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Sample records for single neuron models

  1. 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...

  2. 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...

  3. 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.

  4. 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.

  5. Single neuron computation

    CERN Document Server

    McKenna, Thomas M; Zornetzer, Steven F

    1992-01-01

    This book contains twenty-two original contributions that provide a comprehensive overview of computational approaches to understanding a single neuron structure. The focus on cellular-level processes is twofold. From a computational neuroscience perspective, a thorough understanding of the information processing performed by single neurons leads to an understanding of circuit- and systems-level activity. From the standpoint of artificial neural networks (ANNs), a single real neuron is as complex an operational unit as an entire ANN, and formalizing the complex computations performed by real n

  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. 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

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

    Directory of Open Access Journals (Sweden)

    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.

  9. Biomechanics of single cortical neurons.

    Science.gov (United States)

    Bernick, Kristin B; Prevost, Thibault P; Suresh, Subra; Socrate, Simona

    2011-03-01

    This study presents experimental results and computational analysis of the large strain dynamic behavior of single neurons in vitro with the objective of formulating a novel quantitative framework for the biomechanics of cortical neurons. Relying on the atomic force microscopy (AFM) technique, novel testing protocols are developed to enable the characterization of neural soma deformability over a range of indentation rates spanning three orders of magnitude, 10, 1, and 0.1 μm s(-1). Modified spherical AFM probes were utilized to compress the cell bodies of neonatal rat cortical neurons in load, unload, reload and relaxation conditions. The cell response showed marked hysteretic features, strong non-linearities, and substantial time/rate dependencies. The rheological data were complemented with geometrical measurements of cell body morphology, i.e. cross-diameter and height estimates. A constitutive model, validated by the present experiments, is proposed to quantify the mechanical behavior of cortical neurons. The model aimed to correlate empirical findings with measurable degrees of (hyper)elastic resilience and viscosity at the cell level. The proposed formulation, predicated upon previous constitutive model developments undertaken at the cortical tissue level, was implemented in a three-dimensional finite element framework. The simulated cell response was calibrated to the experimental measurements under the selected test conditions, providing a novel single cell model that could form the basis for further refinements. Copyright © 2010 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

  10. 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.

  11. 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.

  12. Current Source Density Estimation for Single Neurons

    Directory of Open Access Journals (Sweden)

    Dorottya Cserpán

    2014-03-01

    Full Text Available Recent developments of multielectrode technology made it possible to measure the extracellular potential generated in the neural tissue with spatial precision on the order of tens of micrometers and on submillisecond time scale. Combining such measurements with imaging of single neurons within the studied tissue opens up new experimental possibilities for estimating distribution of current sources along a dendritic tree. In this work we show that if we are able to relate part of the recording of extracellular potential to a specific cell of known morphology we can estimate the spatiotemporal distribution of transmembrane currents along it. We present here an extension of the kernel CSD method (Potworowski et al., 2012 applicable in such case. We test it on several model neurons of progressively complicated morphologies from ball-and-stick to realistic, up to analysis of simulated neuron activity embedded in a substantial working network (Traub et al, 2005. We discuss the caveats and possibilities of this new approach.

  13. 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

  14. Neural Plasticity: Single Neuron Models for Discrimination and Generalization and an Experimental Ensemble Approach.

    Science.gov (United States)

    1983-06-01

    in pamp/cm has been computed by Agin (1964) from the equations of Hodgkin and Huxley (1952) to give the response frequency (pulses/sec) of an axon...J.- Y . (1981) lumunocytochem- ical localization of glutamic acid decarboxylase in monkey striate cortex. Nature2i2.: 605-607. Hodgkin . A. L. and...used to express the output y of a neuron to its inputs zi (1). The coefficients ei i_____i___i __ i_______’____’_____,________’__’___"___i 10 are the

  15. 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...

  16. Electro-thermal equivalent 3D Finite Element Model of a Single Neuron.

    Science.gov (United States)

    Cinelli, I; Destrade, M; Duffy, M; McHugh, P

    2017-09-14

    We propose a novel approach for modelling the inter-dependence of electrical and mechanical phenomena in nervous cells, by using electro-thermal equivalences in finite element (FE) analysis so that existing thermo-mechanical tools can be applied. First, the equivalence between electrical and thermal properties of the nerve materials is established, and results of a pure heat conduction analysis performed in Abaqus CAE Software 6.13-3 are validated with analytical solutions for a range of steady and transient conditions. This validation includes the definition of equivalent active membrane properties that enable prediction of the action potential. Then, as a step towards fully coupled models, electro-mechanical coupling is implemented through the definition of equivalent piezoelectric properties of the nerve membrane using the thermal expansion coefficient, enabling prediction of the mechanical response of the nerve to the action potential. Results of the coupled electro-mechanical model are validated with previously published experimental results of deformation for the squid giant axon, crab nerve fibre and garfish olfactory nerve fibre. A simplified coupled electro-mechanical modelling approach is established through an electro-thermal equivalent FE model of a nervous cell for biomedical applications. One of the key findings is the mechanical characterization of the neural activity in a coupled electro-mechanical domain, which provides insights into the electro-mechanical behaviour of nervous cells, such as thinning of the membrane. This is a first step towards modelling 3D electro-mechanical alteration induced by trauma at nerve bundle, tissue and organ levels.

  17. 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

  18. Understanding metal homeostasis in primary cultured neurons. Studies using single neuron subcellular and quantitative metallomics.

    Science.gov (United States)

    Colvin, Robert A; Lai, Barry; Holmes, William R; Lee, Daewoo

    2015-07-01

    The purpose of this study was to demonstrate how single cell quantitative and subcellular metallomics inform us about both the spatial distribution and cellular mechanisms of metal buffering and homeostasis in primary cultured neurons from embryonic rat brain, which are often used as models of human disease involving metal dyshomeostasis. The present studies utilized synchrotron radiation X-ray fluorescence (SRXRF) and focused primarily on zinc and iron, two abundant metals in neurons that have been implicated in the pathogenesis of neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease. Total single cell contents for calcium, iron, zinc, copper, manganese, and nickel were determined. Resting steady state zinc showed a diffuse distribution in both soma and processes, best defined by the mass profile of the neuron with an enrichment in the nucleus compared with the cytoplasm. Zinc buffering and homeostasis was studied using two modes of cellular zinc loading - transporter and ionophore (pyrithione) mediated. Single neuron zinc contents were shown to statistically significantly increase by either loading method - ionophore: 160 million to 7 billion; transporter 160 million to 280 million atoms per neuronal soma. The newly acquired and buffered zinc still showed a diffuse distribution. Soma and processes have about equal abilities to take up zinc via transporter mediated pathways. Copper levels are distributed diffusely as well, but are relatively higher in the processes relative to zinc levels. Prior studies have observed iron puncta in certain cell types, but others have not. In the present study, iron puncta were characterized in several primary neuronal types. The results show that iron puncta could be found in all neuronal types studied and can account for up to 50% of the total steady state content of iron in neuronal soma. Although other metals can be present in iron puncta, they are predominantly iron containing and do not appear to be

  19. 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

  20. Profiling neuronal ion channelopathies with non-invasive brain imaging and dynamic causal models: Case studies of single gene mutations.

    Science.gov (United States)

    Gilbert, Jessica R; Symmonds, Mkael; Hanna, Michael G; Dolan, Raymond J; Friston, Karl J; Moran, Rosalyn J

    2016-01-01

    Clinical assessments of brain function rely upon visual inspection of electroencephalographic waveform abnormalities in tandem with functional magnetic resonance imaging. However, no current technology proffers in vivo assessments of activity at synapses, receptors and ion-channels, the basis of neuronal communication. Using dynamic causal modeling we compared electrophysiological responses from two patients with distinct monogenic ion channelopathies and a large cohort of healthy controls to demonstrate the feasibility of assaying synaptic-level channel communication non-invasively. Synaptic channel abnormality was identified in both patients (100% sensitivity) with assay specificity above 89%, furnishing estimates of neurotransmitter and voltage-gated ion throughput of sodium, calcium, chloride and potassium. This performance indicates a potential novel application as an adjunct for clinical assessments in neurological and psychiatric settings. More broadly, these findings indicate that biophysical models of synaptic channels can be estimated non-invasively, having important implications for advancing human neuroimaging to the level of non-invasive ion channel assays. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  1. 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.

  2. Responses of single neurons and neuronal ensembles in frog first- and second-order olfactory neurons

    Czech Academy of Sciences Publication Activity Database

    Rospars, J. P.; Šanda, Pavel; Lánský, Petr; Duchamp-Viret, P.

    2013-01-01

    Roč. 1536, NOV 6 (2013), s. 144-158 ISSN 0006-8993 R&D Projects: GA ČR(CZ) GBP304/12/G069; GA ČR(CZ) GAP103/11/0282 Institutional support: RVO:67985823 Keywords : olfaction * spiking activity * neuronal model Subject RIV: JD - Computer Applications, Robotics Impact factor: 2.828, year: 2013

  3. Proteomic signatures and aberrations of mouse embryonic stem cells containing a single human chromosome 21 in neuronal differentiation: an in vitro model of Down syndrome.

    Science.gov (United States)

    Kadota, M; Nishigaki, R; Wang, C C; Toda, T; Shirayoshi, Y; Inoue, T; Gojobori, T; Ikeo, K; Rogers, M S; Oshimura, M

    2004-01-01

    Neurodegeneration in fetal development of Down syndrome (DS) patients is proposed to result in apparent neuropathological abnormalities and to contribute to the phenotypic characteristics of mental retardation and premature development of Alzheimer disease. In order to identify the aberrant and specific genes involved in the early differentiation of DS neurons, we have utilized an in vitro neuronal differentiation system of mouse ES cells containing a single human chromosome 21 (TT2F/hChr21) with TT2F parental ES cells as a control. The paired protein extracts from TT2F and TT2F/hChr21 cells at several stages of neuronal differentiation were subjected to two-dimensional polyacrylamide gel electrophoresis protein separation followed by matrix-assisted laser desorption/ionization-time of flight mass spectrometry to identify the proteins differentially expressed between TT2F and TT2F/hChr21 cells. We provide here a novel set of specific gene products altered in early differentiating DS neuronal cells, which differs from that identified in adult or fetal brain with DS. The aberrant protein expression in early differentiating neurons, due to the hChr21 gene dosage effects or chromosomal imbalance, may affect neuronal outgrowth, proliferation and differentiation, producing developmental abnormalities in neural patterning, which eventually leads to formation of a suboptimal functioning neuronal network in DS.

  4. Deep learning and shapes similarity for joint segmentation and tracing single neurons in SEM images

    Science.gov (United States)

    Rao, Qiang; Xiao, Chi; Han, Hua; Chen, Xi; Shen, Lijun; Xie, Qiwei

    2017-02-01

    Extracting the structure of single neurons is critical for understanding how they function within the neural circuits. Recent developments in microscopy techniques, and the widely recognized need for openness and standardization provide a community resource for automated reconstruction of dendritic and axonal morphology of single neurons. In order to look into the fine structure of neurons, we use the Automated Tape-collecting Ultra Microtome Scanning Electron Microscopy (ATUM-SEM) to get images sequence of serial sections of animal brain tissue that densely packed with neurons. Different from other neuron reconstruction method, we propose a method that enhances the SEM images by detecting the neuronal membranes with deep convolutional neural network (DCNN) and segments single neurons by active contour with group shape similarity. We joint the segmentation and tracing together and they interact with each other by alternate iteration that tracing aids the selection of candidate region patch for active contour segmentation while the segmentation provides the neuron geometrical features which improve the robustness of tracing. The tracing model mainly relies on the neuron geometrical features and is updated after neuron being segmented on the every next section. Our method enables the reconstruction of neurons of the drosophila mushroom body which is cut to serial sections and imaged under SEM. Our method provides an elementary step for the whole reconstruction of neuronal networks.

  5. A single-neuron tracing study of arkypallidal and prototypic neurons in healthy rats.

    Science.gov (United States)

    Fujiyama, Fumino; Nakano, Takashi; Matsuda, Wakoto; Furuta, Takahiro; Udagawa, Jun; Kaneko, Takeshi

    2016-12-01

    The external globus pallidus (GP) is known as a relay nucleus of the indirect pathway of the basal ganglia. Recent studies in dopamine-depleted and healthy rats indicate that the GP comprises two main types of pallidofugal neurons: the so-called "prototypic" and "arkypallidal" neurons. However, the reconstruction of complete arkypallidal neurons in healthy rats has not been reported. Here we visualized the entire axonal arborization of four single arkypallidal neurons and six single prototypic neurons in rat brain using labeling with a viral vector expressing membrane-targeted green fluorescent protein and examined the distribution of axon boutons in the target nuclei. Results revealed that not only the arkypallidal neurons but nearly all of the prototypic neurons projected to the striatum with numerous axon varicosities. Thus, the striatum is a major target nucleus for pallidal neurons. Arkypallidal and prototypic GP neurons located in the calbindin-positive and calbindin-negative regions mainly projected to the corresponding positive and negative regions in the striatum. Because the GP and striatum calbindin staining patterns reflect the topographic organization of the striatopallidal projection, the striatal neurons in the sensorimotor and associative regions constitute the reciprocal connection with the GP neurons in the corresponding regions.

  6. Single neuron dynamics during experimentally induced anoxic depolarization

    NARCIS (Netherlands)

    Zandt, B.; Stigen, Tyler; ten Haken, Bernard; Netoff, Theoden; van Putten, Michel Johannes Antonius Maria

    2013-01-01

    We studied single neuron dynamics during anoxic depolarizations, which are often observed in cases of neuronal energy depletion. Anoxic and similar depolarizations play an important role in several pathologies, notably stroke, migraine, and epilepsy. One of the effects of energy depletion was

  7. Training a Single Sigmoidal Neuron is Hard

    Czech Academy of Sciences Publication Activity Database

    Šíma, Jiří

    2002-01-01

    Roč. 14, č. 11 (2002), s. 2709-2729 ISSN 0899-7667 R&D Projects: GA MŠk LN00A056 Keywords : sigmoidal neuron * loading problem * NP-hardness Subject RIV: BA - General Mathematics Impact factor: 2.313, year: 2002

  8. 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.

  9. Racing to learn: statistical inference and learning in a single spiking neuron with adaptive kernels.

    Science.gov (United States)

    Afshar, Saeed; George, Libin; Tapson, Jonathan; van Schaik, André; Hamilton, Tara J

    2014-01-01

    This paper describes the Synapto-dendritic Kernel Adapting Neuron (SKAN), a simple spiking neuron model that performs statistical inference and unsupervised learning of spatiotemporal spike patterns. SKAN is the first proposed neuron model to investigate the effects of dynamic synapto-dendritic kernels and demonstrate their computational power even at the single neuron scale. The rule-set defining the neuron is simple: there are no complex mathematical operations such as normalization, exponentiation or even multiplication. The functionalities of SKAN emerge from the real-time interaction of simple additive and binary processes. Like a biological neuron, SKAN is robust to signal and parameter noise, and can utilize both in its operations. At the network scale neurons are locked in a race with each other with the fastest neuron to spike effectively "hiding" its learnt pattern from its neighbors. The robustness to noise, high speed, and simple building blocks not only make SKAN an interesting neuron model in computational neuroscience, but also make it ideal for implementation in digital and analog neuromorphic systems which is demonstrated through an implementation in a Field Programmable Gate Array (FPGA). Matlab, Python, and Verilog implementations of SKAN are available at: http://www.uws.edu.au/bioelectronics_neuroscience/bens/reproducible_research.

  10. Modeling Spike-Train Processing in the Cerebellum Granular Layer and Changes in Plasticity Reveal Single Neuron Effects in Neural Ensembles

    Directory of Open Access Journals (Sweden)

    Chaitanya Medini

    2012-01-01

    Full Text Available The cerebellum input stage has been known to perform combinatorial operations on input signals. In this paper, two types of mathematical models were used to reproduce the role of feed-forward inhibition and computation in the granular layer microcircuitry to investigate spike train processing. A simple spiking model and a biophysically-detailed model of the network were used to study signal recoding in the granular layer and to test observations like center-surround organization and time-window hypothesis in addition to effects of induced plasticity. Simulations suggest that simple neuron models may be used to abstract timing phenomenon in large networks, however detailed models were needed to reconstruct population coding via evoked local field potentials (LFP and for simulating changes in synaptic plasticity. Our results also indicated that spatio-temporal code of the granular network is mainly controlled by the feed-forward inhibition from the Golgi cell synapses. Spike amplitude and total number of spikes were modulated by LTP and LTD. Reconstructing granular layer evoked-LFP suggests that granular layer propagates the nonlinearities of individual neurons. Simulations indicate that granular layer network operates a robust population code for a wide range of intervals, controlled by the Golgi cell inhibition and is regulated by the post-synaptic excitability.

  11. Neuroprotective effects of a novel single compound 1-methoxyoctadecan-1-ol isolated from Uncaria sinensis in primary cortical neurons and a photothrombotic ischemia model.

    Directory of Open Access Journals (Sweden)

    Ji Yeon Jang

    Full Text Available We identified a novel neuroprotective compound, 1-methoxyoctadecan-1-ol, from Uncaria sinensis (Oliv. Havil and investigated its effects and mechanisms in primary cortical neurons and in a photothrombotic ischemic model. In primary rat cortical neurons against glutamate-induced neurotoxicity, pretreatment with 1-methoxyoctadecan-1-ol resulted in significantly reduced neuronal death in a dose-dependent manner. In addition, treatment with 1-methoxyoctadecan-1-ol resulted in decreased neuronal apoptotic death, as assessed by nuclear morphological approaches. To clarify the neuroprotective mechanism of 1-methoxyoctadecan-1-ol, we explored the downstream signaling pathways of N-methyl-D-aspartate receptor (NMDAR with calpain activation. Treatment with glutamate leads to early activation of NMDAR, which in turn leads to calpain-mediated cleavage of striatal-enriched protein tyrosine phosphatase (STEP and subsequent activation of p38 mitogen activated protein kinase (MAPK. However, pretreatment with 1-methoxyoctadecan-1-ol resulted in significantly attenuated activation of GluN2B-NMDAR and a decrease in calpain-mediated STEP cleavage, leading to subsequent attenuation of p38 MAPK activation. We confirmed the critical role of p38 MAPK in neuroprotective effects of 1-methoxyoctadecan-1-ol using specific inhibitor SB203580. In the photothrombotic ischemic injury in mice, treatment with 1-methoxyoctadecan-1-ol resulted in significantly reduced infarct volume, edema size, and improved neurological function. 1-methoxyoctadecan-1-ol effectively prevents cerebral ischemic damage through down-regulation of calpain-mediated STEP cleavage and activation of p38 MAPK. These results suggest that 1-methoxyoctadecan-1-ol showed neuroprotective effects through down-regulation of calpain-mediated STEP cleavage with activation of GluN2B-NMDAR, and subsequent alleviation of p38 MAPK activation. In addition, 1-methoxyoctadecan-1-ol might be a useful therapeutic agent for

  12. Specific expression of channelrhodopsin-2 in single neurons of Caenorhabditis elegans.

    Directory of Open Access Journals (Sweden)

    Cornelia Schmitt

    Full Text Available Optogenetic approaches using light-activated proteins like Channelrhodopsin-2 (ChR2 enable investigating the function of populations of neurons in live Caenorhabditis elegans (and other animals, as ChR2 expression can be targeted to these cells using specific promoters. Sub-populations of these neurons, or even single cells, can be further addressed by restricting the illumination to the cell of interest. However, this is technically demanding, particularly in free moving animals. Thus, it would be helpful if expression of ChR2 could be restricted to single neurons or neuron pairs, as even wide-field illumination would photostimulate only this particular cell. To this end we adopted the use of Cre or FLP recombinases and conditional ChR2 expression at the intersection of two promoter expression domains, i.e. in the cell of interest only. Success of this method depends on precise knowledge of the individual promoters' expression patterns and on relative expression levels of recombinase and ChR2. A bicistronic expression cassette with GFP helps to identify the correct expression pattern. Here we show specific expression in the AVA reverse command neurons and the aversive polymodal sensory ASH neurons. This approach shall enable to generate strains for optogenetic manipulation of each of the 302 C. elegans neurons. This may eventually allow to model the C. elegans nervous system in its entirety, based on functional data for each neuron.

  13. Laser capture microdissection of enriched populations of neurons or single neurons for gene expression analysis after traumatic brain injury.

    Science.gov (United States)

    Boone, Deborah R; Sell, Stacy L; Hellmich, Helen Lee

    2013-04-10

    Long-term cognitive disability after TBI is associated with injury-induced neurodegeneration in the hippocampus-a region in the medial temporal lobe that is critical for learning, memory and executive function. Hence our studies focus on gene expression analysis of specific neuronal populations in distinct subregions of the hippocampus. The technique of laser capture microdissection (LCM), introduced in 1996 by Emmert-Buck, et al., has allowed for significant advances in gene expression analysis of single cells and enriched populations of cells from heterogeneous tissues such as the mammalian brain that contains thousands of functional cell types. We use LCM and a well established rat model of traumatic brain injury (TBI) to investigate the molecular mechanisms that underlie the pathogenesis of TBI. Following fluid-percussion TBI, brains are removed at pre-determined times post-injury, immediately frozen on dry ice, and prepared for sectioning in a cryostat. The rat brains can be embedded in OCT and sectioned immediately, or stored several months at -80 °C before sectioning for laser capture microdissection. Additionally, we use LCM to study the effects of TBI on circadian rhythms. For this, we capture neurons from the suprachiasmatic nuclei that contain the master clock of the mammalian brain. Here, we demonstrate the use of LCM to obtain single identified neurons (injured and degenerating, Fluoro-Jade-positive, or uninjured, Fluoro-Jade-negative) and enriched populations of hippocampal neurons for subsequent gene expression analysis by real time PCR and/or whole-genome microarrays. These LCM-enabled studies have revealed that the selective vulnerability of anatomically distinct regions of the rat hippocampus are reflected in the different gene expression profiles of different populations of neurons obtained by LCM from these distinct regions. The results from our single-cell studies, where we compare the transcriptional profiles of dying and adjacent surviving

  14. The role of dendritic non-linearities in single neuron computation

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    Boris Gutkin

    2014-05-01

    Full Text Available Experiment has demonstrated that summation of excitatory post-synaptic protientials (EPSPs in dendrites is non-linear. The sum of multiple EPSPs can be larger than their arithmetic sum, a superlinear summation due to the opening of voltage-gated channels and similar to somatic spiking. The so-called dendritic spike. The sum of multiple of EPSPs can also be smaller than their arithmetic sum, because the synaptic current necessarily saturates at some point. While these observations are well-explained by biophysical models the impact of dendritic spikes on computation remains a matter of debate. One reason is that dendritic spikes may fail to make the neuron spike; similarly, dendritic saturations are sometime presented as a glitch which should be corrected by dendritic spikes. We will provide solid arguments against this claim and show that dendritic saturations as well as dendritic spikes enhance single neuron computation, even when they cannot directly make the neuron fire. To explore the computational impact of dendritic spikes and saturations, we are using a binary neuron model in conjunction with Boolean algebra. We demonstrate using these tools that a single dendritic non-linearity, either spiking or saturating, combined with somatic non-linearity, enables a neuron to compute linearly non-separable Boolean functions (lnBfs. These functions are impossible to compute when summation is linear and the exclusive OR is a famous example of lnBfs. Importantly, the implementation of these functions does not require the dendritic non-linearity to make the neuron spike. Next, We show that reduced and realistic biophysical models of the neuron are capable of computing lnBfs. Within these models and contrary to the binary model, the dendritic and somatic non-linearity are tightly coupled. Yet we show that these neuron models are capable of linearly non-separable computations.

  15. Creation of defined single cell resolution neuronal circuits on microelectrode arrays

    Science.gov (United States)

    Pirlo, Russell Kirk

    2009-12-01

    The way cell-cell organization of neuronal networks influences activity and facilitates function is not well understood. Microelectrode arrays (MEAs) and advancing cell patterning technologies have enabled access to and control of in vitro neuronal networks spawning much new research in neuroscience and neuroengineering. We propose that small, simple networks of neurons with defined circuitry may serve as valuable research models where every connection can be analyzed, controlled and manipulated. Towards the goal of creating such neuronal networks we have applied microfabricated elastomeric membranes, surface modification and our unique laser cell patterning system to create defined neuronal circuits with single-cell precision on MEAs. Definition of synaptic connectivity was imposed by the 3D physical constraints of polydimethylsiloxane elastomeric membranes. The membranes had 20mum clear-through holes and 2-3mum deep channels which when applied to the surface of the MEA formed microwells to confine neurons to electrodes connected via shallow tunnels to direct neurite outgrowth. Tapering and turning of channels was used to influence neurite polarity. Biocompatibility of the membranes was increased by vacuum baking, oligomer extraction, and autoclaving. Membranes were bound to the MEA by oxygen plasma treatment and heated pressure. The MEA/membrane surface was treated with oxygen plasma, poly-D-lysine and laminin to improve neuron attachment, survival and neurite outgrowth. Prior to cell patterning the outer edge of culture area was seeded with 5x10 5 cells per cm and incubated for 2 days. Single embryonic day 7 chick forebrain neurons were then patterned into the microwells and onto the electrodes using our laser cell patterning system. Patterned neurons successfully attached to and were confined to the electrodes. Neurites extended through the interconnecting channels and connected with adjacent neurons. These results demonstrate that neuronal circuits can be

  16. 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.

  17. Effective stimuli for constructing reliable neuron models.

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    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.

  18. 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....

  19. 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...

  20. 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

  1. 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

  2. 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.

  3. 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.

  4. Stochastic optimal control of single neuron spike trains

    DEFF Research Database (Denmark)

    Iolov, Alexandre; Ditlevsen, Susanne; Longtin, Andrë

    2014-01-01

    stimulation of a neuron to achieve a target spike train under the physiological constraint to not damage tissue. Approach. We pose a stochastic optimal control problem to precisely specify the spike times in a leaky integrate-and-fire (LIF) model of a neuron with noise assumed to be of intrinsic or synaptic...... to the spike times (open-loop control). Main results. We have developed a stochastic optimal control algorithm to obtain precise spike times. It is applicable in both the supra-threshold and sub-threshold regimes, under open-loop and closed-loop conditions and with an arbitrary noise intensity; the accuracy...... into account physiological constraints on the control. A precise and robust targeting of neural activity based on stochastic optimal control has great potential for regulating neural activity in e.g. prosthetic applications and to improve our understanding of the basic mechanisms by which neuronal firing...

  5. Stimulus-response functions of single avian olfactory bulb neurones.

    Science.gov (United States)

    McKeegan, Dorothy E F; Demmers, Theodorus G M; Wathes, Christopher M; Jones, R Bryan; Gentle, Michael J

    2002-10-25

    This study investigated olfactory processing in a functional context by examining the responses of single avian olfactory bulb neurones to two biologically important gases over relevant concentration ranges. Recordings of extracellular spike activity were made from 80 single units in the left olfactory bulb of 11 anaesthetised, freely breathing adult hens (Gallus domesticus). The units were spontaneously active, exhibiting widely variable firing rates (0.07-47.28 spikes/s) and variable temporal firing patterns. Single units were tested for their response to an ascending concentration series of either ammonia (2.5-100 ppm) or hydrogen sulphide (1-50 ppm), delivered directly to the olfactory epithelium. Stimulation with a calibrated gas delivery system resulted in modification of spontaneous activity causing either inhibition (47% of units) or excitation (53%) of firing. For ammonia, 20 of the 35 units tested exhibited a response, while for hydrogen sulphide, 25 of the 45 units tested were responsive. Approximate response thresholds for ammonia (median threshold 3.75 ppm (range 2.5-60 ppm, n=20)) and hydrogen sulphide (median threshold 1 ppm (range 1-10 ppm, n=25)) were determined with most units exhibiting thresholds near the lower end of these ranges. Stimulus response curves were constructed for 23 units; 16 (the most complete) were subjected to a linear regression analysis to determine whether they were best fitted by a linear, log or power function. No single function provided the best fit for all the curves (seven were linear, eight were log, one was power). These findings show that avian units respond to changes in stimulus concentration in a manner generally consistent with reported responses in mammalian olfactory bulb neurones. However, this study illustrates a level of fine-tuning to small step changes in concentration (<5 ppm) not previously demonstrated in vertebrate single olfactory bulb neurones.

  6. 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....

  7. 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.

  8. 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. .

  9. A Route to Chaotic Behavior of Single Neuron Exposed to External Electromagnetic Radiation.

    Science.gov (United States)

    Feng, Peihua; Wu, Ying; Zhang, Jiazhong

    2017-01-01

    Non-linear behaviors of a single neuron described by Fitzhugh-Nagumo (FHN) neuron model, with external electromagnetic radiation considered, is investigated. It is discovered that with external electromagnetic radiation in form of a cosine function, the mode selection of membrane potential occurs among periodic, quasi-periodic, and chaotic motions as increasing the frequency of external transmembrane current, which is selected as a sinusoidal function. When the frequency is small or large enough, periodic, and quasi-periodic motions are captured alternatively. Otherwise, when frequency is in interval 0.778 electromagnetic radiation. The frequency apparently plays a more important role in determining the system behavior.

