Transfer Entropy as a Measure of Brain Connectivity: A Critical Analysis With the Help of Neural Mass Models.

ABSTRACT: Objective: Assessing brain connectivity from electrophysiological signals is of great relevance in neuroscience, but results are still debated and depend crucially on how connectivity is defined and on mathematical instruments utilized. Aim of this work is to assess the capacity of bivariate Transfer Entropy (TE) to evaluate connectivity, using data generated from simple neural mass models of connected Regions of Interest (ROIs). Approach: Signals simulating mean field potentials were generated assuming two, three or four ROIs, connected via excitatory or by-synaptic inhibitory links. We investigated whether the presence of a statistically significant connection can be detected and if connection strength can be quantified. Main Results: Results suggest that TE can reli

SUBMITTER: Ursino M 

PROVIDER: S-EPMC7292208 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature