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>SPM divides each TR into a finite number of timebins (that number >being fMRI_T). This creates a "high-resolution" timespace (a vector >with fMRI_T * N elements, where N is the number of scans). So >when the user enters onsets in fractions of scans, SPM creates >a delta function (in an event-related experiment) in the bin nearest >to each onset (ie, the onsets are rounded to the nearest bin). >The convolution with the basis functions is then performed this >highresolution space, before being downsampled again to create >a value for each scan (row) in the design matrix. The specific bin >that is chosen as the sample point is that given by fMRI_T0. Hi dear SPMers, I was wondering how SPM does this: "...downsampled again to create a value for each scan (row) in the design matrix" Does SPM choose the value from the oversampled time course at each fMRI_T0 point and ignore the rest, or average all the point in that TR? Or it's some other way? If anyone can tell me or point me to some references, I'll very appreciate. Thanks in advance, Chun-Yu