results suggest the n-spike burst code is a general property of thalamic neurons.

  4. A human mirror neuron system for language: Perspectives from signed languages of the deaf.

    Science.gov (United States)

    Knapp, Heather Patterson; Corina, David P

    2010-01-01

    Language is proposed to have developed atop the human analog of the macaque mirror neuron system for action perception and production [Arbib M.A. 2005. From monkey-like action recognition to human language: An evolutionary framework for neurolinguistics (with commentaries and author's response). Behavioral and Brain Sciences, 28, 105-167; Arbib M.A. (2008). From grasp to language: Embodied concepts and the challenge of abstraction. Journal de Physiologie Paris 102, 4-20]. Signed languages of the deaf are fully-expressive, natural human languages that are perceived visually and produced manually. We suggest that if a unitary mirror neuron system mediates the observation and production of both language and non-linguistic action, three prediction can be made: (1) damage to the human mirror neuron system should non-selectively disrupt both sign language and non-linguistic action processing; (2) within the domain of sign language, a given mirror neuron locus should mediate both perception and production; and (3) the action-based tuning curves of individual mirror neurons should support the highly circumscribed set of motions that form the "vocabulary of action" for signed languages. In this review we evaluate data from the sign language and mirror neuron literatures and find that these predictions are only partially upheld.

  5. Optogenetic dissection of neuronal circuits in zebrafish using viral gene transfer and the Tet system

    Directory of Open Access Journals (Sweden)

    Peixin Zhu

    2009-12-01

    Full Text Available The conditional expression of transgenes at high levels in sparse and specific populations of neurons is important for high-resolution optogenetic analyses of neuronal circuits. We explored two complementary methods, viral gene delivery and the iTet-Off system, to express transgenes in the brain of zebrafish. High-level gene expression in neurons was achieved by Sindbis and Rabies viruses. The Tet system produced strong and specific gene expression that could be modulated conveniently by doxycycline. Moreover, transgenic lines showed expression in distinct, sparse and stable populations of neurons that appeared to be subsets of the neurons targeted by the promoter driving the Tet activator. The Tet system therefore provides the opportunity to generate libraries of diverse expression patterns similar to gene trap approaches or the thy-1 promoter in mice, but with the additional possibility to pre-select cell types of interest. In transgenic lines expressing channelrhodopsin-2, action potential firing could be precisely controlled by two-photon stimulation at low laser power, presumably because the expression levels of the Tet-controlled genes were high even in adults. In channelrhodopsin-2-expressing larvae, optical stimulation with a single blue LED evoked distinct swimming behaviors including backward swimming. These approaches provide new opportunities for the optogenetic dissection of neuronal circuit structure and function.

  6. Reduced motor neuron excitability is an important contributor to weakness in a rat model of sepsis.

    Science.gov (United States)

    Nardelli, Paul; Vincent, Jacob A; Powers, Randall; Cope, Tim C; Rich, Mark M

    2016-08-01

    The mechanisms by which sepsis triggers intensive care unit acquired weakness (ICUAW) remain unclear. We previously identified difficulty with motor unit recruitment in patients as a novel contributor to ICUAW. To study the mechanism underlying poor recruitment of motor units we used the rat cecal ligation and puncture model of sepsis. We identified striking dysfunction of alpha motor neurons during repetitive firing. Firing was more erratic, and often intermittent. Our data raised the possibility that reduced excitability of motor neurons was a significant contributor to weakness induced by sepsis. In this study we quantified the contribution of reduced motor neuron excitability and compared its magnitude to the contributions of myopathy, neuropathy and failure of neuromuscular transmission. We injected constant depolarizing current pulses (5s) into the soma of alpha motor neurons in the lumbosacral spinal cord of anesthetized rats to trigger repetitive firing. In response to constant depolarization, motor neurons in untreated control rats fired at steady and continuous firing rates and generated smooth and sustained tetanic motor unit force as expected. In contrast, following induction of sepsis, motor neurons were often unable to sustain firing throughout the 5s current injection such that force production was reduced. Even when firing, motor neurons from septic rats fired erratically and discontinuously, leading to irregular production of motor unit force. Both fast and slow type motor neurons had similar disruption of excitability. We followed rats after recovery from sepsis to determine the time course of resolution of the defect in motor neuron excitability. By one week, rats appeared to have recovered from sepsis as they had no piloerection and appeared to be in no distress. The defects in motor neuron repetitive firing were still striking at 2weeks and, although improved, were present at one month. We infer that rats suffered from weakness due to reduced

  7. Ongoing spontaneous activity controls access to consciousness: a neuronal model for inattentional blindness.

    Directory of Open Access Journals (Sweden)

    Stanislas Dehaene

    2005-05-01

    Full Text Available Even in the absence of sensory inputs, cortical and thalamic neurons can show structured patterns of ongoing spontaneous activity, whose origins and functional significance are not well understood. We use computer simulations to explore the conditions under which spontaneous activity emerges from a simplified model of multiple interconnected thalamocortical columns linked by long-range, top-down excitatory axons, and to examine its interactions with stimulus-induced activation. Simulations help characterize two main states of activity. First, spontaneous gamma-band oscillations emerge at a precise threshold controlled by ascending neuromodulator systems. Second, within a spontaneously active network, we observe the sudden "ignition" of one out of many possible coherent states of high-level activity amidst cortical neurons with long-distance projections. During such an ignited state, spontaneous activity can block external sensory processing. We relate those properties to experimental observations on the neural bases of endogenous states of consciousness, and particularly the blocking of access to consciousness that occurs in the psychophysical phenomenon of "inattentional blindness," in which normal subjects intensely engaged in mental activity fail to notice salient but irrelevant sensory stimuli. Although highly simplified, the generic properties of a minimal network may help clarify some of the basic cerebral phenomena underlying the autonomy of consciousness.

  8. Reinforcement learning of targeted movement in a spiking neuronal model of motor cortex.

    Directory of Open Access Journals (Sweden)

    George L Chadderdon

    Full Text Available Sensorimotor control has traditionally been considered from a control theory perspective, without relation to neurobiology. In contrast, here we utilized a spiking-neuron model of motor cortex and trained it to perform a simple movement task, which consisted of rotating a single-joint "forearm" to a target. Learning was based on a reinforcement mechanism analogous to that of the dopamine system. This provided a global reward or punishment signal in response to decreasing or increasing distance from hand to target, respectively. Output was partially driven by Poisson motor babbling, creating stochastic movements that could then be shaped by learning. The virtual forearm consisted of a single segment rotated around an elbow joint, controlled by flexor and extensor muscles. The model consisted of 144 excitatory and 64 inhibitory event-based neurons, each with AMPA, NMDA, and GABA synapses. Proprioceptive cell input to this model encoded the 2 muscle lengths. Plasticity was only enabled in feedforward connections between input and output excitatory units, using spike-timing-dependent eligibility traces for synaptic credit or blame assignment. Learning resulted from a global 3-valued signal: reward (+1, no learning (0, or punishment (-1, corresponding to phasic increases, lack of change, or phasic decreases of dopaminergic cell firing, respectively. Successful learning only occurred when both reward and punishment were enabled. In this case, 5 target angles were learned successfully within 180 s of simulation time, with a median error of 8 degrees. Motor babbling allowed exploratory learning, but decreased the stability of the learned behavior, since the hand continued moving after reaching the target. Our model demonstrated that a global reinforcement signal, coupled with eligibility traces for synaptic plasticity, can train a spiking sensorimotor network to perform goal-directed motor behavior.

  9. Computational modeling reveals dendritic origins of GABA(A-mediated excitation in CA1 pyramidal neurons.

    Directory of Open Access Journals (Sweden)

    Naomi Lewin

    Full Text Available GABA is the key inhibitory neurotransmitter in the adult central nervous system, but in some circumstances can lead to a paradoxical excitation that has been causally implicated in diverse pathologies from endocrine stress responses to diseases of excitability including neuropathic pain and temporal lobe epilepsy. We undertook a computational modeling approach to determine plausible ionic mechanisms of GABA(A-dependent excitation in isolated post-synaptic CA1 hippocampal neurons because it may constitute a trigger for pathological synchronous epileptiform discharge. In particular, the interplay intracellular chloride accumulation via the GABA(A receptor and extracellular potassium accumulation via the K/Cl co-transporter KCC2 in promoting GABA(A-mediated excitation is complex. Experimentally it is difficult to determine the ionic mechanisms of depolarizing current since potassium transients are challenging to isolate pharmacologically and much GABA signaling occurs in small, difficult to measure, dendritic compartments. To address this problem and determine plausible ionic mechanisms of GABA(A-mediated excitation, we built a detailed biophysically realistic model of the CA1 pyramidal neuron that includes processes critical for ion homeostasis. Our results suggest that in dendritic compartments, but not in the somatic compartments, chloride buildup is sufficient to cause dramatic depolarization of the GABA(A reversal potential and dominating bicarbonate currents that provide a substantial current source to drive whole-cell depolarization. The model simulations predict that extracellular K(+ transients can augment GABA(A-mediated excitation, but not cause it. Our model also suggests the potential for GABA(A-mediated excitation to promote network synchrony depending on interneuron synapse location - excitatory positive-feedback can occur when interneurons synapse onto distal dendritic compartments, while interneurons projecting to the perisomatic

  10. Reinforcement learning of targeted movement in a spiking neuronal model of motor cortex.

    Science.gov (United States)

    Chadderdon, George L; Neymotin, Samuel A; Kerr, Cliff C; Lytton, William W

    2012-01-01

    Sensorimotor control has traditionally been considered from a control theory perspective, without relation to neurobiology. In contrast, here we utilized a spiking-neuron model of motor cortex and trained it to perform a simple movement task, which consisted of rotating a single-joint "forearm" to a target. Learning was based on a reinforcement mechanism analogous to that of the dopamine system. This provided a global reward or punishment signal in response to decreasing or increasing distance from hand to target, respectively. Output was partially driven by Poisson motor babbling, creating stochastic movements that could then be shaped by learning. The virtual forearm consisted of a single segment rotated around an elbow joint, controlled by flexor and extensor muscles. The model consisted of 144 excitatory and 64 inhibitory event-based neurons, each with AMPA, NMDA, and GABA synapses. Proprioceptive cell input to this model encoded the 2 muscle lengths. Plasticity was only enabled in feedforward connections between input and output excitatory units, using spike-timing-dependent eligibility traces for synaptic credit or blame assignment. Learning resulted from a global 3-valued signal: reward (+1), no learning (0), or punishment (-1), corresponding to phasic increases, lack of change, or phasic decreases of dopaminergic cell firing, respectively. Successful learning only occurred when both reward and punishment were enabled. In this case, 5 target angles were learned successfully within 180 s of simulation time, with a median error of 8 degrees. Motor babbling allowed exploratory learning, but decreased the stability of the learned behavior, since the hand continued moving after reaching the target. Our model demonstrated that a global reinforcement signal, coupled with eligibility traces for synaptic plasticity, can train a spiking sensorimotor network to perform goal-directed motor behavior.

  11. A metabolomic comparison of mouse models of the Neuronal Ceroid Lipofuscinoses

    Energy Technology Data Exchange (ETDEWEB)

    Salek, Reza M.; Pears, Michael R. [University of Cambridge, Department of Biochemistry and Cambridge Systems Biology Centre (United Kingdom); Cooper, Jonathan D. [King' s College London, Pediatric Storage Disorders Laboratory, Department of Neuroscience, Institute of Psychiatry (United Kingdom); Mitchison, Hannah M. [Royal Free and University College Medical School, Department of Paediatrics and Child Health (United Kingdom); Pearce, David A. [Sanford School of Medicine of the University of South Dakota, Department of Pediatrics (United States); Mortishire-Smith, Russell J. [Johnson and Johnson PR and D (Belgium); Griffin, Julian L., E-mail: jlg40@mole.bio.cam.ac.uk [University of Cambridge, Department of Biochemistry and the Cambridge Systems Biology Centre (United Kingdom)

    2011-04-15

    The Neuronal Ceroid Lipofuscinoses (NCL) are a group of fatal inherited neurodegenerative diseases in humans distinguished by a common clinical pathology, characterized by the accumulation of storage body material in cells and gross brain atrophy. In this study, metabolic changes in three NCL mouse models were examined looking for pathways correlated with neurodegeneration. Two mouse models; motor neuron degeneration (mnd) mouse and a variant model of late infantile NCL, termed the neuronal ceroid lipofuscinosis (nclf) mouse were investigated experimentally. Both models exhibit a characteristic accumulation of autofluorescent lipopigment in neuronal and non neuronal cells. The NMR profiles derived from extracts of the cortex and cerebellum from mnd and nclf mice were distinguished according to disease/wildtype status. In particular, a perturbation in glutamine and glutamate metabolism, and a decrease in {gamma}-amino butyric acid (GABA) in the cerebellum and cortices of mnd (adolescent mice) and nclf mice relative to wildtype at all ages were detected. Our results were compared to the Cln3 mouse model of NCL. The metabolism of mnd mice resembled older (6 month) Cln3 mice, where the disease is relatively advanced, while the metabolism of nclf mice was more akin to younger (1-2 months) Cln3 mice, where the disease is in its early stages of progression. Overall, our results allowed the identification of metabolic traits common to all NCL subtypes for the three animal models.

  12. A model explaining synchronization of neuron bioelectric frequency under weak alternating low frequency magnetic field

    Science.gov (United States)

    del Moral, A.; Azanza, María J.

    2015-03-01

    A biomagnetic-electrical model is presented that explains rather well the experimentally observed synchronization of the bioelectric potential firing rate ("frequency"), f, of single unit neurons of Helix aspersa mollusc under the application of extremely low frequency (ELF) weak alternating (AC) magnetic fields (MF). The proposed model incorporates to our widely experimentally tested model of superdiamagnetism (SD) and Ca2+ Coulomb explosion (CE) from lipid (LP) bilayer membrane (SD-CE model), the electrical quadrupolar long range interaction between the bilayer LP membranes of synchronized neuron pairs, not considered before. The quadrupolar interaction is capable of explaining well the observed synchronization. Actual extension of our SD-CE-model shows that the neuron firing frequency field, B, dependence becomes not modified, but the bioelectric frequency is decreased and its spontaneous temperature, T, dependence is modified. A comparison of the model with synchronization experimental results of pair of neurons under weak (B0 ≅0.2-15 mT) AC-MF of frequency fM=50 Hz is reported. From the deduced size of synchronized LP clusters under B, is suggested the formation of small neuron networks via the membrane lipid correlation.

  13. Induced pluripotent stem cell-derived neuronal cells from a sporadic Alzheimer's disease donor as a model for investigating AD-associated gene regulatory networks.

