Description Usage Arguments Value Author(s) Examples
Input 4D time series matrix. (Perform slice timing correction externally). Estimate hemodynamicRF from block design. Compute brain mask on average bold image. Get nuisance variables : motion , compcor , globalsignal. High-frequency filter the time series ( externally ). Correct for autocorrelation using bullmore 1996 MRM and AR(2) model with parameters derived from global residual signal. Estimate final glm.
1 | activationBeta<-taskFMRI( fmriMatrix , blockDesign )
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fmriMatrix |
input matrix |
blockDesign |
input array |
c( betas ) is output
Avants BB
1 2 3 4 5 6 7 8 9 | # read the fmri image in and maybe do slice timing correction
# fmri<-antsImageRead( fn[2] , 4 )
# ImageMath(4,fmri,'SliceTimingCorrection',fmri,'bspline')
myvars<-getfMRInuisanceVariables( fmri, moreaccurate = TRUE , maskThresh=100 )
mat <- timeseries2matrix( fmri, mask )
mat <- filterfMRIforNetworkAnalysis( cbind(mat) , 2.5, cbfnetwork = "BOLD" , freqLo=0.001 , freqHi = 0.15 )$filteredTimeSeries
blockfing = c(0, 36, 72, 108,144)
hrf <- hemodynamicRF( scans=dim(fmri)[4] , onsets=blockfing , durations=rep( 12, length( blockfing ) ) , rt=2.5 )
activationBeta<-taskFMRI( fmriMatrix , hrf , myvars )
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