[caret-users] ROI definition by connection distance

[Leon Deouell]

Interesting. What would you need it for? Do you want to weight the
correlation between voxels by the their axon distance? Maybe we can recruit
a student who wants to do a project and has programming skills to do this?

 

----------------------------------------------------

Dr. Leon Y Deouell, MD, PhD

Department of Psychology

The Hebrew University of Jerusalem

Jerusalem 91905

Israel

Tel: +972-2-5881739

Fax: +972-2-5825659

 http://pissaro.soc.huji.ac.il/~leon/Lab



  _____  

From: caret-users-bounces at brainvis.wustl.edu
[mailto:caret-users-bounces at brainvis.wustl.edu] On Behalf Of Alon Keren
Sent: Wednesday, July 11, 2007 5:57 PM
To: caret-users at brainvis.wustl.edu
Subject: [caret-users] ROI definition by connection distance

 

Hi.

 

I have been using CARET a lot lately, and found it very powerful and useful
for a variety of applications. There is a feature that I am interested in,
and I think is not available at the moment. I am interested in a
sophisticated measure of distance between nodes: 

The "real" distance, or functional or connection distance between two nodes
is neither euclidean nor geodesic. Two nodes on opposite walls of a sulcus
are further away in the connectivity sense then two nodes on opposite walls
of a gyrus, with white matter bridging the gap. In the first case a geodesic
measure is suitable, whereas in the second an euclidean measure is more
adequate. I imagine it is much more complicated to implement, but a measure
of distance that goes around CSF but cuts through WM would be very useful
and more accurate for functional purposes. For instance I would like to
estimate the relationship between this functional distance and co-activation
of nodes. 

 

A question on the same topic:

Is there an automatic way to produce a matrix of node to node geodesic
distances (of size #ofNodes^2)?

 

Thanks,

Alon.

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