    Science.gov (United States)

    Hossini, Amir M; Megges, Matthias; Prigione, Alessandro; Lichtner, Bjoern; Toliat, Mohammad R; Wruck, Wasco; Schröter, Friederike; Nuernberg, Peter; Kroll, Hartmut; Makrantonaki, Eugenia; Zouboulis, Christos C; Zoubouliss, Christos C; Adjaye, James

    2015-02-14

    Alzheimer's disease (AD) is a complex, irreversible neurodegenerative disorder. At present there are neither reliable markers to diagnose AD at an early stage nor therapy. To investigate underlying disease mechanisms, induced pluripotent stem cells (iPSCs) allow the generation of patient-derived neuronal cells in a dish. In this study, employing iPS technology, we derived and characterized iPSCs from dermal fibroblasts of an 82-year-old female patient affected by sporadic AD. The AD-iPSCs were differentiated into neuronal cells, in order to generate disease-specific protein association networks modeling the molecular pathology on the transcriptome level of AD, to analyse the reflection of the disease phenotype in gene expression in AD-iPS neuronal cells, in particular in the ubiquitin-proteasome system (UPS), and to address expression of typical AD proteins. We detected the expression of p-tau and GSK3B, a physiological kinase of tau, in neuronal cells derived from AD-iPSCs. Treatment of neuronal cells differentiated from AD-iPSCs with an inhibitor of γ-secretase resulted in the down-regulation of p-tau. Transcriptome analysis of AD-iPS derived neuronal cells revealed significant changes in the expression of genes associated with AD and with the constitutive as well as the inducible subunits of the proteasome complex. The neuronal cells expressed numerous genes associated with sub-regions within the brain thus suggesting the usefulness of our in-vitro model. Moreover, an AD-related protein interaction network composed of APP and GSK3B among others could be generated using neuronal cells differentiated from two AD-iPS cell lines. Our study demonstrates how an iPSC-based model system could represent (i) a tool to study the underlying molecular basis of sporadic AD, (ii) a platform for drug screening and toxicology studies which might unveil novel therapeutic avenues for this debilitating neuronal disorder.

  14. Corresponding decrease in neuronal markers signals progressive parvalbumin neuron loss in MAM schizophrenia model

    OpenAIRE

    Gill, Kathryn M; Grace, Anthony A.

    2014-01-01

    Alteration in normal hippocampal (HPC) function attributed to reduced parvalbumin (PV) expression has been consistently reported in schizophrenia patients and in animal models of schizophrenia. However, it is unclear whether there is an overall loss of interneurons as opposed to a reduction in activity-dependent PV content. Co-expression of PV and the constitutively-expressed substance P (SP)-receptor protein has been utilized in other models to ascertain the degree of cell survival, as oppos...

  15. Microglia activation and interaction with neuronal cells in a biochemical model of mevalonate kinase deficiency.

    Science.gov (United States)

    Tricarico, Paola Maura; Piscianz, Elisa; Monasta, Lorenzo; Kleiner, Giulio; Crovella, Sergio; Marcuzzi, Annalisa

    2015-08-01

    Mevalonate kinase deficiency is a rare disease whose worst manifestation, characterised by severe neurologic impairment, is called mevalonic aciduria. The progressive neuronal loss associated to cell death can be studied in vitro with a simplified model based on a biochemical block of the mevalonate pathway and a subsequent inflammatory trigger. The aim of this study was to evaluate the effect of the mevalonate blocking on glial cells (BV-2) and the following effects on neuronal cells (SH-SY5Y) when the two populations were cultured together. To better understand the cross-talk between glial and neuronal cells, as it happens in vivo, BV-2 and SH-SY5Y were co-cultured in different experimental settings (alone, transwell, direct contact); the effect of mevalonate pathway biochemical block by Lovastatin, followed by LPS inflammatory trigger, were evaluated by analysing programmed cell death and mitochondrial membrane potential, cytokines' release and cells' morphology modifications. In this experimental condition, glial cells underwent an evident activation, confirmed by elevated pro-inflammatory cytokines release, typical of these disorders, and a modification in morphology. Moreover, the activation induced an increase in apoptosis. When glial cells were co-cultured with neurons, their activation caused an increase of programmed cell death also in neuronal cells, but only if the two populations were cultured in direct contact. Our findings, being aware of the limitations related to the cell models used, represent a preliminary step towards understanding the pathological and neuroinflammatory mechanisms occurring in mevalonate kinase diseases. Contact co-culture between neuronal and microglial cells seems to be a good model to study mevalonic aciduria in vitro, and to contribute to the identification of potential drugs able to block microglial activation for this orphan disease. In fact, in such a pathological condition, we demonstrated that microglial cells are

  16. Dynamic random links enhance diversity-induced coherence in strongly coupled neuronal systems

    Indian Academy of Sciences (India)

    Neeraj Kumar Kamal; Sudeshna Sinha

    2015-02-01

    We investigate the influence of diversity on the temporal regularity of spiking in a ring of coupled model neurons. We find diversity-induced coherence in the spike events, with an optimal amount of parametric heterogeneity at the nodal level yielding the greatest regularity in the spike train. Further, we investigate the system under random spatial connections, where the links are both dynamic and quenched, and in all the cases we observe marked diversity-induced coherence. We quantitatively find the effect of coupling strength and random rewiring probability, on the optimal coherence that can be achieved under diversity. Our results indicate that the largest coherence in the spike events emerge when the coupling strength is high, and when the underlying connections are mostly random and dynamically changing.

  17. Effect of antioxidant treatment on spinal GABA neurons in a neuropathic pain model in the mouse.

    Science.gov (United States)

    Yowtak, June; Wang, Jigong; Kim, Hee Young; Lu, Ying; Chung, Kyungsoon; Chung, Jin Mo

    2013-11-01

    One feature of neuropathic pain is a reduced spinal gamma-aminobutyric acid (GABA)-ergic inhibitory function. However, the mechanisms behind this attenuation remain to be elucidated. This study investigated the involvement of reactive oxygen species in the spinal GABA neuron loss and reduced GABA neuron excitability in spinal nerve ligation (SNL) model of neuropathic pain in mice. The importance of spinal GABAergic inhibition in neuropathic pain was tested by examining the effects of intrathecally administered GABA receptor agonists and antagonists in SNL and naïve mice, respectively. The effects of SNL and antioxidant treatment on GABA neuron loss and functional changes were examined in transgenic GAD67-enhanced green fluorescent protein positive (EGFP+) mice. GABA receptor agonists transiently reversed mechanical hypersensitivity of the hind paw in SNL mice. On the other hand, GABA receptor antagonists made naïve mice mechanically hypersensitive. Stereological analysis showed that the numbers of enhanced green fluorescent protein positive (EGFP+) GABA neurons were significantly decreased in the lateral superficial laminae (I-II) on the ipsilateral L5 spinal cord after SNL. Repeated antioxidant treatments significantly reduced the pain behaviors and prevented the reduction in EGFP+ GABA neurons. The response rate of the tonic firing GABA neurons recorded from SNL mice increased with antioxidant treatment, whereas no change was seen in those recorded from naïve mice, which suggested that oxidative stress impaired some spinal GABA neuron activity in the neuropathic pain condition. Together the data suggest that neuropathic pain, at least partially, is attributed to oxidative stress, which induces both a GABA neuron loss and dysfunction of surviving GABA neurons. Copyright © 2013 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

  18. Non-neuronal cholinergic system in airways and lung cancer susceptibility.

    Science.gov (United States)

    Saracino, Laura; Zorzetto, Michele; Inghilleri, Simona; Pozzi, Ernesto; Stella, Giulia Maria

    2013-08-01

    In the airway tract acetylcholine (ACh) is known to be the mediator of the parasympathetic nervous system. However ACh is also synthesized by a large variety of non-neuronal cells. Strongest expression is documented in neuroendocrine and in epithelial cells (ciliated, basal and secretory elements). Growing evidence suggests that a cell-type specific Ach expression and release do exist and act with local autoparacrine loop in the non-neuronal airway compartment. Here we review the molecular mechanism by which Ach is involved in regulating various aspects of innate mucosal defense, including mucociliary clearance, regulation of macrophage activation as well as in promoting epithelial cells proliferation and conferring susceptibility to lung carcinoma onset. Importantly this non-neuronal cholinergic machinery is differently regulated than the neuronal one and could be specifically therapeutically targeted.

  19. A Radio-Telemetry System for Navigation and Recording Neuronal Activity in Free-Roaming Rats

    Institute of Scientific and Technical Information of China (English)

    Dian Zhang; Yanling Dong; Megan Li; Houjun Wang

    2012-01-01

    A radio-telemetry recording system is presented which is applied to stimulate specific brain areas and record neuronal activity in a free-roaming rat.The system consists of two major parts:stationary section and mobile section.The stationary section contains a laptop,a Micro Control Unit (MCU),an FM transmitter and a receiver.The mobile section is composed of the headstage and the backpack (which includes the mainboard,FM transmitter,and receiver),which can generate biphasic microcurrent pulses and simultaneously acquire neuronal activity.Prior to performing experiments,electrodes are implanted in the Ventral Posterolateral (VPL) thalamic nucleus,primary motor area (M 1) and Medial Forebrain Bundle (MFB) of the rat.The stationary section modulates commands from the laptop for stimulation and demodulates signals for neuronal activity recording.The backpack is strapped on the back of the rat and executes commands from the stationary section,acquires neuronal activity,and transmits the neuronal activity singles of the waking rat to the stationary section.All components in the proposed system are commercially available and are fabricated from Surface Mount Devices (SMD) in order to reduce the size (25 mm × 15 mm × 2 mm) and weight (10 g with battery).During actual experiments,the backpack,which is powered by a rechargeable Lithium battery (4 g),can generate biphasic microcurrent pulse stimuli and can also record neuronal activity via the FM link with a maximum transmission rate of 1 kbps for more than one hour within a 200 m range in an open field or in a neighboring chamber.The test results show that the system is able to remotely navigate and control the rat without any prior training,and acquire neuronal activity with desirable features such as small size,low power consumption and high precision when compared with a commercial 4-channel bio-signal acquisition and processing system.

  20. Changes in Enteric Neurons of Small Intestine in a Rat Model of Irritable Bowel Syndrome with Diarrhea.

    Science.gov (United States)

    Li, Shan; Fei, Guijun; Fang, Xiucai; Yang, Xilin; Sun, Xiaohong; Qian, Jiaming; Wood, Jackie D; Ke, Meiyun

    2016-04-30

    Physical and/or emotional stresses are important factors in the exacerbation of symptoms in irritable bowel syndrome (IBS). Several lines of evidence support that a major impact of stress on the gastrointestinal tract occurs via the enteric nervous system. We aimed to evaluate histological changes in the submucosal plexus (SMP) and myenteric plexus (MP) of the distal ileum in concert with the intestinal motor function in a rat model of IBS with diarrhea. The rat model was induced by heterotypic chronic and acute stress (CAS). The intestinal transit was measured by administering powdered carbon by gastric gavage. Double immunohistochemical fluorescence staining with whole-mount preparations of SMP and MP of enteric nervous system was used to assess changes in expression of choline acetyltransferase, vasoactive intestinal peptide, or nitric oxide synthase in relation to the pan neuronal marker, anti-Hu. The intestinal transit ratio increased significantly from control values of 50.8% to 60.6% in the CAS group. The numbers of enteric ganglia and neurons in the SMP were increased in the CAS group. The proportions of choline acetyltransferase- and vasoactive intestinal peptide-immunoreactive neurons in the SMP were increased (82.1 ± 4.3% vs. 76.0 ± 5.0%, P = 0.021; 40.5 ± 5.9% vs 28.9 ± 3.7%, P = 0.001), while nitric oxide synthase-immunoreactive neurons in the MP were decreased compared with controls (23.3 ± 4.5% vs 32.4 ± 4.5%, P = 0.002). These morphological changes in enteric neurons to CAS might contribute to the dysfunction in motility and secretion in IBS with diarrhea.

  1. Does dysfunction of the mirror neuron system contribute to symptoms in amyotrophic lateral sclerosis?

    Science.gov (United States)

    Eisen, Andrew; Lemon, Roger; Kiernan, Matthew C; Hornberger, Michael; Turner, Martin R

    2015-07-01

    There is growing evidence that mirror neurons, initially discovered over two decades ago in the monkey, are present in the human brain. In the monkey, mirror neurons characteristically fire not only when it is performing an action, such as grasping an object, but also when observing a similar action performed by another agent (human or monkey). In this review we discuss the origin, cortical distribution and possible functions of mirror neurons as a background to exploring their potential relevance in amyotrophic lateral sclerosis (ALS). We have recently proposed that ALS (and the related condition of frontotemporal dementia) may be viewed as a failure of interlinked functional complexes having their origins in key evolutionary adaptations. This can include loss of the direct projections from the corticospinal tract, and this is at least part of the explanation for impaired motor control in ALS. Since, in the monkey, corticospinal neurons also show mirror properties, ALS in humans might also affect the mirror neuron system. We speculate that a defective mirror neuron system might contribute to other ALS deficits affecting motor imagery, gesture, language and empathy. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  2. A model for experience-dependent changes in the responses of inferotemporal neurons.

    Science.gov (United States)

    Sohal, V S; Hasselmo, M E

    2000-08-01

    Neurons in inferior temporal (IT) cortex exhibit selectivity for complex visual stimuli and can maintain activity during the delay following the presentation of a stimulus in delayed match to sample tasks. Experimental work in awake monkeys has shown that the responses of IT neurons decline during presentation of stimuli which have been seen recently (within the past few seconds). In addition, experiments have found that the responses of IT neurons to visual stimuli also decline as the stimuli become familiar, independent of recency. Here a biologically based neural network simulation is used to model these effects primarily through two processes. The recency effects are caused by adaptation due to a calcium-dependent potassium current, and the familiarity effects are caused by competitive self-organization of modifiable feedforward synapses terminating on IT cortex neurons.

  3. Automatic Construction of Predictive Neuron Models through Large Scale Assimilation of Electrophysiological Data

    Science.gov (United States)

    Nogaret, Alain; Meliza, C. Daniel; Margoliash, Daniel; Abarbanel, Henry D. I.

    2016-09-01

    We report on the construction of neuron models by assimilating electrophysiological data with large-scale constrained nonlinear optimization. The method implements interior point line parameter search to determine parameters from the responses to intracellular current injections of zebra finch HVC neurons. We incorporated these parameters into a nine ionic channel conductance model to obtain completed models which we then use to predict the state of the neuron under arbitrary current stimulation. Each model was validated by successfully predicting the dynamics of the membrane potential induced by 20–50 different current protocols. The dispersion of parameters extracted from different assimilation windows was studied. Differences in constraints from current protocols, stochastic variability in neuron output, and noise behave as a residual temperature which broadens the global minimum of the objective function to an ellipsoid domain whose principal axes follow an exponentially decaying distribution. The maximum likelihood expectation of extracted parameters was found to provide an excellent approximation of the global minimum and yields highly consistent kinetics for both neurons studied. Large scale assimilation absorbs the intrinsic variability of electrophysiological data over wide assimilation windows. It builds models in an automatic manner treating all data as equal quantities and requiring minimal additional insight.

  4. A new kind of neuron model with a tunable activation function and its applications

    Institute of Scientific and Technical Information of China (English)

    吴佑寿; 赵明生; 丁晓青

    1997-01-01

    A new neuron model with a tunable activation function, denoted by the TAF model, and its application are addressed. The activation function as well as the connection weights of the neuron model can be adjusted in the training process The two-spiral problem was used as an example to show how to deduce the adjustable activation function required, and how to construct and train the network by the use of the a priori knowledge of the problem. Due to the incorporation of constraints known a priori into the activation function, many novel aspects are revealed, such as small network size, fast learning and good performances. It is believed that the introduction of the new neuron model will pave a new way in ANN studies.

