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Sample records for integrate-and-fire neurons connected

  1. A VLSI recurrent network of integrate-and-fire neurons connected by plastic synapses with long-term memory.

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    Chicca, E; Badoni, D; Dante, V; D'Andreagiovanni, M; Salina, G; Carota, L; Fusi, S; Del Giudice, P

    2003-01-01

    Electronic neuromorphic devices with on-chip, on-line learning should be able to modify quickly the synaptic couplings to acquire information about new patterns to be stored (synaptic plasticity) and, at the same time, preserve this information on very long time scales (synaptic stability). Here, we illustrate the electronic implementation of a simple solution to this stability-plasticity problem, recently proposed and studied in various contexts. It is based on the observation that reducing the analog depth of the synapses to the extreme (bistable synapses) does not necessarily disrupt the performance of the device as an associative memory, provided that 1) the number of neurons is large enough; 2) the transitions between stable synaptic states are stochastic; and 3) learning is slow. The drastic reduction of the analog depth of the synaptic variable also makes this solution appealing from the point of view of electronic implementation and offers a simple methodological alternative to the technological solution based on floating gates. We describe the full custom analog very large-scale integration (VLSI) realization of a small network of integrate-and-fire neurons connected by bistable deterministic plastic synapses which can implement the idea of stochastic learning. In the absence of stimuli, the memory is preserved indefinitely. During the stimulation the synapse undergoes quick temporary changes through the activities of the pre- and postsynaptic neurons; those changes stochastically result in a long-term modification of the synaptic efficacy. The intentionally disordered pattern of connectivity allows the system to generate a randomness suited to drive the stochastic selection mechanism. We check by a suitable stimulation protocol that the stochastic synaptic plasticity produces the expected pattern of potentiation and depression in the electronic network.

  2. Noise adaptation in integrate-and fire neurons.

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    Rudd, M E; Brown, L G

    1997-07-01

    The statistical spiking response of an ensemble of identically prepared stochastic integrate-and-fire neurons to a rectangular input current plus gaussian white noise is analyzed. It is shown that, on average, integrate-and-fire neurons adapt to the root-mean-square noise level of their input. This phenomenon is referred to as noise adaptation. Noise adaptation is characterized by a decrease in the average neural firing rate and an accompanying decrease in the average value of the generator potential, both of which can be attributed to noise-induced resets of the generator potential mediated by the integrate-and-fire mechanism. A quantitative theory of noise adaptation in stochastic integrate-and-fire neurons is developed. It is shown that integrate-and-fire neurons, on average, produce transient spiking activity whenever there is an increase in the level of their input noise. This transient noise response is either reduced or eliminated over time, depending on the parameters of the model neuron. Analytical methods are used to prove that nonleaky integrate-and-fire neurons totally adapt to any constant input noise level, in the sense that their asymptotic spiking rates are independent of the magnitude of their input noise. For leaky integrate-and-fire neurons, the long-run noise adaptation is not total, but the response to noise is partially eliminated. Expressions for the probability density function of the generator potential and the first two moments of the potential distribution are derived for the particular case of a nonleaky neuron driven by gaussian white noise of mean zero and constant variance. The functional significance of noise adaptation for the performance of networks comprising integrate-and-fire neurons is discussed.

  3. Self-organized Criticality and Synchronization in a Pulse-coupled Integrate-and-Fire Neuron Model Based on Small World Networks

    International Nuclear Information System (INIS)

    Lin Min; Chen Tianlun

    2005-01-01

    A lattice model for a set of pulse-coupled integrate-and-fire neurons with small world structure is introduced. We find that our model displays the power-law behavior accompanied with the large-scale synchronized activities among the units. And the different connectivity topologies lead to different behaviors in models of integrate-and-fire neurons.

  4. Integrate-and-fire neurons driven by asymmetric dichotomous noise.

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    Droste, Felix; Lindner, Benjamin

    2014-12-01

    We consider a general integrate-and-fire (IF) neuron driven by asymmetric dichotomous noise. In contrast to the Gaussian white noise usually used in the so-called diffusion approximation, this noise is colored, i.e., it exhibits temporal correlations. We give an analytical expression for the stationary voltage distribution of a neuron receiving such noise and derive recursive relations for the moments of the first passage time density, which allow us to calculate the firing rate and the coefficient of variation of interspike intervals. We study how correlations in the input affect the rate and regularity of firing under variation of the model's parameters for leaky and quadratic IF neurons. Further, we consider the limit of small correlation times and find lowest order corrections to the first passage time moments to be proportional to the square root of the correlation time. We show analytically that to this lowest order, correlations always lead to a decrease in firing rate for a leaky IF neuron. All theoretical expressions are compared to simulations of leaky and quadratic IF neurons.

  5. 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...

  6. Complex Behavior in an Integrate-and-Fire Neuron Model Based on Small World Networks

    International Nuclear Information System (INIS)

    Lin Min; Chen Tianlun

    2005-01-01

    Based on our previously pulse-coupled integrate-and-fire neuron model in small world networks, we investigate the complex behavior of electroencephalographic (EEG)-like activities produced by such a model. We find EEG-like activities have obvious chaotic characteristics. We also analyze the complex behaviors of EEG-like signals, such as spectral analysis, reconstruction of the phase space, the correlation dimension, and so on.

  7. Chimeras in leaky integrate-and-fire neural networks: effects of reflecting connectivities

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    Tsigkri-DeSmedt, Nefeli Dimitra; Hizanidis, Johanne; Schöll, Eckehard; Hövel, Philipp; Provata, Astero

    2017-07-01

    The effects of attracting-nonlocal and reflecting connectivity are investigated in coupled Leaky Integrate-and-Fire (LIF) elements, which model the exchange of electrical signals between neurons. Earlier investigations have demonstrated that repulsive-nonlocal and hierarchical network connectivity can induce complex synchronization patterns and chimera states in systems of coupled oscillators. In the LIF system we show that if the elements are nonlocally linked with positive diffusive coupling on a ring network, the system splits into a number of alternating domains. Half of these domains contain elements whose potential stays near the threshold and they are interrupted by active domains where the elements perform regular LIF oscillations. The active domains travel along the ring with constant velocity, depending on the system parameters. When we introduce reflecting coupling in LIF networks unexpected complex spatio-temporal structures arise. For relatively extensive ranges of parameter values, the system splits into two coexisting domains: one where all elements stay near the threshold and one where incoherent states develop, characterized by multi-leveled mean phase velocity profiles.

  8. Optimal Detection of a Localized Perturbation in Random Networks of Integrate-and-Fire Neurons

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    Bernardi, Davide; Lindner, Benjamin

    2017-06-01

    Experimental and theoretical studies suggest that cortical networks are chaotic and coding relies on averages over large populations. However, there is evidence that rats can respond to the short stimulation of a single cortical cell, a theoretically unexplained fact. We study effects of single-cell stimulation on a large recurrent network of integrate-and-fire neurons and propose a simple way to detect the perturbation. Detection rates obtained from simulations and analytical estimates are similar to experimental response rates if the readout is slightly biased towards specific neurons. Near-optimal detection is attained for a broad range of intermediate values of the mean coupling between neurons.

  9. Leaky Integrate-and-Fire Neuron Circuit Based on Floating-Gate Integrator

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    Kornijcuk, Vladimir; Lim, Hyungkwang; Seok, Jun Yeong; Kim, Guhyun; Kim, Seong Keun; Kim, Inho; Choi, Byung Joon; Jeong, Doo Seok

    2016-01-01

    The artificial spiking neural network (SNN) is promising and has been brought to the notice of the theoretical neuroscience and neuromorphic engineering research communities. In this light, we propose a new type of artificial spiking neuron based on leaky integrate-and-fire (LIF) behavior. A distinctive feature of the proposed FG-LIF neuron is the use of a floating-gate (FG) integrator rather than a capacitor-based one. The relaxation time of the charge on the FG relies mainly on the tunnel barrier profile, e.g., barrier height and thickness (rather than the area). This opens up the possibility of large-scale integration of neurons. The circuit simulation results offered biologically plausible spiking activity (circuit was subject to possible types of noise, e.g., thermal noise and burst noise. The simulation results indicated remarkable distributional features of interspike intervals that are fitted to Gamma distribution functions, similar to biological neurons in the neocortex. PMID:27242416

  10. Symmetry breaking in two interacting populations of quadratic integrate-and-fire neurons

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    Ratas, Irmantas; Pyragas, Kestutis

    2017-10-01

    We analyze the dynamics of two coupled identical populations of quadratic integrate-and-fire neurons, which represent the canonical model for class I neurons near the spiking threshold. The populations are heterogeneous; they include both inherently spiking and excitable neurons. The coupling within and between the populations is global via synapses that take into account the finite width of synaptic pulses. Using a recently developed reduction method based on the Lorentzian ansatz, we derive a closed system of equations for the neuron's firing rates and the mean membrane potentials in both populations. The reduced equations are exact in the infinite-size limit. The bifurcation analysis of the equations reveals a rich variety of nonsymmetric patterns, including a splay state, antiphase periodic oscillations, chimera-like states, and chaotic oscillations as well as bistabilities between various states. The validity of the reduced equations is confirmed by direct numerical simulations of the finite-size networks.

  11. Equilibrium and response properties of the integrate-and-fire neuron in discrete time

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    Moritz Helias

    2010-01-01

    Full Text Available The integrate-and-fire neuron with exponential postsynaptic potentials is a frequently employed model to study neural networks. Simulations in discrete time still have highest performance at moderate numerical errors, which makes them first choice for long-term simulations of plastic networks. Here we extend the population density approach to investigate how the equilibrium and response properties of the leaky integrate-and-fire neuron are affected by time discretization. We present a novel analytical treatment of the boundary condition at threshold, taking both discretization of time and finite synaptic weights into account. We uncover an increased membrane potential density just below threshold as the decisive property that explains the deviations found between simulations and the classical diffusion approximation. Temporal discretization and finite synaptic weights both contribute to this effect. Our treatment improves the standard formula to calculate the neuron’s equilibrium firing rate. Direct solution of the Markov process describing the evolution of the membrane potential density confirms our analysis and yields a method to calculate the firing rate exactly. Knowing the shape of the membrane potential distribution near threshold enables us to devise the transient response properties of the neuron model to synaptic input. We find a pronounced non-linear fast response component that has not been described by the prevailing continuous time theory for Gaussian white noise input.

  12. Intrinsic modulation of pulse-coupled integrate-and-fire neurons

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    Coombes, S.; Lord, G. J.

    1997-11-01

    Intrinsic neuromodulation is observed in sensory and neuromuscular circuits and in biological central pattern generators. We model a simple neuronal circuit with a system of two pulse-coupled integrate-and-fire neurons and explore the parameter regimes for periodic firing behavior. The inclusion of biologically realistic features shows that the speed and onset of neuronal response plays a crucial role in determining the firing phase for periodic rhythms. We explore the neurophysiological function of distributed delays arising from both the synaptic transmission process and dendritic structure as well as discrete delays associated with axonal communication delays. Bifurcation and stability diagrams are constructed with a mixture of simple analysis, numerical continuation and the Kuramoto phase-reduction technique. Moreover, we show that, for asynchronous behavior, the strength of electrical synapses can control the firing rate of the system.

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

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    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.

  14. Impact of adaptation currents on synchronization of coupled exponential integrate-and-fire neurons.

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    Josef Ladenbauer

    Full Text Available The ability of spiking neurons to synchronize their activity in a network depends on the response behavior of these neurons as quantified by the phase response curve (PRC and on coupling properties. The PRC characterizes the effects of transient inputs on spike timing and can be measured experimentally. Here we use the adaptive exponential integrate-and-fire (aEIF neuron model to determine how subthreshold and spike-triggered slow adaptation currents shape the PRC. Based on that, we predict how synchrony and phase locked states of coupled neurons change in presence of synaptic delays and unequal coupling strengths. We find that increased subthreshold adaptation currents cause a transition of the PRC from only phase advances to phase advances and delays in response to excitatory perturbations. Increased spike-triggered adaptation currents on the other hand predominantly skew the PRC to the right. Both adaptation induced changes of the PRC are modulated by spike frequency, being more prominent at lower frequencies. Applying phase reduction theory, we show that subthreshold adaptation stabilizes synchrony for pairs of coupled excitatory neurons, while spike-triggered adaptation causes locking with a small phase difference, as long as synaptic heterogeneities are negligible. For inhibitory pairs synchrony is stable and robust against conduction delays, and adaptation can mediate bistability of in-phase and anti-phase locking. We further demonstrate that stable synchrony and bistable in/anti-phase locking of pairs carry over to synchronization and clustering of larger networks. The effects of adaptation in aEIF neurons on PRCs and network dynamics qualitatively reflect those of biophysical adaptation currents in detailed Hodgkin-Huxley-based neurons, which underscores the utility of the aEIF model for investigating the dynamical behavior of networks. Our results suggest neuronal spike frequency adaptation as a mechanism synchronizing low frequency

  15. The Gamma renewal process as an output of the diffusion leaky integrate-and-fire neuronal model

    Czech Academy of Sciences Publication Activity Database

    Lánský, Petr; Sacerdote, L.; Zucca, C.

    2016-01-01

    Roč. 110, 2-3 (2016), s. 193-200 ISSN 0340-1200 R&D Projects: GA ČR(CZ) GA15-08066S Institutional support: RVO:67985823 Keywords : first-passage-time problem * leaky integrate-and-fire * Stein's neuronal model Subject RIV: BD - Theory of Information Impact factor: 1.716, year: 2016

  16. Reconstructing stimuli from the spike-times of leaky integrate and fire neurons

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    Sebastian eGerwinn

    2011-02-01

    Full Text Available Reconstructing stimuli from the spike-trains of neurons is an important approach for understanding the neural code. One of the difficulties associated with this task is that signals which are varying continuously in time are encoded into sequences of discrete events or spikes. An important problem is to determine how much information about the continuously varying stimulus can be extracted from the time-points at which spikes were observed, especially if these time-points are subject to some sort of randomness. For the special case of spike trains generated by leaky integrate and fire neurons, noise can be introduced by allowing variations in the threshold every time a spike is released. A simple decoding algorithm previously derived for the noiseless case can be extended to the stochastic case, but turns out to be biased. Here, we review a solution to this problem, by presenting a simple yet efficient algorithm which greatly reduces the bias, and therefore leads to better decoding performance in the stochastic case.

  17. Auto- and Crosscorrelograms for the Spike Response of Leaky Integrate-and-Fire Neurons with Slow Synapses

    International Nuclear Information System (INIS)

    Moreno-Bote, Ruben; Parga, Nestor

    2006-01-01

    An analytical description of the response properties of simple but realistic neuron models in the presence of noise is still lacking. We determine completely up to the second order the firing statistics of a single and a pair of leaky integrate-and-fire neurons receiving some common slowly filtered white noise. In particular, the auto- and cross-correlation functions of the output spike trains of pairs of cells are obtained from an improvement of the adiabatic approximation introduced previously by Moreno-Bote and Parga [Phys. Rev. Lett. 92, 028102 (2004)]. These two functions define the firing variability and firing synchronization between neurons, and are of much importance for understanding neuron communication

  18. Random Sampling with Interspike-Intervals of the Exponential Integrate and Fire Neuron: A Computational Interpretation of UP-States.

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    Andreas Steimer

    Full Text Available Oscillations between high and low values of the membrane potential (UP and DOWN states respectively are an ubiquitous feature of cortical neurons during slow wave sleep and anesthesia. Nevertheless, a surprisingly small number of quantitative studies have been conducted only that deal with this phenomenon's implications for computation. Here we present a novel theory that explains on a detailed mathematical level the computational benefits of UP states. The theory is based on random sampling by means of interspike intervals (ISIs of the exponential integrate and fire (EIF model neuron, such that each spike is considered a sample, whose analog value corresponds to the spike's preceding ISI. As we show, the EIF's exponential sodium current, that kicks in when balancing a noisy membrane potential around values close to the firing threshold, leads to a particularly simple, approximative relationship between the neuron's ISI distribution and input current. Approximation quality depends on the frequency spectrum of the current and is improved upon increasing the voltage baseline towards threshold. Thus, the conceptually simpler leaky integrate and fire neuron that is missing such an additional current boost performs consistently worse than the EIF and does not improve when voltage baseline is increased. For the EIF in contrast, the presented mechanism is particularly effective in the high-conductance regime, which is a hallmark feature of UP-states. Our theoretical results are confirmed by accompanying simulations, which were conducted for input currents of varying spectral composition. Moreover, we provide analytical estimations of the range of ISI distributions the EIF neuron can sample from at a given approximation level. Such samples may be considered by any algorithmic procedure that is based on random sampling, such as Markov Chain Monte Carlo or message-passing methods. Finally, we explain how spike-based random sampling relates to existing

  19. Random Sampling with Interspike-Intervals of the Exponential Integrate and Fire Neuron: A Computational Interpretation of UP-States.

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    Steimer, Andreas; Schindler, Kaspar

    2015-01-01

    Oscillations between high and low values of the membrane potential (UP and DOWN states respectively) are an ubiquitous feature of cortical neurons during slow wave sleep and anesthesia. Nevertheless, a surprisingly small number of quantitative studies have been conducted only that deal with this phenomenon's implications for computation. Here we present a novel theory that explains on a detailed mathematical level the computational benefits of UP states. The theory is based on random sampling by means of interspike intervals (ISIs) of the exponential integrate and fire (EIF) model neuron, such that each spike is considered a sample, whose analog value corresponds to the spike's preceding ISI. As we show, the EIF's exponential sodium current, that kicks in when balancing a noisy membrane potential around values close to the firing threshold, leads to a particularly simple, approximative relationship between the neuron's ISI distribution and input current. Approximation quality depends on the frequency spectrum of the current and is improved upon increasing the voltage baseline towards threshold. Thus, the conceptually simpler leaky integrate and fire neuron that is missing such an additional current boost performs consistently worse than the EIF and does not improve when voltage baseline is increased. For the EIF in contrast, the presented mechanism is particularly effective in the high-conductance regime, which is a hallmark feature of UP-states. Our theoretical results are confirmed by accompanying simulations, which were conducted for input currents of varying spectral composition. Moreover, we provide analytical estimations of the range of ISI distributions the EIF neuron can sample from at a given approximation level. Such samples may be considered by any algorithmic procedure that is based on random sampling, such as Markov Chain Monte Carlo or message-passing methods. Finally, we explain how spike-based random sampling relates to existing computational

  20. 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.

  1. Leaky Integrate and Fire Neuron by Charge-Discharge Dynamics in Floating-Body MOSFET.

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    Dutta, Sangya; Kumar, Vinay; Shukla, Aditya; Mohapatra, Nihar R; Ganguly, Udayan

    2017-08-15

    Neuro-biology inspired Spiking Neural Network (SNN) enables efficient learning and recognition tasks. To achieve a large scale network akin to biology, a power and area efficient electronic neuron is essential. Earlier, we had demonstrated an LIF neuron by a novel 4-terminal impact ionization based n+/p/n+ with an extended gate (gated-INPN) device by physics simulation. Excellent improvement in area and power compared to conventional analog circuit implementations was observed. In this paper, we propose and experimentally demonstrate a compact conventional 3-terminal partially depleted (PD) SOI- MOSFET (100 nm gate length) to replace the 4-terminal gated-INPN device. Impact ionization (II) induced floating body effect in SOI-MOSFET is used to capture LIF neuron behavior to demonstrate spiking frequency dependence on input. MHz operation enables attractive hardware acceleration compared to biology. Overall, conventional PD-SOI-CMOS technology enables very-large-scale-integration (VLSI) which is essential for biology scale (~10 11 neuron based) large neural networks.

  2. 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

  3. Analytical approximations of the firing rate of an adaptive exponential integrate-and-fire neuron in the presence of synaptic noise

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    Loreen eHertäg

    2014-09-01

    Full Text Available Computational models offer a unique tool for understanding the network-dynamical mechanisms which mediate between physiological and biophysical properties, and behavioral function. A traditional challenge in computational neuroscience is, however, that simple neuronal models which can be studied analytically fail to reproduce the diversity of electrophysiological behaviors seen in real neurons, while detailed neuronal models which do reproduce such diversity are intractable analytically and computationally expensive. A number of intermediate models have been proposed whose aim is to capture the diversity of firing behaviors and spike times of real neurons while entailing a mathematical description as simple as possible. One such model is the exponential integrate-and-fire neuron with spike rate adaptation (aEIF which consists of two differential equations for the membrane potential (V and an adaptation current (w. Despite its simplicity, it can reproduce a wide variety of physiologically observed spiking patterns, can be fit to physiological recordings quantitatively, and, once done so, is able to predict spike times on traces not used for model fitting. Here we compute the steady-state firing rate of aEIF in the presence of Gaussian synaptic noise, using two approaches. The first approach is based on the 2-dimensional Fokker-Planck equation that describes the (V,w-probability distribution, which is solved using an expansion in the ratio between the time constants of the two variables. The second is based on the firing rate of the EIF model, which is averaged over the distribution of the $w$ variable. These analytically derived closed-form expressions were tested on simulations from a large variety of model cells quantitatively fitted to in vitro electrophysiological recordings from pyramidal cells and interneurons. Theoretical predictions closely agreed with the firing rate of the simulated cells fed with in-vivo-like synaptic noise.

  4. Analytical approximations of the firing rate of an adaptive exponential integrate-and-fire neuron in the presence of synaptic noise.

    Science.gov (United States)

    Hertäg, Loreen; Durstewitz, Daniel; Brunel, Nicolas

    2014-01-01

    Computational models offer a unique tool for understanding the network-dynamical mechanisms which mediate between physiological and biophysical properties, and behavioral function. A traditional challenge in computational neuroscience is, however, that simple neuronal models which can be studied analytically fail to reproduce the diversity of electrophysiological behaviors seen in real neurons, while detailed neuronal models which do reproduce such diversity are intractable analytically and computationally expensive. A number of intermediate models have been proposed whose aim is to capture the diversity of firing behaviors and spike times of real neurons while entailing the simplest possible mathematical description. One such model is the exponential integrate-and-fire neuron with spike rate adaptation (aEIF) which consists of two differential equations for the membrane potential (V) and an adaptation current (w). Despite its simplicity, it can reproduce a wide variety of physiologically observed spiking patterns, can be fit to physiological recordings quantitatively, and, once done so, is able to predict spike times on traces not used for model fitting. Here we compute the steady-state firing rate of aEIF in the presence of Gaussian synaptic noise, using two approaches. The first approach is based on the 2-dimensional Fokker-Planck equation that describes the (V,w)-probability distribution, which is solved using an expansion in the ratio between the time constants of the two variables. The second is based on the firing rate of the EIF model, which is averaged over the distribution of the w variable. These analytically derived closed-form expressions were tested on simulations from a large variety of model cells quantitatively fitted to in vitro electrophysiological recordings from pyramidal cells and interneurons. Theoretical predictions closely agreed with the firing rate of the simulated cells fed with in-vivo-like synaptic noise.

  5. A review of the methods for signal estimation in stochastic diffusion leaky integrate-and-fire neuronal models

    Czech Academy of Sciences Publication Activity Database

    Lánský, Petr; Ditlevsen, S.

    2008-01-01

    Roč. 99, 4-5 (2008), s. 253-262 ISSN 0340-1200 R&D Projects: GA MŠk(CZ) LC554; GA AV ČR(CZ) 1ET400110401 Institutional research plan: CEZ:AV0Z50110509 Keywords : parameter estimation * stochastic diffusion neuronal model Subject RIV: BO - Biophysics Impact factor: 1.935, year: 2008

  6. Connectivity and dynamics of neuronal networks as defined by the shape of individual neurons

    International Nuclear Information System (INIS)

    Ahnert, Sebastian E; A N Travencolo, Bruno; Costa, Luciano da Fontoura

    2009-01-01

    Biological neuronal networks constitute a special class of dynamical systems, as they are formed by individual geometrical components, namely the neurons. In the existing literature, relatively little attention has been given to the influence of neuron shape on the overall connectivity and dynamics of the emerging networks. The current work addresses this issue by considering simplified neuronal shapes consisting of circular regions (soma/axons) with spokes (dendrites). Networks are grown by placing these patterns randomly in the two-dimensional (2D) plane and establishing connections whenever a piece of dendrite falls inside an axon. Several topological and dynamical properties of the resulting graph are measured, including the degree distribution, clustering coefficients, symmetry of connections, size of the largest connected component, as well as three hierarchical measurements of the local topology. By varying the number of processes of the individual basic patterns, we can quantify relationships between the individual neuronal shape and the topological and dynamical features of the networks. Integrate-and-fire dynamics on these networks is also investigated with respect to transient activation from a source node, indicating that long-range connections play an important role in the propagation of avalanches.

  7. How well do mean field theories of spiking quadratic-integrate-and-fire networks work in realistic parameter regimes?

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    Grabska-Barwińska, Agnieszka; Latham, Peter E

    2014-06-01

    We use mean field techniques to compute the distribution of excitatory and inhibitory firing rates in large networks of randomly connected spiking quadratic integrate and fire neurons. These techniques are based on the assumption that activity is asynchronous and Poisson. For most parameter settings these assumptions are strongly violated; nevertheless, so long as the networks are not too synchronous, we find good agreement between mean field prediction and network simulations. Thus, much of the intuition developed for randomly connected networks in the asynchronous regime applies to mildly synchronous networks.

  8. Firing patterns in the adaptive exponential integrate-and-fire model.

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    Naud, Richard; Marcille, Nicolas; Clopath, Claudia; Gerstner, Wulfram

    2008-11-01

    For simulations of large spiking neuron networks, an accurate, simple and versatile single-neuron modeling framework is required. Here we explore the versatility of a simple two-equation model: the adaptive exponential integrate-and-fire neuron. We show that this model generates multiple firing patterns depending on the choice of parameter values, and present a phase diagram describing the transition from one firing type to another. We give an analytical criterion to distinguish between continuous adaption, initial bursting, regular bursting and two types of tonic spiking. Also, we report that the deterministic model is capable of producing irregular spiking when stimulated with constant current, indicating low-dimensional chaos. Lastly, the simple model is fitted to real experiments of cortical neurons under step current stimulation. The results provide support for the suitability of simple models such as the adaptive exponential integrate-and-fire neuron for large network simulations.

  9. Visualizing neuronal network connectivity with connectivity pattern tables

    Directory of Open Access Journals (Sweden)

    Eilen Nordlie

    2010-01-01

    Full Text Available Complex ideas are best conveyed through well-designed illustrations. Up to now, computational neuroscientists have mostly relied on box-and-arrow diagrams of even complex neuronal networks, often using ad hoc notations with conflicting use of symbols from paper to paper. This significantly impedes the communication of ideas in neuronal network modeling. We present here Connectivity Pattern Tables (CPTs as a clutter-free visualization of connectivity in large neuronal networks containing two-dimensional populations of neurons. CPTs can be generated automatically from the same script code used to create the actual network in the NEST simulator. Through aggregation, CPTs can be viewed at different levels, providing either full detail or summary information. We also provide the open source ConnPlotter tool as a means to create connectivity pattern tables.

  10. Chaos in integrate-and-fire dynamical systems

    International Nuclear Information System (INIS)

    Coombes, S.

    2000-01-01

    Integrate-and-fire (IF) mechanisms are often studied within the context of neural dynamics. From a mathematical perspective they represent a minimal yet biologically realistic model of a spiking neuron. The non-smooth nature of the dynamics leads to extremely rich spike train behavior capable of explaining a variety of biological phenomenon including phase-locked states, mode-locking, bursting and pattern formation. The conditions under which chaotic spike trains may be generated in synaptically interacting networks of neural oscillators is an important open question. Using techniques originally introduced for the study of impact oscillators we develop the notion of a Liapunov exponent for IF systems. In the strong coupling regime a network may undergo a discrete Turing-Hopf bifurcation of the firing times from a synchronous state to a state with periodic or quasiperiodic variations of the interspike intervals on closed orbits. Away from the bifurcation point these invariant circles may break up. We establish numerically that in this case the largest IF Liapunov exponent becomes positive. Hence, one route to chaos in networks of synaptically coupled IF neurons is via the breakup of invariant circles

  11. Computing the Local Field Potential (LFP) from Integrate-and-Fire Network Models

    DEFF Research Database (Denmark)

    Mazzoni, Alberto; Linden, Henrik; Cuntz, Hermann

    2015-01-01

    Leaky integrate-and-fire (LIF) network models are commonly used to study how the spiking dynamics of neural networks changes with stimuli, tasks or dynamic network states. However, neurophysiological studies in vivo often rather measure the mass activity of neuronal microcircuits with the local f...... in cases where a single pyramidal population dominates the LFP generation, and thereby facilitate quantitative comparison between computational models and experimental LFP recordings in vivo....

  12. Simulating synchronization in neuronal networks

    Science.gov (United States)

    Fink, Christian G.

    2016-06-01

    We discuss several techniques used in simulating neuronal networks by exploring how a network's connectivity structure affects its propensity for synchronous spiking. Network connectivity is generated using the Watts-Strogatz small-world algorithm, and two key measures of network structure are described. These measures quantify structural characteristics that influence collective neuronal spiking, which is simulated using the leaky integrate-and-fire model. Simulations show that adding a small number of random connections to an otherwise lattice-like connectivity structure leads to a dramatic increase in neuronal synchronization.

  13. Generalization of the event-based Carnevale-Hines integration scheme for integrate-and-fire models

    NARCIS (Netherlands)

    van Elburg, R.A.J.; van Ooyen, A.

    2009-01-01

    An event-based integration scheme for an integrate-and-fire neuron model with exponentially decaying excitatory synaptic currents and double exponential inhibitory synaptic currents has been introduced by Carnevale and Hines. However, the integration scheme imposes nonphysiological constraints on

  14. Generalization of the Event-Based Carnevale-Hines Integration Scheme for Integrate-and-Fire Models

    NARCIS (Netherlands)

    van Elburg, Ronald A. J.; van Ooyen, Arjen

    An event-based integration scheme for an integrate-and-fire neuron model with exponentially decaying excitatory synaptic currents and double exponential inhibitory synaptic currents has been introduced by Carnevale and Hines. However, the integration scheme imposes nonphysiological constraints on

  15. Relationship between the mechanisms of gamma rhythm generation and the magnitude of the macroscopic phase response function in a population of excitatory and inhibitory modified quadratic integrate-and-fire neurons

    Science.gov (United States)

    Akao, Akihiko; Ogawa, Yutaro; Jimbo, Yasuhiko; Ermentrout, G. Bard; Kotani, Kiyoshi

    2018-01-01

    Gamma oscillations are thought to play an important role in brain function. Interneuron gamma (ING) and pyramidal interneuron gamma (PING) mechanisms have been proposed as generation mechanisms for these oscillations. However, the relation between the generation mechanisms and the dynamical properties of the gamma oscillation are still unclear. Among the dynamical properties of the gamma oscillation, the phase response function (PRF) is important because it encodes the response of the oscillation to inputs. Recently, the PRF for an inhibitory population of modified theta neurons that generate an ING rhythm was computed by the adjoint method applied to the associated Fokker-Planck equation (FPE) for the model. The modified theta model incorporates conductance-based synapses as well as the voltage and current dynamics. Here, we extended this previous work by creating an excitatory-inhibitory (E-I) network using the modified theta model and described the population dynamics with the corresponding FPE. We conducted a bifurcation analysis of the FPE to find parameter regions which generate gamma oscillations. In order to label the oscillatory parameter regions by their generation mechanisms, we defined ING- and PING-type gamma oscillation in a mathematically plausible way based on the driver of the inhibitory population. We labeled the oscillatory parameter regions by these generation mechanisms and derived PRFs via the adjoint method on the FPE in order to investigate the differences in the responses of each type of oscillation to inputs. PRFs for PING and ING mechanisms are derived and compared. We found the amplitude of the PRF for the excitatory population is larger in the PING case than in the ING case. Finally, the E-I population of the modified theta neuron enabled us to analyze the PRFs of PING-type gamma oscillation and the entrainment ability of E and I populations. We found a parameter region in which PRFs of E and I are both purely positive in the case of

  16. Population coding in sparsely connected networks of noisy neurons

    OpenAIRE

    Tripp, Bryan P.; Orchard, Jeff

    2012-01-01

    This study examines the relationship between population coding and spatial connection statistics in networks of noisy neurons. Encoding of sensory information in the neocortex is thought to require coordinated neural populations, because individual cortical neurons respond to a wide range of stimuli, and exhibit highly variable spiking in response to repeated stimuli. Population coding is rooted in network structure, because cortical neurons receive information only from other neurons, and be...

  17. Population coding in sparsely connected networks of noisy neurons.

    Science.gov (United States)

    Tripp, Bryan P; Orchard, Jeff

    2012-01-01

    This study examines the relationship between population coding and spatial connection statistics in networks of noisy neurons. Encoding of sensory information in the neocortex is thought to require coordinated neural populations, because individual cortical neurons respond to a wide range of stimuli, and exhibit highly variable spiking in response to repeated stimuli. Population coding is rooted in network structure, because cortical neurons receive information only from other neurons, and because the information they encode must be decoded by other neurons, if it is to affect behavior. However, population coding theory has often ignored network structure, or assumed discrete, fully connected populations (in contrast with the sparsely connected, continuous sheet of the cortex). In this study, we modeled a sheet of cortical neurons with sparse, primarily local connections, and found that a network with this structure could encode multiple internal state variables with high signal-to-noise ratio. However, we were unable to create high-fidelity networks by instantiating connections at random according to spatial connection probabilities. In our models, high-fidelity networks required additional structure, with higher cluster factors and correlations between the inputs to nearby neurons.

  18. Population Coding in Sparsely Connected Networks of Noisy Neurons

    Directory of Open Access Journals (Sweden)

    Bryan Patrick Tripp

    2012-05-01

    Full Text Available This study examines the relationship between population coding and spatial connection statistics in networks of noisy neurons. Encoding of sensory information in the neocortex is thought to require coordinated neural populations, because individual cortical neurons respond to a wide range of stimuli, and exhibit highly variable spiking in response to repeated stimuli. Population coding is rooted in network structure, because cortical neurons receive information only from other neurons, and because the information they encode must be decoded by other neurons, if it is to affect behaviour. However, population coding theory has often ignored network structure, or assumed discrete, fully-connected populations (in contrast with the sparsely connected, continuous sheet of the cortex. In this study, we model a sheet of cortical neurons with sparse, primarily local connections, and find that a network with this structure can encode multiple internal state variables with high signal-to-noise ratio. However, in our model, although connection probability varies with the distance between neurons, we find that the connections cannot be instantiated at random according to these probabilities, but must have additional structure if information is to be encoded with high fidelity.

  19. Training the integrate-and-fire model with the informax principle: I

    Energy Technology Data Exchange (ETDEWEB)

    Feng Jianfeng; Buxton, Hilary [COGS, Sussex University, Brighton (United Kingdom); Deng Yingchun [Department of Mathematics, Hunan Normal University, Changsha (China)

    2002-03-15

    In terms of the informax principle, and the input-output relationship of the integrate-and-fire (IF) model, IF neuron learning rules are developed. For supervised learning and with uniform weight of synapses (the theoretically tractable case), we show that the derived learning rule is stable and the stable state is unique. For unsupervised learning, within physiologically reasonable parameter regions, both long-term potentiation (LTP) and long-term depression (LTD) could happen when the inhibitory input is weak, but LTD cannot be observed when inhibitory input is strong enough. When both LTP and LTD occur, LTD is observable when the output of the postsynaptic neuron is faster than pre-synaptic inputs, otherwise LTP is observable, as observed in recent experiments. Learning rules of general cases are also studied and numerical examples show that the derived learning rule tends to equalize the contribution of different inputs to the output firing rates. (author)

  20. Engineering connectivity by multiscale micropatterning of individual populations of neurons.

    Science.gov (United States)

    Albers, Jonas; Toma, Koji; Offenhäusser, Andreas

    2015-02-01

    Functional networks are the basis of information processing in the central nervous system. Essential for their formation are guided neuronal growth as well as controlled connectivity and information flow. The basis of neuronal development is generated by guiding cues and geometric constraints. To investigate the neuronal growth and connectivity of adjacent neuronal networks, two-dimensional protein patterns were created. A mixture of poly-L-lysine and laminin was transferred onto a silanized glass surface by microcontact printing. The structures were populated with dissociated primary cortical embryonic rat neurons. Triangular structures with diverse opening angles, height, and design were chosen as two-dimensional structures to allow network formation with constricted gateways. Neuronal development was observed by immunohistochemistry to pursue the influence of the chosen structures on the neuronal outgrowth. Neurons were stained for MAP2, while poly-L-lysine was FITC labeled. With this study we present an easy-to-use technique to engineer two-dimensional networks in vitro with defined gateways. The presented micropatterning method is used to generate daisy-chained neuronal networks with predefined connectivity. Signal propagation among geometrically constrained networks can easily be monitored by calcium-sensitive dyes, providing insights into network communication in vitro. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. Comparison of the dynamics of neural interactions in integrate-and-fire networks with current-based and conductance-based synapses

    Directory of Open Access Journals (Sweden)

    Stefano eCavallari

    2014-03-01

    Full Text Available Models of networks of Leaky Integrate-and-Fire neurons (LIF are a widely used tool for theoretical investigations of brain function. These models have been used both with current- and conductance-based synapses. However, the differences in the dynamics expressed by these two approaches have been so far mainly studied at the single neuron level. To investigate how these synaptic models affect network activity, we compared the single-neuron and neural population dynamics of conductance-based networks (COBN and current-based networks (CUBN of LIF neurons. These networks were endowed with sparse excitatory and inhibitory recurrent connections, and were tested in conditions including both low- and high-conductance states. We developed a novel procedure to obtain comparable networks by properly tuning the synaptic parameters not shared by the models. The so defined comparable networks displayed an excellent and robust match of first order statistics (average single neuron firing rates and average frequency spectrum of network activity. However, these comparable networks showed profound differences in the second order statistics of neural population interactions and in the modulation of these properties by external inputs. The correlation between inhibitory and excitatory synaptic currents and the cross-neuron correlation between synaptic inputs, membrane potentials and spike trains were stronger and more stimulus-sensitive in the COBN. Because of these properties, the spike train correlation carried more information about the strength of the input in the COBN, although the firing rates were equally informative in both network models. Moreover, COBN showed stronger neuronal population synchronization in the gamma band, and their spectral information about the network input was higher and spread over a broader range of frequencies. These results suggest that second order properties of network dynamics depend strongly on the choice of synaptic model.

  2. Local connections of layer 5 GABAergic interneurons to corticospinal neurons

    Directory of Open Access Journals (Sweden)

    Yasuyo H Tanaka

    2011-09-01

    Full Text Available In the local circuit of the cerebral cortex, GABAergic inhibitory interneurons are considered to work in collaboration with excitatory neurons. Although many interneuron subgroups have been described in the cortex, local inhibitory connections of each interneuron subgroup are only partially understood with respect to the functional neuron groups that receive these inhibitory connections. In the present study, we morphologically examined local inhibitory inputs to corticospinal neurons (CSNs in motor areas using transgenic rats in which GABAergic neurons expressed fluorescent protein Venus. By analysis of biocytin-filled axons obtained with whole-cell recording/staining in cortical slices, we classified fast-spiking (FS neurons in layer (L 5 into two types, FS1 and FS2, by their high and low densities of axonal arborization, respectively. We then investigated the connections of FS1, FS2, somatostatin-immunopositive (SOM and other (non-FS/non-SOM interneurons to CSNs that were retrogradely labeled in a Golgi-like manner in motor areas. When close appositions between the axon boutons of the intracellularly labeled interneurons and the somata/dendrites of the retrogradely labeled CSNs were examined electron-microscopically, 74% of these appositions made symmetric synaptic contacts. The axon boutons of single FS1 neurons were 2–4-fold more frequent in appositions to the somata/dendrites of CSNs than those of FS2, SOM and non-FS/non-SOM neurons. Axosomatic appositions were most frequently formed with axon boutons of FS1 and FS2 neurons (approximately 30% and least frequently formed with those of SOM neurons (7%. In contrast, SOM neurons most extensively sent axon boutons to the apical dendrites of CSNs. These results might suggest that motor outputs are controlled differentially by the subgroups of L5 GABAergic interneurons in cortical motor areas. 

  3. Connecting mirror neurons and forward models.

    Science.gov (United States)

    Miall, R C

    2003-12-02

    Two recent developments in motor neuroscience are promising the extension of theoretical concepts from motor control towards cognitive processes, including human social interactions and understanding the intentions of others. The first of these is the discovery of what are now called mirror neurons, which code for both observed and executed actions. The second is the concept of internal models, and in particular recent proposals that forward and inverse models operate in paired modules. These two ideas will be briefly introduced, and a recent suggestion linking between the two processes of mirroring and modelling will be described which may underlie our abilities for imitating actions, for cooperation between two actors, and possibly for communication via gesture and language.

  4. Connectivities and synchronous firing in cortical neuronal networks

    International Nuclear Information System (INIS)

    Jia, L.C.; Sano, M.; Lai, P.-Y.; Chan, C.K.

    2004-01-01

    Network connectivities (k-bar) of cortical neural cultures are studied by synchronized firing and determined from measured correlations between fluorescence intensities of firing neurons. The bursting frequency (f) during synchronized firing of the networks is found to be an increasing function of k-bar. With f taken to be proportional to k-bar, a simple random model with a k-bar dependent connection probability p(k-bar) has been constructed to explain our experimental findings successfully

  5. Quantifying chaotic dynamics from integrate-and-fire processes

    Energy Technology Data Exchange (ETDEWEB)

    Pavlov, A. N. [Department of Physics, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov (Russian Federation); Saratov State Technical University, Politehnicheskaya Str. 77, 410054 Saratov (Russian Federation); Pavlova, O. N. [Department of Physics, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov (Russian Federation); Mohammad, Y. K. [Department of Physics, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov (Russian Federation); Tikrit University Salahudin, Tikrit Qadisiyah, University Str. P.O. Box 42, Tikrit (Iraq); Kurths, J. [Potsdam Institute for Climate Impact Research, Telegraphenberg A 31, 14473 Potsdam (Germany); Institute of Physics, Humboldt University Berlin, 12489 Berlin (Germany)

    2015-01-15

    Characterizing chaotic dynamics from integrate-and-fire (IF) interspike intervals (ISIs) is relatively easy performed at high firing rates. When the firing rate is low, a correct estimation of Lyapunov exponents (LEs) describing dynamical features of complex oscillations reflected in the IF ISI sequences becomes more complicated. In this work we discuss peculiarities and limitations of quantifying chaotic dynamics from IF point processes. We consider main factors leading to underestimated LEs and demonstrate a way of improving numerical determining of LEs from IF ISI sequences. We show that estimations of the two largest LEs can be performed using around 400 mean periods of chaotic oscillations in the regime of phase-coherent chaos. Application to real data is discussed.

  6. Examining Neuronal Connectivity and Its Role in Learning and Memory

    Science.gov (United States)

    Gala, Rohan

    Learning and long-term memory formation are accompanied with changes in the patterns and weights of synaptic connections in the underlying neuronal network. However, the fundamental rules that drive connectivity changes, and the precise structure-function relationships within neuronal networks remain elusive. Technological improvements over the last few decades have enabled the observation of large but specific subsets of neurons and their connections in unprecedented detail. Devising robust and automated computational methods is critical to distill information from ever-increasing volumes of raw experimental data. Moreover, statistical models and theoretical frameworks are required to interpret the data and assemble evidence into understanding of brain function. In this thesis, I first describe computational methods to reconstruct connectivity based on light microscopy imaging experiments. Next, I use these methods to quantify structural changes in connectivity based on in vivo time-lapse imaging experiments. Finally, I present a theoretical model of associative learning that can explain many stereotypical features of experimentally observed connectivity.

  7. Complementary responses to mean and variance modulations in the perfect integrate-and-fire model.

    Science.gov (United States)

    Pressley, Joanna; Troyer, Todd W

    2009-07-01

    In the perfect integrate-and-fire model (PIF), the membrane voltage is proportional to the integral of the input current since the time of the previous spike. It has been shown that the firing rate within a noise free ensemble of PIF neurons responds instantaneously to dynamic changes in the input current, whereas in the presence of white noise, model neurons preferentially pass low frequency modulations of the mean current. Here, we prove that when the input variance is perturbed while holding the mean current constant, the PIF responds preferentially to high frequency modulations. Moreover, the linear filters for mean and variance modulations are complementary, adding exactly to one. Since changes in the rate of Poisson distributed inputs lead to proportional changes in the mean and variance, these results imply that an ensemble of PIF neurons transmits a perfect replica of the time-varying input rate for Poisson distributed input. A more general argument shows that this property holds for any signal leading to proportional changes in the mean and variance of the input current.

  8. Computing the Local Field Potential (LFP) from Integrate-and-Fire Network Models

    Science.gov (United States)

    Cuntz, Hermann; Lansner, Anders; Panzeri, Stefano; Einevoll, Gaute T.

    2015-01-01

    Leaky integrate-and-fire (LIF) network models are commonly used to study how the spiking dynamics of neural networks changes with stimuli, tasks or dynamic network states. However, neurophysiological studies in vivo often rather measure the mass activity of neuronal microcircuits with the local field potential (LFP). Given that LFPs are generated by spatially separated currents across the neuronal membrane, they cannot be computed directly from quantities defined in models of point-like LIF neurons. Here, we explore the best approximation for predicting the LFP based on standard output from point-neuron LIF networks. To search for this best “LFP proxy”, we compared LFP predictions from candidate proxies based on LIF network output (e.g, firing rates, membrane potentials, synaptic currents) with “ground-truth” LFP obtained when the LIF network synaptic input currents were injected into an analogous three-dimensional (3D) network model of multi-compartmental neurons with realistic morphology, spatial distributions of somata and synapses. We found that a specific fixed linear combination of the LIF synaptic currents provided an accurate LFP proxy, accounting for most of the variance of the LFP time course observed in the 3D network for all recording locations. This proxy performed well over a broad set of conditions, including substantial variations of the neuronal morphologies. Our results provide a simple formula for estimating the time course of the LFP from LIF network simulations in cases where a single pyramidal population dominates the LFP generation, and thereby facilitate quantitative comparison between computational models and experimental LFP recordings in vivo. PMID:26657024

  9. Computing the Local Field Potential (LFP from Integrate-and-Fire Network Models.

    Directory of Open Access Journals (Sweden)

    Alberto Mazzoni

    2015-12-01

    Full Text Available Leaky integrate-and-fire (LIF network models are commonly used to study how the spiking dynamics of neural networks changes with stimuli, tasks or dynamic network states. However, neurophysiological studies in vivo often rather measure the mass activity of neuronal microcircuits with the local field potential (LFP. Given that LFPs are generated by spatially separated currents across the neuronal membrane, they cannot be computed directly from quantities defined in models of point-like LIF neurons. Here, we explore the best approximation for predicting the LFP based on standard output from point-neuron LIF networks. To search for this best "LFP proxy", we compared LFP predictions from candidate proxies based on LIF network output (e.g, firing rates, membrane potentials, synaptic currents with "ground-truth" LFP obtained when the LIF network synaptic input currents were injected into an analogous three-dimensional (3D network model of multi-compartmental neurons with realistic morphology, spatial distributions of somata and synapses. We found that a specific fixed linear combination of the LIF synaptic currents provided an accurate LFP proxy, accounting for most of the variance of the LFP time course observed in the 3D network for all recording locations. This proxy performed well over a broad set of conditions, including substantial variations of the neuronal morphologies. Our results provide a simple formula for estimating the time course of the LFP from LIF network simulations in cases where a single pyramidal population dominates the LFP generation, and thereby facilitate quantitative comparison between computational models and experimental LFP recordings in vivo.

  10. Recurrently connected and localized neuronal communities initiate coordinated spontaneous activity in neuronal networks

    Science.gov (United States)

    Amin, Hayder; Maccione, Alessandro; Nieus, Thierry

    2017-01-01

    Developing neuronal systems intrinsically generate coordinated spontaneous activity that propagates by involving a large number of synchronously firing neurons. In vivo, waves of spikes transiently characterize the activity of developing brain circuits and are fundamental for activity-dependent circuit formation. In vitro, coordinated spontaneous spiking activity, or network bursts (NBs), interleaved within periods of asynchronous spikes emerge during the development of 2D and 3D neuronal cultures. Several studies have investigated this type of activity and its dynamics, but how a neuronal system generates these coordinated events remains unclear. Here, we investigate at a cellular level the generation of network bursts in spontaneously active neuronal cultures by exploiting high-resolution multielectrode array recordings and computational network modelling. Our analysis reveals that NBs are generated in specialized regions of the network (functional neuronal communities) that feature neuronal links with high cross-correlation peak values, sub-millisecond lags and that share very similar structural connectivity motifs providing recurrent interactions. We show that the particular properties of these local structures enable locally amplifying spontaneous asynchronous spikes and that this mechanism can lead to the initiation of NBs. Through the analysis of simulated and experimental data, we also show that AMPA currents drive the coordinated activity, while NMDA and GABA currents are only involved in shaping the dynamics of NBs. Overall, our results suggest that the presence of functional neuronal communities with recurrent local connections allows a neuronal system to generate spontaneous coordinated spiking activity events. As suggested by the rules used for implementing our computational model, such functional communities might naturally emerge during network development by following simple constraints on distance-based connectivity. PMID:28749937

  11. Recurrently connected and localized neuronal communities initiate coordinated spontaneous activity in neuronal networks.

    Directory of Open Access Journals (Sweden)

    Davide Lonardoni

    2017-07-01

    Full Text Available Developing neuronal systems intrinsically generate coordinated spontaneous activity that propagates by involving a large number of synchronously firing neurons. In vivo, waves of spikes transiently characterize the activity of developing brain circuits and are fundamental for activity-dependent circuit formation. In vitro, coordinated spontaneous spiking activity, or network bursts (NBs, interleaved within periods of asynchronous spikes emerge during the development of 2D and 3D neuronal cultures. Several studies have investigated this type of activity and its dynamics, but how a neuronal system generates these coordinated events remains unclear. Here, we investigate at a cellular level the generation of network bursts in spontaneously active neuronal cultures by exploiting high-resolution multielectrode array recordings and computational network modelling. Our analysis reveals that NBs are generated in specialized regions of the network (functional neuronal communities that feature neuronal links with high cross-correlation peak values, sub-millisecond lags and that share very similar structural connectivity motifs providing recurrent interactions. We show that the particular properties of these local structures enable locally amplifying spontaneous asynchronous spikes and that this mechanism can lead to the initiation of NBs. Through the analysis of simulated and experimental data, we also show that AMPA currents drive the coordinated activity, while NMDA and GABA currents are only involved in shaping the dynamics of NBs. Overall, our results suggest that the presence of functional neuronal communities with recurrent local connections allows a neuronal system to generate spontaneous coordinated spiking activity events. As suggested by the rules used for implementing our computational model, such functional communities might naturally emerge during network development by following simple constraints on distance-based connectivity.

  12. Dynamics of the exponential integrate-and-fire model with slow currents and adaptation.

    Science.gov (United States)

    Barranca, Victor J; Johnson, Daniel C; Moyher, Jennifer L; Sauppe, Joshua P; Shkarayev, Maxim S; Kovačič, Gregor; Cai, David

    2014-08-01

    In order to properly capture spike-frequency adaptation with a simplified point-neuron model, we study approximations of Hodgkin-Huxley (HH) models including slow currents by exponential integrate-and-fire (EIF) models that incorporate the same types of currents. We optimize the parameters of the EIF models under the external drive consisting of AMPA-type conductance pulses using the current-voltage curves and the van Rossum metric to best capture the subthreshold membrane potential, firing rate, and jump size of the slow current at the neuron's spike times. Our numerical simulations demonstrate that, in addition to these quantities, the approximate EIF-type models faithfully reproduce bifurcation properties of the HH neurons with slow currents, which include spike-frequency adaptation, phase-response curves, critical exponents at the transition between a finite and infinite number of spikes with increasing constant external drive, and bifurcation diagrams of interspike intervals in time-periodically forced models. Dynamics of networks of HH neurons with slow currents can also be approximated by corresponding EIF-type networks, with the approximation being at least statistically accurate over a broad range of Poisson rates of the external drive. For the form of external drive resembling realistic, AMPA-like synaptic conductance response to incoming action potentials, the EIF model affords great savings of computation time as compared with the corresponding HH-type model. Our work shows that the EIF model with additional slow currents is well suited for use in large-scale, point-neuron models in which spike-frequency adaptation is important.

  13. Dense neuron clustering explains connectivity statistics in cortical microcircuits.

    Directory of Open Access Journals (Sweden)

    Vladimir V Klinshov

    Full Text Available Local cortical circuits appear highly non-random, but the underlying connectivity rule remains elusive. Here, we analyze experimental data observed in layer 5 of rat neocortex and suggest a model for connectivity from which emerge essential observed non-random features of both wiring and weighting. These features include lognormal distributions of synaptic connection strength, anatomical clustering, and strong correlations between clustering and connection strength. Our model predicts that cortical microcircuits contain large groups of densely connected neurons which we call clusters. We show that such a cluster contains about one fifth of all excitatory neurons of a circuit which are very densely connected with stronger than average synapses. We demonstrate that such clustering plays an important role in the network dynamics, namely, it creates bistable neural spiking in small cortical circuits. Furthermore, introducing local clustering in large-scale networks leads to the emergence of various patterns of persistent local activity in an ongoing network activity. Thus, our results may bridge a gap between anatomical structure and persistent activity observed during working memory and other cognitive processes.

  14. Rich-Club Organization in Effective Connectivity among Cortical Neurons.

    Science.gov (United States)

    Nigam, Sunny; Shimono, Masanori; Ito, Shinya; Yeh, Fang-Chin; Timme, Nicholas; Myroshnychenko, Maxym; Lapish, Christopher C; Tosi, Zachary; Hottowy, Pawel; Smith, Wesley C; Masmanidis, Sotiris C; Litke, Alan M; Sporns, Olaf; Beggs, John M

    2016-01-20

    The performance of complex networks, like the brain, depends on how effectively their elements communicate. Despite the importance of communication, it is virtually unknown how information is transferred in local cortical networks, consisting of hundreds of closely spaced neurons. To address this, it is important to record simultaneously from hundreds of neurons at a spacing that matches typical axonal connection distances, and at a temporal resolution that matches synaptic delays. We used a 512-electrode array (60 μm spacing) to record spontaneous activity at 20 kHz from up to 500 neurons simultaneously in slice cultures of mouse somatosensory cortex for 1 h at a time. We applied a previously validated version of transfer entropy to quantify information transfer. Similar to in vivo reports, we found an approximately lognormal distribution of firing rates. Pairwise information transfer strengths also were nearly lognormally distributed, similar to reports of synaptic strengths. Some neurons transferred and received much more information than others, which is consistent with previous predictions. Neurons with the highest outgoing and incoming information transfer were more strongly connected to each other than chance, thus forming a "rich club." We found similar results in networks recorded in vivo from rodent cortex, suggesting the generality of these findings. A rich-club structure has been found previously in large-scale human brain networks and is thought to facilitate communication between cortical regions. The discovery of a small, but information-rich, subset of neurons within cortical regions suggests that this population will play a vital role in communication, learning, and memory. Significance statement: Many studies have focused on communication networks between cortical brain regions. In contrast, very few studies have examined communication networks within a cortical region. This is the first study to combine such a large number of neurons (several

  15. Rich-Club Organization in Effective Connectivity among Cortical Neurons

    Science.gov (United States)

    Shimono, Masanori; Ito, Shinya; Yeh, Fang-Chin; Timme, Nicholas; Myroshnychenko, Maxym; Lapish, Christopher C.; Tosi, Zachary; Hottowy, Pawel; Smith, Wesley C.; Masmanidis, Sotiris C.; Litke, Alan M.; Sporns, Olaf; Beggs, John M.

    2016-01-01

    The performance of complex networks, like the brain, depends on how effectively their elements communicate. Despite the importance of communication, it is virtually unknown how information is transferred in local cortical networks, consisting of hundreds of closely spaced neurons. To address this, it is important to record simultaneously from hundreds of neurons at a spacing that matches typical axonal connection distances, and at a temporal resolution that matches synaptic delays. We used a 512-electrode array (60 μm spacing) to record spontaneous activity at 20 kHz from up to 500 neurons simultaneously in slice cultures of mouse somatosensory cortex for 1 h at a time. We applied a previously validated version of transfer entropy to quantify information transfer. Similar to in vivo reports, we found an approximately lognormal distribution of firing rates. Pairwise information transfer strengths also were nearly lognormally distributed, similar to reports of synaptic strengths. Some neurons transferred and received much more information than others, which is consistent with previous predictions. Neurons with the highest outgoing and incoming information transfer were more strongly connected to each other than chance, thus forming a “rich club.” We found similar results in networks recorded in vivo from rodent cortex, suggesting the generality of these findings. A rich-club structure has been found previously in large-scale human brain networks and is thought to facilitate communication between cortical regions. The discovery of a small, but information-rich, subset of neurons within cortical regions suggests that this population will play a vital role in communication, learning, and memory. SIGNIFICANCE STATEMENT Many studies have focused on communication networks between cortical brain regions. In contrast, very few studies have examined communication networks within a cortical region. This is the first study to combine such a large number of neurons (several

  16. The dynamics of integrate-and-fire: mean versus variance modulations and dependence on baseline parameters.

    Science.gov (United States)

    Pressley, Joanna; Troyer, Todd W

    2011-05-01

    The leaky integrate-and-fire (LIF) is the simplest neuron model that captures the essential properties of neuronal signaling. Yet common intuitions are inadequate to explain basic properties of LIF responses to sinusoidal modulations of the input. Here we examine responses to low and moderate frequency modulations of both the mean and variance of the input current and quantify how these responses depend on baseline parameters. Across parameters, responses to modulations in the mean current are low pass, approaching zero in the limit of high frequencies. For very low baseline firing rates, the response cutoff frequency matches that expected from membrane integration. However, the cutoff shows a rapid, supralinear increase with firing rate, with a steeper increase in the case of lower noise. For modulations of the input variance, the gain at high frequency remains finite. Here, we show that the low-frequency responses depend strongly on baseline parameters and derive an analytic condition specifying the parameters at which responses switch from being dominated by low versus high frequencies. Additionally, we show that the resonant responses for variance modulations have properties not expected for common oscillatory resonances: they peak at frequencies higher than the baseline firing rate and persist when oscillatory spiking is disrupted by high noise. Finally, the responses to mean and variance modulations are shown to have a complementary dependence on baseline parameters at higher frequencies, resulting in responses to modulations of Poisson input rates that are independent of baseline input statistics.

  17. Characterization of modulated integrate-and-fire systems

    International Nuclear Information System (INIS)

    Alstroem, P.; Christiansen, B.; Levinsen, M.T.

    1988-01-01

    The phase locking structure in threshold modulated integrate-and-fire systems is explored. The existence of a smooth critical line where the Poincare map has an infinite slope inflection point is emphasized. At and below this line the system is related to circle map systems. Especially, this allows realization of systems with higher order scaling structures, qualitatively distinct from ordinary third order circle map structures. Hourglass patterns develop in parameter space and at small modulation amplitudes the behavior of the phase-locking regions (Arnold tongues) change dramatically. Above the critical line the Arnold tongues complete the parameter space, leaving along any line a zero-dimensional Cantor set of points associated with irrational rotation numbers. The critical line is not associated with a transition to chaos. In particular non-chaotic regions with complete phase-locking exist. In the supercritical region a gap is present in the Poincare map. The features at this gap are examined. Also local hysteresis may occur. We discuss the applicability of the local approximation. (orig.)

  18. Dynamics and spike trains statistics in conductance-based integrate-and-fire neural networks with chemical and electric synapses

    International Nuclear Information System (INIS)

    Cofré, Rodrigo; Cessac, Bruno

    2013-01-01

    We investigate the effect of electric synapses (gap junctions) on collective neuronal dynamics and spike statistics in a conductance-based integrate-and-fire neural network, driven by Brownian noise, where conductances depend upon spike history. We compute explicitly the time evolution operator and show that, given the spike-history of the network and the membrane potentials at a given time, the further dynamical evolution can be written in a closed form. We show that spike train statistics is described by a Gibbs distribution whose potential can be approximated with an explicit formula, when the noise is weak. This potential form encompasses existing models for spike trains statistics analysis such as maximum entropy models or generalized linear models (GLM). We also discuss the different types of correlations: those induced by a shared stimulus and those induced by neurons interactions

  19. Integrate-and-fire vs Poisson models of LGN input to V1 cortex: noisier inputs reduce orientation selectivity.

    Science.gov (United States)

    Lin, I-Chun; Xing, Dajun; Shapley, Robert

    2012-12-01

    One of the reasons the visual cortex has attracted the interest of computational neuroscience is that it has well-defined inputs. The lateral geniculate nucleus (LGN) of the thalamus is the source of visual signals to the primary visual cortex (V1). Most large-scale cortical network models approximate the spike trains of LGN neurons as simple Poisson point processes. However, many studies have shown that neurons in the early visual pathway are capable of spiking with high temporal precision and their discharges are not Poisson-like. To gain an understanding of how response variability in the LGN influences the behavior of V1, we study response properties of model V1 neurons that receive purely feedforward inputs from LGN cells modeled either as noisy leaky integrate-and-fire (NLIF) neurons or as inhomogeneous Poisson processes. We first demonstrate that the NLIF model is capable of reproducing many experimentally observed statistical properties of LGN neurons. Then we show that a V1 model in which the LGN input to a V1 neuron is modeled as a group of NLIF neurons produces higher orientation selectivity than the one with Poisson LGN input. The second result implies that statistical characteristics of LGN spike trains are important for V1's function. We conclude that physiologically motivated models of V1 need to include more realistic LGN spike trains that are less noisy than inhomogeneous Poisson processes.

  20. Partial synchronization of relaxation oscillators with repulsive coupling in autocatalytic integrate-and-fire model and electrochemical experiments

    Science.gov (United States)

    Kori, Hiroshi; Kiss, István Z.; Jain, Swati; Hudson, John L.

    2018-04-01

    Experiments and supporting theoretical analysis are presented to describe the synchronization patterns that can be observed with a population of globally coupled electrochemical oscillators close to a homoclinic, saddle-loop bifurcation, where the coupling is repulsive in the electrode potential. While attractive coupling generates phase clusters and desynchronized states, repulsive coupling results in synchronized oscillations. The experiments are interpreted with a phenomenological model that captures the waveform of the oscillations (exponential increase) followed by a refractory period. The globally coupled autocatalytic integrate-and-fire model predicts the development of partially synchronized states that occur through attracting heteroclinic cycles between out-of-phase two-cluster states. Similar behavior can be expected in many other systems where the oscillations occur close to a saddle-loop bifurcation, e.g., with Morris-Lecar neurons.

