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Sample records for model neuronal system

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

    Directory of Open Access Journals (Sweden)

    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. Modelling LGMD2 visual neuron system

    OpenAIRE

    Fu, Qinbing; Yue, Shigang

    2015-01-01

    Two Lobula Giant Movement Detectors (LGMDs) have been identified in the lobula region of the locust visual system: LGMD1 and LGMD2. LGMD1 had been successfully used in robot navigation to avoid impending collision. LGMD2 also responds to looming stimuli in depth, and shares most the same properties with LGMD1; however, LGMD2 has its specific collision selective responds when dealing with different visual stimulus. Therefore, in this paper, we propose a novel way to model LGMD2, in order to em...

  3. Studying the Behaviour of Model of Mirror Neuron System in Case of Autism

    OpenAIRE

    Shikha Anirban; Mohammad Hanif Ali

    2012-01-01

    Several experiment done by the researchers conducted that autism is caused by the dysfunctional mirror neuron system and the dysfunctions of mirror neuron system is proportional to the symptom severity of autism. In the present work those experiments were studied as well as studying a model of mirror neuron system called MNS2 developed by a research group. This research examined the behavior of the model in case of autism and compared the result with those studies conducting dysfunctions of m...

  4. Studying the Behaviour of Model of Mirror Neuron System in Case of Autism

    Directory of Open Access Journals (Sweden)

    Shikha Anirban

    2012-04-01

    Full Text Available Several experiment done by the researchers conducted that autism is caused by the dysfunctional mirror neuron system and the dysfunctions of mirror neuron system is proportional to the symptom severity of autism. In the present work those experiments were studied as well as studying a model of mirror neuron system called MNS2 developed by a research group. This research examined the behavior of the model in case of autism and compared the result with those studies conducting dysfunctions of mirror neuron system in autism. To perform this, a neural network employing the model was developed which recognized the three types of grasping (faster, normal and slower. The network was implemented with back propagation through time learning algorithm. The whole grasping process was divided into 30 time steps and different hand and object states at each time step was used as the input of the network. Normally the network successfully recognized all of the three types of grasps. The network required more times as the number of inactive neurons increased. And in case of maximum inactive neurons of the mirror neuron system the network became unable to recognize the types of grasp. As the time to recognize the types of grasp is proportional to the number of inactive neurons, the experiment result supports the hypothesis that dysfunctions of MNS is proportional to the symptom severity of autism. Keywords— Autism, MNS, mirror neuron, neural network, BPTT

  5. 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...

  6. 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.

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

    Science.gov (United States)

    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.

  8. Radiation Damage to Nervous System: Designing Optimal Models for Realistic Neuron Morphology in Hippocampus

    Science.gov (United States)

    Batmunkh, Munkhbaatar; Bugay, Alexander; Bayarchimeg, Lkhagvaa; Lkhagva, Oidov

    2018-02-01

    The present study is focused on the development of optimal models of neuron morphology for Monte Carlo microdosimetry simulations of initial radiation-induced events of heavy charged particles in the specific types of cells of the hippocampus, which is the most radiation-sensitive structure of the central nervous system. The neuron geometry and particles track structures were simulated by the Geant4/Geant4-DNA Monte Carlo toolkits. The calculations were made for beams of protons and heavy ions with different energies and doses corresponding to real fluxes of galactic cosmic rays. A simple compartmental model and a complex model with realistic morphology extracted from experimental data were constructed and compared. We estimated the distribution of the energy deposition events and the production of reactive chemical species within the developed models of CA3/CA1 pyramidal neurons and DG granule cells of the rat hippocampus under exposure to different particles with the same dose. Similar distributions of the energy deposition events and concentration of some oxidative radical species were obtained in both the simplified and realistic neuron models.

  9. Conceptual Network Model From Sensory Neurons to Astrocytes of the Human Nervous System.

    Science.gov (United States)

    Yang, Yiqun; Yeo, Chai Kiat

    2015-07-01

    From a single-cell animal like paramecium to vertebrates like ape, the nervous system plays an important role in responding to the variations of the environment. Compared to animals, the nervous system in the human body possesses more intricate organization and utility. The nervous system anatomy has been understood progressively, yet the explanation at the cell level regarding complete information transmission is still lacking. Along the signal pathway toward the brain, an external stimulus first activates action potentials in the sensing neuron and these electric pulses transmit along the spinal nerve or cranial nerve to the neurons in the brain. Second, calcium elevation is triggered in the branch of astrocyte at the tripartite synapse. Third, the local calcium wave expands to the entire territory of the astrocyte. Finally, the calcium wave propagates to the neighboring astrocyte via gap junction channel. In our study, we integrate the existing mathematical model and biological experiments in each step of the signal transduction to establish a conceptual network model for the human nervous system. The network is composed of four layers and the communication protocols of each layer could be adapted to entities with different characterizations. We verify our simulation results against the available biological experiments and mathematical models and provide a test case of the integrated network. As the production of conscious episode in the human nervous system is still under intense research, our model serves as a useful tool to facilitate, complement and verify current and future study in human cognition.

  10. NONLINEAR SYSTEM MODELING USING SINGLE NEURON CASCADED NEURAL NETWORK FOR REAL-TIME APPLICATIONS

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    S. Himavathi

    2012-04-01

    Full Text Available Neural Networks (NN have proved its efficacy for nonlinear system modeling. NN based controllers and estimators for nonlinear systems provide promising alternatives to the conventional counterpart. However, NN models have to meet the stringent requirements on execution time for its effective use in real time applications. This requires the NN model to be structurally compact and computationally less complex. In this paper a parametric method of analysis is adopted to determine the compact and faster NN model among various neural network architectures. This work proves through analysis and examples that the Single Neuron Cascaded (SNC architecture is distinct in providing compact and simpler models requiring lower execution time. The unique structural growth of SNC architecture enables automation in design. The SNC Network is shown to combine the advantages of both single and multilayer neural network architectures. Extensive analysis on selected architectures and their models for four benchmark nonlinear theoretical plants and a practical application are tested. A performance comparison of the NN models is presented to demonstrate the superiority of the single neuron cascaded architecture for online real time applications.

  11. 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.

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

    Science.gov (United States)

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

    2014-01-01

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

  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. Mirror neurons: functions, mechanisms and models.

    Science.gov (United States)

    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.

  17. 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

    , which mediate an L-glutamate-induced transmitter release. The pharmacological properties of these glutamate receptors are, however, distinctly different for the 2 types of neurons. While cerebral cortex neurons express both quisqualate-, N-methyl-D-aspartate- and kainate-receptors, the cerebellar...

  18. 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

    action of GABA on evoked release of glutamate, which is the neurotransmitter in cerebellar granule cells. Also glutamate receptors have been studied with regard to the 2 types of neurons. Both cerebral cortex neurons (GABAergic) and cerebellar granule cells (glutamatergic) possess glutamate receptors...

  19. 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.

  20. Neurosemantics, neurons and system theory.

    Science.gov (United States)

    Breidbach, Olaf

    2007-08-01

    Following the concept of internal representations, signal processing in a neuronal system has to be evaluated exclusively based on internal system characteristics. Thus, this approach omits the external observer as a control function for sensory integration. Instead, the configuration of the system and its computational performance are the effects of endogenous factors. Such self-referential operation is due to a strictly local computation in a network and, thereby, computations follow a set of rules that constitute the emergent behaviour of the system. These rules can be shown to correspond to a "logic" that is intrinsic to the system, an idea which provides the basis for neurosemantics.

  1. [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.

  2. 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.

  3. 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. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

    Cheely, Matthew; Horiuchi, Timothy

    2003-12-01

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  6. Robust Master-Slave Synchronization of Neuronal Systems

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    Hector Puebla

    2017-01-01

    Full Text Available The desire to understand physiological mechanisms of neuronal systems has led to the introduction of engineering concepts to explain how the brain works. The synchronization of neurons is a central topic in understanding the behavior of living organisms in neurosciences and has been addressed using concepts from control engineering. We introduce a simple and reliable robust synchronization approach for neuronal systems. The proposed synchronization method is based on a master-slave configuration in conjunction with a coupling input enhanced with compensation of model uncertainties. Our approach has two nice features for the synchronization of neuronal systems: (i a simple structure that uses the minimum information and (ii good robustness properties against model uncertainties and noise. Two benchmark neuronal systems, Hodgkin-Huxley and Hindmarsh-Rose neurons, are used to illustrate our findings. The proposed synchronization approach is aimed at gaining insight into the effect of external electrical stimulation of nerve cells.

  7. A novel enteric neuron-glia coculture system reveals the role of glia in neuronal development.

    Science.gov (United States)

    Le Berre-Scoul, Catherine; Chevalier, Julien; Oleynikova, Elena; Cossais, François; Talon, Sophie; Neunlist, Michel; Boudin, Hélène

    2017-01-15

    Unlike astrocytes in the brain, the potential role of enteric glial cells (EGCs) in the formation of the enteric neuronal circuit is currently unknown. To examine the role of EGCs in the formation of the neuronal network, we developed a novel neuron-enriched culture model from embryonic rat intestine grown in indirect coculture with EGCs. We found that EGCs shape axonal complexity and synapse density in enteric neurons, through purinergic- and glial cell line-derived neurotrophic factor-dependent pathways. Using a novel and valuable culture model to study enteric neuron-glia interactions, our study identified EGCs as a key cellular actor regulating neuronal network maturation. In the nervous system, the formation of neuronal circuitry results from a complex and coordinated action of intrinsic and extrinsic factors. In the CNS, extrinsic mediators derived from astrocytes have been shown to play a key role in neuronal maturation, including dendritic shaping, axon guidance and synaptogenesis. In the enteric nervous system (ENS), the potential role of enteric glial cells (EGCs) in the maturation of developing enteric neuronal circuit is currently unknown. A major obstacle in addressing this question is the difficulty in obtaining a valuable experimental model in which enteric neurons could be isolated and maintained without EGCs. We adapted a cell culture method previously developed for CNS neurons to establish a neuron-enriched primary culture from embryonic rat intestine which was cultured in indirect coculture with EGCs. We demonstrated that enteric neurons grown in such conditions showed several structural, phenotypic and functional hallmarks of proper development and maturation. However, when neurons were grown without EGCs, the complexity of the axonal arbour and the density of synapses were markedly reduced, suggesting that glial-derived factors contribute strongly to the formation of the neuronal circuitry. We found that these effects played by EGCs were

  8. Hyperbolic Plykin attractor can exist in neuron models

    DEFF Research Database (Denmark)

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

    2005-01-01

    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...

  9. 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...

  10. Optical Communication among Oscillatory Reactions and Photo-Excitable Systems: UV and Visible Radiation Can Synchronize Artificial Neuron Models.

    Science.gov (United States)

    Gentili, Pier Luigi; Giubila, Maria Sole; Germani, Raimondo; Romani, Aldo; Nicoziani, Andrea; Spalletti, Anna; Heron, B Mark

    2017-06-19

    Neuromorphic engineering promises to have a revolutionary impact in our societies. A strategy to develop artificial neurons (ANs) is to use oscillatory and excitable chemical systems. Herein, we use UV and visible radiation as both excitatory and inhibitory signals for the communication among oscillatory reactions, such as the Belousov-Zhabotinsky and the chemiluminescent Orban transformations, and photo-excitable photochromic and fluorescent species. We present the experimental results and the simulations regarding pairs of ANs communicating by either one or two optical signals, and triads of ANs arranged in both feed-forward and recurrent networks. We find that the ANs, powered chemically and/or by the energy of electromagnetic radiation, can give rise to the emergent properties of in-phase, out-of-phase, anti-phase synchronizations and phase-locking, dynamically mimicking the communication among real neurons. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. 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

  12. 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.

  13. A COMPUTATIONAL MODEL OF MOTOR NEURON DEGENERATION

    Science.gov (United States)

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

    2014-01-01

    SUMMARY 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. PMID:25088365

  14. Spatio-Temporal Modeling of Neuron Fields

    DEFF Research Database (Denmark)

    Lund, Adam

    The starting point and focal point for this thesis was stochastic dynamical modelling of neuronal imaging data with the declared objective of drawing inference, within this model framework, in a large-scale (high-dimensional) data setting. Implicitly this objective entails carrying out three......-temporal array data. This framework was developed with neuron field models in mind but may in turn be applied to other settings conforming to the spatio-temporal array data setup....

  15. 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...

  16. Stochastic resonance in models of neuronal ensembles

    International Nuclear Information System (INIS)

    Chialvo, D.R.; Longtin, A.; Mueller-Gerkin, J.

    1997-01-01

    Two recently suggested mechanisms for the neuronal encoding of sensory information involving the effect of stochastic resonance with aperiodic time-varying inputs are considered. It is shown, using theoretical arguments and numerical simulations, that the nonmonotonic behavior with increasing noise of the correlation measures used for the so-called aperiodic stochastic resonance (ASR) scenario does not rely on the cooperative effect typical of stochastic resonance in bistable and excitable systems. Rather, ASR with slowly varying signals is more properly interpreted as linearization by noise. Consequently, the broadening of the open-quotes resonance curveclose quotes in the multineuron stochastic resonance without tuning scenario can also be explained by this linearization. Computation of the input-output correlation as a function of both signal frequency and noise for the model system further reveals conditions where noise-induced firing with aperiodic inputs will benefit from stochastic resonance rather than linearization by noise. Thus, our study clarifies the tuning requirements for the optimal transduction of subthreshold aperiodic signals. It also shows that a single deterministic neuron can perform as well as a network when biased into a suprathreshold regime. Finally, we show that the inclusion of a refractory period in the spike-detection scheme produces a better correlation between instantaneous firing rate and input signal. copyright 1997 The American Physical Society

  17. 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.

  18. 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.

  19. 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

  20. 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

  1. 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...... is positively correlated with intracellular Ca2+ whereas lactate utilization is not. This result lends further support for a significant role of glucose in neuronal bioenergetics and that Ca2+ signalling may control the switch between glucose and lactate utilization during synaptic activity. Based...... a positive correlation between oxidative metabolism of glucose and Ca2+ signalling....

  2. 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.

  3. 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.

  4. Untargeted metabolomics of neuronal cell culture: A model system for the toxicity testing of insecticide chemical exposure.

    Science.gov (United States)

    Hayton, Sarah; Maker, Garth L; Mullaney, Ian; Trengove, Robert D

    2017-12-01

    Toxicity testing is essential for the protection of human health from exposure to toxic environmental chemicals. As traditional toxicity testing is carried out using animal models, mammalian cell culture models are becoming an increasingly attractive alternative to animal testing. Combining the use of mammalian cell culture models with screening-style molecular profiling technologies, such as metabolomics, can uncover previously unknown biochemical bases of toxicity. We have used a mass spectrometry-based untargeted metabolomics approach to characterize for the first time the changes in the metabolome of the B50 cell line, an immortalised rat neuronal cell line, following acute exposure to two known neurotoxic chemicals that are common environmental contaminants; the pyrethroid insecticide permethrin and the organophosphate insecticide malathion. B50 cells were exposed to either the dosing vehicle (methanol) or an acute dose of either permethrin or malathion for 6 and 24 hours. Intracellular metabolites were profiled by gas chromatography-mass spectrometry. Using principal components analysis, we selected the key metabolites whose abundance was altered by chemical exposure. By considering the major fold changes in abundance (>2.0 or culture metabolomics to detect finer metabolic effects of acute exposure to known toxic chemicals, and validate the need for further development of this process in the application of trace-level dose and chronic toxicity studies, and toxicity testing of unknown chemicals. Copyright © 2017 John Wiley & Sons, Ltd.

  5. 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. .

  6. 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.

  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: 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

  9. A Unique Model System for Tumor Progression in GBM Comprising Two Developed Human Neuro-Epithelial Cell Lines with Differential Transforming Potential and Coexpressing Neuronal and Glial Markers

    Directory of Open Access Journals (Sweden)

    Anjali Shiras

    2003-11-01

    Full Text Available The molecular mechanisms involved in tumor progression from a low-grade astrocytoma to the most malignant glioblastoma multiforme (GBM have been hampered due to lack of suitable experimental models. We have established a model of tumor progression comprising of two cell lines derived from the same astrocytoma tumor with a set of features corresponding to low-grade glioma (as in HNGC-1 and high-grade GBM (as in HNGC-2. The HNGC-1 cell line is slowgrowing, contact-inhibited, nontumorigenic, and noninvasive, whereas HNGC-2 is a rapidly proliferating, anchorage-independent, highly tumorigenic, and invasive cell line. The proliferation of cell lines is independent of the addition of exogenous growth factors. Interestingly, the HNGC-2 cell line displays a near-haploid karyotype except for a disomy of chromosome 2. The two cell lines express the neuronal precursor and progenitor markers vimentin, nestin, MAP-2, and NFP160, as well as glial differentiation protein S100μ. The HNGC-1 cell line also expresses markers of mature neurons like Tuj1 and GFAP, an astrocytic differentiation marker, hence contributing toward a more morphologically differentiated phenotype with a propensity for neural differentiation in vitro. Additionally, overexpression of epidermal growth factor receptor and c-erbB2, and loss of fibronectin were observed only in the HNGC-2 cell line, implicating the significance of these pathways in tumor progression. This in vitro model system assumes importance in unraveling the cellular and molecular mechanisms in differentiation, transformation, and gliomagenesis.

  10. 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

  11. 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 ...... equation driven by a Poisson random measure, and state associated central limit theorems. We study situations in which the limit system exhibits oscillatory behavior, and relate the results to certain piecewise deterministic Markov processes and their diffusion approximations....

  12. Complete functional characterization of sensory neurons by system identification.

    Science.gov (United States)

    Wu, Michael C-K; David, Stephen V; Gallant, Jack L

    2006-01-01

    System identification is a growing approach to sensory neurophysiology that facilitates the development of quantitative functional models of sensory processing. This approach provides a clear set of guidelines for combining experimental data with other knowledge about sensory function to obtain a description that optimally predicts the way that neurons process sensory information. This prediction paradigm provides an objective method for evaluating and comparing computational models. In this chapter we review many of the system identification algorithms that have been used in sensory neurophysiology, and we show how they can be viewed as variants of a single statistical inference problem. We then review many of the practical issues that arise when applying these methods to neurophysiological experiments: stimulus selection, behavioral control, model visualization, and validation. Finally we discuss several problems to which system identification has been applied recently, including one important long-term goal of sensory neuroscience: developing models of sensory systems that accurately predict neuronal responses under completely natural conditions.

  13. Electrical Activity in a Time-Delay Four-Variable Neuron Model under Electromagnetic Induction

    Directory of Open Access Journals (Sweden)

    Keming Tang

    2017-11-01

    Full Text Available To investigate the effect of electromagnetic induction on the electrical activity of neuron, the variable for magnetic flow is used to improve Hindmarsh–Rose neuron model. Simultaneously, due to the existence of time-delay when signals are propagated between neurons or even in one neuron, it is important to study the role of time-delay in regulating the electrical activity of the neuron. For this end, a four-variable neuron model is proposed to investigate the effects of electromagnetic induction and time-delay. Simulation results suggest that the proposed neuron model can show multiple modes of electrical activity, which is dependent on the time-delay and external forcing current. It means that suitable discharge mode can be obtained by selecting the time-delay or external forcing current, which could be helpful for further investigation of electromagnetic radiation on biological neuronal system.

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

    International Nuclear Information System (INIS)

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

    2016-01-01

    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.

  15. 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.

  16. Diffusion approximation of neuronal models revisited

    Czech Academy of Sciences Publication Activity Database

    Čupera, Jakub

    2014-01-01

    Roč. 11, č. 1 (2014), s. 11-25 ISSN 1547-1063. [International Workshop on Neural Coding (NC) /10./. Praha, 02.09.2012-07.09.2012] R&D Projects: GA ČR(CZ) GAP103/11/0282 Institutional support: RVO:67985823 Keywords : stochastic model * neuronal activity * first-passage time Subject RIV: JD - Computer Applications, Robotics Impact factor: 0.840, year: 2014

  17. Language comprehension warps the mirror neuron system

    Directory of Open Access Journals (Sweden)

    Noah eZarr

    2013-12-01

    Full Text Available 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 mirror neuron system.

  18. Mechanisms of magnetic stimulation of central nervous system neurons.

    Science.gov (United States)

    Pashut, Tamar; Wolfus, Shuki; Friedman, Alex; Lavidor, Michal; Bar-Gad, Izhar; Yeshurun, Yosef; Korngreen, Alon

    2011-03-01

    Transcranial magnetic stimulation (TMS) is a stimulation method in which a magnetic coil generates a magnetic field in an area of interest in the brain. This magnetic field induces an electric field that modulates neuronal activity. The spatial distribution of the induced electric field is determined by the geometry and location of the coil relative to the brain. Although TMS has been used for several decades, the biophysical basis underlying the stimulation of neurons in the central nervous system (CNS) is still unknown. To address this problem we developed a numerical scheme enabling us to combine realistic magnetic stimulation (MS) with compartmental modeling of neurons with arbitrary morphology. The induced electric field for each location in space was combined with standard compartmental modeling software to calculate the membrane current generated by the electromagnetic field for each segment of the neuron. In agreement with previous studies, the simulations suggested that peripheral axons were excited by the spatial gradients of the induced electric field. In both peripheral and central neurons, MS amplitude required for action potential generation was inversely proportional to the square of the diameter of the stimulated compartment. Due to the importance of the fiber's diameter, magnetic stimulation of CNS neurons depolarized the soma followed by initiation of an action potential in the initial segment of the axon. Passive dendrites affect this process primarily as current sinks, not sources. The simulations predict that neurons with low current threshold are more susceptible to magnetic stimulation. Moreover, they suggest that MS does not directly trigger dendritic regenerative mechanisms. These insights into the mechanism of MS may be relevant for the design of multi-intensity TMS protocols, may facilitate the construction of magnetic stimulators, and may aid the interpretation of results of TMS of the CNS.

  19. Mechanisms of magnetic stimulation of central nervous system neurons.

    Directory of Open Access Journals (Sweden)

    Tamar Pashut

    2011-03-01

    Full Text Available Transcranial magnetic stimulation (TMS is a stimulation method in which a magnetic coil generates a magnetic field in an area of interest in the brain. This magnetic field induces an electric field that modulates neuronal activity. The spatial distribution of the induced electric field is determined by the geometry and location of the coil relative to the brain. Although TMS has been used for several decades, the biophysical basis underlying the stimulation of neurons in the central nervous system (CNS is still unknown. To address this problem we developed a numerical scheme enabling us to combine realistic magnetic stimulation (MS with compartmental modeling of neurons with arbitrary morphology. The induced electric field for each location in space was combined with standard compartmental modeling software to calculate the membrane current generated by the electromagnetic field for each segment of the neuron. In agreement with previous studies, the simulations suggested that peripheral axons were excited by the spatial gradients of the induced electric field. In both peripheral and central neurons, MS amplitude required for action potential generation was inversely proportional to the square of the diameter of the stimulated compartment. Due to the importance of the fiber's diameter, magnetic stimulation of CNS neurons depolarized the soma followed by initiation of an action potential in the initial segment of the axon. Passive dendrites affect this process primarily as current sinks, not sources. The simulations predict that neurons with low current threshold are more susceptible to magnetic stimulation. Moreover, they suggest that MS does not directly trigger dendritic regenerative mechanisms. These insights into the mechanism of MS may be relevant for the design of multi-intensity TMS protocols, may facilitate the construction of magnetic stimulators, and may aid the interpretation of results of TMS of the CNS.

  20. A new model of artificial neuron: cyberneuron and its use

    OpenAIRE

    Polikarpov, S. V.; Dergachev, V. S.; Rumyantsev, K. E.; Golubchikov, D. M.

    2009-01-01

    This article describes a new type of artificial neuron, called the authors "cyberneuron". Unlike classical models of artificial neurons, this type of neuron used table substitution instead of the operation of multiplication of input values for the weights. This allowed to significantly increase the information capacity of a single neuron, but also greatly simplify the process of learning. Considered an example of the use of "cyberneuron" with the task of detecting computer viruses.

  1. Integrated neuron circuit for implementing neuromorphic system with synaptic device

    Science.gov (United States)

    Lee, Jeong-Jun; Park, Jungjin; Kwon, Min-Woo; Hwang, Sungmin; Kim, Hyungjin; Park, Byung-Gook

    2018-02-01

    In this paper, we propose and fabricate Integrate & Fire neuron circuit for implementing neuromorphic system. Overall operation of the circuit is verified by measuring discrete devices and the output characteristics of the circuit. Since the neuron circuit shows asymmetric output characteristic that can drive synaptic device with Spike-Timing-Dependent-Plasticity (STDP) characteristic, the autonomous weight update process is also verified by connecting the synaptic device and the neuron circuit. The timing difference of the pre-neuron and the post-neuron induce autonomous weight change of the synaptic device. Unlike 2-terminal devices, which is frequently used to implement neuromorphic system, proposed scheme of the system enables autonomous weight update and simple configuration by using 4-terminal synapse device and appropriate neuron circuit. Weight update process in the multi-layer neuron-synapse connection ensures implementation of the hardware-based artificial intelligence, based on Spiking-Neural- Network (SNN).

  2. 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.

  3. Robot-Embodied Neuronal Networks as an Interactive Model of Learning.

    Science.gov (United States)

    Shultz, Abraham M; Lee, Sangmook; Guaraldi, Mary; Shea, Thomas B; Yanco, Holly C

    2017-01-01

    The reductionist approach of neuronal cell culture has been useful for analyses of synaptic signaling. Murine cortical neurons in culture spontaneously form an ex vivo network capable of transmitting complex signals, and have been useful for analyses of several fundamental aspects of neuronal development hitherto difficult to clarify in situ . However, these networks lack the ability to receive and respond to sensory input from the environment as do neurons in vivo . Establishment of these networks in culture chambers containing multi-electrode arrays allows recording of synaptic activity as well as stimulation. This article describes the embodiment of ex vivo neuronal networks neurons in a closed-loop cybernetic system, consisting of digitized video signals as sensory input and a robot arm as motor output. In this system, the neuronal network essentially functions as a simple central nervous system. This embodied network displays the ability to track a target in a naturalistic environment. These findings underscore that ex vivo neuronal networks can respond to sensory input and direct motor output. These analyses may contribute to optimization of neuronal-computer interfaces for perceptive and locomotive prosthetic applications. Ex vivo networks display critical alterations in signal patterns following treatment with subcytotoxic concentrations of amyloid-beta. Future studies including comparison of tracking accuracy of embodied networks prepared from mice harboring key mutations with those from normal mice, accompanied with exposure to Abeta and/or other neurotoxins, may provide a useful model system for monitoring subtle impairment of neuronal function as well as normal and abnormal development.

  4. A Primal Analysis System of Brain Neurons Data

    Directory of Open Access Journals (Sweden)

    Dong-Mei Pu

    2014-01-01

    Full Text Available 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.

  5. 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.

  6. 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.

  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. 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…

  9. 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

    2016-02-07

    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. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. Population model of hippocampal pyramidal neurons, linking a refractory density approach to conductance-based neurons

    Science.gov (United States)

    Chizhov, Anton V.; Graham, Lyle J.

    2007-01-01

    We propose a macroscopic approach toward realistic simulations of the population activity of hippocampal pyramidal neurons, based on the known refractory density equation with a different hazard function and on a different single-neuron threshold model. The threshold model is a conductance-based model taking into account adaptation-providing currents, which is reduced by omitting the fast sodium current and instead using an explicit threshold criterion for action potential events. Compared to the full pyramidal neuron model, the threshold model well approximates spike-time moments, postspike refractory states, and postsynaptic current integration. The dynamics of a neural population continuum are described by a set of one-dimensional partial differential equations in terms of the distributions of the refractory density (where the refractory state is defined by the time elapsed since the last action potential), the membrane potential, and the gating variables of the voltage-dependent channels, across the entire population. As the source term in the density equation, the probability density of firing, or hazard function, is derived from the Fokker-Planck (FP) equation, assuming that a single neuron is governed by a deterministic average-across-population input and a noise term. A self-similar solution of the FP equation in the subthreshold regime is obtained. Responses of the ensemble to stimulation by a current step and oscillating current are simulated and compared with individual neuron simulations. An example of interictal-like activity of a population of all-to-all connected excitatory neurons is presented.

  11. Multistability in a neuron model with extracellular potassium dynamics

    Science.gov (United States)

    Wu, Xing-Xing; Shuai, J. W.

    2012-06-01

    Experiments show a primary role of extracellular potassium concentrations in neuronal hyperexcitability and in the generation of epileptiform bursting and depolarization blocks without synaptic mechanisms. We adopt a physiologically relevant hippocampal CA1 neuron model in a zero-calcium condition to better understand the function of extracellular potassium in neuronal seizurelike activities. The model neuron is surrounded by interstitial space in which potassium ions are able to accumulate. Potassium currents, Na+-K+ pumps, glial buffering, and ion diffusion are regulatory mechanisms of extracellular potassium. We also consider a reduced model with a fixed potassium concentration. The bifurcation structure and spiking frequency of the two models are studied. We show that, besides hyperexcitability and bursting pattern modulation, the potassium dynamics can induce not only bistability but also tristability of different firing patterns. Our results reveal the emergence of the complex behavior of multistability due to the dynamical [K+]o modulation on neuronal activities.

  12. Modeling of inter-neuronal coupling medium and its impact on neuronal synchronization.

    Directory of Open Access Journals (Sweden)

    Muhammad Iqbal

    Full Text Available In this paper, modeling of the coupling medium between two neurons, the effects of the model parameters on the synchronization of those neurons, and compensation of coupling strength deficiency in synchronization are studied. Our study exploits the inter-neuronal coupling medium and investigates its intrinsic properties in order to get insight into neuronal-information transmittance and, there from, brain-information processing. A novel electrical model of the coupling medium that represents a well-known RLC circuit attributable to the coupling medium's intrinsic resistive, inductive, and capacitive properties is derived. Surprisingly, the integration of such properties reveals the existence of a natural three-term control strategy, referred to in the literature as the proportional integral derivative (PID controller, which can be responsible for synchronization between two neurons. Consequently, brain-information processing can rely on a large number of PID controllers based on the coupling medium properties responsible for the coherent behavior of neurons in a neural network. Herein, the effects of the coupling model (or natural PID controller parameters are studied and, further, a supervisory mechanism is proposed that follows a learning and adaptation policy based on the particle swarm optimization algorithm for compensation of the coupling strength deficiency.

  13. Spike Frequency Adaptation in Neurons of the Central Nervous System.

    Science.gov (United States)

    Ha, Go Eun; Cheong, Eunji

    2017-08-01

    Neuronal firing patterns and frequencies determine the nature of encoded information of the neurons. Here we discuss the molecular identity and cellular mechanisms of spike-frequency adaptation in central nervous system (CNS) neurons. Calcium-activated potassium (K Ca ) channels such as BK Ca and SK Ca channels have long been known to be important mediators of spike adaptation via generation of a large afterhyperpolarization when neurons are hyper-activated. However, it has been shown that a strong hyperpolarization via these K Ca channels would cease action potential generation rather than reducing the frequency of spike generation. In some types of neurons, the strong hyperpolarization is followed by oscillatory activity in these neurons. Recently, spike-frequency adaptation in thalamocortical (TC) and CA1 hippocampal neurons is shown to be mediated by the Ca 2+ -activated Cl- channel (CACC), anoctamin-2 (ANO2). Knockdown of ANO2 in these neurons results in significantly reduced spike-frequency adaptation accompanied by increased number of spikes without shifting the firing mode, which suggests that ANO2 mediates a genuine form of spike adaptation, finely tuning the frequency of spikes in these neurons. Based on the finding of a broad expression of this new class of CACC in the brain, it can be proposed that the ANO2-mediated spike-frequency adaptation may be a general mechanism to control information transmission in the CNS neurons.

  14. A Note on Some Numerical Approaches to Solve a θ˙ Neuron Networks Model

    Directory of Open Access Journals (Sweden)

    Samir Kumar Bhowmik

    2014-01-01

    Full Text Available Space time integration plays an important role in analyzing scientific and engineering models. In this paper, we consider an integrodifferential equation that comes from modeling θ˙ neuron networks. Here, we investigate various schemes for time discretization of a theta-neuron model. We use collocation and midpoint quadrature formula for space integration and then apply various time integration schemes to get a full discrete system. We present some computational results to demonstrate the schemes.

  15. Complete Neuron-Astrocyte Interaction Model: Digital Multiplierless Design and Networking Mechanism.

    Science.gov (United States)

    Haghiri, Saeed; Ahmadi, Arash; Saif, Mehrdad

    2017-02-01

    Glial cells, also known as neuroglia or glia, are non-neuronal cells providing support and protection for neurons in the central nervous system (CNS). They also act as supportive cells in the brain. Among a variety of glial cells, the star-shaped glial cells, i.e., astrocytes, are the largest cell population in the brain. The important role of astrocyte such as neuronal synchronization, synaptic information regulation, feedback to neural activity and extracellular regulation make the astrocytes play a vital role in brain disease. This paper presents a modified complete neuron-astrocyte interaction model that is more suitable for efficient and large scale biological neural network realization on digital platforms. Simulation results show that the modified complete interaction model can reproduce biological-like behavior of the original neuron-astrocyte mechanism. The modified interaction model is investigated in terms of digital realization feasibility and cost targeting a low cost hardware implementation. Networking behavior of this interaction is investigated and compared between two cases: i) the neuron spiking mechanism without astrocyte effects, and ii) the effect of astrocyte in regulating the neurons behavior and synaptic transmission via controlling the LTP and LTD processes. Hardware implementation on FPGA shows that the modified model mimics the main mechanism of neuron-astrocyte communication with higher performance and considerably lower hardware overhead cost compared with the original interaction model.

  16. Multifunctional mechanosensitive neurons in the enteric nervous system.

    Science.gov (United States)

    Schemann, Michael; Mazzuoli, Gemma

    2010-02-16

    One of the most intriguing abilities of the gut is to function in isolation. This is possible because the gut's own nervous system, the enteric nervous system, contains the necessary elements to control reflex behaviors. Much progress has been made in identifying those neurons that encode mechanical or chemical stimuli. Thus, muscle behaviors in the small and large intestines depend on mechanosensitive neurons which encode a variety of mechanical stimuli, ranging from brief deformation of the neurons soma or processes to sustained tissue stretch. Mechanosensitivity has been recorded in a wide variety of neurons which behave like rapid or slowly adapting mechanosensors. Strikingly, mechanosensitive neurons do not appear to belong to a distinct class of highly specialised neurons but rather differ in their electrophysiology, neurochemistry and morphology. While some mechanosensitive neurons may respond to one stimulus type others appear to be polymodal. Available data would suggest that mechanosensitive enteric neurons are multitasking and hence belong to multifunctional circuits. This review summarises the main arguments in favour of this concept, discusses the stimulus modalities, the response patterns and the functional role of mechanosensitive enteric neurons and concludes with identifying future challenges. Copyright 2009 Elsevier B.V. All rights reserved.

  17. Molecular model of cannabis sensitivity in developing neuronal circuits

    OpenAIRE

    Keimpema, Erik; Mackie, Ken; Harkany, Tibor

    2011-01-01

    Prenatal cannabis exposure can complicate in utero development of the nervous system. Cannabis impacts the formation and functions of neuronal circuitries by targeting cannabinoid receptors. Endocannabinoid signaling emerges as a signaling cassette to orchestrate neuronal differentiation programs through the precisely timed interaction of endocannabinoid ligands with their cognate cannabinoid receptors. By indiscriminately prolonging the ‘switched-on’ period of cannabinoid receptors, cannabis...

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

    Directory of Open Access Journals (Sweden)

    Martin ePyka

    2014-09-01

    Full Text Available 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.

  19. 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.

  20. 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 evolut...

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

    Directory of Open Access Journals (Sweden)

    Thomas Nowotny

    2008-07-01

    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.

  2. 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. Copyright © 2012 Elsevier Ltd. All rights reserved.

  3. 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

  4. 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.

  5. 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.

  6. 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. Copyright © 2015 Elsevier Inc. All rights reserved.

  7. Stochastic resonance in noisy spiking retinal and sensory neuron models.

    Science.gov (United States)

    Patel, Ashok; Kosko, Bart

    2005-01-01

    Two new theorems show that small amounts of additive white noise can improve the bit count or mutual information of several popular models of spiking retinal neurons and spiking sensory neurons. The first theorem gives necessary and sufficient conditions for this noise benefit or stochastic resonance (SR) effect for subthreshold signals in a standard family of Poisson spiking models of retinal neurons. The result holds for all types of finite-variance noise and for all types of infinite-variance stable noise: SR occurs if and only if a sum of noise means or location parameters falls outside a 'forbidden interval' of values. The second theorem gives a similar forbidden-interval sufficient condition for the SR effect for several types of spiking sensory neurons that include the Fitzhugh-Nagumo neuron, the leaky integrate-and-fire neuron, and the reduced Type I neuron model if the additive noise is Gaussian white noise. Simulations show that neither the forbidden-interval condition nor Gaussianity is necessary for the SR effect.

  8. Candidate glutamatergic neurons in the visual system of Drosophila.

    Directory of Open Access Journals (Sweden)

    Shamprasad Varija Raghu

    Full Text Available The visual system of Drosophila contains approximately 60,000 neurons that are organized in parallel, retinotopically arranged columns. A large number of these neurons have been characterized in great anatomical detail. However, studies providing direct evidence for synaptic signaling and the neurotransmitter used by individual neurons are relatively sparse. Here we present a first layout of neurons in the Drosophila visual system that likely release glutamate as their major neurotransmitter. We identified 33 different types of neurons of the lamina, medulla, lobula and lobula plate. Based on the previous Golgi-staining analysis, the identified neurons are further classified into 16 major subgroups representing lamina monopolar (L, transmedullary (Tm, transmedullary Y (TmY, Y, medulla intrinsic (Mi, Mt, Pm, Dm, Mi Am, bushy T (T, translobula plate (Tlp, lobula intrinsic (Lcn, Lt, Li, lobula plate tangential (LPTCs and lobula plate intrinsic (LPi cell types. In addition, we found 11 cell types that were not described by the previous Golgi analysis. This classification of candidate glutamatergic neurons fosters the future neurogenetic dissection of information processing in circuits of the fly visual system.

  9. 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.

  10. 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.

  11. Auditory information coding by modeled cochlear nucleus neurons.

    Science.gov (United States)

    Wang, Huan; Isik, Michael; Borst, Alexander; Hemmert, Werner

    2011-06-01

    In this paper we use information theory to quantify the information in the output spike trains of modeled cochlear nucleus globular bushy cells (GBCs). GBCs are part of the sound localization pathway. They are known for their precise temporal processing, and they code amplitude modulations with high fidelity. Here we investigated the information transmission for a natural sound, a recorded vowel. We conclude that the maximum information transmission rate for a single neuron was close to 1,050 bits/s, which corresponds to a value of approximately 5.8 bits per spike. For quasi-periodic signals like voiced speech, the transmitted information saturated as word duration increased. In general, approximately 80% of the available information from the spike trains was transmitted within about 20 ms. Transmitted information for speech signals concentrated around formant frequency regions. The efficiency of neural coding was above 60% up to the highest temporal resolution we investigated (20 μs). The increase in transmitted information to that precision indicates that these neurons are able to code information with extremely high fidelity, which is required for sound localization. On the other hand, only 20% of the information was captured when the temporal resolution was reduced to 4 ms. As the temporal resolution of most speech recognition systems is limited to less than 10 ms, this massive information loss might be one of the reasons which are responsible for the lack of noise robustness of these systems.

  12. Embodied simulation: from mirror neuron systems to interpersonal relations.

    Science.gov (United States)

    Gallese, Vittorio

    2007-01-01

    A direct form of 'experiential understanding' of others is achieved by modelling their behaviours as intentional experiences on the basis of the equivalence between what the others do and feel and what we do and feel. This modelling mechanism is embodied simulation. By means of embodied simulation we do not just 'see' an action, an emotion, or a sensation. Side by side with the sensory description of the observed social stimuli, internal representations of the body states associated with actions, emotions, and sensations are evoked in the observer, as if he/she would be doing a similar action or experiencing a similar emotion or sensation. Mirror neurons are likely the neural correlate of this mechanism. The mirror neuron matching systems map the different intentional relations in a compressed fashion, which is neutral about the specific quality or identity of the agentive/subjective parameter. By means of a shared neural state realized in two different bodies that nevertheless obey to the same functional rules, the 'objectual other' becomes 'another self'.

  13. Modeling neuron-glia interactions: from parametric model to neuromorphic hardware.

    Science.gov (United States)

    Ghaderi, Viviane S; Allam, Sushmita L; Ambert, N; Bouteiller, J-M C; Choma, J; Berger, T W

    2011-01-01

    Recent experimental evidence suggests that glial cells are more than just supporting cells to neurons - they play an active role in signal transmission in the brain. We herein propose to investigate the importance of these mechanisms and model neuron-glia interactions at synapses using three approaches: A parametric model that takes into account the underlying mechanisms of the physiological system, a non-parametric model that extracts its input-output properties, and an ultra-low power, fast processing, neuromorphic hardware model. We use the EONS (Elementary Objects of the Nervous System) platform, a highly elaborate synaptic modeling platform to investigate the influence of astrocytic glutamate transporters on postsynaptic responses in the detailed micro-environment of a tri-partite synapse. The simulation results obtained using EONS are then used to build a non-parametric model that captures the essential features of glutamate dynamics. The structure of the non-parametric model we use is specifically designed for efficient hardware implementation using ultra-low power subthreshold CMOS building blocks. The utilization of the approach described allows us to build large-scale models of neuron/glial interaction and consequently provide useful insights on glial modulation during normal and pathological neural function.

  14. Computational Models of Neuron-Astrocyte Interactions Lead to Improved Efficacy in the Performance of Neural Networks

    Science.gov (United States)

    Alvarellos-González, Alberto; Pazos, Alejandro; Porto-Pazos, Ana B.

    2012-01-01

    The importance of astrocytes, one part of the glial system, for information processing in the brain has recently been demonstrated. Regarding information processing in multilayer connectionist systems, it has been shown that systems which include artificial neurons and astrocytes (Artificial Neuron-Glia Networks) have well-known advantages over identical systems including only artificial neurons. Since the actual impact of astrocytes in neural network function is unknown, we have investigated, using computational models, different astrocyte-neuron interactions for information processing; different neuron-glia algorithms have been implemented for training and validation of multilayer Artificial Neuron-Glia Networks oriented toward classification problem resolution. The results of the tests performed suggest that all the algorithms modelling astrocyte-induced synaptic potentiation improved artificial neural network performance, but their efficacy depended on the complexity of the problem. PMID:22649480

  15. A high-throughput model for investigating neuronal function and synaptic transmission in cultured neuronal networks.

    Science.gov (United States)

    Virdee, Jasmeet K; Saro, Gabriella; Fouillet, Antoine; Findlay, Jeremy; Ferreira, Filipa; Eversden, Sarah; O'Neill, Michael J; Wolak, Joanna; Ursu, Daniel

    2017-11-03

    Loss of synapses or alteration of synaptic activity is associated with cognitive impairment observed in a number of psychiatric and neurological disorders, such as schizophrenia and Alzheimer's disease. Therefore successful development of in vitro methods that can investigate synaptic function in a high-throughput format could be highly impactful for neuroscience drug discovery. We present here the development, characterisation and validation of a novel high-throughput in vitro model for assessing neuronal function and synaptic transmission in primary rodent neurons. The novelty of our approach resides in the combination of the electrical field stimulation (EFS) with data acquisition in spatially separated areas of an interconnected neuronal network. We integrated our methodology with state of the art drug discovery instrumentation (FLIPR Tetra) and used selective tool compounds to perform a systematic pharmacological validation of the model. We investigated pharmacological modulators targeting pre- and post-synaptic receptors (AMPA, NMDA, GABA-A, mGluR2/3 receptors and Nav, Cav voltage-gated ion channels) and demonstrated the ability of our model to discriminate and measure synaptic transmission in cultured neuronal networks. Application of the model described here as an unbiased phenotypic screening approach will help with our long term goals of discovering novel therapeutic strategies for treating neurological disorders.

  16. Neural dynamics as sampling: a model for stochastic computation in recurrent networks of spiking neurons.

    Directory of Open Access Journals (Sweden)

    Lars Buesing

    2011-11-01

    Full Text Available The organization of computations in networks of spiking neurons in the brain is still largely unknown, in particular in view of the inherently stochastic features of their firing activity and the experimentally observed trial-to-trial variability of neural systems in the brain. In principle there exists a powerful computational framework for stochastic computations, probabilistic inference by sampling, which can explain a large number of macroscopic experimental data in neuroscience and cognitive science. But it has turned out to be surprisingly difficult to create a link between these abstract models for stochastic computations and more detailed models of the dynamics of networks of spiking neurons. Here we create such a link and show that under some conditions the stochastic firing activity of networks of spiking neurons can be interpreted as probabilistic inference via Markov chain Monte Carlo (MCMC sampling. Since common methods for MCMC sampling in distributed systems, such as Gibbs sampling, are inconsistent with the dynamics of spiking neurons, we introduce a different approach based on non-reversible Markov chains that is able to reflect inherent temporal processes of spiking neuronal activity through a suitable choice of random variables. We propose a neural network model and show by a rigorous theoretical analysis that its neural activity implements MCMC sampling of a given distribution, both for the case of discrete and continuous time. This provides a step towards closing the gap between abstract functional models of cortical computation and more detailed models of networks of spiking neurons.

  17. 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. © 2015 Anatomical Society.

  18. Response of Electrical Activity in an Improved Neuron Model under Electromagnetic Radiation and Noise

    Directory of Open Access Journals (Sweden)

    Feibiao Zhan

    2017-11-01

    Full Text Available Electrical activities are ubiquitous neuronal bioelectric phenomena, which have many different modes to encode the expression of biological information, and constitute the whole process of signal propagation between neurons. Therefore, we focus on the electrical activities of neurons, which is also causing widespread concern among neuroscientists. In this paper, we mainly investigate the electrical activities of the Morris-Lecar (M-L model with electromagnetic radiation or Gaussian white noise, which can restore the authenticity of neurons in realistic neural network. First, we explore dynamical response of the whole system with electromagnetic induction (EMI and Gaussian white noise. We find that there are slight differences in the discharge behaviors via comparing the response of original system with that of improved system, and electromagnetic induction can transform bursting or spiking state to quiescent state and vice versa. Furthermore, we research bursting transition mode and the corresponding periodic solution mechanism for the isolated neuron model with electromagnetic induction by using one-parameter and bi-parameters bifurcation analysis. Finally, we analyze the effects of Gaussian white noise on the original system and coupled system, which is conducive to understand the actual discharge properties of realistic neurons.

