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21天禁食下成人记忆与注意功能变化的脑电特征

殷瑛 董乐 周前祥 柳忠起

殷瑛,董乐,周前祥,等. 21天禁食下成人记忆与注意功能变化的脑电特征[J]. 北京航空航天大学学报,2025,51(12):4207-4215 doi: 10.13700/j.bh.1001-5965.2023.0681
引用本文: 殷瑛,董乐,周前祥,等. 21天禁食下成人记忆与注意功能变化的脑电特征[J]. 北京航空航天大学学报,2025,51(12):4207-4215 doi: 10.13700/j.bh.1001-5965.2023.0681
YIN Y,DONG L,ZHOU Q X,et al. EEG characteristics of changes in adult memory and attention function under 21 days fasting[J]. Journal of Beijing University of Aeronautics and Astronautics,2025,51(12):4207-4215 (in Chinese) doi: 10.13700/j.bh.1001-5965.2023.0681
Citation: YIN Y,DONG L,ZHOU Q X,et al. EEG characteristics of changes in adult memory and attention function under 21 days fasting[J]. Journal of Beijing University of Aeronautics and Astronautics,2025,51(12):4207-4215 (in Chinese) doi: 10.13700/j.bh.1001-5965.2023.0681

21天禁食下成人记忆与注意功能变化的脑电特征

doi: 10.13700/j.bh.1001-5965.2023.0681
详细信息
    通讯作者:

    E-mail:zqxg@buaa.edu.cn

  • 中图分类号: R318

EEG characteristics of changes in adult memory and attention function under 21 days fasting

More Information
  • 摘要:

    航天救援任务中,被救援人员可能出现食物短缺的现象,因此,研究健康成年人在21天完全禁食状态下执行短时记忆和注意任务时行为绩效和脑电(EEG)信号变化的规律,对确定救援任务十分重要。招募了13名志愿者,全过程参与某实验舱内分为4个实验阶段的21天完全禁食实验,期间采集志愿者完成Two-back范式短时记忆任务的绩效数据和静息态EEG数据;通过功率谱分析得到EEG信号中各节律成分的特征,评估志愿者记忆和注意力的变化。结果表明:长时间禁食过程中,任务反应时显著延长(P<0.05),正确率变化不显著,即志愿者的反应速度、注意力集中程度逐渐减弱,在第16天左右受影响最显著;禁食过程中,δ波活动增加,α波活动下降,(δ+θ)/(α+β)、θ/α比值增大,变化均出现在禁食第10~16天期间,并在恢复期回归正常。基于EEG和绩效数据,认为在21天的禁食状态下,δ波、α波、(δ+θ)/(α+β)、θ/α等指标会发生显著变化,根据各节律成分的特性,这些指标反映了禁食状态下注意力的分散和工作记忆能力的下降,志愿者的基本认知功能受到影响,主要变化出现在禁食第10~16天。研究结果可作为长时间禁食时人的认知能力变化评估的支撑数据,也为未来航天及其他领域进一步探索禁食的作用机制提供参考。

     

  • 图 1  Two-back实验范式

    Figure 1.  Two-back experimental paradigm

    图 2  测试时间安排

    Figure 2.  Test schedule

    图 3  实验流程

    Figure 3.  Experimental process

    图 4  实验期间不同脑区节律波相对功率

    Figure 4.  Relative power of rhythmic waves in different brain regions during the experiment

    图 5  实验期间不同脑区节律波相对功率比值

    Figure 5.  Relative power ratio of rhythmic waves in different brain regions during the experiment

    表  1  10-20电极导联系统电极名称

    Table  1.   10-20 electrode lead system electrode names

    脑区英文缩写电极名称
    额叶FF3、Fz、F4
    中央叶CC3、Cz、C4
    顶叶PP3、Pz、P4
    枕叶OO1、Oz、O2
    颞叶TT7、T8
    下载: 导出CSV

