A Distribution Free Unitary Events Method based on Delayed Coincidence Count

Mélisande Albert (1) , Yann Bouret (2) , Magalie Fromont (3) , Patricia Reynaud-Bouret (1)

1 JAD - Laboratoire Jean Alexandre Dieudonné
2 LPMC - Laboratoire de physique de la matière condensée
3 IRMAR - Institut de Recherche Mathématique de Rennes

We investigate several distribution free dependence detection procedures, mainly based on bootstrap principles and their approximation properties. Thanks to this study, we introduce a new distribution free Unitary Events (UE) method, named Permutation UE, which consists in a multiple testing procedure based on permutation and delayed coincidence count. Each involved single test of this procedure achieves the prescribed level, so that the corresponding multiple testing procedure controls the False Discovery Rate (FDR), and this with as few assumptions as possible on the underneath distribution. Some simulations show that this method outperforms the trial-shuffling and the MTGAUE method in terms of single levels and FDR, for a comparable amount of false negatives. Application on real data is also provided.

Mots clés: Unitary Events; Synchronization; Multiple Testing; Independence Tests; Trial-Shuffling; permutation; bootstrap; point process

Domaines: Statistiques [math.ST]; Neurosciences [q-bio.NC]; Applications [stat.AP]

Mélisande Albert, Yann Bouret, Magalie Fromont, Patricia Reynaud-Bouret. A Distribution Free Unitary Events Method based on Delayed Coincidence Count. 2015. ⟨hal-01154918v1⟩