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EEG signal complexity after repeated mild traumatic brain injury in a mouse model of Alzheimer’s disease.

Poster Session F - Tuesday, March 10, 2026, 8:00 – 10:00 am PDT, Fairview/Kitsilano Ballroom

Victoria Carriquiriborde^1,2, Emad Shams^1,2, Jefferey Yue^1,2, Cheryl Wellington³, Randy McIntosh^1,2, Kelly Shen¹, Brianne Kent^1,2; ¹Institute for Neuroscience and Neurotechnology, Simon Fraser University, ²Simon Fraser University, ³University of British Columbia

Multiscale entropy (MSE) is a measure of neural signal complexity and correlates with cognitive status in healthy aging and dementia. Traumatic brain injuries (TBI) can alter cognitive function and increase the risk of some dementias, such as Alzheimer’s disease (AD). However, whether repetitive TBI affect MSE remains unknown. Here, using a mouse model of AD, we investigate whether repetitive mild TBI (rmTBI) is associated with MSE alterations in the context of AD. Using the closed-head injury model of engineering rotational acceleration (CHIMERA), we delivered three rmTBI 48 hours apart to female and male APPNL-F transgenic mice (n=44) at either 6 or 12 months of age. At 15 months of age, we implanted intracortical EEG electrodes and recorded 72 continuous hours of EEG/EMG. MSE was calculated for each vigilance state: NREM, REM, and wake. Mice receiving rmTBI at 12 months exhibited significantly altered MSE patterns in parietal cortex three months post-injury compared to sham controls. Specifically, the rmTBI group showed reduced MSE at finer timescales and elevated MSE at coarser timescales across all vigilance states. This bidirectional pattern mirrors the shifts in MSE associated with AD and other neurodegenerative diseases in humans. These findings demonstrate that rmTBI produces chronic alterations in neural signal complexity. While these MSE changes may relate to post-TBI cognitive impairments observed clinically, further research is needed to establish direct links between MSE patterns and specific cognitive deficits following TBI.

Topic Area: METHODS: Electrophysiology