Reward-dependent learning in neuronal networks for planning and decision making

S Dehaene, JP Changeux - Progress in brain research, 2000 - Elsevier
Neuronal network models have been proposed for the organization of evaluation and
decision processes in prefrontal circuitry and their putative neuronal and molecular bases.
The models all include an implementation and simulation of an elementary reward
mechanism. Their central hypothesis is that tentative rules of behavior, which are coded by
clusters of active neurons in prefrontal cortex, are selected or rejected based on an
evaluation by this reward signal, which may be conveyed, for instance, by the …