. Three major principles are at the forefront of current understanding about the pathology and potential therapeutic approach to addressing the massive public health burden of Alzheimer?s disease (AD). First, the clinical symptoms and functional dependence resulting from this disease are known to occur after potentially decades of degenerative brain changes linked to amyloid plaque and neurofibrillary tangle cortical pathologies. Second, prevalent comorbid pathologies, particularly metabolic and cerebrovascular dysfunction, contribute to a hastening of disease processes and clinical decline. Third, any therapeutic intervention targeting either of these pathologic domains would need to be implemented at the earliest time possible, prior any substantial irrecoverable neurodegeneration has transpired. Functional magnetic resonance imaging (fMRI) is used to measure brain activity and previously contributed extensively to the characterization of AD progression. Individuals at genetic risk of AD show altered fMRI indicators even prior to expression of cognitive impairment, and thus, fMRI has provided critical insights into pathophysiology of preclinical AD. The fMRI signal is an indirect correlate of neural activity that reflects coupling between metabolic demand of active brain cells and a nutritive increase in cerebral blood flow. This hemodynamic response (HDR) is measured through the blood oxygenation level dependent (BOLD) contrast mechanism. A critical barrier in the application of fMRI to the study of AD is the intricate entanglement of neural and vascular physiology at the basis of the BOLD signal resulting in an inability to differentiate between the effects of neural dysfunction and comorbid vascular pathology. The goal of this R01 research proposal is to distinguish neurophysiological from hemodynamic components of the fMRI BOLD signal and to apply this new technology to the study of the functional synaptic connectome ? the substrate for human thought and memory ? in older adults at genetic risk of AD, before any evidence of cognitive and functional decline. We will implement a cutting-edge scanning and analysis paradigm by [1] simultaneously recording electroencephalographic (EEG) and fMRI data, [2] quantifying transient events of intrinsic neurophysiological activity in brain networks, [3] using these events to anchor measurement of the neurally induced HDR, and [4] isolating changes in neurophysiological events and HDR between stable and learning regimes of the dynamic functional connectome. Successful implementation of this approach would provide novel insight into how genetic vulnerabilities are linked to distinct neural and vascular mechanisms dysregulating balance between stability and learning in the functional connectome. Disruption in stable patterns of spontaneous neural activity has been suggested to influence the plaque pathology in AD. Targeting specific neural and vascular pathophysiology by novel, alternative therapies in preclinical AD holds promise to make prevention and early intervention, to thwart or slow down progressive neurodegeneration, possible.
. There is a great need for functional brain mapping technologies that are sensitive to dynamic synaptic connectivity in memory-related neural networks and can differentiate such abnormalities from functional deficits resulting from highly comorbid metabolic and vascular pathologies in the earliest stages of Alzheimer's disease. We propose to optimize cutting-edge technology to achieve this goal through temporally resolved imaging of resting state and learning consolidation via an innovative combined electroencephalography and functional magnetic resonance imaging procedure to be assessed in individuals with genetic risk for Alzheimer's disease.
