Spike-frequency adapting neural ensembles: beyond mean adaptation and renewal theories.

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Spike-frequency adapting neural ensembles: beyond mean adaptation and renewal theories. Abstract Text:

Eilif Muller,Lars Buesing,Johannes Schemmel,Karlheinz Meier,Eilif Muller,Lars Buesing,Johannes Schemmel,Karlheinz Meier,

We propose a Markov process model for spike-frequency adapting neural ensembles that synthesizes existing mean-adaptation approaches, population density methods, and inhomogeneous renewal theory, resulting in a unified and tractable framework that goes beyond renewal and mean-adaptation theories by accounting for correlations between subsequent interspike intervals. A method for efficiently generating inhomogeneous realizations of the proposed Markov process is given, numerical methods for solving the population equation are presented, and an expression for the first-order interspike interval correlation is derived. Further, we show that the full five-dimensional master equation for a conductance-based integrate-and-fire neuron with spike-frequency adaptation and a relative refractory mechanism driven by Poisson spike trains can be reduced to a two-dimensional generalization of the proposed Markov process by an adiabatic elimination of fast variables. For static and dynamic stimulation, negative serial interspike interval correlations and transient population responses, respectively, of Monte Carlo simulations of the full five-dimensional system can be accurately described by the proposed two-dimensional Markov process.

Spike-frequency adapting neural ensembles: beyond mean adaptation and renewal theories. Publishing Authors By Initials

E Muller,L Buesing,J Schemmel,K Meier,E Muller,L Buesing,J Schemmel,K Meier,

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Spike-frequency adapting neural ensembles: beyond mean adaptation and renewal theories. Journal Published:

PUBLICATION TYPE: Research Support, Non-U.S. Gov

Journal: Neural computation

VOLUME: 19

Page Numbers: 2958-3010

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ISSN: 0899-7667

DAY: 21

MONTH: Nov

YEAR: 2007

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LANGUAGE: eng

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Grant and Affiliation Information for Spike-frequency adapting neural ensembles: beyond mean adaptation and renewal theories.

AFFILIATION: emueller@kip.uni-heidelberg.de

Country: United States

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MEDLINETA: Neural Comput

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