Prediction error during retrospective revaluation of causal associations in humans: fMRI evidence in favor of an associative model of learning

Abstract

Associative learning theory assumes that prediction error is a driving force in learning. A competing view, probabilistic contrast (PC) theory, is that learning and prediction error are unrelated. We tested a learning phenomenon that has proved troublesome for associative theory - retrospective revaluation - to evaluate these two models. We previously showed that activation in right lateral prefrontal cortex (PFC) provides a reliable signature for the presence of prediction error. Thus, if the associative view is correct, retrospective revaluation should be accompanied by right lateral PFC activation. PC theory would be supported by the absence of this activation. Right PFC and ventral striatal activation occurred during retrospective revaluation, supporting the associative account. Activations appeared to reflect the degree of revaluation, predicting later brain responses to revalued cues. Our results support a modified associative account of retrospective revaluation and demonstrate the potential of functional neuroimaging as a tool for evaluating competing learning models.