Hi Dillan - There's a work-around for this, see the reinit variable at the
bottom of the sample config file:
http://surfer.nmr.mgh.harvard.edu/fswiki/dmrirc
I'm hoping to make this happen automatically soon!
Best,
a.y
On Tue, 23 Aug 2016, Newbold, Dillan wrote:
Dear Anastasia,
I’ve been looking at a lot of Tracula path.pd files and I’ve found that some
probability distributions are only a single voxel wide, similar to the path.map
file. The few none-zero voxels in these path.pd files have very high
probability values. When an isosurface is generated for these tracts, it looks
like a short thin blob somewhere in the usual tract distribution. I’ve seen
descriptions in the archives of similar “short thin tracts,” but, from what I
have seen, no one has offered a satisfying explanation for why these occur.
What I think is happening in these tracts is that a maximum-probability (or
local maximum) path is found during a burn-in iteration and all following
perturbations of that path are rejected. Since the probability value in the
path.pd is equal to the number of sample paths intersecting that voxel, finding
a local maximum early on results in a small number of very high-probability
voxels. Consistent with this explanation, I’ve found that this issue occurs
more frequently when nburnin is set to 1000 (default = 200). A similar issue
can occur if a local maximum is found early during the sample iterations, and
this results in a path.pd file containing a small number of voxels with very
high values surrounded by a larger area of low-value voxels. When a 20%
threshold is applied, the result is the same as when a local maximum occurs
during a burn-in iteration.
Does my understanding of this issue seem correct?
None of this would be a problem if my only aim were to find the single path
with the maximum a posteriori probability, but I’m concerned that the average
and weighted_average sats for these tracts will be less accurate. Since these
distributions include small fractions of the number of voxels included in most
tract distributions, is it likely that the average and weighted_average stats
from these narrow distributions are less representative of the whole tract and
more subject to random noise?
Given these concerns, what type of overall path statistics do you think is most
descriptive of a tract? Also, do you feel that higher nburnin and nsample
values should lead to superior results? I would have thought this to be the
case, but now it seems to me that setting either of these values too high will
result in narrow probability distributions and bad statistics.
Thank you,
Dillan
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