Research

Everyday actions like reaching for a glass, adjusting to a new tool, or relearning movement after injury, depend on the brain’s extraordinary capacity to plan, predict, correct, and refine motion. In the CoLA lab, we seek to understand how this is accomplished by the nervous system. Some big questions that we pursue are:

• How do we builds models of the body and environment? 

• How do we use feedback and error to update our movements?

• What are the computational mechanisms and neurophysiological systems that support these capacities?

• How do these processes change when the system is challenged by fatigue, injury, or disease?

By uncovering the fundamental rules of adaptive behavior and skilled action, we aim to reveal not only how movements are mastered, but also why learning breaks down. The insights we generate go beyond touch on health, rehabilitation and robotics. Understanding how movements are controlled, learned or impaired helps us design smarter assessments and therapies for people recovering from Stroke, Parkinson’s disease or other motor-control disorders.

To probe these questions, we employ a combination of behavioural experiments, computational modelling and neuroscience tools. Participants perform a variety of motor tasks with their upper limbs using custom VR and robotic setups that precisely track motion, forces and errors. At the same time, we apply brain stimulation using high-definition transcranial direct current stimulation (hd-tDCS) and transcranial magnetic stimulation (TMS), and build computational models that simulate how the brain predicts, corrects and learns from movement outcomes. This integrative approach allows us to connect the dots between basic neuroscience and practical applications, from understanding healthy motor learning to developing evidence-based tools for rehabilitation and skill training.