Deconvolution Analysis of FMRI Time Series Data - Waisman ...

whereZ =2643Z pZ p+1.Z N;1.7. 5Z 3N;1Z N+pZ N+p+1Z 2N;1Z 2N+pZ 2N+p+1 X =26431 p 0 0 0 0 f p f 01 p +1 0 0 0 0 f p+1 f 1. . . . . . . . .1 N ; 1 0 0 0 0 f N;1 f N;p;10 0 1 p 0 0 f N+p f N0 0 1 p +1 0 0 f N+p+1 f N+1. . . . . . . . .0 0 1 N ; 1 0 0 f 2N;1 f 2N;p;10 0 0 0 1 p f 2N+p f 2N0 0 0 0 1 p +1 f 2N+p+1 . f 2N+17. . . . . . . . . 50 0 0 0 1 N ; 1 f 3N;1 f 3N;p;1 T = 10 11 20 21 30 31 h 0 h p:Implementation: Program 3dDeconvolve allows the user to enter the name of a lewhich simply contains a short (column) listing of the volume indices for the starting pointof each concatenated run. All other details are handled internally. (See the descriptionof the -concat option in Section 1.3, and the Examples in Section 1.4.6.)1.2.13 Censoring of Individual Time PointsOccasionally, a user may wish to remove one or more time points from the analysis (e.g.,wild points due to large measurement noise). In AFNI m / 3dm+, this is accomplishedby placing \99999" at each time point in the ideal time series that is to be excluded.A similar approach would not work for program 3dDeconvolve, due to the time-laggeddependence on the stimulus functions. Therefore, a separate \censor" le can now beusedto indicate which data points are to be excluded from the analysis, without eecting thetemporal representation of the input stim functions. The censor le consists of a columnof all 1's, except for 0's at those time points to be censored. (See the description of the-censor option in Section 1.3, and the Examples in Section 1.4.7)1.2.14 Time Related IssuesAs described in Section 1.2.3, for the deconvolution analysis, the time axis is quantized insteps of TR. This is reasonable, since the measured data is acquired at intervalsof1TRforeach voxel. However, dierent slices in the imaging volume are usually acquired at dierentrelative times. In order to accurately compare IRF's across slices, either graphically, orby the use of program 3dStatClust, it is necessary to take account of the dierent sliceacquisition times.Consider again the discrete time convolution equation:y(nt) =nXm=0f(mt)h(nt ; mt)t:18