Optimal Multivariate Transfer Entropy to Determine Differences in Short and Long-Range EEG Connectivity in Children with ADHD and Healthy Children - Ali Ekhlasi; Ali Motie Nasrabadi; Mohammadreza Mohammadi (Frontiers in Biomedical Technologies)
Purpose: Investigating brain connectivity using Electroencephalogram (EEG) is a valuable method for studying mental disorders, such as Attention-Deficit/Hyperactivity Disorder (ADHD), and optimizing and developing measures of effective connectivity can provide new insights into differences in brain communication in such disorders. Multivariate Transfer Entropy (MuTE) is a measure of causal connectivity that quantifies the influence of multiple variables on each other in a system. In this study, the MuTE measure was modified by incorporating an interaction delay parameter in connectivity calculations to create a measure with self-prediction optimality, which we named .