  19. Response of Electrical Activity in an Improved Neuron Model under Electromagnetic Radiation and Noise.

    Science.gov (United States)

    Zhan, Feibiao; Liu, Shenquan

    2017-01-01

    Electrical activities are ubiquitous neuronal bioelectric phenomena, which have many different modes to encode the expression of biological information, and constitute the whole process of signal propagation between neurons. Therefore, we focus on the electrical activities of neurons, which is also causing widespread concern among neuroscientists. In this paper, we mainly investigate the electrical activities of the Morris-Lecar (M-L) model with electromagnetic radiation or Gaussian white noise, which can restore the authenticity of neurons in realistic neural network. First, we explore dynamical response of the whole system with electromagnetic induction (EMI) and Gaussian white noise. We find that there are slight differences in the discharge behaviors via comparing the response of original system with that of improved system, and electromagnetic induction can transform bursting or spiking state to quiescent state and vice versa. Furthermore, we research bursting transition mode and the corresponding periodic solution mechanism for the isolated neuron model with electromagnetic induction by using one-parameter and bi-parameters bifurcation analysis. Finally, we analyze the effects of Gaussian white noise on the original system and coupled system, which is conducive to understand the actual discharge properties of realistic neurons.

  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. 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.

  2. 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. © 2014 Scandinavian Physiological Society. Published by John Wiley & Sons Ltd.

  3. Expanding the spectrum of neuronal pathology in multiple system atrophy

    Science.gov (United States)

    Cykowski, Matthew D.; Coon, Elizabeth A.; Powell, Suzanne Z.; Jenkins, Sarah M.; Benarroch, Eduardo E.; Low, Phillip A.; Schmeichel, Ann M.

    2015-01-01

    Multiple system atrophy is a sporadic alpha-synucleinopathy that typically affects patients in their sixth decade of life and beyond. The defining clinical features of the disease include progressive autonomic failure, parkinsonism, and cerebellar ataxia leading to significant disability. Pathologically, multiple system atrophy is characterized by glial cytoplasmic inclusions containing filamentous alpha-synuclein. Neuronal inclusions also have been reported but remain less well defined. This study aimed to further define the spectrum of neuronal pathology in 35 patients with multiple system atrophy (20 male, 15 female; mean age at death 64.7 years; median disease duration 6.5 years, range 2.2 to 15.6 years). The morphologic type, topography, and frequencies of neuronal inclusions, including globular cytoplasmic (Lewy body-like) neuronal inclusions, were determined across a wide spectrum of brain regions. A correlation matrix of pathologic severity also was calculated between distinct anatomic regions of involvement (striatum, substantia nigra, olivary and pontine nuclei, hippocampus, forebrain and thalamus, anterior cingulate and neocortex, and white matter of cerebrum, cerebellum, and corpus callosum). The major finding was the identification of widespread neuronal inclusions in the majority of patients, not only in typical disease-associated regions (striatum, substantia nigra), but also within anterior cingulate cortex, amygdala, entorhinal cortex, basal forebrain and hypothalamus. Neuronal inclusion pathology appeared to follow a hierarchy of region-specific susceptibility, independent of the clinical phenotype, and the severity of pathology was duration-dependent. Neuronal inclusions also were identified in regions not previously implicated in the disease, such as within cerebellar roof nuclei. Lewy body-like inclusions in multiple system atrophy followed the stepwise anatomic progression of Lewy body-spectrum disease inclusion pathology in 25.7% of patients

  4. 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.

  5. Neuron-to-Cell Spread of Pseudorabies Virus in a Compartmented Neuronal Culture System

    OpenAIRE

    Ch'ng, T. H.; Enquist, L.W.

    2005-01-01

    Alphaherpesviruses are parasites of the peripheral nervous system in their natural hosts. After the initial infection of peripheral tissues such as mucosal cells, these neurotropic viruses will invade the peripheral nervous system that innervates the site of infection via long-distance axonal transport of the viral genome. In natural hosts, a latent and a nonproductive infection is usually established in the neuronal cell bodies. Upon reactivation, the newly replicated genome will be assemble...

  6. 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.

  7. Generative modelling of regulated dynamical behavior in cultured neuronal networks

    Science.gov (United States)

    Volman, Vladislav; Baruchi, Itay; Persi, Erez; Ben-Jacob, Eshel

    2004-04-01

    The spontaneous activity of cultured in vitro neuronal networks exhibits rich dynamical behavior. Despite the artificial manner of their construction, the networks’ activity includes features which seemingly reflect the action of underlying regulating mechanism rather than arbitrary causes and effects. Here, we study the cultured networks dynamical behavior utilizing a generative modelling approach. The idea is to include the minimal required generic mechanisms to capture the non-autonomous features of the behavior, which can be reproduced by computer modelling, and then, to identify the additional features of biotic regulation in the observed behavior which are beyond the scope of the model. Our model neurons are composed of soma described by the two Morris-Lecar dynamical variables (voltage and fraction of open potassium channels), with dynamical synapses described by the Tsodyks-Markram three variables dynamics. The model neuron satisfies our self-consistency test: when fed with data recorded from a real cultured networks, it exhibits dynamical behavior very close to that of the networks’ “representative” neuron. Specifically, it shows similar statistical scaling properties (approximated by similar symmetric Lévy distribution with finite mean). A network of such M-L elements spontaneously generates (when weak “structured noise” is added) synchronized bursting events (SBEs) similar to the observed ones. Both the neuronal statistical scaling properties within the bursts and the properties of the SBEs time series show generative (a new discussed concept) agreement with the recorded data. Yet, the model network exhibits different structure of temporal variations and does not recover the observed hierarchical temporal ordering, unless fed with recorded special neurons (with much higher rates of activity), thus indicating the existence of self-regulation mechanisms. It also implies that the spontaneous activity is not simply noise-induced. Instead, the

  8. GABA-ergic neurons in the leach central nervous system

    International Nuclear Information System (INIS)

    Cline, H.T.

    1985-01-01

    GABA is a candidate for an inhibitory neurotransmitter in the leech central nervous system because of the well-documented inhibitory action of GABA in other invertebrates. To demonstrate that GABA meets the criteria used to identify a substance as a neurotransmitter, the author examined GABA metabolism and synaptic interactions of inhibitory motor neurons in two leech species, Hirudo medicinalis and Haementeria ghilianii. Segmental ganglia of the leech ventral nerve cord and identified inhibitors have the capacity to synthesize GABA when incubated in the presence of the precursor glutamate. Application of GABA to cell bodies of excitatory motor neurons or muscle fibers innervated by the inhibitors hyperpolarizes the membrane potential of the target cell and activates a chloride ion conductance channel, similar to the inhibitory membrane response following intracellular stimulation of the inhibitor. Bicuculline methiodide (5 x 10 -5 M), GABA receptor antagonist, blocks reversibly the response to applied GABA and the inhibitory synaptic inputs onto the postsynaptic neurons or muscle fibers without interfering with their excitatory inputs. Furthermore, the inhibitors are included among approximately 25 neurons per segmental ganglion that take up GABA by a high affinity uptake system, as revealed by 3 H-GABA-autoradiography. The development of the capacities to synthesize and to take up GABA were examined in leech embryos. The embryos are able to synthesize GABA at early stages of the development of the nervous system, before any neurons have extended neutrites

  9. Neural Plasticity: Single Neuron Models for Discrimination and Generalization and AN Experimental Ensemble Approach.

    Science.gov (United States)

    Munro, Paul Wesley

    A special form for modification of neuronal response properties is described in which the change in the synaptic state vector is parallel to the vector of afferent activity. This process is termed "parallel modification" and its theoretical and experimental implications are examined. A theoretical framework has been devised to describe the complementary functions of generalization and discrimination by single neurons. This constitutes a basis for three models each describing processes for the development of maximum selectivity (discrimination) and minimum selectivity (generalization) by neurons. Strengthening and weakening of synapses is expressed as a product of the presynaptic activity and a nonlinear modulatory function of two postsynaptic variables--namely a measure of the spatially integrated activity of the cell and a temporal integration (time-average) of that activity. Some theorems are given for low-dimensional systems and computer simulation results from more complex systems are discussed. Model neurons that achieve high selectivity mimic the development of cat visual cortex neurons in a wide variety of rearing conditions. A role for low-selectivity neurons is proposed in which they provide inhibitory input to neurons of the opposite type, thereby suppressing the common component of a pattern class and enhancing their selective properties. Such contrast-enhancing circuits are analyzed and supported by computer simulation. To enable maximum selectivity, the net inhibition to a cell must become strong enough to offset whatever excitation is produced by the non-preferred patterns. Ramifications of parallel models for certain experimental paradigms are analyzed. A methodology is outlined for testing synaptic modification hypotheses in the laboratory. A plastic projection from one neuronal population to another will attain stable equilibrium under periodic electrical stimulation of constant intensity. The perturbative effect of shifting this intensity level

  10. The Digital Bee Brain: Integrating and Managing Neurons in a Common 3D Reference System.

    Science.gov (United States)

    Rybak, Jürgen; Kuß, Anja; Lamecker, Hans; Zachow, Stefan; Hege, Hans-Christian; Lienhard, Matthias; Singer, Jochen; Neubert, Kerstin; Menzel, Randolf

    2010-01-01

    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.

  11. 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.

  12. 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....

  13. Neuron Design in Neuromorphic Computing Systems and Its Application in Wireless Communications

    Science.gov (United States)

    2017-03-01

    NEURON DESIGN IN NEUROMORPHIC COMPUTING SYSTEMS AND ITS APPLICATION IN WIRELESS COMMUNICATIONS THE UNIVERSITY OF KANSAS CENTER FOR...2015 – SEP 2016 4. TITLE AND SUBTITLE NEURON DESIGN IN NEUROMORPHIC COMPUTING SYSTEMS AND ITS APPLICATION IN WIRELESS COMMUNICATIONS 5a. CONTRACT...22 14 General Model of Reservoir Computing System …………………………………………..23 15 Whole Layout View of the Encoder Chip……………………………………………………24 16

  14. Neurons other than motor neurons in motor neuron disease.

    Science.gov (United States)

    Ruffoli, Riccardo; Biagioni, Francesca; Busceti, Carla L; Gaglione, Anderson; Ryskalin, Larisa; Gambardella, Stefano; Frati, Alessandro; Fornai, Francesco

    2017-11-01

    Amyotrophic lateral sclerosis (ALS) is typically defined by a loss of motor neurons in the central nervous system. Accordingly, morphological analysis for decades considered motor neurons (in the cortex, brainstem and spinal cord) as the neuronal population selectively involved in ALS. Similarly, this was considered the pathological marker to score disease severity ex vivo both in patients and experimental models. However, the concept of non-autonomous motor neuron death was used recently to indicate the need for additional cell types to produce motor neuron death in ALS. This means that motor neuron loss occurs only when they are connected with other cell types. This concept originally emphasized the need for resident glia as well as non-resident inflammatory cells. Nowadays, the additional role of neurons other than motor neurons emerged in the scenario to induce non-autonomous motor neuron death. In fact, in ALS neurons diverse from motor neurons are involved. These cells play multiple roles in ALS: (i) they participate in the chain of events to produce motor neuron loss; (ii) they may even degenerate more than and before motor neurons. In the present manuscript evidence about multi-neuronal involvement in ALS patients and experimental models is discussed. Specific sub-classes of neurons in the whole spinal cord are reported either to degenerate or to trigger neuronal degeneration, thus portraying ALS as a whole spinal cord disorder rather than a disease affecting motor neurons solely. This is associated with a novel concept in motor neuron disease which recruits abnormal mechanisms of cell to cell communication.

  15. Cochlear spike synchronization and neuron coincidence detection model

    Science.gov (United States)

    Bader, Rolf

    2018-02-01

    Coincidence detection of a spike pattern fed from the cochlea into a single neuron is investigated using a physical Finite-Difference model of the cochlea and a physiologically motivated neuron model. Previous studies have shown experimental evidence of increased spike synchronization in the nucleus cochlearis and the trapezoid body [Joris et al., J. Neurophysiol. 71(3), 1022-1036 and 1037-1051 (1994)] and models show tone partial phase synchronization at the transition from mechanical waves on the basilar membrane into spike patterns [Ch. F. Babbs, J. Biophys. 2011, 435135]. Still the traveling speed of waves on the basilar membrane cause a frequency-dependent time delay of simultaneously incoming sound wavefronts up to 10 ms. The present model shows nearly perfect synchronization of multiple spike inputs as neuron outputs with interspike intervals (ISI) at the periodicity of the incoming sound for frequencies from about 30 to 300 Hz for two different amounts of afferent nerve fiber neuron inputs. Coincidence detection serves here as a fusion of multiple inputs into one single event enhancing pitch periodicity detection for low frequencies, impulse detection, or increased sound or speech intelligibility due to dereverberation.

  16. 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.

  17. A primary neuron culture system for the study of herpes simplex virus latency and reactivation.

    Science.gov (United States)

    Kobayashi, Mariko; Kim, Ju-Youn; Camarena, Vladimir; Roehm, Pamela C; Chao, Moses V; Wilson, Angus C; Mohr, Ian

    2012-04-02

    Herpes simplex virus type-1 (HSV-1) establishes a life-long latent infection in peripheral neurons. This latent reservoir is the source of recurrent reactivation events that ensure transmission and contribute to clinical disease. Current antivirals do not impact the latent reservoir and there are no vaccines. While the molecular details of lytic replication are well-characterized, mechanisms controlling latency in neurons remain elusive. Our present understanding of latency is derived from in vivo studies using small animal models, which have been indispensable for defining viral gene requirements and the role of immune responses. However, it is impossible to distinguish specific effects on the virus-neuron relationship from more general consequences of infection mediated by immune or non-neuronal support cells in live animals. In addition, animal experimentation is costly, time-consuming, and limited in terms of available options for manipulating host processes. To overcome these limitations, a neuron-only system is desperately needed that reproduces the in vivo characteristics of latency and reactivation but offers the benefits of tissue culture in terms of homogeneity and accessibility. Here we present an in vitro model utilizing cultured primary sympathetic neurons from rat superior cervical ganglia (SCG) (Figure 1) to study HSV-1 latency and reactivation that fits most if not all of the desired criteria. After eliminating non-neuronal cells, near-homogeneous TrkA(+) neuron cultures are infected with HSV-1 in the presence of acyclovir (ACV) to suppress lytic replication. Following ACV removal, non-productive HSV-1 infections that faithfully exhibit accepted hallmarks of latency are efficiently established. Notably, lytic mRNAs, proteins, and infectious virus become undetectable, even in the absence of selection, but latency-associated transcript (LAT) expression persists in neuronal nuclei. Viral genomes are maintained at an average copy number of 25 per neuron

  18. Neocortical Neuronal Loss in Patients with Multiple System Atrophy

    DEFF Research Database (Denmark)

    Salvesen, Lisette; Winge, Kristian; Brudek, Tomasz

    2017-01-01

    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...

  19. 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

  20. 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…

  1. 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…

  2. 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

  3. Neuronal Models for Studying Tau Pathology

    Directory of Open Access Journals (Sweden)

    Thorsten Koechling

    2010-01-01

    Full Text Available Alzheimer's disease (AD is the most frequent neurodegenerative disorder leading to dementia in the aged human population. It is characterized by the presence of two main pathological hallmarks in the brain: senile plaques containing -amyloid peptide and neurofibrillary tangles (NFTs, consisting of fibrillar polymers of abnormally phosphorylated tau protein. Both of these histological characteristics of the disease have been simulated in genetically modified animals, which today include numerous mouse, fish, worm, and fly models of AD. The objective of this review is to present some of the main animal models that exist for reproducing symptoms of the disorder and their advantages and shortcomings as suitable models of the pathological processes. Moreover, we will discuss the results and conclusions which have been drawn from the use of these models so far and their contribution to the development of therapeutic applications for AD.

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

    Science.gov (United States)

    2016-03-31

    Neuronal Network Dynamics Sb. GRANT NUMBER N00014-16-1-2252 Sc. PROGRAM ELEMENT NUMBER 6. AUTHOR{S) Sd. PROJECT NUMBER Nikolai Rulkov Se. TASK NUMBER...studies of large-scale neuronal network activity. D 15. SUBJECT TERMS Map-based neuronal model, Discrete time spiking dynamics, Synapses, Neurons ...time involvement (50%) of a postdoc, which have experience with neuronal network simulations using standard conductance-based models and analysis of

  5. Influence of Selective Edge Removal and Refractory Period in a Self-Organized Critical Neuron Model

    International Nuclear Information System (INIS)

    Lin Min; Gang, Zhao; Chen Tianlun

    2009-01-01

    A simple model for a set of integrate-and-fire neurons based on the weighted network is introduced. By considering the neurobiological phenomenon in brain development and the difference of the synaptic strength, we construct weighted networks develop with link additions and followed by selective edge removal. The network exhibits the small-world and scale-free properties with high network efficiency. The model displays an avalanche activity on a power-law distribution. We investigate the effect of selective edge removal and the neuron refractory period on the self-organized criticality of the system. (condensed matter: structural, mechanical, and thermal properties)

  6. Relaxation Cycles in a Generalized Neuron Model with Two Delays

    Directory of Open Access Journals (Sweden)

    S. D. Glyzin

    2013-01-01

    Full Text Available A method of modeling the phenomenon of bursting behavior in neural systems based on delay equations is proposed. A singularly perturbed scalar nonlinear differentialdifference equation of Volterra type is a mathematical model of a neuron and a separate pulse containing one function without delay and two functions with different lags. It is established that this equation, for a suitable choice of parameters, has a stable periodic motion with any preassigned number of bursts in the time interval of the period length. To prove this assertion we first go to a relay-type equation and then determine the asymptotic solutions of a singularly perturbed equation. On the basis of this asymptotics the Poincare operator is constructed. The resulting operator carries a closed bounded convex set of initial conditions into itself, which suggests that it has at least one fixed point. The Frechet derivative evaluation of the succession operator, made in the paper, allows us to prove the uniqueness and stability of the resulting relax of the periodic solution.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  9. Noise-induced divisive gain control in neuron models.

    Science.gov (United States)

    Longtin, André; Doiron, Brent; Bulsara, Adi R

    2002-01-01

    A recent computational study of gain control via shunting inhibition has shown that the slope of the frequency-versus-input (f-I) characteristic of a neuron can be decreased by increasing the noise associated with the inhibitory input (Neural Comput. 13, 227-248). This novel noise-induced divisive gain control relies on the concommittant increase of the noise variance with the mean of the total inhibitory conductance. Here we investigate this effect using different neuronal models. The effect is shown to occur in the standard leaky integrate-and-fire (LIF) model with additive Gaussian white noise, and in the LIF with multiplicative noise acting on the inhibitory conductance. The noisy scaling of input currents is also shown to occur in the one-dimensional theta-neuron model, which has firing dynamics, as well as a large scale compartmental model of a pyramidal cell in the electrosensory lateral line lobe of a weakly electric fish. In this latter case, both the inhibition and the excitatory input have Poisson statistics; noise-induced divisive inhibition is thus seen in f-I curves for which the noise increases along with the input I. We discuss how the variation of the noise intensity along with inputs is constrained by the physiological context and the class of model used, and further provide a comparison of the divisive effect across models.

  10. A Neuronal Model of Classical Conditioning.

    Science.gov (United States)

    1987-10-01

    Moore (1985), Gelperin, HopfieIG, aria Tank (1985), Blazis, Desmond, Moore, and Lerthier (1986), Tesauro (1986), dnd Donegan and Wagner (1987). Proposals...sometimes called Hopfield networks (Hopfield, 1982; Cohen and Grossberg, 1983; Hopfield, 1984; Hopfield and Tank, 1985, 1986; Tesauro , 1986). These latter... Tesauro , G. (1986). S itple neural models of classical conditioning. F1ulogical Cybernetic., 55, 187-200. Thompson, R. F. (1976). The scarch for the

  11. Timing of neuron development in the rodent vestibular system

    Science.gov (United States)

    Keefe, J. R.

    1982-01-01

    The timing of cell generation (onset and duration) in the developing rat vestibular and proprioceptive systems is investigated. The results clearly indicate a defined time-span for generation of all neurons in the central nervous system nuclei studied. This cytogenetic period in both vestibular and proprioceptive sensory nuclei is determined to occur during and immediately after placentation, a potentially critical period for spaceflight exposure due to alterations in maternal physiology.

  12. Model-Based Design of Stimulus Trains for Selective Microstimulation of Targeted Neuronal Populations

    National Research Council Canada - National Science Library

    McIntyre, Cameron

    2001-01-01

    ... that accurately reproduced the dynamic firing properties of mammalian neurons, The neuron models were coupled to a three-dimensional finite element model of the spinal cord that solved for the potentials...

  13. 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.

  14. Colored noise and memory effects on formal spiking neuron models

    Science.gov (United States)

    da Silva, L. A.; Vilela, R. D.

    2015-06-01

    Simplified neuronal models capture the essence of the electrical activity of a generic neuron, besides being more interesting from the computational point of view when compared to higher-dimensional models such as the Hodgkin-Huxley one. In this work, we propose a generalized resonate-and-fire model described by a generalized Langevin equation that takes into account memory effects and colored noise. We perform a comprehensive numerical analysis to study the dynamics and the point process statistics of the proposed model, highlighting interesting new features such as (i) nonmonotonic behavior (emergence of peak structures, enhanced by the choice of colored noise characteristic time scale) of the coefficient of variation (CV) as a function of memory characteristic time scale, (ii) colored noise-induced shift in the CV, and (iii) emergence and suppression of multimodality in the interspike interval (ISI) distribution due to memory-induced subthreshold oscillations. Moreover, in the noise-induced spike regime, we study how memory and colored noise affect the coherence resonance (CR) phenomenon. We found that for sufficiently long memory, not only is CR suppressed but also the minimum of the CV-versus-noise intensity curve that characterizes the presence of CR may be replaced by a maximum. The aforementioned features allow to interpret the interplay between memory and colored noise as an effective control mechanism to neuronal variability. Since both variability and nontrivial temporal patterns in the ISI distribution are ubiquitous in biological cells, we hope the present model can be useful in modeling real aspects of neurons.

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

    Science.gov (United States)

    Albano, Rebecca; Lobner, Doug

    2018-01-01

    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 x c -) were involved in the toxicity. The effects on system x c - are of particular interest. System x c - mediates the transport of cystine into the cell in exchange for releasing glutamate into the extracellular fluid. By releasing glutamate, system x c - 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 x c -. We now present direct evidence that BMAA is transported into both astrocytes and neurons through system x c -. The fact that BMAA is transported by system x c - also provides a mechanism for BMAA to enter brain cells potentially leading to misincorporation into proteins and protein misfolding.

  16. Multiplicative multifractal modeling and discrimination of human neuronal activity

    International Nuclear Information System (INIS)

    Zheng Yi; Gao Jianbo; Sanchez, Justin C.; Principe, Jose C.; Okun, Michael S.

    2005-01-01

    Understanding neuronal firing patterns is one of the most important problems in theoretical neuroscience. It is also very important for clinical neurosurgery. In this Letter, we introduce a computational procedure to examine whether neuronal firing recordings could be characterized by cascade multiplicative multifractals. By analyzing raw recording data as well as generated spike train data from 3 patients collected in two brain areas, the globus pallidus externa (GPe) and the globus pallidus interna (GPi), we show that the neural firings are consistent with a multifractal process over certain time scale range (t 1 ,t 2 ), where t 1 is argued to be not smaller than the mean inter-spike-interval of neuronal firings, while t 2 may be related to the time that neuronal signals propagate in the major neural branching structures pertinent to GPi and GPe. The generalized dimension spectrum D q effectively differentiates the two brain areas, both intra- and inter-patients. For distinguishing between GPe and GPi, it is further shown that the cascade model is more effective than the methods recently examined by Schiff et al. as well as the Fano factor analysis. Therefore, the methodology may be useful in developing computer aided tools to help clinicians perform precision neurosurgery in the operating room

  17. 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.

  18. Effects of neuronal loss in the dynamic model of neural networks

    International Nuclear Information System (INIS)

    Yoon, B-G; Choi, J; Choi, M Y

    2008-01-01

    We study the phase transitions and dynamic behavior of the dynamic model of neural networks, with an emphasis on the effects of neuronal loss due to external stress. In the absence of loss the overall results obtained numerically are found to agree excellently with the theoretical ones. When the external stress is turned on, some neurons may deteriorate and die; such loss of neurons, in general, weakens the memory in the system. As the loss increases beyond a critical value, the order parameter measuring the strength of memory decreases to zero either continuously or discontinuously, namely, the system loses its memory via a second- or a first-order transition, depending on the ratio of the refractory period to the duration of action potential

  19. 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

  20. Learning of Spatial Relationships between Observed and Imitated Actions allows Invariant Inverse Computation in the Frontal Mirror Neuron System

    Science.gov (United States)

    Oh, Hyuk; Gentili, Rodolphe J.; Reggia, James A.; Contreras-Vidal, José L.

    2014-01-01

    It has been suggested that the human mirror neuron system can facilitate learning by imitation through coupling of observation and action execution. During imitation of observed actions, the functional relationship between and within the inferior frontal cortex, the posterior parietal cortex, and the superior temporal sulcus can be modeled within the internal model framework. The proposed biologically plausible mirror neuron system model extends currently available models by explicitly modeling the intraparietal sulcus and the superior parietal lobule in implementing the function of a frame of reference transformation during imitation. Moreover, the model posits the ventral premotor cortex as performing an inverse computation. The simulations reveal that: i) the transformation system can learn and represent the changes in extrinsic to intrinsic coordinates when an imitator observes a demonstrator; ii) the inverse model of the imitator’s frontal mirror neuron system can be trained to provide the motor plans for the imitated actions. PMID:22255261

  1. Effect of Topology Structures on Synchronization Transition in Coupled Neuron Cells System

    International Nuclear Information System (INIS)

    Liang Li-Si; Zhang Ji-Qian; Xu Gui-Xia; Liu Le-Zhu; Huang Shou-Fang

    2013-01-01

    In this paper, by the help of evolutionary algorithm and using Hindmarsh—Rose (HR) neuron model, we investigate the effect of topology structures on synchronization transition between different states in coupled neuron cells system. First, we build different coupling structure with N cells, and found the effect of synchronized transition contact not only closely with the topology of the system, but also with whether there exist the ring structures in the system. In particular, both the size and the number of rings have greater effects on such transition behavior. Secondly, we introduce synchronization error to qualitative analyze the effect of the topology structure. Furthermore, by fitting the simulation results, we find that with the increment of the neurons number, there always exist the optimization structures which have the minimum number of connecting edges in the coupling systems. Above results show that the topology structures have a very crucial role on synchronization transition in coupled neuron system. Biological system may gradually acquire such efficient topology structures through the long-term evolution, thus the systems' information process may be optimized by this scheme. (interdisciplinary physics and related areas of science and technology)

  2. [The mirror neuron system in motor and sensory rehabilitation].

    Science.gov (United States)

    Oouchida, Yutaka; Izumi, Shinichi

    2014-06-01

    The discovery of the mirror neuron system has dramatically changed the study of motor control in neuroscience. The mirror neuron system provides a conceptual framework covering the aspects of motor as well as sensory functions in motor control. Previous studies of motor control can be classified as studies of motor or sensory functions, and these two classes of studies appear to have advanced independently. In rehabilitation requiring motor learning, such as relearning movement after limb paresis, however, sensory information of feedback for motor output as well as motor command are essential. During rehabilitation from chronic pain, motor exercise is one of the most effective treatments for pain caused by dysfunction in the sensory system. In rehabilitation where total intervention unifying the motor and sensory aspects of motor control is important, learning through imitation, which is associated with the mirror neuron system can be effective and suitable. In this paper, we introduce the clinical applications of imitated movement in rehabilitation from motor impairment after brain damage and phantom limb pain after limb amputation.

  3. Stress exacerbates neuron loss and microglia proliferation in a rat model of excitotoxic lower motor neuron injury.

    Science.gov (United States)

    Puga, Denise A; Tovar, C Amy; Guan, Zhen; Gensel, John C; Lyman, Matthew S; McTigue, Dana M; Popovich, Phillip G

    2015-10-01

    All individuals experience stress and hormones (e.g., glucocorticoids/GCs) released during stressful events can affect the structure and function of neurons. These effects of stress are best characterized for brain neurons; however, the mechanisms controlling the expression and binding affinity of glucocorticoid receptors in the spinal cord are different than those in the brain. Accordingly, whether stress exerts unique effects on spinal cord neurons, especially in the context of pathology, is unknown. Using a controlled model of focal excitotoxic lower motor neuron injury in rats, we examined the effects of acute or chronic variable stress on spinal cord motor neuron survival and glial activation. New data indicate that stress exacerbates excitotoxic spinal cord motor neuron loss and associated activation of microglia. In contrast, hypertrophy and hyperplasia of astrocytes and NG2+ glia were unaffected or were modestly suppressed by stress. Although excitotoxic lesions cause significant motor neuron loss and stress exacerbates this pathology, overt functional impairment did not develop in the relevant forelimb up to one week post-lesion. These data indicate that stress is a disease-modifying factor capable of altering neuron and glial responses to pathological challenges in the spinal cord. Copyright © 2015 Elsevier Inc. All rights reserved.

  4. Neuronal expression of muskelin in the rodent central nervous system

    Directory of Open Access Journals (Sweden)

    Georges-Labouesse Elisabeth

    2007-05-01

    Full Text Available Abstract Background The kelch repeat protein muskelin mediates cytoskeletal responses to the extracellular matrix protein thrombospondin 1, (TSP1, that is known to promote synaptogenesis in the central nervous system (CNS. Muskelin displays intracellular localization and affects cytoskeletal organization in adherent cells. Muskelin is expressed in adult brain and has been reported to bind the Cdk5 activator p39, which also facilitates the formation of functional synapses. Since little is known about muskelin in neuronal tissues, we here analysed the tissue distribution of muskelin in rodent brain and analysed its subcellular localization using cultured neurons from multiple life stages. Results Our data show that muskelin transcripts and polypeptides are expressed throughout the central nervous system with significantly high levels in hippocampus and cerebellum, a finding that resembles the tissue distribution of p39. At the subcellular level, muskelin is found in the soma, in neurite projections and the nucleus with a punctate distribution in both axons and dendrites. Immunostaining and synaptosome preparations identify partial localization of muskelin at synaptic sites. Differential centrifugation further reveals muskelin in membrane-enriched, rather than cytosolic fractions. Conclusion Our results suggest that muskelin represents a multifunctional protein associated with membranes and/or large protein complexes in most neurons of the central nervous system. These data are in conclusion with distinct roles of muskelin's functional interaction partners.

  5. Collective excitability in a mesoscopic neuronal model of epileptic activity

    Science.gov (United States)

    Jedynak, Maciej; Pons, Antonio J.; Garcia-Ojalvo, Jordi

    2018-01-01

    At the mesoscopic scale, the brain can be understood as a collection of interacting neuronal oscillators, but the extent to which its sustained activity is due to coupling among brain areas is still unclear. Here we address this issue in a simplified situation by examining the effect of coupling between two cortical columns described via Jansen-Rit neural mass models. Our results show that coupling between the two neuronal populations gives rise to stochastic initiations of sustained collective activity, which can be interpreted as epileptic events. For large enough coupling strengths, termination of these events results mainly from the emergence of synchronization between the columns, and thus it is controlled by coupling instead of noise. Stochastic triggering and noise-independent durations are characteristic of excitable dynamics, and thus we interpret our results in terms of collective excitability.

  6. Neuronal adaptation in the somatosensory system of rodents.

    Science.gov (United States)

    Lampl, I; Katz, Y

    2017-02-20

    The sensory systems in animals constantly monitor the environment and process salient and relevant features while subtracting background activity. This process requires continuous recalibration of neuronal gain based on recent history. Adaptation has been postulated to be the key mechanism by which neurons rapidly tune their response curves to represent the entire dynamic range of external inputs. Rodents heavily rely on their vibrissa system while gathering information about their surroundings using whisking. Neuronal adaptation is observed in all stages of sensory processing, from the whisker follicle through the brainstem and thalamus up to the barrel cortex. In this review, we discuss the intrinsic, synaptic and network mechanisms of adaptation such as short-term synaptic depression, inhibitory suppression, balance between excitation and inhibition as well as the role of cascading adaptation. Furthermore, we describe recent findings about the different intensity dependent adaptation properties in the two major somatosensory pathways and their possible implications about coding. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

    2016-02-29

    network activity. D· 1S. SUBJECT TERMS Map-based neuronal model, Discrete time spiking dynamics, Synapses, Neurons , Neurobiological Networks 16...N00014-16-1-2252 Report #1 Performance/Technical Monthly Report Nonlinear Maps for Design of Discrete-Time Models of Neuronal Network Dynamics...Postdoc. The research plan assumes part-time involvement (50%) of a postdoc, which have experience with neuronal network simulations using standard

  8. 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.

  9. 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

  10. 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

  11. 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.

  12. 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.

  13. Generalized rate-code model for neuron ensembles with finite populations

    International Nuclear Information System (INIS)

    Hasegawa, Hideo

    2007-01-01

    We have proposed a generalized Langevin-type rate-code model subjected to multiplicative noise, in order to study stationary and dynamical properties of an ensemble containing a finite number N of neurons. Calculations using the Fokker-Planck equation have shown that, owing to the multiplicative noise, our rate model yields various kinds of stationary non-Gaussian distributions such as Γ, inverse-Gaussian-like, and log-normal-like distributions, which have been experimentally observed. The dynamical properties of the rate model have been studied with the use of the augmented moment method (AMM), which was previously proposed by the author from a macroscopic point of view for finite-unit stochastic systems. In the AMM, the original N-dimensional stochastic differential equations (DEs) are transformed into three-dimensional deterministic DEs for the means and fluctuations of local and global variables. The dynamical responses of the neuron ensemble to pulse and sinusoidal inputs calculated by the AMM are in good agreement with those obtained by direct simulation. The synchronization in the neuronal ensemble is discussed. The variabilities of the firing rate and of the interspike interval are shown to increase with increasing magnitude of multiplicative noise, which may be a conceivable origin of the observed large variability in cortical neurons

  14. From in silico astrocyte cell models to neuron-astrocyte network models: A review.

    Science.gov (United States)

    Oschmann, Franziska; Berry, Hugues; Obermayer, Klaus; Lenk, Kerstin

    2018-01-01

    The idea that astrocytes may be active partners in synaptic information processing has recently emerged from abundant experimental reports. Because of their spatial proximity to neurons and their bidirectional communication with them, astrocytes are now considered as an important third element of the synapse. Astrocytes integrate and process synaptic information and by doing so generate cytosolic calcium signals that are believed to reflect neuronal transmitter release. Moreover, they regulate neuronal information transmission by releasing gliotransmitters into the synaptic cleft affecting both pre- and postsynaptic receptors. Concurrent with the first experimental reports of the astrocytic impact on neural network dynamics, computational models describing astrocytic functions have been developed. In this review, we give an overview over the published computational models of astrocytic functions, from single-cell dynamics to the tripartite synapse level and network models of astrocytes and neurons. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. 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.

  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. PMID:26998923

  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. Peptides modeled after the alpha-domain of metallothionein induce neurite outgrowth and promote survival of cerebellar granule neurons

    DEFF Research Database (Denmark)

    Asmussen, Johanne Wirenfeldt; Ambjørn, Malene; Bock, Elisabeth

    2009-01-01

    Metallothionein (MT) is a metal-binding protein capable of preventing oxidative stress and apoptotic cell death in the central nervous system of mammals, and hence is of putative therapeutic value in the treatment of neurodegenerative disorders. Recently, we demonstrated that a peptide modeled...... amino acids, as potent stimulators of neuronal differentiation and survival of primary neurons. In addition, we show that a peptide derived from the N-terminus of the MT beta-domain, EmtinBn, promotes neuronal survival. The neuritogenic and survival promoting effects of EmtinAc, similar to MT and Emtin...

  19. Paraneoplastic and non-paraneoplastic autoimmunity to neurons in the central nervous system

    OpenAIRE

    Melzer, Nico; Meuth, Sven G.; Wiendl, Heinz

    2012-01-01

    Autoimmune central nervous system (CNS) inflammation occurs both in a paraneoplastic and non-paraneoplastic context. In a widening spectrum of clinical disorders, the underlying adaptive (auto) immune response targets neurons with a divergent role for cellular and humoral disease mechanisms: (1) in encephalitis associated with antibodies to intracellular neuronal antigens, neuronal antigen-specific CD8+ T cells seemingly account for irreversible progressive neuronal cell death and neurologica...

  20. Biophysics Model of Heavy-Ion Degradation of Neuron Morphology in Mouse Hippocampal Granular Cell Layer Neurons.

    Science.gov (United States)

    Alp, Murat; Cucinotta, Francis A

    2018-03-01

    Exposure to heavy-ion radiation during cancer treatment or space travel may cause cognitive detriments that have been associated with changes in neuron morphology and plasticity. Observations in mice of reduced neuronal dendritic complexity have revealed a dependence on radiation quality and absorbed dose, suggesting that microscopic energy deposition plays an important role. In this work we used morphological data for mouse dentate granular cell layer (GCL) neurons and a stochastic model of particle track structure and microscopic energy deposition (ED) to develop a predictive model of high-charge and energy (HZE) particle-induced morphological changes to the complex structures of dendritic arbors. We represented dendrites as cylindrical segments of varying diameter with unit aspect ratios, and developed a fast sampling method to consider the stochastic distribution of ED by δ rays (secondary electrons) around the path of heavy ions, to reduce computational times. We introduce probabilistic models with a small number of parameters to describe the induction of precursor lesions that precede dendritic snipping, denoted as snip sites. Predictions for oxygen ( 16 O, 600 MeV/n) and titanium ( 48 Ti, 600 MeV/n) particles with LET of 16.3 and 129 keV/μm, respectively, are considered. Morphometric parameters to quantify changes in neuron morphology are described, including reduction in total dendritic length, number of branch points and branch numbers. Sholl analysis is applied for single neurons to elucidate dose-dependent reductions in dendritic complexity. We predict important differences in measurements from imaging of tissues from brain slices with single neuron cell observations due to the role of neuron death through both soma apoptosis and excessive dendritic length reduction. To further elucidate the role of track structure, random segment excision (snips) models are introduced and a sensitivity study of the effects of the modes of neuron death in predictions

  1. 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.

  2. Neuronal Synchronization of Electrical Activity, Using the Hodgkin-Huxley Model and RCLSJ Circuit

    OpenAIRE

    Diaz M, Jose A; Téquita, Oscar; Naranjo, Fernando

    2016-01-01

    We simulated the neuronal electrical activity using the Hodgkin-Huxley model (HH) and a superconductor circuit, containing Josephson junctions. These HH model make possible simulate the main neuronal dynamics characteristics such as action potentials, firing threshold and refractory period. The purpose of the manuscript is show a method to syncronize a RCLshunted Josephson junction to a neuronal dynamics represented by the HH model. Thus the RCLSJ circuit is able to mimics the behavior of the...

  3. 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.

  4. Neurons compute internal models of the physical laws of motion.

    Science.gov (United States)

    Angelaki, Dora E; Shaikh, Aasef G; Green, Andrea M; Dickman, J David

    2004-07-29

    A critical step in self-motion perception and spatial awareness is the integration of motion cues from multiple sensory organs that individually do not provide an accurate representation of the physical world. One of the best-studied sensory ambiguities is found in visual processing, and arises because of the inherent uncertainty in detecting the motion direction of an untextured contour moving within a small aperture. A similar sensory ambiguity arises in identifying the actual motion associated with linear accelerations sensed by the otolith organs in the inner ear. These internal linear accelerometers respond identically during translational motion (for example, running forward) and gravitational accelerations experienced as we reorient the head relative to gravity (that is, head tilt). Using new stimulus combinations, we identify here cerebellar and brainstem motion-sensitive neurons that compute a solution to the inertial motion detection problem. We show that the firing rates of these populations of neurons reflect the computations necessary to construct an internal model representation of the physical equations of motion.

  5. Dynamical analysis of Parkinsonian state emulated by hybrid Izhikevich neuron models

    Science.gov (United States)

    Liu, Chen; Wang, Jiang; Yu, Haitao; Deng, Bin; Wei, Xile; Li, Huiyan; Loparo, Kenneth A.; Fietkiewicz, Chris

    2015-11-01

    Computational models play a significant role in exploring novel theories to complement the findings of physiological experiments. Various computational models have been developed to reveal the mechanisms underlying brain functions. Particularly, in the development of therapies to modulate behavioral and pathological abnormalities, computational models provide the basic foundations to exhibit transitions between physiological and pathological conditions. Considering the significant roles of the intrinsic properties of the globus pallidus and the coupling connections between neurons in determining the firing patterns and the dynamical activities of the basal ganglia neuronal network, we propose a hypothesis that pathological behaviors under the Parkinsonian state may originate from combined effects of intrinsic properties of globus pallidus neurons and synaptic conductances in the whole neuronal network. In order to establish a computational efficient network model, hybrid Izhikevich neuron model is used due to its capacity of capturing the dynamical characteristics of the biological neuronal activities. Detailed analysis of the individual Izhikevich neuron model can assist in understanding the roles of model parameters, which then facilitates the establishment of the basal ganglia-thalamic network model, and contributes to a further exploration of the underlying mechanisms of the Parkinsonian state. Simulation results show that the hybrid Izhikevich neuron model is capable of capturing many of the dynamical properties of the basal ganglia-thalamic neuronal network, such as variations of the firing rates and emergence of synchronous oscillations under the Parkinsonian condition, despite the simplicity of the two-dimensional neuronal model. It may suggest that the computational efficient hybrid Izhikevich neuron model can be used to explore basal ganglia normal and abnormal functions. Especially it provides an efficient way of emulating the large-scale neuron network

  6. Morphological and Physiological Interactions Between GnRH3 and Hypocretin/Orexin Neuronal Systems in Zebrafish (Danio rerio).

    Science.gov (United States)

    Zhao, Yali; Singh, Chanpreet; Prober, David A; Wayne, Nancy L

    2016-10-01

    GnRH neurons integrate internal and external cues to control sexual maturation and fertility. Homeostasis of energy balance and food intake correlates strongly with the status of reproduction. Neuropeptides secreted by the hypothalamus involved in modulating energy balance and feeding may play additional roles in the regulation of reproduction. Hypocretin (Hcrt) (also known as orexin) is one such peptide, primarily controlling sleep/wakefulness, food intake, and reward processing. There is a growing body of evidence indicating that Hcrt/orexin (Hcrt) modulates reproduction through interacting with the hypothalamo-pituitary-gonadal axis in mammals. To explore potential morphological and functional interactions between the GnRH and Hcrt neuronal systems, we employed a variety of experimental approaches including confocal imaging, immunohistochemistry, and electrophysiology in transgenic zebrafish, in which fluorescent proteins are genetically expressed in GnRH3 and Hcrt neurons. Our imaging data revealed close apposition and direct connection between GnRH3 and Hcrt neuronal systems in the hypothalamus during larval development through adulthood. Furthermore, the Hcrt receptor (HcrtR) is expressed in GnRH3 neurons. Electrophysiological data revealed a reversible inhibitory effect of Hcrt on GnRH3 neuron electrical activity, which was blocked by the HcrtR antagonist almorexant. In addition, Hcrt had no effect on the electrical activity of GnRH3 neurons in the HcrtR null mutant zebrafish (HcrtR -/- ). Our findings demonstrate a close anatomical and functional relationship between Hcrt and GnRH neuronal systems in zebrafish. It is the first demonstration of a link between neuronal circuits controlling sleeping/arousal/feeding and reproduction in zebrafish, an important animal model for investigating the molecular genetics of development.

  7. 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.

  8. Loss of functional neuronal nicotinic receptors in dorsal root ganglion neurons in a rat model of neuropathic pain.

    Science.gov (United States)

    Dubé, Gilles R; Kohlhaas, Kathy L; Rueter, Lynne E; Surowy, Carol S; Meyer, Michael D; Briggs, Clark A

    2005-03-07

    Recent evidence has suggested that the anti-allodynic effect of neuronal acetylcholine receptor (nAChR) agonists may have a peripheral component [L.E. Rueter, K.L. Kohlhaas, P. Curzon, C.S. Surowy, M.D. Meyer, Peripheral and central sites of action for A-85380 in the spinal nerve ligation model of neuropathic pain, Pain 103 (2003) 269-276]. In further studies of the peripheral anti-allodynic mechanisms of nAChR agonists, we investigated the function of nAChRs in acutely isolated dorsal root ganglion (DRG) neurons from allodynic [L5-L6 spinal nerve ligation (SNL)] and naive adult rats. Following determination of cell diameter and membrane capacitance, responses to rapid applications of nAChR agonists were recorded under whole cell patch clamp. nAChR inward currents were observed in approximately 60% of naive neurons, across small, medium, and large diameter cells. Evoked nAChR currents could be clustered into three broad classes: fast transient, biphasic, and slow desensitizing currents, consistent with multiple subtypes of nAChR expressed in DRG [J.R. Genzen, W. Van Cleve, D.S. McGehee, Dorsal root ganglion neurons express multiple nicotinic acetylcholine receptor subtypes, J. Neurophysiol. 86 (2001) 1773-1782]. In contrast, in neurons from allodynic animals, the occurrence and amplitude of responses to nAChR agonists were significantly reduced. Reduced responsiveness to nAChR agonists covered the range of DRG neuron sizes. The decrease in the responsiveness to nAChR agonists was not seen in neighboring uninjured L4 neurons. The significant decrease in the number of cells with nAChR agonist responses, compounded with the significant decrease in response amplitude, indicates that there is a marked down regulation of functional nAChRs in DRG somata associated with SNL.

  9. 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

    With rapidly advancing multi-electrode recording technology, the local field potential (LFP) has again become a popular measure of neuronal activity in both research and clinical applications. Proper understanding of the LFP requires detailed mathematical modeling incorporating the anatomical...... 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...

  10. The mechanism of saccade motor pattern generation investigated by a large-scale spiking neuron model of the superior colliculus.

    Directory of Open Access Journals (Sweden)

    Jan Morén

    Full Text Available The subcortical saccade-generating system consists of the retina, superior colliculus, cerebellum and brainstem motoneuron areas. The superior colliculus is the site of sensory-motor convergence within this basic visuomotor loop preserved throughout the vertebrates. While the system has been extensively studied, there are still several outstanding questions regarding how and where the saccade eye movement profile is generated and the contribution of respective parts within this system. Here we construct a spiking neuron model of the whole intermediate layer of the superior colliculus based on the latest anatomy and physiology data. The model consists of conductance-based spiking neurons with quasi-visual, burst, buildup, local inhibitory, and deep layer inhibitory neurons. The visual input is given from the superficial superior colliculus and the burst neurons send the output to the brainstem oculomotor nuclei. Gating input from the basal ganglia and an integral feedback from the reticular formation are also included.We implement the model in the NEST simulator and show that the activity profile of bursting neurons can be reproduced by a combination of NMDA-type and cholinergic excitatory synaptic inputs and integrative inhibitory feedback. The model shows that the spreading neural activity observed in vivo can keep track of the collicular output over time and reset the system at the end of a saccade through activation of deep layer inhibitory neurons. We identify the model parameters according to neural recording data and show that the resulting model recreates the saccade size-velocity curves known as the saccadic main sequence in behavioral studies. The present model is consistent with theories that the superior colliculus takes a principal role in generating the temporal profiles of saccadic eye movements, rather than just specifying the end points of eye movements.

