Dear SPMers,
I'm trying to model event-related activity that is due to two
stimuli presented sequentially with an SOA of 1.5 seconds. In looking at
the raw data, the hemodynamic response to such an event often has a wider
peak than does the typical HRF for a single event. I'm wondering whether
modelling the data using a dispersion derivative (i.e., hrf + time +
dispersion derivatives) will enable SPM to fit a canonical hrf to the
data that has the appropriate width. In other words, does the dispersion
derivative allow the width of the of the canonical HRF to be adjusted
analagous to the way that the temporal derivative allows the onset of the
canonical response to be adjusted?
Many Thanks,
Daniel Weissman
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