  1. Functional Connectome Analysis of Dopamine Neuron Glutamatergic Connections in Forebrain Regions.

    Science.gov (United States)

    Mingote, Susana; Chuhma, Nao; Kusnoor, Sheila V; Field, Bianca; Deutch, Ariel Y; Rayport, Stephen

    2015-12-09

    In the ventral tegmental area (VTA), a subpopulation of dopamine neurons express vesicular glutamate transporter 2 and make glutamatergic connections to nucleus accumbens (NAc) and olfactory tubercle (OT) neurons. However, their glutamatergic connections across the forebrain have not been explored systematically. To visualize dopamine neuron forebrain projections and to enable photostimulation of their axons independent of transmitter status, we virally transfected VTA neurons with channelrhodopsin-2 fused to enhanced yellow fluorescent protein (ChR2-EYFP) and used DAT(IREScre) mice to restrict expression to dopamine neurons. ChR2-EYFP-expressing neurons almost invariably stained for tyrosine hydroxylase, identifying them as dopaminergic. Dopamine neuron axons visualized by ChR2-EYFP fluorescence projected most densely to the striatum, moderately to the amygdala and entorhinal cortex (ERC), sparsely to prefrontal and cingulate cortices, and rarely to the hippocampus. Guided by ChR2-EYFP fluorescence, we recorded systematically from putative principal neurons in target areas and determined the incidence and strength of glutamatergic connections by activating all dopamine neuron terminals impinging on recorded neurons with wide-field photostimulation. This revealed strong glutamatergic connections in the NAc, OT, and ERC; moderate strength connections in the central amygdala; and weak connections in the cingulate cortex. No glutamatergic connections were found in the dorsal striatum, hippocampus, basolateral amygdala, or prefrontal cortex. These results indicate that VTA dopamine neurons elicit widespread, but regionally distinct, glutamatergic signals in the forebrain and begin to define the dopamine neuron excitatory functional connectome. Dopamine neurons are important for the control of motivated behavior and are involved in the pathophysiology of several major neuropsychiatric disorders. Recent studies have shown that some ventral midbrain dopamine neurons are

  2. Interspike interval correlation in a stochastic exponential integrate-and-fire model with subthreshold and spike-triggered adaptation.

    Science.gov (United States)

    Shiau, LieJune; Schwalger, Tilo; Lindner, Benjamin

    2015-06-01

    We study the spike statistics of an adaptive exponential integrate-and-fire neuron stimulated by white Gaussian current noise. We derive analytical approximations for the coefficient of variation and the serial correlation coefficient of the interspike interval assuming that the neuron operates in the mean-driven tonic firing regime and that the stochastic input is weak. Our result for the serial correlation coefficient has the form of a geometric sequence and is confirmed by the comparison to numerical simulations. The theory predicts various patterns of interval correlations (positive or negative at lag one, monotonically decreasing or oscillating) depending on the strength of the spike-triggered and subthreshold components of the adaptation current. In particular, for pure subthreshold adaptation we find strong positive ISI correlations that are usually ascribed to positive correlations in the input current. Our results i) provide an alternative explanation for interspike-interval correlations observed in vivo, ii) may be useful in fitting point neuron models to experimental data, and iii) may be instrumental in exploring the role of adaptation currents for signal detection and signal transmission in single neurons.

  3. 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

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

    Directory of Open Access Journals (Sweden)

    Sadra Sadeh

    2015-01-01

    Full Text Available 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

  5. Neuroeffector connections of giant multimodal neurons in the African snail Achatina fulica.

    Science.gov (United States)

    Bugai, V V; Zhuravlev, V L; Safonova, T A

    2005-07-01

    A new method of making preparations was used to analyse the neuroeffector connections of the paired giant neurons of the African snail Achatina fulica. These neurons were found to induce postsynaptic potentials in the muscles of the mantle, heart, the wall of the pulmonary cavity, and the muscular elements of the renal complex, the pericardium, the sexual apparatus, the walls of the cerebral arteries, the filaments of the columellar muscles, the wall of the abdomen, and the tentacle retractor muscles. Rhythmic neuron activity led to the development of marked facilitation and long-term potentiation of synaptic potentials. The possible significance of the multiple neuroeffector connections of giant neurons is discussed.

  6. A spiking neuron circuit based on a carbon nanotube transistor

    International Nuclear Information System (INIS)

    Chen, C-L; Kim, K; Truong, Q; Shen, A; Li, Z; Chen, Y

    2012-01-01

    A spiking neuron circuit based on a carbon nanotube (CNT) transistor is presented in this paper. The spiking neuron circuit has a crossbar architecture in which the transistor gates are connected to its row electrodes and the transistor sources are connected to its column electrodes. An electrochemical cell is incorporated in the gate of the transistor by sandwiching a hydrogen-doped poly(ethylene glycol)methyl ether (PEG) electrolyte between the CNT channel and the top gate electrode. An input spike applied to the gate triggers a dynamic drift of the hydrogen ions in the PEG electrolyte, resulting in a post-synaptic current (PSC) through the CNT channel. Spikes input into the rows trigger PSCs through multiple CNT transistors, and PSCs cumulate in the columns and integrate into a ‘soma’ circuit to trigger output spikes based on an integrate-and-fire mechanism. The spiking neuron circuit can potentially emulate biological neuron networks and their intelligent functions. (paper)

  7. Analysis of connectivity map: Control to glutamate injured and phenobarbital treated neuronal network

    Science.gov (United States)

    Kamal, Hassan; Kanhirodan, Rajan; Srinivas, Kalyan V.; Sikdar, Sujit K.

    2010-04-01

    We study the responses of a cultured neural network when it is exposed to epileptogenesis glutamate injury causing epilepsy and subsequent treatment with phenobarbital by constructing connectivity map of neurons using correlation matrix. This study is particularly useful in understanding the pharmaceutical drug induced changes in the neuronal network properties with insights into changes at the systems biology level.

  8. The connection-set algebra--a novel formalism for the representation of connectivity structure in neuronal network models.

    Science.gov (United States)

    Djurfeldt, Mikael

    2012-07-01

    The connection-set algebra (CSA) is a novel and general formalism for the description of connectivity in neuronal network models, from small-scale to large-scale structure. The algebra provides operators to form more complex sets of connections from simpler ones and also provides parameterization of such sets. CSA is expressive enough to describe a wide range of connection patterns, including multiple types of random and/or geometrically dependent connectivity, and can serve as a concise notation for network structure in scientific writing. CSA implementations allow for scalable and efficient representation of connectivity in parallel neuronal network simulators and could even allow for avoiding explicit representation of connections in computer memory. The expressiveness of CSA makes prototyping of network structure easy. A C+ + version of the algebra has been implemented and used in a large-scale neuronal network simulation (Djurfeldt et al., IBM J Res Dev 52(1/2):31-42, 2008b) and an implementation in Python has been publicly released.

  9. NeuroLines: A Subway Map Metaphor for Visualizing Nanoscale Neuronal Connectivity

    KAUST Repository

    Al-Awami, Ali K.

    2014-12-31

    We present NeuroLines, a novel visualization technique designed for scalable detailed analysis of neuronal connectivity at the nanoscale level. The topology of 3D brain tissue data is abstracted into a multi-scale, relative distance-preserving subway map visualization that allows domain scientists to conduct an interactive analysis of neurons and their connectivity. Nanoscale connectomics aims at reverse-engineering the wiring of the brain. Reconstructing and analyzing the detailed connectivity of neurons and neurites (axons, dendrites) will be crucial for understanding the brain and its development and diseases. However, the enormous scale and complexity of nanoscale neuronal connectivity pose big challenges to existing visualization techniques in terms of scalability. NeuroLines offers a scalable visualization framework that can interactively render thousands of neurites, and that supports the detailed analysis of neuronal structures and their connectivity. We describe and analyze the design of NeuroLines based on two real-world use-cases of our collaborators in developmental neuroscience, and investigate its scalability to large-scale neuronal connectivity data.

  10. NeuroLines: A Subway Map Metaphor for Visualizing Nanoscale Neuronal Connectivity

    KAUST Repository

    Al-Awami, Ali K.; Beyer, Johanna; Strobelt, Hendrik; Kasthuri, Narayanan; Lichtman, Jeff W.; Pfister, Hanspeter; Hadwiger, Markus

    2014-01-01

    We present NeuroLines, a novel visualization technique designed for scalable detailed analysis of neuronal connectivity at the nanoscale level. The topology of 3D brain tissue data is abstracted into a multi-scale, relative distance-preserving subway map visualization that allows domain scientists to conduct an interactive analysis of neurons and their connectivity. Nanoscale connectomics aims at reverse-engineering the wiring of the brain. Reconstructing and analyzing the detailed connectivity of neurons and neurites (axons, dendrites) will be crucial for understanding the brain and its development and diseases. However, the enormous scale and complexity of nanoscale neuronal connectivity pose big challenges to existing visualization techniques in terms of scalability. NeuroLines offers a scalable visualization framework that can interactively render thousands of neurites, and that supports the detailed analysis of neuronal structures and their connectivity. We describe and analyze the design of NeuroLines based on two real-world use-cases of our collaborators in developmental neuroscience, and investigate its scalability to large-scale neuronal connectivity data.

  11. NeuroLines: A Subway Map Metaphor for Visualizing Nanoscale Neuronal Connectivity.

    Science.gov (United States)

    Al-Awami, Ali K; Beyer, Johanna; Strobelt, Hendrik; Kasthuri, Narayanan; Lichtman, Jeff W; Pfister, Hanspeter; Hadwiger, Markus

    2014-12-01

    We present NeuroLines, a novel visualization technique designed for scalable detailed analysis of neuronal connectivity at the nanoscale level. The topology of 3D brain tissue data is abstracted into a multi-scale, relative distance-preserving subway map visualization that allows domain scientists to conduct an interactive analysis of neurons and their connectivity. Nanoscale connectomics aims at reverse-engineering the wiring of the brain. Reconstructing and analyzing the detailed connectivity of neurons and neurites (axons, dendrites) will be crucial for understanding the brain and its development and diseases. However, the enormous scale and complexity of nanoscale neuronal connectivity pose big challenges to existing visualization techniques in terms of scalability. NeuroLines offers a scalable visualization framework that can interactively render thousands of neurites, and that supports the detailed analysis of neuronal structures and their connectivity. We describe and analyze the design of NeuroLines based on two real-world use-cases of our collaborators in developmental neuroscience, and investigate its scalability to large-scale neuronal connectivity data.

  12. Pseudorabies virus infection alters neuronal activity and connectivity in vitro.

    Directory of Open Access Journals (Sweden)

    Kelly M McCarthy

    2009-10-01

    Full Text Available Alpha-herpesviruses, including human herpes simplex virus 1 & 2, varicella zoster virus and the swine pseudorabies virus (PRV, infect the peripheral nervous system of their hosts. Symptoms of infection often include itching, numbness, or pain indicative of altered neurological function. To determine if there is an in vitro electrophysiological correlate to these characteristic in vivo symptoms, we infected cultured rat sympathetic neurons with well-characterized strains of PRV known to produce virulent or attenuated symptoms in animals. Whole-cell patch clamp recordings were made at various times after infection. By 8 hours of infection with virulent PRV, action potential (AP firing rates increased substantially and were accompanied by hyperpolarized resting membrane potentials and spikelet-like events. Coincident with the increase in AP firing rate, adjacent neurons exhibited coupled firing events, first with AP-spikelets and later with near identical resting membrane potentials and AP firing. Small fusion pores between adjacent cell bodies formed early after infection as demonstrated by transfer of the low molecular weight dye, Lucifer Yellow. Later, larger pores formed as demonstrated by transfer of high molecular weight Texas red-dextran conjugates between infected cells. Further evidence for viral-induced fusion pores was obtained by infecting neurons with a viral mutant defective for glycoprotein B, a component of the viral membrane fusion complex. These infected neurons were essentially identical to mock infected neurons: no increased AP firing, no spikelet-like events, and no electrical or dye transfer. Infection with PRV Bartha, an attenuated circuit-tracing strain delayed, but did not eliminate the increased neuronal activity and coupling events. We suggest that formation of fusion pores between infected neurons results in electrical coupling and elevated firing rates, and that these processes may contribute to the altered neural

  13. [Neuroeffector connections of multimodal neurons in the African snail (Achatina fulica)].

    Science.gov (United States)

    Bugaĭ, V V; Zhuravlev, V L; Safonova, T A

    2004-02-01

    Using a new method of animal preparation, the efferent connections of giant paired neurons on the dorsal surface of visceral and right parietal ganglia of snail, Achatina fulica, were examined. It was found that spikes in giant neurons d-VLN and d-RPLN evoke postjunctional potentials in different points of the snail body and viscerae (in the heart, in pericardium, in lung cavity and kidney walls, in mantle and body wall muscles, in tentacle retractors and in cephalic artery). The preliminary analysis of synaptic latency and facilitation suggests a direct connections between giant neurons and investigated efferents.

  14. Fractional-order leaky integrate-and-fire model with long-term memory and power law dynamics.

    Science.gov (United States)

    Teka, Wondimu W; Upadhyay, Ranjit Kumar; Mondal, Argha

    2017-09-01

    Pyramidal neurons produce different spiking patterns to process information, communicate with each other and transform information. These spiking patterns have complex and multiple time scale dynamics that have been described with the fractional-order leaky integrate-and-Fire (FLIF) model. Models with fractional (non-integer) order differentiation that generalize power law dynamics can be used to describe complex temporal voltage dynamics. The main characteristic of FLIF model is that it depends on all past values of the voltage that causes long-term memory. The model produces spikes with high interspike interval variability and displays several spiking properties such as upward spike-frequency adaptation and long spike latency in response to a constant stimulus. We show that the subthreshold voltage and the firing rate of the fractional-order model make transitions from exponential to power law dynamics when the fractional order α decreases from 1 to smaller values. The firing rate displays different types of spike timing adaptation caused by changes on initial values. We also show that the voltage-memory trace and fractional coefficient are the causes of these different types of spiking properties. The voltage-memory trace that represents the long-term memory has a feedback regulatory mechanism and affects spiking activity. The results suggest that fractional-order models might be appropriate for understanding multiple time scale neuronal dynamics. Overall, a neuron with fractional dynamics displays history dependent activities that might be very useful and powerful for effective information processing. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Effect of stimulation on the input parameters of stochastic leaky integrate-and-fire neuronal model

    Czech Academy of Sciences Publication Activity Database

    Lánský, Petr; Šanda, Pavel; He, J.

    2010-01-01

    Roč. 104, 3-4 (2010), s. 160-166 ISSN 0928-4257 R&D Projects: GA MŠk(CZ) LC554; GA AV ČR(CZ) IAA101120604 Institutional research plan: CEZ:AV0Z50110509 Keywords : membrane depolarization * input parameters * diffusion Subject RIV: BO - Biophysics Impact factor: 3.030, year: 2010

  16. Walk like me, talk like me. The connection between mirror neurons and autism spectrum disorder.

    Science.gov (United States)

    Saffin, Jillian M; Tohid, Hassaan

    2016-04-01

    Understanding social cognition has become a hallmark in deciphering autism spectrum disorder. Neurobiological theories are taking precedence in causation studies as researchers look to abnormalities in brain development as the cause of deficits in social behavior, cognitive processes, and language. Following their discovery in the 1990s, mirror neurons have become a dominant theory for that the mirror neuron system may play a critical role in the pathophysiology of various symptoms of autism. Over the decades, the theory has evolved from the suggestion of a broken mirror neuron system to impairments in mirror neuron circuitry. The mirror neuron system has not gained total support due to inconsistent findings; a comprehensive analysis of the growing body of research could shed light on the benefits, or the disadvantage of continuing to study mirror neurons and their connection to autism.

  17. Optimal and Local Connectivity Between Neuron and Synapse Array in the Quantum Dot/Silicon Brain

    Science.gov (United States)

    Duong, Tuan A.; Assad, Christopher; Thakoor, Anikumar P.

    2010-01-01

    This innovation is used to connect between synapse and neuron arrays using nanowire in quantum dot and metal in CMOS (complementary metal oxide semiconductor) technology to enable the density of a brain-like connection in hardware. The hardware implementation combines three technologies: 1. Quantum dot and nanowire-based compact synaptic cell (50x50 sq nm) with inherently low parasitic capacitance (hence, low dynamic power approx.l0(exp -11) watts/synapse), 2. Neuron and learning circuits implemented in 50-nm CMOS technology, to be integrated with quantum dot and nanowire synapse, and 3. 3D stacking approach to achieve the overall numbers of high density O(10(exp 12)) synapses and O(10(exp 8)) neurons in the overall system. In a 1-sq cm of quantum dot layer sitting on a 50-nm CMOS layer, innovators were able to pack a 10(exp 6)-neuron and 10(exp 10)-synapse array; however, the constraint for the connection scheme is that each neuron will receive a non-identical 10(exp 4)-synapse set, including itself, via its efficacy of the connection. This is not a fully connected system where the 100x100 synapse array only has a 100-input data bus and 100-output data bus. Due to the data bus sharing, it poses a great challenge to have a complete connected system, and its constraint within the quantum dot and silicon wafer layer. For an effective connection scheme, there are three conditions to be met: 1. Local connection. 2. The nanowire should be connected locally, not globally from which it helps to maximize the data flow by sharing the same wire space location. 3. Each synapse can have an alternate summation line if needed (this option is doable based on the simple mask creation). The 10(exp 3)x10(exp 3)-neuron array was partitioned into a 10-block, 10(exp 2)x10(exp 3)-neuron array. This building block can be completely mapped within itself (10,000 synapses to a neuron).

  18. A critical period for experience-dependent remodeling of adult-born neuron connectivity.

    Science.gov (United States)

    Bergami, Matteo; Masserdotti, Giacomo; Temprana, Silvio G; Motori, Elisa; Eriksson, Therese M; Göbel, Jana; Yang, Sung Min; Conzelmann, Karl-Klaus; Schinder, Alejandro F; Götz, Magdalena; Berninger, Benedikt

    2015-02-18

    Neurogenesis in the dentate gyrus (DG) of the adult hippocampus is a process regulated by experience. To understand whether experience also modifies the connectivity of new neurons, we systematically investigated changes in their innervation following environmental enrichment (EE). We found that EE exposure between 2-6 weeks following neuron birth, rather than merely increasing the number of new neurons, profoundly affected their pattern of monosynaptic inputs. Both local innervation by interneurons and to even greater degree long-distance innervation by cortical neurons were markedly enhanced. Furthermore, following EE, new neurons received inputs from CA3 and CA1 inhibitory neurons that were rarely observed under control conditions. While EE-induced changes in inhibitory innervation were largely transient, cortical innervation remained increased after returning animals to control conditions. Our findings demonstrate an unprecedented experience-dependent reorganization of connections impinging onto adult-born neurons, which is likely to have important impact on their contribution to hippocampal information processing. Copyright © 2015 Elsevier Inc. All rights reserved.

  19. Storage of phase-coded patterns via STDP in fully-connected and sparse network: a study of the network capacity

    Directory of Open Access Journals (Sweden)

    Silvia Scarpetta

    2010-08-01

    Full Text Available We study the storage and retrieval of phase-coded patterns as stable dynamical attractors in recurrent neural networks, for both an analog and a integrate-and-fire spiking model. The synaptic strength is determined by a learning rule based on spike-time-dependent plasticity, with an asymmetric time window depending on the relative timing between pre- and post-synaptic activity. We store multiple patterns and study the network capacity. For the analog model, we find that the network capacity scales linearly with the network size, and that both capacity and the oscillation frequency of the retrieval state depend on the asymmetry of the learning time window. In addition to fully-connected networks, we study sparse networks, where each neuron is connected only to a small number $zll N$ of other neurons. Connections can be short range, between neighboring neurons placed on a regular lattice, or long range, between randomly chosen pairs of neurons. We find that a small fraction of long range connections is able to amplify the capacity of the network. This imply that a small-world-network topology is optimal, as a compromise between the cost of long range connections and the capacity increase. Also in the spiking integrate and fire model the crucial result of storing and retrieval of multiple phase-coded patterns is observed. The capacity of the fully-connected spiking network is investigated, together with the relation between oscillation frequency of retrieval state and window asymmetry.

  20. Schaffer collateral inputs to CA1 excitatory and inhibitory neurons follow different connectivity rules.

    Science.gov (United States)

    Kwon, Osung; Feng, Linqing; Druckmann, Shaul; Kim, Jinhyun

    2018-05-04

    Neural circuits, governed by a complex interplay between excitatory and inhibitory neurons, are the substrate for information processing, and the organization of synaptic connectivity in neural network is an important determinant of circuit function. Here, we analyzed the fine structure of connectivity in hippocampal CA1 excitatory and inhibitory neurons innervated by Schaffer collaterals (SCs) using mGRASP in male mice. Our previous study revealed spatially structured synaptic connectivity between CA3-CA1 pyramidal cells (PCs). Surprisingly, parvalbumin-positive interneurons (PVs) showed a significantly more random pattern spatial structure. Notably, application of Peters' Rule for synapse prediction by random overlap between axons and dendrites enhanced structured connectivity in PCs, but, by contrast, made the connectivity pattern in PVs more random. In addition, PCs in a deep sublayer of striatum pyramidale appeared more highly structured than PCs in superficial layers, and little or no sublayer specificity was found in PVs. Our results show that CA1 excitatory PCs and inhibitory PVs innervated by the same SC inputs follow different connectivity rules. The different organizations of fine scale structured connectivity in hippocampal excitatory and inhibitory neurons provide important insights into the development and functions of neural networks. SIGNIFICANCE STATEMENT Understanding how neural circuits generate behavior is one of the central goals of neuroscience. An important component of this endeavor is the mapping of fine-scale connection patterns that underlie, and help us infer, signal processing in the brain. Here, using our recently developed synapse detection technology (mGRASP and neuTube), we provide detailed profiles of synaptic connectivity in excitatory (CA1 pyramidal) and inhibitory (CA1 parvalbumin-positive) neurons innervated by the same presynaptic inputs (CA3 Schaffer collaterals). Our results reveal that these two types of CA1 neurons follow

  1. Three Types of Cortical L5 Neurons that Differ in Brain-Wide Connectivity and Function

    Science.gov (United States)

    Kim, Euiseok J.; Juavinett, Ashley L.; Kyubwa, Espoir M.; Jacobs, Matthew W.; Callaway, Edward M.

    2015-01-01

    SUMMARY Cortical layer 5 (L5) pyramidal neurons integrate inputs from many sources and distribute outputs to cortical and subcortical structures. Previous studies demonstrate two L5 pyramid types: cortico-cortical (CC) and cortico-subcortical (CS). We characterize connectivity and function of these cell types in mouse primary visual cortex and reveal a new subtype. Unlike previously described L5 CC and CS neurons, this new subtype does not project to striatum [cortico-cortical, non-striatal (CC-NS)] and has distinct morphology, physiology and visual responses. Monosynaptic rabies tracing reveals that CC neurons preferentially receive input from higher visual areas, while CS neurons receive more input from structures implicated in top-down modulation of brain states. CS neurons are also more direction-selective and prefer faster stimuli than CC neurons. These differences suggest distinct roles as specialized output channels, with CS neurons integrating information and generating responses more relevant to movement control and CC neurons being more important in visual perception. PMID:26671462

  2. Three Types of Cortical Layer 5 Neurons That Differ in Brain-wide Connectivity and Function.

    Science.gov (United States)

    Kim, Euiseok J; Juavinett, Ashley L; Kyubwa, Espoir M; Jacobs, Matthew W; Callaway, Edward M

    2015-12-16

    Cortical layer 5 (L5) pyramidal neurons integrate inputs from many sources and distribute outputs to cortical and subcortical structures. Previous studies demonstrate two L5 pyramid types: cortico-cortical (CC) and cortico-subcortical (CS). We characterize connectivity and function of these cell types in mouse primary visual cortex and reveal a new subtype. Unlike previously described L5 CC and CS neurons, this new subtype does not project to striatum [cortico-cortical, non-striatal (CC-NS)] and has distinct morphology, physiology, and visual responses. Monosynaptic rabies tracing reveals that CC neurons preferentially receive input from higher visual areas, while CS neurons receive more input from structures implicated in top-down modulation of brain states. CS neurons are also more direction-selective and prefer faster stimuli than CC neurons. These differences suggest distinct roles as specialized output channels, with CS neurons integrating information and generating responses more relevant to movement control and CC neurons being more important in visual perception. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. Altering neuronal excitability to preserve network connectivity in a computational model of Alzheimer's disease.

    Directory of Open Access Journals (Sweden)

    Willem de Haan

    2017-09-01

    Full Text Available Neuronal hyperactivity and hyperexcitability of the cerebral cortex and hippocampal region is an increasingly observed phenomenon in preclinical Alzheimer's disease (AD. In later stages, oscillatory slowing and loss of functional connectivity are ubiquitous. Recent evidence suggests that neuronal dynamics have a prominent role in AD pathophysiology, making it a potentially interesting therapeutic target. However, although neuronal activity can be manipulated by various (non-pharmacological means, intervening in a highly integrated system that depends on complex dynamics can produce counterintuitive and adverse effects. Computational dynamic network modeling may serve as a virtual test ground for developing effective interventions. To explore this approach, a previously introduced large-scale neural mass network with human brain topology was used to simulate the temporal evolution of AD-like, activity-dependent network degeneration. In addition, six defense strategies that either enhanced or diminished neuronal excitability were tested against the degeneration process, targeting excitatory and inhibitory neurons combined or separately. Outcome measures described oscillatory, connectivity and topological features of the damaged networks. Over time, the various interventions produced diverse large-scale network effects. Contrary to our hypothesis, the most successful strategy was a selective stimulation of all excitatory neurons in the network; it substantially prolonged the preservation of network integrity. The results of this study imply that functional network damage due to pathological neuronal activity can be opposed by targeted adjustment of neuronal excitability levels. The present approach may help to explore therapeutic effects aimed at preserving or restoring neuronal network integrity and contribute to better-informed intervention choices in future clinical trials in AD.

  4. Voltage imaging to understand connections and functions of neuronal circuits

    Science.gov (United States)

    Antic, Srdjan D.; Empson, Ruth M.

    2016-01-01

    Understanding of the cellular mechanisms underlying brain functions such as cognition and emotions requires monitoring of membrane voltage at the cellular, circuit, and system levels. Seminal voltage-sensitive dye and calcium-sensitive dye imaging studies have demonstrated parallel detection of electrical activity across populations of interconnected neurons in a variety of preparations. A game-changing advance made in recent years has been the conceptualization and development of optogenetic tools, including genetically encoded indicators of voltage (GEVIs) or calcium (GECIs) and genetically encoded light-gated ion channels (actuators, e.g., channelrhodopsin2). Compared with low-molecular-weight calcium and voltage indicators (dyes), the optogenetic imaging approaches are 1) cell type specific, 2) less invasive, 3) able to relate activity and anatomy, and 4) facilitate long-term recordings of individual cells' activities over weeks, thereby allowing direct monitoring of the emergence of learned behaviors and underlying circuit mechanisms. We highlight the potential of novel approaches based on GEVIs and compare those to calcium imaging approaches. We also discuss how novel approaches based on GEVIs (and GECIs) coupled with genetically encoded actuators will promote progress in our knowledge of brain circuits and systems. PMID:27075539

  5. Tracking Neuronal Connectivity from Electric Brain Signals to Predict Performance.

    Science.gov (United States)

    Vecchio, Fabrizio; Miraglia, Francesca; Rossini, Paolo Maria

    2018-05-01

    The human brain is a complex container of interconnected networks. Network neuroscience is a recent venture aiming to explore the connection matrix built from the human brain or human "Connectome." Network-based algorithms provide parameters that define global organization of the brain; when they are applied to electroencephalographic (EEG) signals network, configuration and excitability can be monitored in millisecond time frames, providing remarkable information on their instantaneous efficacy also for a given task's performance via online evaluation of the underlying instantaneous networks before, during, and after the task. Here we provide an updated summary on the connectome analysis for the prediction of performance via the study of task-related dynamics of brain network organization from EEG signals.

  6. Connectivity, excitability and activity patterns in neuronal networks

    International Nuclear Information System (INIS)

    Le Feber, Joost; Stoyanova, Irina I; Chiappalone, Michela

    2014-01-01

    Extremely synchronized firing patterns such as those observed in brain diseases like epilepsy may result from excessive network excitability. Although network excitability is closely related to (excitatory) connectivity, a direct measure for network excitability remains unavailable. Several methods currently exist for estimating network connectivity, most of which are related to cross-correlation. An example is the conditional firing probability (CFP) analysis which calculates the pairwise probability (CFP i,j ) that electrode j records an action potential at time t = τ, given that electrode i recorded a spike at t = 0. However, electrode i often records multiple spikes within the analysis interval, and CFP values are biased by the on-going dynamic state of the network. Here we show that in a linear approximation this bias may be removed by deconvoluting CFP i,j with the autocorrelation of i (i.e. CFP i,i ), to obtain the single pulse response (SPR i,j )—the average response at electrode j to a single spike at electrode i. Thus, in a linear system SPRs would be independent of the dynamic network state. Nonlinear components of synaptic transmission, such as facilitation and short term depression, will however still affect SPRs. Therefore SPRs provide a clean measure of network excitability. We used carbachol and ghrelin to moderately activate cultured cortical networks to affect their dynamic state. Both neuromodulators transformed the bursting firing patterns of the isolated networks into more dispersed firing. We show that the influence of the dynamic state on SPRs is much smaller than the effect on CFPs, but not zero. The remaining difference reflects the alteration in network excitability. We conclude that SPRs are less contaminated by the dynamic network state and that mild excitation may decrease network excitability, possibly through short term synaptic depression. (papers)

  7. Synaptic Dynamics and Neuronal Network Connectivity are reflected in the Distribution of Times in Up states

    Directory of Open Access Journals (Sweden)

    Khanh eDao Duc

    2015-07-01

    Full Text Available The dynamics of neuronal networks connected by synaptic dynamics can sustain long periods of depolarization that can last for hundreds of milliseconds such as Up states recorded during sleep or anesthesia. Yet the underlying mechanism driving these periods remain unclear. We show here within a mean-field model that the residence times of the neuronal membrane potential in cortical Up states does not follow a Poissonian law, but presents several peaks. Furthermore, the present modeling approach allows extracting some information about the neuronal network connectivity from the time distribution histogram. Based on a synaptic-depression model, we find that these peaks, that can be observed in histograms of patch-clamp recordings are not artifacts of electrophysiological measurements, but rather are an inherent property of the network dynamics. Analysis of the equations reveals a stable focus located close to the unstable limit cycle, delimiting a region that defines the Up state. The model further shows that the peaks observed in the Up state time distribution are due to winding around the focus before escaping from the basin of attraction. Finally, we use in vivo recordings of intracellular membrane potential and we recover from the peak distribution, some information about the network connectivity. We conclude that it is possible to recover the network connectivity from the distribution of times that the neuronal membrane voltage spends in Up states.

  8. Monosynaptic connections between primary afferents and giant neurons in the turtle spinal dorsal horn

    DEFF Research Database (Denmark)

    Fernández, A; Radmilovich, M; Russo, R E

    1996-01-01

    This paper reports the occurrence of monosynaptic connections between dorsal root afferents and a distinct cell type-the giant neuron-deep in the dorsal horn of the turtle spinal cord. Light microscope studies combining Nissl stain and transganglionic HRP-labeling of the primary afferents have...

  9. A riddled basin escaping crisis and the universality in an integrate-and-fire circuit

    Science.gov (United States)

    Dai, Jun; He, Da-Ren; Xu, Xiu-Lian; Hu, Chin-Kun

    2018-06-01

    We investigate an integrate-and-fire model of an electronic relaxation oscillator, which can be described by the discontinuous and non-invertible composition of two mapping functions f1 and f2, with f1 being dissipative. Depending on a control parameter d, f2 can be conservative (for d =dc = 1) or dissipative (for d >dc). We find a kind of crisis, which is induced by the escape from a riddled-like attraction basin sea in the phase space. The averaged crisis transient lifetime (〈 τ 〉), the relative measure of the fat fractal forbidden network (η), and the measure of the escaping hole (Δ) show clear scaling behaviors: 〈 τ 〉 ∝(d -dc) - γ, η ∝(d -dc) σ, and Δ ∝(d -dc) α. Extending an argument by Jiang et al. (2004), we derive γ = σ + α, which agrees well with numerical simulation data.

  10. Efficient generation of connectivity in neuronal networks from simulator-independent descriptions

    Directory of Open Access Journals (Sweden)

    Mikael eDjurfeldt

    2014-04-01

    Full Text Available Simulator-independent descriptions of connectivity in neuronal networks promise greater ease of model sharing, improved reproducibility of simulation results, and reduced programming effort for computational neuroscientists. However, until now, enabling the use of such descriptions in a given simulator in a computationally efficient way has entailed considerable work for simulator developers, which must be repeated for each new connectivity-generating library that is developed.We have developed a generic connection generator interface that provides a standard way to connect a connectivity-generating library to a simulator, such that one library can easily be replaced by another, according to the modeller's needs. We have used the connection generator interface to connect C++ and Python implementations of the connection-set algebra to the NEST simulator. We also demonstrate how the simulator-independent modelling framework PyNN can transparently take advantage of this, passing a connection description through to the simulator layer for rapid processing in C++ where a simulator supports the connection generator interface and falling-back to slower iteration in Python otherwise. A set of benchmarks demonstrates the good performance of the interface.

  11. Effects of tamoxifen on neuronal morphology, connectivity and biochemistry of hypothalamic ventromedial neurons: Impact on the modulators of sexual behavior.

    Science.gov (United States)

    Sá, Susana I; Teixeira, Natércia; Fonseca, Bruno M

    2018-01-01

    Tamoxifen (TAM) is a selective estrogen receptor modulator, widely used in the treatment and prevention of estrogen-dependent breast cancer. Although with great clinical results, women on TAM therapy still report several side effects, such as sexual dysfunction, which impairs quality of life. The anatomo-functional substrates of the human sexual behavior are still unknown; however, these same substrates are very well characterized in the rodent female sexual behavior, which has advantage of being a very simple reflexive response, dependent on the activation of estrogen receptors (ERs) in the ventrolateral division of the hypothalamic ventromedial nucleus (VMNvl). In fact, in the female rodent, the sexual behavior is triggered by increasing circulation levels of estradiol that changes the nucleus neurochemistry and modulates its intricate neuronal network. Therefore, we considered of notice the examination of the possible neurochemical alterations and the synaptic plasticity impairment in VMNvl neurons of estradiol-primed female rats treated with TAM that may be in the basis of this neurological disorder. Accordingly, we used stereological and biochemical methods to study the action of TAM in axospinous and axodendritic synaptic plasticity and on ER expression. The administration of TAM changed the VMNvl neurochemistry by reducing ERα mRNA and increasing ERβ mRNA expression. Furthermore, present results show that TAM induced neuronal atrophy and reduced synaptic connectivity, favoring electrical inactivity. These data suggest that these cellular and molecular changes may be a possible neuronal mechanism of TAM action in the disruption of the VMNvl network, leading to the development of behavioral disorders. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. A signaling network for patterning of neuronal connectivity in the Drosophila brain.

    Directory of Open Access Journals (Sweden)

    Mohammed Srahna

    2006-10-01

    Full Text Available The precise number and pattern of axonal connections generated during brain development regulates animal behavior. Therefore, understanding how developmental signals interact to regulate axonal extension and retraction to achieve precise neuronal connectivity is a fundamental goal of neurobiology. We investigated this question in the developing adult brain of Drosophila and find that it is regulated by crosstalk between Wnt, fibroblast growth factor (FGF receptor, and Jun N-terminal kinase (JNK signaling, but independent of neuronal activity. The Rac1 GTPase integrates a Wnt-Frizzled-Disheveled axon-stabilizing signal and a Branchless (FGF-Breathless (FGF receptor axon-retracting signal to modulate JNK activity. JNK activity is necessary and sufficient for axon extension, whereas the antagonistic Wnt and FGF signals act to balance the extension and retraction required for the generation of the precise wiring pattern.

  13. Connectivity from OR37 expressing olfactory sensory neurons to distinct cell types in the hypothalamus

    Directory of Open Access Journals (Sweden)

    Andrea eBader

    2012-11-01

    Full Text Available Olfactory sensory neurons which express a member from the OR37 subfamily of odorant receptor genes are wired to the main olfactory bulb in a unique monoglomerular fashion; from these glomeruli an untypical connectivity into higher brain centers exists. In the present study we have investigated by DiI and transsynaptic tracing approaches how the connection pattern from these glomeruli into distinct hypothalamic nuclei is organized. The application of DiI onto the ventral domain of the bulb which harbors the OR37 glomeruli resulted in the labeling of fibers within the paraventricular and supraoptic nucleus of the hypothalamus; some of these fibers were covered with varicose-like structures. No DiI-labeled cell somata were detectable in these nuclei. The data indicate that projection neurons which originate in the OR37 region of the main olfactory bulb form direct connections into these nuclei. The cells that were labeled by the transsynaptic tracer WGA in these nuclei were further characterized. Their distribution pattern in the paraventricular nucleus was reminiscent of cells which produce distinct neuropeptides. Double labeling experiments confirmed that they contained vasopressin, but not the related neuropeptide oxytocin. Morphological analysis revealed that they comprise of magno- and parvocellular cells. A comparative investigation of the WGA-positive cells in the supraoptic nucleus demonstrated that these were vasopressin-positive, as well, whereas oxytocin-producing cells of this nucleus also contained no transsynaptic tracer. Together, the data demonstrate a connectivity from OR37 expressing sensory neurons to distinct hypothalamic neurons with the same neuropeptide content.

  14. Connective tissue growth factor (CTGF/CCN2 is negatively regulated during neuron-glioblastoma interaction.

    Directory of Open Access Journals (Sweden)

    Luciana F Romão

    Full Text Available Connective-tissue growth factor (CTGF/CCN2 is a matricellular-secreted protein involved in complex processes such as wound healing, angiogenesis, fibrosis and metastasis, in the regulation of cell proliferation, migration and extracellular matrix remodeling. Glioblastoma (GBM is the major malignant primary brain tumor and its adaptation to the central nervous system microenvironment requires the production and remodeling of the extracellular matrix. Previously, we published an in vitro approach to test if neurons can influence the expression of the GBM extracellular matrix. We demonstrated that neurons remodeled glioma cell laminin. The present study shows that neurons are also able to modulate CTGF expression in GBM. CTGF immnoreactivity and mRNA levels in GBM cells are dramatically decreased when these cells are co-cultured with neonatal neurons. As proof of particular neuron effects, neonatal neurons co-cultured onto GBM cells also inhibit the reporter luciferase activity under control of the CTGF promoter, suggesting inhibition at the transcription level. This inhibition seems to be contact-mediated, since conditioned media from embryonic or neonatal neurons do not affect CTGF expression in GBM cells. Furthermore, the inhibition of CTGF expression in GBM/neuronal co-cultures seems to affect the two main signaling pathways related to CTGF. We observed inhibition of TGFβ luciferase reporter assay; however phopho-SMAD2 levels did not change in these co-cultures. In addition levels of phospho-p44/42 MAPK were decreased in co-cultured GBM cells. Finally, in transwell migration assay, CTGF siRNA transfected GBM cells or GBM cells co-cultured with neurons showed a decrease in the migration rate compared to controls. Previous data regarding laminin and these results demonstrating that CTGF is down-regulated in GBM cells co-cultured with neonatal neurons points out an interesting view in the understanding of the tumor and cerebral microenvironment

  15. The projection and synaptic organisation of NTS afferent connections with presympathetic neurons, GABA and nNOS neurons in the paraventricular nucleus of the hypothalamus

    Science.gov (United States)

    Affleck, V.S.; Coote, J.H.; Pyner, S.

    2012-01-01

    Elevated sympathetic nerve activity, strongly associated with cardiovascular disease, is partly generated from the presympathetic neurons of the paraventricular nucleus of the hypothalamus (PVN). The PVN-presympathetic neurons regulating cardiac and vasomotor sympathetic activity receive information about cardiovascular status from receptors in the heart and circulation. These receptors signal changes via afferent neurons terminating in the nucleus tractus solitarius (NTS), some of which may result in excitation or inhibition of PVN-presympathetic neurons. Understanding the anatomy and neurochemistry of NTS afferent connections within the PVN could provide important clues to the impairment in homeostasis cardiovascular control associated with disease. Transynaptic labelling has shown the presence of neuronal nitric oxide synthase (nNOS)-containing neurons and GABA interneurons that terminate on presympathetic PVN neurons any of which may be the target for NTS afferents. So far NTS connections to these diverse neuronal pools have not been demonstrated and were investigated in this study. Anterograde (biotin dextran amine – BDA) labelling of the ascending projection from the NTS and retrograde (fluorogold – FG or cholera toxin B subunit – CTB) labelling of PVN presympathetic neurons combined with immunohistochemistry for GABA and nNOS was used to identify the terminal neuronal targets of the ascending projection from the NTS. It was shown that NTS afferent terminals are apposed to either PVN-GABA interneurons or to nitric oxide producing neurons or even directly to presympathetic neurons. Furthermore, there was evidence that some NTS axons were positive for vesicular glutamate transporter 2 (vGLUT2). The data provide an anatomical basis for the different functions of cardiovascular receptors that mediate their actions via the NTS–PVN pathways. PMID:22698695

  16. Automatic Generation of Connectivity for Large-Scale Neuronal Network Models through Structural Plasticity.

    Science.gov (United States)

    Diaz-Pier, Sandra; Naveau, Mikaël; Butz-Ostendorf, Markus; Morrison, Abigail

    2016-01-01

    With the emergence of new high performance computation technology in the last decade, the simulation of large scale neural networks which are able to reproduce the behavior and structure of the brain has finally become an achievable target of neuroscience. Due to the number of synaptic connections between neurons and the complexity of biological networks, most contemporary models have manually defined or static connectivity. However, it is expected that modeling the dynamic generation and deletion of the links among neurons, locally and between different regions of the brain, is crucial to unravel important mechanisms associated with learning, memory and healing. Moreover, for many neural circuits that could potentially be modeled, activity data is more readily and reliably available than connectivity data. Thus, a framework that enables networks to wire themselves on the basis of specified activity targets can be of great value in specifying network models where connectivity data is incomplete or has large error margins. To address these issues, in the present work we present an implementation of a model of structural plasticity in the neural network simulator NEST. In this model, synapses consist of two parts, a pre- and a post-synaptic element. Synapses are created and deleted during the execution of the simulation following local homeostatic rules until a mean level of electrical activity is reached in the network. We assess the scalability of the implementation in order to evaluate its potential usage in the self generation of connectivity of large scale networks. We show and discuss the results of simulations on simple two population networks and more complex models of the cortical microcircuit involving 8 populations and 4 layers using the new framework.

  17. Barbed channels enhance unidirectional connectivity between neuronal networks cultured on multi electrode arrays.

    Directory of Open Access Journals (Sweden)

    Joost eLe Feber

    2015-11-01

    Full Text Available Cultured neurons on multi electrode arrays (MEAs have been widely used to study various as-pects of neuronal (network functioning. A possible drawback of this approach is the lack of structure in these networks. At the single cell level, several solutions have been proposed to ena-ble directed connectivity, and promising results were obtained. At the level of connected sub-populations, a few attempts have been made with promising results. First assessment of the de-signs’ functionality, however, suggested room for further improvement.We designed a two chamber MEA aiming to create a unidirectional connection between the net-works in both chambers (‘emitting’ and ‘receiving’. To achieve this unidirectionality, all inter-connecting channels contained barbs that hindered axon growth in the opposite direction (from receiving to emitting chamber. Visual inspection showed that axons predominantly grew through the channels in the promoted direction . This observation was confirmed by spontaneous activity recordings. Cross-correlation between the signals from two electrodes inside the channels suggested signal propagation at ≈2 m/s from emitting to receiving chamber. Cross-correlation between the firing patterns in both chambers indicated that most correlated activity was initiated in the emitting chamber, which was also reflected by a significantly lower fraction of partial bursts (e. a one-chamber-only burst in the emitting chamber. Finally, electrical stimulation in the emitting chamber induced a fast response in that chamber, and a slower response in the receiving chamber. Stimulation in the receiving chamber evoked a fast response in that chamber, but no response in the emitting chamber. These results confirm the predominantly unidirectional nature of the connecting channels from emitting to receiving chamber.

  18. Neuroanatomy of pars intercerebralis neurons with special reference to their connections with neurons immunoreactive for pigment-dispersing factor in the blow fly Protophormia terraenovae.

    Science.gov (United States)

    Yasuyama, Kouji; Hase, Hiroaki; Shiga, Sakiko

    2015-10-01

    Input regions of pars intercerebralis (PI) neurons are examined by confocal and electron microscopies with special reference to their connections with neurons immunoreactive for pigment-dispersing factor (PDF) in the blow fly, Protophormia terraenovae. PI neurons are a prerequisite for ovarian development under long-day conditions. Backfills from the cardiac recurrent nerve after severance of the posterior lateral tracts labeled thin fibers derived from the PI neurons in the superior medial protocerebrum. These PI fibers were mainly synapsin-negative and postsynaptic to unknown varicose profiles containing dense-core vesicles. Backfilled fibers in the periesophageal neuropils, derived from the PI neurons or neurons with somata in the subesophageal zone, were varicose and some were synapsin-positive. Electron microscopy revealed the presence of both presynaptic and postsynaptic sites in backfilled fibers in the periesophageal neuropils. Many PDF-immunoreactive varicosities were found in the superior medial and lateral protocerebrum and double-labeling showed that 60-88 % of PDF-immunoreactive varicosities were also synapsin-immunoreactive. Double-labeling with the backfills and PDF immunocytochemistry showed that the PI fibers and PDF-immunoreactive varicosities were located close to each other in the superior medial protocerebrum. Results of triple-labeling of PI neurons, PDF-immunoreactive neurons and synapsin-immunoreactive terminals demonstrated that the synapsin-positive PDF-immunoreactive varicosities contacted the PI fibers. These data suggest that PI neurons receive synaptic contacts from PDF-immunoreactive fibers, which are derived from circadian clock neurons, of small ventral lateral neurons (previously called OL2) or posterior dorsal (PD) neurons with somata in the pars lateralis.

  19. 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

  20. Barbed channels enhance unidirectional connectivity between neuronal networks cultured on multi electrode arrays

    Science.gov (United States)

    le Feber, Joost; Postma, Wybren; de Weerd, Eddy; Weusthof, Marcel; Rutten, Wim L. C.

    2015-01-01

    Cultured neurons on multi electrode arrays (MEAs) have been widely used to study various aspects of neuronal (network) functioning. A possible drawback of this approach is the lack of structure in these networks. At the single cell level, several solutions have been proposed to enable directed connectivity, and promising results were obtained. At the level of connected sub-populations, a few attempts have been made with promising results. First assessment of the designs' functionality, however, suggested room for further improvement. We designed a two chamber MEA aiming to create a unidirectional connection between the networks in both chambers (“emitting” and “receiving”). To achieve this unidirectionality, all interconnecting channels contained barbs that hindered axon growth in the opposite direction (from receiving to emitting chamber). Visual inspection showed that axons predominantly grew through the channels in the promoted direction. This observation was confirmed by spontaneous activity recordings. Cross-correlation between the signals from two electrodes inside the channels suggested signal propagation at ≈2 m/s from emitting to receiving chamber. Cross-correlation between the firing patterns in both chambers indicated that most correlated activity was initiated in the emitting chamber, which was also reflected by a significantly lower fraction of partial bursts (i.e., a one-chamber-only burst) in the emitting chamber. Finally, electrical stimulation in the emitting chamber induced a fast response in that chamber, and a slower response in the receiving chamber. Stimulation in the receiving chamber evoked a fast response in that chamber, but no response in the emitting chamber. These results confirm the predominantly unidirectional nature of the connecting channels from emitting to receiving chamber. PMID:26578869

  1. The role of degree distribution in shaping the dynamics in networks of sparsely connected spiking neurons

    Directory of Open Access Journals (Sweden)

    Alex eRoxin

    2011-03-01

    Full Text Available Neuronal network models often assume a fixed probability of connectionbetween neurons. This assumption leads to random networks withbinomial in-degree and out-degree distributions which are relatively narrow. Here I study the effect of broaddegree distributions on network dynamics by interpolating between abinomial and a truncated powerlaw distribution for the in-degree andout-degree independently. This is done both for an inhibitory network(I network as well as for the recurrent excitatory connections in anetwork of excitatory and inhibitory neurons (EI network. In bothcases increasing the width of the in-degree distribution affects theglobal state of the network by driving transitions betweenasynchronous behavior and oscillations. This effect is reproduced ina simplified rate model which includes the heterogeneity in neuronalinput due to the in-degree of cells. On the other hand, broadeningthe out-degree distribution is shown to increase the fraction ofcommon inputs to pairs of neurons. This leads to increases in theamplitude of the cross-correlation (CC of synaptic currents. In thecase of the I network, despite strong oscillatory CCs in the currents, CCs of the membrane potential are low due to filtering and reset effects, leading to very weak CCs of the spikecount. In the asynchronous regime ofthe EI network, broadening the out-degree increases the amplitude ofCCs in the recurrent excitatory currents, while CC of the totalcurrent is essentially unaffected as are pairwise spikingcorrelations. This is due to a dynamic balance between excitatoryand inhibitory synaptic currents. In the oscillatory regime, changesin the out-degree can have a large effect on spiking correlations andeven on the qualitative dynamical state of the network.

  2. High Content Analysis of Hippocampal Neuron-Astrocyte Co-cultures Shows a Positive Effect of Fortasyn Connect on Neuronal Survival and Postsynaptic Maturation.

    Science.gov (United States)

    van Deijk, Anne-Lieke F; Broersen, Laus M; Verkuyl, J Martin; Smit, August B; Verheijen, Mark H G

    2017-01-01

    Neuronal and synaptic membranes are composed of a phospholipid bilayer. Supplementation with dietary precursors for phospholipid synthesis -docosahexaenoic acid (DHA), uridine and choline- has been shown to increase neurite outgrowth and synaptogenesis both in vivo and in vitro . A role for multi-nutrient intervention with specific precursors and cofactors has recently emerged in early Alzheimer's disease, which is characterized by decreased synapse numbers in the hippocampus. Moreover, the medical food Souvenaid, containing the specific nutrient combination Fortasyn Connect (FC), improves memory performance in early Alzheimer's disease patients, possibly via maintaining brain connectivity. This suggests an effect of FC on synapses, but the underlying cellular mechanism is not fully understood. Therefore, we investigated the effect of FC (consisting of DHA, eicosapentaenoic acid (EPA), uridine, choline, phospholipids, folic acid, vitamins B12, B6, C and E, and selenium), on synaptogenesis by supplementing it to primary neuron-astrocyte co-cultures, a cellular model that mimics metabolic dependencies in the brain. We measured neuronal developmental processes using high content screening in an automated manner, including neuronal survival, neurite morphology, as well as the formation and maturation of synapses. Here, we show that FC supplementation resulted in increased numbers of neurons without affecting astrocyte number. Furthermore, FC increased postsynaptic PSD95 levels in both immature and mature synapses. These findings suggest that supplementation with FC to neuron-astrocyte co-cultures increased both neuronal survival and the maturation of postsynaptic terminals, which might aid the functional interpretation of FC-based intervention strategies in neurological diseases characterized by neuronal loss and impaired synaptic functioning.

  3. High Content Analysis of Hippocampal Neuron-Astrocyte Co-cultures Shows a Positive Effect of Fortasyn Connect on Neuronal Survival and Postsynaptic Maturation

    Directory of Open Access Journals (Sweden)

    Anne-Lieke F. van Deijk

    2017-08-01

    Full Text Available Neuronal and synaptic membranes are composed of a phospholipid bilayer. Supplementation with dietary precursors for phospholipid synthesis –docosahexaenoic acid (DHA, uridine and choline– has been shown to increase neurite outgrowth and synaptogenesis both in vivo and in vitro. A role for multi-nutrient intervention with specific precursors and cofactors has recently emerged in early Alzheimer's disease, which is characterized by decreased synapse numbers in the hippocampus. Moreover, the medical food Souvenaid, containing the specific nutrient combination Fortasyn Connect (FC, improves memory performance in early Alzheimer's disease patients, possibly via maintaining brain connectivity. This suggests an effect of FC on synapses, but the underlying cellular mechanism is not fully understood. Therefore, we investigated the effect of FC (consisting of DHA, eicosapentaenoic acid (EPA, uridine, choline, phospholipids, folic acid, vitamins B12, B6, C and E, and selenium, on synaptogenesis by supplementing it to primary neuron-astrocyte co-cultures, a cellular model that mimics metabolic dependencies in the brain. We measured neuronal developmental processes using high content screening in an automated manner, including neuronal survival, neurite morphology, as well as the formation and maturation of synapses. Here, we show that FC supplementation resulted in increased numbers of neurons without affecting astrocyte number. Furthermore, FC increased postsynaptic PSD95 levels in both immature and mature synapses. These findings suggest that supplementation with FC to neuron-astrocyte co-cultures increased both neuronal survival and the maturation of postsynaptic terminals, which might aid the functional interpretation of FC-based intervention strategies in neurological diseases characterized by neuronal loss and impaired synaptic functioning.

  4. [RECONSTRUCTION OF LOWER EXTREMITY FUNCTION OF COMPLETE SPINAL CORD INJURY RATS BY FIRST NEURON CONNECTION].

    Science.gov (United States)

    Wang, Fangyong; Yuan, Yuan; Li, Jianjun

    2015-12-01

    To investigate the effects of the first neuron connection for the reconstruction of lower extremity function of complete spinal cord injury rats. Forty adult female Sprague Dawley rats of 300-350 g in weight were selected to prepare the models of L₁ transverse spinal cord injury. After 2 weeks of establishing model, the rats were randomly divided into control group (n = 20) and experimental group (n = 20). In the experimental group, the right hind limb function was reconstructed directly by the first neuron; in the control group, the other treatments were the same to the experimental group except that the distal tibial nerve and the proximal femoral nerve were not sutured. The recovery of motor function of lower extremity was observed by the Basso-Beattie-Bresnahan (BBB) scoring system on bilateral hind limbs at 7, 30, 50, and 70 days after operation. The changes of the spinal cord were observed by HE staining, neurofilament 200 immunohistochemistry staining, and the technique of horseradish peroxidase (HRP) tracing. After establishing models, 6 rats died. The right hind limb had no obvious recovery of the motor function, with the BBB score of 0 in 2 groups; the left hind limb motor function was recovered in different degrees, and there was no significant difference in BBB score between 2 groups (P > 0.05). In the experimental group, HE staining showed that the spinal cord was reconstructed with the sciatic nerve, which was embedded in the spinal cord, and the sciatic nerve membrane was clearly identified, and there was no obvious atrophy in the connecting part of the spinal cord. In the experimental group, the expression of nerve fiber was stained with immunohistochemistry, and the axons of the spinal cord were positively by stained and the peripheral nerve was connected with the spinal cord. HRP labelled synapses were detected by HRP retrograde tracing in the experimental group, while there was no HRP labelled synapse in the control group. Direct reconstruction

  5. The respiratory drive to thoracic motoneurones in the cat and its relation to the connections from expiratory bulbospinal neurones

    DEFF Research Database (Denmark)

    Saywell, S A; Anissimova, N P; Ford, T W

    2007-01-01

    of connection revealed were related to the presence and size of central respiratory drive potentials in the same motoneurones. Intracellular recordings were made from motoneurones in segments T5-T9 of the spinal cord of anaesthetized cats. Spike-triggered averaging from expiratory bulbospinal neurones...... in the caudal medulla revealed monosynaptic EPSPs in all groups of motoneurones, with the strongest connections to expiratory motoneurones with axons in the internal intercostal nerve. In the latter, connection strength was similar irrespective of the target muscle (e.g. external abdominal oblique or internal...... intercostal) and the EPSP amplitude was positively correlated with the amplitude of the central respiratory drive potential of the motoneurone. For this group, EPSPs were found in 45/83 bulbospinal neurone/motoneurone pairs, with a mean amplitude of 40.5 microV. The overall strength of the connection supports...

  6. Determination of relevant neuron-neuron connections for neural prosthetics using time-delayed mutual information: tutorial and preliminary results.

    Science.gov (United States)

    Taghva, Alexander; Song, Dong; Hampson, Robert E; Deadwyler, Sam A; Berger, Theodore W

    2012-12-01

    Identification of functional dependence among neurons is a necessary component in both the rational design of neural prostheses as well as in the characterization of network physiology. The objective of this article is to provide a tutorial for neurosurgeons regarding information theory, specifically time-delayed mutual information, and to compare time-delayed mutual information, an information theoretic quantity based on statistical dependence, with cross-correlation, a commonly used metric for this task in a preliminary analysis of rat hippocampal neurons. Spike trains were recorded from rats performing delayed nonmatch-to-sample task using an array of electrodes surgically implanted into the hippocampus of each hemisphere of the brain. In addition, spike train simulations of positively correlated neurons, negatively correlated neurons, and neurons correlated by nonlinear functions were generated. These were evaluated by time-delayed mutual information (MI) and cross-correlation. Application of time-delayed MI to experimental data indicated the optimal bin size for information capture in the CA3-CA1 system was 40 ms, which may provide some insight into the spatiotemporal nature of encoding in the rat hippocampus. On simulated data, time-delayed MI showed peak values at appropriate time lags in positively correlated, negatively correlated, and complexly correlated data. Cross-correlation showed peak and troughs with positively correlated and negatively correlated data, but failed to capture some higher order correlations. Comparison of time-delayed MI to cross-correlation in identification of functionally dependent neurons indicates that the methods are not equivalent. Time-delayed MI appeared to capture some interactions between CA3-CA1 neurons at physiologically plausible time delays missed by cross-correlation. It should be considered as a method for identification of functional dependence between neurons and may be useful in the development of neural

  7. Fluctuations and information filtering in coupled populations of spiking neurons with adaptation.

    Science.gov (United States)

    Deger, Moritz; Schwalger, Tilo; Naud, Richard; Gerstner, Wulfram

    2014-12-01

    Finite-sized populations of spiking elements are fundamental to brain function but also are used in many areas of physics. Here we present a theory of the dynamics of finite-sized populations of spiking units, based on a quasirenewal description of neurons with adaptation. We derive an integral equation with colored noise that governs the stochastic dynamics of the population activity in response to time-dependent stimulation and calculate the spectral density in the asynchronous state. We show that systems of coupled populations with adaptation can generate a frequency band in which sensory information is preferentially encoded. The theory is applicable to fully as well as randomly connected networks and to leaky integrate-and-fire as well as to generalized spiking neurons with adaptation on multiple time scales.

  8. Developmental Connectivity and Molecular Phenotypes of Unique Cortical Projection Neurons that Express a Synapse-Associated Receptor Tyrosine Kinase.

    Science.gov (United States)

    Kast, Ryan J; Wu, Hsiao-Huei; Levitt, Pat

    2017-11-28

    The complex circuitry and cell-type diversity of the cerebral cortex are required for its high-level functions. The mechanisms underlying the diversification of cortical neurons during prenatal development have received substantial attention, but understanding of neuronal heterogeneity is more limited during later periods of cortical circuit maturation. To address this knowledge gap, connectivity analysis and molecular phenotyping of cortical neuron subtypes that express the developing synapse-enriched MET receptor tyrosine kinase were performed. Experiments used a MetGFP transgenic mouse line, combined with coexpression analysis of class-specific molecular markers and retrograde connectivity mapping. The results reveal that MET is expressed by a minor subset of subcerebral and a larger number of intratelencephalic projection neurons. Remarkably, MET is excluded from most layer 6 corticothalamic neurons. These findings are particularly relevant for understanding the maturation of discrete cortical circuits, given converging evidence that MET influences dendritic elaboration and glutamatergic synapse maturation. The data suggest that classically defined cortical projection classes can be further subdivided based on molecular characteristics that likely influence synaptic maturation and circuit wiring. Additionally, given that MET is classified as a high confidence autism risk gene, the data suggest that projection neuron subpopulations may be differentially vulnerable to disorder-associated genetic variation. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  9. PCB 136 Atropselectively Alters Morphometric and Functional Parameters of Neuronal Connectivity in Cultured Rat Hippocampal Neurons via Ryanodine Receptor-Dependent Mechanisms

    Science.gov (United States)

    Yang, Dongren; Kania-Korwel, Izabela; Ghogha, Atefeh; Chen, Hao; Stamou, Marianna; Bose, Diptiman D.; Pessah, Isaac N.; Lehmler, Hans-Joachim; Lein, Pamela J.

    2014-01-01

    We recently demonstrated that polychlorinated biphenyl (PCB) congeners with multiple ortho chlorine substitutions sensitize ryanodine receptors (RyRs), and this activity promotes Ca2+-dependent dendritic growth in cultured neurons. Many ortho-substituted congeners display axial chirality, and we previously reported that the chiral congener PCB 136 (2,2′,3,3′,6,6′-hexachlorobiphenyl) atropselectively sensitizes RyRs. Here, we test the hypothesis that PCB 136 atropisomers differentially alter dendritic growth and other parameters of neuronal connectivity influenced by RyR activity. (−)-PCB 136, which potently sensitizes RyRs, enhances dendritic growth in primary cultures of rat hippocampal neurons, whereas (+)-PCB 136, which lacks RyR activity, has no effect on dendritic growth. The dendrite-promoting activity of (−)-PCB 136 is observed at concentrations ranging from 0.1 to 100nM and is blocked by pharmacologic RyR antagonism. Neither atropisomer alters axonal growth or cell viability. Quantification of PCB 136 atropisomers in hippocampal cultures indicates that atropselective effects on dendritic growth are not due to differential partitioning of atropisomers into cultured cells. Imaging of hippocampal neurons loaded with Ca2+-sensitive dye demonstrates that (−)-PCB 136 but not (+)-PCB 136 increases the frequency of spontaneous Ca2+ oscillations. Similarly, (−)-PCB 136 but not (+)-PCB 136 increases the activity of hippocampal neurons plated on microelectrode arrays. These data support the hypothesis that atropselective effects on RyR activity translate into atropselective effects of PCB 136 atropisomers on neuronal connectivity, and suggest that the variable atropisomeric enrichment of chiral PCBs observed in the human population may be a significant determinant of individual susceptibility for adverse neurodevelopmental outcomes following PCB exposure. PMID:24385416

  10. Mirror Neuron System and Mentalizing System connect during online social interaction.

    Science.gov (United States)

    Sperduti, Marco; Guionnet, Sophie; Fossati, Philippe; Nadel, Jacqueline

    2014-08-01

    Two sets of brain areas are repeatedly reported in neuroimaging studies on social cognition: the Mirror Neuron System and the Mentalizing System. The Mirror System is involved in goal understanding and has been associated with several emotional and cognitive functions central to social interaction, ranging from empathy to gestural communication and imitation. The Mentalizing System is recruited in tasks requiring cognitive processes such as self-reference and understanding of other's intentions. Although theoretical accounts for an interaction between the two systems have been proposed, little is known about their synergy during social exchanges. In order to explore this question, we have recorded brain activity by means of functional MRI during live social exchanges based on reciprocal imitation of hand gestures. Here, we investigate, using the method of psychophysiological interaction, the changes in functional connectivity of the Mirror System due to the conditions of interest (being imitated, imitating) compared with passive observation of hand gestures. We report a strong coupling between the Mirror System and the Mentalizing System during the imitative exchanges. Our findings suggest a complementary role of the two networks during social encounters. The Mirror System would engage in the preparation of own actions and the simulation of other's actions, while the Mentalizing System would engage in the anticipation of the other's intention and thus would participate to the co-regulation of reciprocal actions. Beyond a specific effect of imitation, the design used offers the opportunity to tackle the role of role-switching in an interpersonal account of social cognition.

