休息和心算状态下正常脑老化过程的复杂性分析
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摘要
研究了休息和心算状态下正常脑老化过程的复杂性变化情况。共招募15名健康年轻人和13名健康老年人,采用多尺度样本熵(MSE)方法对休息和心算状态下的脑电图(EEG)记录并进行复杂性分析。研究结果表明,相同状态下,老年人组休息状态的MSE值在全脑大部分范围高于年轻人组,而老年人组心算状态的MSE值在全脑范围低于年轻人组,但差异均不具有统计学意义。不同状态下,老年人组和年轻人组心算状态的MSE值在全脑大部分范围均较休息状态降低,其中老年人组的差异具有统计学意义,几乎涵盖全脑,其中前额叶区域最为明显,但年轻人组的差异不具有统计学意义。因此,正常脑老化对脑功能复杂性的改变并不明显;相比于休息状态,执行心算任务更能反映老化对脑功能复杂性的影响,且前额叶与脑老化及记忆密切相关。
The purpose of the research is to investigate the complexity alterations of normal brain aging on the resting-state and metal calculation-state.15 healthy young people and 13 healthy old people were recruited, and their EEG recordings on the resting-state and mental calculation-state were analyzed using multiscale sample entropy(MSE) methods. The results showed that on the same state, the resting-state MSE values for old people were higher than young people in most of the whole brain, but the mental calculation-state MSE values for old people were lower than young people in most of the whole brain. However, the differences between old people and young people were not statistically significant. On different states, the mental calculation-state MSE values for young people and old people were lower than the resting-state in most of the whole brain. The differences were statistically significant for old people almost covering the whole brain particularly in the prefrontal lobe regions, but did not existed for young people. Therefore, it can be concluded that the alterations in brain functional complexity of normal brain aging were not obvious, but comparing with the resting-state, the mental calculation-state could better reflect the effect of aging on the complexity of brain function and the prefrontal lobe might be the regions of normal brain aging and memory function.
The purpose of the research is to investigate the complexity alterations of normal brain aging on the resting-state and metal calculation-state.15 healthy young people and 13 healthy old people were recruited, and their EEG recordings on the resting-state and mental calculation-state were analyzed using multiscale sample entropy(MSE) methods. The results showed that on the same state, the resting-state MSE values for old people were higher than young people in most of the whole brain, but the mental calculation-state MSE values for old people were lower than young people in most of the whole brain. However, the differences between old people and young people were not statistically significant. On different states, the mental calculation-state MSE values for young people and old people were lower than the resting-state in most of the whole brain. The differences were statistically significant for old people almost covering the whole brain particularly in the prefrontal lobe regions, but did not existed for young people. Therefore, it can be concluded that the alterations in brain functional complexity of normal brain aging were not obvious, but comparing with the resting-state, the mental calculation-state could better reflect the effect of aging on the complexity of brain function and the prefrontal lobe might be the regions of normal brain aging and memory function.
引文
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[27] 刘凤英, 姚志刚. 错误记忆年老化的认知与神经机制[J]. 应用心理学, 2018, 24(1): 41-51.
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[2] PRINCE M, WIMO A, GUERCHET M, et al. World Alzheimer report 2015: the global impact of dementia[R].An Analysis of Prevalence, Incidence, Cost and Trends, 2015.
[3] QUERFURTH H W, LAFERLA F M. Alzheimer′s disease: mechanism of disease[J].The New England Journal of Medicine, 2010, 362(4): 329-344.
[4] 张奇, 林崇德, 赵冬梅,等. 小学生加法口算速度和广度的发展研究[J]. 心理发展与教育, 2002, 18(1): 16-2l.
[5] BADDELEY A D. Working memory[M].New York: Clarendon Press and Oxford University Press, 1986.
[6] 刘昌. 心算加工的认知神经科学研究[J]. 心理科学, 2006, 29(1):30-33.
[7] RUESCH J. Intellectual impairment in head injuries[J].Nervous & Mental Disease, 1944, 100(5): 480-496.
[8] SALIASI E, GEERLIGS L, LORIST M M, et al. The relationship between P3 amplitude and working memory performance differs in young and older adults[J].Public Library of Science One, 2013, 8(5): 63701.