  5. A Coupled Phase-Temperature Model for Dynamics of Transient Neuronal Signal in Mammals Cold Receptor

    Science.gov (United States)

    Kirana, Firman Ahmad; Husein, Irzaman Sulaiman

    2016-01-01

    We propose a theoretical model consisting of coupled differential equation of membrane potential phase and temperature for describing the neuronal signal in mammals cold receptor. Based on the results from previous work by Roper et al., we modified a nonstochastic phase model for cold receptor neuronal signaling dynamics in mammals. We introduce a new set of temperature adjusted functional parameters which allow saturation characteristic at high and low steady temperatures. The modified model also accommodates the transient neuronal signaling process from high to low temperature by introducing a nonlinear differential equation for the “effective temperature” changes which is coupled to the phase differential equation. This simple model can be considered as a candidate for describing qualitatively the physical mechanism of the corresponding transient process. PMID:27774102

  6. A Coupled Phase-Temperature Model for Dynamics of Transient Neuronal Signal in Mammals Cold Receptor

    Directory of Open Access Journals (Sweden)

    Firman Ahmad Kirana

    2016-01-01

    Full Text Available We propose a theoretical model consisting of coupled differential equation of membrane potential phase and temperature for describing the neuronal signal in mammals cold receptor. Based on the results from previous work by Roper et al., we modified a nonstochastic phase model for cold receptor neuronal signaling dynamics in mammals. We introduce a new set of temperature adjusted functional parameters which allow saturation characteristic at high and low steady temperatures. The modified model also accommodates the transient neuronal signaling process from high to low temperature by introducing a nonlinear differential equation for the “effective temperature” changes which is coupled to the phase differential equation. This simple model can be considered as a candidate for describing qualitatively the physical mechanism of the corresponding transient process.

  7. Neural networks with multiple general neuron models: a hybrid computational intelligence approach using Genetic Programming.

    Science.gov (United States)

    Barton, Alan J; Valdés, Julio J; Orchard, Robert

    2009-01-01

    Classical neural networks are composed of neurons whose nature is determined by a certain function (the neuron model), usually pre-specified. In this paper, a type of neural network (NN-GP) is presented in which: (i) each neuron may have its own neuron model in the form of a general function, (ii) any layout (i.e network interconnection) is possible, and (iii) no bias nodes or weights are associated to the connections, neurons or layers. The general functions associated to a neuron are learned by searching a function space. They are not provided a priori, but are rather built as part of an Evolutionary Computation process based on Genetic Programming. The resulting network solutions are evaluated based on a fitness measure, which may, for example, be based on classification or regression errors. Two real-world examples are presented to illustrate the promising behaviour on classification problems via construction of a low-dimensional representation of a high-dimensional parameter space associated to the set of all network solutions.

  8. Bursting and spiking due to additional direct and stochastic currents in neuron models

    Institute of Scientific and Technical Information of China (English)

    Yang Zhuo-Qin; Lu Qi-Shao

    2006-01-01

    Neurons at rest can exhibit diverse firing activities patterns in response to various external deterministic and random stimuli, especially additional currents. In this paper, neuronal firing patterns from bursting to spiking, induced by additional direct and stochastic currents, are explored in rest states Corresponding to two values of the parameter VK in the Chay neuron system. Three cases are considered by numerical simulation and fast/slow dynamic analysis, in which only the direct current or the stochastic current exists, or the direct and stochastic currents coexist. Meanwhile, several important bursting patterns in neuronal experiments, such as the period-1 "circle/homoclinic" bursting and the integer multiple "fold/homoclinic" bursting with one spike per burst, as well as the transition from integer multiple bursting to period-1 "circle/homoclinic" bursting and that from stochastic "Hopf/homoclinic" bursting to "Hopf/homoclinic" bursting, are investigated in detail.

  9. Phase diagrams and dynamics of a computationally efficient map-based neuron model

    Science.gov (United States)

    Gonsalves, Jheniffer J.; Tragtenberg, Marcelo H. R.

    2017-01-01

    We introduce a new map-based neuron model derived from the dynamical perceptron family that has the best compromise between computational efficiency, analytical tractability, reduced parameter space and many dynamical behaviors. We calculate bifurcation and phase diagrams analytically and computationally that underpins a rich repertoire of autonomous and excitable dynamical behaviors. We report the existence of a new regime of cardiac spikes corresponding to nonchaotic aperiodic behavior. We compare the features of our model to standard neuron models currently available in the literature. PMID:28358843

  10. Measures of transinformation for multiple input/single output neuronal systems.

    Science.gov (United States)

    Windhorst, U; Schultens, H A

    1982-01-01

    This paper presents a method for the calculation of the information transfer, or transinformation, in multiple input/single output neuronal systems. Our approach is an extension of an approach introduced by Eckhorn and Poepel in 1974. These authors computed the transinformation in single input/single output neuronal channels by regarding the spike (or stimulus) trains involved as finite Markov chains. The expressions for multiple input systems presented here are derived in close analogy to formulae in linear systems theory which show explicitly the correlations between the different input channels. A number of equivalent forms for the transinformation are discussed.

  11. Purpose of neuronal method for modeling of solar collector

    Energy Technology Data Exchange (ETDEWEB)

    Salah, Hanini; Moussa, Cherif Si [LBMPt, Universite Yahia Fares de Medea, Quartier Ain D' heb, 2600, Medea (Algeria); Hamid, Abdi [SEEs/MS, B.P. 478, Route de Reggane, Adrar (Algeria); Tariq, Omari [LBMPT, Universite Yahia Fares de Medea, Quartier Ain D' Heb, 2600, Medea (Algeria); SEES/MS, B.P. 478, Route de Reggane, Adrar (Algeria); Unite de developpement des equipments solaires, Bou-Ismail, Tipaza (Algeria)

    2012-07-01

    Artificial Neural Networks (ANN) are widely accepted as a technology offering an alternative way to tackle complex and ill-defined problems. They have been used in diverse applications and have shown to be particularly effective in system identification and modeling as they are fault tolerant and can learn from examples. On the other hand, ANN are able to deal with non-linear problems and once trained can perform prediction at high speed. The objective of this work is the characterization of the integrated collector-storage solar water heater (ICSSWH) by the determination of the day time thermal (and optical) properties, and Night time heat loss coefficient with experimental temperatures, and predictive temperatures by (ANN). Because of that, an ANN has been trained using data for three types of systems, all employing the same collector panel under varying weather conditions. In this way the network was trained to accept and handle a number of unusual cases. The data presented as input were, the working systems (day or night), the type of system, the year, the month, the day, the time, the ambient air temperature, and the solar radiation. The network output is the temperature of the four tanks of storage unit. The correlations coefficients (R2-value) obtained for the training data set was equal to 0.997, 0.998, 0.998, and 0.996 for the four temperatures of each tank. The results obtained in this work indicate that the proposed method can successfully be used for the characterization of the ICSSWH.

  12. Purpose of neuronal method for modeling of solar collector

    Directory of Open Access Journals (Sweden)

    Omari Tariq, Hanini Salah, Cherif Si Moussa, Hamid Abdi

    2012-01-01

    Full Text Available Artificial Neural Networks (ANN are widely accepted as a technology offering an alternative way to tackle complex and ill-defined problems. They have been used in diverse applications and have shown to be particularly effective in system identification and modeling as they are fault tolerant and can learn from examples. On the other hand, ANN are able to deal with non-linear problems and once trained can perform prediction at high speed. The objective of this work is the characterization of the integrated collector-storage solar water heater (ICSSWH by the determination of the day time thermal (and optical properties, and Night time heat loss coefficient with experimental temperatures, and predictive temperatures by (ANN. Because of that, an ANN has been trained using data for three types of systems, all employing the same collector panel under varying weather conditions. In this way the network was trained to accept and handle a number of unusual cases. The data presented as input were, the working systems (day or night, the type of system, the year, the month, the day, the time, the ambient air temperature, and the solar radiation. The network output is the temperature of the four tanks of storage unit. The correlations coefficients (R2 –value obtained for the training data set was equal to 0.997, 0.998, 0.998, and 0.996 for the four temperatures of each tank. The results obtained in this work indicate that the proposed method can successfully be used for the characterization of the ICSSWH.

  13. Cofilin Inhibition Restores Neuronal Cell Death in Oxygen-Glucose Deprivation Model of Ischemia.

    Science.gov (United States)

    Madineni, Anusha; Alhadidi, Qasim; Shah, Zahoor A

    2016-03-01

    Ischemia is a condition associated with decreased blood supply to the brain, eventually leading to death of neurons. It is associated with a diverse cascade of responses involving both degenerative and regenerative mechanisms. At the cellular level, the changes are initiated prominently in the neuronal cytoskeleton. Cofilin, a cytoskeletal actin severing protein, is known to be involved in the early stages of apoptotic cell death. Evidence supports its intervention in the progression of disease states like Alzheimer's and ischemic kidney disease. In the present study, we have hypothesized the possible involvement of cofilin in ischemia. Using PC12 cells and mouse primary cultures of cortical neurons, we investigated the potential role of cofilin in ischemia in two different in vitro ischemic models: chemical induced oxidative stress and oxygen-glucose deprivation/reperfusion (OGD/R). The expression profile studies demonstrated a decrease in phosphocofilin levels in all models of ischemia, implying stress-induced cofilin activation. Furthermore, calcineurin and slingshot 1L (SSH) phosphatases were found to be the signaling mediators of the cofilin activation. In primary cultures of cortical neurons, cofilin was found to be significantly activated after 1 h of OGD. To delineate the role of activated cofilin in ischemia, we knocked down cofilin by small interfering RNA (siRNA) technique and tested the impact of cofilin silencing on neuronal viability. Cofilin siRNA-treated neurons showed a significant reduction of cofilin levels in all treatment groups (control, OGD, and OGD/R). Additionally, cofilin siRNA-reduced cofilin mitochondrial translocation and caspase 3 cleavage, with a concomitant increase in neuronal viability. These results strongly support the active role of cofilin in ischemia-induced neuronal degeneration and apoptosis. We believe that targeting this protein mediator has a potential for therapeutic intervention in ischemic brain injury and stroke.

  14. Coculture of Primary Motor Neurons and Schwann Cells as a Model for In Vitro Myelination.

    Science.gov (United States)

    Hyung, Sujin; Yoon Lee, Bo; Park, Jong-Chul; Kim, Jinseok; Hur, Eun-Mi; Francis Suh, Jun-Kyo

    2015-10-12

    A culture system that can recapitulate myelination in vitro will not only help us better understand the mechanism of myelination and demyelination, but also find out possible therapeutic interventions for treating demyelinating diseases. Here, we introduce a simple and reproducible myelination culture system using mouse motor neurons (MNs) and Schwann cells (SCs). Dissociated motor neurons are plated on a feeder layer of SCs, which interact with and wrap around the axons of MNs as they differentiate in culture. In our MN-SC coculture system, MNs survived over 3 weeks and extended long axons. Both viability and axon growth of MNs in the coculture were markedly enhanced as compared to those of MN monoculture. Co-labeling of myelin basic proteins (MBPs) and neuronal microtubules revealed that SC formed myelin sheaths by wrapping around the axons of MNs. Furthermore, using the coculture system we found that treatment of an antioxidant substance coenzyme Q10 (Co-Q10) markedly facilitated myelination.

  15. Two cell circuits of oriented adult hippocampal neurons on self-assembled monolayers for use in the study of neuronal communication in a defined system.

    Science.gov (United States)

    Edwards, Darin; Stancescu, Maria; Molnar, Peter; Hickman, James J

    2013-08-21

    In this study, we demonstrate the directed formation of small circuits of electrically active, synaptically connected neurons derived from the hippocampus of adult rats through the use of engineered chemically modified culture surfaces that orient the polarity of the neuronal processes. Although synaptogenesis, synaptic communication, synaptic plasticity, and brain disease pathophysiology can be studied using brain slice or dissociated embryonic neuronal culture systems, the complex elements found in neuronal synapses makes specific studies difficult in these random cultures. The study of synaptic transmission in mature adult neurons and factors affecting synaptic transmission are generally studied in organotypic cultures, in brain slices, or in vivo. However, engineered neuronal networks would allow these studies to be performed instead on simple functional neuronal circuits derived from adult brain tissue. Photolithographic patterned self-assembled monolayers (SAMs) were used to create the two-cell "bidirectional polarity" circuit patterns. This pattern consisted of a cell permissive SAM, N-1[3-(trimethoxysilyl)propyl] diethylenetriamine (DETA), and was composed of two 25 μm somal adhesion sites connected with 5 μm lines acting as surface cues for guided axonal and dendritic regeneration. Surrounding the DETA pattern was a background of a non-cell-permissive poly(ethylene glycol) (PEG) SAM. Adult hippocampal neurons were first cultured on coverslips coated with DETA monolayers and were later passaged onto the PEG-DETA bidirectional polarity patterns in serum-free medium. These neurons followed surface cues, attaching and regenerating only along the DETA substrate to form small engineered neuronal circuits. These circuits were stable for more than 21 days in vitro (DIV), during which synaptic connectivity was evaluated using basic electrophysiological methods.

  16. Changes in the Excitability of Neocortical Neurons in a Mouse Model of Amyotrophic Lateral Sclerosis Are Not Specific to Corticospinal Neurons and Are Modulated by Advancing Disease.

    Science.gov (United States)

    Kim, Juhyun; Hughes, Ethan G; Shetty, Ashwin S; Arlotta, Paola; Goff, Loyal A; Bergles, Dwight E; Brown, Solange P

    2017-09-13

    Cell type-specific changes in neuronal excitability have been proposed to contribute to the selective degeneration of corticospinal neurons in amyotrophic lateral sclerosis (ALS) and to neocortical hyperexcitability, a prominent feature of both inherited and sporadic variants of the disease, but the mechanisms underlying selective loss of specific cell types in ALS are not known. We analyzed the physiological properties of distinct classes of cortical neurons in the motor cortex of hSOD1(G93A) mice of both sexes and found that they all exhibit increases in intrinsic excitability that depend on disease stage. Targeted recordings and in vivo calcium imaging further revealed that neurons adapt their functional properties to normalize cortical excitability as the disease progresses. Although different neuron classes all exhibited increases in intrinsic excitability, transcriptional profiling indicated that the molecular mechanisms underlying these changes are cell type specific. The increases in excitability in both excitatory and inhibitory cortical neurons show that selective dysfunction of neuronal cell types cannot account for the specific vulnerability of corticospinal motor neurons in ALS. Furthermore, the stage-dependent alterations in neuronal function highlight the ability of cortical circuits to adapt as disease progresses. These findings show that both disease stage and cell type must be considered when developing therapeutic strategies for treating ALS.SIGNIFICANCE STATEMENT It is not known why certain classes of neurons preferentially die in different neurodegenerative diseases. It has been proposed that the enhanced excitability of affected neurons is a major contributor to their selective loss. We show using a mouse model of amyotrophic lateral sclerosis (ALS), a disease in which corticospinal neurons exhibit selective vulnerability, that changes in excitability are not restricted to this neuronal class and that excitability does not increase

  17. Cell Death, Neuronal Plasticity and Functional Loading in the Development of the Central Nervous System

    Science.gov (United States)

    Keefe, J. R.

    1985-01-01

    Research on the precise timing and regulation of neuron production and maturation in the vestibular and visual systems of Wistar rats and several inbred strains of mice (C57B16 and Pallid mutant) concentrated upon establishing a timing baseline for mitotic development of the neurons of the vestibular nuclei and the peripheral vestibular sensory structures (maculae, cristae). This involved studies of the timing and site of neuronal cell birth and preliminary studies of neuronal cell death in both central and peripheral elements of the mammalian vestibular system. Studies on neuronal generation and maturation in the retina were recently added to provide a mechanism for more properly defining the in utero' developmental age of the individual fetal subject and to closely monitor potential transplacental effects of environmentally stressed maternal systems. Information is given on current efforts concentrating upon the (1) perinatal period of development (E18 thru P14) and (2) the role of cell death in response to variation in the functional loading of the vestibular and proprioreceptive systems in developing mammalian organisms.

