Poster A94, Saturday, March 25, 5:00 – 7:00 pm, Pacific Concourse
Age Related Changes in Neural Noise in the Default Mode Network
Nicole Dosamantes1, Jorge Yanar1, Lorri Kais1, Hannah Walker1, Mark Albert1, Robert G Morrison1; 1Loyola University Chicago
The Default Mode Network (DMN) describes a network of highly connected brain regions that are more active in the absence of task engagement. These regions, including medial prefrontal cortex, posterior cingulate, and areas in lateral parietal and temporal cortices show a high degree of functional connectivity when active. Activation and connectivity in these regions show declines with aging, particularly when neurodegeneration is present. Recently, Voytek et al. (2015) argued that increases in neural noise may be an important mechanism responsible for cognitive aging. They estimate neural noise by calculating the slope of the power spectral density (PSD) in semi-log space using a general linear model with a robust regression method, and find that the slope of the PSD gradually flattens with age in electrophysiological recordings made during the performance of a visual working memory task. In this study we aimed to investigate whether neural noise as measured through these techniques also underwent age-related increases during rest in the DMN. Specifically, we recorded resting-state scalp electroencephalography (rsEEG) from 36 young adults (24 to 52 YO, M=31) and 49 older adults (65 to 92 YO, M=80) and utilized source modeling as implemented in BESA to estimate EEG from these six regions of the DMN. We then calculated the PSD from artifact-free rsEEG segments and calculated the slope using RANSAC regression. Younger adults showed more negative PSD slopes throughout the 6 DMN regions, suggesting that older adults show evidence of more neural noise in areas associated with DMN during rest.
Topic Area: METHODS: Electrophysiology