Chih-Chung Chen1, Chien-Yeh Hsu2, Hung-Wen Chiu3, Chaur-Jong Hu4, Tsung-Chieh Lee5. 1. Graduate Institute of Biomedical Informatics, Taipei Medical University, Taipei, Taiwan; Department of Neurology, Taipei Medical University-Shuang Ho Hospital, Taipei, Taiwan. 2. Graduate Institute of Biomedical Informatics, Taipei Medical University, Taipei, Taiwan. 3. Graduate Institute of Biomedical Informatics, Taipei Medical University, Taipei, Taiwan. Electronic address: hwchiu@tmu.edu.tw. 4. Department of Neurology, Taipei Medical University-Shuang Ho Hospital, Taipei, Taiwan. 5. Graduate Institute of Biomedical Informatics, Taipei Medical University, Taipei, Taiwan; Department of Biomedical Engineering, Yuanpei University, HsinChu, Taiwan.
Abstract
BACKGROUND/ PURPOSE: Slowing of average electroencephalography (EEG) frequency in Alzheimer's disease (AD) is well established, but whether EEG changes are able to reflect the severity of AD is uncertain. We attempt to establish quantitative EEG parameters that are suitable for evaluating AD in clinical practice. METHODS: Ninety-five patients with newly diagnosed AD at different stages from four neurologic institutes were enrolled for the study. Standard scalp resting EEG data were collected for quantitative analysis. Global band power ratio and interhemispheric alpha band coherence were calculated. RESULTS: Patients with advanced AD had a greater slow-to-fast wave power ratio. Among several power ratio parameters, global theta and delta to alpha and beta band power ratio showed the best correlation with stages of AD (p < 0.05 between any two patient groups). Patients with advanced AD had decreased coherence in multiple brain regions. The phenomenon was most prominent in the centroparietal region (p < 0.05 between any two patient groups). CONCLUSION: Increased global slow-to-fast power ratio and decreased centroparietal interhemispheric alpha band coherence are strongly correlated with disease progress in AD patients. These two quantitative EEG parameters may help evaluate AD patients in daily clinical practice. Global power ratio changes may suggest a shift of dominant frequency, and decreased interhemispheric alpha band coherence may suggest functional disconnection and corpus callosum abnormalities in AD patients.
BACKGROUND/ PURPOSE: Slowing of average electroencephalography (EEG) frequency in Alzheimer's disease (AD) is well established, but whether EEG changes are able to reflect the severity of AD is uncertain. We attempt to establish quantitative EEG parameters that are suitable for evaluating AD in clinical practice. METHODS: Ninety-five patients with newly diagnosed AD at different stages from four neurologic institutes were enrolled for the study. Standard scalp resting EEG data were collected for quantitative analysis. Global band power ratio and interhemispheric alpha band coherence were calculated. RESULTS:Patients with advanced AD had a greater slow-to-fast wave power ratio. Among several power ratio parameters, global theta and delta to alpha and beta band power ratio showed the best correlation with stages of AD (p < 0.05 between any two patient groups). Patients with advanced AD had decreased coherence in multiple brain regions. The phenomenon was most prominent in the centroparietal region (p < 0.05 between any two patient groups). CONCLUSION: Increased global slow-to-fast power ratio and decreased centroparietal interhemispheric alpha band coherence are strongly correlated with disease progress in ADpatients. These two quantitative EEG parameters may help evaluate ADpatients in daily clinical practice. Global power ratio changes may suggest a shift of dominant frequency, and decreased interhemispheric alpha band coherence may suggest functional disconnection and corpus callosum abnormalities in ADpatients.
Authors: Chinnakkaruppan Adaikkan; Jun Wang; Karim Abdelaal; Steven J Middleton; P Lorenzo Bozzelli; Ian R Wickersham; Thomas J McHugh; Li-Huei Tsai Journal: Neuron Date: 2022-08-19 Impact factor: 18.688
Authors: David López-Sanz; Ricardo Bruña; María Luisa Delgado-Losada; Ramón López-Higes; Alberto Marcos-Dolado; Fernando Maestú; Stefan Walter Journal: Alzheimers Res Ther Date: 2019-06-01 Impact factor: 6.982
Authors: B Wang; Y Liu; L Huang; J Chen; J J Li; R Wang; E Kim; Y Chen; C Justicia; K Sakata; H Chen; A Planas; R S Ostrom; W Li; G Yang; M P McDonald; R Chen; D H Heck; F-F Liao Journal: Mol Psychiatry Date: 2016-07-26 Impact factor: 15.992