  11. Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size

    Science.gov (United States)

    Gerstner, Wulfram

    2017-01-01

    Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of single neurons is unclear. Here we derive an equation for several interacting populations at the mesoscopic scale starting from a microscopic model of randomly connected generalized integrate-and-fire neuron models. Each population consists of 50–2000 neurons of the same type but different populations account for different neuron types. The stochastic population equations that we find reveal how spike-history effects in single-neuron dynamics such as refractoriness and adaptation interact with finite-size fluctuations on the population level. Efficient integration of the stochastic mesoscopic equations reproduces the statistical behavior of the population activities obtained from microscopic simulations of a full spiking neural network model. The theory describes nonlinear emergent dynamics such as finite-size-induced stochastic transitions in multistable networks and synchronization in balanced networks of excitatory and inhibitory neurons. The mesoscopic equations are employed to rapidly integrate a model of a cortical microcircuit consisting of eight neuron types, which allows us to predict spontaneous population activities as well as evoked responses to thalamic input. Our theory establishes a general framework for modeling finite-size neural population dynamics based on single cell and synapse parameters and offers an efficient approach to analyzing cortical circuits and computations. PMID:28422957

  12. Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size.

    Science.gov (United States)

    Schwalger, Tilo; Deger, Moritz; Gerstner, Wulfram

    2017-04-01

    Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of single neurons is unclear. Here we derive an equation for several interacting populations at the mesoscopic scale starting from a microscopic model of randomly connected generalized integrate-and-fire neuron models. Each population consists of 50-2000 neurons of the same type but different populations account for different neuron types. The stochastic population equations that we find reveal how spike-history effects in single-neuron dynamics such as refractoriness and adaptation interact with finite-size fluctuations on the population level. Efficient integration of the stochastic mesoscopic equations reproduces the statistical behavior of the population activities obtained from microscopic simulations of a full spiking neural network model. The theory describes nonlinear emergent dynamics such as finite-size-induced stochastic transitions in multistable networks and synchronization in balanced networks of excitatory and inhibitory neurons. The mesoscopic equations are employed to rapidly integrate a model of a cortical microcircuit consisting of eight neuron types, which allows us to predict spontaneous population activities as well as evoked responses to thalamic input. Our theory establishes a general framework for modeling finite-size neural population dynamics based on single cell and synapse parameters and offers an efficient approach to analyzing cortical circuits and computations.

  13. Strong, reliable and precise synaptic connections between thalamic relay cells and neurones of the nucleus reticularis in juvenile rats

    Science.gov (United States)

    Gentet, Luc J; Ulrich, Daniel

    2003-01-01

    The thalamic reticular nucleus (nRT) is composed entirely of GABAergic inhibitory neurones that receive input from pyramidal cortical neurones and excitatory relay cells of the ventrobasal complex of the thalamus (VB). It plays a major role in the synchrony of thalamic networks, yet the synaptic connections it receives from VB cells have never been fully physiologically characterised. Here, whole-cell current-clamp recordings were obtained from 22 synaptically connected VB-nRT cell pairs in slices of juvenile (P14–20) rats. At 34–36 °C, single presynaptic APs evoked unitary EPSPs in nRT cells with a peak amplitude of 7.4 ± 1.5 mV (mean ± s.e.m.) and a decay time constant of 15.1 ± 0.9 ms. Only four out of 22 pairs showed transmission failures at a mean rate of 6.8 ± 1.1 %. An NMDA receptor (NMDAR)-mediated component was significant at rest and subsequent EPSPs in a train were depressed. Only one out of 14 pairs tested was reciprocally connected; the observed IPSPs in the VB cell had a peak amplitude of 0.8 mV and were completely abolished in the presence of 10 μm bicuculline. Thus, synaptic connections from VB cells to nRT neurones are mainly ‘drivers’, while a small subset of cells form closed disynaptic loops. PMID:12563005

  14. Information in a Network of Neuronal Cells: Effect of Cell Density and Short-Term Depression

    KAUST Repository

    Onesto, Valentina

    2016-05-10

    Neurons are specialized, electrically excitable cells which use electrical to chemical signals to transmit and elaborate information. Understanding how the cooperation of a great many of neurons in a grid may modify and perhaps improve the information quality, in contrast to few neurons in isolation, is critical for the rational design of cell-materials interfaces for applications in regenerative medicine, tissue engineering, and personalized lab-on-a-chips. In the present paper, we couple an integrate-and-fire model with information theory variables to analyse the extent of information in a network of nerve cells. We provide an estimate of the information in the network in bits as a function of cell density and short-term depression time. In the model, neurons are connected through a Delaunay triangulation of not-intersecting edges; in doing so, the number of connecting synapses per neuron is approximately constant to reproduce the early time of network development in planar neural cell cultures. In simulations where the number of nodes is varied, we observe an optimal value of cell density for which information in the grid is maximized. In simulations in which the posttransmission latency time is varied, we observe that information increases as the latency time decreases and, for specific configurations of the grid, it is largely enhanced in a resonance effect.

  15. Information in a Network of Neuronal Cells: Effect of Cell Density and Short-Term Depression

    Directory of Open Access Journals (Sweden)

    Valentina Onesto

    2016-01-01

    Full Text Available Neurons are specialized, electrically excitable cells which use electrical to chemical signals to transmit and elaborate information. Understanding how the cooperation of a great many of neurons in a grid may modify and perhaps improve the information quality, in contrast to few neurons in isolation, is critical for the rational design of cell-materials interfaces for applications in regenerative medicine, tissue engineering, and personalized lab-on-a-chips. In the present paper, we couple an integrate-and-fire model with information theory variables to analyse the extent of information in a network of nerve cells. We provide an estimate of the information in the network in bits as a function of cell density and short-term depression time. In the model, neurons are connected through a Delaunay triangulation of not-intersecting edges; in doing so, the number of connecting synapses per neuron is approximately constant to reproduce the early time of network development in planar neural cell cultures. In simulations where the number of nodes is varied, we observe an optimal value of cell density for which information in the grid is maximized. In simulations in which the posttransmission latency time is varied, we observe that information increases as the latency time decreases and, for specific configurations of the grid, it is largely enhanced in a resonance effect.

  16. Information in a Network of Neuronal Cells: Effect of Cell Density and Short-Term Depression

    KAUST Repository

    Onesto, Valentina; Cosentino, Carlo; Di Fabrizio, Enzo M.; Cesarelli, Mario; Amato, Francesco; Gentile, Francesco

    2016-01-01

    Neurons are specialized, electrically excitable cells which use electrical to chemical signals to transmit and elaborate information. Understanding how the cooperation of a great many of neurons in a grid may modify and perhaps improve the information quality, in contrast to few neurons in isolation, is critical for the rational design of cell-materials interfaces for applications in regenerative medicine, tissue engineering, and personalized lab-on-a-chips. In the present paper, we couple an integrate-and-fire model with information theory variables to analyse the extent of information in a network of nerve cells. We provide an estimate of the information in the network in bits as a function of cell density and short-term depression time. In the model, neurons are connected through a Delaunay triangulation of not-intersecting edges; in doing so, the number of connecting synapses per neuron is approximately constant to reproduce the early time of network development in planar neural cell cultures. In simulations where the number of nodes is varied, we observe an optimal value of cell density for which information in the grid is maximized. In simulations in which the posttransmission latency time is varied, we observe that information increases as the latency time decreases and, for specific configurations of the grid, it is largely enhanced in a resonance effect.

  17. Xbp1s in Pomc neurons connects ER stress with energy balance and glucose homeostasis

    Science.gov (United States)

    The molecular mechanisms underlying neuronal leptin and insulin resistance in obesity and diabetes remain unclear. Here we show that induction ofthe unfolded protein response transcription factor spliced X-box binding protein 1(Xbp1s) in pro-opio-melanocortin (Pomc) neurons alone is sufficient to pr...

  18. The respiratory drive to thoracic motoneurones in the cat and its relation to the connections from expiratory bulbospinal neurones

    Science.gov (United States)

    Saywell, S A; Anissimova, N P; Ford, T W; Meehan, C F; Kirkwood, P A

    2007-01-01

    The descending control of respiratory-related motoneurones in the thoracic spinal cord remains the subject of some debate. In this study, direct connections from expiratory bulbospinal neurones to identified motoneurones were investigated using spike-triggered averaging and the strengths of connection revealed were related to the presence and size of central respiratory drive potentials in the same motoneurones. Intracellular recordings were made from motoneurones in segments T5–T9 of the spinal cord of anaesthetized cats. Spike-triggered averaging from expiratory bulbospinal neurones in the caudal medulla revealed monosynaptic EPSPs in all groups of motoneurones, with the strongest connections to expiratory motoneurones with axons in the internal intercostal nerve. In the latter, connection strength was similar irrespective of the target muscle (e.g. external abdominal oblique or internal intercostal) and the EPSP amplitude was positively correlated with the amplitude of the central respiratory drive potential of the motoneurone. For this group, EPSPs were found in 45/83 bulbospinal neurone/motoneurone pairs, with a mean amplitude of 40.5 μV. The overall strength of the connection supports previous measurements made by cross-correlation, but is about 10 times stronger than that reported in the only previous similar survey to use spike-triggered averaging. Calculations are presented to suggest that this input alone is sufficient to account for all the expiratory depolarization seen in the recorded motoneurones. However, extra sources of input, or amplification of this one, are likely to be necessary to produce a useful motoneurone output. PMID:17204500

  19. Neuromorphic Silicon Neuron Circuits

    Science.gov (United States)

    Indiveri, Giacomo; Linares-Barranco, Bernabé; Hamilton, Tara Julia; van Schaik, André; Etienne-Cummings, Ralph; Delbruck, Tobi; Liu, Shih-Chii; Dudek, Piotr; Häfliger, Philipp; Renaud, Sylvie; Schemmel, Johannes; Cauwenberghs, Gert; Arthur, John; Hynna, Kai; Folowosele, Fopefolu; Saighi, Sylvain; Serrano-Gotarredona, Teresa; Wijekoon, Jayawan; Wang, Yingxue; Boahen, Kwabena

    2011-01-01

    Hardware implementations of spiking neurons can be extremely useful for a large variety of applications, ranging from high-speed modeling of large-scale neural systems to real-time behaving systems, to bidirectional brain–machine interfaces. The specific circuit solutions used to implement silicon neurons depend on the application requirements. In this paper we describe the most common building blocks and techniques used to implement these circuits, and present an overview of a wide range of neuromorphic silicon neurons, which implement different computational models, ranging from biophysically realistic and conductance-based Hodgkin–Huxley models to bi-dimensional generalized adaptive integrate and fire models. We compare the different design methodologies used for each silicon neuron design described, and demonstrate their features with experimental results, measured from a wide range of fabricated VLSI chips. PMID:21747754

  20. Neuromorphic silicon neuron circuits

    Directory of Open Access Journals (Sweden)

    Giacomo eIndiveri

    2011-05-01

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

  1. A dual-immunocytochemical method to localize c-fos protein in specific neurons based on their content of neuropeptides and connectivity

    DEFF Research Database (Denmark)

    Mikkelsen, J D; Larsen, P J; Sørensen, G G

    1994-01-01

    Enhanced expression of the immediate early gene c-fos has been used as a marker of cellular activation in many different neuronal pathways. We wished to determine the neurochemical content and the connectivity of neurons, in which expression of c-fos is induced. For this purpose, a dual...

  2. Connectivity of Pacemaker Neurons in the Neonatal Rat Superficial Dorsal Horn

    Science.gov (United States)

    Ford, Neil C.; Arbabi, Shahriar; Baccei, Mark L.

    2014-01-01

    Pacemaker neurons with an intrinsic ability to generate rhythmic burst-firing have been characterized in lamina I of the neonatal spinal cord, where they are innervated by high-threshold sensory afferents. However, little is known about the output of these pacemakers, as the neuronal populations which are targeted by pacemaker axons have yet to be identified. The present study combines patch clamp recordings in the intact neonatal rat spinal cord with tract-tracing to demonstrate that lamina I pacemaker neurons contact multiple spinal motor pathways during early life. Retrograde labeling of premotor interneurons with the trans-synaptic virus PRV-152 revealed the presence of burst-firing in PRV-infected lamina I neurons, thereby confirming that pacemakers are synaptically coupled to motor networks in the spinal ventral horn. Notably, two classes of pacemakers could be distinguished in lamina I based on cell size and the pattern of their axonal projections. While small pacemaker neurons possessed ramified axons which contacted ipsilateral motor circuits, large pacemaker neurons had unbranched axons which crossed the midline and ascended rostrally in the contralateral white matter. Recordings from identified spino-parabrachial and spino-PAG neurons indicated the presence of pacemaker activity within neonatal lamina I projection neurons. Overall, these results show that lamina I pacemakers are positioned to regulate both the level of activity in developing motor circuits as well as the ascending flow of nociceptive information to the brain, thus highlighting a potential role for pacemaker activity in the maturation of pain and sensorimotor networks in the CNS. PMID:25380417

  3. Prediction of rat behavior outcomes in memory tasks using functional connections among neurons.

    Directory of Open Access Journals (Sweden)

    Hu Lu

    Full Text Available BACKGROUND: Analyzing the neuronal organizational structures and studying the changes in the behavior of the organism is key to understanding cognitive functions of the brain. Although some studies have indicated that spatiotemporal firing patterns of neuronal populations have a certain relationship with the behavioral responses, the issues of whether there are any relationships between the functional networks comprised of these cortical neurons and behavioral tasks and whether it is possible to take advantage of these networks to predict correct and incorrect outcomes of single trials of animals are still unresolved. METHODOLOGY/PRINCIPAL FINDINGS: This paper presents a new method of analyzing the structures of whole-recorded neuronal functional networks (WNFNs and local neuronal circuit groups (LNCGs. The activity of these neurons was recorded in several rats. The rats performed two different behavioral tasks, the Y-maze task and the U-maze task. Using the results of the assessment of the WNFNs and LNCGs, this paper describes a realization procedure for predicting the behavioral outcomes of single trials. The methodology consists of four main parts: construction of WNFNs from recorded neuronal spike trains, partitioning the WNFNs into the optimal LNCGs using social community analysis, unsupervised clustering of all trials from each dataset into two different clusters, and predicting the behavioral outcomes of single trials. The results show that WNFNs and LNCGs correlate with the behavior of the animal. The U-maze datasets show higher accuracy for unsupervised clustering results than those from the Y-maze task, and these datasets can be used to predict behavioral responses effectively. CONCLUSIONS/SIGNIFICANCE: The results of the present study suggest that a methodology proposed in this paper is suitable for analysis of the characteristics of neuronal functional networks and the prediction of rat behavior. These types of structures in cortical

  4. Cited2 Regulates Neocortical Layer II/III Generation and Somatosensory Callosal Projection Neuron Development and Connectivity.

    Science.gov (United States)

    Fame, Ryann M; MacDonald, Jessica L; Dunwoodie, Sally L; Takahashi, Emi; Macklis, Jeffrey D

    2016-06-15

    The neocortex contains hundreds to thousands of distinct subtypes of precisely connected neurons, allowing it to perform remarkably complex tasks of high-level cognition. Callosal projection neurons (CPN) connect the cerebral hemispheres via the corpus callosum, integrating cortical information and playing key roles in associative cognition. CPN are a strikingly diverse set of neuronal subpopulations, and development of this diversity requires precise control by a complex, interactive set of molecular effectors. We have found that the transcriptional coregulator Cited2 regulates and refines two stages of CPN development. Cited2 is expressed broadly by progenitors in the embryonic day 15.5 subventricular zone, during the peak of superficial layer CPN birth, with a progressive postmitotic refinement in expression, becoming restricted to CPN of the somatosensory cortex postnatally. We generated progenitor-stage and postmitotic forebrain-specific Cited2 conditional knock-out mice, using the Emx1-Cre and NEX-Cre mouse lines, respectively. We demonstrate that Cited2 functions in progenitors, but is not necessary postmitotically, to regulate both (1) broad generation of layer II/III CPN and (2) acquisition of precise area-specific molecular identity and axonal/dendritic connectivity of somatosensory CPN. This novel CPN subtype-specific and area-specific control from progenitor action of Cited2 adds yet another layer of complexity to the multistage developmental regulation of neocortical development. This study identifies Cited2 as a novel subtype-specific and area-specific control over development of distinct subpopulations within the broad population of callosal projection neurons (CPN), whose axons connect the two cerebral hemispheres via the corpus callosum (CC). Currently, how the remarkable diversity of CPN subtypes is specified, and how they differentiate to form highly precise and specific circuits, are largely unknown. We found that Cited2 functions within

  5. Xbp1s in Pomc neurons connects ER stress with energy balance and glucose homeostasis.

    Science.gov (United States)

    Williams, Kevin W; Liu, Tiemin; Kong, Xingxing; Fukuda, Makoto; Deng, Yingfeng; Berglund, Eric D; Deng, Zhuo; Gao, Yong; Liu, Tianya; Sohn, Jong-Woo; Jia, Lin; Fujikawa, Teppei; Kohno, Daisuke; Scott, Michael M; Lee, Syann; Lee, Charlotte E; Sun, Kai; Chang, Yongsheng; Scherer, Philipp E; Elmquist, Joel K

    2014-09-02

    The molecular mechanisms underlying neuronal leptin and insulin resistance in obesity and diabetes remain unclear. Here we show that induction of the unfolded protein response transcription factor spliced X-box binding protein 1 (Xbp1s) in pro-opiomelanocortin (Pomc) neurons alone is sufficient to protect against diet-induced obesity as well as improve leptin and insulin sensitivity, even in the presence of strong activators of ER stress. We also demonstrate that constitutive expression of Xbp1s in Pomc neurons contributes to improved hepatic insulin sensitivity and suppression of endogenous glucose production. Notably, elevated Xbp1s levels in Pomc neurons also resulted in activation of the Xbp1s axis in the liver via a cell-nonautonomous mechanism. Together our results identify critical molecular mechanisms linking ER stress in arcuate Pomc neurons to acute leptin and insulin resistance as well as liver metabolism in diet-induced obesity and diabetes. Copyright © 2014 Elsevier Inc. All rights reserved.

  6. From Structure to Activity: Using Centrality Measures to Predict Neuronal Activity.

    Science.gov (United States)

    Fletcher, Jack McKay; Wennekers, Thomas

    2018-03-01

    It is clear that the topological structure of a neural network somehow determines the activity of the neurons within it. In the present work, we ask to what extent it is possible to examine the structural features of a network and learn something about its activity? Specifically, we consider how the centrality (the importance of a node in a network) of a neuron correlates with its firing rate. To investigate, we apply an array of centrality measures, including In-Degree, Closeness, Betweenness, Eigenvector, Katz, PageRank, Hyperlink-Induced Topic Search (HITS) and NeuronRank to Leaky-Integrate and Fire neural networks with different connectivity schemes. We find that Katz centrality is the best predictor of firing rate given the network structure, with almost perfect correlation in all cases studied, which include purely excitatory and excitatory-inhibitory networks, with either homogeneous connections or a small-world structure. We identify the properties of a network which will cause this correlation to hold. We argue that the reason Katz centrality correlates so highly with neuronal activity compared to other centrality measures is because it nicely captures disinhibition in neural networks. In addition, we argue that these theoretical findings are applicable to neuroscientists who apply centrality measures to functional brain networks, as well as offer a neurophysiological justification to high level cognitive models which use certain centrality measures.

  7. Dynamics of Competition between Subnetworks of Spiking Neuronal Networks in the Balanced State.

    Science.gov (United States)

    Lagzi, Fereshteh; Rotter, Stefan

    2015-01-01

    We explore and analyze the nonlinear switching dynamics of neuronal networks with non-homogeneous connectivity. The general significance of such transient dynamics for brain function is unclear; however, for instance decision-making processes in perception and cognition have been implicated with it. The network under study here is comprised of three subnetworks of either excitatory or inhibitory leaky integrate-and-fire neurons, of which two are of the same type. The synaptic weights are arranged to establish and maintain a balance between excitation and inhibition in case of a constant external drive. Each subnetwork is randomly connected, where all neurons belonging to a particular population have the same in-degree and the same out-degree. Neurons in different subnetworks are also randomly connected with the same probability; however, depending on the type of the pre-synaptic neuron, the synaptic weight is scaled by a factor. We observed that for a certain range of the "within" versus "between" connection weights (bifurcation parameter), the network activation spontaneously switches between the two sub-networks of the same type. This kind of dynamics has been termed "winnerless competition", which also has a random component here. In our model, this phenomenon is well described by a set of coupled stochastic differential equations of Lotka-Volterra type that imply a competition between the subnetworks. The associated mean-field model shows the same dynamical behavior as observed in simulations of large networks comprising thousands of spiking neurons. The deterministic phase portrait is characterized by two attractors and a saddle node, its stochastic component is essentially given by the multiplicative inherent noise of the system. We find that the dwell time distribution of the active states is exponential, indicating that the noise drives the system randomly from one attractor to the other. A similar model for a larger number of populations might suggest a

  8. Motif statistics and spike correlations in neuronal networks

    International Nuclear Information System (INIS)

    Hu, Yu; Shea-Brown, Eric; Trousdale, James; Josić, Krešimir

    2013-01-01

    Motifs are patterns of subgraphs of complex networks. We studied the impact of such patterns of connectivity on the level of correlated, or synchronized, spiking activity among pairs of cells in a recurrent network of integrate and fire neurons. For a range of network architectures, we find that the pairwise correlation coefficients, averaged across the network, can be closely approximated using only three statistics of network connectivity. These are the overall network connection probability and the frequencies of two second order motifs: diverging motifs, in which one cell provides input to two others, and chain motifs, in which two cells are connected via a third intermediary cell. Specifically, the prevalence of diverging and chain motifs tends to increase correlation. Our method is based on linear response theory, which enables us to express spiking statistics using linear algebra, and a resumming technique, which extrapolates from second order motifs to predict the overall effect of coupling on network correlation. Our motif-based results seek to isolate the effect of network architecture perturbatively from a known network state. (paper)

  9. Effects of inhibitory neurons on the quorum percolation model and dynamical extension with the Brette-Gerstner model

    Science.gov (United States)

    Fardet, Tanguy; Bottani, Samuel; Métens, Stéphane; Monceau, Pascal

    2018-06-01

    The Quorum Percolation model (QP) has been designed in the context of neurobiology to describe the initiation of activity bursts occurring in neuronal cultures from the point of view of statistical physics rather than from a dynamical synchronization approach. This paper aims at investigating an extension of the original QP model by taking into account the presence of inhibitory neurons in the cultures (IQP model). The first part of this paper is focused on an equivalence between the presence of inhibitory neurons and a reduction of the network connectivity. By relying on a simple topological argument, we show that the mean activation behavior of networks containing a fraction η of inhibitory neurons can be mapped onto purely excitatory networks with an appropriately modified wiring, provided that η remains in the range usually observed in neuronal cultures, namely η ⪅ 20%. As a striking result, we show that such a mapping enables to predict the evolution of the critical point of the IQP model with the fraction of inhibitory neurons. In a second part, we bridge the gap between the description of bursts in the framework of percolation and the temporal description of neural networks activity by showing how dynamical simulations of bursts with an adaptive exponential integrate-and-fire model lead to a mean description of bursts activation which is captured by Quorum Percolation.

  10. Self-consistent determination of the spike-train power spectrum in a neural network with sparse connectivity

    Directory of Open Access Journals (Sweden)

    Benjamin eDummer

    2014-09-01

    Full Text Available A major source of random variability in cortical networks is the quasi-random arrival of presynaptic action potentials from many other cells. In network studies as well as in the study of the response properties of single cells embedded in a network, synaptic background input is often approximated by Poissonian spike trains. However, the output statistics of the cells is in most cases far from being Poisson. This is inconsistent with the assumption of similar spike-train statistics for pre- and postsynaptic cells in a recurrent network. Here we tackle this problem for the popular class of integrate-and-fire neurons and study a self-consistent statistics of input and output spectra of neural spike trains. Instead of actually using a large network, we use an iterative scheme, in which we simulate a single neuron over several generations. In each of these generations, the neuron is stimulated with surrogate stochastic input that has a similar statistics as the output of the previous generation. For the surrogate input, we employ two distinct approximations: (i a superposition of renewal spike trains with the same interspike interval density as observed in the previous generation and (ii a Gaussian current with a power spectrum proportional to that observed in the previous generation. For input parameters that correspond to balanced input in the network, both the renewal and the Gaussian iteration procedure converge quickly and yield comparable results for the self-consistent spike-train power spectrum. We compare our results to large-scale simulations of a random sparsely connected network of leaky integrate-and-fire neurons (Brunel, J. Comp. Neurosci. 2000 and show that in the asynchronous regime close to a state of balanced synaptic input from the network, our iterative schemes provide excellent approximations to the autocorrelation of spike trains in the recurrent network.

  11. Delay selection by spike-timing-dependent plasticity in recurrent networks of spiking neurons receiving oscillatory inputs.

    Directory of Open Access Journals (Sweden)

    Robert R Kerr

    Full Text Available Learning rules, such as spike-timing-dependent plasticity (STDP, change the structure of networks of neurons based on the firing activity. A network level understanding of these mechanisms can help infer how the brain learns patterns and processes information. Previous studies have shown that STDP selectively potentiates feed-forward connections that have specific axonal delays, and that this underlies behavioral functions such as sound localization in the auditory brainstem of the barn owl. In this study, we investigate how STDP leads to the selective potentiation of recurrent connections with different axonal and dendritic delays during oscillatory activity. We develop analytical models of learning with additive STDP in recurrent networks driven by oscillatory inputs, and support the results using simulations with leaky integrate-and-fire neurons. Our results show selective potentiation of connections with specific axonal delays, which depended on the input frequency. In addition, we demonstrate how this can lead to a network becoming selective in the amplitude of its oscillatory response to this frequency. We extend this model of axonal delay selection within a single recurrent network in two ways. First, we show the selective potentiation of connections with a range of both axonal and dendritic delays. Second, we show axonal delay selection between multiple groups receiving out-of-phase, oscillatory inputs. We discuss the application of these models to the formation and activation of neuronal ensembles or cell assemblies in the cortex, and also to missing fundamental pitch perception in the auditory brainstem.

  12. Universal Connection through Art: Role of Mirror Neurons in Art Production and Reception.

    Science.gov (United States)

    Piechowski-Jozwiak, Bartlomiej; Boller, François; Bogousslavsky, Julien

    2017-05-05

    Art is defined as expression or application of human creative skill and imagination producing works to be appreciated primarily for their aesthetic value or emotional power. This definition encompasses two very important elements-the creation and reception of art-and by doing so it establishes a link, a dialogue between the artist and spectator. From the evolutionary biological perspective, activities need to have an immediate or remote effect on the population through improving survival, gene selection, and environmental adjustment, and this includes art. It may serve as a universal means of communication bypassing time, cultural, ethnic, and social differences. The neurological mechanisms of both art production and appreciation are researched by neuroscientists and discussed both in terms of healthy brain biology and complex neuronal networking perspectives. In this paper, we describe folk art and the issue of symbolic archetypes in psychoanalytic thought as well as offer neuronal mechanisms for art by emphasizing mirror/neurons and the role they play in it.

  13. Response of spiking neurons to correlated inputs

    International Nuclear Information System (INIS)

    Moreno, Ruben; Rocha, Jaime de la; Renart, Alfonso; Parga, Nestor

    2002-01-01

    The effect of a temporally correlated afferent current on the firing rate of a leaky integrate-and-fire neuron is studied. This current is characterized in terms of rates, autocorrelations, and cross correlations, and correlation time scale τ c of excitatory and inhibitory inputs. The output rate ν out is calculated in the Fokker-Planck formalism in the limit of both small and large τ c compared to the membrane time constant τ of the neuron. By simulations we check the analytical results, provide an interpolation valid for all τ c , and study the neuron's response to rapid changes in the correlation magnitude

  14. Spiking neuron devices consisting of single-flux-quantum circuits

    International Nuclear Information System (INIS)

    Hirose, Tetsuya; Asai, Tetsuya; Amemiya, Yoshihito

    2006-01-01

    Single-flux-quantum (SFQ) circuits can be used for making spiking neuron devices, which are useful elements for constructing intelligent, brain-like computers. The device we propose is based on the leaky integrate-and-fire neuron (IFN) model and uses a SFQ pulse as an action signal or a spike of neurons. The operation of the neuron device is confirmed by computer simulator. It can operate with a short delay of 100 ps or less and is the highest-speed neuron device ever reported

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

    Directory of Open Access Journals (Sweden)

    Viswanathan Arunachalam

    2013-01-01

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

  16. The terminal nerve plays a prominent role in GnRH-1 neuronal migration independent from proper olfactory and vomeronasal connections to the olfactory bulbs

    Directory of Open Access Journals (Sweden)

    Ed Zandro M. Taroc

    2017-10-01

    Yoshihara et al., 2005. Our data prove that correct development of the OBs and axonal connection of the olfactory/vomeronasal sensory neurons to the forebrain are not required for GnRH-1 ns migration, and suggest that the terminal nerve, which forms the GnRH-1 migratory scaffold, follows different guidance cues and differs in gene expression from olfactory/vomeronasal sensory neurons.

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

    Directory of Open Access Journals (Sweden)

    A. Novellino

    2007-01-01

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

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

    Science.gov (United States)

    Novellino, A.; D'Angelo, P.; Cozzi, L.; Chiappalone, M.; Sanguineti, V.; Martinoia, S.

    2007-01-01

    One of the key properties of intelligent behaviors is the capability to learn and adapt to changing environmental conditions. These features are the result of the continuous and intense interaction of the brain with the external world, mediated by the body. For this reason “embodiment” represents an innovative and very suitable experimental paradigm when studying the neural processes underlying learning new behaviors and adapting to unpredicted situations. To this purpose, we developed a novel bidirectional neural interface. We interconnected in vitro neurons, extracted from rat embryos and plated on a microelectrode array (MEA), to external devices, thus allowing real-time closed-loop interaction. The novelty of this experimental approach entails the necessity to explore different computational schemes and experimental hypotheses. In this paper, we present an open, scalable architecture, which allows fast prototyping of different modules and where coding and decoding schemes and different experimental configurations can be tested. This hybrid system can be used for studying the computational properties and information coding in biological neuronal networks with far-reaching implications for the future development of advanced neuroprostheses. PMID:18350128

  19. Sleep deprivation causes memory deficits by negatively impacting neuronal connectivity in hippocampal area CA1

    NARCIS (Netherlands)

    Havekes, Robbert; Park, Alan J; Tudor, Jennifer C; Luczak, Vincent G; Hansen, Rolf T; Ferri, Sarah L; Bruinenberg, Vibeke M; Poplawski, Shane G; Day, Jonathan P; Aton, Sara J; Radwańska, Kasia; Meerlo, Peter; Houslay, Miles D; Baillie, George S; Abel, Ted

    2016-01-01

    Brief periods of sleep loss have long-lasting consequences such as impaired memory consolidation. Structural changes in synaptic connectivity have been proposed as a substrate of memory storage. Here, we examine the impact of brief periods of sleep deprivation on dendritic structure. In mice, we

  20. Burst firing and modulation of functional connectivity in cat striate cortex.

    Science.gov (United States)

    Snider, R K; Kabara, J F; Roig, B R; Bonds, A B

    1998-08-01

    We studied the influences of the temporal firing patterns of presynaptic cat visual cortical cells on spike generation by postsynaptic cells. Multiunit recordings were dissected into the activity of individual neurons within the recorded group. Cross-correlation analysis was then used to identify directly coupled neuron pairs. The 22 multiunit groups recorded typically showed activity from two to six neurons, each containing between 1 and 15 neuron pairs. From a total of 241 neuron pairs, 91 (38%) had a shifted cross-correlation peak, which indicated a possible direct connection. Only two multiunit groups contained no shifted peaks. Burst activity, defined by groups of two or more spikes with intervals of neuron, was analyzed in terms of its effectiveness in eliciting a spike from a second, driven neuron. We defined effectiveness as the percentage of spikes from the driving neuron that are time related to spikes of the driven neuron. The effectiveness of bursts (of any length) in eliciting a time-related response spike averaged 18.53% across all measurements as compared with the effectiveness of single spikes, which averaged 9.53%. Longer bursts were more effective than shorter ones. Effectiveness was reduced with spatially nonoptimal, as opposed to optimal, stimuli. The effectiveness of both bursts and single spikes decreased by the same amount across measurements with nonoptimal orientations, spatial frequencies and contrasts. At similar firing rates and burst lengths, the decrease was more pronounced for nonoptimal orientations than for lower contrasts, suggesting the existence of a mechanism that reduces effectiveness at nonoptimal orientations. These results support the hypothesis that neural information can be emphasized via instantaneous rate coding that is not preserved over long intervals or over trials. This is consistent with the integrate and fire model, where bursts participate in temporal integration.

  1. Bifurcation analysis for a discrete-time Hopfield neural network of two neurons with two delays and self-connections

    International Nuclear Information System (INIS)

    Kaslik, E.; Balint, St.

    2009-01-01

    In this paper, a bifurcation analysis is undertaken for a discrete-time Hopfield neural network of two neurons with two different delays and self-connections. Conditions ensuring the asymptotic stability of the null solution are found, with respect to two characteristic parameters of the system. It is shown that for certain values of these parameters, Fold or Neimark-Sacker bifurcations occur, but Flip and codimension 2 (Fold-Neimark-Sacker, double Neimark-Sacker, resonance 1:1 and Flip-Neimark-Sacker) bifurcations may also be present. The direction and the stability of the Neimark-Sacker bifurcations are investigated by applying the center manifold theorem and the normal form theory

  2. Time Delay and Long-Range Connection Induced Synchronization Transitions in Newman-Watts Small-World Neuronal Networks

    Science.gov (United States)

    Qian, Yu

    2014-01-01

    The synchronization transitions in Newman-Watts small-world neuronal networks (SWNNs) induced by time delay and long-range connection (LRC) probability have been investigated by synchronization parameter and space-time plots. Four distinct parameter regions, that is, asynchronous region, transition region, synchronous region, and oscillatory region have been discovered at certain LRC probability as time delay is increased. Interestingly, desynchronization is observed in oscillatory region. More importantly, we consider the spatiotemporal patterns obtained in delayed Newman-Watts SWNNs are the competition results between long-range drivings (LRDs) and neighboring interactions. In addition, for moderate time delay, the synchronization of neuronal network can be enhanced remarkably by increasing LRC probability. Furthermore, lag synchronization has been found between weak synchronization and complete synchronization as LRC probability is a little less than 1.0. Finally, the two necessary conditions, moderate time delay and large numbers of LRCs, are exposed explicitly for synchronization in delayed Newman-Watts SWNNs. PMID:24810595

  3. CNS activation and regional connectivity during pantomime observation: no engagement of the mirror neuron system for deaf signers.

    Science.gov (United States)

    Emmorey, Karen; Xu, Jiang; Gannon, Patrick; Goldin-Meadow, Susan; Braun, Allen

    2010-01-01

    Deaf signers have extensive experience using their hands to communicate. Using fMRI, we examined the neural systems engaged during the perception of manual communication in 14 deaf signers and 14 hearing non-signers. Participants passively viewed blocked video clips of pantomimes (e.g., peeling an imaginary banana) and action verbs in American Sign Language (ASL) that were rated as meaningless by non-signers (e.g., TO-DANCE). In contrast to visual fixation, pantomimes strongly activated fronto-parietal regions (the mirror neuron system, MNS) in hearing non-signers, but only bilateral middle temporal regions in deaf signers. When contrasted with ASL verbs, pantomimes selectively engaged inferior and superior parietal regions in hearing non-signers, but right superior temporal cortex in deaf signers. The perception of ASL verbs recruited similar regions as pantomimes for deaf signers, with some evidence of greater involvement of left inferior frontal gyrus for ASL verbs. Functional connectivity analyses with left hemisphere seed voxels (ventral premotor, inferior parietal lobule, fusiform gyrus) revealed robust connectivity with the MNS for the hearing non-signers. Deaf signers exhibited functional connectivity with the right hemisphere that was not observed for the hearing group for the fusiform gyrus seed voxel. We suggest that life-long experience with manual communication, and/or auditory deprivation, may alter regional connectivity and brain activation when viewing pantomimes. We conclude that the lack of activation within the MNS for deaf signers does not support an account of human communication that depends upon automatic sensorimotor resonance between perception and action.

  4. SPICODYN: A Toolbox for the Analysis of Neuronal Network Dynamics and Connectivity from Multi-Site Spike Signal Recordings.

    Science.gov (United States)

    Pastore, Vito Paolo; Godjoski, Aleksandar; Martinoia, Sergio; Massobrio, Paolo

    2018-01-01

    We implemented an automated and efficient open-source software for the analysis of multi-site neuronal spike signals. The software package, named SPICODYN, has been developed as a standalone windows GUI application, using C# programming language with Microsoft Visual Studio based on .NET framework 4.5 development environment. Accepted input data formats are HDF5, level 5 MAT and text files, containing recorded or generated time series spike signals data. SPICODYN processes such electrophysiological signals focusing on: spiking and bursting dynamics and functional-effective connectivity analysis. In particular, for inferring network connectivity, a new implementation of the transfer entropy method is presented dealing with multiple time delays (temporal extension) and with multiple binary patterns (high order extension). SPICODYN is specifically tailored to process data coming from different Multi-Electrode Arrays setups, guarantying, in those specific cases, automated processing. The optimized implementation of the Delayed Transfer Entropy and the High-Order Transfer Entropy algorithms, allows performing accurate and rapid analysis on multiple spike trains from thousands of electrodes.

  5. Monosynaptic connections made by the sensory neurons of the gill- and siphon-withdrawal reflex in Aplysia participate in the storage of long-term memory for sensitization

    OpenAIRE

    Frost, William N.; Castellucci, Vincent F.; Hawkins, Robert D.; Kandel, Eric R.

    1985-01-01

    We have found that in the gill- and siphon- withdrawal reflex of Aplysia, the memory for short-term sensitization grades smoothly into long-term memory with increased amounts of sensitization training. One cellular locus for the storage of the memory underlying short-term sensitization is the set of monosynaptic connections between the siphon sensory cells and the gill and siphon motor neurons. We have now also found that these same monosynaptic connections participate in the storage of the m...

  6. Evolution amplified processing with temporally dispersed slow neuronal connectivity in primates.

    Science.gov (United States)

    Caminiti, Roberto; Ghaziri, Hassan; Galuske, Ralf; Hof, Patrick R; Innocenti, Giorgio M

    2009-11-17

    The corpus callosum (CC) provides the main route of communication between the 2 hemispheres of the brain. In monkeys, chimpanzees, and humans, callosal axons of distinct size interconnect functionally different cortical areas. Thinner axons in the genu and in the posterior body of the CC interconnect the prefrontal and parietal areas, respectively, and thicker axons in the midbody and in the splenium interconnect primary motor, somatosensory, and visual areas. At all locations, axon diameter, and hence its conduction velocity, increases slightly in the chimpanzee compared with the macaque because of an increased number of large axons but not between the chimpanzee and man. This, together with the longer connections in larger brains, doubles the expected conduction delays between the hemispheres, from macaque to man, and amplifies their range about 3-fold. These changes can have several consequences for cortical dynamics, particularly on the cycle of interhemispheric oscillators.

  7. Synaptic Conductance Estimates of the Connection Between Local Inhibitor Interneurons and Pyramidal Neurons in Layer 2/3 of a Cortical Column

    Science.gov (United States)

    Hoffmann, Jochen H.O.; Meyer, H. S.; Schmitt, Arno C.; Straehle, Jakob; Weitbrecht, Trinh; Sakmann, Bert; Helmstaedter, Moritz

    2015-01-01

    Stimulation of a principal whisker yields sparse action potential (AP) spiking in layer 2/3 (L2/3) pyramidal neurons in a cortical column of rat barrel cortex. The low AP rates in pyramidal neurons could be explained by activation of interneurons in L2/3 providing inhibition onto L2/3 pyramidal neurons. L2/3 interneurons classified as local inhibitors based on their axonal projection in the same column were reported to receive strong excitatory input from spiny neurons in L4, which are also the main source of the excitatory input to L2/3 pyramidal neurons. Here, we investigated the remaining synaptic connection in this intracolumnar microcircuit. We found strong and reliable inhibitory synaptic transmission between intracolumnar L2/3 local-inhibitor-to-L2/3 pyramidal neuron pairs [inhibitory postsynaptic potential (IPSP) amplitude −0.88 ± 0.67 mV]. On average, 6.2 ± 2 synaptic contacts were made by L2/3 local inhibitors onto L2/3 pyramidal neurons at 107 ± 64 µm path distance from the pyramidal neuron soma, thus overlapping with the distribution of synaptic contacts from L4 spiny neurons onto L2/3 pyramidal neurons (67 ± 34 µm). Finally, using compartmental simulations, we determined the synaptic conductance per synaptic contact to be 0.77 ± 0.4 nS. We conclude that the synaptic circuit from L4 to L2/3 can provide efficient shunting inhibition that is temporally and spatially aligned with the excitatory input from L4 to L2/3. PMID:25761638

  8. 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

  9. Sleep deprivation causes memory deficits by negatively impacting neuronal connectivity in hippocampal area CA1

    Science.gov (United States)

    Havekes, Robbert; Park, Alan J; Tudor, Jennifer C; Luczak, Vincent G; Hansen, Rolf T; Ferri, Sarah L; Bruinenberg, Vibeke M; Poplawski, Shane G; Day, Jonathan P; Aton, Sara J; Radwańska, Kasia; Meerlo, Peter; Houslay, Miles D; Baillie, George S; Abel, Ted

    2016-01-01

    Brief periods of sleep loss have long-lasting consequences such as impaired memory consolidation. Structural changes in synaptic connectivity have been proposed as a substrate of memory storage. Here, we examine the impact of brief periods of sleep deprivation on dendritic structure. In mice, we find that five hours of sleep deprivation decreases dendritic spine numbers selectively in hippocampal area CA1 and increased activity of the filamentous actin severing protein cofilin. Recovery sleep normalizes these structural alterations. Suppression of cofilin function prevents spine loss, deficits in hippocampal synaptic plasticity, and impairments in long-term memory caused by sleep deprivation. The elevated cofilin activity is caused by cAMP-degrading phosphodiesterase-4A5 (PDE4A5), which hampers cAMP-PKA-LIMK signaling. Attenuating PDE4A5 function prevents changes in cAMP-PKA-LIMK-cofilin signaling and cognitive deficits associated with sleep deprivation. Our work demonstrates the necessity of an intact cAMP-PDE4-PKA-LIMK-cofilin activation-signaling pathway for sleep deprivation-induced memory disruption and reduction in hippocampal spine density. DOI: http://dx.doi.org/10.7554/eLife.13424.001 PMID:27549340

  10. The Functional Networks of Prepulse Inhibition: Neuronal Connectivity Analysis Based on FDG-PET in Awake and Unrestrained Rats.

    Directory of Open Access Journals (Sweden)

    Cathrin Rohleder

    2016-07-01

    Full Text Available Prepulse inhibition (PPI is a neuropsychological process during which a weak sensory stimulus (prepulse attenuates the motor response (startle reaction to a subsequent strong startling stimulus. It is measured as a surrogate marker of sensorimotor gating in patients suffering from neuropsychological diseases such as schizophrenia, as well as in corresponding animal models. A variety of studies has shown that PPI of the acoustical startle reaction comprises three brain circuitries for: i startle mediation, ii PPI mediation and iii modulation of PPI mediation. While anatomical connections and information flow in the startle and PPI mediation pathways are well known, spatial and temporal interactions of the numerous regions involved in PPI modulation are incompletely understood.We therefore combined [18F]fluoro-2-deoxyglucose positron-emission-tomography (FDG-PET with PPI and resting state control paradigms in awake rats. A battery of subtractive, correlative as well as seed-based functional connectivity analyses revealed a default mode-like network (DMN active during resting state only. Furthermore, two functional networks were observed during PPI: Metabolic activity in the lateral circuitry was positively correlated with PPI effectiveness and involved the auditory system and emotional regions. The medial network was negatively correlated with PPI effectiveness, i.e. associated with startle, and recruited a spatial/cognitive network. Our study provides evidence for two distinct neuronal networks, whose continuous interplay determines PPI effectiveness in rats, probably by either protecting the prepulse or facilitating startle processing.Discovering similar networks affected in neuropsychological disorders may help to better understand mechanisms of sensorimotor gating deficits and provide new perspectives for therapeutic strategies.

  11. The Functional Networks of Prepulse Inhibition: Neuronal Connectivity Analysis Based on FDG-PET in Awake and Unrestrained Rats.

    Science.gov (United States)

    Rohleder, Cathrin; Wiedermann, Dirk; Neumaier, Bernd; Drzezga, Alexander; Timmermann, Lars; Graf, Rudolf; Leweke, F Markus; Endepols, Heike

    2016-01-01

    Prepulse inhibition (PPI) is a neuropsychological process during which a weak sensory stimulus ("prepulse") attenuates the motor response ("startle reaction") to a subsequent strong startling stimulus. It is measured as a surrogate marker of sensorimotor gating in patients suffering from neuropsychological diseases such as schizophrenia, as well as in corresponding animal models. A variety of studies has shown that PPI of the acoustical startle reaction comprises three brain circuitries for: (i) startle mediation, (ii) PPI mediation, and (iii) modulation of PPI mediation. While anatomical connections and information flow in the startle and PPI mediation pathways are well known, spatial and temporal interactions of the numerous regions involved in PPI modulation are incompletely understood. We therefore combined [(18)F]fluoro-2-deoxyglucose positron-emission-tomography (FDG-PET) with PPI and resting state control paradigms in awake rats. A battery of subtractive, correlative as well as seed-based functional connectivity analyses revealed a default mode-like network (DMN) active during resting state only. Furthermore, two functional networks were observed during PPI: Metabolic activity in the lateral circuitry was positively correlated with PPI effectiveness and involved the auditory system and emotional regions. The medial network was negatively correlated with PPI effectiveness, i.e., associated with startle, and recruited a spatial/cognitive network. Our study provides evidence for two distinct neuronal networks, whose continuous interplay determines PPI effectiveness in rats, probably by either protecting the prepulse or facilitating startle processing. Discovering similar networks affected in neuropsychological disorders may help to better understand mechanisms of sensorimotor gating deficits and provide new perspectives for therapeutic strategies.

  12. High Content Analysis of Hippocampal Neuron-Astrocyte Co-cultures Shows a Positive Effect of Fortasyn Connect on Neuronal Survival and Postsynaptic Maturation

    NARCIS (Netherlands)

    van Deijk, Anne-Lieke F; Broersen, Laus M; Verkuyl, J Martin; Smit, August B; Verheijen, Mark H G

    2017-01-01

    Neuronal and synaptic membranes are composed of a phospholipid bilayer. Supplementation with dietary precursors for phospholipid synthesis -docosahexaenoic acid (DHA), uridine and choline- has been shown to increase neurite outgrowth and synaptogenesis bothin vivoandin vitro. A role for

  13. Qualitative and quantitative estimation of comprehensive synaptic connectivity in short- and long-term cultured rat hippocampal neurons with new analytical methods inspired by Scatchard and Hill plots

    Energy Technology Data Exchange (ETDEWEB)

    Tanamoto, Ryo; Shindo, Yutaka; Niwano, Mariko [Department of Biosciences and Informatics, Faculty of Science and Technology, Keio University (Japan); Matsumoto, Yoshinori [Department of Applied Physics and Physico-Informatics, Faculty of Science and Technology, Keio University (Japan); Miki, Norihisa [Department of Mechanical Engineering, Faculty of Science and Technology, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama, Kanagawa, 223-8522 (Japan); Hotta, Kohji [Department of Biosciences and Informatics, Faculty of Science and Technology, Keio University (Japan); Oka, Kotaro, E-mail: oka@bio.keio.ac.jp [Department of Biosciences and Informatics, Faculty of Science and Technology, Keio University (Japan)

    2016-03-18

    To investigate comprehensive synaptic connectivity, we examined Ca{sup 2+} responses with quantitative electric current stimulation by indium-tin-oxide (ITO) glass electrode with transparent and high electro-conductivity. The number of neurons with Ca{sup 2+} responses was low during the application of stepwise increase of electric current in short-term cultured neurons (less than 17 days in-vitro (DIV)). The neurons cultured over 17 DIV showed two-type responses: S-shaped (sigmoid) and monotonous saturated responses, and Scatchard plots well illustrated the difference of these two responses. Furthermore, sigmoid like neural network responses over 17 DIV were altered to the monotonous saturated ones by the application of the mixture of AP5 and CNQX, specific blockers of NMDA and AMPA receptors, respectively. This alternation was also characterized by the change of Hill coefficients. These findings indicate that the neural network with sigmoid-like responses has strong synergetic or cooperative synaptic connectivity via excitatory glutamate synapses. - Highlights: • We succeed to evaluate the maturation of neural network by Scathard and Hill Plots. • Long-term cultured neurons showed two-type responses: sigmoid and monotonous. • The sigmoid-like increase indicates the cooperatevity of neural networks. • Excitatory glutamate synapses cause the cooperatevity of neural networks.

  14. Connections between EM2-containing terminals and GABA/μ-opioid receptor co-expressing neurons in the rat spinal trigeminal caudal nucleus

    Science.gov (United States)

    Li, Meng-Ying; Wu, Zhen-Yu; Lu, Ya-Cheng; Yin, Jun-Bin; Wang, Jian; Zhang, Ting; Dong, Yu-Lin; Wang, Feng

    2014-01-01

    Endomorphin-2 (EM2) demonstrates a potent antinociceptive effect via the μ-opioid receptor (MOR). To provide morphological evidence for the pain control effect of EM2, the synaptic connections between EM2-immunoreactive (IR) axonal terminals and γ-amino butyric acid (GABA)/MOR co-expressing neurons in lamina II of the spinal trigeminal caudal nucleus (Vc) were investigated in the rat. Dense EM2-, MOR- and GABA-IR fibers and terminals were mainly observed in lamina II of the Vc. Within lamina II, GABA- and MOR-neuronal cell bodies were also encountered. The results of immunofluorescent histochemical triple-staining showed that approximately 14.2 or 18.9% of GABA-IR or MOR-IR neurons also showed MOR- or GABA-immunopositive staining in lamina II; approximately 45.2 and 36.1% of the GABA-IR and MOR-IR neurons, respectively, expressed FOS protein in their nuclei induced by injecting formalin into the left lower lip of the mouth. Most of the GABA/MOR, GABA/FOS, and MOR/FOS double-labeled neurons made close contacts with EM2-IR fibers and terminals. Immuno-electron microscopy confirmed that the EM2-IR terminals formed synapses with GABA-IR or MOR-IR dendritic processes and neuronal cell bodies in lamina II of the Vc. These results suggest that EM2 might participate in pain transmission and modulation by binding to MOR-IR and GABAergic inhibitory interneuron in lamina II of the Vc to exert inhibitory effect on the excitatory interneuron in lamina II and projection neurons in laminae I and III. PMID:25386121

  15. Bayesian population decoding of spiking neurons.

    Science.gov (United States)

    Gerwinn, Sebastian; Macke, Jakob; Bethge, Matthias

    2009-01-01

    The timing of action potentials in spiking neurons depends on the temporal dynamics of their inputs and contains information about temporal fluctuations in the stimulus. Leaky integrate-and-fire neurons constitute a popular class of encoding models, in which spike times depend directly on the temporal structure of the inputs. However, optimal decoding rules for these models have only been studied explicitly in the noiseless case. Here, we study decoding rules for probabilistic inference of a continuous stimulus from the spike times of a population of leaky integrate-and-fire neurons with threshold noise. We derive three algorithms for approximating the posterior distribution over stimuli as a function of the observed spike trains. In addition to a reconstruction of the stimulus we thus obtain an estimate of the uncertainty as well. Furthermore, we derive a 'spike-by-spike' online decoding scheme that recursively updates the posterior with the arrival of each new spike. We use these decoding rules to reconstruct time-varying stimuli represented by a Gaussian process from spike trains of single neurons as well as neural populations.

  16. Bayesian population decoding of spiking neurons

    Directory of Open Access Journals (Sweden)

    Sebastian Gerwinn

    2009-10-01

    Full Text Available The timing of action potentials in spiking neurons depends on the temporal dynamics of their inputs and contains information about temporal fluctuations in the stimulus. Leaky integrate-and-fire neurons constitute a popular class of encoding models, in which spike times depend directly on the temporal structure of the inputs. However, optimal decoding rules for these models have only been studied explicitly in the noiseless case. Here, we study decoding rules for probabilistic inference of a continuous stimulus from the spike times of a population of leaky integrate-and-fire neurons with threshold noise. We derive three algorithms for approximating the posterior distribution over stimuli as a function of the observed spike trains. In addition to a reconstruction of the stimulus we thus obtain an estimate of the uncertainty as well. Furthermore, we derive a `spike-by-spike' online decoding scheme that recursively updates the posterior with the arrival of each new spike. We use these decoding rules to reconstruct time-varying stimuli represented by a Gaussian process from spike trains of single neurons as well as neural populations.

  17. Mirrored STDP Implements Autoencoder Learning in a Network of Spiking Neurons.

    Science.gov (United States)

    Burbank, Kendra S

    2015-12-01

    The autoencoder algorithm is a simple but powerful unsupervised method for training neural networks. Autoencoder networks can learn sparse distributed codes similar to those seen in cortical sensory areas such as visual area V1, but they can also be stacked to learn increasingly abstract representations. Several computational neuroscience models of sensory areas, including Olshausen & Field's Sparse Coding algorithm, can be seen as autoencoder variants, and autoencoders have seen extensive use in the machine learning community. Despite their power and versatility, autoencoders have been difficult to implement in a biologically realistic fashion. The challenges include their need to calculate differences between two neuronal activities and their requirement for learning rules which lead to identical changes at feedforward and feedback connections. Here, we study a biologically realistic network of integrate-and-fire neurons with anatomical connectivity and synaptic plasticity that closely matches that observed in cortical sensory areas. Our choice of synaptic plasticity rules is inspired by recent experimental and theoretical results suggesting that learning at feedback connections may have a different form from learning at feedforward connections, and our results depend critically on this novel choice of plasticity rules. Specifically, we propose that plasticity rules at feedforward versus feedback connections are temporally opposed versions of spike-timing dependent plasticity (STDP), leading to a symmetric combined rule we call Mirrored STDP (mSTDP). We show that with mSTDP, our network follows a learning rule that approximately minimizes an autoencoder loss function. When trained with whitened natural image patches, the learned synaptic weights resemble the receptive fields seen in V1. Our results use realistic synaptic plasticity rules to show that the powerful autoencoder learning algorithm could be within the reach of real biological networks.

  18. Reconstruction of sparse connectivity in neural networks from spike train covariances

    International Nuclear Information System (INIS)

    Pernice, Volker; Rotter, Stefan

    2013-01-01

    The inference of causation from correlation is in general highly problematic. Correspondingly, it is difficult to infer the existence of physical synaptic connections between neurons from correlations in their activity. Covariances in neural spike trains and their relation to network structure have been the subject of intense research, both experimentally and theoretically. The influence of recurrent connections on covariances can be characterized directly in linear models, where connectivity in the network is described by a matrix of linear coupling kernels. However, as indirect connections also give rise to covariances, the inverse problem of inferring network structure from covariances can generally not be solved unambiguously. Here we study to what degree this ambiguity can be resolved if the sparseness of neural networks is taken into account. To reconstruct a sparse network, we determine the minimal set of linear couplings consistent with the measured covariances by minimizing the L 1 norm of the coupling matrix under appropriate constraints. Contrary to intuition, after stochastic optimization of the coupling matrix, the resulting estimate of the underlying network is directed, despite the fact that a symmetric matrix of count covariances is used for inference. The performance of the new method is best if connections are neither exceedingly sparse, nor too dense, and it is easily applicable for networks of a few hundred nodes. Full coupling kernels can be obtained from the matrix of full covariance functions. We apply our method to networks of leaky integrate-and-fire neurons in an asynchronous–irregular state, where spike train covariances are well described by a linear model. (paper)

  19. Migration Pathways of Thalamic Neurons and Development of Thalamocortical Connections in Humans Revealed by Diffusion MR Tractography.

    Science.gov (United States)

    Wilkinson, Molly; Kane, Tara; Wang, Rongpin; Takahashi, Emi

    2017-12-01

    The thalamus plays an important role in signal relays in the brain, with thalamocortical (TC) neuronal pathways linked to various sensory/cognitive functions. In this study, we aimed to see fetal and postnatal development of the thalamus including neuronal migration to the thalamus and the emergence/maturation of the TC pathways. Pathways from/to the thalami of human postmortem fetuses and in vivo subjects ranging from newborns to adults with no neurological histories were studied using high angular resolution diffusion MR imaging (HARDI) tractography. Pathways likely linked to neuronal migration from the ventricular zone and ganglionic eminence (GE) to the thalami were both successfully detected. Between the ventricular zone and thalami, more tractography pathways were found in anterior compared with posterior regions, which was well in agreement with postnatal observations that the anterior TC segment had more tract count and volume than the posterior segment. Three different pathways likely linked to neuronal migration from the GE to the thalami were detected. No hemispheric asymmetry of the TC pathways was quantitatively observed during development. These results suggest that HARDI tractography is useful to identify multiple differential neuronal migration pathways in human brains, and regional differences in brain development in fetal ages persisted in postnatal development. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  20. Dynamics of Competition between Subnetworks of Spiking Neuronal Networks in the Balanced State

    Science.gov (United States)

    Lagzi, Fereshteh; Rotter, Stefan

    2015-01-01

    We explore and analyze the nonlinear switching dynamics of neuronal networks with non-homogeneous connectivity. The general significance of such transient dynamics for brain function is unclear; however, for instance decision-making processes in perception and cognition have been implicated with it. The network under study here is comprised of three subnetworks of either excitatory or inhibitory leaky integrate-and-fire neurons, of which two are of the same type. The synaptic weights are arranged to establish and maintain a balance between excitation and inhibition in case of a constant external drive. Each subnetwork is randomly connected, where all neurons belonging to a particular population have the same in-degree and the same out-degree. Neurons in different subnetworks are also randomly connected with the same probability; however, depending on the type of the pre-synaptic neuron, the synaptic weight is scaled by a factor. We observed that for a certain range of the “within” versus “between” connection weights (bifurcation parameter), the network activation spontaneously switches between the two sub-networks of the same type. This kind of dynamics has been termed “winnerless competition”, which also has a random component here. In our model, this phenomenon is well described by a set of coupled stochastic differential equations of Lotka-Volterra type that imply a competition between the subnetworks. The associated mean-field model shows the same dynamical behavior as observed in simulations of large networks comprising thousands of spiking neurons. The deterministic phase portrait is characterized by two attractors and a saddle node, its stochastic component is essentially given by the multiplicative inherent noise of the system. We find that the dwell time distribution of the active states is exponential, indicating that the noise drives the system randomly from one attractor to the other. A similar model for a larger number of populations might

  1. Alterations of parenchymal microstructure, neuronal connectivity and cerebrovascular resistance at adolescence following mild to moderate traumatic brain injury in early development.

    Science.gov (United States)

    Parent, Maxime; Li, Ying; Santhakumar, Vijayalakshmi; Hyder, Fahmeed; Sanganahalli, Basavaraju G; Kannurpatti, Sridhar

    2018-06-01

    TBI is a leading cause of morbidity in children. To investigate outcome of early developmental TBI during adolescence, a rat model of fluid percussion injury was developed, where previous work reported deficits in sensorimotor behavior and cortical blood flow at adolescence. 1 Based on the non-localized outcome, we hypothesized that multiple neurophysiological components of brain function, namely neuronal connectivity, synapse/axonal microstructural integrity and neurovascular function are altered and magnetic resonance imaging (MRI) methods could be used to determine regional alterations. Adolescent outcomes of developmental TBI were studied 2-months after injury, using functional MRI (fMRI) and Diffusion Tensor Imaging (DTI). fMRI based resting state functional connectivity (RSFC), representing neural connectivity, was significantly altered between sham and TBI. RSFC strength decreased in the cortex, hippocampus and thalamus accompanied by decrease in the spatial extent of their corresponding RSFC networks and inter-hemispheric asymmetry. Cerebrovascular reactivity to arterial CO2 changes diminished after TBI across both hemispheres, with a more pronounced decrease in the ipsilateral hippocampus, thalamus and motor cortex. DTI measures of fractional anisotropy (FA) and apparent diffusion coefficient (ADC), reporting on axonal and microstructural integrity of the brain, indicated similar inter-hemispheric asymmetry, with highest change in the ipsilateral hippocampus and regions adjoining the ipsilateral thalamus, hypothalamus and amygdala. TBI-induced corpus callosal microstructural alterations indicated measurable changes in inter-hemispheric structural connectivity. Hippocampus, thalamus and select cortical regions were most consistently affected in multiple imaging markers. The multi-modal MRI results demonstrate cortical and subcortical alterations in neural connectivity, cerebrovascular resistance and parenchymal microstructure in the adolescent brain

  2. Bistability induces episodic spike communication by inhibitory neurons in neuronal networks.

    Science.gov (United States)

    Kazantsev, V B; Asatryan, S Yu

    2011-09-01

    Bistability is one of the important features of nonlinear dynamical systems. In neurodynamics, bistability has been found in basic Hodgkin-Huxley equations describing the cell membrane dynamics. When the neuron is clamped near its threshold, the stable rest potential may coexist with the stable limit cycle describing periodic spiking. However, this effect is often neglected in network computations where the neurons are typically reduced to threshold firing units (e.g., integrate-and-fire models). We found that the bistability may induce spike communication by inhibitory coupled neurons in the spiking network. The communication is realized in the form of episodic discharges with synchronous (correlated) spikes during the episodes. A spiking phase map is constructed to describe the synchronization and to estimate basic spike phase locking modes.

