Brain models help explain Human Neuroscience data in terms of underlying biophysical mechanisms. In this work, we developed a brain model which produces functional networks corresponding closely to those observed in Human Neuroscience data. Further, we identified the specific model components that contribute to the correspondence between model-generated and experimentally observed networks. These models will help pinpoint disrupted brain mechanisms underlying neurodegenerative disorders, e.g. Alzheimer’s Disease (AD).