Spectral graph modeling reveals global slowing of neurophysiological network transmission in Alzheimer's disease.

Alzheimer's disease (AD) is the most common form of dementia, progressively impairing memory and cognition. While neuroimaging studies have revealed functional abnormalities in AD, how these relate to aberrant neuronal circuit mechanisms remains unclear. We employed a spectral graph-theory model (SGM) to identify abnormal biophysical markers of neuronal activity in AD. SGM is an analytic model that describes how long-range fiber projections in the brain mediate excitatory and inhibitory activity of local neuronal subpopulations. We estimated SGM parameters that captured the regional power spectra obtained from magnetoencephalography imaging of a well-characterized population of patients with AD and controls. The long-range excitatory time constant was the most important feature for the accurate classification of AD and controls and was associated with global cognitive deficits in AD. These results indicate that a global impairment in the long-range excitatory neurons might be a sufficient factor underlying spatiotemporal alterations of neuronal activity in AD.