On the application of information theory to neural spike trains.
The nervous system represents time-dependent signals in sequences of discrete action potentials or spikes are identical so that information is carried only in the spike arrival times. We show how to quantify this information, in bits, free from any assumptions about which features of the spike train or input waveform are most important. We apply this approach to the analysis of experiments on a variety of systems, including some where we confront severe sampling problems, and discuss some to the results obtained and hopes for future extensions.
Institute for Advanced Study, Princeton, New Jersey 08540, USA.
S P
SP
Strong
R R
RR
de Ruyter van Steveninck
W
W
Bialek
R
R
Koberle
D000818:Animals; D001921:Brain / Q000502:physiology*; D004175:Diptera; D019277:Entropy; D006801:Humans; D007257:Information Theory; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*; D009900:Optic Nerve / Q000502:physiology; D011336:Probability; D014794:Visual Fields; D014796:Visual Perception / Q000502:physiology*