Adrienne Fairhall, NEC Institute, Princeton, NJ
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The dynamics of adaptation to statistics
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Information theoretically, efficient coding requires a matching of the
coding strategy to the statistics of the input signals. In a natural
environment, these statistics can fluctuate on many timescales.  We
examine the dynamics of the adaptation of the neural code of the
motion-sensitive cell H1 in the fly visual system to stimuli whose
statistical properties are themselves evolving dynamically.
Adaptation to these statistics occurs over a wide range of timescales,
from tens of milliseconds to minutes.  Rapid components of adaptation
serve to optimise the information that action potentials carry about
rapid stimulus variations within the local statistical ensemble.
Changes in the rate and statistics of action potential firing encode
information about the ensemble itself, resolving the ambiguities
inherent in an adaptive coding scheme.  The speed with which
information is optimised and ambiguities are resolved approaches the
physical limit imposed by statistical sampling and noise.