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经颅直流电刺激下脑卒中患者康复期脑功能网络特性研究 被引量:8

Research on characteristics of brain functional network in stroke patients during convalescent period under transcranial direct current stimulation
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摘要 经颅直流电刺激(tDCS)作为一种新兴的非侵入性脑刺激技术,对脑卒中疾病的康复作用目前尚未明确。本文结合脑电图(EEG)与复杂网络分析方法研究了tDCS对脑卒中患者康复期脑功能网络的影响。试验采集了31名脑卒中患者康复期的静息态EEG信号,其中16名患者作为试验组施加真刺激,15名患者作为对照组施加伪刺激。利用皮尔逊相关系数法计算EEG信号之间的相关系数,并构建了两组受试者tDCS刺激前、后的脑功能网络,分析对比了不同状态下脑功能网络的节点度、聚类系数、特征路径长度、全局效率和"小世界"属性5个特征参数。结果发现,tDCS真刺激后脑卒中患者脑功能网络的节点度、聚类系数、全局效率和"小世界"属性显著升高,特征路径长度显著降低,且差异具有统计学意义(P<0.05)。该结果表明tDCS能够改善脑卒中患者康复期的脑功能网络,本研究可为tDCS应用于脑卒中康复治疗提供理论和试验依据。 Transcranial direct current stimulation(tDCS)is an emerging non-invasive brain stimulation technique.However,the rehabilitation effect of tDCS on stroke disease is unclear.In this paper,based on electroencephalogram(EEG)and complex network analysis methods,the effect of tDCS on brain function network of stroke patients during rehabilitation was investigated.The resting state EEG signals of 31 stroke rehabilitation patients were collected and divided into stimulation group(16 cases)and control group(15 cases).The Pearson correlation coefficients were calculated between the channels,brain functional network of two groups were constructed before and after stimulation,and five characteristic parameters were analyzed and compared such as node degree,clustering coefficient,characteristic path length,global efficiency,and small world attribute.The results showed that node degree,clustering coefficient,global efficiency,and small world attributes of brain functional network in the tDCS group were significantly increased,characteristic path length was significantly reduced,and the difference was statistically significant(P<0.05).It indicates that tDCS can improve the brain function network of stroke patients in rehabilitation period,and may provide theory and experimental basis for the application of tDCS in stroke rehabilitation treatment.
作者 刘蒙蒙 徐桂芝 于洪丽 王春方 孙长城 郭磊 LIU Mengmeng;XU Guizhi;YU Hongli;WANG Chunfang;SUN Changcheng;GUO Lei(State Key Laboratory of Reliability and Intelligence of Electrical Equipment,School of Electrical Engineering,Hebei University of Technology,Tianjin 300130,P.R.China;Tianjin Key Laboratory of Bioelectromagnetic Technology and Intelligent Health,Hebei University of Technology,Tianjin 300130,P.R.China;Rehabilitation Medical Department,Tianjin Union Medical Center,Tianjin 300121,P.R.China)
出处 《生物医学工程学杂志》 EI CAS CSCD 北大核心 2021年第3期498-506,511,共10页 Journal of Biomedical Engineering
基金 国家自然科学基金资助项目(51877068,81871469,51737003,52077056) 河北省自然科学基金资助项目(E2020202033)。
关键词 经颅直流电刺激 脑卒中 脑电图 脑功能网络 transcranial direct current stimulation stroke electroencephalogram brain function network
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  • 1Cammoun L, Gigandet X, Sporns O, et al. Connectome alterations in schizophrenia. Neurolmage, 2009, 47:S157.
  • 2Vaessen M J, Jansen J F, Hofman P A, et al. Impaired small-world structural brain networks in chronic epilepsy. Neurolmage, 2009, 47: S113.
  • 3Friston K J, Frith C D, Liddle P F, et al. Functional connectivity: The principal component analysis of large (PET) data sets. J Cereb Blood Flow Metab, 1993, 13:5-14.
  • 4Stam C J. From synchronization to networks: Assessment of functional connectivity in the brain. In: Perez Velazquez J L, Richard W, eds. Coordinated Activity in the Brain, vol 2. Berlin Heidelberg: Springer-Verlag, 2009.91-115.
  • 5Stephan, Hilgetag K E, Burns C C, et al. Computational analysis of functional connectivity between areas of primate cerebral cortex. Philos Trans R Soc Lond B Biol Sci, 2000, 355:111-126.
  • 6Micheloyannis S, Pachou S, Stam C J, et al. Using graph theoretical analysis of multi channel EEG to evaluate the neural efficiency hypothesis. Neurosci Lett, 2006, 402:273-277.
  • 7Micheloyannis S, Vourkas S, Tsirka M, et al. The influence of ageing on complex brain networks: A graph theoretical analysis. Hum Brain Mapp, 2009, 30:200-208.
  • 8Ferri R, Rundo F, Bruni O, et al. Small-world network organization of functional connectivity of EEG slow-wave activity during sleep. Clin Neurophysiol, 2007, 118:449-456.
  • 9Dimitriadis S I, Laskaris N A, Del Rio-Portilla Y, et al. Characterizing dynamic functional connectivity across sleep stages from EEG. Brain Topogr, 2009, 22:119-133.
  • 10Stam C J. Functional connectivity patterns of human magnetoencephalographic recordings: A 'small-world' network? Neurosci Lett, 2004, 355:25-28.

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