Generation of synthetic spike trains with defined pairwise correlations.

Generation of synthetic spike trains with defined pairwise correlations. Research Abstract Details 

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Generation of synthetic spike trains with defined pairwise correlations. Abstract Text:

Ernst Niebur,

Recent technological advances as well as progress in theoretical understanding of neural systems have created a need for synthetic spike trains with controlled mean rate and pairwise cross-correlation. This report introduces and analyzes a novel algorithm for the generation of discretized spike trains with arbitrary mean rates and controlled cross correlation. Pairs of spike trains with any pairwise correlation can be generated, and higher-order correlations are compatible with common synaptic input. Relations between allowable mean rates and correlations within a population are discussed. The algorithm is highly efficient, its complexity increasing linearly with the number of spike trains generated and therefore inversely with the number of cross-correlated pairs.

Generation of synthetic spike trains with defined pairwise correlations. Publishing Authors By Initials

E Niebur,

For similar nervous system: synapses research abstracts see: nervous system: synapses research

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Generation of synthetic spike trains with defined pairwise correlations. Journal Published:

PUBLICATION TYPE: Research Support, N.I.H., Extr

Journal: Neural computation

VOLUME: 19

Page Numbers: 1720-38

Journal Abbreviation:

ISSN: 0899-7667

DAY: 3

MONTH: Jul

YEAR: 2007

Generation of synthetic spike trains with defined pairwise correlations. Information

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LANGUAGE: eng

NlmUniqueID: 9426182

Generation of synthetic spike trains with defined pairwise correlations. Keywords Mesh Terms:

KEYWORDS: Synapses

MESH TERMS: physiology

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Grant and Affiliation Information for Generation of synthetic spike trains with defined pairwise correlations.

AFFILIATION: Krieger Mind/Brain Institute and Department of Neuroscience, Johns Hopkins University, Baltimore, MD 21218, USA. niebur@jhu.edu

Country: United States

AGENCY: United States NINDS

GRANT: R01-NS40596

ACRONYM: NS

MEDLINETA: Neural Comput

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