  10. Generation of Induced Neuronal Cells by the Single Reprogramming Factor ASCL1

    Directory of Open Access Journals (Sweden)

    Soham Chanda

    2014-08-01

    Full Text Available Direct conversion of nonneural cells to functional neurons holds great promise for neurological disease modeling and regenerative medicine. We previously reported rapid reprogramming of mouse embryonic fibroblasts (MEFs into mature induced neuronal (iN cells by forced expression of three transcription factors: ASCL1, MYT1L, and BRN2. Here, we show that ASCL1 alone is sufficient to generate functional iN cells from mouse and human fibroblasts and embryonic stem cells, indicating that ASCL1 is the key driver of iN cell reprogramming in different cell contexts and that the role of MYT1L and BRN2 is primarily to enhance the neuronal maturation process. ASCL1-induced single-factor neurons (1F-iN expressed mature neuronal markers, exhibited typical passive and active intrinsic membrane properties, and formed functional pre- and postsynaptic structures. Surprisingly, ASCL1-induced iN cells were predominantly excitatory, demonstrating that ASCL1 is permissive but alone not deterministic for the inhibitory neuronal lineage.

  11. Single-cell resolution mapping of neuronal damage in acute focal cerebral ischemia using thallium autometallography.

    Science.gov (United States)

    Stöber, Franziska; Baldauf, Kathrin; Ziabreva, Iryna; Harhausen, Denise; Zille, Marietta; Neubert, Jenni; Reymann, Klaus G; Scheich, Henning; Dirnagl, Ulrich; Schröder, Ulrich H; Wunder, Andreas; Goldschmidt, Jürgen

    2014-01-01

    Neuronal damage shortly after onset or after brief episodes of cerebral ischemia has remained difficult to assess with clinical and preclinical imaging techniques as well as with microscopical methods. We here show, in rodent models of middle cerebral artery occlusion (MCAO), that neuronal damage in acute focal cerebral ischemia can be mapped with single-cell resolution using thallium autometallography (TlAMG), a histochemical technique for the detection of the K(+)-probe thallium (Tl(+)) in the brain. We intravenously injected rats and mice with thallium diethyldithiocarbamate (TlDDC), a lipophilic chelate complex that releases Tl(+) after crossing the blood-brain barrier. We found, within the territories of the affected arteries, areas of markedly reduced neuronal Tl(+) uptake in all animals at all time points studied ranging from 15 minutes to 24 hours after MCAO. In large lesions at early time points, areas with neuronal and astrocytic Tl(+) uptake below thresholds of detection were surrounded by putative penumbral zones with preserved but diminished Tl(+) uptake. At 24 hours, the areas of reduced Tl(+)uptake matched with areas delineated by established markers of neuronal damage. The results suggest the use of (201)TlDDC for preclinical and clinical single-photon emission computed tomography (SPECT) imaging of hyperacute alterations in brain K(+) metabolism and prediction of tissue viability in cerebral ischemia.

  12. Single-cell resolution mapping of neuronal damage in acute focal cerebral ischemia using thallium autometallography

    Science.gov (United States)

    Stöber, Franziska; Baldauf, Kathrin; Ziabreva, Iryna; Harhausen, Denise; Zille, Marietta; Neubert, Jenni; Reymann, Klaus G; Scheich, Henning; Dirnagl, Ulrich; Schröder, Ulrich H; Wunder, Andreas; Goldschmidt, Jürgen

    2014-01-01

    Neuronal damage shortly after onset or after brief episodes of cerebral ischemia has remained difficult to assess with clinical and preclinical imaging techniques as well as with microscopical methods. We here show, in rodent models of middle cerebral artery occlusion (MCAO), that neuronal damage in acute focal cerebral ischemia can be mapped with single-cell resolution using thallium autometallography (TlAMG), a histochemical technique for the detection of the K+-probe thallium (Tl+) in the brain. We intravenously injected rats and mice with thallium diethyldithiocarbamate (TlDDC), a lipophilic chelate complex that releases Tl+ after crossing the blood–brain barrier. We found, within the territories of the affected arteries, areas of markedly reduced neuronal Tl+ uptake in all animals at all time points studied ranging from 15 minutes to 24 hours after MCAO. In large lesions at early time points, areas with neuronal and astrocytic Tl+ uptake below thresholds of detection were surrounded by putative penumbral zones with preserved but diminished Tl+ uptake. At 24 hours, the areas of reduced Tl+uptake matched with areas delineated by established markers of neuronal damage. The results suggest the use of 201TlDDC for preclinical and clinical single-photon emission computed tomography (SPECT) imaging of hyperacute alterations in brain K+ metabolism and prediction of tissue viability in cerebral ischemia. PMID:24129748

  13. 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.

  14. 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.

  15. Synaptic and intrinsic homeostasis cooperate to optimize single neuron response properties and tune integrator circuits

    Science.gov (United States)

    2016-01-01

    Homeostatic processes that provide negative feedback to regulate neuronal firing rate are essential for normal brain function, and observations suggest that multiple such processes may operate simultaneously in the same network. We pose two questions: why might a diversity of homeostatic pathways be necessary, and how can they operate in concert without opposing and undermining each other? To address these questions, we perform a computational and analytical study of cell-intrinsic homeostasis and synaptic homeostasis in single-neuron and recurrent circuit models. We demonstrate analytically and in simulation that when two such mechanisms are controlled on a long time scale by firing rate via simple and general feedback rules, they can robustly operate in tandem to tune the mean and variance of single neuron's firing rate to desired goals. This property allows the system to recover desired behavior after chronic changes in input statistics. We illustrate the power of this homeostatic tuning scheme by using it to regain high mutual information between neuronal input and output after major changes in input statistics. We then show that such dual homeostasis can be applied to tune the behavior of a neural integrator, a system that is notoriously sensitive to variation in parameters. These results are robust to variation in goals and model parameters. We argue that a set of homeostatic processes that appear to redundantly regulate mean firing rate may work together to control firing rate mean and variance and thus maintain performance in a parameter-sensitive task such as integration. PMID:27306675

  16. On the Non-Learnability of a Single Spiking Neuron

    Czech Academy of Sciences Publication Activity Database

    Šíma, Jiří; Sgall, Jiří

    2005-01-01

    Roč. 17, č. 12 (2005), s. 2635-2647 ISSN 0899-7667 R&D Projects: GA ČR GA201/02/1456; GA AV ČR 1ET100300517; GA MŠk LN00A056; GA MŠk(CZ) 1M0545 Institutional research plan: CEZ:AV0Z10300504; CEZ:AV0Z10190503 Keywords : spiking neuron * consistency problem * NP-completness * PAC model * robust learning * representation problem Subject RIV: BA - General Mathematics Impact factor: 2.591, year: 2005

  17. Spiking irregularity and frequency modulate the behavioral report of single-neuron stimulation.

    Science.gov (United States)

    Doron, Guy; von Heimendahl, Moritz; Schlattmann, Peter; Houweling, Arthur R; Brecht, Michael

    2014-02-05

    The action potential activity of single cortical neurons can evoke measurable sensory effects, but it is not known how spiking parameters and neuronal subtypes affect the evoked sensations. Here, we examined the effects of spike train irregularity, spike frequency, and spike number on the detectability of single-neuron stimulation in rat somatosensory cortex. For regular-spiking, putative excitatory neurons, detectability increased with spike train irregularity and decreasing spike frequencies but was not affected by spike number. Stimulation of single, fast-spiking, putative inhibitory neurons led to a larger sensory effect compared to regular-spiking neurons, and the effect size depended only on spike irregularity. An ideal-observer analysis suggests that, under our experimental conditions, rats were using integration windows of a few hundred milliseconds or more. Our data imply that the behaving animal is sensitive to single neurons' spikes and even to their temporal patterning. Copyright © 2014 Elsevier Inc. All rights reserved.

  18. Variations in interpulse interval of double action potentials during propagation in single neurons.

    Science.gov (United States)

    Villagran-Vargas, Edgar; Rodríguez-Sosa, Leonardo; Hustert, Reinhold; Blicher, Andreas; Laub, Katrine; Heimburg, Thomas

    2013-02-01

    In this work, we analyzed the interpulse interval (IPI) of doublets and triplets in single neurons of three biological models. Pulse trains with two or three spikes originate from the process of sensory mechanotransduction in neurons of the locust femoral nerve, as well as through spontaneous activity both in the abdominal motor neurons and the caudal photoreceptor of the crayfish. We show that the IPI for successive low-frequency single action potentials, as recorded with two electrodes at two different points along a nerve axon, remains constant. On the other hand, IPI in doublets either remains constant, increases or decreases by up to about 3 ms as the pair propagates. When IPI increases, the succeeding pulse travels at a slower speed than the preceding one. When IPI is reduced, the succeeding pulse travels faster than the preceding one and may exceed the normal value for the specific neuron. In both cases, IPI increase and reduction, the speed of the preceding pulse differs slightly from the normal value, therefore the two pulses travel at different speeds in the same nerve axon. On the basis of our results, we may state that the effect of attraction or repulsion in doublets suggests a tendency of the spikes to reach a stable configuration. We strongly suggest that the change in IPI during spike propagation of doublets opens up a whole new realm of possibilities for neural coding and may have major implications for understanding information processing in nervous systems. Copyright © 2012 Wiley Periodicals, Inc.

  19. 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

  20. 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.

  1. Reward-timing-dependent bidirectional modulation of cortical microcircuits during optical single-neuron operant conditioning.

    Science.gov (United States)

    Hira, Riichiro; Ohkubo, Fuki; Masamizu, Yoshito; Ohkura, Masamichi; Nakai, Junichi; Okada, Takashi; Matsuzaki, Masanori

    2014-11-24

    Animals rapidly adapt to environmental change. To reveal how cortical microcircuits are rapidly reorganized when an animal recognizes novel reward contingency, we conduct two-photon calcium imaging of layer 2/3 motor cortex neurons in mice and simultaneously reinforce the activity of a single cortical neuron with water delivery. Here we show that when the target neuron is not relevant to a pre-trained forelimb movement, the mouse increases the target neuron activity and the number of rewards delivered during 15-min operant conditioning without changing forelimb movement behaviour. The reinforcement bidirectionally modulates the activity of subsets of non-target neurons, independent of distance from the target neuron. The bidirectional modulation depends on the relative timing between the reward delivery and the neuronal activity, and is recreated by pairing reward delivery and photoactivation of a subset of neurons. Reward-timing-dependent bidirectional modulation may be one of the fundamental processes in microcircuit reorganization for rapid adaptation.

  2. Imaging Action Potential in Single Mammalian Neurons by Tracking the Accompanying Sub-Nanometer Mechanical Motion.

    Science.gov (United States)

    Yang, Yunze; Liu, Xian-Wei; Wang, Hui; Yu, Hui; Guan, Yan; Wang, Shaopeng; Tao, Nongjian

    2018-03-28

    Action potentials in neurons have been studied traditionally by intracellular electrophysiological recordings and more recently by the fluorescence detection methods. Here we describe a label-free optical imaging method that can measure mechanical motion in single cells with a sub-nanometer detection limit. Using the method, we have observed sub-nanometer mechanical motion accompanying the action potential in single mammalian neurons by averaging the repeated action potential spikes. The shape and width of the transient displacement are similar to those of the electrically recorded action potential, but the amplitude varies from neuron to neuron, and from one region of a neuron to another, ranging from 0.2-0.4 nm. The work indicates that action potentials may be studied noninvasively in single mammalian neurons by label-free imaging of the accompanying sub-nanometer mechanical motion.

  3. Zooming Out of Single Neurons Reveals Structure in Mnemonic Representations.

    Science.gov (United States)

    Jazayeri, Mehrdad

    2017-12-20

    In this issue of Neuron, Rossi-Pool et al. (2017) show that the complex and heterogeneous response profiles of individual neurons in the dorsal premotor cortex during comparison of tactile temporal patterns can be understood in terms of two robust activity patterns that emerge across the population. Copyright © 2017 Elsevier Inc. All rights reserved.

  4. A Route to Chaotic Behavior of Single Neuron Exposed to External Electromagnetic Radiation

    Directory of Open Access Journals (Sweden)

    Peihua Feng

    2017-10-01

    Full Text Available Non-linear behaviors of a single neuron described by Fitzhugh-Nagumo (FHN neuron model, with external electromagnetic radiation considered, is investigated. It is discovered that with external electromagnetic radiation in form of a cosine function, the mode selection of membrane potential occurs among periodic, quasi-periodic, and chaotic motions as increasing the frequency of external transmembrane current, which is selected as a sinusoidal function. When the frequency is small or large enough, periodic, and quasi-periodic motions are captured alternatively. Otherwise, when frequency is in interval 0.778 < ω < 2.208, chaotic motion characterizes the main behavior type. The mechanism of mode transition from quasi-periodic to chaotic motion is also observed when varying the amplitude of external electromagnetic radiation. The frequency apparently plays a more important role in determining the system behavior.

  5. 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.

  6. Single-Cell Gene Expression Analysis of Cholinergic Neurons in the Arcuate Nucleus of the Hypothalamus.

    Directory of Open Access Journals (Sweden)

    Jae Hoon Jeong

    Full Text Available The cholinoceptive system in the hypothalamus, in particular in the arcuate nucleus (ARC, plays a role in regulating food intake. Neurons in the ARC contain multiple neuropeptides, amines, and neurotransmitters. To study molecular and neurochemical heterogeneity of ARC neurons, we combine single-cell qRT-PCR and single-cell whole transcriptome amplification methods to analyze expression patterns of our hand-picked 60 genes in individual neurons in the ARC. Immunohistochemical and single-cell qRT-PCR analyses show choline acetyltransferase (ChAT-expressing neurons in the ARC. Gene expression patterns are remarkably distinct in each individual cholinergic neuron. Two-thirds of cholinergic neurons express tyrosine hydroxylase (Th mRNA. A large subset of these Th-positive cholinergic neurons is GABAergic as they express the GABA synthesizing enzyme glutamate decarboxylase and vesicular GABA transporter transcripts. Some cholinergic neurons also express the vesicular glutamate transporter transcript gene. POMC and POMC-processing enzyme transcripts are found in a subpopulation of cholinergic neurons. Despite this heterogeneity, gene expression patterns in individual cholinergic cells appear to be highly regulated in a cell-specific manner. In fact, membrane receptor transcripts are clustered with their respective intracellular signaling and downstream targets. This novel population of cholinergic neurons may be part of the neural circuitries that detect homeostatic need for food and control the drive to eat.

  7. A single gene target of an ETS-family transcription factor determines neuronal CO2-chemosensitivity.

    Directory of Open Access Journals (Sweden)

    Julia P Brandt

    Full Text Available Many animals possess neurons specialized for the detection of carbon dioxide (CO(2, which acts as a cue to elicit behavioral responses and is also an internally generated product of respiration that regulates animal physiology. In many organisms how such neurons detect CO(2 is poorly understood. We report here a mechanism that endows C. elegans neurons with the ability to detect CO(2. The ETS-5 transcription factor is necessary for the specification of CO(2-sensing BAG neurons. Expression of a single ETS-5 target gene, gcy-9, which encodes a receptor-type guanylate cyclase, is sufficient to bypass a requirement for ets-5 in CO(2-detection and transforms neurons into CO(2-sensing neurons. Because ETS-5 and GCY-9 are members of gene families that are conserved between nematodes and vertebrates, a similar mechanism might act in the specification of CO(2-sensing neurons in other phyla.

  8. Computation in a single neuron: Hodgkin and Huxley revisited

    OpenAIRE

    Arcas, Blaise Aguera y; Fairhall, Adrienne L.; Bialek, William

    2002-01-01

    A spiking neuron ``computes'' by transforming a complex dynamical input into a train of action potentials, or spikes. The computation performed by the neuron can be formulated as dimensional reduction, or feature detection, followed by a nonlinear decision function over the low dimensional space. Generalizations of the reverse correlation technique with white noise input provide a numerical strategy for extracting the relevant low dimensional features from experimental data, and information t...

  9. Binaural response characteristics of single neurons in the medial superior olivary nucleus of the albino rat.

    Science.gov (United States)

    Inbody, S B; Feng, A S

    1981-04-06

    Binaural response properties of single neurons in the medial superior olivary nucleus (MSO) were investigated in the anesthetized rat. Stimulus parameters studied included interaural time difference and interaural intensity difference. In the present study, of the two cell types observed in the rat MSO nucleus, EE and EI, variations in the binaural response properties of the MSO neurons permitted further subclassifications, which may be related to the dendritic dominance of the MSO neurons.

  10. A single gene target of an ETS-family transcription factor determines neuronal CO2-chemosensitivity

    DEFF Research Database (Denmark)

    Brandt, Julia P; Aziz-Zaman, Sonya; Juozaityte, Vaida

    2012-01-01

    . We report here a mechanism that endows C. elegans neurons with the ability to detect CO(2). The ETS-5 transcription factor is necessary for the specification of CO(2)-sensing BAG neurons. Expression of a single ETS-5 target gene, gcy-9, which encodes a receptor-type guanylate cyclase, is sufficient...

  11. Single photon emission computed tomography in motor neuron disease with dementia.

    Science.gov (United States)

    Sawada, H; Udaka, F; Kishi, Y; Seriu, N; Mezaki, T; Kameyama, M; Honda, M; Tomonobu, M

    1988-01-01

    Single photon emission computed tomography with [123 I] isopropylamphetamine was carried out on a patient with motor neuron disease with dementia. [123 I] uptake was decreased in the frontal lobes. This would reflect the histopathological findings such as neuronal loss and gliosis in the frontal lobes.

  12. Divisive normalization and neuronal oscillations in a single hierarchical framework of selective visual attention

    Directory of Open Access Journals (Sweden)

    Jorrit Steven Montijn

    2012-05-01

    Full Text Available In divisive normalization models of covert attention, spike rate modulations are commonly used as indicators of the effect of top-down attention. In addition, an increasing number of studies have shown that top-down attention increases the synchronization of neuronal oscillations as well, particularly those in gamma-band frequencies (25 to 100 Hz. Although modulations of spike rate and synchronous oscillations are not mutually exclusive as mechanisms of attention, there has thus far been little effort to integrate these concepts into a single framework of attention. Here, we aim to provide such a unified framework by expanding the normalization model of attention with a time dimension; allowing the simulation of a recently reported backward progression of attentional effects along the visual cortical hierarchy. A simple hierarchical cascade of normalization models simulating different cortical areas however leads to signal degradation and a loss of discriminability over time. To negate this degradation and ensure stable neuronal stimulus representations, we incorporate oscillatory phase entrainment into our model, a mechanism previously proposed as the communication-through-coherence (CTC hypothesis. Our analysis shows that divisive normalization and oscillation models can complement each other in a unified account of the neural mechanisms of selective visual attention. The resulting hierarchical normalization and oscillation (HNO model reproduces several additional spatial and temporal aspects of attentional modulation.

  13. Predicting the functional states of human iPSC-derived neurons with single-cell RNA-seq and electrophysiology.

    Science.gov (United States)

    Bardy, C; van den Hurk, M; Kakaradov, B; Erwin, J A; Jaeger, B N; Hernandez, R V; Eames, T; Paucar, A A; Gorris, M; Marchand, C; Jappelli, R; Barron, J; Bryant, A K; Kellogg, M; Lasken, R S; Rutten, B P F; Steinbusch, H W M; Yeo, G W; Gage, F H

    2016-11-01

    Human neural progenitors derived from pluripotent stem cells develop into electrophysiologically active neurons at heterogeneous rates, which can confound disease-relevant discoveries in neurology and psychiatry. By combining patch clamping, morphological and transcriptome analysis on single-human neurons in vitro, we defined a continuum of poor to highly functional electrophysiological states of differentiated neurons. The strong correlations between action potentials, synaptic activity, dendritic complexity and gene expression highlight the importance of methods for isolating functionally comparable neurons for in vitro investigations of brain disorders. Although whole-cell electrophysiology is the gold standard for functional evaluation, it often lacks the scalability required for disease modeling studies. Here, we demonstrate a multimodal machine-learning strategy to identify new molecular features that predict the physiological states of single neurons, independently of the time spent in vitro. As further proof of concept, we selected one of the potential neurophysiological biomarkers identified in this study-GDAP1L1-to isolate highly functional live human neurons in vitro.

  14. 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

  15. Carbon nanotubes: artificial nanomaterials to engineer single neurons and neuronal networks.

    Science.gov (United States)

    Fabbro, Alessandra; Bosi, Susanna; Ballerini, Laura; Prato, Maurizio

    2012-08-15

    In the past decade, nanotechnology applications to the nervous system have often involved the study and the use of novel nanomaterials to improve the diagnosis and therapy of neurological diseases. In the field of nanomedicine, carbon nanotubes are evaluated as promising materials for diverse therapeutic and diagnostic applications. Besides, carbon nanotubes are increasingly employed in basic neuroscience approaches, and they have been used in the design of neuronal interfaces or in that of scaffolds promoting neuronal growth in vitro. Ultimately, carbon nanotubes are thought to hold the potential for the development of innovative neurological implants. In this framework, it is particularly relevant to document the impact of interfacing such materials with nerve cells. Carbon nanotubes were shown, when modified with biologically active compounds or functionalized in order to alter their charge, to affect neurite outgrowth and branching. Notably, purified carbon nanotubes used as scaffolds can promote the formation of nanotube-neuron hybrid networks, able per se to affect neuron integrative abilities, network connectivity, and synaptic plasticity. We focus this review on our work over several years directed to investigate the ability of carbon nanotube platforms in providing a new tool for nongenetic manipulations of neuronal performance and network signaling.

  16. 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.

  17. High-Throughput Mapping of Single-Neuron Projections by Sequencing of Barcoded RNA.

    Science.gov (United States)

    Kebschull, Justus M; Garcia da Silva, Pedro; Reid, Ashlan P; Peikon, Ian D; Albeanu, Dinu F; Zador, Anthony M

    2016-09-07

    Neurons transmit information to distant brain regions via long-range axonal projections. In the mouse, area-to-area connections have only been systematically mapped using bulk labeling techniques, which obscure the diverse projections of intermingled single neurons. Here we describe MAPseq (Multiplexed Analysis of Projections by Sequencing), a technique that can map the projections of thousands or even millions of single neurons by labeling large sets of neurons with random RNA sequences ("barcodes"). Axons are filled with barcode mRNA, each putative projection area is dissected, and the barcode mRNA is extracted and sequenced. Applying MAPseq to the locus coeruleus (LC), we find that individual LC neurons have preferred cortical targets. By recasting neuroanatomy, which is traditionally viewed as a problem of microscopy, as a problem of sequencing, MAPseq harnesses advances in sequencing technology to permit high-throughput interrogation of brain circuits. Copyright © 2016 Elsevier Inc. All rights reserved.

  18. Orientation selectivity in inhibition-dominated networks of spiking neurons: effect of single neuron properties and network dynamics.

    Science.gov (United States)

    Sadeh, Sadra; Rotter, Stefan

    2015-01-01

    The neuronal mechanisms underlying the emergence of orientation selectivity in the primary visual cortex of mammals are still elusive. In rodents, visual neurons show highly selective responses to oriented stimuli, but neighboring neurons do not necessarily have similar preferences. Instead of a smooth map, one observes a salt-and-pepper organization of orientation selectivity. Modeling studies have recently confirmed that balanced random networks are indeed capable of amplifying weakly tuned inputs and generating highly selective output responses, even in absence of feature-selective recurrent connectivity. Here we seek to elucidate the neuronal mechanisms underlying this phenomenon by resorting to networks of integrate-and-fire neurons, which are amenable to analytic treatment. Specifically, in networks of perfect integrate-and-fire neurons, we observe that highly selective and contrast invariant output responses emerge, very similar to networks of leaky integrate-and-fire neurons. We then demonstrate that a theory based on mean firing rates and the detailed network topology predicts the output responses, and explains the mechanisms underlying the suppression of the common-mode, amplification of modulation, and contrast invariance. Increasing inhibition dominance in our networks makes the rectifying nonlinearity more prominent, which in turn adds some distortions to the otherwise essentially linear prediction. An extension of the linear theory can account for all the distortions, enabling us to compute the exact shape of every individual tuning curve in our networks. We show that this simple form of nonlinearity adds two important properties to orientation selectivity in the network, namely sharpening of tuning curves and extra suppression of the modulation. The theory can be further extended to account for the nonlinearity of the leaky model by replacing the rectifier by the appropriate smooth input-output transfer function. These results are robust and do not

  19. Stable long-term chronic brain mapping at the single-neuron level.

    Science.gov (United States)

    Fu, Tian-Ming; Hong, Guosong; Zhou, Tao; Schuhmann, Thomas G; Viveros, Robert D; Lieber, Charles M

    2016-10-01

    Stable in vivo mapping and modulation of the same neurons and brain circuits over extended periods is critical to both neuroscience and medicine. Current electrical implants offer single-neuron spatiotemporal resolution but are limited by such factors as relative shear motion and chronic immune responses during long-term recording. To overcome these limitations, we developed a chronic in vivo recording and stimulation platform based on flexible mesh electronics, and we demonstrated stable multiplexed local field potentials and single-unit recordings in mouse brains for at least 8 months without probe repositioning. Properties of acquired signals suggest robust tracking of the same neurons over this period. This recording and stimulation platform allowed us to evoke stable single-neuron responses to chronic electrical stimulation and to carry out longitudinal studies of brain aging in freely behaving mice. Such advantages could open up future studies in mapping and modulating changes associated with learning, aging and neurodegenerative diseases.

  20. 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.

  1. 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

  2. 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.

  3. Kaleido: Visualizing Big Brain Data with Automatic Color Assignment for Single-Neuron Images.

    Science.gov (United States)

    Wang, Ting-Yuan; Chen, Nan-Yow; He, Guan-Wei; Wang, Guo-Tzau; Shih, Chi-Tin; Chiang, Ann-Shyn

    2018-03-03

    Effective 3D visualization is essential for connectomics analysis, where the number of neural images easily reaches over tens of thousands. A formidable challenge is to simultaneously visualize a large number of distinguishable single-neuron images, with reasonable processing time and memory for file management and 3D rendering. In the present study, we proposed an algorithm named "Kaleido" that can visualize up to at least ten thousand single neurons from the Drosophila brain using only a fraction of the memory traditionally required, without increasing computing time. Adding more brain neurons increases memory only nominally. Importantly, Kaleido maximizes color contrast between neighboring neurons so that individual neurons can be easily distinguished. Colors can also be assigned to neurons based on biological relevance, such as gene expression, neurotransmitters, and/or development history. For cross-lab examination, the identity of every neuron is retrievable from the displayed image. To demonstrate the effectiveness and tractability of the method, we applied Kaleido to visualize the 10,000 Drosophila brain neurons obtained from the FlyCircuit database ( http://www.flycircuit.tw/modules.php?name=kaleido ). Thus, Kaleido visualization requires only sensible computer memory for manual examination of big connectomics data.

  4. Crypt neurons express a single V1R-related ora gene.

    Science.gov (United States)

    Oka, Yuichiro; Saraiva, Luis R; Korsching, Sigrun I

    2012-03-01

    Both ciliated and microvillous olfactory sensory neuron populations express large families of olfactory receptor genes. However, individual neurons generally express only a single receptor gene according to the "one neuron-one receptor" rule. We report here that crypt neurons, the third type of olfactory neurons in fish species, use an even more restricted mode of expression. We recently identified a novel olfactory receptor family of 6 highly conserved G protein-coupled receptors, the v1r-like ora genes. We show now that a single member of this family, ora4 is expressed in nearly all crypt neurons, whereas the other 5 ora genes are not found in this cell type. Consistent with these findings, ora4 is never coexpressed with any of the remaining 5 ora genes. Furthermore, several lines of evidence indicate the absence of any other olfactory receptor families in crypt neurons. These results suggest that the vast majority of the crypt neuron population may select one and the same olfactory receptor gene, a "one cell type-one receptor" mode of expression. Such an expression pattern is familiar in the visual system, with rhodopsin as the sole light receptor of rod photoreceptor cells, but unexpected in the sense of smell.

