Graph theory has been applied to study brain network connectivity on cross-sectional imaging. We extend the existing study to analyze brain network connectivity on longitudinal imaging. Representing the temporal brain network as a multi-layer graphical network, various metrics are proposed to analyse the temporal brain connectivity that involves the intra/inter-layer communications. The supra-Laplacian is considered along with inter layer graph-Laplacian to provide insights into the temporal evolution.

This is poster number 12 in Poster Session

Authors:

Poay Hoon Lim (University of Calgary)

Wee Keong Lim (Marianopolis College)

Keywords:

brain network, machine learning