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

    International Nuclear Information System (INIS)

    Li Xiaoli

    2006-01-01

    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

  12. Stochastic resonance induced by novel random transitions of motion of FitzHugh-Nagumo neuron model

    International Nuclear Information System (INIS)

    Zhang Guangjun; Xu Jianxue

    2005-01-01

    In contrast to the previous studies which have dealt with stochastic resonance induced by random transitions of system motion between two coexisting limit cycle attractors in the FitzHugh-Nagumo (FHN) neuron model after Hopf bifurcation and which have dealt with the phenomenon of stochastic resonance induced by external noise when the model with periodic input has only one attractor before Hopf bifurcation, in this paper we have focused our attention on stochastic resonance (SR) induced by a novel transition behavior, the transitions of motion of the model among one attractor on the left side of bifurcation point and two attractors on the right side of bifurcation point under the perturbation of noise. The results of research show: since one bifurcation of transition from one to two limit cycle attractors and the other bifurcation of transition from two to one limit cycle attractors occur in turn besides Hopf bifurcation, the novel transitions of motion of the model occur when bifurcation parameter is perturbed by weak internal noise; the bifurcation point of the model may stochastically slightly shift to the left or right when FHN neuron model is perturbed by external Gaussian distributed white noise, and then the novel transitions of system motion also occur under the perturbation of external noise; the novel transitions could induce SR alone, and when the novel transitions of motion of the model and the traditional transitions between two coexisting limit cycle attractors after bifurcation occur in the same process the SR also may occur with complicated behaviors types; the mechanism of SR induced by external noise when FHN neuron model with periodic input has only one attractor before Hopf bifurcation is related to this kind of novel transition mentioned above

  13. Cultures of Cerebellar Granule Neurons

    OpenAIRE

    sprotocols

    2014-01-01

    Authors: Parizad M. Bilimoria and Azad Bonni1 Corresponding author ([]()) ### INTRODUCTION Primary cultures of granule neurons from the post-natal rat cerebellum provide an excellent model system for molecular and cell biological studies of neuronal development and function. The cerebellar cortex, with its highly organized structure and few neuronal subtypes, offers a well-characterized neural circuitry. Many fundamental insight...

  14. 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.

  15. Regularization of Ill-Posed Point Neuron Models.

    Science.gov (United States)

    Nielsen, Bjørn Fredrik

    2017-12-01

    Point neuron models with a Heaviside firing rate function can be ill-posed. That is, the initial-condition-to-solution map might become discontinuous in finite time. If a Lipschitz continuous but steep firing rate function is employed, then standard ODE theory implies that such models are well-posed and can thus, approximately, be solved with finite precision arithmetic. We investigate whether the solution of this well-posed model converges to a solution of the ill-posed limit problem as the steepness parameter of the firing rate function tends to infinity. Our argument employs the Arzelà-Ascoli theorem and also yields the existence of a solution of the limit problem. However, we only obtain convergence of a subsequence of the regularized solutions. This is consistent with the fact that models with a Heaviside firing rate function can have several solutions, as we show. Our analysis assumes that the vector-valued limit function v, provided by the Arzelà-Ascoli theorem, is threshold simple: That is, the set containing the times when one or more of the component functions of v equal the threshold value for firing, has zero Lebesgue measure. If this assumption does not hold, we argue that the regularized solutions may not converge to a solution of the limit problem with a Heaviside firing function.

  16. Sensorimotor learning and the ontogeny of the mirror neuron system

    OpenAIRE

    Catmur, C

    2013-01-01

    Mirror neurons, which have now been found in the human and songbird as well as the macaque, respond to both the observation and the performance of the same action. It has been suggested that their matching response properties have evolved as an adaptation for action understanding; alternatively, these properties may arise through sensorimotor experience. Here I review mirror neuron response characteristics from the perspective of ontogeny; I discuss the limited evidence for mirror neurons in ...

  17. Mirror Neurons Modeled Through Spike-Timing-Dependent Plasticity are Affected by Channelopathies Associated with Autism Spectrum Disorder.

    Science.gov (United States)

    Antunes, Gabriela; da Silva, Samuel F Faria; de Souza, Fabio M Simoes

    2017-11-28

    Mirror neurons fire action potentials both when the agent performs a certain behavior and watches someone performing a similar action. Here, we present an original mirror neuron model based on the spike-timing-dependent plasticity (STDP) between two morpho-electrical models of neocortical pyramidal neurons. Both neurons fired spontaneously with basal firing rate that follows a Poisson distribution, and the STDP between them was modeled by the triplet algorithm. Our simulation results demonstrated that STDP is sufficient for the rise of mirror neuron function between the pairs of neocortical neurons. This is a proof of concept that pairs of neocortical neurons associating sensory inputs to motor outputs could operate like mirror neurons. In addition, we used the mirror neuron model to investigate whether channelopathies associated with autism spectrum disorder could impair the modeled mirror function. Our simulation results showed that impaired hyperpolarization-activated cationic currents (Ih) affected the mirror function between the pairs of neocortical neurons coupled by STDP.

  18. Prenatal stress and inhibitory neuron systems: implications for neuropsychiatric disorders

    Science.gov (United States)

    Fine, Rebecca; Zhang, Jie; Stevens, Hanna E.

    2014-01-01

    Prenatal stress is a risk factor for several psychiatric disorders in which inhibitory neuron pathology is implicated. A growing body of research demonstrates that inhibitory circuitry in the brain is directly and persistently affected by prenatal stress. This review synthesizes research that elucidates how this early, developmental risk factor impacts inhibitory neurons and how these findings intersect with research on risk factors and inhibitory neuron pathophysiology in schizophrenia, anxiety, autism and Tourette syndrome. The specific impact of prenatal stress on inhibitory neurons, particularly developmental mechanisms, may elucidate further the pathophysiology of these disorders. PMID:24751963

  19. Central serotonergic neuron deficiency in a mouse model of Zellweger syndrome.

    Science.gov (United States)

    Rahim, R S; Meedeniya, A C B; Crane, D I

    2014-08-22

    Zellweger syndrome (ZS) is a severe peroxisomal disorder caused by mutations in peroxisome biogenesis, or PEX, genes. A central hallmark of ZS is abnormal neuronal migration and neurodegeneration, which manifests as widespread neurological dysfunction. The molecular basis of ZS neuropathology is not well understood. Here we present findings using a mouse model of ZS neuropathology with conditional brain inactivation of the PEX13 gene. We demonstrate that PEX13 brain mutants display changes that reflect an abnormal serotonergic system - decreased levels of tryptophan hydroxylase-2, the rate-limiting enzyme of serotonin (5-hydroxytryptamine, 5-HT) synthesis, dysmorphic 5-HT-positive neurons, abnormal distribution of 5-HT neurons, and dystrophic serotonergic axons. The raphe nuclei region of PEX13 brain mutants also display increased levels of apoptotic cells and reactive, inflammatory gliosis. Given the role of the serotonergic system in brain development and motor control, dysfunction of this system would account in part for the observed neurological changes of PEX13 brain mutants. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

  20. Self-repair in a Bidirectionally Coupled Astrocyte-Neuron (AN System based on Retrograde Signaling

    Directory of Open Access Journals (Sweden)

    John eWade

    2012-09-01

    Full Text Available In this paper we demonstrate that retrograde signaling via astrocytes may underpin self-repair in the brain. Faults manifest themselves in silent or near silent neurons caused by low transmission probability synapses; the enhancement of the transmission probability of a healthy neighbouring synapse by retrograde signaling can enhance the transmission probability of the faulty synapse (repair. Our model of self-repair is based on recent research showing that retrograde signaling via astrocytes can increase the probability of neurotransmitter release at damaged or low transmission probability synapses. The model demonstrates that astrocytes are capable of bidirectional communication with neurons which leads to modulation of synaptic activity, and that indirect signaling through retrograde messengers such as endocannabinoids leads to modulation of synaptic transmission probability. Although our model operates at the level of cells, it provides a new research direction on brain-like self-repair which can be extended to networks of astrocytes and neurons. It also provides a biologically inspired basis for developing highly adaptive, distributed computing systems that can, at fine levels of granularity, fault detect, diagnose and self-repair autonomously, without the traditional constraint of a central fault detect/repair unit.

  1. 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

  2. Geometry based finite element modeling of the electrical contact between a cultured neuron and a microelectrode

    NARCIS (Netherlands)

    Buitenweg, Jan R.; Rutten, Wim; Marani, Enrico

    2003-01-01

    The electrical contact between a substrate embedded microelectrode and a cultured neuron depends on the geometry of the neuron-electrode interface. Interpretation and improvement of these contacts requires proper modeling of all coupling mechanisms. In literature, it is common practice to model the

  3. The mirror neuron system simply. An hypothesis? - biomed 2013.

    Science.gov (United States)

    Pascolo, Paolo B

    2013-01-01

    The announcement that mirror neurons (MNs) had been found in macaques was made in 1996. The ensuing MN System theory (MNST) was based on the “nearly simultaneous” activity of some neurons detected both when the macaque observed an investigator's action and when it performed the action (e.g. grasp to eat). Studying the seminal investigations on macaques published in the literature, we realized that poorly defined time-scales could lead to multiple interpretations. We also noticed that in the original experimental protocol the synchronization between the observed event and the neural activity hypothetically related to the event itself was not investigated. In spite of this criticism, the MNST has enjoyed an extraordinary popularity in general media as well as in the scientific community, and monkeys have, almost magically, acquired the functional ability of MNs. In this paper, we analyze some recent studies about the MNST, specifically those about direct measurements on humans by means of implanted electrodes performed by Mukamel and colleagues in 2010. We also consider some experiments performed on monkeys by Rochat et al. in 2010 and some indirect measurements on humans made by Kujala et al. in 2012. We find the conclusions of the authors of these works to be quite simplistic relative to the inherent complexity of neural networks, reinforcing our interpretation against the MNST. We suggest the reported measurements are the result of conventional neural activity related to the events considered (i.e. grasping, both observed and executed) and are not necessarily imputable to the hypothetical MNs.

  4. Basic neuron model electrical equivalent circuit: an undergraduate laboratory exercise.

    Science.gov (United States)

    Dabrowski, Katie M; Castaño, Diego J; Tartar, Jaime L

    2013-01-01

    We developed a hands-on laboratory exercise for undergraduate students in which they can build and manipulate a neuron equivalent circuit. This exercise uses electrical circuit components that resemble neuron components and are easy to construct. We describe the methods for creating the equivalent circuit and how to observe different neuron properties through altering the structure of the equivalent circuit. We explain how this hands-on laboratory activity allows for the better understanding of this fundamental neuroscience concept. At the conclusion of this laboratory exercise, undergraduate students will be able to apply the principles of Ohm's law, cable theory with regards to neurons, and understand the functions of resistance and capacitance in a neuron.

  5. 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.

  6. Noise in Neuronal and Electronic Circuits: A General Modeling Framework and Non-Monte Carlo Simulation Techniques.

    Science.gov (United States)

    Kilinc, Deniz; Demir, Alper

    2017-08-01

    The brain is extremely energy efficient and remarkably robust in what it does despite the considerable variability and noise caused by the stochastic mechanisms in neurons and synapses. Computational modeling is a powerful tool that can help us gain insight into this important aspect of brain mechanism. A deep understanding and computational design tools can help develop robust neuromorphic electronic circuits and hybrid neuroelectronic systems. In this paper, we present a general modeling framework for biological neuronal circuits that systematically captures the nonstationary stochastic behavior of ion channels and synaptic processes. In this framework, fine-grained, discrete-state, continuous-time Markov chain models of both ion channels and synaptic processes are treated in a unified manner. Our modeling framework features a mechanism for the automatic generation of the corresponding coarse-grained, continuous-state, continuous-time stochastic differential equation models for neuronal variability and noise. Furthermore, we repurpose non-Monte Carlo noise analysis techniques, which were previously developed for analog electronic circuits, for the stochastic characterization of neuronal circuits both in time and frequency domain. We verify that the fast non-Monte Carlo analysis methods produce results with the same accuracy as computationally expensive Monte Carlo simulations. We have implemented the proposed techniques in a prototype simulator, where both biological neuronal and analog electronic circuits can be simulated together in a coupled manner.

  7. Human in vitro reporter model of neuronal development and early differentiation processes

    Directory of Open Access Journals (Sweden)

    Bogdahn Ulrich

    2008-02-01

    Full Text Available Abstract Background During developmental and adult neurogenesis, doublecortin is an early neuronal marker expressed when neural stem cells assume a neuronal cell fate. To understand mechanisms involved in early processes of neuronal fate decision, we investigated cell lines for their capacity to induce expression of doublecortin upon neuronal differentiation and develop in vitro reporter models using doublecortin promoter sequences. Results Among various cell lines investigated, the human teratocarcinoma cell line NTERA-2 was found to fulfill our criteria. Following induction of differentiation using retinoic acid treatment, we observed a 16-fold increase in doublecortin mRNA expression, as well as strong induction of doublecortin polypeptide expression. The acquisition of a neuronal precursor phenotype was also substantiated by the establishment of a multipolar neuronal morphology and expression of additional neuronal markers, such as Map2, βIII-tubulin and neuron-specific enolase. Moreover, stable transfection in NTERA-2 cells of reporter constructs encoding fluorescent or luminescent genes under the control of the doublecortin promoter allowed us to directly detect induction of neuronal differentiation in cell culture, such as following retinoic acid treatment or mouse Ngn2 transient overexpression. Conclusion Induction of doublecortin expression in differentiating NTERA-2 cells suggests that these cells accurately recapitulate some of the very early events of neuronal determination. Hence, the use of reporter genes under the control of the doublecortin promoter in NTERA-2 cells will help us to investigate factors involved early in the course of neuronal differentiation processes. Moreover the ease to detect the induction of a neuronal program in this model will permit to perform high throughput screening for compounds acting on the early neuronal differentiation mechanisms.

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

    Science.gov (United States)

    Hagen, Espen; Dahmen, David; Stavrinou, Maria L; Lindén, Henrik; Tetzlaff, Tom; van Albada, Sacha J; Grün, Sonja; Diesmann, Markus; Einevoll, Gaute T

    2016-12-01

    With rapidly advancing multi-electrode recording technology, the local field potential (LFP) has again become a popular measure of neuronal activity in both research and clinical applications. Proper understanding of the LFP requires detailed mathematical modeling incorporating the anatomical 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 public implementation in hybridLFPy form the basis for LFP predictions from other and larger point-neuron network models, as well as extensions of the current application with additional biological detail. © The Author 2016. Published by Oxford University Press.

  9. 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...

  10. 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

  11. 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.

  12. Sexually dimorphic distribution of Prokr2 neurons revealed by the Prokr2-Cre mouse model.

    Science.gov (United States)

    Mohsen, Zaid; Sim, Hosung; Garcia-Galiano, David; Han, Xingfa; Bellefontaine, Nicole; Saunders, Thomas L; Elias, Carol F

    2017-12-01

    Prokineticin receptor 2 (PROKR2) is predominantly expressed in the mammalian central nervous system. Loss-of-function mutations of PROKR2 in humans are associated with Kallmann syndrome due to the disruption of gonadotropin releasing hormone neuronal migration and deficient olfactory bulb morphogenesis. PROKR2 has been also implicated in the neuroendocrine control of GnRH neurons post-migration and other physiological systems. However, the brain circuitry and mechanisms associated with these actions have been difficult to investigate mainly due to the widespread distribution of Prokr2-expressing cells, and the lack of animal models and molecular tools. Here, we describe the generation, validation and characterization of a new mouse model that expresses Cre recombinase driven by the Prokr2 promoter, using CRISPR-Cas9 technology. Cre expression was visualized using reporter genes, tdTomato and GFP, in males and females. Expression of Cre-induced reporter genes was found in brain sites previously described to express Prokr2, e.g., the paraventricular and the suprachiasmatic nuclei, and the area postrema. The Prokr2-Cre mouse model was further validated by colocalization of Cre-induced GFP and Prokr2 mRNA. No disruption of Prokr2 expression, GnRH neuronal migration or fertility was observed. Comparative analysis of Prokr2-Cre expression in male and female brains revealed a sexually dimorphic distribution confirmed by in situ hybridization. In females, higher Cre activity was found in the medial preoptic area, ventromedial nucleus of the hypothalamus, arcuate nucleus, medial amygdala and lateral parabrachial nucleus. In males, Cre was higher in the amygdalo-hippocampal area. The sexually dimorphic pattern of Prokr2 expression indicates differential roles in reproductive function and, potentially, in other physiological systems.

  13. Neuronal model with distributed delay: analysis and simulation study for gamma distribution memory kernel.

    Science.gov (United States)

    Karmeshu; Gupta, Varun; Kadambari, K V

    2011-06-01

    A single neuronal model incorporating distributed delay (memory)is proposed. The stochastic model has been formulated as a Stochastic Integro-Differential Equation (SIDE) which results in the underlying process being non-Markovian. A detailed analysis of the model when the distributed delay kernel has exponential form (weak delay) has been carried out. The selection of exponential kernel has enabled the transformation of the non-Markovian model to a Markovian model in an extended state space. For the study of First Passage Time (FPT) with exponential delay kernel, the model has been transformed to a system of coupled Stochastic Differential Equations (SDEs) in two-dimensional state space. Simulation studies of the SDEs provide insight into the effect of weak delay kernel on the Inter-Spike Interval(ISI) distribution. A measure based on Jensen-Shannon divergence is proposed which can be used to make a choice between two competing models viz. distributed delay model vis-á-vis LIF model. An interesting feature of the model is that the behavior of (CV(t))((ISI)) (Coefficient of Variation) of the ISI distribution with respect to memory kernel time constant parameter η reveals that neuron can switch from a bursting state to non-bursting state as the noise intensity parameter changes. The membrane potential exhibits decaying auto-correlation structure with or without damped oscillatory behavior depending on the choice of parameters. This behavior is in agreement with empirically observed pattern of spike count in a fixed time window. The power spectral density derived from the auto-correlation function is found to exhibit single and double peaks. The model is also examined for the case of strong delay with memory kernel having the form of Gamma distribution. In contrast to fast decay of damped oscillations of the ISI distribution for the model with weak delay kernel, the decay of damped oscillations is found to be slower for the model with strong delay kernel.

  14. Computational model of neuron-astrocyte interactions during focal seizure generation

    Directory of Open Access Journals (Sweden)

    Davide eReato

    2012-10-01

    Full Text Available Empirical research in the last decade revealed that astrocytes can respond to neurotransmitters with Ca2+ elevations and generate feedback signals to neurons which modulate synaptic transmission and neuronal excitability. This discovery changed our basic understanding of brain function and provided new perspectives for how astrocytes can participate not only to information processing, but also to the genesis of brain disorders, such as epilepsy. Epilepsy is a neurological disorder characterized by recurrent seizures that can arise focally at restricted areas and propagate throughout the brain. Studies in brain slice models suggest that astrocytes contribute to epileptiform activity by increasing neuronal excitability through a Ca2+-dependent release of glutamate. The underlying mechanism remains, however, unclear. In this study, we implemented a parsimonious network model of neurons and astrocytes. The model consists of excitatory and inhibitory neurons described by Izhikevich's neuron dynamics. The experimentally observed Ca2+ change in astrocytes in response to neuronal activity was modeled with linear equations. We considered that glutamate is released from astrocytes above certain intracellular Ca2+ concentrations thus providing a non-linear positive feedback signal to neurons. Propagating seizure-like ictal discharges (IDs were reliably evoked in our computational model by repeatedly exciting a small area of the network, which replicates experimental results in a slice model of focal ID in entorhinal cortex. We found that the threshold of focal ID generation was lowered when an excitatory feedback-loop between astrocytes and neurons was included. Simulations show that astrocytes can contribute to ID generation by directly affecting the excitatory/inhibitory balance of the neuronal network. Our model can be used to obtain mechanistic insights into the distinct contributions of the different signaling pathways to the generation and

  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. Finite element modeling of the neuron-electrode interface: stimulus transfer and geometry

    NARCIS (Netherlands)

    Buitenweg, Jan R.; Rutten, Wim; Marani, Enrico

    1999-01-01

    The relation between stimulus transfer and the geometry of the neuron-electrode interface can not be determined properly using electrical equivalent circuits, since current that flows from the sealing gap through the neuronal membrane is difficult to model in these circuits. Therefore, finite

  17. 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.

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

    International Nuclear Information System (INIS)

    Moral, A. del; Azanza, María J.

    2015-01-01

    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 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 0 ≅0.2–15 mT) AC-MF of frequency f 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 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

  19. 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.

  20. 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

  1. 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.

  2. Memory-induced resonancelike suppression of spike generation in a resonate-and-fire neuron model

    Science.gov (United States)

    Mankin, Romi; Paekivi, Sander

    2018-01-01

    The behavior of a stochastic resonate-and-fire neuron model based on a reduction of a fractional noise-driven generalized Langevin equation (GLE) with a power-law memory kernel is considered. The effect of temporally correlated random activity of synaptic inputs, which arise from other neurons forming local and distant networks, is modeled as an additive fractional Gaussian noise in the GLE. Using a first-passage-time formulation, in certain system parameter domains exact expressions for the output interspike interval (ISI) density and for the survival probability (the probability that a spike is not generated) are derived and their dependence on input parameters, especially on the memory exponent, is analyzed. In the case of external white noise, it is shown that at intermediate values of the memory exponent the survival probability is significantly enhanced in comparison with the cases of strong and weak memory, which causes a resonancelike suppression of the probability of spike generation as a function of the memory exponent. Moreover, an examination of the dependence of multimodality in the ISI distribution on input parameters shows that there exists a critical memory exponent αc≈0.402 , which marks a dynamical transition in the behavior of the system. That phenomenon is illustrated by a phase diagram describing the emergence of three qualitatively different structures of the ISI distribution. Similarities and differences between the behavior of the model at internal and external noises are also discussed.

  3. 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.

  4. 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

  5. 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.

  6. 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

  7. 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.

  8. Dynamical analysis of periodic bursting in piece-wise linear planar neuron model.

    Science.gov (United States)

    Ji, Ying; Zhang, Xiaofang; Liang, Minjie; Hua, Tingting; Wang, Yawei

    2015-12-01

    A piece-wise linear planar neuron model, namely, two-dimensional McKean model with periodic drive is investigated in this paper. Periodical bursting phenomenon can be observed in the numerical simulations. By assuming the formal solutions associated with different intervals of this non-autonomous system and introducing the generalized Jacobian matrix at the non-smooth boundaries, the bifurcation mechanism for the bursting solution induced by the slowly varying periodic drive is presented. It is shown that, the discontinuous Hopf bifurcation occurring at the non-smooth boundaries, i.e., the bifurcation taking place at the thresholds of the stimulation, leads the alternation between the rest state and spiking state. That is, different oscillation modes of this non-autonomous system convert periodically due to the non-smoothness of the vector field and the slow variation of the periodic drive as well.

  9. Competition model for aperiodic stochastic resonance in a Fitzhugh-Nagumo model of cardiac sensory neurons.

    Science.gov (United States)

    Kember, G C; Fenton, G A; Armour, J A; Kalyaniwalla, N

    2001-04-01

    Regional cardiac control depends upon feedback of the status of the heart from afferent neurons responding to chemical and mechanical stimuli as transduced by an array of sensory neurites. Emerging experimental evidence shows that neural control in the heart may be partially exerted using subthreshold inputs that are amplified by noisy mechanical fluctuations. This amplification is known as aperiodic stochastic resonance (ASR). Neural control in the noisy, subthreshold regime is difficult to see since there is a near absence of any correlation between input and the output, the latter being the average firing (spiking) rate of the neuron. This lack of correlation is unresolved by traditional energy models of ASR since these models are unsuitable for identifying "cause and effect" between such inputs and outputs. In this paper, the "competition between averages" model is used to determine what portion of a noisy, subthreshold input is responsible, on average, for the output of sensory neurons as represented by the Fitzhugh-Nagumo equations. A physiologically relevant conclusion of this analysis is that a nearly constant amount of input is responsible for a spike, on average, and this amount is approximately independent of the firing rate. Hence, correlation measures are generally reduced as the firing rate is lowered even though neural control under this model is actually unaffected.

  10. Dynamic modeling of neuronal responses in fMRI using cubature Kalman filtering.

    Science.gov (United States)

    Havlicek, Martin; Friston, Karl J; Jan, Jiri; Brazdil, Milan; Calhoun, Vince D

    2011-06-15

    This paper presents a new approach to inverting (fitting) models of coupled dynamical systems based on state-of-the-art (cubature) Kalman filtering. Crucially, this inversion furnishes posterior estimates of both the hidden states and parameters of a system, including any unknown exogenous input. Because the underlying generative model is formulated in continuous time (with a discrete observation process) it can be applied to a wide variety of models specified with either ordinary or stochastic differential equations. These are an important class of models that are particularly appropriate for biological time-series, where the underlying system is specified in terms of kinetics or dynamics (i.e., dynamic causal models). We provide comparative evaluations with generalized Bayesian filtering (dynamic expectation maximization) and demonstrate marked improvements in accuracy and computational efficiency. We compare the schemes using a series of difficult (nonlinear) toy examples and conclude with a special focus on hemodynamic models of evoked brain responses in fMRI. Our scheme promises to provide a significant advance in characterizing the functional architectures of distributed neuronal systems, even in the absence of known exogenous (experimental) input; e.g., resting state fMRI studies and spontaneous fluctuations in electrophysiological studies. Importantly, unlike current Bayesian filters (e.g. DEM), our scheme provides estimates of time-varying parameters, which we will exploit in future work on the adaptation and enabling of connections in the brain. Copyright © 2011 Elsevier Inc. All rights reserved.

  11. 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.

  12. Multiscale analysis of slow-fast neuronal learning models with noise.

    Science.gov (United States)

    Galtier, Mathieu; Wainrib, Gilles

    2012-11-22

    This paper deals with the application of temporal averaging methods to recurrent networks of noisy neurons undergoing a slow and unsupervised modification of their connectivity matrix called learning. Three time-scales arise for these models: (i) the fast neuronal dynamics, (ii) the intermediate external input to the system, and (iii) the slow learning mechanisms. Based on this time-scale separation, we apply an extension of the mathematical theory of stochastic averaging with periodic forcing in order to derive a reduced deterministic model for the connectivity dynamics. We focus on a class of models where the activity is linear to understand the specificity of several learning rules (Hebbian, trace or anti-symmetric learning). In a weakly connected regime, we study the equilibrium connectivity which gathers the entire 'knowledge' of the network about the inputs. We develop an asymptotic method to approximate this equilibrium. We show that the symmetric part of the connectivity post-learning encodes the correlation structure of the inputs, whereas the anti-symmetric part corresponds to the cross correlation between the inputs and their time derivative. Moreover, the time-scales ratio appears as an important parameter revealing temporal correlations.

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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.

  18. Seizure-like afterdischarges simulated in a model neuron.

    NARCIS (Netherlands)

    Kager, J.; Wadman, W.J.; Somjen, G.G.

    2006-01-01

    To explore non-synaptic mechanisms in paroxysmal discharges, we used a computer model of a simplified hippocampal pyramidal cell, surrounded by interstitial space and a "glial-endothelial" buffer system. Ion channels for Na(+), K(+), Ca(2+) and Cl(-) (,) ion antiport 3Na/Ca, and "active" ion pumps

  19. Tp53 gene mediates distinct dopaminergic neuronal damage in different dopaminergic neurotoxicant models

    Directory of Open Access Journals (Sweden)

    Tao Lu

    2017-01-01

    Full Text Available Tp53, a stress response gene, is involved in diverse cell death pathways and its activation is implicated in the pathogenesis of Parkinson's disease. However, whether the neuronal Tp53 protein plays a direct role in regulating dopaminergic (DA neuronal cell death or neuronal terminal damage in different neurotoxicant models is unknown. In our recent studies, in contrast to the global inhibition of Tp53 function by pharmacological inhibitors and in traditional Tp53 knock-out mice, we examined the effects of DA-specific Tp53 gene deletion after 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine and methamphetamine exposure. Our data suggests that the Tp53 gene might be involved in both neuronal apoptosis and neuronal terminal damage caused by different neurotoxicants. Additional results from other studies also suggest that as a master regulator of many pathways that regulate apoptosis and synaptic terminal damage, it is possible that Tp53 may function as a signaling hub to integrate different signaling pathways to mediate distinctive target pathways. Tp53 protein as a signaling hub might be able to evaluate the microenvironment of neurons, assess the forms and severities of injury incurred, and determine whether apoptotic cell death or neuronal terminal degeneration occurs. Identification of the precise mechanisms activated in distinct neuronal damage caused by different forms and severities of injuries might allow for development of specific Tp53 inhibitors or ways to modulate distinct downstream target pathways involved.

  20. 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.

  1. 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 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 (CA1.2-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.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.

  2. The mirror-neuron system and observational learning: Implications for the effectiveness of dynamic visualizations.

    OpenAIRE

    Van Gog, Tamara; Paas, Fred; Marcus, Nadine; Ayres, Paul; Sweller, John

    2009-01-01

    Van Gog, T., Paas, F., Marcus, N., Ayres, P., & Sweller, J. (2009). The mirror-neuron system and observational learning: Implications for the effectiveness of dynamic visualizations. Educational Psychology Review, 21, 21-30.

  3. Image-guided recording system for spatial and temporal mapping of neuronal activities in brain slice.

    Science.gov (United States)

    Choi, Geonho; Lee, Jeonghyeon; Kim, Hyeongeun; Jang, Jaemyung; Im, Changkyun; Jeon, Nooli; Jung, Woonggyu

    2018-03-01

    In this study, we introduce the novel image-guided recording system (IGRS) for efficient interpretation of neuronal activities in the brain slice. IGRS is designed to combine microelectrode array (MEA) and optical coherence tomography at the customized upright microscope. It allows to record multi-site neuronal signals and image of the volumetric brain anatomy in a single body configuration. For convenient interconnection between a brain image and neuronal signals, we developed the automatic mapping protocol that enables us to project acquired neuronal signals on a brain image. To evaluate the performance of IGRS, hippocampal signals of the brain slice were monitored, and corresponding with two-dimensional neuronal maps were successfully reconstructed. Our results indicated that IGRS and mapping protocol can provide the intuitive information regarding long-term and multi-sites neuronal signals. In particular, the temporal and spatial mapping capability of neuronal signals would be a very promising tool to observe and analyze the massive neuronal activity and connectivity in MEA-based electrophysiological studies. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. Novel Spiking Neuron-Astrocyte Networks based on nonlinear transistor-like models of tripartite synapses.

    Science.gov (United States)

    Valenza, Gaetano; Tedesco, Luciano; Lanata, Antonio; De Rossi, Danilo; Scilingo, Enzo Pasquale

    2013-01-01

    In this paper a novel and efficient computational implementation of a Spiking Neuron-Astrocyte Network (SNAN) is reported. Neurons are modeled according to the Izhikevich formulation and the neuron-astrocyte interactions are intended as tripartite synapsis and modeled with the previously proposed nonlinear transistor-like model. Concerning the learning rules, the original spike-timing dependent plasticity is used for the neural part of the SNAN whereas an ad-hoc rule is proposed for the astrocyte part. SNAN performances are compared with a standard spiking neural network (SNN) and evaluated using the polychronization concept, i.e., number of co-existing groups that spontaneously generate patterns of polychronous activity. The astrocyte-neuron ratio is the biologically inspired value of 1.5. The proposed SNAN shows higher number of polychronous groups than SNN, remarkably achieved for the whole duration of simulation (24 hours).

  5. In vitro system using human neurons demonstrates that varicella-zoster vaccine virus is impaired for reactivation, but not latency

    Science.gov (United States)

    Sadaoka, Tomohiko; Depledge, Daniel P.; Rajbhandari, Labchan; Venkatesan, Arun; Breuer, Judith; Cohen, Jeffrey I.

    2016-01-01

    Varicella-zoster virus (VZV) establishes latency in human sensory and cranial nerve ganglia during primary infection (varicella), and the virus can reactivate and cause zoster after primary infection. The mechanism of how the virus establishes and maintains latency and how it reactivates is poorly understood, largely due to the lack of robust models. We found that axonal infection of neurons derived from hESCs in a microfluidic device with cell-free parental Oka (POka) VZV resulted in latent infection with inability to detect several viral mRNAs by reverse transcriptase-quantitative PCR, no production of infectious virus, and maintenance of the viral DNA genome in endless configuration, consistent with an episome configuration. With deep sequencing, however, multiple viral mRNAs were detected. Treatment of the latently infected neurons with Ab to NGF resulted in production of infectious virus in about 25% of the latently infected cultures. Axonal infection of neurons with vaccine Oka (VOka) VZV resulted in a latent infection similar to infection with POka; however, in contrast to POka, VOka-infected neurons were markedly impaired for reactivation after treatment with Ab to NGF. In addition, viral transcription was markedly reduced in neurons latently infected with VOka compared with POka. Our in vitro system recapitulates both VZV latency and reactivation in vivo and may be used to study viral vaccines for their ability to establish latency and reactivate. PMID:27078099

  6. Model-based iterative learning control of Parkinsonian state in thalamic relay neuron

    Science.gov (United States)

    Liu, Chen; Wang, Jiang; Li, Huiyan; Xue, Zhiqin; Deng, Bin; Wei, Xile

    2014-09-01

    Although the beneficial effects of chronic deep brain stimulation on Parkinson's disease motor symptoms are now largely confirmed, the underlying mechanisms behind deep brain stimulation remain unclear and under debate. Hence, the selection of stimulation parameters is full of challenges. Additionally, due to the complexity of neural system, together with omnipresent noises, the accurate model of thalamic relay neuron is unknown. Thus, the iterative learning control of the thalamic relay neuron's Parkinsonian state based on various variables is presented. Combining the iterative learning control with typical proportional-integral control algorithm, a novel and efficient control strategy is proposed, which does not require any particular knowledge on the detailed physiological characteristics of cortico-basal ganglia-thalamocortical loop and can automatically adjust the stimulation parameters. Simulation results demonstrate the feasibility of the proposed control strategy to restore the fidelity of thalamic relay in the Parkinsonian condition. Furthermore, through changing the important parameter—the maximum ionic conductance densities of low-threshold calcium current, the dominant characteristic of the proposed method which is independent of the accurate model can be further verified.

  7. 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.

  8. Is the Langevin phase equation an efficient model for oscillating neurons?

    International Nuclear Information System (INIS)

    Ota, Keisuke; Tsunoda, Takamasa; Aonishi, Toru; Omori, Toshiaki; Okada, Masato; Watanabe, Shigeo; Miyakawa, Hiroyoshi

    2009-01-01

    The Langevin phase model is an important canonical model for capturing coherent oscillations of neural populations. However, little attention has been given to verifying its applicability. In this paper, we demonstrate that the Langevin phase equation is an efficient model for neural oscillators by using the machine learning method in two steps: (a) Learning of the Langevin phase model. We estimated the parameters of the Langevin phase equation, i.e., a phase response curve and the intensity of white noise from physiological data measured in the hippocampal CA1 pyramidal neurons. (b) Test of the estimated model. We verified whether a Fokker-Planck equation derived from the Langevin phase equation with the estimated parameters could capture the stochastic oscillatory behavior of the same neurons disturbed by periodic perturbations. The estimated model could predict the neural behavior, so we can say that the Langevin phase equation is an efficient model for oscillating neurons.

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

    Science.gov (United States)

    Chersi, Fabian; Ferrari, Pier Francesco; Fogassi, Leonardo

    2011-01-01

    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.

  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. Neuronal Chains for Actions in the Parietal Lobe: A Computational Model

    Science.gov (United States)

    Chersi, Fabian; Ferrari, Pier Francesco; Fogassi, Leonardo

    2011-01-01

    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. PMID:22140455

  12. Vibrotactile discrimination in the rat whisker system is based on neuronal coding of instantaneous kinematic cues.

    Science.gov (United States)

    Waiblinger, Christian; Brugger, Dominik; Schwarz, Cornelius

    2015-04-01

    Which physical parameter of vibrissa deflections is extracted by the rodent tactile system for discrimination? Particularly, it remains unclear whether perception has access to instantaneous kinematic parameters (i.e., the details of the trajectory) or relies on temporally integration of the movement trajectory such as frequency (e.g., spectral information) and intensity (e.g., mean speed). Here, we use a novel detection of change paradigm in head-fixed rats, which presents pulsatile vibrissa stimuli in seamless sequence for discrimination. This procedure ensures that processes of decision making can directly tap into sensory signals (no memory functions involved). We find that discrimination performance based on instantaneous kinematic cues far exceeds the ones provided by frequency and intensity. Neuronal modeling based on barrel cortex single units shows that small populations of sensitive neurons provide a transient signal that optimally fits the characteristic of the subject's perception. The present study is the first to show that perceptual read-out is superior in situations allowing the subject to base perception on detailed trajectory cues, that is, instantaneous kinematic variables. A possible impact of this finding on tactile systems of other species is suggested by evidence for instantaneous coding also in primates. © The Author 2013. Published by Oxford University Press.

  13. Comparative mapping of GABA-immunoreactive neurons in the central nervous systems of nudibranch molluscs.

    Science.gov (United States)

    Gunaratne, Charuni A; Sakurai, Akira; Katz, Paul S

    2014-03-01

    The relative simplicity of certain invertebrate nervous systems, such as those of gastropod molluscs, allows behaviors to be dissected at the level of small neural circuits composed of individually identifiable neurons. Elucidating the neurotransmitter phenotype of neurons in neural circuits is important for understanding how those neural circuits function. In this study, we examined the distribution of γ-aminobutyric-acid;-immunoreactive (GABA-ir) neurons in four species of sea slugs (Mollusca, Gastropoda, Opisthobranchia, Nudibranchia): Tritonia diomedea, Melibe leonina, Dendronotus iris, and Hermissenda crassicornis. We found consistent patterns of GABA immunoreactivity in the pedal and cerebral-pleural ganglia across species. In particular, there were bilateral clusters in the lateral and medial regions of the dorsal surface of the cerebral ganglia as well as a cluster on the ventral surface of the pedal ganglia. There were also individual GABA-ir neurons that were recognizable across species. The invariant presence of these individual neurons and clusters suggests that they are homologous, although there were interspecies differences in the numbers of neurons in the clusters. The GABAergic system was largely restricted to the central nervous system, with the majority of axons confined to ganglionic connectives and commissures, suggesting a central, integrative role for GABA. GABA was a candidate inhibitory neurotransmitter for neurons in central pattern generator (CPG) circuits underlying swimming behaviors in these species, however none of the known swim CPG neurons were GABA-ir. Although the functions of these GABA-ir neurons are not known, it is clear that their presence has been strongly conserved across nudibranchs. Copyright © 2013 Wiley Periodicals, Inc.

  14. Neuronal Subset-Specific Migration and Axonal Wiring Mechanisms in the Developing Midbrain Dopamine System

    Directory of Open Access Journals (Sweden)

    Sara Brignani

    2017-07-01

    Full Text Available The midbrain dopamine (mDA system is involved in the control of cognitive and motor behaviors, and is associated with several psychiatric and neurodegenerative diseases. mDA neurons receive diverse afferent inputs and establish efferent connections with many brain areas. Recent studies have unveiled a high level of molecular and cellular heterogeneity within the mDA system with specific subsets of mDA neurons displaying select molecular profiles and connectivity patterns. During mDA neuron development, molecular differences between mDA neuron subsets allow the establishment of subset-specific afferent and efferent connections and functional roles. In this review, we summarize and discuss recent work defining novel mDA neuron subsets based on specific molecular signatures. Then, molecular cues are highlighted that control mDA neuron migration during embryonic development and that facilitate the formation of selective patterns of efferent connections. The review focuses largely on studies that show differences in these mechanisms between different subsets of mDA neurons and for which in vivo data is available, and is concluded by a section that discusses open questions and provides directions for further research.

  15. A Dynamic Bayesian Model for Characterizing Cross-Neuronal Interactions During Decision-Making.

    Science.gov (United States)

    Zhou, Bo; Moorman, David E; Behseta, Sam; Ombao, Hernando; Shahbaba, Babak

    2016-01-01

    The goal of this paper is to develop a novel statistical model for studying cross-neuronal spike train interactions during decision making. For an individual to successfully complete the task of decision-making, a number of temporally-organized events must occur: stimuli must be detected, potential outcomes must be evaluated, behaviors must be executed or inhibited, and outcomes (such as reward or no-reward) must be experienced. Due to the complexity of this process, it is likely the case that decision-making is encoded by the temporally-precise interactions between large populations of neurons. Most existing statistical models, however, are inadequate for analyzing such a phenomenon because they provide only an aggregated measure of interactions over time. To address this considerable limitation, we propose a dynamic Bayesian model which captures the time-varying nature of neuronal activity (such as the time-varying strength of the interactions between neurons). The proposed method yielded results that reveal new insight into the dynamic nature of population coding in the prefrontal cortex during decision making. In our analysis, we note that while some neurons in the prefrontal cortex do not synchronize their firing activity until the presence of a reward, a different set of neurons synchronize their activity shortly after stimulus onset. These differentially synchronizing sub-populations of neurons suggests a continuum of population representation of the reward-seeking task. Secondly, our analyses also suggest that the degree of synchronization differs between the rewarded and non-rewarded conditions. Moreover, the proposed model is scalable to handle data on many simultaneously-recorded neurons and is applicable to analyzing other types of multivariate time series data with latent structure. Supplementary materials (including computer codes) for our paper are available online.

  16. Two-population model for medial temporal lobe neurons: The vast majority are almost silent.

    Science.gov (United States)

    Magyar, Andrew; Collins, John

    2015-07-01

    Recordings in the human medial temporal lobe have found many neurons that respond to pictures (and related stimuli) of just one particular person of those presented. It has been proposed that these are concept cells, responding to just a single concept. However, a direct experimental test of the concept cell idea appears impossible, because it would need the measurement of the response of each cell to enormous numbers of other stimuli. Here we propose a new statistical method for analysis of the data that gives a more powerful way to analyze how close data are to the concept-cell idea. Central to the model is the neuronal sparsity, defined as the total fraction of stimuli that elicit an above-threshold response in the neuron. The model exploits the large number of sampled neurons to give sensitivity to situations where the average response sparsity is much less than one response for the number of presented stimuli. We show that a conventional model where a single sparsity is postulated for all neurons gives an extremely poor fit to the data. In contrast, a model with two dramatically different populations gives an excellent fit to data from the hippocampus and entorhinal cortex. In the hippocampus, one population has 7% of the cells with a 2.6% sparsity. But a much larger fraction (93%) respond to only 0.1% of the stimuli. This can result in an extreme bias in the responsiveness of reported neurons compared with a typical neuron. Finally, we show how to allow for the fact that some identified units correspond to multiple neurons and find that our conclusions at the neural level are quantitatively changed but strengthened, with an even stronger difference between the two populations.

  17. The Glutamatergic System in Primary Somatosensory Neurons and Its Involvement in Sensory Input-Dependent Plasticity.

    Science.gov (United States)

    Fernández-Montoya, Julia; Avendaño, Carlos; Negredo, Pilar

    2017-12-27

    Glutamate is the most common neurotransmitter in both the central and the peripheral nervous system. Glutamate is present in all types of neurons in sensory ganglia, and is released not only from their peripheral and central axon terminals but also from their cell bodies. Consistently, these neurons express ionotropic and metabotropic receptors, as well as other molecules involved in the synthesis, transport and release of the neurotransmitter. Primary sensory neurons are the first neurons in the sensory channels, which receive information from the periphery, and are thus key players in the sensory transduction and in the transmission of this information to higher centers in the pathway. These neurons are tightly enclosed by satellite glial cells, which also express several ionotropic and metabotropic glutamate receptors, and display increases in intracellular calcium accompanying the release of glutamate. One of the main interests in our group has been the study of the implication of the peripheral nervous system in sensory-dependent plasticity. Recently, we have provided novel evidence in favor of morphological changes in first- and second-order neurons of the trigeminal system after sustained alterations of the sensory input. Moreover, these anatomical changes are paralleled by several molecular changes, among which those related to glutamatergic neurotransmission are particularly relevant. In this review, we will describe the state of the art of the glutamatergic system in sensory ganglia and its involvement in input-dependent plasticity, a fundamental ground for advancing our knowledge of the neural mechanisms of learning and adaptation, reaction to injury, and chronic pain.

  18. Comparison of Langevin and Markov channel noise models for neuronal signal generation.

    Science.gov (United States)

    Sengupta, B; Laughlin, S B; Niven, J E

    2010-01-01

    The stochastic opening and closing of voltage-gated ion channels produce noise in neurons. The effect of this noise on the neuronal performance has been modeled using either an approximate or Langevin model based on stochastic differential equations or an exact model based on a Markov process model of channel gating. Yet whether the Langevin model accurately reproduces the channel noise produced by the Markov model remains unclear. Here we present a comparison between Langevin and Markov models of channel noise in neurons using single compartment Hodgkin-Huxley models containing either Na+ and K+, or only K+ voltage-gated ion channels. The performance of the Langevin and Markov models was quantified over a range of stimulus statistics, membrane areas, and channel numbers. We find that in comparison to the Markov model, the Langevin model underestimates the noise contributed by voltage-gated ion channels, overestimating information rates for both spiking and nonspiking membranes. Even with increasing numbers of channels, the difference between the two models persists. This suggests that the Langevin model may not be suitable for accurately simulating channel noise in neurons, even in simulations with large numbers of ion channels.

  19. 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

  20. Bidirectional communication between sensory neurons and osteoblasts in an in vitro coculture system.

    Science.gov (United States)

    Kodama, Daisuke; Hirai, Takao; Kondo, Hisataka; Hamamura, Kazunori; Togari, Akifumi

    2017-02-01

    Recent studies have revealed that the sensory nervous system is involved in bone metabolism. However, the mechanism of communication between neurons and osteoblasts is yet to be elucidated. In this study, we investigated the signaling pathways between sensory neurons of the dorsal root ganglion (DRG) and the osteoblast-like MC3T3-E1 cells using an in vitro coculture system. Our findings indicate that signal transduction from DRG-derived neurons to MC3T3-E1 cells is suppressed by antagonists of the AMPA receptor and the NK 1 receptor. Conversely, signal transduction from MC3T3-E1 cells to DRG-derived neurons is suppressed by a P2X 7 receptor antagonist. Our results suggest that these cells communicate with each other by exocytosis of glutamate, substance P in the efferent signal, and ATP in the afferent signal. © 2017 Federation of European Biochemical Societies.