  5. Single low doses of MPTP decrease tyrosine hydroxylase expression in the absence of overt neuron loss.

    Science.gov (United States)

    Alam, Gelareh; Edler, Melissa; Burchfield, Shelbie; Richardson, Jason R

    2017-05-01

    Parkinson's disease (PD) is the second most common age-related neurodegenerative disease. 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) is a prototypical neurotoxicant used in mice to mimic primary features of PD pathology including striatal dopamine depletion and dopamine neuron loss in the substantia nigra pars compacta (SNc). In the literature, there are several experimental paradigms involving multiple doses of MPTP that are used to elicit dopamine neuron loss. However, a recent study reported that a single low dose caused significant loss of dopamine neurons. Here, we determined the effect of a single intraperitoneal injection of one of three doses of MPTP (0.1, 2 and 20mg/kg) on dopamine neurons, labeled by tyrosine hydroxylase (TH + ), and total neuron number (Nissl + ) in the SNc using unbiased stereological counting. Data reveal a significant loss of neurons in the SNc (TH + and Nissl + ) only in the group treated with 20mg/kg MPTP. Groups treated with lower dose of MPTP (0.1 and 2mg/kg) only showed significant loss of TH + neurons rather than TH + and Nissl + neurons. Striatal dopamine levels were decreased in the groups treated with 2 and 20mg/kg MPTP and striatal terminal markers including, TH and the dopamine transporter (DAT), were only decreased in the groups treated with 20mg/kg MPTP. These data demonstrate that lower doses of MPTP likely result in loss of TH expression rather than actual dopamine neuron loss in the SN. This finding reinforces the need to measure both total neuron number along with TH + cells in determining dopamine neuron loss. Copyright © 2017 Elsevier B.V. All rights reserved.

  6. 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.

  7. 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.

  8. Induction of associative olfactory memory by targeted activation of single olfactory neurons in Drosophila larvae.

    Science.gov (United States)

    Honda, Takato; Lee, Chi-Yu; Yoshida-Kasikawa, Maki; Honjo, Ken; Furukubo-Tokunaga, Katsuo

    2014-04-25

    It has been postulated that associative memory is formed by at least two sets of external stimuli, CS and US, that are transmitted to the memory centers by distinctive conversing pathways. However, whether associative memory can be induced by the activation of only the olfactory CS and a biogenic amine-mediated US pathways remains to be elucidated. In this study, we substituted the reward signals with dTrpA1-mediated thermogenetic activation of octopaminergic neurons and the odor signals by ChR2-mediated optical activation of a specific class of olfactory neurons. We show that targeted activation of the olfactory receptor and the octopaminergic neurons is indeed sufficient for the formation of associative olfactory memory in the larval brain. We also show that targeted stimulation of only a single type of olfactory receptor neurons is sufficient to induce olfactory memory that is indistinguishable from natural memory induced by the activation of multiple olfactory receptor neurons.

  9. 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.

  10. Task-dependent changes in cross-level coupling between single neurons and oscillatory activity in multiscale networks.

    Directory of Open Access Journals (Sweden)

    Ryan T Canolty

    Full Text Available Understanding the principles governing the dynamic coordination of functional brain networks remains an important unmet goal within neuroscience. How do distributed ensembles of neurons transiently coordinate their activity across a variety of spatial and temporal scales? While a complete mechanistic account of this process remains elusive, evidence suggests that neuronal oscillations may play a key role in this process, with different rhythms influencing both local computation and long-range communication. To investigate this question, we recorded multiple single unit and local field potential (LFP activity from microelectrode arrays implanted bilaterally in macaque motor areas. Monkeys performed a delayed center-out reach task either manually using their natural arm (Manual Control, MC or under direct neural control through a brain-machine interface (Brain Control, BC. In accord with prior work, we found that the spiking activity of individual neurons is coupled to multiple aspects of the ongoing motor beta rhythm (10-45 Hz during both MC and BC, with neurons exhibiting a diversity of coupling preferences. However, here we show that for identified single neurons, this beta-to-rate mapping can change in a reversible and task-dependent way. For example, as beta power increases, a given neuron may increase spiking during MC but decrease spiking during BC, or exhibit a reversible shift in the preferred phase of firing. The within-task stability of coupling, combined with the reversible cross-task changes in coupling, suggest that task-dependent changes in the beta-to-rate mapping play a role in the transient functional reorganization of neural ensembles. We characterize the range of task-dependent changes in the mapping from beta amplitude, phase, and inter-hemispheric phase differences to the spike rates of an ensemble of simultaneously-recorded neurons, and discuss the potential implications that dynamic remapping from oscillatory activity to

  11. 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.

  12. Single Ih channels in pyramidal neuron dendrites: properties, distribution, and impact on action potential output

    NARCIS (Netherlands)

    Kole, Maarten H. P.; Hallermann, Stefan; Stuart, Greg J.

    2006-01-01

    The hyperpolarization-activated cation current (Ih) plays an important role in regulating neuronal excitability, yet its native single-channel properties in the brain are essentially unknown. Here we use variance-mean analysis to study the properties of single Ih channels in the apical dendrites of

  13. Simultaneous transcranial magnetic stimulation and single neuron recording in alert non-human primates

    OpenAIRE

    Mueller, Jerel K.; Grigsby, Erinn M.; Prevosto, Vincent; Petraglia, Frank W.; Rao, Hrishikesh; Deng, Zhi-De; Peterchev, Angel V.; Sommer, Marc A.; Egner, Tobias; Platt, Michael L.; Grill, Warren M.

    2014-01-01

    Transcranial magnetic stimulation (TMS) is a widely used, noninvasive method for stimulating nervous tissue, yet its mechanisms of effect are poorly understood. Here we report novel methods for studying the influence of TMS on single neurons in the brain of alert non-human primates. We designed a TMS coil that focuses its effect near the tip of a recording electrode and recording electronics that enable direct acquisition of neuronal signals at the site of peak stimulus strength minimally per...

  14. Functional adaptation to loading of a single bone is neuronally regulated and involves multiple bones.

    Science.gov (United States)

    Sample, Susannah J; Behan, Mary; Smith, Lesley; Oldenhoff, William E; Markel, Mark D; Kalscheur, Vicki L; Hao, Zhengling; Miletic, Vjekoslav; Muir, Peter

    2008-09-01

    Regulation of load-induced bone formation is considered a local phenomenon controlled by osteocytes, although it has also been hypothesized that functional adaptation may be neuronally regulated. The aim of this study was to examine bone formation in multiple bones, in response to loading of a single bone, and to determine whether adaptation may be neuronally regulated. Load-induced responses in the left and right ulnas and humeri were determined after loading of the right ulna in male Sprague-Dawley rats (69 +/- 16 days of age). After a single period of loading at -760-, -2000-, or -3750-microepsilon initial peak strain, rats were given calcein to label new bone formation. Bone formation and bone neuropeptide concentrations were determined at 10 days. In one group, temporary neuronal blocking was achieved by perineural anesthesia of the brachial plexus with bupivicaine during loading. We found right ulna loading induces adaptive responses in other bones in both thoracic limbs compared with Sham controls and that neuronal blocking during loading abrogated bone formation in the loaded ulna and other thoracic limb bones. Skeletal adaptation was more evident in distal long bones compared with proximal long bones. We also found that the single period of loading modulated bone neuropeptide concentrations persistently for 10 days. We conclude that functional adaptation to loading of a single bone in young rapidly growing rats is neuronally regulated and involves multiple bones. Persistent changes in bone neuropeptide concentrations after a single loading period suggest that plasticity exists in the innervation of bone.

  15. 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...

  16. 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.

  17. 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...

  18. Auditory and audio-vocal responses of single neurons in the monkey ventral premotor cortex.

    Science.gov (United States)

    Hage, Steffen R

    2018-03-20

    Monkey vocalization is a complex behavioral pattern, which is flexibly used in audio-vocal communication. A recently proposed dual neural network model suggests that cognitive control might be involved in this behavior, originating from a frontal cortical network in the prefrontal cortex and mediated via projections from the rostral portion of the ventral premotor cortex (PMvr) and motor cortex to the primary vocal motor network in the brainstem. For the rapid adjustment of vocal output to external acoustic events, strong interconnections between vocal motor and auditory sites are needed, which are present at cortical and subcortical levels. However, the role of the PMvr in audio-vocal integration processes remains unclear. In the present study, single neurons in the PMvr were recorded in rhesus monkeys (Macaca mulatta) while volitionally producing vocalizations in a visual detection task or passively listening to monkey vocalizations. Ten percent of randomly selected neurons in the PMvr modulated their discharge rate in response to acoustic stimulation with species-specific calls. More than four-fifths of these auditory neurons showed an additional modulation of their discharge rates either before and/or during the monkeys' motor production of the vocalization. Based on these audio-vocal interactions, the PMvr might be well positioned to mediate higher order auditory processing with cognitive control of the vocal motor output to the primary vocal motor network. Such audio-vocal integration processes in the premotor cortex might constitute a precursor for the evolution of complex learned audio-vocal integration systems, ultimately giving rise to human speech. Copyright © 2018 Elsevier B.V. All rights reserved.

  19. Neurons the decision makers, Part I: The firing function of a single neuron.

    Science.gov (United States)

    Saaty, Thomas

    2017-02-01

    This paper is concerned with understanding synthesis of electric signals in the neural system based on making pairwise comparisons. Fundamentally, every person and every animal are born with the talent to compare stimuli from things that share properties in space or over time. Comparisons always need experience to distinguish among things. Pairwise comparisons are numerically reciprocal. If a value is assigned to the larger of two elements that have a given property when compared with the smaller one, then the smaller has the reciprocal of that value when compared with the larger. Because making comparisons requires the reciprocal property, we need mathematics that can cope with division. There are four division algebras that would allow us to use our reciprocals arising from comparisons: The real numbers, the complex numbers, the non-commutative quaternions and the non-associative octonions. Rather than inferring function as from electric flow in a network, in this paper we infer the flow from function. Neurons fire in response to stimuli and their firings vary relative to the intensities of the stimuli. We believe neurons use some kind of pairwise comparison mechanism to determine when to fire based on the stimuli they receive. The ideas we develop here about flows are used to deduce how a system based on this kind of firing determination works and can be described. Furthermore the firing of neurons requires continuous comparisons. To develop a formula describing the output of these pairwise comparisons requires solving Fredholm's equation of the second kind which is satisfied if and only if a simple functional equation has solutions. The Fourier transform of the real solution of this equation leads to inverse square laws like those that are common in physics. The Fourier transform applied to a complex valued solution leads to Dirac type of firings. Such firings are dense in the very general fields of functions known as Sobolev spaces and thus can be used to

  20. Single Item Inventory Models

    NARCIS (Netherlands)

    E.M. Bazsa-Oldenkamp; P. den Iseger

    2001-01-01

    textabstractThis paper extends a fundamental result about single-item inventory systems. This approach allows more general performance measures, demand processes and order policies, and leads to easier analysis and implementation, than prior research. We obtain closed form expressions for the

  1. 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.

  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. Integrative Single-Cell Transcriptomics Reveals Molecular Networks Defining Neuronal Maturation During Postnatal Neurogenesis.

    Science.gov (United States)

    Gao, Yu; Wang, Feifei; Eisinger, Brian E; Kelnhofer, Laurel E; Jobe, Emily M; Zhao, Xinyu

    2017-03-01

    In mammalian hippocampus, new neurons are continuously produced from neural stem cells throughout life. This postnatal neurogenesis may contribute to information processing critical for cognition, adaptation, learning, and memory, and is implicated in numerous neurological disorders. During neurogenesis, the immature neuron stage defined by doublecortin (DCX) expression is the most sensitive to regulation by extrinsic factors. However, little is known about the dynamic biology within this critical interval that drives maturation and confers susceptibility to regulatory signals. This study aims to test the hypothesis that DCX-expressing immature neurons progress through developmental stages via activity of specific transcriptional networks. Using single-cell RNA-seq combined with a novel integrative bioinformatics approach, we discovered that individual immature neurons can be classified into distinct developmental subgroups based on characteristic gene expression profiles and subgroup-specific markers. Comparisons between immature and more mature subgroups revealed novel pathways involved in neuronal maturation. Genes enriched in less mature cells shared significant overlap with genes implicated in neurodegenerative diseases, while genes positively associated with neuronal maturation were enriched for autism-related gene sets. Our study thus discovers molecular signatures of individual immature neurons and unveils potential novel targets for therapeutic approaches to treat neurodevelopmental and neurological diseases. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  4. Transcriptional profiling at whole population and single cell levels reveals somatosensory neuron molecular diversity

    Science.gov (United States)

    Chiu, Isaac M; Barrett, Lee B; Williams, Erika K; Strochlic, David E; Lee, Seungkyu; Weyer, Andy D; Lou, Shan; Bryman, Gregory S; Roberson, David P; Ghasemlou, Nader; Piccoli, Cara; Ahat, Ezgi; Wang, Victor; Cobos, Enrique J; Stucky, Cheryl L; Ma, Qiufu; Liberles, Stephen D; Woolf, Clifford J

    2014-01-01

    The somatosensory nervous system is critical for the organism's ability to respond to mechanical, thermal, and nociceptive stimuli. Somatosensory neurons are functionally and anatomically diverse but their molecular profiles are not well-defined. Here, we used transcriptional profiling to analyze the detailed molecular signatures of dorsal root ganglion (DRG) sensory neurons. We used two mouse reporter lines and surface IB4 labeling to purify three major non-overlapping classes of neurons: 1) IB4+SNS-Cre/TdTomato+, 2) IB4−SNS-Cre/TdTomato+, and 3) Parv-Cre/TdTomato+ cells, encompassing the majority of nociceptive, pruriceptive, and proprioceptive neurons. These neurons displayed distinct expression patterns of ion channels, transcription factors, and GPCRs. Highly parallel qRT-PCR analysis of 334 single neurons selected by membership of the three populations demonstrated further diversity, with unbiased clustering analysis identifying six distinct subgroups. These data significantly increase our knowledge of the molecular identities of known DRG populations and uncover potentially novel subsets, revealing the complexity and diversity of those neurons underlying somatosensation. DOI: http://dx.doi.org/10.7554/eLife.04660.001 PMID:25525749

  5. Stochastic biomathematical models with applications to neuronal modeling

    CERN Document Server

    Batzel, Jerry; Ditlevsen, Susanne

    2013-01-01

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

  6. 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.

  7. 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.

  8. 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.

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

    Science.gov (United States)

    Postnova, Svetlana; Peters, Achim; Braun, Hans

    2008-03-01

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

  10. 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.

  11. Massively Parallel Single Nucleus Transcriptional Profiling Defines Spinal Cord Neurons and Their Activity during Behavior

    Directory of Open Access Journals (Sweden)

    Anupama Sathyamurthy

    2018-02-01

    Full Text Available To understand the cellular basis of behavior, it is necessary to know the cell types that exist in the nervous system and their contributions to function. Spinal networks are essential for sensory processing and motor behavior and provide a powerful system for identifying the cellular correlates of behavior. Here, we used massively parallel single nucleus RNA sequencing (snRNA-seq to create an atlas of the adult mouse lumbar spinal cord. We identified and molecularly characterized 43 neuronal populations. Next, we leveraged the snRNA-seq approach to provide unbiased identification of neuronal populations that were active following a sensory and a motor behavior, using a transcriptional signature of neuronal activity. This approach can be used in the future to link single nucleus gene expression data with dynamic biological responses to behavior, injury, and disease.

  12. Massively Parallel Single Nucleus Transcriptional Profiling Defines Spinal Cord Neurons and Their Activity during Behavior.

    Science.gov (United States)

    Sathyamurthy, Anupama; Johnson, Kory R; Matson, Kaya J E; Dobrott, Courtney I; Li, Li; Ryba, Anna R; Bergman, Tzipporah B; Kelly, Michael C; Kelley, Matthew W; Levine, Ariel J

    2018-02-20

    To understand the cellular basis of behavior, it is necessary to know the cell types that exist in the nervous system and their contributions to function. Spinal networks are essential for sensory processing and motor behavior and provide a powerful system for identifying the cellular correlates of behavior. Here, we used massively parallel single nucleus RNA sequencing (snRNA-seq) to create an atlas of the adult mouse lumbar spinal cord. We identified and molecularly characterized 43 neuronal populations. Next, we leveraged the snRNA-seq approach to provide unbiased identification of neuronal populations that were active following a sensory and a motor behavior, using a transcriptional signature of neuronal activity. This approach can be used in the future to link single nucleus gene expression data with dynamic biological responses to behavior, injury, and disease. Published by Elsevier Inc.

  13. Single photon emission computed tomography in motor neuron disease with dementia

    Energy Technology Data Exchange (ETDEWEB)

    Sawada, H.; Udaka, F.; Kishi, Y.; Seriu, N.; Ohtani, S.; Abe, K.; Mezaki, T.; Kameyama, M.; Honda, M.; Tomonobu, M.

    1988-12-01

    Single photon emission computed tomography with (123 I) isopropylamphetamine was carried out on a patient with motor neutron disease with dementia. (123 I) uptake was decreased in the frontal lobes. This would reflect the histopathological findings such as neuronal loss and gliosis in the frontal lobes.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  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. Energetics based spike generation of a single neuron: simulation results and analysis

    Directory of Open Access Journals (Sweden)

    Nagarajan eVenkateswaran

    2012-02-01

    Full Text Available Existing current based models that capture spike activity, though useful in studying information processing capabilities of neurons, fail to throw light on their internal functioning. It is imperative to develop a model that captures the spike train of a neuron as a function of its intra cellular parameters for non-invasive diagnosis of diseased neurons. This is the first ever article to present such an integrated model that quantifies the inter-dependency between spike activity and intra cellular energetics. The generated spike trains from our integrated model will throw greater light on the intra-cellular energetics than existing current models. Now, an abnormality in the spike of a diseased neuron can be linked and hence effectively analyzed at the energetics level. The spectral analysis of the generated spike trains in a time-frequency domain will help identify abnormalities in the internals of a neuron. As a case study, the parameters of our model are tuned for Alzheimer disease and its resultant spike trains are studied and presented.

  20. 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.

  1. Single-molecule folding mechanism of an EF-hand neuronal calcium sensor

    DEFF Research Database (Denmark)

    Heiðarsson, Pétur Orri; Otazo, Mariela R.; Bellucci, Luca

    2013-01-01

    EF-hand calcium sensors respond structurally to changes in intracellular Ca2+ concentration, triggering diverse cellular responses and resulting in broad interactomes. Despite impressive advances in decoding their structure-function relationships, the folding mechanism of neuronal calcium sensors...... is still elusive. We used single-molecule optical tweezers to study the folding mechanism of the human neuronal calcium sensor 1 (NCS1). Two intermediate structures induced by Ca2+ binding to the EF-hands were observed during refolding. The complete folding of the C domain is obligatory for the folding...

  2. Synergistic combinations of five single drugs from Centella asiatica for neuronal differentiation.

    Science.gov (United States)

    Lin, Jinjin; Jiang, Hui; Ding, Xianting

    2017-01-01

    To identify alternatives of nerve growth factor, which could promote NF68 protein expression and contribute toward neuronal differentiation, five compounds namely: asiatic acid, madecassic, madecassoside, quercetin, and isoquercetin, obtained from Centella asiatica, were examined for their neuronal differentiation effects on PC12 cells. C. asiatica has been applied as an effective herbal medicine for the treatment of various diseases, including depression. According to a statistical design of experiments, both single compound and compound combinations were evaluated. A further statistical analysis indicated quantitative interactions between these five single compounds and led to the identification of the optimal drug combinations. Asiatic acid and madecassic appeared to show profound synergistic effects on neurofilaments expression in vitro. The optimized drug combinations were significantly more potent than single drugs and further investigation suggested that the optimal drug combination could be an analogue of nerve growth factor and could represent a potential treatment for neurodegenerative diseases.

  3. Study of GABAergic extra-synaptic tonic inhibition in single neurons and neural populations by traversing neural scales: application to propofol-induced anaesthesia.

    Science.gov (United States)

    Hutt, Axel; Buhry, Laure

    2014-12-01

    Anaesthetic agents are known to affect extra-synaptic GABAergic receptors, which induce tonic inhibitory currents. Since these receptors are very sensitive to small concentrations of agents, they are supposed to play an important role in the underlying neural mechanism of general anaesthesia. Moreover anaesthetic agents modulate the encephalographic activity (EEG) of subjects and hence show an effect on neural populations. To understand better the tonic inhibition effect in single neurons on neural populations and hence how it affects the EEG, the work considers single neurons and neural populations in a steady-state and studies numerically and analytically the modulation of their firing rate and nonlinear gain with respect to different levels of tonic inhibition. We consider populations of both type-I (Leaky Integrate-and-Fire model) and type-II (Morris-Lecar model) neurons. To bridge the single neuron description to the population description analytically, a recently proposed statistical approach is employed which allows to derive new analytical expressions for the population firing rate for type-I neurons. In addition, the work shows the derivation of a novel transfer function for type-I neurons as considered in neural mass models and studies briefly the interaction of synaptic and extra-synaptic inhibition. We reveal a strong subtractive and divisive effect of tonic inhibition in type-I neurons, i.e. a shift of the firing rate to higher excitation levels accompanied by a change of the nonlinear gain. Tonic inhibition shortens the excitation window of type-II neurons and their populations while maintaining the nonlinear gain. The gained results are interpreted in the context of recent experimental findings under propofol-induced anaesthesia.

  4. G gene-deficient single-round rabies viruses for neuronal circuit analysis.

    Science.gov (United States)

    Ghanem, Alexander; Conzelmann, Karl-Klaus

    2016-05-02

    Rhabdoviruses like the neurotropic rabies virus are fully amenable to pseudotyping with homologous and heterologous membrane proteins, which is being harnessed for the study of viral envelope proteins, viral retargeting, or immunization purposes. Particularly, pseudotyped delta G rabies viruses are emerging as safe and superb tools for mapping direct synaptic connections and analyzing neuronal circuits in the central and peripheral nervous system, which is a fundamental pillar of modern neuroscience. Such retrograde rabies mono-transsynaptic tracers in combination with optogenetics and modern in vivo imaging methods are opening entirely new avenues of investigation in neuroscience and help in answering major outstanding questions of connectivity and function of the nervous system. Here, we provide a brief overview on the biology and life cycle of rabies virus with emphasis on neuronal infection via axon ends, transport, and transsynaptic transmission of the virus. Pseudotyping of single-round, G-deleted virus with foreign glycoproteins allows to determine tropism and entry route, resulting in either retro- or anterograde labeling of neurons. Pseudotyping in vitro also allows specific targeting of cells that serve as starter cells for transsynaptic tracing, and pseudotyping in situ for a single (mono-transsynaptic) step of transmission to presynaptic neurons. We describe principle and experimental variations for defining "starter" cells for mono-transsynaptic tracing with ΔG rabies virus and outline open questions and limitations of the approach. Copyright © 2015 Elsevier B.V. All rights reserved.

  5. Audio-vocal interaction in single neurons of the monkey ventrolateral prefrontal cortex.

    Science.gov (United States)

    Hage, Steffen R; Nieder, Andreas

    2015-05-06

    Complex audio-vocal integration systems depend on a strong interconnection between the auditory and the vocal motor system. To gain cognitive control over audio-vocal interaction during vocal motor control, the PFC needs to be involved. Neurons in the ventrolateral PFC (VLPFC) have been shown to separately encode the sensory perceptions and motor production of vocalizations. It is unknown, however, whether single neurons in the PFC reflect audio-vocal interactions. We therefore recorded single-unit activity in the VLPFC of rhesus monkeys (Macaca mulatta) while they produced vocalizations on command or passively listened to monkey calls. We found that 12% of randomly selected neurons in VLPFC modulated their discharge rate in response to acoustic stimulation with species-specific calls. Almost three-fourths of these auditory neurons showed an additional modulation of their discharge rates either before and/or during the monkeys' motor production of vocalization. Based on these audio-vocal interactions, the VLPFC might be well positioned to combine higher order auditory processing with cognitive control of the vocal motor output. Such audio-vocal integration processes in the VLPFC might constitute a precursor for the evolution of complex learned audio-vocal integration systems, ultimately giving rise to human speech. Copyright © 2015 the authors 0270-6474/15/357030-11$15.00/0.

  6. Somatosensory neuron types identified by high-coverage single-cell RNA-sequencing and functional heterogeneity

    Science.gov (United States)

    Li, Chang-Lin; Li, Kai-Cheng; Wu, Dan; Chen, Yan; Luo, Hao; Zhao, Jing-Rong; Wang, Sa-Shuang; Sun, Ming-Ming; Lu, Ying-Jin; Zhong, Yan-Qing; Hu, Xu-Ye; Hou, Rui; Zhou, Bei-Bei; Bao, Lan; Xiao, Hua-Sheng; Zhang, Xu

    2016-01-01

    Sensory neurons are distinguished by distinct signaling networks and receptive characteristics. Thus, sensory neuron types can be defined by linking transcriptome-based neuron typing with the sensory phenotypes. Here we classify somatosensory neurons of the mouse dorsal root ganglion (DRG) by high-coverage single-cell RNA-sequencing (10 950 ± 1 218 genes per neuron) and neuron size-based hierarchical clustering. Moreover, single DRG neurons responding to cutaneous stimuli are recorded using an in vivo whole-cell patch clamp technique and classified by neuron-type genetic markers. Small diameter DRG neurons are classified into one type of low-threshold mechanoreceptor and five types of mechanoheat nociceptors (MHNs). Each of the MHN types is further categorized into two subtypes. Large DRG neurons are categorized into four types, including neurexophilin 1-expressing MHNs and mechanical nociceptors (MNs) expressing BAI1-associated protein 2-like 1 (Baiap2l1). Mechanoreceptors expressing trafficking protein particle complex 3-like and Baiap2l1-marked MNs are subdivided into two subtypes each. These results provide a new system for cataloging somatosensory neurons and their transcriptome databases. PMID:26691752

  7. Single Neurons in the Avian Auditory Cortex Encode Individual Identity and Propagation Distance in Naturally Degraded Communication Calls.

    Science.gov (United States)

    Mouterde, Solveig C; Elie, Julie E; Mathevon, Nicolas; Theunissen, Frédéric E

    2017-03-29

    One of the most complex tasks performed by sensory systems is "scene analysis": the interpretation of complex signals as behaviorally relevant objects. The study of this problem, universal to species and sensory modalities, is particularly challenging in audition, where sounds from various sources and localizations, degraded by propagation through the environment, sum to form a single acoustical signal. Here we investigated in a songbird model, the zebra finch, the neural substrate for ranging and identifying a single source. We relied on ecologically and behaviorally relevant stimuli, contact calls, to investigate the neural discrimination of individual vocal signature as well as sound source distance when calls have been degraded through propagation in a natural environment. Performing electrophysiological recordings in anesthetized birds, we found neurons in the auditory forebrain that discriminate individual vocal signatures despite long-range degradation, as well as neurons discriminating propagation distance, with varying degrees of multiplexing between both information types. Moreover, the neural discrimination performance of individual identity was not affected by propagation-induced degradation beyond what was induced by the decreased intensity. For the first time, neurons with distance-invariant identity discrimination properties as well as distance-discriminant neurons are revealed in the avian auditory cortex. Because these neurons were recorded in animals that had prior experience neither with the vocalizers of the stimuli nor with long-range propagation of calls, we suggest that this neural population is part of a general-purpose system for vocalizer discrimination and ranging. SIGNIFICANCE STATEMENT Understanding how the brain makes sense of the multitude of stimuli that it continually receives in natural conditions is a challenge for scientists. Here we provide a new understanding of how the auditory system extracts behaviorally relevant information

  8. 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.

  9. 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

  10. Individual mediodorsal thalamic neurons project to multiple areas of the rat prefrontal cortex: A single neuron-tracing study using virus vectors.

    Science.gov (United States)

    Kuramoto, Eriko; Pan, Shixiu; Furuta, Takahiro; Tanaka, Yasuhiro R; Iwai, Haruki; Yamanaka, Atsushi; Ohno, Sachi; Kaneko, Takeshi; Goto, Tetsuya; Hioki, Hiroyuki

    2017-01-01

    The prefrontal cortex has an important role in a variety of cognitive and executive processes, and is generally defined by its reciprocal connections with the mediodorsal thalamic nucleus (MD). The rat MD is mainly subdivided into three segments, the medial (MDm), central (MDc), and lateral (MDl) divisions, on the basis of the cytoarchitecture and chemoarchitecture. The MD segments are known to topographically project to multiple prefrontal areas at the population level: the MDm mainly to the prelimbic, infralimbic, and agranular insular areas; the MDc to the orbital and agranular insular areas; and the MDl to the prelimbic and anterior cingulate areas. However, it is unknown whether individual MD neurons project to single or multiple prefrontal cortical areas. In the present study, we visualized individual MD neurons with Sindbis virus vectors, and reconstructed whole structures of MD neurons. While the main cortical projection targets of MDm, MDc, and MDl neurons were generally consistent with those of previous results, it was found that individual MD neurons sent their axon fibers to multiple prefrontal areas, and displayed various projection patterns in the target areas. Furthermore, the axons of single MD neurons were not homogeneously spread, but were rather distributed to form patchy axon arbors approximately 1 mm in diameter. The multiple-area projections and patchy axon arbors of single MD neurons might be able to coactivate cortical neuron groups in distant prefrontal areas simultaneously. Furthermore, considerable heterogeneity of the projection patterns is likely, to recruit the different sets of cortical neurons, and thus contributes to a variety of prefrontal functions. J. Comp. Neurol. 525:166-185, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  11. Spike Train SIMilarity Space (SSIMS): a frame-work for single neuron and ensemble data analysis

    Science.gov (United States)

    Vargas-Irwin, Carlos E.; Brandman, David M.; Zimmermann, Jonas B.; Donoghue, John P.; Black, Michael J.

