CNS Seminar

Title: "Starting new actions and learning from it"

Abstract: The ability of animals to build individual repertoires based on the consequences of their actions is fascinating, and essential for survival. Understanding this process, i.e. how actions are learned through trial and feedback, requires mechanistic insight into how self-paced actions are initiated, how they can be selected/initiated again, and how feedback can shape their execution and organization. We use behavioral, genetic, electrophysiological, and optical approaches to gain this mechanistic insight. The combination of these approaches allowed us to uncover that dopaminergic neurons are transiently active before self-paced movement initiation. This activity is not action-specific and modulates both the probability of initiation and the vigor of future movements, but does not affect ongoing movement. Dopamine is supposed to have opposite effects on downstream striatal direct and indirect pathways. Contrary to what is classically postulated, we found that both striatal direct and indirect pathways are active during movement initiation. The activity in both pathways is action-specific, is organized into specific spatiotemporal patterns, and has complementary but different roles in movement initiation. Furthermore, when animals organize their individual movements in sequences or chunks, activity related to the initiation or termination of these chunks emerges in dopaminergic and striatal circuits. The behavioral and neuronal re-organization that accompanies sequence learning requires plasticity between the cortex and striatum. Finally, using operant tasks and closed-loop brain machine paradigms, we revealed that cortico-striatal plasticity is necessary to select, reinforce and shape the specific neural and behavioral patterns that lead to desirable outcomes. These data invite new models on the mechanisms underlying self-paced movement initiation, and motor dysfunction in Parkinson's disease. They also suggest that cortico-basal ganglia circuits play a generic role in learning to produce task-relevant neural activity and behavioral patterns.