Neural synchrony network disruptions in Alzheimer's disease revealed with MEG imaging

Poster Session F - Tuesday, April 1, 2025, 8:00 – 10:00 am EDT, Back Bay Ballroom/Republic Ballroom

Pooja Prabhu¹, Kiwamu Kudo^1,2, Leighton Hinkley¹, Faatimah Syed³, Anne Findlay¹, Bruce Miller³, Joel Kramer³, John Houde⁴, Keith Vossel^3,5, Kamalini Ranasinghe³, Srikantan Nagarajan¹; ¹Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA, ²Medical Imaging Business Center, Ricoh Company Ltd., Kanazawa, Japan, ³Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA, ⁴Speech Neuroscience Laboratory, Department of Otolaryngology—Head and Neck Surgery, University of California San Francisco, San Francisco, California 94143, USA, ⁵Mary S. Easton Center for Alzheimer’s Disease Research, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA

Changes in brain network function, specifically neural synchrony have been clearly demonstrated in patients with Alzheimer's disease (AD). Previous electrophysiological studies reveal that delta and theta oscillatory activity increases in AD, while alpha and beta activity decreases. These abnormalities are frequency-specific and region-dependent, but their consistency across different local and long-range neural synchrony metrics remains unknown. Here, in a well characterized, AD biomarker positive cohort of 77 AD patients and age-matched controls (n=90), we used magnetoencephalography (MEG) to examine the local and long-range oscillatory abnormalities. Specifically, source-space reconstructed MEG signal for 40 modular level cortical regions (Brainnetome-atlas) was used to compute three different metrics: local synchrony estimated as regional spectral power; long-range synchrony at slow time-scale estimated from amplitude-envelope correlation; and long-range synchrony at fast time-scale estimated from imaginary coherence. Each measure was computed for 2–7 Hz (delta-theta), 8–12 Hz (alpha), and 15–29 Hz (beta) bands. Consistent with previous results, we found that increased delta-theta and reduced alpha and beta oscillatory activity patterns in AD compared to controls. A conjoint analysis, in which we examined the common spatial patterns across different metrics of neural synchrony demonstrated that the frequency-specific patterns have consistent regional dependencies. The dorsal frontal and anterior cingulate cortices showed the highest delta-theta increases, while the inferolateral temporal cortices and posterior temporoparietal regions consistently showed the greatest reductions in alpha band. Our results show that frequency-specific, region-dependent neurophysiological manifestations in AD are conserved across different synchronization paradigms that contribute to the functional architecture of neural networks.

Topic Area: METHODS: Neuroimaging