Alzheimer’s Research & Therapy (Dec 2023)

Neurophysiological markers in community-dwelling older adults with mild cognitive impairment: an EEG study

  • Osamu Katayama,
  • Yaakov Stern,
  • Christian Habeck,
  • Sangyoon Lee,
  • Kenji Harada,
  • Keitaro Makino,
  • Kouki Tomida,
  • Masanori Morikawa,
  • Ryo Yamaguchi,
  • Chiharu Nishijima,
  • Yuka Misu,
  • Kazuya Fujii,
  • Takayuki Kodama,
  • Hiroyuki Shimada

DOI
https://doi.org/10.1186/s13195-023-01368-6
Journal volume & issue
Vol. 15, no. 1
pp. 1 – 17

Abstract

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Abstract Background Neurodegeneration and structural changes in the brain due to amyloid deposition have been observed even in individuals with mild cognitive impairment (MCI). EEG measurement is considered an effective tool because it is noninvasive, has few restrictions on the measurement environment, and is simple and easy to use. In this study, we investigated the neurophysiological characteristics of community-dwelling older adults with MCI using EEG. Methods Demographic characteristics, cognitive function, physical function, resting-state MRI and electroencephalogram (rs-EEG), event-related potentials (ERPs) during Simon tasks, and task proportion of correct responses and reaction times (RTs) were obtained from 402 healthy controls (HC) and 47 MCI participants. We introduced exact low-resolution brain electromagnetic tomography-independent component analysis (eLORETA-ICA) to assess the rs-EEG network in community-dwelling older adults with MCI. Results A lower proportion of correct responses to the Simon task and slower RTs were observed in the MCI group (p < 0.01). Despite no difference in brain volume between the HC and MCI groups, significant decreases in dorsal attention network (DAN) activity (p < 0.05) and N2 amplitude of ERP (p < 0.001) were observed in the MCI group. Moreover, DAN activity demonstrated a correlation with education (Rs = 0.32, p = 0.027), global cognitive function (Rs = 0.32, p = 0.030), and processing speed (Rs = 0.37, p = 0.010) in the MCI group. The discrimination accuracy for MCI with the addition of the eLORETA-ICA network ranged from 0.7817 to 0.7929, and the area under the curve ranged from 0.8492 to 0.8495. Conclusions The eLORETA-ICA approach of rs-EEG using noninvasive and relatively inexpensive EEG demonstrates specific changes in elders with MCI. It may provide a simple and valid assessment method with few restrictions on the measurement environment and may be useful for early detection of MCI in community-dwelling older adults.

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