    表  2  不同时间段下Two-back平均正确率和反应时结果

    Table  2.   Two-back average accuracy and reaction time results at different time periods

    时间段 平均正确率/% 反应时/ms
    BL 88.74(24.03) 318.99(39.8)
    CF4 88.27(13.16) 346.32(55.65)
    CF10 86.18(21.28) 361.01*(24.52)
    CF16 83.85(13.81) 391.81*(58.17)
    CF21 87.98(11.67) 381.87*(41.15)
    CR5 89.51(10.39) 343.72(64.02)
    R4 91.82(13.49) 320.37(69.07)
     注:“*”表示P<0.05;括号中数值表示标准差。
    下载: 导出CSV

    表  3  脑电节律波相对功率配对t检验结果

    Table  3.   Paired t-test results of relative power of EEG rhythm waves

    EEG参数 实验条件 t检验结果
    额叶 中央叶 顶叶 枕叶 颞叶
    δ BLvsCF4 0.065 0.428 0.732 0.943 0.942
    BLvsCF10 0.288 0.409 0.407 0.821 0.915
    BLvsCF16 0.017* 0.041* 0.158 0.633 0.366
    BLvsCF21 0.080 0.196 0.242 0.558 0.722
    BLvsCR5 0.013* 0.036* 0.113 0.690 0.598
    BLvsR4 0.408 0.698 0.593 0.812 0.638
    θ BLvsCF4 0.178 0.072 0.037* 0.009** 0.093
    BLvsCF10 0.943 0.453 0.637 0.645 0.671
    BLvsCF16 0.980 0.397 0.239 0.258 0.543
    BLvsCF21 0.386 0.775 0.719 0.603 0.223
    BLvsCR5 0.385 0.766 0.506 0.509 0.202
    BLvsR4 0.324 0.897 0.491 0.287 0.074
    α BLvsCF4 0.203 0.476 0.531 0.374 0.788
    BLvsCF10 0.140 0.103 0.103 0.709 0.212
    BLvsCF16 0.014* 0.010* 0.015* 0.067 0.009**
    BLvsCF21 0.141 0.087 0.279 0.901 0.194
    BLvsCR5 0.003** 0.001** <0.001** 0.010* 0.005**
    BLvsR4 0.307 0.411 0.409 0.985 0.347
    β BLvsCF4 0.142 0.074 0.112 0.121 0.214
    BLvsCF10 0.551 0.619 0.436 0.611 0.181
    BLvsCF16 0.068 0.049* 0.021* 0.206 0.033*
    BLvsCF21 0.866 0.525 0.966 0.461 0.104
    BLvsCR5 0.031* 0.081 0.005** 0.035* 0.034*
    BLvsR4 0.176 0.275 0.267 0.487 0.139
     注:“*”表示P<0.05;“**”表示P<0.01。
    下载: 导出CSV

    表  4  脑电节律波相对功率比值配对t检验结果

    Table  4.   Paired t-test results of relative power ratio of EEG rhythm waves

    EEG参数 实验条件 t检验结果
    额叶 中央叶 顶叶 枕叶 颞叶
    (δ+θ)/(α+β) BLvsCF4 0.035* 0.099 0.060 0.331 0.251
    BLvsCF10 0.274 0.235 0.267 0.811 0.876
    BLvsCF16 0.063 0.035* 0.067 0.619 0.244
    BLvsCF21 0.201 0.147 0.185 0.383 0.756
    BLvsCR5 0.007** 0.009** 0.048* 0.635 0.699
    BLvsR4 0.683 0.374 0.146 0.451 0.474
    θ/α BLvsCF4 0.066 0.023* 0.012* 0.072 0.064
    BLvsCF10 0.335 0.027* 0.037* 0.395 0.112
    BLvsCF16 0.060 0.023* 0.019* 0.227 0.323
    BLvsCF21 0.592 0.119 0.049* 0.358 0.979
    BLvsCR5 0.012* 0.013* 0.004** 0.091 0.085
    BLvsR4 0.722 0.083 0.066 0.200 0.343
     注:“*”表示P<0.05;“**”表示P<0.01。
    下载: 导出CSV
  • [1] POLICH J, CRIADO J R. Neuropsychology and neuropharmacology of P3a and P3b[J]. International Journal of Psychophysiology, 2006, 60(2): 172-185. doi: 10.1016/j.ijpsycho.2005.12.012
    [2] POLICH J. Updating P300: an integrative theory of P3a and P3b[J]. Clinical Neurophysiology, 2007, 118(10): 2128-2148. doi: 10.1016/j.clinph.2007.04.019
    [3] 张明, 张阳. 工作记忆与选择性注意的交互关系[J]. 心理科学进展, 2007, 15(1): 8-15.

