Empirical methods are employed to investigate time perception, human motor (skill) learning, and implicit motor learning. On the computational front, we use state-of-the-art deep learning models for structure-function mapping, classification of brain disorders, whole-brain models as well as for modeling phases of skill learning.

Theoretical investigation is being carried out to understand the sense of magnitude, sense of agency / volition and brain measures of consciousness. Going forward, we are also eager to understand how cognitive science can contribute to developing AI models.