  18. Labeling second-order sensory neurons in the posterior lateral-line system of zebrafish.

    Science.gov (United States)

    Schuster, Kevin; Ghysen, Alain

    2013-12-01

    The lateral line is a mechanosensory system that comprises a set of discrete sense organs called neuromasts, which are arranged in reproducible patterns on the surface of fish and amphibians. The posterior component of the system, the posterior lateral line (PLL), comprises the neuromasts on the body and tail and has its ganglion just posterior to the otic vesicle. The peripheral location of the PLL system makes it accessible and easily visualized by imaging methods. Neuromasts are innervated by a few afferent neurons (usually two, but sometimes more), which have their cell bodies clustered in cranial ganglia and project their central axons to the hindbrain, where they extend longitudinally along all rhombomeres. Positively charged lipophilic carbocyanine dyes, such as DiI, have traditionally been used to label neurons, as described here. This method is especially useful for the analysis of PLL innervation because injection of the dye into a neuromast leads to specific labeling of the afferent neurons. The method can also be used to follow the flow of PLL information to higher central nervous system levels by first labeling the central projection of chosen afferent neurons and then making a second injection of DiI within the synaptic field to label the second-order neurons that extend dendrites to this field.

  19. Control of neuronal excitability by calcium binding proteins : a new mathematical model for striatal fast-spiking interneurons.

    Directory of Open Access Journals (Sweden)

    Don Patrick eBischop

    2012-07-01

    Full Text Available Calcium binding proteins, such as parvalbumin, are abundantly expressed in very distinctive patterns in the central nervous system but their physiological function remains poorly understood. Notably, at the level of the striatum, parvalbumin is only expressed in the fast spiking (FS interneurons, which form a inhibitory network modulating the output of the striatum by synchronizing medium-sized spiny neurons (MSN. So far the existing conductance-based computational models for FS neurons did not allow the study of the the coupling between parvalbumin concentration and electrical activity. In the present paper, we propose a new mathematical model for the striatal FS interneurons that includes apamin-sensitive small conductance ca -dependent kk channels (SK and takes into account the presence of a calcium buffer. Our results demonstrate that a variation in the concentration of parvalbumin can modulate substantially the intrinsic excitability of the FS interneurons and therefore may be involved in the information processing at the striatal level.

  20. Corresponding decrease in neuronal markers signals progressive parvalbumin neuron loss in MAM schizophrenia model.

    Science.gov (United States)

    Gill, Kathryn M; Grace, Anthony A

    2014-10-01

    Alteration in normal hippocampal (HPC) function attributed to reduced parvalbumin (PV) expression has been consistently reported in schizophrenia patients and in animal models of schizophrenia. However, it is unclear whether there is an overall loss of interneurons as opposed to a reduction in activity-dependent PV content. Co-expression of PV and the constitutively expressed substance P (SP)-receptor protein has been utilized in other models to ascertain the degree of cell survival, as opposed to reduction in activity-dependent PV content, in the HPC. The present study measured the co-expression of PV and SP-receptors in the dentate and dorsal and ventral CA3 subregions of the HPC in the methylazoymethanol acetate (MAM) rat neurodevelopmental model of schizophrenia. In addition, these changes were compared at the post-natal day 27 (PND27) and post-natal day 240 (PND > 240) time points. Brains from PND27 and PND > 240 MAM (n = 8) and saline (SAL, n = 8) treated offspring were immunohistochemically processed for the co-expression of PV and SP-receptors. The dorsal dentate, dorsal CA3 and ventral CA3 subregions of PND27 and PND > 240 MAM rats demonstrated significant reductions in PV but not SP-receptor expression, signifying a loss of PV-content. In contrast, in the ventral dentate the co-expression of PV and SP-receptors was significantly reduced only in PND > 240 MAM animals, suggesting a reduction in cell number. While MAM-induced reduction of PV content occurs in CA3 of dorsal and ventral HPC, the most substantial loss of interneuron number is localized to the ventral dentate of PND > 240 animals. The disparate loss of PV in HPC subregions likely impacts intra-HPC network activity in MAM rats.

  1. Plasticity-modulated seizure dynamics for seizure termination in realistic neuronal models

    NARCIS (Netherlands)

    Koppert, M.M.J.; Kalitzin, S.; Lopes da Silva, F.H.; Viergever, M.A.

    2011-01-01

    In previous studies we showed that autonomous absence seizure generation and termination can be explained by realistic neuronal models eliciting bi-stable dynamics. In these models epileptic seizures are triggered either by external stimuli (reflex epilepsies) or by internal fluctuations. This scena

  2. Plasticity-modulated seizure dynamics for seizure termination in realistic neuronal models

    NARCIS (Netherlands)

    Koppert, M.M.J.; Kalitzin, S.; Lopes da Silva, F.H.; Viergever, M.A.

    2011-01-01

    In previous studies we showed that autonomous absence seizure generation and termination can be explained by realistic neuronal models eliciting bi-stable dynamics. In these models epileptic seizures are triggered either by external stimuli (reflex epilepsies) or by internal fluctuations. This

  3. Rat model of cancer-induced bone pain: changes in nonnociceptive sensory neurons in vivo

    Directory of Open Access Journals (Sweden)

    Yong Fang Zhu

    2017-08-01

    Conclusion:. After induction of the CIBP model, Aβ-fiber LTMs at >2 weeks but not <1 week had undergone changes in electrophysiological properties. Importantly, changes observed are consistent with observations in models of peripheral neuropathy. Thus, Aβ-fiber nonnociceptive primary sensory neurons might be involved in the peripheral sensitization and tumor-induced tactile hypersensitivity in CIBP.

  4. Conversational Rate of a Non-Vocal Person with Motor Neurone Disease Using the 'TALK' System.

    Science.gov (United States)

    Todman, J.; Lewins, E.

    1996-01-01

    This study evaluated the use of TALK, a computer-based augmentative and alternative communication (AAC) system, in the social communications of a nonvocal woman with motor neurone disease. She was able to achieve an average conversational rate of 42 words per minute (wpm) using TALK, compared with 2 to 10 wpm with other AAC systems using…

  5. The anthropomorphic brain : The mirror neuron system responds to human and robotic actions

    NARCIS (Netherlands)

    Gazzola, V.; Rizzolatti, G.; Wicker, B.; Keysers, C.

    2007-01-01

    In humans and monkeys the mirror neuron system transforms seen actions into our inner representation of these actions. Here we asked if this system responds also if we see an industrial robot perform similar actions. We localised the motor areas involved in the execution of hand actions, presented t

  6. Statistics of a leaky integrate-and-fire model of neurons driven by dichotomous noise

    Science.gov (United States)

    Mankin, Romi; Lumi, Neeme

    2016-05-01

    The behavior of a stochastic leaky integrate-and-fire model of neurons is considered. The effect of temporally correlated random neuronal input is modeled as a colored two-level (dichotomous) Markovian noise. Relying on the Riemann method, exact expressions for the output interspike interval density and for the serial correlation coefficient are derived, and their dependence on noise parameters (such as correlation time and amplitude) is analyzed. Particularly, noise-induced sign reversal and a resonancelike amplification of the kurtosis of the interspike interval distribution are established. The features of spike statistics, analytically revealed in our study, are compared with recently obtained results for a perfect integrate-and-fire neuron model.

  7. Emergent Central Pattern Generator Behavior in Gap-Junction-Coupled Hodgkin-Huxley Style Neuron Model

    Directory of Open Access Journals (Sweden)

    Kyle G. Horn

    2012-01-01

    Full Text Available Most models of central pattern generators (CPGs involve two distinct nuclei mutually inhibiting one another via synapses. Here, we present a single-nucleus model of biologically realistic Hodgkin-Huxley neurons with random gap junction coupling. Despite no explicit division of neurons into two groups, we observe a spontaneous division of neurons into two distinct firing groups. In addition, we also demonstrate this phenomenon in a simplified version of the model, highlighting the importance of afterhyperpolarization currents ( to CPGs utilizing gap junction coupling. The properties of these CPGs also appear sensitive to gap junction conductance, probability of gap junction coupling between cells, topology of gap junction coupling, and, to a lesser extent, input current into our simulated nucleus.

  8. Organization of the histaminergic system in adult zebrafish (Danio rerio) brain: neuron number, location, and cotransmitters.

    Science.gov (United States)

    Sundvik, Maria; Panula, Pertti

    2012-12-01

    Histamine is an essential factor in the ascending arousal system (AAS) during motivated behaviors. Histamine and hypocretin/orexin (hcrt) are proposed to be responsible for different aspects of arousal and wakefulness, histamine mainly for cognitive and motivated behaviors. In this study we visualized the entire histaminergic neuron population in adult male and female zebrafish brain and quantified the histaminergic neuron numbers. There were 40-45 histaminergic neurons in both male and female zebrafish brain. Further, we identified cotransmitters of histaminergic neurons in the ventrocaudal hypothalamus, i.e., around the posterior recess (PR) in adult zebrafish. Galanin, γ-aminobutyric acid (GABA), and thyrotropin-releasing hormone (TRH) were colocalized with histamine in some but not all neurons, a result that was verified by intracerebroventricular injections of colchicine into adult zebrafish. Fibers immunoreactive (ir) for galanin, GABA, TRH, or methionine-enkephalin (mENK) were dense in the ventrocaudal hypothalamus around the histaminergic neurons. In histamine-ir fibers TRH and galanin immunoreactivities were also detected in the ventral telencephalon. All these neurotransmitters are involved in maintaining the equilibrium of the sleep-wake state. Our results are in accordance with results from rats, further supporting the use of zebrafish as a tool to study molecular mechanisms underlying complex behaviors.

  9. Changes in response properties of nociceptive dorsal horn neurons in a murine model of cancer pain

    Institute of Scientific and Technical Information of China (English)

    Donald A. Simone; Sergey G. Khasabov; Darryl T. Hamamoto

    2008-01-01

    Pain associated with cancer that metastasizes to bone is often severe and debilitating. A better understanding of the neural mechanisms that mediate cancer pain is needed for the development of more effective treatments. In this study, we used an established model of cancer pain to characterize changes in response properties of dorsal horn neurons. Fibrosarcoma cells were implanted into and around the calcaneus bone in mice and extracellular electrophysiological recordings were made from wide dynamic range (WDR) and high threshold (HT) dorsal horn neurons. Responses of WDR and HT neurons evoked by mechanical, heat, and cold stimuli applied to the plantar surface of the hind paw were compared between tumor bearing mice and control mice. Mice exhibited hyperalgesia to mechanical and heat stimuli applied to their tumor-bearing hind paw. WDR neurons in tumor-beating mice exhibited an increase in spontaneous activity, and enhanced responses to mechanical, heat, and cold stimuli as compared to controls. Our findings show that sensitization of WDR neurons, but not HT neurons, contributes to tumor-evoked hyperalgesia.

  10. Temporal profile of neuronal damage in a model of transient forebrain ischemia.

    Science.gov (United States)

    Pulsinelli, W A; Brierley, J B; Plum, F

    1982-05-01

    This study examined the temporal profile of ischemic neuronal damage following transient bilateral forebrain ischemia in the rat model of four-vessel occlusion. Wistar rats were subjected to transient but severe forebrain ischemia by permanently occluding the vertebral arteries and 24 hours later temporarily occluding the common carotid arteries for 10, 20, or 30 minutes. Carotid artery blood flow was restored and the rats were killed by perfusion-fixation after 3, 6, 24, and 72 hours. Rats with postischemic convulsions were discarded. Ischemic neuronal damage was graded in accordance with conventional neuropathological criteria. Ten minutes of four-vessel occlusion produced scattered ischemic cell change in the cerebral hemispheres of most rats. The time to onset of visible neuronal damage varied among brain regions and in some regions progressively worsened with time. After 30 minutes of ischemia, small to medium-sized striatal neurons were damaged early while the initiation of visible damage to hippocampal neurons in the h1 zone was delayed for 3 to 6 hours. The number of damaged neurons in neocortex (layer 3, layers 5 and 6, or both) and hippocampus (h1, h3-5, paramedian zone) increased significantly (p less than 0.01) between 24 and 72 hours. The unique delay in onset of ischemic cell change and the protracted increase in its incidence between 24 and 72 hours could reflect either delayed appearance of ischemic change in previously killed neurons or a delayed insult that continued to jeopardize compromised but otherwise viable neurons during the postischemic period.

  11. Estrous Cycle Induces Peripheral Sensitization in Trigeminal Ganglion Neurons: An Animal Model of Menstrual Migraine.

    Science.gov (United States)

    Saleeon, Wachirapong; Jansri, Ukkrit; Srikiatkhachorn, Anan; Bongsebandhu-phubhakdi, Saknan

    2016-02-01

    Many women experience menstrual migraines that develop into recurrent migraine attacks during menstruation. In the human menstrual cycle, the estrogen level fluctuates according to changes in the follicular and luteal phases. The rat estrous cycle is used as an animal model to study the effects of estrogen fluctuation. To investigate whether the estrous cycle is involved in migraine development by comparing the neuronal excitability of trigeminal ganglion (TG) neurons in each stage of the estrous cycle. Female rats were divided into four experimental groups based on examinations of the cytologies of vaginal smears, and serum analyses of estrogen levels following each stage of the estrous cycle. The rats in each stage of the estrous cycle were anesthetized and their trigeminal ganglia were removed The collections of trigeminal ganglia were cultured for two to three hours, after which whole-cell patch clamp experiments were recorded to estimate the electrophysiological properties of the TG neurons. There were many vaginal epithelial cells and high estrogen levels in the proestrus and estrus stages of the estrous cycle. Electrophysiological studies revealed that the TG neurons in the proestrus and estrus stages exhibited significantly lower thresholds of stimulation, and significant increase in total spikes compared to the TG neurons that were collected in the diestrus stage. Our results revealed that high estrogen levels in the proestrus and estrus stages altered the thresholds, rheobases, and total spikes of the TG neurons. High estrogen levels in the estrous cycle induced an increase in neuronal excitability and the peripheral sensitization of TG neurons. These findings may provide an explanation for the correlation of estrogen fluctuations during the menstrual cycle with the pathogenesis of menstrual migraines.

  12. C. elegans as a model system for Parkinson disease

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Parkinson disease( PD) is characterized by the selective loss of dopaminergic neurons in the substantia nigra.Although investigation in mammalian animal models of PD has enhanced our understanding of PD, the complexity of the mammalian nervous system and our inability to visualize DA neurons in vivo restricts the advances in elucidating the molecular mechanisms of PD. Conservation between C. elegans and mammals in genomic, biosynthetic and metabolic pathways as well as the advantages of observing DA neurons morphology in vivo and the ease of transgenic and genetic manipulation make C. elegans an excellent model organism for PD.

  13. How modeling can reconcile apparently discrepant experimental results: the case of pacemaking in dopaminergic neurons.