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

    Science.gov (United States)

    Ortigue, Stephanie; Bianchi-Demicheli, Francesco

    2008-12-01

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

  4. Changes of Functional and Directed Resting-State Connectivity Are Associated with Neuronal Oscillations, ApoE Genotype and Amyloid Deposition in Mild Cognitive Impairment

    Directory of Open Access Journals (Sweden)

    Lars Michels

    2017-09-01

    Full Text Available The assessment of effects associated with cognitive impairment using electroencephalography (EEG power mapping allows the visualization of frequency-band specific local changes in oscillatory activity. In contrast, measures of coherence and dynamic source synchronization allow for the study of functional and effective connectivity, respectively. Yet, these measures have rarely been assessed in parallel in the context of mild cognitive impairment (MCI and furthermore it has not been examined if they are related to risk factors of Alzheimer’s disease (AD such as amyloid deposition and apolipoprotein ε4 (ApoE allele occurrence. Here, we investigated functional and directed connectivities with Renormalized Partial Directed Coherence (RPDC in 17 healthy controls (HC and 17 participants with MCI. Participants underwent ApoE-genotyping and Pittsburgh compound B positron emission tomography (PiB-PET to assess amyloid deposition. We observed lower spectral source power in MCI in the alpha and beta bands. Coherence was stronger in HC than MCI across different neuronal sources in the delta, theta, alpha, beta and gamma bands. The directed coherence analysis indicated lower information flow between fronto-temporal (including the hippocampus sources and unidirectional connectivity in MCI. In MCI, alpha and beta RPDC showed an inverse correlation to age and gender; global amyloid deposition was inversely correlated to alpha coherence, RPDC and beta and gamma coherence. Furthermore, the ApoE status was negatively correlated to alpha coherence and RPDC, beta RPDC and gamma coherence. A classification analysis of cognitive state revealed the highest accuracy using EEG power, coherence and RPDC as input. For this small but statistically robust (Bayesian power analyses sample, our results suggest that resting EEG related functional and directed connectivities are sensitive to the cognitive state and are linked to ApoE and amyloid burden.

  5. Forced phase-locked states and information retrieval in a two-layer network of oscillatory neurons with directional connectivity

    International Nuclear Information System (INIS)

    Kazantsev, Victor; Pimashkin, Alexey

    2007-01-01

    We propose two-layer architecture of associative memory oscillatory network with directional interlayer connectivity. The network is capable to store information in the form of phase-locked (in-phase and antiphase) oscillatory patterns. The first (input) layer takes an input pattern to be recognized and their units are unidirectionally connected with all units of the second (control) layer. The connection strengths are weighted using the Hebbian rule. The output (retrieved) patterns appear as forced-phase locked states of the control layer. The conditions are found and analytically expressed for pattern retrieval in response on incoming stimulus. It is shown that the system is capable to recover patterns with a certain level of distortions or noises in their profiles. The architecture is implemented with the Kuramoto phase model and using synaptically coupled neural oscillators with spikes. It is found that the spiking model is capable to retrieve patterns using the spiking phase that translates memorized patterns into the spiking phase shifts at different time scales

  6. 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.

  7. Joint statistics of strongly correlated neurons via dimensionality reduction

    International Nuclear Information System (INIS)

    Deniz, Taşkın; Rotter, Stefan

    2017-01-01

    The relative timing of action potentials in neurons recorded from local cortical networks often shows a non-trivial dependence, which is then quantified by cross-correlation functions. Theoretical models emphasize that such spike train correlations are an inevitable consequence of two neurons being part of the same network and sharing some synaptic input. For non-linear neuron models, however, explicit correlation functions are difficult to compute analytically, and perturbative methods work only for weak shared input. In order to treat strong correlations, we suggest here an alternative non-perturbative method. Specifically, we study the case of two leaky integrate-and-fire neurons with strong shared input. Correlation functions derived from simulated spike trains fit our theoretical predictions very accurately. Using our method, we computed the non-linear correlation transfer as well as correlation functions that are asymmetric due to inhomogeneous intrinsic parameters or unequal input. (paper)

  8. Functional connectivity and neuronal variability of resting state activity in bipolar disorder--reduction and decoupling in anterior cortical midline structures.

    Science.gov (United States)

    Magioncalda, Paola; Martino, Matteo; Conio, Benedetta; Escelsior, Andrea; Piaggio, Niccolò; Presta, Andrea; Marozzi, Valentina; Rocchi, Giulio; Anastasio, Loris; Vassallo, Linda; Ferri, Francesca; Huang, Zirui; Roccatagliata, Luca; Pardini, Matteo; Northoff, Georg; Amore, Mario

    2015-02-01

    The cortical midline structures seem to be involved in the modulation of different resting state networks, such as the default mode network (DMN) and salience network (SN). Alterations in these systems, in particular in the perigenual anterior cingulate cortex (PACC), seem to play a central role in bipolar disorder (BD). However, the exact role of the PACC, and its functional connections to other midline regions (within and outside DMN) still remains unclear in BD. We investigated functional connectivity (FC), standard deviation (SD, as a measure of neuronal variability) and their correlation in bipolar patients (n = 40) versus healthy controls (n = 40), in the PACC and in its connections in different frequency bands (standard: 0.01-0.10 Hz; Slow-5: 0.01-0.027 Hz; Slow-4: 0.027-0.073 Hz). Finally, we studied the correlations between FC alterations and clinical-neuropsychological parameters and we explored whether subgroups of patients in different phases of the illness present different patterns of FC abnormalities. We found in BD decreased FC (especially in Slow-5) from the PACC to other regions located predominantly in the posterior DMN (such as the posterior cingulate cortex (PCC) and inferior temporal gyrus) and in the SN (such as the supragenual anterior cingulate cortex and ventrolateral prefrontal cortex). Second, we found in BD a decoupling between PACC-based FC and variability in the various target regions (without alteration in variability itself). Finally, in our subgroups explorative analysis, we found a decrease in FC between the PACC and supragenual ACC (in depressive phase) and between the PACC and PCC (in manic phase). These findings suggest that in BD the communication, that is, information transfer, between the different cortical midline regions within the cingulate gyrus does not seem to work properly. This may result in dysbalance between different resting state networks like the DMN and SN. A deficit in the anterior DMN-SN connectivity

  9. Phase precession through acceleration of local theta rhythm: a biophysical model for the interaction between place cells and local inhibitory neurons.

    Science.gov (United States)

    Castro, Luísa; Aguiar, Paulo

    2012-08-01

    Phase precession is one of the most well known examples within the temporal coding hypothesis. Here we present a biophysical spiking model for phase precession in hippocampal CA1 which focuses on the interaction between place cells and local inhibitory interneurons. The model's functional block is composed of a place cell (PC) connected with a local inhibitory cell (IC) which is modulated by the population theta rhythm. Both cells receive excitatory inputs from the entorhinal cortex (EC). These inputs are both theta modulated and space modulated. The dynamics of the two neuron types are described by integrate-and-fire models with conductance synapses, and the EC inputs are described using non-homogeneous Poisson processes. Phase precession in our model is caused by increased drive to specific PC/IC pairs when the animal is in their place field. The excitation increases the IC's firing rate, and this modulates the PC's firing rate such that both cells precess relative to theta. Our model implies that phase coding in place cells may not be independent from rate coding. The absence of restrictive connectivity constraints in this model predicts the generation of phase precession in any network with similar architecture and subject to a clocking rhythm, independently of the involvement in spatial tasks.

  10. Information transmission with spiking Bayesian neurons

    International Nuclear Information System (INIS)

    Lochmann, Timm; Deneve, Sophie

    2008-01-01

    Spike trains of cortical neurons resulting from repeatedpresentations of a stimulus are variable and exhibit Poisson-like statistics. Many models of neural coding therefore assumed that sensory information is contained in instantaneous firing rates, not spike times. Here, we ask how much information about time-varying stimuli can be transmitted by spiking neurons with such input and output variability. In particular, does this variability imply spike generation to be intrinsically stochastic? We consider a model neuron that estimates optimally the current state of a time-varying binary variable (e.g. presence of a stimulus) by integrating incoming spikes. The unit signals its current estimate to other units with spikes whenever the estimate increased by a fixed amount. As shown previously, this computation results in integrate and fire dynamics with Poisson-like output spike trains. This output variability is entirely due to the stochastic input rather than noisy spike generation. As a result such a deterministic neuron can transmit most of the information about the time varying stimulus. This contrasts with a standard model of sensory neurons, the linear-nonlinear Poisson (LNP) model which assumes that most variability in output spike trains is due to stochastic spike generation. Although it yields the same firing statistics, we found that such noisy firing results in the loss of most information. Finally, we use this framework to compare potential effects of top-down attention versus bottom-up saliency on information transfer with spiking neurons

  11. Enhanced Sensitivity to Rapid Input Fluctuations by Nonlinear Threshold Dynamics in Neocortical Pyramidal Neurons.

    Science.gov (United States)

    Mensi, Skander; Hagens, Olivier; Gerstner, Wulfram; Pozzorini, Christian

    2016-02-01

    The way in which single neurons transform input into output spike trains has fundamental consequences for network coding. Theories and modeling studies based on standard Integrate-and-Fire models implicitly assume that, in response to increasingly strong inputs, neurons modify their coding strategy by progressively reducing their selective sensitivity to rapid input fluctuations. Combining mathematical modeling with in vitro experiments, we demonstrate that, in L5 pyramidal neurons, the firing threshold dynamics adaptively adjust the effective timescale of somatic integration in order to preserve sensitivity to rapid signals over a broad range of input statistics. For that, a new Generalized Integrate-and-Fire model featuring nonlinear firing threshold dynamics and conductance-based adaptation is introduced that outperforms state-of-the-art neuron models in predicting the spiking activity of neurons responding to a variety of in vivo-like fluctuating currents. Our model allows for efficient parameter extraction and can be analytically mapped to a Generalized Linear Model in which both the input filter--describing somatic integration--and the spike-history filter--accounting for spike-frequency adaptation--dynamically adapt to the input statistics, as experimentally observed. Overall, our results provide new insights on the computational role of different biophysical processes known to underlie adaptive coding in single neurons and support previous theoretical findings indicating that the nonlinear dynamics of the firing threshold due to Na+-channel inactivation regulate the sensitivity to rapid input fluctuations.

  12. Time Resolution Dependence of Information Measures for Spiking Neurons: Scaling and Universality

    Directory of Open Access Journals (Sweden)

    James P Crutchfield

    2015-08-01

    Full Text Available The mutual information between stimulus and spike-train response is commonly used to monitor neural coding efficiency, but neuronal computation broadly conceived requires more refined and targeted information measures of input-output joint processes. A first step towards that larger goal is todevelop information measures for individual output processes, including information generation (entropy rate, stored information (statisticalcomplexity, predictable information (excess entropy, and active information accumulation (bound information rate. We calculate these for spike trains generated by a variety of noise-driven integrate-and-fire neurons as a function of time resolution and for alternating renewal processes. We show that their time-resolution dependence reveals coarse-grained structural properties of interspike interval statistics; e.g., $tau$-entropy rates that diverge less quickly than the firing rate indicate interspike interval correlations. We also find evidence that the excess entropy and regularized statistical complexity of different types of integrate-and-fire neurons are universal in the continuous-time limit in the sense that they do not depend on mechanism details. This suggests a surprising simplicity in the spike trains generated by these model neurons. Interestingly, neurons with gamma-distributed ISIs and neurons whose spike trains are alternating renewal processes do not fall into the same universality class. These results lead to two conclusions. First, the dependence of information measures on time resolution reveals mechanistic details about spike train generation. Second, information measures can be used as model selection tools for analyzing spike train processes.

  13. 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)

  14. A self-resetting spiking phase-change neuron

    Science.gov (United States)

    Cobley, R. A.; Hayat, H.; Wright, C. D.

    2018-05-01

    Neuromorphic, or brain-inspired, computing applications of phase-change devices have to date concentrated primarily on the implementation of phase-change synapses. However, the so-called accumulation mode of operation inherent in phase-change materials and devices can also be used to mimic the integrative properties of a biological neuron. Here we demonstrate, using physical modelling of nanoscale devices and SPICE modelling of associated circuits, that a single phase-change memory cell integrated into a comparator type circuit can deliver a basic hardware mimic of an integrate-and-fire spiking neuron with self-resetting capabilities. Such phase-change neurons, in combination with phase-change synapses, can potentially open a new route for the realisation of all-phase-change neuromorphic computing.

  15. A self-resetting spiking phase-change neuron.

    Science.gov (United States)

    Cobley, R A; Hayat, H; Wright, C D

    2018-05-11

    Neuromorphic, or brain-inspired, computing applications of phase-change devices have to date concentrated primarily on the implementation of phase-change synapses. However, the so-called accumulation mode of operation inherent in phase-change materials and devices can also be used to mimic the integrative properties of a biological neuron. Here we demonstrate, using physical modelling of nanoscale devices and SPICE modelling of associated circuits, that a single phase-change memory cell integrated into a comparator type circuit can deliver a basic hardware mimic of an integrate-and-fire spiking neuron with self-resetting capabilities. Such phase-change neurons, in combination with phase-change synapses, can potentially open a new route for the realisation of all-phase-change neuromorphic computing.

  16. Modulation of neuronal dynamic range using two different adaptation mechanisms

    Directory of Open Access Journals (Sweden)

    Lei Wang

    2017-01-01

    Full Text Available The capability of neurons to discriminate between intensity of external stimulus is measured by its dynamic range. A larger dynamic range indicates a greater probability of neuronal survival. In this study, the potential roles of adaptation mechanisms (ion currents in modulating neuronal dynamic range were numerically investigated. Based on the adaptive exponential integrate-and-fire model, which includes two different adaptation mechanisms, i.e. subthreshold and suprathreshold (spike-triggered adaptation, our results reveal that the two adaptation mechanisms exhibit rather different roles in regulating neuronal dynamic range. Specifically, subthreshold adaptation acts as a negative factor that observably decreases the neuronal dynamic range, while suprathreshold adaptation has little influence on the neuronal dynamic range. Moreover, when stochastic noise was introduced into the adaptation mechanisms, the dynamic range was apparently enhanced, regardless of what state the neuron was in, e.g. adaptive or non-adaptive. Our model results suggested that the neuronal dynamic range can be differentially modulated by different adaptation mechanisms. Additionally, noise was a non-ignorable factor, which could effectively modulate the neuronal dynamic range.

  17. 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.

  18. NeuronBank: a tool for cataloging neuronal circuitry

    Directory of Open Access Journals (Sweden)

    Paul S Katz

    2010-04-01

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

  19. 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...... origin. In particular, we allow for the noise to be of arbitrary intensity. The optimal control problem is solved using dynamic programming when the controller has access to the voltage (closed-loop control), and using a maximum principle for the transition density when the controller only has access...... 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...

  20. Simulation of a spiking neuron circuit using carbon nanotube transistors

    International Nuclear Information System (INIS)

    Najari, Montassar; El-Grour, Tarek; Jelliti, Sami; Hakami, Othman Mousa

    2016-01-01

    Neuromorphic engineering is related to the existing analogies between the physical semiconductor VLSI (Very Large Scale Integration) and biophysics. Neuromorphic systems propose to reproduce the structure and function of biological neural systems for transferring their calculation capacity on silicon. Since the innovative research of Carver Mead, the neuromorphic engineering continues to emerge remarkable implementation of biological system. This work presents a simulation of an elementary neuron cell with a carbon nanotube transistor (CNTFET) based technology. The model of the cell neuron which was simulated is called integrate and fire (I&F) model firstly introduced by G. Indiveri in 2009. This circuit has been simulated with CNTFET technology using ADS environment to verify the neuromorphic activities in terms of membrane potential. This work has demonstrated the efficiency of this emergent device; i.e CNTFET on the design of such architecture in terms of power consumption and technology integration density.

  1. Simulation of a spiking neuron circuit using carbon nanotube transistors

    Energy Technology Data Exchange (ETDEWEB)

    Najari, Montassar, E-mail: malnjar@jazanu.edu.sa [Departement of Physics, Faculty of Sciences, University of Gabes, Gabes (Tunisia); IKCE unit, Jazan University, Jazan (Saudi Arabia); El-Grour, Tarek, E-mail: grour-tarek@hotmail.fr [Departement of Physics, Faculty of Sciences, University of Gabes, Gabes (Tunisia); Jelliti, Sami, E-mail: sjelliti@jazanu.edu.sa [IKCE unit, Jazan University, Jazan (Saudi Arabia); Hakami, Othman Mousa, E-mail: omhakami@jazanu.edu.sa [IKCE unit, Jazan University, Jazan (Saudi Arabia); Faculty of Sciences, Jazan University, Jazan (Saudi Arabia)

    2016-06-10

    Neuromorphic engineering is related to the existing analogies between the physical semiconductor VLSI (Very Large Scale Integration) and biophysics. Neuromorphic systems propose to reproduce the structure and function of biological neural systems for transferring their calculation capacity on silicon. Since the innovative research of Carver Mead, the neuromorphic engineering continues to emerge remarkable implementation of biological system. This work presents a simulation of an elementary neuron cell with a carbon nanotube transistor (CNTFET) based technology. The model of the cell neuron which was simulated is called integrate and fire (I&F) model firstly introduced by G. Indiveri in 2009. This circuit has been simulated with CNTFET technology using ADS environment to verify the neuromorphic activities in terms of membrane potential. This work has demonstrated the efficiency of this emergent device; i.e CNTFET on the design of such architecture in terms of power consumption and technology integration density.

  2. Phase-locking and bistability in neuronal networks with synaptic depression

    Science.gov (United States)

    Akcay, Zeynep; Huang, Xinxian; Nadim, Farzan; Bose, Amitabha

    2018-02-01

    We consider a recurrent network of two oscillatory neurons that are coupled with inhibitory synapses. We use the phase response curves of the neurons and the properties of short-term synaptic depression to define Poincaré maps for the activity of the network. The fixed points of these maps correspond to phase-locked modes of the network. Using these maps, we analyze the conditions that allow short-term synaptic depression to lead to the existence of bistable phase-locked, periodic solutions. We show that bistability arises when either the phase response curve of the neuron or the short-term depression profile changes steeply enough. The results apply to any Type I oscillator and we illustrate our findings using the Quadratic Integrate-and-Fire and Morris-Lecar neuron models.

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

    Science.gov (United States)

    Ostojic, Srdjan; Brunel, Nicolas

    2011-01-20

    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.

  4. Spiking Neural Networks with Unsupervised Learning Based on STDP Using Resistive Synaptic Devices and Analog CMOS Neuron Circuit.

    Science.gov (United States)

    Kwon, Min-Woo; Baek, Myung-Hyun; Hwang, Sungmin; Kim, Sungjun; Park, Byung-Gook

    2018-09-01

    We designed the CMOS analog integrate and fire (I&F) neuron circuit can drive resistive synaptic device. The neuron circuit consists of a current mirror for spatial integration, a capacitor for temporal integration, asymmetric negative and positive pulse generation part, a refractory part, and finally a back-propagation pulse generation part for learning of the synaptic devices. The resistive synaptic devices were fabricated using HfOx switching layer by atomic layer deposition (ALD). The resistive synaptic device had gradual set and reset characteristics and the conductance was adjusted by spike-timing-dependent-plasticity (STDP) learning rule. We carried out circuit simulation of synaptic device and CMOS neuron circuit. And we have developed an unsupervised spiking neural networks (SNNs) for 5 × 5 pattern recognition and classification using the neuron circuit and synaptic devices. The hardware-based SNNs can autonomously and efficiently control the weight updates of the synapses between neurons, without the aid of software calculations.

  5. Understanding the Generation of Network Bursts by Adaptive Oscillatory Neurons

    Directory of Open Access Journals (Sweden)

    Tanguy Fardet

    2018-02-01

    Full Text Available Experimental and numerical studies have revealed that isolated populations of oscillatory neurons can spontaneously synchronize and generate periodic bursts involving the whole network. Such a behavior has notably been observed for cultured neurons in rodent's cortex or hippocampus. We show here that a sufficient condition for this network bursting is the presence of an excitatory population of oscillatory neurons which displays spike-driven adaptation. We provide an analytic model to analyze network bursts generated by coupled adaptive exponential integrate-and-fire neurons. We show that, for strong synaptic coupling, intrinsically tonic spiking neurons evolve to reach a synchronized intermittent bursting state. The presence of inhibitory neurons or plastic synapses can then modulate this dynamics in many ways but is not necessary for its appearance. Thanks to a simple self-consistent equation, our model gives an intuitive and semi-quantitative tool to understand the bursting behavior. Furthermore, it suggests that after-hyperpolarization currents are sufficient to explain bursting termination. Through a thorough mapping between the theoretical parameters and ion-channel properties, we discuss the biological mechanisms that could be involved and the relevance of the explored parameter-space. Such an insight enables us to propose experimentally-testable predictions regarding how blocking fast, medium or slow after-hyperpolarization channels would affect the firing rate and burst duration, as well as the interburst interval.

  6. Evolution and Development of the Inner Ear Efferent System: Transforming a Motor Neuron Population to Connect to the Most Unusual Motor Protein via Ancient Nicotinic Receptors

    Directory of Open Access Journals (Sweden)

    Bernd Fritzsch

    2017-04-01

    Full Text Available All craniate chordates have inner ears with hair cells that receive input from the brain by cholinergic centrifugal fibers, the so-called inner ear efferents (IEEs. Comparative data suggest that IEEs derive from facial branchial motor (FBM neurons that project to the inner ear instead of facial muscles. Developmental data showed that IEEs develop adjacent to FBMs and segregation from IEEs might depend on few transcription factors uniquely associated with IEEs. Like other cholinergic terminals in the peripheral nervous system (PNS, efferent terminals signal on hair cells through nicotinic acetylcholine channels, likely composed out of alpha 9 and alpha 10 units (Chrna9, Chrna10. Consistent with the evolutionary ancestry of IEEs is the even more conserved ancestry of Chrna9 and 10. The evolutionary appearance of IEEs may reflect access of FBMs to a novel target, possibly related to displacement or loss of mesoderm-derived muscle fibers by the ectoderm-derived ear vesicle. Experimental transplantations mimicking this possible aspect of ear evolution showed that different motor neurons of the spinal cord or brainstem form cholinergic synapses on hair cells when ears replace somites or eyes. Transplantation provides experimental evidence in support of the evolutionary switch of FBM neurons to become IEEs. Mammals uniquely evolved a prestin related motor system to cause shape changes in outer hair cells regulated by the IEEs. In summary, an ancient motor neuron population drives in craniates via signaling through highly conserved Chrna receptors a uniquely derived cellular contractility system that is essential for hearing in mammals.

  7. Noise focusing and the emergence of coherent activity in neuronal cultures

    Science.gov (United States)

    Orlandi, Javier G.; Soriano, Jordi; Alvarez-Lacalle, Enrique; Teller, Sara; Casademunt, Jaume

    2013-09-01

    At early stages of development, neuronal cultures in vitro spontaneously reach a coherent state of collective firing in a pattern of nearly periodic global bursts. Although understanding the spontaneous activity of neuronal networks is of chief importance in neuroscience, the origin and nature of that pulsation has remained elusive. By combining high-resolution calcium imaging with modelling in silico, we show that this behaviour is controlled by the propagation of waves that nucleate randomly in a set of points that is specific to each culture and is selected by a non-trivial interplay between dynamics and topology. The phenomenon is explained by the noise focusing effect--a strong spatio-temporal localization of the noise dynamics that originates in the complex structure of avalanches of spontaneous activity. Results are relevant to neuronal tissues and to complex networks with integrate-and-fire dynamics and metric correlations, for instance, in rumour spreading on social networks.

  8. A neuronal network model with simplified tonotopicity for tinnitus generation and its relief by sound therapy.

    Science.gov (United States)

    Nagashino, Hirofumi; Kinouchi, Yohsuke; Danesh, Ali A; Pandya, Abhijit S

    2013-01-01

    Tinnitus is the perception of sound in the ears or in the head where no external source is present. Sound therapy is one of the most effective techniques for tinnitus treatment that have been proposed. In order to investigate mechanisms of tinnitus generation and the clinical effects of sound therapy, we have proposed conceptual and computational models with plasticity using a neural oscillator or a neuronal network model. In the present paper, we propose a neuronal network model with simplified tonotopicity of the auditory system as more detailed structure. In this model an integrate-and-fire neuron model is employed and homeostatic plasticity is incorporated. The computer simulation results show that the present model can show the generation of oscillation and its cessation by external input. It suggests that the present framework is promising as a modeling for the tinnitus generation and the effects of sound therapy.

  9. Increasing inhibitory input increases neuronal firing rate: why and when? Diffusion process cases

    Energy Technology Data Exchange (ETDEWEB)

    Feng Jianfeng [COGS, Sussex University (United Kingdom)]. E-mail: jf218@cam.ac.uk; Wei Gang [Department of Mathematics, Hong Kong Baptist University, Hong Kong (China)]. E-mail gwei@math.hkbu.edu.hk

    2001-09-21

    Increasing inhibitory input to single neuronal models, such as the FitzHugh-Nagumo model and the Hodgkin-Huxley model, can sometimes increase their firing rates, a phenomenon which we term inhibition-boosted firing (IBF). Here we consider neuronal models with diffusion approximation inputs, i.e. they share the identical first- and second-order statistics of the corresponding Poisson process inputs. Using the integrate-and-fire model and the IF-FHN model, we explore theoretically how and when IBF can happen. For both models, it is shown that there is a critical input frequency at which the efferent firing rate is identical when the neuron receives purely excitatory inputs or exactly balanced inhibitory and excitatory inputs. When the input frequency is lower than the critical frequency, IBF occurs. (author)

  10. 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.

  11. 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.

  12. 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.

  13. The Relevance of AgRP Neuron-Derived GABA Inputs to POMC Neurons Differs for Spontaneous and Evoked Release

    OpenAIRE

    Rau, Andrew R.; Hentges, Shane T.

    2017-01-01

    Hypothalamic agouti-related peptide (AgRP) neurons potently stimulate food intake, whereas proopiomelanocortin (POMC) neurons inhibit feeding. Whether AgRP neurons exert their orexigenic actions, at least in part, by inhibiting anorexigenic POMC neurons remains unclear. Here, the connectivity between GABA-releasing AgRP neurons and POMC neurons was examined in brain slices from male and female mice. GABA-mediated spontaneous IPSCs (sIPSCs) in POMC neurons were unaffected by disturbing GABA re...

  14. Firing dynamics of an autaptic neuron

    International Nuclear Information System (INIS)

    Wang Heng-Tong; Chen Yong

    2015-01-01

    Autapses are synapses that connect a neuron to itself in the nervous system. Previously, both experimental and theoretical studies have demonstrated that autaptic connections in the nervous system have a significant physiological function. Autapses in nature provide self-delayed feedback, thus introducing an additional timescale to neuronal activities and causing many dynamic behaviors in neurons. Recently, theoretical studies have revealed that an autapse provides a control option for adjusting the response of a neuron: e.g., an autaptic connection can cause the electrical activities of the Hindmarsh–Rose neuron to switch between quiescent, periodic, and chaotic firing patterns; an autapse can enhance or suppress the mode-locking status of a neuron injected with sinusoidal current; and the firing frequency and interspike interval distributions of the response spike train can also be modified by the autapse. In this paper, we review recent studies that showed how an autapse affects the response of a single neuron. (topical review)

  15. Neuronal synchrony: peculiarity and generality.

    Science.gov (United States)

    Nowotny, Thomas; Huerta, Ramon; Rabinovich, Mikhail I

    2008-09-01

    Synchronization in neuronal systems is a new and intriguing application of dynamical systems theory. Why are neuronal systems different as a subject for synchronization? (1) Neurons in themselves are multidimensional nonlinear systems that are able to exhibit a wide variety of different activity patterns. Their "dynamical repertoire" includes regular or chaotic spiking, regular or chaotic bursting, multistability, and complex transient regimes. (2) Usually, neuronal oscillations are the result of the cooperative activity of many synaptically connected neurons (a neuronal circuit). Thus, it is necessary to consider synchronization between different neuronal circuits as well. (3) The synapses that implement the coupling between neurons are also dynamical elements and their intrinsic dynamics influences the process of synchronization or entrainment significantly. In this review we will focus on four new problems: (i) the synchronization in minimal neuronal networks with plastic synapses (synchronization with activity dependent coupling), (ii) synchronization of bursts that are generated by a group of nonsymmetrically coupled inhibitory neurons (heteroclinic synchronization), (iii) the coordination of activities of two coupled neuronal networks (partial synchronization of small composite structures), and (iv) coarse grained synchronization in larger systems (synchronization on a mesoscopic scale). (c) 2008 American Institute of Physics.

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

    Science.gov (United States)

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

    2015-02-01

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

  17. Finite post synaptic potentials cause a fast neuronal response

    Directory of Open Access Journals (Sweden)

    Moritz eHelias

    2011-02-01

    Full Text Available A generic property of the communication between neurons is the exchange of pulsesat discrete time points, the action potentials. However, the prevalenttheory of spiking neuronal networks of integrate-and-fire model neuronsrelies on two assumptions: the superposition of many afferent synapticimpulses is approximated by Gaussian white noise, equivalent to avanishing magnitude of the synaptic impulses, and the transfer oftime varying signals by neurons is assessable by linearization. Goingbeyond both approximations, we find that in the presence of synapticimpulses the response to transient inputs differs qualitatively fromprevious predictions. It is instantaneous rather than exhibiting low-passcharacteristics, depends non-linearly on the amplitude of the impulse,is asymmetric for excitation and inhibition and is promoted by a characteristiclevel of synaptic background noise. These findings resolve contradictionsbetween the earlier theory and experimental observations. Here wereview the recent theoretical progress that enabled these insights.We explain why the membrane potential near threshold is sensitiveto properties of the afferent noise and show how this shapes the neuralresponse. A further extension of the theory to time evolution in discretesteps quantifies simulation artifacts and yields improved methodsto cross check results.

  18. 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.

  19. High-Degree Neurons Feed Cortical Computations.

    Directory of Open Access Journals (Sweden)

    Nicholas M Timme

    2016-05-01

    Full Text Available Recent work has shown that functional connectivity among cortical neurons is highly varied, with a small percentage of neurons having many more connections than others. Also, recent theoretical developments now make it possible to quantify how neurons modify information from the connections they receive. Therefore, it is now possible to investigate how information modification, or computation, depends on the number of connections a neuron receives (in-degree or sends out (out-degree. To do this, we recorded the simultaneous spiking activity of hundreds of neurons in cortico-hippocampal slice cultures using a high-density 512-electrode array. This preparation and recording method combination produced large numbers of neurons recorded at temporal and spatial resolutions that are not currently available in any in vivo recording system. We utilized transfer entropy (a well-established method for detecting linear and nonlinear interactions in time series and the partial information decomposition (a powerful, recently developed tool for dissecting multivariate information processing into distinct parts to quantify computation between neurons where information flows converged. We found that computations did not occur equally in all neurons throughout the networks. Surprisingly, neurons that computed large amounts of information tended to receive connections from high out-degree neurons. However, the in-degree of a neuron was not related to the amount of information it computed. To gain insight into these findings, we developed a simple feedforward network model. We found that a degree-modified Hebbian wiring rule best reproduced the pattern of computation and degree correlation results seen in the real data. Interestingly, this rule also maximized signal propagation in the presence of network-wide correlations, suggesting a mechanism by which cortex could deal with common random background input. These are the first results to show that the extent to

  20. Handbook of Brain Connectivity

    CERN Document Server

    Jirsa, Viktor K

    2007-01-01

    Our contemporary understanding of brain function is deeply rooted in the ideas of the nonlinear dynamics of distributed networks. Cognition and motor coordination seem to arise from the interactions of local neuronal networks, which themselves are connected in large scales across the entire brain. The spatial architectures between various scales inevitably influence the dynamics of the brain and thereby its function. But how can we integrate brain connectivity amongst these structural and functional domains? Our Handbook provides an account of the current knowledge on the measurement, analysis and theory of the anatomical and functional connectivity of the brain. All contributors are leading experts in various fields concerning structural and functional brain connectivity. In the first part of the Handbook, the chapters focus on an introduction and discussion of the principles underlying connected neural systems. The second part introduces the currently available non-invasive technologies for measuring struct...

  1. Modeling Structural Brain Connectivity

    DEFF Research Database (Denmark)

    Ambrosen, Karen Marie Sandø

    The human brain consists of a gigantic complex network of interconnected neurons. Together all these connections determine who we are, how we react and how we interpret the world. Knowledge about how the brain is connected can further our understanding of the brain’s structural organization, help...... improve diagnosis, and potentially allow better treatment of a wide range of neurological disorders. Tractography based on diffusion magnetic resonance imaging is a unique tool to estimate this “structural connectivity” of the brain non-invasively and in vivo. During the last decade, brain connectivity...... has increasingly been analyzed using graph theoretic measures adopted from network science and this characterization of the brain’s structural connectivity has been shown to be useful for the classification of populations, such as healthy and diseased subjects. The structural connectivity of the brain...

  2. Synaptic Circuit Organization of Motor Corticothalamic Neurons

    Science.gov (United States)

    Yamawaki, Naoki

    2015-01-01

    Corticothalamic (CT) neurons in layer 6 constitute a large but enigmatic class of cortical projection neurons. How they are integrated into intracortical and thalamo-cortico-thalamic circuits is incompletely understood, especially outside of sensory cortex. Here, we investigated CT circuits in mouse forelimb motor cortex (M1) using multiple circuit-analysis methods. Stimulating and recording from CT, intratelencephalic (IT), and pyramidal tract (PT) projection neurons, we found strong CT↔ CT and CT↔ IT connections; however, CT→IT connections were limited to IT neurons in layer 6, not 5B. There was strikingly little CT↔ PT excitatory connectivity. Disynaptic inhibition systematically accompanied excitation in these pathways, scaling with the amplitude of excitation according to both presynaptic (class-specific) and postsynaptic (cell-by-cell) factors. In particular, CT neurons evoked proportionally more inhibition relative to excitation (I/E ratio) than IT neurons. Furthermore, the amplitude of inhibition was tuned to match the amount of excitation at the level of individual neurons; in the extreme, neurons receiving no excitation received no inhibition either. Extending these studies to dissect the connectivity between cortex and thalamus, we found that M1-CT neurons and thalamocortical neurons in the ventrolateral (VL) nucleus were remarkably unconnected in either direction. Instead, VL axons in the cortex excited both IT and PT neurons, and CT axons in the thalamus excited other thalamic neurons, including those in the posterior nucleus, which additionally received PT excitation. These findings, which contrast in several ways with previous observations in sensory areas, illuminate the basic circuit organization of CT neurons within M1 and between M1 and thalamus. PMID:25653383

  3. Representation of dynamical stimuli in populations of threshold neurons.

    Directory of Open Access Journals (Sweden)

    Tatjana Tchumatchenko

    2011-10-01

    Full Text Available Many sensory or cognitive events are associated with dynamic current modulations in cortical neurons. This raises an urgent demand for tractable model approaches addressing the merits and limits of potential encoding strategies. Yet, current theoretical approaches addressing the response to mean- and variance-encoded stimuli rarely provide complete response functions for both modes of encoding in the presence of correlated noise. Here, we investigate the neuronal population response to dynamical modifications of the mean or variance of the synaptic bombardment using an alternative threshold model framework. In the variance and mean channel, we provide explicit expressions for the linear and non-linear frequency response functions in the presence of correlated noise and use them to derive population rate response to step-like stimuli. For mean-encoded signals, we find that the complete response function depends only on the temporal width of the input correlation function, but not on other functional specifics. Furthermore, we show that both mean- and variance-encoded signals can relay high-frequency inputs, and in both schemes step-like changes can be detected instantaneously. Finally, we obtain the pairwise spike correlation function and the spike triggered average from the linear mean-evoked response function. These results provide a maximally tractable limiting case that complements and extends previous results obtained in the integrate and fire framework.

  4. Motor Neurons

    DEFF Research Database (Denmark)

    Hounsgaard, Jorn

    2017-01-01

    Motor neurons translate synaptic input from widely distributed premotor networks into patterns of action potentials that orchestrate motor unit force and motor behavior. Intercalated between the CNS and muscles, motor neurons add to and adjust the final motor command. The identity and functional...... in in vitro preparations is far from complete. Nevertheless, a foundation has been provided for pursuing functional significance of intrinsic response properties in motoneurons in vivo during motor behavior at levels from molecules to systems....

  5. The chronotron: a neuron that learns to fire temporally precise spike patterns.

    Directory of Open Access Journals (Sweden)

    Răzvan V Florian

    Full Text Available In many cases, neurons process information carried by the precise timings of spikes. Here we show how neurons can learn to generate specific temporally precise output spikes in response to input patterns of spikes having precise timings, thus processing and memorizing information that is entirely temporally coded, both as input and as output. We introduce two new supervised learning rules for spiking neurons with temporal coding of information (chronotrons, one that provides high memory capacity (E-learning, and one that has a higher biological plausibility (I-learning. With I-learning, the neuron learns to fire the target spike trains through synaptic changes that are proportional to the synaptic currents at the timings of real and target output spikes. We study these learning rules in computer simulations where we train integrate-and-fire neurons. Both learning rules allow neurons to fire at the desired timings, with sub-millisecond precision. We show how chronotrons can learn to classify their inputs, by firing identical, temporally precise spike trains for different inputs belonging to the same class. When the input is noisy, the classification also leads to noise reduction. We compute lower bounds for the memory capacity of chronotrons and explore the influence of various parameters on chronotrons' performance. The chronotrons can model neurons that encode information in the time of the first spike relative to the onset of salient stimuli or neurons in oscillatory networks that encode information in the phases of spikes relative to the background oscillation. Our results show that firing one spike per cycle optimizes memory capacity in neurons encoding information in the phase of firing relative to a background rhythm.

  6. A chimeric path to neuronal synchronization

    Science.gov (United States)

    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).

  7. 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)

  8. 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)

  9. A network of spiking neurons for computing sparse representations in an energy-efficient way.

    Science.gov (United States)

    Hu, Tao; Genkin, Alexander; Chklovskii, Dmitri B

    2012-11-01

    Computing sparse redundant representations is an important problem in both applied mathematics and neuroscience. In many applications, this problem must be solved in an energy-efficient way. Here, we propose a hybrid distributed algorithm (HDA), which solves this problem on a network of simple nodes communicating by low-bandwidth channels. HDA nodes perform both gradient-descent-like steps on analog internal variables and coordinate-descent-like steps via quantized external variables communicated to each other. Interestingly, the operation is equivalent to a network of integrate-and-fire neurons, suggesting that HDA may serve as a model of neural computation. We show that the numerical performance of HDA is on par with existing algorithms. In the asymptotic regime, the representation error of HDA decays with time, t, as 1/t. HDA is stable against time-varying noise; specifically, the representation error decays as 1/√t for gaussian white noise.

  10. Design of memristive interface between electronic neurons

    Science.gov (United States)

    Gerasimova, S. A.; Mikhaylov, A. N.; Belov, A. I.; Korolev, D. S.; Guseinov, D. V.; Lebedeva, A. V.; Gorshkov, O. N.; Kazantsev, V. B.

    2018-05-01

    Nonlinear dynamics of two electronic oscillators coupled via a memristive device has been investigated. Such model mimics the interaction between synaptically coupled brain neurons with the memristive device imitating neuron axon. The synaptic connection is provided by the adaptive behavior of memristive device that changes its resistance under the action of spike-like activity. Mathematical model of such a memristive interface has been developed to describe and predict the experimentally observed regularities of forced synchronization of neuron-like oscillators.

  11. Constructing Precisely Computing Networks with Biophysical Spiking Neurons.

    Science.gov (United States)

    Schwemmer, Michael A; Fairhall, Adrienne L; Denéve, Sophie; Shea-Brown, Eric T

    2015-07-15

    While spike timing has been shown to carry detailed stimulus information at the sensory periphery, its possible role in network computation is less clear. Most models of computation by neural networks are based on population firing rates. In equivalent spiking implementations, firing is assumed to be random such that averaging across populations of neurons recovers the rate-based approach. Recently, however, Denéve and colleagues have suggested that the spiking behavior of neurons may be fundamental to how neuronal networks compute, with precise spike timing determined by each neuron's contribution to producing the desired output (Boerlin and Denéve, 2011; Boerlin et al., 2013). By postulating that each neuron fires to reduce the error in the network's output, it was demonstrated that linear computations can be performed by networks of integrate-and-fire neurons that communicate through instantaneous synapses. This left open, however, the possibility that realistic networks, with conductance-based neurons with subthreshold nonlinearity and the slower timescales of biophysical synapses, may not fit into this framework. Here, we show how the spike-based approach can be extended to biophysically plausible networks. We then show that our network reproduces a number of key features of cortical networks including irregular and Poisson-like spike times and a tight balance between excitation and inhibition. Lastly, we discuss how the behavior of our model scales with network size or with the number of neurons "recorded" from a larger computing network. These results significantly increase the biological plausibility of the spike-based approach to network computation. We derive a network of neurons with standard spike-generating currents and synapses with realistic timescales that computes based upon the principle that the precise timing of each spike is important for the computation. We then show that our network reproduces a number of key features of cortical networks

  12. Autapse-induced synchronization in a coupled neuronal network

    International Nuclear Information System (INIS)

    Ma, Jun; Song, Xinlin; Jin, Wuyin; Wang, Chuni

    2015-01-01

    Highlights: • The functional effect of autapse on neuronal activity is detected. • Autapse driving plays active role in regulating electrical activities as pacemaker. • It confirms biological experimental results for rhythm synchronization between heterogeneous cells. - Abstract: The effect of autapse on coupled neuronal network is detected. In our studies, three identical neurons are connected with ring type and autapse connected to one neuron of the network. The autapse connected to neuron can impose time-delayed feedback in close loop on the neuron thus the dynamics of membrane potentials can be changed. Firstly, the effect of autapse driving on single neuron is confirmed that negative feedback can calm down the neuronal activity while positive feedback can excite the neuronal activity. Secondly, the collective electrical behaviors of neurons are regulated by a pacemaker, which associated with the autapse forcing. By using appropriate gain and time delay in the autapse, the neurons can reach synchronization and the membrane potentials of all neurons can oscillate with the same rhythm under mutual coupling. It indicates that autapse forcing plays an important role in changing the collective electric activities of neuronal network, and appropriate electric modes can be selected due to the switch of feedback type(positive or negative) in autapse. And the autapse-induced synchronization in network is also consistent with some biological experiments about synchronization between nonidentical neurons.

  13. Self-organized criticality occurs in non-conservative neuronal networks during `up' states

    Science.gov (United States)

    Millman, Daniel; Mihalas, Stefan; Kirkwood, Alfredo; Niebur, Ernst

    2010-10-01

    During sleep, under anaesthesia and in vitro, cortical neurons in sensory, motor, association and executive areas fluctuate between so-called up and down states, which are characterized by distinct membrane potentials and spike rates. Another phenomenon observed in preparations similar to those that exhibit up and down states-such as anaesthetized rats, brain slices and cultures devoid of sensory input, as well as awake monkey cortex-is self-organized criticality (SOC). SOC is characterized by activity `avalanches' with a branching parameter near unity and size distribution that obeys a power law with a critical exponent of about -3/2. Recent work has demonstrated SOC in conservative neuronal network models, but critical behaviour breaks down when biologically realistic `leaky' neurons are introduced. Here, we report robust SOC behaviour in networks of non-conservative leaky integrate-and-fire neurons with short-term synaptic depression. We show analytically and numerically that these networks typically have two stable activity levels, corresponding to up and down states, that the networks switch spontaneously between these states and that up states are critical and down states are subcritical.

  14. [Mirror neurons].

    Science.gov (United States)

    Rubia Vila, Francisco José

    2011-01-01

    Mirror neurons were recently discovered in frontal brain areas of the monkey. They are activated when the animal makes a specific movement, but also when the animal observes the same movement in another animal. Some of them also respond to the emotional expression of other animals of the same species. These mirror neurons have also been found in humans. They respond to or "reflect" actions of other individuals in the brain and are thought to represent the basis for imitation and empathy and hence the neurobiological substrate for "theory of mind", the potential origin of language and the so-called moral instinct.

  15. The Relevance of AgRP Neuron-Derived GABA Inputs to POMC Neurons Differs for Spontaneous and Evoked Release.

    Science.gov (United States)

    Rau, Andrew R; Hentges, Shane T

    2017-08-02

    Hypothalamic agouti-related peptide (AgRP) neurons potently stimulate food intake, whereas proopiomelanocortin (POMC) neurons inhibit feeding. Whether AgRP neurons exert their orexigenic actions, at least in part, by inhibiting anorexigenic POMC neurons remains unclear. Here, the connectivity between GABA-releasing AgRP neurons and POMC neurons was examined in brain slices from male and female mice. GABA-mediated spontaneous IPSCs (sIPSCs) in POMC neurons were unaffected by disturbing GABA release from AgRP neurons either by cell type-specific deletion of the vesicular GABA transporter or by expression of botulinum toxin in AgRP neurons to prevent vesicle-associated membrane protein 2-dependent vesicle fusion. Additionally, there was no difference in the ability of μ-opioid receptor (MOR) agonists to inhibit sIPSCs in POMC neurons when MORs were deleted from AgRP neurons, and activation of the inhibitory designer receptor hM4Di on AgRP neurons did not affect sIPSCs recorded from POMC neurons. These approaches collectively indicate that AgRP neurons do not significantly contribute to the strong spontaneous GABA input to POMC neurons. Despite these observations, optogenetic stimulation of AgRP neurons reliably produced evoked IPSCs in POMC neurons, leading to the inhibition of POMC neuron firing. Thus, AgRP neurons can potently affect POMC neuron function without contributing a significant source of spontaneous GABA input to POMC neurons. Together, these results indicate that the relevance of GABAergic inputs from AgRP to POMC neurons is state dependent and highlight the need to consider different types of transmitter release in circuit mapping and physiologic regulation. SIGNIFICANCE STATEMENT Agouti-related peptide (AgRP) neurons play an important role in driving food intake, while proopiomelanocortin (POMC) neurons inhibit feeding. Despite the importance of these two well characterized neuron types in maintaining metabolic homeostasis, communication between these

  16. Developmental time windows for axon growth influence neuronal network topology.

    Science.gov (United States)

    Lim, Sol; Kaiser, Marcus

    2015-04-01

    Early brain connectivity development consists of multiple stages: birth of neurons, their migration and the subsequent growth of axons and dendrites. Each stage occurs within a certain period of time depending on types of neurons and cortical layers. Forming synapses between neurons either by growing axons starting at similar times for all neurons (much-overlapped time windows) or at different time points (less-overlapped) may affect the topological and spatial properties of neuronal networks. Here, we explore the extreme cases of axon formation during early development, either starting at the same time for all neurons (parallel, i.e., maximally overlapped time windows) or occurring for each neuron separately one neuron after another (serial, i.e., no overlaps in time windows). For both cases, the number of potential and established synapses remained comparable. Topological and spatial properties, however, differed: Neurons that started axon growth early on in serial growth achieved higher out-degrees, higher local efficiency and longer axon lengths while neurons demonstrated more homogeneous connectivity patterns for parallel growth. Second, connection probability decreased more rapidly with distance between neurons for parallel growth than for serial growth. Third, bidirectional connections were more numerous for parallel growth. Finally, we tested our predictions with C. elegans data. Together, this indicates that time windows for axon growth influence the topological and spatial properties of neuronal networks opening up the possibility to a posteriori estimate developmental mechanisms based on network properties of a developed network.

  17. The origin and function of mirror neurons: the missing link.

    Science.gov (United States)

    Lingnau, Angelika; Caramazza, Alfonso

    2014-04-01

    We argue, by analogy to the neural organization of the object recognition system, that demonstration of modulation of mirror neurons by associative learning does not imply absence of genetic adaptation. Innate connectivity defines the types of processes mirror neurons can participate in while allowing for extensive local plasticity. However, the proper function of these neurons remains to be worked out.

  18. A latent low-dimensional common input drives a pool of motor neurons: a probabilistic latent state-space model.

    Science.gov (United States)

    Feeney, Daniel F; Meyer, François G; Noone, Nicholas; Enoka, Roger M

    2017-10-01

    Motor neurons appear to be activated with a common input signal that modulates the discharge activity of all neurons in the motor nucleus. It has proven difficult for neurophysiologists to quantify the variability in a common input signal, but characterization of such a signal may improve our understanding of how the activation signal varies across motor tasks. Contemporary methods of quantifying the common input to motor neurons rely on compiling discrete action potentials into continuous time series, assuming the motor pool acts as a linear filter, and requiring signals to be of sufficient duration for frequency analysis. We introduce a space-state model in which the discharge activity of motor neurons is modeled as inhomogeneous Poisson processes and propose a method to quantify an abstract latent trajectory that represents the common input received by motor neurons. The approach also approximates the variation in synaptic noise in the common input signal. The model is validated with four data sets: a simulation of 120 motor units, a pair of integrate-and-fire neurons with a Renshaw cell providing inhibitory feedback, the discharge activity of 10 integrate-and-fire neurons, and the discharge times of concurrently active motor units during an isometric voluntary contraction. The simulations revealed that a latent state-space model is able to quantify the trajectory and variability of the common input signal across all four conditions. When compared with the cumulative spike train method of characterizing common input, the state-space approach was more sensitive to the details of the common input current and was less influenced by the duration of the signal. The state-space approach appears to be capable of detecting rather modest changes in common input signals across conditions. NEW & NOTEWORTHY We propose a state-space model that explicitly delineates a common input signal sent to motor neurons and the physiological noise inherent in synaptic signal

  19. Synchronization from second order network connectivity statistics

    Directory of Open Access Journals (Sweden)

    Liqiong eZhao

    2011-07-01

    Full Text Available We investigate how network structure can influence the tendency for a neuronal network to synchronize, or its synchronizability, independent of the dynamical model for each neuron. The synchrony analysis takes advantage of the framework of second order networks (SONETs, which defines four second order connectivity statistics based on the relative frequency of two-connection network motifs. The analysis identifies two of these statistics, convergent connections and chain connections, as highly influencing the synchrony. Simulations verify that synchrony decreases with the frequency of convergent connections and increases with the frequency of chain connections. These trends persist with simulations of multiple models for the neuron dynamics and for different types of networks. Surprisingly, divergent connections, which determine the fraction of shared inputs, do not strongly influence the synchrony. The critical role of chains, rather than divergent connections, in influencing synchrony can be explained by a pool and redistribute mechanism. The pooling of many inputs averages out independent fluctuations, amplifying weak correlations in the inputs. With increased chain connections, neurons with many inputs tend to have many outputs. Hence, chains ensure that the amplified correlations in the neurons with many inputs are redistributed throughout the network, enhancing the development of synchrony across the network.

  20. Response variability in balanced cortical networks

    DEFF Research Database (Denmark)

    Lerchner, Alexander; Ursta, C.; Hertz, J.

    2006-01-01

    We study the spike statistics of neurons in a network with dynamically balanced excitation and inhibition. Our model, intended to represent a generic cortical column, comprises randomly connected excitatory and inhibitory leaky integrate-and-fire neurons, driven by excitatory input from an external...

  1. Mirror neurons and language in schizophrenia

    OpenAIRE

    Bendová, Marie

    2016-01-01

    Mirror neurons are a specific kind of visuomotor neurons that are involved in action execution and also in action perception. The mirror mechanism is linked to a variety of complex psychological functions such as social-cognitive functions and language. People with schizophrenia have often difficulties both in mirror neuron system and in language skills. In the first part of our research we studied the connectivity of mirror neuron areas (such as IFG, STG, PMC, SMC and so on) by fMRI in resti...

  2. Species-Specific Mechanisms of Neuron Subtype Specification Reveal Evolutionary Plasticity of Amniote Brain Development

    Directory of Open Access Journals (Sweden)

    Tadashi Nomura

    2018-03-01

    Full Text Available Summary: Highly ordered brain architectures in vertebrates consist of multiple neuron subtypes with specific neuronal connections. However, the origin of and evolutionary changes in neuron specification mechanisms remain unclear. Here, we report that regulatory mechanisms of neuron subtype specification are divergent in developing amniote brains. In the mammalian neocortex, the transcription factors (TFs Ctip2 and Satb2 are differentially expressed in layer-specific neurons. In contrast, these TFs are co-localized in reptilian and avian dorsal pallial neurons. Multi-potential progenitors that produce distinct neuronal subtypes commonly exist in the reptilian and avian dorsal pallium, whereas a cis-regulatory element of avian Ctip2 exhibits attenuated transcription suppressive activity. Furthermore, the neuronal subtypes distinguished by these TFs are not tightly associated with conserved neuronal connections among amniotes. Our findings reveal the evolutionary plasticity of regulatory gene functions that contribute to species differences in neuronal heterogeneity and connectivity in developing amniote brains. : Neuronal heterogeneity is essential for assembling intricate neuronal circuits. Nomura et al. find that species-specific transcriptional mechanisms underlie diversities of excitatory neuron subtypes in mammalian and non-mammalian brains. Species differences in neuronal subtypes and connections suggest functional plasticity of regulatory genes for neuronal specification during amniote brain evolution. Keywords: Ctip2, Satb2, multi-potential progenitors, transcriptional regulation, neuronal connectivity

  3. Nonrandom network connectivity comes in pairs

    Directory of Open Access Journals (Sweden)

    Felix Z. Hoffmann

    2017-02-01

    Full Text Available Overrepresentation of bidirectional connections in local cortical networks has been repeatedly reported and is a focus of the ongoing discussion of nonrandom connectivity. Here we show in a brief mathematical analysis that in a network in which connection probabilities are symmetric in pairs, Pij = Pji, the occurrences of bidirectional connections and nonrandom structures are inherently linked; an overabundance of reciprocally connected pairs emerges necessarily when some pairs of neurons are more likely to be connected than others. Our numerical results imply that such overrepresentation can also be sustained when connection probabilities are only approximately symmetric.

  4. Neuronal replacement therapy: previous achievements and challenges ahead

    Science.gov (United States)

    Grade, Sofia; Götz, Magdalena

    2017-10-01

    Lifelong neurogenesis and incorporation of newborn neurons into mature neuronal circuits operates in specialized niches of the mammalian brain and serves as role model for neuronal replacement strategies. However, to which extent can the remaining brain parenchyma, which never incorporates new neurons during the adulthood, be as plastic and readily accommodate neurons in networks that suffered neuronal loss due to injury or neurological disease? Which microenvironment is permissive for neuronal replacement and synaptic integration and which cells perform best? Can lost function be restored and how adequate is the participation in the pre-existing circuitry? Could aberrant connections cause malfunction especially in networks dominated by excitatory neurons, such as the cerebral cortex? These questions show how important connectivity and circuitry aspects are for regenerative medicine, which is the focus of this review. We will discuss the impressive advances in neuronal replacement strategies and success from exogenous as well as endogenous cell sources. Both have seen key novel technologies, like the groundbreaking discovery of induced pluripotent stem cells and direct neuronal reprogramming, offering alternatives to the transplantation of fetal neurons, and both herald great expectations. For these to become reality, neuronal circuitry analysis is key now. As our understanding of neuronal circuits increases, neuronal replacement therapy should fulfill those prerequisites in network structure and function, in brain-wide input and output. Now is the time to incorporate neural circuitry research into regenerative medicine if we ever want to truly repair brain injury.

  5. Identification of neuronal network properties from the spectral analysis of calcium imaging signals in neuronal cultures.

    Science.gov (United States)

    Tibau, Elisenda; Valencia, Miguel; Soriano, Jordi

    2013-01-01

    Neuronal networks in vitro are prominent systems to study the development of connections in living neuronal networks and the interplay between connectivity, activity and function. These cultured networks show a rich spontaneous activity that evolves concurrently with the connectivity of the underlying network. In this work we monitor the development of neuronal cultures, and record their activity using calcium fluorescence imaging. We use spectral analysis to characterize global dynamical and structural traits of the neuronal cultures. We first observe that the power spectrum can be used as a signature of the state of the network, for instance when inhibition is active or silent, as well as a measure of the network's connectivity strength. Second, the power spectrum identifies prominent developmental changes in the network such as GABAA switch. And third, the analysis of the spatial distribution of the spectral density, in experiments with a controlled disintegration of the network through CNQX, an AMPA-glutamate receptor antagonist in excitatory neurons, reveals the existence of communities of strongly connected, highly active neurons that display synchronous oscillations. Our work illustrates the interest of spectral analysis for the study of in vitro networks, and its potential use as a network-state indicator, for instance to compare healthy and diseased neuronal networks.

  6. Npas4: Linking Neuronal Activity to Memory.

    Science.gov (United States)

    Sun, Xiaochen; Lin, Yingxi

    2016-04-01

    Immediate-early genes (IEGs) are rapidly activated after sensory and behavioral experience and are believed to be crucial for converting experience into long-term memory. Neuronal PAS domain protein 4 (Npas4), a recently discovered IEG, has several characteristics that make it likely to be a particularly important molecular link between neuronal activity and memory: it is among the most rapidly induced IEGs, is expressed only in neurons, and is selectively induced by neuronal activity. By orchestrating distinct activity-dependent gene programs in different neuronal populations, Npas4 affects synaptic connections in excitatory and inhibitory neurons, neural circuit plasticity, and memory formation. It may also be involved in circuit homeostasis through negative feedback and psychiatric disorders. We summarize these findings and discuss their implications. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. Cerebellar Nuclear Neurons Use Time and Rate Coding to Transmit Purkinje Neuron Pauses.

    Science.gov (United States)

    Sudhakar, Shyam Kumar; Torben-Nielsen, Benjamin; De Schutter, Erik

    2015-12-01

    Neurons of the cerebellar nuclei convey the final output of the cerebellum to their targets in various parts of the brain. Within the cerebellum their direct upstream connections originate from inhibitory Purkinje neurons. Purkinje neurons have a complex firing pattern of regular spikes interrupted by intermittent pauses of variable length. How can the cerebellar nucleus process this complex input pattern? In this modeling study, we investigate different forms of Purkinje neuron simple spike pause synchrony and its influence on candidate coding strategies in the cerebellar nuclei. That is, we investigate how different alignments of synchronous pauses in synthetic Purkinje neuron spike trains affect either time-locking or rate-changes in the downstream nuclei. We find that Purkinje neuron synchrony is mainly represented by changes in the firing rate of cerebellar nuclei neurons. Pause beginning synchronization produced a unique effect on nuclei neuron firing, while the effect of pause ending and pause overlapping synchronization could not be distinguished from each other. Pause beginning synchronization produced better time-locking of nuclear neurons for short length pauses. We also characterize the effect of pause length and spike jitter on the nuclear neuron firing. Additionally, we find that the rate of rebound responses in nuclear neurons after a synchronous pause is controlled by the firing rate of Purkinje neurons preceding it.

  8. Cerebellar Nuclear Neurons Use Time and Rate Coding to Transmit Purkinje Neuron Pauses

    Science.gov (United States)

    Sudhakar, Shyam Kumar; Torben-Nielsen, Benjamin; De Schutter, Erik

    2015-01-01

    Neurons of the cerebellar nuclei convey the final output of the cerebellum to their targets in various parts of the brain. Within the cerebellum their direct upstream connections originate from inhibitory Purkinje neurons. Purkinje neurons have a complex firing pattern of regular spikes interrupted by intermittent pauses of variable length. How can the cerebellar nucleus process this complex input pattern? In this modeling study, we investigate different forms of Purkinje neuron simple spike pause synchrony and its influence on candidate coding strategies in the cerebellar nuclei. That is, we investigate how different alignments of synchronous pauses in synthetic Purkinje neuron spike trains affect either time-locking or rate-changes in the downstream nuclei. We find that Purkinje neuron synchrony is mainly represented by changes in the firing rate of cerebellar nuclei neurons. Pause beginning synchronization produced a unique effect on nuclei neuron firing, while the effect of pause ending and pause overlapping synchronization could not be distinguished from each other. Pause beginning synchronization produced better time-locking of nuclear neurons for short length pauses. We also characterize the effect of pause length and spike jitter on the nuclear neuron firing. Additionally, we find that the rate of rebound responses in nuclear neurons after a synchronous pause is controlled by the firing rate of Purkinje neurons preceding it. PMID:26630202

  9. Chimera patterns in two-dimensional networks of coupled neurons

    Science.gov (United States)

    Schmidt, Alexander; Kasimatis, Theodoros; Hizanidis, Johanne; Provata, Astero; Hövel, Philipp

    2017-03-01

    We discuss synchronization patterns in networks of FitzHugh-Nagumo and leaky integrate-and-fire oscillators coupled in a two-dimensional toroidal geometry. A common feature between the two models is the presence of fast and slow dynamics, a typical characteristic of neurons. Earlier studies have demonstrated that both models when coupled nonlocally in one-dimensional ring networks produce chimera states for a large range of parameter values. In this study, we give evidence of a plethora of two-dimensional chimera patterns of various shapes, including spots, rings, stripes, and grids, observed in both models, as well as additional patterns found mainly in the FitzHugh-Nagumo system. Both systems exhibit multistability: For the same parameter values, different initial conditions give rise to different dynamical states. Transitions occur between various patterns when the parameters (coupling range, coupling strength, refractory period, and coupling phase) are varied. Many patterns observed in the two models follow similar rules. For example, the diameter of the rings grows linearly with the coupling radius.

  10. Neuronal spike-train responses in the presence of threshold noise.

    Science.gov (United States)

    Coombes, S; Thul, R; Laudanski, J; Palmer, A R; Sumner, C J

    2011-03-01

    The variability of neuronal firing has been an intense topic of study for many years. From a modelling perspective it has often been studied in conductance based spiking models with the use of additive or multiplicative noise terms to represent channel fluctuations or the stochastic nature of neurotransmitter release. Here we propose an alternative approach using a simple leaky integrate-and-fire model with a noisy threshold. Initially, we develop a mathematical treatment of the neuronal response to periodic forcing using tools from linear response theory and use this to highlight how a noisy threshold can enhance downstream signal reconstruction. We further develop a more general framework for understanding the responses to large amplitude forcing based on a calculation of first passage times. This is ideally suited to understanding stochastic mode-locking, for which we numerically determine the Arnol'd tongue structure. An examination of data from regularly firing stellate neurons within the ventral cochlear nucleus, responding to sinusoidally amplitude modulated pure tones, shows tongue structures consistent with these predictions and highlights that stochastic, as opposed to deterministic, mode-locking is utilised at the level of the single stellate cell to faithfully encode periodic stimuli.

