Overfitting mitigation in correlation matrices and applications to the study of brain connectivity

We compare various known and original strategies of overfitting mitigation in correlation matrices, in the context of brain functional connectivity. In particular, we infer a database of human brain activity from functional Magnetic Resonance Imaging (fMRI), beyond Maximum Likelihood inference and using the multivariate Gaussian as likelihood. We show that the relative algorithm performances are consistent across subjects, and across samples of a synthetic database of similar characteristics. We observe as well that the resulting cleaned correlation matrices, that are proposed as a refined model of functional connectivity, depend crucially on the cleaning algorithm. We discuss possible applications of these findings to network neuroscience.

Ponente: Dr. Miguel Ibáñez. ISTC-CNR (Italy).

Fecha y hora: lunes, 28 de junio de 2021 a las 12:00. 

Lugar: Seminario de Física Computacional, planta baja del edificio de Física (hasta completar aforo) y vía Google Meet: https://meet.google.com/ijd-agcd-rye..