Effect on movement selection of an evolving sensory representation: a multiple controller model of skill acquisition.
Change in behavior and neural activity in skill acquisition suggests that control is transferred from cortical planning areas (e.g., the prefrontal cortex, PFC) to the basal ganglia (BG). Planning has large computational and representational requirements but requires little experience with a task. The BG are thought to employ a simpler control scheme and reinforcement learning; these mechanisms rely on extensive experience. Many theoretical accounts of behavior in the face of uncertainty invoke planning mechanisms that explicitly take uncertainty into account. We suggest that the simpler mechanisms of the BG can also contribute to the development of behavior under such conditions. We focus on learning under conditions in which sensory information takes time to resolve, e.g., when a poorly perceived goal stimulus takes non-negligible time to identify. It may be advantageous to begin acting quickly under uncertainty--possibly via decisions that are suboptimal for the actual goal--rather than to wait for sensory information to fully resolve. We present a model of skill acquisition in which control is transferred, with experience, from a planning controller (denoted A), corresponding to the PFC, to a simpler controller (B), corresponding to the BG. We apply our model to a task in which a learning agent must execute a series of actions to achieve a goal (selected randomly at each trial from a small set). Over the course of a trial, the agent's goal representation evolves from representing all possible goals to only the selected goal. A is restricted to select movements only when goal representation is fully resolved. Model behavior is similar to that observed in humans accomplishing similar tasks. Thus, B can by itself account for the development of behavior under an evolving sensory representation, suggesting that the BG can contribute to learning and control under conditions of uncertainty.
Shah
Ashvin
A
Neuroscience and Behavior Program, University of Massachusetts Amherst, USA. ashvin@gmail.com
Barto
Andrew G
AG
D003198:Computer Simulation; D003657:Decision Making / Q000502:physiology*; D004777:Environment; D006801:Humans; D007858:Learning / Q000502:physiology; D008959:Models, Neurological; D009068:Movement; D009415:Nerve Net / Q000502:physiology; D016571:Neural Networks, Computer; D009473:Neuronal Plasticity / Q000502:physiology*; D009474:Neurons / Q000502:physiology; D011214:Practice, Psychological