Contextual modulation of value signals in reward and punishment learning.

ABSTRACT: Compared with reward seeking, punishment avoidance learning is less clearly understood at both the computational and neurobiological levels. Here we demonstrate, using computational modelling and fMRI in humans, that learning option values in a relative--context-dependent--scale offers a simple computational solution for avoidance learning. The context (or state) value sets the reference point to which an outcome should be compared before updating the option value. Consequently, in contexts with an overall negative expected value, successful punishment avoidance acquires a positive value, thus reinforcing the response. As revealed by post-learning assessment of options values, contextual influences are enhanced when subjects are informed about the result of the forgone alternative (counter

SUBMITTER: Palminteri S 

PROVIDER: S-EPMC4560823 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature