CRCNS: Investigating Brain Dynamics through the Lens of Statistical Mechanics

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Synaptic dysfunction has been hypothesized to be one of the earliest brain changes in Alzheimer’s disease (AD), leading to hyper-excitation in neuronal circuits. However, network changes related to age and sex tend to overlap with disease neuropathology, increasing the difficulty of separating disease-specific alterations from those related to normal aging trajectories in males and females. Indeed, AD disproportionately affects women, who comprise two thirds of all persons diagnosed with AD dementia. Leveraging resting state fMRI connectome and diffusion MRI-derived structural connectome, we will use a novel hybrid resting-state structural connectome (rs-SC) to study excitation-inhibition balance. Recently, using a group of cognitively normal APOE-ε4 carriers and age/gender matched non-carriers we demonstrated a sex-by-age-by-phenotype interaction, with significant hyperexcitation with increasing age only observable in women, but not in men. Further, hyperexcitation in female carriers began to exhibit at age 50 in the anterior cingulate, parahippocampal gyrus and temporal lobe regions, and the degree of hyperexcitation is linked to compensatory recruitment of neuronal resources during a spatial learning memory task. In this proposal, we will characterize 1) sex-specific normative trajectories of excitation-inhibition balance using the Human Connectome Project (HCP) data, and 2) altered excitation-inhibition balance in abnormal aging using the Alzheimer’s Disease Neuroimaging Initiative (ADNI) data, as well as 3) further test and validate our hyperexcitation framework in longitudinal mouse models of AD. RELEVANCE (See instructions): In this proposal, we will develop novel computational tools to characterize hyper-excitation patterns in aging and Alzheimer's Disease and validate our hyperexcitation framework on human data (ADNI and HCP) as well as longitudinal mouse models of AD. This will significantly improve our understanding of AD and potentially accelerate the discovery of more robust non-invasive imaging biomarkers of AD.