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当代阿耳茨海默病研究

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ISSN (Print): 1567-2050
ISSN (Online): 1875-5828

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Research Article

基于加权相位滞后指数的功能连接改变：阿尔茨海默病的探索性脑电图研究

卷 18, 期 6, 2021

发表于: 01 October, 2021

页: [513 - 522] 页: 10

弟呕挨: 10.2174/1567205018666211001110824

价格: $65

摘要

目的：许多脑电图 (EEG) 研究关注阿尔茨海默病 (AD) 患者的电活动改变，但没有一致的结果，尤其是在功能连接方面。我们假设加权相位滞后指数（w-PLI）作为功能连接的基于相位的度量，可以用作 AD 的辅助诊断方法。 方法：我们招募了 30 名 AD 患者、30 名轻度认知障碍 (MCI) 患者和 30 名健康对照 (HC)。在放松清醒期间，所有参与者的基线脑电图都被记录下来。在 EEG 预处理之后，确定了功率谱密度 (PSD) 和 wPLI 参数，以进一步分析它们是否与认知评分相关。 结果：在AD患者中，与MCI和HC组相比，θ波段PSD增加，这与定向、计算和延迟记忆容量的障碍有关。此外，wPLI 显示，对于 AD 患者，delta 波段中额叶和远处区域之间的连接强度明显较低，而 theta 波段中中央和颞枕区的连接强度较高。此外，我们发现 theta 功能连接与认知评分之间存在显着的负相关。 结论：增加的 theta PSD 和减少的 delta wPLI 可能是 AD 最早的变化之一，并且与疾病的严重程度有关。参数 wPLI 是一种新颖的相位同步测量方法，具有理解潜在功能连接性和帮助诊断 AD 的潜力。

