fMRI signal + - Neurometrika

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The General Linear Model (GLM)β 0×X 0fMRI signal= β 1×X 1+++residualsTimeβ 2×X 2Timedesign matrixTime...The expected time courses are obtained byconvolving the condition “box-car” functions(red / green) with the assumed impulseresponse (HRF, two-gamma function).
The General Linear Model (GLM)Time= β 0× + β 1× + β 2× +TimefMRI signaldesign matrixresidualsThe time courses of the signal, predictors and residuals can be rearranged in column form with timerunning from top to bottom. This view is helpful to understand the matrix form of the General LinearModel.
Page 3 and 4: NMRData AnalysisPracticalitiesMRIPs
Page 5 and 6: Overview of SPMImagetime-seriesSpat
Page 7 and 8: Lecture 2Preprocessing: Realignment
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 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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