抑郁症自发脑电信号特异性研究进展

doi:10.3969/j.issn.0258-8021. 2014. 01.013

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摘要自发脑电（EEG）信号反映了大脑皮层神经元细胞群自发性、节律性的电生理活动，含有丰富的生理与病理信息，是临床脑神经与精神疾病诊断的重要依据。文中从频域分析、非线性动力学分析和因果性、同步性、独立成分分析等方面，综述了抑郁患者症自发EEG信号特异性研究进展并探讨了可能发展动向。抑郁症患者EEG信号频域分析方法，受性别、年龄及方法本身的限制，结论差异较大。非线性动力学及其他分析方法，得到了相对可靠的特异性分析结果，且部分参数变化与抑郁症状的临床变化有显著的相关性，有望为客观评价抗抑郁药物治疗效果提供新的检测手段，值得进行深入研究。

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	王春方张力新张希赵欣綦宏志周鹏万柏坤明

关键词 ：抑郁症, 自发脑电, 频域, 非线性

Abstract：Resting EEG reflects spontaneous and rhythmic electrical activity of the cortical neurons and contains rich physiological and pathological information, which is an important tool for the clinical diagnosis of brain disorders and mental illness. This article reviewed the research progress and development of the resting EEG of depression in three aspects: the frequency domain analysis, the nonlinear dynamic analysis and other methods such as causality, synchronization and independent component analysis. Influenced by gender, age and the restriction of the method itself, the conclusions achieved by frequency domain analysis were different in some aspects. In contrast, nonlinear dynamic and other analysis methods got relatively reliable results. Moreover, some parameters changed with clinical depressive symptoms were expected to be the marker of depression diagnosis and treatment effect evaluation of antidepressant drugs, which was worthy of further study.

Key words： depression resting EEG frequency domain nonlinear dynamic

基金资助:国家自然科学基金 ( 81222021，81171423)；天津市自然科学基金( 3JCQNJC14400)

引用本文:

王春方张力新张希赵欣綦宏志周鹏万柏坤明. 抑郁症自发脑电信号特异性研究进展[J]. 中国生物医学工程学报, 2014, 33(1): 86-92.
WANG Chun Fang ZHANG Li Xin ZHANG Xi ZHAO Xin QI Hong ZhiZHOU Peng WAN Bai Kun &. Research Progress on the Specificity of Resting EEG in Depression. journal1, 2014, 33(1): 86-92.

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http://cjbme.csbme.org/CN/ 10.3969/j.issn.0258-8021. 2014. 01.013 或 http://cjbme.csbme.org/CN/Y2014/V33/I1/86

