Mike,
In addition to Donna's helpful comments regarding mapping of regional
volume data to average fiducial surfaces, there are a couple of other
ways to adjust colors that might prove useful. One is the Attributes:
Metric: Convert Metric to RGB paint file option. Another is Surface:
ROI: Operations: Assign paint attributes to selected nodes.
Since this dialog now contains various items that may be of interest to
others, I am copying this to the caret-users list.
David
On Oct 26, 2005, at 11:08 AM, Donna Hanlon wrote:
Hi Mike,
If nothing else, you could make sure your visualization spec has the
appropriate average fiducial surface in it; load the spec file and
make sure that fiducial was selected; and use the Map to Caret vs the
Map to Caret with Atlas option. (In fact, if you think you'll almost
always be using AFM vs MFM, then there's no advantage to the Map to
Caret with Atlas over the Map to Caret option, assuming you have the
correct average fiducial loaded.) Just remember to save the resulting
metric/paint, since I believe the Map to Caret function doesn't
generate an output file; it just loads the mapping in memory as a
metric/paint column, but disappears if you exit Caret without saving
as a metric/paint.
If you go the paint route, the areacolor file (Attributes: Area Color,
http://brainmap.wustl.edu/caret/html/file_formats/
file_formats.html#areaColor) controls the color mapping. If you go the
metric route, the palette file
(http://brainmap.wustl.edu/caret/html/file_formats/
file_formats.html#paletteFile) controls the color mapping.
Donna
On 10/26/2005 10:57 AM, Mike Fox wrote:
Is there a way to map regional data to the average fiducial map? When
I map functional data I appear to have this option, but not when I
map regional data (with which AFM would be most useful).
Alternatively, If I map regional data as functional data (ie data
with discreet integer values) using AFM, is there a way to specify
the color of each region. I’m currently using this approach and plan
to try and change the colors of each region later using photoshop,
but I figure there must be a way to do it in caret.
Thanks,
Mike
Michael Fox
Laboratory of Dr. Marcus Raichle
Mallinckrodt Institute of Radiology
Washington University in St. Louis
Medical Scientist Training Program
(314) 747-3073
----------------------------------------------------------------------
--
*From:* David Van Essen [mailto:[EMAIL PROTECTED]
*Sent:* Friday, October 21, 2005 9:36 PM
*To:* Mike Fox
*Cc:* Donna Hanlon; David Van Essen
*Subject:* Re: visualization specs; MFM vs AFM
Mike,
On Oct 21, 2005, at 10:48 AM, Mike Fox wrote:
Dr. Van Essen,
Thanks for the spec files. I was having a tremendous amount of
difficulty finding them on sums without your links.
We are working to enhance our search capabilities, but obviously have
quite a ways to go on this.
The question I had concerned the validity of mapping to 12
individuals, then averaging those results, as compared to mapping
just once to the average anatomy of the 12 individuals (a new
function of caret). The two do not always give the same result,
and I was wondering if you felt one was superior to the other and
why. I know that volume space atlas registration has adopted the
second approach (ie data is warped to a single atlas which is the
average of multiple subjects anatomy), but this does not
necessarily make it superior.
For starters, it's useful to review what I said about this topic in
the Discussion of the PALS paper:
In order to interpret the results of MFM, it is important to consider
several underlying assumptions. Without access to the individual
structural and fMRI data in any given study, it is impossible to work
backwards from volume-averaged group data to determine what the
actual pattern would be in any individual. Hence, the activations
seen on any of the individual PALS-B12 surfaces do not reflect a
pattern in fact attributable to any of the actual fMRI subjects. Nor
do they necessarily reflect the pattern that would have arisen in the
12 subjects whose structural data contributed to the atlas if they
had been tested using the same fMRI paradigm. MFM does provide an
objective strategy for estimating both the region of most likely
activation and a plausible upper bound on the total extent of
activation. This constitutes an important advance over the common
current practice of mapping volume-averaged results onto a
single-subject atlas.
In many situations, it is appropriate to map group-average data using
both AFM and MFM. The two mapping methods yield similar but not
identical spatial patterns and are inherently complementary. AFM is
conceptually simpler and allows readout of values at each surface
node that correspond to a particular voxel value. MFM provides a more
objective assessment of the most likely spatial distribution on the
atlas surface.
-----
In short, I contend that MFM is a superior way to estimate the most
likely spatial location of regions likely to have been modulated in
any given paradigm. AFM can give significant biases in spatial
localization, depending on the nature and location of the data.
However, a price is paid in terms of relating the surface node values
in an MFM map to the voxel values in the volume. In some situations
that's pretty important, but in others it may be largely irrelevant.
These issues are truly complex, as they are intimately linked to the
nature of structural and functional variability and what is really
meant by corresponding locations in different individual hemispheres.
I hope this is helpful. If you have further comments, questions, or
discussion points, let me know.
David