  1. Dynamics and transitions of firing patterns in deterministic and stochastic neuronal systems

    Energy Technology Data Exchange (ETDEWEB)

    Lu Qishao [School of Science, Beijing University of Aeronautics and Astronautics, Beijing 100083 (China)], E-mail: qishaolu@hotmail.com; Yang Zhuoqin; Duan Lixia [School of Science, Beijing University of Aeronautics and Astronautics, Beijing 100083 (China); Gu Huaguang; Ren Wei [Institute of Space Medico-Engineering, P.O. Box 5104, Branch 15, Beijing 100094 (China)

    2009-04-30

    Some recent work on experimental and theoretical studies on complex firing patterns of neurons and their dynamical mechanisms is reviewed. At first, experimental results on various neural firings and the bifurcation scenarios of ISI series are discovered in neural pacemakers. Next, a thorough analysis on dynamical behaviour and transitions of neuronal firing patterns, including the period-adding bursting sequence without chaos, the integer multiple firing and GWN-induced firing activities, are demonstrated in both the deterministic and stochastic Chay neuronal systems by means of the bifurcation theory and fast/slow dynamics. Finally, the parameter regions for different types of bursting as well as their transitions in the Chay and ML neuronal systems are presented.

  2. Modeling Neurological Disease by Rapid Conversion of Human Urine Cells into Functional Neurons

    Directory of Open Access Journals (Sweden)

    Shu-Zhen Zhang

    2016-01-01

    Full Text Available Somatic cells can be directly converted into functional neurons by ectopic expression of defined factors and/or microRNAs. Since the first report of conversion mouse embryonic fibroblasts into functional neurons, the postnatal mouse, and human fibroblasts, astroglia, hepatocytes, and pericyte-derived cells have been converted into functional dopaminergic and motor neurons both in vitro and in vivo. However, it is invasive to get all these materials. In the current study, we provide a noninvasive approach to obtain directly reprogrammed functional neurons by overexpression of the transcription factors Ascl1, Brn2, NeuroD, c-Myc, and Myt1l in human urine cells. These induced neuronal (iN cells could express multiple neuron-specific proteins and generate action potentials. Moreover, urine cells from Wilson’s disease (WD patient could also be directly converted into neurons. In conclusion, generation of iN cells from nonneural lineages is a feasible and befitting approach for neurological disease modeling.

  3. Population density models of integrate-and-fire neurons with jumps: well-posedness.

    Science.gov (United States)

    Dumont, Grégory; Henry, Jacques

    2013-09-01

    In this paper we study the well-posedness of different models of population of leaky integrate-and-fire neurons with a population density approach. The synaptic interaction between neurons is modeled by a potential jump at the reception of a spike. We study populations that are self excitatory or self inhibitory. We distinguish the cases where this interaction is instantaneous from the one where there is a repartition of conduction delays. In the case of a bounded density of delays both excitatory and inhibitory population models are shown to be well-posed. But without conduction delay the solution of the model of self excitatory neurons may blow up. We analyze the different behaviours of the model with jumps compared to its diffusion approximation.

  4. On-demand activation of the endocannabinoid system in the control of neuronal excitability and epileptiform seizures.

    Science.gov (United States)

    Lutz, Beat

    2004-11-01

    Neurons intensively exchange information among each other using both inhibitory and excitatory neurotransmitters. However, if the balance of excitation and inhibition is perturbed, the intensity of excitatory transmission may exceed a certain threshold and epileptic seizures can occur. As the occurrence of epilepsy in the human population is about 1%, the search for therapeutic targets to alleviate seizures is warranted. Extracts of Cannabis sativa have a long history in the treatment of various neurological diseases, including epilepsy. However, cannabinoids have been reported to exert both pro- and anti-convulsive activities. The recent progress in understanding the endogenous cannabinoid system has allowed new insights into these opposing effects of cannabinoids. When excessive neuronal activity occurs, endocannabinoids are generated on demand and activate cannabinoid type 1 (CB1) receptors. Using mice lacking CB1 receptors in principal forebrain neurons in a model of epileptiform seizures, it was shown that CB1 receptors expressed on excitatory glutamatergic neurons mediate the anti-convulsive activity of endocannabinoids. Systemic activation of CB1 receptors by exogenous cannabinoids, however, are anti- or pro-convulsive, depending on the seizure model used. The pro-convulsive activity of exogenous cannabinoids might be explained by the notion that CB1 receptors expressed on inhibitory GABAergic neurons are also activated, leading to a decreased release of GABA, and to a concomitant increase in seizure susceptibility. The concept that the endogenous cannabinoid system is activated on demand suggests that a promising strategy to alleviate seizure frequency is the enhancement of endocannabinoid levels by inhibiting the cellular uptake and the degradation of these endogenous compounds.

  5. The Importance of Non-neuronal Cell Types in hiPSC-Based Disease Modeling and Drug Screening

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    David M. Gonzalez

    2017-12-01

    Full Text Available Current applications of human induced pluripotent stem cell (hiPSC technologies in patient-specific models of neurodegenerative and neuropsychiatric disorders tend to focus on neuronal phenotypes. Here, we review recent efforts toward advancing hiPSCs toward non-neuronal cell types of the central nervous system (CNS and highlight their potential use for the development of more complex in vitro models of neurodevelopment and disease. We present evidence from previous works in both rodents and humans of the importance of these cell types (oligodendrocytes, microglia, astrocytes in neurological disease and highlight new hiPSC-based models that have sought to explore these relationships in vitro. Lastly, we summarize efforts toward conducting high-throughput screening experiments with hiPSCs and propose methods by which new screening platforms could be designed to better capture complex relationships between neural cell populations in health and disease.

  6. 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.

  7. Ongoing spontaneous activity controls access to consciousness: a neuronal model for inattentional blindness.

    Science.gov (United States)

    Dehaene, Stanislas; Changeux, Jean-Pierre

    2005-05-01

    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. A metabolomic comparison of mouse models of the Neuronal Ceroid Lipofuscinoses

    International Nuclear Information System (INIS)

    Salek, Reza M.; Pears, Michael R.; Cooper, Jonathan D.; Mitchison, Hannah M.; Pearce, David A.; Mortishire-Smith, Russell J.; Griffin, Julian L.

    2011-01-01

    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 γ-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.

  9. 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.

  10. 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.

  11. 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. 2009 Elsevier Inc. All rights reserved.

  12. 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.

  13. One-dimensional map-based neuron model: A logistic modification

    International Nuclear Information System (INIS)

    Mesbah, Samineh; Moghtadaei, Motahareh; Hashemi Golpayegani, Mohammad Reza; Towhidkhah, Farzad

    2014-01-01

    A one-dimensional map is proposed for modeling some of the neuronal activities, including different spiking and bursting behaviors. The model is obtained by applying some modifications on the well-known Logistic map and is named the Modified and Confined Logistic (MCL) model. Map-based neuron models are known as phenomenological models and recently, they are widely applied in modeling tasks due to their computational efficacy. Most of discrete map-based models involve two variables representing the slow-fast prototype. There are also some one-dimensional maps, which can replicate some of the neuronal activities. However, the existence of four bifurcation parameters in the MCL model gives rise to reproduction of spiking behavior with control over the frequency of the spikes, and imitation of chaotic and regular bursting responses concurrently. It is also shown that the proposed model has the potential to reproduce more realistic bursting activity by adding a second variable. Moreover the MCL model is able to replicate considerable number of experimentally observed neuronal responses introduced in Izhikevich (2004) [23]. Some analytical and numerical analyses of the MCL model dynamics are presented to explain the emersion of complex dynamics from this one-dimensional map

  14. 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.

  15. 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.

  16. Role of Serotonin Neurons in L-DOPA- and Graft-Induced Dyskinesia in a Rat Model of Parkinson's Disease

    Directory of Open Access Journals (Sweden)

    Eunju Shin

    2012-01-01

    Full Text Available L-DOPA, the most effective drug to treat motor symptoms of Parkinson's disease, causes abnormal involuntary movements, limiting its use in advanced stages of the disease. An increasing body of evidence points to the serotonin system as a key player in the appearance of L-DOPA-induced dyskinesia (LID. In fact, exogenously administered L-DOPA can be taken up by serotonin neurons, converted to dopamine and released as a false transmitter, contributing to pulsatile stimulation of striatal dopamine receptors. Accordingly, destruction of serotonin fibers or silencing serotonin neurons by serotonin agonists could counteract LID in animal models. Recent clinical work has also shown that serotonin neurons are present in the caudate/putamen of patients grafted with embryonic ventral mesencephalic cells, producing intense serotonin hyperinnervation. These patients experience graft-induced dyskinesia (GID, a type of dyskinesia phenotypically similar to the one induced by L-DOPA but independent from its administration. Interestingly, the 5-HT1A receptor agonist buspirone has been shown to suppress GID in these patients, suggesting that serotonin neurons might be involved in the etiology of GID as for LID. In this paper we will discuss the experimental and clinical evidence supporting the involvement of the serotonin system in both LID and GID.

  17. Modeling of multisensory convergence with a network of spiking neurons: a reverse engineering approach.

    Science.gov (United States)

    Lim, Hun Ki; Keniston, Leslie P; Cios, Krzysztof J

    2011-07-01

    Multisensory processing in the brain underlies a wide variety of perceptual phenomena, but little is known about the underlying mechanisms of how multisensory neurons are formed. This lack of knowledge is due to the difficulty for biological experiments to manipulate and test the parameters of multisensory convergence, the first and definitive step in the multisensory process. Therefore, by using a computational model of multisensory convergence, this study seeks to provide insight into the mechanisms of multisensory convergence. To reverse-engineer multisensory convergence, we used a biologically realistic neuron model and a biology-inspired plasticity rule, but did not make any a priori assumptions about multisensory properties of neurons in the network. The network consisted of two separate projection areas that converged upon neurons in a third area, and stimulation involved activation of one of the projection areas (or the other) or their combination. Experiments consisted of two parts: network training and multisensory simulation. Analyses were performed, first, to find multisensory properties in the simulated networks; second, to reveal properties of the network using graph theoretical approach; and third, to generate hypothesis related to the multisensory convergence. The results showed that the generation of multisensory neurons related to the topological properties of the network, in particular, the strengths of connections after training, was found to play an important role in forming and thus distinguishing multisensory neuron types. © 2011 IEEE

  18. 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.

  19. 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.

  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. Adaptation of velocity encoding in synaptically coupled neurons in the fly visual system.

    Science.gov (United States)

    Kalb, Julia; Egelhaaf, Martin; Kurtz, Rafael

    2008-09-10

    Although many adaptation-induced effects on neuronal response properties have been described, it is often unknown at what processing stages in the nervous system they are generated. We focused on fly visual motion-sensitive neurons to identify changes in response characteristics during prolonged visual motion stimulation. By simultaneous recordings of synaptically coupled neurons, we were able to directly compare adaptation-induced effects at two consecutive processing stages in the fly visual motion pathway. This allowed us to narrow the potential sites of adaptation effects within the visual system and to relate them to the properties of signal transfer between neurons. Motion adaptation was accompanied by a response reduction, which was somewhat stronger in postsynaptic than in presynaptic cells. We found that the linear representation of motion velocity degrades during adaptation to a white-noise velocity-modulated stimulus. This effect is caused by an increasingly nonlinear velocity representation rather than by an increase of noise and is similarly strong in presynaptic and postsynaptic neurons. In accordance with this similarity, the dynamics and the reliability of interneuronal signal transfer remained nearly constant. Thus, adaptation is mainly based on processes located in the presynaptic neuron or in more peripheral processing stages. In contrast, changes of transfer properties at the analyzed synapse or in postsynaptic spike generation contribute little to changes in velocity coding during motion adaptation.

  3. 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.

  4. 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.

  5. Neuronal models for evaluation of proliferation in vitro using high content screening

    International Nuclear Information System (INIS)

    Mundy, William R.; Radio, Nicholas M.; Freudenrich, Theresa M.

    2010-01-01

    In vitro test methods can provide a rapid approach for the screening of large numbers of chemicals for their potential to produce toxicity (hazard identification). In order to identify potential developmental neurotoxicants, a battery of in vitro tests for neurodevelopmental processes such as cell proliferation, differentiation, growth, and synaptogenesis has been proposed. The development of in vitro approaches for toxicity testing will require choosing a model system that is appropriate to the endpoint of concern. This study compared several cell lines as models for neuronal proliferation. The sensitivities of neuronal cell lines derived from three species (PC12, rat; N1E-115, mouse; SH-SY5Y, human) to chemicals known to affect cell proliferation were assessed using a high content screening system. After optimizing conditions for cell growth in 96-well plates, proliferation was measured as the incorporation of 5-bromo-2'-deoxyuridine (BrdU) into replicating DNA during S phase. BrdU-labeled cells were detected by immunocytochemistry and cell counts were obtained using automated image acquisition and analysis. The three cell lines showed approximately 30-40% of the population in S phase after a 4 h pulse of BrdU. Exposure to the DNA polymerase inhibitor aphidicolin for 20 h prior to the 4 h pulse of BrdU significantly decreased proliferation in all three cell lines. The sensitivities of the cell lines were compared by exposure to eight chemicals known to affect proliferation (positive controls) and determination of the concentration inhibiting proliferation by 50% of control (I 50 ). PC12 cells were the most sensitive to chemicals; 6 out of 8 chemicals (aphidicolin, cadmium, cytosine arabinoside, dexamethasone, 5-fluorouracil, and methylmercury) inhibited proliferation at the concentrations tested. SH-SY5Y cells were somewhat less sensitive to chemical effects, with five out of eight chemicals inhibiting proliferation; dexamethasone had no effect, and cadmium

  6. Development of neuronal and sensorimotor systems in the absence of gravity: Neurobiological research on four soyuz taxi flights to the international space station

    Science.gov (United States)

    Horn, Eberhard R.; Dournon, Christian; Frippiat, Jean-Pol; Marco, Roberto; Böser, Sybille; Kirschnick, Uta

    2007-09-01

    Neurobiological experiments on 4 animal species (Xenopus laevis, Pleurodeles waltl, Drosophila melanogaster, Acheta domesticus) were performed to study effects of microgravity on development and aging of neuronal, sensory and motor systems. Animal models were selected according to their suitability to answer questions concerning μg-effects on neuroanatomy, neuronal activity, and behaviour. The studies were performed on the Soyuz Taxi flights Andromède, Cervantes, Eneide and LDM-TMA8/TMA7. Observations from these flights include: (1) In tadpoles and cricket larvae, morphological features of sensory cells and neurons are rarely affected by microgravity. (2) In crickets, in-flight fertilization was successful; after landing, flight larvae hatched earlier than ground reared siblings. (3) In crickets, proliferation of peptidergic neurons and their projection patterns within the nervous system were not affected by microgravity. (4) During aging, the impact of microgravity on peptidergic neurons of male Drosophila was limited to the size of cell body. (5) In Xenopus, neurophysiological features of the spinal motor system during fictive swimming were partially modified. (6) In Xenopus tadpoles, the vestibuloocular reflex was affected in an age-related manner. Modifications were also related to the occurrence of a tail lordosis induced by microgravity. It is concluded that adaptation to microgravity during development and aging is mainly based on physiological mechanisms within the central nervous system while structural modifications of the sensory and neuronal system contribute less.

  7. 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.

  8. 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...

  9. Stimulus conflation and tuning selectivity in V4 neurons: a model of visual crowding.

    Science.gov (United States)

    Motter, Brad C

    2018-01-01

    Visual crowding is a fundamental constraint on our ability to identify peripheral objects in cluttered environments. This study proposes a descriptive model for understanding crowding based on the tuning selectivity for stimuli within the receptive field (RF) and examines potential neural correlates in cortical area V4. For V4 neurons, optimally sized, letter-like stimuli are much smaller than the RF. This permits stimulus conflation, the fusing of separate objects into a single identity, to occur within the RF of single neurons. Flanking interactions between such stimuli were found to be limited to the RF. The response to an optimal stimulus centered in the neuron's RF, is suppressed by the simultaneous presentation of flanking stimuli within the RF. The degree of suppression is a function of the neuron's stimulus tuning properties and the position of the flanker within the RF. A single neuron may show suppression or facilitation depending on the detailed stimulus conditions and the relationship to tuning selectivity. Loss of activity in the set of neurons tuned to a particular stimulus alters its overall representation and potential identification, thus forming a basis for visual crowding effects. The mechanisms that determine the outcome of conflation are associated with object identification, and are not some other independent visual phenomena.

  10. Modeling Protein Aggregation and the Heat Shock Response in ALS iPSC-Derived Motor Neurons.

    Science.gov (United States)

    Seminary, Emily R; Sison, Samantha L; Ebert, Allison D

    2018-01-01

    Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disorder caused by the selective loss of the upper and lower motor neurons. Only 10% of all cases are caused by a mutation in one of the two dozen different identified genes, while the remaining 90% are likely caused by a combination of as yet unidentified genetic and environmental factors. Mutations in C9orf72, SOD1 , or TDP-43 are the most common causes of familial ALS, together responsible for at least 60% of these cases. Remarkably, despite the large degree of heterogeneity, all cases of ALS have protein aggregates in the brain and spinal cord that are immunopositive for SOD1, TDP-43, OPTN, and/or p62. These inclusions are normally prevented and cleared by heat shock proteins (Hsps), suggesting that ALS motor neurons have an impaired ability to induce the heat shock response (HSR). Accordingly, there is evidence of decreased induction of Hsps in ALS mouse models and in human post-mortem samples compared to unaffected controls. However, the role of Hsps in protein accumulation in human motor neurons has not been fully elucidated. Here, we generated motor neuron cultures from human induced pluripotent stem cell (iPSC) lines carrying mutations in SOD1, TDP-43 , or C9orf72 . In this study, we provide evidence that despite a lack of overt motor neuron loss, there is an accumulation of insoluble, aggregation-prone proteins in iPSC-derived motor neuron cultures but that content and levels vary with genetic background. Additionally, although iPSC-derived motor neurons are generally capable of inducing the HSR when exposed to a heat stress, protein aggregation itself is not sufficient to induce the HSR or stress granule formation. We therefore conclude that ALS iPSC-derived motor neurons recapitulate key early pathological features of the disease and fail to endogenously upregulate the HSR in response to increased protein burden.

  11. Activation of hypothalamic RIP-Cre neurons promotes beiging of WAT via sympathetic nervous system.

    Science.gov (United States)

    Wang, Baile; Li, Ang; Li, Xiaomu; Ho, Philip Wl; Wu, Donghai; Wang, Xiaoqi; Liu, Zhuohao; Wu, Kelvin Kl; Yau, Sonata Sy; Xu, Aimin; Cheng, Kenneth Ky

    2018-04-01

    Activation of brown adipose tissue (BAT) and beige fat by cold increases energy expenditure. Although their activation is known to be differentially regulated in part by hypothalamus, the underlying neural pathways and populations remain poorly characterized. Here, we show that activation of rat-insulin-promoter-Cre (RIP-Cre) neurons in ventromedial hypothalamus (VMH) preferentially promotes recruitment of beige fat via a selective control of sympathetic nervous system (SNS) outflow to subcutaneous white adipose tissue (sWAT), but has no effect on BAT Genetic ablation of APPL2 in RIP-Cre neurons diminishes beiging in sWAT without affecting BAT, leading to cold intolerance and obesity in mice. Such defects are reversed by activation of RIP-Cre neurons, inactivation of VMH AMPK, or treatment with a β3-adrenergic receptor agonist. Hypothalamic APPL2 enhances neuronal activation in VMH RIP-Cre neurons and raphe pallidus, thereby eliciting SNS outflow to sWAT and subsequent beiging. These data suggest that beige fat can be selectively activated by VMH RIP-Cre neurons, in which the APPL2-AMPK signaling axis is crucial for this defending mechanism to cold and obesity. © 2018 The Authors.

  12. A principled dimension-reduction method for the population density approach to modeling networks of neurons with synaptic dynamics.

    Science.gov (United States)

    Ly, Cheng

    2013-10-01

    The population density approach to neural network modeling has been utilized in a variety of contexts. The idea is to group many similar noisy neurons into populations and track the probability density function for each population that encompasses the proportion of neurons with a particular state rather than simulating individual neurons (i.e., Monte Carlo). It is commonly used for both analytic insight and as a time-saving computational tool. The main shortcoming of this method is that when realistic attributes are incorporated in the underlying neuron model, the dimension of the probability density function increases, leading to intractable equations or, at best, computationally intensive simulations. Thus, developing principled dimension-reduction methods is essential for the robustness of these powerful methods. As a more pragmatic tool, it would be of great value for the larger theoretical neuroscience community. For exposition of this method, we consider a single uncoupled population of leaky integrate-and-fire neurons receiving external excitatory synaptic input only. We present a dimension-reduction method that reduces a two-dimensional partial differential-integral equation to a computationally efficient one-dimensional system and gives qualitatively accurate results in both the steady-state and nonequilibrium regimes. The method, termed modified mean-field method, is based entirely on the governing equations and not on any auxiliary variables or parameters, and it does not require fine-tuning. The principles of the modified mean-field method have potential applicability to more realistic (i.e., higher-dimensional) neural networks.

  13. 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

  14. Computational modeling of direct neuronal recruitment during intracortical microstimulation in somatosensory cortex

    Science.gov (United States)

    Overstreet, C. K.; Klein, J. D.; Helms Tillery, S. I.

    2013-12-01

    Objective. Electrical stimulation of cortical tissue could be used to deliver sensory information as part of a neuroprosthetic device, but current control of the location, resolution, quality, and intensity of sensations elicited by intracortical microstimulation (ICMS) remains inadequate for this purpose. One major obstacle to resolving this problem is the poor understanding of the neural activity induced by ICMS. Even with new imaging methods, quantifying the activity of many individual neurons within cortex is difficult. Approach. We used computational modeling to examine the response of somatosensory cortex to ICMS. We modeled the axonal arbors of eight distinct morphologies of interneurons and seven types of pyramidal neurons found in somatosensory cortex and identified their responses to extracellular stimulation. We then combined these axonal elements to form a multi-layered slab of simulated cortex and investigated the patterns of neural activity directly induced by ICMS. Specifically we estimated the number, location, and variety of neurons directly recruited by stimulation on a single penetrating microelectrode. Main results. The population of neurons activated by ICMS was dependent on both stimulation strength and the depth of the electrode within cortex. Strikingly, stimulation recruited interneurons and pyramidal neurons in very different patterns. Interneurons are primarily recruited within a dense, continuous region around the electrode, while pyramidal neurons were recruited in a sparse fashion both near the electrode and up to several millimeters away. Thus ICMS can lead to an unexpectedly complex spatial distribution of firing neurons. Significance. These results lend new insights to the complexity and range of neural activity that can be induced by ICMS. This work also suggests mechanisms potentially responsible for the inconsistency and unnatural quality of sensations initiated by ICMS. Understanding these mechanisms will aid in the design of

  15. Routes to Chaos Induced by a Discontinuous Resetting Process in a Hybrid Spiking Neuron Model.

    Science.gov (United States)

    Nobukawa, Sou; Nishimura, Haruhiko; Yamanishi, Teruya

    2018-01-10

    Several hybrid spiking neuron models combining continuous spike generation mechanisms and discontinuous resetting processes following spiking have been proposed. The Izhikevich neuron model, for example, can reproduce many spiking patterns. This model clearly possesses various types of bifurcations and routes to chaos under the effect of a state-dependent jump in the resetting process. In this study, we focus further on the relation between chaotic behaviour and the state-dependent jump, approaching the subject by comparing spiking neuron model versions with and without the resetting process. We first adopt a continuous two-dimensional spiking neuron model in which the orbit in the spiking state does not exhibit divergent behaviour. We then insert the resetting process into the model. An evaluation using the Lyapunov exponent with a saltation matrix and a characteristic multiplier of the Poincar'e map reveals that two types of chaotic behaviour (i.e. bursting chaotic spikes and near-period-two chaotic spikes) are induced by the resetting process. In addition, we confirm that this chaotic bursting state is generated from the periodic spiking state because of the slow- and fast-scale dynamics that arise when jumping to the hyperpolarization and depolarization regions, respectively.

  16. 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.

  17. Postnatal Gene Therapy Improves Spatial Learning Despite the Presence of Neuronal Ectopia in a Model of Neuronal Migration Disorder

    Directory of Open Access Journals (Sweden)

    Huaiyu Hu

    2016-11-01

    Full Text Available Patients with type II lissencephaly, a neuronal migration disorder with ectopic neurons, suffer from severe mental retardation, including learning deficits. There is no effective therapy to prevent or correct the formation of neuronal ectopia, which is presumed to cause cognitive deficits. We hypothesized that learning deficits were not solely caused by neuronal ectopia and that postnatal gene therapy could improve learning without correcting the neuronal ectopia formed during fetal development. To test this hypothesis, we evaluated spatial learning of cerebral cortex-specific protein O-mannosyltransferase 2 (POMT2, an enzyme required for O-mannosyl glycosylation knockout mice and compared to the knockout mice that were injected with an adeno-associated viral vector (AAV encoding POMT2 into the postnatal brains with Barnes maze. The data showed that the knockout mice exhibited reduced glycosylation in the cerebral cortex, reduced dendritic spine density on CA1 neurons, and increased latency to the target hole in the Barnes maze, indicating learning deficits. Postnatal gene therapy restored functional glycosylation, rescued dendritic spine defects, and improved performance on the Barnes maze by the knockout mice even though neuronal ectopia was not corrected. These results indicate that postnatal gene therapy improves spatial learning despite the presence of neuronal ectopia.

  18. Synaptic potentiation onto habenula neurons in the learned helplessness model of depression

    International Nuclear Information System (INIS)

    Li, B.; Schulz, D.; Piriz, J.; Mirrione, M.; Chung, C.H.; Proulx, C.D.; Schulz, D.; Henn, F.; Malinow, R.

    2011-01-01

    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.

  19. Synaptic potentiation onto habenula neurons in learned helplessness model of depression

    Science.gov (United States)

    Li, Bo; Piriz, Joaquin; Mirrione, Martine; Chung, ChiHye; Proulx, Christophe D.; Schulz, Daniela; Henn, Fritz; Malinow, Roberto

    2010-01-01

    The cellular basis of depressive disorders is poorly understood1. 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 (i.e. disappointment or anticipation of a negative outcome)2, 3, 4. LHb neurons project to and modulate dopamine-rich regions such as the ventral-tegmental area (VTA)2, 5 that control reward-seeking behavior6 and participate in depressive disorders7. Here we show in two learned helplessness models of depression that excitatory synapses onto LHb neurons projecting to the VTA are potentiated. Synaptic potentiation correlates with an animal’s helplessness behavior 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 on depressed patients8, 9, dramatically suppresses synaptic drive onto VTA-projecting LHb neurons in brain slices and can significantly reduce learned helplessness behavior in rats. Our results indicate that increased presynaptic action onto LHb neurons contributes to the rodent learned helplessness model of depression. PMID:21350486

  20. New neurons for injured brains? The emergence of new genetic model organisms to study brain regeneration.

    Science.gov (United States)

    Fernández-Hernández, Ismael; Rhiner, Christa

    2015-09-01

    Neuronal circuits in the adult brain have long been viewed as static and stable. However, research in the past 20 years has shown that specialized regions of the adult brain, which harbor adult neural stem cells, continue to produce new neurons in a wide range of species. Brain plasticity is also observed after injury. Depending on the extent and permissive environment of neurogenic regions, different organisms show great variability in their capacity to replace lost neurons by endogenous neurogenesis. In Zebrafish and Drosophila, the formation of new neurons from progenitor cells in the adult brain was only discovered recently. Here, we compare properties of adult neural stem cells, their niches and regenerative responses from mammals to flies. Current models of brain injury have revealed that specific injury-induced genetic programs and comparison of neuronal fitness are implicated in brain repair. We highlight the potential of these recently implemented models of brain regeneration to identify novel regulators of stem cell activation and regenerative neurogenesis. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons

    Science.gov (United States)

    Pecevski, Dejan; Buesing, Lars; Maass, Wolfgang

    2011-01-01

    An important open problem of computational neuroscience is the generic organization of computations in networks of neurons in the brain. We show here through rigorous theoretical analysis that inherent stochastic features of spiking neurons, in combination with simple nonlinear computational operations in specific network motifs and dendritic arbors, enable networks of spiking neurons to carry out probabilistic inference through sampling in general graphical models. In particular, it enables them to carry out probabilistic inference in Bayesian networks with converging arrows (“explaining away”) and with undirected loops, that occur in many real-world tasks. Ubiquitous stochastic features of networks of spiking neurons, such as trial-to-trial variability and spontaneous activity, are necessary ingredients of the underlying computational organization. We demonstrate through computer simulations that this approach can be scaled up to neural emulations of probabilistic inference in fairly large graphical models, yielding some of the most complex computations that have been carried out so far in networks of spiking neurons. PMID:22219717

  2. 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.

  3. Linked Gauss-Diffusion processes for modeling a finite-size neuronal network.

    Science.gov (United States)

    Carfora, M F; Pirozzi, E

    2017-11-01

    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.

  4. 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.

  5. Computational modeling of spike generation in serotonergic neurons of the dorsal raphe nucleus.

    Science.gov (United States)

    Tuckwell, Henry C; Penington, Nicholas J

    2014-07-01

    Serotonergic neurons of the dorsal raphe nucleus, with their extensive innervation of limbic and higher brain regions and interactions with the endocrine system have important modulatory or regulatory effects on many cognitive, emotional and physiological processes. They have been strongly implicated in responses to stress and in the occurrence of major depressive disorder and other psychiatric disorders. In order to quantify some of these effects, detailed mathematical models of the activity of such cells are required which describe their complex neurochemistry and neurophysiology. We consider here a single-compartment model of these neurons which is capable of describing many of the known features of spike generation, particularly the slow rhythmic pacemaking activity often observed in these cells in a variety of species. Included in the model are 11 kinds of ion channels: a fast sodium current INa, a delayed rectifier potassium current IKDR, a transient potassium current IA, a slow non-inactivating potassium current IM, a low-threshold calcium current IT, two high threshold calcium currents IL and IN, small and large conductance potassium currents ISK and IBK, a hyperpolarization-activated cation current IH and a leak current ILeak. In Sections 3-8, each current type is considered in detail and parameters estimated from voltage clamp data where possible. Three kinds of model are considered for the BK current and two for the leak current. Intracellular calcium ion concentration Cai is an additional component and calcium dynamics along with buffering and pumping is discussed in Section 9. The remainder of the article contains descriptions of computed solutions which reveal both spontaneous and driven spiking with several parameter sets. Attention is focused on the properties usually associated with these neurons, particularly long duration of action potential, steep upslope on the leading edge of spikes, pacemaker-like spiking, long-lasting afterhyperpolarization

  6. An Efficient and Versatile System for Visualization and Genetic Modification of Dopaminergic Neurons in Transgenic Mice.

    Directory of Open Access Journals (Sweden)

    Karsten Tillack

    Full Text Available The brain dopaminergic (DA system is involved in fine tuning many behaviors and several human diseases are associated with pathological alterations of the DA system such as Parkinson's disease (PD and drug addiction. Because of its complex network integration, detailed analyses of physiological and pathophysiological conditions are only possible in a whole organism with a sophisticated tool box for visualization and functional modification.Here, we have generated transgenic mice expressing the tetracycline-regulated transactivator (tTA or the reverse tetracycline-regulated transactivator (rtTA under control of the tyrosine hydroxylase (TH promoter, TH-tTA (tet-OFF and TH-rtTA (tet-ON mice, to visualize and genetically modify DA neurons. We show their tight regulation and efficient use to overexpress proteins under the control of tet-responsive elements or to delete genes of interest with tet-responsive Cre. In combination with mice encoding tet-responsive luciferase, we visualized the DA system in living mice progressively over time.These experiments establish TH-tTA and TH-rtTA mice as a powerful tool to generate and monitor mouse models for DA system diseases.

  7. Heterogeneous delay-induced asynchrony and resonance in a small-world neuronal network system

    Science.gov (United States)

    Yu, Wen-Ting; Tang, Jun; Ma, Jun; Yang, Xianqing

    2016-06-01

    A neuronal network often involves time delay caused by the finite signal propagation time in a given biological network. This time delay is not a homogenous fluctuation in a biological system. The heterogeneous delay-induced asynchrony and resonance in a noisy small-world neuronal network system are numerically studied in this work by calculating synchronization measure and spike interval distribution. We focus on three different delay conditions: double-values delay, triple-values delay, and Gaussian-distributed delay. Our results show the following: 1) the heterogeneity in delay results in asynchronous firing in the neuronal network, and 2) maximum synchronization could be achieved through resonance given that the delay values are integer or half-integer times of each other.

  8. Modeling chronic brain exposure to amphetamines using primary rat neuronal cortical cultures.

    Science.gov (United States)

    Nogueira, T B; da Costa Araújo, S; Carvalho, F; Pereira, F C; Fernandes, E; Bastos, M L; Costa, V M; Capela, J P

    2014-09-26

    Amphetamine-type psychostimulants (ATS) are used worldwide by millions of patients for several psychiatric disorders. Amphetamine (AMPH) and "ecstasy" (3,4-methylenedioxymethamphetamine or MDMA) are common drugs of abuse. The impact of chronic ATS exposure to neurons and brain aging is still undisclosed. Current neuronal culture paradigms are designed to access acute ATS toxicity. We report for the first time a model of chronic exposure to AMPH and MDMA using long-term rat cortical cultures. In two paradigms, ATS were applied to neurons at day 1 in vitro (DIV) (0, 1, 10 and 100 μM of each drug) up to 28 days (200 μM was applied to cultures up to 14 DIV). Our reincubation protocol assured no decrease in the neuronal media's drug concentration. Chronic exposure of neurons to concentrations equal to or above 100 μM of ATS up to 28 DIV promoted significant mitochondrial dysfunction and elicited neuronal death, which was not prevented by glutamate receptor antagonists at 14 DIV. ATS failed to promote accelerated senescence as no increase in β-galactosidase activity at 21 DIV was found. In younger cultures (4 or 8 DIV), AMPH promoted mitochondrial dysfunction and neuronal death earlier than MDMA. Overall, AMPH proved more toxic and was the only drug that decreased intraneuronal glutathione levels. Meanwhile, caspase 3 activity increased for either drug at 200 μM in younger cultures at 8 DIV, but not at 14 DIV. At 8 DIV, ATS promoted a significant change in the percentage of neurons and astroglia present in culture, promoting a global decrease in the number of both cells. Importantly, concentrations equal to or below 10 μM of either drug did not promote neuronal death or oxidative stress. Our paradigm of neuronal cultures long-term exposure to low micromolar concentrations of ATS closely reproduces the in vivo scenario, being valuable to study the chronic impact of ATS. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

  9. In vivo modeling of neuronal function, axonal impairment and connectivity in neurodegenerative and neuropsychiatric disorders using induced pluripotent stem cells.

    Science.gov (United States)

    Korecka, J A; Levy, S; Isacson, O

    2016-06-01

    Modeling neurological diseases using human embryonic or patient-derived induced pluripotent stem cells (iPSCs) improves the understanding of molecular and cellular changes underlying these diseases and can lead to new, potentially personalized therapies. Changes in expression of axon guidance cues and altered cytoskeletal maintenance have been implicated in neurodegenerative and neuropsychiatric disorders. To date, most of the iPSC patient-derived cellular dysfunction and phenotypic studies have been performed in vitro. To study the intrinsic axonal impairments and neuronal connectivity deficits in human disease iPSC-derived neurons we propose to graft these cells into the physiological three-dimensional multi-structural environment of the central nervous system of rodent models to obtain relevant in vivo data. Such human iPSC in vivo chimeric models can allow for neuronal maturation, capture neuropathological phenotypes of axonal and connectivity impairments, and serve as target engagement and drug validation studies using human cells, thus highly relevant for advancement of the drug development process in the late pre-clinical stages. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  10. Effects of Chronic Hypergravity on the Dopaminergic Neuronal System in Drosophila Melanogaster

    Science.gov (United States)

    Pelos, Andrew; Hosamani, Ravikumar; Bhattacharya, Sharmila

    2017-01-01

    Upon atmospheric exitre-entry and during training, astronauts are subjected to temporary periods of hypergravity, which has been implicated in the activation of oxidative stress pathways contributing to mitochondrial dysfunction and neuronal degeneration. The pathogenesis of Parkinsons disease and other neurodegenerative disorders is associated with oxidative damage to neurons involved in dopamine systems of the brain. Our study aims to examine the effects of a hypergravitational developmental environment on the degeneration of dopaminergic systems in Drosophila melanogaster. Male and female flies (Gal4-UAS transgenic line) were hatched and raised to adulthood in centrifugal hypergravity (97rpm, 3g). The nuclear expression of the reporter, Green Fluorescent Protein (GFP) is driven by the dopaminergic enzyme tyrosine hydroxylase (TH) promoter, allowing for the targeted visualization of dopamine producing neurons. After being raised to adulthood and kept in hypergravity until 18 days of age, flies were dissected and the expression of TH was measured by fluorescence confocal microscopy. TH expression in the fly brains was used to obtain counts of healthy dopaminergic neurons for flies raised in chronic hypergravity and control groups. Dopaminergic neuron expression data were compared with those of previous studies that limited hypergravity exposure to late life in order to determine the flies adaptability to the gravitational environment when raised from hatching through adulthood. Overall, we observed a significant effect of chronic hypergravity exposure contributing to deficits in dopaminergic neuron expression (p 0.003). Flies raised in 3g had on average lower dopaminergic neuron counts (mean 97.7) when compared with flies raised in 1g (mean 122.8). We suspect these lower levels of TH expression are a result of oxidative dopaminergic cell loss in flies raised in hypergravity. In future studies, we hope to further elucidate the mechanism by which hypergravity

  11. Chronic Hypergravity Induces Changes in the Dopaminergic Neuronal System in Drosophila Melanogaster

    Science.gov (United States)

    Pelos, Andrew; Hosamani, Ravikumar; Bhattacharya, Sharmila

    2017-01-01

    Upon atmospheric exitre-entry and during training, astronauts are subjected to temporary periods of hypergravity, which has been implicated in the activation of oxidative stress pathways contributing to mitochondrial dysfunction and neuronal degeneration. The pathogenesis of Parkinsons disease and other neurodegenerative disorders is associated with oxidative damage to neurons involved in dopamine systems of the brain. Our study aims to examine the effects of a hypergravitational developmental environment on the degeneration of dopaminergic systems in Drosophila melanogaster. Male and female flies (Gal4-UAS transgenic line) were hatched and raised to adulthood in centrifugal hypergravity (97rpm, 3g). The nuclear expression of the reporter, Green Fluorescent Protein (GFP) is driven by the dopaminergic enzyme tyrosine hydroxylase (TH) promoter, allowing for the targeted visualization of dopamine producing neurons. After being raised to adulthood and kept in hypergravity until 18 days of age, flies were dissected and the expression of TH was measured by fluorescence confocal microscopy. TH expression in the fly brains was used to obtain counts of healthy dopaminergic neurons for flies raised in chronic hypergravity and control groups. Dopaminergic neuron expression data were compared with those of previous studies that limited hypergravity exposure to late life in order to determine the flies adaptability to the gravitational environment when raised from hatching through adulthood. Overall, we observed a significant effect of chronic hypergravity exposure contributing to deficits in dopaminergic neuron expression (p 0.003). Flies raised in 3g had on average lower dopaminergic neuron counts (mean 97.7) when compared with flies raised in 1g (mean 122.8). We suspect these lower levels of TH expression are a result of oxidative dopaminergic cell loss in flies raised in hypergravity. In future studies, we hope to further elucidate the mechanism by which hypergravity

  12. The VD1/RPD2 neuronal system in the central nervous system of the pond snail Lymnaea stagnalis studied by in situ hybridization and immunocytochemistry.

    Science.gov (United States)

    Kerkhoven, R M; Croll, R P; Ramkema, M D; Van Minnen, J; Bogerd, J; Boer, H H

    1992-03-01

    VD1 and RPD2 are two giant neuropeptidergic neurons in the central nervous system (CNS) of the pond snail Lymnaea stagnalis. We wished to determine whether other central neurons in the CNS of L. stagnalis express the VD1/RPD2 gene. To this end, in situ hybridization with the cDNA probe of the VD1/RPD2 gene and immunocytochemistry with antisera specific to VD1 and RPD2 (the alpha 1-antiserum, Mab4H5 and ALMA 6) and to R15 (the alpha 1 and 16-mer antisera) were performed on alternate tissue sections. A VD1/RPD2 neuronal system comprising three classes of neurons (A1-A3) was found. All neurons of the system express the gene. Division into classes is based on immunocytochemical characteristics. Class A1 neurons (VD1 and RPD2) immunoreact with the alpha 1-antiserum, Mab4H5 and ALMA 6. Class A2 neurons (1-5 small and 1-5 medium sized neurons in the visceral and right parietal ganglion, and two clusters of small neurons and 5 medium-sized neurons in the cerebral ganglia) immunoreact with the alpha 1-antiserum and Mab4H5, but not with ALMA 6. Class A3 neurons (3-4 medium-sized neurons and a cluster of 4-5 small neurons located in the pedal ganglion) immunoreact with the alpha 1-antiserum only. All neurons of the system are immunonegative to the R15 antisera. The observations suggest that the neurons of the VD1/RPD2 system produce different sets of neuropeptides. A group of approximately 15 neurons (class B), scattered in the ganglia, immunostained with one or more of the antisera, but did not react with the cDNA probe in in situ hybridization.

  13. Homer1 knockdown protects dopamine neurons through regulating calcium homeostasis in an in vitro model of Parkinson's disease.

    Science.gov (United States)

    Chen, Tao; Yang, Yue-fan; Luo, Peng; Liu, Wei; Dai, Shu-hui; Zheng, Xin-rui; Fei, Zhou; Jiang, Xiao-fan

    2013-12-01

    Homer1 protein is an important scaffold protein at postsynaptic density and has been demonstrated to play a central role in calcium signaling in the central nervous system. The aim of this study was to investigate the effects of Homer1 knockdown on MPP(+) induced neuronal injury in cultured dopamine (DA) neurons. We found that down-regulating Homer1 expression with specific small interfering RNA (siRNA) significantly suppressed LDH release, reduced Propidium iodide (PI) or Hoechst staining, increased the number of tyrosine hydroxylase (TH) positive cells and DA uptake, and attenuated apoptotic and necrotic cell death after MPP(+) injury. Homer1 knockdown decreased intracellular reactive oxygen species (ROS) generation through inhibition of intracellular calcium overload, but did not affect the endogenous antioxidant enzyme activities. Calcium imaging was used to examine the changes of intracellular Ca(2+) concentration ([Ca(2+)]cyt) and Ca(2+) in endoplasmic reticulum (ER) ([Ca(2+)]ER), and the results showed that Homer1 siRNA transfection attenuated ER Ca(2+) release up to 120min after MPP(+) injury. Furthermore, decrease of [Ca(2+)]cyt induced by Homer1 knockdown in MPP(+) treated neurons was further enhanced by NMDA receptor antagonists MK-801 and AP-5, but not canonical transient receptor potential (TRPC) channel antagonist SKF-96365. l-type calcium antagonist isradipine but not nimodipine further inhibited intracellular calcium overload after MPP(+) insult in Homer1 down-regulated neurons. These results suggest that Homer1 knockdown has protective effects against neuronal injury in in vitro PD model by reducing calcium overload mediated ROS generation, and this protection may be dependent at least in part on the regulatory effects on the function of calcium channels in both plasma membrane and ER. © 2013.

  14. 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

  15. Studies on functional roles of the histaminergic neuron system by using pharmacological agents, knockout mice and positron emission tomography

    International Nuclear Information System (INIS)

    Watanabe, Takehiko; Yanai, Kazuhiko

    2001-01-01

    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)

  16. 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)

  17. Computational Model of a Positive BDNF Feedback Loop in Hippocampal Neurons Following Inhibitory Avoidance Training

    Science.gov (United States)

    Zhang, Yili; Smolen, Paul; Alberini, Cristina M.; Baxter, Douglas A.; Byrne, John H.

    2016-01-01

    Inhibitory avoidance (IA) training in rodents initiates a molecular cascade within hippocampal neurons. This cascade contributes to the transition of short- to long-term memory (i.e., consolidation). Here, a differential equation-based model was developed to describe a positive feedback loop within this molecular cascade. The feedback loop begins…

  18. The Effects of Guanfacine and Phenylephrine on a Spiking Neuron Model of Working Memory.

    Science.gov (United States)

    Duggins, Peter; Stewart, Terrence C; Choo, Xuan; Eliasmith, Chris

    2017-01-01

    We use a spiking neural network model of working memory (WM) capable of performing the spatial delayed response task (DRT) to investigate two drugs that affect WM: guanfacine (GFC) and phenylephrine (PHE). In this model, the loss of information over time results from changes in the spiking neural activity through recurrent connections. We reproduce the standard forgetting curve and then show that this curve changes in the presence of GFC and PHE, whose application is simulated by manipulating functional, neural, and biophysical properties of the model. In particular, applying GFC causes increased activity in neurons that are sensitive to the information currently being remembered, while applying PHE leads to decreased activity in these same neurons. Interestingly, these differential effects emerge from network-level interactions because GFC and PHE affect all neurons equally. We compare our model to both electrophysiological data from neurons in monkey dorsolateral prefrontal cortex and to behavioral evidence from monkeys performing the DRT. Copyright © 2016 Cognitive Science Society, Inc.

  19. 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.

  20. Inhibition of β-amyloid1-42 internalization attenuates neuronal death by stabilizing the endosomal-lysosomal system in rat cortical cultured neurons.

    Science.gov (United States)

    Song, M S; Baker, G B; Todd, K G; Kar, S

    2011-03-31

    A number of recent studies have indicated that accumulation of β amyloid (Aβ) peptides within neurons is an early event which may trigger degeneration of neurons and subsequent development of Alzheimer's disease (AD) pathology. However, very little is known about the internalization and/or subcellular sites involved in trafficking of Aβ peptides into the neurons that are vulnerable in AD pathology. To address this issue we evaluated internalization of fluoroscein conjugated Aβ1-42 (FAβ1-42) and subsequent alteration of endosomal-lysosomal (EL) markers such as cathepsin D, Rab5 and Rab7 in rat cortical cultured neurons. It is evident from our results that internalization of FAβ1-42, which occurred in a dose- and time-dependent manner, triggered degeneration of neurons along with increased levels and/or altered distribution of cathepsin D, Rab5 and Rab7. Our results further revealed that FAβ1-42 internalization was attenuated by phenylarsine oxide (a general inhibitor of endocytosis) and sucrose (an inhibitor of clathrin-mediated endocytosis) but not by antagonists of N-methyl-d-aspartate (NMDA) glutamate receptors. Additionally, inhibition of FAβ1-42 endocytosis not only protected neurons against toxicity but also reversed the altered levels/distributions of EL markers. These results, taken together, suggest that internalization of exogenous Aβ1-42, which is partly mediated via a clathrin-dependent process, can lead to degeneration of neurons, possibly by activating the EL system. Inhibition of FAβ endocytosis attenuated toxicity, thus suggesting a potential strategy for preventing loss of neurons in AD pathology. Copyright © 2011 IBRO. Published by Elsevier Ltd. All rights reserved.

