graph theory raises its ugly head

For the last couple of weeks I’ve been working not quite as hard as I should have on a graph-theoretic analysis of some resting-state fMRI data. Thanks to Brian Avants and ANTS, I’ve generated the following average connectome for default-mode and task-positive networks:

The key thing here is that connections between nodes of the same color are overwhelmingly red (positive correlations, significant across subjects) and connections between nodes of different colors are overwhelmingly blue (negative correlations). So the default-mode network and the task-positive network are correlated with themselves and anticorrelated with one another. This is not a shocking result (see link), but it’s fun to verify in my own data with new technology. There’s something attractive about a graph theory approach to functional connectivity that more sophisticated super-data-driven approaches like ICA just don’t have — maybe because people actually have some vague sense of how to think about and analyze graphs. (For “people,” you can probably substitute “Matt” with no particular loss of accuracy.)

Next: nonparametric approaches to edge analysis, visualization tweaks, and (most importantly) between-groups analysis of the effects of electrical brain stimulation on the connectome…

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One thought on “graph theory raises its ugly head

  1. Graph theory can be quite beautiful, it’s such a comparatively simple approach too. I think it helps that it’s so easy to visualise, compared to many other mathematical techniques.

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