    2014-01-01

    Increased emphasis on circuit level activity in the brain makes it necessary to have methods to visualize and evaluate large scale ensemble activity, beyond that revealed by raster-histograms or pairwise correlations. We present a method to evaluate the relative similarity of neural spiking patterns by combining spike train distance metrics with dimensionality reduction. Spike train distance metrics provide an estimate of similarity between activity patterns at multiple temporal resolutions. Vectors of pair-wise distances are used to represent the intrinsic relationships between multiple activity patterns at the level of single units or neuronal ensembles. Dimensionality reduction is then used to project the data into concise representations suitable for clustering analysis as well as exploratory visualization. Algorithm performance and robustness are evaluated using multielectrode ensemble activity data recorded in behaving primates. We demonstrate how Spike train SIMilarity Space (SSIMS) analysis captures the relationship between goal directions for an 8-directional reaching task and successfully segregates grasp types in a 3D grasping task in the absence of kinematic information. The algorithm enables exploration of virtually any type of neural spiking (time series) data, providing similarity-based clustering of neural activity states with minimal assumptions about potential information encoding models. PMID:25380335

  12. Effects of dynamic synapses on noise-delayed response latency of a single neuron

    Science.gov (United States)

    Uzuntarla, M.; Ozer, M.; Ileri, U.; Calim, A.; Torres, J. J.

    2015-12-01

    The noise-delayed decay (NDD) phenomenon emerges when the first-spike latency of a periodically forced stochastic neuron exhibits a maximum for a particular range of noise intensity. Here, we investigate the latency response dynamics of a single Hodgkin-Huxley neuron that is subject to both a suprathreshold periodic stimulus and a background activity arriving through dynamic synapses. We study the first-spike latency response as a function of the presynaptic firing rate f . This constitutes a more realistic scenario than previous works, since f provides a suitable biophysically realistic parameter to control the level of activity in actual neural systems. We first report on the emergence of classical NDD behavior as a function of f for the limit of static synapses. Second, we show that when short-term depression and facilitation mechanisms are included at the synapses, different NDD features can be found due to their modulatory effect on synaptic current fluctuations. For example, an intriguing double NDD (DNDD) behavior occurs for different sets of relevant synaptic parameters. Moreover, depending on the balance between synaptic depression and synaptic facilitation, single NDD or DNDD can prevail, in such a way that synaptic facilitation favors the emergence of DNDD whereas synaptic depression favors the existence of single NDD. Here we report the existence of the DNDD effect in the response latency dynamics of a neuron.

  13. 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.

  14. Comprehensive Identification and Spatial Mapping of Habenular Neuronal Types Using Single-Cell RNA-Seq.

    Science.gov (United States)

    Pandey, Shristi; Shekhar, Karthik; Regev, Aviv; Schier, Alexander F

    2018-04-02

    The identification of cell types and marker genes is critical for dissecting neural development and function, but the size and complexity of the brain has hindered the comprehensive discovery of cell types. We combined single-cell RNA-seq (scRNA-seq) with anatomical brain registration to create a comprehensive map of the zebrafish habenula, a conserved forebrain hub involved in pain processing and learning. Single-cell transcriptomes of ∼13,000 habenular cells with 4× cellular coverage identified 18 neuronal types and dozens of marker genes. Registration of marker genes onto a reference atlas created a resource for anatomical and functional studies and enabled the mapping of active neurons onto neuronal types following aversive stimuli. Strikingly, despite brain growth and functional maturation, cell types were retained between the larval and adult habenula. This study provides a gene expression atlas to dissect habenular development and function and offers a general framework for the comprehensive characterization of other brain regions. Copyright © 2018 Elsevier Ltd. All rights reserved.

  15. 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

  16. Neuronal modelling of baroreflex response to orthostatic stress

    Science.gov (United States)

    Samin, Azfar

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

  17. 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.

  18. 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.

  19. 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

  20. Simultaneous transcranial magnetic stimulation and single-neuron recording in alert non-human primates.

    Science.gov (United States)

    Mueller, Jerel K; Grigsby, Erinn M; Prevosto, Vincent; Petraglia, Frank W; Rao, Hrishikesh; Deng, Zhi-De; Peterchev, Angel V; Sommer, Marc A; Egner, Tobias; Platt, Michael L; Grill, Warren M

    2014-08-01

    Transcranial magnetic stimulation (TMS) is a widely used, noninvasive method for stimulating nervous tissue, yet its mechanisms of effect are poorly understood. Here we report new methods for studying the influence of TMS on single neurons in the brain of alert non-human primates. We designed a TMS coil that focuses its effect near the tip of a recording electrode and recording electronics that enable direct acquisition of neuronal signals at the site of peak stimulus strength minimally perturbed by stimulation artifact in awake monkeys (Macaca mulatta). We recorded action potentials within ∼1 ms after 0.4-ms TMS pulses and observed changes in activity that differed significantly for active stimulation as compared with sham stimulation. This methodology is compatible with standard equipment in primate laboratories, allowing easy implementation. Application of these tools will facilitate the refinement of next generation TMS devices, experiments and treatment protocols.

  1. Simultaneous transcranial magnetic stimulation and single neuron recording in alert non-human primates

    Science.gov (United States)

    Mueller, Jerel K.; Grigsby, Erinn M.; Prevosto, Vincent; Petraglia, Frank W.; Rao, Hrishikesh; Deng, Zhi-De; Peterchev, Angel V.; Sommer, Marc A.; Egner, Tobias; Platt, Michael L.; Grill, Warren M.

    2014-01-01

    Transcranial magnetic stimulation (TMS) is a widely used, noninvasive method for stimulating nervous tissue, yet its mechanisms of effect are poorly understood. Here we report novel methods for studying the influence of TMS on single neurons in the brain of alert non-human primates. We designed a TMS coil that focuses its effect near the tip of a recording electrode and recording electronics that enable direct acquisition of neuronal signals at the site of peak stimulus strength minimally perturbed by stimulation artifact in intact, awake monkeys (Macaca mulatta). We recorded action potentials within ~1 ms after 0.4 ms TMS pulses and observed changes in activity that differed significantly for active stimulation as compared to sham stimulation. The methodology is compatible with standard equipment in primate laboratories, allowing for easy implementation. Application of these new tools will facilitate the refinement of next generation TMS devices, experiments, and treatment protocols. PMID:24974797

  2. Single-Cell Transcriptional Analysis Reveals Novel Neuronal Phenotypes and Interaction Networks Involved in the Central Circadian Clock.

    Science.gov (United States)

    Park, James; Zhu, Haisun; O'Sullivan, Sean; Ogunnaike, Babatunde A; Weaver, David R; Schwaber, James S; Vadigepalli, Rajanikanth

    2016-01-01

    Single-cell heterogeneity confounds efforts to understand how a population of cells organizes into cellular networks that underlie tissue-level function. This complexity is prominent in the mammalian suprachiasmatic nucleus (SCN). Here, individual neurons exhibit a remarkable amount of asynchronous behavior and transcriptional heterogeneity. However, SCN neurons are able to generate precisely coordinated synaptic and molecular outputs that synchronize the body to a common circadian cycle by organizing into cellular networks. To understand this emergent cellular network property, it is important to reconcile single-neuron heterogeneity with network organization. In light of recent studies suggesting that transcriptionally heterogeneous cells organize into distinct cellular phenotypes, we characterized the transcriptional, spatial, and functional organization of 352 SCN neurons from mice experiencing phase-shifts in their circadian cycle. Using the community structure detection method and multivariate analytical techniques, we identified previously undescribed neuronal phenotypes that are likely to participate in regulatory networks with known SCN cell types. Based on the newly discovered neuronal phenotypes, we developed a data-driven neuronal network structure in which multiple cell types interact through known synaptic and paracrine signaling mechanisms. These results provide a basis from which to interpret the functional variability of SCN neurons and describe methodologies toward understanding how a population of heterogeneous single cells organizes into cellular networks that underlie tissue-level function.

  3. Single-cell Transcriptional Analysis Reveals Novel Neuronal Phenotypes and Interaction Networks involved In the Central Circadian Clock

    Directory of Open Access Journals (Sweden)

    James Park

    2016-10-01

    Full Text Available Single-cell heterogeneity confounds efforts to understand how a population of cells organizes into cellular networks that underlie tissue-level function. This complexity is prominent in the mammalian suprachiasmatic nucleus (SCN. Here, individual neurons exhibit a remarkable amount of asynchronous behavior and transcriptional heterogeneity. However, SCN neurons are able to generate precisely coordinated synaptic and molecular outputs that synchronize the body to a common circadian cycle by organizing into cellular networks. To understand this emergent cellular network property, it is important to reconcile single-neuron heterogeneity with network organization. In light of recent studies suggesting that transcriptionally heterogeneous cells organize into distinct cellular phenotypes, we characterized the transcriptional, spatial, and functional organization of 352 SCN neurons from mice experiencing phase-shifts in their circadian cycle. Using the community structure detection method and multivariate analytical techniques, we identified previously undescribed neuronal phenotypes that are likely to participate in regulatory networks with known SCN cell types. Based on the newly discovered neuronal phenotypes, we developed a data-driven neuronal network structure in which multiple cell types interact through known synaptic and paracrine signaling mechanisms. These results provide a basis from which to interpret the functional variability of SCN neurons and describe methodologies towards understanding how a population of heterogeneous single cells organizes into cellular networks that underlie tissue-level function.

  4. Two-photon compatibility and single-voxel, single-trial detection of subthreshold neuronal activity by a two-component optical voltage sensor.

    Science.gov (United States)

    Fink, Ann E; Bender, Kevin J; Trussell, Laurence O; Otis, Thomas S; DiGregorio, David A

    2012-01-01

    Minimally invasive measurements of neuronal activity are essential for understanding how signal processing is performed by neuronal networks. While optical strategies for making such measurements hold great promise, optical sensors generally lack the speed and sensitivity necessary to record neuronal activity on a single-trial, single-neuron basis. Here we present additional biophysical characterization and practical improvements of a two-component optical voltage sensor (2cVoS), comprised of the neuronal tracer dye, DiO, and dipicrylamine (DiO/DPA). Using laser spot illumination we demonstrate that membrane potential-dependent fluorescence changes can be obtained in a wide variety of cell types within brain slices. We show a correlation between membrane labeling and the sensitivity of the magnitude of fluorescence signal, such that neurons with the brightest membrane labeling yield the largest ΔF/F values per action potential (AP; ∼40%). By substituting a blue-shifted donor for DiO we confirm that DiO/DPA works, at least in part, via a Förster resonance energy transfer (FRET) mechanism. We also describe a straightforward iontophoretic method for labeling multiple neurons with DiO and show that DiO/DPA is compatible with two-photon (2P) imaging. Finally, exploiting the high sensitivity of DiO/DPA, we demonstrate AP-induced fluorescence transients (fAPs) recorded from single spines of hippocampal pyramidal neurons and single-trial measurements of subthreshold synaptic inputs to granule cell dendrites. Our findings suggest that the 2cVoS, DiO/DPA, enables optical measurements of trial-to-trial voltage fluctuations with very high spatial and temporal resolution, properties well suited for monitoring electrical signals from multiple neurons within intact neuronal networks.

  5. Two-photon compatibility and single-voxel, single-trial detection of subthreshold neuronal activity by a two-component optical voltage sensor.

    Directory of Open Access Journals (Sweden)

    Ann E Fink

    Full Text Available Minimally invasive measurements of neuronal activity are essential for understanding how signal processing is performed by neuronal networks. While optical strategies for making such measurements hold great promise, optical sensors generally lack the speed and sensitivity necessary to record neuronal activity on a single-trial, single-neuron basis. Here we present additional biophysical characterization and practical improvements of a two-component optical voltage sensor (2cVoS, comprised of the neuronal tracer dye, DiO, and dipicrylamine (DiO/DPA. Using laser spot illumination we demonstrate that membrane potential-dependent fluorescence changes can be obtained in a wide variety of cell types within brain slices. We show a correlation between membrane labeling and the sensitivity of the magnitude of fluorescence signal, such that neurons with the brightest membrane labeling yield the largest ΔF/F values per action potential (AP; ∼40%. By substituting a blue-shifted donor for DiO we confirm that DiO/DPA works, at least in part, via a Förster resonance energy transfer (FRET mechanism. We also describe a straightforward iontophoretic method for labeling multiple neurons with DiO and show that DiO/DPA is compatible with two-photon (2P imaging. Finally, exploiting the high sensitivity of DiO/DPA, we demonstrate AP-induced fluorescence transients (fAPs recorded from single spines of hippocampal pyramidal neurons and single-trial measurements of subthreshold synaptic inputs to granule cell dendrites. Our findings suggest that the 2cVoS, DiO/DPA, enables optical measurements of trial-to-trial voltage fluctuations with very high spatial and temporal resolution, properties well suited for monitoring electrical signals from multiple neurons within intact neuronal networks.

  6. Retrograde labeling of single neurons in conjunction with MALDI high-energy collision-induced dissociation MS/MS analysis for peptide profiling and structural characterization

    NARCIS (Netherlands)

    El Filali, Z.; Hornshaw, M.; Smit, A.B.; Li, K.W.

    2003-01-01

    To reveal the peptide contents of the visually nonidentifiable neurons from a neuronal circuit of interest, we combined retrograde labeling of neurons with mass spectrometric single cell analysis. We used the neuronal circuit involved in the copulation behavior of a freshwater snail, Lymnaea

  7. 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.

  8. 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

  9. 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...

  10. Operant conditioning of synaptic and spiking activity patterns in single hippocampal neurons.

    Science.gov (United States)

    Ishikawa, Daisuke; Matsumoto, Nobuyoshi; Sakaguchi, Tetsuya; Matsuki, Norio; Ikegaya, Yuji

    2014-04-02

    Learning is a process of plastic adaptation through which a neural circuit generates a more preferable outcome; however, at a microscopic level, little is known about how synaptic activity is patterned into a desired configuration. Here, we report that animals can generate a specific form of synaptic activity in a given neuron in the hippocampus. In awake, head-restricted mice, we applied electrical stimulation to the lateral hypothalamus, a reward-associated brain region, when whole-cell patch-clamped CA1 neurons exhibited spontaneous synaptic activity that met preset criteria. Within 15 min, the mice learned to generate frequently the excitatory synaptic input pattern that satisfied the criteria. This reinforcement learning of synaptic activity was not observed for inhibitory input patterns. When a burst unit activity pattern was conditioned in paired and nonpaired paradigms, the frequency of burst-spiking events increased and decreased, respectively. The burst reinforcement occurred in the conditioned neuron but not in other adjacent neurons; however, ripple field oscillations were concomitantly reinforced. Neural conditioning depended on activation of NMDA receptors and dopamine D1 receptors. Acutely stressed mice and depression model mice that were subjected to forced swimming failed to exhibit the neural conditioning. This learning deficit was rescued by repetitive treatment with fluoxetine, an antidepressant. Therefore, internally motivated animals are capable of routing an ongoing action potential series into a specific neural pathway of the hippocampal network.

  11. 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

  12. 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...

  13. 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.

  14. Single-photon emission computed tomographic findings and motor neuron signs in amyotrophic lateral sclerosis

    International Nuclear Information System (INIS)

    Terao, Shin-ichi; Sobue, Gen; Higashi, Naoki; Takahashi, Masahiko; Suga, Hidemichi; Mitsuma, Terunori

    1995-01-01

    123 I-amphetamine-single photon emission computed tomography (SPECT) was performed on 16 patients with amyotrophic lateral sclerosis (ALS) to investigate the correlation between regional cerebral blood flow (rCBF) and upper motor neuron signs. Significant decreased blood flow less than 2 SDs below the mean of controls was observed in the frontal lobe in 4 patients (25%) and in the frontoparietal lobe including the cortical motor area in 4 patients, respectively. The severity of extermity muscular weakness was significantly correlate with decrease in blood flow through the frontal lobe (p<0.05) and through the frontoparietal lobe (p<0.001). A significant correlation was also noted to exist between the severity of bulbar paralysis and decrease in blood flow through the frontoparietal lobe. No correlation, however, was observed between rCBF and severity of spasticity, presence or absence of Babinski's sign and the duration of illness. Although muscular weakness in the limbs and bulbar paralysis are not pure upper motor neuron signs, the observed reduction in blood flow through the frontal or frontoparietal lobes appears to reflect extensive progression of functional or organic lesions of cortical neurons including the motor area. (author)

  15. Diversity of bilateral synaptic assemblies for binaural computation in midbrain single neurons.

    Science.gov (United States)

    He, Na; Kong, Lingzhi; Lin, Tao; Wang, Shaohui; Liu, Xiuping; Qi, Jiyao; Yan, Jun

    2017-11-01

    Binaural hearing confers many beneficial functions but our understanding of its underlying neural substrates is limited. This study examines the bilateral synaptic assemblies and binaural computation (or integration) in the central nucleus of the inferior colliculus (ICc) of the auditory midbrain, a key convergent center. Using in-vivo whole-cell patch-clamp, the excitatory and inhibitory postsynaptic potentials (EPSPs/IPSPs) of single ICc neurons to contralateral, ipsilateral and bilateral stimulation were recorded. According to the contralateral and ipsilateral EPSP/IPSP, 7 types of bilateral synaptic assemblies were identified. These include EPSP-EPSP (EE), E-IPSP (EI), E-no response (EO), II, IE, IO and complex-mode (CM) neurons. The CM neurons showed frequency- and/or amplitude-dependent EPSPs/IPSPs to contralateral or ipsilateral stimulation. Bilateral stimulation induced EPSPs/IPSPs that could be larger than (facilitation), similar to (ineffectiveness) or smaller than (suppression) those induced by contralateral stimulation. Our findings have allowed our group to characterize novel neural circuitry for binaural computation in the midbrain. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Overexpression of cypin alters dendrite morphology, single neuron activity, and network properties via distinct mechanisms

    Science.gov (United States)

    Rodríguez, Ana R.; O'Neill, Kate M.; Swiatkowski, Przemyslaw; Patel, Mihir V.; Firestein, Bonnie L.

    2018-02-01

    Objective. This study investigates the effect that overexpression of cytosolic PSD-95 interactor (cypin), a regulator of synaptic PSD-95 protein localization and a core regulator of dendrite branching, exerts on the electrical activity of rat hippocampal neurons and networks. Approach. We cultured rat hippocampal neurons and used lipid-mediated transfection and lentiviral gene transfer to achieve high levels of cypin or cypin mutant (cypinΔPDZ PSD-95 non-binding) expression cellularly and network-wide, respectively. Main results. Our analysis revealed that although overexpression of cypin and cypinΔPDZ increase dendrite numbers and decrease spine density, cypin and cypinΔPDZ distinctly regulate neuronal activity. At the single cell level, cypin promotes decreases in bursting activity while cypinΔPDZ reduces sEPSC frequency and further decreases bursting compared to cypin. At the network level, by using the Fano factor as a measure of spike count variability, cypin overexpression results in an increase in variability of spike count, and this effect is abolished when cypin cannot bind PSD-95. This variability is also dependent on baseline activity levels and on mean spike rate over time. Finally, our spike sorting data show that overexpression of cypin results in a more complex distribution of spike waveforms and that binding to PSD-95 is essential for this complexity. Significance. Our data suggest that dendrite morphology does not play a major role in cypin action on electrical activity.

  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. 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

  19. STDP allows close-to-optimal spatiotemporal spike pattern detection by single coincidence detector neurons.

    Science.gov (United States)

    Masquelier, Timothée

    2017-06-29

    Repeating spatiotemporal spike patterns exist and carry information. How this information is extracted by downstream neurons is unclear. Here we theoretically investigate to what extent a single cell could detect a given spike pattern and what the optimal parameters to do so are, in particular the membrane time constant τ. Using a leaky integrate-and-fire (LIF) neuron with homogeneous Poisson input, we computed this optimum analytically. We found that a relatively small τ (at most a few tens of ms) is usually optimal, even when the pattern is much longer. This is somewhat counter-intuitive as the resulting detector ignores most of the pattern, due to its fast memory decay. Next, we wondered if spike-timing-dependent plasticity (STDP) could enable a neuron to reach the theoretical optimum. We simulated a LIF equipped with additive STDP, and repeatedly exposed it to a given input spike pattern. As in previous studies, the LIF progressively became selective to the repeating pattern with no supervision, even when the pattern was embedded in Poisson activity. Here we show that, using certain STDP parameters, the resulting pattern detector is optimal. These mechanisms may explain how humans learn repeating sensory sequences. Long sequences could be recognized thanks to coincidence detectors working at a much shorter timescale. This is consistent with the fact that recognition is still possible if a sound sequence is compressed, played backward, or scrambled using 10-ms bins. Coincidence detection is a simple yet powerful mechanism, which could be the main function of neurons in the brain. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  20. A single GABAergic neuron mediates feedback of odor-evoked signals in the mushroom body of larval Drosophila

    Directory of Open Access Journals (Sweden)

    Liria Monica Masuda-Nakagawa

    2014-04-01

    Full Text Available Inhibition has a central role in defining the selectivity of the responses of higher order neurons to sensory stimuli. However, the circuit mechanisms of regulation of these responses by inhibitory neurons are still unclear. In Drosophila, the mushroom bodies (MBs are necessary for olfactory memory, and by implication for the selectivity of learned responses to specific odors. To understand the circuitry of inhibition in the calyx (the input dendritic region of the MBs, and its relationship with MB excitatory activity, we used the simple anatomy of the Drosophila larval olfactory system to identify any inhibitory inputs that could contribute to the selectivity of MB odor responses. We found that a single neuron accounts for all detectable GABA innervation in the calyx of the MBs, and that this neuron has presynaptic terminals in the calyx and postsynaptic branches in the MB lobes (output axonal area. We call this neuron the larval anterior paired lateral (APL neuron, because of its similarity to the previously described adult APL neuron. Reconstitution of GFP partners (GRASP suggests that the larval APL makes extensive contacts with the MB intrinsic neurons, Kenyon Cells (KCs, but few contacts with incoming projection neurons. Using calcium imaging of neuronal activity in live larvae, we show that the larval APL responds to odors, in a mannner that requires output from KCs. Our data suggest that the larval APL is the sole GABAergic neuron that innervates the MB input region and carries inhibitory feedback from the MB output region, consistent with a role in modulating the olfactory selectivity of MB neurons.

  1. 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.

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

    Science.gov (United States)

    Ebner, Marc; Hameroff, Stuart

    2011-01-01

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

  3. 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

  4. 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.

  5. Elucidating distinct ion channel populations on the surface of hippocampal neurons via single-particle tracking recurrence analysis

    Science.gov (United States)

    Sikora, Grzegorz; Wyłomańska, Agnieszka; Gajda, Janusz; Solé, Laura; Akin, Elizabeth J.; Tamkun, Michael M.; Krapf, Diego

    2017-12-01

    Protein and lipid nanodomains are prevalent on the surface of mammalian cells. In particular, it has been recently recognized that ion channels assemble into surface nanoclusters in the soma of cultured neurons. However, the interactions of these molecules with surface nanodomains display a considerable degree of heterogeneity. Here, we investigate this heterogeneity and develop statistical tools based on the recurrence of individual trajectories to identify subpopulations within ion channels in the neuronal surface. We specifically study the dynamics of the K+ channel Kv1.4 and the Na+ channel Nav1.6 on the surface of cultured hippocampal neurons at the single-molecule level. We find that both these molecules are expressed in two different forms with distinct kinetics with regards to surface interactions, emphasizing the complex proteomic landscape of the neuronal surface. Further, the tools presented in this work provide new methods for the analysis of membrane nanodomains, transient confinement, and identification of populations within single-particle trajectories.

  6. 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)

  7. Quantitative analysis of axon bouton distribution of subthalamic nucleus neurons in the rat by single neuron visualization with a viral vector.

    Science.gov (United States)

    Koshimizu, Yoshinori; Fujiyama, Fumino; Nakamura, Kouichi C; Furuta, Takahiro; Kaneko, Takeshi

    2013-06-15

    The subthalamic nucleus (STN) of the basal ganglia plays a key role in motor control, and STN efferents are known to mainly target the external segment of the globus pallidus (GPe), entopeduncular nucleus (Ep), and substantia nigra (SN) with some axon collaterals to the other regions. However, it remains to be clarified how each STN neuron projects axon fibers and collaterals to those target nuclei of the STN. Here we visualized the whole axonal arborization of single STN neurons in the rat brain by using a viral vector expressing membrane-targeted green fluorescent protein, and examined the distribution of axon boutons in those target nuclei. The vast majority (8-9) of 10 reconstructed STN neurons projected to the GPe, SN, caudate-putamen (CPu), and Ep, which received, on average ± SD, 457 ± 425, 400 ± 347, 126 ± 143, and 106 ± 100 axon boutons per STN neuron, respectively. Furthermore, the density of axon boutons in the GPe was highest among these nuclei. Although these target nuclei were divided into calbindin-rich and -poor portions, STN projection showed no exclusive preference for those portions. Since STN neurons mainly projected not only to the GPe, SN, and Ep but also to the CPu, the subthalamostriatal projection might serve as a positive feedback path for the striato-GPe-subthalamic disinhibitory pathway, or work as another route of cortical inputs to the striatum through the corticosubthalamostriatal disynaptic excitatory pathway. Copyright © 2012 Wiley Periodicals, Inc.

  8. A single hidden layer feedforward network with only one neuron in the hidden layer can approximate any univariate function

    OpenAIRE

    Guliyev, Namig; Ismailov, Vugar

    2016-01-01

    The possibility of approximating a continuous function on a compact subset of the real line by a feedforward single hidden layer neural network with a sigmoidal activation function has been studied in many papers. Such networks can approximate an arbitrary continuous function provided that an unlimited number of neurons in a hidden layer is permitted. In this paper, we consider constructive approximation on any finite interval of $\\mathbb{R}$ by neural networks with only one neuron in the hid...

  9. Plasticity of marrow mesenchymal stem cells from human first-trimester fetus: from single-cell clone to neuronal differentiation.

    Science.gov (United States)

    Zhang, Yihua; Shen, Wenzheng; Sun, Bingjie; Lv, Changrong; Dou, Zhongying

    2011-02-01

    Recent results have shown that bone marrow mesenchymal stem cells (BMSCs) from human first-trimester abortus (hfBMSCs) are closer to embryonic stem cells and perform greater telomerase activity and faster propagation than mid- and late-prophase fetal and adult BMSCs. However, no research has been done on the plasticity of hfBMSCs into neuronal cells using single-cell cloned strains without cell contamination. In this study, we isolated five single cells from hfBMSCs and obtained five single-cell cloned strains, and investigated their biological property and neuronal differentiation potential. We found that four of the five strains showed similar expression profile of surface antigen markers to hfBMSCs, and most of them differentiated into neuron-like cells expressing Nestin, Pax6, Sox1, β-III Tubulin, NF-L, and NSE under induction. One strain showed different expression profile of surface antigen markers from the four strains and hfBMSCs, and did not differentiate toward neuronal cells. We demonstrated for the first time that some of single-cell cloned strains from hfBMSCs can differentiate into nerve tissue-like cell clusters under induction in vitro, and that the plasticity of each single-cell cloned strain into neuronal cells is different.

  10. 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

  11. 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.

  12. 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

  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. 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.

  15. Single-neuron diversity generated by Protocadherin-β cluster in mouse central and peripheral nervous systems

    Directory of Open Access Journals (Sweden)

    Keizo eHirano

    2012-08-01

    Full Text Available The generation of complex neural circuits depends on the correct wiring of neurons with diverse individual characteristics. To understand the complexity of the nervous system, the molecular mechanisms for specifying the identity and diversity of individual neurons must be elucidated. The clustered protocadherins (Pcdh in mammals consist of approximately 50 Pcdh genes (Pcdh-α, Pcdh-β, and Pcdh-γ that encode cadherin-family cell surface adhesion proteins. Individual neurons express a random combination of Pcdh-α and Pcdh-γ, whereas the expression patterns for the Pcdh-β genes, 22 one-exon genes in mouse, are not fully understood. Here we show that the Pcdh-β genes are expressed in a 3’-polyadenylated form in mouse brain. In situ hybridization using a pan-Pcdh-β probe against a conserved Pcdh-β sequence showed widespread labeling in the brain, with prominent signals in the olfactory bulb, hippocampus, and cerebellum. In situ hybridization with specific probes for individual Pcdh-β genes showed their expression to be scattered in Purkinje cells from P10 to P150. The scattered expression patterns were confirmed by performing a newly developed single-cell 3’-RACE analysis of Purkinje cells, which clearly demonstrated that the Pcdh-β genes are expressed monoallelically and combinatorially in individual Purkinje cells. Scattered expression patterns of individual Pcdh-β genes were also observed in pyramidal neurons in the hippocampus and cerebral cortex, neurons in the trigeminal and dorsal root ganglion, GABAergic interneurons, and cholinergic neurons. Our results extend previous observations of diversity at the single-neuron level generated by Pcdh expression and suggest that the Pcdh-β cluster genes contribute to specifying the identity and diversity of individual neurons.