关键词: 阿尔茨海默病、轻度认知障碍、脑电图、功率谱密度、加权相位滞后指数、认知评分。

« Previous Next »
[1]
Alzheimer’s Association. 2015 Alzheimer’s disease facts and figures. Alzheimers Dement 2015; 11(3): 332-84.
[http://dx.doi.org/10.1016/j.jalz.2015.02.003] [PMID: 25984581]
[2]
Bahar-Fuchs A, Martyr A, Goh AM, Sabates J, Clare L. Cognitive training for people with mild to moderate dementia. Cochrane Database Syst Rev 2019; 3: CD013069.
[http://dx.doi.org/10.1002/14651858.CD013069.pub2] [PMID: 30909318]
[3]
Ganguli M, Dodge HH, Shen C, DeKosky ST. Mild cognitive impairment, amnestic type: an epidemiologic study. Neurology 2004; 63(1): 115-21.
[http://dx.doi.org/10.1212/01.WNL.0000132523.27540.81] [PMID: 15249620]
[4]
Langa KM, Levine DA. The diagnosis and management of mild cognitive impairment: a clinical review. JAMA 2014; 312(23): 2551-61.
[http://dx.doi.org/10.1001/jama.2014.13806] [PMID: 25514304]
[5]
Roberts R, Knopman DS. Classification and epidemiology of MCI. Clin Geriatr Med 2013; 29(4): 753-72.
[http://dx.doi.org/10.1016/j.cger.2013.07.003] [PMID: 24094295]
[6]
Ruiz-Gómez SJ, Gómez C, Poza J, et al. Measuring alterations of spontaneous EEG neural coupling in Alzheimer’s disease and mild cognitive impairment by means of cross-entropy metrics. Front Neuroinform 2018; 12: 76.
[http://dx.doi.org/10.3389/fninf.2018.00076] [PMID: 30459586]
[7]
Kinnunen KM, Cash DM, Poole T, et al. Presymptomatic atrophy in autosomal dominant Alzheimer’s disease: A serial magnetic resonance imaging study. Alzheimers Dement 2018; 14(1): 43-53.
[http://dx.doi.org/10.1016/j.jalz.2017.06.2268] [PMID: 28738187]
[8]
Whitwell JL. Alzheimer’s disease neuroimaging. Curr Opin Neurol 2018; 31(4): 396-404.
[http://dx.doi.org/10.1097/WCO.0000000000000570] [PMID: 29762152]
[9]
Fan M, Chou CA. Detecting abnormal pattern of epileptic seizures via temporal synchronization of EEG signals. IEEE Trans Biomed Eng 2019; 66(3): 601-8.
[http://dx.doi.org/10.1109/TBME.2018.2850959] [PMID: 29993518]
[10]
Engels MM, Stam CJ, van der Flier WM, Scheltens P, de Waal H, van Straaten EC. Declining functional connectivity and changing hub locations in Alzheimer’s disease: an EEG study. BMC Neurol 2015; 15: 145.
[http://dx.doi.org/10.1186/s12883-015-0400-7] [PMID: 26289045]
[11]
Park YM, Che HJ, Im CH, Jung HT, Bae SM, Lee SH. Decreased EEG synchronization and its correlation with symptom severity in Alzheimer’s disease. Neurosci Res 2008; 62(2): 112-7.
[http://dx.doi.org/10.1016/j.neures.2008.06.009] [PMID: 18672010]
[12]
Soininen H, Partanen J, Pääkkönen A, Koivisto E, Riekkinen PJ. Changes in absolute power values of EEG spectra in the follow-up of Alzheimer’s disease. Acta Neurol Scand 1991; 83(2): 133-6.
[http://dx.doi.org/10.1111/j.1600-0404.1991.tb04662.x] [PMID: 2017898]
[13]
Jelic V, Shigeta M, Julin P, Almkvist O, Winblad B, Wahlund LO. Quantitative electroencephalography power and coherence in Alzheimer’s disease and mild cognitive impairment. Dementia 1996; 7(6): 314-23.
[PMID: 8915037]
[14]
Rubinov M, Sporns O. Complex network measures of brain connectivity: uses and interpretations. Neuroimage 2010; 52(3): 1059-69.
[http://dx.doi.org/10.1016/j.neuroimage.2009.10.003] [PMID: 19819337]
[15]
Sankari Z, Adeli H, Adeli A. Intrahemispheric, interhemispheric, and distal EEG coherence in Alzheimer’s disease. Clin Neurophysiol 2011; 122(5): 897-906.
[http://dx.doi.org/10.1016/j.clinph.2010.09.008] [PMID: 21056936]
[16]
