Hey Catherine -
Which filtering are you referring to? The high pass filtering in FEAT
is performed by a running lines smoother - a Gaussian-weighted
least-squares straight line fitting (uses a straight line fit through
nearby voxels to estimate trend - see A New Statistical Approach to
Detecting Significant Activation in Functional MRI - Jonathan L.
Marchini and Brian D. Ripley). This nonlinear approach is not greatly
affected by end effects, so no mirroring is used, as I understand it.
All the best,
Eugene
--
Centre for Functional MRI of the Brain (FMRIB) | University of Oxford
John Radcliffe Hospital | Headington
OX3 9DU | Oxford | UK
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On 12 October 2010 03:52, Catherine Davey <[log in to unmask]> wrote:
>
> Hi, I just wondered if the FSL filter implementation uses the reflection method, in which an initial portion of the time series is reflected (as a mirror image) around time point zero (and then repeated at the end of the time series and filtered backwards), to avoid losing time points to initialisation (this is the method used by both the matlab filter function, and the spm spm_filter function)?
>
> If not, then how does FSL deal with initialising in IIR filter? and, can my filter theoretical require as many coefficients as the number of time points I have?
>
> I hope this makes sense!
> Cheers,
> Catherine
>
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