    Directory of Open Access Journals (Sweden)

    Guillaume Drion

    2011-05-01

    Full Text Available Midbrain dopaminergic neurons are endowed with endogenous slow pacemaking properties. In recent years, many different groups have studied the basis for this phenomenon, often with conflicting conclusions. In particular, the role of a slowly-inactivating L-type calcium channel in the depolarizing phase between spikes is controversial, and the analysis of slow oscillatory potential (SOP recordings during the blockade of sodium channels has led to conflicting conclusions. Based on a minimal model of a dopaminergic neuron, our analysis suggests that the same experimental protocol may lead to drastically different observations in almost identical neurons. For example, complete L-type calcium channel blockade eliminates spontaneous firing or has almost no effect in two neurons differing by less than 1% in their maximal sodium conductance. The same prediction can be reproduced in a state of the art detailed model of a dopaminergic neuron. Some of these predictions are confirmed experimentally using single-cell recordings in brain slices. Our minimal model exhibits SOPs when sodium channels are blocked, these SOPs being uncorrelated with the spiking activity, as has been shown experimentally. We also show that block of a specific conductance (in this case, the SK conductance can have a different effect on these two oscillatory behaviors (pacemaking and SOPs, despite the fact that they have the same initiating mechanism. These results highlight the fact that computational approaches, besides their well known confirmatory and predictive interests in neurophysiology, may also be useful to resolve apparent discrepancies between experimental results.

  14. Computational connectionism within neurons: A model of cytoskeletal automata subserving neural networks

    Science.gov (United States)

    Rasmussen, Steen; Karampurwala, Hasnain; Vaidyanath, Rajesh; Jensen, Klaus S.; Hameroff, Stuart

    1990-06-01

    “Neural network” models of brain function assume neurons and their synaptic connections to be the fundamental units of information processing, somewhat like switches within computers. However, neurons and synapses are extremely complex and resemble entire computers rather than switches. The interiors of the neurons (and other eucaryotic cells) are now known to contain highly ordered parallel networks of filamentous protein polymers collectively termed the cytoskeleton. Originally assumed to provide merely structural “bone-like” support, cytoskeletal structures such as microtubules are now recognized to organize cell interiors dynamically. The cytoskeleton is the internal communication network for the eucaryotic cell, both by means of simple transport and by means of coordinating extremely complicated events like cell division, growth and differentiation. The cytoskeleton may therefore be viewed as the cell's “nervous system”. Consequently the neuronal cytoskeleton may be involved in molecular level information processing which subserves higher, collective neuronal functions ultimately relating to cognition. Numerous models of information processing within the cytoskeleton (in particular, microtubules) have been proposed. We have utilized cellular automata as a means to model and demonstrate the potential for information processing in cytoskeletal microtubules. In this paper, we extend previous work and simulate associative learning in a cytoskeletal network as well as assembly and disassembly of microtubules. We also discuss possible relevance and implications of cytoskeletal information processing to cognition.

  15. Automated reconstruction of neuronal morphology based on local geometrical and global structural models.

    Science.gov (United States)

    Zhao, Ting; Xie, Jun; Amat, Fernando; Clack, Nathan; Ahammad, Parvez; Peng, Hanchuan; Long, Fuhui; Myers, Eugene

    2011-09-01

    Digital reconstruction of neurons from microscope images is an important and challenging problem in neuroscience. In this paper, we propose a model-based method to tackle this problem. We first formulate a model structure, then develop an algorithm for computing it by carefully taking into account morphological characteristics of neurons, as well as the image properties under typical imaging protocols. The method has been tested on the data sets used in the DIADEM competition and produced promising results for four out of the five data sets.

  16. A novel subset of enteric neurons revealed by ptf1a:GFP in the developing zebrafish enteric nervous system.

    Science.gov (United States)

    Uribe, Rosa A; Gu, Tiffany; Bronner, Marianne E

    2016-03-01

    The enteric nervous system, the largest division of the peripheral nervous system, is derived from vagal neural crest cells that invade and populate the entire length of the gut to form diverse neuronal subtypes. Here, we identify a novel population of neurons within the enteric nervous system of zebrafish larvae that express the transgenic marker ptf1a:GFP within the midgut. Genetic lineage analysis reveals that enteric ptf1a:GFP(+) cells are derived from the neural crest and that most ptf1a:GFP(+) neurons express the neurotransmitter 5HT, demonstrating that they are serotonergic. This transgenic line, Tg(ptf1a:GFP), provides a novel neuronal marker for a subpopulation of neurons within the enteric nervous system, and highlights the possibility that Ptf1a may act as an important transcription factor for enteric neuron development.

  17. Emulating the Visual Receptive Field Properties of MST Neurons with a Template Model of Heading Estimation

    Science.gov (United States)

    Perrone, John A.; Stone, Leland S.

    1997-01-01

    We have previously proposed a computational neural-network model by which the complex patterns of retinal image motion generated during locomotion (optic flow) can be processed by specialized detectors acting as templates for specific instances of self-motion. The detectors in this template model respond to global optic flow by sampling image motion over a large portion of the visual field through networks of local motion sensors with properties similar to neurons found in the middle temporal (MT) area of primate extrastriate visual cortex. The model detectors were designed to extract self-translation (heading), self-rotation, as well as the scene layout (relative distances) ahead of a moving observer, and are arranged in cortical-like heading maps to perform this function. Heading estimation from optic flow has been postulated by some to be implemented within the medial superior temporal (MST) area. Others have questioned whether MST neurons can fulfill this role because some of their receptive-field properties appear inconsistent with a role in heading estimation. To resolve this issue, we systematically compared MST single-unit responses with the outputs of model detectors under matched stimulus conditions. We found that the basic physiological properties of MST neurons can be explained by the template model. We conclude that MST neurons are well suited to support heading estimation and that the template model provides an explicit set of testable hypotheses which can guide future exploration of MST and adjacent areas within the primate superior temporal sulcus.

  18. Modulation of excitatory neurotransmission by neuronal/glial signalling molecules: interplay between purinergic and glutamatergic systems.

    Science.gov (United States)

    Köles, László; Kató, Erzsébet; Hanuska, Adrienn; Zádori, Zoltán S; Al-Khrasani, Mahmoud; Zelles, Tibor; Rubini, Patrizia; Illes, Peter

    2016-03-01

    Glutamate is the main excitatory neurotransmitter of the central nervous system (CNS), released both from neurons and glial cells. Acting via ionotropic (NMDA, AMPA, kainate) and metabotropic glutamate receptors, it is critically involved in essential regulatory functions. Disturbances of glutamatergic neurotransmission can be detected in cognitive and neurodegenerative disorders. This paper summarizes the present knowledge on the modulation of glutamate-mediated responses in the CNS. Emphasis will be put on NMDA receptor channels, which are essential executive and integrative elements of the glutamatergic system. This receptor is crucial for proper functioning of neuronal circuits; its hypofunction or overactivation can result in neuronal disturbances and neurotoxicity. Somewhat surprisingly, NMDA receptors are not widely targeted by pharmacotherapy in clinics; their robust activation or inhibition seems to be desirable only in exceptional cases. However, their fine-tuning might provide a promising manipulation to optimize the activity of the glutamatergic system and to restore proper CNS function. This orchestration utilizes several neuromodulators. Besides the classical ones such as dopamine, novel candidates emerged in the last two decades. The purinergic system is a promising possibility to optimize the activity of the glutamatergic system. It exerts not only direct and indirect influences on NMDA receptors but, by modulating glutamatergic transmission, also plays an important role in glia-neuron communication. These purinergic functions will be illustrated mostly by depicting the modulatory role of the purinergic system on glutamatergic transmission in the prefrontal cortex, a CNS area important for attention, memory and learning.

  19. Bidirectional coupling between astrocytes and neurons mediates learning and dynamic coordination in the brain: a multiple modeling approach.

    Directory of Open Access Journals (Sweden)

    John J Wade

    Full Text Available In recent years research suggests that astrocyte networks, in addition to nutrient and waste processing functions, regulate both structural and synaptic plasticity. To understand the biological mechanisms that underpin such plasticity requires the development of cell level models that capture the mutual interaction between astrocytes and neurons. This paper presents a detailed model of bidirectional signaling between astrocytes and neurons (the astrocyte-neuron model or AN model which yields new insights into the computational role of astrocyte-neuronal coupling. From a set of modeling studies we demonstrate two significant findings. Firstly, that spatial signaling via astrocytes can relay a "learning signal" to remote synaptic sites. Results show that slow inward currents cause synchronized postsynaptic activity in remote neurons and subsequently allow Spike-Timing-Dependent Plasticity based learning to occur at the associated synapses. Secondly, that bidirectional communication between neurons and astrocytes underpins dynamic coordination between neuron clusters. Although our composite AN model is presently applied to simplified neural structures and limited to coordination between localized neurons, the principle (which embodies structural, functional and dynamic complexity, and the modeling strategy may be extended to coordination among remote neuron clusters.

  20. The neuronal ceroid lipofuscinosis Cln8 gene expression is developmentally regulated in mouse brain and up-regulated in the hippocampal kindling model of epilepsy

    Directory of Open Access Journals (Sweden)

    Kuronen Mervi

    2005-04-01

    Full Text Available Abstract Background The neuronal ceroid lipofuscinoses (NCLs are a group of inherited neurodegenerative disorders characterized by accumulation of autofluorescent material in many tissues, especially in neurons. Mutations in the CLN8 gene, encoding an endoplasmic reticulum (ER transmembrane protein of unknown function, underlie NCL phenotypes in humans and mice. The human phenotype is characterized by epilepsy, progressive psychomotor deterioration and visual loss, while motor neuron degeneration (mnd mice with a Cln8 mutation show progressive motor neuron dysfunction and retinal degeneration. Results We investigated spatial and temporal expression of Cln8 messenger ribonucleic acid (mRNA using in situ hybridization, reverse transcriptase polymerase chain reaction (RT-PCR and northern blotting. Cln8 is ubiquitously expressed at low levels in embryonic and adult tissues. In prenatal embryos Cln8 is most prominently expressed in the developing gastrointestinal tract, dorsal root ganglia (DRG and brain. In postnatal brain the highest expression is in the cortex and hippocampus. Expression of Cln8 mRNA in the central nervous system (CNS was also analyzed in the hippocampal electrical kindling model of epilepsy, in which Cln8 expression was rapidly up-regulated in hippocampal pyramidal and granular neurons. Conclusion Expression of Cln8 in the developing and mature brain suggests roles for Cln8 in maturation, differentiation and supporting the survival of different neuronal populations. The relevance of Cln8 up-regulation in hippocampal neurons of kindled mice should be further explored.

  1. A High Density Electrophysiological Data Analysis System for a Peripheral Nerve Interface Communicating with Individual Neurons in the Brain

    Science.gov (United States)

    2016-11-14

    of-the-art instrumentation to communicate with individual neurons in the brain and the peripheral nervous system. The major theme of the research is...Nerve Interface Communicating with Individual Neurons in the Brain The views, opinions and/or findings contained in this report are those of the author...Communicating with Individual Neurons in the Brain Report Title The high density electrophysiological data acquisition system obtained through this

  2. Study of apoptosis pattern of dopaminergic neurons and neuroprotective effect of nicotine in MPTP mouse model

    Institute of Scientific and Technical Information of China (English)

    Dan Hu; Wei Cao; Shenggang Sun

    2007-01-01

    Objective:To investigate the apoptosis of dopaminergic neurons and the protective effect of nicotine in 1-methyl-4-phenyl-1, 2,3,6-tetrahydropyridine (MPTP)-induced mouse model of Parkinson's disease. Methods :The mouse model of Parkinson's disease were formed by MPTP (30 mg/kg/d×7, i.p.); and the loss and apoptosis of dopaminergic neurons was observed by Tyrosine Hydroxylase (TH) and TUNEL stains. In "Nicotime plus MPTP" group, mice were pretreated with nicotine before MPTP injection. The putative protective effect of nicotine was analyzed. Results:The number of TH-positive cells decreased during MPTP treatment. Apoptotic neurons began to appear after three injections of MPTP and peaked on the 8th day.In the MPTP-intoxicated mice treated with nicotine, the loss of TH-positive cells was significantly less than that of MPTP-treated group (30 mg/kg/d×7)(P < 0.05). Conclusion:The chronic treatment of MPTP can induce the apoptosis of dopaminergic neurons in substantia nigra, and nicotine might have a neuroprotecitve effect on dopaminergic neurons against MPTP toxicity.

  3. Induced Pluripotent Stem Cell Models of Progranulin-Deficient Frontotemporal Dementia Uncover Specific Reversible Neuronal Defects

    Directory of Open Access Journals (Sweden)

    Sandra Almeida

    2012-10-01

    Full Text Available The pathogenic mechanisms of frontotemporal dementia (FTD remain poorly understood. Here we generated multiple induced pluripotent stem cell lines from a control subject, a patient with sporadic FTD, and an FTD patient with a novel heterozygous GRN mutation (progranulin [PGRN] S116X. In neurons and microglia differentiated from PGRN S116X induced pluripotent stem cells, the levels of intracellular and secreted PGRN were reduced, establishing patient-specific cellular models of PGRN haploinsufficiency. Through a systematic screen of inducers of cellular stress, we found that PGRN S116X neurons, but not sporadic FTD neurons, exhibited increased sensitivity to staurosporine and other kinase inhibitors. Moreover, the serine/threonine kinase S6K2, a component of the phosphatidylinositol 3-kinase and mitogen-activated protein kinase pathways, was specifically downregulated in PGRN S116X neurons. Both increased sensitivity to kinase inhibitors and reduced S6K2 were rescued by PGRN expression. Our findings identify cell-autonomous, reversible defects in patient neurons with PGRN deficiency, and provide a compelling model for studying PGRN-dependent pathogenic mechanisms and testing potential therapies.

  4. Synaptic potentiation onto habenula neurons in the learned helplessness model of depression

    Energy Technology Data Exchange (ETDEWEB)

    Li, B.; Schulz, D.; Li, B; Piriz, J.; Mirrione, M.; Chung, C.H.; Proulx, C.D.; Schulz, D.; Henn, F.; Malinow, R.

    2011-02-24

    The cellular basis of depressive disorders is poorly understood. Recent studies in monkeys indicate that neurons in the lateral habenula (LHb), a nucleus that mediates communication between forebrain and midbrain structures, can increase their activity when an animal fails to receive an expected positive reward or receives a stimulus that predicts aversive conditions (that is, disappointment or anticipation of a negative outcome). LHb neurons project to, and modulate, dopamine-rich regions, such as the ventral tegmental area (VTA), that control reward-seeking behaviour and participate in depressive disorders. Here we show that in two learned helplessness models of depression, excitatory synapses onto LHb neurons projecting to the VTA are potentiated. Synaptic potentiation correlates with an animal's helplessness behaviour and is due to an enhanced presynaptic release probability. Depleting transmitter release by repeated electrical stimulation of LHb afferents, using a protocol that can be effective for patients who are depressed, markedly suppresses synaptic drive onto VTA-projecting LHb neurons in brain slices and can significantly reduce learned helplessness behaviour in rats. Our results indicate that increased presynaptic action onto LHb neurons contributes to the rodent learned helplessness model of depression.

  5. Linked Gauss-Diffusion processes for modeling a finite-size neuronal network.

    Science.gov (United States)

    Carfora, M F; Pirozzi, E

    2017-08-02

    A Leaky Integrate-and-Fire (LIF) model with stochastic current-based linkages is considered to describe the firing activity of neurons interacting in a (2×2)-size feed-forward network. In the subthreshold regime and under the assumption that no more than one spike is exchanged between coupled neurons, the stochastic evolution of the neuronal membrane voltage is subject to random jumps due to interactions in the network. Linked Gauss-Diffusion processes are proposed to describe this dynamics and to provide estimates of the firing probability density of each neuron. To this end, an iterated integral equation-based approach is applied to evaluate numerically the first passage time density of such processes through the firing threshold. Asymptotic approximations of the firing densities of surrounding neurons are used to obtain closed-form expressions for the mean of the involved processes and to simplify the numerical procedure. An extension of the model to an (N×N)-size network is also given. Histograms of firing times obtained by simulations of the LIF dynamics and numerical firings estimates are compared. Copyright © 2017 Elsevier B.V. All rights reserved.