  11. Three-dimensional chimera patterns in networks of spiking neuron oscillators

    Science.gov (United States)

    Kasimatis, T.; Hizanidis, J.; Provata, A.

    2018-05-01

    We study the stable spatiotemporal patterns that arise in a three-dimensional (3D) network of neuron oscillators, whose dynamics is described by the leaky integrate-and-fire (LIF) model. More specifically, we investigate the form of the chimera states induced by a 3D coupling matrix with nonlocal topology. The observed patterns are in many cases direct generalizations of the corresponding two-dimensional (2D) patterns, e.g., spheres, layers, and cylinder grids. We also find cylindrical and "cross-layered" chimeras that do not have an equivalent in 2D systems. Quantitative measures are calculated, such as the ratio of synchronized and unsynchronized neurons as a function of the coupling range, the mean phase velocities, and the distribution of neurons in mean phase velocities. Based on these measures, the chimeras are categorized in two families. The first family of patterns is observed for weaker coupling and exhibits higher mean phase velocities for the unsynchronized areas of the network. The opposite holds for the second family, where the unsynchronized areas have lower mean phase velocities. The various measures demonstrate discontinuities, indicating criticality as the parameters cross from the first family of patterns to the second.

  12. Connecting Grammaticalisation

    DEFF Research Database (Denmark)

    Nørgård-Sørensen, Jens; Heltoft, Lars; Schøsler, Lene

    morphological, topological and constructional paradigms often connect to form complex paradigms. The book introduces the concept of connecting grammaticalisation to describe the formation, restructuring and dismantling of such complex paradigms. Drawing primarily on data from Germanic, Romance and Slavic...

  13. Learning of time series through neuron-to-neuron instruction

    Energy Technology Data Exchange (ETDEWEB)

    Miyazaki, Y [Department of Physics, Kyoto University, Kyoto 606-8502, (Japan); Kinzel, W [Institut fuer Theoretische Physik, Universitaet Wurzburg, 97074 Wurzburg (Germany); Shinomoto, S [Department of Physics, Kyoto University, Kyoto (Japan)

    2003-02-07

    A model neuron with delayline feedback connections can learn a time series generated by another model neuron. It has been known that some student neurons that have completed such learning under the instruction of a teacher's quasi-periodic sequence mimic the teacher's time series over a long interval, even after instruction has ceased. We found that in addition to such faithful students, there are unfaithful students whose time series eventually diverge exponentially from that of the teacher. In order to understand the circumstances that allow for such a variety of students, the orbit dimension was estimated numerically. The quasi-periodic orbits in question were found to be confined in spaces with dimensions significantly smaller than that of the full phase space.

  14. Learning of time series through neuron-to-neuron instruction

    International Nuclear Information System (INIS)

    Miyazaki, Y; Kinzel, W; Shinomoto, S

    2003-01-01

    A model neuron with delayline feedback connections can learn a time series generated by another model neuron. It has been known that some student neurons that have completed such learning under the instruction of a teacher's quasi-periodic sequence mimic the teacher's time series over a long interval, even after instruction has ceased. We found that in addition to such faithful students, there are unfaithful students whose time series eventually diverge exponentially from that of the teacher. In order to understand the circumstances that allow for such a variety of students, the orbit dimension was estimated numerically. The quasi-periodic orbits in question were found to be confined in spaces with dimensions significantly smaller than that of the full phase space

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

    Science.gov (United States)

    Friedrich, Péter; Vella, Michael; Gulyás, Attila I; Freund, Tamás F; Káli, Szabolcs

    2014-01-01

    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 problems 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 tool.

  16. A reanalysis of "Two types of asynchronous activity in networks of excitatory and inhibitory spiking neurons".

    Science.gov (United States)

    Engelken, Rainer; Farkhooi, Farzad; Hansel, David; van Vreeswijk, Carl; Wolf, Fred

    2016-01-01

    Neuronal activity in the central nervous system varies strongly in time and across neuronal populations. It is a longstanding proposal that such fluctuations generically arise from chaotic network dynamics. Various theoretical studies predict that the rich dynamics of rate models operating in the chaotic regime can subserve circuit computation and learning. Neurons in the brain, however, communicate via spikes and it is a theoretical challenge to obtain similar rate fluctuations in networks of spiking neuron models. A recent study investigated spiking balanced networks of leaky integrate and fire (LIF) neurons and compared their dynamics to a matched rate network with identical topology, where single unit input-output functions were chosen from isolated LIF neurons receiving Gaussian white noise input. A mathematical analogy between the chaotic instability in networks of rate units and the spiking network dynamics was proposed. Here we revisit the behavior of the spiking LIF networks and these matched rate networks. We find expected hallmarks of a chaotic instability in the rate network: For supercritical coupling strength near the transition point, the autocorrelation time diverges. For subcritical coupling strengths, we observe critical slowing down in response to small external perturbations. In the spiking network, we found in contrast that the timescale of the autocorrelations is insensitive to the coupling strength and that rate deviations resulting from small input perturbations rapidly decay. The decay speed even accelerates for increasing coupling strength. In conclusion, our reanalysis demonstrates fundamental differences between the behavior of pulse-coupled spiking LIF networks and rate networks with matched topology and input-output function. In particular there is no indication of a corresponding chaotic instability in the spiking network.

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

    Directory of Open Access Journals (Sweden)

    Péter eFriedrich

    2014-07-01

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

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

    Science.gov (United States)

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

    2018-02-01

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

  19. Innervation by a GABAergic neuron depresses spontaneous release in glutamatergic neurons and unveils the clamping phenotype of synaptotagmin-1

    DEFF Research Database (Denmark)

    Wierda, Keimpe D B; Sørensen, Jakob Balslev

    2014-01-01

    The role of spontaneously occurring release events in glutamatergic and GABAergic neurons and their regulation is intensely debated. To study the interdependence of glutamatergic and GABAergic spontaneous release, we compared reciprocally connected "mixed" glutamatergic/GABAergic neuronal pairs...... from mice cultured on astrocyte islands with "homotypic" glutamatergic or GABAergic pairs and autaptic neurons. We measured mEPSC and mIPSC frequencies simultaneously from both neurons. Neuronal pairs formed both interneuronal synaptic and autaptic connections indiscriminately. We find that whereas m......EPSC and mIPSC frequencies did not deviate between autaptic and synaptic connections, the frequency of mEPSCs in mixed pairs was strongly depressed compared with either autaptic neurons or glutamatergic pairs. Simultaneous imaging of synapses, or comparison to evoked release amplitudes, showed...

  20. 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.

  1. Dynamics of a structured neuron population

    International Nuclear Information System (INIS)

    Pakdaman, Khashayar; Salort, Delphine; Perthame, Benoît

    2010-01-01

    We study the dynamics of assemblies of interacting neurons. For large fully connected networks, the dynamics of the system can be described by a partial differential equation reminiscent of age-structure models used in mathematical ecology, where the 'age' of a neuron represents the time elapsed since its last discharge. The nonlinearity arises from the connectivity J of the network. We prove some mathematical properties of the model that are directly related to qualitative properties. On the one hand, we prove that it is well-posed and that it admits stationary states which, depending upon the connectivity, can be unique or not. On the other hand, we study the long time behaviour of solutions; both for small and large J, we prove the relaxation to the steady state describing asynchronous firing of the neurons. In the middle range, numerical experiments show that periodic solutions appear expressing re-synchronization of the network and asynchronous firing

  2. Neuronal migration, apoptosis and bipolar disorder.

    Science.gov (United States)

    Uribe, Ezequiel; Wix, Richard

    2012-01-01

    Bipolar disorder, like the majority of psychiatric disorders, is considered a neurodevelopment disease of neurodevelopment. There is an increased rate of neuronal birth and death during this development period. In the particular case of the processes that determine neuronal death, it is known that those neurons that establish connections have to be removed from the central nervous system. There is a deficit of GABAergic interneurons in the cerebral cortex in bipolar disorder, accompanied by overexpression of proapoptic genes. There is also an alteration in the expression of molecules that mediate in the migration of these neurons and their inclusion in functional synapsis during the foetal stage. The role of these molecules in the neuronal death pathways by apoptosis will be reviewed here in an attempt to establish biological hypotheses of the genesis of bipolar disorder. Copyright © 2011 SEP y SEPB. Published by Elsevier Espana. All rights reserved.

  3. Attractor dynamics in local neuronal networks

    Directory of Open Access Journals (Sweden)

    Jean-Philippe eThivierge

    2014-03-01

    Full Text Available Patterns of synaptic connectivity in various regions of the brain are characterized by the presence of synaptic motifs, defined as unidirectional and bidirectional synaptic contacts that follow a particular configuration and link together small groups of neurons. Recent computational work proposes that a relay network (two populations communicating via a third, relay population of neurons can generate precise patterns of neural synchronization. Here, we employ two distinct models of neuronal dynamics and show that simulated neural circuits designed in this way are caught in a global attractor of activity that prevents neurons from modulating their response on the basis of incoming stimuli. To circumvent the emergence of a fixed global attractor, we propose a mechanism of selective gain inhibition that promotes flexible responses to external stimuli. We suggest that local neuronal circuits may employ this mechanism to generate precise patterns of neural synchronization whose transient nature delimits the occurrence of a brief stimulus.

  4. Spike timing precision of neuronal circuits.

    Science.gov (United States)

    Kilinc, Deniz; Demir, Alper

    2018-04-17

    Spike timing is believed to be a key factor in sensory information encoding and computations performed by the neurons and neuronal circuits. However, the considerable noise and variability, arising from the inherently stochastic mechanisms that exist in the neurons and the synapses, degrade spike timing precision. Computational modeling can help decipher the mechanisms utilized by the neuronal circuits in order to regulate timing precision. In this paper, we utilize semi-analytical techniques, which were adapted from previously developed methods for electronic circuits, for the stochastic characterization of neuronal circuits. These techniques, which are orders of magnitude faster than traditional Monte Carlo type simulations, can be used to directly compute the spike timing jitter variance, power spectral densities, correlation functions, and other stochastic characterizations of neuronal circuit operation. We consider three distinct neuronal circuit motifs: Feedback inhibition, synaptic integration, and synaptic coupling. First, we show that both the spike timing precision and the energy efficiency of a spiking neuron are improved with feedback inhibition. We unveil the underlying mechanism through which this is achieved. Then, we demonstrate that a neuron can improve on the timing precision of its synaptic inputs, coming from multiple sources, via synaptic integration: The phase of the output spikes of the integrator neuron has the same variance as that of the sample average of the phases of its inputs. Finally, we reveal that weak synaptic coupling among neurons, in a fully connected network, enables them to behave like a single neuron with a larger membrane area, resulting in an improvement in the timing precision through cooperation.

  5. Making Connections

    Science.gov (United States)

    Pien, Cheng Lu; Dongsheng, Zhao

    2011-01-01

    Effective teaching includes enabling learners to make connections within mathematics. It is easy to accord with this statement, but how often is it a reality in the mathematics classroom? This article describes an approach in "connecting equivalent" fractions and whole number operations. The authors illustrate how a teacher can combine a common…

  6. The interplay between neurons and glia in synapse development and plasticity

    OpenAIRE

    Stogsdill, Jeff A; Eroglu, Cagla

    2016-01-01

    In the brain, the formation of complex neuronal networks amenable to experience-dependent remodeling is complicated by the diversity of neurons and synapse types. The establishment of a functional brain depends not only on neurons, but also non-neuronal glial cells. Glia are in continuous bi-directional communication with neurons to direct the formation and refinement of synaptic connectivity. This article reviews important findings, which uncovered cellular and molecular aspects of the neuro...

  7. Synchronization from Second Order Network Connectivity Statistics

    Science.gov (United States)

    Zhao, Liqiong; Beverlin, Bryce; Netoff, Theoden; Nykamp, Duane Q.

    2011-01-01

    We investigate how network structure can influence the tendency for a neuronal network to synchronize, or its synchronizability, independent of the dynamical model for each neuron. The synchrony analysis takes advantage of the framework of second order networks, which defines four second order connectivity statistics based on the relative frequency of two-connection network motifs. The analysis identifies two of these statistics, convergent connections, and chain connections, as highly influencing the synchrony. Simulations verify that synchrony decreases with the frequency of convergent connections and increases with the frequency of chain connections. These trends persist with simulations of multiple models for the neuron dynamics and for different types of networks. Surprisingly, divergent connections, which determine the fraction of shared inputs, do not strongly influence the synchrony. The critical role of chains, rather than divergent connections, in influencing synchrony can be explained by their increasing the effective coupling strength. The decrease of synchrony with convergent connections is primarily due to the resulting heterogeneity in firing rates. PMID:21779239

  8. About Connections

    Directory of Open Access Journals (Sweden)

    Kathleen S Rockland

    2015-05-01

    Full Text Available Despite the attention attracted by connectomics, one can lose sight of the very real questions concerning What are connections? In the neuroimaging community, structural connectivity is ground truth and underlying constraint on functional or effective connectivity. It is referenced to underlying anatomy; but, as increasingly remarked, there is a large gap between the wealth of human brain mapping and the relatively scant data on actual anatomical connectivity. Moreover, connections have typically been discussed as pairwise, point x projecting to point y (or: to points y and z, or more recently, in graph theoretical terms, as nodes or regions and the interconnecting edges. This is a convenient shorthand, but tends not to capture the richness and nuance of basic anatomical properties as identified in the classic tradition of tracer studies. The present short review accordingly revisits connectional weights, heterogeneity, reciprocity, topography, and hierarchical organization, drawing on concrete examples. The emphasis is on presynaptic long-distance connections, motivated by the intention to probe current assumptions and promote discussions about further progress and synthesis.

  9. Emulating the electrical activity of the neuron using a silicon oxide RRAM cell

    Directory of Open Access Journals (Sweden)

    Adnan eMehonic

    2016-02-01

    Full Text Available In recent years, formidable effort has been devoted to exploring the potential of Resistive RAM (RRAM devices to model key features of biological synapses. This is done to strengthen the link between neuro-computing architectures and neuroscience, bearing in mind the extremely low power consumption and immense parallelism of biological systems. Here we demonstrate the feasibility of using the RRAM cell to go further and to model aspects of the electrical activity of the neuron. We focus on the specific operational procedures required for the generation of controlled voltage transients, which resemble spike-like responses. Further, we demonstrate that RRAM devices are capable of integrating input current pulses over time to produce thresholded voltage transients. We show that the frequency of the output transients can be controlled by the input signal, and we relate recent models of the redox-based nanoionic resistive memory cell to two common neuronal models, the Hodgkin-Huxley (HH conductance model and the leaky integrate-and-fire model. We employ a simplified circuit model to phenomenologically describe voltage transient generation.

  10. Emulating the Electrical Activity of the Neuron Using a Silicon Oxide RRAM Cell

    Science.gov (United States)

    Mehonic, Adnan; Kenyon, Anthony J.

    2016-01-01

    In recent years, formidable effort has been devoted to exploring the potential of Resistive RAM (RRAM) devices to model key features of biological synapses. This is done to strengthen the link between neuro-computing architectures and neuroscience, bearing in mind the extremely low power consumption and immense parallelism of biological systems. Here we demonstrate the feasibility of using the RRAM cell to go further and to model aspects of the electrical activity of the neuron. We focus on the specific operational procedures required for the generation of controlled voltage transients, which resemble spike-like responses. Further, we demonstrate that RRAM devices are capable of integrating input current pulses over time to produce thresholded voltage transients. We show that the frequency of the output transients can be controlled by the input signal, and we relate recent models of the redox-based nanoionic resistive memory cell to two common neuronal models, the Hodgkin-Huxley (HH) conductance model and the leaky integrate-and-fire model. We employ a simplified circuit model to phenomenologically describe voltage transient generation. PMID:26941598

  11. Large-scale Ising-machines composed of magnetic neurons

    Science.gov (United States)

    Mizushima, Koichi; Goto, Hayato; Sato, Rie

    2017-10-01

    We propose Ising-machines composed of magnetic neurons, that is, magnetic bits in a recording track. In large-scale machines, the sizes of both neurons and synapses need to be reduced, and neat and smart connections among neurons are also required to achieve all-to-all connectivity among them. These requirements can be fulfilled by adopting magnetic recording technologies such as race-track memories and skyrmion tracks because the area of a magnetic bit is almost two orders of magnitude smaller than that of static random access memory, which has normally been used as a semiconductor neuron, and the smart connections among neurons are realized by using the read and write methods of these technologies.

  12. Neurons on the couch.

    Science.gov (United States)

    Marić, Nadja P; Jašović-Gašić, Miroslava

    2010-12-01

    A hundred years after psychoanalysis was introduced, neuroscience has taken a giant step forward. It seems nowadays that effects of psychotherapy could be monitored and measured by state-of-the art brain imaging techniques. Today, the psychotherapy is considered as a strategic and purposeful environmental influence intended to enhance learning. Since gene expression is regulated by environmental influences throughout life and these processes create brain architecture and influence the strength of synaptic connections, psychotherapy (as a kind of learning) should be explored in the context of aforementioned paradigm. In other words, when placing a client on the couch, therapist actually placed client's neuronal network; while listening and talking, expressing and analyzing, experiencing transference and counter transference, therapist tends to stabilize synaptic connections and influence dendritic growth by regulating gene-transcriptional activity. Therefore, we strongly believe that, in the near future, an increasing knowledge on cellular and molecular interactions and mechanisms of action of different psycho- and pharmaco-therapeutic procedures will enable us to tailor a sophisticated therapeutic approach toward a person, by combining major therapeutic strategies in psychiatry on the basis of rational goals and evidence-based therapeutic expectations.

  13. Internet Connectivity

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. Internet Connectivity. BSNL, SIFY, HCL in Guwahati; only BSNL elsewhere in NE (local player in Shillong). Service poor; All vendors lease BW from BSNL.

  14. Mathematics Connection

    African Journals Online (AJOL)

    MATHEMATICS CONNECTION aims at providing a forum topromote the development of Mathematics Education in Ghana. Articles that seekto enhance the teaching and/or learning of mathematics at all levels of theeducational system are welcome.

  15. HR Connect

    Data.gov (United States)

    US Agency for International Development — HR Connect is the USAID HR personnel system which allows HR professionals to process HR actions related to employee's personal and position information. This system...

  16. Sensory experience regulates cortical inhibition by inducing IGF1 in VIP neurons.

    Science.gov (United States)

    Mardinly, A R; Spiegel, I; Patrizi, A; Centofante, E; Bazinet, J E; Tzeng, C P; Mandel-Brehm, C; Harmin, D A; Adesnik, H; Fagiolini, M; Greenberg, M E

    2016-03-17

    Inhibitory neurons regulate the adaptation of neural circuits to sensory experience, but the molecular mechanisms by which experience controls the connectivity between different types of inhibitory neuron to regulate cortical plasticity are largely unknown. Here we show that exposure of dark-housed mice to light induces a gene program in cortical vasoactive intestinal peptide (VIP)-expressing neurons that is markedly distinct from that induced in excitatory neurons and other subtypes of inhibitory neuron. We identify Igf1 as one of several activity-regulated genes that are specific to VIP neurons, and demonstrate that IGF1 functions cell-autonomously in VIP neurons to increase inhibitory synaptic input onto these neurons. Our findings further suggest that in cortical VIP neurons, experience-dependent gene transcription regulates visual acuity by activating the expression of IGF1, thus promoting the inhibition of disinhibitory neurons and affecting inhibition onto cortical pyramidal neurons.

  17. Intrinsic control of electroresponsive properties of transplanted mammalian brain neurons

    DEFF Research Database (Denmark)

    Hounsgaard, J; Yarom, Y

    1985-01-01

    The present study presents the first analysis of neurons in mammalian brain transplants based on intracellular recording. The results, obtained in brain slices including both donor and host tissue, showed that neuronal precursor cells in embryonic transplants retained their ability to complete...... their normal differentiation of cell-type-specific electroresponsive properties. Distortions in cell aggregation and synaptic connectivity did not affect this aspect of neuronal differentiation....

  18. A decaying factor accounts for contained activity in neuronal networks with no need of hierarchical or modular organization

    International Nuclear Information System (INIS)

    Amancio, Diego R; Oliveira Jr, Osvaldo N; Costa, Luciano da F

    2012-01-01

    The mechanisms responsible for containing activity in systems represented by networks are crucial in various phenomena, for example, in diseases such as epilepsy that affect the neuronal networks and for information dissemination in social networks. The first models to account for contained activity included triggering and inhibition processes, but they cannot be applied to social networks where inhibition is clearly absent. A recent model showed that contained activity can be achieved with no need of inhibition processes provided that the network is subdivided into modules (communities). In this paper, we introduce a new concept inspired in the Hebbian theory, through which containment of activity is achieved by incorporating a dynamics based on a decaying activity in a random walk mechanism preferential to the node activity. Upon selecting the decay coefficient within a proper range, we observed sustained activity in all the networks tested, namely, random, Barabási–Albert and geographical networks. The generality of this finding was confirmed by showing that modularity is no longer needed if the dynamics based on the integrate-and-fire dynamics incorporated the decay factor. Taken together, these results provide a proof of principle that persistent, restrained network activation might occur in the absence of any particular topological structure. This may be the reason why neuronal activity does not spread out to the entire neuronal network, even when no special topological organization exists. (paper)

  19. Rate response of neurons subject to fast or frozen noise: from stochastic and homogeneous to deterministic and heterogeneous populations.

    Science.gov (United States)

    Alijani, Azadeh Khajeh; Richardson, Magnus J E

    2011-07-01

    The response of a neuronal population to afferent drive can be expected to be sensitive to both the distribution and dynamics of membrane voltages within the population. Voltage fluctuations can be driven by synaptic noise, neuromodulators, or cellular inhomogeneities: processes ranging from millisecond autocorrelation times to effectively static or "frozen" noise. Here we extend previous studies of filtered fluctuations to the experimentally verified exponential integrate-and-fire model. How fast or frozen fluctuations affect the steady-state rate and firing-rate response are both examined using perturbative solutions and limits of a 1 + 2 dimensional Fokker-Planck equation. The central finding is that, under conditions of a more-or-less constant population voltage variance, the firing-rate response is only weakly dependent on the fluctuation filter constant: The voltage distribution is the principal determinant of the population response. This result is unexpected given the nature of the systems underlying the extreme limits of fast and frozen fluctuations; the first limit represents a homogeneous population of neurons firing stochastically, whereas the second limit is equivalent to a heterogeneous population of neurons firing deterministically.

  20. Dicer maintains the identity and function of proprioceptive sensory neurons.

    Science.gov (United States)

    O'Toole, Sean M; Ferrer, Monica M; Mekonnen, Jennifer; Zhang, Haihan; Shima, Yasuyuki; Ladle, David R; Nelson, Sacha B

    2017-03-01

    Neuronal cell identity is established during development and must be maintained throughout an animal's life (Fishell G, Heintz N. Neuron 80: 602-612, 2013). Transcription factors critical for establishing neuronal identity can be required for maintaining it (Deneris ES, Hobert O. Nat Neurosci 17: 899-907, 2014). Posttranscriptional regulation also plays an important role in neuronal differentiation (Bian S, Sun T. Mol Neurobiol 44: 359-373, 2011), but its role in maintaining cell identity is less established. To better understand how posttranscriptional regulation might contribute to cell identity, we examined the proprioceptive neurons in the dorsal root ganglion (DRG), a highly specialized sensory neuron class, with well-established properties that distinguish them from other neurons in the ganglion. By conditionally ablating Dicer in mice, using parvalbumin (Pvalb)-driven Cre recombinase, we impaired posttranscriptional regulation in the proprioceptive sensory neuron population. Knockout (KO) animals display a progressive form of ataxia at the beginning of the fourth postnatal week that is accompanied by a cell death within the DRG. Before cell loss, expression profiling shows a reduction of proprioceptor specific genes and an increased expression of nonproprioceptive genes normally enriched in other ganglion neurons. Furthermore, although central connections of these neurons are intact, the peripheral connections to the muscle are functionally impaired. Posttranscriptional regulation is therefore necessary to retain the transcriptional identity and support functional specialization of the proprioceptive sensory neurons. NEW & NOTEWORTHY We have demonstrated that selectively impairing Dicer in parvalbumin-positive neurons, which include the proprioceptors, triggers behavioral changes, a lack of muscle connectivity, and a loss of transcriptional identity as observed through RNA sequencing. These results suggest that Dicer and, most likely by extension, micro

  1. Behavioral plasticity through the modulation of switch neurons.

    Science.gov (United States)

    Vassiliades, Vassilis; Christodoulou, Chris

    2016-02-01

    A central question in artificial intelligence is how to design agents capable of switching between different behaviors in response to environmental changes. Taking inspiration from neuroscience, we address this problem by utilizing artificial neural networks (NNs) as agent controllers, and mechanisms such as neuromodulation and synaptic gating. The novel aspect of this work is the introduction of a type of artificial neuron we call "switch neuron". A switch neuron regulates the flow of information in NNs by selectively gating all but one of its incoming synaptic connections, effectively allowing only one signal to propagate forward. The allowed connection is determined by the switch neuron's level of modulatory activation which is affected by modulatory signals, such as signals that encode some information about the reward received by the agent. An important aspect of the switch neuron is that it can be used in appropriate "switch modules" in order to modulate other switch neurons. As we show, the introduction of the switch modules enables the creation of sequences of gating events. This is achieved through the design of a modulatory pathway capable of exploring in a principled manner all permutations of the connections arriving on the switch neurons. We test the model by presenting appropriate architectures in nonstationary binary association problems and T-maze tasks. The results show that for all tasks, the switch neuron architectures generate optimal adaptive behaviors, providing evidence that the switch neuron model could be a valuable tool in simulations where behavioral plasticity is required. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Finite connectivity attractor neural networks

    International Nuclear Information System (INIS)

    Wemmenhove, B; Coolen, A C C

    2003-01-01

    We study a family of diluted attractor neural networks with a finite average number of (symmetric) connections per neuron. As in finite connectivity spin glasses, their equilibrium properties are described by order parameter functions, for which we derive an integral equation in replica symmetric approximation. A bifurcation analysis of this equation reveals the locations of the paramagnetic to recall and paramagnetic to spin-glass transition lines in the phase diagram. The line separating the retrieval phase from the spin-glass phase is calculated at zero temperature. All phase transitions are found to be continuous

  3. Layer 5 Callosal Parvalbumin-Expressing Neurons: A Distinct Functional Group of GABAergic Neurons.

    Science.gov (United States)

    Zurita, Hector; Feyen, Paul L C; Apicella, Alfonso Junior

    2018-01-01

    Previous studies have shown that parvalbumin-expressing neurons (CC-Parv neurons) connect the two hemispheres of motor and sensory areas via the corpus callosum, and are a functional part of the cortical circuit. Here we test the hypothesis that layer 5 CC-Parv neurons possess anatomical and molecular mechanisms which dampen excitability and modulate the gating of interhemispheric inhibition. In order to investigate this hypothesis we use viral tracing to determine the anatomical and electrophysiological properties of layer 5 CC-Parv and parvalbumin-expressing (Parv) neurons of the mouse auditory cortex (AC). Here we show that layer 5 CC-Parv neurons had larger dendritic fields characterized by longer dendrites that branched farther from the soma, whereas layer 5 Parv neurons had smaller dendritic fields characterized by shorter dendrites that branched nearer to the soma. The layer 5 CC-Parv neurons are characterized by delayed action potential (AP) responses to threshold currents, lower firing rates, and lower instantaneous frequencies compared to the layer 5 Parv neurons. Kv1.1 containing K + channels are the main source of the AP repolarization of the layer 5 CC-Parv and have a major role in determining both the spike delayed response, firing rate and instantaneous frequency of these neurons.

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

    Directory of Open Access Journals (Sweden)

    Wassim M. Haddad

    2014-07-01

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

  5. Establishing Connectivity

    DEFF Research Database (Denmark)

    Kjær, Poul F.

    Global law settings are characterised by a structural pre-eminence of connectivity norms, a type of norm which differs from coherency or possibility norms. The centrality of connectivity norms emerges from the function of global law, which is to increase the probability of transfers of condensed ...... and human rights can be understood as serving a constitutionalising function aimed at stabilising and facilitating connectivity. This allows for an understanding of colonialism and contemporary global governance as functional, but not as normative, equivalents.......Global law settings are characterised by a structural pre-eminence of connectivity norms, a type of norm which differs from coherency or possibility norms. The centrality of connectivity norms emerges from the function of global law, which is to increase the probability of transfers of condensed...... social components, such as economic capital and products, religious doctrines and scientific knowledge, from one legally structured context to another within world society. This was the case from colonialism and colonial law to contemporary global supply chains and human rights. Both colonial law...

  6. Reliable activation of immature neurons in the adult hippocampus.

    Directory of Open Access Journals (Sweden)

    Lucas A Mongiat

    Full Text Available Neurons born in the adult dentate gyrus develop, mature, and connect over a long interval that can last from six to eight weeks. It has been proposed that, during this period, developing neurons play a relevant role in hippocampal signal processing owing to their distinctive electrical properties. However, it has remained unknown whether immature neurons can be recruited into a network before synaptic and functional maturity have been achieved. To address this question, we used retroviral expression of green fluorescent protein to identify developing granule cells of the adult mouse hippocampus and investigate the balance of afferent excitation, intrinsic excitability, and firing behavior by patch clamp recordings in acute slices. We found that glutamatergic inputs onto young neurons are significantly weaker than those of mature cells, yet stimulation of cortical excitatory axons elicits a similar spiking probability in neurons at either developmental stage. Young neurons are highly efficient in transducing ionic currents into membrane depolarization due to their high input resistance, which decreases substantially in mature neurons as the inward rectifier potassium (Kir conductance increases. Pharmacological blockade of Kir channels in mature neurons mimics the high excitability characteristic of young neurons. Conversely, Kir overexpression induces mature-like firing properties in young neurons. Therefore, the differences in excitatory drive of young and mature neurons are compensated by changes in membrane excitability that render an equalized firing activity. These observations demonstrate that the adult hippocampus continuously generates a population of highly excitable young neurons capable of information processing.

  7. 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.

  8. Connected Traveler

    Energy Technology Data Exchange (ETDEWEB)

    2016-06-01

    The Connected Traveler framework seeks to boost the energy efficiency of personal travel and the overall transportation system by maximizing the accuracy of predicted traveler behavior in response to real-time feedback and incentives. It is anticipated that this approach will establish a feedback loop that 'learns' traveler preferences and customizes incentives to meet or exceed energy efficiency targets by empowering individual travelers with information needed to make energy-efficient choices and reducing the complexity required to validate transportation system energy savings. This handout provides an overview of NREL's Connected Traveler project, including graphics, milestones, and contact information.

  9. Optogenetic identification of hypothalamic orexin neuron projections to paraventricular spinally projecting neurons.

    Science.gov (United States)

    Dergacheva, Olga; Yamanaka, Akihiro; Schwartz, Alan R; Polotsky, Vsevolod Y; Mendelowitz, David

    2017-04-01

    Orexin neurons, and activation of orexin receptors, are generally thought to be sympathoexcitatory; however, the functional connectivity between orexin neurons and a likely sympathetic target, the hypothalamic spinally projecting neurons (SPNs) in the paraventricular nucleus of the hypothalamus (PVN) has not been established. To test the hypothesis that orexin neurons project directly to SPNs in the PVN, channelrhodopsin-2 (ChR2) was selectively expressed in orexin neurons to enable photoactivation of ChR2-expressing fibers while examining evoked postsynaptic currents in SPNs in rat hypothalamic slices. Selective photoactivation of orexin fibers elicited short-latency postsynaptic currents in all SPNs tested ( n = 34). These light-triggered responses were heterogeneous, with a majority being excitatory glutamatergic responses (59%) and a minority of inhibitory GABAergic (35%) and mixed glutamatergic and GABAergic currents (6%). Both glutamatergic and GABAergic responses were present in the presence of tetrodotoxin and 4-aminopyridine, suggesting a monosynaptic connection between orexin neurons and SPNs. In addition to generating postsynaptic responses, photostimulation facilitated action potential firing in SPNs (current clamp configuration). Glutamatergic, but not GABAergic, postsynaptic currents were diminished by application of the orexin receptor antagonist almorexant, indicating orexin release facilitates glutamatergic neurotransmission in this pathway. This work identifies a neuronal circuit by which orexin neurons likely exert sympathoexcitatory control of cardiovascular function. NEW & NOTEWORTHY This is the first study to establish, using innovative optogenetic approaches in a transgenic rat model, that there are robust heterogeneous projections from orexin neurons to paraventricular spinally projecting neurons, including excitatory glutamatergic and inhibitory GABAergic neurotransmission. Endogenous orexin release modulates glutamatergic, but not

  10. Energy-efficient neural information processing in individual neurons and neuronal networks.

    Science.gov (United States)

    Yu, Lianchun; Yu, Yuguo

    2017-11-01

    Brains are composed of networks of an enormous number of neurons interconnected with synapses. Neural information is carried by the electrical signals within neurons and the chemical signals among neurons. Generating these electrical and chemical signals is metabolically expensive. The fundamental issue raised here is whether brains have evolved efficient ways of developing an energy-efficient neural code from the molecular level to the circuit level. Here, we summarize the factors and biophysical mechanisms that could contribute to the energy-efficient neural code for processing input signals. The factors range from ion channel kinetics, body temperature, axonal propagation of action potentials, low-probability release of synaptic neurotransmitters, optimal input and noise, the size of neurons and neuronal clusters, excitation/inhibition balance, coding strategy, cortical wiring, and the organization of functional connectivity. Both experimental and computational evidence suggests that neural systems may use these factors to maximize the efficiency of energy consumption in processing neural signals. Studies indicate that efficient energy utilization may be universal in neuronal systems as an evolutionary consequence of the pressure of limited energy. As a result, neuronal connections may be wired in a highly economical manner to lower energy costs and space. Individual neurons within a network may encode independent stimulus components to allow a minimal number of neurons to represent whole stimulus characteristics efficiently. This basic principle may fundamentally change our view of how billions of neurons organize themselves into complex circuits to operate and generate the most powerful intelligent cognition in nature. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  11. The critical period for peripheral specification of dorsal root ganglion neurons is related to the period of sensory neurogenesis

    International Nuclear Information System (INIS)

    Smith, C.L.

    1990-01-01

    Thoracic sensory neurons in bullfrog tadpoles can be induced to form connections typical of brachial sensory neurons by transplanting thoracic ganglia to the branchial level at stages when some thoracic sensory neurons already have formed connections. In order to find out how many postmitotic sensory neurons survive transplantation, [ 3 H]thymidine was administered to tadpoles in which thoracic ganglia were transplanted to the brachial level unilaterally at stages VII to IX. Between 16 and 37% of the neurons in transplanted ganglia were unlabeled, as compared to 46 to 60% in unoperated ganglia. Transplanted ganglia contained fewer unlabeled neurons than corresponding unoperated ganglia, indicating that transplantation caused degeneration of postmitotic neurons. Therefore, a large fraction of the neurons that formed connections typical of brachial sensory neurons probably differentiated while they were at the brachial level

  12. Making connections

    NARCIS (Netherlands)

    Marion Duimel

    2007-01-01

    Original title: Verbinding maken; senioren en internet. More and more older people are finding their way to the Internet. Many people aged over 50 who have only recently gone online say that a new world has opened up for them. By connecting to the Internet they have the feeling that they

  13. CMS Connect

    Science.gov (United States)

    Balcas, J.; Bockelman, B.; Gardner, R., Jr.; Hurtado Anampa, K.; Jayatilaka, B.; Aftab Khan, F.; Lannon, K.; Larson, K.; Letts, J.; Marra Da Silva, J.; Mascheroni, M.; Mason, D.; Perez-Calero Yzquierdo, A.; Tiradani, A.

    2017-10-01

    The CMS experiment collects and analyzes large amounts of data coming from high energy particle collisions produced by the Large Hadron Collider (LHC) at CERN. This involves a huge amount of real and simulated data processing that needs to be handled in batch-oriented platforms. The CMS Global Pool of computing resources provide +100K dedicated CPU cores and another 50K to 100K CPU cores from opportunistic resources for these kind of tasks and even though production and event processing analysis workflows are already managed by existing tools, there is still a lack of support to submit final stage condor-like analysis jobs familiar to Tier-3 or local Computing Facilities users into these distributed resources in an integrated (with other CMS services) and friendly way. CMS Connect is a set of computing tools and services designed to augment existing services in the CMS Physics community focusing on these kind of condor analysis jobs. It is based on the CI-Connect platform developed by the Open Science Grid and uses the CMS GlideInWMS infrastructure to transparently plug CMS global grid resources into a virtual pool accessed via a single submission machine. This paper describes the specific developments and deployment of CMS Connect beyond the CI-Connect platform in order to integrate the service with CMS specific needs, including specific Site submission, accounting of jobs and automated reporting to standard CMS monitoring resources in an effortless way to their users.

  14. Dynamics and Synchronization of Noise Perturbed Ensembles of Periodically Activated neuron Cells

    DEFF Research Database (Denmark)

    Belykh, V. N.; Pankratova, Evgeniya; Mosekilde, Erik

    2008-01-01

    The role of noise for a single neuron and for an ensemble of mutually coupled neurons is investigated. For a single element we show that an increase in noise intensity in the regime of irregular. ring enhances the coherence of the neuronal response. For this regime of spiking a study...... based on the connection graph stability method and through numerical simulation....

  15. Detecting dependencies between spike trains of pairs of neurons through copulas

    DEFF Research Database (Denmark)

    Sacerdote, Laura; Tamborrino, Massimiliano; Zucca, Cristina

    2011-01-01

    The dynamics of a neuron are influenced by the connections with the network where it lies. Recorded spike trains exhibit patterns due to the interactions between neurons. However, the structure of the network is not known. A challenging task is to investigate it from the analysis of simultaneously...... the two neurons. Furthermore, the method recognizes the presence of delays in the spike propagation....

  16. Neuron array with plastic synapses and programmable dendrites.

    Science.gov (United States)

    Ramakrishnan, Shubha; Wunderlich, Richard; Hasler, Jennifer; George, Suma

    2013-10-01

    We describe a novel neuromorphic chip architecture that models neurons for efficient computation. Traditional architectures of neuron array chips consist of large scale systems that are interfaced with AER for implementing intra- or inter-chip connectivity. We present a chip that uses AER for inter-chip communication but uses fast, reconfigurable FPGA-style routing with local memory for intra-chip connectivity. We model neurons with biologically realistic channel models, synapses and dendrites. This chip is suitable for small-scale network simulations and can also be used for sequence detection, utilizing directional selectivity properties of dendrites, ultimately for use in word recognition.

  17. Charting Monosynaptic Connectivity Maps by Two-Color Light-Sheet Fluorescence Microscopy

    Directory of Open Access Journals (Sweden)

    Christian J. Niedworok

    2012-11-01

    Full Text Available Cellular resolution three-dimensional (3D visualization of defined, fluorescently labeled long-range neuronal networks in the uncut adult mouse brain has been elusive. Here, a virus-based strategy is described that allowed fluorescent labeling of centrifugally projecting neuronal populations in the ventral forebrain and their directly, monosynaptically connected bulbar interneurons upon a single stereotaxic injection into select neuronal populations. Implementation of improved tissue clearing combined with light-sheet fluorescence microscopy permitted imaging of the resulting connectivity maps in a single whole-brain scan. Subsequent 3D reconstructions revealed the exact distribution of the diverse neuronal ensembles monosynaptically connected with distinct bulbar interneuron populations. Moreover, rehydratation of brains after light-sheet fluorescence imaging enabled the immunohistochemical identification of synaptically connected neurons. Thus, this study describes a method for identifying monosynaptic connectivity maps from distinct, virally labeled neuronal populations that helps in better understanding of information flow in neural systems.

  18. Neuronal Migration Disorders

    Science.gov (United States)

    ... Understanding Sleep The Life and Death of a Neuron Genes At Work In The Brain Order Publications ... birth defects caused by the abnormal migration of neurons in the developing brain and nervous system. In ...

  19. Motor Neuron Diseases

    Science.gov (United States)

    ... and other neurodegenerative diseases to better understand the function of neurons and other support cells and identify candidate therapeutic ... and other neurodegenerative diseases to better understand the function of neurons and other support cells and identify candidate therapeutic ...

  20. Cerebro-cerebellar connectivity is increased in primary lateral sclerosis.

    Science.gov (United States)

    Meoded, Avner; Morrissette, Arthur E; Katipally, Rohan; Schanz, Olivia; Gotts, Stephen J; Floeter, Mary Kay

    2015-01-01

    Increased functional connectivity in resting state networks was found in several studies of patients with motor neuron disorders, although diffusion tensor imaging studies consistently show loss of white matter integrity. To understand the relationship between structural connectivity and functional connectivity, we examined the structural connections between regions with altered functional connectivity in patients with primary lateral sclerosis (PLS), a long-lived motor neuron disease. Connectivity matrices were constructed from resting state fMRI in 16 PLS patients to identify areas of differing connectivity between patients and healthy controls. Probabilistic fiber tracking was used to examine structural connections between regions of differing connectivity. PLS patients had 12 regions with increased functional connectivity compared to controls, with a predominance of cerebro-cerebellar connections. Increased functional connectivity was strongest between the cerebellum and cortical motor areas and between the cerebellum and frontal and temporal cortex. Fiber tracking detected no difference in connections between regions with increased functional connectivity. We conclude that functional connectivity changes are not strongly based in structural connectivity. Increased functional connectivity may be caused by common inputs, or by reduced selectivity of cortical activation, which could result from loss of intracortical inhibition when cortical afferents are intact.

  1. Statistics of Visual Responses to Image Object Stimuli from Primate AIT Neurons to DNN Neurons.

    Science.gov (United States)

    Dong, Qiulei; Wang, Hong; Hu, Zhanyi

    2018-02-01

    convolutional layers of VGG19 are considerably larger than the value of approximately 100 reported for IT neurons in Lehky et al. ( 2014 ), whereas those at the high fully connected layers are close to or lower than 100. To the best of our knowledge, this work is the first attempt to analyze the response statistics of DNN neurons with respect to primate IT neurons in image object representation.

  2. Gendered Connections

    DEFF Research Database (Denmark)

    Jensen, Steffen Bo

    2009-01-01

    This article explores the gendered nature of urban politics in Cape Town by focusing on a group of female, township politicians. Employing the Deleuzian concept of `wild connectivity', it argues that these politically entrepreneurial women were able to negotiate a highly volatile urban landscape...... by drawing on and operationalizing violent, male networks — from struggle activists' networks, to vigilante groups and gangs, to the police. The fact that they were women helped them to tap into and exploit these networks. At the same time, they were restricted by their sex, as their ability to navigate...... space also drew on quite traditional notions of female respectability. Furthermore, the article argues, the form of wild connectivity to an extent was a function of the political transition, which destabilized formal structures of gendered authority. It remains a question whether this form...

  3. 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.

  4. Bifurcation software in Matlab with applications in neuronal modeling.

    Science.gov (United States)

    Govaerts, Willy; Sautois, Bart

    2005-02-01

    Many biological phenomena, notably in neuroscience, can be modeled by dynamical systems. We describe a recent improvement of a Matlab software package for dynamical systems with applications to modeling single neurons and all-to-all connected networks of neurons. The new software features consist of an object-oriented approach to bifurcation computations and the partial inclusion of C-code to speed up the computation. As an application, we study the origin of the spiking behaviour of neurons when the equilibrium state is destabilized by an incoming current. We show that Class II behaviour, i.e. firing with a finite frequency, is possible even if the destabilization occurs through a saddle-node bifurcation. Furthermore, we show that synchronization of an all-to-all connected network of such neurons with only excitatory connections is also possible in this case.

  5. Synchronous behavior of two coupled electronic neurons

    International Nuclear Information System (INIS)

    Pinto, R. D.; Varona, P.; Volkovskii, A. R.; Szuecs, A.; Abarbanel, Henry D. I.; Rabinovich, M. I.

    2000-01-01

    We report on experimental studies of synchronization phenomena in a pair of analog electronic neurons (ENs). The ENs were designed to reproduce the observed membrane voltage oscillations of isolated biological neurons from the stomatogastric ganglion of the California spiny lobster Panulirus interruptus. The ENs are simple analog circuits which integrate four-dimensional differential equations representing fast and slow subcellular mechanisms that produce the characteristic regular/chaotic spiking-bursting behavior of these cells. In this paper we study their dynamical behavior as we couple them in the same configurations as we have done for their counterpart biological neurons. The interconnections we use for these neural oscillators are both direct electrical connections and excitatory and inhibitory chemical connections: each realized by analog circuitry and suggested by biological examples. We provide here quantitative evidence that the ENs and the biological neurons behave similarly when coupled in the same manner. They each display well defined bifurcations in their mutual synchronization and regularization. We report briefly on an experiment on coupled biological neurons and four-dimensional ENs, which provides further ground for testing the validity of our numerical and electronic models of individual neural behavior. Our experiments as a whole present interesting new examples of regularization and synchronization in coupled nonlinear oscillators. (c) 2000 The American Physical Society

  6. Dense reconstruction of brain-wide neuronal population close to the ground truth

    OpenAIRE

    Li, Yun; Zhou, Hang; Li, Shiwei; Li, Jing; Su, Lei; Li, Anan; Feng, Xiong; Li, Ning; Han, Jiacheng; Kang, Hongtao; Chen, Yijun; Fang, Wenqian; Liu, Yidong; Lin, Huimin; Jin, Sen

    2017-01-01

    Neuron is the basic structure and functional unit of the brain, its projection and connections with other neurons provide a basic physical infrastructure for neural signal storage, allocation, processing, and integration. Recent technique progresses allow for labeling and imaging specific neuronal populations at single axonal level across a whole mouse brain. However, digital reconstruction of these neuron individuals needs months of human labor or sometimes is even an impossible task. Here w...

  7. Soft chitosan microbeads scaffold for 3D functional neuronal networks.

    Science.gov (United States)

    Tedesco, Maria Teresa; Di Lisa, Donatella; Massobrio, Paolo; Colistra, Nicolò; Pesce, Mattia; Catelani, Tiziano; Dellacasa, Elena; Raiteri, Roberto; Martinoia, Sergio; Pastorino, Laura

    2018-02-01

    The availability of 3D biomimetic in vitro neuronal networks of mammalian neurons represents a pivotal step for the development of brain-on-a-chip experimental models to study neuronal (dys)functions and particularly neuronal connectivity. The use of hydrogel-based scaffolds for 3D cell cultures has been extensively studied in the last years. However, limited work on biomimetic 3D neuronal cultures has been carried out to date. In this respect, here we investigated the use of a widely popular polysaccharide, chitosan (CHI), for the fabrication of a microbead based 3D scaffold to be coupled to primary neuronal cells. CHI microbeads were characterized by optical and atomic force microscopies. The cell/scaffold interaction was deeply characterized by transmission electron microscopy and by immunocytochemistry using confocal microscopy. Finally, a preliminary electrophysiological characterization by micro-electrode arrays was carried out. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Development of rat telencephalic neurons after prenatal x-irradiation

    International Nuclear Information System (INIS)

    Norton, S.

    1979-01-01

    Telencephalic neurons of rats, irradiated at day 15 of gestation with 125 R, develop synaptic connections on dendrites during maturation which appear to be normal spines in Golgi-stained light microscope preparations. At six weeks of postnatal age both control and irradiated rats have spiny dendritic processes on cortical pyramidal cells and caudate Golgi type II neurons. However, when the rats are 6 months old the irradiated rats have more neurons with beaded dendritic processes that lack spines or neurons and are likely to be degenerating neurons. The apparently normal development of the neurons followed by degeneration in the irradiated rat has a parallel in previous reports of the delayed hyperactivity which develops in rats irradiated on the fifteenth gestational day

  9. Stages of neuronal network formation

    International Nuclear Information System (INIS)

    Woiterski, Lydia; Käs, Josef A; Claudepierre, Thomas; Luxenhofer, Robert; Jordan, Rainer

    2013-01-01

    Graph theoretical approaches have become a powerful tool for investigating the architecture and dynamics of complex networks. The topology of network graphs revealed small-world properties for very different real systems among these neuronal networks. In this study, we observed the early development of mouse retinal ganglion cell (RGC) networks in vitro using time-lapse video microscopy. By means of a time-resolved graph theoretical analysis of the connectivity, shortest path length and the edge length, we were able to discover the different stages during the network formation. Starting from single cells, at the first stage neurons connected to each other ending up in a network with maximum complexity. In the further course, we observed a simplification of the network which manifested in a change of relevant network parameters such as the minimization of the path length. Moreover, we found that RGC networks self-organized as small-world networks at both stages; however, the optimization occurred only in the second stage. (paper)

  10. Cosmic Connections

    CERN Document Server

    Ellis, Jonathan Richard

    2003-01-01

    A National Research Council study on connecting quarks with the cosmos has recently posed a number of the more important open questions at the interface between particle physics and cosmology. These questions include the nature of dark matter and dark energy, how the Universe began, modifications to gravity, the effects of neutrinos on the Universe, how cosmic accelerators work, and whether there are new states of matter at high density and pressure. These questions are discussed in the context of the talks presented at this Summer Institute.

  11. KV7 Channels Regulate Firing during Synaptic Integration in GABAergic Striatal Neurons

    Directory of Open Access Journals (Sweden)

    M. Belén Pérez-Ramírez

    2015-01-01

    Full Text Available Striatal projection neurons (SPNs process motor and cognitive information. Their activity is affected by Parkinson’s disease, in which dopamine concentration is decreased and acetylcholine concentration is increased. Acetylcholine activates muscarinic receptors in SPNs. Its main source is the cholinergic interneuron that responds with a briefer latency than SPNs during a cortical command. Therefore, an important question is whether muscarinic G-protein coupled receptors and their signaling cascades are fast enough to intervene during synaptic responses to regulate synaptic integration and firing. One of the most known voltage dependent channels regulated by muscarinic receptors is the KV7/KCNQ channel. It is not known whether these channels regulate the integration of suprathreshold corticostriatal responses. Here, we study the impact of cholinergic muscarinic modulation on the synaptic response of SPNs by regulating KV7 channels. We found that KV7 channels regulate corticostriatal synaptic integration and that this modulation occurs in the dendritic/spines compartment. In contrast, it is negligible in the somatic compartment. This modulation occurs on sub- and suprathreshold responses and lasts during the whole duration of the responses, hundreds of milliseconds, greatly altering SPNs firing properties. This modulation affected the behavior of the striatal microcircuit.

  12. From migration to settlement: the pathways, migration modes and dynamics of neurons in the developing brain

    Science.gov (United States)

    HATANAKA, Yumiko; ZHU, Yan; TORIGOE, Makio; KITA, Yoshiaki; MURAKAMI, Fujio

    2016-01-01

    Neuronal migration is crucial for the construction of the nervous system. To reach their correct destination, migrating neurons choose pathways using physical substrates and chemical cues of either diffusible or non-diffusible nature. Migrating neurons extend a leading and a trailing process. The leading process, which extends in the direction of migration, determines navigation, in particular when a neuron changes its direction of migration. While most neurons simply migrate radially, certain neurons switch their mode of migration between radial and tangential, with the latter allowing migration to destinations far from the neurons’ site of generation. Consequently, neurons with distinct origins are intermingled, which results in intricate neuronal architectures and connectivities and provides an important basis for higher brain function. The trailing process, in contrast, contributes to the late stage of development by turning into the axon, thus contributing to the formation of neuronal circuits. PMID:26755396

  13. Places Connected:

    DEFF Research Database (Denmark)

    Hansen, Annette Skovsted

    This paper argues that development assistance contributed to the globalization of the 20th century by financing truly global networks of people. By focusing on the networks financed by development assistance bound by the national histories of Denmark and Japan, I illustrate how the people who...... experiences of place, however, when it is often the same people who experience many different places? Along with many other so-called donors in the 1950s, Denmark and Japan chose to invest in the education of own and other nationals involved in development and thereby financed personal connections between...... individuals throughout the world. Development assistance , where there are two or three links only between a Bangladeshi farmer, a street child in Sao Paolo and the President of the United States, the Queen of Denmark, or a suburban house wife in Japan, who has never left the Osaka area, but mothered a United...

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

    DEFF Research Database (Denmark)

    Tamborrino, Massimiliano

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

  15. Memory formation orchestrates the wiring of adult-born hippocampal neurons into brain circuits.

    Science.gov (United States)

    Petsophonsakul, Petnoi; Richetin, Kevin; Andraini, Trinovita; Roybon, Laurent; Rampon, Claire

    2017-08-01

    During memory formation, structural rearrangements of dendritic spines provide a mean to durably modulate synaptic connectivity within neuronal networks. New neurons generated throughout the adult life in the dentate gyrus of the hippocampus contribute to learning and memory. As these neurons become incorporated into the network, they generate huge numbers of new connections that modify hippocampal circuitry and functioning. However, it is yet unclear as to how the dynamic process of memory formation influences their synaptic integration into neuronal circuits. New memories are established according to a multistep process during which new information is first acquired and then consolidated to form a stable memory trace. Upon recall, memory is transiently destabilized and vulnerable to modification. Using contextual fear conditioning, we found that learning was associated with an acceleration of dendritic spines formation of adult-born neurons, and that spine connectivity becomes strengthened after memory consolidation. Moreover, we observed that afferent connectivity onto adult-born neurons is enhanced after memory retrieval, while extinction training induces a change of spine shapes. Together, these findings reveal that the neuronal activity supporting memory processes strongly influences the structural dendritic integration of adult-born neurons into pre-existing neuronal circuits. Such change of afferent connectivity is likely to impact the overall wiring of hippocampal network, and consequently, to regulate hippocampal function.

  16. Neuron-to-neuron transmission of α-synuclein fibrils through axonal transport

    Science.gov (United States)

    Freundt, Eric C.; Maynard, Nate; Clancy, Eileen K.; Roy, Shyamali; Bousset, Luc; Sourigues, Yannick; Covert, Markus; Melki, Ronald; Kirkegaard, Karla; Brahic, Michel

    2012-01-01

    Objective The lesions of Parkinson's disease spread through the brain in a characteristic pattern that corresponds to axonal projections. Previous observations suggest that misfolded α-synuclein could behave as a prion, moving from neuron to neuron and causing endogenous α-synuclein to misfold. Here, we characterized and quantified the axonal transport of α-synuclein fibrils and showed that fibrils could be transferred from axons to second-order neurons following anterograde transport. Methods We grew primary cortical mouse neurons in microfluidic devices to separate soma from axonal projections in fluidically isolated microenvironments. We used live-cell imaging and immunofluorescence to characterize the transport of fluorescent α-synuclein fibrils and their transfer to second-order neurons. Results Fibrillar α-synuclein was internalized by primary neurons and transported in axons with kinetics consistent with slow component-b of axonal transport (fast axonal transport with saltatory movement). Fibrillar α-synuclein was readily observed in the cell bodies of second-order neurons following anterograde axonal transport. Axon-to-soma transfer appeared not to require synaptic contacts. Interpretation These results support the hypothesis that the progression of Parkinson's disease can be caused by neuron-to-neuron spread of α-synuclein aggregates and that the anatomical pattern of progression of lesions between axonally connected areas results from the axonal transport of such aggregates. That the transfer did not appear to be transsynaptic gives hope that α-synuclein fibrils could be intercepted by drugs during the extra-cellular phase of their journey. PMID:23109146

  17. Kappe neurons, a novel population of olfactory sensory neurons

    OpenAIRE

    Ahuja, Gaurav; Nia, Shahrzad Bozorg; Zapilko, Veronika; Shiriagin, Vladimir; Kowatschew, Daniel; Oka, Yuichiro; Korsching, Sigrun I.

    2014-01-01

    Perception of olfactory stimuli is mediated by distinct populations of olfactory sensory neurons, each with a characteristic set of morphological as well as functional parameters. Beyond two large populations of ciliated and microvillous neurons, a third population, crypt neurons, has been identified in teleost and cartilaginous fishes. We report here a novel, fourth olfactory sensory neuron population in zebrafish, which we named kappe neurons for their characteristic shape. Kappe neurons ar...

  18. Associative memory in phasing neuron networks

    Energy Technology Data Exchange (ETDEWEB)

    Nair, Niketh S [ORNL; Bochove, Erik J. [United States Air Force Research Laboratory, Kirtland Air Force Base; Braiman, Yehuda [ORNL

    2014-01-01

    We studied pattern formation in a network of coupled Hindmarsh-Rose model neurons and introduced a new model for associative memory retrieval using networks of Kuramoto oscillators. Hindmarsh-Rose Neural Networks can exhibit a rich set of collective dynamics that can be controlled by their connectivity. Specifically, we showed an instance of Hebb's rule where spiking was correlated with network topology. Based on this, we presented a simple model of associative memory in coupled phase oscillators.

  19. Zebrafish transgenic constructs label specific neurons in Xenopus laevis spinal cord and identify frog V0v spinal neurons.

    Science.gov (United States)

    Juárez-Morales, José L; Martinez-De Luna, Reyna I; Zuber, Michael E; Roberts, Alan; Lewis, Katharine E

    2017-09-01

    A correctly functioning spinal cord is crucial for locomotion and communication between body and brain but there are fundamental gaps in our knowledge of how spinal neuronal circuitry is established and functions. To understand the genetic program that regulates specification and functions of this circuitry, we need to connect neuronal molecular phenotypes with physiological analyses. Studies using Xenopus laevis tadpoles have increased our understanding of spinal cord neuronal physiology and function, particularly in locomotor circuitry. However, the X. laevis tetraploid genome and long generation time make it difficult to investigate how neurons are specified. The opacity of X. laevis embryos also makes it hard to connect functional classes of neurons and the genes that they express. We demonstrate here that Tol2 transgenic constructs using zebrafish enhancers that drive expression in specific zebrafish spinal neurons label equivalent neurons in X. laevis and that the incorporation of a Gal4:UAS amplification cassette enables cells to be observed in live X. laevis tadpoles. This technique should enable the molecular phenotypes, morphologies and physiologies of distinct X. laevis spinal neurons to be examined together in vivo. We have used an islet1 enhancer to label Rohon-Beard sensory neurons and evx enhancers to identify V0v neurons, for the first time, in X. laevis spinal cord. Our work demonstrates the homology of spinal cord circuitry in zebrafish and X. laevis, suggesting that future work could combine their relative strengths to elucidate a more complete picture of how vertebrate spinal cord neurons are specified, and function to generate behavior. © 2017 Wiley Periodicals, Inc. Develop Neurobiol 77: 1007-1020, 2017. © 2017 Wiley Periodicals, Inc.

  20. Selectivity and sparseness in randomly connected balanced networks.

    Directory of Open Access Journals (Sweden)

    Cengiz Pehlevan

    Full Text Available Neurons in sensory cortex show stimulus selectivity and sparse population response, even in cases where no strong functionally specific structure in connectivity can be detected. This raises the question whether selectivity and sparseness can be generated and maintained in randomly connected networks. We consider a recurrent network of excitatory and inhibitory spiking neurons with random connectivity, driven by random projections from an input layer of stimulus selective neurons. In this architecture, the stimulus-to-stimulus and neuron-to-neuron modulation of total synaptic input is weak compared to the mean input. Surprisingly, we show that in the balanced state the network can still support high stimulus selectivity and sparse population response. In the balanced state, strong synapses amplify the variation in synaptic input and recurrent inhibition cancels the mean. Functional specificity in connectivity emerges due to the inhomogeneity caused by the generative statistical rule used to build the network. We further elucidate the mechanism behind and evaluate the effects of model parameters on population sparseness and stimulus selectivity. Network response to mixtures of stimuli is investigated. It is shown that a balanced state with unselective inhibition can be achieved with densely connected input to inhibitory population. Balanced networks exhibit the "paradoxical" effect: an increase in excitatory drive to inhibition leads to decreased inhibitory population firing rate. We compare and contrast selectivity and sparseness generated by the balanced network to randomly connected unbalanced networks. Finally, we discuss our results in light of experiments.

  1. Depression-biased reverse plasticity rule is required for stable learning at top-down connections.

    Directory of Open Access Journals (Sweden)

    Kendra S Burbank

    Full Text Available Top-down synapses are ubiquitous throughout neocortex and play a central role in cognition, yet little is known about their development and specificity. During sensory experience, lower neocortical areas are activated before higher ones, causing top-down synapses to experience a preponderance of post-synaptic activity preceding pre-synaptic activity. This timing pattern is the opposite of that experienced by bottom-up synapses, which suggests that different versions of spike-timing dependent synaptic plasticity (STDP rules may be required at top-down synapses. We consider a two-layer neural network model and investigate which STDP rules can lead to a distribution of top-down synaptic weights that is stable, diverse and avoids strong loops. We introduce a temporally reversed rule (rSTDP where top-down synapses are potentiated if post-synaptic activity precedes pre-synaptic activity. Combining analytical work and integrate-and-fire simulations, we show that only depression-biased rSTDP (and not classical STDP produces stable and diverse top-down weights. The conclusions did not change upon addition of homeostatic mechanisms, multiplicative STDP rules or weak external input to the top neurons. Our prediction for rSTDP at top-down synapses, which are distally located, is supported by recent neurophysiological evidence showing the existence of temporally reversed STDP in synapses that are distal to the post-synaptic cell body.

  2. Depression-Biased Reverse Plasticity Rule Is Required for Stable Learning at Top-Down Connections

    Science.gov (United States)

    Burbank, Kendra S.; Kreiman, Gabriel

    2012-01-01

    Top-down synapses are ubiquitous throughout neocortex and play a central role in cognition, yet little is known about their development and specificity. During sensory experience, lower neocortical areas are activated before higher ones, causing top-down synapses to experience a preponderance of post-synaptic activity preceding pre-synaptic activity. This timing pattern is the opposite of that experienced by bottom-up synapses, which suggests that different versions of spike-timing dependent synaptic plasticity (STDP) rules may be required at top-down synapses. We consider a two-layer neural network model and investigate which STDP rules can lead to a distribution of top-down synaptic weights that is stable, diverse and avoids strong loops. We introduce a temporally reversed rule (rSTDP) where top-down synapses are potentiated if post-synaptic activity precedes pre-synaptic activity. Combining analytical work and integrate-and-fire simulations, we show that only depression-biased rSTDP (and not classical STDP) produces stable and diverse top-down weights. The conclusions did not change upon addition of homeostatic mechanisms, multiplicative STDP rules or weak external input to the top neurons. Our prediction for rSTDP at top-down synapses, which are distally located, is supported by recent neurophysiological evidence showing the existence of temporally reversed STDP in synapses that are distal to the post-synaptic cell body. PMID:22396630

  3. Growth of cortical neuronal network in vitro: Modeling and analysis

    International Nuclear Information System (INIS)

    Lai, P.-Y.; Jia, L. C.; Chan, C. K.

