S
Sami El Boustani
Researcher at Centre national de la recherche scientifique
Publications - 18
Citations - 1391
Sami El Boustani is an academic researcher from Centre national de la recherche scientifique. The author has contributed to research in topics: Local field potential & Master equation. The author has an hindex of 9, co-authored 18 publications receiving 1254 citations. Previous affiliations of Sami El Boustani include École Polytechnique Fédérale de Lausanne & Picower Institute for Learning and Memory.
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Journal ArticleDOI
Simulation of networks of spiking neurons: A review of tools and strategies
Romain Brette,Michelle Rudolph,Ted Carnevale,Michael L. Hines,David Beeman,James M. Bower,Markus Diesmann,Markus Diesmann,Abigail Morrison,Philip H. Goodman,Frederick C. Harris,Milind Zirpe,Thomas Natschläger,Dejan Pecevski,G. Bard Ermentrout,Mikael Djurfeldt,Anders Lansner,Olivier Rochel,Thierry Viéville,Eilif Muller,Andrew P. Davison,Sami El Boustani,Alain Destexhe +22 more
TL;DR: In this paper, a review of different aspects of the simulation of spiking neural networks is presented, with the aim of identifying the appropriate integration strategy and simulation tool to use for a given modeling problem related to spiking networks.
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A master equation formalism for macroscopic modeling of asynchronous irregular activity states
Sami El Boustani,Alain Destexhe +1 more
TL;DR: Using master equation formalism, a second-order mean-field set of ordinary differential equations describing the temporal evolution of randomly connected balanced networks is derived, applicable to any neuron model as long as its transfer function can be characterized.
Journal ArticleDOI
Correlated input reveals coexisting coding schemes in a sensory cortex
TL;DR: It is suggested that similar context-dependent coexisting coding strategies may be present in other sensory systems to adapt sensory integration to specific stimulus statistics.
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Network-state modulation of power-law frequency-scaling in visual cortical neurons.
Sami El Boustani,Olivier Marre,Sébastien Béhuret,Pierre Baudot,Pierre Yger,Thierry Bal,Alain Destexhe,Yves Frégnac +7 more
TL;DR: It is proposed that the scaling exponent could be used to read-out the “effective” connectivity responsible for the dynamical signature of the population signals measured at different integration levels, from Vm to LFP, EEG and fMRI.
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Topologically invariant macroscopic statistics in balanced networks of conductance-based integrate-and-fire neurons
TL;DR: Sparsely-connected networks of conductance-based integrate-and-fire neurons with balanced excitatory and inhibitory connections with finite axonal propagation speed are studied, finding that first and second-order “mean-field” statistics of such networks do not depend on the details of the connectivity at a microscopic scale.