research

The DyCoN Lab investigates the computational and neural foundations of learning and performance. Our work spans multiple methods and disciplines:

Computational Modeling

We build models of neural dynamics and learning systems to understand how the brain adapts to complex environments.

Behavioral Experiments

Using immersive VR tasks and standard computer-based tasks with eyetracking, we study how movement, feedback, and task structure influence learning and decision-making.

Neuroimaging

We use fMRI and MRS to examine the neural mechanisms underlying learning, with recent focus on how the brain achieves task-specific sensory processing and the implications this has for learning and performance.

Brain-Inspired AI

Our models inform the design of AI systems that learn and adapt using biologically grounded principles.