title: Dynamic switching of neural codes in networks with gap junctions.
abstract: Population rate coding and temporal coding are common neural codes. Recent studies suggest that these two codes may be alternatively used in one neural system. Based on the fact that there are massive gap junctions in the brain, we explore how this switching behavior may be related to neural codes in networks of neurons connected by gap junctions. First, we show that under time-varying inputs, such neural networks show switching between synchronous and asynchronous states. Then, we quantify network dynamics by three mutual information measures to show that population rate coding carries more information in asynchronous states and temporal coding does so in synchronous states.
authors.affiliation: Aihara Complexity Modelling Project, ERATO, JST, 3-23-5 Uehara, Shibuya-ku, Tokyo 151-0064, Japan. katori@sat.t.u-tokyo.ac.jp
authors.forename: Yuichi
authors.initials: Y
authors.lastname: Katori
authors.forename: Naoki
authors.initials: N
authors.lastname: Masuda
authors.forename: Kazuyuki
authors.initials: K
authors.lastname: Aihara
mesh_terms: D000200:Action Potentials / Q000502:physiology; D000818:Animals; D017629:Gap Junctions / Q000502:physiology*; D009415:Nerve Net / Q000502:physiology*; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology*; D017711:Nonlinear Dynamics