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

Abstract

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.

Time-Frequency Wavelet Based Coherence Analysis of EEG in EC and EO during Resting State

“…Relative power and coherence used by [9] to analyze the amnestic mild cognitive impairment in diabetes. They investigated alpha coherence and correlations in intra region (parietal) and inter region (right temporo-posterior, fronto-posterior), interhemispheric (LH, RH), Left posterior (LP)-right posterior (RP) regions in aMIC and control groups and found significant results in alpha frequency band while other bands exhibits no significant differences.…”

Weighted-Permutation Entropy Analysis of Resting State EEG from Diabetics with Amnestic Mild Cognitive Impairment

“…And type 2 diabetes may increase the risk In order to further support the utility of WPE in detecting aMCI in diabetes, the correlations between the WPE values and neuropsychological assessment scores were analysed. The scores of MoCA, AVLT-Immediate recall, AVLT-Delayed recall, AVLT-Delayed recognition, BNT, and WAIS-DST were significantly different between the two groups, which was reported in [23]. The correlations between the normalized values of WPE in RT with these neuropsychological test scores are shown in Figure 4 In order to further support the utility of WPE in detecting aMCI in diabetes, the correlations between the WPE values and neuropsychological assessment scores were analysed.…”

“…The participants had no histories of mental illness, systemic disease, and nervous system disease which may result in cognitive impairment [23], and organic brain disease and depression were all ruled out by using MRI and the DSM IV criteria for depression [35], as reported in [23].…”

“…Artifacts (such as ocular and muscular noise) in all channels were eliminated by visual inspection of the raw EEG data, but there almost no for the patients were closed eyes and relaxed, so the segment length of data was at least N = 4500 (500 Hz × 60 s × 1.5 min). In this study, 3-min of data from each channel were selected for further analysis, and the electrodes and areas of interest (five regions: frontal (F), left temporal (LT), central (C), right temporal (RT) and posterior (P)) were the same as described in [23].…”

“…In the previous study [23], the role of relative power and coherence was investigated in distinguishing aMCI and controls in diabetes, and the methods were linear. In this study, we try to investigate whether PE or WPE can be a potential objective complexity index of EEG to distinguish diabetics with aMCI from non-aMCI diabetic controls.…”