Animal brains evolved to optimize behavior in dynamic environments, flexibly selecting actions that maximize future rewards in different contexts. 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, and environmental context with rewards is ambiguous. The credit assignment problem can be categorized into context-independent structural credit assignment and context-dependent continual learning . In this perspective, we survey prior approaches to these two 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 serves 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 behavioral flexibility, while the slower one enables generalization to new contexts. Author Summary Deep learning has shown great promise over the last decades, allowing artificial neural networks to solve difficult tasks. The key to success is the optimization process by which task errors are translated to connectivity patterns. A major unsolved question is how the brain optimally adjusts the wiring of neural circuits to minimize task error analogously. In our perspective, we advance the notion that the brain’s specialized architecture is part of the solution and spell out a path towards its theoretical, computational, and experimental testing. Specifically, we propose that the interaction between the cortex, thalamus, and basal ganglia induces plasticity in two timescales to enable flexible behaviors. The faster timescale establishes contextual associations to enable behavioral flexibility, while the slower one enables generalization to new contexts.