不同体力活动水平大学生的生物运动工作记忆加工特征研究
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摘要
以生物运动光点视频为刺激方式,探讨不同体力活动水平大学生生物运动工作记忆加工的差异性特征。方法:通过64导脑电设备记录18名高体力活动水平大学生(高体力活动组)和19名低体力活动水平大学生(低体力活动组)在生物运动工作记忆任务中的脑电(EEG)变化情况,在这一任务中的正确率和反应时作为行为评价指标,以alpha频段能量、theta频段能量和theta频段能量/alpha频段能量作为脑电指标。结果:高体力活动组的行为指标优于低体力活动组,正确率组间差异显著。高体力活动组在alpha频段能量上显著高于低体力活动组,并且在额区和中央区满足高记忆负荷下的alpha频段能量大于低记忆负荷。theta频段能量和theta频段能量/alpha频段能量均存在组别与脑区的交互作用,且2组被试均满足大脑额区>大脑中央区>大脑顶区>大脑枕区这一规律。结论:在进行生物运动工作记忆加工过程中,高体力活动水平的大学生有着更高的大脑唤醒水平和更好的行为表现。
Objective: Point light displays were used as the stimulating approach to explore the differences between different levels of physical activity in biological motion working memory of university students.Method: The electroencephalogram(EEG) data in biological motion working memory task were recorded in19 participants with low physical activity and 18 participants high physical activity. Behavioral data of the participants were recorded including correct rate and response time were used as evaluation indicators of cognitive behavior. In terms of EEG, alpha(8-13 Hz), theta(4-7 Hz) and theta/alpha were used as indicators for EEG changes. Results: The behavior of the high physical activity group was better than that of the low physical activity group, and there was a significant difference in the correct rate between the groups. The alpha energy value of the high physical activity group was significantly higher than that of the low physical activity group, and the alpha energy value under the high memory load condition was significantly higher than that of the low memory load condition in the frontal and central regions. Both theta energy value and theta/alpha ratio had interaction between groups and brain regions, and both groups met the rule of frontal area > central area > parietal area > occipital area. Conclusion: Individuals in the high physical activity group have greater levels of brain activation and better cognitive behavior performance than those in the low physical activity group.
Objective: Point light displays were used as the stimulating approach to explore the differences between different levels of physical activity in biological motion working memory of university students.Method: The electroencephalogram(EEG) data in biological motion working memory task were recorded in19 participants with low physical activity and 18 participants high physical activity. Behavioral data of the participants were recorded including correct rate and response time were used as evaluation indicators of cognitive behavior. In terms of EEG, alpha(8-13 Hz), theta(4-7 Hz) and theta/alpha were used as indicators for EEG changes. Results: The behavior of the high physical activity group was better than that of the low physical activity group, and there was a significant difference in the correct rate between the groups. The alpha energy value of the high physical activity group was significantly higher than that of the low physical activity group, and the alpha energy value under the high memory load condition was significantly higher than that of the low memory load condition in the frontal and central regions. Both theta energy value and theta/alpha ratio had interaction between groups and brain regions, and both groups met the rule of frontal area > central area > parietal area > occipital area. Conclusion: Individuals in the high physical activity group have greater levels of brain activation and better cognitive behavior performance than those in the low physical activity group.
引文
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[20] KYLE J, LO L, RODOLPHE G, et al. Changes in mental workload and motor performance throughout multiple practice sessions under various levels of task difficulty[J]. Journal of Neuroscience, 2018, 19(17):2.
[21]王正伦,孙飙,戴剑松.大学生体质与体力活动的相关分析和研究[J].武汉体育学院学报,2006,40(12):67.
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[23]VANRIE J, VERFAILLIE K. Perception of biological motion:a stimulus set of human point-light actions[J]. Behavior Research Methods Instruments&Computers, 2004, 36(4):625.
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[25] XIQIAN L, JIAN H, YUJI Y, et al. Holding biological motion in working memory:an fmri study[J].Cognitive Neuroscience Journal, 2016,10(1):198.
[26] DONNELLY J E, HILLMAN C H, CASTELLI D, et al. Physical activity, fitness, cognitive function, and academic achievement in children:a systematic review[J]. Med Sci Sports Exerc, 2016, 48(6):1197.
[27] CHANG Y K, HUANG C J, CHEN K F, et al. Physical activity and working memory in healthy older adults:an erp study[J]. Psychophysiology, 2013, 50(11):1174.
[28] PETRIDES M, MILNER B. Deficits on subject-ordered tasks after frontal-and temporal-lobe lesions in man[J]. Neuropsychologia,1982, 20(3):249.
[29]OWEN A M, DOWNES J J, SAHAKIAN B J, et al. Planning and spatial working memory following frontal lobe lesions in man[J]. Neuropsychologia, 1990, 28(10):1021.
[30]HOLM A, LUKANDER K, KORPELA J, et al. Estimating brain load from the EEG[J]. Scientific World Journal, 2009(9):639.
[31]GENTILI R J, RIETSCHEL J C, JAQUESS K J, et al. Brain biomarkers based assessment of cognitive workload in pilots under various task demands[C]//Chicago:Engineering in Medicine&Biology Society, 36th Annual International Conference of the IEEE, 2014.
[2]WOOD J N. A core knowledge architecture of visual working memory:correction to wood(2011)[J]. J Exp Psychol Hum Percept Perform,2011, 37(2):357.
