基于认知功能的精神分裂症特征的分类研究
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摘要
通过任务转换实验(task-switching task,TST)与机器学习相结合的方法对精神分裂症患者进行客观辨别。本实验中,45例精神分裂症患者和55例正常被试参与了实验,原始特征为反应时间、准确率、转换代价、干扰、年龄和性别等17个特征,利用Relief算法进行特征选择,并利用支持向量机(SVM)对不同的特征组合进行分类。研究结果表明短提示一致有转换、短提示一致无转换、短提示不一致无转换、长提示一致有转换、长提示一致无转换、转换代价、剩余转换代价和反应转换代价8个特征创建的SVM分类模型达到了90%的分类准确率,ROC曲线下面积(AUC)大小为0.89.该方法能够客观、有效地鉴别精神分裂症患者,能运用于精神分裂症的辅助诊断,以提高医生诊断结果的准确率。
Schizophrenia is a chronic and complex heavy psychosis.Its barriers on thought,emotion,behavior and so on seriously affect the patient's life.In addition to the assessment of the clinical scale,there is still a lack of an objective and convenient method for discriminating patients with Schizophrenia.Therefore,the research of auxiliary diagnostic techniques for schizophrenia has become a hot spot.This study objectively identified Schizophrenia patients by combining task switching(task-switching task,TST)and machine learning.In this study,45 patients with Schizophrenia and 55 normal subjects were involved in the experiment.The original features included 17 characteristics of reaction time,accuracy,switch cost,interference,age and gender.Relief algorithm was used to make feature selection and the support vector machine was used to classify different feature combinations.Research results show that the SVM classification model based on the 8 features,that is,short cue congruent switch,short cue congruent without switch,short cue incongruent without switch,long cue congruent switch,long cue congruent without switch,switch cost,residual switch cost,and response switch,reached a classification accuracy rate of 90% .The area under ROC curve(AUC)was 0.89.The experimental results show that this method can objectively and effectively identify Schizophrenia patients,and it can be applied to the auxiliary diagnosis of Schizophrenia,so as to improve the accuracy of diagnosis.
Schizophrenia is a chronic and complex heavy psychosis.Its barriers on thought,emotion,behavior and so on seriously affect the patient's life.In addition to the assessment of the clinical scale,there is still a lack of an objective and convenient method for discriminating patients with Schizophrenia.Therefore,the research of auxiliary diagnostic techniques for schizophrenia has become a hot spot.This study objectively identified Schizophrenia patients by combining task switching(task-switching task,TST)and machine learning.In this study,45 patients with Schizophrenia and 55 normal subjects were involved in the experiment.The original features included 17 characteristics of reaction time,accuracy,switch cost,interference,age and gender.Relief algorithm was used to make feature selection and the support vector machine was used to classify different feature combinations.Research results show that the SVM classification model based on the 8 features,that is,short cue congruent switch,short cue congruent without switch,short cue incongruent without switch,long cue congruent switch,long cue congruent without switch,switch cost,residual switch cost,and response switch,reached a classification accuracy rate of 90% .The area under ROC curve(AUC)was 0.89.The experimental results show that this method can objectively and effectively identify Schizophrenia patients,and it can be applied to the auxiliary diagnosis of Schizophrenia,so as to improve the accuracy of diagnosis.
引文
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[21]杨丽霞.精神分裂症患者的执行功能的研究[D].上海:华东师范大学,2014.YANG L X.Research on the executive function of patients with schizophrenia[D].Shanghai:East China Normal University,2014.
[22]REICHENBERG A,HARVEY P D.Neuropsychological impairments in schizophrenia:Integration of performance-based and brain imaging findings[J].Psychological Bulletin,2007,133(5):833-858.
[2]周平,刘联琦,张斌,等.卡尔加里精神分裂症抑郁量表(中文版)信效度初步分析[J].中国心理卫生杂志,2009,23(9):638-642.ZHOU P,LIU L Q,ZHANG B,et al.Preliminary analysis of the reliability of Calgary depression scale(Chinese version)[J].Chinese Journal of Mental Health,2009,23(9):638-642.
[3]朱春燕,汪凯.执行功能与精神分裂症[J].心理科学进展,2004,12(5):743-745.ZHU C Y,WANG K.Executive function and schizophrenia[J].Advances in Psychological,2004,12(5):743-745.
