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目的:采用事件相关电位技术考察中老年人身体锻炼对数字运算能力老化延缓作用。方法:30位中老年参与者参与本研究,剔除无效数据,剩余有效参与者26人。使用德国Brain Products公司的ERP记录与分析系统记录参与者完成数字运算任务(简单加减运算测验)时的EEG信号。结果:1)行为学上,锻炼组反应时为(2 153.847±589.919)ms,非锻炼组反应时为(3 098.449±773.798)ms;进行独立样本t检验显示,2组别反应时差异可靠,t=-3.500,P<0.01。2)脑电方面,在顶点Pz上,锻炼组P200~300波幅为(3.396±1.913)μV,非锻炼组P200~300波幅为(1.719±0.716)μV;中央点Cz上,锻炼组P200~300波幅为(5.180±2.251)μV,非锻炼组P200~300波幅为(3.517±1.192)μV。对2组别的P200~300波幅进行差异检验,发现2组别的P200~300波幅的差异显著,F(1,24)=7.834,P<0.05,partialη2=0.246,2个电极点上P200~300波幅的差异也可靠,F(1,24)=59.381,P<0.001,partialη2=0.712。电极点和组别之间交互作用不可靠,F(1,24)=0.976,P>0.05。结论:有氧锻炼延缓了数字运算能力的老化速度,体现在大脑机能上是锻炼者较非锻炼者的ERPs(P200~300)波幅更大,能够动员更多的神经元同步兴奋。这提示在数字认知加工的早期阶段,锻炼者与非锻炼者脑内即出现加工的差异,锻炼者的认知加工资源动员程度更高。
OBJECTIVE: To investigate the effect of physical exercise on the aging of digital computing ability of middle-aged and elderly people using event-related potential technique. Methods: Thirty middle-aged and elderly participants participated in this study, excluding invalid data and remaining 26 valid participants. The ERP recording and analysis system at Brain Products, Germany, was used to record the EEG signals of participants completing the numerical calculations (simple addition and subtraction tests). Results: 1) In behavioral training, the response time of exercise group was (2 153.847 ± 589.919) ms and that of non-exercise group was (3 098.449 ± 773.798) ms. Independent sample t-test showed that the difference between 2 groups was reliable, t = -3.500, P <0.01.2) In the electroencephalogram, the amplitude of P200 ~ 300 in training group was (3.396 ± 1.913) μV, P200 ~ 300 in training group was (1.719 ± 0.716) μV; At point Cz, the amplitude of P200 ~ 300 in exercise group was (5.180 ± 2.251) μV, and the amplitude of P200 ~ 300 in non-exercise group was (3.517 ± 1.192) μV. The differences of P200 ~ 300 amplitude between the two groups were significant (P (subscript f) = 7.834, P <0.05, partialη2 = 0.246, P200 ~ The difference of 300 amplitude is also reliable, F (1,24) = 59.381, P <0.001, partialη2 = 0.712. The interaction between electrode points and groups was not reliable, F (1,24) = 0.976, P> 0.05. CONCLUSIONS: Aerobic exercise slowed the rate of aging of digital computing power by reflecting greater amplitude of brain ERPs (P200-300) than exercisers in the brain and mobilizing more neurons to synchronize their excitation. This suggests that in the early stages of digital cognitive processing, there is difference in the process of training in the brains and non-exercisers, and the exercisers’ cognitive processing resources are mobilized to a higher degree.