Information theory of adaptation in neurons, behavior, and mood.
The ability to make accurate predictions of future stimuli and consequences of one's actions are crucial for the survival and appropriate decision-making. These predictions are constantly being made at different levels of the nervous system. This is evidenced by adaptation to stimulus parameters in sensory coding, and in learning of an up-to-date model of the environment at the behavioral level. This review will discuss recent findings that actions of neurons and animals are selected based on detailed stimulus history in such a way as to maximize information for achieving the task at hand. Information maximization dictates not only how sensory coding should adapt to various statistical aspects of stimuli, but also that reward function should adapt to match the predictive information from past to future.
Computational Neurobiology Laboratory, Salk Institute for Biological Studies, United States. Electronic address: sharpee@salk.edu.
Tatyana O
TO
Sharpee
Computational Neurobiology Laboratory, Salk Institute for Biological Studies, United States; Molecular Neurobiology Laboratory, Salk Institute for Biological Studies, United States.
Adam J
AJ
Calhoun
Molecular Neurobiology Laboratory, Salk Institute for Biological Studies, United States.
Sreekanth H
SH
Chalasani
D000220:Adaptation, Biological / Q000502:physiology*; D000339:Affect / Q000502:physiology*; D000818:Animals; D001519:Behavior / Q000502:physiology*; D006801:Humans; D007257:Information Theory; D009474:Neurons / Q000502:physiology*