[4]高原.功能性磁共振成像(fMRI)在视觉注意研究中的应用[J].内蒙古师大学报(哲社汉文版),2002,31(5):16-20.GAO Y.The application of fMRI to the study of visual attention[J].Journal of Inner Mongolia Normal University(Philosophy&Social Science),2002,31(5):16-20.
[5]倪睿,吴新年,齐翔,等.fMRI在视觉研究中的应用和进展[J].生物化学与生物物理进展,2000,27(3):254-257.NI R,WU X N,QI X,et al.The application and achievements of fMRI in vision research[J].Progress in Biochemistry and Biophysics,2000,27(3):254-257.
[6]张喆.神经影像技术对心理学的贡献及限度研究[J].学理论,2012(14):65-66.ZHANG Z.Research on the contribution and limitation of neuroimaging technology to psychology[J].Theory Research,2012(14):65-66.
[7]刘晋,林敬晖,洪楠.精神分裂症影像学研究[J].中国介入影像与治疗学,2014,11(2):121-124.LIU J,LIN J H,HONG N.Imaging studies of schizophrenia[J].China's Involvement in Imaging and Therapeutics,2014,11(2):121-124.
[8]MEDALIA A,LIM R.Treatment of cognitive dysfunction in psychiatric disorders[J].Journal of Psychiatric Practice,2004,10(1):17.
[9]向云.精神分裂症与认知功能障碍[J].中华行为医学与脑科学杂志,2005,14(7):620-622.XIANG Y.Schizophrenia and cognitive impairment[J].Chin J of Behavioral Med Sci,2005,14(7):620-622.
[10]王久菊,王鹏飞,权文香,等.精神分裂症的语言认知特点及其脑机制[J].生物化学与生物物理进展,2015,42(1):49-55.WANG J J,WANG P F,QUAN W X,et al.The linguistic cognitive characteristics of schizophrenia and its brain mechanism[J].Biochemical and Biological Advances,2015,42(1):49-55.
[11]WOODWARD T S,RUFF C C,NGAN E T.Short-and long-term changes in anterior cingulate activation during resolution of task-set competition[J].Brain Research,2006,1068(1):161.
[12]SABB F W,BEARDEN C E,GLAHN D C,et al.A collaborative knowledge base for cognitive phenomics[J].Molecular Psychiatry,2008,13(4):350-360.
[13]MONSELL S.Task switching[J].Trends in Cognitive Sciences,2003,7(3):134-140.
[14]LEE J,PARK S.Working memory impairments in schizophrenia:a meta-analysis[J].Journal of Abnormal Psychology,2005,114(4):599.
[15]KIRA K,RENDELL L A.The feature selection problem:traditional methods and a new algorithm[C]∥Proceedings of Tenth National Conference on Artificial Intelligence.San Jose:AAAI Press,1992:129-134.
[16]CORTES C,VAPMIK V.Support-vector networks[J].Machine Learning,1995,20(3):273-297.
[17]谢刚,古赟,王芳,等.基于支持向量机的图像语义提取研究[J].太原理工大学学报,2011,42(6):563-565.XIE G,GU Y,WANG F,et al.Semantic extraction of image using support vector machines[J].Journal of Taiyuan University of Technology,2011,42(6):563-565.
[18]陈曦.视觉认知心理学反应时实验研究的新技术[J].华南师范大学学报(社会科学版),1996(4):70-74.CHEN X.New techniques of experimental research on visual cognitive psychology reaction[J].Journal of South China Normal University(Social Sciences Edition),1996(4):70-74.
[19]STERNBERG S.Memory-scanning:mental processes revealed by reaction-time experiments.[J].American Scientist,1969,57(4):421.
[20]BARCH D M.What can research on schizophrenia tell us about the cognitive neuroscience of working memory[J].Neuroscience,2006,139(1):73.
[21]杨丽霞.精神分裂症患者的执行功能的研究[D].上海:华东师范大学,2014.YANG L X.Research on the executive function of patients with schizophrenia[D].Shanghai:East China Normal University,2014.
[22]REICHENBERG A,HARVEY P D.Neuropsychological impairments in schizophrenia:Integration of performance-based and brain imaging findings[J].Psychological Bulletin,2007,133(5):833-858.