Skip to Main content Skip to Navigation
Journal articles

Detection of dependence patterns with delay

Abstract : The Unitary Events (UE) method is a popular and efficient method used this last decade to detect dependence patterns of joint spike activity among simultaneously recorded neurons. The first introduced method is based on binned coincidence count (Grün, 1996) and can be applied on two or more simultaneously recorded neurons. Among the improvements of the methods, a transposition to the continuous framework has recently been proposed in (Muiño and Borgelt, 2014) and fully investigated in (Tuleau-Malot et al., 2014) for two neurons. The goal of the present paper is to extend this study to more than two neurons. The main result is the determination of the limit distribution of the coincidence count. This leads to the construction of an independence test between $L\geq 2$ neurons. Finally we propose a multiple test procedure via a Benjamini and Hochberg approach (Benjamini and Hochberg, 1995). All the theoretical results are illustrated by a simulation study, and compared to the UE method proposed in (Grün et al., 2002). Furthermore our method is applied on real data.
Complete list of metadata

https://hal.archives-ouvertes.fr/hal-00998864
Contributor : Julien Chevallier <>
Submitted on : Monday, July 13, 2015 - 3:04:08 PM
Last modification on : Tuesday, December 8, 2020 - 10:26:01 AM
Long-term archiving on: : Wednesday, April 26, 2017 - 3:44:03 AM

Files

PatternDetection_HAL.pdf
Files produced by the author(s)

Licence


Distributed under a Creative Commons Attribution - NonCommercial - NoDerivatives 4.0 International License

Identifiers

Collections

Citation

Julien Chevallier, Thomas Laloë. Detection of dependence patterns with delay. Biometrical Journal, Wiley-VCH Verlag, 2015, 57 (6), ⟨10.1002/bimj.201400235⟩. ⟨hal-00998864v3⟩

Share

Metrics

Record views

683

Files downloads

470