Dear Vincent,
I was starting from the assumption that a Gaussian autocorrelation was
required. It may be that the smoothness estimate is robust to an
"anything-padded-with-zeros-multiplied-by-Gaussian" PSD. I don't have
first-hand experience of this case. Anyone else?
Oliver
> From [log in to unmask] Mon Oct 25 16:05:59 1999
> Date: Mon, 25 Oct 1999 17:17:21 +0200
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> Subject: Re: interpolation of raw data
> From: Vincent Denolin <[log in to unmask]>
> To: Oliver Josephs <[log in to unmask]>
> Cc: [log in to unmask]
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> Dear Oliver, dear SPM-ers,
>
> In "Detecting activations in PET and fMRI : levels of inference and power", Friston
> et al., Neuroimage 4 : 223-235 1995 it is stated that :
>
> "Usual estimates of smoothness fail when the reasonable lattice assumption is
> violated. In our work we side-step this issue by simply interpolating the data to
> reduce voxel size or smoothing the data to increase smoothness."
>
> Of course you cannot get additional information by interpolating the data, but I
> thought it was a good way to avoid the loss of spatial resolution which occurs when
> smoothing with a kernel of width 2-3 times the acquisition voxel size. With
> interpolated data it would be possible to reach the criterion "voxel size < FWHM",
> i.e. a sufficient smoothness for the lattice assumption to hold, with very little
> smoothing, i.e. nearly no loss in spatial resolution.
>
> Could you or anyone else comment this ?
>
> Thanks a lot,
>
> Vincent
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