    ZHANG M, ZHANG Y. The relationship between working memory and selective attention[J]. Advances in Psychological Science, 2007, 15(1): 8-15(in Chinese).
    [4] AWH E, JONIDES J. Overlapping mechanisms of attention and spatial working memory[J]. Trends in Cognitive Sciences, 2001, 5(3): 119-126. doi: 10.1016/S1364-6613(00)01593-X
    [5] SOLIANIK R, SUJETA A, TERENTJEVIENĖ A, et al. Effect of 48 h fasting on autonomic function, brain activity, cognition, and mood in amateur weight lifters[J]. BioMed Research International, 2016, 2016: 1503956.
    [6] SOLIANIK R, SUJETA A. Two-day fasting evokes stress, but does not affect mood, brain activity, cognitive, psychomotor, and motor performance in overweight women[J]. Behavioural Brain Research, 2018, 338: 166-172. doi: 10.1016/j.bbr.2017.10.028
    [7] YANG C, MA Q Y, ZHANG H Y, et al. Ten days of complete fasting affected subjective sensations but not cognitive abilities in healthy adults[J]. European Journal of Nutrition, 2021, 60(5): 2747-2758. doi: 10.1007/s00394-020-02450-7
    [8] JAMES D, SEARS D, LARKEY L, et al. Prolonged nightly fasting among older adults: a pilot study exploring changes in cognitive function[J]. Innovation in Aging, 2022, 6(Supplement_1): 823.
    [9] ENRIQUEZ-GEPPERT S, HUSTER R J, HERRMANN C S. EEG-neurofeedback as a tool to modulate cognition and behavior: a review tutorial[J]. Frontiers in Human Neuroscience, 2017, 11: 51. doi: 10.3389/fncom.2017.00051
    [10] DERAMBURE P, LABIDI J, BOURRIEZ J L, et al. O-40 EEGmine: EEG as a prognosis tool of cognitive decline in routine clinical practice[J]. Clinical Neurophysiology, 2019, 130(7): e34.
    [11] WESTWOOD S J, BOZHILOVA N, CRIAUD M, et al. The effect of transcranial direct current stimulation (tDCS) combined with cognitive training on EEG spectral power in adolescent boys with ADHD: a double-blind, randomized, sham-controlled trial[J]. IBRO Neuroscience Reports, 2022, 12: 55-64. doi: 10.1016/j.ibneur.2021.12.005
    [12] KUNHIMANGALAM R, JOSEPH P K, SUJITH O K. Nonlinear analysis of EEG signals: surrogate data analysis[J]. IRBM, 2008, 29(4): 239-244. doi: 10.1016/j.rbmret.2007.09.006
    [13] YAMAMOTO H. An electroencephalographical study of fasting therapy with special reference to EEG power spectral changes[J]. Japanese Journal of Psychosomatic Medicine, 1980, 20(4): 325-335.
    [14] MOSTAFAVI S A, KHALEGHI A, VAND S R, et al. Neuro-cognitive ramifications of fasting and feeding in obese and non-obese cases[J]. Clinical Psychopharmacology and Neuroscience, 2018, 16(4): 481-488. doi: 10.9758/cpn.2018.16.4.481
    [15] BRIER M R, FERREE T C, MAGUIRE M J, et al. Frontal theta and alpha power and coherence changes are modulated by semantic complexity in Go/NoGo tasks[J]. International Journal of Psychophysiology, 2010, 78(3): 215-224. doi: 10.1016/j.ijpsycho.2010.07.011
    [16] SAUSENG P, KLIMESCH W, SCHABUS M, et al. Fronto-parietal EEG coherence in theta and upper alpha reflect central executive functions of working memory[J]. International Journal of Psychophysiology, 2005, 57(2): 97-103. doi: 10.1016/j.ijpsycho.2005.03.018
    [17] KLIMESCH W. EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis[J]. Brain Research Reviews, 1999, 29(2-3): 169-195. doi: 10.1016/S0165-0173(98)00056-3
    [18] LEON-CARRION J, MARTIN-RODRIGUEZ J F, DAMAS-LOPEZ J, et al. Brain function in the minimally conscious state: a quantitative neurophysiological study[J]. Clinical Neurophysiology, 2008, 119(7): 1506-1514. doi: 10.1016/j.clinph.2008.03.030
    [19] 张奕文, 牛建平, 陈丽虹. 脑电功率谱分析对轻度认知障碍的诊断价值[J]. 齐齐哈尔医学院学报, 2010, 31(17): 2699-2700.

