Prospective contingency explains behavior and dopamine signals during associative learning

Associative learning depends on contingency, the degree to which a
stimulus predicts an outcome. Despite its importance, the neural
mechanisms linking contingency to behavior remain elusive. In the present
study, we examined the dopamine activity in the ventral striatum—a signal
implicated in associative learning—in a Pavlovian contingency degradation
task in mice. We show that both anticipatory licking and dopamine
responses to a conditioned stimulus decreased when additional rewards were
delivered uncued, but remained unchanged if additional rewards were cued.
These results conflict with contingency-based accounts using a traditional
definition of contingency or a new causal learning model (ANCCR), but can
be explained by temporal difference (TD) learning models equipped with an
appropriate intertrial interval state representation. Recurrent neural
networks trained within a TD framework develop state representations akin
to our best ‘handcrafted’ model. Our findings suggest that the TD error
can be a measure that describes both contingency and dopaminergic
activity.