TY - JOUR
T1 - Sensory adaptation
AU - Wark, Barry
AU - Lundstrom, Brian Nils
AU - Fairhall, Adrienne
N1 - Funding Information:
We would like to thank Felice Dunn, Gabe Murphy, Fred Rieke, Rebecca Mease and David Wark for useful comments and discussions. This work was supported by a Burroughs-Welcome Careers at the Scientific Interface grant (AF, BW and BL), NIH T32EY-0731 (BW), NIH MSTP T32-07266 (BL), ARCS (BL).
PY - 2007/8
Y1 - 2007/8
N2 - Adaptation occurs in a variety of forms in all sensory systems, motivating the question: what is its purpose? A productive approach has been to hypothesize that adaptation helps neural systems to efficiently encode stimuli whose statistics vary in time. To encode efficiently, a neural system must change its coding strategy, or computation, as the distribution of stimuli changes. Information theoretic methods allow this efficient coding hypothesis to be tested quantitatively. Empirically, adaptive processes occur over a wide range of timescales. On short timescales, underlying mechanisms include the contribution of intrinsic nonlinearities. Over longer timescales, adaptation is often power-law-like, implying the coexistence of multiple timescales in a single adaptive process. Models demonstrate that this can result from mechanisms within a single neuron.
AB - Adaptation occurs in a variety of forms in all sensory systems, motivating the question: what is its purpose? A productive approach has been to hypothesize that adaptation helps neural systems to efficiently encode stimuli whose statistics vary in time. To encode efficiently, a neural system must change its coding strategy, or computation, as the distribution of stimuli changes. Information theoretic methods allow this efficient coding hypothesis to be tested quantitatively. Empirically, adaptive processes occur over a wide range of timescales. On short timescales, underlying mechanisms include the contribution of intrinsic nonlinearities. Over longer timescales, adaptation is often power-law-like, implying the coexistence of multiple timescales in a single adaptive process. Models demonstrate that this can result from mechanisms within a single neuron.
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U2 - 10.1016/j.conb.2007.07.001
DO - 10.1016/j.conb.2007.07.001
M3 - Review article
C2 - 17714934
AN - SCOPUS:34948900353
SN - 0959-4388
VL - 17
SP - 423
EP - 429
JO - Current Opinion in Neurobiology
JF - Current Opinion in Neurobiology
IS - 4
ER -