Literature DB >> 17501315

Diverse population-bursting modes of adapting spiking neurons.

Guido Gigante1, Maurizio Mattia, Paolo Del Giudice.   

Abstract

We study the dynamics of a noisy network of spiking neurons with spike-frequency adaptation (SFA), using a mean-field approach, in terms of a two-dimensional Fokker-Planck equation for the membrane potential of the neurons and the calcium concentration gating SFA. The long time scales of SFA allow us to use an adiabatic approximation and to describe the network as an effective nonlinear two-dimensional system. The phase diagram is computed for varying levels of SFA and synaptic coupling. Two different population-bursting regimes emerge, depending on the level of SFA in networks with noisy emission rate, due to the finite number of neurons.

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Year:  2007        PMID: 17501315     DOI: 10.1103/PhysRevLett.98.148101

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  23 in total

1.  Heterogeneous attractor cell assemblies for motor planning in premotor cortex.

Authors:  Maurizio Mattia; Pierpaolo Pani; Giovanni Mirabella; Stefania Costa; Paolo Del Giudice; Stefano Ferraina
Journal:  J Neurosci       Date:  2013-07-03       Impact factor: 6.167

2.  Exploring the spectrum of dynamical regimes and timescales in spontaneous cortical activity.

Authors:  Maurizio Mattia; Maria V Sanchez-Vives
Journal:  Cogn Neurodyn       Date:  2011-11-01       Impact factor: 5.082

3.  Fluctuation-driven rhythmogenesis in an excitatory neuronal network with slow adaptation.

Authors:  William H Nesse; Alla Borisyuk; Paul C Bressloff
Journal:  J Comput Neurosci       Date:  2008-04-22       Impact factor: 1.621

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

Authors:  Tilo Schwalger; Moritz Deger; Wulfram Gerstner
Journal:  PLoS Comput Biol       Date:  2017-04-19       Impact factor: 4.475

5.  Rhythmogenic neuronal networks, emergent leaders, and k-cores.

Authors:  David J Schwab; Robijn F Bruinsma; Jack L Feldman; Alex J Levine
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2010-11-08

6.  Low-dimensional spike rate models derived from networks of adaptive integrate-and-fire neurons: Comparison and implementation.

Authors:  Moritz Augustin; Josef Ladenbauer; Fabian Baumann; Klaus Obermayer
Journal:  PLoS Comput Biol       Date:  2017-06-23       Impact factor: 4.475

7.  Extracting non-linear integrate-and-fire models from experimental data using dynamic I-V curves.

Authors:  Laurent Badel; Sandrine Lefort; Thomas K Berger; Carl C H Petersen; Wulfram Gerstner; Magnus J E Richardson
Journal:  Biol Cybern       Date:  2008-11-15       Impact factor: 2.086

8.  Inferring network dynamics and neuron properties from population recordings.

Authors:  Daniele Linaro; Marco Storace; Maurizio Mattia
Journal:  Front Comput Neurosci       Date:  2011-10-10       Impact factor: 2.380

9.  Experimentally Verified Parameter Sets for Modelling Heterogeneous Neocortical Pyramidal-Cell Populations.

Authors:  Paul M Harrison; Laurent Badel; Mark J Wall; Magnus J E Richardson
Journal:  PLoS Comput Biol       Date:  2015-08-20       Impact factor: 4.475

10.  How adaptation shapes spike rate oscillations in recurrent neuronal networks.

Authors:  Moritz Augustin; Josef Ladenbauer; Klaus Obermayer
Journal:  Front Comput Neurosci       Date:  2013-02-27       Impact factor: 2.380

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