Information theory of adaptation in neurons, behavior, and mood

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Highlights

  • Information maximization describes search strategies in different species.

  • Transition between tasks in the absence of new sensory stimuli explained.

  • Information-theoretic approach to mood and its disorders.

  • Perfect adaptation: reward equals predictive information from past to future.

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.

Section snippets

References and recommended reading

Papers of particular interest, published within the period of review, have been highlighted as:

  • • of special interest

  • •• of outstanding interest

Acknowledgments

We thank Charles Stevens for many helpful discussions. This research was supported by the National Science Foundation (NSF) CAREER award number 1254123, the National Eye Institute of the National Institutes of Health under Award Number R01EY019493, McKnight Scholarship and Ray Thomas Edwards Career Award (TOS), a graduate research fellowship from the NSF (AJC), the National Institute of Mental Health (NIMH) and the University of California, San Diego Institute for Neural Computation graduate

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