身体锻炼对中老年人数字运算能力的影响:来自ERP的证据
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- 英文论文题名：Effect of Physical Exercise on Middle-aged and Elder People's Mathematical Computing ability:Evidence from ERP
- 论文作者：高淑青
- 英文论文作者：Gao Shuqing ; Key Lab of Sport Psychological and Physio-logical Regulation ; Tianjin University of Sport
- 年：2015
- 作者机构：天津体育学院竞技运动心理与生理调控重点实验室;
- 论文关键词：身体锻炼 ; 中老年人 ; 数字运算能力 ; ERP
- 英文论文关键词：physical exercise ; middle-aged and elder people's ; mathematical computing ability ; ERP
- 会议召开时间：2015-10-16
- 会议录名称：第十八届全国心理学学术会议摘要集——心理学与社会发展
- 英文会议录名称：Proceedings of the 18th National Academic Congress of Psychology
- 语种：中文
- 分类号：G804.8
- 学会代码：ZGXG
- 会议名称：第十八届全国心理学学术会议
- 会议地点：中国天津
- 主办单位：中国心理学会
- 学会名称：中国心理学会
- 页数：2
- 文件大小：788k
- 原文格式：D
- 会议级别：全国
摘要
目的:采用ERP技术考察身体锻炼对中老年人数字运算能力的影响,从脑功能层面获得身体锻炼延缓数字运算能力老化的证据。方法:天津市天塔街社区的中老年参与者30人,剔除脑电伪迹过多和测试正确率低于95%的参与者4人,剩余有效参与者26人。锻炼者13人,平均年龄为60.08±2.22岁,非锻炼者13人,平均年龄为60.38±2.84岁。参与者均为右利手,均无神经及精神疾病史,身体健康,受教育程度均为高中以上。采用【锻炼阶段诊断量表】获得参与者锻炼情况。使用德国Brain Products公司的ERP记录与分析系统,按国际10/20系统扩展的64导电极帽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2153.847±589.919ms,非锻炼组反应时为3098.449±773.798ms,进行独立样本t检验,结果显示,两组别反应时差异可靠,t=-3.500,p<.01,锻炼者运算速度快于非锻炼者。(2)脑电方面,根据以往研究,本研究选取脑部顶点Pz和中央点Cz所诱发出的P200-300指标进行分析。结果显示,在顶点Pz上,锻炼组P200-300波幅为3.396±1.913mv,非锻炼组P200-300波幅为1.7187±0.716mv;中央点Cz上,锻炼组P200-300波幅为5.180±2.251mv,非锻炼组P200-300波幅为3.5167±1.192mv。对两组参与者的P200-300波幅进行混合设计的重复测量方差分析,结果显示,两组参与者的P200-300波幅的差异可靠,F(1,24)=7.834,p<.05,partial η~2=.246,两个电极点上P200-300波幅的差异也可靠,F(1,24)=59.381,p<.001,partialη~2=.712。电极点和组别之间交互作用不可靠,F(1,24)=0.976,p>.05。结论:锻炼者较非锻炼者在完成数字运算任务时反应更快,P200-300波幅更大,能够动员更多的神经元同步兴奋。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。身体锻炼可以改善中老年人的脑功能,在认知加工时,认知加工资源动员程度更高。
Objective: ERP technical was used to test the effect of physical exercise on middle-aged and elder people's mathematical computing ability, which can reveal the brain mechanism of physical exercise delaying Aging of mathematical computing ability. Method: Thirty middle-aged and elder people from Tianjin Tower Street Community were invited to participate in this study. Four people were eliminated because of EEG artifacts and the accuracy of less than 95%. The average age of exercise group(n=13) was 60.08 ± 2.22, and non-exercisers(n=13) was 60.38 ± 2.84. All participants were right handedness, have no history of nervous and mental disease, in good condition, and have high school degree or above. ERP record and analysis system were from Germany Brain Products company, according to the international 10/20 system of 64 participants completed conducting electrode Cap record the EEG signal of mathematical computing tasks(simple addition and subtraction tests). Results:(1) There was significant differences between exercise group and non-exercise group on reaction time(2153.847 ± 589.919 ms vs. 3098.449 ± 773.798ms; t =-3.500,p <. 01).(2) EEG results showed that exercise group's amplitude of P200-300 in brain vertex Pz was 3.396 ± 1.913, and 1.7187 ± 0.716 in non-exercise group, as well as exercise group's amplitude of P200-300 in central point of Cz was 5.180 ±2.251, and 3.5167 ±1.192 in non-exercise group; Repeated measures ANOVA showed that There were significant differences between exercise group and non-exercise group on amplitude of P200-300[f(1, 24) = 7.834,p <. 05,partial η 2 =. 246], also significant differences between two electrodes' P200-300 amplitude [f(1, 24) = 59.381,p <. 001,partial η 2 = 712]. But, there was no significant interaction between electrodes and groups[f(1, 24) = 0.976,p >. 05]. Conclusion: Exercise group, which can mobilize more excited neurons synchronization, have faster speed and stronger amplitude of P200-300 than non-exercise group when complete number compute task. In the early stages of digital processing, there maybe have differences in the brain between exercisers and non-exercisers. Those results suggested that physical exercise can improve brain function in the elderly, which can promote mobilization of cognitive processing resource at the moment of cognitive processing.
Objective: ERP technical was used to test the effect of physical exercise on middle-aged and elder people's mathematical computing ability, which can reveal the brain mechanism of physical exercise delaying Aging of mathematical computing ability. Method: Thirty middle-aged and elder people from Tianjin Tower Street Community were invited to participate in this study. Four people were eliminated because of EEG artifacts and the accuracy of less than 95%. The average age of exercise group(n=13) was 60.08 ± 2.22, and non-exercisers(n=13) was 60.38 ± 2.84. All participants were right handedness, have no history of nervous and mental disease, in good condition, and have high school degree or above. ERP record and analysis system were from Germany Brain Products company, according to the international 10/20 system of 64 participants completed conducting electrode Cap record the EEG signal of mathematical computing tasks(simple addition and subtraction tests). Results:(1) There was significant differences between exercise group and non-exercise group on reaction time(2153.847 ± 589.919 ms vs. 3098.449 ± 773.798ms; t =-3.500,p <. 01).(2) EEG results showed that exercise group's amplitude of P200-300 in brain vertex Pz was 3.396 ± 1.913, and 1.7187 ± 0.716 in non-exercise group, as well as exercise group's amplitude of P200-300 in central point of Cz was 5.180 ±2.251, and 3.5167 ±1.192 in non-exercise group; Repeated measures ANOVA showed that There were significant differences between exercise group and non-exercise group on amplitude of P200-300[f(1, 24) = 7.834,p <. 05,partial η 2 =. 246], also significant differences between two electrodes' P200-300 amplitude [f(1, 24) = 59.381,p <. 001,partial η 2 = 712]. But, there was no significant interaction between electrodes and groups[f(1, 24) = 0.976,p >. 05]. Conclusion: Exercise group, which can mobilize more excited neurons synchronization, have faster speed and stronger amplitude of P200-300 than non-exercise group when complete number compute task. In the early stages of digital processing, there maybe have differences in the brain between exercisers and non-exercisers. Those results suggested that physical exercise can improve brain function in the elderly, which can promote mobilization of cognitive processing resource at the moment of cognitive processing.
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