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An Investigation of the Dynamical Transitions in Harmonically Driven Random Networks of Firing-Rate Neurons
2017
Cognitive Computation
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Additionally, we propose a novel technique for exploring the stationary points and locally linear dynamics of these networks in order to understand the origin of input-dependent dynamical transitions. ...
In this article, we study the response of stable and unstable networks to different harmonically oscillating stimuli by varying a parameter ρ, the ratio between the timescale of the network and the stimulus ...
the European Union Future and Emerging Technologies grant (GA:641100) TIMESTORM-Mind and Time: Investigation of the Temporal Traits of Human-Machine Convergence. ...
doi:10.1007/s12559-017-9464-6
pmid:28680506
pmcid:PMC5487873
fatcat:up4rsq6fxbaf7fzeoyje5c7e2q
Complexity matching in neural networks
2015
New Journal of Physics
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We use an integrate-and-fire model where the randomness of each neuron is only due to the random choice of a new initial condition after firing. ...
In the wide literature on the brain and neural network dynamics the notion of criticality is being adopted by an increasing number of researchers, with no general agreement on its theoretical definition ...
In the earlier work of [20] this rate was expected to remain constant because after firing each neurons jumps back to x = 0, while here each neuron after firing moves to a random value > x 0, with a ...
doi:10.1088/1367-2630/17/1/015003
fatcat:accemajktja2zkat5z5jmf7c64
Emergent Oscillations in Networks of Stochastic Spiking Neurons
2011
PLoS ONE
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Both mechanisms are shown to produce gamma band oscillations at the population level while individual neurons fire at a rate much lower than the population frequency. ...
These mechanisms provide a new perspective on the emergence of rhythmic firing in neural networks, showing the coexistence of population-level oscillations with very irregular individual spike trains in ...
Author Contributions Analyzed the data: EW MB. Wrote the paper: EW MB WvD JDC. Conceived and designed simulations: EW MB WvD JDC. Wrote and performed simulations: EW MB. ...
doi:10.1371/journal.pone.0014804
pmid:21573105
pmcid:PMC3089610
fatcat:rkh6e6caivdlhgohfn5txfk5nu
An effective kinetic representation of fluctuation-driven neuronal networks with application to simple and complex cells in visual cortex
2004
Proceedings of the National Academy of Sciences of the United States of America
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This powerful kinetic theory captures the full dynamic range of neuronal networks, from the mean-driven limit (a limit such as the number of neurons N 3 ؕ, in which the fluctuations vanish) to the fluctuation-dominated ...
dynamic phenomena, such as, transitions to bistability and hysteresis, even in the presence of large fluctuations. ...
We thank Bob Shapley for many discussions throughout the entire course of this work, Dan Tranchina for introducing us to pdf representations of neuronal networks and his comments on this work, and Fernand ...
doi:10.1073/pnas.0401906101
pmid:15131268
pmcid:PMC419679
fatcat:y34i3t7srbhonnrplyo2sikdsa
Shaping Intrinsic Neural Oscillations with Periodic Stimulation
2016
Journal of Neuroscience
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Our results suggest that rhythmic stimulation can form the basis of a control paradigm in which one can manipulate the intrinsic oscillatory properties of driven networks via a plurality of input-driven ...
Our results show that, in addition to resonance and entrainment, nonlinear acceleration is involved in shaping the rhythmic response of our modeled network. ...
This is also reflected in the spiking activity of driven neurons: firing rates increase into tightly synchronized bursts of spike discharges. ...
doi:10.1523/jneurosci.0236-16.2016
pmid:27170129
fatcat:swzcplpbxzdf7nwf5bdc6y5sbe
Critical and resonance phenomena in neural networks
[article]
2012
arXiv
pre-print
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Using an analytical approach and simulations of a cortical circuit model of neural networks with stochastic neurons in the presence of noise, we show that spontaneous appearance of network oscillations ...
occurs as a dynamical (non-equilibrium) phase transition at a critical point determined by the noise level, network structure, the balance between excitatory and inhibitory neurons, and other parameters ...
In the present paper, we study collective dynamics of neural networks composed by excitatory and inhibitory neurons in the presence of noise. ...
arXiv:1211.5686v1
fatcat:vrr6iuun4bdyvikm5irrzcjemm
Advances in Biologically Inspired Reservoir Computing
2017
Cognitive Computation
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The interplay between randomness and optimization has always been a major theme in the design of neural networks [3] . ...
As long as the recurrent part of the network possesses a form of fading memory of the input, the dynamics of the neurons are enough to efficiently process many spatio-temporal signals, provided that their ...
We would like to thank the editor in chief of the journal, Amir Hussain, for the strong support given when organizing and publishing this special issue; all the authors who participated in the issue; and ...
doi:10.1007/s12559-017-9469-1
fatcat:pgdtsxvqvndr5ijsddht537fzm
Network mechanisms underlying the role of oscillations in cognitive tasks
2018
PLoS Computational Biology
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Specifically, we investigate how the frequency of oscillatory input interacts with the intrinsic dynamics in networks of recurrently coupled spiking neurons to cause changes of state: the neuronal correlates ...
We leverage a recently derived set of exact mean-field equations for networks of quadratic integrate-and-fire neurons to systematically study the bifurcation structure in the periodically forced spiking ...
This type of spike synchrony is seen ubiquitously in networks of both heterogeneous and noise-driven spiking neurons operating in the mean-driven regime, in which neurons fire as oscillators [15, 22, ...
doi:10.1371/journal.pcbi.1006430
pmid:30188889
pmcid:PMC6143269
fatcat:zybx3u63u5fankgqpyrvmkebh4
Asynchronous and Coherent Dynamics in Balanced Excitatory-Inhibitory Spiking Networks
2021
Frontiers in Systems Neuroscience
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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. ...
Dynamic excitatory-inhibitory (E-I) balance is a paradigmatic mechanism invoked to explain the irregular low firing activity observed in the cortex. ...
On the distribution of firing rates in networks of cortical neurons. J. ...
doi:10.3389/fnsys.2021.752261
pmid:34955768
pmcid:PMC8702645
fatcat:7tma4kbpf5ft3dwozqvldzh2na
Asynchronous and coherent dynamics in balanced excitatory-inhibitory spiking networks
[article]
2021
arXiv
pre-print
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2021 pre-print arXiv:2108.13666v1 fatcat:rwcjrjomo5ginkjkiwlkwfgveu
The analysis is performed by combining simulations of sparse E-I networks composed of N spiking neurons with analytical investigations of low dimensional neural mass models. ...
Dynamic excitatory-inhibitory (E-I) balance is a paradigmatic mechanism invoked to explain the irregular low firing activity observed in the cortex. ...
ACKNOWLEDGMENTS The authors acknowledge extremely useful discussions with D.G. Goldobin, G. Mongillo, E. Montbrió, S. Olmi, and A. Politi. ...
arXiv:2108.13666v2
fatcat:xpnftxv6ozcn3pid74hdqo2nbm
A large-scale simulation of the piriform cortex by a cell automaton-based network model
2002
IEEE Transactions on Biomedical Engineering
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An event-driven framework is used to construct a physiologically motivated large-scale model of the piriform cortex containing in the order of 10 5 neuron-like computing units. ...
The network model incorporates four neuron types, and glutamatergic excitatory and and inhibitory synapses. ...
To investigate the dynamics of a large-scale cortical model, the cell types and the connectivity patterns in the network were constrained by piriform cortex anatomy. ...
doi:10.1109/tbme.2002.801986
pmid:12214882
fatcat:qbihejuwevc3vm2gw5w72riwvu
Dynamic Control of Synchronous Activity in Networks of Spiking Neurons
2016
PLoS ONE
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Using mean-field and stability analyses, we investigate the influence of dynamic inputs on the frequency of firing rate oscillations. ...
We here analyze a network of recurrently connected spiking neurons with time delay displaying stable synchronous dynamics. ...
Fig 1 . 1 Frequency transitions in a random network of spiking neurons. A. ...
doi:10.1371/journal.pone.0161488
pmid:27669018
pmcid:PMC5036852
fatcat:lrf65rbrx5cg5ccrp75cohr32q
Neuronal Dynamics
[chapter]
2009
Encyclopedia of Complexity and Systems Science
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Presentation of an external stimulus (sample 1 in the figure) increases the firing rate of the relevant neurons (see red curve in bottom panel, average firing rate of neurons in population 1). ...
Architectures in Rate Models Rate models are often used to investigate the dynamics of spatially extended networks, or systems which encode continuous stimuli. ...
doi:10.1007/978-0-387-30440-3_359
fatcat:lmiylxvqozdjhl44ydfuma35z4
How pattern formation in ring networks of excitatory and inhibitory spiking neurons depends on the input current regime
2013
BMC Neuroscience
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Pattern formation in networks of spiking neurons Frontiers in Computational Neuroscience www.frontiersin.org January 2014 | Volume 7 | Article 187 | 2 350 J = 1.1 mV J = 0.9 mV Rate [1/s] J = 0.6 mV J ...
Frontiers in Computational Neuroscience www.frontiersin.org January 2014 | Volume 7 | Article 187 | 1 COMPUTATIONAL NEUROSCIENCE Kriener et al. ...
We gratefully acknowledge funding by the eScience program of the Research Council of Norway under grant 178892/V30 (eNeuro), the Helmholtz Association: HASB and portfolio theme SMHB, the Next-Generation ...
doi:10.1186/1471-2202-14-s1-p123
pmcid:PMC3704539
fatcat:m6fngrzvezcwvbjqic4ft4rony
How pattern formation in ring networks of excitatory and inhibitory spiking neurons depends on the input current regime
2014
Frontiers in Computational Neuroscience
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Pattern formation in networks of spiking neurons Frontiers in Computational Neuroscience www.frontiersin.org January 2014 | Volume 7 | Article 187 | 2 350 J = 1.1 mV J = 0.9 mV Rate [1/s] J = 0.6 mV J ...
Frontiers in Computational Neuroscience www.frontiersin.org January 2014 | Volume 7 | Article 187 | 1 COMPUTATIONAL NEUROSCIENCE Kriener et al. ...
We gratefully acknowledge funding by the eScience program of the Research Council of Norway under grant 178892/V30 (eNeuro), the Helmholtz Association: HASB and portfolio theme SMHB, the Next-Generation ...
doi:10.3389/fncom.2013.00187
pmid:24501591
pmcid:PMC3882721
fatcat:ixmls5rcmjbvtawawpbriady2u
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