［1］李青栋.抑郁症的概念及分类研究历史［J］.医学与哲学(临床决策论坛版)，2009，30（11）：68-80.
［2］Buyukdura JS, McClintock SM, Croarkin PE. Psychomotor retardation in depression: Biological underpinnings, measurement, and treatment ［J］. NeuroPsychopharmacology & Biological Psychiatry, 2011, 35: 395-409.
［3］崔利坤，谢卫红.抑郁症的临床亚型及治疗［J］.临床荟萃，2004,19（13）：765-766.
［4］江开达.抑郁症的诊断与治疗［J］.医学与哲学（临床决策论坛版），2010，31（2）：12-13.
［5］和昱辰.抑郁症临床研究进展［J］.国际检验医学杂志，2013，34（7）：832-834.
［6］何舒，林渝峰，李霞. 抑郁症的发病机制研究进展［J］.四川生理科学杂志，2008,28（3）:126-128.
［7］Cai X, Kallarackal AJ, Kvarta MD, et al. Local potentiation of excitatory synapses by serotonin and its alteration in rodent models of depression ［J］. Nat Neurosci, 2013,16(4): 464-472.
［8］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.
［9］Verner K, Colleen M, Sidney K, et al. EEG power, frequency, asymmetry and coherence in male depression ［J］. Psychiatry Research: Neuroimaging Section, 2001, 106: 123-140.
［10］Pollock VE, Schneider LS. Quantitative, waking EEG research on depression ［J］. Biol Psychiatry, 1990, 27(7):757-780.
［11］Yamada M, Kimura M, Mori T, et al. EEG power and coherence in presenile and senile depression. Characteristic findings related to differences between anxiety type and retardation type ［J］. Nihon Ika Daigaku Zasshi, 1995, 62(2):176-185.
［12］Fachner J, Gold C, Erkkil J. Music therapy modulates frontotemporal activity in restEEG in depressed clients ［J］. Brain Topogr, 2013, 26(2):338-354.
［13］Iznak, AF, Iznak EV, Sorokin SA. Changes in EEG and reaction times during the treatment of apathetic depression ［J］. Neuroscience and Behavioral Physiology, 2013, 43(1): 79-83.
［14］Lubar JF, Congedo M, Askew JH. Lowresolution electromagnetic tomography (LORETA) of cerebral activity in chronic depressive disorder ［J］. International Journal of Psychophysiology, 2003, 49:175-185.
［15］Mathersul D, Williams LM, HopKinson PJ, et al. Investigating models of affect: relationships among EEG alpha asymmetry, depression, and anxiety ［J］. Emotion, 2008,8(4):560-572.
［16］Gold C, Fachner J, Erkkil, J. Validity and reliability of electroencephalographic frontal alpha asymmetry and frontal midline theta as biomarkers for depression ［J］. Scandinavian Journal of Psychology, 2013,54(2): 118-126. 
［17］Allen JJB, Urry HL, Hitt SK, et al. The stability of resting frontal electroencephalographic asymmetry in depression ［J］. Psychophysiology, 2004, 41:269-280.
［18］Lee TW, Yu YW, Chen MC, et al. Cortical mechanisms of the symptomatology in major depressive disorder: A resting EEG study ［J］. Journal of Affective Disorders, 2011, 131:243-250.
［19］Flor-Henry P, Lind JC, Koles ZJ. A sourceimaging (lowresolution electromagnetic tomography) study of the EEGs from unmedicated males with depression ［J］. Psychiatry Res, 2004,130(2):191-207.
［20］Reid SA, Duke LM, Allen JJ. Resting frontal electroencephalographic asymmetry in depression: inconsistencies suggest the need to identify mediating factors ［J］. Psychophysiology, 1998,35(4):389-404.
［21］Hinrikus H, Suhhova A, Bachmann M, et al. Electroencephalographic spectral asymmetry index for detection of depression ［J］. Med Biol Eng Comput, 2009, 47:1291-1299.
［22］Bachmann M, Lass J, Suhhova A, et al. Spectral asymmetry and higuchi's fractal dimension measures of depression electroencephalogram ［J］. Comput Math Methods Med, 2013, art no 251638.
［23］Sun Yu, Hu Sijung, Zhu Yisheng, et al. Electroencephalographic differences between depressed and control subjects: An aspect of interdependence analysis ［J］. Brain Research Bulletin, 2008,76:559-564.
［24］Jimbo Y, Tateno T, Robinson HP. Simultaneous induction of pathwayspecific potentiation and depression in networks of cortical neurons ［J］. Biophys J, 1999,76(2):670-678.［25］瞿祥，王艺明. 脑电非线性动力学分析在抑郁症中的应用及抗抑郁药的疗效观察［J］. 临床研究，2012,9（34）：52-54.
［26］Hosseinifard B, Moradi MH, Rostami R. Classifying depression patients and normal subjects using machine learning techniques and nonlinear features from EEG signal ［J］. Computer Methods and Programs in Biomedicine, 2013, 109:339-345.
［27］Ahmadlou M, Adeli H, Adeli A. Fractality analysis of frontal brain in major depressive disorder ［J］. International Journal of Psychophysiology, 2012, 85:206-211.
［28］张胜，乔世妮，王蔚. 抑郁症患者脑电复杂度的小波熵分析［J］. 计算机工程与应用，2012,48（4）：143-145.
［29］Frantzidis CA, Diamantoudi MD, Grigoriadou, E, et al. A Mahalanobis distance based approach towards the reliable detection of geriatric depression symptoms coexisting with cognitive decline ［J］. IFIP Advances in Information and Communication Technology, 2012, 382(2):16-25.
［30］Mateo A, Roberto H, Daniel A, et al. Interpretation of the LempelZiv complexity measure in the context of biomedical signal analysis ［J］. IEEE Transactions on Biomedical Engineering, 2006,53(11): 2282-2288. 
［31］Yingjie L, Shanbao T, Dan L. Abnormal EEG complexity in patients with schizophrenia and depression ［J］. Clinical Neruophysiology, 2008, 119(6):1232-1241.
［32］Méndez MA, Zuluaga P, Hornero R, et al. Complexity analysis of spontaneous brain activity: effects of depression and antidepressant treatment ［J］. Journal of Psychopharmacology, 2012, 26(5):636-643.
［33］LinkenkaerHansen K, Monto S, Rytsl H, et al. Breakdown of longrange temporal correlations in Theta oscillations in patients with major depressive disorder ［J］. The Journal of Neuroscience, 2005,25(44):10131-10137.
［34］JunSeok L, ByungHwan Y, JangHan L, et al. Detrended fluctuation analysis of resting EEG in depressed outpatients and healthy controls ［J］. Clinical Neurophysiology, 2007, 118：2489-2496.
［35］胡巧莉. 基于相位同步分析方法的抑郁症脑电信号的研究［J］. 中国医疗器械杂志，2010, 34（4）：246-249.
［36］Bornas X, Noguera M, Balle M, et al. Longrange temporal correlations in resting EEG ［J］. Journal of Psychophysiology, 2013, 27(2):60-66.
［37］Okazaki R, Takahashi T, Ueno K, et al. Effects of electroconvulsive therapy on neural complexity in patients with depression: Report of three cases ［J］. Journal of Affective Disorders, 2013, 150 (2): 389-392.
［38］Kim DJ, Bolbecker AR, Howell J, et al. Disturbed resting state EEG synchronization in bipolar disorder: A graphtheoretic analysis ［J］. NeuroImage: Clinical, 2013, 2(1): 414-423.
［39］Yu Sun, Sijung Hu, Yisheng Zhu, et al. Graphic patterns of cortical functional connectivity of depressed patients on the basis of EEG measurements ［C］//Proceedings of 33rd Annual International Conference of IEEE EMBS. Boston:IEEE, 2011:1419-1422.
［40］GrinYatsenko VA, Baas I, Ponomarev VA, et al. Independent component approach to the analysis of EEG recordings at early stages of depressive disorders ［J］. Clinical Neurophysiology, 2010, 121:281-289.
［41］GrinYatsenko VA, Baas I, Ponomarev VA, et al. Electroencephalograms of patients with initial signs of depression: independent component analysis ［J］. Human Physiology, 2011, 37(1):39-48.
［42］张振中.基于ICA方法的脑电信号消噪及特征提取的研究［D］. 西安:西北工业大学，2007.