[9] DONG S S, REDER L M, YAO Y, et al. Individual differences in working memory capacity are reflected in different ERP and EEG patterns to task difficulty[J].Brain Research, 2015, 1616: 146-156.
[10] PADGAONKAR N A, ZANTO T P, BOLLINGER J, et al. Predictive cues and age-related declines in working memory performance[J].Neurobiology of Aging, 2017, 49: 31-39.
[11] PINCUS S M. Approximate entropy as a measure of system complexity[J].Proceedings of National Academy of Sciences, 1991, 88(6): 2297-2301.
[12] RICHMAN J S, MOORMAN J R. Physiological time-series analysis using approximate entropy and sample entropy[J].Physiology-Heart and Circulatory Physiology, 2000, 278(6): 2039-2049.
[13] ROSSO O A, MARTIN M T, PLASTINO A. Brain electrical activity analysis using wavelet-based informational tools[J].Physica A, 2002, 313(3/4): 587-608.
[14] GOLDBERGER A L, PENG C K, LIPSITZ L A. What is physiologic complexity and how does it change with aging and disease?[J].Neurobiology of Aging, 2002, 23(1): 6-23.
[15] COSTA M, GOLDBERGER A L, PENG C K. Reply: comment on multiscale entropy analysis of complex physiologic time series[J].Physical Review Letters, 2003, 91: 119802.
[16] COSTA M, GOLDBERGER A L, PENG C K. Multiscale entropy analysis of biological signals[J].Physical Review Letters, 2005, 71(2): 199-201.
[17] COSTA M, GOLDBERGER A L, PENG C K. Multiscale entropy analysis of complex physiologic time series[J].Physical Review Letters, 2002, 89(6): 068102.
[18] FOLSTEIN M F, FOLSTEIN S E, MCHUGH P R.Mini-mental state: a practical method for grading the cognitive state of patients for the clinician[J].Psychiatric Research, 1975, 12(3): 189-198.
[19] 王新沛, 杨静, 李远洋, 等. 基于样本熵快速算法的心音信号动力学分析[J]. 振动与冲击, 2010, 29(11): 115-118.
[20] 王瑶, 黄国睿, 谢康宁. 脑电多尺度熵用于睡意检测的初步研究[J]. 医疗卫生装备, 2016, 37(12): 1-6.
[21] 刘雪峰, 马州生, 赵艳阳, 等. 基于MSE-PCA的脑电睡眠分期方法研究[J]. 电子技术应用, 2017, 43(9): 22-24.
[22] YANG A C, WANG S J, LAI K L, et al. Cognitive and neuropsychiatric correlates of EEG dynamic complexity in patients with Alzheimer′s disease[J].Progress in Neuropsychopharmacology & Biological psychiatry, 2013, 47(1): 52-61.
[23] BIORK M H, STOVNER L J, ENGSTROM M, et al. Interictal quantitative EEG in migraine: a blinded controlled study[J].Headache Pain, 2009, 10: 331-339.
[24] NORRIS P R, STEIN P K, MORRIS J A. Reduced heart rate multiscale entropy predicts death in critical illness: a study of physiologic complexity in 285 trauma patients[J].Critical Care, 2008, 23(3): 399-405.
[25] YANG A C, TSAI S J, YANG C H, et al. Reduced physiologic complexity is associated with poor sleep in patients with major depression and primary insomnia[J].Affective Disorders, 2011, 131(1/2/3): 179-185.
[26] 史洁, 王英, 谷田正弘, 等. 额极功能在工作记忆中的年龄差异[J].中国老年学, 2014, 20: 5637-5639.
[27] 刘凤英, 姚志刚. 错误记忆年老化的认知与神经机制[J]. 应用心理学, 2018, 24(1): 41-51.
[28] 苏玉盛, 马云川, 王红艳, 等. 正常脑老化进程中脑局部葡萄糖代谢减低的规律[J].CT 理论与应用研究, 2009, 18(4): 75-83.
[29] CHAWLUK J B, ALAVI A, DANN R, et al. Positron emission tomography in aging and dementia: effect of cerebral atrophy[J].Investigative Radiology, 1988, 23(11): 879.