Introduction: Spectral power analyses of resting-state electroencephalography (rs-EEG) yield spatially-distributed
networks of coherently oscillating activity. These patterns are thought to represent
the brain’s intrinsic connectivity and can predict individual cognitive abilities
and inform on pathological brain states. The present study investigates rs-EEG and
its relationship to both TMS-based neurophysiological measures and learning and memory
function in older adults with Alzheimer’s disease (AD), type-2 diabetes mellitus (T2DM),
and non-AD/non-T2DM controls.
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© 2017 Published by Elsevier Inc.