  16. 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...

  17. 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.

  18. A Computational Model Based on Multi-Regional Calcium Imaging Represents the Spatio-Temporal Dynamics in a Caenorhabditis elegans Sensory Neuron.

    Directory of Open Access Journals (Sweden)

    Masahiro Kuramochi

    Full Text Available Due to the huge number of neuronal cells in the brain and their complex circuit formation, computer simulation of neuronal activity is indispensable to understanding whole brain dynamics. Recently, various computational models have been developed based on whole-brain calcium imaging data. However, these analyses monitor only the activity of neuronal cell bodies and treat the cells as point unit. This point-neuron model is inexpensive in computational costs, but the model is unrealistically simplistic at representing intact neural activities in the brain. Here, we describe a novel three-unit Ordinary Differential Equation (ODE model based on the neuronal responses derived from a Caenorhabditis elegans salt-sensing neuron. We recorded calcium responses in three regions of the ASER neuron using a simple downstep of NaCl concentration. Our simple ODE model generated from a single recording can adequately reproduce and predict the temporal responses of each part of the neuron to various types of NaCl concentration changes. Our strategy which combines a simple recording data and an ODE mathematical model may be extended to realistically understand whole brain dynamics by computational simulation.

  19. 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

  20. 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.

  1. 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.

  2. Morphological Characteristics of Motor Neurons Do Not Determine Their Relative Susceptibility to Degeneration in a Mouse Model of Severe Spinal Muscular Atrophy

    Science.gov (United States)

    Mutsaers, Chantal A.; Thomson, Derek; Hamilton, Gillian; Parson, Simon H.; Gillingwater, Thomas H.

    2012-01-01

    Spinal muscular atrophy (SMA) is a leading genetic cause of infant mortality, resulting primarily from the degeneration and loss of lower motor neurons. Studies using mouse models of SMA have revealed widespread heterogeneity in the susceptibility of individual motor neurons to neurodegeneration, but the underlying reasons remain unclear. Data from related motor neuron diseases, such as amyotrophic lateral sclerosis (ALS), suggest that morphological properties of motor neurons may regulate susceptibility: in ALS larger motor units innervating fast-twitch muscles degenerate first. We therefore set out to determine whether intrinsic morphological characteristics of motor neurons influenced their relative vulnerability to SMA. Motor neuron vulnerability was mapped across 10 muscle groups in SMA mice. Neither the position of the muscle in the body, nor the fibre type of the muscle innervated, influenced susceptibility. Morphological properties of vulnerable and disease-resistant motor neurons were then determined from single motor units reconstructed in Thy.1-YFP-H mice. None of the parameters we investigated in healthy young adult mice – including motor unit size, motor unit arbor length, branching patterns, motor endplate size, developmental pruning and numbers of terminal Schwann cells at neuromuscular junctions - correlated with vulnerability. We conclude that morphological characteristics of motor neurons are not a major determinant of disease-susceptibility in SMA, in stark contrast to related forms of motor neuron disease such as ALS. This suggests that subtle molecular differences between motor neurons, or extrinsic factors arising from other cell types, are more likely to determine relative susceptibility in SMA. PMID:23285108

  3. 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.

  4. 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.

  5. 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...

  6. 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...

  7. Coordinate control of integral reactor based on single neuron PID controller

    International Nuclear Information System (INIS)

    Liu Yan; Xia Hong

    2014-01-01

    As one of the main type of reactors in the future, the development of the integral reactor has attracted worldwide attention. On the basis of understanding the background of the integral reactor, the author will be familiar with and master the power control of reactor and the feedwater flow control of steam generator, and the speed control of turbine (turbine speed control is associated with the turbine load control). According to the expectative program 'reactor power following turbine load' of the reactor, it will make coordinate control of the three and come to a overall control scheme. The author will use the supervisory learning algorithm of Hebb for single neuron PID controller with self-adaptation to study the coordinate control of integral reactor. Compared with conventional PI or PID controller, to a certain extent, it solves the problems that traditional PID controller is not easy to tune real-time parameters and lack of effective control for a number of complex processes and slow-varying parameter systems. It improves the security, reliability, stability and flexibility of control process and achieves effective control of the system. (authors)

  8. Single neuron recordings of bilinguals performing in a continuous recognition memory task.

    Directory of Open Access Journals (Sweden)

    Erika K Hussey

    Full Text Available We report the results of a bilingual continuous recognition memory task during which single- and multi-neuron activity was recorded in human subjects with intracranial microwire implants. Subjects (n = 5 were right-handed Spanish-English bilinguals who were undergoing evaluation prior to surgery for severe epilepsy. Subjects were presented with Spanish and English words and the task was to determine whether any given word had been seen earlier in the testing session, irrespective of the language in which it had appeared. Recordings in the left and right hippocampus revealed notable laterality, whereby both Spanish and English items that had been seen previously in the other language (switch trials triggered increased neural firing in the left hippocampus. Items that had been seen previously in the same language (repeat trials triggered increased neural firings in the right hippocampus. These results are consistent with theories that propose roles of both the left- and right-hemisphere in real-time linguistic processing. Importantly, this experiment presents the first instance of intracranial recordings in bilinguals performing a task with switching demands.

  9. 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

  10. 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

  11. Long-range projection neurons of the mouse ventral tegmental area: a single-cell axon tracing analysis.

    Science.gov (United States)

    Aransay, Ana; Rodríguez-López, Claudia; García-Amado, María; Clascá, Francisco; Prensa, Lucía

    2015-01-01

    Pathways arising from the ventral tegmental area (VTA) release dopamine and other neurotransmitters during the expectation and achievement of reward, and are regarded as central links of the brain networks that create drive, pleasure, and addiction. While the global pattern of VTA projections is well-known, the actual axonal wiring of individual VTA neurons had never been investigated. Here, we labeled and analyzed the axons of 30 VTA single neurons by means of single-cell transfection with the Sindbis-pal-eGFP vector in mice. These observations were complemented with those obtained by labeling the axons of small populations of VTA cells with iontophoretic microdeposits of biotinylated dextran amine. In the single-cell labeling experiments, each entire axonal tree was reconstructed from serial sections, the length of terminal axonal arbors was estimated by stereology, and the dopaminergic phenotype was tested by double-labeling for tyrosine hydroxylase immunofluorescence. We observed two main, markedly different VTA cell morphologies: neurons with a single main axon targeting only forebrain structures (FPN cells), and neurons with multibranched axons targeting both the forebrain and the brainstem (F + BSPN cells). Dopaminergic phenotype was observed in FPN cells. Moreover, four "subtypes" could be distinguished among the FPN cells based on their projection targets: (1) "Mesocorticolimbic" FPN projecting to both neocortex and basal forebrain; (2) "Mesocortical" FPN innervating the neocortex almost exclusively; (3) "Mesolimbic" FPN projecting to the basal forebrain, accumbens and caudateputamen; and (4) "Mesostriatal" FPN targeting only the caudateputamen. While the F + BSPN cells were scattered within VTA, the mesolimbic neurons were abundant in the paranigral nucleus. The observed diversity in wiring architectures is consistent with the notion that different VTA cell subpopulations modulate the activity of specific sets of prosencephalic and brainstem structures.

  12. 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.

  13. A codimension-2 bifurcation controlling endogenous bursting activity and pulse-triggered responses of a neuron model.

    Science.gov (United States)

    Barnett, William H; Cymbalyuk, Gennady S

    2014-01-01

    The dynamics of individual neurons are crucial for producing functional activity in neuronal networks. An open question is how temporal characteristics can be controlled in bursting activity and in transient neuronal responses to synaptic input. Bifurcation theory provides a framework to discover generic mechanisms addressing this question. We present a family of mechanisms organized around a global codimension-2 bifurcation. The cornerstone bifurcation is located at the intersection of the border between bursting and spiking and the border between bursting and silence. These borders correspond to the blue sky catastrophe bifurcation and the saddle-node bifurcation on an invariant circle (SNIC) curves, respectively. The cornerstone bifurcation satisfies the conditions for both the blue sky catastrophe and SNIC. The burst duration and interburst interval increase as the inverse of the square root of the difference between the corresponding bifurcation parameter and its bifurcation value. For a given set of burst duration and interburst interval, one can find the parameter values supporting these temporal characteristics. The cornerstone bifurcation also determines the responses of silent and spiking neurons. In a silent neuron with parameters close to the SNIC, a pulse of current triggers a single burst. In a spiking neuron with parameters close to the blue sky catastrophe, a pulse of current temporarily silences the neuron. These responses are stereotypical: the durations of the transient intervals-the duration of the burst and the duration of latency to spiking-are governed by the inverse-square-root laws. The mechanisms described here could be used to coordinate neuromuscular control in central pattern generators. As proof of principle, we construct small networks that control metachronal-wave motor pattern exhibited in locomotion. This pattern is determined by the phase relations of bursting neurons in a simple central pattern generator modeled by a chain of

  14. ELECTRICITY DEMAND FORECASTING USING A SARIMAMULTIPLICATIVE SINGLE NEURON HYBRID MODEL

    Directory of Open Access Journals (Sweden)

    JUAN DAVID VELÁSQUEZ HENAO

    2013-01-01

    Full Text Available La combinación de modelos SARIMA y redes neuronales son una aproximación común para pronosticar series de tiempo no lineales. Mientras la metodología SARIMA es usada para capturar las componentes lineales en la serie de tiempo, las redes neuronales artifi ciales son aplicadas para pronosticar las no-linealidades remanentes en los residuos del modelo SARIMA. En este artículo, se propone un modelo simple no lineal para el pronóstico de series de tiempo obtenido por la combinación de un modelo SARIMA y una neurona simple multiplicativa que usa las mismas entradas del modelo SARIMA. Para evaluar la capacidad de la nueva aproximación, la demanda mensual de electricidad en el mercado de energía de Colombia es pronosticada y comparada con los modelos SARIMA y la neurona simple multiplicativa.

  15. 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.

  16. 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.

  17. Spontaneous Neuronal Activity in Developing Neocortical Networks: From Single Cells to Large-Scale Interactions.

    Science.gov (United States)

    Luhmann, Heiko J; Sinning, Anne; Yang, Jenq-Wei; Reyes-Puerta, Vicente; Stüttgen, Maik C; Kirischuk, Sergei; Kilb, Werner

    2016-01-01

    Neuronal activity has been shown to be essential for the proper formation of neuronal circuits, affecting developmental processes like neurogenesis, migration, programmed cell death, cellular differentiation, formation of local and long-range axonal connections, synaptic plasticity or myelination. Accordingly, neocortical areas reveal distinct spontaneous and sensory-driven neuronal activity patterns already at early phases of development. At embryonic stages, when immature neurons start to develop voltage-dependent channels, spontaneous activity is highly synchronized within small neuronal networks and governed by electrical synaptic transmission. Subsequently, spontaneous activity patterns become more complex, involve larger networks and propagate over several neocortical areas. The developmental shift from local to large-scale network activity is accompanied by a gradual shift from electrical to chemical synaptic transmission with an initial excitatory action of chloride-gated channels activated by GABA, glycine and taurine. Transient neuronal populations in the subplate (SP) support temporary circuits that play an important role in tuning early neocortical activity and the formation of mature neuronal networks. Thus, early spontaneous activity patterns control the formation of developing networks in sensory cortices, and disturbances of these activity patterns may lead to long-lasting neuronal deficits.

  18. 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.

  19. Not a single but multiple populations of GABAergic neurons control sleep.

    Science.gov (United States)

    Luppi, Pierre-Hervé; Peyron, Christelle; Fort, Patrice

    2017-04-01

    The role of gamma-amino butyric acid (GABA) in sleep induction and maintenance is well accepted since most insomnia treatments target GABAa receptors. However, the population(s) of GABAergic neurons involved in the beneficial effect of GABA on sleep remains to be identified. This is not an easy task since GABAergic neurons are widely distributed in all brain structures. A recently growing number of populations of GABAergic neurons have been involved in sleep control. We first review here possible candidates for inducing non-rapid eye movement (NREM) sleep including the GABAergic neurons of the ventrolateral preoptic area, the parafacial zone in the brainstem, the nucleus accumbens and the cortex. We also discuss the role of several populations of GABAergic neurons in rapid eye movement (REM) sleep control. Indeed, it is well accepted that muscle atonia occurring during REM sleep is due to a GABA/glycinergic hyperpolarization of motoneurons. Recent evidence strongly suggests that these neurons are located in the ventral medullary reticular formation. It has also recently been shown that neurons containing the neuropeptide melanin concentrating hormone and GABA located in the lateral hypothalamic area control REM sleep expression. Finally, a population of REM-off GABAergic neurons located in the ventrolateral periaqueductal gray has been shown to gate REM sleep by inhibiting glutamatergic neurons located in the sublaterodorsal tegmental nucleus. In summary, recent data clearly indicate that multiple populations of GABAergic neurons located throughout the brain from the cortex to the medulla oblongata control NREM and REM sleep. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. 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

  1. 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...

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. Different cortical projections from three subdivisions of the rat lateral posterior thalamic nucleus: a single-neuron tracing study with viral vectors.

    Science.gov (United States)

    Nakamura, Hisashi; Hioki, Hiroyuki; Furuta, Takahiro; Kaneko, Takeshi

    2015-05-01

    The lateral posterior thalamic nucleus (LP) is one of the components of the extrageniculate pathway in the rat visual system, and is cytoarchitecturally divided into three subdivisions--lateral (LPl), rostromedial (LPrm), and caudomedial (LPcm) portions. To clarify the differences in the dendritic fields and axonal arborisations among the three subdivisions, we applied a single-neuron labeling technique with viral vectors to LP neurons. The proximal dendrites of LPl neurons were more numerous than those of LPrm and LPcm neurons, and LPrm neurons tended to have wider dendritic fields than LPl neurons. We then analysed the axonal arborisations of LP neurons by reconstructing the axon fibers in the cortex. The LPl, LPrm and LPcm were different from one another in terms of the projection targets--the main target cortical regions of LPl and LPrm neurons were the secondary and primary visual areas, whereas those of LPcm neurons were the postrhinal and temporal association areas. Furthermore, the principal target cortical layers of LPl neurons in the visual areas were middle layers, but that of LPrm neurons was layer 1. This indicates that LPl and LPrm neurons can be categorised into the core and matrix types of thalamic neurons, respectively, in the visual areas. In addition, LPl neurons formed multiple axonal clusters within the visual areas, whereas the fibers of LPrm neurons were widely and diffusely distributed. It is therefore presumed that these two types of neurons play different roles in visual information processing by dual thalamocortical innervation of the visual areas. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  8. 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...

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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

  18. μ-Opioid receptor activation and noradrenaline transport inhibition by tapentadol in rat single locus coeruleus neurons.

    Science.gov (United States)

    Sadeghi, Mahsa; Tzschentke, Thomas M; Christie, MacDonald J

    2015-01-01

    Tapentadol is a novel analgesic that combines moderate μ-opioid receptor agonism and noradrenaline reuptake inhibition in a single molecule. Both mechanisms of action are involved in producing analgesia; however, the potency and efficacy of tapentadol in individual neurons has not been characterized. Whole-cell patch-clamp recordings of G-protein-coupled inwardly rectifying K(+) (KIR 3.x) currents were made from rat locus coeruleus neurons in brain slices to investigate the potency and relative efficacy of tapentadol and compare its intrinsic activity with other clinically used opioids. Tapentadol showed agonist activity at μ receptors and was approximately six times less potent than morphine with respect to KIR 3.x current modulation. The intrinsic activity of tapentadol was lower than [Met]enkephalin, morphine and oxycodone, but higher than buprenorphine and pentazocine. Tapentadol inhibited the noradrenaline transporter (NAT) with potency similar to that at μ receptors. The interaction between these two mechanisms of action was additive in individual LC neurons. Tapentadol displays similar potency for both µ receptor activation and NAT inhibition in functioning neurons. The intrinsic activity of tapentadol at the μ receptor lies between that of buprenorphine and oxycodone, potentially explaining the favourable profile of side effects, related to μ receptors. This article is part of a themed section on Opioids: New Pathways to Functional Selectivity. To view the other articles in this section visit http://dx.doi.org/10.1111/bph.2015.172.issue-2. © 2013 The British Pharmacological Society.

  19. 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.

  20. Induction of specific neuron types by overexpression of single transcription factors.

    Science.gov (United States)

    Teratani-Ota, Yusuke; Yamamizu, Kohei; Piao, Yulan; Sharova, Lioudmila; Amano, Misa; Yu, Hong; Schlessinger, David; Ko, Minoru S H; Sharov, Alexei A

    2016-10-01

    Specific neuronal types derived from embryonic stem cells (ESCs) can facilitate mechanistic studies and potentially aid in regenerative medicine. Existing induction methods, however, mostly rely on the effects of the combined action of multiple added growth factors, which generally tend to result in mixed populations of neurons. Here, we report that overexpression of specific transcription factors (TFs) in ESCs can rather guide the differentiation of ESCs towards specific neuron lineages. Analysis of data on gene expression changes 2 d after induction of each of 185 TFs implicated candidate TFs for further ESC differentiation studies. Induction of 23 TFs (out of 49 TFs tested) for 6 d facilitated neural differentiation of ESCs as inferred from increased proportion of cells with neural progenitor marker PSA-NCAM. We identified early activation of the Notch signaling pathway as a common feature of most potent inducers of neural differentiation. The majority of neuron-like cells generated by induction of Ascl1, Smad7, Nr2f1, Dlx2, Dlx4, Nr2f2, Barhl2, and Lhx1 were GABA-positive and expressed other markers of GABAergic neurons. In the same way, we identified Lmx1a and Nr4a2 as inducers for neurons bearing dopaminergic markers and Isl1, Fezf2, and St18 for cholinergic motor neurons. A time-course experiment with induction of Ascl1 showed early upregulation of most neural-specific messenger RNA (mRNA) and microRNAs (miRNAs). Sets of Ascl1-induced mRNAs and miRNAs were enriched in Ascl1 targets. In further studies, enrichment of cells obtained with the induction of Ascl1, Smad7, and Nr2f1 using microbeads resulted in essentially pure population of neuron-like cells with expression profiles similar to neural tissues and expressed markers of GABAergic neurons. In summary, this study indicates that induction of transcription factors is a promising approach to generate cultures that show the transcription profiles characteristic of specific neural cell types.

  1. A single pair of neurons links sleep to memory consolidation in Drosophila melanogaster.

    Science.gov (United States)

    Haynes, Paula R; Christmann, Bethany L; Griffith, Leslie C

    2015-01-07

    Sleep promotes memory consolidation in humans and many other species, but the physiological and anatomical relationships between sleep and memory remain unclear. Here, we show the dorsal paired medial (DPM) neurons, which are required for memory consolidation in Drosophila, are sleep-promoting inhibitory neurons. DPMs increase sleep via release of GABA onto wake-promoting mushroom body (MB) α'/β' neurons. Functional imaging demonstrates that DPM activation evokes robust increases in chloride in MB neurons, but is unable to cause detectable increases in calcium or cAMP. Downregulation of α'/β' GABAA and GABABR3 receptors results in sleep loss, suggesting these receptors are the sleep-relevant targets of DPM-mediated inhibition. Regulation of sleep by neurons necessary for consolidation suggests that these brain processes may be functionally interrelated via their shared anatomy. These findings have important implications for the mechanistic relationship between sleep and memory consolidation, arguing for a significant role of inhibitory neurotransmission in regulating these processes.

  2. 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.

  3. 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.

  4. 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.

  5. Challenging the neuronal MIBG uptake by pharmacological intervention: effect of a single dose of oral amitriptyline on regional cardiac MIBG uptake

    Energy Technology Data Exchange (ETDEWEB)

    Estorch, Montserrat; Carrio, Ignasi; Mena, Esther; Flotats, Albert; Camacho, Valle; Fuertes, Jordi [Autonomous University of Barcelona, Department of Nuclear Medicine, Hospital Sant Pau, Barcelona (Spain); Kulisewsky, Jaume [Autonomous University of Barcelona, Department of Neurology, Hospital Sant Pau, Barcelona (Spain); Narula, Jagat [Irvine College of Medicine, Division of Cardiology, University of California, Irvine, CA (United States)

    2004-12-01

    Imaging with metaiodobenzylguanidine (MIBG) is used for the assessment of neuronal dysfunction in various cardiovascular disorders. Although valuable information is obtained by resting MIBG imaging, it is conceivable that competitive interference with the re-uptake mechanism would exaggerate MIBG defects and might unmask subclinical neuronal dysfunction. Tricyclic antidepressants, such as amitriptyline, have been reported to significantly increase cardiac MIBG washout and inhibit uptake into presynaptic neurons. This study was undertaken to assess whether a single oral dose of amitriptyline could influence cardiac MIBG distribution. Six patients (aged 62-81 years; four males, two females) who had demonstrated a normal cardiac MIBG scan during work-up for movement disorders were studied. The patients underwent a second {sup 123}I-MIBG study after oral administration of 25 mg amitriptyline within 1 week. Single-photon emission computed tomography images were acquired at 4 h to assess the regional distribution of MIBG, after generation of polar maps and employing a 20-segment model. Mean percentage of peak activity was calculated for each segment at rest and after amitriptyline administration. After amitriptyline administration, there was a decrease in regional MIBG uptake in 10{+-}4 segments per patient [62/120 segments (52%): 37 segments with a 5-10% decrease, 25 segments with a >10% decrease]. This change was statistically significant in lateral (P=0.003), apical (P<0.0001) and inferior (P=0.03) regions. A single oral dose of amitriptyline can induce changes in the uptake and retention of cardiac MIBG, indicating the feasibility of use of pharmacological intervention in cardiac neurotransmission imaging. (orig.)

  6. 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.

  7. Bioenergetic status modulates motor neuron vulnerability and pathogenesis in a zebrafish model of spinal muscular atrophy.

    Science.gov (United States)

    Boyd, Penelope J; Tu, Wen-Yo; Shorrock, Hannah K; Groen, Ewout J N; Carter, Roderick N; Powis, Rachael A; Thomson, Sophie R; Thomson, Derek; Graham, Laura C; Motyl, Anna A L; Wishart, Thomas M; Highley, J Robin; Morton, Nicholas M; Becker, Thomas; Becker, Catherina G; Heath, Paul R; Gillingwater, Thomas H

    2017-04-01

    Degeneration and loss of lower motor neurons is the major pathological hallmark of spinal muscular atrophy (SMA), resulting from low levels of ubiquitously-expressed survival motor neuron (SMN) protein. One remarkable, yet unresolved, feature of SMA is that not all motor neurons are equally affected, with some populations displaying a robust resistance to the disease. Here, we demonstrate that selective vulnerability of distinct motor neuron pools arises from fundamental modifications to their basal molecular profiles. Comparative gene expression profiling of motor neurons innervating the extensor digitorum longus (disease-resistant), gastrocnemius (intermediate vulnerability), and tibialis anterior (vulnerable) muscles in mice revealed that disease susceptibility correlates strongly with a modified bioenergetic profile. Targeting of identified bioenergetic pathways by enhancing mitochondrial biogenesis rescued motor axon defects in SMA zebrafish. Moreover, targeting of a single bioenergetic protein, phosphoglycerate kinase 1 (Pgk1), was found to modulate motor neuron vulnerability in vivo. Knockdown of pgk1 alone was sufficient to partially mimic the SMA phenotype in wild-type zebrafish. Conversely, Pgk1 overexpression, or treatment with terazosin (an FDA-approved small molecule that binds and activates Pgk1), rescued motor axon phenotypes in SMA zebrafish. We conclude that global bioenergetics pathways can be therapeutically manipulated to ameliorate SMA motor neuron phenotypes in vivo.

  8. Bioenergetic status modulates motor neuron vulnerability and pathogenesis in a zebrafish model of spinal muscular atrophy.

    Directory of Open Access Journals (Sweden)

    Penelope J Boyd

    2017-04-01

    Full Text Available Degeneration and loss of lower motor neurons is the major pathological hallmark of spinal muscular atrophy (SMA, resulting from low levels of ubiquitously-expressed survival motor neuron (SMN protein. One remarkable, yet unresolved, feature of SMA is that not all motor neurons are equally affected, with some populations displaying a robust resistance to the disease. Here, we demonstrate that selective vulnerability of distinct motor neuron pools arises from fundamental modifications to their basal molecular profiles. Comparative gene expression profiling of motor neurons innervating the extensor digitorum longus (disease-resistant, gastrocnemius (intermediate vulnerability, and tibialis anterior (vulnerable muscles in mice revealed that disease susceptibility correlates strongly with a modified bioenergetic profile. Targeting of identified bioenergetic pathways by enhancing mitochondrial biogenesis rescued motor axon defects in SMA zebrafish. Moreover, targeting of a single bioenergetic protein, phosphoglycerate kinase 1 (Pgk1, was found to modulate motor neuron vulnerability in vivo. Knockdown of pgk1 alone was sufficient to partially mimic the SMA phenotype in wild-type zebrafish. Conversely, Pgk1 overexpression, or treatment with terazosin (an FDA-approved small molecule that binds and activates Pgk1, rescued motor axon phenotypes in SMA zebrafish. We conclude that global bioenergetics pathways can be therapeutically manipulated to ameliorate SMA motor neuron phenotypes in vivo.

  9. 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

  10. 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

  11. 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.

  12. 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.

  13. Wireless Sensor Network Congestion Control Based on Standard Particle Swarm Optimization and Single Neuron PID.

    Science.gov (United States)

    Yang, Xiaoping; Chen, Xueying; Xia, Riting; Qian, Zhihong

    2018-04-19

    Aiming at the problem of network congestion caused by the large number of data transmissions in wireless routing nodes of wireless sensor network (WSN), this paper puts forward an algorithm based on standard particle swarm⁻neural PID congestion control (PNPID). Firstly, PID control theory was applied to the queue management of wireless sensor nodes. Then, the self-learning and self-organizing ability of neurons was used to achieve online adjustment of weights to adjust the proportion, integral and differential parameters of the PID controller. Finally, the standard particle swarm optimization to neural PID (NPID) algorithm of initial values of proportion, integral and differential parameters and neuron learning rates were used for online optimization. This paper describes experiments and simulations which show that the PNPID algorithm effectively stabilized queue length near the expected value. At the same time, network performance, such as throughput and packet loss rate, was greatly improved, which alleviated network congestion and improved network QoS.

  14. Spike propagation through the dorsal root ganglia in an unmyelinated sensory neuron: a modeling study.

    Science.gov (United States)

    Sundt, Danielle; Gamper, Nikita; Jaffe, David B

    2015-12-01

    Unmyelinated C-fibers are a major type of sensory neurons conveying pain information. Action potential conduction is regulated by the bifurcation (T-junction) of sensory neuron axons within the dorsal root ganglia (DRG). Understanding how C-fiber signaling is influenced by the morphology of the T-junction and the local expression of ion channels is important for understanding pain signaling. In this study we used biophysical computer modeling to investigate the influence of axon morphology within the DRG and various membrane conductances on the reliability of spike propagation. As expected, calculated input impedance and the amplitude of propagating action potentials were both lowest at the T-junction. Propagation reliability for single spikes was highly sensitive to the diameter of the stem axon and the density of voltage-gated Na(+) channels. A model containing only fast voltage-gated Na(+) and delayed-rectifier K(+) channels conducted trains of spikes up to frequencies of 110 Hz. The addition of slowly activating KCNQ channels (i.e., KV7 or M-channels) to the model reduced the following frequency to 30 Hz. Hyperpolarization produced by addition of a much slower conductance, such as a Ca(2+)-dependent K(+) current, was needed to reduce the following frequency to 6 Hz. Attenuation of driving force due to ion accumulation or hyperpolarization produced by a Na(+)-K(+) pump had no effect on following frequency but could influence the reliability of spike propagation mutually with the voltage shift generated by a Ca(2+)-dependent K(+) current. These simulations suggest how specific ion channels within the DRG may contribute toward therapeutic treatments for chronic pain. Copyright © 2015 the American Physiological Society.

