Testing the Efficiency of Sensory Coding with Optimal Stimulus Ensembles

Christian K. Machens, Tim Gollisch, Olga Kolesnikova & Andreas V. M. Herz

Journal of Computational Neuroscience 17(1): 47-56 (2005)

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Abstract

According to Barlow's seminal 'efficient coding hypothesis' the coding strategy of sensory neurons should be matched to the statistics of stimuli that occur in an animal's natural habitat. Using an automatic search technique, we here test this hypothesis and identify stimulus ensembles that sensory neurons are optimized for. Focusing on grasshopper auditory receptor neurons, we find that their optimal stimulus ensembles differ from the natural environment, but largely overlap with a behaviorally important sub-ensemble of the natural sounds. This indicates that the receptors are optimized for peak rather than average performance. More generally, our results suggest that the coding strategies of sensory neurons are heavily influenced by differences in behavioral relevance among natural stimuli.
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