title: Adaptation in spiking neurons based on the noise shaping neural coding hypothesis.
abstract: Shin, Koch and Douglas [Shin, J., Koch, C., & Douglas, R. (1999). Adaptive neural coding dependent on the time-varying statistics of the somatic input current. Neural Computation, 11, 1983-2003] proposed an adaptive neural coding model that makes spiking neurons adapt its input/output relation to the stimulus statistics. In a surprisingly precise manner, the adaptive neural coding model has been supported by recent experiments. However, the previous report has two problems: (a) although the adaptive neural coding model was developed based on the noise shaping neural coding hypothesis, their connection was not explained clearly in the previous report; and (b) the previous model did not suggest a biologically plausible method to estimate the stimulus mean and variance from spike-evoked intracellular calcium concentration. In this paper, I present how the noise shaping neural coding hypothesis produced such a precise model without any available experimental data at that time. Moreover, I propose a computational model for a biologically plausible signal statistics extraction from spike-evoked intracellular calcium concentration. An asymmetry in contrast adaptation time between increasing and decreasing variance, observed in biological experiments, is explained using the signal statistics extraction method. In addition, a new perspective on the relationship between the spike train of spiking neurons and EEG (or local field potential (LFP)) is suggested based on the noise shaping neural coding hypothesis.
authors.affiliation: Computation and Neural Systems Program, Division of Biology, California Institute of Technology, Pasadena 91125, USA. shin@corpus.brain.riken.go.jp
authors.forename: J
authors.initials: J
authors.lastname: Shin
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000222:Adaptation, Physiological / Q000502:physiology*; D000818:Animals; D016477:Artifacts; D020013:Calcium Signaling / Q000502:physiology; D002451:Cell Compartmentation / Q000502:physiology; D006801:Humans; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*; D009435:Synaptic Transmission / Q000502:physiology*