  15. Modeling the Activity of Single Genes

    Science.gov (United States)

    Mjolsness, Eric; Gibson, Michael

    1999-01-01

    the key questions in gene regulation are: What genes are expressed in a certain cell at a certain time? How does gene expression differ from cell to cell in a multicellular organism? Which proteins act as transcription factors, i.e., are important in regulating gene expression? From questions like these, we hope to understand which genes are important for various macroscopic processes. Nearly all of the cells of a multicellular organism contain the same DNA. Yet this same genetic information yields a large number of different cell types. The fundamental difference between a neuron and a liver cell, for example, is which genes are expressed. Thus understanding gene regulation is an important step in understanding development. Furthermore, understanding the usual genes that are expressed in cells may give important clues about various diseases. Some diseases, such as sickle cell anemia and cystic fibrosis, are caused by defects in single, non-regulatory genes; others, such as certain cancers, are caused when the cellular control circuitry malfunctions - an understanding of these diseases will involve pathways of multiple interacting gene products. There are numerous challenges in the area of understanding and modeling gene regulation. First and foremost, biologists would like to develop a deeper understanding of the processes involved, including which genes and families of genes are important, how they interact, etc. From a computation point of view, there has been embarrassingly little work done. In this chapter there are many areas in which we can phrase meaningful, non-trivial computational questions, but questions that have not been addressed. Some of these are purely computational (what is a good algorithm for dealing with a model of type X) and others are more mathematical (given a system with certain characteristics, what sort of model can one use? How does one find biochemical parameters from system-level behavior using as few experiments as possible?). In

  16. 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).

  17. Assessing Model Characterization of Single Source ...

    Science.gov (United States)

    Aircraft measurements made downwind from specific coal fired power plants during the 2013 Southeast Nexus field campaign provide a unique opportunity to evaluate single source photochemical model predictions of both O3 and secondary PM2.5 species. The model did well at predicting downwind plume placement. The model shows similar patterns of an increasing fraction of PM2.5 sulfate ion to the sum of SO2 and PM2.5 sulfate ion by distance from the source compared with ambient based estimates. The model was less consistent in capturing downwind ambient based trends in conversion of NOX to NOY from these sources. Source sensitivity approaches capture near-source O3 titration by fresh NO emissions, in particular subgrid plume treatment. However, capturing this near-source chemical feature did not translate into better downwind peak estimates of single source O3 impacts. The model estimated O3 production from these sources but often was lower than ambient based source production. The downwind transect ambient measurements, in particular secondary PM2.5 and O3, have some level of contribution from other sources which makes direct comparison with model source contribution challenging. Model source attribution results suggest contribution to secondary pollutants from multiple sources even where primary pollutants indicate the presence of a single source. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, deci

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. Graphical models for inferring single molecule dynamics

    Directory of Open Access Journals (Sweden)

    Gonzalez Ruben L

    2010-10-01

    Full Text Available Abstract Background The recent explosion of experimental techniques in single molecule biophysics has generated a variety of novel time series data requiring equally novel computational tools for analysis and inference. This article describes in general terms how graphical modeling may be used to learn from biophysical time series data using the variational Bayesian expectation maximization algorithm (VBEM. The discussion is illustrated by the example of single-molecule fluorescence resonance energy transfer (smFRET versus time data, where the smFRET time series is modeled as a hidden Markov model (HMM with Gaussian observables. A detailed description of smFRET is provided as well. Results The VBEM algorithm returns the model’s evidence and an approximating posterior parameter distribution given the data. The former provides a metric for model selection via maximum evidence (ME, and the latter a description of the model’s parameters learned from the data. ME/VBEM provide several advantages over the more commonly used approach of maximum likelihood (ML optimized by the expectation maximization (EM algorithm, the most important being a natural form of model selection and a well-posed (non-divergent optimization problem. Conclusions The results demonstrate the utility of graphical modeling for inference of dynamic processes in single molecule biophysics.

  5. 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.

  6. 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.

  7. 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.

  8. Integration of Plasticity Mechanisms within a Single Sensory Neuron of C. elegans Actuates a Memory.

    Science.gov (United States)

    Hawk, Josh D; Calvo, Ana C; Liu, Ping; Almoril-Porras, Agustin; Aljobeh, Ahmad; Torruella-Suárez, María Luisa; Ren, Ivy; Cook, Nathan; Greenwood, Joel; Luo, Linjiao; Wang, Zhao-Wen; Samuel, Aravinthan D T; Colón-Ramos, Daniel A

    2018-01-17

    Neural plasticity, the ability of neurons to change their properties in response to experiences, underpins the nervous system's capacity to form memories and actuate behaviors. How different plasticity mechanisms act together in vivo and at a cellular level to transform sensory information into behavior is not well understood. We show that in Caenorhabditis elegans two plasticity mechanisms-sensory adaptation and presynaptic plasticity-act within a single cell to encode thermosensory information and actuate a temperature preference memory. Sensory adaptation adjusts the temperature range of the sensory neuron (called AFD) to optimize detection of temperature fluctuations associated with migration. Presynaptic plasticity in AFD is regulated by the conserved kinase nPKCε and transforms thermosensory information into a behavioral preference. Bypassing AFD presynaptic plasticity predictably changes learned behavioral preferences without affecting sensory responses. Our findings indicate that two distinct neuroplasticity mechanisms function together through a single-cell logic system to enact thermotactic behavior. VIDEO ABSTRACT. Copyright © 2017 Elsevier Inc. All rights reserved.

  9. 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.

  10. Single Canonical Model of Reflexive Memory and Spatial Attention.

    Science.gov (United States)

    Patel, Saumil S; Red, Stuart; Lin, Eric; Sereno, Anne B

    2015-10-23

    Many neurons in the dorsal and ventral visual stream have the property that after a brief visual stimulus presentation in their receptive field, the spiking activity in these neurons persists above their baseline levels for several seconds. This maintained activity is not always correlated with the monkey's task and its origin is unknown. We have previously proposed a simple neural network model, based on shape selective neurons in monkey lateral intraparietal cortex, which predicts the valence and time course of reflexive (bottom-up) spatial attention. In the same simple model, we demonstrate here that passive maintained activity or short-term memory of specific visual events can result without need for an external or top-down modulatory signal. Mutual inhibition and neuronal adaptation play distinct roles in reflexive attention and memory. This modest 4-cell model provides the first simple and unified physiologically plausible mechanism of reflexive spatial attention and passive short-term memory processes.

  11. Induction of Associative Olfactory Memory by Targeted Activation of Single Olfactory Neurons in Drosophila Larvae

    OpenAIRE

    Honda, Takato; Lee, Chi-Yu; Yoshida-Kasikawa, Maki; Honjo, Ken; Furukubo-Tokunaga, Katsuo

    2014-01-01

    It has been postulated that associative memory is formed by at least two sets of external stimuli, CS and US, that are transmitted to the memory centers by distinctive conversing pathways. However, whether associative memory can be induced by the activation of only the olfactory CS and a biogenic amine-mediated US pathways remains to be elucidated. In this study, we substituted the reward signals with dTrpA1-mediated thermogenetic activation of octopaminergic neurons and the odor signals by C...

  12. 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.

  13. 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

  14. Curcumin protects dopaminergic neurons against inflammation-mediated damage and improves motor dysfunction induced by single intranigral lipopolysaccharide injection.

    Science.gov (United States)

    Sharma, Neha; Sharma, Sheetal; Nehru, Bimla

    2017-06-01

    Various studies have indicated a lower incidence and prevalence of neurological conditions in people consuming curcumin. The ability of curcumin to target multiple cascades, simultaneously, could be held responsible for its neuroprotective effects. The present study was designed to investigate the potential of curcumin in minimizing microglia-mediated damage in lipopolysaccharide (LPS) induced model of PD. Altered microglial functions and increased inflammatory profile of the CNS have severe behavioral consequences. In the current investigation, a single injection of LPS (5 ug/5 µl PBS) was injected into the substantia nigra (SN) of rats, and curcumin [40 mg/kg b.wt (i.p.)] was administered daily for a period of 21 days. LPS triggered an inflammatory response characterized by glial activation [Iba-1 and glial fibrillary acidic protein (GFAP)] and pro-inflammatory cytokine production (TNF-α and IL-1β) leading to extensive dopaminergic loss and behavioral abnormality in rats. The behavioral observations, biochemical markers, quantification of dopamine and its metabolites (DOPAC and HVA) using HPLC followed by IHC of tyrosine hydroxylase (TH) were evaluated after 21 days of LPS injection. Curcumin supplementation prevented dopaminergic degeneration in LPS-treated animals by normalizing the altered levels of biomarkers. Also, a significant improvement in TH levels as well as behavioral parameters (actophotometer, rotarod, beam walking and grid walking tests) were seen in LPS injected rats. Curcumin shielded the dopaminergic neurons against LPS-induced inflammatory response, which was associated with suppression of glial activation (microglia and astrocytes) and transcription factor NF-κB as depicted from RT-PCR and EMSA assay. Curcumin also suppressed microglial NADPH oxidase activation as observed from NADPH oxidase activity. The results suggested that one of the important mechanisms by which curcumin mediates its protective effects in the LPS-induced PD

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. [Effects of blokade of the dopaminergic D1/D2 receptors on the single and network neuronal activity in the frontal and visual cortices and behavior of cats].

    Science.gov (United States)

    Kuleshova, E P; Zaleshin, A V; Sidorina, V V; Merzhanova, G Kh

    2010-01-01

    The results obtained at the levels of single and network neuronal activity in the frontal and visual cortices of cats with different types of behavior revealed features of activity of these structures in normal conditions and after local introductions of antagonists of DI/D2 receptors (SCH23390 and raclopride) into the n. accumbens and frontal cortex. Under the influence of the antagonists, long-latency reactions were characterized by a significant increase in the average frequency of neuronal activity in the frontal cortex, whereas in the visual cortex the average frequency decreased as compared to norm. At the same time, the network activity of the same neurons in the frontal cortex did not change but weakened in the visual cortex, which was expressed in a reduction of the number of neuronal interactions within the visual cortex and between the neurons of the frontal and visual cortices. Normally, during the long-latency conditioned reactions, the average frequency of single neuronal activity and the rate of neuronal interactions in the structures under study were significantly higher as compared to the loss of conditioned reactions. Administration of the dopamine antagonists did not change these features. The results suggest different dopamine modulations of the network activity of the cortical zones under study during the conditioned performance, which is expressed in responsiveness of the cortical projection of a trigger signal (the visual cortex) and visual-frontal networks generated in the course of training.

  20. 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

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. 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

  7. Protective Effects of Cannabidiol against Seizures and Neuronal Death in a Rat Model of Mesial Temporal Lobe Epilepsy.

    Science.gov (United States)

    Do Val-da Silva, Raquel A; Peixoto-Santos, Jose E; Kandratavicius, Ludmyla; De Ross, Jana B; Esteves, Ingrid; De Martinis, Bruno S; Alves, Marcela N R; Scandiuzzi, Renata C; Hallak, Jaime E C; Zuardi, Antonio W; Crippa, Jose A; Leite, Joao P

    2017-01-01

    The present study reports the behavioral, electrophysiological, and neuropathological effects of cannabidiol (CBD), a major non-psychotropic constituent of Cannabis sativa , in the intrahippocampal pilocarpine-induced status epilepticus (SE) rat model. CBD was administered before pilocarpine-induced SE (group SE+CBDp) or before and after SE (group SE+CBDt), and compared to rats submitted only to SE (SE group), CBD, or vehicle (VH group). Groups were evaluated during SE (behavioral and electrophysiological analysis), as well as at days one and three post-SE (exploratory activity, electrophysiological analysis, neuron density, and neuron degeneration). Compared to SE group, SE+CBD groups (SE+CBDp and SE+CBDt) had increased SE latency, diminished SE severity, increased contralateral afterdischarge latency and decreased relative powers in delta (0.5-4 Hz) and theta (4-10 Hz) bands. Only SE+CBDp had increased vertical exploratory activity 1-day post SE and decreased contralateral relative power in delta 3 days after SE, when compared to SE group. SE+CBD groups also showed decreased neurodegeneration in the hilus and CA3, and higher neuron density in granule cell layer, hilus, CA3, and CA1, when compared to SE group. Our findings demonstrate anticonvulsant and neuroprotective effects of CBD preventive treatment in the intrahippocampal pilocarpine epilepsy model, either as single or multiple administrations, reinforcing the potential role of CBD in the treatment of epileptic disorders.

  8. 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.

  9. Enhanced Peptide Detection Toward Single-Neuron Proteomics by Reversed-Phase Fractionation Capillary Electrophoresis Mass Spectrometry

    Science.gov (United States)

    Choi, Sam B.; Lombard-Banek, Camille; Muñoz-LLancao, Pablo; Manzini, M. Chiara; Nemes, Peter

    2017-11-01

    The ability to detect peptides and proteins in single cells is vital for understanding cell heterogeneity in the nervous system. Capillary electrophoresis (CE) nanoelectrospray ionization (nanoESI) provides high-resolution mass spectrometry (HRMS) with trace-level sensitivity, but compressed separation during CE challenges protein identification by tandem HRMS with limited MS/MS duty cycle. Here, we supplemented ultrasensitive CE-nanoESI-HRMS with reversed-phase (RP) fractionation to enhance identifications from protein digest amounts that approximate to a few mammalian neurons. An 1 to 20 μg neuronal protein digest was fractionated on a RP column (ZipTip), and 1 ng to 500 pg of peptides were analyzed by a custom-built CE-HRMS system. Compared with the control (no fractionation), RP fractionation improved CE separation (theoretical plates 274,000 versus 412,000 maximum, resp.), which enhanced detection sensitivity (2.5-fold higher signal-to-noise ratio), minimized co-isolation spectral interferences during MS/MS, and increased the temporal rate of peptide identification by up to 57%. From 1 ng of protein digest (development of the brain, including those involved in synaptic transmission and plasticity and cytoskeletal organization. [Figure not available: see fulltext.

  10. 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.

  11. 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...

  12. 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.

  13. 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.

  14. Real-time subpixel-accuracy tracking of single mitochondria in neurons reveals heterogeneous mitochondrial motion.

    Science.gov (United States)

    Alsina, Adolfo; Lai, Wu Ming; Wong, Wai Kin; Qin, Xianan; Zhang, Min; Park, Hyokeun

    2017-11-04

    Mitochondria are essential for cellular survival and function. In neurons, mitochondria are transported to various subcellular regions as needed. Thus, defects in the axonal transport of mitochondria are related to the pathogenesis of neurodegenerative diseases, and the movement of mitochondria has been the subject of intense research. However, the inability to accurately track mitochondria with subpixel accuracy has hindered this research. Here, we report an automated method for tracking mitochondria based on the center of fluorescence. This tracking method, which is accurate to approximately one-tenth of a pixel, uses the centroid of an individual mitochondrion and provides information regarding the distance traveled between consecutive imaging frames, instantaneous speed, net distance traveled, and average speed. Importantly, this new tracking method enables researchers to observe both directed motion and undirected movement (i.e., in which the mitochondrion moves randomly within a small region, following a sub-diffusive motion). This method significantly improves our ability to analyze the movement of mitochondria and sheds light on the dynamic features of mitochondrial movement. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. 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)

  16. Erythropoietin attenuates motor neuron programmed cell death in a burn animal model.

    Directory of Open Access Journals (Sweden)

    Sheng-Hua Wu

    Full Text Available Burn-induced neuromuscular dysfunction may contribute to long-term morbidity; therefore, it is imperative to develop novel treatments. The present study investigated whether erythropoietin (EPO administration attenuates burn-induced motor neuron apoptosis and neuroinflammatory response. To validate our hypothesis, a third-degree hind paw burn rat model was developed by bringing the paw into contact with a metal surface at 75°C for 10 s. A total of 24 male Sprague-Dawley rats were randomly assigned to four groups: Group A, sham-control; Group B, burn-induced; Group C, burn + single EPO dose (5000 IU/kg i.p. at D0; and Group D, burn + daily EPO dosage (3000 IU/kg/day i.p. at D0-D6. Two treatment regimens were used to evaluate single versus multiple doses treatment effects. Before sacrifice, blood samples were collected for hematological parameter examination. The histological analyses of microglia activation, iNOS, and COX-2 in the spinal cord ventral horn were performed at week 1 post-burn. In addition, we examined autophagy changes by biomarkers of LC3B and ATG5. The expression of BCL-2, BAX, cleaved caspase-3, phospho-AKT, and mTOR was assessed simultaneously through Western blotting. EPO administration after burn injury attenuated neuroinflammation through various mechanisms, including the reduction of microglia activity as well as iNOS and COX-2 expression in the spinal cord ventral horn. In addition, the expression of phospho-AKT, mTOR and apoptotic indicators, such as BAX, BCL-2, and cleaved caspase-3, was modulated. Furthermore, the activity of burn-induced autophagy in the spinal cord ventral horn characterized by the expression of autophagic biomarkers, LC3B and ATG5, was reduced after EPO administration. The present results indicate that EPO inhibits the AKT-mTOR pathway to attenuate burn-induced motor neuron programmed cell death and microglia activation. EPO can modulate neuroinflammation and programmed cell death and may be a

  17. 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.

  18. 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.

  19. Bidirectional coupling between astrocytes and neurons mediates learning and dynamic coordination in the brain: a multiple modeling approach.

    Directory of Open Access Journals (Sweden)

    John J Wade

    Full Text Available In recent years research suggests that astrocyte networks, in addition to nutrient and waste processing functions, regulate both structural and synaptic plasticity. To understand the biological mechanisms that underpin such plasticity requires the development of cell level models that capture the mutual interaction between astrocytes and neurons. This paper presents a detailed model of bidirectional signaling between astrocytes and neurons (the astrocyte-neuron model or AN model which yields new insights into the computational role of astrocyte-neuronal coupling. From a set of modeling studies we demonstrate two significant findings. Firstly, that spatial signaling via astrocytes can relay a "learning signal" to remote synaptic sites. Results show that slow inward currents cause synchronized postsynaptic activity in remote neurons and subsequently allow Spike-Timing-Dependent Plasticity based learning to occur at the associated synapses. Secondly, that bidirectional communication between neurons and astrocytes underpins dynamic coordination between neuron clusters. Although our composite AN model is presently applied to simplified neural structures and limited to coordination between localized neurons, the principle (which embodies structural, functional and dynamic complexity, and the modeling strategy may be extended to coordination among remote neuron clusters.

  20. Single Cell Electroporation Method for Mammalian CNS Neurons in Organotypic Slice Cultures

    Science.gov (United States)

    Uesaka, Naofumi; Hayano, Yasufumi; Yamada, Akito; Yamamoto, Nobuhiko

    Axon tracing is an essential technique to study the projection pattern of neurons in the CNS. Horse radish peroxidase and lectins have contributed to revealing many neural connection patterns in the CNS (Itaya and van Hoesen, 1982; Fabian and Coulter, 1985; Yoshihara, 2002). Moreover, a tracing method with fluorescent dye has enabled the observation of growing axons in living conditions, and demon strated a lot of developmental aspects in axon growth and guidance (Harris et al., 1987; O'Rourke and Fraser, 1990; Kaethner and Stuermer, 1992; Halloran and Kalil, 1994; Yamamoto et al., 1997). More recently, genetically encoded fluores cent proteins can be used as a powerful tool to observe various biological events. Several gene transfer techniques such as microinjection, biolistic gene gun, viral infection, lipofection and transgenic technology have been developed (Feng et al., 2000; Ehrengruber et al., 2001; O'Brien et al., 2001; Ma et al., 2002; Sahly et al., 2003). In particular, the electroporation technique was proved as a valuable tool, since it can be applied to a wide range of tissues and cell types with little toxicity and can be performed with relative technical easiness. Most methods, including a stand ard electroporation technique, are suitable for gene transfer to a large number of cells. However, this is not ideal for axonal tracing, because observation of individ ual axons is occasionally required. To overcome this problem, we have developed an electroporation method using glass micropipettes containing plasmid solutions and small current injection. Here we introduce the method in detail and exemplified results with some example applications and discuss its usefulness.

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. Neuronal changes induced by Varicella Zoster Virus in a rat model of Postherpetic Neuralgia

    Science.gov (United States)

    Guedon, Jean-Marc G.; Yee, Michael B.; Zhang, Mingdi; Harvey, Stephen A. K.; Goins, William F.; Kinchington, Paul R.

    2015-01-01

    A significant fraction of patients with herpes zoster, caused by varicella zoster virus (VZV), experience chronic pain termed postherpetic neuralgia (PHN). VZV-inoculated rats develop prolonged nocifensive behaviors and serve as a model of PHN. We demonstrate that primary rat cultures show a post-entry block for VZV replication, suggesting the rat is not fully permissive. However, footpads of VZV infected animals show reduced peripheral innervation and innervating dorsal root ganglia (DRG) contained VZV DNA and transcripts of candidate immediate early and early genes. The VZV-infected DRG showed changes in host gene expression patterns, with 84 up-regulated and 116 down-regulated genes seen in gene array studies. qRT-PCR validated the modulation of nociception-associated genes Ntrk2, Trpv1, and Calca (CGRP). The data suggests that VZV inoculation of the rat results in a single round, incomplete infection that is sufficient to induce pain behaviors, and this involves infection of and changes induced in neuronal populations. PMID:25880108

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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…

  14. 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.

  15. Shaping Neuronal Network Activity by Presynaptic Mechanisms.

    Directory of Open Access Journals (Sweden)

    Ayal Lavi

    2015-09-01

    Full Text Available Neuronal microcircuits generate oscillatory activity, which has been linked to basic functions such as sleep, learning and sensorimotor gating. Although synaptic release processes are well known for their ability to shape the interaction between neurons in microcircuits, most computational models do not simulate the synaptic transmission process directly and hence cannot explain how changes in synaptic parameters alter neuronal network activity. In this paper, we present a novel neuronal network model that incorporates presynaptic release mechanisms, such as vesicle pool dynamics and calcium-dependent release probability, to model the spontaneous activity of neuronal networks. The model, which is based on modified leaky integrate-and-fire neurons, generates spontaneous network activity patterns, which are similar to experimental data and robust under changes in the model's primary gain parameters such as excitatory postsynaptic potential and connectivity ratio. Furthermore, it reliably recreates experimental findings and provides mechanistic explanations for data obtained from microelectrode array recordings, such as network burst termination and the effects of pharmacological and genetic manipulations. The model demonstrates how elevated asynchronous release, but not spontaneous release, synchronizes neuronal network activity and reveals that asynchronous release enhances utilization of the recycling vesicle pool to induce the network effect. The model further predicts a positive correlation between vesicle priming at the single-neuron level and burst frequency at the network level; this prediction is supported by experimental findings. Thus, the model is utilized to reveal how synaptic release processes at the neuronal level govern activity patterns and synchronization at the network level.

  16. 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.

  17. 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

  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. 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.

  20. Network dynamics in nociceptive pathways assessed by the neuronal avalanche model

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    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.

  1. 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

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. Prefrontal Single-Neuron Responses after Changes in Task Contingencies during Trace Eyeblink Conditioning in Rabbits.

    Science.gov (United States)

    Siegel, Jennifer J

    2016-01-01

    A number of studies indicate that the medial prefrontal cortex (mPFC) plays a role in mediating the expression of behavioral responses during tasks that require flexible changes in behavior. During trace eyeblink conditioning, evidence suggests that the mPFC provides the cerebellum with a persistent input to bridge the temporal gap between conditioned and unconditioned stimuli. Therefore, the mPFC is in a position to directly mediate the expression of trace conditioned responses. However, it is unknown whether persistent neural responses are associated with the flexible expression of behavior when task contingencies are changed during trace eyeblink conditioning. To investigate this, single-unit activity was recorded in the mPFC of rabbits during extinction and reacquisition of trace eyeblink conditioning, and during training to a different conditional stimulus. Persistent responses remained unchanged after full extinction, and also did not change during reacquisition training. During training to a different tone, however, the generalization of persistent responses to the new stimulus was associated with an animal's performance-when persistent responses generalized to the new tone, performance was high (>50% response rate). When persistent responses decreased to baseline rates, performance was poor (<50% response rate). The data suggest that persistent mPFC responses do not appear to mediate flexible changes in the expression of the original learning, but do appear to play a role in the generalization of that learning when the task is modified.

  8. [Compared Markov with fractal models by using single-channel experimental and simulation data].

    Science.gov (United States)

    Lan, Tonghan; Wu, Hongxiu; Lin, Jiarui

    2006-10-01

    The gating mechanical kinetical of ion channels has been modeled as a Markov process. In these models it is assumed that the channel protein has a small number of discrete conformational states and kinetic rate constants connecting these states are constant, the transition rate constants among the states is independent both of time and of the previous channel activity. It is assumed in Liebovitch's fractal model that the channel exists in an infinite number of energy states, consequently, transitions from one conductance state to another would be governed by a continuum of rate constants. In this paper, a statistical comparison is presented of Markov and fractal models of ion channel gating, the analysis is based on single-channel data from ion channel voltage-dependence K+ single channel of neuron cell and simulation data from three-states Markov model.

  9. 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.

  10. 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.

  11. 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...

  12. 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

  13. Morphine dependence in single enteric neurons from the mouse colon requires deletion of β‐arrestin2

    OpenAIRE

    Smith, Tricia H.; Ngwainmbi, Joy; Hashimoto, Atsushi; Dewey, William L.; Akbarali, Hamid I.

    2014-01-01

    Abstract Chronic administration of morphine results in the development of tolerance to the analgesic effects and to inhibition of upper gastrointestinal motility but not to colonic motility, resulting in persistent constipation. In this study we examined the effect of chronic morphine in myenteric neurons from the adult mouse colon. Similar to the ileum, distinct neuronal populations exhibiting afterhyperpolarization (AHP)‐positive and AHP‐negative neurons were identified in the colon. Acute ...

  14. 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.

  15. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  17. 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

  18. A single cDNA encodes two isoforms of stathmin, a developmentally regulated neuron-enriched phosphoprotein.

    Science.gov (United States)

    Doye, V; Soubrier, F; Bauw, G; Boutterin, M C; Beretta, L; Koppel, J; Vandekerckhove, J; Sobel, A

    1989-07-25

    Stathmin, a 19-kDa neuron-enriched soluble phosphoprotein, has been recently proposed as an ubiquitous intracellular relay for the diverse extracellular signals regulating cell proliferation, differentiation, and functions through various second messenger pathways (Sobel, A., Boutterin, M.C., Beretta, L., Chneiweiss, H., Doye, V., and peyro-Saint-Paul, H. (1989) J. Biol. Chem. 264, 3765-3772). Internal sequences of the protein from rat brain were determined after purification by two-dimensional polyacrylamide gel electrophoresis, electrotransfer onto Immobilon, and in situ proteolysis. Oligonucleotide mixtures based on these sequences were used to clone a cDNA for stathmin from a rat PC12 cell lambda gt 10 library. The deduced amino acid sequence reveals partial homologies with the coiled coil structural regions of several intracellular matrix phosphoproteins. Using this cDNA as a probe, we show that the expression of stathmin mRNA parallels that of the protein during brain ontogenesis, reaching a maximum at the neonatal stage. In vitro translation of the derived cRNA yielded all the known molecular forms of stathmin, namely its alpha and beta isoforms in their unphosphorylated and phosphorylated states. Thus, a single cDNA codes for both biologically relevant isoforms of the protein, indicating that they differ by co- or post-translational modifications.

  19. Attending to and remembering tactile stimuli: a review of brain imaging data and single-neuron responses.

    Science.gov (United States)

    Burton, H; Sinclair, R J

    2000-11-01

    Clinical and neuroimaging observations of the cortical network implicated in tactile attention have identified foci in parietal somatosensory, posterior parietal, and superior frontal locations. Tasks involving intentional hand-arm movements activate similar or nearby parietal and frontal foci. Visual spatial attention tasks and deliberate visuomotor behavior also activate overlapping posterior parietal and frontal foci. Studies in the visual and somatosensory systems thus support a proposal that attention to the spatial location of an object engages cortical regions responsible for the same coordinate referents used for guiding purposeful motor behavior. Tactile attention also biases processing in the somatosensory cortex through amplification of responses to relevant features of selected stimuli. Psychophysical studies demonstrate retention gradients for tactile stimuli like those reported for visual and auditory stimuli, and suggest analogous neural mechanisms for working memory across modalities. Neuroimaging studies in humans using memory tasks, and anatomic studies in monkeys support the idea that tactile information relayed from the somatosensory cortex is directed ventrally through the insula to the frontal cortex for short-term retention and to structures of the medial temporal lobe for long-term encoding. At the level of single neurons, tactile (such as visual and auditory) short-term memory appears as a persistent response during delay intervals between sampled stimuli.

  20. 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.

  1. 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.

  2. The Role of Inhibition in a Computational Model of an Auditory Cortical Neuron during the Encoding of Temporal Information

    Science.gov (United States)

    Bendor, Daniel

    2015-01-01

    In auditory cortex, temporal information within a sound is represented by two complementary neural codes: a temporal representation based on stimulus-locked firing and a rate representation, where discharge rate co-varies with the timing between acoustic events but lacks a stimulus-synchronized response. Using a computational neuronal model, we find that stimulus-locked responses are generated when sound-evoked excitation is combined with strong, delayed inhibition. In contrast to this, a non-synchronized rate representation is generated when the net excitation evoked by the sound is weak, which occurs when excitation is coincident and balanced with inhibition. Using single-unit recordings from awake marmosets (Callithrix jacchus), we validate several model predictions, including differences in the temporal fidelity, discharge rates and temporal dynamics of stimulus-evoked responses between neurons with rate and temporal representations. Together these data suggest that feedforward inhibition provides a parsimonious explanation of the neural coding dichotomy observed in auditory cortex. PMID:25879843

  3. 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.

