fMRI-SPM原理与应用ppt课件

.,1,StatisticalParametricMapping,基本原理与使用,北京师范大学,认知神经科学与学习国家重点实验室,朱朝喆研究员,czzhu,.,2,fMRI研究框架,实验设计被试招募与扫描,科学问题结果解释,实验假设数据统计分析SPM,AFNI,FSL,VoxBo,.,3,SPM版本历史,TheforthcomingversionisSPM5ThecurrentversionisSPM2Previousversions,SPM2breleased21stNovember2002SPM99released25thJanuary2000SPM96released9thApril1997,http:/www.fil.ion.ucl.ac.uk/spm/,.,4,线性代数,统计理论,GLM模型,随机场模型,MR成像,信号处理,计算神经解剖学,神经科学,.,5,SPM数据分析基本流程,.,6,预处理部分,模型构建与,参数估计,常用工具与,参数设置,.,7,讲座提纲,SPMI:Preprocessing,SPMII:Single-subjectanalysesSPMIII:Groupanalyses,.,8,SPMI:预处理,.,Slicetiming(获取时间校正)Realignment-(头动校正)Normalisation-(空间标准化）Smoothing-(空间平滑),.,9,MRIvs.fMRI,neuralactivity,bloodoxygen,fMRIsignal,MRI,fMRI,oneimage,highresolution(1mm),lowresolution(3mmbutcanbebetter),fMRIBloodOxygenationLevelDependent(BOLD)signalindirectmeasureofneuralactivity,manyimages(e.g.,every2secfor5mins),.,10,预处理SliceTiming-SPM,选择参考slice拉齐其它slice,.,11,预处理Realign（头动校正）,不同scan之间像素对应关系遭到破坏。血液动力学响应被头动引起的信号淹没。,.,12,预处理Realign（头动校正）,刚体变换六个头动参数估计:,3个方向的平移(mm)3个轴向的旋转,.,13,预处理Realign-SPM,将同一被试不同采样时间点上的3D脑对齐,.,14,空间标准化问题,.,15,空间标准化问题,个体大脑在形状、大小等方面存在明显差异，我们如何进行不同人之间的比较呢？,使不同被试脑图像中的同一像素代,表相同的解剖位置,一个标准脑空间,.,16,标准脑空间-Talairach坐标系,Source:BrainVoyagercourseslides,Talairach&Tournoux,1988,squishorstretchbraininto“shoebox”extract3Dcoordinate(x,y,z)foreachactivationfocus,.,17,使不同被试脑图像中的同一像素,代表相同的解剖位置,粗配准仿射变换,精配准非线性变换,.,18,Why,使不同被试脑图像中的同一像素代表相同的解剖位置一个公共的标准空间,How,先使用简单的线性变换进行粗配准再用复杂的非线性变换精配准,Problems,计算复杂度（高精度算法配准一个脑需要几个小时）个体之间的脑并非一一映射关系不可能有完全准确的配准,Solutions,对空间标准化后的脑图像进行适当的平滑使用变形场信息,预处理空间标准化小结,.,19,预处理空间标准化-SPM,使不同被试脑图像中的同一像素代表相同的解剖位置,将每个个体脑放入一个公共的标准空间,.,20,Template,NormalisedImage,预处理空间标准化结果,.,21,空间平滑的问题使残差项更符合高斯分布假设,减少标准化后剩余的个体间差异提高信噪比,5,-50,.,22,预处理空间平滑-SPM,.,23,SPM预处理部分小结,.,Slicetiming(adjusttimedifferenceamongdifferentslice)Realignment-(adjustformovementbetweenslices)Normalisation-(warpfunctionaldataintotemplatespace)Smoothing-(toincreasesignaltonoiseratio),.,24,LectureOutline,SPMI:Preprocessing,SPMII:Single-subjectanalysesSPMIII:Groupanalyses,.,25,Single-subjectAnalyses,基本过程与原理,GLM,PrincipleofGLMDesignMatrix,SolutiontoGLM,EffectofInterestandstatistics,.,26,个体水平分析的基本过程与目的,实验设计,个体扫描,个体激活区,检测,SpatialMemoryCondition500msec200msec3000msecTime1500msec500msec3000msec200msecSpatialControlCondition1500msec对这个被试，你感兴趣的effect在那些脑区出现，其强度如何？,.,27,Single-subjectAnalyses,基本过程与原理,GLM,PrincipleofGLMDesignMatrix,SolutiontoGLM,EffectofInterest&Statistics,Example,.,28,Single-subjectAnalyses,基本过程与原理,GLM,PrincipleofGLMDesignMatrix,SolutiontoGLM,EffectofInterest&Statistics,Example,.,29,InMatrixForm,GLM的数学表示,1:l,:,:,:,:,:,:,YJ,xJ1,xJl,xJL,L,J,X,Y=观测数据,设计矩阵,参数,+残差,x1l,x1L,1恐惧,Y1:,x11:,Yj,=xj11+.+xjll+.+xjLL+j,:Y1x11x1l:YJ:x:Yj=xj1xjl,J1,x1L:xJlxjL,1:xJL+j,J,Y,Y,.,30,Single-subjectAnalyses,基本过程与原理,GLM,PrincipleofGLMDesignMatrix,SolutiontoGLM,EffectofInterest&Statistics,Example,.,31,Time,Time,GLM：设计矩阵X,X2,X1,Y=X+SPMrepresentstimeasgoingdownSPMrepresentspredictorswithinthedesignmatrixasgrayscaleplots(whereblack=low,white=high)overtimeSPMincludesaconstanttotakecareoftheaverageactivationlevelthroughouteachrun,X,Intensity,Y,.,32,G(刺激因素）,DesignmatrixX,G1,H(干扰因素),H1,Globalactivity:E.g.head,motionparameters,Hc,Lineartrends,Gc,stimulus,GLM：设计矩阵X的结构,.,33,血氧系统对单次刺激的响应,.,34,刺激序列,HRF,设计矩阵中的刺激因素X,.,35,G(stimulating),DesignmatrixX,G1,H(non-interesting),H1,E.g.