  Animal brains evolved to optimize behavior in dynamically changing
environments, selecting actions that maximize future rewards. A large body of
experimental work indicates that such optimization changes the wiring of neural
circuits, appropriately mapping environmental input onto behavioral outputs. A
major unsolved scientific question is how optimal wiring adjustments, which
must target the connections responsible for rewards, can be accomplished when
the relation between sensory inputs, action taken, environmental context with
rewards is ambiguous. The computational problem of properly targeting cues,
contexts and actions that lead to reward is known as structural, contextual and
temporal credit assignment respectively. In this review, we survey prior
approaches to these three types of problems and advance the notion that the
brain's specialized neural architectures provide efficient solutions. Within
this framework, the thalamus with its cortical and basal ganglia interactions
serve as a systems-level solution to credit assignment. Specifically, we
propose that thalamocortical interaction is the locus of meta-learning where
the thalamus provides cortical control functions that parametrize the cortical
activity association space. By selecting among these control functions, the
basal ganglia hierarchically guide thalamocortical plasticity across two
timescales to enable meta-learning. The faster timescale establishes contextual
associations to enable rapid behavioral flexibility while the slower one
enables generalization to new contexts. Incorporating different thalamic
control functions under this framework clarifies how thalamocortical-basal
ganglia interactions may simultaneously solve the three credit assignment
problems.
