Over the last decade, there has been a growing interest in understanding the brain mechanisms underlying the loss of the brain homeostasis in the continuum of Alzheimer's Disease (AD). Animal models suggest that the substrate for this phenomenon is the loss of the excitatory/inhibitory (E/I) balance due to the toxic effects of amyloid oligomers and plaques on inhibitory terminals. This hyperexcitability is presumed to underlie the observed increases in power and interarea synchronization of alpha/beta frequency oscillations measured in humans with electro- and magneto-encephalography (M/EEG). Amnesic mild cognitively impaired (aMCI) patients present increased resting-state MEG power in (7-14Hz) alpha and (15-29Hz) beta bands in brain regions with higher amyloid deposition. Additionally, aMCI patients who later converted to AD (CONV), compared to non-converters (NOCONV), showed increased synchrony between anterior and posterior brain regions. While animal and human studies are highly synergistic, it is unknown if the hyperexcitability found in animal models is the origin of the hypersynchronization found in human neurophysiology. To bridge this gap, the current proposal will apply a recently developed a computational neural modeling framework uniquely designed to link human macroscale M/EEG signals to the underlying cellular and circuit level dynamics that can be interrogated with invasive animal recordings or other imaging modalities (e.g., MR spectroscopy, tractography), namely Human Neocortical Neurosolver (HNN). We will apply new analysis methods to previously collected longitudinal MEG, tractography, volumetry, and MR GABA spectroscopy data in CONV- and NOCONV- aMCI patients and controls (Aims 1 and 3) and integrate the results with the HNN framework (Aim 2) to establish new early diagnostic AD biomarkers and to interpret the detailed neural mechanisms underlying these biomarkers. RELEVANCE (See instructions): There is a growing public health need to understanding the brain mechanisms underlying the loss of the brain homeostasis in the continuum of Alzheimer's Disease (AD). This project aims to define new early diagnostic measures for AD and targeted treatment strategies for early intervention based on identified neural circuit abnormalities. The project has the potential to open a completely new window to counteract and delay cognitive decline with aging, ultimately reducing the cost for caregivers and improving the