  6. Modeling non-syndromic autism and the impact of TRPC6 disruption in human neurons.

    Science.gov (United States)

    Griesi-Oliveira, K; Acab, A; Gupta, A R; Sunaga, D Y; Chailangkarn, T; Nicol, X; Nunez, Y; Walker, M F; Murdoch, J D; Sanders, S J; Fernandez, T V; Ji, W; Lifton, R P; Vadasz, E; Dietrich, A; Pradhan, D; Song, H; Ming, G-L; Gu, X; Haddad, G; Marchetto, M C N; Spitzer, N; Passos-Bueno, M R; State, M W; Muotri, A R

    2015-11-01

    An increasing number of genetic variants have been implicated in autism spectrum disorders (ASDs), and the functional study of such variants will be critical for the elucidation of autism pathophysiology. Here, we report a de novo balanced translocation disruption of TRPC6, a cation channel, in a non-syndromic autistic individual. Using multiple models, such as dental pulp cells, induced pluripotent stem cell (iPSC)-derived neuronal cells and mouse models, we demonstrate that TRPC6 reduction or haploinsufficiency leads to altered neuronal development, morphology and function. The observed neuronal phenotypes could then be rescued by TRPC6 complementation and by treatment with insulin-like growth factor-1 or hyperforin, a TRPC6-specific agonist, suggesting that ASD individuals with alterations in this pathway may benefit from these drugs. We also demonstrate that methyl CpG binding protein-2 (MeCP2) levels affect TRPC6 expression. Mutations in MeCP2 cause Rett syndrome, revealing common pathways among ASDs. Genetic sequencing of TRPC6 in 1041 ASD individuals and 2872 controls revealed significantly more nonsynonymous mutations in the ASD population, and identified loss-of-function mutations with incomplete penetrance in two patients. Taken together, these findings suggest that TRPC6 is a novel predisposing gene for ASD that may act in a multiple-hit model. This is the first study to use iPSC-derived human neurons to model non-syndromic ASD and illustrate the potential of modeling genetically complex sporadic diseases using such cells.

  7. Modeling non-syndromic autism and the impact of TRPC6 disruption in human neurons

    Science.gov (United States)

    Griesi-Oliveira, Karina; Acab, Allan; Gupta, Abha R.; Sunaga, Daniele Yumi; Chailangkarn, Thanathom; Nicol, Xavier; Nunez, Yanelli; Walker, Michael F.; Murdoch, John D.; Sanders, Stephan J.; Fernandez, Thomas V.; Ji, Weizhen; Lifton, Richard P.; Vadasz, Estevão; Dietrich, Alexander; Pradhan, Dennis; Song, Hongjun; Ming, Guo-li; Guoe, Xiang; Haddad, Gabriel; Marchetto, Maria C. N.; Spitzer, Nicholas; Passos-Bueno, Maria Rita; State, Matthew W.; Muotri, Alysson R.

    2014-01-01

    An increasing number of genetic variants have been implicated in autism spectrum disorders (ASD), and the functional study of such variants will be critical for the elucidation of autism pathophysiology. Here, we report a de novo balanced translocation disruption of TRPC6, a cation channel, in a non-syndromic autistic individual. Using multiple models, such as dental pulp cells, iPSC-derived neuronal cells and mouse models, we demonstrate that TRPC6 reduction or haploinsufficiency leads to altered neuronal development, morphology, and function. The observed neuronal phenotypes could then be rescued by TRPC6 complementation and by treatment with IGF1 or hyperforin, a TRPC6-specific agonist, suggesting that ASD individuals with alterations in this pathway might benefit from these drugs. We also demonstrate that MeCP2 levels affect TRPC6 expression. Mutations in MeCP2 cause Rett syndrome, revealing common pathways among ASDs. Genetic sequencing of TRPC6 in 1041 ASD individuals and 2872 controls revealed significantly more nonsynonymous mutations in the ASD population, and identified loss-of-function mutations with incomplete penetrance in two patients. Taken together, these findings suggest that TRPC6 is a novel predisposing gene for ASD that may act in a multiple-hit model. This is the first study to use iPSC-derived human neurons to model non-syndromic ASD and illustrate the potential of modeling genetically complex sporadic diseases using such cells. PMID:25385366

  8. Self-sustaining non-repetitive activity in a large scale neuronal-level model of the hippocampal circuit.

    Science.gov (United States)

    Scorcioni, Ruggero; Hamilton, David J; Ascoli, Giorgio A

    2008-10-01

    The mammalian hippocampus is involved in spatial representation and memory storage and retrieval, and much research is ongoing to elucidate the cellular and system-level mechanisms underlying these cognitive functions. Modeling may be useful to link network-level activity patterns to the relevant features of hippocampal anatomy and electrophysiology. Investigating the effects of circuit connectivity requires simulations of a number of neurons close to real scale. To this end, we construct a model of the hippocampus with 16 distinct neuronal classes (including both local and projection cells) and 200,000 individual neurons. The number of neurons in each class and their interconnectivity are drawn from rat anatomy. Here we analyze the emergent network activity and how it is affected by reducing either the size or the connectivity diversity of the model. When the model is run with a simple variation of the McCulloch-Pitts formalism, self-sustaining non-repetitive activity patterns consistently emerge. Specific firing threshold values are narrowly constrained for each cell class upon multiple runs with different stochastic wiring and initial conditions, yet these values do not directly affect network stability. Analysis of the model at different network sizes demonstrates that a scale reduction of one order of magnitude drastically alters network dynamics, including the variability of the output range, the distribution of firing frequencies, and the duration of self-sustained activity. Moreover, comparing the model to a control condition with an equivalent number of (excitatory/inhibitory balanced) synapses, but removing all class-specific information (i.e. collapsing the network to homogeneous random connectivity) has surprisingly similar effects to downsizing the total number of neurons. The reduced-scale model is also compared directly with integrate-and-fire simulations, which capture considerably more physiological detail at the single-cell level, but still fail

  9. Studies on functional roles of the histaminergic neuron system by using pharmacological agents, knockout mice and positron emission tomography

    Energy Technology Data Exchange (ETDEWEB)

    Watanabe, Takehiko; Yanai, Kazuhiko [Tohoku Univ., Sendai (Japan). Graduate School of Medicine

    2001-12-01

    Since one of us, Takehiko Watanabe (TW), elucidated the location and distribution of the histaminergic neuron system in the brain with antibody raised against L-histidine decarboxylase (a histamine-forming enzyme, HDC) as a marker in 1984 and came to Tohoku University School of Medicine in Sendai, we have been collaborating on the functions of this neuron system by using pharmacological agents, knockout mice of the histamine-related genes, and, in some cases, positron emission tomography (PET). Many of our graduate students and colleagues have been actively involved in histamine research since 1985. Our extensive studies have clarified some of the functions of histamine neurons using methods from molecular techniques to non-invasive human PET imaging. Histamine neurons are involved in many brain functions, such as spontaneous locomotion, arousal in wake-sleep cycle, appetite control, seizures, learning and memory, aggressive behavior and emotion. Particularly, the histaminergic neuron system is one of the most important neuron systems to maintain and stimulate wakefulness. Histamine also functions as a biprotection system against various noxious and unfavorable stimuli (for examples, convulsion, nociception, drug sensitization, ischemic lesions, and stress). Although activators of histamine neurons have not been clinically available until now, we would like to point out that the activation of the histaminergic neuron system is important to maintain mental health. Here, we summarize the newly-discovered functions of histamine neurons mainly on the basis of results from our research groups. (author)

  10. Intervention of Peiyuan Huayu Decoction on the neuron damage in model rats with acute subdural hematoma

    Directory of Open Access Journals (Sweden)

    Xiao-Xuan Fan

    2017-07-01

    Full Text Available Objective: To study the intervention effect of Peiyuan Huayu Decoction on the neuron damage in model rats with acute subdural hematoma (ASDH. Methods: 160 SD rats were randomly divided into four groups, and the ASDH model rats were made by stereotactic autoblood injection, and sham operation group received craniotomy without blood injection. Sham operation group and model group were normally bred after model establishment, and 6 h after model establishment, the treatment group received intragastric administration of Peiyuan Huayu Decoction, and control group received intragastric administration of Piracetam Tablets, 1 time a day. On the 1d, 3d, 5d and 7d after model establishment, the general conditions of rats (activity, food intake and mental state were observed, blood was collected via auricula dextra, ELISA method was used to determine peripheral plasma NSE and S100毬 protein contents, routine HE staining was conducted after perfusion fixation, the neurons in blood injection side of brain tissue were counted, and the neuron damage was observed. Results: 26 rats were dead in the experiment. The general conditions of sham operation group were significantly better than those of other groups, treatment group was significantly better than model group and control group on the 5d group (P0.05; neuron count of sham operation group was basically stable, treatment group was not different from model group and control group on the 1d (P>0.05, treatment group was better than model group (P0.05 on the 3d, and treatment group was better than model group and control group on the 5d and 7d (P0.05, S100毬 protein and NSE contents decreased significantly on the 3d, and treatment group was significantly different from model group and control group (P<0.05, S100毬 protein and NSE contents increased on the 5d and 7d, the increase in treatment group was slower than that in model group and control group, and there was significant difference (P<0.05. Conclusion

  11. Ascorbate prevents cell death from prolonged exposure to glutamate in an in vitro model of human dopaminergic neurons.

    Science.gov (United States)

    Ballaz, Santiago; Morales, Ingrid; Rodríguez, Manuel; Obeso, José A

    2013-12-01

    Ascorbate (vitamin C) is a nonenzymatic antioxidant highly concentrated in the brain. In addition to mediating redox balance, ascorbate is linked to glutamate neurotransmission in the striatum, where it renders neuroprotection against excessive glutamate stimulation. Oxidative stress and glutamatergic overactivity are key biochemical features accompanying the loss of dopaminergic neurons in the substantia nigra that characterizes Parkinson's disease (PD). At present, it is not clear whether antiglutamate agents and ascorbate might be neuroprotective agents for PD. Thus, we tested whether ascorbate can prevent cell death from prolonged exposure to glutamate using dopaminergic neurons of human origin. To this purpose, dopamine-like neurons were obtained by differentiation of SH-SY5Y cells and then cultured for 4 days without antioxidant (antiaging) protection to evaluate glutamate toxicity and ascorbate protection as a model system of potential factors contributing to dopaminergic neuron death in PD. Glutamate dose dependently induced toxicity in dopaminergic cells largely by the stimulation of AMPA and metabotropic receptors and to a lesser extent by N-methyl-D-aspartate and kainate receptors. At relatively physiological levels of extracellular concentration, ascorbate protected cells against glutamate excitotoxicity. This neuroprotection apparently relies on the inhibition of oxidative stress, because ascorbate prevented the pro-oxidant action of the scavenging molecule quercetin, which occurred over the course of prolonged exposure, as is also seen with glutamate. Our findings show the relevance of ascorbate as a neuroprotective agent and emphasize an often underappreciated role of oxidative stress in glutamate excitotoxicity. Occurrence of a glutamate-ascorbate link in dopaminergic neurons may explain previous contradictions regarding their putative role in PD.

  12. Early deficits in glycolysis are specific to striatal neurons from a rat model of huntington disease.

    Directory of Open Access Journals (Sweden)

    Caroline Gouarné

    Full Text Available In Huntington disease (HD, there is increasing evidence for a link between mutant huntingtin expression, mitochondrial dysfunction, energetic deficits and neurodegeneration but the precise nature, causes and order of these events remain to be determined. In this work, our objective was to evaluate mitochondrial respiratory function in intact, non-permeabilized, neurons derived from a transgenic rat model for HD compared to their wild type littermates by measuring oxygen consumption rates and extracellular acidification rates. Although HD striatal neurons had similar respiratory capacity as those from their wild-type littermates when they were incubated in rich medium containing a supra-physiological glucose concentration (25 mM, pyruvate and amino acids, respiratory defects emerged when cells were incubated in media containing only a physiological cerebral level of glucose (2.5 mM. According to the concept that glucose is not the sole substrate used by the brain for neuronal energy production, we provide evidence that primary neurons can use lactate as well as pyruvate to fuel the mitochondrial respiratory chain. In contrast to glucose, we found no major deficits in HD striatal neurons' capacity to use pyruvate as a respiratory substrate compared to wild type littermates. Additionally, we used extracellular acidification rates to confirm a reduction in anaerobic glycolysis in the same cells. Interestingly, the metabolic disturbances observed in striatal neurons were not seen in primary cortical neurons, a brain region affected in later stages of HD. In conclusion, our results argue for a dysfunction in glycolysis, which might precede any defects in the respiratory chain itself, and these are early events in the onset of disease.

  13. A Human Mirror Neuron System for Language: Perspectives from Signed Languages of the Deaf

    Science.gov (United States)

    Knapp, Heather Patterson; Corina, David P.

    2010-01-01

    Language is proposed to have developed atop the human analog of the macaque mirror neuron system for action perception and production [Arbib M.A. 2005. From monkey-like action recognition to human language: An evolutionary framework for neurolinguistics (with commentaries and author's response). "Behavioral and Brain Sciences, 28", 105-167; Arbib…

  14. The Mirror Neuron System and Observational Learning: Implications for the Effectiveness of Dynamic Visualizations

    Science.gov (United States)

    van Gog, Tamara; Paas, Fred; Marcus, Nadine; Ayres, Paul; Sweller, John

    2009-01-01

    Learning by observing and imitating others has long been recognized as constituting a powerful learning strategy for humans. Recent findings from neuroscience research, more specifically on the mirror neuron system, begin to provide insight into the neural bases of learning by observation and imitation. These findings are discussed here, along…

  15. A Human Mirror Neuron System for Language: Perspectives from Signed Languages of the Deaf

    Science.gov (United States)

    Knapp, Heather Patterson; Corina, David P.

    2010-01-01

    Language is proposed to have developed atop the human analog of the macaque mirror neuron system for action perception and production [Arbib M.A. 2005. From monkey-like action recognition to human language: An evolutionary framework for neurolinguistics (with commentaries and author's response). "Behavioral and Brain Sciences, 28", 105-167; Arbib…

  16. The Mirror Neuron System and Observational Learning: Implications for the Effectiveness of Dynamic Visualizations

    Science.gov (United States)

    van Gog, Tamara; Paas, Fred; Marcus, Nadine; Ayres, Paul; Sweller, John

    2009-01-01

    Learning by observing and imitating others has long been recognized as constituting a powerful learning strategy for humans. Recent findings from neuroscience research, more specifically on the mirror neuron system, begin to provide insight into the neural bases of learning by observation and imitation. These findings are discussed here, along…

  17. Model for the effect of static magnetic fields on isolated neurons

    Science.gov (United States)

    del Moral, A.; Azanza, María J.

    1992-08-01

    A model which explains the effect of static magnetic fields on isolated neurons through Ca 2+ liberation from their binding sites at cell membrane, by a combined effect of lipid membrane molecules cooperative superdiamagnetism and electrostatic repulsion (Coulomb explosion) of Ca 2+ at both sides of the membrane, is developed.