    ZHANG Y W, NIU J P, CHEN L H. Diagnostic value of EEG power spectrum analysis in mild cognitive impairment[J]. Journal of Qiqihar Medical College, 2010, 31(17): 2699-2700(in Chinese).
    [20] MILLER E K, ERICKSON C A, DESIMONE R. Neural mechanisms of visual working memory in prefrontal cortex of the macaque[J]. The Journal of Neuroscience, 1996, 16(16): 5154-5167. doi: 10.1523/JNEUROSCI.16-16-05154.1996
    [21] DIAMOND A. Executive functions[J]. Annual Review of Psychology, 2013, 64: 135-168. doi: 10.1146/annurev-psych-113011-143750
    [22] DELORME A, MAKEIG S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis[J]. Journal of Neuroscience Methods, 2004, 134(1): 9-21. doi: 10.1016/j.jneumeth.2003.10.009
    [23] ALBERA L, KACHENOURA A, COMON P, et al. ICA-based EEG denoising: a comparative analysis of fifteen methods[J]. Bulletin of the Polish Academy of Sciences-Technical Sciences, 2012, 60(3): 407-418. doi: 10.2478/v10175-012-0052-3
    [24] 李颖洁, 邱意弘, 朱贻盛. 脑电信号分析方法及其应用[M]. 北京: 科学出版社, 2009.

    LI Y J, QIU Y H, ZHU Y S. Analysis method of EEG signal and its application[M]. Beijing: Science Press, 2009(in Chinese).
    [25] BACIGALUPO F, LUCK S J. Lateralized suppression of alpha-band EEG activity as a mechanism of target processing[J]. The Journal of Neuroscience, 2019, 39(5): 900-917. doi: 10.1523/JNEUROSCI.0183-18.2018
    [26] MARSHALL T R, DEN BOER S, COOLS R, et al. Occipital alpha and gamma oscillations support complementary mechanisms for processing stimulus value associations[J]. Journal of Cognitive Neuroscience, 2018, 30(1): 119-129. doi: 10.1162/jocn_a_01185
    [27] CLARKE A R, BARRY R J, KARAMACOSKA D, et al. The EEG theta/beta ratio: a marker of arousal or cognitive processing capacity?[J]. Applied Psychophysiology and Biofeedback, 2019, 44(2): 123-129. doi: 10.1007/s10484-018-09428-6
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出版历程
  • 收稿日期:  2023-10-24
  • 录用日期:  2023-11-10
  • 网络出版日期:  2023-12-11
  • 整期出版日期:  2025-12-31

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