fMRI signal + - Neurometrika

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Lecture 1Optimizing Data AcquisitionThis is the attempt to get the best quality images that you canfrom your scanner, subject, and experiment.
Lecture 2Preprocessing: RealignmentPrimarily, this is to compensate, on a global level, for the factthat living subjects move. It is “realigning” images withsimilarly collected images---images like themselves.
Page 3 and 4: NMRData AnalysisPracticalitiesMRIPs
Page 5: Overview of SPMImagetime-seriesSpat
Page 9 and 10: Lecture 2Preprocessing: Spatial Nor
Page 11 and 12: Overview of SPMImagetime-seriesSpat
Page 13 and 14: Lecture 4Modeling for Second Level
Page 16 and 17: View 1:A series of volumes(scans, 3
Page 18 and 19: From Experimental Timing to Expecte
Page 20 and 21: The General Linear Model (GLM)β 0
Page 22 and 23: The General Linear Model (GLM)estim
Page 24 and 25: Time= + + +fMRI signal= datadesign
Page 26 and 27: ⊗
Page 28 and 29: Stimulus timing convolved with the
Page 30 and 31: The General Linear Model (GLM)
Page 32 and 33: The GLM in Matrix Notation
Page 34 and 35: Fitting a GLM
Page 36 and 37: Observed fMRI signalPredicted fMRI
Page 38 and 39: Observed fMRI signalPredicted fMRI
Page 40: Functional MRI WorkshopsIntroductio

fMRI signal + - Neurometrika

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