基于SPM2动态因果模型操作练习课件.ppt

1、Dynamic Causal Modeling(DCM)A Practical PerspectiveOllie HulmeBarrie RoulstonZeki labDisclaimer The following speakers have never used DCM.Any impression of expertise or experience is entirely accidental.Structure 1.Quick recap on what DCM can do for you.2.What to think about when designing a DCM ex

2、periment 3.How to do DCM.What buttons to press etc.A Re-cap for DummiesYou can ask different types of questions about brain processing.Questions of WhereQuestions of HowFunctional Specialization is a question of Where?Where in the brain is a certain cognitive/perceptual attribute processed?What are

3、the Regionally specific effectsyour normal SPM analysis(GLM)Functional Integration is a question of HOWExperimentally designed inputHow does the system work?MODEL-FREEMODEL-DEPENDENTHypothesis drivenDCM!Functional connectivityEffective connectivity2 Categories of Functional integration analysisPPI D

4、CM overviewDCM allows you model brain activity at the neuronal level(which is not directly accessible in fMRI)taking into account the anatomical architecture of the system and the interactions within that architecture under different conditions of stimulus input and context.The modelled neuronal dyn

5、amics(z)are transformed into area-specific BOLD signals(y)by a hemodynamic forward model().The aim of DCM is to estimate parameters at the neuronal level so that the modelled BOLD signals are most similar to the experimentally measured BOLD signals.Planning a DCM-compatible study Experimental design

6、:preferably multi-factorial(e.g.at least 2 x 2)StaticMovingNo attentAttent.1.Sensory input factor At least one factor that varies the sensory input changing the stimulus a perturbationto the system 2.Contextual factor At least one factor that varies the context in which the perturbation occurs.Often

7、 attentional factor,or change in cognitive set etc.Planning a DCM-compatible studyTR should be as short as possible parameter b,One-sample t-test:parameter a 0 rmANOVA (in case of multiple sessions per subject)3.Ensure that the model you generate is able to test yourhypothesesThe model should incorp

8、orate every component of the hypothesisParietal areasV5Direct influenceV1PulvinarIndirect influenceDCM cannot distinguish between direct and indirect!Hypotheses of this nature cannot be tested4.Evaluate whether DCM can answer your questionCan DCM distinguish between your hypotheses?In case of1.Speci

9、fy your main hypothesis and its competing hypotheses as precisely as possible using convergent evidence from the empirical and theoretical literature2.Think specifically about how your experiment will test the hypothesis and whether the hypothesis is suitable for DCM to test.3.Klaas emphasises that

10、you should Test your model before conducting the experiment using synthetic data.Simulation is the key!4.DCM is tricky,ask the experts during the design stage.They are very helpful.A DCM in 5 easy steps1.Specify the design matrix2.Define the VOIs3.Enter your chosen model4.Look at the results5.Compar

11、e models Specify design matrixNormal SPM regressors-no motion,no attention-motion,no attention-no motion,attention-motion,attention DCM analysis regressors-no motion(photic)-motion-attention Defining VOIs Single subject:choose co-ordinates from appropriate contrast.e.g.V5 from motion vs.no motion RF

12、X:DCM performed at 1st level,but define group maximum for area of interest,then in single subject find nearest local maximum to this using the same contrast and a liberal threshold(e.g.P0.05,uncorrected).DCM button specifyNB:in order!Can select:-effects of each condition-intrinsic connections-contra

13、st of connections OutputLatent(intrinsic)connectivity(A)Modulation of connections(B)PhoticAttentionMotionInput(C)Comparing modelsSee what model best explains the data,e.g.Original ModelAttention modulates V1 to V5Alternative ModelAttention modulates V5?DCM button compareThe read-out in MatLab indicates which model is most likely