Literature DB >> 10026377

Differential diagnosis of aging, dementia of the Alzheimer type and depression with EEG-segmentation.

R Ihl1, J Brinkmeyer.   

Abstract

EEG segmentation can be used to measure altered brain function in aging and diseases of the brain. The parameter 'number of different segments' makes clear how many different potential fields are involved in brain activity during a given period of time. It should represent effects of aging and disease. To prove this assumption, 11 young and 10 aged controls, 12 patients with mild dementia of the Alzheimer type (DAT), 10 young and 12 aged patients with endogenous depression were included in the study. The number of different segments in the beta frequency band between 16 and 19.75 Hz was measured according to the theory of Lehmann et al. [Clinical Neurophysiology 1987;67:271-288], and the segments were classified by their location on the scalp. The Mann-Whitney U test was used for statistical comparison. Aged controls had more different segments than young controls (n = 21, U = 14, p < 0.0038). Patients with DAT had less different segments than healthy aged controls (n = 22, U = 18.5, p < 0.0061). Aged patients with endogenous depression had more different segments than patients with mild DAT (n = 24, U = 32, p < 0.021). The reduction of the number of different segments in DAT compared to controls and patients suffering from depression may be helpful for differential diagnosis. The higher number of different segments in aged versus young controls could be interpreted as a sign of increased complexity in the aged brain.

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Year:  1999        PMID: 10026377     DOI: 10.1159/000017103

Source DB:  PubMed          Journal:  Dement Geriatr Cogn Disord        ISSN: 1420-8008            Impact factor:   2.959


  3 in total

1.  EEG microstate temporal Dynamics Predict depressive symptoms in College Students.

Authors:  Xiaorong Qin; Jingyi Xiong; Ruifang Cui; Guimin Zou; Changquan Long; Xu Lei
Journal:  Brain Topogr       Date:  2022-07-05       Impact factor: 4.275

2.  The pro-inflammatory factors contribute to the EEG microstate abnormalities in patients with major depressive disorder.

Authors:  Ya-Nan Zhao; Jia-Kai He; Yu Wang; Shao-Yuan Li; Bao-Hui Jia; Shuai Zhang; Chun-Lei Guo; Jin-Ling Zhang; Guo-Lei Zhang; Bin Hu; Ji-Liang Fang; Pei-Jing Rong
Journal:  Brain Behav Immun Health       Date:  2022-10-04

3.  Regional Beta Index of Electroencephalography May Differentiate Alzheimer's Disease from Depression.

Authors:  Kanghee Lee; Ji Won Han; Ki Woong Kim
Journal:  Psychiatry Investig       Date:  2017-09-11       Impact factor: 2.505

  3 in total

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