EEG characteristics of changes in adult memory and attention function under 21 days fasting
-
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。Abstract:In space rescue missions, the rescued personnel may experience food shortages. In order to determine rescue missions, it is essential to examine the behavioral performance and electroencephalogram (EEG) signal changes of healthy adults completing short-term memory and concentration activities while fasting for 21 days. This paper recruited 13 volunteers and had them participate in a 21-day complete fasting experiment divided into 4 experimental stages in an experimental cabin. During this time, volunteers who completed the Two-back paradigm short-term memory task had their performance and resting state EEG data collected. Power spectrum analysis was used to determine the characteristics of the different rhythmic components in the EEG signals in order to assess the volunteers’ memory and attention changes. The results showed that the task response time was significantly prolonged during prolonged fasting (
P <0.05), and the change in accuracy was not significant. The reaction speed and concentration level of volunteers gradually weaken, and the impact is most significant around the 16th day; During fasting,δ activity increased, α activity decreased, (δ +θ )/(α +β ),θ /α ratio increased, and changes occur during the 10th to 16th day of fasting, and return to normal during the recovery period. Based on EEG and performance data, this paper believes that after 21 days of fastingδ ,α , (δ +θ )/(α +β ),θ /α changes significantly in the long period of fasting. Based on the features of each rhythmic element, these markers show how volunteers’ basic cognitive function will be impacted by attentional distraction and working memory loss during fasting. The main changes occur from the 10th to the 16th day of fasting. The research results of the paper can be used as supporting data for the assessment of cognitive ability changes during long fasting, and it also provides a reference for further exploring the mechanism of fasting in future aerospace and other fields.-
Key words:
- long-term fasting /
- electroencephalogram signal /
- power spectrum analysis /
- memory /
- attention function
-
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 F F3、Fz、F4 中央叶 C C3、Cz、C4 顶叶 P P3、Pz、P4 枕叶 O O1、Oz、O2 颞叶 T T7、T8 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。 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波 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波 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波 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波 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。 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。 -
[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 -


下载: