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The Brain Resilience Study: Neural signal complexity from low-resolution EEG reflects cognitive performance in aging

Poster Session D - Monday, March 9, 2026, 8:00 – 10:00 am PDT, Fairview/Kitsilano Ballroom

Maryam Faeed¹, Leanne Rokos^1,2, Kelly Shen², Cathlin J. Han¹, Aina Roenningen¹, Kashish Mehta¹, Anthony Randal McIntosh^1,2, Brianne Kent^1,2; ¹Simon Fraser University, ²Institute for Neuroscience and Neurotechnology, Simon Fraser University

Aging is accompanied by changes in brain structure and function that are thought to be related to cognitive decline. Neural complexity is an indicator of information processing capacity in brain networks and is associated with cognitive function. In the present study, we investigated the relationship between signal complexity measured using multiscale entropy (MSE) and cognitive performance (MoCA and CANTAB) in older adults. While previous studies have established associations between MSE of EEG signals and cognitive outcomes, these findings have mostly relied on high-density EEG systems. Here, we aim to determine whether similar relationships could be detected using a low-resolution, portable EEG device. We recorded 5 minutes of resting-state EEG in older adults (82 participants; 39 females; ages 52–84 years) using the Muse S (InterAxon) 4-channel system. Data were band-pass filtered, epoched, and artifacts were identified for rejection by local Autoreject. MSE was calculated for each channel and epoch and averaged per participant. Then, it was examined using Partial Least Squares to extract patterns associated with cognition. Participants were differentiated by cognitive scores and revealed a shift toward higher entropy at finer time scales and lower entropy at coarser time scales, with better memory performance (p < 0.05), with stronger effects at finer temporal scales. Additionally, the mean-centered PLS showed different MSE between sexes (p < 0.05). These findings suggest that EEG signal complexity from low-resolution EEG can provide unique insight into cognitive function across aging and sexes.

Topic Area: METHODS: Electrophysiology