Single neuron dynamics and computation.
At the single neuron level, information processing involves the transformation of input spike trains into an appropriate output spike train. Building upon the classical view of a neuron as a threshold device, models have been developed in recent years that take into account the diverse electrophysiological make-up of neurons and accurately describe their input-output relations. Here, we review these recent advances and survey the computational roles that they have uncovered for various electrophysiological properties, for dendritic arbor anatomy as well as for short-term synaptic plasticity.
Departments of Statistics and Neurobiology, University of Chicago, Chicago, USA. Electronic address: nbrunel@uchicago.edu.
Nicolas
N
Brunel
Laboratoire de Physique Statistique, CNRS, University Pierre et Marie Curie, Ecole Normale Supérieure, Paris, France.
Vincent
V
Hakim
Warwick Systems Biology Centre, University of Warwick, Coventry, United Kingdom.
Magnus J E
MJ
Richardson
D000818:Animals; D055724:Electrophysiological Phenomena / Q000502:physiology*; D006801:Humans; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*