  18. Modeling the Formation Process of Grouping Stimuli Sets through Cortical Columns and Microcircuits to Feature Neurons

    Directory of Open Access Journals (Sweden)

    Frank Klefenz

    2013-01-01

    Full Text Available A computational model of a self-structuring neuronal net is presented in which repetitively applied pattern sets induce the formation of cortical columns and microcircuits which decode distinct patterns after a learning phase. In a case study, it is demonstrated how specific neurons in a feature classifier layer become orientation selective if they receive bar patterns of different slopes from an input layer. The input layer is mapped and intertwined by self-evolving neuronal microcircuits to the feature classifier layer. In this topical overview, several models are discussed which indicate that the net formation converges in its functionality to a mathematical transform which maps the input pattern space to a feature representing output space. The self-learning of the mathematical transform is discussed and its implications are interpreted. Model assumptions are deduced which serve as a guide to apply model derived repetitive stimuli pattern sets to in vitro cultures of neuron ensembles to condition them to learn and execute a mathematical transform.

  19. Hopf Bifurcation and Chaos in a Single Inertial Neuron Model with Time Delay

    OpenAIRE

    Li, Chunguang; Chen, Guanrong; Liao, Xiaofeng; Yu, Juebang

    2004-01-01

    A delayed differential equation modelling a single neuron with inertial term is considered in this paper. Hopf bifurcation is studied by using the normal form theory of retarded functional differential equations. When adopting a nonmonotonic activation function, chaotic behavior is observed. Phase plots, waveform plots, and power spectra are presented to confirm the chaoticity.

  20. Responses of Hodgkin-Huxley Neuronal Systems to Spike-Train Inputs

    Institute of Scientific and Technical Information of China (English)

    CHANG Wen-Li; WANG Sheng-Jun; WANG Ying-Hai

    2007-01-01

    We investigate responses of the Hodgkin-Huxley globally neuronal systems to periodic spike-train inputs. The firing activities of the neuronal networks show different rhythmic patterns for different parameters. These rhythmic patterns can be used to explain cycles of firing in real brain. These activity patterns, average activity and coherence measure are affected by two quantities such as the percentage of excitatory couplings and stimulus intensity, in which the percentage of excitatory couplings is more important than stimulus intensity since the transition phenomenon of average activity comes about.

  1. On the applicability of STDP-based learning mechanisms to spiking neuron network models

    Science.gov (United States)

    Sboev, A.; Vlasov, D.; Serenko, A.; Rybka, R.; Moloshnikov, I.

    2016-11-01

    The ways to creating practically effective method for spiking neuron networks learning, that would be appropriate for implementing in neuromorphic hardware and at the same time based on the biologically plausible plasticity rules, namely, on STDP, are discussed. The influence of the amount of correlation between input and output spike trains on the learnability by different STDP rules is evaluated. A usability of alternative combined learning schemes, involving artificial and spiking neuron models is demonstrated on the iris benchmark task and on the practical task of gender recognition.

  2. Stochastic Phenomena in One-Dimensional Rulkov Model of Neuronal Dynamics

    Directory of Open Access Journals (Sweden)

    Irina Bashkirtseva

    2015-01-01

    transitions in a zone of bistability are considered. It is shown how such random transitions can generate a new neuronal regime of the stochastic bursting and transfer the system from order to chaos. A transient zone of values of noise intensity corresponding to the onset of noise-induced bursting and chaotization is localized by the stochastic sensitivity functions technique.

  3. Motor-Auditory-Visual Integration: The Role of the Human Mirror Neuron System in Communication and Communication Disorders

    Science.gov (United States)

    Le Bel, Ronald M.; Pineda, Jaime A.; Sharma, Anu

    2009-01-01

    The mirror neuron system (MNS) is a trimodal system composed of neuronal populations that respond to motor, visual, and auditory stimulation, such as when an action is performed, observed, heard or read about. In humans, the MNS has been identified using neuroimaging techniques (such as fMRI and mu suppression in the EEG). It reflects an…

  4. Motor-Auditory-Visual Integration: The Role of the Human Mirror Neuron System in Communication and Communication Disorders

    Science.gov (United States)

    Le Bel, Ronald M.; Pineda, Jaime A.; Sharma, Anu

    2009-01-01

    The mirror neuron system (MNS) is a trimodal system composed of neuronal populations that respond to motor, visual, and auditory stimulation, such as when an action is performed, observed, heard or read about. In humans, the MNS has been identified using neuroimaging techniques (such as fMRI and mu suppression in the EEG). It reflects an…

  5. Persistent neuronal Ube3a expression in the suprachiasmatic nucleus of Angelman syndrome model mice.

    Science.gov (United States)

    Jones, Kelly A; Han, Ji Eun; DeBruyne, Jason P; Philpot, Benjamin D

    2016-06-16

    Mutations or deletions of the maternal allele of the UBE3A gene cause Angelman syndrome (AS), a severe neurodevelopmental disorder. The paternal UBE3A/Ube3a allele becomes epigenetically silenced in most neurons during postnatal development in humans and mice; hence, loss of the maternal allele largely eliminates neuronal expression of UBE3A protein. However, recent studies suggest that paternal Ube3a may escape silencing in certain neuron populations, allowing for persistent expression of paternal UBE3A protein. Here we extend evidence in AS model mice (Ube3a(m-/p+)) of paternal UBE3A expression within the suprachiasmatic nucleus (SCN), the master circadian pacemaker. Paternal UBE3A-positive cells in the SCN show partial colocalization with the neuropeptide arginine vasopressin (AVP) and clock proteins (PER2 and BMAL1), supporting that paternal UBE3A expression in the SCN is often of neuronal origin. Paternal UBE3A also partially colocalizes with a marker of neural progenitors, SOX2, implying that relaxed or incomplete imprinting of paternal Ube3a reflects an overall immature molecular phenotype. Our findings highlight the complexity of Ube3a imprinting in the brain and illuminate a subpopulation of SCN neurons as a focal point for future studies aimed at understanding the mechanisms of Ube3a imprinting.

  6. Dopaminergic neurons generated from monkey embryonic stem cells function in a Parkinson primate model.

    Science.gov (United States)

    Takagi, Yasushi; Takahashi, Jun; Saiki, Hidemoto; Morizane, Asuka; Hayashi, Takuya; Kishi, Yo; Fukuda, Hitoshi; Okamoto, Yo; Koyanagi, Masaomi; Ideguchi, Makoto; Hayashi, Hideki; Imazato, Takayuki; Kawasaki, Hiroshi; Suemori, Hirofumi; Omachi, Shigeki; Iida, Hidehiko; Itoh, Nobuyuki; Nakatsuji, Norio; Sasai, Yoshiki; Hashimoto, Nobuo

    2005-01-01

    Parkinson disease (PD) is a neurodegenerative disorder characterized by loss of midbrain dopaminergic (DA) neurons. ES cells are currently the most promising donor cell source for cell-replacement therapy in PD. We previously described a strong neuralizing activity present on the surface of stromal cells, named stromal cell-derived inducing activity (SDIA). In this study, we generated neurospheres composed of neural progenitors from monkey ES cells, which are capable of producing large numbers of DA neurons. We demonstrated that FGF20, preferentially expressed in the substantia nigra, acts synergistically with FGF2 to increase the number of DA neurons in ES cell-derived neurospheres. We also analyzed the effect of transplantation of DA neurons generated from monkey ES cells into 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine-treated (MPTP-treated) monkeys, a primate model for PD. Behavioral studies and functional imaging revealed that the transplanted cells functioned as DA neurons and attenuated MPTP-induced neurological symptoms.

  7. Modelling Railway Interlocking Systems

    DEFF Research Database (Denmark)

    Lindegaard, Morten Peter; Viuf, P.; Haxthausen, Anne Elisabeth

    2000-01-01

    In this report we present a model of interlocking systems, and describe how the model may be validated by simulation. Station topologies are modelled by graphs in which the nodes denote track segments, and the edges denote connectivity for train traÆc. Points and signals are modelled by annotatio...

  8. Excitability of Aβ sensory neurons is altered in an animal model of peripheral neuropathy

    Directory of Open Access Journals (Sweden)

    Zhu Yong

    2012-01-01

    Full Text Available Abstract Background Causes of neuropathic pain following nerve injury remain unclear, limiting the development of mechanism-based therapeutic approaches. Animal models have provided some directions, but little is known about the specific sensory neurons that undergo changes in such a way as to induce and maintain activation of sensory pain pathways. Our previous studies implicated changes in the Aβ, normally non-nociceptive neurons in activating spinal nociceptive neurons in a cuff-induced animal model of neuropathic pain and the present study was directed specifically at determining any change in excitability of these neurons. Thus, the present study aimed at recording intracellularly from Aβ-fiber dorsal root ganglion (DRG neurons and determining excitability of the peripheral receptive field, of the cell body and of the dorsal roots. Methods A peripheral neuropathy was induced in Sprague Dawley rats by inserting two thin polyethylene cuffs around the right sciatic nerve. All animals were confirmed to exhibit tactile hypersensitivity to von Frey filaments three weeks later, before the acute electrophysiological experiments. Under stable intracellular recording conditions neurons were classified functionally on the basis of their response to natural activation of their peripheral receptive field. In addition, conduction velocity of the dorsal roots, configuration of the action potential and rate of adaptation to stimulation were also criteria for classification. Excitability was measured as the threshold to activation of the peripheral receptive field, the response to intracellular injection of depolarizing current into the soma and the response to electrical stimulation of the dorsal roots. Results In control animals mechanical thresholds of all neurons were within normal ranges. Aβ DRG neurons in neuropathic rats demonstrated a mean mechanical threshold to receptive field stimulation that were significantly lower than in control rats, a

  9. Cell output, cell cycle duration and neuronal specification: a model of integrated mechanisms of the neocortical proliferative process

    Science.gov (United States)

    Caviness, V. S. Jr; Goto, T.; Tarui, T.; Takahashi, T.; Bhide, P. G.; Nowakowski, R. S.

    2003-01-01

    The neurons of the neocortex are generated over a 6 day neuronogenetic interval that comprises 11 cell cycles. During these 11 cell cycles, the length of cell cycle increases and the proportion of cells that exits (Q) versus re-enters (P) the cell cycle changes systematically. At the same time, the fate of the neurons produced at each of the 11 cell cycles appears to be specified at least in terms of their laminar destination. As a first step towards determining the causal interrelationships of the proliferative process with the process of laminar specification, we present a two-pronged approach. This consists of (i) a mathematical model that integrates the output of the proliferative process with the laminar fate of the output and predicts the effects of induced changes in Q and P during the neuronogenetic interval on the developing and mature cortex and (ii) an experimental system that allows the manipulation of Q and P in vivo. Here we show that the predictions of the model and the results of the experiments agree. The results indicate that events affecting the output of the proliferative population affect both the number of neurons produced and their specification with regard to their laminar fate.

  10. Changes in Aβ non-nociceptive primary sensory neurons in a rat model of osteoarthritis pain

    Directory of Open Access Journals (Sweden)

    Henry James L

    2010-07-01

    Full Text Available Abstract Background Pain is a major debilitating factor in osteoarthritis (OA, yet few mechanism-based therapies are available. To address the need to understand underlying mechanisms the aim of the present study was to determine changes in sensory neurons in an animal model of OA pain. Results The model displayed typical osteoarthritis pathology characterized by cartilage degeneration in the knee joint and also manifested knee pathophysiology (edema and increased vasculature permeability of the joint and altered nociception of the affected limb (hind paw tenderness and knee articulation-evoked reduction in the tail flick latency. Neurons included in this report innervated regions throughout the entire hind limb. Aβ-fiber low threshold mechanoreceptors exhibited a slowing of the dynamics of action potential (AP genesis, including wider AP duration and slower maximum rising rate, and muscle spindle neurons were the most affected subgroup. Only minor AP configuration changes were observed in either C- or Aδ-fiber nociceptors. Conclusion Thus, at one month after induction of the OA model Aβ-fiber low threshold mechanoreceptors but not C- or Aδ-fiber nociceptors had undergone changes in electrophysiological properties. If these changes reflect a change in functional role of these neurons in primary afferent sensory processing, then Aβ-fiber non-nociceptive primary sensory neurons may be involved in the pathogenesis of OA pain. Further, it is important to point out that the patterns of the changes we observed are consistent with observations in models of peripheral neuropathy but not models of peripheral inflammation.

  11. Neuronal avalanches and learning

    Energy Technology Data Exchange (ETDEWEB)

    Arcangelis, Lucilla de, E-mail: dearcangelis@na.infn.it [Department of Information Engineering and CNISM, Second University of Naples, 81031 Aversa (Italy)

    2011-05-01

    Networks of living neurons represent one of the most fascinating systems of biology. If the physical and chemical mechanisms at the basis of the functioning of a single neuron are quite well understood, the collective behaviour of a system of many neurons is an extremely intriguing subject. Crucial ingredient of this complex behaviour is the plasticity property of the network, namely the capacity to adapt and evolve depending on the level of activity. This plastic ability is believed, nowadays, to be at the basis of learning and memory in real brains. Spontaneous neuronal activity has recently shown features in common to other complex systems. Experimental data have, in fact, shown that electrical information propagates in a cortex slice via an avalanche mode. These avalanches are characterized by a power law distribution for the size and duration, features found in other problems in the context of the physics of complex systems and successful models have been developed to describe their behaviour. In this contribution we discuss a statistical mechanical model for the complex activity in a neuronal network. The model implements the main physiological properties of living neurons and is able to reproduce recent experimental results. Then, we discuss the learning abilities of this neuronal network. Learning occurs via plastic adaptation of synaptic strengths by a non-uniform negative feedback mechanism. The system is able to learn all the tested rules, in particular the exclusive OR (XOR) and a random rule with three inputs. The learning dynamics exhibits universal features as function of the strength of plastic adaptation. Any rule could be learned provided that the plastic adaptation is sufficiently slow.

  12. Glial response in the rat models of functionally distinct cholinergic neuronal denervations.

    Science.gov (United States)

    Bataveljic, Danijela; Petrovic, Jelena; Lazic, Katarina; Saponjic, Jasna; Andjus, Pavle

    2015-02-01

    Alzheimer's disease (AD) involves selective loss of basal forebrain cholinergic neurons, particularly in the nucleus basalis (NB). Similarly, Parkinson's disease (PD) might involve the selective loss of pedunculopontine tegmental nucleus (PPT) cholinergic neurons. Therefore, lesions of these functionally distinct cholinergic centers in rats might serve as models of AD and PD cholinergic neuropathologies. Our previous articles described dissimilar sleep/wake-state disorders in rat models of AD and PD cholinergic neuropathologies. This study further examines astroglial and microglial responses as underlying pathologies in these distinct sleep disorders. Unilateral lesions of the NB or the PPT were induced with rats under ketamine/diazepam anesthesia (50 mg/kg i.p.) by using stereotaxically guided microinfusion of the excitotoxin ibotenic acid (IBO). Twenty-one days after the lesion, loss of cholinergic neurons was quantified by nicotinamide adenine dinucleotide phosphate-diaphorase histochemistry, and the astroglial and microglial responses were quantified by glia fibrillary acidic protein/OX42 immunohistochemistry. This study demonstrates, for the first time, the anatomofunctionally related astroglial response following unilateral excitotoxic PPT cholinergic neuronal lesion. Whereas IBO NB and PPT lesions similarly enhanced local astroglial and microglial responses, astrogliosis in the PPT was followed by a remote astrogliosis within the ipslilateral NB. Conversely, there was no microglial response within the NB after PPT lesions. Our results reveal the rostrorostral PPT-NB astrogliosis after denervation of cholinergic neurons in the PPT. This hierarchically and anatomofunctionally guided PPT-NB astrogliosis emerged following cholinergic neuronal loss greater than 17% throughout the overall rostrocaudal PPT dimension.

