1,720,978 research outputs found
The influence of noise on synchronous dynamics in a diluted neural network
We study the influence of noise on the dynamics of a simple model of excitatory leaky integrate - and - fire neurons in a diluted network. The stochastic process amounts to a random walk with boundaries acting on the external current, whose average value plays the role of a control parameter identifying different dynamical phases. Above a given threshold value one observes a gaussian statistics of synchronous firing events, that changes to an asymmetric long-tail distribution below threshold. For uncorrelated noise the distribution below threshold exhibits an exponential tail for large rare events, while for strongly correlated noise the long-tail turns to a power-law. This interesting dynamical scenario is shown to persist also when short-term plasticity is introduced in the model. Synchronous firing events change to population bursts and the model with plasticity is shown to reproduce quantitatively what observed in in vitro experiments. We also discuss the persistence of this scenario in the thermodynamic limit. © 2013 The Authors. Published by Elsevier Ltd. All rights reserved
Transition from Asynchronous to Oscillatory Dynamics in Balanced Spiking Networks with Instantaneous Synapses
We report a transition from asynchronous to oscillatory behavior in balanced inhibitory networks for class I and II neurons with instantaneous synapses. Collective oscillations emerge for sufficiently connected networks. Their origin is understood in terms of a recently developed mean-field model, whose stable solution is a focus. Microscopic irregular firings, due to balance, trigger sustained oscillations by exciting the relaxation dynamics towards the macroscopic focus. The same mechanism induces in balanced excitatory-inhibitory networks quasiperiodic collective oscillations
Nonlinear collision between propagating waves in mouse somatosensory cortex
How does cellular organization shape the spatio-temporal patterns of activity in the cortex while processing sensory information? After measuring the propagation of activity in the mouse primary somatosensory cortex (S1) in response to single whisker deflections with Voltage Sensitive Dye (VSD) imaging, we developed a two dimensional model of S1. We designed an inference method to reconstruct model parameters from VSD data, revealing that a spatially heterogeneous organization of synaptic strengths between pyramidal neurons in S1 is likely to be responsible for the heterogeneous spatio-temporal patterns of activity measured experimentally. The model shows that, for strong enough excitatory cortical interactions, whisker deflections generate a propagating wave in S1. Finally, we report that two consecutive stimuli activating different spatial locations in S1 generate two waves which collide sub-linearly, giving rise to a suppressive wave. In the inferred model, the suppressive wave is explained by a lower sensitivity to external perturbations of neural networks during activated states
Measures to prevent stress corrosion cracking of aluminum cans for carbonated beverages
Common containers for carbonated beverages are PET bottles and aluminum cans. These different materials are chosen based on marketing and convenience reasons. While the shelf life of carbonated beverages packed in PET bottles is affected by the CO2 permeation through the polymer matrix, aluminum cans allow the gas retention and guarantee a higher quality during storage. Indeed, the shelf life of canned carbonated beverages is commonly ≥1 year. While the longer commercial life is an advantage from a commercial point of view, it increases the probability of occurrence of failure due to corrosion. Stress Corrosion Cracking (SCC) occurring from the outside of the can would prejudice the integrity of the container, provoke the product loss and, what is probably worst, could determine a chain-effect on other adjacent cans if the product is spilled from the damaged can. Normally, aluminum cans are internally lacquered for protecting the metal from corrosion by the food components. Chlorine from the conditioning water bath and storage environmental moisture determines the onset of SSC, while temperature and internal gas pressure speed up the failure of cans. This study aimed at evaluating the potential of a supplementary outer enamel for preventing stress corrosion cracking, and proved that this measure, which does not imply significant process changes or supplementary costs, could effectively reduce the risk of product loss, with consequent need for damaged products withdraw and disposal, and prejudice for the image of the producer
Coexistence of fast and slow gamma oscillations in one population of inhibitory spiking neurons
Oscillations are a hallmark of neural population activity in various brain regions with a spectrum covering a wide range of frequencies. Within this spectrum γ oscillations have received particular attention due to their ubiquitous nature and their correlation with higher brain functions. Recently, it has been reported that γ oscillations in the hippocampus of behaving rodents are segregated in two distinct frequency bands: slow and fast. These two γ rhythms correspond to different states of the network, but their origin has been not yet clarified. Here we show theoretically and numerically that a single inhibitory population can give rise to coexisting slow and fast γ rhythms corresponding to collective oscillations of a balanced spiking network. The slow and fast γ rhythms are generated via two different mechanisms: the fast one being driven by the coordinated tonic neural firing and the slow one by endogenous fluctuations due to irregular neural activity. We show that almost instantaneous stimulations can switch the collective γ oscillations from slow to fast and vice versa. Furthermore, to draw a connection with the experimental observations, we consider the modulation of the γ rhythms induced by a slower (θ) rhythm driving the network dynamics. In this context, depending on the strength of the forcing and the noise amplitude, we observe phase-amplitude and phase-phase coupling between the fast and slow γ oscillations and the θ forcing. Phase-phase coupling reveals on average different θ-phase preferences for the two coexisting γ rhythms joined to a wide cycle-to-cycle variability
Reduction Methodology for Fluctuation Driven Population Dynamics
Lorentzian distributions have been largely employed in statistical mechanics to obtain exact results for heterogeneous systems. Analytic continuation of these results is impossible even for slightly deformed Lorentzian distributions due to the divergence of all the moments (cumulants). We have solved this problem by introducing a "pseudocumulants"expansion. This allows us to develop a reduction methodology for heterogeneous spiking neural networks subject to extrinsic and endogenous fluctuations, thus obtaining a unified mean-field formulation encompassing quenched and dynamical sources of disorder
Asynchronous and Coherent Dynamics in Balanced Excitatory-Inhibitory Spiking Networks
Dynamic excitatory-inhibitory (E-I) balance is a paradigmatic mechanism invoked to explain the irregular low firing activity observed in the cortex. However, we will show that the E-I balance can be at the origin of other regimes observable in the brain. The analysis is performed by combining extensive simulations of sparse E-I networks composed of N spiking neurons with analytical investigations of low dimensional neural mass models. The bifurcation diagrams, derived for the neural mass model, allow us to classify the possible asynchronous and coherent behaviors emerging in balanced E-I networks with structural heterogeneity for any finite in-degree K. Analytic mean-field (MF) results show that both supra and sub-threshold balanced asynchronous regimes are observable in our system in the limit N >> K >> 1. Due to the heterogeneity, the asynchronous states are characterized at the microscopic level by the splitting of the neurons in to three groups: silent, fluctuation, and mean driven. These features are consistent with experimental observations reported for heterogeneous neural circuits. The coherent rhythms observed in our system can range from periodic and quasi-periodic collective oscillations (COs) to coherent chaos. These rhythms are characterized by regular or irregular temporal fluctuations joined to spatial coherence somehow similar to coherent fluctuations observed in the cortex over multiple spatial scales. The COs can emerge due to two different mechanisms. A first mechanism analogous to the pyramidal-interneuron gamma (PING), usually invoked for the emergence of γ-oscillations. The second mechanism is intimately related to the presence of current fluctuations, which sustain COs characterized by an essentially simultaneous bursting of the two populations. We observe period-doubling cascades involving the PING-like COs finally leading to the appearance of coherent chaos. Fluctuation driven COs are usually observable in our system as quasi-periodic collective motions characterized by two incommensurate frequencies. However, for sufficiently strong current fluctuations these collective rhythms can lock. This represents a novel mechanism of frequency locking in neural populations promoted by intrinsic fluctuations. COs are observable for any finite in-degree K, however, their existence in the limit N >> K >> 1 appears as uncertain
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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