The research suggests that the circuits, which are located in the basal ganglia, select the best sensory-motor associations to generate the most rewarding courses of action. The computational model can account for the diverse functions in which the circuits are involved—making decisions, acquiring skills through reinforcement learning, and planning routes—among others.
Previous models of the basal ganglia have focused on the role of the circuits in motor control. The new model proposes a more comprehensive computational framework that can explain both the motor and the cognitive functions of this brain area.
"Our goal was to understand the computation that takes place in the basal ganglia across different species and behaviors, and provide a unifying computational framework that accounts for all the different functions in which the basal ganglia have been implicated," said senior author Samuel A. Musallam, PhD, an associate professor of neuroscience at the University of California, Irvine.
"The new model allows us to understand the neural mechanisms that give rise to behavior on many time scales, from rapid adjustments of movements in response to immediate rewards and errors, to long-term learning of behavioral sequences that unfold over many seconds," he said.
The research was published on Aug. 30 in the journal Neuron.
The model can explain how animals perform an array of sensory-motor tasks in the natural world, including skilled reaching movements toward visual targets, planning the trajectories of eye movements to select target objects to fixate while foraging for food, and acquiring language through associative learning.
"The model reveals common computational mechanisms across species and tasks," said Musallam. "Despite large differences in the motor and cognitive systems across animals, the basal ganglia appear to use similar principles of computation regardless of whether the system is controlling reaching movements or eye movements; and that these principles are shared across different tasks such as motor planning and decision-making."
Musallam and his team are now using the model to make more precise predictions that can be tested with neural recordings in experimental animals. They also plan to use the model to develop novel treatment strategies for neurological diseases that affect the basal ganglia, such as Parkinson's disease.
