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  • Title: [Analytic study on EEG features of aging with/without psychiatric disorders: focussing at the alterations in the EEGs of the healthy, depressive and demented elderlies].
    Author: Saito N.
    Journal: Seishin Shinkeigaku Zasshi; 1995; 97(10):801-24. PubMed ID: 8552725.
    Abstract:
    The EEG alterations attributed to senescence are the complex result of functional as well as organic factors, such as normal physiological aging, pathological process which results in cognitive deterioration, and/or psychological phenomena including depression. The aim of this study is to clarify which factors influence which EEG features and to evaluate the relationship between the clinical and electrophysiological indices. For simplicity, this study focused on the major three factors that are important in dealing with senescence; 1) normal, physiological aging; 2) dementia; 3) depression. A total of 191 subjects participated in this study. The subject groups were classified into 9 groups based on their age and pathology. Two healthy elderly groups (N = 60; between the ages of 60 and 80 years; subclassified according to their social activity), a healthy young volunteers' group (N = 30; between the ages of 20 and 39), a healthy middle-aged volunteers' group (N = 30; between the ages of 40 and 59), four subject groups of dementia of Alzheimer's type [DAT] classified according to the severity of dementia (total number of subjects = 44), depressive elderly subjects (N = 12), and one group of subjects who are older than 80 years (N = 15). The depressive subjects were diagnosed as major depression with their main symptom being psychomotor retardation which resembles the clinical picture of early dementia. The EEGs change with age. This well-approved fact is also confirmed in this study based on ANOVA. Within the same age groups, there were little differences in EEGs regardless of the quality of their social activities. More slow activity, more 20-32Hz fast activity, and less 13.5-20.0Hz beta activity were seen in the socially-inactive group than in the socially-active group (multiple range test based on Tukey's method). The fact that no tendency of increases in slow and fast activities accompanied by a decrease of alpha activity were seen in the socially-active group suggest that having such tendency in their EEG features may be indicative of underlying pathological process that are qualitatively different from normal physiological aging. The moderate grade of those change may not yet cause clinical impairment noticeable as dementia, but appear as less social activity. The EEGs of depressed elderly differed from the socially-inactive elderly as well as the mild dementia particularly in beta frequency bands. There were no significant differences between the socially-inactive elderly and the mild dementia. The tendency of an increase of slow activity and a decrease of alpha activity was seen as the clinical severity of dementia increases. However, these changes reached at the statistically significant level only in the extremely demented subject group. To extract the feature indices of the EEGs, PCA was applied. Five principal components were descriptive of 88% of the data. The EEG features summarized by these components could differentiate the socially-active elderly and the socially-inactive elderly, and the depressed group was distinctively differed from other groups. Interestingly PCA showed the similarity between the socially-inactive elderly and the mild dementia, and the similarity between the middle-aged and the young volunteers. Except for the extreme dementia, subgroups of DAT patients according to the clinical severity did not show distinctive differences in EEG features. The correlation among the EEG derivations was investigated using cluster analysis. The result indicated that the interhemispheric electrophysiological correlation diminishes along with the advancement of the pathological process of the brain. This study indicated that the EEG indices derived from the multivariate analyses are more informative in regard to the relationship among EEG variables as well as these spatial relationship than evaluating the changes in each frequency band alone.
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