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Hi Kevin,

I've looked at the data and ... I don't understand them. :) Especially, could you describe what these columns are? Are these correlated activities of different brain regions? If so, then I guess the heading of a column encodes the two areas, i.e. LR_TG_mul1_LR_EC = LR_TG + LR_EC. If this is still right, then you have a matrix per subject stored in a line. And what do you want to do with the lines, aggregate them by summing them up for each column?

Feel free to start a non-list email for details.

Best,

Jürgen

 

 

From: Social Networks Discussion Forum [mailto:[log in to unmask]] On Behalf Of Kevin Bickart
Sent: Thursday, January 14, 2016 11:12 PM
To: [log in to unmask]
Subject: [SOCNET] resting-state brain networks

 

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Hi all,

 

I'm a neuroscientist studying genetic drivers and behavioral targets of resting-state brain networks. I'm looking for help computing network parameters from resting-state functional connectivity MRI data, with the aim of using those parameters as variables in regression analyses with gene and behavior data.

 

Currently I have correlation matrices containing a row for every subject with columns of node-to-node correlation values, or strength of functional connectivity, representing weighted edges (see link). I would like to use this file to visualize and compute such parameters as degree, density, betweenness centrality, closeness, etc. Could anyone help me transform such a file into one usable for Gephi or another program to visualize and compute network properties for multiple subjects in one step or relatively efficiently? Alternative strategies/ideas also also welcome.

Thanks so much in advance. 

Best,


--
Kevin Bickart, MD/PhD
Anatomy & Neurobiology
Medicine intern, CPMC 2015-16
Neurology resident, Stanford 2016-19

 

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