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Implement Average Headmodel #2

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neurofractal opened this issue Apr 25, 2018 · 2 comments
Open

Implement Average Headmodel #2

neurofractal opened this issue Apr 25, 2018 · 2 comments
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enhancement New feature or request test

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" The averaged rank pseudo MRI [PSM(AR,n), PHM(AR,n, Equation 6] was the average of first n rank pseudo MRIs [PSMi,rank=1 to n and PHMi, rank=1 to n, models are in the head coordinate system (BTi coordinate) after the ICP registration process] for a given subject. An averaged sourcemodel was directly computed by taking the centroid of the particular source grid point location (r) of first n rank pseudo sourcemodels (Equation 6a)."

Gohel et al., (2017)

Therefore need to load pre-computed headmodel and average (?) over first n iterations
@neurofractal neurofractal self-assigned this Apr 25, 2018
@neurofractal neurofractal added the enhancement New feature or request label Apr 25, 2018
neurofractal added a commit that referenced this issue Oct 30, 2018
@neurofractal
Average Sourcemodel - Try 2
3c184b7 
Addresses #2

- Averages the headmodel and sourcemodel over the best 20 fitting MRIs
(ie. least error)
- Seems to work.. visual gamma is localised correctly
- Can we ‘average’ over the meshes for visualisation purposes?
- Could be make it less computationally demanding?
- Is 20 the optimal number (as according to Gohel et al, 2017 paper)
- Obviously we can’t produce a warped ‘average’ MRI.. Is there are way
around this? Could we ‘average’ the transform matrices? IDK..
@neurofractal
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We probably need to test whether n=20 averages is the optimal (like for Gohel et al., 2017)

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neurofractal commented Dec 5, 2018 •
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Works well... but needs more testing

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