    2006-01-01

    We present a detailed analysis and theoretical growth models to account for recent experimental data on the growth of cortical neuronal networks in vitro [Phys. Rev. Lett. 93, 088101 (2004)]. The experimentally observed synchronized firing frequency of a well-connected neuronal network is shown to be proportional to the mean network connectivity. The growth of the network is consistent with the model of an early enhanced growth of connection, but followed by a retarded growth once the synchronized cluster is formed. Microscopic models with dominant excluded volume interactions are consistent with the observed exponential decay of the mean connection probability as a function of the mean network connectivity. The biological implications of the growth model are also discussed

  4. Diverse coupling of neurons to populations in sensory cortex.

    Science.gov (United States)

    Okun, Michael; Steinmetz, Nicholas; Cossell, Lee; Iacaruso, M Florencia; Ko, Ho; Barthó, Péter; Moore, Tirin; Hofer, Sonja B; Mrsic-Flogel, Thomas D; Carandini, Matteo; Harris, Kenneth D

    2015-05-28

    A large population of neurons can, in principle, produce an astronomical number of distinct firing patterns. In cortex, however, these patterns lie in a space of lower dimension, as if individual neurons were "obedient members of a huge orchestra". Here we use recordings from the visual cortex of mouse (Mus musculus) and monkey (Macaca mulatta) to investigate the relationship between individual neurons and the population, and to establish the underlying circuit mechanisms. We show that neighbouring neurons can differ in their coupling to the overall firing of the population, ranging from strongly coupled 'choristers' to weakly coupled 'soloists'. Population coupling is largely independent of sensory preferences, and it is a fixed cellular attribute, invariant to stimulus conditions. Neurons with high population coupling are more strongly affected by non-sensory behavioural variables such as motor intention. Population coupling reflects a causal relationship, predicting the response of a neuron to optogenetically driven increases in local activity. Moreover, population coupling indicates synaptic connectivity; the population coupling of a neuron, measured in vivo, predicted subsequent in vitro estimates of the number of synapses received from its neighbours. Finally, population coupling provides a compact summary of population activity; knowledge of the population couplings of n neurons predicts a substantial portion of their n(2) pairwise correlations. Population coupling therefore represents a novel, simple measure that characterizes the relationship of each neuron to a larger population, explaining seemingly complex network firing patterns in terms of basic circuit variables.

  5. Doubly stochastic coherence in complex neuronal networks

    Science.gov (United States)

    Gao, Yang; Wang, Jianjun

    2012-11-01

    A system composed of coupled FitzHugh-Nagumo neurons with various topological structures is investigated under the co-presence of two independently additive and multiplicative Gaussian white noises, in which particular attention is paid to the neuronal networks spiking regularity. As the additive noise intensity and the multiplicative noise intensity are simultaneously adjusted to optimal values, the temporal periodicity of the output of the system reaches the maximum, indicating the occurrence of doubly stochastic coherence. The network topology randomness exerts different influences on the temporal coherence of the spiking oscillation for dissimilar coupling strength regimes. At a small coupling strength, the spiking regularity shows nearly no difference in the regular, small-world, and completely random networks. At an intermediate coupling strength, the temporal periodicity in a small-world neuronal network can be improved slightly by adding a small fraction of long-range connections. At a large coupling strength, the dynamical behavior of the neurons completely loses the resonance property with regard to the additive noise intensity or the multiplicative noise intensity, and the spiking regularity decreases considerably with the increase of the network topology randomness. The network topology randomness plays more of a depressed role than a favorable role in improving the temporal coherence of the spiking oscillation in the neuronal network research study.

  6. Bursting synchronization in clustered neuronal networks

    International Nuclear Information System (INIS)

    Yu Hai-Tao; Wang Jiang; Deng Bin; Wei Xi-Le

    2013-01-01

    Neuronal networks in the brain exhibit the modular (clustered) property, i.e., they are composed of certain subnetworks with differential internal and external connectivity. We investigate bursting synchronization in a clustered neuronal network. A transition to mutual-phase synchronization takes place on the bursting time scale of coupled neurons, while on the spiking time scale, they behave asynchronously. This synchronization transition can be induced by the variations of inter- and intracoupling strengths, as well as the probability of random links between different subnetworks. Considering that some pathological conditions are related with the synchronization of bursting neurons in the brain, we analyze the control of bursting synchronization by using a time-periodic external signal in the clustered neuronal network. Simulation results show a frequency locking tongue in the driving parameter plane, where bursting synchronization is maintained, even in the presence of external driving. Hence, effective synchronization suppression can be realized with the driving parameters outside the frequency locking region. (interdisciplinary physics and related areas of science and technology)

  7. Epigenetic Basis of Neuronal and Synaptic Plasticity.

    Science.gov (United States)

    Karpova, Nina N; Sales, Amanda J; Joca, Samia R

    2017-01-01

    Neuronal network and plasticity change as a function of experience. Altered neural connectivity leads to distinct transcriptional programs of neuronal plasticity-related genes. The environmental challenges throughout life may promote long-lasting reprogramming of gene expression and the development of brain disorders. The modifications in neuronal epigenome mediate gene-environmental interactions and are required for activity-dependent regulation of neuronal differentiation, maturation and plasticity. Here, we highlight the latest advances in understanding the role of the main players of epigenetic machinery (DNA methylation and demethylation, histone modifications, chromatin-remodeling enzymes, transposons, and non-coding RNAs) in activity-dependent and long- term neural and synaptic plasticity. The review focuses on both the transcriptional and post-transcriptional regulation of gene expression levels, including the processes of promoter activation, alternative splicing, regulation of stability of gene transcripts by natural antisense RNAs, and alternative polyadenylation. Further, we discuss the epigenetic aspects of impaired neuronal plasticity and the pathogenesis of neurodevelopmental (Rett syndrome, Fragile X Syndrome, genomic imprinting disorders, schizophrenia, and others), stressrelated (mood disorders) and neurodegenerative Alzheimer's, Parkinson's and Huntington's disorders. The review also highlights the pharmacological compounds that modulate epigenetic programming of gene expression, the potential treatment strategies of discussed brain disorders, and the questions that should be addressed during the development of effective and safe approaches for the treatment of brain disorders.

  8. Large-scale modelling of neuronal systems

    International Nuclear Information System (INIS)

    Castellani, G.; Verondini, E.; Giampieri, E.; Bersani, F.; Remondini, D.; Milanesi, L.; Zironi, I.

    2009-01-01

    The brain is, without any doubt, the most, complex system of the human body. Its complexity is also due to the extremely high number of neurons, as well as the huge number of synapses connecting them. Each neuron is capable to perform complex tasks, like learning and memorizing a large class of patterns. The simulation of large neuronal systems is challenging for both technological and computational reasons, and can open new perspectives for the comprehension of brain functioning. A well-known and widely accepted model of bidirectional synaptic plasticity, the BCM model, is stated by a differential equation approach based on bistability and selectivity properties. We have modified the BCM model extending it from a single-neuron to a whole-network model. This new model is capable to generate interesting network topologies starting from a small number of local parameters, describing the interaction between incoming and outgoing links from each neuron. We have characterized this model in terms of complex network theory, showing how this, learning rule can be a support For network generation.

  9. NEURON and Python.

    Science.gov (United States)

    Hines, Michael L; Davison, Andrew P; Muller, Eilif

    2009-01-01

    The NEURON simulation program now allows Python to be used, alone or in combination with NEURON's traditional Hoc interpreter. Adding Python to NEURON has the immediate benefit of making available a very extensive suite of analysis tools written for engineering and science. It also catalyzes NEURON software development by offering users a modern programming tool that is recognized for its flexibility and power to create and maintain complex programs. At the same time, nothing is lost because all existing models written in Hoc, including graphical user interface tools, continue to work without change and are also available within the Python context. An example of the benefits of Python availability is the use of the xml module in implementing NEURON's Import3D and CellBuild tools to read MorphML and NeuroML model specifications.

  10. Early functional impairment of sensory-motor connectivity in a mouse model of spinal muscular atrophy

    Science.gov (United States)

    Mentis, George Z.; Blivis, Dvir; Liu, Wenfang; Drobac, Estelle; Crowder, Melissa E.; Kong, Lingling; Alvarez, Francisco J.; Sumner, Charlotte J.; O'Donovan, Michael J.

    2011-01-01

    SUMMARY To define alterations of neuronal connectivity that occur during motor neuron degeneration, we characterized the function and structure of spinal circuitry in spinal muscular atrophy (SMA) model mice. SMA motor neurons show reduced proprioceptive reflexes that correlate with decreased number and function of synapses on motor neuron somata and proximal dendrites. These abnormalities occur at an early stage of disease in motor neurons innervating proximal hindlimb muscles and medial motor neurons innervating axial muscles, but only at end-stage disease in motor neurons innervating distal hindlimb muscles. Motor neuron loss follows afferent synapse loss with the same temporal and topographical pattern. Trichostatin A, which improves motor behavior and survival of SMA mice, partially restores spinal reflexes illustrating the reversibility of these synaptic defects. De-afferentation of motor neurons is an early event in SMA and may be a primary cause of motor dysfunction that is amenable to therapeutic intervention. PMID:21315257

  11. Connectivity effects in the dynamic model of neural networks

    International Nuclear Information System (INIS)

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

    2009-01-01

    We study, via extensive Monte Carlo calculations, the effects of connectivity in the dynamic model of neural networks, to observe that the Mattis-state order parameter increases with the number of coupled neurons. Such effects appear more pronounced when the average number of connections is increased by introducing shortcuts in the network. In particular, the power spectra of the order parameter at stationarity are found to exhibit power-law behavior, depending on how the average number of connections is increased. The cluster size distribution of the 'memory-unmatched' sites also follows a power law and possesses strong correlations with the power spectra. It is further observed that the distribution of waiting times for neuron firing fits roughly to a power law, again depending on how neuronal connections are increased

  12. Spinal cord: motor neuron diseases.

    Science.gov (United States)

    Rezania, Kourosh; Roos, Raymond P

    2013-02-01

    Spinal cord motor neuron diseases affect lower motor neurons in the ventral horn. This article focuses on the most common spinal cord motor neuron disease, amyotrophic lateral sclerosis, which also affects upper motor neurons. Also discussed are other motor neuron diseases that only affect the lower motor neurons. Despite the identification of several genes associated with familial amyotrophic lateral sclerosis, the pathogenesis of this complex disease remains elusive. Copyright © 2013 Elsevier Inc. All rights reserved.

  13. Chaos synchronization of coupled neurons with gap junctions

    International Nuclear Information System (INIS)

    Wang Qingyun; Lu Qishao; Chen Guanrong; Guo Dinghui

    2006-01-01

    Based on the asymptotic stability theory of dynamical systems and matrix theory, a general criterion of synchronization stability of N coupled neurons with symmetric configurations is established in this Letter. Especially, three types of connection styles (that is, chain, ring and global connections) are considered. As an illustration, complete synchronization of four coupled identical chaotic Chay neurons is investigated. The maximal conditional Lyapunov exponent is calculated and used to determine complete synchronization. As a result, complete synchronization of four coupled identical chaotic Chay neurons can be achieved when the coupling strength is above a critical value, which is dependent on the specific connection style. Numerical simulation is in good agreement with the theoretical analysis

  14. Neuronal Networks on Nanocellulose Scaffolds.

    Science.gov (United States)

    Jonsson, Malin; Brackmann, Christian; Puchades, Maja; Brattås, Karoline; Ewing, Andrew; Gatenholm, Paul; Enejder, Annika

    2015-11-01

    Proliferation, integration, and neurite extension of PC12 cells, a widely used culture model for cholinergic neurons, were studied in nanocellulose scaffolds biosynthesized by Gluconacetobacter xylinus to allow a three-dimensional (3D) extension of neurites better mimicking neuronal networks in tissue. The interaction with control scaffolds was compared with cationized nanocellulose (trimethyl ammonium betahydroxy propyl [TMAHP] cellulose) to investigate the impact of surface charges on the cell interaction mechanisms. Furthermore, coatings with extracellular matrix proteins (collagen, fibronectin, and laminin) were investigated to determine the importance of integrin-mediated cell attachment. Cell proliferation was evaluated by a cellular proliferation assay, while cell integration and neurite propagation were studied by simultaneous label-free Coherent anti-Stokes Raman Scattering and second harmonic generation microscopy, providing 3D images of PC12 cells and arrangement of nanocellulose fibrils, respectively. Cell attachment and proliferation were enhanced by TMAHP modification, but not by protein coating. Protein coating instead promoted active interaction between the cells and the scaffold, hence lateral cell migration and integration. Irrespective of surface modification, deepest cell integration measured was one to two cell layers, whereas neurites have a capacity to integrate deeper than the cell bodies in the scaffold due to their fine dimensions and amoeba-like migration pattern. Neurites with lengths of >50 μm were observed, successfully connecting individual cells and cell clusters. In conclusion, TMAHP-modified nanocellulose scaffolds promote initial cellular scaffold adhesion, which combined with additional cell-scaffold treatments enables further formation of 3D neuronal networks.

  15. Neuronal-glial trafficking

    International Nuclear Information System (INIS)

    Bachelard, H.S.

    2001-01-01

    Full text: The name 'glia' originates from the Greek word for glue, because astro glia (or astrocytes) were thought only to provide an anatomical framework for the electrically-excitable neurones. However, awareness that astrocytes perform vital roles in protecting the neurones, which they surround, emerged from evidence that they act as neuroprotective K + -sinks, and that they remove potentially toxic extracellular glutamate from the vicinity of the neurones. The astrocytes convert the glutamate to non-toxic glutamine which is returned to the neurones and used to replenish transmitter glutamate. This 'glutamate-glutamine cycle' (established in the 1960s by Berl and his colleagues) also contributes to protecting the neurones against a build-up of toxic ammonia. Glial cells also supply the neurones with components for free-radical scavenging glutathione. Recent studies have revealed that glial cells play a more positive interactive role in furnishing the neurones with fuels. Studies using radioactive 14 C, 13 C-MRS and 15 N-GCMS have revealed that glia produce alanine, lactate and proline for consumption by neurones, with increased formation of neurotransmitter glutamate. On neuronal activation the release of NH 4 + and glutamate from the neurones stimulates glucose uptake and glycolysis in the glia to produce more alanine, which can be regarded as an 'alanine-glutamate cycle' Use of 14 C-labelled precursors provided early evidence that neurotransmitter GABA may be partly derived from glial glutamine, and this has been confirmed recently in vivo by MRS isotopomer analysis of the GABA and glutamine labelled from 13 C-acetate. Relative rates of intermediary metabolism in glia and neurones can be calculated using a combination of [1- 13 C] glucose and [1,2- 13 C] acetate. When glutamate is released by neurones there is a net neuronal loss of TCA intermediates which have to be replenished. Part of this is derived from carboxylation of pyruvate, (pyruvate carboxylase

  16. The interplay between neurons and glia in synapse development and plasticity.

    Science.gov (United States)

    Stogsdill, Jeff A; Eroglu, Cagla

    2017-02-01

    In the brain, the formation of complex neuronal networks amenable to experience-dependent remodeling is complicated by the diversity of neurons and synapse types. The establishment of a functional brain depends not only on neurons, but also non-neuronal glial cells. Glia are in continuous bi-directional communication with neurons to direct the formation and refinement of synaptic connectivity. This article reviews important findings, which uncovered cellular and molecular aspects of the neuron-glia cross-talk that govern the formation and remodeling of synapses and circuits. In vivo evidence demonstrating the critical interplay between neurons and glia will be the major focus. Additional attention will be given to how aberrant communication between neurons and glia may contribute to neural pathologies. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Local probing and stimulation of neuronal cells by optical manipulation

    Science.gov (United States)

    Cojoc, Dan

    2014-09-01

    During development and in the adult brain, neurons continuously explore the environment searching for guidance cues, leading to the appropriate connections. Elucidating these mechanisms represents a gold goal in neurobiology. Here, I discuss our recent achievements developing new approaches to locally probe the growth cones and stimulate neuronal cell compartments with high spatial and temporal resolution. Optical tweezers force spectroscopy applied in conjunction with metabolic inhibitors reveals new properties of the cytoskeleton dynamics. On the other hand, using optically manipulated microvectors as functionalized beads or filled liposomes, we demonstrate focal stimulation of neurons by small number of signaling molecules.

  18. Dynamic effective connectivity of inter-areal brain circuits.

    Directory of Open Access Journals (Sweden)

    Demian Battaglia

    Full Text Available Anatomic connections between brain areas affect information flow between neuronal circuits and the synchronization of neuronal activity. However, such structural connectivity does not coincide with effective connectivity (or, more precisely, causal connectivity, related to the elusive question "Which areas cause the present activity of which others?". Effective connectivity is directed and depends flexibly on contexts and tasks. Here we show that dynamic effective connectivity can emerge from transitions in the collective organization of coherent neural activity. Integrating simulation and semi-analytic approaches, we study mesoscale network motifs of interacting cortical areas, modeled as large random networks of spiking neurons or as simple rate units. Through a causal analysis of time-series of model neural activity, we show that different dynamical states generated by a same structural connectivity motif correspond to distinct effective connectivity motifs. Such effective motifs can display a dominant directionality, due to spontaneous symmetry breaking and effective entrainment between local brain rhythms, although all connections in the considered structural motifs are reciprocal. We show then that transitions between effective connectivity configurations (like, for instance, reversal in the direction of inter-areal interactions can be triggered reliably by brief perturbation inputs, properly timed with respect to an ongoing local oscillation, without the need for plastic synaptic changes. Finally, we analyze how the information encoded in spiking patterns of a local neuronal population is propagated across a fixed structural connectivity motif, demonstrating that changes in the active effective connectivity regulate both the efficiency and the directionality of information transfer. Previous studies stressed the role played by coherent oscillations in establishing efficient communication between distant areas. Going beyond these early

  19. Feedforward and feedback inhibition in neostriatal GABAergic spiny neurons.

    Science.gov (United States)

    Tepper, James M; Wilson, Charles J; Koós, Tibor

    2008-08-01

    There are two distinct inhibitory GABAergic circuits in the neostriatum. The feedforward circuit consists of a relatively small population of GABAergic interneurons that receives excitatory input from the neocortex and exerts monosynaptic inhibition onto striatal spiny projection neurons. The feedback circuit comprises the numerous spiny projection neurons and their interconnections via local axon collaterals. This network has long been assumed to provide the majority of striatal GABAergic inhibition and to sharpen and shape striatal output through lateral inhibition, producing increased activity in the most strongly excited spiny cells at the expense of their less strongly excited neighbors. Recent results, mostly from recording experiments of synaptically connected pairs of neurons, have revealed that the two GABAergic circuits differ markedly in terms of the total number of synapses made by each, the strength of the postsynaptic response detected at the soma, the extent of presynaptic convergence and divergence and the net effect of the activation of each circuit on the postsynaptic activity of the spiny neuron. These data have revealed that the feedforward inhibition is powerful and widespread, with spiking in a single interneuron being capable of significantly delaying or even blocking the generation of spikes in a large number of postsynaptic spiny neurons. In contrast, the postsynaptic effects of spiking in a single presynaptic spiny neuron on postsynaptic spiny neurons are weak when measured at the soma, and unable to significantly affect spike timing or generation. Further, reciprocity of synaptic connections between spiny neurons is only rarely observed. These results suggest that the bulk of the fast inhibition that has the strongest effects on spiny neuron spike timing comes from the feedforward interneuronal system whereas the axon collateral feedback system acts principally at the dendrites to control local excitability as well as the overall level of

  20. 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

  1. Mesmerising mirror neurons.

    Science.gov (United States)

    Heyes, Cecilia

    2010-06-01

    Mirror neurons have been hailed as the key to understanding social cognition. I argue that three currents of thought-relating to evolution, atomism and telepathy-have magnified the perceived importance of mirror neurons. When they are understood to be a product of associative learning, rather than an adaptation for social cognition, mirror neurons are no longer mesmerising, but they continue to raise important questions about both the psychology of science and the neural bases of social cognition. Copyright 2010 Elsevier Inc. All rights reserved.

  2. The mirror neuron system.

    Science.gov (United States)

    Cattaneo, Luigi; Rizzolatti, Giacomo

    2009-05-01

    Mirror neurons are a class of neurons, originally discovered in the premotor cortex of monkeys, that discharge both when individuals perform a given motor act and when they observe others perform that same motor act. Ample evidence demonstrates the existence of a cortical network with the properties of mirror neurons (mirror system) in humans. The human mirror system is involved in understanding others' actions and their intentions behind them, and it underlies mechanisms of observational learning. Herein, we will discuss the clinical implications of the mirror system.

  3. Dynamical Encoding by Networks of Competing Neuron Groups: Winnerless Competition

    International Nuclear Information System (INIS)

    Rabinovich, M.; Volkovskii, A.; Lecanda, P.; Huerta, R.; Abarbanel, H. D. I.; Laurent, G.

    2001-01-01

    Following studies of olfactory processing in insects and fish, we investigate neural networks whose dynamics in phase space is represented by orbits near the heteroclinic connections between saddle regions (fixed points or limit cycles). These networks encode input information as trajectories along the heteroclinic connections. If there are N neurons in the network, the capacity is approximately e(N-1) ! , i.e., much larger than that of most traditional network structures. We show that a small winnerless competition network composed of FitzHugh-Nagumo spiking neurons efficiently transforms input information into a spatiotemporal output

  4. Detecting Functional Connectivity During Audiovisual Integration with MEG: A Comparison of Connectivity Metrics.

    Science.gov (United States)

    Ard, Tyler; Carver, Frederick W; Holroyd, Tom; Horwitz, Barry; Coppola, Richard

    2015-08-01

    In typical magnetoencephalography and/or electroencephalography functional connectivity analysis, researchers select one of several methods that measure a relationship between regions to determine connectivity, such as coherence, power correlations, and others. However, it is largely unknown if some are more suited than others for various types of investigations. In this study, the authors investigate seven connectivity metrics to evaluate which, if any, are sensitive to audiovisual integration by contrasting connectivity when tracking an audiovisual object versus connectivity when tracking a visual object uncorrelated with the auditory stimulus. The authors are able to assess the metrics' performances at detecting audiovisual integration by investigating connectivity between auditory and visual areas. Critically, the authors perform their investigation on a whole-cortex all-to-all mapping, avoiding confounds introduced in seed selection. The authors find that amplitude-based connectivity measures in the beta band detect strong connections between visual and auditory areas during audiovisual integration, specifically between V4/V5 and auditory cortices in the right hemisphere. Conversely, phase-based connectivity measures in the beta band as well as phase and power measures in alpha, gamma, and theta do not show connectivity between audiovisual areas. The authors postulate that while beta power correlations detect audiovisual integration in the current experimental context, it may not always be the best measure to detect connectivity. Instead, it is likely that the brain utilizes a variety of mechanisms in neuronal communication that may produce differential types of temporal relationships.

  5. [Functional organization and structure of the serotonergic neuronal network of terrestrial snail].

    Science.gov (United States)

    Nikitin, E S; Balaban, P M

    2011-01-01

    The extension of knowledge how the brain works requires permanent improvement of methods of recording of neuronal activity and increase in the number of neurons recorded simultaneously to better understand the collective work of neuronal networks and assemblies. Conventional methods allow simultaneous intracellular recording up to 2-5 neurons and their membrane potentials, currents or monosynaptic connections or observation of spiking of neuronal groups with subsequent discrimination of individual spikes with loss of details of the dynamics of membrane potential. We recorded activity of a compact group of serotonergic neurons (up to 56 simultaneously) in the ganglion of a terrestrial mollusk using the method of optical recording of membrane potential that allowed to record individual action potentials in details with action potential parameters and to reveal morphology of the neurons rcorded. We demonstrated clear clustering in the group in relation with the dynamics of action potentials and phasic or tonic components in the neuronal responses to external electrophysiological and tactile stimuli. Also, we showed that identified neuron Pd2 could induce activation of a significant number of neurons in the group whereas neuron Pd4 did not induce any activation. However, its activation is delayed with regard to activation of the reacting group of neurons. Our data strongly support the concept of possible delegation of the integrative function by the network to a single neuron.

  6. Membrane potential dye imaging of ventromedial hypothalamus neurons from adult mice to study glucose sensing.

    Science.gov (United States)

    Vazirani, Reema P; Fioramonti, Xavier; Routh, Vanessa H

    2013-11-27

    Studies of neuronal activity are often performed using neurons from rodents less than 2 months of age due to the technical difficulties associated with increasing connective tissue and decreased neuronal viability that occur with age. Here, we describe a methodology for the dissociation of healthy hypothalamic neurons from adult-aged mice. The ability to study neurons from adult-aged mice allows the use of disease models that manifest at a later age and might be more developmentally accurate for certain studies. Fluorescence imaging of dissociated neurons can be used to study the activity of a population of neurons, as opposed to using electrophysiology to study a single neuron. This is particularly useful when studying a heterogeneous neuronal population in which the desired neuronal type is rare such as for hypothalamic glucose sensing neurons. We utilized membrane potential dye imaging of adult ventromedial hypothalamic neurons to study their responses to changes in extracellular glucose. Glucose sensing neurons are believed to play a role in central regulation of energy balance. The ability to study glucose sensing in adult rodents is particularly useful since the predominance of diseases related to dysfunctional energy balance (e.g. obesity) increase with age.

  7. Extracting functionally feedforward networks from a population of spiking neurons.

    Science.gov (United States)

    Vincent, Kathleen; Tauskela, Joseph S; Thivierge, Jean-Philippe

    2012-01-01

    Neuronal avalanches are a ubiquitous form of activity characterized by spontaneous bursts whose size distribution follows a power-law. Recent theoretical models have replicated power-law avalanches by assuming the presence of functionally feedforward connections (FFCs) in the underlying dynamics of the system. Accordingly, avalanches are generated by a feedforward chain of activation that persists despite being embedded in a larger, massively recurrent circuit. However, it is unclear to what extent networks of living neurons that exhibit power-law avalanches rely on FFCs. Here, we employed a computational approach to reconstruct the functional connectivity of cultured cortical neurons plated on multielectrode arrays (MEAs) and investigated whether pharmacologically induced alterations in avalanche dynamics are accompanied by changes in FFCs. This approach begins by extracting a functional network of directed links between pairs of neurons, and then evaluates the strength of FFCs using Schur decomposition. In a first step, we examined the ability of this approach to extract FFCs from simulated spiking neurons. The strength of FFCs obtained in strictly feedforward networks diminished monotonically as links were gradually rewired at random. Next, we estimated the FFCs of spontaneously active cortical neuron cultures in the presence of either a control medium, a GABA(A) receptor antagonist (PTX), or an AMPA receptor antagonist combined with an NMDA receptor antagonist (APV/DNQX). The distribution of avalanche sizes in these cultures was modulated by this pharmacology, with a shallower power-law under PTX (due to the prominence of larger avalanches) and a steeper power-law under APV/DNQX (due to avalanches recruiting fewer neurons) relative to control cultures. The strength of FFCs increased in networks after application of PTX, consistent with an amplification of feedforward activity during avalanches. Conversely, FFCs decreased after application of APV

  8. [The detector, the command neuron and plastic convergence].

    Science.gov (United States)

    Sokolov, E N

    1977-01-01

    The paper deals with the structure of detectors, the function of commanding neurones and the problem of relationship between detectors and commanding neurons. An example of hierarchial organization of detectors is provided by the colour analyser in which a layer of receptors, a layer of opponent neurones and a layer of colour-selective detectors are singled out. The colour detector is selectively sensitive to a certain combination of excitations at the input. If the detector is selectively activated by a certain combination of excitations at the input, the selective activation of the commanding neurone through a pool of motoneurones brings about a reaction at the output, specific in its organization. The reflexogenic zone of the reaction is determined by the detectors which converge on the commanding neurone controlling the given reaction. The plasticity of the reaction results from a plastic convergence of the detectors on the commanding neurone which controls the reaction. This comprises selective switching off the detectors from the commanding neurone (habituation) and connecting the detectors to the commanding neurone (facilitation).

  9. Regulatory Mechanisms Controlling Maturation of Serotonin Neuron Identity and Function.

    Science.gov (United States)

    Spencer, William C; Deneris, Evan S

    2017-01-01

    The brain serotonin (5-hydroxytryptamine; 5-HT) system has been extensively studied for its role in normal physiology and behavior, as well as, neuropsychiatric disorders. The broad influence of 5-HT on brain function, is in part due to the vast connectivity pattern of 5-HT-producing neurons throughout the CNS. 5-HT neurons are born and terminally specified midway through embryogenesis, then enter a protracted period of maturation, where they functionally integrate into CNS circuitry and then are maintained throughout life. The transcriptional regulatory networks controlling progenitor cell generation and terminal specification of 5-HT neurons are relatively well-understood, yet the factors controlling 5-HT neuron maturation are only recently coming to light. In this review, we first provide an update on the regulatory network controlling 5-HT neuron development, then delve deeper into the properties and regulatory strategies governing 5-HT neuron maturation. In particular, we discuss the role of the 5-HT neuron terminal selector transcription factor (TF) Pet-1 as a key regulator of 5-HT neuron maturation. Pet-1 was originally shown to positively regulate genes needed for 5-HT synthesis, reuptake and vesicular transport, hence 5-HT neuron-type transmitter identity. It has now been shown to regulate, both positively and negatively, many other categories of genes in 5-HT neurons including ion channels, GPCRs, transporters, neuropeptides, and other transcription factors. Its function as a terminal selector results in the maturation of 5-HT neuron excitability, firing characteristics, and synaptic modulation by several neurotransmitters. Furthermore, there is a temporal requirement for Pet-1 in the control of postmitotic gene expression trajectories thus indicating a direct role in 5-HT neuron maturation. Proper regulation of the maturation of cellular identity is critical for normal neuronal functioning and perturbations in the gene regulatory networks controlling

  10. Minimum cost connection networks

    DEFF Research Database (Denmark)

    Hougaard, Jens Leth; Tvede, Mich

    In the present paper we consider the allocation of cost in connection networks. Agents have connection demands in form of pairs of locations they want to be connected. Connections between locations are costly to build. The problem is to allocate costs of networks satisfying all connection demands...

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

    DEFF Research Database (Denmark)

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

    2011-01-01

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

  12. The Languages of Neurons: An Analysis of Coding Mechanisms by Which Neurons Communicate, Learn and Store Information

    Directory of Open Access Journals (Sweden)

    Morris H. Baslow

    2009-11-01

    Full Text Available In this paper evidence is provided that individual neurons possess language, and that the basic unit for communication consists of two neurons and their entire field of interacting dendritic and synaptic connections. While information processing in the brain is highly complex, each neuron uses a simple mechanism for transmitting information. This is in the form of temporal electrophysiological action potentials or spikes (S operating on a millisecond timescale that, along with pauses (P between spikes constitute a two letter “alphabet” that generates meaningful frequency-encoded signals or neuronal S/P “words” in a primary language. However, when a word from an afferent neuron enters the dendritic-synaptic-dendritic field between two neurons, it is translated into a new frequency-encoded word with the same meaning, but in a different spike-pause language, that is delivered to and understood by the efferent neuron. It is suggested that this unidirectional inter-neuronal language-based word translation step is of utmost importance to brain function in that it allows for variations in meaning to occur. Thus, structural or biochemical changes in dendrites or synapses can produce novel words in the second language that have changed meanings, allowing for a specific signaling experience, either external or internal, to modify the meaning of an original word (learning, and store the learned information of that experience (memory in the form of an altered dendritic-synaptic-dendritic field.

  13. Afferent neuronal control of type-I gonadotropin releasing hormone (GnRH neurons in the human

    Directory of Open Access Journals (Sweden)

    Erik eHrabovszky

    2013-09-01

    Full Text Available Understanding the regulation of the human menstrual cycle represents an important ultimate challenge of reproductive neuroendocrine research. However, direct translation of information from laboratory animal experiments to the human is often complicated by strikingly different and unique reproductive strategies and central regulatory mechanisms that can be present in even closely related animal species. In all mammals studied so far, type-I gonadotropin releasing hormone (GnRH synthesizing neurons form the final common output way from the hypothalamus in the neuroendocrine control of the adenohypophysis. Under various physiological and pathological conditions, hormonal and metabolic signals either regulate GnRH neurons directly or act on upstream neuronal circuitries to influence the pattern of pulsatile GnRH secretion into the hypophysial portal circulation. Neuronal afferents to GnRH cells convey important metabolic-, stress-, sex steroid-, lactational- and circadian signals to the reproductive axis, among other effects. This article gives an overview of the available neuroanatomical literature that described the afferent regulation of human GnRH neurons by peptidergic, monoaminergic and amino acidergic neuronal systems. Recent studies of human genetics provided evidence that central peptidergic signaling by kisspeptins and neurokinin B play particularly important roles in puberty onset and later, in the sex steroid-dependent feedback regulation of GnRH neurons. This review article places special emphasis on the topographic distribution, sexual dimorphism, aging-dependent neuroanatomical changes and plastic connectivity to GnRH neurons of the critically important human hypothalamic kisspeptin and neurokinin B systems.

  14. Roles of octopaminergic and dopaminergic neurons in appetitive and aversive memory recall in an insect.

    Science.gov (United States)

    Mizunami, Makoto; Unoki, Sae; Mori, Yasuhiro; Hirashima, Daisuke; Hatano, Ai; Matsumoto, Yukihisa

    2009-08-04

    In insect classical conditioning, octopamine (the invertebrate counterpart of noradrenaline) or dopamine has been suggested to mediate reinforcing properties of appetitive or aversive unconditioned stimulus, respectively. However, the roles of octopaminergic and dopaminergic neurons in memory recall have remained unclear. We studied the roles of octopaminergic and dopaminergic neurons in appetitive and aversive memory recall in olfactory and visual conditioning in crickets. We found that pharmacological blockade of octopamine and dopamine receptors impaired aversive memory recall and appetitive memory recall, respectively, thereby suggesting that activation of octopaminergic and dopaminergic neurons and the resulting release of octopamine and dopamine are needed for appetitive and aversive memory recall, respectively. On the basis of this finding, we propose a new model in which it is assumed that two types of synaptic connections are formed by conditioning and are activated during memory recall, one type being connections from neurons representing conditioned stimulus to neurons inducing conditioned response and the other being connections from neurons representing conditioned stimulus to octopaminergic or dopaminergic neurons representing appetitive or aversive unconditioned stimulus, respectively. The former is called 'stimulus-response connection' and the latter is called 'stimulus-stimulus connection' by theorists studying classical conditioning in higher vertebrates. Our model predicts that pharmacological blockade of octopamine or dopamine receptors during the first stage of second-order conditioning does not impair second-order conditioning, because it impairs the formation of the stimulus-response connection but not the stimulus-stimulus connection. The results of our study with a cross-modal second-order conditioning were in full accordance with this prediction. We suggest that insect classical conditioning involves the formation of two kinds of memory

  15. Tunneling nanotube (TNT)-mediated neuron-to neuron transfer of pathological Tau protein assemblies

    OpenAIRE

    TARDIVEL , Meryem; Bégard , Séverine; Bousset , Luc; Dujardin , Simon; Coens , Audrey; Melki , Ronald; Buée , Luc; Colin , Morvane

    2016-01-01

    A given cell makes exchanges with its neighbors through a variety of means ranging from diffusible factors to vesicles. Cells use also tunneling nanotubes (TNTs), filamentous-actin-containing membranous structures that bridge and connect cells. First described in immune cells, TNTs facilitate HIV-1 transfer and are found in various cell types, including neurons. We show that the microtubule-associated protein Tau, a key player in Alzheimer?s disease, is a bona fide constituent of TNTs. This i...

  16. Traveling wave front solutions in lateral-excitatory neuronal networks

    Directory of Open Access Journals (Sweden)

    Sittipong Ruktamatakul

    2008-05-01

    Full Text Available In this paper, we discuss the shape of traveling wave front solutions to a neuronal model with the connection function to be of lateral excitation type. This means that close connecting cells have an inhibitory influence, while cells that aremore distant have an excitatory influence. We give results on the shape of the wave fronts solutions, which exhibit different shapes depend ing on the size of a threshold parameter.

  17. Asynchronous Rate Chaos in Spiking Neuronal Circuits.

    Directory of Open Access Journals (Sweden)

    Omri Harish

    2015-07-01

    Full Text Available The brain exhibits temporally complex patterns of activity with features similar to those of chaotic systems. Theoretical studies over the last twenty years have described various computational advantages for such regimes in neuronal systems. Nevertheless, it still remains unclear whether chaos requires specific cellular properties or network architectures, or whether it is a generic property of neuronal circuits. We investigate the dynamics of networks of excitatory-inhibitory (EI spiking neurons with random sparse connectivity operating in the regime of balance of excitation and inhibition. Combining Dynamical Mean-Field Theory with numerical simulations, we show that chaotic, asynchronous firing rate fluctuations emerge generically for sufficiently strong synapses. Two different mechanisms can lead to these chaotic fluctuations. One mechanism relies on slow I-I inhibition which gives rise to slow subthreshold voltage and rate fluctuations. The decorrelation time of these fluctuations is proportional to the time constant of the inhibition. The second mechanism relies on the recurrent E-I-E feedback loop. It requires slow excitation but the inhibition can be fast. In the corresponding dynamical regime all neurons exhibit rate fluctuations on the time scale of the excitation. Another feature of this regime is that the population-averaged firing rate is substantially smaller in the excitatory population than in the inhibitory population. This is not necessarily the case in the I-I mechanism. Finally, we discuss the neurophysiological and computational significance of our results.

  18. Asynchronous Rate Chaos in Spiking Neuronal Circuits

    Science.gov (United States)

    Harish, Omri; Hansel, David

    2015-01-01

    The brain exhibits temporally complex patterns of activity with features similar to those of chaotic systems. Theoretical studies over the last twenty years have described various computational advantages for such regimes in neuronal systems. Nevertheless, it still remains unclear whether chaos requires specific cellular properties or network architectures, or whether it is a generic property of neuronal circuits. We investigate the dynamics of networks of excitatory-inhibitory (EI) spiking neurons with random sparse connectivity operating in the regime of balance of excitation and inhibition. Combining Dynamical Mean-Field Theory with numerical simulations, we show that chaotic, asynchronous firing rate fluctuations emerge generically for sufficiently strong synapses. Two different mechanisms can lead to these chaotic fluctuations. One mechanism relies on slow I-I inhibition which gives rise to slow subthreshold voltage and rate fluctuations. The decorrelation time of these fluctuations is proportional to the time constant of the inhibition. The second mechanism relies on the recurrent E-I-E feedback loop. It requires slow excitation but the inhibition can be fast. In the corresponding dynamical regime all neurons exhibit rate fluctuations on the time scale of the excitation. Another feature of this regime is that the population-averaged firing rate is substantially smaller in the excitatory population than in the inhibitory population. This is not necessarily the case in the I-I mechanism. Finally, we discuss the neurophysiological and computational significance of our results. PMID:26230679

  19. Neuronal avalanches and learning

    Energy Technology Data Exchange (ETDEWEB)

    Arcangelis, Lucilla de, E-mail: dearcangelis@na.infn.it [Department of Information Engineering and CNISM, Second University of Naples, 81031 Aversa (Italy)

    2011-05-01

    Networks of living neurons represent one of the most fascinating systems of biology. If the physical and chemical mechanisms at the basis of the functioning of a single neuron are quite well understood, the collective behaviour of a system of many neurons is an extremely intriguing subject. Crucial ingredient of this complex behaviour is the plasticity property of the network, namely the capacity to adapt and evolve depending on the level of activity. This plastic ability is believed, nowadays, to be at the basis of learning and memory in real brains. Spontaneous neuronal activity has recently shown features in common to other complex systems. Experimental data have, in fact, shown that electrical information propagates in a cortex slice via an avalanche mode. These avalanches are characterized by a power law distribution for the size and duration, features found in other problems in the context of the physics of complex systems and successful models have been developed to describe their behaviour. In this contribution we discuss a statistical mechanical model for the complex activity in a neuronal network. The model implements the main physiological properties of living neurons and is able to reproduce recent experimental results. Then, we discuss the learning abilities of this neuronal network. Learning occurs via plastic adaptation of synaptic strengths by a non-uniform negative feedback mechanism. The system is able to learn all the tested rules, in particular the exclusive OR (XOR) and a random rule with three inputs. The learning dynamics exhibits universal features as function of the strength of plastic adaptation. Any rule could be learned provided that the plastic adaptation is sufficiently slow.

  20. Neuronal avalanches and learning

    International Nuclear Information System (INIS)

    Arcangelis, Lucilla de

    2011-01-01

    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.

  1. Respiratory Neuron Activity in the Mesencephalon, Diencephalon and Cerebellum of the Carp

    NARCIS (Netherlands)

    Ballintijn, C.M.; Luiten, P.G.M.; Jüch, P.J.W.

    1979-01-01

    The functional properties, localization and connections of neurons with a respiratory-rhythmic firing pattern in the mesencephalon, diencephalon and cerebellum of the carp were studied. Some neurons acquire respiratory rhythm only as a side effect of respiration via sensory stimulation by movements

  2. Cross-interval histogram analysis of neuronal activity on multi-electrode arrays

    NARCIS (Netherlands)

    Castellone, P.; Rutten, Wim; Marani, Enrico

    2003-01-01

    Cross-neuron-interval histogram (CNIH) analysis has been performed in order to study correlated activity and connectivity between pairs of neurons in a spontaneously active developing cultured network of rat cortical cells. Thirty-eight histograms could be analyzed using two parameters, one for the

  3. Associative learning is necessary but not sufficient for mirror neuron development

    OpenAIRE

    Bonaiuto, James

    2014-01-01

    Existing computational models of the mirror system demonstrate the additional circuitry needed for mirror neurons to display the range of properties that they exhibit. Such models emphasize the need for existing connectivity to form visuomotor associations, processing to reduce the space of possible inputs, and demonstrate the role neurons with mirror properties might play in monitoring one's own actions.

  4. Associative learning is necessary but not sufficient for mirror neuron development.

    Science.gov (United States)

    Bonaiuto, James

    2014-04-01

    Existing computational models of the mirror system demonstrate the additional circuitry needed for mirror neurons to display the range of properties that they exhibit. Such models emphasize the need for existing connectivity to form visuomotor associations, processing to reduce the space of possible inputs, and demonstrate the role neurons with mirror properties might play in monitoring one's own actions.

  5. DISSECTING HABITAT CONNECTIVITY

    Science.gov (United States)

    abstractConnectivity is increasingly recognized as an important element of a successful reserve design. Connectivity matters in reserve design to the extent that it promotes or hinders the viability of target populations. While conceptually straightforward, connectivity i...

  6. Mixed Connective Tissue Disease

    Science.gov (United States)

    Mixed connective tissue disease Overview Mixed connective tissue disease has signs and symptoms of a combination of disorders — primarily lupus, scleroderma and polymyositis. For this reason, mixed connective tissue disease ...

  7. Undifferentiated Connective Tissue Disease

    Science.gov (United States)

    ... Home Conditions Undifferentiated Connective Tissue Disease (UCTD) Undifferentiated Connective Tissue Disease (UCTD) Make an Appointment Find a Doctor ... by Barbara Goldstein, MD (February 01, 2016) Undifferentiated connective tissue disease (UCTD) is a systemic autoimmune disease. This ...

  8. Robust emergence of small-world structure in networks of spiking neurons.

    Science.gov (United States)

    Kwok, Hoi Fei; Jurica, Peter; Raffone, Antonino; van Leeuwen, Cees

    2007-03-01

    Spontaneous activity in biological neural networks shows patterns of dynamic synchronization. We propose that these patterns support the formation of a small-world structure-network connectivity optimal for distributed information processing. We present numerical simulations with connected Hindmarsh-Rose neurons in which, starting from random connection distributions, small-world networks evolve as a result of applying an adaptive rewiring rule. The rule connects pairs of neurons that tend fire in synchrony, and disconnects ones that fail to synchronize. Repeated application of the rule leads to small-world structures. This mechanism is robustly observed for bursting and irregular firing regimes.

  9. An FPGA-based silicon neuronal network with selectable excitability silicon neurons

    Directory of Open Access Journals (Sweden)

    Jing eLi

    2012-12-01

    Full Text Available This paper presents a digital silicon neuronal network which simulates the nerve system in creatures and has the ability to execute intelligent tasks, such as associative memory. Two essential elements, the mathematical-structure-based digital spiking silicon neuron (DSSN and the transmitter release based silicon synapse, allow the network to show rich dynamic behaviors and are computationally efficient for hardware implementation. We adopt mixed pipeline and parallel structure and shift operations to design a sufficient large and complex network without excessive hardware resource cost. The network with $256$ full-connected neurons is built on a Digilent Atlys board equipped with a Xilinx Spartan-6 LX45 FPGA. Besides, a memory control block and USB control block are designed to accomplish the task of data communication between the network and the host PC. This paper also describes the mechanism of associative memory performed in the silicon neuronal network. The network is capable of retrieving stored patterns if the inputs contain enough information of them. The retrieving probability increases with the similarity between the input and the stored pattern increasing. Synchronization of neurons is observed when the successful stored pattern retrieval occurs.

  10. Signal transfer within a cultured asymmetric cortical neuron circuit.

    Science.gov (United States)

    Isomura, Takuya; Shimba, Kenta; Takayama, Yuzo; Takeuchi, Akimasa; Kotani, Kiyoshi; Jimbo, Yasuhiko

    2015-12-01

    Simplified neuronal circuits are required for investigating information representation in nervous systems and for validating theoretical neural network models. Here, we developed patterned neuronal circuits using micro fabricated devices, comprising a micro-well array bonded to a microelectrode-array substrate. The micro-well array consisted of micrometre-scale wells connected by tunnels, all contained within a silicone slab called a micro-chamber. The design of the micro-chamber confined somata to the wells and allowed axons to grow through the tunnels bidirectionally but with a designed, unidirectional bias. We guided axons into the point of the arrow structure where one of the two tunnel entrances is located, making that the preferred direction. When rat cortical neurons were cultured in the wells, their axons grew through the tunnels and connected to neurons in adjoining wells. Unidirectional burst transfers and other asymmetric signal-propagation phenomena were observed via the substrate-embedded electrodes. Seventy-nine percent of burst transfers were in the forward direction. We also observed rapid propagation of activity from sites of local electrical stimulation, and significant effects of inhibitory synapse blockade on bursting activity. These results suggest that this simple, substrate-controlled neuronal circuit can be applied to develop in vitro models of the function of cortical microcircuits or deep neural networks, better to elucidate the laws governing the dynamics of neuronal networks.

  11. Inverse stochastic resonance in networks of spiking neurons.

    Science.gov (United States)

    Uzuntarla, Muhammet; Barreto, Ernest; Torres, Joaquin J

    2017-07-01

    Inverse Stochastic Resonance (ISR) is a phenomenon in which the average spiking rate of a neuron exhibits a minimum with respect to noise. ISR has been studied in individual neurons, but here, we investigate ISR in scale-free networks, where the average spiking rate is calculated over the neuronal population. We use Hodgkin-Huxley model neurons with channel noise (i.e., stochastic gating variable dynamics), and the network connectivity is implemented via electrical or chemical connections (i.e., gap junctions or excitatory/inhibitory synapses). We find that the emergence of ISR depends on the interplay between each neuron's intrinsic dynamical structure, channel noise, and network inputs, where the latter in turn depend on network structure parameters. We observe that with weak gap junction or excitatory synaptic coupling, network heterogeneity and sparseness tend to favor the emergence of ISR. With inhibitory coupling, ISR is quite robust. We also identify dynamical mechanisms that underlie various features of this ISR behavior. Our results suggest possible ways of experimentally observing ISR in actual neuronal systems.

  12. Signal transfer within a cultured asymmetric cortical neuron circuit

    Science.gov (United States)

    Isomura, Takuya; Shimba, Kenta; Takayama, Yuzo; Takeuchi, Akimasa; Kotani, Kiyoshi; Jimbo, Yasuhiko

    2015-12-01

    Objective. Simplified neuronal circuits are required for investigating information representation in nervous systems and for validating theoretical neural network models. Here, we developed patterned neuronal circuits using micro fabricated devices, comprising a micro-well array bonded to a microelectrode-array substrate. Approach. The micro-well array consisted of micrometre-scale wells connected by tunnels, all contained within a silicone slab called a micro-chamber. The design of the micro-chamber confined somata to the wells and allowed axons to grow through the tunnels bidirectionally but with a designed, unidirectional bias. We guided axons into the point of the arrow structure where one of the two tunnel entrances is located, making that the preferred direction. Main results. When rat cortical neurons were cultured in the wells, their axons grew through the tunnels and connected to neurons in adjoining wells. Unidirectional burst transfers and other asymmetric signal-propagation phenomena were observed via the substrate-embedded electrodes. Seventy-nine percent of burst transfers were in the forward direction. We also observed rapid propagation of activity from sites of local electrical stimulation, and significant effects of inhibitory synapse blockade on bursting activity. Significance. These results suggest that this simple, substrate-controlled neuronal circuit can be applied to develop in vitro models of the function of cortical microcircuits or deep neural networks, better to elucidate the laws governing the dynamics of neuronal networks.

  13. The Age of Enlightenment: Evolving Opportunities in Brain Research Through Optical Manipulation of Neuronal Activity

    OpenAIRE

    Jerome, Jason; Heck, Detlef H.

    2011-01-01

    Optical manipulation of neuronal activity has rapidly developed into the most powerful and widely used approach to study mechanisms related to neuronal connectivity over a range of scales. Since the early use of single site uncaging to map network connectivity, rapid technological development of light modulation techniques has added important new options, such as fast scanning photostimulation, massively parallel control of light stimuli, holographic uncaging, and two-photon stimulation techn...

  14. Intermodal Passenger Connectivity Database -

    Data.gov (United States)

    Department of Transportation — The Intermodal Passenger Connectivity Database (IPCD) is a nationwide data table of passenger transportation terminals, with data on the availability of connections...

  15. Production and survival of projection neurons in a forebrain vocal center of adult male canaries

    International Nuclear Information System (INIS)

    Kirn, J.R.; Alvarez-Buylla, A.; Nottebohm, F.

    1991-01-01

    Neurons are produced in the adult canary telencephalon. Many of these cells are incorporated into the high vocal center (nucleus HVC), which participates in the control of learned song. In the present work, 3H-thymidine and fluorogold were employed to follow the differentiation and survival of HVC neurons born in adulthood. We found that many HVC neurons born in September grow long axons to the robust nucleus of the archistriatum (nucleus RA) and thus become part of the efferent pathway for song control. Many of these new neurons have already established their connections with RA by 30 d after their birth. By 240 d, 75-80% of the September-born HVC neurons project to RA. Most of these new projection neurons survive at least 8 months. The longevity of HVC neurons born in September suggests that these cells remain part of the vocal control circuit long enough to participate in the yearly renewal of the song repertoire

  16. Glucose rapidly induces different forms of excitatory synaptic plasticity in hypothalamic POMC neurons.

    Directory of Open Access Journals (Sweden)

    Jun Hu

    Full Text Available Hypothalamic POMC neurons are required for glucose and energy homeostasis. POMC neurons have a wide synaptic connection with neurons both within and outside the hypothalamus, and their activity is controlled by a balance between excitatory and inhibitory synaptic inputs. Brain glucose-sensing plays an essential role in the maintenance of normal body weight and metabolism; however, the effect of glucose on synaptic transmission in POMC neurons is largely unknown. Here we identified three types of POMC neurons (EPSC(+, EPSC(-, and EPSC(+/- based on their glucose-regulated spontaneous excitatory postsynaptic currents (sEPSCs, using whole-cell patch-clamp recordings. Lowering extracellular glucose decreased the frequency of sEPSCs in EPSC(+ neurons, but increased it in EPSC(- neurons. Unlike EPSC(+ and EPSC(- neurons, EPSC(+/- neurons displayed a bi-phasic sEPSC response to glucoprivation. In the first phase of glucoprivation, both the frequency and the amplitude of sEPSCs decreased, whereas in the second phase, they increased progressively to the levels above the baseline values. Accordingly, lowering glucose exerted a bi-phasic effect on spontaneous action potentials in EPSC(+/- neurons. Glucoprivation decreased firing rates in the first phase, but increased them in the second phase. These data indicate that glucose induces distinct excitatory synaptic plasticity in different subpopulations of POMC neurons. This synaptic remodeling is likely to regulate the sensitivity of the melanocortin system to neuronal and hormonal signals.

  17. Glucose Rapidly Induces Different Forms of Excitatory Synaptic Plasticity in Hypothalamic POMC Neurons

    Science.gov (United States)

    Hu, Jun; Jiang, Lin; Low, Malcolm J.; Rui, Liangyou

    2014-01-01

    Hypothalamic POMC neurons are required for glucose and energy homeostasis. POMC neurons have a wide synaptic connection with neurons both within and outside the hypothalamus, and their activity is controlled by a balance between excitatory and inhibitory synaptic inputs. Brain glucose-sensing plays an essential role in the maintenance of normal body weight and metabolism; however, the effect of glucose on synaptic transmission in POMC neurons is largely unknown. Here we identified three types of POMC neurons (EPSC(+), EPSC(−), and EPSC(+/−)) based on their glucose-regulated spontaneous excitatory postsynaptic currents (sEPSCs), using whole-cell patch-clamp recordings. Lowering extracellular glucose decreased the frequency of sEPSCs in EPSC(+) neurons, but increased it in EPSC(−) neurons. Unlike EPSC(+) and EPSC(−) neurons, EPSC(+/−) neurons displayed a bi-phasic sEPSC response to glucoprivation. In the first phase of glucoprivation, both the frequency and the amplitude of sEPSCs decreased, whereas in the second phase, they increased progressively to the levels above the baseline values. Accordingly, lowering glucose exerted a bi-phasic effect on spontaneous action potentials in EPSC(+/−) neurons. Glucoprivation decreased firing rates in the first phase, but increased them in the second phase. These data indicate that glucose induces distinct excitatory synaptic plasticity in different subpopulations of POMC neurons. This synaptic remodeling is likely to regulate the sensitivity of the melanocortin system to neuronal and hormonal signals. PMID:25127258

  18. Glucose rapidly induces different forms of excitatory synaptic plasticity in hypothalamic POMC neurons.

    Science.gov (United States)

    Hu, Jun; Jiang, Lin; Low, Malcolm J; Rui, Liangyou

    2014-01-01

    Hypothalamic POMC neurons are required for glucose and energy homeostasis. POMC neurons have a wide synaptic connection with neurons both within and outside the hypothalamus, and their activity is controlled by a balance between excitatory and inhibitory synaptic inputs. Brain glucose-sensing plays an essential role in the maintenance of normal body weight and metabolism; however, the effect of glucose on synaptic transmission in POMC neurons is largely unknown. Here we identified three types of POMC neurons (EPSC(+), EPSC(-), and EPSC(+/-)) based on their glucose-regulated spontaneous excitatory postsynaptic currents (sEPSCs), using whole-cell patch-clamp recordings. Lowering extracellular glucose decreased the frequency of sEPSCs in EPSC(+) neurons, but increased it in EPSC(-) neurons. Unlike EPSC(+) and EPSC(-) neurons, EPSC(+/-) neurons displayed a bi-phasic sEPSC response to glucoprivation. In the first phase of glucoprivation, both the frequency and the amplitude of sEPSCs decreased, whereas in the second phase, they increased progressively to the levels above the baseline values. Accordingly, lowering glucose exerted a bi-phasic effect on spontaneous action potentials in EPSC(+/-) neurons. Glucoprivation decreased firing rates in the first phase, but increased them in the second phase. These data indicate that glucose induces distinct excitatory synaptic plasticity in different subpopulations of POMC neurons. This synaptic remodeling is likely to regulate the sensitivity of the melanocortin system to neuronal and hormonal signals.

  19. Effects of partial time delays on phase synchronization in Watts-Strogatz small-world neuronal networks

    Science.gov (United States)

    Sun, Xiaojuan; Perc, Matjaž; Kurths, Jürgen

    2017-05-01

    In this paper, we study effects of partial time delays on phase synchronization in Watts-Strogatz small-world neuronal networks. Our focus is on the impact of two parameters, namely the time delay τ and the probability of partial time delay pdelay, whereby the latter determines the probability with which a connection between two neurons is delayed. Our research reveals that partial time delays significantly affect phase synchronization in this system. In particular, partial time delays can either enhance or decrease phase synchronization and induce synchronization transitions with changes in the mean firing rate of neurons, as well as induce switching between synchronized neurons with period-1 firing to synchronized neurons with period-2 firing. Moreover, in comparison to a neuronal network where all connections are delayed, we show that small partial time delay probabilities have especially different influences on phase synchronization of neuronal networks.

  20. Kappe neurons, a novel population of olfactory sensory neurons.

    Science.gov (United States)

    Ahuja, Gaurav; Bozorg Nia, Shahrzad; Zapilko, Veronika; Shiriagin, Vladimir; Kowatschew, Daniel; Oka, Yuichiro; Korsching, Sigrun I

    2014-02-10

    Perception of olfactory stimuli is mediated by distinct populations of olfactory sensory neurons, each with a characteristic set of morphological as well as functional parameters. Beyond two large populations of ciliated and microvillous neurons, a third population, crypt neurons, has been identified in teleost and cartilaginous fishes. We report here a novel, fourth olfactory sensory neuron population in zebrafish, which we named kappe neurons for their characteristic shape. Kappe neurons are identified by their Go-like immunoreactivity, and show a distinct spatial distribution within the olfactory epithelium, similar to, but significantly different from that of crypt neurons. Furthermore, kappe neurons project to a single identified target glomerulus within the olfactory bulb, mdg5 of the mediodorsal cluster, whereas crypt neurons are known to project exclusively to the mdg2 glomerulus. Kappe neurons are negative for established markers of ciliated, microvillous and crypt neurons, but appear to have microvilli. Kappe neurons constitute the fourth type of olfactory sensory neurons reported in teleost fishes and their existence suggests that encoding of olfactory stimuli may require a higher complexity than hitherto assumed already in the peripheral olfactory system.

  1. Confounding the origin and function of mirror neurons.

    Science.gov (United States)

    Rizzolatti, Giacomo

    2014-04-01

    Cook et al. argue that mirror neurons originate in sensorimotor associative learning and that their function is determined by their origin. Both these claims are hard to accept. It is here suggested that a major role in the origin of the mirror mechanism is played by top-down connections rather than by associative learning.

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

    Science.gov (United States)

    Jeffers, Carol S.

    2009-01-01

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

  3. Differential labelling of retinal neurones by 3H-2-deoxyglucose

    International Nuclear Information System (INIS)

    Basinger, S.F.; Gordon, W.C.; Lam, D.M.K.

    1979-01-01

    The use of tritium-labelled 2-deoxyglucose in combination with plastic embedding is reported to produce stimulus dependent labelling at cellular level in the isolated goldfish retina. The results suggest that the use of tritium in place of the more usual 14 C labelled tracer is advantageous in studying the physiology and functional connections of retinal neurones. (U.K.)

  4. 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...

  5. Target tissue influences on cholinergic development of parasympathetic motor neurons

    International Nuclear Information System (INIS)

    Tuttle, J.B.; Pilar, G.

    1986-01-01

    The normal function of neurons in the nervous system depends upon the orderly formation and maintenance of appropriate connections with other neurons and with non-neural target tissues. Having formed an appropriate synapse, the authors attempt to find how the interaction influences the subsequent program of neuronal differentiation and survival. The studies were made on neurons from the avian ciliary ganglion and their terminals in the iris. Concomitantly in time with the shift from an embryonic, fatiguable junction to the mature, more secure transmission, there is a large change in the capacity for ACh synthesis measured using radiolableled substrate. Only at this point in development does one detect and increase in the amount of tritium-ACh synthesized from tritium-choline in response to a pre-conditioning depolarization. The studies of development in vivo have provided a description of the steps taking place during maturation of a neuromuscular junction

  6. Regulation of neuronal communication by G protein-coupled receptors.

    Science.gov (United States)

    Huang, Yunhong; Thathiah, Amantha

    2015-06-22

    Neuronal communication plays an essential role in the propagation of information in the brain and requires a precisely orchestrated connectivity between neurons. Synaptic transmission is the mechanism through which neurons communicate with each other. It is a strictly regulated process which involves membrane depolarization, the cellular exocytosis machinery, neurotransmitter release from synaptic vesicles into the synaptic cleft, and the interaction between ion channels, G protein-coupled receptors (GPCRs), and downstream effector molecules. The focus of this review is to explore the role of GPCRs and G protein-signaling in neurotransmission, to highlight the function of GPCRs, which are localized in both presynaptic and postsynaptic membrane terminals, in regulation of intrasynaptic and intersynaptic communication, and to discuss the involvement of astrocytic GPCRs in the regulation of neuronal communication. Copyright © 2015 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

  7. Microfluidic Neurons, a New Way in Neuromorphic Engineering?

    Directory of Open Access Journals (Sweden)

    Timothée Levi

    2016-08-01

    Full Text Available This article describes a new way to explore neuromorphic engineering, the biomimetic artificial neuron using microfluidic techniques. This new device could replace silicon neurons and solve the issues of biocompatibility and power consumption. The biological neuron transmits electrical signals based on ion flow through their plasma membrane. Action potentials are propagated along axons and represent the fundamental electrical signals by which information are transmitted from one place to another in the nervous system. Based on this physiological behavior, we propose a microfluidic structure composed of chambers representing the intra and extracellular environments, connected by channels actuated by Quake valves. These channels are equipped with selective ion permeable membranes to mimic the exchange of chemical species found in the biological neuron. A thick polydimethylsiloxane (PDMS membrane is used to create the Quake valve membrane. Integrated electrodes are used to measure the potential difference between the intracellular and extracellular environments: the membrane potential.

