You raise a good point. 

In practice, it seems that you should keep the uneven distribution of nodes. 
The reason is as follows: If you resample the nodes to a more sparse uniform 
distribution, then you will distort the surface to some degree. The surface 
distortion will inevitable shift the center of gravity. I had thought about 
using the border points of a cluster to calculate the region; however, it seems 
that approach may unequally weight some parts of the cluster if there is an odd 
shape. It might be interesting to do a comparison between these methods.

In the end, it probably doesn't matter how you do the calculation for COG, as 
they should be similar, as long as the method is reported. I should also note, 
a recently accepted article: Cortical network for vibrotactile attention: A 
fMRI study in Human Brain Mapping describes the method and uses the traditional 
method; so there is an established standard that one could rely on and cite in 
future work.

Best Regards, Donald McLaren
D.G. McLaren
University of Wisconsin - Madison
Neuroscience Training Program
Tel: (773) 406 2464
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----- Original Message -----
From: Mateus Joffily <[EMAIL PROTECTED]>
Date: Friday, January 26, 2007 12:12 pm
Subject: [caret-users] ROI center of gravity
To: "Caret, SureFit, and SuMS software users" <>

> Hi,
> I would like to calculate the center of gravity (COG) of a surface 
> ROI. 
> I see that 'Surface Region of Interest':'Statistical Report' gives me 
> that information. However, if the nodes distribution over the surface 
> is 
> not uniform, the COG is biased toward the more dense regions.
> I understand that, if someone wants to calculate the COG, taking into 
> account the nodes-density, this is the right calculation. But, if I 
> suppose that the surface density is uniform, is there a way of 
> calculating the COG avoiding the nodes distribution effect?
> Thanks,
> Mateus
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> caret-users mailing list

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