  1. Development of a high-affinity GABA uptake system in embryonic amphibian spinal neurons.

    Science.gov (United States)

    Lamborghini, J E; Iles, A

    1985-11-01

    High-affinity uptake systems for amino acid neurotransmitter precursors have been highly correlated with the use of the particular amino acid or its derivative as a transmitter. We have found interneurons in the Xenopus embryo spinal cord which accumulate GABA by a high-affinity uptake system. They originate near the end of gastrulation and their ability to accumulate GABA first appears at the early tail bud stage. By position and appearance they are comparable to some of the embryonic interneurons described by A. Roberts and J. D. W. Clarke (1982, Phil. Trans. R. Soc. London Ser. B 296, 195-212). GABA-accumulating neurons also develop in dissociated cell cultures made from the presumptive spinal cord of neural plate stage Xenopus embryos. GABA accumulation in cultured neurons, as in cells in vivo, occurs via a high-affinity uptake system; GABA-accumulating cells have the same time of origin as the cells in vivo, and the ability to accumulate GABA in the population of cultured neurons appears at a time equivalent to that observed in intact sibling embryos. Thus it seems likely that the population of GABA-accumulating neurons developing in cell culture corresponds to the GABA-accumulating interneurons in vivo. The development of these neurons in dissociated cell cultures permits perturbation experiments that would be difficult to perform in vivo. We have examined the development of high-affinity GABA uptake in conditions that permit no electrical impulse activity in the cultures. The onset and extent of development of GABA accumulation in the neuronal population are normal under these conditions.

  2. Self-organization of orientation maps in a formal neuron model using a cluster learning rule.

    Science.gov (United States)

    Kuroiwa, J; Inawashiro, S; Miyake, S; Aso, H

    2000-01-01

    Self-organization of orientation maps due to external stimuli in the primary visual area of the cerebral cortex is studied in a two-layered neural network which consists of formal neuron models with a sigmoidal output function. A cluster learning rule is proposed as an extended Hebbian learning rule, where a modification of synaptic connections is influenced by an activation of neighboring output neurons. By making use of self-consistent Monte Carlo method, we evaluate output responses of neurons against explicit inputs after the learning. An orientation map calculated from the output responses reproduces characteristic features of biological ones. Moreover quantitative analysis of our results are consistent with those of experimental results. It is shown that the cluster learning rule plays an important role in forming smooth changes of preferred orientations.

  3. Tyrosinase-Expressing Neuronal Cell Line as in Vitro Model of Parkinson’s Disease

    Science.gov (United States)

    Hasegawa, Takafumi

    2010-01-01

    Oxidized metabolites of dopamine known as dopamine quinone derivatives are thought to play a pivotal role in the degeneration of nigrostriatal dopaminergic neurons in Parkinson’s disease. Although such quinone derivatives are usually produced via the autoxidation of catecholamines, tyrosinase, which is a key enzyme in melanin biosynthesis via the production of DOPA and subsequent molecules, can potentially accelerate the induction of catecholamine quinone derivatives by its oxidase activity. We have developed neuronal cell lines in which the expression of human tyrosinase was inducible. Overexpression of tyrosinase resulted in increased intracellular dopamine content in association with the formation of melanin pigments in neuronal somata, which eventually causes apoptotic cell death. This cellular model will provide a useful tool for detailed analyses of the neurotoxicity of oxidized catechol metabolites. PMID:20480001

  4. Ontogeny of pioneer neurons in the antennal nervous system of the grasshopper Schistocerca gregaria.

    Science.gov (United States)

    Boyan, George; Ehrhardt, Erica

    2017-01-01

    The nervous system of the antenna of the grasshopper Schistocerca gregaria consists of two nerve tracts in which sensory cells project their axons to the brain. Each tract is pioneered early in embryogenesis by a pair of identified cells located apically in the antennal lumen. The pioneers are thought to originate in the epithelium of the antenna and then delaminate into the lumen where they commence axogenesis. However, unambiguous molecular identification of these cells in the epithelium, of an identifiable precursor, and of their mode of generation has been lacking. In this study, we have used immunolabeling against neuron-specific horseradish peroxidase and against Lachesin, a marker for differentiating epithelial cells, in combination with the nuclear stain DAPI, to identify the pioneers within the epithelium of the early embryonic antenna. We then track their delamination into the lumen as differentiated neurons. The pioneers are not labeled by the mesodermal/mesectodermal marker Mes3, consistent with an epithelial (ectodermal) origin. Intracellular dye injection, as well as labeling against the mitosis marker phospho-histone 3, identifies precursor cells in the epithelium, each associated with a column of cells. Culturing with the S-phase label 5-ethynyl-2'-deoxyuridine (EdU) shows that both a precursor and its column have incorporated the label, confirming a lineage relationship. Each set of pioneers can be shown to belong to a separate lineage of such epithelial cells, and the precursors remain and are proliferative after generating the pioneers. Analyses of mitotic spindle orientation then enable us to propose a model in which a precursor generates its pioneers asymmetrically via self-renewal.

  5. Neuronal nicotinic receptor agonists ameliorate spontaneous motor asymmetries and motor discoordination in a unilateral mouse model of Parkinson's disease.

    Science.gov (United States)

    Kucinski, Aaron; Wersinger, Scott; Stachowiak, Ewa K; Corso, Thomas D; Parry, Matthew J; Zhang, Jenny; Jordan, Kristen; Letchworth, Sharon; Bencherif, Merouane; Stachowiak, Michal K

    2013-10-01

    The degeneration of the nigrostriatal dopamine (DA) system underlies the motor deficits in Parkinson's disease (PD). In recent years, epidemiological reports that smokers have lower incidences of PD have brought attention to the nicotinic acetylcholine system as a potential target for novel therapeutics. Nicotine, an agonist of neuronal nicotinic receptors (NNRs), modulates functions relevant to PD via stimulation of dopaminergic transmission in the nigrostriatal pathway, particularly via activation of α6β2* and α4β2* NNRs. Recently, reduced support of DA neurons by neurotrophic growth factors has been described in PD. Fibroblast growth factor (FGF) is critical for the development and protection of adult DA neurons. In FGF-2 knockout mice and the related th-fgfr1(tk-) mouse model there is heightened sensitivity to DA neuronal oxidative neurotoxin 6-hydroxydopamine (6-OHDA). In the present study, FGF-deficient transgenic mice th-fgfr1(tk-) were used to analyze the effects of novel full (TC-8831) and partial (TC-8581) agonists of β2-containing nicotinic receptors on impaired motor behavior following unilateral 6-OHDA lesions. The lesions generated spontaneous (drug-naïve) turning asymmetries that correlated exponentially with the depletion of DA biomarkers in the lesioned striata. These mice also exhibited a reduced capacity to remain on the accelerating rotarod. Oral administration of TC-8831, an NNR agonist with high specificity for β2 subunits and a full agonist at producing DA release from striatal synaptosomes, attenuated unidirectional turning and improved motor coordination. In contrast, partial β2 NNR agonist TC-8581 had no effect on behaviors in this model. This study demonstrates the potential of NNR targeting-compounds to facilitate motor function in PD. © 2013. Published by Elsevier Inc. All rights reserved.

  6. Temporal Information Processing and Stability Analysis of the MHSN Neuron Model in DDF

    Directory of Open Access Journals (Sweden)

    Saket Kumar Choudhary

    2016-12-01

    Full Text Available Implementation of a neuron like information processing structure at hardware level is a burning research problem. In this article, we analyze the modified hybrid spiking neuron model (the MHSN model in distributed delay framework (DDF for hardware level implementation point of view. We investigate its temporal information processing capability in term of inter-spike-interval (ISI distribution. We also perform the stability analysis of the MHSN model, in which, we compute nullclines, steady state solution, eigenvalues corresponding the MHSN model. During phase plane analysis, we notice that the MHSN model generates limit cycle oscillations which is an important phenomenon in many biological processes. Qualitative behavior of these limit cycle does not changes due to the variation in applied input stimulus, however, delay effect the spiking activity and duration of cycle get altered.

  7. The sensory neurone membrane protein SNMP1 contributes to the sensitivity of a pheromone detection system.

    Science.gov (United States)

    Pregitzer, P; Greschista, M; Breer, H; Krieger, J

    2014-12-01

    Male moths detect female-released sex pheromones with extraordinary sensitivity. The remarkable sensory ability is based on a cooperative interplay of pheromone binding proteins in the lymph of hair-like sensilla trichodea and pheromone receptors in the dendrites of sensory neurones. Here we examined whether in Heliothis virescens the so-called 'sensory neurone membrane protein 1' (SNMP1) may contribute to responsiveness to the pheromone component, (Z)-11-hexadecenal (Z11-16:Ald). By means of immunohistochemistry and in situ hybridization we demonstrated that SNMP1 is in fact present in cells expressing the Z11-16:Ald receptor HR13 and the dendrites of sensory neurones. To assess a possible function of SNMP1 we monitored the responsiveness of cell lines that expressed HR13 alone or the combination SNMP1/HR13 to stimulation with Z11-16:Ald by calcium imaging. It was found that SNMP1/HR13 cells were 1000-fold more sensitive to pheromone stimulation compared with HR13 cells. In contrast, cells that expressed HR13 and the non-neuronal SNMP2-type showed no change in pheromone sensitivity. Overall, our reconstitution experiments demonstrate that the presence of SNMP1 significantly increases the HR13-based responsiveness of cells to Z11-16:Ald, suggesting that SNMP1 also contributes to the response of the antennal neurones and thus to the remarkable sensitivity of the pheromone detection system. © 2014 The Royal Entomological Society.

  8. 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…

  9. Frequent occurrence of nicotinic acetylcholine receptors in GABAergic neurons of the chick visual system

    Directory of Open Access Journals (Sweden)

    A.S. Torrão

    2001-10-01

    Full Text Available Double-labeling immunohistochemical methods were used to investigate the occurrence of the alpha8 and alpha5 nicotinic receptor subunits in presumptive GABAergic neurons of the chick nervous system. Nicotinic receptor immunoreactivity was often found in cells exhibiting GABA-like immunoreactivity, especially in the visual system. The alpha8 subunit appeared to be present in presumptive GABAergic cells of the ventral lateral geniculate nucleus, nucleus of the basal optic root of the accessory optic system, and the optic tectum, among several other structures. The alpha5 subunit was also found in GABA-positive neurons, as observed in the lentiform nucleus of the mesencephalon and other pretectal nuclei. The numbers of alpha8- and alpha5-positive neurons that were also GABA-positive represented high percentages of the total number of neurons containing nicotinic receptor labeling in several brain areas, which indicates that most of the alpha8 and alpha5 nicotinic receptor subunits are present in GABAergic cells. Taken together with data from other studies, our results indicate an important role of the nicotinic acetylcholine receptors in the functional organization of GABAergic circuits in the visual system.

  10. Spatio-temporal dynamics of the mirror neuron system during social intentions.

    Science.gov (United States)

    Cacioppo, Stephanie; Bolmont, Mylene; Monteleone, George

    2017-10-27

    Previous research has shown that specific goals and intentions influence a person's allocation of social attention. From a neural viewpoint, a growing body of evidence suggests that the inferior fronto-parietal network, including the mirror neuron system, plays a role in the planning and the understanding of motor intentions. However, it is unclear whether and when the mirror neuron system plays a role in social intentions. Combining a behavioral task with electrical neuroimaging in 22 healthy male participants, the current study investigates whether the temporal brain dynamic of the mirror neuron system differs during two types of social intentions i.e., lust vs. romantic intentions. Our results showed that 62% of the stimuli evoking lustful intentions also evoked romantic intentions, and both intentions were sustained by similar activations of the inferior frontal gyrus and the inferior parietal lobule/angular gyrus for the first 432 ms after stimulus onset. Intentions to not love or not lust, on the other hand, were characterized by earlier differential activations of the inferior fronto-parietal network i.e., as early as 244 ms after stimulus onset. These results suggest that the mirror neuron system may not only code for the motor correlates of intentions, but also for the social meaning of intentions and its valence at both early/automatic and later/more elaborative stages of information processing.

  11. Inflammatory cells in the peripheral nervous system in motor neuron disease

    NARCIS (Netherlands)

    Kerkhoff, H.; Troost, D.; Louwerse, E. S.; van Dijk, M.; Veldman, H.; Jennekens, F. G.

    1993-01-01

    We examined post-mortem material of the peripheral nervous system of 26 cases of motor neuron disease (MND) for the presence of lymphocyte subsets and macrophages. Findings were quantified and compared with those in control nerves. Lymphocytes in chronic and acute axonal degeneration were studied in

  12. 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…

  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. Leptin and insulin signaling in dopaminergic neurons: relationship between energy balance and reward system.

    Science.gov (United States)

    Khanh, Doan V; Choi, Yun-Hee; Moh, Sang Hyun; Kinyua, Ann W; Kim, Ki Woo

    2014-01-01

    The central actions of leptin and insulin are essential for the regulation of energy and glucose homeostasis. In addition to the crucial effects on the hypothalamus, emerging evidence suggests that the leptin and insulin signaling can act on other brain regions to mediate the reward value of nutrients. Recent studies have indicated the midbrain dopaminergic neurons as a potential site for leptin' and insulin's actions on mediating the feeding behaviors and therefore affecting the energy balance. Although molecular details about the integrative roles of leptin and insulin in this subset of neurons remain to be investigated, substantial body of evidence by far imply that the signaling pathways regulated by leptin and insulin may play an essential role in the regulation of energy balance through the control of food-associated reward. This review therefore describes the convergence of energy regulation and reward system, particularly focusing on leptin and insulin signaling in the midbrain dopaminergic neurons.

  15. Uncoupling neuronal death and dysfunction in Drosophila models of neurodegenerative disease.

    Science.gov (United States)

    Chouhan, Amit K; Guo, Caiwei; Hsieh, Yi-Chen; Ye, Hui; Senturk, Mumine; Zuo, Zhongyuan; Li, Yarong; Chatterjee, Shreyasi; Botas, Juan; Jackson, George R; Bellen, Hugo J; Shulman, Joshua M

    2016-06-23

    Common neurodegenerative proteinopathies, such as Alzheimer's disease (AD) and Parkinson's disease (PD), are characterized by the misfolding and aggregation of toxic protein species, including the amyloid beta (Aß) peptide, microtubule-associated protein Tau (Tau), and alpha-synuclein (αSyn) protein. These factors also show toxicity in Drosophila; however, potential limitations of prior studies include poor discrimination between effects on the adult versus developing nervous system and neuronal versus glial cell types. In addition, variable expression paradigms and outcomes hinder systematic comparison of toxicity profiles. Using standardized conditions and medium-throughput assays, we express human Tau, Aß or αSyn selectively in neurons of the adult Drosophila retina and monitor age-dependent changes in both structure and function, based on tissue histology and recordings of the electroretinogram (ERG), respectively. We find that each protein causes a unique profile of neurodegenerative pathology, demonstrating distinct and separable impacts on neuronal death and dysfunction. Strikingly, expression of Tau leads to progressive loss of ERG responses whereas retinal architecture and neuronal numbers are largely preserved. By contrast, Aß induces modest, age-dependent neuronal loss without degrading the retinal ERG. αSyn expression, using a codon-optimized transgene, is characterized by marked retinal vacuolar change, progressive photoreceptor cell death, and delayed-onset but modest ERG changes. Lastly, to address potential mechanisms, we perform transmission electron microscopy (TEM) to reveal potential degenerative changes at the ultrastructural level. Surprisingly, Tau and αSyn each cause prominent but distinct synaptotoxic profiles, including disorganization or enlargement of photoreceptor terminals, respectively. Our findings highlight variable and dynamic properties of neurodegeneration triggered by these disease-relevant proteins in vivo, and suggest

  16. Human iPS cell-derived dopaminergic neurons function in a primate Parkinson's disease model.

    Science.gov (United States)

    Kikuchi, Tetsuhiro; Morizane, Asuka; Doi, Daisuke; Magotani, Hiroaki; Onoe, Hirotaka; Hayashi, Takuya; Mizuma, Hiroshi; Takara, Sayuki; Takahashi, Ryosuke; Inoue, Haruhisa; Morita, Satoshi; Yamamoto, Michio; Okita, Keisuke; Nakagawa, Masato; Parmar, Malin; Takahashi, Jun

    2017-08-30

    Induced pluripotent stem cells (iPS cells) are a promising source for a cell-based therapy to treat Parkinson's disease (PD), in which midbrain dopaminergic neurons progressively degenerate. However, long-term analysis of human iPS cell-derived dopaminergic neurons in primate PD models has never been performed to our knowledge. Here we show that human iPS cell-derived dopaminergic progenitor cells survived and functioned as midbrain dopaminergic neurons in a primate model of PD (Macaca fascicularis) treated with the neurotoxin MPTP. Score-based and video-recording analyses revealed an increase in spontaneous movement of the monkeys after transplantation. Histological studies showed that the mature dopaminergic neurons extended dense neurites into the host striatum; this effect was consistent regardless of whether the cells were derived from patients with PD or from healthy individuals. Cells sorted by the floor plate marker CORIN did not form any tumours in the brains for at least two years. Finally, magnetic resonance imaging and positron emission tomography were used to monitor the survival, expansion and function of the grafted cells as well as the immune response in the host brain. Thus, this preclinical study using a primate model indicates that human iPS cell-derived dopaminergic progenitors are clinically applicable for the treatment of patients with PD.

  17. 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.

  18. Activation of endogenous arginine vasopressin neurons inhibit food intake: by using a novel transgenic rat line with DREADDs system.

    Science.gov (United States)

    Yoshimura, Mitsuhiro; Nishimura, Kazuaki; Nishimura, Haruki; Sonoda, Satomi; Ueno, Hiromichi; Motojima, Yasuhito; Saito, Reiko; Maruyama, Takashi; Nonaka, Yuki; Ueta, Yoichi

    2017-11-16

    Various studies contributed to discover novel mechanisms of central arginine vasopressin (AVP) system responsible for the behaviour albeit endogenous vasopressin activation. We established a novel transgenic rat line which expresses both human muscarinic acetylcholine receptors (hM3Dq), of which ligand is clozapine-N-oxide (CNO), and mCherry fluorescence specifically in AVP neurons. The mCherry neurons that indicate the expression of the hM3Dq gene were observed in the suprachiasmatic (SCN), supraoptic (SON), and paraventricular nuclei (PVN). hM3Dq-mCherry fluorescence was localized mainly in the membrane of the neurons. The mCherry neurons were co-localized with AVP-like immunoreactive (LI) neurons, but not with oxytocin-LI neurons. The induction of Fos, which is the indicator for neuronal activity, was observed in approximately 90% of the AVP-LI neurons in the SON and PVN 90 min after intraperitoneal (i.p.) administration of CNO. Plasma AVP was significantly increased and food intake, water intake, and urine volume were significantly attenuated after i.p. administration of CNO. Although the detailed mechanism has unveiled, we demonstrated, for the first time, that activation of endogenous AVP neurons decreased food intake. This novel transgenic rat line may provide a revolutionary insight into the neuronal mechanism regarding central AVP system responsible for various kind of behaviours.

  19. 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…

  20. Selective disruption of acetylcholine synthesis in subsets of motor neurons: a new model of late-onset motor neuron disease.

    Science.gov (United States)

    Lecomte, Marie-José; Bertolus, Chloé; Santamaria, Julie; Bauchet, Anne-Laure; Herbin, Marc; Saurini, Françoise; Misawa, Hidemi; Maisonobe, Thierry; Pradat, Pierre-François; Nosten-Bertrand, Marika; Mallet, Jacques; Berrard, Sylvie

    2014-05-01

    Motor neuron diseases are characterized by the selective chronic dysfunction of a subset of motor neurons and the subsequent impairment of neuromuscular function. To reproduce in the mouse these hallmarks of diseases affecting motor neurons, we generated a mouse line in which ~40% of motor neurons in the spinal cord and the brainstem become unable to sustain neuromuscular transmission. These mice were obtained by conditional knockout of the gene encoding choline acetyltransferase (ChAT), the biosynthetic enzyme for acetylcholine. The mutant mice are viable and spontaneously display abnormal phenotypes that worsen with age including hunched back, reduced lifespan, weight loss, as well as striking deficits in muscle strength and motor function. This slowly progressive neuromuscular dysfunction is accompanied by muscle fiber histopathological features characteristic of neurogenic diseases. Unexpectedly, most changes appeared with a 6-month delay relative to the onset of reduction in ChAT levels, suggesting that compensatory mechanisms preserve muscular function for several months and then are overwhelmed. Deterioration of mouse phenotype after ChAT gene disruption is a specific aging process reminiscent of human pathological situations, particularly among survivors of paralytic poliomyelitis. These mutant mice may represent an invaluable tool to determine the sequence of events that follow the loss of function of a motor neuron subset as the disease progresses, and to evaluate therapeutic strategies. They also offer the opportunity to explore fundamental issues of motor neuron biology. Copyright © 2014 Elsevier Inc. All rights reserved.

  1. Human stem cell-derived neurons: a system to study human tau function and dysfunction.

    Directory of Open Access Journals (Sweden)

    Mariangela Iovino

    2010-11-01

    Full Text Available Intracellular filamentous deposits containing microtubule-associated protein tau constitute a defining characteristic of many neurodegenerative disorders. Current experimental models to study tau pathology in vitro do not usually recapitulate the tau expression pattern characteristic of adult human brain. In this study, we have investigated whether human embryonic stem cell-derived neurons could be a good model to study human tau distribution, function and dysfunction.Using RT-PCR, immunohistochemistry, western blotting and cell transfections we have investigated whether all 6 adult human brain tau isoforms are expressed in neurons derived from human embryonic and fetal stem cells and whether 4 repeat tau over-expression alone, or with the F3 tau repeat fragment, (amino acid 258-380 of the 2N4R tau isoform with the ΔK280 mutation affects tau distribution. We found that the shortest 3 repeat tau isoform, similarly to human brain, is the first to be expressed during neuronal differentiation while the other 5 tau isoforms are expressed later. Over expression of tau with 4 repeats affects tau cellular distribution and the short tau F3 fragment appears to increase tau phosphorylation but this effect does not appear to be toxic for the cell.Our results indicate that human embryonic stem cell-derived neurons express all 6 tau isoforms and are a good model in which to study tau physiology and pathology.

  2. Mean-field approximations for coupled populations of generalized linear model spiking neurons with Markov refractoriness.

    Science.gov (United States)

    Toyoizumi, Taro; Rad, Kamiar Rahnama; Paninski, Liam

    2009-05-01

    There has recently been a great deal of interest in inferring network connectivity from the spike trains in populations of neurons. One class of useful models that can be fit easily to spiking data is based on generalized linear point process models from statistics. Once the parameters for these models are fit, the analyst is left with a nonlinear spiking network model with delays, which in general may be very difficult to understand analytically. Here we develop mean-field methods for approximating the stimulus-driven firing rates (in both the time-varying and steady-state cases), auto- and cross-correlations, and stimulus-dependent filtering properties of these networks. These approximations are valid when the contributions of individual network coupling terms are small and, hence, the total input to a neuron is approximately gaussian. These approximations lead to deterministic ordinary differential equations that are much easier to solve and analyze than direct Monte Carlo simulation of the network activity. These approximations also provide an analytical way to evaluate the linear input-output filter of neurons and how the filters are modulated by network interactions and some stimulus feature. Finally, in the case of strong refractory effects, the mean-field approximations in the generalized linear model become inaccurate; therefore, we introduce a model that captures strong refractoriness, retains all of the easy fitting properties of the standard generalized linear model, and leads to much more accurate approximations of mean firing rates and cross-correlations that retain fine temporal behaviors.

  3. Recapitulation of spinal motor neuron-specific disease phenotypes in a human cell model of spinal muscular atrophy.

    Science.gov (United States)

    Wang, Zhi-Bo; Zhang, Xiaoqing; Li, Xue-Jun

    2013-03-01

    Establishing human cell models of spinal muscular atrophy (SMA) to mimic motor neuron-specific phenotypes holds the key to understanding the pathogenesis of this devastating disease. Here, we developed a closely representative cell model of SMA by knocking down the disease-determining gene, survival motor neuron (SMN), in human embryonic stem cells (hESCs). Our study with this cell model demonstrated that knocking down of SMN does not interfere with neural induction or the initial specification of spinal motor neurons. Notably, the axonal outgrowth of spinal motor neurons was significantly impaired and these disease-mimicking neurons subsequently degenerated. Furthermore, these disease phenotypes were caused by SMN-full length (SMN-FL) but not SMN-Δ7 (lacking exon 7) knockdown, and were specific to spinal motor neurons. Restoring the expression of SMN-FL completely ameliorated all of the disease phenotypes, including specific axonal defects and motor neuron loss. Finally, knockdown of SMN-FL led to excessive mitochondrial oxidative stress in human motor neuron progenitors. The involvement of oxidative stress in the degeneration of spinal motor neurons in the SMA cell model was further confirmed by the administration of N-acetylcysteine, a potent antioxidant, which prevented disease-related apoptosis and subsequent motor neuron death. Thus, we report here the successful establishment of an hESC-based SMA model, which exhibits disease gene isoform specificity, cell type specificity, and phenotype reversibility. Our model provides a unique paradigm for studying how motor neurons specifically degenerate and highlights the potential importance of antioxidants for the treatment of SMA.

  4. Stochastic differential equation models for ion channel noise in Hodgkin-Huxley neurons

    OpenAIRE

    Goldwyn, Joshua H.; Imennov, Nikita S.; Famulare, Michael; Shea-Brown, Eric

    2011-01-01

    The random transitions of ion channels between conducting and nonconducting states generate a source of internal fluctuations in a neuron, known as channel noise. The standard method for modeling the states of ion channels nonlinearly couples continuous-time Markov chains to a differential equation for voltage. Beginning with the work of R. F. Fox and Y.-N. Lu [Phys. Rev. E 49, 3421 (1994)], there have been attempts to generate simpler models that use stochastic differential equation (SDEs) t...

  5. 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.

  6. 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

  7. Inhibiting sphingosine kinase 2 mitigates mutant Huntingtin-induced neurodegeneration in neuron models of Huntington disease.

    Science.gov (United States)

    Moruno-Manchon, Jose F; Uzor, Ndidi-Ese; Blasco-Conesa, Maria P; Mannuru, Sishira; Putluri, Nagireddy; Furr-Stimming, Erin E; Tsvetkov, Andrey S

    2017-04-01

    Huntington disease (HD) is the most common inherited neurodegenerative disorder. It has no cure. The protein huntingtin causes HD, and mutations to it confer toxic functions to the protein that lead to neurodegeneration. Thus, identifying modifiers of mutant huntingtin-mediated neurotoxicity might be a therapeutic strategy for HD. Sphingosine kinases 1 (SK1) and 2 (SK2) synthesize sphingosine-1-phosphate (S1P), a bioactive lipid messenger critically involved in many vital cellular processes, such as cell survival. In the nucleus, SK2 binds to and inhibits histone deacetylases 1 and 2 (HDAC1/2). Inhibiting both HDACs has been suggested as a potential therapy in HD. Here, we found that SK2 is nuclear in primary neurons and, unexpectedly, overexpressed SK2 is neurotoxic in a dose-dependent manner. SK2 promotes DNA double-strand breaks in cultured primary neurons. We also found that SK2 is hyperphosphorylated in the brain samples from a model of HD, the BACHD mice. These data suggest that the SK2 pathway may be a part of a pathogenic pathway in HD. ABC294640, an inhibitor of SK2, reduces DNA damage in neurons and increases survival in two neuron models of HD. Our results identify a novel regulator of mutant huntingtin-mediated neurotoxicity and provide a new target for developing therapies for HD. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  8. Oleuropein Prevents Neuronal Death, Mitigates Mitochondrial Superoxide Production and Modulates Autophagy in a Dopaminergic Cellular Model

    Directory of Open Access Journals (Sweden)

    Imène Achour

    2016-08-01

    Full Text Available Parkinson’s disease (PD is a progressive neurodegenerative disorder, primarily affecting dopaminergic neurons in the substantia nigra. There is currently no cure for PD and present medications aim to alleviate clinical symptoms, thus prevention remains the ideal strategy to reduce the prevalence of this disease. The goal of this study was to investigate whether oleuropein (OLE, the major phenolic compound in olive derivatives, may prevent neuronal degeneration in a cellular dopaminergic model of PD, differentiated PC12 cells exposed to the potent parkinsonian toxin 6-hydroxydopamine (6-OHDA. We also investigated OLE’s ability to mitigate mitochondrial oxidative stress and modulate the autophagic flux. Our results obtained by measuring cytotoxicity and apoptotic events demonstrate that OLE significantly decreases neuronal death. OLE could also reduce mitochondrial production of reactive oxygen species resulting from blocking superoxide dismutase activity. Moreover, quantification of autophagic and acidic vesicles in the cytoplasm alongside expression of specific autophagic markers uncovered a regulatory role for OLE against autophagic flux impairment induced by bafilomycin A1. Altogether, our results define OLE as a neuroprotective, anti-oxidative and autophagy-regulating molecule, in a neuronal dopaminergic cellular model.

  9. A mathematical model towards understanding the mechanism of neuronal regulation of wake-NREMS-REMS states.

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    Rupesh Kumar

    Full Text Available In this study we have constructed a mathematical model of a recently proposed functional model known to be responsible for inducing waking, NREMS and REMS. Simulation studies using this model reproduced sleep-wake patterns as reported in normal animals. The model helps to explain neural mechanism(s that underlie the transitions between wake, NREMS and REMS as well as how both the homeostatic sleep-drive and the circadian rhythm shape the duration of each of these episodes. In particular, this mathematical model demonstrates and confirms that an underlying mechanism for REMS generation is pre-synaptic inhibition from substantia nigra onto the REM-off terminals that project on REM-on neurons, as has been recently proposed. The importance of orexinergic neurons in stabilizing the wake-sleep cycle is demonstrated by showing how even small changes in inputs to or from those neurons can have a large impact on the ensuing dynamics. The results from this model allow us to make predictions of the neural mechanisms of regulation and patho-physiology of REMS.

  10. Ontogenesis of Gonadotropin-Releasing Hormone Neurons: A Model for Hypothalamic Neuroendocrine Cell Development

    OpenAIRE

    Stevenson, Erica L.; Corella, Kristina M.; Chung, Wilson C. J.

    2013-01-01

    The vertebrate hypothalamo–pituitary–gonadal axis is the anatomical framework responsible for reproductive competence and species propagation. Essential to the coordinated actions of this three-tiered biological system is the fact that the regulatory inputs ultimately converge on the gonadotropin-releasing hormone (GnRH) neuronal system, which in rodents primarily resides in the preoptic/hypothalamic region. In this short review we will focus on: (1) the general embryonic temporal and spatial...

  11. Modelling the Somatic Electrical Response of Hippocampal Pyramidal Neurons

    Science.gov (United States)

    1989-09-01

    these quick " customized " HIPPOs was effective in developing an intuitive sense of the behavior of the model, and presumably that of the cell. For...ca (Set Caret USIA a-cal) as-ca: ’point-Index) (mset Caret SOSIA v-cal) me-cas apoint-Indnc) CSat (g-ca 1.0 Caret IOWA a-cal)Caef SIOA v-cal)) ag-cas

  12. Hybrid Cubature Kalman filtering for identifying nonlinear models from sampled recording: Estimation of neuronal dynamics

    Science.gov (United States)

    2017-01-01

    Kalman filtering methods have long been regarded as efficient adaptive Bayesian techniques for estimating hidden states in models of linear dynamical systems under Gaussian uncertainty. Recent advents of the Cubature Kalman filter (CKF) have extended this efficient estimation property to nonlinear systems, and also to hybrid nonlinear problems where by the processes are continuous and the observations are discrete (continuous-discrete CD-CKF). Employing CKF techniques, therefore, carries high promise for modeling many biological phenomena where the underlying processes exhibit inherently nonlinear, continuous, and noisy dynamics and the associated measurements are uncertain and time-sampled. This paper investigates the performance of cubature filtering (CKF and CD-CKF) in two flagship problems arising in the field of neuroscience upon relating brain functionality to aggregate neurophysiological recordings: (i) estimation of the firing dynamics and the neural circuit model parameters from electric potentials (EP) observations, and (ii) estimation of the hemodynamic model parameters and the underlying neural drive from BOLD (fMRI) signals. First, in simulated neural circuit models, estimation accuracy was investigated under varying levels of observation noise (SNR), process noise structures, and observation sampling intervals (dt). When compared to the CKF, the CD-CKF consistently exhibited better accuracy for a given SNR, sharp accuracy increase with higher SNR, and persistent error reduction with smaller dt. Remarkably, CD-CKF accuracy shows only a mild deterioration for non-Gaussian process noise, specifically with Poisson noise, a commonly assumed form of background fluctuations in neuronal systems. Second, in simulated hemodynamic models, parametric estimates were consistently improved under CD-CKF. Critically, time-localization of the underlying neural drive, a determinant factor in fMRI-based functional connectivity studies, was significantly more accurate

  13. Predicting Intentions of a Familiar Significant Other Beyond the Mirror Neuron System

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    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

  14. Dendritic development of Drosophila high order visual system neurons is independent of sensory experience

    Directory of Open Access Journals (Sweden)

    Reuter John E

    2003-06-01

    Full Text Available Abstract Background The complex and characteristic structures of dendrites are a crucial part of the neuronal architecture that underlies brain function, and as such, their development has been a focal point of recent research. It is generally believed that dendritic development is controlled by a combination of endogenous genetic mechanisms and activity-dependent mechanisms. Therefore, it is of interest to test the relative contributions of these two types of mechanisms towards the construction of specific dendritic trees. In this study, we make use of the highly complex Vertical System (VS of motion sensing neurons in the lobula plate of the Drosophila visual system to gauge the importance of visual input and synaptic activity to dendritic development. Results We find that the dendrites of VS1 neurons are unchanged in dark-reared flies as compared to control flies raised on a 12 hour light, 12 hour dark cycle. The dendrites of these flies show no differences from control in dendrite complexity, spine number, spine density, or axon complexity. Flies with genetically ablated eyes show a slight but significant reduction in the complexity and overall length of VS1 dendrites, although this effect may be due to a reduction in the overall size of the dendritic field in these flies. Conclusions Overall, our results indicate no role for visual experience in the development of VS dendrites, while spontaneous activity from photoreceptors may play at most a subtle role in the formation of fully complex dendrites in these high-order visual processing neurons.

  15. Bayesian nonparametric modeling for comparison of single-neuron firing intensities.

    Science.gov (United States)

    Kottas, Athanasios; Behseta, Sam

    2010-03-01

    We propose a fully inferential model-based approach to the problem of comparing the firing patterns of a neuron recorded under two distinct experimental conditions. The methodology is based on nonhomogeneous Poisson process models for the firing times of each condition with flexible nonparametric mixture prior models for the corresponding intensity functions. We demonstrate posterior inferences from a global analysis, which may be used to compare the two conditions over the entire experimental time window, as well as from a pointwise analysis at selected time points to detect local deviations of firing patterns from one condition to another. We apply our method on two neurons recorded from the primary motor cortex area of a monkey's brain while performing a sequence of reaching tasks.

  16. Neuroprotective Role of Gap Junctions in a Neuron Astrocyte Network Model.

    Science.gov (United States)

    Huguet, Gemma; Joglekar, Anoushka; Messi, Leopold Matamba; Buckalew, Richard; Wong, Sarah; Terman, David

    2016-07-26

    A detailed biophysical model for a neuron/astrocyte network is developed to explore mechanisms responsible for the initiation and propagation of cortical spreading depolarizations and the role of astrocytes in maintaining ion homeostasis, thereby preventing these pathological waves. Simulations of the model illustrate how properties of spreading depolarizations, such as wave speed and duration of depolarization, depend on several factors, including the neuron and astrocyte Na(+)-K(+) ATPase pump strengths. In particular, we consider the neuroprotective role of astrocyte gap junction coupling. The model demonstrates that a syncytium of electrically coupled astrocytes can maintain a physiological membrane potential in the presence of an elevated extracellular K(+) concentration and efficiently distribute the excess K(+) across the syncytium. This provides an effective neuroprotective mechanism for delaying or preventing the initiation of spreading depolarizations. Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  17. Energy metabolism in neuronal/glial induction and in iPSC models of brain disorders.

    Science.gov (United States)

    Mlody, Barbara; Lorenz, Carmen; Inak, Gizem; Prigione, Alessandro

    2016-04-01

    The metabolic switch associated with the reprogramming of somatic cells to pluripotency has received increasing attention in recent years. However, the impact of mitochondrial and metabolic modulation on stem cell differentiation into neuronal/glial cells and related brain disease modeling still remains to be fully addressed. Here, we seek to focus on this aspect by first addressing brain energy metabolism and its inter-cellular metabolic compartmentalization. We then review the findings related to the mitochondrial and metabolic reconfiguration occurring upon neuronal/glial specification from pluripotent stem cells (PSCs). Finally, we provide an update of the PSC-based models of mitochondria-related brain disorders and discuss the challenges and opportunities that may exist on the road to develop a new era of brain disease modeling and therapy. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Human iPSC-Derived Neuronal Model of Tau-A152T Frontotemporal Dementia Reveals Tau-Mediated Mechanisms of Neuronal Vulnerability

    Directory of Open Access Journals (Sweden)

    M. Catarina Silva

    2016-09-01

    Full Text Available Frontotemporal dementia (FTD and other tauopathies characterized by focal brain neurodegeneration and pathological accumulation of proteins are commonly associated with tau mutations. However, the mechanism of neuronal loss is not fully understood. To identify molecular events associated with tauopathy, we studied induced pluripotent stem cell (iPSC-derived neurons from individuals carrying the tau-A152T variant. We highlight the potential of in-depth phenotyping of human neuronal cell models for pre-clinical studies and identification of modulators of endogenous tau toxicity. Through a panel of biochemical and cellular assays, A152T neurons showed accumulation, redistribution, and decreased solubility of tau. Upregulation of tau was coupled to enhanced stress-inducible markers and cell vulnerability to proteotoxic, excitotoxic, and mitochondrial stressors, which was rescued upon CRISPR/Cas9-mediated targeting of tau or by pharmacological activation of autophagy. Our findings unmask tau-mediated perturbations of specific pathways associated with neuronal vulnerability, revealing potential early disease biomarkers and therapeutic targets for FTD and other tauopathies.

  19. Electrodiffusive model for astrocytic and neuronal ion concentration dynamics.

    Directory of Open Access Journals (Sweden)

    Geir Halnes

    Full Text Available The cable equation is a proper framework for modeling electrical neural signalling that takes place at a timescale at which the ionic concentrations vary little. However, in neural tissue there are also key dynamic processes that occur at longer timescales. For example, endured periods of intense neural signaling may cause the local extracellular K(+-concentration to increase by several millimolars. The clearance of this excess K(+ depends partly on diffusion in the extracellular space, partly on local uptake by astrocytes, and partly on intracellular transport (spatial buffering within astrocytes. These processes, that take place at the time scale of seconds, demand a mathematical description able to account for the spatiotemporal variations in ion concentrations as well as the subsequent effects of these variations on the membrane potential. Here, we present a general electrodiffusive formalism for modeling of ion concentration dynamics in a one-dimensional geometry, including both the intra- and extracellular domains. Based on the Nernst-Planck equations, this formalism ensures that the membrane potential and ion concentrations are in consistency, it ensures global particle/charge conservation and it accounts for diffusion and concentration dependent variations in resistivity. We apply the formalism to a model of astrocytes exchanging ions with the extracellular space. The simulations show that K(+-removal from high-concentration regions is driven by a local depolarization of the astrocyte membrane, which concertedly (i increases the local astrocytic uptake of K(+, (ii suppresses extracellular transport of K(+, (iii increases axial transport of K(+ within astrocytes, and (iv facilitates astrocytic relase of K(+ in regions where the extracellular concentration is low. Together, these mechanisms seem to provide a robust regulatory scheme for shielding the extracellular space from excess K(+.

  20. Optical imaging of neuronal activity and visualization of fine neural structures in non-desheathed nervous systems.

    Directory of Open Access Journals (Sweden)

    Christopher John Goldsmith

    Full Text Available Locating circuit neurons and recording from them with single-cell resolution is a prerequisite for studying neural circuits. Determining neuron location can be challenging even in small nervous systems because neurons are densely packed, found in different layers, and are often covered by ganglion and nerve sheaths that impede access for recording electrodes and neuronal markers. We revisited the voltage-sensitive dye RH795 for its ability to stain and record neurons through the ganglion sheath. Bath-application of RH795 stained neuronal membranes in cricket, earthworm and crab ganglia without removing the ganglion sheath, revealing neuron cell body locations in different ganglion layers. Using the pyloric and gastric mill central pattern generating neurons in the stomatogastric ganglion (STG of the crab, Cancer borealis, we found that RH795 permeated the ganglion without major residue in the sheath and brightly stained somatic, axonal and dendritic membranes. Visibility improved significantly in comparison to unstained ganglia, allowing the identification of somata location and number of most STG neurons. RH795 also stained axons and varicosities in non-desheathed nerves, and it revealed the location of sensory cell bodies in peripheral nerves. Importantly, the spike activity of the sensory neuron AGR, which influences the STG motor patterns, remained unaffected by RH795, while desheathing caused significant changes in AGR activity. With respect to recording neural activity, RH795 allowed us to optically record membrane potential changes of sub-sheath neuronal membranes without impairing sensory activity. The signal-to-noise ratio was comparable with that previously observed in desheathed preparations and sufficiently high to identify neurons in single-sweep recordings and synaptic events after spike-triggered averaging. In conclusion, RH795 enabled staining and optical recording of neurons through the ganglion sheath and is therefore both a

  1. Stability and Hopf Bifurcation of Fractional-Order Complex-Valued Single Neuron Model with Time Delay

    Science.gov (United States)

    Wang, Zhen; Wang, Xiaohong; Li, Yuxia; Huang, Xia

    2017-12-01

    In this paper, the problems of stability and Hopf bifurcation in a class of fractional-order complex-valued single neuron model with time delay are addressed. With the help of the stability theory of fractional-order differential equations and Laplace transforms, several new sufficient conditions, which ensure the stability of the system are derived. Taking the time delay as the bifurcation parameter, Hopf bifurcation is investigated and the critical value of the time delay for the occurrence of Hopf bifurcation is determined. Finally, two representative numerical examples are given to show the effectiveness of the theoretical results.

  2. Improved system identification using artificial neural networks and analysis of individual differences in responses of an identified neuron.

    Science.gov (United States)

    Costalago Meruelo, Alicia; Simpson, David M; Veres, Sandor M; Newland, Philip L

    2016-03-01

    Mathematical modelling is used routinely to understand the coding properties and dynamics of responses of neurons and neural networks. Here we analyse the effectiveness of Artificial Neural Networks (ANNs) as a modelling tool for motor neuron responses. We used ANNs to model the synaptic responses of an identified motor neuron, the fast extensor motor neuron, of the desert locust in response to displacement of a sensory organ, the femoral chordotonal organ, which monitors movements of the tibia relative to the femur of the leg. The aim of the study was threefold: first to determine the potential value of ANNs as tools to model and investigate neural networks, second to understand the generalisation properties of ANNs across individuals and to different input signals and third, to understand individual differences in responses of an identified neuron. A metaheuristic algorithm was developed to design the ANN architectures. The performance of the models generated by the ANNs was compared with those generated through previous mathematical models of the same neuron. The results suggest that ANNs are significantly better than LNL and Wiener models in predicting specific neural responses to Gaussian White Noise, but not significantly different when tested with sinusoidal inputs. They are also able to predict responses of the same neuron in different individuals irrespective of which animal was used to develop the model, although notable differences between some individuals were evident. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  3. A self-organizing state-space-model approach for parameter estimation in hodgkin-huxley-type models of single neurons.

    Directory of Open Access Journals (Sweden)

    Dimitrios V Vavoulis

    Full Text Available Traditional approaches to the problem of parameter estimation in biophysical models of neurons and neural networks usually adopt a global search algorithm (for example, an evolutionary algorithm, often in combination with a local search method (such as gradient descent in order to minimize the value of a cost function, which measures the discrepancy between various features of the available experimental data and model output. In this study, we approach the problem of parameter estimation in conductance-based models of single neurons from a different perspective. By adopting a hidden-dynamical-systems formalism, we expressed parameter estimation as an inference problem in these systems, which can then be tackled using a range of well-established statistical inference methods. The particular method we used was Kitagawa's self-organizing state-space model, which was applied on a number of Hodgkin-Huxley-type models using simulated or actual electrophysiological data. We showed that the algorithm can be used to estimate a large number of parameters, including maximal conductances, reversal potentials, kinetics of ionic currents, measurement and intrinsic noise, based on low-dimensional experimental data and sufficiently informative priors in the form of pre-defined constraints imposed on model parameters. The algorithm remained operational even when very noisy experimental data were used. Importantly, by combining the self-organizing state-space model with an adaptive sampling algorithm akin to the Covariance Matrix Adaptation Evolution Strategy, we achieved a significant reduction in the variance of parameter estimates. The algorithm did not require the explicit formulation of a cost function and it was straightforward to apply on compartmental models and multiple data sets. Overall, the proposed methodology is particularly suitable for resolving high-dimensional inference problems based on noisy electrophysiological data and, therefore, a

  4. Comparison of current-driven and conductance-driven neocortical model neurons with Hodgkin-Huxley voltage-gated channels.

    Science.gov (United States)

    Tiesinga, P H; José, J V; Sejnowski, T J

    2000-12-01

    Intrinsic noise and random synaptic inputs generate a fluctuating current across neuron membranes. We determine the statistics of the output spike train of a biophysical model neuron as a function of the mean and variance of the fluctuating current, when the current is white noise, or when it derives from Poisson trains of excitatory and inhibitory postsynaptic conductances. In the first case, the firing rate increases with increasing variance of the current, whereas in the latter case it decreases. In contrast, the firing rate is independent of variance (for constant mean) in the commonly used random walk, and perfect integrate-and-fire models for spike generation. The model neuron can be in the current-dominated state, representative of neurons in the in vitro slice preparation, or in the fluctuation-dominated state, representative of in vivo neurons. We discuss the functional relevance of these states to cortical information processing.

  5. From Neurons to Social Beings: Short Review of the Mirror Neuron System Research and Its Socio-Psychological and Psychiatric Implications.

    Science.gov (United States)

    Jeon, Hyeonjin; Lee, Seung-Hwan

    2018-02-28

    The mirror neuron system (MNS) is a brain network activated when we move our body parts and when we observe the actions of other agent. Since the mirror neuron's discovery in research on monkeys, several studies have examined its network and properties in both animals and humans. This review discusses MNS studies of animals and human MNS studies related to high-order social cognitions such as emotion and empathy, as well as relations between MNS dysfunction and mental disorders. Finally, these evidences are understood from an evolutionary perspective.

