A Computational Model of Dual Competition between the Basal Ganglia and the Cortex

We propose a model that includes interactions between the cortex, the basal ganglia (BG), and the thalamusbased on a dual competition. We hypothesize that the striatum, the subthalamic nucleus (STN), the internal globuspallidus (GPi), the thalamus, and the cortex are involved in closed feedback loops through the hyperdirect anddirect pathways. These loops support a competition process that results in the ability of BG to make a cognitivedecision followed by a motor one. Considering lateral cortical interactions, another competition takes place insidethe cortex allowing the latter to make a cognitive and a motor decision. We show how this dual competitionendows the model with two regimes. One is driven by reinforcement learning and the other by Hebbian learning.The final decision is made according to a combination of these two mechanisms with a gradual transfer from theformer to the latter. We confirmed these theoretical results on primates (Macaca mulatta) using a novel paradigmpredicted by the model.Key words:covert learning; decision making; Hebbian learning; primate; reinforcement learning; theoreticalapproach

Auteurs Bordeaux Neurocampus