(1)headmotionparameters(2)breathing(3)heartbeat,Hc,Lineartrends,duetoMRIscannerGlobalactivity:,Gc,stimulus,GLM：设计矩阵X的结构,.,36,为什么要考虑这些干扰因素？,LinearTrend,Probable,Respiration,Artifact,headmotionparameters,Effect/Error,.,37,Single-subjectAnalyses,基本过程与原理,GLM,PrincipleofGLMDesignMatrix,SolutiontoGLM,EffectofInterestandstatistics,.,38,0,100,-10,+10,0,12,-0.01,+0.01,=,+,*,5+,Y,=,X1*1+,Xn*,+e,*50,FittingXtoYgivesyouone(parameterestimate)foreachcolumnofX,aande.BetasprovideinformationaboutfitofregressorXtodata,Y,ineachvoxel,.,39,GLM求解的几何表示：勾股定理,E,用X线性组合Y近似表达Y,.,40,Single-subjectAnalyses,基本过程与原理,GLM,PrincipleofGLMDesignMatrix,SolutiontoGLM,EffectofInterest&statistics,多重比较,Example,.,41,构造Contrast对感兴趣的解释变量进行比较,X2,X1,Y=,X+,=1X1+2X2+3X3+NXN+X1X2X3XN123NT检验：构造Contrast向量F检验：构造Contrast矩阵实验设计=感兴趣effect=contrast,所以contrast在数据采集之前就定下了！,.,42,本质Effects解释空间Xscontrast向量,1-1,x1x2,Ex1x2(x1x2),.,43,Single-subjectAnalyses,基本过程与原理,GLM,PrincipleofGLMDesignMatrix,SolutiontoGLM,EffectofInterest&statisticsMultipleComparisons,.,44,Time,Y=,X+,Intensity,Y,Preprocessing.,TheProblemofMultiple,Comparisons,TToPo=0.01,.,45,200activated,噪声脑的“激活”P=0.01,20,000voxs噪声脑,.,46,怎么办？,200activated,2activated,200activated5activated,.,47,200activated,200activated,Uncorrectedp=0.01我在进行探索性研究！,探索性研究,.,48,Bonferronicorrection最严格的校正,200activated,2activated,onevoxelTypeIerrorp=？numberofvoxels：N=50,000overallcorrectdetection=(1-p)(1-p)(1-p)=(1-p)NoverallTypeIerror=1-(1-p)N=NpDesiredoverallTypeIerror：Np=.05RequiredonevoxelTypeIerrorp=.05/50,000=.000001,.,49,BonferroniCorrection的思想及其在,fMRI数据分析中的问题,Bonferroni校正的假设,pvoxel=poverall/NN为独立观测个数,相邻体元的BOLD信号会相互独立的吗？,头动等噪声对同一脑区的影响很相似BOLD信号本身就对应着一定空间范围预处理中的平滑,.,50,SPM中的多重比较校正的原理,根据数据的空间相关程度计算独立观测个,数（独立比较的次数Nindepentent）,根据整体虚警概率poverall和Nindepentent得到单个体元的pvoxel值,pvoxel=poverall/Nindepentent,.,51,SPM个体激活区检测基本过程,.,52,个体水平effect计算的SPM实现（个体激活区检测）,模型定义,DesignMatrixSpecification,数据定义参数估计,DataSpecificationParameterEstimation,统计结果Result,.,53,参数估计,常用工具与参数设置,预处理部分First-level模型构建与,Second-level,.,54,LectureOutline,SPMI:Intro,PreprocessingSPMII:Single-subjectanalysesSPMIII:Groupanalyses,.,55,Howdowecompareacrosssubjects?,建立不同人之间的可比性,NormalizationROI,多个被试的统计分析,Fixed-effectsModel,Random-effectsModel,.,56,Fixed-effectsModel,Assumethattheexperimentalmanipulationhassameeffectineachsubject,Usesdatafromallsubjectstoconstructstatisticaltest,Averaging/connectingacrosssubjectsbeforeat-test,Sensitivetoextremeresultsfromindividualsubject,strongeffectinonesubjectcanleadtosignificanceevenwhenothersshowweakornoeffects,Allowsinferencetosubjectsample,youcansaythateffectwassignificantinyourgroupofsubjectsbutcannotgeneralizetoothersubjectsthatyoudidnttest,Howabout,thepopulation?,.,57,Randomeffectanalysis,AssumesthateffectvariesacrossthepopulationAccountsforinter-subjectvarianceinanalyses,Allowsinferencestopopulationfromwhichsubjectsaredrawn,EspeciallyimportantforgroupcomparisonsRequiredbymanyreviewers/journals,.,58,SPM双层统计,First-level：个体水平effect计算,Second-level：群体水平effect计算,.,59,SPM个体激活区检测基本过程,.,60,Fixed-&Random-effectsModel,小结,Fixed-effectsModel,Assumesthateffectisconstant(“fixed”)inthepo