[Neuroimaging] Effects of motion outliers on HRF model (in sparse acquisition fMRI)

[Satrajit Ghosh]

hi chris,

the outliers are taken into account at the estimation stage. one column for
each volume discarded, not convolved with a canonical hrf.

cheers,

satra

On Fri, Dec 11, 2015 at 3:44 PM, Christopher J Markiewicz <effigies at bu.edu>
wrote:

> On 12/11/2015 03:05 PM, Satrajit Ghosh wrote:
> > hi chris,
> >
> > this is a standard sparse design and you can use the sparse model in
> > nipype to get at events and amplitudes that you feed into standard
> > SPM/FSL designers. the key is to not use a canonical HRF in the modeling
> > stage.
>
> Thanks Satra. Looking at the SpecifySparseModel code, it looks like
> motion outliers are not taken into consideration at estimation time, so
> I'm inferring that these pipelines also don't worry about
> artifact-induced issues at this stage.
>
> That's fine. I just want to make sure that there isn't a standard (or
> emerging consensus) step that we're skipping.
>
> > we have a standard openfmri (not BIDS yet) sparse script that can do the
> > entire preprocessing and estimation on such data and would be happy to
> > share.
>
> That would be great, at the very least to validate that our approach
> hasn't been giving us wildly different results.
>
> <snip>
>
> Thanks,
> --
> Christopher J Markiewicz
> Ph.D. Candidate, Quantitative Neuroscience Laboratory
> Boston University
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