[3] PADILLA C, PéREZ L, ANDRéS P. Chronic exercise keeps working memory and inhibitory capacities fit[J]. Frontiers in Behavioral Neuroscience, 2014, 8(8):49.
[4] CONN V S, HAFDAHL A R, MEHR D R. Interventions to increase physical activity among healthy adults:meta-analysis of outcomes[J].American Journal of Public Health, 2011, 101(4):751.
[5]BADDELEY A. Working memory[J]. Psychology of Learning&Motivation, 1992, 255(5044):556.
[6]郭玮.不同运动锻炼方式老年人的视空间工作记忆的特征[D].上海:上海体育学院,2017.
[7]徐畅,周成林,马阳.生活方式对延缓老年人认知功能衰退的研究[J].体育科学,2014,34(5):35.
[8]文椈.学龄前儿童睡眠及体力活动对认知能力的交互作用[D].上海:上海体育学院,2017.
[9]DING X, ZHAO Y, WU F, et al. Binding biological motion and visual features in working memory[J]. J Exp Psychol Hum Percept Perform,2015, 41(3):850.
[10] PAVLOVA M A. Biological motion processing as a hallmark of social cognition[J]. Cerebral Cortex, 2012, 22(5):981.
[11]HIRIS E, KREBECK A, EDMONDS J, et al. What learning to see arbitrary motion tells us about biological motion perception[J]. Journal of Experimental Psychology Human Perception&Performan, 2005, 31(5):1096.
[12] SAUSENG P, GRIESMAYR B, FREUNBERGER R, et al. Control mechanisms in working memory:a possible function of eeg theta oscillations[J]. Neurosci Biobehav Rev, 2010, 34(7):1015.
[13]NASSEF A. On-line monitoring and adaptive control of psychophysiological markers relating to humans under stress[D]. Sheffield:University of Sheffield, 2009.
[14] GEVINS A, SMITH M E, LE J, et al. High resolution evoked potential imaging of the cortical dynamics of human working memory[J]. Electroencephalography&clinical neurophysiology, 1996, 98(4):327.
[15] NEYMOTIN S A, JACOBS K M, FENTON A A, et al. Synaptic information transfer in computer models of neocortical columns[J]. Journal of Computational Neuroscience, 2011, 30(1):69.
[16]GOLDMAN R I, STERN J M, JR E J, et al. Simultaneous eeg and fmri of the alpha rhythm[J]. Neuroreport, 2002, 13(18):2487.
[17] SHAGASS C. Electrophysiological studies of psychiatric problems[J]. Rev Can Biol, 1972(31):77.
[18]KLIMESCH W. Eeg alpha and theta oscillations reflect cognitive and memory performance:a review and analysis[J]. Brain Res Brain Res Rev, 1999, 29(2-3):169.
[19]HOCKEY G R, NICKEL P, ROBERTS A C, et al. Sensitivity of candidate markers of psychophysiological strain to cyclical changes in manual control load during simulated process control[J].Applied Ergonomics, 2009, 40(6):1011.
[20] KYLE J, LO L, RODOLPHE G, et al. Changes in mental workload and motor performance throughout multiple practice sessions under various levels of task difficulty[J]. Journal of Neuroscience, 2018, 19(17):2.
[21]王正伦,孙飙,戴剑松.大学生体质与体力活动的相关分析和研究[J].武汉体育学院学报,2006,40(12):67.
[22]JOHANSSON G. Visual perception of biological motion and a model for its analysis[J]. Perception&Psychophysics, 1973, 14(2):201.
[23]VANRIE J, VERFAILLIE K. Perception of biological motion:a stimulus set of human point-light actions[J]. Behavior Research Methods Instruments&Computers, 2004, 36(4):625.
[24]CURBY K M, GAUTHIER I. A visual short-term memory advantage for faces[J]. Psychonomic Bulletin&Review, 2007, 74(4):620.
[25] XIQIAN L, JIAN H, YUJI Y, et al. Holding biological motion in working memory:an fmri study[J].Cognitive Neuroscience Journal, 2016,10(1):198.
[26] DONNELLY J E, HILLMAN C H, CASTELLI D, et al. Physical activity, fitness, cognitive function, and academic achievement in children:a systematic review[J]. Med Sci Sports Exerc, 2016, 48(6):1197.
[27] CHANG Y K, HUANG C J, CHEN K F, et al. Physical activity and working memory in healthy older adults:an erp study[J]. Psychophysiology, 2013, 50(11):1174.
[28] PETRIDES M, MILNER B. Deficits on subject-ordered tasks after frontal-and temporal-lobe lesions in man[J]. Neuropsychologia,1982, 20(3):249.
[29]OWEN A M, DOWNES J J, SAHAKIAN B J, et al. Planning and spatial working memory following frontal lobe lesions in man[J]. Neuropsychologia, 1990, 28(10):1021.
[30]HOLM A, LUKANDER K, KORPELA J, et al. Estimating brain load from the EEG[J]. Scientific World Journal, 2009(9):639.
[31]GENTILI R J, RIETSCHEL J C, JAQUESS K J, et al. Brain biomarkers based assessment of cognitive workload in pilots under various task demands[C]//Chicago:Engineering in Medicine&Biology Society, 36th Annual International Conference of the IEEE, 2014.