  6. Single bumps in a 2-population homogenized neuronal network model

    Science.gov (United States)

    Kolodina, Karina; Oleynik, Anna; Wyller, John

    2018-05-01

    We investigate existence and stability of single bumps in a homogenized 2-population neural field model, when the firing rate functions are given by the Heaviside function. The model is derived by means of the two-scale convergence technique of Nguetseng in the case of periodic microvariation in the connectivity functions. The connectivity functions are periodically modulated in both the synaptic footprint and in the spatial scale. The bump solutions are constructed by using a pinning function technique for the case where the solutions are independent of the local variable. In the weakly modulated case the generic picture consists of two bumps (one narrow and one broad bump) for each admissible set of threshold values for firing. In addition, a new threshold value regime for existence of bumps is detected. Beyond the weakly modulated regime the number of bumps depends sensitively on the degree of heterogeneity. For the latter case we present a configuration consisting of three coexisting bumps. The linear stability of the bumps is studied by means of the spectral properties of a Fredholm integral operator, block diagonalization of this operator and the Fourier decomposition method. In the weakly modulated regime, one of the bumps is unstable for all relative inhibition times, while the other one is stable for small and moderate values of this parameter. The latter bump becomes unstable as the relative inhibition time exceeds a certain threshold. In the case of the three coexisting bumps detected in the regime of finite degree of heterogeneity, we have at least one stable bump (and maximum two stable bumps) for small and moderate values of the relative inhibition time.

  7. NAP (davunetide) rescues neuronal dysfunction in a Drosophila model of tauopathy

    Science.gov (United States)

    Quraishe, S; Cowan, C M; Mudher, A

    2013-01-01

    Alzheimer's disease (AD) is a devastating neurodegenerative disease causing irreversible cognitive decline in the elderly. There is no disease-modifying therapy for this condition and the mechanisms underpinning neuronal dysfunction and neurodegeneration are unclear. Compromised cytoskeletal integrity within neurons is reported in AD. This is believed to result from loss-of-function of the microtubule-associated protein tau, which becomes hyper-phosphorylated and deposits into neurofibrillary tangles in AD. We have developed a Drosophila model of tauopathy in which abnormal human tau mediates neuronal dysfunction characterised by microtubule destabilisation, axonal transport disruption, synaptic defects and behavioural impairments. Here we show that a microtubule-stabilising drug, NAPVSIPQ (NAP), prevents as well as reverses these phenotypes even after they have become established. Moreover, it does not alter abnormal tau levels indicating that it by-passes toxic tau altogether. Thus, microtubule stabilisation is a disease-modifying therapeutic strategy protecting against tau-mediated neuronal dysfunction, which holds great promise for tauopathies like AD. PMID:23587881

  8. Metabolic cost of neuronal information in an empirical stimulus-response model.

    Science.gov (United States)

    Kostal, Lubomir; Lansky, Petr; McDonnell, Mark D

    2013-06-01

    The limits on maximum information that can be transferred by single neurons may help us to understand how sensory and other information is being processed in the brain. According to the efficient-coding hypothesis (Barlow, Sensory Comunication, MIT press, Cambridge, 1961), neurons are adapted to the statistical properties of the signals to which they are exposed. In this paper we employ methods of information theory to calculate, both exactly (numerically) and approximately, the ultimate limits on reliable information transmission for an empirical neuronal model. We couple information transfer with the metabolic cost of neuronal activity and determine the optimal information-to-metabolic cost ratios. We find that the optimal input distribution is discrete with only six points of support, both with and without a metabolic constraint. However, we also find that many different input distributions achieve mutual information close to capacity, which implies that the precise structure of the capacity-achieving input is of lesser importance than the value of capacity.

  9. Mitochondrial mislocalization underlies Abeta42-induced neuronal dysfunction in a Drosophila model of Alzheimer's disease.

    Directory of Open Access Journals (Sweden)

    Kanae Iijima-Ando

    2009-12-01

    Full Text Available The amyloid-beta 42 (Abeta42 is thought to play a central role in the pathogenesis of Alzheimer's disease (AD. However, the molecular mechanisms by which Abeta42 induces neuronal dysfunction and degeneration remain elusive. Mitochondrial dysfunctions are implicated in AD brains. Whether mitochondrial dysfunctions are merely a consequence of AD pathology, or are early seminal events in AD pathogenesis remains to be determined. Here, we show that Abeta42 induces mitochondrial mislocalization, which contributes to Abeta42-induced neuronal dysfunction in a transgenic Drosophila model. In the Abeta42 fly brain, mitochondria were reduced in axons and dendrites, and accumulated in the somata without severe mitochondrial damage or neurodegeneration. In contrast, organization of microtubule or global axonal transport was not significantly altered at this stage. Abeta42-induced behavioral defects were exacerbated by genetic reductions in mitochondrial transport, and were modulated by cAMP levels and PKA activity. Levels of putative PKA substrate phosphoproteins were reduced in the Abeta42 fly brains. Importantly, perturbations in mitochondrial transport in neurons were sufficient to disrupt PKA signaling and induce late-onset behavioral deficits, suggesting a mechanism whereby mitochondrial mislocalization contributes to Abeta42-induced neuronal dysfunction. These results demonstrate that mislocalization of mitochondria underlies the pathogenic effects of Abeta42 in vivo.

  10. Serum neuron specific enolase - a novel indicator for neuropsychiatric systemic lupus erythematosus?

    Science.gov (United States)

    Hawro, T; Bogucki, A; Krupińska-Kun, M; Maurer, M; Woźniacka, A

    2015-12-01

    Neuropsychiatric (NP) lupus, a common manifestation of systemic lupus erythematosus (SLE), is still insufficiently understood, in part, because of the lack of specific biomarkers. Neuron specific enolase (NSE), an important neuronal glycolytic enzyme, shows increased serum levels following acute brain injury, and decreased serum levels in several chronic disorders of the nervous system, including multi infarct dementia, multiple sclerosis and depression. The aim of the study was to evaluate serum NSE levels in SLE patients with and without nervous system involvement, and in healthy controls, and to assess the correlation of NSE serum levels of patients with neuropsychiatric systemic lupus erythematosus (NPSLE) with clinical parameters. The study comprised 47 SLE patients and 28 controls. SLE activity was assessed using the Systemic Lupus Activity Measure (SLAM). A neurologist and a psychiatrist examined all patients. NP involvement was diagnosed according to strict NPSLE criteria proposed by Ainiala and coworkers, as modification to American College of Rheumatology (ACR) nomenclature and case definitions. NSE serum levels were determined by use of an immunoassay. Mean NSE serum concentrations in patients with NPSLE were significantly lower than in non-NPSLE patients (6.3 ± 2.6 µg/L vs. 9.7 ± 3.3 µg/L, p manifestations diagnosed (-0.37; p = 0.001). Decreased serum concentrations of NSE may reflect chronic neuronal damage with declined metabolism of the nervous tissue in patients with NPSLE. © The Author(s) 2015.

  11. Large-Scale Modeling of Epileptic Seizures: Scaling Properties of Two Parallel Neuronal Network Simulation Algorithms

    Directory of Open Access Journals (Sweden)

    Lorenzo L. Pesce

    2013-01-01

    Full Text Available Our limited understanding of the relationship between the behavior of individual neurons and large neuronal networks is an important limitation in current epilepsy research and may be one of the main causes of our inadequate ability to treat it. Addressing this problem directly via experiments is impossibly complex; thus, we have been developing and studying medium-large-scale simulations of detailed neuronal networks to guide us. Flexibility in the connection schemas and a complete description of the cortical tissue seem necessary for this purpose. In this paper we examine some of the basic issues encountered in these multiscale simulations. We have determined the detailed behavior of two such simulators on parallel computer systems. The observed memory and computation-time scaling behavior for a distributed memory implementation were very good over the range studied, both in terms of network sizes (2,000 to 400,000 neurons and processor pool sizes (1 to 256 processors. Our simulations required between a few megabytes and about 150 gigabytes of RAM and lasted between a few minutes and about a week, well within the capability of most multinode clusters. Therefore, simulations of epileptic seizures on networks with millions of cells should be feasible on current supercomputers.

  12. Large-scale modeling of epileptic seizures: scaling properties of two parallel neuronal network simulation algorithms.

    Science.gov (United States)

    Pesce, Lorenzo L; Lee, Hyong C; Hereld, Mark; Visser, Sid; Stevens, Rick L; Wildeman, Albert; van Drongelen, Wim

    2013-01-01

    Our limited understanding of the relationship between the behavior of individual neurons and large neuronal networks is an important limitation in current epilepsy research and may be one of the main causes of our inadequate ability to treat it. Addressing this problem directly via experiments is impossibly complex; thus, we have been developing and studying medium-large-scale simulations of detailed neuronal networks to guide us. Flexibility in the connection schemas and a complete description of the cortical tissue seem necessary for this purpose. In this paper we examine some of the basic issues encountered in these multiscale simulations. We have determined the detailed behavior of two such simulators on parallel computer systems. The observed memory and computation-time scaling behavior for a distributed memory implementation were very good over the range studied, both in terms of network sizes (2,000 to 400,000 neurons) and processor pool sizes (1 to 256 processors). Our simulations required between a few megabytes and about 150 gigabytes of RAM and lasted between a few minutes and about a week, well within the capability of most multinode clusters. Therefore, simulations of epileptic seizures on networks with millions of cells should be feasible on current supercomputers.

  13. Small GSK-3 Inhibitor Shows Efficacy in a Motor Neuron Disease Murine Model Modulating Autophagy.

    Directory of Open Access Journals (Sweden)

    Estefanía de Munck

    Full Text Available Amyotrophic lateral sclerosis (ALS is a progressive motor neuron degenerative disease that has no effective treatment up to date. Drug discovery tasks have been hampered due to the lack of knowledge in its molecular etiology together with the limited animal models for research. Recently, a motor neuron disease animal model has been developed using β-N-methylamino-L-alanine (L-BMAA, a neurotoxic amino acid related to the appearing of ALS. In the present work, the neuroprotective role of VP2.51, a small heterocyclic GSK-3 inhibitor, is analysed in this novel murine model together with the analysis of autophagy. VP2.51 daily administration for two weeks, starting the first day after L-BMAA treatment, leads to total recovery of neurological symptoms and prevents the activation of autophagic processes in rats. These results show that the L-BMAA murine model can be used to test the efficacy of new drugs. In addition, the results confirm the therapeutic potential of GSK-3 inhibitors, and specially VP2.51, for the disease-modifying future treatment of motor neuron disorders like ALS.

  14. Metastable states and quasicycles in a stochastic Wilson-Cowan model of neuronal population dynamics

    KAUST Repository

    Bressloff, Paul C.

    2010-11-03

    We analyze a stochastic model of neuronal population dynamics with intrinsic noise. In the thermodynamic limit N→∞, where N determines the size of each population, the dynamics is described by deterministic Wilson-Cowan equations. On the other hand, for finite N the dynamics is described by a master equation that determines the probability of spiking activity within each population. We first consider a single excitatory population that exhibits bistability in the deterministic limit. The steady-state probability distribution of the stochastic network has maxima at points corresponding to the stable fixed points of the deterministic network; the relative weighting of the two maxima depends on the system size. For large but finite N, we calculate the exponentially small rate of noise-induced transitions between the resulting metastable states using a Wentzel-Kramers- Brillouin (WKB) approximation and matched asymptotic expansions. We then consider a two-population excitatory or inhibitory network that supports limit cycle oscillations. Using a diffusion approximation, we reduce the dynamics to a neural Langevin equation, and show how the intrinsic noise amplifies subthreshold oscillations (quasicycles). © 2010 The American Physical Society.

  15. Deformation of attractor landscape via cholinergic presynaptic modulations: a computational study using a phase neuron model.

    Directory of Open Access Journals (Sweden)

    Takashi Kanamaru

    Full Text Available Corticopetal acetylcholine (ACh is released transiently from the nucleus basalis of Meynert (NBM into the cortical layers and is associated with top-down attention. Recent experimental data suggest that this release of ACh disinhibits layer 2/3 pyramidal neurons (PYRs via muscarinic presynaptic effects on inhibitory synapses. Together with other possible presynaptic cholinergic effects on excitatory synapses, this may result in dynamic and temporal modifications of synapses associated with top-down attention. However, the system-level consequences and cognitive relevance of such disinhibitions are poorly understood. Herein, we propose a theoretical possibility that such transient modifications of connectivity associated with ACh release, in addition to top-down glutamatergic input, may provide a neural mechanism for the temporal reactivation of attractors as neural correlates of memories. With baseline levels of ACh, the brain returns to quasi-attractor states, exhibiting transitive dynamics between several intrinsic internal states. This suggests that top-down attention may cause the attention-induced deformations between two types of attractor landscapes: the quasi-attractor landscape (Q-landscape, present under low-ACh, non-attentional conditions and the attractor landscape (A-landscape, present under high-ACh, top-down attentional conditions. We present a conceptual computational model based on experimental knowledge of the structure of PYRs and interneurons (INs in cortical layers 1 and 2/3 and discuss the possible physiological implications of our results.

  16. Neuronal classification and distribution in the central nervous system of the female mud crab, Scylla olivacea.

    Science.gov (United States)

    Kornthong, Napamanee; Tinikul, Yotsawan; Khornchatri, Kanjana; Saeton, Jirawat; Magerd, Sirilug; Suwansa-Ard, Saowaros; Kruangkum, Thanapong; Hanna, Peter J; Sobhon, Prasert

    2014-03-01

    The mud crab, Scylla olivacea, is one of the most economically valuable marine species in Southeast Asian countries. However, commercial cultivation is disadvantaged by reduced reproductive capacity in captivity. Therefore, an understanding of the general and detailed anatomy of central nervous system (CNS) is required before investigating the distribution and functions of neurotransmitters, neurohormones, and other biomolecules, involved with reproduction. We found that the anatomical structure of the brain is similar to other crabs. However, the ventral nerve cord (VNC) is unlike other caridian and dendrobrachiate decapods, as the subesophageal (SEG), thoracic and abdominal ganglia are fused, due to the reduction of abdominal segments and the tail. Neurons in clusters within the CNS varied in sizes, and we found that there were five distinct size classes (i.e., very small globuli, small, medium, large, and giant). Clusters in the brain and SEG contained mainly very small globuli and small-sized neurons, whereas, the VNC contained small-, medium-, large-, and giant-sized neurons. We postulate that the different sized neurons are involved in different functions. Copyright © 2013 Wiley Periodicals, Inc.

  17. Interaction of basal forebrain cholinergic neurons with the glucocorticoid system in stress regulation and cognitive impairment

    Directory of Open Access Journals (Sweden)

    Saswati ePaul

    2015-04-01

    Full Text Available A substantial number of studies on basal forebrain cholinergic neurons (BFCN have provided compelling evidence for their role in the etiology of stress, cognitive aging, Alzheimer’s disease (AD, and other neurodegenerative diseases. BFCN project to a broad range of cortical sites and limbic structures, including the hippocampus, and are involved in stress and cognition. In particular, the hippocampus, the primary target tissue of the glucocorticoid stress hormones, is associated with cognitive function in tandem with hypothalamic-pituitary-adrenal (HPA axis modulation. The present review summarizes glucocorticoid and HPA axis research to date in an effort to establish the manner in which stress affects the release of acetylcholine, glucocorticoids, and their receptor in the context of cognitive processes. We attempt to provide the molecular interactive link between the glucocorticoids and cholinergic system that contributes to BFCN degeneration in stress-induced acceleration of cognitive decline in aging and AD. We also discuss the importance of animal models in facilitating such studies for pharmacological use, which could help decipher disease states and propose leads for pharmacological intervention.

  18. Spread of neuronal degeneration in a dopaminergic, Lrrk-G2019S model of Parkinson disease

    Science.gov (United States)

    Hindle, Samantha J.; Elliott, Christopher J.H.

    2013-01-01

    Flies expressing the most common Parkinson disease (PD)-related mutation, LRRK2-G2019S, in their dopaminergic neurons show loss of visual function and degeneration of the retina, including mitochondrial abnormalities, apoptosis and autophagy. Since the photoreceptors that degenerate are not dopaminergic, this demonstrates nonautonomous degeneration, and a spread of pathology. This provides a model consistent with Braak’s hypothesis on progressive PD. The loss of visual function is specific for the G2019S mutation, implying the cause is its increased kinase activity, and is enhanced by increased neuronal activity. These data suggest novel explanations for the variability in animal models of PD. The specificity of visual loss to G2019S, coupled with the differences in neural firing rate, provide an explanation for the variability between people with PD in visual tests. PMID:23529190

  19. Unaltered Neuronal and Glial Counts in Animal Models of Magnetic Seizure Therapy and Electroconvulsive Therapy

    DEFF Research Database (Denmark)

    Dwork, A.J.; Christensen, J.R.; Larsen, K.B.

    2009-01-01

    Anatomical evidence of brain damage from electroconvulsive therapy (ECT) is lacking; but there are no modern stereological studies in primates documenting its safety. Magnetic seizure therapy (MST) is under development as a less invasive form of convulsive therapy, and there is only one prior...... report on its anatomical effects. We discerned no histological lesions in the brains of higher mammals subjected to electroconvulsive shock (ECS) or MST, under conditions that model closely those used in humans. We sought to extend these findings by determining whether these interventions affected...... no effect of either intervention on volumes or total number or numerical density of neurons or glia in hippocampus, frontal cortex, or subregions of these structures. Induction of seizures in a rigorous model of human ECT and MST therapy does not cause a change in the number of neurons or glia...

  20. DNA methylation alterations in iPSC- and hESC-derived neurons: potential implications for neurological disease modeling.

    Science.gov (United States)

    de Boni, Laura; Gasparoni, Gilles; Haubenreich, Carolin; Tierling, Sascha; Schmitt, Ina; Peitz, Michael; Koch, Philipp; Walter, Jörn; Wüllner, Ullrich; Brüstle, Oliver

    2018-01-01

    Genetic predisposition and epigenetic alterations are both considered to contribute to sporadic neurodegenerative diseases (NDDs) such as Parkinson's disease (PD). Since cell reprogramming and the generation of induced pluripotent stem cells (iPSCs) are themselves associated with major epigenetic remodeling, it remains unclear to what extent iPSC-derived neurons lend themselves to model epigenetic disease-associated changes. A key question to be addressed in this context is whether iPSC-derived neurons exhibit epigenetic signatures typically observed in neurons derived from non-reprogrammed human embryonic stem cells (hESCs). Here, we compare mature neurons derived from hESC and isogenic human iPSC generated from hESC-derived neural stem cells. Genome-wide 450 K-based DNA methylation and HT12v4 gene array expression analyses were complemented by a deep analysis of selected genes known to be involved in NDD. Our studies show that DNA methylation and gene expression patterns of isogenic hESC- and iPSC-derived neurons are markedly preserved on a genome-wide and single gene level. Overall, iPSC-derived neurons exhibit similar DNA methylation patterns compared to isogenic hESC-derived neurons. Further studies will be required to explore whether the epigenetic patterns observed in iPSC-derived neurons correspond to those detectable in native brain neurons.

  1. Multi-timescale Modeling of Activity-Dependent Metabolic Coupling in the Neuron-Glia-Vasculature Ensemble

    KAUST Repository

    Jolivet, Renaud

    2015-02-26

    Glucose is the main energy substrate in the adult brain under normal conditions. Accumulating evidence, however, indicates that lactate produced in astrocytes (a type of glial cell) can also fuel neuronal activity. The quantitative aspects of this so-called astrocyte-neuron lactate shuttle (ANLS) are still debated. To address this question, we developed a detailed biophysical model of the brain’s metabolic interactions. Our model integrates three modeling approaches, the Buxton-Wang model of vascular dynamics, the Hodgkin-Huxley formulation of neuronal membrane excitability and a biophysical model of metabolic pathways. This approach provides a template for large-scale simulations of the neuron-glia-vasculature (NGV) ensemble, and for the first time integrates the respective timescales at which energy metabolism and neuronal excitability occur. The model is constrained by relative neuronal and astrocytic oxygen and glucose utilization, by the concentration of metabolites at rest and by the temporal dynamics of NADH upon activation. These constraints produced four observations. First, a transfer of lactate from astrocytes to neurons emerged in response to activity. Second, constrained by activity-dependent NADH transients, neuronal oxidative metabolism increased first upon activation with a subsequent delayed astrocytic glycolysis increase. Third, the model correctly predicted the dynamics of extracellular lactate and oxygen as observed in vivo in rats. Fourth, the model correctly predicted the temporal dynamics of tissue lactate, of tissue glucose and oxygen consumption, and of the BOLD signal as reported in human studies. These findings not only support the ANLS hypothesis but also provide a quantitative mathematical description of the metabolic activation in neurons and glial cells, as well as of the macroscopic measurements obtained during brain imaging.

  2. Techniques for obtaining analytical solutions to the multicylinder somatic shunt cable model for passive neurones

    OpenAIRE

    Evans, J.D.; Kember, G.C.; Major, G.

    1992-01-01

    The somatic shunt cable model for neurones is extended to the case in which several equivalent cylinders, not necessarily of the same electrotonic length, emanate from the cell soma. The cable equation is assumed to hold in each cylinder and is solved with sealed end conditions and a lumped soma boundary condition at a common origin. A Green's function (G) is defined, corresponding to the voltage response to an instantaneous current pulse at an arbitrary point along one of the cylinders. An e...

  3. Errors in estimation of the input signal for integrate-and-fire neuronal models

    Czech Academy of Sciences Publication Activity Database

    Bibbona, E.; Lánský, Petr; Sacerdote, L.; Sirovich, R.

    2008-01-01

    Roč. 78, č. 1 (2008), s. 1-10 ISSN 1539-3755 R&D Projects: GA MŠk(CZ) LC554; GA AV ČR(CZ) 1ET400110401 Grant - others:EC(XE) MIUR PRIN 2005 Institutional research plan: CEZ:AV0Z50110509 Keywords : parameter estimation * stochastic neuronal model Subject RIV: BO - Biophysics Impact factor: 2.508, year: 2008 http://link.aps.org/abstract/PRE/v78/e011918

  4. Reduced activity of AMP-activated protein kinase protects against genetic models of motor neuron disease.

    Science.gov (United States)

    Lim, M A; Selak, M A; Xiang, Z; Krainc, D; Neve, R L; Kraemer, B C; Watts, J L; Kalb, R G

    2012-01-18

    A growing body of research indicates that amyotrophic lateral sclerosis (ALS) patients and mouse models of ALS exhibit metabolic dysfunction. A subpopulation of ALS patients possesses higher levels of resting energy expenditure and lower fat-free mass compared to healthy controls. Similarly, two mutant copper zinc superoxide dismutase 1 (mSOD1) mouse models of familial ALS possess a hypermetabolic phenotype. The pathophysiological relevance of the bioenergetic defects observed in ALS remains largely elusive. AMP-activated protein kinase (AMPK) is a key sensor of cellular energy status and thus might be activated in various models of ALS. Here, we report that AMPK activity is increased in spinal cord cultures expressing mSOD1, as well as in spinal cord lysates from mSOD1 mice. Reducing AMPK activity either pharmacologically or genetically prevents mSOD1-induced motor neuron death in vitro. To investigate the role of AMPK in vivo, we used Caenorhabditis elegans models of motor neuron disease. C. elegans engineered to express human mSOD1 (G85R) in neurons develops locomotor dysfunction and severe fecundity defects when compared to transgenic worms expressing human wild-type SOD1. Genetic reduction of aak-2, the ortholog of the AMPK α2 catalytic subunit in nematodes, improved locomotor behavior and fecundity in G85R animals. Similar observations were made with nematodes engineered to express mutant tat-activating regulatory (TAR) DNA-binding protein of 43 kDa molecular weight. Altogether, these data suggest that bioenergetic abnormalities are likely to be pathophysiologically relevant to motor neuron disease.

  5. Antipsychotic drugs rapidly induce dopamine neuron depolarization block in a developmental rat model of schizophrenia.

    Science.gov (United States)

    Valenti, Ornella; Cifelli, Pierangelo; Gill, Kathryn M; Grace, Anthony A

    2011-08-24

    Repeated administration of antipsychotic drugs to normal rats has been shown to induce a state of dopamine neuron inactivation known as depolarization block, which correlates with the ability of the drugs to exhibit antipsychotic efficacy and extrapyramidal side effects in schizophrenia patients. Nonetheless, in normal rats depolarization block requires weeks of antipsychotic drug administration, whereas schizophrenia patients exhibit initial effects soon after initiating antipsychotic drug treatment. We now report that, in a developmental disruption rat model of schizophrenia [methyl-azoxymethanol acetate (20 mg/kg, i.p.) injected into G17 pregnant female rats, with offspring tested as adults], the extant hyperdopaminergic state combines with the excitatory actions of a first- (haloperidol; 0.6 mg/kg, i.p.) and a second- (sertindole; 2.5 mg/kg, i.p.) generation antipsychotic drug to rapidly induce depolarization block in ventral tegmental area dopamine neurons. Acute injection of either antipsychotic drug induced an immediate reduction in the number of spontaneously active dopamine neurons (cells per electrode track; termed population activity). Repeated administration of either antipsychotic drug for 1, 3, 7, 15, and 21 d continued to reduce dopamine neuron population activity. Both acute and repeated effects on population activity were reversed by acute apomorphine injections, which is consistent with the reversal of dopamine neuron depolarization block. Although this action may account for the effects of D2 antagonist drugs on alleviating psychosis and the lack of development of tolerance in humans, the drugs appear to do so by inducing an offsetting deficit rather than attacking the primary pathology present in schizophrenia.

  6. Capturing Spike Variability in Noisy Izhikevich Neurons Using Point Process Generalized Linear Models.

    Science.gov (United States)

    Østergaard, Jacob; Kramer, Mark A; Eden, Uri T

    2018-01-01

    To understand neural activity, two broad categories of models exist: statistical and dynamical. While statistical models possess rigorous methods for parameter estimation and goodness-of-fit assessment, dynamical models provide mechanistic insight. In general, these two categories of models are separately applied; understanding the relationships between these modeling approaches remains an area of active research. In this letter, we examine this relationship using simulation. To do so, we first generate spike train data from a well-known dynamical model, the Izhikevich neuron, with a noisy input current. We then fit these spike train data with a statistical model (a generalized linear model, GLM, with multiplicative influences of past spiking). For different levels of noise, we show how the GLM captures both the deterministic features of the Izhikevich neuron and the variability driven by the noise. We conclude that the GLM captures essential features of the simulated spike trains, but for near-deterministic spike trains, goodness-of-fit analyses reveal that the model does not fit very well in a statistical sense; the essential random part of the GLM is not captured.

  7. Is the human mirror neuron system plastic? Evidence from a transcranial magnetic stimulation study.

    Science.gov (United States)

    Mehta, Urvakhsh Meherwan; Waghmare, Avinash V; Thirthalli, Jagadisha; Venkatasubramanian, Ganesan; Gangadhar, Bangalore N

    2015-10-01

    Virtual lesions in the mirror neuron network using inhibitory low-frequency (1Hz) transcranial magnetic stimulation (TMS) have been employed to understand its spatio-functional properties. However, no studies have examined the influence of neuro-enhancement by using excitatory high-frequency (20Hz) repetitive transcranial magnetic stimulation (HF-rTMS) on these networks. We used three forms of TMS stimulation (HF-rTMS, single and paired pulse) to investigate whether the mirror neuron system facilitates the motor system during goal-directed action observation relative to inanimate motion (motor resonance), a marker of putative mirror neuron activity. 31 healthy individuals were randomized to receive single-sessions of true or sham HF-rTMS delivered to the left inferior frontal gyrus - a component of the human mirror system. Motor resonance was assessed before and after HF-rTMS using three TMS cortical reactivity paradigms: (a) 120% of resting motor threshold (RMT), (b) stimulus intensity set to evoke motor evoked potential of 1-millivolt amplitude (SI1mV) and (c) a short latency paired pulse paradigm. Two-way RMANOVA showed a significant group (true versus sham) X occasion (pre- and post-HF-rTMS motor resonance) interaction effect for SI1mV [F(df)=6.26 (1, 29), p=0.018] and 120% RMT stimuli [F(df)=7.01 (1, 29), p=0.013] indicating greater enhancement of motor resonance in the true HF-rTMS group than the sham-group. This suggests that HF-rTMS could adaptively modulate properties of the mirror neuron system. This neuro-enhancement effect is a preliminary step that can open translational avenues for novel brain stimulation therapeutics targeting social-cognition deficits in schizophrenia and autism. Copyright © 2015 Elsevier B.V. All rights reserved.

  8. Autism and the mirror neuron system: Insights from learning and teaching

    OpenAIRE

    Vivanti, G; Rogers, SJ

    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 an...

  9. Functional integration of grafted neural stem cell-derived dopaminergic neurons monitored by optogenetics in an in vitro Parkinson model.

    Directory of Open Access Journals (Sweden)

    Jan Tønnesen

    Full Text Available Intrastriatal grafts of stem cell-derived dopamine (DA neurons induce behavioral recovery in animal models of Parkinson's disease (PD, but how they functionally integrate in host neural circuitries is poorly understood. Here, Wnt5a-overexpressing neural stem cells derived from embryonic ventral mesencephalon of tyrosine hydroxylase-GFP transgenic mice were expanded as neurospheres and transplanted into organotypic cultures of wild type mouse striatum. Differentiated GFP-labeled DA neurons in the grafts exhibited mature neuronal properties, including spontaneous firing of action potentials, presence of post-synaptic currents, and functional expression of DA D₂ autoreceptors. These properties resembled those recorded from identical cells in acute slices of intrastriatal grafts in the 6-hydroxy-DA-induced mouse PD model and from DA neurons in intact substantia nigra. Optogenetic activation or inhibition of grafted cells and host neurons using channelrhodopsin-2 (ChR2 and halorhodopsin (NpHR, respectively, revealed complex, bi-directional synaptic interactions between grafted cells and host neurons and extensive synaptic connectivity within the graft. Our data demonstrate for the first time using optogenetics that ectopically grafted stem cell-derived DA neurons become functionally integrated in the DA-denervated striatum. Further optogenetic dissection of the synaptic wiring between grafted and host neurons will be crucial to clarify the cellular and synaptic mechanisms underlying behavioral recovery as well as adverse effects following stem cell-based DA cell replacement strategies in PD.

  10. Neuronal functional connection graphs among multiple areas of the rat somatosensory system during spontaneous and evoked activities.

    Science.gov (United States)

    Zippo, Antonio G; Storchi, Riccardo; Nencini, Sara; Caramenti, Gian Carlo; Valente, Maurizio; Biella, Gabriele Eliseo M

    2013-01-01

    Small-World Networks (SWNs) represent a fundamental model for the comprehension of many complex man-made and biological networks. In the central nervous system, SWN models have been shown to fit well both anatomical and functional maps at the macroscopic level. However, the functional microscopic level, where the nodes of a network are represented by single neurons, is still poorly understood. At this level, although recent evidences suggest that functional connection graphs exhibit small-world organization, it is not known whether and how these maps, potentially distributed in multiple brain regions, change across different conditions, such as spontaneous and stimulus-evoked activities. We addressed these questions by analyzing the data from simultaneous multi-array extracellular recordings in three brain regions of rats, diversely involved in somatosensory information processing: the ventropostero-lateral thalamic nuclei, the primary somatosensory cortex and the centro-median thalamic nuclei. From both spike and Local Field Potential (LFP) recordings, we estimated the functional connection graphs by using the Normalized Compression Similarity for spikes and the Phase Synchrony for LFPs. Then, by using graph-theoretical statistics, we characterized the functional topology both during spontaneous activity and sensory stimulation. Our main results show that: (i) spikes and LFPs show SWN organization during spontaneous activity; (ii) after stimulation onset, while substantial functional graph reconfigurations occur both in spike and LFPs, small-worldness is nonetheless preserved; (iii) the stimulus triggers a significant increase of inter-area LFP connections without modifying the topology of intra-area functional connections. Finally, investigating computationally the functional substrate that supports the observed phenomena, we found that (iv) the fundamental concept of cell assemblies, transient groups of activating neurons, can be described by small

  11. Ghrelin Attenuates Retinal Neuronal Autophagy and Apoptosis in an Experimental Rat Glaucoma Model.

    Science.gov (United States)

    Zhu, Ke; Zhang, Meng-Lu; Liu, Shu-Ting; Li, Xue-Yan; Zhong, Shu-Min; Li, Fang; Xu, Ge-Zhi; Wang, Zhongfeng; Miao, Yanying

    2017-12-01

    Ghrelin, a natural ligand for the growth hormone secretagogue receptor type 1a (GHSR-1a), may protect retinal neurons against glaucomatous injury. We therefore characterized the underlying mechanism of the ghrelin/GHSR-1a-mediated neuroprotection with a rat chronic intraocular hypertension (COH) model. The rat COH model was produced by blocking episcleral veins. A combination of immunohistochemistry, Western blot, TUNEL assay, and retrograde labeling of retinal ganglion cells (RGCs) was used. Elevation of intraocular pressure induced a significant increase in ghrelin and GHSR-1a expression in retinal cells, including RGCs and Müller cells. Western blot confirmed that the protein levels of ghrelin exhibited a transient upregulation at week 2 after surgery (G2w), while the GHSR-1a protein levels were maintained at high levels from G2w to G4w. In COH retinas, the ratio of LC3-II/LC-I and beclin1, two autophagy-related proteins, were increased from G1w to G4w, and the cleavage product of caspase3, an apoptotic executioner, was detected from G2w to G4w. Intraperitoneal injection of ghrelin significantly increased the number of surviving RGCs; inhibited the changes of LC3-II/LC-I, beclin1, and the cleavage products of caspase3; and reduced the number of TUNEL-positive cells in COH retinas. Ghrelin treatment also reversed the decreased levels of p-Akt and p-mTOR, upregulated GHSR-1a protein levels, and attenuated glial fibrillary acidic protein levels in COH retinas. All these results suggest that ghrelin may provide neuroprotective effect in COH retinas through activating ghrelin/GHSR-1a system, which was mediated by inhibiting retinal autophagy, ganglion cell apoptosis, and Müller cell gliosis.

  12. Mathematical model of neuronal morphology: prenatal development of the human dentate nucleus.

    Science.gov (United States)

    Rajković, Katarina; Bačić, Goran; Ristanović, Dušan; Milošević, Nebojša T

    2014-01-01

    The aim of the study was to quantify the morphological changes of the human dentate nucleus during prenatal development using mathematical models that take into account main morphometric parameters. The camera lucida drawings of Golgi impregnated neurons taken from human fetuses of gestational ages ranging from 14 to 41 weeks were analyzed. Four morphometric parameters, the size of the neuron, the dendritic complexity, maximum dendritic density, and the position of maximum density, were obtained using the modified Scholl method and fractal analysis. Their increase during the entire prenatal development can be adequately fitted with a simple exponential. The three parameters describing the evolution of branching complexity of the dendritic arbor positively correlated with the increase of the size of neurons, but with different rate constants, showing that the complex development of the dendritic arbor is complete during the prenatal period. The findings of the present study are in accordance with previous crude qualitative data on prenatal development of the human dentate nucleus, but provide much greater amount of fine details. The mathematical model developed here provides a sound foundation enabling further studies on natal development or analyzing neurological disorders during prenatal development.

  13. Inferring structural connectivity using Ising couplings in models of neuronal networks.

    Science.gov (United States)

    Kadirvelu, Balasundaram; Hayashi, Yoshikatsu; Nasuto, Slawomir J

    2017-08-15

    Functional connectivity metrics have been widely used to infer the underlying structural connectivity in neuronal networks. Maximum entropy based Ising models have been suggested to discount the effect of indirect interactions and give good results in inferring the true anatomical connections. However, no benchmarking is currently available to assess the performance of Ising couplings against other functional connectivity metrics in the microscopic scale of neuronal networks through a wide set of network conditions and network structures. In this paper, we study the performance of the Ising model couplings to infer the synaptic connectivity in in silico networks of neurons and compare its performance against partial and cross-correlations for different correlation levels, firing rates, network sizes, network densities, and topologies. Our results show that the relative performance amongst the three functional connectivity metrics depends primarily on the network correlation levels. Ising couplings detected the most structural links at very weak network correlation levels, and partial correlations outperformed Ising couplings and cross-correlations at strong correlation levels. The result was consistent across varying firing rates, network sizes, and topologies. The findings of this paper serve as a guide in choosing the right functional connectivity tool to reconstruct the structural connectivity.

  14. Locus coeruleus: A brain region exhibiting neuronal alterations in Parkinson’s disease rat model

    Directory of Open Access Journals (Sweden)

    Samah M. Fathy

    2015-05-01

    Full Text Available Toxic insults lead to increased α-synuclein expression in dopaminergic neurons. However, little information is known about α-synuclein alterations in relation to tyrosine hydroxylase (TH changes in locus coeruleus (LC of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP rat model for Parkinson’s disease (PD. Four injections (15 mg/kg each of the neurotoxicant MPTP to rats led to an upregulation of α-synuclein level and increased immunoreactivity with aggregated protein in the MPTP-treated group as revealed by Western blotting and immunohistochemical techniques. Meanwhile, MPTP reduced the level of and caused immunoreactivity toward TH antibody in LC and adjoining noradrenergic neurons. These data indicate that MPTP can induce α-synuclein alterations in other brain regions that have been implicated in the pathogenesis of PD. The findings are also consistent with a pattern that α-synuclein modification influences the TH level.

  15. Alzheimer's Proteins, Oxidative Stress, and Mitochondrial Dysfunction Interplay in a Neuronal Model of Alzheimer's Disease

    Directory of Open Access Journals (Sweden)

    Antonella Bobba

    2010-01-01

    Full Text Available In this paper, we discuss the interplay between beta-amyloid (A peptide, Tau fragments, oxidative stress, and mitochondria in the neuronal model of cerebellar granule neurons (CGNs in which the molecular events reminiscent of AD are activated. The identification of the death route and the cause/effect relationships between the events leading to death could be helpful to manage the progression of apoptosis in neurodegeneration and to define antiapoptotic treatments acting on precocious steps of the death process. Mitochondrial dysfunction is among the earliest events linked to AD and might play a causative role in disease onset and progression. Recent studies on CGNs have shown that adenine nucleotide translocator (ANT impairment, due to interaction with toxic N-ter Tau fragment, contributes in a significant manner to bioenergetic failure and mitochondrial dysfunction. These findings open a window for new therapeutic strategies aimed at preserving and/or improving mitochondrial function.

  16. Modeling of Neuronal Growth In Vitro: Comparison of Simulation Tools NETMORPH and CX3D

    Directory of Open Access Journals (Sweden)

    Aćimović J

    2011-01-01

    Full Text Available We simulate the growth of neuronal networks using the two recently published tools, NETMORPH and CX3D. The goals of the work are (1 to examine and compare the simulation tools, (2 to construct a model of growth of neocortical cultures, and (3 to characterize the changes in network connectivity during growth, using standard graph theoretic methods. Parameters for the neocortical culture are chosen after consulting both the experimental and the computational work presented in the literature. The first (three weeks in culture are known to be a time of development of extensive dendritic and axonal arbors and establishment of synaptic connections between the neurons. We simulate the growth of networks from day 1 to day 21. It is shown that for the properly selected parameters, the simulators can reproduce the experimentally obtained connectivity. The selected graph theoretic methods can capture the structural changes during growth.

  17. Modeling of Neuronal Growth In Vitro: Comparison of Simulation Tools NETMORPH and CX3D.

    Science.gov (United States)

    Aćimović, J; Mäki-Marttunen, T; Havela, R; Teppola, H; Linne, M-L

    2011-01-01

    We simulate the growth of neuronal networks using the two recently published tools, NETMORPH and CX3D. The goals of the work are (1) to examine and compare the simulation tools, (2) to construct a model of growth of neocortical cultures, and (3) to characterize the changes in network connectivity during growth, using standard graph theoretic methods. Parameters for the neocortical culture are chosen after consulting both the experimental and the computational work presented in the literature. The first (three) weeks in culture are known to be a time of development of extensive dendritic and axonal arbors and establishment of synaptic connections between the neurons. We simulate the growth of networks from day 1 to day 21. It is shown that for the properly selected parameters, the simulators can reproduce the experimentally obtained connectivity. The selected graph theoretic methods can capture the structural changes during growth.

  18. Estimation in the partially observed stochastic Morris-Lecar neuronal model with particle filter and stochastic approximation methods

    DEFF Research Database (Denmark)

    Ditlevsen, Susanne; Samson, Adeline

    2014-01-01

    Parameter estimation in multidimensional diffusion models with only one coordinate observed is highly relevant in many biological applications, but a statistically difficult problem. In neuroscience, the membrane potential evolution in single neurons can be measured at high frequency, but biophys...

  19. Mirror neurons as a model for the science and treatment of stuttering.

    Science.gov (United States)

    Snyder, Gregory J; Waddell, Dwight E; Blanchet, Paul

    2016-01-06

    Persistent developmental stuttering is generally considered a speech disorder and affects ∼1% of the global population. While mainstream treatments continue to rely on unreliable behavioral speech motor targets, an emerging research perspective utilizes the mirror neuron system hypothesis as a neural substrate in the science and treatment of stuttering. The purpose of this exploratory study is to test the viability of the mirror neuron system hypothesis in the fluency enhancement of those who stutter. Participants were asked to speak while they were producing self-generated manual gestures, producing and visually perceiving self-generated manual gestures, and visually perceiving manual gestures, relative to a nonmanual gesture control speaking condition. Data reveal that all experimental speaking conditions enhanced fluent speech in all research participants, and the simultaneous perception and production of manual gesturing trended toward greater efficacious fluency enhancement. Coupled with existing research, we interpret these data as suggestive of fluency enhancement through subcortical involvement within multiple levels of an action understanding mirror neuron network. In addition, incidental findings report that stuttering moments were observed to simultaneously occur both orally and manually. Consequently, these data suggest that stuttering behaviors are compensatory, distal manifestations over multiple expressive modalities to an underlying centralized genetic neural substrate of the disorder.

  20. A model for the neuronal substrate of dead reckoning and memory in arthropods: a comparative computational and behavioral study.

    Science.gov (United States)

    Bernardet, Ulysses; Bermúdez I Badia, Sergi; Verschure, Paul F M J

    2008-06-01

    Returning to the point of departure after exploring the environment is a key capability for most animals. In the absence of landmarks, this task will be solved by integrating direction and distance traveled over time. This is referred to as path integration or dead reckoning. An important question is how the nervous systems of navigating animals such as the 1 mm(3) brain of ants can integrate local information in order to make global decision. In this article we propose a neurobiologically plausible system of storing and retrieving direction and distance information. The path memory of our model builds on the well established concept of population codes, moreover our system does not rely on trigonometric functions or other complex non-linear operations such as multiplication, but only uses biologically plausible operations such as integration and thresholding. We test our model in two paradigms; in the first paradigm the system receives input from a simulated compass, in the second paradigm, the model is tested against behavioral data recorded from 17 ants. We were able to show that our path memory system was able to reliably encode and compute the angle of the vector pointing to the start location, and that the system stores the total length of the trajectory in a dependable way. From the structure and behavior of our model, we derive testable predictions both at the level of observable behavior as well as on the anatomy and physiology of its underlying neuronal substrate.

  1. Exendin-4 ameliorates motor neuron degeneration in cellular and animal models of amyotrophic lateral sclerosis.

    Directory of Open Access Journals (Sweden)

    Yazhou Li

    Full Text Available Amyotrophic lateral sclerosis (ALS is a devastating neurodegenerative disease characterized by a progressive loss of lower motor neurons in the spinal cord. The incretin hormone, glucagon-like peptide-1 (GLP-1, facilitates insulin signaling, and the long acting GLP-1 receptor agonist exendin-4 (Ex-4 is currently used as an anti-diabetic drug. GLP-1 receptors are widely expressed in the brain and spinal cord, and our prior studies have shown that Ex-4 is neuroprotective in several neurodegenerative disease rodent models, including stroke, Parkinson's disease and Alzheimer's disease. Here we hypothesized that Ex-4 may provide neuroprotective activity in ALS, and hence characterized Ex-4 actions in both cell culture (NSC-19 neuroblastoma cells and in vivo (SOD1 G93A mutant mice models of ALS. Ex-4 proved to be neurotrophic in NSC-19 cells, elevating choline acetyltransferase (ChAT activity, as well as neuroprotective, protecting cells from hydrogen peroxide-induced oxidative stress and staurosporine-induced apoptosis. Additionally, in both wild-type SOD1 and mutant SOD1 (G37R stably transfected NSC-19 cell lines, Ex-4 protected against trophic factor withdrawal-induced toxicity. To assess in vivo translation, SOD1 mutant mice were administered vehicle or Ex-4 at 6-weeks of age onwards to end-stage disease via subcutaneous osmotic pump to provide steady-state infusion. ALS mice treated with Ex-4 showed improved glucose tolerance and normalization of behavior, as assessed by running wheel, compared to control ALS mice. Furthermore, Ex-4 treatment attenuated neuronal cell death in the lumbar spinal cord; immunohistochemical analysis demonstrated the rescue of neuronal markers, such as ChAT, associated with motor neurons. Together, our results suggest that GLP-1 receptor agonists warrant further evaluation to assess whether their neuroprotective potential is of therapeutic relevance in ALS.

  2. Identification models of the nervous system.

    Science.gov (United States)

    Zipser, D

    1992-01-01

    It has been widely observed that when artificial neural networks are trained by supervised learning to do computations that also occur in the nervous system, the behavior of the model neurons often closely resembles that of the real neurons involved in the task. It is not immediately clear why this should be the case or what use can be made of models generated by supervised learning. Here, recent developments are reviewed and analysed in an attempt to clarify these issues. This analysis is facilitated by treating supervised learning models of the brain as a special case of system identification, a general and well-studied modeling paradigm. The neural systems identification paradigm provides a systematic way to generate realistic models starting with a high-level description of a hypothesized computation and some architectural and physiological constraints about the area being modeled. There is no inherent limitation to the realism that can be incorporated into identification models. This approach eliminates the need to find neural implementation algorithms by ad hoc means and provides neuroscientists with a convenient way to build models that account for observed data.

  3. Dysregulation of the Autophagy-Endolysosomal System in Amyotrophic Lateral Sclerosis and Related Motor Neuron Diseases

    Directory of Open Access Journals (Sweden)

    Asako Otomo

    2012-01-01

    Full Text Available Amyotrophic lateral sclerosis (ALS is a heterogeneous group of incurable motor neuron diseases (MNDs characterized by a selective loss of upper and lower motor neurons in the brain and spinal cord. Most cases of ALS are sporadic, while approximately 5–10% cases are familial. More than 16 causative genes for ALS/MNDs have been identified and their underlying pathogenesis, including oxidative stress, endoplasmic reticulum stress, excitotoxicity, mitochondrial dysfunction, neural inflammation, protein misfolding and accumulation, dysfunctional intracellular trafficking, abnormal RNA processing, and noncell-autonomous damage, has begun to emerge. It is currently believed that a complex interplay of multiple toxicity pathways is implicated in disease onset and progression. Among such mechanisms, ones that are associated with disturbances of protein homeostasis, the ubiquitin-proteasome system and autophagy, have recently been highlighted. Although it remains to be determined whether disease-associated protein aggregates have a toxic or protective role in the pathogenesis, the formation of them results from the imbalance between generation and degradation of misfolded proteins within neuronal cells. In this paper, we focus on the autophagy-lysosomal and endocytic degradation systems and implication of their dysfunction to the pathogenesis of ALS/MNDs. The autophagy-endolysosomal pathway could be a major target for the development of therapeutic agents for ALS/MNDs.