  8. The neuronal identity bias behind neocortical GABAergic plasticity.

    Science.gov (United States)

    Allene, Camille; Lourenço, Joana; Bacci, Alberto

    2015-09-01

    In the neocortex, different types of excitatory and inhibitory neurons connect to one another following a detailed blueprint, defining functionally-distinct subnetworks, whose activity and modulation underlie complex cognitive functions. We review the cell-autonomous plasticity of perisomatic inhibition onto principal excitatory neurons. We propose that the tendency of different cortical layers to exhibit depression or potentiation of perisomatic inhibition is dictated by the specific identities of principal neurons (PNs). These are mainly defined by their projection targets and by their preference to be innervated by specific perisomatic-targeting basket cell types. Therefore, principal neurons responsible for relaying information to subcortical nuclei are differentially inhibited and show specific forms of plasticity compared to other PNs that are specialized in more associative functions. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. Effects of homeostatic constraints on associative memory storage and synaptic connectivity of cortical circuits

    Directory of Open Access Journals (Sweden)

    Julio eChapeton

    2015-06-01

    Full Text Available The impact of learning and long-term memory storage on synaptic connectivity is not completely understood. In this study, we examine the effects of associative learning on synaptic connectivity in adult cortical circuits by hypothesizing that these circuits function in a steady-state, in which the memory capacity of a circuit is maximal and learning must be accompanied by forgetting. Steady-state circuits should be characterized by unique connectivity features. To uncover such features we developed a biologically constrained, exactly solvable model of associative memory storage. The model is applicable to networks of multiple excitatory and inhibitory neuron classes and can account for homeostatic constraints on the number and the overall weight of functional connections received by each neuron. The results show that in spite of a large number of neuron classes, functional connections between potentially connected cells are realized with less than 50% probability if the presynaptic cell is excitatory and generally a much greater probability if it is inhibitory. We also find that constraining the overall weight of presynaptic connections leads to Gaussian connection weight distributions that are truncated at zero. In contrast, constraining the total number of functional presynaptic connections leads to non-Gaussian distributions, in which weak connections are absent. These theoretical predictions are compared with a large dataset of published experimental studies reporting amplitudes of unitary postsynaptic potentials and probabilities of connections between various classes of excitatory and inhibitory neurons in the cerebellum, neocortex, and hippocampus.

  10. Galanin-Expressing GABA Neurons in the Lateral Hypothalamus Modulate Food Reward and Noncompulsive Locomotion.

    Science.gov (United States)

    Qualls-Creekmore, Emily; Yu, Sangho; Francois, Marie; Hoang, John; Huesing, Clara; Bruce-Keller, Annadora; Burk, David; Berthoud, Hans-Rudolf; Morrison, Christopher D; Münzberg, Heike

    2017-06-21

    The lateral hypothalamus (LHA) integrates reward and appetitive behavior and is composed of many overlapping neuronal populations. Recent studies associated LHA GABAergic neurons (LHA GABA ), which densely innervate the ventral tegmental area (VTA), with modulation of food reward and consumption; yet, LHA GABA projections to the VTA exclusively modulated food consumption, not reward. We identified a subpopulation of LHA GABA neurons that coexpress the neuropeptide galanin (LHA Gal ). These LHA Gal neurons also modulate food reward, but lack direct VTA innervation. We hypothesized that LHA Gal neurons may represent a subpopulation of LHA GABA neurons that mediates food reward independent of direct VTA innervation. We used chemogenetic activation of LHA Gal or LHA GABA neurons in mice to compare their role in feeding behavior. We further analyzed locomotor behavior to understand how differential VTA connectivity and transmitter release in these LHA neurons influences this behavior. LHA Gal or LHA GABA neuronal activation both increased operant food-seeking behavior, but only activation of LHA GABA neurons increased overall chow consumption. Additionally, LHA Gal or LHA GABA neuronal activation similarly induced locomotor activity, but with striking differences in modality. Activation of LHA GABA neurons induced compulsive-like locomotor behavior; while LHA Gal neurons induced locomotor activity without compulsivity. Thus, LHA Gal neurons define a subpopulation of LHA GABA neurons without direct VTA innervation that mediate noncompulsive food-seeking behavior. We speculate that the striking difference in compulsive-like locomotor behavior is also based on differential VTA innervation. The downstream neural network responsible for this behavior and a potential role for galanin as neuromodulator remains to be identified. SIGNIFICANCE STATEMENT The lateral hypothalamus (LHA) regulates motivated feeding behavior via GABAergic LHA neurons. The molecular identity of LHA

  11. Modeling task-specific neuronal ensembles improves decoding of grasp

    Science.gov (United States)

    Smith, Ryan J.; Soares, Alcimar B.; Rouse, Adam G.; Schieber, Marc H.; Thakor, Nitish V.

    2018-06-01

    Objective. Dexterous movement involves the activation and coordination of networks of neuronal populations across multiple cortical regions. Attempts to model firing of individual neurons commonly treat the firing rate as directly modulating with motor behavior. However, motor behavior may additionally be associated with modulations in the activity and functional connectivity of neurons in a broader ensemble. Accounting for variations in neural ensemble connectivity may provide additional information about the behavior being performed. Approach. In this study, we examined neural ensemble activity in primary motor cortex (M1) and premotor cortex (PM) of two male rhesus monkeys during performance of a center-out reach, grasp and manipulate task. We constructed point process encoding models of neuronal firing that incorporated task-specific variations in the baseline firing rate as well as variations in functional connectivity with the neural ensemble. Models were evaluated both in terms of their encoding capabilities and their ability to properly classify the grasp being performed. Main results. Task-specific ensemble models correctly predicted the performed grasp with over 95% accuracy and were shown to outperform models of neuronal activity that assume only a variable baseline firing rate. Task-specific ensemble models exhibited superior decoding performance in 82% of units in both monkeys (p  <  0.01). Inclusion of ensemble activity also broadly improved the ability of models to describe observed spiking. Encoding performance of task-specific ensemble models, measured by spike timing predictability, improved upon baseline models in 62% of units. Significance. These results suggest that additional discriminative information about motor behavior found in the variations in functional connectivity of neuronal ensembles located in motor-related cortical regions is relevant to decode complex tasks such as grasping objects, and may serve the basis for more

  12. Neurons in the human amygdala selective for perceived emotion

    Science.gov (United States)

    Wang, Shuo; Tudusciuc, Oana; Mamelak, Adam N.; Ross, Ian B.; Adolphs, Ralph; Rutishauser, Ueli

    2014-01-01

    The human amygdala plays a key role in recognizing facial emotions and neurons in the monkey and human amygdala respond to the emotional expression of faces. However, it remains unknown whether these responses are driven primarily by properties of the stimulus or by the perceptual judgments of the perceiver. We investigated these questions by recording from over 200 single neurons in the amygdalae of 7 neurosurgical patients with implanted depth electrodes. We presented degraded fear and happy faces and asked subjects to discriminate their emotion by button press. During trials where subjects responded correctly, we found neurons that distinguished fear vs. happy emotions as expressed by the displayed faces. During incorrect trials, these neurons indicated the patients’ subjective judgment. Additional analysis revealed that, on average, all neuronal responses were modulated most by increases or decreases in response to happy faces, and driven predominantly by judgments about the eye region of the face stimuli. Following the same analyses, we showed that hippocampal neurons, unlike amygdala neurons, only encoded emotions but not subjective judgment. Our results suggest that the amygdala specifically encodes the subjective judgment of emotional faces, but that it plays less of a role in simply encoding aspects of the image array. The conscious percept of the emotion shown in a face may thus arise from interactions between the amygdala and its connections within a distributed cortical network, a scheme also consistent with the long response latencies observed in human amygdala recordings. PMID:24982200

  13. Neuronal Migration and Neuronal Migration Disorder in Cerebral Cortex

    OpenAIRE

    SUN, Xue-Zhi; TAKAHASHI, Sentaro; GUI, Chun; ZHANG, Rui; KOGA, Kazuo; NOUYE, Minoru; MURATA, Yoshiharu

    2002-01-01

    Neuronal cell migration is one of the most significant features during cortical development. After final mitosis, neurons migrate from the ventricular zone into the cortical plate, and then establish neuronal lamina and settle onto the outermost layer, forming an "inside-out" gradient of maturation. Neuronal migration is guided by radial glial fibers and also needs proper receptors, ligands, and other unknown extracellular factors, requests local signaling (e.g. some emitted by the Cajal-Retz...

  14. 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.

  15. Synapse Formation in Monosynaptic Sensory–Motor Connections Is Regulated by Presynaptic Rho GTPase Cdc42

    Science.gov (United States)

    Imai, Fumiyasu; Ladle, David R.; Leslie, Jennifer R.; Duan, Xin; Rizvi, Tilat A.; Ciraolo, Georgianne M.; Zheng, Yi

    2016-01-01

    Spinal reflex circuit development requires the precise regulation of axon trajectories, synaptic specificity, and synapse formation. Of these three crucial steps, the molecular mechanisms underlying synapse formation between group Ia proprioceptive sensory neurons and motor neurons is the least understood. Here, we show that the Rho GTPase Cdc42 controls synapse formation in monosynaptic sensory–motor connections in presynaptic, but not postsynaptic, neurons. In mice lacking Cdc42 in presynaptic sensory neurons, proprioceptive sensory axons appropriately reach the ventral spinal cord, but significantly fewer synapses are formed with motor neurons compared with wild-type mice. Concordantly, electrophysiological analyses show diminished EPSP amplitudes in monosynaptic sensory–motor circuits in these mutants. Temporally targeted deletion of Cdc42 in sensory neurons after sensory–motor circuit establishment reveals that Cdc42 does not affect synaptic transmission. Furthermore, addition of the synaptic organizers, neuroligins, induces presynaptic differentiation of wild-type, but not Cdc42-deficient, proprioceptive sensory neurons in vitro. Together, our findings demonstrate that Cdc42 in presynaptic neurons is required for synapse formation in monosynaptic sensory–motor circuits. SIGNIFICANCE STATEMENT Group Ia proprioceptive sensory neurons form direct synapses with motor neurons, but the molecular mechanisms underlying synapse formation in these monosynaptic sensory–motor connections are unknown. We show that deleting Cdc42 in sensory neurons does not affect proprioceptive sensory axon targeting because axons reach the ventral spinal cord appropriately, but these neurons form significantly fewer presynaptic terminals on motor neurons. Electrophysiological analysis further shows that EPSPs are decreased in these mice. Finally, we demonstrate that Cdc42 is involved in neuroligin-dependent presynaptic differentiation of proprioceptive sensory neurons in vitro

  16. Association Between Brain Activation and Functional Connectivity.

    Science.gov (United States)

    Tomasi, Dardo; Volkow, Nora D

    2018-04-13

    The origin of the "resting-state" brain activity recorded with functional magnetic resonance imaging (fMRI) is still uncertain. Here we provide evidence for the neurovascular origins of the amplitude of the low-frequency fluctuations (ALFF) and the local functional connectivity density (lFCD) by comparing them with task-induced blood-oxygen level dependent (BOLD) responses, which are considered a proxy for neuronal activation. Using fMRI data for 2 different tasks (Relational and Social) collected by the Human Connectome Project in 426 healthy adults, we show that ALFF and lFCD have linear associations with the BOLD response. This association was significantly attenuated by a novel task signal regression (TSR) procedure, indicating that task performance enhances lFCD and ALFF in activated regions. We also show that lFCD predicts BOLD activation patterns, as was recently shown for other functional connectivity metrics, which corroborates that resting functional connectivity architecture impacts brain activation responses. Thus, our findings indicate a common source for BOLD responses, ALFF and lFCD, which is consistent with the neurovascular origin of local hemodynamic synchrony presumably reflecting coordinated fluctuations in neuronal activity. This study also supports the development of task-evoked functional connectivity density mapping.

  17. Neuronal nets in robotics

    International Nuclear Information System (INIS)

    Jimenez Sanchez, Raul

    1999-01-01

    The paper gives a generic idea of the solutions that the neuronal nets contribute to the robotics. The advantages and the inconveniences are exposed that have regarding the conventional techniques. It also describe the more excellent applications as the pursuit of trajectories, the positioning based on images, the force control or of the mobile robots management, among others

  18. Interlayer neurones in the rat superior colliculus: a tracer study using Dil/Di-ASP.

    Science.gov (United States)

    Hilbig, H; Schierwagen, A

    1994-01-12

    Five different populations of interlayer neurones (ILNs) can be described after DiI/Di-ASP tracing in rat superior colliculus (SC). All of these labelled neurones preferentially lay in the rostro-medial part of the SC. Most of them are located in the stratum opticum and in the stratum griseum superficiale. Our results indicate that ILNs represent a minority of neurones in the superficial layers but may constitute a substantial population of neurones in the stratum opticum connecting the visual and the multimodal collicular layers.

  19. Birth of projection neurons in adult avian brain may be related to perceptual or motor learning

    International Nuclear Information System (INIS)

    Alvarez-Buylla, A.; Kirn, J.R.; Nottebohm, F.

    1990-01-01

    Projection neurons that form part of the motor pathway for song control continue to be produced and to replace older projection neurons in adult canaries and zebra finches. This is shown by combining [3H]thymidine, a cell birth marker, and fluorogold, a retrogradely transported tracer of neuronal connectivity. Species and seasonal comparisons suggest that this process is related to the acquisition of perceptual or motor memories. The ability of an adult brain to produce and replace projection neurons should influence our thinking on brain repair

  20. Transition Dynamics of a Dentate Gyrus-CA3 Neuronal Network during Temporal Lobe Epilepsy

    Directory of Open Access Journals (Sweden)

    Liyuan Zhang

    2017-07-01

    Full Text Available In temporal lobe epilepsy (TLE, the variation of chemical receptor expression underlies the basis of neural network activity shifts, resulting in neuronal hyperexcitability and epileptiform discharges. However, dynamical mechanisms involved in the transitions of TLE are not fully understood, because of the neuronal diversity and the indeterminacy of network connection. Hence, based on Hodgkin–Huxley (HH type neurons and Pinsky–Rinzel (PR type neurons coupling with glutamatergic and GABAergic synaptic connections respectively, we propose a computational framework which contains dentate gyrus (DG region and CA3 region. By regulating the concentration range of N-methyl-D-aspartate-type glutamate receptor (NMDAR, we demonstrate the pyramidal neuron can generate transitions from interictal to seizure discharges. This suggests that enhanced endogenous activity of NMDAR contributes to excitability in pyramidal neuron. Moreover, we conclude that excitatory discharges in CA3 region vary considerably on account of the excitatory currents produced by the excitatory pyramidal neuron. Interestingly, by changing the backprojection connection, we find that glutamatergic type backprojection can promote the dominant frequency of firings and further motivate excitatory counterpropagation from CA3 region to DG region. However, GABAergic type backprojection can reduce firing rate and block morbid counterpropagation, which may be factored into the terminations of TLE. In addition, neuronal diversity dominated network shows weak correlation with different backprojections. Our modeling and simulation studies provide new insights into the mechanisms of seizures generation and connectionism in local hippocampus, along with the synaptic mechanisms of this disease.

  1. Network control principles predict neuron function in the Caenorhabditis elegans connectome

    Science.gov (United States)

    Yan, Gang; Vértes, Petra E.; Towlson, Emma K.; Chew, Yee Lian; Walker, Denise S.; Schafer, William R.; Barabási, Albert-László

    2017-10-01

    Recent studies on the controllability of complex systems offer a powerful mathematical framework to systematically explore the structure-function relationship in biological, social, and technological networks. Despite theoretical advances, we lack direct experimental proof of the validity of these widely used control principles. Here we fill this gap by applying a control framework to the connectome of the nematode Caenorhabditis elegans, allowing us to predict the involvement of each C. elegans neuron in locomotor behaviours. We predict that control of the muscles or motor neurons requires 12 neuronal classes, which include neuronal groups previously implicated in locomotion by laser ablation, as well as one previously uncharacterized neuron, PDB. We validate this prediction experimentally, finding that the ablation of PDB leads to a significant loss of dorsoventral polarity in large body bends. Importantly, control principles also allow us to investigate the involvement of individual neurons within each neuronal class. For example, we predict that, within the class of DD motor neurons, only three (DD04, DD05, or DD06) should affect locomotion when ablated individually. This prediction is also confirmed; single cell ablations of DD04 or DD05 specifically affect posterior body movements, whereas ablations of DD02 or DD03 do not. Our predictions are robust to deletions of weak connections, missing connections, and rewired connections in the current connectome, indicating the potential applicability of this analytical framework to larger and less well-characterized connectomes.

  2. Network control principles predict neuron function in the Caenorhabditis elegans connectome.

    Science.gov (United States)

    Yan, Gang; Vértes, Petra E; Towlson, Emma K; Chew, Yee Lian; Walker, Denise S; Schafer, William R; Barabási, Albert-László

    2017-10-26

    Recent studies on the controllability of complex systems offer a powerful mathematical framework to systematically explore the structure-function relationship in biological, social, and technological networks. Despite theoretical advances, we lack direct experimental proof of the validity of these widely used control principles. Here we fill this gap by applying a control framework to the connectome of the nematode Caenorhabditis elegans, allowing us to predict the involvement of each C. elegans neuron in locomotor behaviours. We predict that control of the muscles or motor neurons requires 12 neuronal classes, which include neuronal groups previously implicated in locomotion by laser ablation, as well as one previously uncharacterized neuron, PDB. We validate this prediction experimentally, finding that the ablation of PDB leads to a significant loss of dorsoventral polarity in large body bends. Importantly, control principles also allow us to investigate the involvement of individual neurons within each neuronal class. For example, we predict that, within the class of DD motor neurons, only three (DD04, DD05, or DD06) should affect locomotion when ablated individually. This prediction is also confirmed; single cell ablations of DD04 or DD05 specifically affect posterior body movements, whereas ablations of DD02 or DD03 do not. Our predictions are robust to deletions of weak connections, missing connections, and rewired connections in the current connectome, indicating the potential applicability of this analytical framework to larger and less well-characterized connectomes.

  3. Transition Dynamics of a Dentate Gyrus-CA3 Neuronal Network during Temporal Lobe Epilepsy.

    Science.gov (United States)

    Zhang, Liyuan; Fan, Denggui; Wang, Qingyun

    2017-01-01

    In temporal lobe epilepsy (TLE), the variation of chemical receptor expression underlies the basis of neural network activity shifts, resulting in neuronal hyperexcitability and epileptiform discharges. However, dynamical mechanisms involved in the transitions of TLE are not fully understood, because of the neuronal diversity and the indeterminacy of network connection. Hence, based on Hodgkin-Huxley (HH) type neurons and Pinsky-Rinzel (PR) type neurons coupling with glutamatergic and GABAergic synaptic connections respectively, we propose a computational framework which contains dentate gyrus (DG) region and CA3 region. By regulating the concentration range of N-methyl-D-aspartate-type glutamate receptor (NMDAR), we demonstrate the pyramidal neuron can generate transitions from interictal to seizure discharges. This suggests that enhanced endogenous activity of NMDAR contributes to excitability in pyramidal neuron. Moreover, we conclude that excitatory discharges in CA3 region vary considerably on account of the excitatory currents produced by the excitatory pyramidal neuron. Interestingly, by changing the backprojection connection, we find that glutamatergic type backprojection can promote the dominant frequency of firings and further motivate excitatory counterpropagation from CA3 region to DG region. However, GABAergic type backprojection can reduce firing rate and block morbid counterpropagation, which may be factored into the terminations of TLE. In addition, neuronal diversity dominated network shows weak correlation with different backprojections. Our modeling and simulation studies provide new insights into the mechanisms of seizures generation and connectionism in local hippocampus, along with the synaptic mechanisms of this disease.

  4. Vasculo-Neuronal Coupling: Retrograde Vascular Communication to Brain Neurons.

    Science.gov (United States)

    Kim, Ki Jung; Ramiro Diaz, Juan; Iddings, Jennifer A; Filosa, Jessica A

    2016-12-14

    Continuous cerebral blood flow is essential for neuronal survival, but whether vascular tone influences resting neuronal function is not known. Using a multidisciplinary approach in both rat and mice brain slices, we determined whether flow/pressure-evoked increases or decreases in parenchymal arteriole vascular tone, which result in arteriole constriction and dilation, respectively, altered resting cortical pyramidal neuron activity. We present evidence for intercellular communication in the brain involving a flow of information from vessel to astrocyte to neuron, a direction opposite to that of classic neurovascular coupling and referred to here as vasculo-neuronal coupling (VNC). Flow/pressure increases within parenchymal arterioles increased vascular tone and simultaneously decreased resting pyramidal neuron firing activity. On the other hand, flow/pressure decreases evoke parenchymal arteriole dilation and increased resting pyramidal neuron firing activity. In GLAST-CreERT2; R26-lsl-GCaMP3 mice, we demonstrate that increased parenchymal arteriole tone significantly increased intracellular calcium in perivascular astrocyte processes, the onset of astrocyte calcium changes preceded the inhibition of cortical pyramidal neuronal firing activity. During increases in parenchymal arteriole tone, the pyramidal neuron response was unaffected by blockers of nitric oxide, GABA A , glutamate, or ecto-ATPase. However, VNC was abrogated by TRPV4 channel, GABA B , as well as an adenosine A 1 receptor blocker. Differently to pyramidal neuron responses, increases in flow/pressure within parenchymal arterioles increased the firing activity of a subtype of interneuron. Together, these data suggest that VNC is a complex constitutive active process that enables neurons to efficiently adjust their resting activity according to brain perfusion levels, thus safeguarding cellular homeostasis by preventing mismatches between energy supply and demand. We present evidence for vessel-to-neuron

  5. Organization of Functional Long-Range Circuits Controlling the Activity of Serotonergic Neurons in the Dorsal Raphe Nucleus

    Directory of Open Access Journals (Sweden)

    Li Zhou

    2017-03-01

    Full Text Available Serotonergic neurons play key roles in various biological processes. However, circuit mechanisms underlying tight control of serotonergic neurons remain largely unknown. Here, we systematically investigated the organization of long-range synaptic inputs to serotonergic neurons and GABAergic neurons in the dorsal raphe nucleus (DRN of mice with a combination of viral tracing, slice electrophysiological, and optogenetic techniques. We found that DRN serotonergic neurons and GABAergic neurons receive largely comparable synaptic inputs from six major upstream brain areas. Upon further analysis of the fine functional circuit structures, we found both bilateral and ipsilateral patterns of topographic connectivity in the DRN for the axons from different inputs. Moreover, the upstream brain areas were found to bidirectionally control the activity of DRN serotonergic neurons by recruiting feedforward inhibition or via a push-pull mechanism. Our study provides a framework for further deciphering the functional roles of long-range circuits controlling the activity of serotonergic neurons in the DRN.

  6. Just-in-time connectivity for large spiking networks.

    Science.gov (United States)

    Lytton, William W; Omurtag, Ahmet; Neymotin, Samuel A; Hines, Michael L

    2008-11-01

    The scale of large neuronal network simulations is memory limited due to the need to store connectivity information: connectivity storage grows as the square of neuron number up to anatomically relevant limits. Using the NEURON simulator as a discrete-event simulator (no integration), we explored the consequences of avoiding the space costs of connectivity through regenerating connectivity parameters when needed: just in time after a presynaptic cell fires. We explored various strategies for automated generation of one or more of the basic static connectivity parameters: delays, postsynaptic cell identities, and weights, as well as run-time connectivity state: the event queue. Comparison of the JitCon implementation to NEURON's standard NetCon connectivity method showed substantial space savings, with associated run-time penalty. Although JitCon saved space by eliminating connectivity parameters, larger simulations were still memory limited due to growth of the synaptic event queue. We therefore designed a JitEvent algorithm that added items to the queue only when required: instead of alerting multiple postsynaptic cells, a spiking presynaptic cell posted a callback event at the shortest synaptic delay time. At the time of the callback, this same presynaptic cell directly notified the first postsynaptic cell and generated another self-callback for the next delay time. The JitEvent implementation yielded substantial additional time and space savings. We conclude that just-in-time strategies are necessary for very large network simulations but that a variety of alternative strategies should be considered whose optimality will depend on the characteristics of the simulation to be run.

  7. Minimum cost connection networks

    DEFF Research Database (Denmark)

    Hougaard, Jens Leth; Tvede, Mich

    2015-01-01

    In the present paper we consider the allocation of costs in connection networks. Agents have connection demands in form of pairs of locations they want to have connected. Connections between locations are costly to build. The problem is to allocate costs of networks satisfying all connection...... demands. We use a few axioms to characterize allocation rules that truthfully implement cost minimizing networks satisfying all connection demands in a game where: (1) a central planner announces an allocation rule and a cost estimation rule; (2) every agent reports her own connection demand as well...... as all connection costs; (3) the central planner selects a cost minimizing network satisfying reported connection demands based on the estimated costs; and, (4) the planner allocates the true costs of the selected network. It turns out that an allocation rule satisfies the axioms if and only if relative...

  8. Investigation of synapse formation and function in a glutamatergic-GABAergic two-neuron microcircuit.

    Science.gov (United States)

    Chang, Chia-Ling; Trimbuch, Thorsten; Chao, Hsiao-Tuan; Jordan, Julia-Christine; Herman, Melissa A; Rosenmund, Christian

    2014-01-15

    Neural circuits are composed of mainly glutamatergic and GABAergic neurons, which communicate through synaptic connections. Many factors instruct the formation and function of these synapses; however, it is difficult to dissect the contribution of intrinsic cell programs from that of extrinsic environmental effects in an intact network. Here, we perform paired recordings from two-neuron microculture preparations of mouse hippocampal glutamatergic and GABAergic neurons to investigate how synaptic input and output of these two principal cells develop. In our reduced preparation, we found that glutamatergic neurons showed no change in synaptic output or input regardless of partner neuron cell type or neuronal activity level. In contrast, we found that glutamatergic input caused the GABAergic neuron to modify its output by way of an increase in synapse formation and a decrease in synaptic release efficiency. These findings are consistent with aspects of GABAergic synapse maturation observed in many brain regions. In addition, changes in GABAergic output are cell wide and not target-cell specific. We also found that glutamatergic neuronal activity determined the AMPA receptor properties of synapses on the partner GABAergic neuron. All modifications of GABAergic input and output required activity of the glutamatergic neuron. Because our system has reduced extrinsic factors, the changes we saw in the GABAergic neuron due to glutamatergic input may reflect initiation of maturation programs that underlie the formation and function of in vivo neural circuits.

  9. Two cell circuits of oriented adult hippocampal neurons on self-assembled monolayers for use in the study of neuronal communication in a defined system.

    Science.gov (United States)

    Edwards, Darin; Stancescu, Maria; Molnar, Peter; Hickman, James J

    2013-08-21

    In this study, we demonstrate the directed formation of small circuits of electrically active, synaptically connected neurons derived from the hippocampus of adult rats through the use of engineered chemically modified culture surfaces that orient the polarity of the neuronal processes. Although synaptogenesis, synaptic communication, synaptic plasticity, and brain disease pathophysiology can be studied using brain slice or dissociated embryonic neuronal culture systems, the complex elements found in neuronal synapses makes specific studies difficult in these random cultures. The study of synaptic transmission in mature adult neurons and factors affecting synaptic transmission are generally studied in organotypic cultures, in brain slices, or in vivo. However, engineered neuronal networks would allow these studies to be performed instead on simple functional neuronal circuits derived from adult brain tissue. Photolithographic patterned self-assembled monolayers (SAMs) were used to create the two-cell "bidirectional polarity" circuit patterns. This pattern consisted of a cell permissive SAM, N-1[3-(trimethoxysilyl)propyl] diethylenetriamine (DETA), and was composed of two 25 μm somal adhesion sites connected with 5 μm lines acting as surface cues for guided axonal and dendritic regeneration. Surrounding the DETA pattern was a background of a non-cell-permissive poly(ethylene glycol) (PEG) SAM. Adult hippocampal neurons were first cultured on coverslips coated with DETA monolayers and were later passaged onto the PEG-DETA bidirectional polarity patterns in serum-free medium. These neurons followed surface cues, attaching and regenerating only along the DETA substrate to form small engineered neuronal circuits. These circuits were stable for more than 21 days in vitro (DIV), during which synaptic connectivity was evaluated using basic electrophysiological methods.

  10. Neuronal survival in the brain: neuron type-specific mechanisms

    DEFF Research Database (Denmark)

    Pfisterer, Ulrich Gottfried; Khodosevich, Konstantin

    2017-01-01

    Neurogenic regions of mammalian brain produce many more neurons that will eventually survive and reach a mature stage. Developmental cell death affects both embryonically produced immature neurons and those immature neurons that are generated in regions of adult neurogenesis. Removal of substantial...... numbers of neurons that are not yet completely integrated into the local circuits helps to ensure that maturation and homeostatic function of neuronal networks in the brain proceed correctly. External signals from brain microenvironment together with intrinsic signaling pathways determine whether...... for survival in a certain brain region. This review focuses on how immature neurons survive during normal and impaired brain development, both in the embryonic/neonatal brain and in brain regions associated with adult neurogenesis, and emphasizes neuron type-specific mechanisms that help to survive for various...

  11. The changing roles of neurons in the cortical subplate

    Directory of Open Access Journals (Sweden)

    Michael J Friedlander

    2009-08-01

    Full Text Available Neurons may serve different functions over the course of an organism’s life. Recent evidence suggests that cortical subplate neurons including those that reside in the white matter may perform longitudinal multi-tasking at different stages of development. These cells play a key role in early cortical development in coordinating thalamocortical reciprocal innervation. At later stages of development, they become integrated within the cortical microcircuitry. This type of longitudinal multi-tasking can enhance the capacity for information processing by populations of cells serving different functions over the lifespan. Subplate cells are initially derived when cells from the ventricular zone underlying the cortex migrate to the cortical preplate that is subsequently split by the differentiating neurons of the cortical plate with some neurons locating in the marginal zone and others settling below in the subplate (SP. While the cortical plate neurons form most of the cortical layers (layers 2-6, the marginal zone neurons form layer 1 and the SP neurons become interstitial cells of the white matter as well as forming a compact sublayer along the bottom of layer 6. After serving as transient innervation targets for thalamocortical axons, most of these cells die and layer 4 neurons become innervated by thalamic axons. However, 10-20% survives, remaining into adulthood along the bottom of layer 6 and as a scattered population of interstitial neurons in the white matter. Surviving subplate cells’ axons project throughout the overlying laminae, reaching layer 1 and issuing axon collaterals within white matter and in lower layer 6. This suggests that they participate in local synaptic networks, as well. Moreover, they receive excitatory and inhibitory synaptic inputs, potentially monitoring outputs from axon collaterals of cortical efferents, from cortical afferents and/or from each other. We explore our understanding of the functional connectivity of

  12. The function of mirror neurons in the learning process

    Directory of Open Access Journals (Sweden)

    Mara Daniel

    2017-01-01

    Full Text Available In the last years, Neurosciences have developed very much, being elaborated many important theories scientific research in the field. The main goal of neuroscience is to understand how groups of neurons interact to create the behavior. Neuroscientists studying the action of molecules, genes and cells. It also explores the complex interactions involved in motion perception, thoughts, emotions and learning. Brick fundamental nervous system is the nerve cell, neuron. Neurons exchange information by sending electrical signals and chemical through connections called synapses. Discovered by a group of Italian researchers from the University of Parma, neurons - mirror are a special class of nerve cells played an important role in the direct knowledge, automatic and unconscious environment. These cortical neurons are activated not only when an action is fulfilled, but when we see how the same action is performed by someone else, they represent neural mechanism by which the actions, intentions and emotions of others can be understood automatically. In childhood neurons - mirror are extremely important. Thanks to them we learned a lot in the early years: smile, to ask for help and, in fact, all the behaviors and family and group norms. People learn by what they see and sense the others. Neurons - mirror are important to understanding the actions and intentions of other people and learn new skills through mirror image. They are involved in planning and controlling actions, abstract thinking and memory. If a child observes an action, neurons - mirror is activated and forming new neural pathways as if even he takes that action. Efficient activity of mirror neurons leads to good development in all areas at a higher emotional intelligence and the ability to empathize with others.

  13. Retrograde monosynaptic tracing reveals the temporal evolution of inputs onto new neurons in the adult dentate gyrus and olfactory bulb

    Science.gov (United States)

    Deshpande, Aditi; Bergami, Matteo; Ghanem, Alexander; Conzelmann, Karl-Klaus; Lepier, Alexandra; Götz, Magdalena; Berninger, Benedikt

    2013-01-01

    Identifying the connectome of adult-generated neurons is essential for understanding how the preexisting circuitry is refined by neurogenesis. Changes in the pattern of connectivity are likely to control the differentiation process of newly generated neurons and exert an important influence on their unique capacity to contribute to information processing. Using a monosynaptic rabies virus-based tracing technique, we studied the evolving presynaptic connectivity of adult-generated neurons in the dentate gyrus (DG) of the hippocampus and olfactory bulb (OB) during the first weeks of their life. In both neurogenic zones, adult-generated neurons first receive local connections from multiple types of GABAergic interneurons before long-range projections become established, such as those originating from cortical areas. Interestingly, despite fundamental similarities in the overall pattern of evolution of presynaptic connectivity, there were notable differences with regard to the development of cortical projections: although DG granule neuron input originating from the entorhinal cortex could be traced starting only from 3 to 5 wk on, newly generated neurons in the OB received input from the anterior olfactory nucleus and piriform cortex already by the second week. This early glutamatergic input onto newly generated interneurons in the OB was matched in time by the equally early innervations of DG granule neurons by glutamatergic mossy cells. The development of connectivity revealed by our study may suggest common principles for incorporating newly generated neurons into a preexisting circuit. PMID:23487772

  14. Functional Characterization of Lamina X Neurons in ex-Vivo Spinal Cord Preparation

    Directory of Open Access Journals (Sweden)

    Volodymyr Krotov

    2017-11-01

    Full Text Available Functional properties of lamina X neurons in the spinal cord remain unknown despite the established role of this area for somatosensory integration, visceral nociception, autonomic regulation and motoneuron output modulation. Investigations of neuronal functioning in the lamina X have been hampered by technical challenges. Here we introduce an ex-vivo spinal cord preparation with both dorsal and ventral roots still attached for functional studies of the lamina X neurons and their connectivity using an oblique LED illumination for resolved visualization of lamina X neurons in a thick tissue. With the elaborated approach, we demonstrate electrophysiological characteristics of lamina X neurons by their membrane properties, firing pattern discharge and fiber innervation (either afferent or efferent. The tissue preparation has been also probed using Ca2+ imaging with fluorescent Ca2+ dyes (membrane-impermeable or -permeable to demonstrate the depolarization-induced changes in intracellular calcium concentration in lamina X neurons. Finally, we performed visualization of subpopulations of lamina X neurons stained by retrograde labeling with aminostilbamidine dye to identify sympathetic preganglionic and projection neurons in the lamina X. Thus, the elaborated approach provides a reliable tool for investigation of functional properties and connectivity in specific neuronal subpopulations, boosting research of lamina X of the spinal cord.

  15. Democratic reinforcement: A principle for brain function

    International Nuclear Information System (INIS)

    Stassinopoulos, D.; Bak, P.

    1995-01-01

    We introduce a simple ''toy'' brain model. The model consists of a set of randomly connected, or layered integrate-and-fire neurons. Inputs to and outputs from the environment are connected randomly to subsets of neurons. The connections between firing neurons are strengthened or weakened according to whether the action was successful or not. Unlike previous reinforcement learning algorithms, the feedback from the environment is democratic: it affects all neurons in the same way, irrespective of their position in the network and independent of the output signal. Thus no unrealistic back propagation or other external computation is needed. This is accomplished by a global threshold regulation which allows the system to self-organize into a highly susceptible, possibly ''critical'' state with low activity and sparse connections between firing neurons. The low activity permits memory in quiescent areas to be conserved since only firing neurons are modified when new information is being taught

  16. Metabolic connectivity mapping reveals effective connectivity in the resting human brain.

    Science.gov (United States)

    Riedl, Valentin; Utz, Lukas; Castrillón, Gabriel; Grimmer, Timo; Rauschecker, Josef P; Ploner, Markus; Friston, Karl J; Drzezga, Alexander; Sorg, Christian

    2016-01-12

    Directionality of signaling among brain regions provides essential information about human cognition and disease states. Assessing such effective connectivity (EC) across brain states using functional magnetic resonance imaging (fMRI) alone has proven difficult, however. We propose a novel measure of EC, termed metabolic connectivity mapping (MCM), that integrates undirected functional connectivity (FC) with local energy metabolism from fMRI and positron emission tomography (PET) data acquired simultaneously. This method is based on the concept that most energy required for neuronal communication is consumed postsynaptically, i.e., at the target neurons. We investigated MCM and possible changes in EC within the physiological range using "eyes open" versus "eyes closed" conditions in healthy subjects. Independent of condition, MCM reliably detected stable and bidirectional communication between early and higher visual regions. Moreover, we found stable top-down signaling from a frontoparietal network including frontal eye fields. In contrast, we found additional top-down signaling from all major clusters of the salience network to early visual cortex only in the eyes open condition. MCM revealed consistent bidirectional and unidirectional signaling across the entire cortex, along with prominent changes in network interactions across two simple brain states. We propose MCM as a novel approach for inferring EC from neuronal energy metabolism that is ideally suited to study signaling hierarchies in the brain and their defects in brain disorders.

  17. In Vitro Reconstruction of Neuronal Networks Derived from Human iPS Cells Using Microfabricated Devices.

    Directory of Open Access Journals (Sweden)

    Yuzo Takayama

    Full Text Available Morphology and function of the nervous system is maintained via well-coordinated processes both in central and peripheral nervous tissues, which govern the homeostasis of organs/tissues. Impairments of the nervous system induce neuronal disorders such as peripheral neuropathy or cardiac arrhythmia. Although further investigation is warranted to reveal the molecular mechanisms of progression in such diseases, appropriate model systems mimicking the patient-specific communication between neurons and organs are not established yet. In this study, we reconstructed the neuronal network in vitro either between neurons of the human induced pluripotent stem (iPS cell derived peripheral nervous system (PNS and central nervous system (CNS, or between PNS neurons and cardiac cells in a morphologically and functionally compartmentalized manner. Networks were constructed in photolithographically microfabricated devices with two culture compartments connected by 20 microtunnels. We confirmed that PNS and CNS neurons connected via synapses and formed a network. Additionally, calcium-imaging experiments showed that the bundles originating from the PNS neurons were functionally active and responded reproducibly to external stimuli. Next, we confirmed that CNS neurons showed an increase in calcium activity during electrical stimulation of networked bundles from PNS neurons in order to demonstrate the formation of functional cell-cell interactions. We also confirmed the formation of synapses between PNS neurons and mature cardiac cells. These results indicate that compartmentalized culture devices are promising tools for reconstructing network-wide connections between PNS neurons and various organs, and might help to understand patient-specific molecular and functional mechanisms under normal and pathological conditions.

  18. From Neurons to Newtons

    DEFF Research Database (Denmark)

    Nielsen, Bjørn Gilbert

    2001-01-01

    proteins generate forces, to the macroscopic levels where overt arm movements are vol- untarily controlled within an unpredictable environment by legions of neurons¯ring in orderly fashion. An extensive computer simulation system has been developed for this thesis, which at present contains a neural...... network scripting language for specifying arbitrary neural architectures, de¯nition ¯les for detailed spinal networks, various biologically realistic models of neurons, and dynamic synapses. Also included are structurally accurate models of intrafusal and extra-fusal muscle ¯bers and a general body...... that an explicit function may be derived which expresses the force that the spindle contractile elements must produce to exactly counter spindle unloading during muscle shortening. This information was used to calculate the corresponding "optimal" °-motoneuronal activity level. For some simple arm movement tasks...

  19. Criticality in Neuronal Networks

    Science.gov (United States)

    Friedman, Nir; Ito, Shinya; Brinkman, Braden A. W.; Shimono, Masanori; Deville, R. E. Lee; Beggs, John M.; Dahmen, Karin A.; Butler, Tom C.

    2012-02-01

    In recent years, experiments detecting the electrical firing patterns in slices of in vitro brain tissue have been analyzed to suggest the presence of scale invariance and possibly criticality in the brain. Much of the work done however has been limited in two ways: 1) the data collected is from local field potentials that do not represent the firing of individual neurons; 2) the analysis has been primarily limited to histograms. In our work we examine data based on the firing of individual neurons (spike data), and greatly extend the analysis by considering shape collapse and exponents. Our results strongly suggest that the brain operates near a tuned critical point of a highly distinctive universality class.

  20. Connected vehicle standards.

    Science.gov (United States)

    2016-01-01

    Connected vehicles have the potential to transform the way Americans travel by : allowing cars, buses, trucks, trains, traffic signals, smart phones, and other devices to : communicate through a safe, interoperable wireless network. A connected vehic...

  1. 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

    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......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...

  2. Direct Signaling from Astrocytes to Neurons in Cultures of Mammalian Brain Cells

    Science.gov (United States)

    Nedergaard, Maiken

    1994-03-01

    Although astrocytes have been considered to be supportive, rather than transmissive, in the adult nervous system, recent studies have challenged this assumption by demonstrating that astrocytes possess functional neurotransmitter receptors. Astrocytes are now shown to directly modulate the free cytosolic calcium, and hence transmission characteristics, of neighboring neurons. When a focal electric field potential was applied to single astrocytes in mixed cultures of rat forebrain astrocytes and neurons, a prompt elevation of calcium occurred in the target cell. This in turn triggered a wave of calcium increase, which propagated from astrocyte to astrocyte. Neurons resting on these astrocytes responded with large increases in their concentration of cytosolic calcium. The gap junction blocker octanol attenuated the neuronal response, which suggests that the astrocytic-neuronal signaling is mediated through intercellular connections rather than synaptically. This neuronal response to local astrocytic stimulation may mediate local intercellular communication within the brain.

  3. A multisensory centrifugal neuron in the olfactory pathway of heliothine moths

    DEFF Research Database (Denmark)

    Zhao, Xin-Cheng; Pfuhl, Gerit; Surlykke, Annemarie

    2013-01-01

    fine processes in the dorsomedial region of the protocerebrum and extensive neuronal branches with blebby terminals in all glomeruli of the antennal lobe. Its soma is located dorsally of the central body close to the brain midline. Mass-fills of antennal-lobe connections with protocerebral regions...... showed that the centrifugal neuron is, in each brain hemisphere, one within a small group of neurons having their somata clustered. In both species the neuron was excited during application of non-odorant airborne signals, including transient sound pulses of broad bandwidth and air velocity changes....... Additional responses to odors were recorded from the neuron in Heliothis virescens. The putative biological significance of the centrifugal antennal-lobe neuron is discussed with regard to its morphological and physiological properties. In particular, a possible role in multisensory processes underlying...

  4. Complete and phase synchronization in a heterogeneous small-world neuronal network

    International Nuclear Information System (INIS)

    Fang, Han; Qi-Shao, Lu; Quan-Bao, Ji; Marian, Wiercigroch

    2009-01-01

    Synchronous firing of neurons is thought to be important for information communication in neuronal networks. This paper investigates the complete and phase synchronization in a heterogeneous small-world chaotic Hindmarsh–Rose neuronal network. The effects of various network parameters on synchronization behaviour are discussed with some biological explanations. Complete synchronization of small-world neuronal networks is studied theoretically by the master stability function method. It is shown that the coupling strength necessary for complete or phase synchronization decreases with the neuron number, the node degree and the connection density are increased. The effect of heterogeneity of neuronal networks is also considered and it is found that the network heterogeneity has an adverse effect on synchrony. (general)

  5. Eph receptors and ephrins in neuron-astrocyte communication at synapses.

    Science.gov (United States)

    Murai, Keith K; Pasquale, Elena B

    2011-11-01

    Neuron-glia communication is essential for regulating the properties of synaptic connections in the brain. Astrocytes, in particular, play a critical and complex role in synapse development, maintenance, and plasticity. Likewise, neurons reciprocally influence astrocyte physiology. However, the molecular signaling events that enable astrocytes and neurons to effectively communicate with each other are only partially defined. Recent findings have revealed that Eph receptor tyrosine kinases and ephrins play an important role in contact-dependent neuron-glia communication at synapses. Upon binding, these two families of cell surface-associated proteins trigger bidirectional signaling events that regulate the structural and physiological properties of both neurons and astrocytes. This review will focus on the emerging role of Eph receptors and ephrins in neuron-astrocyte interaction at synapses and discuss implications for synaptic plasticity, behavior, and disease. Copyright © 2011 Wiley-Liss, Inc.

  6. Asymmetry in electrical coupling between neurons alters multistable firing behavior

    Science.gov (United States)

    Pisarchik, A. N.; Jaimes-Reátegui, R.; García-Vellisca, M. A.

    2018-03-01

    The role of asymmetry in electrical synaptic connection between two neuronal oscillators is studied in the Hindmarsh-Rose model. We demonstrate that the asymmetry induces multistability in spiking dynamics of the coupled neuronal oscillators. The coexistence of at least three attractors, one chaotic and two periodic orbits, for certain coupling strengths is demonstrated with time series, phase portraits, bifurcation diagrams, basins of attraction of the coexisting states, Lyapunov exponents, and standard deviations of peak amplitudes and interspike intervals. The experimental results with analog electronic circuits are in good agreement with the results of numerical simulations.

  7. Local-circuit phenotypes of layer 5 neurons in motor-frontal cortex of YFP-H mice

    Directory of Open Access Journals (Sweden)

    Jianing Yu

    2008-12-01

    Full Text Available Layer 5 pyramidal neurons comprise an important but heterogeneous group of cortical projection neurons. In motor-frontal cortex, these neurons are centrally involved in the cortical control of movement. Recent studies indicate that local excitatory networks in mouse motor-frontal cortex are dominated by descending pathways from layer 2/3 to 5. However, those pathways were identified in experiments involving unlabeled neurons in wild type mice. Here, to explore the possibility of class-specific connectivity in this descending pathway, we mapped the local sources of excitatory synaptic input to a genetically labeled population of cortical neurons: YFP-positive layer 5 neurons of YFP-H mice. We found, first, that in motor cortex, YFP-positive neurons were distributed in a double blade, consistent with the idea of layer 5B having greater thickness in frontal neocortex. Second, whereas unlabeled neurons in upper layer 5 received their strongest inputs from layer 2, YFP-positive neurons in the upper blade received prominent layer 3 inputs. Third, YFP-positive neurons exhibited distinct electrophysiological properties, including low spike frequency adaptation, as reported previously. Our results with this genetically labeled neuronal population indicate the presence of distinct local-circuit phenotypes among layer 5 pyramidal neurons in mouse motor-frontal cortex, and present a paradigm for investigating local circuit organization in other genetically labeled populations of cortical neurons.

  8. Connecting to Everyday Practices

    DEFF Research Database (Denmark)

    Iversen, Ole Sejer; Smith, Rachel Charlotte

    2012-01-01

    construction and reproduction of cultural heritage creating novel connections between self and others and between past, present and future. We present experiences from a current research project, the Digital Natives exhibition, in which social media was designed as an integral part of the exhibition to connect...... focusing on the connections between audiences practices and the museum exhibition....

  9. Communication through resonance in spiking neuronal networks.

    Science.gov (United States)

    Hahn, Gerald; Bujan, Alejandro F; Frégnac, Yves; Aertsen, Ad; Kumar, Arvind

    2014-08-01

    The cortex processes stimuli through a distributed network of specialized brain areas. This processing requires mechanisms that can route neuronal activity across weakly connected cortical regions. Routing models proposed thus far are either limited to propagation of spiking activity across strongly connected networks or require distinct mechanisms that create local oscillations and establish their coherence between distant cortical areas. Here, we propose a novel mechanism which explains how synchronous spiking activity propagates across weakly connected brain areas supported by oscillations. In our model, oscillatory activity unleashes network resonance that amplifies feeble synchronous signals and promotes their propagation along weak connections ("communication through resonance"). The emergence of coherent oscillations is a natural consequence of synchronous activity propagation and therefore the assumption of different mechanisms that create oscillations and provide coherence is not necessary. Moreover, the phase-locking of oscillations is a side effect of communication rather than its requirement. Finally, we show how the state of ongoing activity could affect the communication through resonance and propose that modulations of the ongoing activity state could influence information processing in distributed cortical networks.

  10. Analyzing the structure and function of neuronal circuits in zebrafish

    Directory of Open Access Journals (Sweden)

    Rainer eFriedrich

    2013-04-01

    Full Text Available The clever choice of animal models has been instrumental for many breakthrough discoveries in life sciences. One of the outstanding challenges in neuroscience is the in-depth analysis of neuronal circuits to understand how interactions between large numbers of neurons give rise to the computational power of the brain. A promising model organism to address this challenge is the zebrafish, not only because it is cheap, transparent and accessible to sophisticated genetic manipulations but also because it offers unique advantages for quantitative analyses of circuit structure and function. One of the most important advantages of zebrafish is its small brain size, both at larval and adult stages. Small brains enable exhaustive measurements of neuronal activity patterns by optical imaging and facilitate large-scale reconstructions of wiring diagrams by electron microscopic approaches. Such information is important, and probably essential, to obtain mechanistic insights into neuronal computations underlying higher brain functions and dysfunctions. This review provides a brief overview over current methods and motivations for dense reconstructions of neuronal activity and connectivity patterns. It then discusses selective advantages of zebrafish and provides examples how these advantages are exploited to study neuronal computations in the olfactory bulb.

  11. A map of octopaminergic neurons in the Drosophila brain.

    Science.gov (United States)

    Busch, Sebastian; Selcho, Mareike; Ito, Kei; Tanimoto, Hiromu

    2009-04-20

    The biogenic amine octopamine modulates diverse behaviors in invertebrates. At the single neuron level, the mode of action is well understood in the peripheral nervous system owing to its simple structure and accessibility. For elucidating the role of individual octopaminergic neurons in the modulation of complex behaviors, a detailed analysis of the connectivity in the central nervous system is required. Here we present a comprehensive anatomical map of candidate octopaminergic neurons in the adult Drosophila brain: including the supra- and subesophageal ganglia. Application of the Flp-out technique enabled visualization of 27 types of individual octopaminergic neurons. Based on their morphology and distribution of genetic markers, we found that most octopaminergic neurons project to multiple brain structures with a clear separation of dendritic and presynaptic regions. Whereas their major dendrites are confined to specific brain regions, each cell type targets different, yet defined, neuropils distributed throughout the central nervous system. This would allow them to constitute combinatorial modules assigned to the modulation of distinct neuronal processes. The map may provide an anatomical framework for the functional constitution of the octopaminergic system. It also serves as a model for the single-cell organization of a particular neurotransmitter in the brain. 2009 Wiley-Liss, Inc.

  12. Tunneling nanotube (TNT)-mediated neuron-to neuron transfer of pathological Tau protein assemblies.

    Science.gov (United States)

    Tardivel, Meryem; Bégard, Séverine; Bousset, Luc; Dujardin, Simon; Coens, Audrey; Melki, Ronald; Buée, Luc; Colin, Morvane

    2016-11-04

    A given cell makes exchanges with its neighbors through a variety of means ranging from diffusible factors to vesicles. Cells use also tunneling nanotubes (TNTs), filamentous-actin-containing membranous structures that bridge and connect cells. First described in immune cells, TNTs facilitate HIV-1 transfer and are found in various cell types, including neurons. We show that the microtubule-associated protein Tau, a key player in Alzheimer's disease, is a bona fide constituent of TNTs. This is important because Tau appears beside filamentous actin and myosin 10 as a specific marker of these fine protrusions of membranes and cytosol that are difficult to visualize. Furthermore, we observed that exogenous Tau species increase the number of TNTs established between primary neurons, thereby facilitating the intercellular transfer of Tau fibrils. In conclusion, Tau may contribute to the formation and function of the highly dynamic TNTs that may be involved in the prion-like propagation of Tau assemblies.

  13. Inhibitory coherence in a heterogeneous population of subthreshold and suprathreshold type-I neurons

    International Nuclear Information System (INIS)

    Kim, Sang-Yoon; Hong, Duk-Geun; Kim, Jean; Lim, Woochang

    2012-01-01

    We study inhibitory coherence (i.e. collective coherence by synaptic inhibition) in a population of globally coupled type-I neurons, which can fire at arbitrarily low frequency. No inhibitory coherence is observed in a homogeneous population composed of only subthreshold neurons, which exhibit noise-induced firings. In addition to subthreshold neurons, there exist spontaneously firing suprathreshold neurons in a noisy environment of a real brain. To take into consideration the effect of suprathreshold neurons on inhibitory coherence, we consider a heterogeneous population of subthreshold and suprathreshold neurons and investigate the inhibitory coherence by increasing the fraction of suprathreshold neurons P supra . As P supra passes a threshold P* supra , suprathreshold neurons begin to synchronize and play the role of coherent inhibitors for the emergence of inhibitory coherence. Thus, regularly oscillating population-averaged global potential appears for P supra > P* supra . For this coherent case, suprathreshold neurons exhibit sparse spike synchronization (i.e. individual potentials of suprathreshold neurons consist of coherent sparse spikings and coherent subthreshold small-amplitude hoppings). By virtue of their coherent inhibition, sparsely synchronized suprathreshold neurons suppress the noisy activity of subthreshold neurons. Thus, subthreshold neurons exhibit hopping synchronization (i.e. only coherent subthreshold hopping oscillations without spikings appear in the individual potentials of subthreshold neurons). We also characterize the inhibitory coherence in terms of the ‘statistical-mechanical’ spike-based and correlation-based measures, which quantify the average contributions of the microscopic individual spikes and individual potentials to the macroscopic global potential. Finally, the effect of sparse randomness of synaptic connectivity on the inhibitory coherence is briefly discussed. (paper)

  14. Genetic deficiency of GABA differentially regulates respiratory and non-respiratory motor neuron development.

    Directory of Open Access Journals (Sweden)

    Matthew J Fogarty

    Full Text Available Central nervous system GABAergic and glycinergic synaptic activity switches from postsynaptic excitation to inhibition during the stage when motor neuron numbers are being reduced, and when synaptic connections are being established onto and by motor neurons. In mice this occurs between embryonic (E day 13 and birth (postnatal day 0. Our previous work on mice lacking glycinergic transmission suggested that altered motor neuron activity levels correspondingly regulated motor neuron survival and muscle innervation for all respiratory and non respiratory motor neuron pools, during this period of development [1]. To determine if GABAergic transmission plays a similar role, we quantified motor neuron number and the extent of muscle innervation in four distinct regions of the brain stem and spinal cord; hypoglossal, phrenic, brachial and lumbar motor pools, in mice lacking the enzyme GAD67. These mice display a 90% drop in CNS GABA levels ( [2]; this study. For respiratory-based motor neurons (hypoglossal and phrenic motor pools, we have observed significant drops in motor neuron number (17% decline for hypoglossal and 23% decline for phrenic and muscle innervations (55% decrease. By contrast for non-respiratory motor neurons of the brachial lateral motor column, we have observed an increase in motor neuron number (43% increase and muscle innervations (99% increase; however for more caudally located motor neurons within the lumbar lateral motor column, we observed no change in either neuron number or muscle innervation. These results show in mice lacking physiological levels of GABA, there are distinct regional changes in motor neuron number and muscle innervation, which appear to be linked to their physiological function and to their rostral-caudal position within the developing spinal cord. Our results also suggest that for more caudal (lumbar regions of the spinal cord, the effect of GABA is less influential on motor neuron development compared to

  15. Parvalbumin+ Neurons and Npas1+ Neurons Are Distinct Neuron Classes in the Mouse External Globus Pallidus.

    Science.gov (United States)

    Hernández, Vivian M; Hegeman, Daniel J; Cui, Qiaoling; Kelver, Daniel A; Fiske, Michael P; Glajch, Kelly E; Pitt, Jason E; Huang, Tina Y; Justice, Nicholas J; Chan, C Savio

    2015-08-26

    Compelling evidence suggests that pathological activity of the external globus pallidus (GPe), a nucleus in the basal ganglia, contributes to the motor symptoms of a variety of movement disorders such as Parkinson's disease. Recent studies have challenged the idea that the GPe comprises a single, homogenous population of neurons that serves as a simple relay in the indirect pathway. However, we still lack a full understanding of the diversity of the neurons that make up the GPe. Specifically, a more precise classification scheme is needed to better describe the fundamental biology and function of different GPe neuron classes. To this end, we generated a novel multicistronic BAC (bacterial artificial chromosome) transgenic mouse line under the regulatory elements of the Npas1 gene. Using a combinatorial transgenic and immunohistochemical approach, we discovered that parvalbumin-expressing neurons and Npas1-expressing neurons in the GPe represent two nonoverlapping cell classes, amounting to 55% and 27% of the total GPe neuron population, respectively. These two genetically identified cell classes projected primarily to the subthalamic nucleus and to the striatum, respectively. Additionally, parvalbumin-expressing neurons and Npas1-expressing neurons were distinct in their autonomous and driven firing characteristics, their expression of intrinsic ion conductances, and their responsiveness to chronic 6-hydroxydopamine lesion. In summary, our data argue that parvalbumin-expressing neurons and Npas1-expressing neurons are two distinct functional classes of GPe neurons. This work revises our understanding of the GPe, and provides the foundation for future studies of its function and dysfunction. Until recently, the heterogeneity of the constituent neurons within the external globus pallidus (GPe) was not fully appreciated. We addressed this knowledge gap by discovering two principal GPe neuron classes, which were identified by their nonoverlapping expression of the

  16. Parvalbumin+ Neurons and Npas1+ Neurons Are Distinct Neuron Classes in the Mouse External Globus Pallidus

    Science.gov (United States)

    Hernández, Vivian M.; Hegeman, Daniel J.; Cui, Qiaoling; Kelver, Daniel A.; Fiske, Michael P.; Glajch, Kelly E.; Pitt, Jason E.; Huang, Tina Y.; Justice, Nicholas J.

    2015-01-01

    Compelling evidence suggests that pathological activity of the external globus pallidus (GPe), a nucleus in the basal ganglia, contributes to the motor symptoms of a variety of movement disorders such as Parkinson's disease. Recent studies have challenged the idea that the GPe comprises a single, homogenous population of neurons that serves as a simple relay in the indirect pathway. However, we still lack a full understanding of the diversity of the neurons that make up the GPe. Specifically, a more precise classification scheme is needed to better describe the fundamental biology and function of different GPe neuron classes. To this end, we generated a novel multicistronic BAC (bacterial artificial chromosome) transgenic mouse line under the regulatory elements of the Npas1 gene. Using a combinatorial transgenic and immunohistochemical approach, we discovered that parvalbumin-expressing neurons and Npas1-expressing neurons in the GPe represent two nonoverlapping cell classes, amounting to 55% and 27% of the total GPe neuron population, respectively. These two genetically identified cell classes projected primarily to the subthalamic nucleus and to the striatum, respectively. Additionally, parvalbumin-expressing neurons and Npas1-expressing neurons were distinct in their autonomous and driven firing characteristics, their expression of intrinsic ion conductances, and their responsiveness to chronic 6-hydroxydopamine lesion. In summary, our data argue that parvalbumin-expressing neurons and Npas1-expressing neurons are two distinct functional classes of GPe neurons. This work revises our understanding of the GPe, and provides the foundation for future studies of its function and dysfunction. SIGNIFICANCE STATEMENT Until recently, the heterogeneity of the constituent neurons within the external globus pallidus (GPe) was not fully appreciated. We addressed this knowledge gap by discovering two principal GPe neuron classes, which were identified by their nonoverlapping

  17. Metabolic reprogramming during neuronal differentiation.

    Science.gov (United States)

    Agostini, M; Romeo, F; Inoue, S; Niklison-Chirou, M V; Elia, A J; Dinsdale, D; Morone, N; Knight, R A; Mak, T W; Melino, G

    2016-09-01

    Newly generated neurons pass through a series of well-defined developmental stages, which allow them to integrate into existing neuronal circuits. After exit from the cell cycle, postmitotic neurons undergo neuronal migration, axonal elongation, axon pruning, dendrite morphogenesis and synaptic maturation and plasticity. Lack of a global metabolic analysis during early cortical neuronal development led us to explore the role of cellular metabolism and mitochondrial biology during ex vivo differentiation of primary cortical neurons. Unexpectedly, we observed a huge increase in mitochondrial biogenesis. Changes in mitochondrial mass, morphology and function were correlated with the upregulation of the master regulators of mitochondrial biogenesis, TFAM and PGC-1α. Concomitant with mitochondrial biogenesis, we observed an increase in glucose metabolism during neuronal differentiation, which was linked to an increase in glucose uptake and enhanced GLUT3 mRNA expression and platelet isoform of phosphofructokinase 1 (PFKp) protein expression. In addition, glutamate-glutamine metabolism was also increased during the differentiation of cortical neurons. We identified PI3K-Akt-mTOR signalling as a critical regulator role of energy metabolism in neurons. Selective pharmacological inhibition of these metabolic pathways indicate existence of metabolic checkpoint that need to be satisfied in order to allow neuronal differentiation.

  18. Selectivity of neuronal [3H]GABA accumulation in the visual cortex as revealed by Golgi staining of the labeled neurons

    International Nuclear Information System (INIS)

    Somogyi, P.; Freund, T.F.; Kisvarday, Z.F.; Halasz, N.

    1981-01-01

    [ 3 H]GABA was injected into the visual cortex of rats in vivo. The labeled amino acid was demonstrated by autoradiography using semithin sections of Golgi material. Selective accumulation was seen in the perikarya of Golgi-stained, gold-toned, aspinous stellate neurons. Spine-laden pyramidal-like cells did not show labeling. This method gives direct information about the dendritic arborization of a neuron, and its putative transmitter, and allows the identification of its synaptic connections. (Auth.)

  19. Subtype-Specific Corticostriatal Projection Neuron Developmental Gene Expression and Corticospinal Expression of the Paroxysmal Nonkinesigenic Dyskinesia Gene

    OpenAIRE

    Xu, Zhaoying

    2016-01-01

    The mammalian neocortex is responsible for motor control, integration of sensory information, perception, cognitive function, and consciousness. It is complex, yet highly organized, with six layers containing broad classes of excitatory projection neurons (along with interneurons) with diverse subtype and area identities. Corticostriatal projection neurons (CStrPN) are the major cortical efferent neurons connecting the cerebral cortex to the striatum of the basal ganglia, and are critically i...

