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Related Experiment Video

Updated: Jun 18, 2025

Combined Invasive Subcortical and Non-invasive Surface Neurophysiological Recordings for the Assessment of Cognitive and Emotional Functions in Humans
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Difference between subjective and objective cognitive decline confirmed by power spectral density.

Ho Tae Jeong1, Young Chul Youn1, Kwang-Yeol Park1

  • 1Department of Neurology, Chung-Ang University Hospital, College of Medicine, Chung-Ang University, Seoul, Korea.

Cognitive Neuropsychiatry
|July 28, 2024
PubMed
Summary

Power spectrum analysis of resting-state EEG can identify subjective cognitive decline (SCD), a preclinical stage of Alzheimer's disease (AD). This method shows potential for early AD diagnosis and biomarker development.

Keywords:
Preclinicalmild cognitive impairmentquantitative EEGsubject cognitive decline

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Area of Science:

  • Neuroscience
  • Biomarkers
  • Alzheimer's Disease Research

Background:

  • Subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) represent preclinical stages of Alzheimer's disease (AD).
  • Early diagnosis of AD is crucial for timely intervention and management.
  • Identifying reliable biomarkers for preclinical AD is an ongoing research priority.

Purpose of the Study:

  • To investigate power spectrum changes in electroencephalography (EEG) as potential biomarkers for SCD and aMCI.
  • To explore the utility of relative power spectral density (PSD) in differentiating between SCD and aMCI.
  • To assess the potential of EEG-based biomarkers for early Alzheimer's disease diagnosis.

Main Methods:

  • Recruited 23 SCD and 32 aMCI subjects for comparative analysis.
  • Utilized relative power spectral density (PSD) analysis of resting-state EEG data.
  • Employed automated preprocessing and statistical analysis via iSync Brain® software.

Main Results:

  • Significant differences in theta band power were observed in temporal and parietal regions between SCD and aMCI groups.
  • Beta1 band power showed distinct patterns in the frontal and temporal regions differentiating the two groups.
  • PSD analysis revealed electrical-physiological characteristics distinguishing preclinical AD stages.

Conclusions:

  • Resting-state EEG PSD analysis shows promise in predicting subjective cognitive decline (SCD), an early stage of Alzheimer's disease (AD).
  • This study highlights the potential of EEG-based measures as biomarkers for preclinical AD.
  • Further longitudinal studies are required to confirm the predictive value of these findings for future cognitive decline.