Longitudinal FBA: small absolute / large standard effect

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Hi Jeroen / Michele,

There’s a principal issue with FC that I think stems from a misunderstanding of the referenced text. Quoting @sgenc:

In order to build an unbiased longitudinal template, we selected 22 individuals (11 female) to first generate intra-subject templates. For each of these individuals, the time-point 1 and time-point 2 FOD maps were rigidly transformed to their midway space and subsequently averaged to generate an unbiased intra-subject template. The 22 intra-subject FOD templates were used as input for the population template generation step. Following generation of the population template, each individual’s FOD image was registered to this longitudinal template, …

Let’s enumerate this for clarity:

  1. Template generation:

    1. Select a subset of 22 individuals

    2. For each of these individuals:

      1. Perform rigid-body registration between two time points

      2. Compute mean of two time-points in midway space

    3. Use non-linear registration of results of 1.2.2 to produce template.

  2. Transformation of data to template:

    1. For every individual:

      1. For both time points:

        1. Perform non-linear registration of image to template

        2. Transform FOD data to template space

        3. Segment FODs into fixels in template space

        4. Compute FC for that time point based on results of 2.1.1.2-3.

While for a subset of of subjects, a rigid-body averaging of two time points is performed (1.2.2), this is done for template construction only. When it comes to producing quantitative data in template space (2.1.1.3-4), this is done independently per time point.

If you have utilised some other pipeline structure, where FC is derived from a composition of a within-subject transformation and then a transformation of a per-subject mean to the template, then yes, the difference in FC between the two time points will be driven entirely by any non-rigid component of the within-subject transformation. So if that’s what you’ve done, that’s almost certainly what’s leading to your suspiciously small values.

Side note: the raw FD values range between 0 and 1.81. The change scores of FD range between -0.1 and 0.1.

PS: Is it normal that for each person the minimum FD is 0 (as long as this is only the case for a few fixels each time)? Or is this something we should look into as well?

This is quite common. If, for any given template fixel, when establishing fixel correspondence for a particular subject, there does not exist a fixel in that subject whose orientation is within 45 degrees of the template fixel, then the value of FD for that subject in that fixel will be zero. I seem to recall this thread some years back being the first public reporting of such, but it’s been in the back of my head for a long time. I’m hoping that this effect can be mitigated in the future (:crossed_fingers: for 3.1.0), using a combination of reduced fixel segmentation thresholds, more sophisticated fixel correspondence, and fixel-wise regressors / subject exclusion. For now you could probably think about excluding from the analysis mask those fixels for which the number of subjects with FD=0 is too large.

Rob