  4. Relationship between activity in human primary motor cortex during action observation and the mirror neuron system.

    Directory of Open Access Journals (Sweden)

    James M Kilner

    Full Text Available The attenuation of the beta cortical oscillations during action observation has been interpreted as evidence of a mirror neuron system (MNS in humans. Here we investigated the modulation of beta cortical oscillations with the viewpoint of an observed action. We asked subjects to observe videos of an actor making a variety of arm movements. We show that when subjects were observing arm movements there was a significant modulation of beta oscillations overlying left and right sensorimotor cortices. This pattern of attenuation was driven by the side of the screen on which the observed movement occurred and not by the hand that was observed moving. These results are discussed in terms of the firing patterns of mirror neurons in F5 which have been reported to have similar properties.

  5. Testing Brain Overgrowth and Synaptic Models of Autism Using NPC’s and Neurons from Patient-Derived IPS Cells

    Science.gov (United States)

    2014-10-01

    Zikopoulos, B. & Barbas, H. Altered neural connectivity in excitatory and inhibitory cortical circuits in autism . Frontiers in human neuroscience 7, 609, doi:10.3389/fnhum.2013.00609 (2013). 11. APPENDICES: Nothing to report ...Models of Autism Using NPC’s and Neurons from Patient- Derived IPS Cells PRINCIPAL INVESTIGATOR: Fred H. Gage, Ph.D...SUBTITLE Testing Brain Overgrowth and Synaptic Models of Autism Using NPC’s and Neurons from Patient- Derived IPS Cells 5a. CONTRACT

  6. Using induced pluripotent stem cells derived neurons to model brain diseases

    Directory of Open Access Journals (Sweden)

    Cindy E McKinney

    2017-01-01

    Full Text Available The ability to use induced pluripotent stem cells (iPSC to model brain diseases is a powerful tool for unraveling mechanistic alterations in these disorders. Rodent models of brain diseases have spurred understanding of pathology but the concern arises that they may not recapitulate the full spectrum of neuron disruptions associated with human neuropathology. iPSC derived neurons, or other neural cell types, provide the ability to access pathology in cells derived directly from a patient's blood sample or skin biopsy where availability of brain tissue is limiting. Thus, utilization of iPSC to study brain diseases provides an unlimited resource for disease modelling but may also be used for drug screening for effective therapies and may potentially be used to regenerate aged or damaged cells in the future. Many brain diseases across the spectrum of neurodevelopment, neurodegenerative and neuropsychiatric are being approached by iPSC models. The goal of an iPSC based disease model is to identify a cellular phenotype that discriminates the disease-bearing cells from the control cells. In this mini-review, the importance of iPSC cell models validated for pluripotency, germline competency and function assessments is discussed. Selected examples for the variety of brain diseases that are being approached by iPSC technology to discover or establish the molecular basis of the neuropathology are discussed.

  7. The stomatogastric nervous system of the medicinal leech: its anatomy, physiology and associated aminergic neurons.

    Science.gov (United States)

    Mesce, Karen A; Alania, Magda; Gaudry, Quentin; Puhl, Joshua G

    2018-03-29

    Blood feeding is an essential and signature activity of the medicinal leech species H irudo verbana Despite keen interest in understanding the neuronal substrates of this behavior, a major component of the nervous system associated with feeding has remained overlooked. In this study, for the first time, we report on the presence and characteristics of five stomatogastric ganglia (STGs) comprising the visceral stomatogastric nervous system (STN) of the leech. Although a brief report was published by Ruth Hanke in 1948 indicating that a ring of three ganglia (not five) was associated with the cephalic ganglia, this information was never integrated into subsequent neurobiological studies of feeding. Here, the anatomical features of the STGs are described, as are the morphological and electrophysiological characteristics of neurons originating in them. We also determined that two of the five STGs (STG-1 and STG-3) each contained two relatively large (ca. 40 µm diameter) serotonergic neurons. The STN was also enriched with dopaminergic and serotonergic arborizations; however, no intrinsic dopaminergic somata were observed. The trajectory of the serotonergic large lateral (LL) neuron, a command-like cell for feeding, was documented to project directly to the STN and not to the jaw and pharyngeal musculature as previously reported, thus reopening the important question of how the LL cell activates and coordinates biting activity with pharyngeal swallowing. Additional studies revealed that the LL cell is excited by blood serum applied to the lip and is strongly inhibited by dopamine. These findings provide a new foundation for understanding the regulation and modulation of neural networks involved in feeding. © 2018. Published by The Company of Biologists Ltd.

  8. Dynamical modeling of the moth pheromone-sensitive olfactory receptor neuron within its sensillar environment.

    Directory of Open Access Journals (Sweden)

    Yuqiao Gu

    Full Text Available In insects, olfactory receptor neurons (ORNs, surrounded with auxiliary cells and protected by a cuticular wall, form small discrete sensory organs--the sensilla. The moth pheromone-sensitive sensillum is a well studied example of hair-like sensillum that is favorable to both experimental and modeling investigations. The model presented takes into account both the molecular processes of ORNs, i.e. the biochemical reactions and ionic currents giving rise to the receptor potential, and the cellular organization and compartmentalization of the organ represented by an electrical circuit. The number of isopotential compartments needed to describe the long dendrite bearing pheromone receptors was determined. The transduction parameters that must be modified when the number of compartments is increased were identified. This model reproduces the amplitude and time course of the experimentally recorded receptor potential. A first complete version of the model was analyzed in response to pheromone pulses of various strengths. It provided a quantitative description of the spatial and temporal evolution of the pheromone-dependent conductances, currents and potentials along the outer dendrite and served to determine the contribution of the various steps in the cascade to its global sensitivity. A second simplified version of the model, utilizing a single depolarizing conductance and leak conductances for repolarizing the ORN, was derived from the first version. It served to analyze the effects on the sensory properties of varying the electrical parameters and the size of the main sensillum parts. The consequences of the results obtained on the still uncertain mechanisms of olfactory transduction in moth ORNs--involvement or not of G-proteins, role of chloride and potassium currents--are discussed as well as the optimality of the sensillum organization, the dependence of biochemical parameters on the neuron spatial extension and the respective contributions

  9. Motor-auditory-visual integration: The role of the human mirror neuron system in communication and communication disorders

    OpenAIRE

    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 neuro-imaging techniques (such as fMRI and mu suppression in the EEG). It reflects an integration of motor-auditory-visual information processing related to aspects of language learning including action understanding and recognition. Such int...

  10. Neuronal deletion of caspase 8 protects against brain injury in mouse models of controlled cortical impact and kainic acid-induced excitotoxicity.

    Directory of Open Access Journals (Sweden)

    Maryla Krajewska

    Full Text Available Acute brain injury is an important health problem. Given the critical position of caspase 8 at the crossroads of cell death pathways, we generated a new viable mouse line (Ncasp8(-/-, in which the gene encoding caspase 8 was selectively deleted in neurons by cre-lox system.Caspase 8 deletion reduced rates of neuronal cell death in primary neuronal cultures and in whole brain organotypic coronal slice cultures prepared from 4 and 8 month old mice and cultivated up to 14 days in vitro. Treatments of cultures with recombinant murine TNFα (100 ng/ml or TRAIL (250 ng/mL plus cyclohexamide significantly protected neurons against cell death induced by these apoptosis-inducing ligands. A protective role of caspase 8 deletion in vivo was also demonstrated using a controlled cortical impact (CCI model of traumatic brain injury (TBI and seizure-induced brain injury caused by kainic acid (KA. Morphometric analyses were performed using digital imaging in conjunction with image analysis algorithms. By employing virtual images of hundreds of brain sections, we were able to perform quantitative morphometry of histological and immunohistochemical staining data in an unbiased manner. In the TBI model, homozygous deletion of caspase 8 resulted in reduced lesion volumes, improved post-injury motor performance, superior learning and memory retention, decreased apoptosis, diminished proteolytic processing of caspases and caspase substrates, and less neuronal degeneration, compared to wild type, homozygous cre, and caspase 8-floxed control mice. In the KA model, Ncasp8(-/- mice demonstrated superior survival, reduced seizure severity, less apoptosis, and reduced caspase 3 processing. Uninjured aged knockout mice showed improved learning and memory, implicating a possible role for caspase 8 in cognitive decline with aging.Neuron-specific deletion of caspase 8 reduces brain damage and improves post-traumatic functional outcomes, suggesting an important role for this

  11. Whole-Brain Mapping of Neuronal Activity in the Learned Helplessness Model of Depression.

    Science.gov (United States)

    Kim, Yongsoo; Perova, Zinaida; Mirrione, Martine M; Pradhan, Kith; Henn, Fritz A; Shea, Stephen; Osten, Pavel; Li, Bo

    2016-01-01

    Some individuals are resilient, whereas others succumb to despair in repeated stressful situations. The neurobiological mechanisms underlying such divergent behavioral responses remain unclear. Here, we employed an automated method for mapping neuronal activity in search of signatures of stress responses in the entire mouse brain. We used serial two-photon tomography to detect expression of c-FosGFP - a marker of neuronal activation - in c-fosGFP transgenic mice subjected to the learned helplessness (LH) procedure, a widely used model of stress-induced depression-like phenotype in laboratory animals. We found that mice showing "helpless" behavior had an overall brain-wide reduction in the level of neuronal activation compared with mice showing "resilient" behavior, with the exception of a few brain areas, including the locus coeruleus, that were more activated in the helpless mice. In addition, the helpless mice showed a strong trend of having higher similarity in whole-brain activity profile among individuals, suggesting that helplessness is represented by a more stereotypic brain-wide activation pattern. This latter effect was confirmed in rats subjected to the LH procedure, using 2-deoxy-2[18F]fluoro-D-glucose positron emission tomography to assess neural activity. Our findings reveal distinct brain activity markings that correlate with adaptive and maladaptive behavioral responses to stress, and provide a framework for further studies investigating the contribution of specific brain regions to maladaptive stress responses.

  12. Biophysical properties and computational modeling of calcium spikes in serotonergic neurons of the dorsal raphe nucleus.

    Science.gov (United States)

    Tuckwell, Henry C

    2013-06-01

    Serotonergic neurons of the dorsal raphe nuclei, with their extensive innervation of nearly the whole brain have important modulatory effects on many cognitive and physiological processes. They play important roles in clinical depression and other psychiatric disorders. In order to quantify the effects of serotonergic transmission on target cells it is desirable to construct computational models and to this end these it is necessary to have details of the biophysical and spike properties of the serotonergic neurons. Here several basic properties are reviewed with data from several studies since the 1960s to the present. The quantities included are input resistance, resting membrane potential, membrane time constant, firing rate, spike duration, spike and afterhyperpolarization (AHP) amplitude, spike threshold, cell capacitance, soma and somadendritic areas. The action potentials of these cells are normally triggered by a combination of sodium and calcium currents which may result in autonomous pacemaker activity. We here analyse the mechanisms of high-threshold calcium spikes which have been demonstrated in these cells the presence of TTX (tetrodotoxin). The parameters for calcium dynamics required to give calcium spikes are quite different from those for regular spiking which suggests the involvement of restricted parts of the soma-dendritic surface as has been found, for example, in hippocampal neurons. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  13. Peripheral Mechanosensory Neuron Dysfunction Underlies Tactile and Behavioral Deficits in Mouse Models of ASDs.

    Science.gov (United States)

    Orefice, Lauren L; Zimmerman, Amanda L; Chirila, Anda M; Sleboda, Steven J; Head, Joshua P; Ginty, David D

    2016-07-14

    Patients with autism spectrum disorders (ASDs) commonly experience aberrant tactile sensitivity, yet the neural alterations underlying somatosensory dysfunction and the extent to which tactile deficits contribute to ASD characteristics are unknown. We report that mice harboring mutations in Mecp2, Gabrb3, Shank3, and Fmr1 genes associated with ASDs in humans exhibit altered tactile discrimination and hypersensitivity to gentle touch. Deletion of Mecp2 or Gabrb3 in peripheral somatosensory neurons causes mechanosensory dysfunction through loss of GABAA receptor-mediated presynaptic inhibition of inputs to the CNS. Remarkably, tactile defects resulting from Mecp2 or Gabrb3 deletion in somatosensory neurons during development, but not in adulthood, cause social interaction deficits and anxiety-like behavior. Restoring Mecp2 expression exclusively in the somatosensory neurons of Mecp2-null mice rescues tactile sensitivity, anxiety-like behavior, and social interaction deficits, but not lethality, memory, or motor deficits. Thus, mechanosensory processing defects contribute to anxiety-like behavior and social interaction deficits in ASD mouse models. PAPERCLIP. Copyright © 2016 Elsevier Inc. All rights reserved.

  14. iPSC-Based Models to Unravel Key Pathogenetic Processes Underlying Motor Neuron Disease Development

    Directory of Open Access Journals (Sweden)

    Irene Faravelli

    2014-10-01

    Full Text Available Motor neuron diseases (MNDs are neuromuscular disorders affecting rather exclusively upper motor neurons (UMNs and/or lower motor neurons (LMNs. The clinical phenotype is characterized by muscular weakness and atrophy leading to paralysis and almost invariably death due to respiratory failure. Adult MNDs include sporadic and familial amyotrophic lateral sclerosis (sALS-fALS, while the most common infantile MND is represented by spinal muscular atrophy (SMA. No effective treatment is ccurrently available for MNDs, as for the vast majority of neurodegenerative disorders, and cures are limited to supportive care and symptom relief. The lack of a deep understanding of MND pathogenesis accounts for the difficulties in finding a cure, together with the scarcity of reliable in vitro models. Recent progresses in stem cell field, in particular in the generation of induced Pluripotent Stem Cells (iPSCs has made possible for the first time obtaining substantial amounts of human cells to recapitulate in vitro some of the key pathogenetic processes underlying MNDs. In the present review, recently published studies involving the use of iPSCs to unravel aspects of ALS and SMA pathogenesis are discussed with an overview of their implications in the process of finding a cure for these still orphan disorders.

  15. The frequency response, coherence, and information capacity of two neuronal models.

    Science.gov (United States)

    Stein, R B; French, A S; Holden, A V

    1972-03-01

    Two neuronal models are analyzed in which subthreshold inputs are integrated either without loss (perfect integrator) or with a decay which follows an exponential time course (leaky integrator). Linear frequency response functions for these models are compared using sinusoids, Poisson-distributed impulses, or gaussian white noise as inputs. The responses of both models show the nonlinear behavior characteristic of a rectifier for sinusoidal inputs of sufficient amplitude. The leaky integrator shows another nonlinearity in which responses become phase locked to cyclic stimuli. Addition of white noise reduces the distortions due to phase locking. Both models also show selective attenuation of high-frequency components with white noise inputs. Input, output, and cross-spectra are computed using inputs having a broad frequency spectrum. Measures of the coherence and information transmission between the input and output of the models are also derived. Steady inputs, which produce a constant "carrier" rate, and intrinsic sources, which produce variability in the discharge of neurons, may either increase or decrease coherence; however, information transmission using inputs with a broad spectrum is generally increased by steady inputs and reduced by intrinsic variability.

  16. Modeling of System Families

    National Research Council Canada - National Science Library

    Feiler, Peter

    2007-01-01

    .... The Society of Automotive Engineers (SAE) Architecture Analysis & Design Language (AADL) is an industry-standard, architecture-modeling notation specifically designed to support a component- based approach to modeling embedded systems...

  17. 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...

  18. Stochastic differential equation models for ion channel noise in Hodgkin-Huxley neurons

    Science.gov (United States)

    Goldwyn, Joshua H.; Imennov, Nikita S.; Famulare, Michael; Shea-Brown, Eric

    2011-04-01

    The random transitions of ion channels between conducting and nonconducting states generate a source of internal fluctuations in a neuron, known as channel noise. The standard method for modeling the states of ion channels nonlinearly couples continuous-time Markov chains to a differential equation for voltage. Beginning with the work of R. F. Fox and Y.-N. Lu [Phys. Rev. EMTHDE91539-375510.1103/PhysRevE.49.3421 49, 3421 (1994)], there have been attempts to generate simpler models that use stochastic differential equation (SDEs) to approximate the stochastic spiking activity produced by Markov chain models. Recent numerical investigations, however, have raised doubts that SDE models can capture the stochastic dynamics of Markov chain models.We analyze three SDE models that have been proposed as approximations to the Markov chain model: one that describes the states of the ion channels and two that describe the states of the ion channel subunits. We show that the former channel-based approach can capture the distribution of channel noise and its effects on spiking in a Hodgkin-Huxley neuron model to a degree not previously demonstrated, but the latter two subunit-based approaches cannot. Our analysis provides intuitive and mathematical explanations for why this is the case. The temporal correlation in the channel noise is determined by the combinatorics of bundling subunits into channels, but the subunit-based approaches do not correctly account for this structure. Our study confirms and elucidates the findings of previous numerical investigations of subunit-based SDE models. Moreover, it presents evidence that Markov chain models of the nonlinear, stochastic dynamics of neural membranes can be accurately approximated by SDEs. This finding opens a door to future modeling work using SDE techniques to further illuminate the effects of ion channel fluctuations on electrically active cells.

  19. Central Projection of Antennal Sensory Neurons in the Central Nervous System of the Mirid Bug Apolygus lucorum (Meyer-Dür).

    Science.gov (United States)

    Xie, Gui-Ying; Zhao, Xin-Cheng; Ma, Bai-Wei; Guo, Pei; Li, Guo-Ping; Feng, Hong-Qiang; Wu, Guo-Liang

    2016-01-01

    The mirid bug Apolygus lucorum (Meyer-Dür), a polyphagous pest, is dependent on olfactory cues to locate various host plant species and mates. In this study, we traced the projection pathway of the antennal sensory neurons and visualized their projection patterns in the central nervous system of A. lucorum through confocal microscopy and digital reconstructions. We also examined the glomerular organization of the primary olfactory center of the brain, the antennal lobe, and created a three-dimensional model of the glomeruli. We found that the axons of the sensory neurons project into the brain via the ipsilateral antennal nerve, and descend further into the gnathal ganglion, prothoracic ganglion, mesothoracic ganglion, and metathoracic ganglion, and reach as far as to the abdominal ganglion. Such a projection pattern indicates that antennal sensory neurons of A. lucorum may be potentially directly connected to motor neurons. The antennal lobe, however, is the major target area of antennal sensory neurons. The antennal lobe is composed of a large number of glomeruli, i.e. 70-80 glomeruli in one AL of A. lucorum. The results of this study which provide information about the basic anatomical arrangement of the brain olfactory center of A. lucorum, are important for further investigations of chemosensory encoding mechanisms of the mirid bug.

  20. Central Projection of Antennal Sensory Neurons in the Central Nervous System of the Mirid Bug Apolygus lucorum (Meyer-Dür.

    Directory of Open Access Journals (Sweden)

    Gui-Ying Xie

    Full Text Available The mirid bug Apolygus lucorum (Meyer-Dür, a polyphagous pest, is dependent on olfactory cues to locate various host plant species and mates. In this study, we traced the projection pathway of the antennal sensory neurons and visualized their projection patterns in the central nervous system of A. lucorum through confocal microscopy and digital reconstructions. We also examined the glomerular organization of the primary olfactory center of the brain, the antennal lobe, and created a three-dimensional model of the glomeruli. We found that the axons of the sensory neurons project into the brain via the ipsilateral antennal nerve, and descend further into the gnathal ganglion, prothoracic ganglion, mesothoracic ganglion, and metathoracic ganglion, and reach as far as to the abdominal ganglion. Such a projection pattern indicates that antennal sensory neurons of A. lucorum may be potentially directly connected to motor neurons. The antennal lobe, however, is the major target area of antennal sensory neurons. The antennal lobe is composed of a large number of glomeruli, i.e. 70-80 glomeruli in one AL of A. lucorum. The results of this study which provide information about the basic anatomical arrangement of the brain olfactory center of A. lucorum, are important for further investigations of chemosensory encoding mechanisms of the mirid bug.

  1. A model based approach in observing the activity of neuronal populations for the prediction of epileptic seizures

    International Nuclear Information System (INIS)

    Chong, M.S.; Nesic, D.; Kuhlmann, L.; Postoyan, R.; Varsavsky, A.; Cook, M.

    2010-01-01

    Full text: Epilepsy is a common neurological disease that affects 0.5-1 % of the world's population. In cases where known treatments cannot achieve complete recovery, seizure prediction is essential so that preventive measures can be undertaken to prevent resultant injury. The elcctroencephalogram (EEG) is a widely used diagnostic tool for epilepsy. However, the EEG does not provide a detailed view of the underlying seizure causing neuronal mechanisms. Knowing the dynamics of the neuronal population is useful because tracking the evolution of the neuronal mechanisms will allow us to track the brain's progression from interictal to ictal state. Wendling and colleagues proposed a parameterised mathematical model that represents the activity of interconnected neuronal populations. By modifying the parameters, this model is able to reproduce signals that are very similar to the real EEG depicting commonly observed patterns during interictal and ictal periods. The transition from non-seizure to seizure activity, as seen in the EEG. is hypothesised to be due to the impairment of inhibition. Using Wendling's model, we designed a deterministic nonlinear estimator to recover the average membrane potential of the neuronal populations from a single channel EEG signal. for any fixed and known parameter values. Our nonlinear estimator is analytically proven to asymptotically converge to the true state of the model and illustrated in simulations. We were able to computationally observe the dynamics of the three neuronal populations described in the model: excitatory, fast and slow inhibitory populations. This forms a first step towards the prediction of epileptic seiwres. (author)

  2. Modeling the emergence of circadian rhythms in a clock neuron network.

    Directory of Open Access Journals (Sweden)

    Luis Diambra

    Full Text Available Circadian rhythms in pacemaker cells persist for weeks in constant darkness, while in other types of cells the molecular oscillations that underlie circadian rhythms damp rapidly under the same conditions. Although much progress has been made in understanding the biochemical and cellular basis of circadian rhythms, the mechanisms leading to damped or self-sustained oscillations remain largely unknown. There exist many mathematical models that reproduce the circadian rhythms in the case of a single cell of the Drosophila fly. However, not much is known about the mechanisms leading to coherent circadian oscillation in clock neuron networks. In this work we have implemented a model for a network of interacting clock neurons to describe the emergence (or damping of circadian rhythms in Drosophila fly, in the absence of zeitgebers. Our model consists of an array of pacemakers that interact through the modulation of some parameters by a network feedback. The individual pacemakers are described by a well-known biochemical model for circadian oscillation, to which we have added degradation of PER protein by light and multiplicative noise. The network feedback is the PER protein level averaged over the whole network. In particular, we have investigated the effect of modulation of the parameters associated with (i the control of net entrance of PER into the nucleus and (ii the non-photic degradation of PER. Our results indicate that the modulation of PER entrance into the nucleus allows the synchronization of clock neurons, leading to coherent circadian oscillations under constant dark condition. On the other hand, the modulation of non-photic degradation cannot reset the phases of individual clocks subjected to intrinsic biochemical noise.

  3. Neuron Growth on Carbon Nanotube Thread Bio-Scaffolds for Repair of Central Nervous System Damage

    Science.gov (United States)

    Mast, David; Pixley, Sarah; Schulz, Mark; Shanov, Vessilin

    2012-02-01

    Approximately 11,000 new spinal cord injuries occur each year. Repairing such central nervous system (CNS) damage has proven to be very difficult. We report on in vitro experiments using carbon nanotube (CNT) threads as a bio-scaffold for promoting CNS repair via directed neuron regrowth along the CNT material. Mouse brain neurospheres, containing neuronal stem cells, neurons and support glia, were observed to attach to and grow along laminin-coated CNT threads in vitro. However, due to their limited mobility, only neurospheres close to the threads attach. To increase cellular attachment to the threads, we exploit the fact that these cells can exhibit enhanced, directed migration along an externally applied electric field. Recent in vitro cell growth was carried out in chambers containing several parallel CNT threads with electrical connections extending out of the incubator so that a voltage applied across adjacent threads established an appropriate electric field. Electrochemical Impedance Spectroscopy, Cyclic Voltammetry and dc and ac IV measurements were used to monitor cell growth and attachment as a function of applied electric field and time. Cell migration and attachment were also investigated using time lapse photography in a separate growth chamber mounted on the stage of an optical microscope.

  4. Sensitivity to perception level differentiates two subnetworks within the mirror neuron system.

    Science.gov (United States)

    Simon, Shiri; Mukamel, Roy

    2017-05-01

    Mirror neurons are a subset of brain cells that discharge during action execution and passive observation of similar actions. An open question concerns the functional role of their ability to match observed and executed actions. Since understanding of goals requires conscious perception of actions, we expect that mirror neurons potentially involved in action goal coding, will be modulated by changes in action perception level. Here, we manipulated perception level of action videos depicting short hand movements and measured the corresponding fMRI BOLD responses in mirror regions. Our results show that activity levels within a network of regions, including the sensorimotor cortex, primary motor cortex, dorsal premotor cortex and posterior superior temporal sulcus, are sensitive to changes in action perception level, whereas activity levels in the inferior frontal gyrus, ventral premotor cortex, supplementary motor area and superior parietal lobule are invariant to such changes. In addition, this parcellation to two sub-networks manifest as smaller functional distances within each group of regions during task and resting state. Our results point to functional differences between regions within the mirror neurons system which may have implications with respect to their possible role in action understanding. © The Author (2017). Published by Oxford University Press.

  5. Structural and functional properties of a probabilistic model of neuronal connectivity in a simple locomotor network

    Science.gov (United States)

    Merrison-Hort, Robert; Soffe, Stephen R; Borisyuk, Roman

    2018-01-01

    Although, in most animals, brain connectivity varies between individuals, behaviour is often similar across a species. What fundamental structural properties are shared across individual networks that define this behaviour? We describe a probabilistic model of connectivity in the hatchling Xenopus tadpole spinal cord which, when combined with a spiking model, reliably produces rhythmic activity corresponding to swimming. The probabilistic model allows calculation of structural characteristics that reflect common network properties, independent of individual network realisations. We use the structural characteristics to study examples of neuronal dynamics, in the complete network and various sub-networks, and this allows us to explain the basis for key experimental findings, and make predictions for experiments. We also study how structural and functional features differ between detailed anatomical connectomes and those generated by our new, simpler, model (meta-model). PMID:29589828

  6. Developing a neuronal model for the pathophysiology of schizophrenia based on the nature of electrophysiological actions of dopamine in the prefrontal cortex.

    Science.gov (United States)

    Yang, C R; Seamans, J K; Gorelova, N

    1999-08-01

    This review covers some recent findings of the electrophysiological mechanisms through which mesocortical dopamine modulates prefrontal cortical neurons. Dopamine has been shown to modulate several ionic conductances located along the soma-dendritic axis of prefrontal cortical pyramidal neurons. These ionic currents include high-voltage-activated calcium currents and slowly inactivating Na+ and K+ currents. They contribute actively in processing functionally segregated inputs during synaptic integration. In addition, dopamine mainly depolarizes the fast-spiking subtype of local GABAergic interneurons that connect the pyramidal neurons. This latter action can indirectly control pyramidal cell excitability. These electrophysiological data indicate that the actions of dopamine are neither "excitatory" nor "inhibitory" in pyramidal prefrontal cortex neurons. Rather, the actions of dopamine are dependent on somadendritic loci, timing of the arrival of synaptic inputs, strength of synaptic inputs, as well as the membrane potential range at which the PFC neuron is operating at a given moment. Based on available electrophysiological findings, a neuronal model of the pathophysiology of schizophrenia is presented. This model proposes that episodic hypo- and hyperactivity of the PFC and the associated dysfunctional mesocortical dopamine system (and their interconnected brain regions) may coexist in the same schizophrenic patient in the course of the illness. We hypothesize that the dysfunctional mesocortical dopamine input to the PFC may lead to abnormal modulation of ionic channels distributed in the dendritic-somatic compartments of PFC pyramidal neurons that project to the ventral tegmental area and/or nucleus accumbens. In some schizophrenics, a reduction of mesocortical dopamine to below optimal levels and/or a loss of local GABAergic inputs may result in a dysfunctional integration of extrinsic associative inputs by Ca2+ channel activity in the distal dendrites of PFC

  7. Early-life Social Isolation Impairs the Gonadotropin-Inhibitory Hormone Neuronal Activity and Serotonergic System in Male Rats

    Directory of Open Access Journals (Sweden)

    Tomoko eSoga

    2015-11-01

    Full Text Available Social isolation in early life deregulates the serotonergic system of the brain, compromising reproductive function. Gonadotropin-inhibitory hormone (GnIH neurons in the dorsomedial hypothalamic nucleus are critical to the inhibitory regulation of gonadotropin-releasing hormone neuronal activity in the brain and release of luteinising hormone by the pituitary gland. Although GnIH responds to stress, the role of GnIH in social isolation-induced deregulation of the serotonin system and reproductive function remains unclear. We investigated the effect of social isolation in early life on the serotonergic–GnIH neuronal system using enhanced green fluorescent protein (EGFP-tagged GnIH-transgenic rats. Socially isolated rats were observed for anxious and depressive behaviours. Using immunohistochemistry, we examined c-Fos protein expression in EGFP–GnIH neurons in 9-week-old adult male rats after 6 weeks post-weaning isolation or group -housing. We also inspected serotonergic fibre juxtapositions in EGFP–GnIH neurons in control and socially isolated male rats. Socially isolated rats exhibited anxious and depressive behaviours. The total number of EGFP–GnIH neurons was the same in control and socially isolated rats, but c-Fos expression in GnIH neurons was significantly reduced in socially isolated rats. Serotonin fibre juxtapositions on EGFP–GnIH neurons was also lower in socially isolated rats. In addition, levels of tryptophan hydroxylase mRNA expression in the dorsal raphe nucleus were significantly attenuated in these rats. These results suggest that social isolation in early life results in lower serotonin levels, which reduce GnIH neuronal activity and may lead to reproductive failure.

  8. Nanotopography induced contact guidance of the F11 cell line during neuronal differentiation: a neuronal model cell line for tissue scaffold development

    International Nuclear Information System (INIS)

    Wieringa, Paul; Micera, Silvestro; Tonazzini, Ilaria; Cecchini, Marco

    2012-01-01

    The F11 hybridoma, a dorsal root ganglion-derived cell line, was used to investigate the response of nociceptive sensory neurons to nanotopographical guidance cues. This established this cell line as a model of peripheral sensory neuron growth for tissue scaffold design. Cells were seeded on substrates of cyclic olefin copolymer (COC) films imprinted via nanoimprint lithography (NIL) with a grating pattern of nano-scale grooves and ridges. Different ridge widths were employed to alter the focal adhesion formation, thereby changing the cell/substrate interaction. Differentiation was stimulated with forskolin in culture medium consisting of either 1 or 10% fetal bovine serum (FBS). Per medium condition, similar neurite alignment was achieved over the four day period, with the 1% serum condition exhibiting longer, more aligned neurites. Immunostaining for focal adhesions found the 1% FBS condition to also have fewer, less developed focal adhesions. The robust response of the F11 to guidance cues further builds on the utility of this cell line as a sensory neuron model, representing a useful tool to explore the design of regenerative guidance tissue scaffolds. (paper)

  9. A three-dimensional spatiotemporal receptive field model explains responses of area MT neurons to naturalistic movies

    Science.gov (United States)

    Nishimoto, Shinji; Gallant, Jack L.

    2012-01-01

    Area MT has been an important target for studies of motion processing. However, previous neurophysiological studies of MT have used simple stimuli that do not contain many of the motion signals that occur during natural vision. In this study we sought to determine whether views of area MT neurons developed using simple stimuli can account for MT responses under more naturalistic conditions. We recorded responses from macaque area MT neurons during stimulation with naturalistic movies. We then used a quantitative modeling framework to discover which specific mechanisms best predict neuronal responses under these challenging conditions. We find that the simplest model that accurately predicts responses of MT neurons consists of a bank of V1-like filters, each followed by a compressive nonlinearity, a divisive nonlinearity and linear pooling. Inspection of the fit models shows that the excitatory receptive fields of MT neurons tend to lie on a single plane within the three-dimensional spatiotemporal frequency domain, and suppressive receptive fields lie off this plane. However, most excitatory receptive fields form a partial ring in the plane and avoid low temporal frequencies. This receptive field organization ensures that most MT neurons are tuned for velocity but do not tend to respond to ambiguous static textures that are aligned with the direction of motion. In sum, MT responses to naturalistic movies are largely consistent with predictions based on simple stimuli. However, models fit using naturalistic stimuli reveal several novel properties of MT receptive fields that had not been shown in prior experiments. PMID:21994372

  10. Mulberry fruit protects dopaminergic neurons in toxin-induced Parkinson's disease models.

    Science.gov (United States)

    Kim, Hyo Geun; Ju, Mi Sun; Shim, Jin Sup; Kim, Min Cheol; Lee, Sang-Hun; Huh, Youngbuhm; Kim, Sun Yeou; Oh, Myung Sook

    2010-07-01

    Parkinson's disease (PD), one of the most common neurodegenerative disorders, is characterised by the loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc) to the striatum (ST), and involves oxidative stress. Mulberry fruit from Morus alba L. (Moraceae) is commonly eaten, and has long been used in traditional oriental medicine. It contains well-known antioxidant agents such as anthocyanins. The present study examined the protective effects of 70 % ethanol extract of mulberry fruit (ME) against neurotoxicity in in vitro and in vivo PD models. In SH-SY5Y cells stressed with 6-hydroxydopamine (6-OHDA), ME significantly protected the cells from neurotoxicity in a dose-dependent manner. Other assays demonstrated that the protective effect of ME was mediated by its antioxidant and anti-apoptotic effects, regulating reactive oxygen species and NO generation, Bcl-2 and Bax proteins, mitochondrial membrane depolarisation and caspase-3 activation. In mesencephalic primary cells stressed with 6-OHDA or 1-methyl-4-phenylpyridinium (MPP+), pre-treatment with ME also protected dopamine neurons, showing a wide range of effective concentrations in MPP+-induced toxicity. In the sub-acute mouse PD model induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), ME showed a preventative effect against PD-like symptoms (bradykinesia) in the behavioural test and prevented MPTP-induced dopaminergic neuronal damage in an immunocytochemical analysis of the SNpc and ST. These results indicate that ME has neuroprotective effects in in vitro and in vivo PD models, and that it may be useful in preventing or treating PD.

  11. Modeling pharmacological clock and memory patterns of interval timing in a striatal beat-frequency model with realistic, noisy neurons

    Directory of Open Access Journals (Sweden)

    Sorinel A. Oprisan

    2011-09-01

    Full Text Available In most species, the capability of perceiving and using the passage of time in the seconds-to-minutes range (interval timing is not only accurate but also scalar: errors in time estimation are linearly related to the estimated duration. The ubiquity of scalar timing extends over behavioral, lesion, and pharmacological manipulations. For example, in mammals, dopaminergic drugs induce an immediate, scalar change in the perceived time (clock pattern, whereas cholinergic drugs induce a gradual, scalar change in perceived time (memory pattern. How do these properties emerge from unreliable, noisy neurons firing in the milliseconds range? Neurobiological information relative to the brain circuits involved in interval timing provide support for an Striatal Beat Frequency (SBF model, in which time is coded by the coincidental activation of striatal spiny neurons by cortical neural oscillators. While biologically plausible, the impracticality of perfect oscillators, or their lack thereof, questions this mechanism in a brain with noisy neurons. We explored the computational mechanisms required for the clock and memory patterns in an SBF model with biophysically realistic and noisy Morris-Lecar neurons (SBF-ML. Under the assumption that dopaminergic drugs modulate the firing frequency of cortical oscillators, and that cholinergic drugs modulate the memory representation of the criterion time, we show that our SBF-ML model can reproduce the pharmacological clock and memory patterns observed in the literature. Numerical results also indicate that parameter variability (noise – which is ubiquitous in the form of small fluctuations in the intrinsic frequencies of neural oscillators within and between trails, and in the errors in recording/retrieving stored information related to criterion time – seems to be critical for the time-scale invariance of the clock and memory patterns.

  12. Oxidative Stress Associated with Neuronal Apoptosis in Experimental Models of Epilepsy

    Directory of Open Access Journals (Sweden)

    Marisela Méndez-Armenta

    2014-01-01

    Full Text Available Epilepsy is considered one of the most common neurological disorders worldwide. Oxidative stress produced by free radicals may play a role in the initiation and progression of epilepsy; the changes in the mitochondrial and the oxidative stress state can lead mechanism associated with neuronal death pathway. Bioenergetics state failure and impaired mitochondrial function include excessive free radical production with impaired synthesis of antioxidants. This review summarizes evidence that suggest what is the role of oxidative stress on induction of apoptosis in experimental models of epilepsy.

  13. Effects of cocaine history on postsynaptic GABA receptors on dorsal raphe serotonin neurons in a stress-induced relapse model in rats.

    Science.gov (United States)

    Li, Chen; Kirby, Lynn G

    2016-01-01

    The serotonin (5-hydroxytryptamine, 5-HT) system plays an important role in stress-related psychiatric disorders and substance abuse. Stressors and stress hormones can inhibit the dorsal raphe nucleus (DRN)-5-HT system, which composes the majority of forebrain-projecting 5-HT. This inhibition is mediated via stimulation of GABA synaptic activity at DRN-5-HT neurons. Using swim stress-induced reinstatement of morphine conditioned place-preference, recent data from our laboratory indicate that morphine history sensitizes DRN-5-HT neurons to GABAergic inhibitory effects of stress. Moreover, GABAA receptor-mediated inhibition of the serotonergic DRN is required for this reinstatement. In our current experiment, we tested the hypothesis that GABAergic sensitization of DRN-5-HT neurons is a neuroadaptation elicited by multiple classes of abused drugs across multiple models of stress-induced relapse by applying a chemical stressor (yohimbine) to induce reinstatement of previously extinguished cocaine self-administration in Sprague-Dawley rats. Whole-cell patch-clamp recordings of GABA synaptic activity in DRN-5-HT neurons were conducted after the reinstatement. Behavioral data indicate that yohimbine triggered reinstatement of cocaine self-administration. Electrophysiology data indicate that 5-HT neurons in the cocaine group exposed to yohimbine had increased amplitude of inhibitory postsynaptic currents compared to yoked-saline controls exposed to yohimbine or unstressed animals in both drug groups. These data, together with previous findings, indicate that interaction between psychostimulant or opioid history and chemical or physical stressors may increase postsynaptic GABA receptor density and/or sensitivity in DRN-5-HT neurons. Such mechanisms may result in serotonergic hypofunction and consequent dysphoric mood states which confer vulnerability to stress-induced drug reinstatement. Copyright © 2015 Elsevier B.V. and ECNP. All rights reserved.

  14. Genetic background effects on disease onset and lifespan of the mutant dynactin p150Glued mouse model of motor neuron disease.

    Science.gov (United States)

    Heiman-Patterson, Terry D; Blankenhorn, Elizabeth P; Sher, Roger B; Jiang, Juliann; Welsh, Priscilla; Dixon, Meredith C; Jeffrey, Jeremy I; Wong, Philip; Cox, Gregory A; Alexander, Guillermo M

    2015-01-01

    Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease primarily affecting motor neurons in the central nervous system. Although most cases of ALS are sporadic, about 5-10% of cases are familial (FALS) with approximately 20% of FALS caused by mutations in the Cu/Zn superoxide dismutase (SOD1) gene. We have reported that hSOD1-G93A transgenic mice modeling this disease show a more severe phenotype when the transgene is bred on a pure SJL background and a milder phenotype when bred on a pure B6 background and that these phenotype differences link to a region on mouse Chromosome 17.To examine whether other models of motor neuron degeneration are affected by genetic background, we bred the mutant human dynactin p150Glued (G59S-hDCTN1) transgene onto inbred SJL and B6 congenic lines. This model is based on an autosomal dominant lower motor neuron disease in humans linked to a mutation in the p150Glued subunit of the dynactin complex. As seen in hSOD1-G93A mice, we observed a more severe phenotype with earlier disease onset (pdisease onset in hSOD1-G93A mice also showed delays onset in G59S-hDCTN1 mice suggesting that at least some genetic modifiers are shared. We have shown that genetic background influences phenotype in G59S-hDCTN1 mice, in part through a region of chromosome 17 similar to the G93-hSOD1 ALS mouse model. These results support the presence of genetic modifiers in both these models some of which may be shared. Identification of these modifiers will highlight intracellular pathways involved in motor neuron disease and provide new therapeutic targets that may be applicable to motor neuron degeneration.

  15. A new glucocerebrosidase-deficient neuronal cell model provides a tool to probe pathophysiology and therapeutics for Gaucher disease

    Directory of Open Access Journals (Sweden)

    Wendy Westbroek

    2016-07-01

    Full Text Available Glucocerebrosidase is a lysosomal hydrolase involved in the breakdown of glucosylceramide. Gaucher disease, a recessive lysosomal storage disorder, is caused by mutations in the gene GBA1. Dysfunctional glucocerebrosidase leads to accumulation of glucosylceramide and glycosylsphingosine in various cell types and organs. Mutations in GBA1 are also a common genetic risk factor for Parkinson disease and related synucleinopathies. In recent years, research on the pathophysiology of Gaucher disease, the molecular link between Gaucher and Parkinson disease, and novel therapeutics, have accelerated the need for relevant cell models with GBA1 mutations. Although induced pluripotent stem cells, primary rodent neurons, and transfected neuroblastoma cell lines have been used to study the effect of glucocerebrosidase deficiency on neuronal function, these models have limitations because of challenges in culturing and propagating the cells, low yield, and the introduction of exogenous mutant GBA1. To address some of these difficulties, we established a high yield, easy-to-culture mouse neuronal cell model with nearly complete glucocerebrosidase deficiency representative of Gaucher disease. We successfully immortalized cortical neurons from embryonic null allele gba−/− mice and the control littermate (gba+/+ by infecting differentiated primary cortical neurons in culture with an EF1α-SV40T lentivirus. Immortalized gba−/− neurons lack glucocerebrosidase protein and enzyme activity, and exhibit a dramatic increase in glucosylceramide and glucosylsphingosine accumulation, enlarged lysosomes, and an impaired ATP-dependent calcium-influx response; these phenotypical characteristics were absent in gba+/+ neurons. This null allele gba−/− mouse neuronal model provides a much-needed tool to study the pathophysiology of Gaucher disease and to evaluate new therapies.

  16. No neuronal loss, but alterations of the GDNF system in asymptomatic diverticulosis.

    Science.gov (United States)

    Barrenschee, Martina; Wedel, Thilo; Lange, Christina; Hohmeier, Ines; Cossais, François; Ebsen, Michael; Vogel, Ilka; Böttner, Martina

    2017-01-01

    Glial cell line-derived neurotrophic factor (GDNF) is a potent neurotrophic factor known to promote the survival and maintenance of neurons not only in the developing but also in the adult enteric nervous system. As diverticular disease (DD) is associated with reduced myenteric neurons, alterations of the GDNF system were studied in asymptomatic diverticulosis (diverticulosis) and DD. Morphometric analysis for quantifying myenteric ganglia and neurons were assessed in colonic full-thickness sections of patients with diverticulosis and controls. Samples of tunica muscularis (TM) and laser-microdissected myenteric ganglia from patients with diverticulosis, DD and controls were analyzed for mRNA expression levels of GDNF, GFRA1, and RET by RT-qPCR. Myenteric protein expression of both receptors was quantified by fluorescence-immunohistochemistry of patients with diverticulosis, DD, and controls. Although no myenteric morphometric alterations were found in patients with diverticulosis, GDNF, GFRA1 and RET mRNA expression was down-regulated in the TM of patients with diverticulosis as well as DD. Furthermore GFRA1 and RET myenteric plexus mRNA expression of patients with diverticulosis and DD was down-regulated, whereas GDNF remained unaltered. Myenteric immunoreactivity of the receptors GFRα1 and RET was decreased in both asymptomatic diverticulosis and DD patients. Our data provide evidence for an impaired GDNF system at gene and protein level not only in DD but also during early stages of diverticula formation. Thus, the results strengthen the idea of a disturbed GDNF-responsiveness as contributive factor for a primary enteric neuropathy involved in the pathogenesis and disturbed intestinal motility observed in DD.

  17. Neuronal background of activation of estivated snails, with special attention to the monoaminergic system: a biochemical, physiological, and neuroanatomical study.

    Science.gov (United States)

    Hernádi, L; Vehovszky, A; Gyori, J; Hiripi, L

    2008-02-01

    Osmotic stimulation activates both estivated and inactivated specimens of Helix pomatia and increases their central arousal. High-pressure liquid chromatography has shown that, during activation, the level of both serotonin and dopamine decreases in the central nervous system (CNS) but increases in the foot and heart, organs that are involved in the eversion of the body. In isolated CNS from activated animals, the firing frequency of the heart-modulator serotonergic (RPas) neurons is significantly higher than that in the CNS of estivated or inactivated animals. These neurons innervate both the heart and the anterior aorta. In semi-intact preparations, distilled water (an osmotic stimulus) applied to the mantle collar increases their firing frequency, whereas tactile stimulation evokes their inhibition. Extracellularly applied monoamines mimic the effect of peripheral stimuli: serotonin (0.1-10 microM) increases the activity of the RPas neurons, whereas dopamine (0.1-10 microM) inhibits their activity. Tyrosine-hydroxylase immunocytochemistry and retrograde neurobiotin tracing have revealed similar bipolar receptor cells in the mantle collar and tail, organs that are exposed to environmental stimuli in estivated animals. Serotonin immunocytochemistry carried out on the same tissues does not visualize receptor cells but labels a dense network of fibers that appear to innervate neurobiotin-labeled receptor cells. The combination of neurobiotin-labeling of RPas neurons and immunolabeling suggests that RPas neurons receive direct dopaminergic inputs from receptor cells and serotonergic inputs from central serotonergic neurons, indicating that central serotonergic neurons are interconnected. Thus, the RPas neurons may belong to neuronal elements of the arousal system.

