In the Escola lab we use computational models and theory to understand motor control and sequence generation. Experimental results from the mammalian motor system provide the primary constraints for our models. Thus, we actively collaborate with and gain insights from experimental colleagues including Rui Costa and Mark Churchland at Columbia and Bence Olveczky at Harvard. Current questions we are pursuing in the lab include: What learning rules are needed between cortex and subcortical systems to support the expression of many motor skills and modes of behavior? How and when does subcortical consolidation occur for highly practiced motor skills? Can networks that learn to control biomechanically realistic virtual bodies and limbs with realistic feedback inform our understanding of motor learning in the motor cortex? And what is the role of ongoing dopamine mediated plasticity in the basal ganglia and climbing fiber mediated plasticity in the cerebellum during motor learning and task performance?
See the lab website for details.