Resting state networks from functional conductivity imaging

Motivation: Dynamic measurement of brain tissue conductivity with functional conductivity imaging (fCI) could potentially provide different information to BOLD resting state fMRI. Goal(s): To demonstrate the feasibility of constructing resting state networks using fCI. Approach: Resting state data were acquired from 10 participants scanned in two sessions (two fCI and fMRI scans at each session), and were analysed using Betti0 curves, ndPH test and group ICA. Results: Repeatable networks were constructed from fCI data and were significantly different from rsfMRI. These share some similarity to rsfMRI but involve more brain regions, including white matter. Impact: Tissue electrical conductivity time series can be used to construct robust network information that provides a different perspective to the more common BOLD rsfMRI.