Multiple timescales of normalized value coding underlie adaptive choice behavior

Abstract

Previous work has shown that the neural representation of value adapts to the recent history of rewards. Here, the authors report that a computational model based on divisive normalization over multiple timescales can explain changes in value coding driven by changes in the reward statistics.