A framework for mesencephalic dopamine systems based on predictive Hebbian learning

TLDR

The authors develop a theoretical framework showing that mesencephalic dopamine systems can distribute signals representing future expectations to their targets. The framework models cortical predictions of future reward, with dopamine neuron activity encoding prediction errors that modulate synaptic plasticity, and it predicts human choice behavior in simple decision tasks. The study finds that dopamine release fluctuations influence synaptic plasticity, thereby adjusting predictions appropriately.

Abstract

We develop a theoretical framework that shows how mesencephalic dopamine systems could distribute to their targets a signal that represents information about future expectations. In particular, we show how activity in the cerebral cortex can make predictions about future receipt of reward and how fluctuations in the activity levels of neurons in diffuse dopamine systems above and below baseline levels would represent errors in these predictions that are delivered to cortical and subcortical targets. We present a model for how such errors could be constructed in a real brain that is consistent with physiological results for a subset of dopaminergic neurons located in the ventral tegmental area and surrounding dopaminergic neurons. The theory also makes testable predictions about human choice behavior on a simple decision-making task. Furthermore, we show that, through a simple influence on synaptic plasticity, fluctuations in dopamine release can act to change the predictions in an appropriate manner.