Recurrence analysis of neuronal behaviors and networks

The goal of this project is to bridge the fields of neuroscience and nonlinear dynamics by leveraging advanced machine learning algorithms to analyze recurrence patterns in neural wave data. Specifically, the project focuses on studying traveling cortical waves – a fundamental phenomenon in brain activity – using recurrence quantification analysis enhanced by machine learning techniques. By combining these approaches, we aim to uncover novel physical relationships and dynamical properties underlying neural processes, providing deeper insights into how the brain organizes and propagates information.

Faculty Supervisor:

Lyle Muller

Student:

Partner:

Federal University of Parana

Discipline:

Physics

Sector:

Artificial Intelligence; Life Sciences (not health)

University:

The University of Western Ontario

Program: