Universität zu Köln

Quaglio, Pietro, Rostami, Vahid, Torre, Emiliano and Gruen, Sonja (2018). Methods for identification of spike patterns in massively parallel spike trains. Biol. Cybern., 112 (1-2). S. 57 - 81. NEW YORK: SPRINGER. ISSN 1432-0770

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Abstract

Temporally, precise correlations between simultaneously recorded neurons have been interpreted as signatures of cell assemblies, i.e., groups of neurons that form processing units. Evidence for this hypothesis was found on the level of pairwise correlations in simultaneous recordings of few neurons. Increasing the number of simultaneously recorded neurons increases the chances to detect cell assembly activity due to the larger sample size. Recent technological advances have enabled the recording of 100 or more neurons in parallel. However, these massively parallel spike train data require novel statistical tools to be analyzed for correlations, because they raise considerable combinatorial and multiple testing issues. Recently, various of such methods have started to develop. First approaches were based on population or pairwise measures of synchronization, and later led to methods for the detection of various types of higher-order synchronization and of spatio-temporal patterns. The latest techniques combine data mining with analysis of statistical significance. Here, we give a comparative overview of these methods, of their assumptions and of the types of correlations they can detect.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Quaglio, Pietro UNSPECIFIED UNSPECIFIED UNSPECIFIED Rostami, Vahid UNSPECIFIED UNSPECIFIED UNSPECIFIED Torre, Emiliano UNSPECIFIED UNSPECIFIED UNSPECIFIED Gruen, Sonja UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-190826
DOI:	10.1007/s00422-018-0755-0
Journal or Publication Title:	Biol. Cybern.
Volume:	112
Number:	1-2
Page Range:	S. 57 - 81
Date:	2018
Publisher:	SPRINGER
Place of Publication:	NEW YORK
ISSN:	1432-0770
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language HIGHER-ORDER CORRELATIONS; FIRING PATTERNS; COINCIDENCE DETECTOR; NEURONAL ASSEMBLIES; TEMPORAL PRECISION; NEURAL POPULATION; CORTICAL NETWORKS; CELL ASSEMBLIES; VISUAL-CORTEX; MOTOR CORTEX Multiple languages Computer Science, Cybernetics; Neurosciences Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/19082