Research interests in Yale's ACT Lab

The Action, Computation, & Thinking (ACT) Lab is directed by Samuel McDougle at Yale's Department of Psychology. The goal of our research is to leverage behavioral, computational, and neuroscience approaches to better understand the interface between cognition and action.

Humans possess an extraordinary capacity for motor skills. Alongside language and complex social cognition, one of our species' defining features is the ability to develop a vast repertoire of precise motor behaviors. While we often refer to "muscle memory" (a useful misnomer) in everyday language, acquiring and performing motor skills is more than just automatic processes and habits - it is also cognitively demanding. Expertise in domains such as music, dance, athletics, and even everyday skills like driving relies on interactions between cognitive processes, perception, and the motor system. In the ACT Lab, we explore the intersection of cognition and motor behavior using a range of methods, including behavioral experiments, computational modeling, neuroimaging, and neuropsychology.

In the lab we are broadly interested in studying how humans learn, remember, and produce intelligent actions, with special attention to the cognitive and perceptual processes involved. We think it is time we move past overly restrictive concepts when we think about motor control and motor learning - intelligent motor behavior contains multitudes. It relies on a wide variety of psychological processes, neural systems, and mental algorithms. Here are some broad questions we are currently scratching our heads over:

• How do learned motor behaviors go from controlled and effortful to automatic?

• How do cognitive computations and abstract thoughts interact with movement control?

• How does our perception of space influence how we move within it?

• Which aspects of motor memory are explicit, and which are implicit? Do these systems interact? What are their neural substrates?

• How might different cognitive systems vie for control during the selection of movements?

• What is the relationship between attention and movement planning?

• Are there domain-general neural algorithms that cut across different perceptual and motor processes?

• Do brain regions conventionally linked to motor behavior also play a role in cognition (e.g., the cerebellum)? What are these roles, and what can they tell us about the relationship between sensorimotor and cognitive processes?

We leverage multiple methodological approaches for investigating the psychology and neuroscience of cognition and action.

The careful study of behavior is key to addressing psychological and neuroscientific questions. We use a variety of behavioral paradigms, ranging from sensorimotor and reinforcement learning tasks, to working memory assays and visual and auditory perceptual psychophysics. Our goal is to use behavioral experiments to holistically test new ideas about action, perception, learning, and memory.

Computational modeling has many functions for our research, from generating precise behavioral and neural predictions, to simply organizing our thoughts. Our modeling approach relies on machine learning techniques, neuro-inspired models, and cognitive psychological methods.

Functional Magnetic Resonance Imaging has made great progress as a cognitive neuroscience technique over the last two decades. We use a combination of model-driven and multivariate fMRI methods to characterize the neural circuits underlying action, perception, and cognition. We also work with populations with particular neural pathologies, such as spino-cerebellar ataxia, to study how different brain regions (e.g., the cerebellum, basal ganglia, etc.) contribute to different components of learning and memory. We use neuropsychology both to address basic research questions, and to try and inspire improvements in neurorehabilitation protocols.