  18. Dental pulp stem cells promote regeneration of damaged neuron cells on the cellular model of Alzheimer's disease.

    Science.gov (United States)

    Wang, Feixiang; Jia, Yali; Liu, Jiajing; Zhai, Jinglei; Cao, Ning; Yue, Wen; He, Huixia; Pei, Xuetao

    2017-06-01

    Alzheimer's disease (AD) is an incurable neurodegenerative disease and many types of stem cells have been used in AD therapy with some favorable effects. In this study, we investigated the potential therapeutical effects of human dental pulp stem cells (hDPSCs) on AD cellular model which established by okadaic acid (OA)-induced damage to human neuroblastoma cell line, SH-SY5Y, in vitro for 24 h. After confirmed the AD cellular model, the cells were co-culture with hDPSCs by transwell co-culture system till 24 h for treatment. Then the cytomorphology of the hDPSCs-treated cells were found to restore gradually with re-elongation of retracted dendrites. Meanwhile, Cell Counting Kit-8 assay and Hoechst 33258 staining showed that hDPSCs caused significant increase in the viability and decrease in apoptosis of the model cells, respectively. Observation of DiI labeling also exhibited the prolongation dendrites in hDPSCs-treated cells which were obviously different from the retraction dendrites in AD model cells. Furthermore, specific staining of α-tubulin and F-actin demonstrated that the hDPSCs-treated cells had the morphology of restored neurons, with elongated dendrites, densely arranged microfilaments, and thickened microtubular fibrils. In addition, results from western blotting revealed that phosphorylation at Ser 396 of Tau protein was significantly suppressed by adding of hDPSCs. These results indicate that hDPSCs may promote regeneration of damaged neuron cells in vitro model of AD and may serve as a useful cell source for treatment of AD. © 2017 International Federation for Cell Biology.

  19. Extraction of Inter-Aural Time Differences Using a Spiking Neuron Network Model of the Medial Superior Olive

    Directory of Open Access Journals (Sweden)

    Jörg Encke

    2018-03-01

    Full Text Available The mammalian auditory system is able to extract temporal and spectral features from sound signals at the two ears. One important cue for localization of low-frequency sound sources in the horizontal plane are inter-aural time differences (ITDs which are first analyzed in the medial superior olive (MSO in the brainstem. Neural recordings of ITD tuning curves at various stages along the auditory pathway suggest that ITDs in the mammalian brainstem are not represented in form of a Jeffress-type place code. An alternative is the hemispheric opponent-channel code, according to which ITDs are encoded as the difference in the responses of the MSO nuclei in the two hemispheres. In this study, we present a physiologically-plausible, spiking neuron network model of the mammalian MSO circuit and apply two different methods of extracting ITDs from arbitrary sound signals. The network model is driven by a functional model of the auditory periphery and physiological models of the cochlear nucleus and the MSO. Using a linear opponent-channel decoder, we show that the network is able to detect changes in ITD with a precision down to 10 μs and that the sensitivity of the decoder depends on the slope of the ITD-rate functions. A second approach uses an artificial neuronal network to predict ITDs directly from the spiking output of the MSO and ANF model. Using this predictor, we show that the MSO-network is able to reliably encode static and time-dependent ITDs over a large frequency range, also for complex signals like speech.

  20. In vitro differentiation of bone marrow stromal cells into neurons and glial cells and differential protein expression in a two-compartment bone marrow stromal cell/neuron co-culture system.

    Science.gov (United States)

    Qi, Xu; Shao, Ming; Peng, Haisheng; Bi, Zhenggang; Su, Zhiqiang; Li, Hulun

    2010-07-01

    This study was performed to establish a bone marrow stromal cell (BMSC)/neuron two-compartment co-culture model in which differentiation of BMSCs into neurons could occur without direct contact between the two cell types, and to investigate protein expression changes during differentiation of this entirely BMSC-derived population. Cultured BMSCs isolated from Wistar rats were divided into three groups: BMSC culture, BMSC/neuron co-culture and BMSC/neuron two-compartment co-culture. Cells were examined for neuron-specific enolase (NSE) and glial fibrillary acidic protein (GFAP) expression. The electrophysiological behavior of the BMSCs was examined using patch clamping. Proteins that had significantly different expression levels in BMSCs cultured alone and co-cultured with neurons were studied using a protein chip-mass spectroscopy technique. Expression of NSE and GFAP were significantly higher in co-culture cells than in two-compartment co-culture cells, and significantly higher in both co-culture groups than in BMSCs cultured alone. Five proteins showed significant changes in expression during differentiation: TIP39_RAT and CALC_RAT underwent increases, and INSL6_RAT, PNOC_RAT and PCSK1_RAT underwent decreases in expression. We conclude that BMSCs can differentiate into neurons during both contact co-culture with neurons and two-compartment co-culture with neurons. The rate at which BMSCs differentiated into neurons was higher in contact co-culture than in non-contact co-culture.

  1. eGFP expression under the Uchl1 promoter labels corticospinal motor neurons and a subpopulation of degeneration resistant spinal motor neurons in ALS mouse models

    Science.gov (United States)

    Yasvoina, Marina V.

    Current understanding of basic cellular and molecular mechanisms for motor neuron vulnerability during motor neuron disease initiation and progression is incomplete. The complex cytoarchitecture and cellular heterogeneity of the cortex and spinal cord greatly impedes our ability to visualize, isolate, and study specific neuron populations in both healthy and diseased states. We generated a novel reporter line, the Uchl1-eGFP mouse, in which cortical and spinal components of motor neuron circuitry are genetically labeled with eGFP under the Uchl1 promoter. A series of cellular and anatomical analyses combined with retrograde labeling, molecular marker expression, and electrophysiology were employed to determine identity of eGFP expressing cells in the motor cortex and the spinal cord of novel Uchl1-eGFP reporter mice. We conclude that eGFP is expressed in corticospinal motor neurons (CSMN) in the motor cortex and a subset of S-type alpha and gamma spinal motor neurons (SMN) in the spinal cord. hSOD1G93A and Alsin-/- mice, mouse models for amyotrophic lateral sclerosis (ALS), were bred to Uchl1-eGFP reporter mouse line to investigate the pathophysiology and underlying mechanisms of CSMN degeneration in vivo. Evidence suggests early and progressive degeneration of CSMN and SMN in the hSOD1G93A transgenic mice. We show an early increase of autophagosome formation in the apical dendrites of vulnerable CSMN in hSOD1G93A-UeGFP mice, which is localized to the apical dendrites. In addition, labeling S-type alpha and gamma SMN in the hSOD1G93A-UeGFP mice provide a unique opportunity to study basis of their resistance to degeneration. Mice lacking alsin show moderate clinical phenotype and mild CSMN axon degeneration in the spinal cord, which suggests vulnerability of CSMN. Therefore, we investigated the CSMN cellular and axon defects in aged Alsin-/- mice bred to Uchl1-eGFP reporter mouse line. We show that while CSMN are preserved and lack signs of degeneration, CSMN axons

  2. Discrimination of communication vocalizations by single neurons and groups of neurons in the auditory midbrain.

    Science.gov (United States)

    Schneider, David M; Woolley, Sarah M N

    2010-06-01

    Many social animals including songbirds use communication vocalizations for individual recognition. The perception of vocalizations depends on the encoding of complex sounds by neurons in the ascending auditory system, each of which is tuned to a particular subset of acoustic features. Here, we examined how well the responses of single auditory neurons could be used to discriminate among bird songs and we compared discriminability to spectrotemporal tuning. We then used biologically realistic models of pooled neural responses to test whether the responses of groups of neurons discriminated among songs better than the responses of single neurons and whether discrimination by groups of neurons was related to spectrotemporal tuning and trial-to-trial response variability. The responses of single auditory midbrain neurons could be used to discriminate among vocalizations with a wide range of abilities, ranging from chance to 100%. The ability to discriminate among songs using single neuron responses was not correlated with spectrotemporal tuning. Pooling the responses of pairs of neurons generally led to better discrimination than the average of the two inputs and the most discriminating input. Pooling the responses of three to five single neurons continued to improve neural discrimination. The increase in discriminability was largest for groups of neurons with similar spectrotemporal tuning. Further, we found that groups of neurons with correlated spike trains achieved the largest gains in discriminability. We simulated neurons with varying levels of temporal precision and measured the discriminability of responses from single simulated neurons and groups of simulated neurons. Simulated neurons with biologically observed levels of temporal precision benefited more from pooling correlated inputs than did neurons with highly precise or imprecise spike trains. These findings suggest that pooling correlated neural responses with the levels of precision observed in the

  3. Development of a sensory neuronal cell model for the estimation of mild eye irritation.

    Science.gov (United States)

    Lilja, Johanna; Forsby, Anna

    2004-10-01

    In an attempt to improve the in vitro test strategy for the estimation of eye irritation, a neuronal cell model has been developed, with cells expressing vanilloid receptor type 1 (VR1) nociceptors. The currently accepted method for measuring eye irritancy is the ethically and scientifically criticised Draize rabbit eye test, despite the fact that alternative in vitro methods are available which have proved to be reliable and reproducible for predicting severe ocular toxicity. However, no alternative tests for measuring neuronal stimulation have yet been developed, and the prediction of eye irritation in the mild range is therefore insufficient. VR1 is a nociceptor localised in C-fibre neurons innervating the cornea and the surrounding tissue, and it responds to potentially damaging stimuli by releasing Ca2+ into the cytoplasm. As a sensory endpoint, [Ca2+]i was measured in VR1 transfected cells, as well as in control cells. Short-term cell cytotoxicity studies (cell membrane rupture and morphological divergence) were used to determine the non-corrosive concentrations of the test chemicals. Preliminary results indicated that hygiene products used daily may induce eye irritation via VR1 nociceptors. The lowest toxic concentration (0.025%) of liquid hand soap, as determined by morphologic divergences of cells, generated an 80% increase in [Ca2+]i over the basal [Ca2+]i in VR1 transfected cells, whereas the non-specific [Ca2+]i increased by 33%. Furthermore, all the endpoints studied indicated that shampoo for children was less active than shampoo for adults. If this method is successfully validated with standardised reference chemicals, the model could complete the test battery of in vitro alternatives, resulting in the saving of thousands of laboratory animals.

  4. MicroRNA Profiling Reveals Marker of Motor Neuron Disease in ALS Models.

    Science.gov (United States)

    Hoye, Mariah L; Koval, Erica D; Wegener, Amy J; Hyman, Theodore S; Yang, Chengran; O'Brien, David R; Miller, Rebecca L; Cole, Tracy; Schoch, Kathleen M; Shen, Tao; Kunikata, Tomonori; Richard, Jean-Philippe; Gutmann, David H; Maragakis, Nicholas J; Kordasiewicz, Holly B; Dougherty, Joseph D; Miller, Timothy M

    2017-05-31

    Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder marked by the loss of motor neurons (MNs) in the brain and spinal cord, leading to fatally debilitating weakness. Because this disease predominantly affects MNs, we aimed to characterize the distinct expression profile of that cell type to elucidate underlying disease mechanisms and to identify novel targets that inform on MN health during ALS disease time course. microRNAs (miRNAs) are short, noncoding RNAs that can shape the expression profile of a cell and thus often exhibit cell-type-enriched expression. To determine MN-enriched miRNA expression, we used Cre recombinase-dependent miRNA tagging and affinity purification in mice. By defining the in vivo miRNA expression of MNs, all neurons, astrocytes, and microglia, we then focused on MN-enriched miRNAs via a comparative analysis and found that they may functionally distinguish MNs postnatally from other spinal neurons. Characterizing the levels of the MN-enriched miRNAs in CSF harvested from ALS models of MN disease demonstrated that one miRNA (miR-218) tracked with MN loss and was responsive to an ALS therapy in rodent models. Therefore, we have used cellular expression profiling tools to define the distinct miRNA expression of MNs, which is likely to enrich future studies of MN disease. This approach enabled the development of a novel, drug-responsive marker of MN disease in ALS rodents. SIGNIFICANCE STATEMENT Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease in which motor neurons (MNs) in the brain and spinal cord are selectively lost. To develop tools to aid in our understanding of the distinct expression profiles of MNs and, ultimately, to monitor MN disease progression, we identified small regulatory microRNAs (miRNAs) that were highly enriched or exclusive in MNs. The signal for one of these MN-enriched miRNAs is detectable in spinal tap biofluid from an ALS rat model, where its levels change as disease

  5. Postirradiation changes in the systems of active ion transport. Na,K-ATPase of neurons in neuroglia

    International Nuclear Information System (INIS)

    Shainskaya, A.M.; Dvoretskij, A.I.; Valetova, Yu.O.

    1989-01-01

    A study was made of the effect of X-radiation (0.31 C/kg and 3.875 C/kg) on Na,K-ATPase in fractions enriched with neurons and neuroglia. The results show the impairment of the neuronal-glial relationship in Na,K-ATPase activity. The most important differences in the pattern of changes in Na,K-ATPase system of brain cells were followed up after irradiaion with lethal and sublethal doses

  6. Protein carbonylation, protein aggregation and neuronal cell death in a murine model of multiple sclerosis

    Science.gov (United States)

    Dasgupta, Anushka

    Many studies have suggested that oxidative stress plays an important role in the pathophysiology of both multiple sclerosis (MS) and its animal model experimental autoimmune encephalomyelitis (EAE). Yet, the mechanism by which oxidative stress leads to tissue damage in these disorders is unclear. Recent work from our laboratory has revealed that protein carbonylation, a major oxidative modification caused by severe and/or chronic oxidative stress conditions, is elevated in MS and EAE. Furthermore, protein carbonylation has been shown to alter protein structure leading to misfolding/aggregation. These findings prompted me to hypothesize that carbonylated proteins, formed as a consequence of oxidative stress and/or decreased proteasomal activity, promote protein aggregation to mediate neuronal apoptosis in vitro and in EAE. To test this novel hypothesis, I first characterized protein carbonylation, protein aggregation and apoptosis along the spinal cord during the course of myelin-oligodendrocyte glycoprotein (MOG)35-55 peptide-induced EAE in C57BL/6 mice [Chapter 2]. The results show that carbonylated proteins accumulate throughout the course of the disease, albeit by different mechanisms: increased oxidative stress in acute EAE and decreased proteasomal activity in chronic EAE. I discovered not only that there is a temporal correlation between protein carbonylation and apoptosis but also that carbonyl levels are significantly higher in apoptotic cells. A high number of juxta-nuclear and cytoplasmic protein aggregates containing the majority of the oxidized proteins are also present during the course of EAE, which seems to be due to reduced autophagy. In chapter 3, I show that when gluthathione levels are reduced to those in EAE spinal cord, both neuron-like PC12 (nPC12) cells and primary neuronal cultures accumulate carbonylated proteins and undergo cell death (both by necrosis and apoptosis). Immunocytochemical and biochemical studies also revealed a temporal

  7. A spiking neuron model of the cortico-basal ganglia circuits for goal-directed and habitual action learning.

    Science.gov (United States)

    Chersi, Fabian; Mirolli, Marco; Pezzulo, Giovanni; Baldassarre, Gianluca

    2013-05-01

    Dual-system theories postulate that actions are supported either by a goal-directed or by a habit-driven response system. Neuroimaging and anatomo-functional studies have provided evidence that the prefrontal cortex plays a fundamental role in the first type of action control, while internal brain areas such as the basal ganglia are more active during habitual and overtrained responses. Additionally, it has been shown that areas of the cortex and the basal ganglia are connected through multiple parallel "channels", which are thought to function as an action selection mechanism resolving competitions between alternative options available in a given context. In this paper we propose a multi-layer network of spiking neurons that implements in detail the thalamo-cortical circuits that are believed to be involved in action learning and execution. A key feature of this model is that neurons are organized in small pools in the motor cortex and form independent loops with specific pools of the basal ganglia where inhibitory circuits implement a multistep selection mechanism. The described model has been validated utilizing it to control the actions of a virtual monkey that has to learn to turn on briefly flashing lights by pressing corresponding buttons on a board. When the animal is able to fluently execute the task the button-light associations are remapped so that it has to suppress its habitual behavior in order to execute goal-directed actions. The model nicely shows how sensory-motor associations for action sequences are formed at the cortico-basal ganglia level and how goal-directed decisions may override automatic motor responses. Copyright © 2012 Elsevier Ltd. All rights reserved.

  8. Noisy Neurons

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 20; Issue 1. Noisy Neurons: Hodgkin-Huxley Model and Stochastic Variants. Shurti Paranjape. General Article Volume 20 Issue 1 January 2015 pp 34-43. Fulltext. Click here to view fulltext PDF. Permanent link:

  9. Neuronal and molecular effects of cannabidiol on the mesolimbic dopamine system: Implications for novel schizophrenia treatments.

    Science.gov (United States)

    Renard, Justine; Norris, Christopher; Rushlow, Walter; Laviolette, Steven R

    2017-04-01

    Growing clinical and pre-clinical evidence points to a critical role for cannabidiol (CBD), the largest phytochemical component of cannabis, as a potential pharmacotherapy for various neuropsychiatric disorders. In contrast to delta-9-tetrahydrocannabinol (THC), which is associated with acute and neurodevelopmental pro-psychotic side-effects, CBD possesses no known psychoactive or dependence-producing properties. However, evidence has demonstrated that CBD strongly modulates the mesolimbic dopamine (DA) system and may possess promising anti-psychotic properties. Despite the psychotropic differences between CBD and THC, little is known regarding their molecular and neuronal effects on the mesolimbic DA system, nor how these differential effects may relate to their potential pro vs. anti-psychotic properties. This review summarizes clinical and pre-clinical evidence demonstrating CBD's modulatory effects on DA activity states within the mesolimbic pathway, functional interactions with the serotonin 5-HT 1A receptor system, and their downstream molecular signaling effects. Together with clinical evidence showing that CBD may normalize affective and cognitive deficits associated with schizophrenia, CBD may represent a promising treatment for schizophrenia, acting through novel molecular and neuronal mesolimbic substrates. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Giant neurons and associated synapses in the peripheral nervous system of whip spiders.

    Science.gov (United States)

    Foelix, R F; Troyer, D

    1980-08-01

    Whip spiders (Amblypygi) are arachnids with a specialized first pair of legs. These legs are unusually long (20-25 cm) and are not used for walking. Instead their lengthy tarsi (7-8 cm) are covered with thousands of sensory hairs (mechano- and chemoreceptors). The legs thus resemble antennae of insects. Each sensory hair is associated with 4-40 neurons whose axons are grouped together to form two large tarsal nerves. The nerves contain about 23 000 sensory axons. Whereas most of the axons measure only 0.1-0.2 microns in diameter, a few are exceptionally large (3-20 microns). These are giant fibres. Their large somata are located in specific segments of the tarsi. The branched dendrites of the giant neurons receive hundreds of chemical synapses, presumably from the sensory axons of the hair sensilla. Since stimulation of the tarsal tip elicits fast withdrawal reaction (greater than or equal to 80 ms), it is likely that the giant fibres provide the pathway for the rapid conduction of nerve impulses to the motor centres of the C.N.S. The system is comparable to the giant fibre system of certain insects. In contrast, however, the giant interneurons and associated synapses of whip spiders are not located in the C.N.S., but lie some 20 cm removed in the periphery. Thus, some primary sensory information already becomes processed in the peripheral nervous system, before it reaches the C.N.S.

  11. Melanin-concentrating hormone: unique peptide neuronal systems in the rat brain and pituitary gland

    Energy Technology Data Exchange (ETDEWEB)

    Zamir, N.; Skofitsch, G.; Bannon, M.J.; Jacobowitz, D.M.

    1986-03-01

    A unique neuronal system was detected in the rat central nervous system by immunohistochemistry and radioimmunoassay with antibodies to salmon melanin-concentrating hormone (MCH). MCH-like immunoreactive (MCH-LI) cell bodies were confined to the hypothalamus. MCH-LI fibers were found throughout the brain but were most prevalent in hypothalamus, mesencephalon, and pons-medulla regions. High concentrations of MCH-LI were measured in the hypothalamic medial forebrain bundle (MFB), posterior hypothalamic nucleus, and nucleus of the diagonal band. Reversed-phase high-performance liquid chromatography of MFB extracts from rat brain indicate that MCH-like peptide from the rat has a different retention time than that of the salmon MCH. An osmotic stimuls (2% NaCl as drinking water for 120 hr) caused a marked increase in MCH-LI concentrations in the lateral hypothalamus and neurointermediate lobe. The present studies establish the presence of MCH-like peptide in the rat brain. The MCH-LI neuronal system is well situated to coordinate complex functions such as regulation of water intake.

  12. RSMASS system model development

    International Nuclear Information System (INIS)

    Marshall, A.C.; Gallup, D.R.

    1998-01-01

    RSMASS system mass models have been used for more than a decade to make rapid estimates of space reactor power system masses. This paper reviews the evolution of the RSMASS models and summarizes present capabilities. RSMASS has evolved from a simple model used to make rough estimates of space reactor and shield masses to a versatile space reactor power system model. RSMASS uses unique reactor and shield models that permit rapid mass optimization calculations for a variety of space reactor power and propulsion systems. The RSMASS-D upgrade of the original model includes algorithms for the balance of the power system, a number of reactor and shield modeling improvements, and an automatic mass optimization scheme. The RSMASS-D suite of codes cover a very broad range of reactor and power conversion system options as well as propulsion and bimodal reactor systems. Reactor choices include in-core and ex-core thermionic reactors, liquid metal cooled reactors, particle bed reactors, and prismatic configuration reactors. Power conversion options include thermoelectric, thermionic, Stirling, Brayton, and Rankine approaches. Program output includes all major component masses and dimensions, efficiencies, and a description of the design parameters for a mass optimized system. In the past, RSMASS has been used as an aid to identify and select promising concepts for space power applications. The RSMASS modeling approach has been demonstrated to be a valuable tool for guiding optimization of the power system design; consequently, the model is useful during system design and development as well as during the selection process. An improved in-core thermionic reactor system model RSMASS-T is now under development. The current development of the RSMASS-T code represents the next evolutionary stage of the RSMASS models. RSMASS-T includes many modeling improvements and is planned to be more user-friendly. RSMASS-T will be released as a fully documented, certified code at the end of

  13. Lychee Seed Saponins Improve Cognitive Function and Prevent Neuronal Injury via Inhibiting Neuronal Apoptosis in a Rat Model of Alzheimer’s Disease

    Directory of Open Access Journals (Sweden)

    Xiuling Wang

    2017-02-01

    Full Text Available Lychee seed is a traditional Chinese medicine and possesses many activities, including hypoglycemia, liver protection, antioxidation, antivirus, and antitumor. However, its effect on neuroprotection is still unclear. The present study investigated the effects of lychee seed saponins (LSS on neuroprotection and associated mechanisms. We established a rat model of Alzheimer’s disease (AD by injecting Aβ25–35 into the lateral ventricle of rats and evaluated the effect of LSS on spatial learning and memory ability via the Morris water maze. Neuronal apoptosis was analyzed by hematoxylin and eosin stain and terminal deoxynucleotidyl transferase (Tdt-mediated dUTP nick-end labeling analysis, and mRNA expression of caspase-3 and protein expressions of Bax and Bcl-2 by reverse transcription-polymerase chain reaction (RT-PCR and Western blotting, respectively. The results showed that LSS remarkably improved cognitive function and alleviated neuronal injury by inhibiting apoptosis in the hippocampus of AD rats. Furthermore, the mRNA expression of caspase-3 and the protein expression of Bax were downregulated, while the protein expression of Bcl-2 and the ratio of Bcl-2/Bax were increased by LSS. We demonstrate that LSS significantly improves cognitive function and prevent neuronal injury in the AD rats via regulation of the apoptosis pathway. Therefore, LSS may be developed as a nutritional supplement and sold as a drug for AD prevention and/or treatment.

  14. Irrelevant sensory stimuli interfere with working memory storage: evidence from a computational model of prefrontal neurons.

    Science.gov (United States)

    Bancroft, Tyler D; Hockley, William E; Servos, Philip

    2013-03-01

    The encoding of irrelevant stimuli into the memory store has previously been suggested as a mechanism of interference in working memory (e.g., Lange & Oberauer, Memory, 13, 333-339, 2005; Nairne, Memory & Cognition, 18, 251-269, 1990). Recently, Bancroft and Servos (Experimental Brain Research, 208, 529-532, 2011) used a tactile working memory task to provide experimental evidence that irrelevant stimuli were, in fact, encoded into working memory. In the present study, we replicated Bancroft and Servos's experimental findings using a biologically based computational model of prefrontal neurons, providing a neurocomputational model of overwriting in working memory. Furthermore, our modeling results show that inhibition acts to protect the contents of working memory, and they suggest a need for further experimental research into the capacity of vibrotactile working memory.

  15. Arginine vasopressin neuronal loss results from autophagy-associated cell death in a mouse model for familial neurohypophysial diabetes insipidus

    Science.gov (United States)

    Hagiwara, D; Arima, H; Morishita, Y; Wenjun, L; Azuma, Y; Ito, Y; Suga, H; Goto, M; Banno, R; Sugimura, Y; Shiota, A; Asai, N; Takahashi, M; Oiso, Y

    2014-01-01

    Familial neurohypophysial diabetes insipidus (FNDI) characterized by progressive polyuria is mostly caused by mutations in the gene encoding neurophysin II (NPII), which is the carrier protein of the antidiuretic hormone, arginine vasopressin (AVP). Although accumulation of mutant NPII in the endoplasmic reticulum (ER) could be toxic for AVP neurons, the precise mechanisms of cell death of AVP neurons, reported in autopsy studies, remain unclear. Here, we subjected FNDI model mice to intermittent water deprivation (WD) in order to promote the phenotypes. Electron microscopic analyses demonstrated that, while aggregates are confined to a certain compartment of the ER in the AVP neurons of FNDI mice with water access ad libitum, they were scattered throughout the dilated ER lumen in the FNDI mice subjected to WD for 4 weeks. It is also demonstrated that phagophores, the autophagosome precursors, emerged in the vicinity of aggregates and engulfed the ER containing scattered aggregates. Immunohistochemical analyses revealed that expression of p62, an adapter protein between ubiquitin and autophagosome, was elicited on autophagosomal membranes in the AVP neurons, suggesting selective autophagy induction at this time point. Treatment of hypothalamic explants of green fluorescent protein (GFP)-microtubule-associated protein 1 light chain 3 (LC3) transgenic mice with an ER stressor thapsigargin increased the number of GFP-LC3 puncta, suggesting that ER stress could induce autophagosome formation in the hypothalamus of wild-type mice as well. The cytoplasm of AVP neurons in FNDI mice was occupied with vacuoles in the mice subjected to WD for 12 weeks, when 30–40% of AVP neurons are lost. Our data thus demonstrated that autophagy was induced in the AVP neurons subjected to ER stress in FNDI mice. Although autophagy should primarily be protective for neurons, it is suggested that the organelles including ER were lost over time through autophagy, leading to autophagy

  16. Enhancement of a robust arcuate GABAergic input to gonadotropin-releasing hormone neurons in a model of polycystic ovarian syndrome.

    Science.gov (United States)

    Moore, Aleisha M; Prescott, Mel; Marshall, Christopher J; Yip, Siew Hoong; Campbell, Rebecca E

    2015-01-13

    Polycystic ovarian syndrome (PCOS), the leading cause of female infertility, is associated with an increase in luteinizing hormone (LH) pulse frequency, implicating abnormal steroid hormone feedback to gonadotropin-releasing hormone (GnRH) neurons. This study investigated whether modifications in the synaptically connected neuronal network of GnRH neurons could account for this pathology. The PCOS phenotype was induced in mice following prenatal androgen (PNA) exposure. Serial blood sampling confirmed that PNA elicits increased LH pulse frequency and impaired progesterone negative feedback in adult females, mimicking the neuroendocrine abnormalities of the clinical syndrome. Imaging of GnRH neurons revealed greater dendritic spine density that correlated with increased putative GABAergic but not glutamatergic inputs in PNA mice. Mapping of steroid hormone receptor expression revealed that PNA mice had 59% fewer progesterone receptor-expressing cells in the arcuate nucleus of the hypothalamus (ARN). To address whether increased GABA innervation to GnRH neurons originates in the ARN, a viral-mediated Cre-lox approach was taken to trace the projections of ARN GABA neurons in vivo. Remarkably, projections from ARN GABAergic neurons heavily contacted and even bundled with GnRH neuron dendrites, and the density of fibers apposing GnRH neurons was even greater in PNA mice (56%). Additionally, this ARN GABA population showed significantly less colocalization with progesterone receptor in PNA animals compared with controls. Together, these data describe a robust GABAergic circuit originating in the ARN that is enhanced in a model of PCOS and may underpin the neuroendocrine pathophysiology of the syndrome.

  17. Muscle expression of mutant androgen receptor accounts for systemic and motor neuron disease phenotypes in spinal and bulbar muscular atrophy.

    Science.gov (United States)

    Cortes, Constanza J; Ling, Shuo-Chien; Guo, Ling T; Hung, Gene; Tsunemi, Taiji; Ly, Linda; Tokunaga, Seiya; Lopez, Edith; Sopher, Bryce L; Bennett, C Frank; Shelton, G Diane; Cleveland, Don W; La Spada, Albert R

    2014-04-16

    X-linked spinal and bulbar muscular atrophy (SBMA) is characterized by adult-onset muscle weakness and lower motor neuron degeneration. SBMA is caused by CAG-polyglutamine (polyQ) repeat expansions in the androgen receptor (AR) gene. Pathological findings include motor neuron loss, with polyQ-AR accumulation in intranuclear inclusions. SBMA patients exhibit myopathic features, suggesting a role for muscle in disease pathogenesis. To determine the contribution of muscle, we developed a BAC mouse model featuring a floxed first exon to permit cell-type-specific excision of human AR121Q. BAC fxAR121 mice develop systemic and neuromuscular phenotypes, including shortened survival. After validating termination of AR121 expression and full rescue with ubiquitous Cre, we crossed BAC fxAR121 mice with Human Skeletal Actin-Cre mice. Muscle-specific excision prevented weight loss, motor phenotypes, muscle pathology, and motor neuronopathy and dramatically extended survival. Our results reveal a crucial role for muscle expression of polyQ-AR in SBMA and suggest muscle-directed therapies as effective treatments. Copyright © 2014 Elsevier Inc. All rights reserved.

  18. Understanding dielectrophoretic trapping of neuronal cells: modelling electric field, electrode-liquid interface and fluid flow

    International Nuclear Information System (INIS)

    Heida, T.; Rutten, W.L.C.; Marani, E.

    2002-01-01

    By application of dielectrophoresis neuronal cells can be trapped successfully. Several trapping experiments have been performed using a quadrupole electrode structure at different amplitudes (1, 3, and 5 V pp ) and frequencies (10-50 MHz). Due to the high conductivity of the suspending medium negative dielectrophoretic forces are created. The dielectrophoretic force is determined by the gradient of the electric field. However, the electrode-liquid interfaces are responsible for decreased electric field strengths, and thus decreased field gradients, inside the medium, especially at lower frequencies. Circuit modelling is used to determine the frequency-dependent electric field inside the medium. The creation of an electric field in high conductivity of the medium results in local heating, which in turn induces fluid flow. This flow also drives the neurons and was found to enhance the trapping effect of the dielectrophoretic force. With the use of finite element modelling, this aspect was investigated. The results show that the dielectrophoretic force is dominating just above the substrate. When the upward dielectrophoretic force is large enough to levitate the cells, they may be dragged along with the fluid flow. The result is that more cells may be trapped than expected on the basis of dielectrophoresis alone. (author)

  19. Biological modelling of a computational spiking neural network with neuronal avalanches

    Science.gov (United States)

    Li, Xiumin; Chen, Qing; Xue, Fangzheng

    2017-05-01

    In recent years, an increasing number of studies have demonstrated that networks in the brain can self-organize into a critical state where dynamics exhibit a mixture of ordered and disordered patterns. This critical branching phenomenon is termed neuronal avalanches. It has been hypothesized that the homeostatic level balanced between stability and plasticity of this critical state may be the optimal state for performing diverse neural computational tasks. However, the critical region for high performance is narrow and sensitive for spiking neural networks (SNNs). In this paper, we investigated the role of the critical state in neural computations based on liquid-state machines, a biologically plausible computational neural network model for real-time computing. The computational performance of an SNN when operating at the critical state and, in particular, with spike-timing-dependent plasticity for updating synaptic weights is investigated. The network is found to show the best computational performance when it is subjected to critical dynamic states. Moreover, the active-neuron-dominant structure refined from synaptic learning can remarkably enhance the robustness of the critical state and further improve computational accuracy. These results may have important implications in the modelling of spiking neural networks with optimal computational performance. This article is part of the themed issue `Mathematical methods in medicine: neuroscience, cardiology and pathology'.

  20. Systemic resilience model

    International Nuclear Information System (INIS)

    Lundberg, Jonas; Johansson, Björn JE

    2015-01-01

    It has been realized that resilience as a concept involves several contradictory definitions, both for instance resilience as agile adjustment and as robust resistance to situations. Our analysis of resilience concepts and models suggest that beyond simplistic definitions, it is possible to draw up a systemic resilience model (SyRes) that maintains these opposing characteristics without contradiction. We outline six functions in a systemic model, drawing primarily on resilience engineering, and disaster response: anticipation, monitoring, response, recovery, learning, and self-monitoring. The model consists of four areas: Event-based constraints, Functional Dependencies, Adaptive Capacity and Strategy. The paper describes dependencies between constraints, functions and strategies. We argue that models such as SyRes should be useful both for envisioning new resilience methods and metrics, as well as for engineering and evaluating resilient systems. - Highlights: • The SyRes model resolves contradictions between previous resilience definitions. • SyRes is a core model for envisioning and evaluating resilience metrics and models. • SyRes describes six functions in a systemic model. • They are anticipation, monitoring, response, recovery, learning, self-monitoring. • The model describes dependencies between constraints, functions and strategies

  1. Inhibition of apoptosis blocks human motor neuron cell death in a stem cell model of spinal muscular atrophy.

    Directory of Open Access Journals (Sweden)

    Dhruv Sareen

    Full Text Available Spinal muscular atrophy (SMA is a genetic disorder caused by a deletion of the survival motor neuron 1 gene leading to motor neuron loss, muscle atrophy, paralysis, and death. We show here that induced pluripotent stem cell (iPSC lines generated from two Type I SMA subjects-one produced with lentiviral constructs and the second using a virus-free plasmid-based approach-recapitulate the disease phenotype and generate significantly fewer motor neurons at later developmental time periods in culture compared to two separate control subject iPSC lines. During motor neuron development, both SMA lines showed an increase in Fas ligand-mediated apoptosis and increased caspase-8 and-3 activation. Importantly, this could be mitigated by addition of either a Fas blocking antibody or a caspase-3 inhibitor. Together, these data further validate this human stem cell model of SMA, suggesting that specific inhibitors of apoptotic pathways may be beneficial for patients.

  2. Ubiquitin-Positive Intranuclear Inclusions in Neuronal and Glial Cells in a Mouse Model of the Fragile-X Premutation

    Science.gov (United States)

    Wenzel, H. Jürgen; Hunsaker, Michael R.; Greco, Claudia M.; Willemsen, Rob; Berman, Robert F.

    2010-01-01

    Fragile X-associated tremor/ataxia syndrome (FXTAS) is an adult-onset neurodegenerative disorder caused by CGG trinucleotide repeat expansions in the fragile X mental retardation 1 (FMR1) gene. The neuropathological hallmark of the disease is the presence of ubiquitin-positive intranuclear inclusions in neurons and in astrocytes. Ubiquitin-positive intranuclear inclusions have also been found in the neurons of transgenic mice model carrying an expanded CGG(98) trinucleotide repeat of human origin, but have not previously been described in glial cells. Therefore, we used immunocytochemical methods to determine the pathological features of nuclear and/or cytoplasmic inclusions in astrocytes, Bergmann glia and neurons, as well as relationships between inclusion patterns, age, and repeat length in CGG knock-in (KI) mice in comparison with wild type mice. In CGG KI mice, ubiquitin-positive intranuclear inclusions were found in neurons (e.g., pyramidal cells, GABAergic neurons) throughout the brain in cortical and subcortical brain regions; these inclusions increased in number and size with advanced age. Ubiquitin-positive intranuclear inclusions were also present in protoplasmic astrocytes, including Bergmann glia in the cerebellum. The morphology of intranuclear inclusions in CGG KI mice was compared to that of typical inclusions in human neurons and astrocytes in postmortem FXTAS brain tissue. This new finding of previously unreported pathology in astrocytes of CGG KI mice now provides an important mouse model to study astrocyte pathology in human FXTAS. PMID:20051238

  3. Selected System Models

    Science.gov (United States)

    Schmidt-Eisenlohr, F.; Puñal, O.; Klagges, K.; Kirsche, M.

    Apart from the general issue of modeling the channel, the PHY and the MAC of wireless networks, there are specific modeling assumptions that are considered for different systems. In this chapter we consider three specific wireless standards and highlight modeling options for them. These are IEEE 802.11 (as example for wireless local area networks), IEEE 802.16 (as example for wireless metropolitan networks) and IEEE 802.15 (as example for body area networks). Each section on these three systems discusses also at the end a set of model implementations that are available today.

  4. A transcranial magnetic stimulation study of the effect of visual orientation on the putative human mirror neuron system

    Science.gov (United States)

    Burgess, Jed D.; Arnold, Sara L.; Fitzgibbon, Bernadette M.; Fitzgerald, Paul B.; Enticott, Peter G.

    2013-01-01

    Mirror neurons are a class of motor neuron that are active during both the performance and observation of behavior, and have been implicated in interpersonal understanding. There is evidence to suggest that the mirror response is modulated by the perspective from which an action is presented (e.g., egocentric or allocentric). Most human research, however, has only examined this when presenting intransitive actions. Twenty-three healthy adult participants completed a transcranial magnetic stimulation experiment that assessed corticospinal excitability whilst viewing transitive hand gestures from both egocentric (i.e., self) and allocentric (i.e., other) viewpoints. Although action observation was associated with increases in corticospinal excitability (reflecting putative human mirror neuron activity), there was no effect of visual perspective. These findings are discussed in the context of contemporary theories of mirror neuron ontogeny, including models concerning associative learning and evolutionary adaptation. PMID:24137125

  5. A transcranial magnetic stimulation study of the effect of visual orientation on the putative human mirror neuron system

    Directory of Open Access Journals (Sweden)

    Jed Donald Burgess

    2013-10-01

    Full Text Available Mirror neurons are a class of motor neuron that are active during both the performance and observation of behavior, and have been implicated in interpersonal understanding There is evidence to suggest that the mirror response is modulated by the perspective from which an action is presented (e.g., egocentric or allocentric. Most human research, however, has only examined this when presenting intransitive actions. Twenty-three healthy adult participants completed a transcranial magnetic stimulation (TMS experiment that assessed corticospinal excitability whilst viewing transitive hand gestures from both egocentric (i.e., self and allocentric (i.e., other viewpoints. Although action observation was associated with increases in corticospinal excitability (reflecting putative human mirror neuron activity, there was no effect of visual perspective. These findings are discussed in the context of contemporary theories of mirror neuron ontogeny, including models concerning associative learning and evolutionary adaptation.

  6. Interdisciplinary approaches of transcranial magnetic stimulation applied to a respiratory neuronal circuitry model.

    Directory of Open Access Journals (Sweden)

    Stéphane Vinit

    Full Text Available Respiratory related diseases associated with the neuronal control of breathing represent life-threatening issues and to date, no effective therapeutics are available to enhance the impaired function. The aim of this study was to determine whether a preclinical respiratory model could be used for further studies to develop a non-invasive therapeutic tool applied to rat diaphragmatic neuronal circuitry. Transcranial magnetic stimulation (TMS was performed on adult male Sprague-Dawley rats using a human figure-of-eight coil. The largest diaphragmatic motor evoked potentials (MEPdia were recorded when the center of the coil was positioned 6 mm caudal from Bregma, involving a stimulation of respiratory supraspinal pathways. Magnetic shielding of the coil with mu metal reduced magnetic field intensities and improved focality with increased motor threshold and lower amplitude recruitment curve. Moreover, transynaptic neuroanatomical tracing with pseudorabies virus (applied to the diaphragm suggest that connections exist between the motor cortex, the periaqueductal grey cell regions, several brainstem neurons and spinal phrenic motoneurons (distributed in the C3-4 spinal cord. These results reveal the anatomical substrate through which supraspinal stimulation can convey descending action potential volleys to the spinal motoneurons (directly or indirectly. We conclude that MEPdia following a single pulse of TMS can be successfully recorded in the rat and may be used in the assessment of respiratory supraspinal plasticity. Supraspinal non-invasive stimulations aimed to neuromodulate respiratory circuitry will enable new avenues of research into neuroplasticity and the development of therapies for respiratory dysfunction associated with neural injury and disease (e.g. spinal cord injury, amyotrophic lateral sclerosis.

  7. Treadmill exercise represses neuronal cell death in an aged transgenic mouse model of Alzheimer's disease.

    Science.gov (United States)

    Um, Hyun-Sub; Kang, Eun-Bum; Koo, Jung-Hoon; Kim, Hyun-Tae; Jin-Lee; Kim, Eung-Joon; Yang, Chun-Ho; An, Gil-Young; Cho, In-Ho; Cho, Joon-Yong

    2011-02-01

    The present study was undertaken to further investigate the protective effect of treadmill exercise on the hippocampal proteins associated with neuronal cell death in an aged transgenic (Tg) mice with Alzheimer's disease (AD). To address this, Tg mouse model of AD, Tg-NSE/PS2m, which expresses human mutant PS2 in the brain, was chosen. Animals were subjected to treadmill exercise for 12 weeks from 24 months of age. The exercised mice were treadmill run at speed of 12 m/min, 60 min/day, 5 days/week on a 0% gradient for 3 months. Treadmill exercised mice improved cognitive function in water maze test. Treadmill exercised mice significantly reduced the expression of Aβ-42, Cox-2, and caspase-3 in the hippocampus. In parallel, treadmill exercised Tg mice decreased the phosphorylation levels of JNK, p38MAPK and tau (Ser404, Ser202, Thr231), and increased the phosphorylation levels of ERK, PI3K, Akt and GSK-3α/β. In addition, treadmill exercised Tg mice up-regulated the expressions of NGF, BDNF and phospho-CREB, and the expressions of SOD-1, SOD-2 and HSP-70. Treadmill exercised Tg mice up-regulated the expression of Bcl-2, and down-regulated the expressions of cytochrome c and Bax in the hippocampus. The number of TUNEL-positive cells in the hippocampus in mice was significantly decreased after treadmill exercise. Finally, serum TC, insulin, glucose, and corticosterone levels were significantly decreased in the Tg mice after treadmill exercise. As a consequence of such change, Aβ-dependent neuronal cell death in the hippocampus of Tg mice was markedly suppressed following treadmill exercise. These results strongly suggest that treadmill exercise provides a therapeutic potential to inhibit both Aβ-42 and neuronal death pathways. Therefore, treadmill exercise may be beneficial in prevention or treatment of AD. Copyright © 2010 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

  8. Iron-induced neuronal damage in a rat model of post-traumatic stress disorder.

    Science.gov (United States)

    Zhao, Ming; Yu, Zhibo; Zhang, Yang; Huang, Xueling; Hou, Jingming; Zhao, YanGang; Luo, Wei; Chen, Lin; Ou, Lan; Li, Haitao; Zhang, Jiqiang

    2016-08-25

    Previous studies have shown that iron redistribution and deposition in the brain occurs in some neurodegenerative diseases, and oxidative damage due to abnormal iron level is a primary cause of neuronal death. In the present study, we used the single prolonged stress (SPS) model to mimic post-traumatic stress disorder (PTSD), and examined whether iron was involved in the progression of PTSD. The anxiety-like behaviors of the SPS group were assessed by the elevated plus maze (EPM) and open field tests, and iron levels were measured by inductively coupled plasma optical emission spectrometer (ICP-OES). Expression of glucocorticoid receptors and transferrin receptor 1 (TfR1) and ferritin (Fn) was detected by Western blot and immunohistochemistry in selected brain areas; TfR1 and Fn mRNA expression were detected by quantitative-polymerase chain reaction (Q-PCR). Ultrastructures of the hippocampus were observed under a transmission electron microscope. Our results showed that SPS exposure induced anxiety-like symptoms and increased the level of serum cortisol and the concentration of iron in key brain areas such as the hippocampus, prefrontal cortex, and striatum. The stress induced region-specific changes in both protein and mRNA levels of TfR1 and Fn. Moreover, swelling mitochondria and cell apoptosis were observed in neurons in brain regions with iron accumulation. We concluded that SPS stress increased iron in some cognition-related brain regions and subsequently cause neuronal injury, indicating that the iron may function in the pathology of PTSD. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

  9. Modeled channel distributions explain extracellular recordings from cultured neurons sealed to microelectrodes

    NARCIS (Netherlands)

    Buitenweg, Jan R.; Rutten, Wim; Marani, Enrico

    2002-01-01

    Amplitudes and shapes of extracellular recordings from single neurons cultured on a substrate embedded microelectrode depend not only on the volume conducting properties of the neuron-electrode interface, but might also depend on the distribution of voltage-sensitive channels over the neuronal

  10. Variational calculation of the limit cycle and its frequency in a two-neuron model with delay

    International Nuclear Information System (INIS)

    Brandt, Sebastian F.; Wessel, Ralf; Pelster, Axel

    2006-01-01

    We consider a model system of two coupled Hopfield neurons, which is described by delay differential equations taking into account the finite signal propagation and processing times. When the delay exceeds a critical value, a limit cycle emerges via a supercritical Hopf bifurcation. First, we calculate its frequency and trajectory perturbatively by applying the Poincare-Lindstedt method. Then, the perturbation series are resummed by means of the Shohat expansion in good agreement with numerical values. However, with increasing delay, the accuracy of the results from the Shohat expansion worsens. We thus apply variational perturbation theory (VPT) to the perturbation expansions to obtain more accurate results, which moreover hold even in the limit of large delays

  11. [The pathological TDP-43 protein expression in the central nervous system of motor neuron disease].

    Science.gov (United States)

    Zhu, Mingwei; Liu, Jia; Wang, Luning; Gui, Qiuping

    2015-01-01

    To understand pathological TDP-43 features in the central nervous systems of patients with clinically and autopsy confirmed motor neuron disease (MND). The clinical and histopathological features of 4 cases with MND confirmed by autopsy were summarized; anti-ubiquitin (Ub) and anti-TDP-43 immunohistochemical staining were carried out on tissue of brains and spinal cords from 4 cases with MND and 3 control cases without history of neurological disorders. These 4 cases presented with typical clinical and histologic features of MND. Ub-positive inclusions were observed in brain and spinal cord from 3 cases with the Ub-positive inclusions of skein- round- and lewy body- like structures. Strong TDP-43 pathological staining in brain and spinal cord was identified in 2 cases with MND presented as neuronal and glial cytoplasmic inclusions with various shapes. The TDP-43 positive inclusions were widely distributed in the motor cortex of brain and the anterior horn of spinal cord. TDP-43 weak staining in the spinal cord tissue was observed in 1 case with MND. No Ub- and TDP-43 positive inclusions were found in 3 control cases. There is widespread pathological TDP-43 expression in the central nervous system of MND. TDP-43 positive inclusions in MND have relatively high specificity. It is worth further study on their formation mechanism.

  12. Phase transition approach to bursting in neuronal cultures: quorum percolation models

    Science.gov (United States)

    Monceau, P.; Renault, R.; Métens, S.; Bottani, S.; Fardet, T.

    2017-10-01

    The Quorum Percolation model has been designed in the context of neurobiology to describe bursts of activity occurring in neuronal cultures from the point of view of statistical physics rather than from a dynamical synchronization approach. It is based upon information propagation on a directed graph with a threshold activation rule; this leads to a phase d