  4. 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(+.

  5. 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.

  6. 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.

  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. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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...

  13. 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.

  14. 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...

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. Models of synchronized hippocampal bursts in the presence of inhibition. I. Single population events.

    Science.gov (United States)

    Traub, R D; Miles, R; Wong, R K

    1987-10-01

    1. We constructed model networks with 520 or 1,020 cells intended to represent the CA3 region of the hippocampus. Model neurons were simulated in enough detail to reproduce intrinsic bursting and the electrotonic flow of currents along dendritic cables. Neurons exerted either excitatory or inhibitory postsynaptic actions on other cells. The network models were simulated with different levels of excitatory and inhibitory synaptic strengths in order to study epileptic and other interesting collective behaviors in the system. 2. Excitatory synapses between neurons in the network were powerful enough so that burst firing in a presynaptic neuron would evoke bursting in its connected cells. Since orthodromic or antidromic stimulation evokes both a fast and a slow phase of inhibition, two types of inhibitory cells were simulated. The properties of these inhibitory cells were modeled to resemble those of two types of inhibitory cells characterized by dual intracellular recordings in the slice preparation. 3. With fast inhibition totally blocked, a stimulus to a single cell lead to a synchronized population burst. Thus the principles of our epileptic synchronization model, developed earlier, apply even when slow inhibitory postsynaptic potentials (IPSPs) are present, as apparently occurs in the epileptic hippocampal slice. The model performs in this way because bursting can propagate through several generations in the network before slow inhibition builds up enough to block burst propagation. This can occur, however, only if connectivity is sufficiently large. With very low connection densities, slow IPSPs will prevent the development of full synchronization. 4. We performed multiple simulations in which the fast inhibitory conductance strength was kept fixed at various levels while the strength of the excitatory synapses was varied. In each simulation, we stimulated either one or four cells. For each level of inhibition, the peak number of cells bursting depended

  20. 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.

  1. A chimeric path to neuronal synchronization

    Energy Technology Data Exchange (ETDEWEB)

    Essaki Arumugam, Easwara Moorthy; Spano, Mark L. [School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona 85287-9709 (United States)

    2015-01-15

    Synchronization of neuronal activity is associated with neurological disorders such as epilepsy. This process of neuronal synchronization is not fully understood. To further our understanding, we have experimentally studied the progression of this synchronization from normal neuronal firing to full synchronization. We implemented nine FitzHugh-Nagumo neurons (a simplified Hodgkin-Huxley model) via discrete electronics. For different coupling parameters (synaptic strengths), the neurons in the ring were either unsynchronized or completely synchronized when locally coupled in a ring. When a single long-range connection (nonlocal coupling) was introduced, an intermediate state known as a chimera appeared. The results indicate that (1) epilepsy is likely not only a dynamical disease but also a topological disease, strongly tied to the connectivity of the underlying network of neurons, and (2) the synchronization process in epilepsy may not be an “all or none” phenomenon, but can pass through an intermediate stage (chimera)

  2. A chimeric path to neuronal synchronization

    International Nuclear Information System (INIS)

    Essaki Arumugam, Easwara Moorthy; Spano, Mark L.

    2015-01-01

    Synchronization of neuronal activity is associated with neurological disorders such as epilepsy. This process of neuronal synchronization is not fully understood. To further our understanding, we have experimentally studied the progression of this synchronization from normal neuronal firing to full synchronization. We implemented nine FitzHugh-Nagumo neurons (a simplified Hodgkin-Huxley model) via discrete electronics. For different coupling parameters (synaptic strengths), the neurons in the ring were either unsynchronized or completely synchronized when locally coupled in a ring. When a single long-range connection (nonlocal coupling) was introduced, an intermediate state known as a chimera appeared. The results indicate that (1) epilepsy is likely not only a dynamical disease but also a topological disease, strongly tied to the connectivity of the underlying network of neurons, and (2) the synchronization process in epilepsy may not be an “all or none” phenomenon, but can pass through an intermediate stage (chimera)

  3. 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

  4. 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.

  5. Power laws from linear neuronal cable theory

    DEFF Research Database (Denmark)

    Pettersen, Klas H; Lindén, Henrik Anders; Tetzlaff, Tom

    2014-01-01

    suggested to be at the root of this phenomenon, we here demonstrate a possible origin of such power laws in the biophysical properties of single neurons described by the standard cable equation. Taking advantage of the analytical tractability of the so called ball and stick neuron model, we derive general...... expressions for the PSD transfer functions for a set of measures of neuronal activity: the soma membrane current, the current-dipole moment (corresponding to the single-neuron EEG contribution), and the soma membrane potential. These PSD transfer functions relate the PSDs of the respective measurements...... to the PSDs of the noisy input currents. With homogeneously distributed input currents across the neuronal membrane we find that all PSD transfer functions express asymptotic high-frequency [Formula: see text] power laws with power-law exponents analytically identified as [Formula: see text] for the soma...

  6. 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.

  7. 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.

  8. What the training of a neuronal network optimizes.

    Science.gov (United States)

    Tabor, Zbisław

    2007-09-01

    In the study a model of training of neuronal networks built of integrate-and-fire neurons is investigated. Neurons are assembled into complex networks of Watts-Strogatz type. Every neuronal network contains a single receptor neuron. The receptor neuron, stimulated by an external signal, evokes spikes in equal time intervals. The spikes generated by the receptor neuron induce subsequent activity of a whole network. The depolarization signals, traveling the network, modify synaptic couplings according to a kick-and-delay rule, whose process is termed "training." It is shown that the training decreases the mean length of paths along which a depolarization signal is transmitted from the receptor neuron. Consequently, the training also decreases the reaction time and the energy expense necessary for the network to react to the external stimulus. It is shown that the initial distribution of synaptic couplings crucially determines the performance of trained networks.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. The nigrostriatal pathway in the rat: A single-axon study of the relationship between dorsal and ventral tier nigral neurons and the striosome/matrix striatal compartments.

    Science.gov (United States)

    Prensa, L; Parent, A

    2001-09-15

    Axons from dorsal/ventral tiers of substantia nigra pars compacta (SNc), ventral tegmental area (VTA), and retrorubral field (RRF) were traced after injecting their cell body with biotinylated dextran amine. Fifty-three single axons were reconstructed from serial sagittal sections with a camera lucida, and mu-opiate receptor immunostaining served to differentiate the striosome/matrix striatal compartments. Most dorsal tier SNc axons terminate within the matrix of the dorsal striatum, but their patterns of arborization vary markedly; some axons innervate one specific matriceal area, whereas others arborize in multiple discontinuous loci. Some dorsal tier SNc axons also project to both striosomes and matrix. Other dorsal tier SNc axons, as well as VTA axons, innervate the ventral striatum and send collaterals to striosomes lying ventrally in the dorsal striatum or to the ventral sector of the subcallosal streak (SS). Ventral tier SNc axons arborize principally in striosomes, but some ramify in both compartments or in striosomes and the SS. Ventral tier neurons that form deep clusters in substantia nigra pars reticulata innervate principally the matrix and the SS. The amygdala and ventral pallidum receive secondary collaterals from striatal axons of dorsal/ventral tier neurons or RRF neurons. The subthalamic nucleus receives collaterals from striatal axons of SNc clustered neurons, whereas the globus pallidus gets collaterals from striatal axons of dorsal/ventral tier SNc neurons. These findings reveal that the nigrostriatal pathway is composed of several neuronal subsystems, each endowed with a widely distributed axonal arborization that allows them to exert a multifaceted influence on striatal and/or extrastriatal structures.

  17. Differing effects of attention in single-units and populations are well predicted by heterogeneous tuning and the normalization model of attention.

    Science.gov (United States)

    Hara, Yuko; Pestilli, Franco; Gardner, Justin L

    2014-01-01

    Single-unit measurements have reported many different effects of attention on contrast-response (e.g., contrast-gain, response-gain, additive-offset dependent on visibility), while functional imaging measurements have more uniformly reported increases in response across all contrasts (additive-offset). The normalization model of attention elegantly predicts the diversity of effects of attention reported in single-units well-tuned to the stimulus, but what predictions does it make for more realistic populations of neurons with heterogeneous tuning? Are predictions in accordance with population-scale measurements? We used functional imaging data from humans to determine a realistic ratio of attention-field to stimulus-drive size (a key parameter for the model) and predicted effects of attention in a population of model neurons with heterogeneous tuning. We found that within the population, neurons well-tuned to the stimulus showed a response-gain effect, while less-well-tuned neurons showed a contrast-gain effect. Averaged across the population, these disparate effects of attention gave rise to additive-offsets in contrast-response, similar to reports in human functional imaging as well as population averages of single-units. Differences in predictions for single-units and populations were observed across a wide range of model parameters (ratios of attention-field to stimulus-drive size and the amount of baseline response modifiable by attention), offering an explanation for disparity in physiological reports. Thus, by accounting for heterogeneity in tuning of realistic neuronal populations, the normalization model of attention can not only predict responses of well-tuned neurons, but also the activity of large populations of neurons. More generally, computational models can unify physiological findings across different scales of measurement, and make links to behavior, but only if factors such as heterogeneous tuning within a population are properly accounted for.

  18. 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.

  19. 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

  20. 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.

  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. 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.

  3. 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.

  4. 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.

  5. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  7. 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.

  8. WINKLER'S SINGLE-PARAMETER SUBGRADE MODEL FROM ...

    African Journals Online (AJOL)

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    SUBGRADE MODELING. Asrat Worku. Department of ... The models give consistently larger stiffness for the Winkler springs as compared to previously proposed similar continuum-based models that ignore the lateral stresses. ...... (ν = 0.25 and E = 40MPa); (b) a medium stiff clay (ν = 0.45 and E = 50MPa). In contrast to this, ...

  9. 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.

  10. A single exposure to alcohol during brain development induces microencephaly and neuronal losses in genetically susceptible mice, but not in wild type mice.

    Science.gov (United States)

    de Licona, Hannah Klein; Karacay, Bahri; Mahoney, Jo; McDonald, Elizabeth; Luang, Thirath; Bonthius, Daniel J

    2009-05-01

    Maternal alcohol abuse during pregnancy can damage the fetal brain and lead to fetal alcohol syndrome (FAS). Despite public warnings discouraging alcohol use during pregnancy, many pregnant women continue to drink intermittently because they do not believe that occasional exposures to alcohol can be harmful to a fetus. However, because of genetic differences, some fetuses are much more susceptible than others to alcohol-induced brain injury. Thus, a relatively low quantity of alcohol that may be innocuous to most fetuses could damage a genetically susceptible fetus. Neuronal nitric oxide synthase (nNOS) can protect developing mouse neurons against alcohol toxicity by synthesizing neuroprotective nitric oxide. This study examined whether a single exposure to alcohol, which causes no evident injury in wild type mice, can damage the brains of mice genetically deficient for nNOS (nNOS-/- mice). Wild type and nNOS-/- mice received intraperitoneal injections of alcohol (0.0, 2.2, or 4.4mg/g body weight) either as a single dose on postnatal day (PD) 4 or as repeated daily doses over PD4-9. Brain volumes and neuronal numbers within the hippocampus and cerebral cortex were determined on PD10. Alcohol exposure on PD4-9 restricted brain growth and caused neuronal death in both strains of mice, but the severity of microencephaly and neuronal loss were more severe in the nNOS-/- mice than in wild type. The 4.4 mg/g alcohol dose administered on PD4 alone caused significant neuronal loss and microencephaly in the nNOS-/- mice, while this same dose caused no evident injury in the wild type mice. Thus, during development, a single exposure to alcohol can injure a genetically vulnerable brain, while it leaves a wild type brain unaffected. Since the genes that confer alcohol resistance and vulnerability in developing humans are unknown, any particular human fetus is potentially vulnerable. Thus, women should be counseled to consume no alcohol during pregnancy.

  11. 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.

  12. 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

  13. 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

  14. Single-cluster dynamics for the random-cluster model

    NARCIS (Netherlands)

    Deng, Y.; Qian, X.; Blöte, H.W.J.

    2009-01-01

    We formulate a single-cluster Monte Carlo algorithm for the simulation of the random-cluster model. This algorithm is a generalization of the Wolff single-cluster method for the q-state Potts model to noninteger values q>1. Its results for static quantities are in a satisfactory agreement with those

  15. 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...

  16. 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)

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Loss of Ca(2+)-permeable AMPA receptors in synapses of tonic firing substantia gelatinosa neurons in the chronic constriction injury model of neuropathic pain.

    Science.gov (United States)

    Chen, Yishen; Derkach, Victor A; Smith, Peter A

    2016-05-01

    Synapses transmitting nociceptive information in the spinal dorsal horn undergo enduring changes following peripheral nerve injury. Indeed, such injury alters the expression of the GluA2 subunit of glutamatergic AMPA receptors (AMPARs) in the substantia gelatinosa and this predicts altered channel conductance and calcium permeability, leading to an altered function of excitatory synapses. We therefore investigated the functional properties of synaptic AMPA receptors in rat substantia gelatinosa neurons following 10-20d chronic constriction injury (CCI) of the sciatic nerve; a model of neuropathic pain. We measured their single-channel conductance and sensitivity to a blocker of calcium permeable AMPA receptors (CP-AMPARs), IEM1460 (50μM). In putative inhibitory, tonic firing neurons, CCI reduced the average single-channel conductance of synaptic AMPAR from 14.4±3.5pS (n=12) to 9.2±1.0pS (n=10, pinjury acting at synapses of inhibitory neurons to reduce their drive and therefore inhibitory tone in the spinal cord, therefore contributing to the central sensitization associated with neuropathic pain. Copyright © 2016 Elsevier Inc. All rights reserved.

  3. Spiking Activity of a LIF Neuron in Distributed Delay Framework

    Directory of Open Access Journals (Sweden)

    Saket Kumar Choudhary

    2016-06-01

    Full Text Available Evolution of membrane potential and spiking activity for a single leaky integrate-and-fire (LIF neuron in distributed delay framework (DDF is investigated. DDF provides a mechanism to incorporate memory element in terms of delay (kernel function into a single neuron models. This investigation includes LIF neuron model with two different kinds of delay kernel functions, namely, gamma distributed delay kernel function and hypo-exponential distributed delay kernel function. Evolution of membrane potential for considered models is studied in terms of stationary state probability distribution (SPD. Stationary state probability distribution of membrane potential (SPDV for considered neuron models are found asymptotically similar which is Gaussian distributed. In order to investigate the effect of membrane potential delay, rate code scheme for neuronal information processing is applied. Firing rate and Fano-factor for considered neuron models are calculated and standard LIF model is used for comparative study. It is noticed that distributed delay increases the spiking activity of a neuron. Increase in spiking activity of neuron in DDF is larger for hypo-exponential distributed delay function than gamma distributed delay function. Moreover, in case of hypo-exponential delay function, a LIF neuron generates spikes with Fano-factor less than 1.

  4. 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.

  5. 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

  6. Single-layer model for surface roughness.

    Science.gov (United States)

    Carniglia, C K; Jensen, D G

    2002-06-01

    Random roughness of an optical surface reduces its specular reflectance and transmittance by the scattering of light. The reduction in reflectance can be modeled by a homogeneous layer on the surface if the refractive index of the layer is intermediate to the indices of the media on either side of the surface. Such a layer predicts an increase in the transmittance of the surface and therefore does not provide a valid model for the effects of scatter on the transmittance. Adding a small amount of absorption to the layer provides a model that predicts a reduction in both reflectance and transmittance. The absorbing layer model agrees with the predictions of a scalar scattering theory for a layer with a thickness that is twice the rms roughness of the surface. The extinction coefficient k for the layer is proportional to the thickness of the layer.

  7. 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.

  8. 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.

  9. 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.

  10. Patterns of spontaneous activity in single rat olfactory receptor neurons are different in normally breathing and tracheotomized animals

    Czech Academy of Sciences Publication Activity Database

    Duchamp-Viret, P.; Košťál, Lubomír; Chaput, M.; Lánský, Petr; Rospars, J. P.

    2005-01-01

    Roč. 65, č. 2 (2005), s. 97-114 ISSN 0022-3034 R&D Projects: GA AV ČR(CZ) 1ET400110401 Grant - others:Barrande(FR) 9146 QL Institutional research plan: CEZ:AV0Z50110509 Keywords : olfactory neurons * unit activity * receptors Subject RIV: ED - Physiology Impact factor: 4.170, year: 2005

  11. 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

  12. 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.

  13. 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

  14. 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

  15. A phase plane analysis of neuron-astrocyte interactions.

    Science.gov (United States)

    Amiri, Mahmood; Montaseri, Ghazal; Bahrami, Fariba

    2013-08-01

    Intensive experimental studies have shown that astrocytes are active partners in modulation of synaptic transmission. In the present research, we study neuron-astrocyte signaling using a biologically inspired model of one neuron synapsing one astrocyte. In this model, the firing dynamics of the neuron is described by the Morris-Lecar model and the Ca(2+) dynamics of a single astrocyte explained by a functional model introduced by Postnov and colleagues. Using the coupled neuron-astrocyte model and based on the results of the phase plane analyses, it is demonstrated that the astrocyte is able to activate the silent neuron or change the neuron spiking frequency through bidirectional communication. This suggests that astrocyte feedback signaling is capable of modulating spike transmission frequency by changing neuron spiking frequency. This effect is described by a saddle-node on invariant circle bifurcation in the coupled neuron-astrocyte model. In this way, our results suggest that the neuron-astrocyte crosstalk has a fundamental role in producing diverse neuronal activities and therefore enhances the information processing capabilities of the brain. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

  16. 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:

  17. 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.

  18. 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.

  19. 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

  20. 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.

  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. 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.

  3. 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)

  4. 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'.

  5. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1996-12-31

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

  7. 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

  8. 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.

  9. 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.

  10. General single phase wellbore flow model

    Energy Technology Data Exchange (ETDEWEB)

    Ouyang, Liang-Biao; Arbabi, S.; Aziz, K.

    1997-02-05

    A general wellbore flow model, which incorporates not only frictional, accelerational and gravitational pressure drops, but also the pressure drop caused by inflow, is presented in this report. The new wellbore model is readily applicable to any wellbore perforation patterns and well completions, and can be easily incorporated in reservoir simulators or analytical reservoir inflow models. Three dimensionless numbers, the accelerational to frictional pressure gradient ratio R{sub af}, the gravitational to frictional pressure gradient ratio R{sub gf}, and the inflow-directional to accelerational pressure gradient ratio R{sub da}, have been introduced to quantitatively describe the relative importance of different pressure gradient components. For fluid flow in a production well, it is expected that there may exist up to three different regions of the wellbore: the laminar flow region, the partially-developed turbulent flow region, and the fully-developed turbulent flow region. The laminar flow region is located near the well toe, the partially-turbulent flow region lies in the middle of the wellbore, while the fully-developed turbulent flow region is at the downstream end or the heel of the wellbore. Length of each region depends on fluid properties, wellbore geometry and flow rate. As the distance from the well toe increases, flow rate in the wellbore increases and the ratios R{sub af} and R{sub da} decrease. Consequently accelerational and inflow-directional pressure drops have the greatest impact in the toe region of the wellbore. Near the well heel the local wellbore flow rate becomes large and close to the total well production rate, here R{sub af} and R{sub da} are small, therefore, both the accelerational and inflow-directional pressure drops can be neglected.

  11. 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.

  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. 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 diagram which exhibits a giant percolation cluster below some critical value mC of the excitability. We describe the main characteristics of the original model and derive extensions according to additional relevant biological features. Firstly, we investigate the effects of an excitability variability on the phase diagram and show that the percolation transition can be destroyed by a sufficient amount of such a disorder; we stress the weakly averaging character of the order parameter and show that connectivity and excitability can be seen as two overlapping aspects of the same reality. Secondly, we elaborate a discrete time stochastic model taking into account the decay originating from ionic leakage through the membrane of neurons and synaptic depression; we give evidence that the decay softens and shifts the transition, and conjecture than decay destroys the transition in the thermodynamical limit. We were able to develop mean-field theories associated with each of the two effects; we discuss the framework of their agreement with Monte Carlo simulations. It turns out that the the critical point mC from which information on the connectivity of the network can be inferred is affected by each of these additional effects. Lastly, we show how dynamical simulations of bursts with an adaptive exponential integrateand- fire model can be interpreted in terms of Quorum Percolation. Moreover, the usefulness of the percolation model including the set of sophistication we investigated can be extended to many scientific fields involving information propagation, such as the spread of rumors in sociology, ethology, ecology.

  15. Single-molecule folding mechanisms of the apo- and Mg2+-bound states of human neuronal calcium sensor-1

    DEFF Research Database (Denmark)

    Naqvi, Mohsin M; Heiðarsson, Pétur Orri; Otazo, Mariela R

    2015-01-01

    Neuronal calcium sensor-1 (NCS-1) is the primordial member of a family of proteins responsible primarily for sensing changes in neuronal Ca(2+) concentration. NCS-1 is a multispecific protein interacting with a number of binding partners in both calcium-dependent and independent manners, and acting...... in a variety of cellular processes in which it has been linked to a number of disorders such as schizophrenia and autism. Despite extensive studies on the Ca(2+)-activated state of NCS proteins, little is known about the conformational dynamics of the Mg(2+)-bound and apo states, both of which are populated...... by populating one intermediate state consisting of a folded C-domain and an unfolded N-domain. The interconversion at equilibrium between the different molecular states populated by NCS-1 was monitored in real time through constant-force measurements and the energy landscapes underlying the observed transitions...

  16. Modelling a singly resonant, intracavity ring optical parametric oscillator

    DEFF Research Database (Denmark)

    Buchhave, Preben; Tidemand-Lichtenberg, Peter; Wei, Hou

    2003-01-01

    We study theoretically and experimentally the dynamics of a single-frequency, unidirectional ring laser with an intracavity nonlinear singly resonant OPO-crystal in a coupled resonator. We find for a range of operating conditions good agreement between model results and measurements of the laser...

  17. Homology modelling and bivalent single-chain Fv construction of ...

    Indian Academy of Sciences (India)

    Homology modelling and bivalent single-chain Fv construction of anti-HepG2 single-chain immunoglobulin Fv fragments from a phage display library ... Department of Infectious Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China; Department of ...

  18. 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

  19. 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.

  20. Long-term neuronal damage and recovery after a single dose of MDMA: expression and distribution of serotonin transporter in the rat brain.

    Science.gov (United States)

    Kirilly, Eszter

    2010-09-01

    "Ecstasy", 3,4-methylenedioxymethamphetamine (MDMA), an amphetamine analogue is one of the most widely used recreational drugs. In spite of the fact that neurotoxic effects of MDMA has been found in several species from rodents to non-human primates, and results increasingly point to damage also in human MDMA users, data about the sensitivity of different brain areas and the recovery after neuronal damage are scarce. Serotonin transporter (5-HTT) mRNA in the raphe nuclei also has not been examined. Humans with genetic predisposition for the slow metabolism of MDMA, the so-called "poor metabolizers" of debrisoquin are at higher risk. Five- 9% of the Caucasian population is considered to carry this phenotype. These studies were carried out in Dark Agouti rats, a special strain that show decreased microsomal CYP2D1 isoenzyme activity, and thus may serve as a model of vulnerable human users. These works were designed to characterize MDMA-induced damage and recovery of the serotonergic system including sleep and morphological changes within 180 days. In our experiments we investigated the 5-HTT mRNA expression in the brainstem and medullary raphe nuclei, 5-HTT immunoreactive (IR) fibre densities in several brain areas, and 16 functional measures of sleep in response to a single dose of +/- MDMA (15mg\\kg). Furthermore, behavioural experiments were performed 21 days after MDMA treatment. We found similar changes in 5-HTT mRNA expression in the examined raphe nuclei, namely transient increases 7 days after MDMA treatment followed by transient decreases at 21 days. Significant (20-40%), widespread reductions in 5-HTT-IR fibre density were detected in most brain areas at 7 and 21 days after MDMA administration. All cortical, but only some brainstem areas were damaged. Parallel to the neuronal damage we observed significant reductions in rapid eye movement (REM) sleep latency, increased fragmentation of sleep and increases in delta power spectra in non-REM sleep. At 180 days

  1. Single particle degrees of freedom in the interacting boson model

    NARCIS (Netherlands)

    Scholten, O.

    1985-01-01

    An overview is given of different aspects of the Interacting Boson Fermion Model, the extension of the interacting Boson Model to odd mass nuclei. The microscopic model for the coupling of single-particle degrees of freedom to the system of bosons is outlined and the interaction between the bosons

  2. Numerical study of a cylinder model of the diffusion MRI signal for neuronal dendrite trees

    Science.gov (United States)

    Van Nguyen, Dang; Grebenkov, Denis; Le Bihan, Denis; Li, Jing-Rebecca

    2015-03-01

    We study numerically how the neuronal dendrite tree structure can affect the diffusion magnetic resonance imaging (dMRI) signal in brain tissue. For a large set of randomly generated dendrite trees, synthetic dMRI signals are computed and fitted to a cylinder model to estimate the effective longitudinal diffusivity DL in the direction of neurites. When the dendrite branches are short compared to the diffusion length, DL depends significantly on the ratio between the average branch length and the diffusion length. In turn, DL has very weak dependence on the distribution of branch lengths and orientations of a dendrite tree, and the number of branches per node. We conclude that the cylinder model which ignores the connectivity of the dendrite tree, can still be adapted to describe the apparent diffusion coefficient in brain tissue.

  3. Homoclinic bifurcation in a Hodgkin-Huxley model of thermally sensitive neurons

    International Nuclear Information System (INIS)

    Feudel, Ulrike; Neiman, Alexander; Pei, Xing; Wojtenek, Winfried; Braun, Hans; Huber, Martin; Moss, Frank

    2000-01-01

    We study global bifurcations of the chaotic attractor in a modified Hodgkin-Huxley model of thermally sensitive neurons. The control parameter for this model is the temperature. The chaotic behavior is realized over a wide range of temperatures and is visualized using interspike intervals. We observe an abrupt increase of the interspike intervals in a certain temperature region. We identify this as a homoclinic bifurcation of a saddle-focus fixed point which is embedded in the chaotic attractors. The transition is accompanied by intermittency, which obeys a universal scaling law for the average length of trajectory segments exhibiting only short interspike intervals with the distance from the onset of intermittency. We also present experimental results of interspike interval measurements taken from the crayfish caudal photoreceptor, which qualitatively demonstrate the same bifurcation structure. (c) 2000 American Institute of Physics

  4. Homoclinic bifurcation in a Hodgkin-Huxley model of thermally sensitive neurons

    Energy Technology Data Exchange (ETDEWEB)

    Feudel, Ulrike [Department of Physics, University of Potsdam, Potsdam 14415, (Germany); Neiman, Alexander [Center for Neurodynamics, University of Missouri at St. Louis, St. Louis, Missouri 63121 (United States); Pei, Xing [Center for Neurodynamics, University of Missouri at St. Louis, St. Louis, Missouri 63121 (United States); Wojtenek, Winfried [Center for Neurodynamics, University of Missouri at St. Louis, St. Louis, Missouri 63121 (United States); Braun, Hans [Institute of Physiology, University of Marburg, Marburg 35037, (Germany); Huber, Martin [Institute of Physiology, University of Marburg, Marburg 35037, (Germany); Moss, Frank [Center for Neurodynamics, University of Missouri at St. Louis, St. Louis, Missouri 63121 (United States)

    2000-03-01

    We study global bifurcations of the chaotic attractor in a modified Hodgkin-Huxley model of thermally sensitive neurons. The control parameter for this model is the temperature. The chaotic behavior is realized over a wide range of temperatures and is visualized using interspike intervals. We observe an abrupt increase of the interspike intervals in a certain temperature region. We identify this as a homoclinic bifurcation of a saddle-focus fixed point which is embedded in the chaotic attractors. The transition is accompanied by intermittency, which obeys a universal scaling law for the average length of trajectory segments exhibiting only short interspike intervals with the distance from the onset of intermittency. We also present experimental results of interspike interval measurements taken from the crayfish caudal photoreceptor, which qualitatively demonstrate the same bifurcation structure. (c) 2000 American Institute of Physics.