Babiloni C, Del Percio C, Lizio R, et al. Abnormalities of resting-state functional cortical connectivity in patients with dementia due to Alzheimer’s and Lewy body diseases: an EEG study. Neurobiol Aging 2018; 65: 18-40.
[http://dx.doi.org/10.1016/j.neurobiolaging.2017.12.023] [PMID: 29407464]
[17]
Adler G, Brassen S, Jajcevic A. EEG coherence in Alzheimer’s dementia. J Neural Transm (Vienna) 2003; 110(9): 1051-8.
[http://dx.doi.org/10.1007/s00702-003-0024-8] [PMID: 12928837]
[18]
Musaeus CS, Nielsen MS, Høgh P. Altered low-frequency EEG connectivity in mild cognitive impairment as a sign of clinical progression. J Alzheimers Dis 2019; 68(3): 947-60.
[http://dx.doi.org/10.3233/JAD-181081] [PMID: 30883355]
[19]
Wang R, Wang J, Yu H, Wei X, Yang C, Deng B. Decreased coherence and functional connectivity of electroencephalograph in Alzheimer’s disease. Chaos 2014; 24(3): 033136.
[http://dx.doi.org/10.1063/1.4896095] [PMID: 25273216]
[20]
Vinck M, Oostenveld R, van Wingerden M, Battaglia F, Pennartz CM. An improved index of phase-synchronization for electrophysiological data in the presence of volume-conduction, noise and sample-size bias. Neuroimage 2011; 55(4): 1548-65.
[http://dx.doi.org/10.1016/j.neuroimage.2011.01.055] [PMID: 21276857]
[21]
Musaeus CS, Engedal K, Høgh P, et al. Oscillatory connectivity as a diagnostic marker of dementia due to Alzheimer’s disease. Clin Neurophysiol 2019; 130(10): 1889-99.
[http://dx.doi.org/10.1016/j.clinph.2019.07.016] [PMID: 31408790]
[22]
Briels CT, Schoonhoven DN, Stam CJ, de Waal H, Scheltens P, Gouw AA. Reproducibility of EEG functional connectivity in Alzheimer’s disease. Alzheimers Res Ther 2020; 12(1): 68.
[http://dx.doi.org/10.1186/s13195-020-00632-3] [PMID: 32493476]
[23]
McKhann GM, Knopman DS, Chertkow H, et al. The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 2011; 7(3): 263-9.
[http://dx.doi.org/10.1016/j.jalz.2011.03.005] [PMID: 21514250]
[24]
Knopman DS, Petersen RC. Mild cognitive impairment and mild dementia: a clinical perspective. Mayo Clin Proc 2014; 89(10): 1452-9.
[http://dx.doi.org/10.1016/j.mayocp.2014.06.019] [PMID: 25282431]
[25]
Petersen RC. Mild cognitive impairment as a diagnostic entity. J Intern Med 2004; 256(3): 183-94.
[http://dx.doi.org/10.1111/j.1365-2796.2004.01388.x] [PMID: 15324362]
[26]
Stam CJ, Nolte G, Daffertshofer A. Phase lag index: assessment of functional connectivity from multi channel EEG and MEG with diminished bias from common sources. Hum Brain Mapp 2007; 28(11): 1178-93.
[http://dx.doi.org/10.1002/hbm.20346] [PMID: 17266107]
[27]
Sunwoo JS, Lee S, Kim JH, et al. Altered functional connectivity in idiopathic rapid eye movement sleep behavior disorder: A resting-state EEG study. Sleep 2017; 40(6)
[http://dx.doi.org/10.1093/sleep/zsx058] [PMID: 28431177]
[28]
Benjamini Y, Hochberg Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J R Stat Soc B 1995; 57(1): 289-300.
[http://dx.doi.org/10.1111/j.2517-6161.1995.tb02031.x]
[29]
Zalesky A, Fornito A, Bullmore ET. Network-based statistic: identifying differences in brain networks. Neuroimage 2010; 53(4): 1197-207.
[http://dx.doi.org/10.1016/j.neuroimage.2010.06.041] [PMID: 20600983]
[30]
Babiloni C, Lizio R, Del Percio C, et al. Cortical sources of resting state EEG rhythms are sensitive to the progression of early stage Alzheimer’s disease. J Alzheimers Dis 2013; 34(4): 1015-35.
[http://dx.doi.org/10.3233/JAD-121750] [PMID: 23340039]
[31]
