SIS Epidemics and the Direction of Information Flow in Brain Networks

Jil Meier¹

The interplay between structural connections and emerging information flow in the human brain remains an open research problem. A recent study observed global patterns of directional information flow in empirical data using the measure of transfer entropy. For higher frequency bands, the overall direction of information flow was from posterior to anterior regions whereas an anterior-to-posterior pattern was observed in lower frequency bands. In this study, we applied a simple SIS epidemic spreading model on the human connectome with the aim to reveal the topological properties of the structural network that give rise to these global patterns. In order to quantify the information flow between regions, we computed the transfer entropy values for all node pairs evaluating different time windows. We found that direct structural connections induced higher transfer entropy between two brain regions and that transfer entropy decreased with increasing distance between nodes (in terms of hops in the structural network). Applying the SIS model, we were able to confirm the empirically observed opposite information flow patterns, which seem to be linked to different time scales of the spreading process. Posterior hubs in the structural network appear to play a dominant role in the network dynamics since the global pattern of information flow is in the posterior-to-anterior direction when these hubs are strong senders, and in the opposite direction when they are strong receivers. Our analysis suggests that these global patterns of directional information flow are the result of an unequal spatial distribution of the structural degree between posterior and anterior regions.