  5. Dream interpretation, affect, and the theory of neuronal group selection: Freud, Winnicott, Bion, and Modell.

    Science.gov (United States)

    Shields, Walker

    2006-12-01

    The author uses a dream specimen as interpreted during psychoanalysis to illustrate Modell's hypothesis that Edelman's theory of neuronal group selection (TNGS) may provide a valuable neurobiological model for Freud's dynamic unconscious, imaginative processes in the mind, the retranscription of memory in psychoanalysis, and intersubjective processes in the analytic relationship. He draws parallels between the interpretation of the dream material with keen attention to affect-laden meanings in the evolving analytic relationship in the domain of psychoanalysis and the principles of Edelman's TNGS in the domain of neurobiology. The author notes how this correlation may underscore the importance of dream interpretation in psychoanalysis. He also suggests areas for further investigation in both realms based on study of their interplay.

  6. 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.

  7. Mixture of Regression Models with Single-Index

    OpenAIRE

    Xiang, Sijia; Yao, Weixin

    2016-01-01

    In this article, we propose a class of semiparametric mixture regression models with single-index. We argue that many recently proposed semiparametric/nonparametric mixture regression models can be considered special cases of the proposed model. However, unlike existing semiparametric mixture regression models, the new pro- posed model can easily incorporate multivariate predictors into the nonparametric components. Backfitting estimates and the corresponding algorithms have been proposed for...

  8. Dipeptide Piracetam Analogue Noopept Improves Viability of Hippocampal HT-22 Neurons in the Glutamate Toxicity Model.

    Science.gov (United States)

    Antipova, T A; Nikolaev, S V; Ostrovskaya, P U; Gudasheva, T A; Seredenin, S B

    2016-05-01

    Effect of noopept (N-phenylacetyl-prolylglycine ethyl ester) on viability of neurons exposed to neurotoxic action of glutamic acid (5 mM) was studied in vitro in immortalized mouse hippocampal HT-22 neurons. Noopept added to the medium before or after glutamic acid improved neuronal survival in a concentration range of 10-11-10-5 M. Comparison of the effective noopept concentrations determined in previous studies on cultured cortical and cerebellar neurons showed that hippocampal neurons are more sensitive to the protective effect of noopept.

  9. 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.

  10. 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.

  11. 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.

  12. The Chihuahua dog: A new animal model for neuronal ceroid lipofuscinosis CLN7 disease?

    Science.gov (United States)

    Faller, Kiterie M E; Bras, Jose; Sharpe, Samuel J; Anderson, Glenn W; Darwent, Lee; Kun-Rodrigues, Celia; Alroy, Joseph; Penderis, Jacques; Mole, Sara E; Gutierrez-Quintana, Rodrigo; Guerreiro, Rita J

    2016-04-01

    Neuronal ceroid lipofuscinoses (NCLs) are a group of incurable lysosomal storage disorders characterized by neurodegeneration and accumulation of lipopigments mainly within the neurons. We studied two littermate Chihuahua dogs presenting with progressive signs of blindness, ataxia, pacing, and cognitive impairment from 1 year of age. Because of worsening of clinical signs, both dogs were euthanized at about 2 years of age. Postmortem examination revealed marked accumulation of autofluorescent intracellular inclusions within the brain, characteristic of NCL. Whole-genome sequencing was performed on one of the affected dogs. After sequence alignment and variant calling against the canine reference genome, variants were identified in the coding region or splicing regions of four previously known NCL genes (CLN6, ARSG, CLN2 [=TPP1], and CLN7 [=MFSD8]). Subsequent segregation analysis within the family (two affected dogs, both parents, and three relatives) identified MFSD8:p.Phe282Leufs13*, which had previously been identified in one Chinese crested dog with no available ancestries, as the causal mutation. Because of the similarities of the clinical signs and histopathological changes with the human form of the disease, we propose that the Chihuahua dog could be a good animal model of CLN7 disease. © 2016 Wiley Periodicals, Inc.

  13. Tanshinone inhibits neuronal cell apoptosis and inflammatory response in cerebral infarction rat model.

    Science.gov (United States)

    Zhou, Liang; Zhang, Jie; Wang, Chao; Sun, Qiangsan

    2017-06-01

    We aimed to investigate the effect and mechanisms of tanshinone (TSN) IIA in cerebral infarction. The cerebral infarction rat model was established by middle cerebral artery occlusion (MCAO). After pretreatment with TSN, cerebral infarct volume, cerebral edema, and neurological deficits score were evaluated, as well as cell apoptosis in hippocampus and cortex of the brain was examined with terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) and the levels of interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and C-reactive protein (CRP) were determined by Enzyme-Linked Immunosorbent Assay (ELISA). In addition, rat primary neuronal cells were isolated and cultured in oxygen-glucose deprivation (OGD) conditions. After pretreatment with TSN, cell viability and apoptosis were observed by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and flow cytometry analysis, respectively. The expressions of Bax and B-cell lymphoma 2 (Bcl-2) were detected by quantitative reverse transcription polymerase chain reaction (qRT-PCR) and western blotting. Compared with untreated cerebral infarction rat, TSN treatment significantly reduced cerebral infarct volume, cerebral edema, and neurological deficits score ( P TSN ( P TSN remarkably increased cell viability and inhibited cell apoptosis ratio ( P TSN significantly downregulated the expression of Bax and upregulated Bcl-2 ( P TSN IIA has a preventive effect on cerebral infarction by inhibiting neuronal cell apoptosis and inflammatory response in vitro and in vivo.

  14. The interspike interval of a cable model neuron with white noise input.

    Science.gov (United States)

    Tuckwell, H C; Wan, F Y; Wong, Y S

    1984-01-01

    The firing time of a cable model neuron in response to white noise current injection is investigated with various methods. The Fourier decomposition of the depolarization leads to partial differential equations for the moments of the firing time. These are solved by perturbation and numerical methods, and the results obtained are in excellent agreement with those obtained by Monte Carlo simulation. The convergence of the random Fourier series is found to be very slow for small times so that when the firing time is small it is more efficient to simulate the solution of the stochastic cable equation directly using the two different representations of the Green's function, one which converges rapidly for small times and the other which converges rapidly for large times. The shape of the interspike interval density is found to depend strongly on input position. The various shapes obtained for different input positions resemble those for real neurons. The coefficient of variation of the interspike interval decreases monotonically as the distance between the input and trigger zone increases. A diffusion approximation for a nerve cell receiving Poisson input is considered and input/output frequency relations obtained for different input sites. The cases of multiple trigger zones and multiple input sites are briefly discussed.

  15. Pharmacological Inhibition of Necroptosis Protects from Dopaminergic Neuronal Cell Death in Parkinson’s Disease Models

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    Angelo Iannielli

    2018-02-01

    Full Text Available Dysfunctions in mitochondrial dynamics and metabolism are common pathological processes associated with Parkinson’s disease (PD. It was recently shown that an inherited form of PD and dementia is caused by mutations in the OPA1 gene, which encodes for a key player in mitochondrial fusion and structure. iPSC-derived neural cells from these patients exhibited severe mitochondrial fragmentation, respiration impairment, ATP deficits, and heightened oxidative stress. Reconstitution of normal levels of OPA1 in PD-derived neural cells normalized mitochondria morphology and function. OPA1-mutated neuronal cultures showed reduced survival in vitro. Intriguingly, selective inhibition of necroptosis effectively rescued this survival deficit. Additionally, dampening necroptosis in MPTP-treated mice protected from DA neuronal cell loss. This human iPSC-based model captures both early pathological events in OPA1 mutant neural cells and the beneficial effects of blocking necroptosis, highlighting this cell death process as a potential therapeutic target for PD.

  16. The Limited Utility of Multiunit Data in Differentiating Neuronal Population Activity.

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    Corey J Keller

    Full Text Available To date, single neuron recordings remain the gold standard for monitoring the activity of neuronal populations. Since obtaining single neuron recordings is not always possible, high frequency or 'multiunit activity' (MUA is often used as a surrogate. Although MUA recordings allow one to monitor the activity of a large number of neurons, they do not allow identification of specific neuronal subtypes, the knowledge of which is often critical for understanding electrophysiological processes. Here, we explored whether prior knowledge of the single unit waveform of specific neuron types is sufficient to permit the use of MUA to monitor and distinguish differential activity of individual neuron types. We used an experimental and modeling approach to determine if components of the MUA can monitor medium spiny neurons (MSNs and fast-spiking interneurons (FSIs in the mouse dorsal striatum. We demonstrate that when well-isolated spikes are recorded, the MUA at frequencies greater than 100Hz is correlated with single unit spiking, highly dependent on the waveform of each neuron type, and accurately reflects the timing and spectral signature of each neuron. However, in the absence of well-isolated spikes (the norm in most MUA recordings, the MUA did not typically contain sufficient information to permit accurate prediction of the respective population activity of MSNs and FSIs. Thus, even under ideal conditions for the MUA to reliably predict the moment-to-moment activity of specific local neuronal ensembles, knowledge of the spike waveform of the underlying neuronal populations is necessary, but not sufficient.

  17. The Docosanoid Neuroprotectin D1 Induces TH-Positive Neuronal Survival in a Cellular Model of Parkinson's Disease.

    Science.gov (United States)

    Calandria, Jorgelina M; Sharp, Michelle W; Bazan, Nicolas G

    2015-11-01

    Parkinson's disease (PD) does not manifest clinically until 80 % of striatal dopamine is reduced, thus most neuronal damage takes place before the patient presents clinical symptoms. Therefore, it is important to develop preventive strategies for this disease. In the experimental models of PD, 1-methyl-4-phenylpyridinium ion (MPP+) and rotenone induce toxicity in dopaminergic neurons. Neuroprotectin D1 (NPD1) displays neuroprotection in cells undergoing proteotoxic and oxidative stress. In the present report, we established an in vitro model using a primary neuronal culture from mesencephalic embryonic mouse tissue in which 17-20 % of neurons were TH-positive when differentiated in vitro. NPD1 (100 nM) rescued cells from apoptosis induced by MPP+ and rotenone, and the dendritic arbor of surviving neurons was examined using Sholl analysis. Rotenone, as well as MPP+ and its precursor 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), severely promoted retraction of dendritic arbor distal segments, thus decreasing the maximum branch order reached. On average, NPD1 counteracted the effects of MPP+ on the dendritic arborization, but failed to do so in the rotenone-treated neurons. However, rotenone did decrease the Sholl intersection number from radii 25 to 125 µm, and NPD1 did restore the pattern to control levels. Similarly, NPD1 partially reverted the dendrite retraction caused by MPP+ and MPTP. These results suggest that the apoptosis occurring in mesencephalic TH-positive neurons is not a direct consequence of mitochondrial dysfunction alone and that NPD1 signaling may be counteracting this damage. These findings lay the groundwork for the use of the in vitro model developed for future studies and for the search of specific molecular events that NPD1 targets to prevent early neurodegeneration in PD.

  18. Global Asymptotic Stability for Discrete Single Species Population Models

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    A. Bilgin

    2017-01-01

    Full Text Available We present some basic discrete models in populations dynamics of single species with several age classes. Starting with the basic Beverton-Holt model that describes the change of single species we discuss its basic properties such as a convergence of all solutions to the equilibrium, oscillation of solutions about the equilibrium solutions, Allee’s effect, and Jillson’s effect. We consider the effect of the constant and periodic immigration and emigration on the global properties of Beverton-Holt model. We also consider the effect of the periodic environment on the global properties of Beverton-Holt model.

  19. BarTeL, a Genetically Versatile, Bioluminescent and Granule Neuron Precursor-Targeted Mouse Model for Medulloblastoma.

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    Gregory M Shackleford

    Full Text Available Medulloblastomas are the most common malignant pediatric brain tumor and have been divided into four major molecular subgroups. Animal models that mimic the principal molecular aberrations of these subgroups will be important tools for preclinical studies and allow greater understanding of medulloblastoma biology. We report a new transgenic model of medulloblastoma that possesses a unique combination of desirable characteristics including, among others, the ability to incorporate multiple and variable genes of choice and to produce bioluminescent tumors from a limited number of somatic cells within a normal cellular environment. This model, termed BarTeL, utilizes a Barhl1 homeobox gene promoter to target expression of a bicistronic transgene encoding both the avian retroviral receptor TVA and an eGFP-Luciferase fusion protein to neonatal cerebellar granule neuron precursor (cGNP cells, which are cells of origin for the sonic hedgehog (SHH subgroup of human medulloblastomas. The Barhl1 promoter-driven transgene is expressed strongly in mammalian cGNPs and weakly or not at all in mature granule neurons. We efficiently induced bioluminescent medulloblastomas expressing eGFP-luciferase in BarTeL mice by infection of a limited number of somatic cGNPs with avian retroviral vectors encoding the active N-terminal fragment of SHH and a stabilized MYCN mutant. Detection and quantification of the increasing bioluminescence of growing tumors in young BarTeL mice was facilitated by the declining bioluminescence of their uninfected maturing cGNPs. Inclusion of eGFP in the transgene allowed enriched sorting of cGNPs from neonatal cerebella. Use of a single bicistronic avian vector simultaneously expressing both Shh and Mycn oncogenes increased the medulloblastoma incidence and aggressiveness compared to mixed virus infections. Bioluminescent tumors could also be produced by ex vivo transduction of neonatal BarTeL cerebellar cells by avian retroviruses and

  20. Organization of left–right coordination of neuronal activity in the mammalian spinal cord: Insights from computational modelling

    Science.gov (United States)

    Shevtsova, Natalia A; Talpalar, Adolfo E; Markin, Sergey N; Harris-Warrick, Ronald M; Kiehn, Ole; Rybak, Ilya A

    2015-01-01

    Different locomotor gaits in mammals, such as walking or galloping, are produced by coordinated activity in neuronal circuits in the spinal cord. Coordination of neuronal activity between left and right sides of the cord is provided by commissural interneurons (CINs), whose axons cross the midline. In this study, we construct and analyse two computational models of spinal locomotor circuits consisting of left and right rhythm generators interacting bilaterally via several neuronal pathways mediated by different CINs. The CIN populations incorporated in the models include the genetically identified inhibitory (V0D) and excitatory (V0V) subtypes of V0 CINs and excitatory V3 CINs. The model also includes the ipsilaterally projecting excitatory V2a interneurons mediating excitatory drive to the V0V CINs. The proposed network architectures and CIN connectivity allow the models to closely reproduce and suggest mechanistic explanations for several experimental observations. These phenomena include: different speed-dependent contributions of V0D and V0V CINs and V2a interneurons to left–right alternation of neural activity, switching gaits between the left–right alternating walking-like activity and the left–right synchronous hopping-like pattern in mutants lacking specific neuron classes, and speed-dependent asymmetric changes of flexor and extensor phase durations. The models provide insights into the architecture of spinal network and the organization of parallel inhibitory and excitatory CIN pathways and suggest explanations for how these pathways maintain alternating and synchronous gaits at different locomotor speeds. The models propose testable predictions about the neural organization and operation of mammalian locomotor circuits. Key points Coordination of neuronal activity between left and right sides of the mammalian spinal cord is provided by several sets of commissural interneurons (CINs) whose axons cross the midline. Genetically identified inhibitory V

  1. 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.

  2. The advantage of flexible neuronal tunings in neural network models for motor learning.

    Science.gov (United States)

    Marongelli, Ellisha N; Thoroughman, Kurt A

    2013-01-01

    Human motor adaptation to novel environments is often modeled by a basis function network that transforms desired movement properties into estimated forces. This network employs a layer of nodes that have fixed broad tunings that generalize across the input domain. Learning is achieved by updating the weights of these nodes in response to training experience. This conventional model is unable to account for rapid flexibility observed in human spatial generalization during motor adaptation. However, added plasticity in the widths of the basis function tunings can achieve this flexibility, and several neurophysiological experiments have revealed flexibility in tunings of sensorimotor neurons. We found a model, Locally Weighted Projection Regression (LWPR), which uniquely possesses the structure of a basis function network in which both the weights and tuning widths of the nodes are updated incrementally during adaptation. We presented this LWPR model with training functions of different spatial complexities and monitored incremental updates to receptive field widths. An inverse pattern of dependence of receptive field adaptation on experienced error became evident, underlying both a relationship between generalization and complexity, and a unique behavior in which generalization always narrows after a sudden switch in environmental complexity. These results implicate a model that is flexible in both basis function widths and weights, like LWPR, as a viable alternative model for human motor adaptation that can account for previously observed plasticity in spatial generalization. This theory can be tested by using the behaviors observed in our experiments as novel hypotheses in human studies.

  3. The advantage of flexible neuronal tunings in neural network models for motor learning

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    Ellisha N Marongelli

    2013-07-01

    Full Text Available Human motor adaptation to novel environments is often modeled by a basis function network that transforms desired movement properties into estimated forces. This network employs a layer of nodes that have fixed broad tunings that generalize across the input domain. Learning is achieved by updating the weights of these nodes in response to training experience. This conventional model is unable to account for rapid flexibility observed in human spatial generalization during motor adaptation. However, added plasticity in the breadths of the basis function tunings can achieve this flexibility, and several neurophysiological experiments have revealed flexibility in tunings of sensorimotor neurons. We found a model, Locally Weighted Projection Regression (LWPR, which uniquely possesses the structure of a basis function network in which both the weights and tuning widths of the nodes are updated incrementally during adaptation. We presented this LWPR model with training functions of different spatial complexities and monitored incremental updates to receptive field sizes. An inverse pattern of dependence of receptive field adaptation on experienced error became evident, underlying both a relationship between generalization and complexity, and a unique behavior in which generalization always narrows after a sudden switch in environmental complexity. These results implicate a model with a flexible structure, like LWPR, as a viable alternative model for human motor adaptation that can account for previously observed plasticity in spatial generalization. This theory can be tested by using the behaviors observed in our experiments as novel hypotheses in human studies.

  4. 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.

  5. Eff ect of a single asenapine treatment on Fos expression in the brain catecholamine-synthesizing neurons: impact of a chronic mild stress preconditioning

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    Osacka J.

    2017-04-01

    Full Text Available Objective. Fos protein expression in catecholamine-synthesizing neurons of the substantia nigra (SN pars compacta (SNC, A8, pars reticulata (SNR, A9, and pars lateralis (SNL, the ventral tegmental area (VTA, A10, the locus coeruleus (LC, A6 and subcoeruleus (sLC, the ventrolateral pons (PON-A5, the nucleus of the solitary tract (NTS-A2, the area postrema (AP, and the ventrolateral medulla (VLM-A1 was quantitatively evaluated aft er a single administration of asenapine (ASE (designated for schizophrenia treatment in male Wistar rats preconditioned with a chronic unpredictable variable mild stress (CMS for 21 days. Th e aim of the present study was to reveal whether a single ASE treatment may 1 activate Fos expression in the brain areas selected; 2 activate tyrosine hydroxylase (TH-synthesizing cells displaying Fos presence; and 3 be modulated by CMS preconditioning.

  6. Variance Function Partially Linear Single-Index Models1.

    Science.gov (United States)

    Lian, Heng; Liang, Hua; Carroll, Raymond J

    2015-01-01

    We consider heteroscedastic regression models where the mean function is a partially linear single index model and the variance function depends upon a generalized partially linear single index model. We do not insist that the variance function depend only upon the mean function, as happens in the classical generalized partially linear single index model. We develop efficient and practical estimation methods for the variance function and for the mean function. Asymptotic theory for the parametric and nonparametric parts of the model is developed. Simulations illustrate the results. An empirical example involving ozone levels is used to further illustrate the results, and is shown to be a case where the variance function does not depend upon the mean function.

  7. An approximation to the adaptive exponential integrate-and-fire neuron model allows fast and predictive fitting to physiological data

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    Loreen eHertäg

    2012-09-01

    Full Text Available For large-scale network simulations, it is often desirable to have computationally tractable, yet in a defined sense still physiologically valid neuron models. In particular, these models should be able to reproduce physiological measurements, ideally in a predictive sense, and under different input regimes in which neurons may operate in vivo. Here we present an approach to parameter estimation for a simple spiking neuron model mainly based on standard f-I curves obtained from in vitro recordings. Such recordings are routinely obtained in standard protocols and assess a neuron's response under a wide range of mean input currents. Our fitting procedure makes use of closed-form expressions for the firing rate derived from an approximation to the adaptive exponential integrate-and-fire (AdEx model. The resulting fitting process is simple and about two orders of magnitude faster compared to methods based on numerical integration of the differential equations. We probe this method on different cell types recorded from rodent prefrontal cortex. After fitting to the f-I current-clamp data, the model cells are tested on completely different sets of recordings obtained by fluctuating ('in-vivo-like' input currents. For a wide range of different input regimes, cell types, and cortical layers, the model could predict spike times on these test traces quite accurately within the bounds of physiological reliability, although no information from these distinct test sets was used for model fitting. Further analyses delineated some of the empirical factors constraining model fitting and the model's generalization performance. An even simpler adaptive LIF neuron was also examined in this context. Hence, we have developed a 'high-throughput' model fitting procedure which is simple and fast, with good prediction performance, and which relies only on firing rate information and standard physiological data widely and easily available.

  8. A Single Neonatal Exposure to BMAA in a Rat Model Produces Neuropathology Consistent with Neurodegenerative Diseases

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    Laura Louise Scott

    2017-12-01

    Full Text Available Although cyanobacterial β-N-methylamino-l-alanine (BMAA has been implicated in the development of Alzheimer’s Disease (AD, Parkinson’s Disease (PD and Amyotrophic Lateral Sclerosis (ALS, no BMAA animal model has reproduced all the neuropathology typically associated with these neurodegenerative diseases. We present here a neonatal BMAA model that causes β-amyloid deposition, neurofibrillary tangles of hyper-phosphorylated tau, TDP-43 inclusions, Lewy bodies, microbleeds and microgliosis as well as severe neuronal loss in the hippocampus, striatum, substantia nigra pars compacta, and ventral horn of the spinal cord in rats following a single BMAA exposure. We also report here that BMAA exposure on particularly PND3, but also PND4 and 5, the critical period of neurogenesis in the rodent brain, is substantially more toxic than exposure to BMAA on G14, PND6, 7 and 10 which suggests that BMAA could potentially interfere with neonatal neurogenesis in rats. The observed selective toxicity of BMAA during neurogenesis and, in particular, the observed pattern of neuronal loss observed in BMAA-exposed rats suggest that BMAA elicits its effect by altering dopamine and/or serotonin signaling in rats.

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

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    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

  10. Motor neurons and glia exhibit specific individualized responses to TDP-43 expression in a Drosophila model of amyotrophic lateral sclerosis.

    Science.gov (United States)

    Estes, Patricia S; Daniel, Scott G; McCallum, Abigail P; Boehringer, Ashley V; Sukhina, Alona S; Zwick, Rebecca A; Zarnescu, Daniela C

    2013-05-01

    Amyotrophic lateral sclerosis (ALS) is a fatal disease characterized by complex neuronal and glial phenotypes. Recently, RNA-based mechanisms have been linked to ALS via RNA-binding proteins such as TDP-43, which has been studied in vivo using models ranging from yeast to rodents. We have developed a Drosophila model of ALS based on TDP-43 that recapitulates several aspects of pathology, including motor neuron loss, locomotor dysfunction and reduced survival. Here we report the phenotypic consequences of expressing wild-type and four different ALS-linked TDP-43 mutations in neurons and glia. We show that TDP-43-driven neurodegeneration phenotypes are dose- and age-dependent. In motor neurons, TDP-43 appears restricted to nuclei, which are significantly misshapen due to mutant but not wild-type protein expression. In glia and in the developing neuroepithelium, TDP-43 associates with cytoplasmic puncta. TDP-43-containing RNA granules are motile in cultured motor neurons, although wild-type and mutant variants exhibit different kinetic properties. At the neuromuscular junction, the expression of TDP-43 in motor neurons versus glia leads to seemingly opposite synaptic phenotypes that, surprisingly, translate into comparable locomotor defects. Finally, we explore sleep as a behavioral readout of TDP-43 expression and find evidence of sleep fragmentation consistent with hyperexcitability, a suggested mechanism in ALS. These findings support the notion that although motor neurons and glia are both involved in ALS pathology, at the cellular level they can exhibit different responses to TDP-43. In addition, our data suggest that individual TDP-43 alleles utilize distinct molecular mechanisms, which will be important for developing therapeutic strategies.

  11. Motor neurons and glia exhibit specific individualized responses to TDP-43 expression in a Drosophila model of amyotrophic lateral sclerosis

    Directory of Open Access Journals (Sweden)

    Patricia S. Estes

    2013-05-01

    Amyotrophic lateral sclerosis (ALS is a fatal disease characterized by complex neuronal and glial phenotypes. Recently, RNA-based mechanisms have been linked to ALS via RNA-binding proteins such as TDP-43, which has been studied in vivo using models ranging from yeast to rodents. We have developed a Drosophila model of ALS based on TDP-43 that recapitulates several aspects of pathology, including motor neuron loss, locomotor dysfunction and reduced survival. Here we report the phenotypic consequences of expressing wild-type and four different ALS-linked TDP-43 mutations in neurons and glia. We show that TDP-43-driven neurodegeneration phenotypes are dose- and age-dependent. In motor neurons, TDP-43 appears restricted to nuclei, which are significantly misshapen due to mutant but not wild-type protein expression. In glia and in the developing neuroepithelium, TDP-43 associates with cytoplasmic puncta. TDP-43-containing RNA granules are motile in cultured motor neurons, although wild-type and mutant variants exhibit different kinetic properties. At the neuromuscular junction, the expression of TDP-43 in motor neurons versus glia leads to seemingly opposite synaptic phenotypes that, surprisingly, translate into comparable locomotor defects. Finally, we explore sleep as a behavioral readout of TDP-43 expression and find evidence of sleep fragmentation consistent with hyperexcitability, a suggested mechanism in ALS. These findings support the notion that although motor neurons and glia are both involved in ALS pathology, at the cellular level they can exhibit different responses to TDP-43. In addition, our data suggest that individual TDP-43 alleles utilize distinct molecular mechanisms, which will be important for developing therapeutic strategies.

  12. 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

  13. Methods of Stochastic Analysis of Complex Regimes in the 3D Hindmarsh-Rose Neuron Model

    Science.gov (United States)

    Bashkirtseva, Irina; Ryashko, Lev; Slepukhina, Evdokia

    A problem of the stochastic nonlinear analysis of neuronal activity is studied by the example of the Hindmarsh-Rose (HR) model. For the parametric region of tonic spiking oscillations, it is shown that random noise transforms the spiking dynamic regime into the bursting one. This stochastic phenomenon is specified by qualitative changes in distributions of random trajectories and interspike intervals (ISIs). For a quantitative analysis of the noise-induced bursting, we suggest a constructive semi-analytical approach based on the stochastic sensitivity function (SSF) technique and the method of confidence domains that allows us to describe geometrically a distribution of random states around the deterministic attractors. Using this approach, we develop a new algorithm for estimation of critical values for the noise intensity corresponding to the qualitative changes in stochastic dynamics. We show that the obtained estimations are in good agreement with the numerical results. An interplay between noise-induced bursting and transitions from order to chaos is discussed.

  14. Macro- and micro-chaotic structures in the Hindmarsh-Rose model of bursting neurons

    Energy Technology Data Exchange (ETDEWEB)

    Barrio, Roberto, E-mail: rbarrio@unizar.es; Serrano, Sergio [Computational Dynamics Group, Departamento de Matemática Aplicada, GME and IUMA, Universidad de Zaragoza, E-50009 Zaragoza (Spain); Angeles Martínez, M. [Computational Dynamics Group, GME, Universidad de Zaragoza, E-50009 Zaragoza (Spain); Shilnikov, Andrey [Neuroscience Institute and Department of Mathematics and Statistics, Georgia State University, Atlanta, Georgia 30078 (United States); Department of Computational Mathematics and Cybernetics, Lobachevsky State University of Nizhni Novgorod, 603950 Nizhni Novgorod (Russian Federation)

    2014-06-01

    We study a plethora of chaotic phenomena in the Hindmarsh-Rose neuron model with the use of several computational techniques including the bifurcation parameter continuation, spike-quantification, and evaluation of Lyapunov exponents in bi-parameter diagrams. Such an aggregated approach allows for detecting regions of simple and chaotic dynamics, and demarcating borderlines—exact bifurcation curves. We demonstrate how the organizing centers—points corresponding to codimension-two homoclinic bifurcations—along with fold and period-doubling bifurcation curves structure the biparametric plane, thus forming macro-chaotic regions of onion bulb shapes and revealing spike-adding cascades that generate micro-chaotic structures due to the hysteresis.

  15. Neurocognitive Poetics: methods and models for investigating the neuronal and cognitive- affective bases of literature reception

    Directory of Open Access Journals (Sweden)

    Arthur M Jacobs

    2015-04-01

    Full Text Available A long tradition of research including classical rhetoric, aesthetics and poetics theory, formalism and structuralism, as well as current perspectives in (neurocognitive poetics has investigated structural and functional aspects of literature reception. Despite a wealth of literature published in specialised journals like Poetics, however, still little is known about how the brain processes and creates literary and poetic texts. Still, such stimulus material might be suited better than other genres for demonstrating the complexities with which our brain constructs the world in and around us, because it unifies thought and lan