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Related Experiment Video

Updated: Jan 7, 2026

Dried Blood Spot Collection of Health Biomarkers to Maximize Participation in Population Studies
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Biomarkers.

Pooja Prabhu1, Kamalini G Ranasinghe1, Kiwamu Kudo1,2

  • 1University of California San Francisco, San Francisco, CA, USA.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|December 24, 2025
PubMed
Summary
This summary is machine-generated.

Alzheimer's disease (AD) shows consistent brain network abnormalities across different measures. These findings reveal specific brain regions and frequencies affected by AD, aiding future research.

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Area of Science:

  • Neuroscience
  • Biomagnetism
  • Brain Network Analysis

Background:

  • Alzheimer's disease (AD) is characterized by altered brain network function, with increased delta-theta and decreased alpha-beta oscillatory activity observed.
  • These frequency-specific changes in AD are region-dependent, affecting frontal, temporal, and parietal cortices differently.
  • The consistency of these abnormalities across various connectivity metrics in AD remains largely unexplored.

Purpose of the Study:

  • To investigate the consistency of frequency-specific and region-dependent oscillatory abnormalities in Alzheimer's disease (AD).
  • To examine local and long-range brain network synchrony using magnetoencephalography (MEG) in AD patients and controls.
  • To compare different metrics of oscillatory activity for their ability to detect AD-related neurophysiological changes.

Main Methods:

  • Utilized magnetoencephalography (MEG) in a cohort of 77 AD patients and 90 age-matched controls.
  • Computed regional spectral power (SP) for local neural synchrony.
  • Calculated amplitude-envelope correlation (AEC) for slow timescale long-range synchrony and imaginary coherence (IMCOH) for fast timescale long-range synchrony across delta-theta, alpha, and beta bands.

Main Results:

  • Confirmed increased delta-theta and reduced alpha-beta oscillatory activity in AD patients compared to controls.
  • Demonstrated consistent regional dependencies for frequency-specific patterns across different connectivity metrics.
  • Identified specific regions, such as dorsal frontal and anterior cingulate cortices for delta-theta increases, and temporal/parietal regions for alpha/beta reductions.

Conclusions:

  • Neurophysiological manifestations in AD are conserved across various synchronization paradigms, reflecting the functional architecture of neural networks.
  • Established unified regions-of-interest for delta-theta, alpha, and beta frequency components in AD.
  • Findings provide a basis for future investigations into pathobiological relationships within these defined AD-related brain regions and frequency bands.