  13. Network dynamics in nociceptive pathways assessed by the neuronal avalanche model

    Directory of Open Access Journals (Sweden)

    Wu José

    2012-04-01

    Full Text Available Abstract Background Traditional electroencephalography provides a critical assessment of pain responses. The perception of pain, however, may involve a series of signal transmission pathways in higher cortical function. Recent studies have shown that a mathematical method, the neuronal avalanche model, may be applied to evaluate higher-order network dynamics. The neuronal avalanche is a cascade of neuronal activity, the size distribution of which can be approximated by a power law relationship manifested by the slope of a straight line (i.e., the α value. We investigated whether the neuronal avalanche could be a useful index for nociceptive assessment. Findings Neuronal activity was recorded with a 4 × 8 multichannel electrode array in the primary somatosensory cortex (S1 and anterior cingulate cortex (ACC. Under light anesthesia, peripheral pinch stimulation increased the slope of the α value in both the ACC and S1, whereas brush stimulation increased the α value only in the S1. The increase in α values was blocked in both regions under deep anesthesia. The increase in α values in the ACC induced by peripheral pinch stimulation was blocked by medial thalamic lesion, but the increase in α values in the S1 induced by brush and pinch stimulation was not affected. Conclusions The neuronal avalanche model shows a critical state in the cortical network for noxious-related signal processing. The α value may provide an index of brain network activity that distinguishes the responses to somatic stimuli from the control state. These network dynamics may be valuable for the evaluation of acute nociceptive processes and may be applied to chronic pathological pain conditions.

  14. Autism and the mirror neuron system: insights from learning and teaching.

    Science.gov (United States)

    Vivanti, Giacomo; Rogers, Sally J

    2014-01-01

    Individuals with autism have difficulties in social learning domains which typically involve mirror neuron system (MNS) activation. However, the precise role of the MNS in the development of autism and its relevance to treatment remain unclear. In this paper, we argue that three distinct aspects of social learning are critical for advancing knowledge in this area: (i) the mechanisms that allow for the implicit mapping of and learning from others' behaviour, (ii) the motivation to attend to and model conspecifics and (iii) the flexible and selective use of social learning. These factors are key targets of the Early Start Denver Model, an autism treatment approach which emphasizes social imitation, dyadic engagement, verbal and non-verbal communication and affect sharing. Analysis of the developmental processes and treatment-related changes in these different aspects of social learning in autism can shed light on the nature of the neuropsychological mechanisms underlying social learning and positive treatment outcomes in autism. This knowledge in turn may assist in developing more successful pedagogic approaches to autism spectrum disorder. Thus, intervention research can inform the debate on relations among neuropsychology of social learning, the role of the MNS, and educational practice in autism.

  15. Autism and the mirror neuron system: insights from learning and teaching

    Science.gov (United States)

    Vivanti, Giacomo; Rogers, Sally J.

    2014-01-01

    Individuals with autism have difficulties in social learning domains which typically involve mirror neuron system (MNS) activation. However, the precise role of the MNS in the development of autism and its relevance to treatment remain unclear. In this paper, we argue that three distinct aspects of social learning are critical for advancing knowledge in this area: (i) the mechanisms that allow for the implicit mapping of and learning from others' behaviour, (ii) the motivation to attend to and model conspecifics and (iii) the flexible and selective use of social learning. These factors are key targets of the Early Start Denver Model, an autism treatment approach which emphasizes social imitation, dyadic engagement, verbal and non-verbal communication and affect sharing. Analysis of the developmental processes and treatment-related changes in these different aspects of social learning in autism can shed light on the nature of the neuropsychological mechanisms underlying social learning and positive treatment outcomes in autism. This knowledge in turn may assist in developing more successful pedagogic approaches to autism spectrum disorder. Thus, intervention research can inform the debate on relations among neuropsychology of social learning, the role of the MNS, and educational practice in autism. PMID:24778379

  16. Noise and Synchronization Analysis of the Cold-Receptor Neuronal Network Model

    Directory of Open Access Journals (Sweden)

    Ying Du

    2014-01-01

    Full Text Available This paper analyzes the dynamics of the cold receptor neural network model. First, it examines noise effects on neuronal stimulus in the model. From ISI plots, it is shown that there are considerable differences between purely deterministic simulations and noisy ones. The ISI-distance is used to measure the noise effects on spike trains quantitatively. It is found that spike trains observed in neural models can be more strongly affected by noise for different temperatures in some aspects; meanwhile, spike train has greater variability with the noise intensity increasing. The synchronization of neuronal network with different connectivity patterns is also studied. It is shown that chaotic and high period patterns are more difficult to get complete synchronization than the situation in single spike and low period patterns. The neuronal network will exhibit various patterns of firing synchronization by varying some key parameters such as the coupling strength. Different types of firing synchronization are diagnosed by a correlation coefficient and the ISI-distance method. The simulations show that the synchronization status of neurons is related to the network connectivity patterns.

  17. Chemogenetic Inhibition of Pain Neurons in a Mouse Model of Osteoarthritis.

    Science.gov (United States)

    Miller, Rachel E; Ishihara, Shingo; Bhattacharyya, Bula; Delaney, Ada; Menichella, Daniela M; Miller, Richard J; Malfait, Anne-Marie

    2017-07-01

    To determine the ability of drugs that activate inhibitory G protein-coupled receptors (GPCRs) expressed in peripheral voltage-gated sodium channel 1.8 (NaV 1.8)-positive sensory neurons to control osteoarthritis (OA)-associated pain. We used designer receptors exclusively activated by a designer drug (DREADD) technology, which employs engineered GPCRs to activate or inhibit neurons upon binding the synthetic ligand clozapine N-oxide (CNO). NaV 1.8-Pdi C57BL/6 mice were generated to express the inhibitory DREADD receptor Pdi in NaV 1.8-expressing sensory neurons. Destabilization of the medial meniscus (DMM) surgery was performed in 10-week-old male mice. Four, 8, 12, or 16 weeks after surgery, knee hyperalgesia or hind paw mechanical allodynia was tested. Subsequently, CNO or vehicle was administered, and the effect on pain-related behaviors was measured by a blinded observer. Morphine was used as a control. Immunohistochemistry and electrophysiology confirmed functional expression of the inhibitory DREADD receptor Pdi by NaV 1.8-positive sensory neurons. Acute inhibition of NaV 1.8-expressing neurons in mice treated with CNO reduced knee hyperalgesia 4 weeks after DMM surgery and reduced mechanical allodynia 8 weeks after DMM surgery. Inhibition had no effect on pain-related behaviors 12 and 16 weeks after DMM surgery. Morphine, a drug that activates GPCRs in the peripheral and central nervous systems, was still effective in the later stage of experimental OA. Chemogenetic inhibition of NaV 1.8-expressing neurons blocks knee hyperalgesia and mechanical allodynia in early experimental OA, but is no longer efficacious in the later stages. These data indicate that activation of inhibitory GPCRs located solely outside the central nervous system may be ineffective in treating chronic OA pain. © 2017, American College of Rheumatology.

  18. Modeling ALS and FTD with iPSC-derived neurons

    OpenAIRE

    Lee, S.; Huang, EJ

    2015-01-01

    © 2015. Recent advances in genetics and neuropathology support the idea that amyotrophic lateral sclerosis (ALS) and frontotemporal lobar dementia (FTD) are two ends of a disease spectrum. Although several animal models have been developed to investigate the pathogenesis and disease progression in ALS and FTD, there are significant limitations that hamper our ability to connect these models with the neurodegenerative processes in human diseases. With the technical breakthrough in reprogrammin...

  19. Co-localization of Gamma-Aminobutyric Acid and Glutamate in Neurons of the Spider Central Nervous System.

    Science.gov (United States)

    Fabian-Fine, Ruth; Meisner, Shannon; Torkkeli, Päivi H; Meinertzhagen, Ian A

    2015-12-01

    Spider sensory neurons with cell bodies close to various sensory organs are innervated by putative efferent axons from the central nervous system (CNS). Light and electronmicroscopic imaging of immunolabeled neurons has demonstrated that neurotransmitters present at peripheral synapses include γ-aminobutyric acid (GABA), glutamate and octopamine. Moreover, electrophysiological studies show that these neurotransmitters modulate the sensitivity of peripheral sensory neurons. Here, we undertook immunocytochemical investigations to characterize GABA and glutamate-immunoreactive neurons in three-dimensional reconstructions of the spider CNS. We document that both neurotransmitters are abundant in morphologically distinct neurons throughout the CNS. Labeling for the vesicular transporters, VGAT for GABA and VGLUT for glutamate, showed corresponding patterns, supporting the specificity of antibody binding. Whereas some neurons displayed strong immunolabeling, others were only weakly labeled. Double labeling showed that a subpopulation of weakly labeled neurons present in all ganglia expresses both GABA and glutamate. Double labeled, strongly and weakly labeled GABA and glutamate immunoreactive axons were also observed in the periphery along muscle fibers and peripheral sensory neurons. Electron microscopic investigations showed presynaptic profiles of various diameters with mixed vesicle populations innervating muscle tissue as well as sensory neurons. Our findings provide evidence that: (1) sensory neurons and muscle fibers are innervated by morphologically distinct, centrally located GABA- and glutamate immunoreactive neurons; (2) a subpopulation of these neurons may co-release both neurotransmitters; and (3) sensory neurons and muscles are innervated by all of these neurochemically and morphologically distinct types of neurons. The biochemical diversity of presynaptic innervation may contribute to how spiders filter natural stimuli and coordinate appropriate response

  20. Modeling study of the light stimulation of a neuron cell with channelrhodopsin-2 mutants.

    Science.gov (United States)

    Grossman, Nir; Nikolic, Konstantin; Toumazou, Christofer; Degenaar, Patrick

    2011-06-01

    Channelrhodopsin-2 (ChR2) has become a widely used tool for stimulating neurons with light. Nevertheless, the underlying dynamics of the ChR2-evoked spikes are still not yet fully understood. Here, we develop a model that describes the response of ChR2-expressing neurons to light stimuli and use the model to explore the light-to-spike process. We show that an optimal stimulation yield is achieved when the optical energies are delivered in short pulses. The model allows us to theoretically examine the effects of using various types of ChR2 mutants. We show that while increasing the lifetime and shuttering speed of ChR2 have limited effect, reducing the threshold irradiance by increased conductance will eliminate adaptation and allow constant dynamic range. The model and the conclusion presented in this study can help to interpret experimental results, design illumination protocols, and seek improvement strategies in the nascent optogenetic field.

  1. Predicting Intentions of a Familiar Significant Other Beyond the Mirror Neuron System

    Directory of Open Access Journals (Sweden)

    Stephanie Cacioppo

    2017-08-01

    Full Text Available Inferring intentions of others is one of the most intriguing issues in interpersonal interaction. Theories of embodied cognition and simulation suggest that this mechanism takes place through a direct and automatic matching process that occurs between an observed action and past actions. This process occurs via the reactivation of past self-related sensorimotor experiences within the inferior frontoparietal network (including the mirror neuron system, MNS. The working model is that the anticipatory representations of others' behaviors require internal predictive models of actions formed from pre-established, shared representations between the observer and the actor. This model suggests that observers should be better at predicting intentions performed by a familiar actor, rather than a stranger. However, little is known about the modulations of the intention brain network as a function of the familiarity between the observer and the actor. Here, we combined functional magnetic resonance imaging (fMRI with a behavioral intention inference task, in which participants were asked to predict intentions from three types of actors: A familiar actor (their significant other, themselves (another familiar actor, and a non-familiar actor (a stranger. Our results showed that the participants were better at inferring intentions performed by familiar actors than non-familiar actors and that this better performance was associated with greater activation within and beyond the inferior frontoparietal network i.e., in brain areas related to familiarity (e.g., precuneus. In addition, and in line with Hebbian principles of neural modulations, the more the participants reported being cognitively close to their partner, the less the brain areas associated with action self-other comparison (e.g., inferior parietal lobule, attention (e.g., superior parietal lobule, recollection (hippocampus, and pair bond (ventral tegmental area, VTA were recruited, suggesting that the

  2. A robust activity marking system for exploring active neuronal ensembles

    DEFF Research Database (Denmark)

    Sorensen, Andreas T.; Cooper, Yonatan A.; Baratta, Michael V.

    2016-01-01

    -Off system that achieves improved temporal control. Due to its compact design, RAM can be packaged into a single adeno-associated virus (AAV), providing great versatility and ease of use, including application to mice, rats, flies, and potentially many other species. Cre-dependent RAM, CRAM, allows...

  3. Neuronal chemokines : Versatile messengers in central nervous system cell interaction

    NARCIS (Netherlands)

    de Haas, A. H.; van Weering, H. R. J.; de Jong, E. K.; Boddeke, H. W. G. M.; Biber, K. P. H.

    2007-01-01

    Whereas chemokines are well known for their ability to induce cell migration, only recently it became evident that chemokines also control a variety of other cell functions and are versatile messengers in the interaction between a diversity of cell types. In the central nervous system (CNS), chemoki

  4. Inhibition of the leucine-rich repeat protein LINGO-1 enhances survival, structure, and function of dopaminergic neurons in Parkinson's disease models.

    Science.gov (United States)

    Inoue, Haruhisa; Lin, Ling; Lee, Xinhua; Shao, Zhaohui; Mendes, Shannon; Snodgrass-Belt, Pamela; Sweigard, Harry; Engber, Tom; Pepinsky, Blake; Yang, Lichuan; Beal, M Flint; Mi, Sha; Isacson, Ole

    2007-09-04

    The nervous system-specific leucine-rich repeat Ig-containing protein LINGO-1 is associated with the Nogo-66 receptor complex and is endowed with a canonical EGF receptor (EGFR)-like tyrosine phosphorylation site. Our studies indicate that LINGO-1 expression is elevated in the substantia nigra of Parkinson's disease (PD) patients compared with age-matched controls and in animal models of PD after neurotoxic lesions. LINGO-1 expression is present in midbrain dopaminergic (DA) neurons in the human and rodent brain. Therefore, the role of LINGO-1 in cell damage responses of DA neurons was examined in vitro and in experimental models of PD induced by either oxidative (6-hydroxydopamine) or mitochondrial (N-methyl-4-phenyl-1,2,3,6-tetrahydropyridine) toxicity. In LINGO-1 knockout mice, DA neuron survival was increased and behavioral abnormalities were reduced compared with WT. This neuroprotection was accompanied by increased Akt phosphorylation (p-Akt). Similar neuroprotective in vivo effects on midbrain DA neurons were obtained in WT mice by blocking LINGO-1 activity using LINGO-1-Fc protein. Neuroprotection and enhanced neurite growth were also demonstrated for midbrain DA neurons in vitro. LINGO-1 antagonists (LINGO-1-Fc, dominant negative LINGO-1, and anti-LINGO-1 antibody) improved DA neuron survival in response to MPP+ in part by mechanisms that involve activation of the EGFR/Akt signaling pathway through a direct inhibition of LINGO-1's binding to EGFR. These results show that inhibitory agents of LINGO-1 activity can protect DA neurons against degeneration and indicate a role for the leucine-rich repeat protein LINGO-1 and related classes of proteins in the pathophysiological responses of midbrain DA neurons in PD.

  5. Complex Behavior in an Integrate-and-Fire