Gutiérrez-de Pablo V, Gómez C, Poza J, et al. Relationship between the presence of the ApoE ε4 allele and EEG complexity along the Alzheimer’s disease continuum. Sensors (Basel) 2020; 20(14): E3849.
[http://dx.doi.org/10.3390/s20143849] [PMID: 32664228]
[32]
Benwell CSY, Davila-Pérez P, Fried PJ, et al. EEG spectral power abnormalities and their relationship with cognitive dysfunction in patients with Alzheimer’s disease and type 2 diabetes. Neurobiol Aging 2020; 85: 83-95.
[http://dx.doi.org/10.1016/j.neurobiolaging.2019.10.004] [PMID: 31727363]
[33]
Musaeus CS, Engedal K, Høgh P, et al. EEG theta power is an early marker of cognitive decline in dementia due to Alzheimer’s disease. J Alzheimers Dis 2018; 64(4): 1359-71.
[http://dx.doi.org/10.3233/JAD-180300] [PMID: 29991135]
[34]
Chen AC, Feng W, Zhao H, Yin Y, Wang P. EEG default mode network in the human brain: spectral regional field powers. Neuroimage 2008; 41(2): 561-74.
[http://dx.doi.org/10.1016/j.neuroimage.2007.12.064] [PMID: 18403217]
[35]
Kim JS, Lee SH, Park G, et al. Clinical implications of quantitative electroencephalography and current source density in patients with Alzheimer’s disease. Brain Topogr 2012; 25(4): 461-74.
[http://dx.doi.org/10.1007/s10548-012-0234-1] [PMID: 22736322]
[36]
Fox SE, Wolfson S, Ranck JB Jr. Hippocampal theta rhythm and the firing of neurons in walking and urethane anesthetized rats. Exp Brain Res 1986; 62(3): 495-508.
[http://dx.doi.org/10.1007/BF00236028] [PMID: 3720881]
[37]
Zhang H, Jacobs J. Traveling theta waves in the human hippocampus. J Neurosci 2015; 35(36): 12477-87.
[http://dx.doi.org/10.1523/JNEUROSCI.5102-14.2015] [PMID: 26354915]
[38]
Jeong J. EEG dynamics in patients with Alzheimer’s disease. Clin Neurophysiol 2004; 115(7): 1490-505.
[http://dx.doi.org/10.1016/j.clinph.2004.01.001] [PMID: 15203050]
[39]
Musaeus CS, Nielsen MS, Østerbye NN, Høgh P. Decreased parietal beta power as a sign of disease progression in patients with mild cognitive impairment. J Alzheimers Dis 2018; 65(2): 475-87.
[http://dx.doi.org/10.3233/JAD-180384] [PMID: 30056426]
[40]
Marshall AC, Cooper NR. The association between high levels of cumulative life stress and aberrant resting state EEG dynamics in old age. Biol Psychol 2017; 127: 64-73.
[http://dx.doi.org/10.1016/j.biopsycho.2017.05.005] [PMID: 28501607]
[41]
Mierau A, Klimesch W, Lefebvre J. State-dependent alpha peak frequency shifts: Experimental evidence, potential mechanisms and functional implications. Neuroscience 2017; 360: 146-54.
[http://dx.doi.org/10.1016/j.neuroscience.2017.07.037] [PMID: 28739525]
[42]
Badhwar A, Tam A, Dansereau C, Orban P, Hoffstaedter F, Bellec P. Resting-state network dysfunction in Alzheimer’s disease: A systematic review and meta-analysis. Alzheimers Dement (Amst) 2017; 8: 73-85.
[http://dx.doi.org/10.1016/j.dadm.2017.03.007] [PMID: 28560308]
[43]
Vecchio F, Miraglia F, Alù F, et al. Classification of Alzheimer’s disease with respect to physiological aging with innovative EEG biomarkers in a machine learning implementation. J Alzheimers Dis 2020; 75(4): 1253-61.
[http://dx.doi.org/10.3233/JAD-200171] [PMID: 32417784]
[44]
Minati L, Chan D, Mastropasqua C, et al. Widespread alterations in functional brain network architecture in amnestic mild cognitive impairment. J Alzheimers Dis 2014; 40(1): 213-20.
[http://dx.doi.org/10.3233/JAD-131766] [PMID: 24366921]
[45]
Tran XA, Mcdonald N, Dickinson A, et al. Functional connectivity during language processing in 3-month-old infants at familial risk for autism spectrum disorder. Eur J Neurosci 2021; 53(5): 1621-37.
