  Obesity is a serious issue in the modern society and is often associated to
significantly reduced quality of life. Current research conducted to explore
obesity-related neurological evidences using electroencephalography (EEG) data
are limited to traditional approaches. In this study, we developed a novel
machine learning model to identify brain networks of obese females using alpha
band functional connectivity features derived from EEG data. An overall
classification accuracy of 0.937 is achieved. Our finding suggests that the
obese brain is characterized by a dysfunctional network in which the areas that
responsible for processing self-referential information and environmental
context information are impaired.
