Overview
As a theorist, I use concepts from Statistical Physics, Inormation Theory and Deep Learning to understand various aspects of neural dynamics, cognition and consciousness.
Self-Organized Criticality in the Brain
According to statistical physics, there exists a space between order and disorder where special proprties such as long range correlations, scale invariance and optimal information processing arise. I have been exploring the brain criticality hypothesis which posits that the brain self-organizes close to this critical phase to learn and adapt optimally.
Altered States of Consciousness
ASCs such as sleep, anesthesia and psychedelic states are characterized by profound changes in subjective experience and brain dynamics. I have been analyzing and modeling the information-theoretic signatures that characterize these states.
Neuro-AI
Inspired by the brain’s remarkable ability to learn and adapt, I am also exploring how principles of self-organized criticality and emergence can be harnessed to improve the generalization capabilities of artificial neural networks.