Saito N
Department of Neuropsychiatry, Kansai Medical University.
Seishin Shinkeigaku Zasshi. 1995;97(10):801-24.
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.
归因于衰老的脑电图改变是功能以及器质性因素的复杂结果,这些因素包括正常的生理衰老、导致认知衰退的病理过程,和/或包括抑郁在内的心理现象。本研究的目的是阐明哪些因素影响哪些脑电图特征,并评估临床指标与电生理指标之间的关系。为简单起见,本研究聚焦于处理衰老过程中重要的三个主要因素:1)正常的生理衰老;2)痴呆;3)抑郁。共有191名受试者参与了本研究。根据年龄和病理情况,将受试者组分为9组。两个健康老年组(N = 60;年龄在60至80岁之间;根据社交活动情况进一步细分),一个健康青年志愿者组(N = 30;年龄在20至39岁之间),一个健康中年志愿者组(N = 30;年龄在40至59岁之间),四个根据痴呆严重程度分类的阿尔茨海默病型痴呆[DAT]受试者组(受试者总数 = 44),抑郁老年受试者(N = 12),以及一组年龄大于80岁的受试者(N = 15)。抑郁受试者被诊断为重度抑郁症,其主要症状为精神运动迟缓,类似于早期痴呆的临床表现。脑电图随年龄变化。基于方差分析,本研究也证实了这一公认事实。在同一年龄组内,无论社交活动质量如何,脑电图差异不大。与社交活跃组相比,社交不活跃组出现更多的慢波活动、更多的20 - 32Hz快波活动以及更少的13.5 - 20.0Hzβ波活动(基于图基方法的多重范围检验)。社交活跃组未出现慢波和快波活动增加以及α波活动减少的趋势,这一事实表明脑电图特征出现这种趋势可能表明存在与正常生理衰老在性质上不同的潜在病理过程。这些变化的中等程度可能尚未导致如痴呆那样明显的临床损害,但表现为社交活动减少。抑郁老年受试者的脑电图与社交不活跃老年受试者以及轻度痴呆患者的脑电图不同,特别是在β频段。社交不活跃老年受试者与轻度痴呆患者之间无显著差异。随着痴呆临床严重程度的增加,可见慢波活动增加和α波活动减少的趋势。然而,这些变化仅在极度痴呆受试者组达到统计学显著水平。为提取脑电图的特征指标,应用了主成分分析(PCA)。五个主成分描述了88%的数据。由这些成分总结的脑电图特征能够区分社交活跃老年受试者和社交不活跃老年受试者,并且抑郁组与其他组明显不同。有趣的是,主成分分析显示社交不活跃老年受试者与轻度痴呆患者相似,中年志愿者与青年志愿者相似。除了极度痴呆患者外,根据临床严重程度划分的DAT患者亚组在脑电图特征上未显示出明显差异。使用聚类分析研究脑电图导联之间的相关性。结果表明,随着大脑病理过程的进展,半球间电生理相关性降低。本研究表明,与单独评估每个频段的变化相比,多变量分析得出的脑电图指标在脑电图变量之间的关系以及这些空间关系方面提供了更多信息。