Wednesday, January 15, 2025
1/15/2025
Abstract/Project Summary The United States population is becoming increasingly older and the prevalence of Alzheimer’s disease (AD) and its common precursor, mild cognitive impairment (MCI), is expected to dramatically rise in the coming years. As such, there is an immediate national need to further understand the neurophysiological basis of these neuro- degenerative diseases. Recent studies have shown disruption of gamma-band neural oscillatory activity in animal models of AD. Further, visual stimulation at gamma frequencies has been shown to increase the clearance of amyloid-β (Aβ) and hyperphosphorylated tau in mouse models, while improving cognitive performance. Despite these groundbreaking findings, research into gamma oscillatory activity in humans with AD remains scarce. Relatedly, visuospatial attention processes are among the earliest and most severely affected cognitive functions in MCI and AD. Dysfunction in this domain has also been shown to be more specific for identifying Alzheimer’s type dementia relative to other forms (e.g., frontotemporal dementia) when compared to dysfunction in other cognitive domains (e.g., memory). Although neuropsychological testing has shown clear deficits in visuospatial attention in patients with MCI and AD, very little is known about the neural oscillatory activity that underlies these deficits. The current study aims to partially remedy these knowledge gaps by utilizing the spatial precision and exquisite temporal resolution (i.e., millisecond) of magnetoencephalographic (MEG) imaging. Briefly, persons with AD, MCI, and demographically-matched controls will complete two cognitive tasks during MEG recording; one examining multispectral visual entrainment activity and another investigating visuospatial attention processing. The resulting MEG data will be transformed into the time-frequency domain and imaged using a beamforming approach. The output dynamic functional maps of electrical neural activity will be used to examine baseline and task-related entrainment and oscillatory activity among regions serving visual and visuospatial processing. In particular, we will identify the statistically anomalous neural oscillations in patients with MCI and AD, and then link these neural data to regional Aβ deposition and overall performance (e.g., general and domain-specific cognition, functional capacity, etc.). Our Aims are: (1) To quantify the cortical dynamics during visual entrainment at specific frequencies (i.e., 20, 35, 40, and 45 Hz) in patients with MCI or mild AD, and decifer the relationship between local gamma activity and quantitative Aβ deposition, and (2) to identify deficits in the tracking of attended visual stimuli in patients with MCI and mild AD, and determine how this relates to cognitive performance. To this end, we will utilize the latest MEG and source reconstruction techniques, neural oscillatory analysis methods, quantitative Aβ PET imaging, and neuropsychological assessments to delineate the neurophysiological bases of cognitive impairments in patients with MCI and AD. This research will aid in illuminating the neural dynamics underlying cognitive dysfunction in those with MCI and AD, with the primary goals of scientific discovery and developing the research and clinical skills of the applicant to produce a successful physician-scientist.
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