4.6 Article

Relative power and coherence of EEG series are related to amnestic mild cognitive impairment in diabetes

Journal

FRONTIERS IN AGING NEUROSCIENCE
Volume 6, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fnagi.2014.00011

Keywords

resting-state EEG; a mnestic mild cognitive impairment; diabetes; relative power; coherence

Funding

  1. National Science Foundation of China [61025019, 31070938, 81230023]
  2. State Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University

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Objective: Diabetes is a risk factor for dementia and mild cognitive impairment. The aim of this study was to investigate whether some features of resting-state EEG (rsEEG) could be applied as a biomarker to distinguish the subjects with amnestic mild cognitive impairment (aMCI) from normal cognitive function in type 2 diabetes. Materials and Methods: In this study, 28 patients with type 2 diabetes (16 aMCI patients and 12 controls) were investigated. Recording of the rsEEG series and neuropsychological assessments were performed. The rsEEG signal was first decomposed into delta, theta, alpha, beta, gamma frequency bands. The relative power of each given band/sum of power and the coherence of waves from different brain areas were calculated. The extracted features from rsEEG and neuropsychological assessments were analyzed as well. Results: The main findings of this study were that: (1) compared with the control group, the ratios of power in theta band [P(theta)] vs. power in alpha band [P(alpha)] [P(theta)/P(alpha)] in the frontal region and left temporal region were significantly higher for aMCI, and (2) for aMCI, the alpha coherences in posterior, fronto-right temporal, fronto-posterior, right temporo-posterior were decreased; the theta coherences in left central-right central (LC-RC) and left posterior-right posterior (LP-RP) regions were also decreased; but the delta coherences in left temporal-right temporal (LT-RT) region were increased. Conclusion: The proposed indexes from rsEEG recordings could be employed to track cognitive function of diabetic patients and also to help in the diagnosis of those who develop aMCI.

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