Learning exact patterns of quasi-synchronization among spiking neurons from data on multi-unit recordings

Laura Martignon, Kathryn Laskey, Gustavo Deco, Eilon Vaadia

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

This paper develops arguments for a family of temporal log-linear models to represent spatio-temporal correlations among the spiking events in a group of neurons. The models can represent not just pairwise correlations but also correlations of higher order. Methods are discussed for inferring the existence or absence of correlations and estimating their strength. A frequentist and a Bayesian approach to correlation detection are compared. The frequentist method is based on G2 statistic with estimates obtained via the Max-Ent principle. In the Bayesian approach a Markov Chain Monte Carlo Model Composition (MC3) algorithm is applied to search over connectivity structures and Laplace's method is used to approximate their posterior probability. Performance of the methods was tested on synthetic data. The methods were applied to experimental data obtained by the fourth author by means of measurements carried out on behaving Rhesus monkeys at the Hadassah Medical School of the Hebrew University. As conjectured, neural connectivity structures need not be neither hierarchical nor decomposable.

Original languageEnglish
Title of host publicationAdvances in Neural Information Processing Systems 9 - Proceedings of the 1996 Conference, NIPS 1996
PublisherNeural information processing systems foundation
Pages76-82
Number of pages7
ISBN (Print)0262100657, 9780262100656
StatePublished - 1997
Event10th Annual Conference on Neural Information Processing Systems, NIPS 1996 - Denver, CO, United States
Duration: 2 Dec 19965 Dec 1996

Publication series

NameAdvances in Neural Information Processing Systems
ISSN (Print)1049-5258

Conference

Conference10th Annual Conference on Neural Information Processing Systems, NIPS 1996
Country/TerritoryUnited States
CityDenver, CO
Period2/12/965/12/96

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