Motor control, skill learning, and sensorimotor cognition
From becoming a tennis pro to mastering a musical instrument, the human brain has given us powerful tools to support motor learning. In the ACT lab, we investigate the psychological and neural principles of motor behavior. To do this, we use behavioral experiments, computational modeling, neuroimaging, and neuropsychology techniques. One of our main interests is how neural systems supporting higher-level cognition intertwine with the lower-level control of movements, the so-called "cognitive-motor interface." We are currently focusing on the following questions: How do skills evolve from being cognitively demanding to automatic? How does abstract thought facilitate motor learning Which aspects of motor skill rely on explicit versus implicit memory? We believe that uncovering the fundamental neural and computational principles of motor skill learning will broaden our understanding of complex human mental functions, inspire new computational frameworks of animal and machine learning, and inform novel clinical approaches.
McDougle earned his BA in Neuroscience and Behavior from Vassar College in 2009 and his PhD in Neuroscience and Psychology from Princeton University in 2018. After completing a postdoctoral fellowship at UC Berkeley, Sam opened the Action, Computation, and Thinking (ACT) Lab in Yale's Department of Psychology in 2020. Sam enjoys playing and performing old-time, folk, and bluegrass music (fiddle and mandolin) and backyard lounging with his partner Kelly and son Leo.