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      Information theory and neural coding.

      1 ,
      Nature neuroscience
      Springer Science and Business Media LLC

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          Abstract

          Information theory quantifies how much information a neural response carries about the stimulus. This can be compared to the information transferred in particular models of the stimulus-response function and to maximum possible information transfer. Such comparisons are crucial because they validate assumptions present in any neurophysiological analysis. Here we review information-theory basics before demonstrating its use in neural coding. We show how to use information theory to validate simple stimulus-response models of neural coding of dynamic stimuli. Because these models require specification of spike timing precision, they can reveal which time scales contain information in neural coding. This approach shows that dynamic stimuli can be encoded efficiently by single neurons and that each spike contributes to information transmission. We argue, however, that the data obtained so far do not suggest a temporal code, in which the placement of spikes relative to each other yields additional information.

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          Author and article information

          Journal
          Nat Neurosci
          Nature neuroscience
          Springer Science and Business Media LLC
          1097-6256
          1097-6256
          Nov 1999
          : 2
          : 11
          Affiliations
          [1 ] ESPM-Division of Insect Biology, University of California, Berkeley, California 94720, USA. borst@nature.berkeley.edu
          Article
          10.1038/14731
          10526332
          9098725c-a547-4b6b-a7c7-e3f0e4e485e8
          History

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