Contributors: Laboratoire de neurosciences cognitives et adaptatives (LNCA); Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS); Institut cellule souche et cerveau / Stem Cell and Brain Research Institute (SBRI); Université Claude Bernard Lyon 1 (UCBL); Université de Lyon-Université de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE); Laboratoire de Physique Théorique et Modélisation (LPTM - UMR 8089); Centre National de la Recherche Scientifique (CNRS)-CY Cergy Paris Université (CY); Istituto dei Sistemi Complessi Firenze (ISC); National Research Council of Italy; Institut de Neurosciences des Systèmes (INS); Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM); ANR-10-IDEX-0002,UNISTRA,Par-delà les frontières, l'Université de Strasbourg(2010); ANR-18-CE37-0014,ERMUNDY,Réduction exacte de la dynamique neuronale multi-échelle(2018); ANR-17-CE37-0002,DG-Goal,GOAL-DIRECTED PLANNING IN DENTATE NETWORKS(2017); ANR-21-CE37-0011,HippoComp,Decoder la complexité des oscillations hippocampiques (et corticales) pour prédire le comportement et ses alterations(2021)
نبذة مختصرة : International audience ; The hippocampus and entorhinal cortex exhibit rich oscillatory patterns critical for cognitive functions. In the hippocampal region CA1, specific gamma-frequency oscillations, timed at different phases of the ongoing theta rhythm, are hypothesized to facilitate the integration of information from varied sources and contribute to distinct cognitive processes. Here, we show that gamma elements -a multidimensional characterization of transient gamma oscillatory episodes- occur at any frequency or phase relative to the ongoing theta rhythm across all CA1 layers in male mice. Despite their low power and stochastic-like nature, individual gamma elements still carry behavior-related information and computational modeling suggests that they reflect neuronal firing. Our findings challenge the idea of rigid gamma sub-bands, showing that behavior shapes ensembles of irregular gamma elements that evolve with learning and depend on hippocampal layers. Widespread gamma diversity, beyond randomness, may thus reflect complexity, likely functional but invisible to classic average-based analyses.
Processing Request
No Comments.