[46]
Raeisi K, Mohebbi M, Khazaei M, Seraji M, Yoonessi A. Phase-synchrony evaluation of EEG signals for Multiple Sclerosis diagnosis based on bivariate empirical mode decomposition during a visual task. Comput Biol Med 2020; 117: 103596.
[http://dx.doi.org/10.1016/j.compbiomed.2019.103596] [PMID: 32072973]
[47]
Racz FS, Stylianou O, Mukli P, Eke A. Multifractal dynamic functional connectivity in the resting-state brain. Front Physiol 2018; 9: 1704.
[http://dx.doi.org/10.3389/fphys.2018.01704] [PMID: 30555345]
[48]
Das S, Puthankattil SD. Complex network analysis of MCI-AD EEG signals under cognitive and resting state. Brain Res 2020; 1735: 146743.
[http://dx.doi.org/10.1016/j.brainres.2020.146743] [PMID: 32114060]
[49]
Miraglia F, Vecchio F, Bramanti P, Rossini PM. EEG characteristics in “eyes-open” versus “eyes-closed” conditions: Small-world network architecture in healthy aging and age-related brain degeneration. Clin Neurophysiol 2016; 127(2): 1261-8.
[http://dx.doi.org/10.1016/j.clinph.2015.07.040] [PMID: 26603651]
[50]
Moretti DV, Frisoni GB, Pievani M, et al. Cerebrovascular disease and hippocampal atrophy are differently linked to functional coupling of brain areas: an EEG coherence study in MCI subjects. J Alzheimers Dis 2008; 14(3): 285-99.
[http://dx.doi.org/10.3233/JAD-2008-14303] [PMID: 18599955]
[51]
Buckner RL, Snyder AZ, Shannon BJ, et al. Molecular, structural, and functional characterization of Alzheimer’s disease: evidence for a relationship between default activity, amyloid, and memory. J Neurosci 2005; 25(34): 7709-17.
[http://dx.doi.org/10.1523/JNEUROSCI.2177-05.2005] [PMID: 16120771]
[52]
Colgin LL. Mechanisms and functions of theta rhythms. Annu Rev Neurosci 2013; 36: 295-312.
[http://dx.doi.org/10.1146/annurev-neuro-062012-170330] [PMID: 23724998]
[53]
Guderian S, Düzel E. Induced theta oscillations mediate large-scale synchrony with mediotemporal areas during recollection in humans. Hippocampus 2005; 15(7): 901-12.
[http://dx.doi.org/10.1002/hipo.20125] [PMID: 16161060]
[54]
Henneman WJ, Sluimer JD, Barnes J, et al. Hippocampal atrophy rates in Alzheimer disease: added value over whole brain volume measures. Neurology 2009; 72(11): 999-1007.
[http://dx.doi.org/10.1212/01.wnl.0000344568.09360.31] [PMID: 19289740]
[55]
Babiloni C, Ferri R, Noce G, et al. Resting-state electroencephalographic delta rhythms may reflect global cortical arousal in healthy old seniors and patients with Alzheimer’s disease dementia. Int J Psychophysiol 2020; 158: 259-70.
[http://dx.doi.org/10.1016/j.ijpsycho.2020.08.012] [PMID: 33080295]
[56]
Das N, Ren J, Spence JS, Rackley A, Chapman SB. Relationship of parieto-occipital brain energy phosphate metabolism and cognition using 31P MRS at 7-tesla in amnestic mild cognitive impairment. Front Aging Neurosci 2020; 12: 222.
[http://dx.doi.org/10.3389/fnagi.2020.00222] [PMID: 33005142]
[57]
Han Y, Wang K, Jia J, Wu W. Changes of EEG spectra and functional connectivity during an object-location memory task in Alzheimer’s disease. Front Behav Neurosci 2017; 11: 107.
[http://dx.doi.org/10.3389/fnbeh.2017.00107] [PMID: 28620287]
[58]
Hidasi Z, Czigler B, Salacz P, Csibri E, Molnár M. Changes of EEG spectra and coherence following performance in a cognitive task in Alzheimer’s disease. Int J Psychophysiol 2007; 65(3): 252-60.
[http://dx.doi.org/10.1016/j.ijpsycho.2007.05.002] [PMID: 17586077]

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