title: 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 by Muiño and Borgelt (2014) and fully investigated by 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≥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 by Grün et al. (2002). Furthermore our method is applied on real data.
authors: Laboratoire de Mathématiques J.A. Dieudonné, UMR 7351 CNRS, Université de Nice Sophia Antipolis, 06108, Nice Cedex 02, France.
authors: Julien
authors: J
authors: Chevallier
authors: Laboratoire de Mathématiques J.A. Dieudonné, UMR 7351 CNRS, Université de Nice Sophia Antipolis, 06108, Nice Cedex 02, France.
authors: Thomas
authors: T
authors: Laloë
mesh_terms: D001699:Biometry / Q000379:methods*; D002450:Cell Communication; D009474:Neurons / Q000166:cytology*; D016012:Poisson Distribution
keywords: Coincidence pattern; Independence tests; Neuronal assemblies; Poisson processes; Unitary Events