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)
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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