  20. Network connectivity value.

    Science.gov (United States)

    Dragicevic, Arnaud; Boulanger, Vincent; Bruciamacchie, Max; Chauchard, Sandrine; Dupouey, Jean-Luc; Stenger, Anne

    2017-04-21

    In order to unveil the value of network connectivity, we formalize the construction of ecological networks in forest environments as an optimal control dynamic graph-theoretic problem. The network is based on a set of bioreserves and patches linked by ecological corridors. The node dynamics, built upon the consensus protocol, form a time evolutive Mahalanobis distance weighted by the opportunity costs of timber production. We consider a case of complete graph, where the ecological network is fully connected, and a case of incomplete graph, where the ecological network is partially connected. The results show that the network equilibrium depends on the size of the reception zone, while the network connectivity depends on the environmental compatibility between the ecological areas. Through shadow prices, we find that securing connectivity in partially connected networks is more expensive than in fully connected networks, but should be undertaken when the opportunity costs are significant. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Extracellular Monomeric and Aggregated Tau Efficiently Enter Human Neurons through Overlapping but Distinct Pathways

    Directory of Open Access Journals (Sweden)

    Lewis D. Evans

    2018-03-01

    Full Text Available Summary: In Alzheimer’s disease, neurofibrillary tangle pathology appears to spread along neuronal connections, proposed to be mediated by the release and uptake of abnormal, disease-specific forms of microtubule-binding protein tau MAPT. It is currently unclear whether transfer of tau between neurons is a toxic gain-of-function process in dementia or reflects a constitutive biological process. We report two entry mechanisms for monomeric tau to human neurons: a rapid dynamin-dependent phase typical of endocytosis and a second, slower actin-dependent phase of macropinocytosis. Aggregated tau entry is independent of actin polymerization and largely dynamin dependent, consistent with endocytosis and distinct from macropinocytosis, the major route for aggregated tau entry reported for non-neuronal cells. Anti-tau antibodies abrogate monomeric tau entry into neurons, but less efficiently in the case of aggregated tau, where internalized tau carries antibody with it into neurons. These data suggest that tau entry to human neurons is a physiological process and not a disease-specific phenomenon. : In contrast with predictions that transfer of the microtubule-associated protein tau between neurons is a toxic gain-of-function process in dementia, Evans et al. show that healthy human neurons efficiently take up both normal and aggregated tau, by distinct but overlapping uptake mechanisms. Keywords: Alzheimer’s disease, frontotemporal dementia, Tau, MAPT, iPSC, endocytosis, human neurons, intracellular transport

  2. A Ground-Based Analog for CNS Exposure to Space Radiation: A System for Integrating Microbeam Technology and Neuronal Culture

    Data.gov (United States)

    National Aeronautics and Space Administration — Problem Statement: The connection between radiation-induced neuronal damage and deficits in behavior and cellular function is still largely unknown. Previous studies...

  3. Neurons in the white matter of the adult human neocortex

    Directory of Open Access Journals (Sweden)

    M Luisa Suarez-Sola

    2009-06-01

    Full Text Available The white matter (WM of the adult human neocortex contains the so-called “interstitial neurons”. They are most numerous in the superficial WM underlying the cortical gyri, and decrease in density toward the deep WM. They are morphologically heterogeneous. A subgroup of interstitial neurons display pyramidal-cell like morphologies, characterized by a polarized dendritic tree with a dominant apical dendrite, and covered with a variable number of dendritic spines. In addition, a large contingent of interstitial neurons can be classified as interneurons based on their neurochemical profile as well as on morphological criteria. WM- interneurons have multipolar or bipolar shapes and express GABA and a variety of other neuronal markers, such as calbindin and calretinin, the extracellular matrix protein reelin, or neuropeptide Y, somatostatin, and nitric oxide synthase. The heterogeneity of interstitial neurons may be relevant for the pathogenesis of Alzheimer disease and schizophrenia. Interstitial neurons are most prominent in human brain, and only rudimentary in the brain of non-primate mammals. These evolutionary differences have precluded adequate experimental work on this cell population, which is usually considered as a relict of the subplate, a transient compartment proper of development and without a known function in the adult brain. The primate-specific prominence of the subplate in late fetal stages points to an important role in the establishment of interstitial neurons. Neurons in the adult WM may be actively involved in coordinating inter-areal connectivity and regulation of blood flow. Further studies in primates will be needed to elucidate the developmental history, adult components and activities of this large neuronal system.

  4. 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

  5. Focusing on neuronal cell-type specific mechanisms for brain circuit organization, function and dysfunction

    Institute of Scientific and Technical Information of China (English)

    Lu Li

    2017-01-01

    Mammalian brain circuits consist of dynamically interconnected neurons with characteristic morphology, physiology, connectivity and genetics which are often called neuronal cell types. Neuronal cell types have been considered as building blocks of brain circuits, but knowledge of how neuron types or subtypes connect to and interact with each other to perform neural computation is still lacking. Such mechanistic insights are critical not only to our understanding of normal brain functions, such as perception, motion and cognition, but also to brain disorders including Alzheimer's disease, Schizophrenia and epilepsy, to name a few. Thus it is necessary to carry out systematic and standardized studies on neuronal cell-type specific mechanisms for brain circuit organization and function, which will provide good opportunities to bridge basic and clinical research. Here based on recent technology advancements, we discuss the strategy to target and manipulate specific populations of neuronsin vivo to provide unique insights on how neuron types or subtypes behave, interact, and generate emergent properties in a fully connected brain network. Our approach is highlighted by combining transgenic animal models, targeted electrophysiology and imaging with robotics, thus complete and standardized mapping ofin vivo properties of genetically defined neuron populations can be achieved in transgenic mouse models, which will facilitate the development of novel therapeutic strategies for brain disorders.

  6. Properties of Neurons in External Globus Pallidus Can Support Optimal Action Selection

    Science.gov (United States)

    Bogacz, Rafal; Martin Moraud, Eduardo; Abdi, Azzedine; Magill, Peter J.; Baufreton, Jérôme

    2016-01-01

    The external globus pallidus (GPe) is a key nucleus within basal ganglia circuits that are thought to be involved in action selection. A class of computational models assumes that, during action selection, the basal ganglia compute for all actions available in a given context the probabilities that they should be selected. These models suggest that a network of GPe and subthalamic nucleus (STN) neurons computes the normalization term in Bayes’ equation. In order to perform such computation, the GPe needs to send feedback to the STN equal to a particular function of the activity of STN neurons. However, the complex form of this function makes it unlikely that individual GPe neurons, or even a single GPe cell type, could compute it. Here, we demonstrate how this function could be computed within a network containing two types of GABAergic GPe projection neuron, so-called ‘prototypic’ and ‘arkypallidal’ neurons, that have different response properties in vivo and distinct connections. We compare our model predictions with the experimentally-reported connectivity and input-output functions (f-I curves) of the two populations of GPe neurons. We show that, together, these dichotomous cell types fulfil the requirements necessary to compute the function needed for optimal action selection. We conclude that, by virtue of their distinct response properties and connectivities, a network of arkypallidal and prototypic GPe neurons comprises a neural substrate capable of supporting the computation of the posterior probabilities of actions. PMID:27389780

  7. Cortical Divergent Projections in Mice Originate from Two Sequentially Generated, Distinct Populations of Excitatory Cortical Neurons with Different Initial Axonal Outgrowth Characteristics.

    Science.gov (United States)

    Hatanaka, Yumiko; Namikawa, Tomohiro; Yamauchi, Kenta; Kawaguchi, Yasuo

    2016-05-01

    Excitatory cortical neurons project to various subcortical and intracortical regions, and exhibit diversity in their axonal connections. Although this diversity may develop from primary axons, how many types of axons initially occur remains unknown. Using a sparse-labeling in utero electroporation method, we investigated the axonal outgrowth of these neurons in mice and correlated the data with axonal projections in adults. Examination of lateral cortex neurons labeled during the main period of cortical neurogenesis (E11.5-E15.5) indicated that axonal outgrowth commonly occurs in the intermediate zone. Conversely, the axonal direction varied; neurons labeled before E12.5 and the earliest cortical plate neurons labeled at E12.5 projected laterally, whereas neurons labeled thereafter projected medially. The expression of Ctip2 and Satb2 and the layer destinations of these neurons support the view that lateral and medial projection neurons are groups of prospective subcortical and callosal projection neurons, respectively. Consistently, birthdating experiments demonstrated that presumptive lateral projection neurons were generated earlier than medial projection neurons, even within the same layer. These results suggest that the divergent axonal connections of excitatory cortical neurons begin from two types of primary axons, which originate from two sequentially generated distinct subpopulations: early-born lateral (subcortical) and later-born medial (callosal) projection neuron groups. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  8. How structure determines correlations in neuronal networks.

    Directory of Open Access Journals (Sweden)

    Volker Pernice

    2011-05-01

    Full Text Available Networks are becoming a ubiquitous metaphor for the understanding of complex biological systems, spanning the range between molecular signalling pathways, neural networks in the brain, and interacting species in a food web. In many models, we face an intricate interplay between the topology of the network and the dynamics of the system, which is generally very hard to disentangle. A dynamical feature that has been subject of intense research in various fields are correlations between the noisy activity of nodes in a network. We consider a class of systems, where discrete signals are sent along the links of the network. Such systems are of particular relevance in neuroscience, because they provide models for networks of neurons that use action potentials for communication. We study correlations in dynamic networks with arbitrary topology, assuming linear pulse coupling. With our novel approach, we are able to understand in detail how specific structural motifs affect pairwise correlations. Based on a power series decomposition of the covariance matrix, we describe the conditions under which very indirect interactions will have a pronounced effect on correlations and population dynamics. In random networks, we find that indirect interactions may lead to a broad distribution of activation levels with low average but highly variable correlations. This phenomenon is even more pronounced in networks with distance dependent connectivity. In contrast, networks with highly connected hubs or patchy connections often exhibit strong average correlations. Our results are particularly relevant in view of new experimental techniques that enable the parallel recording of spiking activity from a large number of neurons, an appropriate interpretation of which is hampered by the currently limited understanding of structure-dynamics relations in complex networks.

  9. Sugar Antennae for Guidance Signals: Syndecans and Glypicans Integrate Directional Cues for Navigating Neurons

    Directory of Open Access Journals (Sweden)

    Christa Rhiner

    2006-01-01

    Full Text Available Attractive and repulsive signals guide migrating nerve cells in all directions when the nervous system starts to form. The neurons extend thin processes, axons, that connect over wide distances with other brain cells to form a complicated neuronal network. One of the most fascinating questions in neuroscience is how the correct wiring of billions of nerve cells in our brain is controlled. Several protein families are known to serve as guidance cues for navigating neurons and axons. Nevertheless, the combinatorial potential of these proteins seems to be insufficient to sculpt the entire neuronal network and the appropriate formation of connections. Recently, heparan sulfate proteoglycans (HSPGs, which are present on the cell surface of neurons and in the extracellular matrix through which neurons and axons migrate, have been found to play a role in regulating cell migration and axon guidance. Intriguingly, the large number of distinct modifications that can be put onto the sugar side chains of these PGs would in principle allow for an enormous diversity of HSPGs, which could help in regulating the vast number of guidance choices taken by individual neurons. In this review, we will focus on the role of the cell surface HSPGs syndecan and glypican and specific HS modifications in promoting neuronal migration, axon guidance, and synapse formation.

  10. Wiring economy and volume exclusion determine neuronal placement in the Drosophila brain.

    Science.gov (United States)

    Rivera-Alba, Marta; Vitaladevuni, Shiv N; Mishchenko, Yuriy; Mischenko, Yuriy; Lu, Zhiyuan; Takemura, Shin-Ya; Scheffer, Lou; Meinertzhagen, Ian A; Chklovskii, Dmitri B; de Polavieja, Gonzalo G

    2011-12-06

    Wiring economy has successfully explained the individual placement of neurons in simple nervous systems like that of Caenorhabditis elegans [1-3] and the locations of coarser structures like cortical areas in complex vertebrate brains [4]. However, it remains unclear whether wiring economy can explain the placement of individual neurons in brains larger than that of C. elegans. Indeed, given the greater number of neuronal interconnections in larger brains, simply minimizing the length of connections results in unrealistic configurations, with multiple neurons occupying the same position in space. Avoiding such configurations, or volume exclusion, repels neurons from each other, thus counteracting wiring economy. Here we test whether wiring economy together with volume exclusion can explain the placement of neurons in a module of the Drosophila melanogaster brain known as lamina cartridge [5-13]. We used newly developed techniques for semiautomated reconstruction from serial electron microscopy (EM) [14] to obtain the shapes of neurons, the location of synapses, and the resultant synaptic connectivity. We show that wiring length minimization and volume exclusion together can explain the structure of the lamina microcircuit. Therefore, even in brains larger than that of C. elegans, at least for some circuits, optimization can play an important role in individual neuron placement. Copyright © 2011 Elsevier Ltd. All rights reserved.

  11. Imitation, mirror neurons and autism

    OpenAIRE

    Williams, Justin H.G.; Whiten, Andrew; Suddendorf, Thomas; Perrett, David I.

    2001-01-01

    Various deficits in the cognitive functioning of people with autism have been documented in recent years but these provide only partial explanations for the condition. We focus instead on an imitative disturbance involving difficulties both in copying actions and in inhibiting more stereotyped mimicking, such as echolalia. A candidate for the neural basis of this disturbance may be found in a recently discovered class of neurons in frontal cortex, 'mirror neurons' (MNs). These neurons show ac...

  12. The biophysics of neuronal growth

    International Nuclear Information System (INIS)

    Franze, Kristian; Guck, Jochen

    2010-01-01

    For a long time, neuroscience has focused on biochemical, molecular biological and electrophysiological aspects of neuronal physiology and pathology. However, there is a growing body of evidence indicating the importance of physical stimuli for neuronal growth and development. In this review we briefly summarize the historical background of neurobiophysics and give an overview over the current understanding of neuronal growth from a physics perspective. We show how biophysics has so far contributed to a better understanding of neuronal growth and discuss current inconsistencies. Finally, we speculate how biophysics may contribute to the successful treatment of lesions to the central nervous system, which have been considered incurable until very recently.

  13. Handbook of networking & connectivity

    CERN Document Server

    McClain, Gary R

    1994-01-01

    Handbook of Networking & Connectivity focuses on connectivity standards in use, including hardware and software options. The book serves as a guide for solving specific problems that arise in designing and maintaining organizational networks.The selection first tackles open systems interconnection, guide to digital communications, and implementing TCP/IP in an SNA environment. Discussions focus on elimination of the SNA backbone, routing SNA over internets, connectionless versus connection-oriented networks, internet concepts, application program interfaces, basic principles of layering, proto

  14. 78 FR 55684 - ConnectED Workshop

    Science.gov (United States)

    2013-09-11

    ... tools move everything from homework assignments to testing into the cloud. The workshop will explore possible strategies to connect virtually all of our students to next-generation broadband in a timely, cost-effective way. It will also share promising practices, from NTIA's Broadband Technology Opportunities...

  15. The Connected Traveler

    Energy Technology Data Exchange (ETDEWEB)

    Young, Stanley

    2017-04-24

    The Connected Traveler project is a multi-disciplinary undertaking that seeks to validate potential for transformative transportation system energy savings by incentivizing energy efficient travel behavior.

  16. Connections: All Issues

    Science.gov (United States)

    Goals Recycling Green Purchasing Pollution Prevention Reusing Water Resources Environmental Management Plateau, and more... Connections Newsletter December 2016 December 2016 Science-themed gifts available at

  17. Anatomic and Molecular Development of Corticostriatal Projection Neurons in Mice

    OpenAIRE

    Sohur, U. Shivraj; Padmanabhan, Hari K.; Kotchetkov, Ivan S.; Menezes, Joao R.L.; Macklis, Jeffrey D.

    2012-01-01

    Corticostriatal projection neurons (CStrPN) project from the neocortex to ipsilateral and contralateral striata to control and coordinate motor programs and movement. They are clinically important as the predominant cortical population that degenerates in Huntington's disease and corticobasal ganglionic degeneration, and their injury contributes to multiple forms of cerebral palsy. Together with their well-studied functions in motor control, these clinical connections make them a functionally...

  18. The Intrinsic Electrophysiological Properties of Mammalian Neurons: Insights into Central Nervous System Function

    Science.gov (United States)

    Llinas, Rodolfo R.

    1988-12-01

    This article reviews the electroresponsive properties of single neurons in the mammalian central nervous system (CNS). In some of these cells the ionic conductances responsible for their excitability also endow them with autorhythmic electrical oscillatory properties. Chemical or electrical synaptic contacts between these neurons often result in network oscillations. In such networks, autorhytmic neurons may act as true oscillators (as pacemakers) or as resonators (responding preferentially to certain firing frequencies). Oscillations and resonance in the CNS are proposed to have diverse functional roles, such as (i) determining global functional states (for example, sleep-wakefulness or attention), (ii) timing in motor coordination, and (iii) specifying connectivity during development. Also, oscillation, especially in the thalamo-cortical circuits, may be related to certain neurological and psychiatric disorders. This review proposes that the autorhythmic electrical properties of central neurons and their connectivity form the basis for an intrinsic functional coordinate system that provides internal context to sensory input.

  19. Hyper-Connectivity and Hyper-Plasticity in the Medial Prefrontal Cortex in the Valproic Acid Animal Model of Autism

    OpenAIRE

    Rinaldi, Tania; Perrodin, Catherine; Markram, Henry

    2008-01-01

    The prefrontal cortex has been extensively implicated in autism to explain deficits in executive and other higher-order functions related to cognition, language, sociability and emotion. The possible changes at the level of the neuronal microcircuit are however not known. We studied microcircuit alterations in the prefrontal cortex in the valproic acid rat model of autism and found that the layer 5 pyramidal neurons are connected to significantly more neighbouring neurons than in controls. Th...

  20. The Neuronal Ceroid-Lipofuscinoses

    Science.gov (United States)

    Bennett, Michael J.; Rakheja, Dinesh

    2013-01-01

    The neuronal ceroid-lipofuscinoses (NCL's, Batten disease) represent a group of severe neurodegenerative diseases, which mostly present in childhood. The phenotypes are similar and include visual loss, seizures, loss of motor and cognitive function, and early death. At autopsy, there is massive neuronal loss with characteristic storage in…

  1. The straintronic spin-neuron

    International Nuclear Information System (INIS)

    Biswas, Ayan K; Bandyopadhyay, Supriyo; Atulasimha, Jayasimha

    2015-01-01

    In artificial neural networks, neurons are usually implemented with highly dissipative CMOS-based operational amplifiers. A more energy-efficient implementation is a ‘spin-neuron’ realized with a magneto-tunneling junction (MTJ) that is switched with a spin-polarized current (representing weighted sum of input currents) that either delivers a spin transfer torque or induces domain wall motion in the soft layer of the MTJ to mimic neuron firing. Here, we propose and analyze a different type of spin-neuron in which the soft layer of the MTJ is switched with mechanical strain generated by a voltage (representing weighted sum of input voltages) and term it straintronic spin-neuron. It dissipates orders of magnitude less energy in threshold operations than the traditional current-driven spin neuron at 0 K temperature and may even be faster. We have also studied the room-temperature firing behaviors of both types of spin neurons and find that thermal noise degrades the performance of both types, but the current-driven type is degraded much more than the straintronic type if both are optimized for maximum energy-efficiency. On the other hand, if both are designed to have the same level of thermal degradation, then the current-driven version will dissipate orders of magnitude more energy than the straintronic version. Thus, the straintronic spin-neuron is superior to current-driven spin neurons. (paper)

  2. Spatiotemporal intracellular dynamics of neurotrophin and its receptors. Implications for neurotrophin signaling and neuronal function.

    Science.gov (United States)

    Bronfman, F C; Lazo, O M; Flores, C; Escudero, C A

    2014-01-01

    Neurons possess a polarized morphology specialized to contribute to neuronal networks, and this morphology imposes an important challenge for neuronal signaling and communication. The physiology of the network is regulated by neurotrophic factors that are secreted in an activity-dependent manner modulating neuronal connectivity. Neurotrophins are a well-known family of neurotrophic factors that, together with their cognate receptors, the Trks and the p75 neurotrophin receptor, regulate neuronal plasticity and survival and determine the neuronal phenotype in healthy and regenerating neurons. Is it now becoming clear that neurotrophin signaling and vesicular transport are coordinated to modify neuronal function because disturbances of vesicular transport mechanisms lead to disturbed neurotrophin signaling and to diseases of the nervous system. This chapter summarizes our current understanding of how the regulated secretion of neurotrophin, the distribution of neurotrophin receptors in different locations of neurons, and the intracellular transport of neurotrophin-induced signaling in distal processes are achieved to allow coordinated neurotrophin signaling in the cell body and axons.

  3. The Role of Adult-Born Neurons in the Constantly Changing Olfactory Bulb Network

    Directory of Open Access Journals (Sweden)

    Sarah Malvaut

    2016-01-01

    Full Text Available The adult mammalian brain is remarkably plastic and constantly undergoes structurofunctional modifications in response to environmental stimuli. In many regions plasticity is manifested by modifications in the efficacy of existing synaptic connections or synapse formation and elimination. In a few regions, however, plasticity is brought by the addition of new neurons that integrate into established neuronal networks. This type of neuronal plasticity is particularly prominent in the olfactory bulb (OB where thousands of neuronal progenitors are produced on a daily basis in the subventricular zone (SVZ and migrate along the rostral migratory stream (RMS towards the OB. In the OB, these neuronal precursors differentiate into local interneurons, mature, and functionally integrate into the bulbar network by establishing output synapses with principal neurons. Despite continuous progress, it is still not well understood how normal functioning of the OB is preserved in the constantly remodelling bulbar network and what role adult-born neurons play in odor behaviour. In this review we will discuss different levels of morphofunctional plasticity effected by adult-born neurons and their functional role in the adult OB and also highlight the possibility that different subpopulations of adult-born cells may fulfill distinct functions in the OB neuronal network and odor behaviour.

  4. The Role of Adult-Born Neurons in the Constantly Changing Olfactory Bulb Network

    Science.gov (United States)

    Malvaut, Sarah; Saghatelyan, Armen

    2016-01-01

    The adult mammalian brain is remarkably plastic and constantly undergoes structurofunctional modifications in response to environmental stimuli. In many regions plasticity is manifested by modifications in the efficacy of existing synaptic connections or synapse formation and elimination. In a few regions, however, plasticity is brought by the addition of new neurons that integrate into established neuronal networks. This type of neuronal plasticity is particularly prominent in the olfactory bulb (OB) where thousands of neuronal progenitors are produced on a daily basis in the subventricular zone (SVZ) and migrate along the rostral migratory stream (RMS) towards the OB. In the OB, these neuronal precursors differentiate into local interneurons, mature, and functionally integrate into the bulbar network by establishing output synapses with principal neurons. Despite continuous progress, it is still not well understood how normal functioning of the OB is preserved in the constantly remodelling bulbar network and what role adult-born neurons play in odor behaviour. In this review we will discuss different levels of morphofunctional plasticity effected by adult-born neurons and their functional role in the adult OB and also highlight the possibility that different subpopulations of adult-born cells may fulfill distinct functions in the OB neuronal network and odor behaviour. PMID:26839709

  5. Archives: Mathematics Connection

    African Journals Online (AJOL)

    Items 1 - 9 of 9 ... Archives: Mathematics Connection. Journal Home > Archives: Mathematics Connection. Log in or Register to get access to full text downloads. Username, Password, Remember me, or Register · Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue · Archives. 1 - 9 of 9 Items. 2011 ...

  6. Connective Tissue Disorders

    Science.gov (United States)

    ... of connective tissue. Over 200 disorders that impact connective tissue. There are different types: Genetic disorders, such as Ehlers-Danlos syndrome, Marfan syndrome, and osteogenesis imperfecta Autoimmune disorders, such as lupus and scleroderma Cancers, like some types of soft tissue sarcoma Each ...

  7. Synaptic Plasticity and Spike Synchronisation in Neuronal Networks

    Science.gov (United States)

    Borges, Rafael R.; Borges, Fernando S.; Lameu, Ewandson L.; Protachevicz, Paulo R.; Iarosz, Kelly C.; Caldas, Iberê L.; Viana, Ricardo L.; Macau, Elbert E. N.; Baptista, Murilo S.; Grebogi, Celso; Batista, Antonio M.

    2017-12-01

    Brain plasticity, also known as neuroplasticity, is a fundamental mechanism of neuronal adaptation in response to changes in the environment or due to brain injury. In this review, we show our results about the effects of synaptic plasticity on neuronal networks composed by Hodgkin-Huxley neurons. We show that the final topology of the evolved network depends crucially on the ratio between the strengths of the inhibitory and excitatory synapses. Excitation of the same order of inhibition revels an evolved network that presents the rich-club phenomenon, well known to exist in the brain. For initial networks with considerably larger inhibitory strengths, we observe the emergence of a complex evolved topology, where neurons sparsely connected to other neurons, also a typical topology of the brain. The presence of noise enhances the strength of both types of synapses, but if the initial network has synapses of both natures with similar strengths. Finally, we show how the synchronous behaviour of the evolved network will reflect its evolved topology.

  8. Identifying Chaotic FitzHugh–Nagumo Neurons Using Compressive Sensing

    Directory of Open Access Journals (Sweden)

    Ri-Qi Su

    2014-07-01

    Full Text Available We develop a completely data-driven approach to reconstructing coupled neuronal networks that contain a small subset of chaotic neurons. Such chaotic elements can be the result of parameter shift in their individual dynamical systems and may lead to abnormal functions of the network. To accurately identify the chaotic neurons may thus be necessary and important, for example, applying appropriate controls to bring the network to a normal state. However, due to couplings among the nodes, the measured time series, even from non-chaotic neurons, would appear random, rendering inapplicable traditional nonlinear time-series analysis, such as the delay-coordinate embedding method, which yields information about the global dynamics of the entire network. Our method is based on compressive sensing. In particular, we demonstrate that identifying chaotic elements can be formulated as a general problem of reconstructing the nodal dynamical systems, network connections and all coupling functions, as well as their weights. The working and efficiency of the method are illustrated by using networks of non-identical FitzHugh–Nagumo neurons with randomly-distributed coupling weights.

  9. PERSPECTIVE: Electrical activity enhances neuronal survival and regeneration

    Science.gov (United States)

    Corredor, Raul G.; Goldberg, Jeffrey L.

    2009-10-01

    The failure of regeneration in the central nervous system (CNS) remains an enormous scientific and clinical challenge. After injury or in degenerative diseases, neurons in the adult mammalian CNS fail to regrow their axons and reconnect with their normal targets, and furthermore the neurons frequently die and are not normally replaced. While significant progress has been made in understanding the molecular basis for this lack of regenerative ability, a second approach has gained momentum: replacing lost neurons or lost connections with artificial electrical circuits that interface with the nervous system. In the visual system, gene therapy-based 'optogenetics' prostheses represent a competing technology. Now, the two approaches are converging, as recent data suggest that electrical activity itself, via the molecular signaling pathways such activity stimulates, is sufficient to induce neuronal survival and regeneration, particularly in retinal ganglion cells. Here, we review these data, discuss the effects of electrical activity on neurons' molecular signaling pathways and propose specific mechanisms by which exogenous electrical activity may be acting to enhance survival and regeneration.

  10. Midcervical neuronal discharge patterns during and following hypoxia

    Science.gov (United States)

    Sandhu, M. S.; Baekey, D. M.; Maling, N. G.; Sanchez, J. C.; Reier, P. J.

    2014-01-01

    Anatomical evidence indicates that midcervical interneurons can be synaptically coupled with phrenic motoneurons. Accordingly, we hypothesized that interneurons in the C3–C4 spinal cord can display discharge patterns temporally linked with inspiratory phrenic motor output. Anesthetized adult rats were studied before, during, and after a 4-min bout of moderate hypoxia. Neuronal discharge in C3–C4 lamina I–IX was monitored using a multielectrode array while phrenic nerve activity was extracellularly recorded. For the majority of cells, spike-triggered averaging (STA) of ipsilateral inspiratory phrenic nerve activity based on neuronal discharge provided no evidence of discharge synchrony. However, a distinct STA phrenic peak with a 6.83 ± 1.1 ms lag was present for 5% of neurons, a result that indicates a monosynaptic connection with phrenic motoneurons. The majority (93%) of neurons changed discharge rate during hypoxia, and the diverse responses included both increased and decreased firing. Hypoxia did not change the incidence of STA peaks in the phrenic nerve signal. Following hypoxia, 40% of neurons continued to discharge at rates above prehypoxia values (i.e., short-term potentiation, STP), and cells with initially low discharge rates were more likely to show STP (P phrenic motoneuron pool, and these cells can modulate inspiratory phrenic output. In addition, the C3–C4 propriospinal network shows a robust and complex pattern of activation both during and following an acute bout of hypoxia. PMID:25552641

  11. Decreased adrenoceptor stimulation in heart failure rats reduces NGF expression by cardiac parasympathetic neurons

    OpenAIRE

    Hasan, Wohaib; Smith, Peter G

    2013-01-01

    Postganglionic cardiac parasympathetic and sympathetic nerves are physically proximate in atrial cardiac tissue allowing reciprocal inhibition of neurotransmitter release, depending on demands from central cardiovascular centers or reflex pathways. Parasympathetic cardiac ganglion (CG) neurons synthesize and release the sympathetic neurotrophin nerve growth factor (NGF), which may serve to maintain these close connections. In this study we investigated whether NGF synthesis by CG neurons is a...

  12. Delay-dependent asymptotic stability of a two-neuron system with different time delays

    International Nuclear Information System (INIS)

    Tu Fenghua; Liao Xiaofeng; Zhang Wei

    2006-01-01

    In this paper, we consider a two-neuron system with time-delayed connections between neurons. Based on the construction of Lyapunov functionals, we obtain sufficient criteria to ensure local and global asymptotic stability of the equilibrium of the neural network. The obtained conditions are shown to be less conservative and restrictive than those reported in the literature. Some examples are included to illustrate our results

  13. Chimera states in a multilayer network of coupled and uncoupled neurons

    Science.gov (United States)

    Majhi, Soumen; Perc, Matjaž; Ghosh, Dibakar

    2017-07-01

    We study the emergence of chimera states in a multilayer neuronal network, where one layer is composed of coupled and the other layer of uncoupled neurons. Through the multilayer structure, the layer with coupled neurons acts as the medium by means of which neurons in the uncoupled layer share information in spite of the absence of physical connections among them. Neurons in the coupled layer are connected with electrical synapses, while across the two layers, neurons are connected through chemical synapses. In both layers, the dynamics of each neuron is described by the Hindmarsh-Rose square wave bursting dynamics. We show that the presence of two different types of connecting synapses within and between the two layers, together with the multilayer network structure, plays a key role in the emergence of between-layer synchronous chimera states and patterns of synchronous clusters. In particular, we find that these chimera states can emerge in the coupled layer regardless of the range of electrical synapses. Even in all-to-all and nearest-neighbor coupling within the coupled layer, we observe qualitatively identical between-layer chimera states. Moreover, we show that the role of information transmission delay between the two layers must not be neglected, and we obtain precise parameter bounds at which chimera states can be observed. The expansion of the chimera region and annihilation of cluster and fully coherent states in the parameter plane for increasing values of inter-layer chemical synaptic time delay are illustrated using effective range measurements. These results are discussed in the light of neuronal evolution, where the coexistence of coherent and incoherent dynamics during the developmental stage is particularly likely.

  14. Neuronal representations of stimulus associations develop in the temporal lobe during learning

    OpenAIRE

    Messinger, Adam; Squire, Larry R.; Zola, Stuart M.; Albright, Thomas D.

    2001-01-01

    Visual stimuli that are frequently seen together become associated in long-term memory, such that the sight of one stimulus readily brings to mind the thought or image of the other. It has been hypothesized that acquisition of such long-term associative memories proceeds via the strengthening of connections between neurons representing the associated stimuli, such that a neuron initially responding only to one stimulus of an associated pair eventually comes to respond to both. Consistent with...

  15. Pulsed neural networks consisting of single-flux-quantum spiking neurons

    International Nuclear Information System (INIS)

    Hirose, T.; Asai, T.; Amemiya, Y.

    2007-01-01

    An inhibitory pulsed neural network was developed for brain-like information processing, by using single-flux-quantum (SFQ) circuits. It consists of spiking neuron devices that are coupled to each other through all-to-all inhibitory connections. The network selects neural activity. The operation of the neural network was confirmed by computer simulation. SFQ neuron devices can imitate the operation of the inhibition phenomenon of neural networks

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

    International Nuclear Information System (INIS)

    Lin Min; Wang Gang; Chen Tianlun

    2006-01-01

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

  17. Ca2+-induced uncoupling of Aplysia bag cell neurons.

    Science.gov (United States)

    Dargaei, Zahra; Standage, Dominic; Groten, Christopher J; Blohm, Gunnar; Magoski, Neil S

    2015-02-01

    Electrical transmission is a dynamically regulated form of communication and key to synchronizing neuronal activity. The bag cell neurons of Aplysia are a group of electrically coupled neuroendocrine cells that initiate ovulation by secreting egg-laying hormone during a prolonged period of synchronous firing called the afterdischarge. Accompanying the afterdischarge is an increase in intracellular Ca2+ and the activation of protein kinase C (PKC). We used whole cell recording from paired cultured bag cell neurons to demonstrate that electrical coupling is regulated by both Ca2+ and PKC. Elevating Ca2+ with a train of voltage steps, mimicking the onset of the afterdischarge, decreased junctional current for up to 30 min. Inhibition was most effective when Ca2+ entry occurred in both neurons. Depletion of Ca2+ from the mitochondria, but not the endoplasmic reticulum, also attenuated the electrical synapse. Buffering Ca2+ with high intracellular EGTA or inhibiting calmodulin kinase prevented uncoupling. Furthermore, activating PKC produced a small but clear decrease in junctional current, while triggering both Ca2+ influx and PKC inhibited the electrical synapse to a greater extent than Ca2+ alone. Finally, the amplitude and time course of the postsynaptic electrotonic response were attenuated after Ca2+ influx. A mathematical model of electrically connected neurons showed that excessive coupling reduced recruitment of the cells to fire, whereas less coupling led to spiking of essentially all neurons. Thus a decrease in electrical synapses could promote the afterdischarge by ensuring prompt recovery of electrotonic potentials or making the neurons more responsive to current spreading through the network. Copyright © 2015 the American Physiological Society.

  18. Generalized connectivity of graphs

    CERN Document Server

    Li, Xueliang

    2016-01-01

    Noteworthy results, proof techniques, open problems and conjectures in generalized (edge-) connectivity are discussed in this book. Both theoretical and practical analyses for generalized (edge-) connectivity of graphs are provided. Topics covered in this book include: generalized (edge-) connectivity of graph classes, algorithms, computational complexity, sharp bounds, Nordhaus-Gaddum-type results, maximum generalized local connectivity, extremal problems, random graphs, multigraphs, relations with the Steiner tree packing problem and generalizations of connectivity. This book enables graduate students to understand and master a segment of graph theory and combinatorial optimization. Researchers in graph theory, combinatorics, combinatorial optimization, probability, computer science, discrete algorithms, complexity analysis, network design, and the information transferring models will find this book useful in their studies.

  19. Neuronal discrimination capacity

    International Nuclear Information System (INIS)

    Deng Yingchun; Williams, Peter; Feng Jianfeng; Liu Feng

    2003-01-01

    We explore neuronal mechanisms of discriminating between masked signals. It is found that when the correlation between input signals is zero, the output signals are separable if and only if input signals are separable. With positively (negatively) correlated signals, the output signals are separable (mixed) even when input signals are mixed (separable). Exact values of discrimination capacity are obtained for two most interesting cases: the exactly balanced inhibitory and excitatory input case and the uncorrelated input case. Interestingly, the discrimination capacity obtained in these cases is independent of model parameters, input distribution and is universal. Our results also suggest a functional role of inhibitory inputs and correlated inputs or, more generally, the large variability of efferent spike trains observed in in vivo experiments: the larger the variability of efferent spike trains, the easier it is to discriminate between masked input signals

  20. Neuronal discrimination capacity

    Energy Technology Data Exchange (ETDEWEB)

    Deng Yingchun [Department of Mathematics, Hunan Normal University 410081, Changsha (China); COGS, University of Sussex at Brighton, BN1 9QH (United Kingdom); Williams, Peter; Feng Jianfeng [COGS, University of Sussex at Brighton, BN1 9QH (United Kingdom); Liu Feng [COGS, University of Sussex at Brighton, BN1 9QH (United Kingdom); Physics Department, Nanjing University (China)

    2003-12-19

    We explore neuronal mechanisms of discriminating between masked signals. It is found that when the correlation between input signals is zero, the output signals are separable if and only if input signals are separable. With positively (negatively) correlated signals, the output signals are separable (mixed) even when input signals are mixed (separable). Exact values of discrimination capacity are obtained for two most interesting cases: the exactly balanced inhibitory and excitatory input case and the uncorrelated input case. Interestingly, the discrimination capacity obtained in these cases is independent of model parameters, input distribution and is universal. Our results also suggest a functional role of inhibitory inputs and correlated inputs or, more generally, the large variability of efferent spike trains observed in in vivo experiments: the larger the variability of efferent spike trains, the easier it is to discriminate between masked input signals.

  1. Orexin neurons receive glycinergic innervations.

    Directory of Open Access Journals (Sweden)

    Mari Hondo

    Full Text Available Glycine, a nonessential amino-acid that acts as an inhibitory neurotransmitter in the central nervous system, is currently used as a dietary supplement to improve the quality of sleep, but its mechanism of action is poorly understood. We confirmed the effects of glycine on sleep/wakefulness behavior in mice when administered peripherally. Glycine administration increased non-rapid eye movement (NREM sleep time and decreased the amount and mean episode duration of wakefulness when administered in the dark period. Since peripheral administration of glycine induced fragmentation of sleep/wakefulness states, which is a characteristic of orexin deficiency, we examined the effects of glycine on orexin neurons. The number of Fos-positive orexin neurons markedly decreased after intraperitoneal administration of glycine to mice. To examine whether glycine acts directly on orexin neurons, we examined the effects of glycine on orexin neurons by patch-clamp electrophysiology. Glycine directly induced hyperpolarization and cessation of firing of orexin neurons. These responses were inhibited by a specific glycine receptor antagonist, strychnine. Triple-labeling immunofluorescent analysis showed close apposition of glycine transporter 2 (GlyT2-immunoreactive glycinergic fibers onto orexin-immunoreactive neurons. Immunoelectron microscopic analysis revealed that GlyT2-immunoreactive terminals made symmetrical synaptic contacts with somata and dendrites of orexin neurons. Double-labeling immunoelectron microscopy demonstrated that glycine receptor alpha subunits were localized in the postsynaptic membrane of symmetrical inhibitory synapses on orexin neurons. Considering the importance of glycinergic regulation during REM sleep, our observations suggest that glycine injection might affect the activity of orexin neurons, and that glycinergic inhibition of orexin neurons might play a role in physiological sleep regulation.

  2. Impacts of clustering on noise-induced spiking regularity in the excitatory neuronal networks of subnetworks.

    Science.gov (United States)

    Li, Huiyan; Sun, Xiaojuan; Xiao, Jinghua

    2015-01-01

    In this paper, we investigate how clustering factors influent spiking regularity of the neuronal network of subnetworks. In order to do so, we fix the averaged coupling probability and the averaged coupling strength, and take the cluster number M, the ratio of intra-connection probability and inter-connection probability R, the ratio of intra-coupling strength and inter-coupling strength S as controlled parameters. With the obtained simulation results, we find that spiking regularity of the neuronal networks has little variations with changing of R and S when M is fixed. However, cluster number M could reduce the spiking regularity to low level when the uniform neuronal network's spiking regularity is at high level. Combined the obtained results, we can see that clustering factors have little influences on the spiking regularity when the entire energy is fixed, which could be controlled by the averaged coupling strength and the averaged connection probability.

  3. Association analysis of schizophrenia on 18 genes involved in neuronal migration

    DEFF Research Database (Denmark)

    Kähler, Anna K; Djurovic, Srdjan; Kulle, Bettina

    2008-01-01

    neuronal function, morphology, and formation of synaptic connections. We have investigated the putative association between SZ and gene variants engaged in the neuronal migration process, by performing an association study on 839 cases and 1,473 controls of Scandinavian origin. Using a gene-wide approach......Several lines of evidence support the theory of schizophrenia (SZ) being a neurodevelopmental disorder. The structural, cytoarchitectural and functional brain abnormalities reported in patients with SZ, might be due to aberrant neuronal migration, since the final position of neurons affects......, tagSNPs in 18 candidate genes have been genotyped, with gene products involved in the neuron-to-glial cell adhesion, interactions with the DISC1 protein and/or rearrangements of the cytoskeleton. Of the 289 markers tested, 19 markers located in genes MDGA1, RELN, ITGA3, DLX1, SPARCL1, and ASTN1...

  4. 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.

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

    Science.gov (United States)

    Segawa, Masaya

    2008-09-01

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

  6. Neurons to algorithms LDRD final report.

    Energy Technology Data Exchange (ETDEWEB)

    Rothganger, Fredrick H.; Aimone, James Bradley; Warrender, Christina E.; Trumbo, Derek

    2013-09-01

    Over the last three years the Neurons to Algorithms (N2A) LDRD project teams has built infrastructure to discover computational structures in the brain. This consists of a modeling language, a tool that enables model development and simulation in that language, and initial connections with the Neuroinformatics community, a group working toward similar goals. The approach of N2A is to express large complex systems like the brain as populations of a discrete part types that have specific structural relationships with each other, along with internal and structural dynamics. Such an evolving mathematical system may be able to capture the essence of neural processing, and ultimately of thought itself. This final report is a cover for the actual products of the project: the N2A Language Specification, the N2A Application, and a journal paper summarizing our methods.

  7. 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

  8. Physiological, anatomical and genetic identification of CPG neurons in the developing mammalian spinal cord

    DEFF Research Database (Denmark)

    Kiehn, Ole; Butt, Simon J.B.

    2003-01-01

    . These latter experiments have defined EphA4 as a molecular marker for mammalian excitatory hindlimb CPG neurons. We also review genetic approaches that can be applied to the mouse spinal cord. These include methods for identifying sub-populations of neurons by genetically encoded reporters, techniques to trace...... network connectivity with cell-specific genetically encoded tracers, and ways to selectively ablate or eliminate neuron populations from the CPG. We propose that by applying a multidisciplinary approach it will be possible to understand the network structure of the mammalian locomotor CPG...

  9. Control of neuronal network organization by chemical surface functionalization of multi-walled carbon nanotube arrays

    International Nuclear Information System (INIS)

    Liu Jie; Bibari, Olivier; Marchand, Gilles; Benabid, Alim-Louis; Sauter-Starace, Fabien; Appaix, Florence; De Waard, Michel

    2011-01-01

    Carbon nanotube substrates are promising candidates for biological applications and devices. Interfacing of these carbon nanotubes with neurons can be controlled by chemical modifications. In this study, we investigated how chemical surface functionalization of multi-walled carbon nanotube arrays (MWNT-A) influences neuronal adhesion and network organization. Functionalization of MWNT-A dramatically modifies the length of neurite fascicles, cluster inter-connection success rate, and the percentage of neurites that escape from the clusters. We propose that chemical functionalization represents a method of choice for developing applications in which neuronal patterning on MWNT-A substrates is required.

  10. Molecular mechanisms of Ca(2+) signaling in neurons induced by the S100A4 protein

    DEFF Research Database (Denmark)

    Kiryushko, Darya; Novitskaya, Vera; Soroka, Vladislav

    2006-01-01

    The S100A4 protein belongs to the S100 family of vertebrate-specific proteins possessing both intra- and extracellular functions. In the nervous system, high levels of S100A4 expression are observed at sites of neurogenesis and lesions, suggesting a role of the protein in neuronal plasticity. Ext...... at the cell surface. Thus, glycosaminoglycans may act as coreceptors of S100 proteins in neurons. This may provide a mechanism by which S100 proteins could locally regulate neuronal plasticity in connection with brain lesions and neurological disorders....

  11. Control of neuronal network organization by chemical surface functionalization of multi-walled carbon nanotube arrays

    Energy Technology Data Exchange (ETDEWEB)

    Liu Jie; Bibari, Olivier; Marchand, Gilles; Benabid, Alim-Louis; Sauter-Starace, Fabien [CEA, LETI-Minatec, 17 Rue des Martyrs, 38054 Grenoble Cedex 9 (France); Appaix, Florence; De Waard, Michel, E-mail: fabien.sauter@cea.fr, E-mail: michel.dewaard@ujf-grenoble.fr [Inserm U836, Grenoble Institute of Neuroscience, Site Sante la Tronche, Batiment Edmond J Safra, Chemin Fortune Ferrini, BP170, 38042 Grenoble Cedex 09 (France)

    2011-05-13

    Carbon nanotube substrates are promising candidates for biological applications and devices. Interfacing of these carbon nanotubes with neurons can be controlled by chemical modifications. In this study, we investigated how chemical surface functionalization of multi-walled carbon nanotube arrays (MWNT-A) influences neuronal adhesion and network organization. Functionalization of MWNT-A dramatically modifies the length of neurite fascicles, cluster inter-connection success rate, and the percentage of neurites that escape from the clusters. We propose that chemical functionalization represents a method of choice for developing applications in which neuronal patterning on MWNT-A substrates is required.

  12. Subset specification of central serotonergic neurons

    Directory of Open Access Journals (Sweden)

    Marten P Smidt

    2013-10-01

    Full Text Available The last decade the serotonin (5-hydroxytryptamine; 5-HT system has received enormous attention due to its role in regulation of behavior, exemplified by the discovery that increased 5-HT tone in the central nervous system is able to alleviate affective disorders. Here, we review the developmental processes, with a special emphasis on subset specification, leading to the formation of the 5-HT system in the brain. Molecular classification of 5-HT neuronal groups leads to the definition of two independent rostral groups positioned in rhombomere 1 and 2/3 and a caudal group in rhombomere 5-8. In addition, more disperse refinement of these subsets is present as shown by the selective expression of the 5-HT1A autoreceptor, indicating functional diversity between 5-HT subsets. The functional significance of the molecular coding differences is not well known and the molecular basis of described specific connectivity patterns remain to be elucidated. Recent developments in genetic lineage tracing models will provide these data and form a major step-up towards the full understanding of the importance of developmental programming and function of 5-HT neuronal subsets.

  13. Overproduction of Upper-Layer Neurons in the Neocortex Leads to Autism-like Features in Mice

    Directory of Open Access Journals (Sweden)

    Wei-Qun Fang

    2014-12-01

    Full Text Available Summary: The functional integrity of the neocortex depends upon proper numbers of excitatory and inhibitory neurons; however, the consequences of dysregulated neuronal production during the development of the neocortex are unclear. As excess cortical neurons are linked to the neurodevelopmental disorder autism, we investigated whether the overproduction of neurons leads to neocortical malformation and malfunction in mice. We experimentally increased the number of pyramidal neurons in the upper neocortical layers by using the small molecule XAV939 to expand the intermediate progenitor population. The resultant overpopulation of neurons perturbs development of dendrites and spines of excitatory neurons and alters the laminar distribution of interneurons. Furthermore, these phenotypic changes are accompanied by dysregulated excitatory and inhibitory synaptic connection and balance. Importantly, these mice exhibit behavioral abnormalities resembling those of human autism. Thus, our findings collectively suggest a causal relationship between neuronal overproduction and autism-like features, providing developmental insights into the etiology of autism. : Fang et al. generated a mouse model with excessive excitatory neurons in the neocortex by manipulating embryonic neurogenesis. Overproduction of neurons results in autism-like anatomical and behavioral features. These findings suggest a causal relationship between overproduction of neurons and cortical malfunction and provide developmental insights into the etiology of autism.

  14. Roles of aminergic neurons in formation and recall of associative memory in crickets

    Directory of Open Access Journals (Sweden)

    Makoto Mizunami

    2010-11-01

    Full Text Available We review recent progress in the study of roles of octopaminergic (OA-ergic and dopaminergic (DA-ergic signaling in insect classical conditioning, focusing on our studies on crickets. Studies on olfactory learning in honey bees and fruit-flies have suggested that OA-ergic and DA-ergic neurons convey reinforcing signals of appetitive unconditioned stimulus (US and aversive US, respectively. Our work suggested that this is applicable to olfactory, visual pattern and color learning in crickets, indicating that this feature is ubiquitous in learning of various sensory stimuli. We also showed that aversive memory decayed much faster than did appetitive memory, and we proposed that this feature is common in insects and humans. Our study also suggested that activation of OA- or DA-ergic neurons is needed for appetitive or aversive memory recall, respectively. To account for this finding, we proposed a model in which it is assumed that two types of synaptic connections are strengthened by conditioning and are activated during memory recall, one type being connections from neurons representing conditioned stimulus (CS to neurons inducing conditioned response and the other being connections from neurons representing CS to OA- or DA-ergic neurons representing appetitive or aversive US, respectively. The former is called stimulus-response (S-R connection and the latter is called stimulus-stimulus (S-S connection by theorists studying classical conditioning in vertebrates. Results of our studies using a second-order conditioning procedure supported our model. We propose that insect classical conditioning involves the formation of S-S connection and its activation for memory recall, which are often called cognitive processes.

  15. Pathogenesis of motor neuron disease

    Institute of Scientific and Technical Information of China (English)

    Xuefei Wang

    2006-01-01

    OBJECTIVE: To summarize and analyze the factors and theories related to the attack of motor neuron disease, and comprehensively investigate the pathogenesis of motor neuron disease.DATA SOURCES: A search of Pubmed database was undertaken to identify articles about motor neuron disease published in English from January 1994 to June 2006 by using the keywords of "neurodegenerative diseases". Other literatures were collected by retrieving specific journals and articles.STUDY SELECTION: The data were checked primarily, articles related to the pathogenesis of motor neuron disease were involved, and those obviously irrelated to the articles were excluded.DATA EXTRACTION: Totally 54 articles were collected, 30 of them were involved, and the other 24 were excluded.DATA SYNTHESIS: The pathogenesis of motor neuron disease has multiple factors, and the present related theories included free radical oxidation, excitotoxicity, genetic and immune factors, lack of neurotrophic factor,injury of neurofilament, etc. The studies mainly come from transgenic animal models, cell culture in vitro and patients with familial motor neuron disease, but there are still many restrictions and disadvantages.CONCLUSION: It is necessary to try to find whether there is internal association among different mechanisms,comprehensively investigate the pathogenesis of motor neuron diseases, in order to provide reliable evidence for the clinical treatment.

  16. NADPH- Diaphorase positive cardiac neurons in the atria of mice. A morphoquantitative study

    Directory of Open Access Journals (Sweden)

    Castelucci Patrícia

    2006-02-01

    Full Text Available Abstract Background The present study was conducted to determine the location, the morphology and distribution of NADPH-diaphorase positive neurons in the cardiac nerve plexus of the atria of mice (ASn. This plexus lies over the muscular layer of the atria, dorsal to the muscle itself, in the connective tissue of the subepicardium. NADPH- diaphorase staining was performed on whole-mount preparations of the atria mice. For descriptive purposes, all data are presented as means ± SEM. Results The majority of the NADPH-diaphorase positive neurons were observed in the ganglia of the plexus. A few single neurons were also observed. The number of NADPH-d positive neurons was 57 ± 4 (ranging from 39 to 79 neurons. The ganglion neurons were located in 3 distinct groups: (1 in the region situated cranial to the pulmonary veins, (2 caudally to the pulmonary veins, and (3 in the atrial groove. The largest group of neurons was located cranially to the pulmonary veins (66.7%. Three morphological types of NADPH-diaphorase neurons could be distinguished on the basis of their shape: unipolar cells, bipolar cells and cells with three processes (multipolar cells. The unipolar neurons predominated (78.9%, whereas the multipolar were encountered less frequently (5,3%. The sizes (area of maximal cell profile of the neurons ranged from about 90 μm2to about 220 μm2. Morphometrically, the three types of neurons were similar and there were no significant differences in their sizes. The total number of cardiac neurons (obtained by staining the neurons with NADH-diaphorase method was 530 ± 23. Therefore, the NADPH-diaphorase positive neurons of the heart represent 10% of the number of cardiac neurons stained by NADH. Conclusion The obtained data have shown that the NADPH-d positive neurons in the cardiac plexus of the atria of mice are morphologically different, and therefore, it is possible that the function of the neurons may also be different.

  17. Glial tumors with neuronal differentiation.

    Science.gov (United States)

    Park, Chul-Kee; Phi, Ji Hoon; Park, Sung-Hye

    2015-01-01

    Immunohistochemical studies for neuronal differentiation in glial tumors revealed subsets of tumors having both characteristics of glial and neuronal lineages. Glial tumors with neuronal differentiation can be observed with diverse phenotypes and histologic grades. The rosette-forming glioneuronal tumor of the fourth ventricle and papillary glioneuronal tumor have been newly classified as distinct disease entities. There are other candidates for classification, such as the glioneuronal tumor without pseudopapillary architecture, glioneuronal tumor with neuropil-like islands, and the malignant glioneuronal tumor. The clinical significance of these previously unclassified tumors should be confirmed. Copyright © 2015 Elsevier Inc. All rights reserved.

  18. Mechanosensing in hypothalamic osmosensory neurons.

    Science.gov (United States)

    Prager-Khoutorsky, Masha

    2017-11-01

    Osmosensory neurons are specialized cells activated by increases in blood osmolality to trigger thirst, secretion of the antidiuretic hormone vasopressin, and elevated sympathetic tone during dehydration. In addition to multiple extrinsic factors modulating their activity, osmosensory neurons are intrinsically osmosensitive, as they are activated by increased osmolality in the absence of neighboring cells or synaptic contacts. This intrinsic osmosensitivity is a mechanical process associated with osmolality-induced changes in cell volume. This review summarises recent findings revealing molecular mechanisms underlying the mechanical activation of osmosensory neurons and highlighting important roles of microtubules, actin, and mechanosensitive ion channels in this process. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. From Neurons to Brain: Adaptive Self-Wiring of Neurons

    OpenAIRE

    Segev, Ronen; Ben-Jacob, Eshel

    1998-01-01

    During embryonic morpho-genesis, a collection of individual neurons turns into a functioning network with unique capabilities. Only recently has this most staggering example of emergent process in the natural world, began to be studied. Here we propose a navigational strategy for neurites growth cones, based on sophisticated chemical signaling. We further propose that the embryonic environment (the neurons and the glia cells) acts as an excitable media in which concentric and spiral chemical ...

  20. Connected motorcycle system performance.

    Science.gov (United States)

    2016-01-15

    This project characterized the performance of Connected Vehicle Systems (CVS) on motorcycles based on two key components: global positioning and wireless communication systems. Considering that Global Positioning System (GPS) and 5.9 GHz Dedicated Sh...

  1. Connected vehicle applications : environment.

    Science.gov (United States)

    2016-01-01

    The U.S. Department of Transportation has developed a number of connected vehicle environmental applications, including the Applications for the Environment Real-Time Information Synthesis (AERIS) research program applications and road weather applic...

  2. Connected vehicle applications : safety.

    Science.gov (United States)

    2016-01-01

    Connected vehicle safety applications are designed to increase situational awareness : and reduce or eliminate crashes through vehicle-to-infrastructure, vehicle-to-vehicle, : and vehicle-to-pedestrian data transmissions. Applications support advisor...

  3. IDRC Connect User Guide

    International Development Research Centre (IDRC) Digital Library (Canada)

    Kristina Kamichaitis

    Once an account has been created by IDRC staff, you will receive .... content label in the table to access additional information. Table 3: ... One of the primary functions of IDRC Connect is to enable efficient and automated submission of final.

  4. Connected vehicles and cybersecurity.

    Science.gov (United States)

    2016-01-01

    Connected vehicles are a next-generation technology in vehicles and in infrastructure that will make travel safer, cleaner, and more efficient. The advanced wireless technology enables vehicles to share and communicate information with each other and...

  5. Hydrologically Connected Road Segments

    Data.gov (United States)

    Vermont Center for Geographic Information — Link it ArcGIS Item is HERE.The connectivity layer was created to assist municipalities in preparing for the forthcoming DEC Municipal Roads General Permit in 2018....

  6. IDRC Connect User Guide

    International Development Research Centre (IDRC) Digital Library (Canada)

    Kristina Kamichaitis

    IDRC Extranet home page, which is an umbrella for a number of applications available to IDRC external users. ... IDRC Connect is not formatted for mobile users. ..... Thesis. • Training Material. • Website. • Working Paper. • Workshop Report.

  7. Imaging of intracranial neuronal and mixed neuronal-glial tumours

    International Nuclear Information System (INIS)

    Cui Shimin; Qin Jinxi; Zhang Leili; Liu Meili; Jin Song; Yan Shixin; Liu Li; Dai Weiying; Li Tao; Gao Man

    2001-01-01

    Objective: To investigate the characteristic clinical, imaging , and pathologic findings of intracranial neuronal and mixed neuronal-glial tumours. Methods: The imaging findings of surgery and pathobiology proved intracranial neuronal and mixed neuronal-glial tumours in 14 cases (7 male and 7 female, ranging in age from 6-56 years; mean age 33.8 years) were retrospectively analyzed. Results: Eight gangliogliomas were located in the frontal lobe (4 cases), temporal lobe (1 case), front- temporal lobe (2 cases), and pons (1 case). They appeared as iso-or low density on CT, iso-or low signal intensity on T 1 WI, and high signal intensity on T 2 WI on MR imaging. Two central neurocytomas were located in the supratentorial ventricles. Four desmoplastic gangliogliomas were seen as cystic masses, appearing as low signal intensity on T 1 WI and high signal intensity on T 2 WI. Conclusion: Intracranial neuronal and mixed neuronal-glial tumours had imaging characteristics. Combined with clinical history, it was possible to make a tendency preoperative diagnosis using CT or MR

  8. [Connective tissue and inflammation].

    Science.gov (United States)

    Jakab, Lajos

    2014-03-23

    The author summarizes the structure of the connective tissues, the increasing motion of the constituents, which determine the role in establishing the structure and function of that. The structure and function of the connective tissue are related to each other in the resting as well as inflammatory states. It is emphasized that cellular events in the connective tissue are part of the defence of the organism, the localisation of the damage and, if possible, the maintenance of restitutio ad integrum. The organism responds to damage with inflammation, the non specific immune response, as well as specific, adaptive immunity. These processes are located in the connective tissue. Sterile and pathogenic inflammation are relatively similar processes, but inevitable differences are present, too. Sialic acids and glycoproteins containing sialic acids have important roles, and the role of Siglecs is also highlighted. Also, similarities and differences in damages caused by pathogens and sterile agents are briefly summarized. In addition, the roles of adhesion molecules linked to each other, and the whole event of inflammatory processes are presented. When considering practical consequences it is stressed that the structure (building up) of the organism and the defending function of inflammation both have fundamental importance. Inflammation has a crucial role in maintaining the integrity and the unimpaired somato-psychological state of the organism. Thus, inflammation serves as a tool of organism identical with the natural immune response, inseparably connected with the specific, adaptive immune response. The main events of the inflammatory processes take place in the connective tissue.

  9. Quick connect fastener

    Science.gov (United States)

    Weddendorf, Bruce

    1994-01-01

    A quick connect fastener and method of use is presented wherein the quick connect fastener is suitable for replacing available bolts and screws, the quick connect fastener being capable of installation by simply pushing a threaded portion of the connector into a member receptacle hole, the inventive apparatus being comprised of an externally threaded fastener having a threaded portion slidably mounted upon a stud or bolt shaft, wherein the externally threaded fastener portion is expandable by a preloaded spring member. The fastener, upon contact with the member receptacle hole, has the capacity of presenting cylindrical threads of a reduced diameter for insertion purposes and once inserted into the receiving threads of the receptacle member hole, are expandable for engagement of the receptacle hole threads forming a quick connect of the fastener and the member to be fastened, the quick connect fastener can be further secured by rotation after insertion, even to the point of locking engagement, the quick connect fastener being disengagable only by reverse rotation of the mated thread engagement.

  10. Connectivity in river deltas

    Science.gov (United States)

    Passalacqua, P.; Hiatt, M. R.; Sendrowski, A.

    2016-12-01

    Deltas host approximately half a billion people and are rich in ecosystem diversity and economic resources. However, human-induced activities and climatic shifts are significantly impacting deltas around the world; anthropogenic disturbance, natural subsidence, and eustatic sea-level rise are major causes of threat to deltas and in many cases have compromised their safety and sustainability, putting at risk the people that live on them. In this presentation, I will introduce a framework called Delta Connectome for studying connectivity in river deltas based on different representations of a delta as a network. Here connectivity indicates both physical connectivity (how different portions of the system interact with each other) as well as conceptual (pathways of process coupling). I will explore several network representations and show how quantifying connectivity can advance our understanding of system functioning and can be used to inform coastal management and restoration. From connectivity considerations, the delta emerges as a leaky network that evolves over time and is characterized by continuous exchanges of fluxes of matter, energy, and information. I will discuss the implications of connectivity on delta functioning, land growth, and potential for nutrient removal.

  11. Ultrastructure of GABA- and tachykinin-immunoreactive neurons in the lower division of the central body of the desert locust

    Directory of Open Access Journals (Sweden)

    Uwe Homberg

    2016-12-01

    Full Text Available The central complex, a group of neuropils spanning the midline of the insect brain, plays a key role in spatial orientation and navigation. In the desert locust and other species, many neurons of the central complex are sensitive to the oscillation plane of polarized light above the animal and are likely involved in the coding of compass directions derived from the polarization pattern of the sky. Polarized light signals enter the locust central complex primarily through two types of -aminobutyric acid (GABA-immunoreactive tangential neurons, termed TL2 and TL3 that innervate specific layers of the lower division of the central body (CBL. Candidate postsynaptic partners are columnar neurons (CL1 connecting the CBL to the protocerebral bridge. Subsets of CL1 neurons are immunoreactive to antisera against locustatachykinin (LomTK. To better understand the synaptic connectivities of tangential and columnar neurons in the CBL, we studied its ultrastructural organization in the desert locust, both with conventional electron microscopy and in preparations immunolabeled for GABA or LomTK. Neuronal profiles in the CBL were rich in mitochondria and vesicles. Three types of vesicles were distinguished: small clear vesicles with diameters of 20-40 nm, dark dense-core vesicles (diameter 70-120 nm, and granular dense-core vesicles (diameter 70-80 nm. Neurons were connected via divergent dyads and, less frequently, through convergent dyads. GABA-immunoreactive neurons contained small clear vesicles and small numbers of dark dense core vesicles. They had both pre- and postsynaptic contacts but output synapses were observed more frequently than input synapses. LomTK immunostaining was concentrated on large granular vesicles; neurons had pre- and postsynaptic connections often with neurons assumed to be GABAergic. The data suggest that GABA-immunoreactive tangential neurons provide signals to postsynaptic neurons in the CBL, including LomTK-immunolabeled CL1

  12. Tinbergen on mirror neurons

    Science.gov (United States)

    Heyes, Cecilia

    2014-01-01

    Fifty years ago, Niko Tinbergen defined the scope of behavioural biology with his four problems: causation, ontogeny, survival value and evolution. About 20 years ago, there was anothe