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Abstract #3154

Unbiased validation of connectivity-based cohesive brain parcellation

Ajay Nemani1 and Mark Lowe1
1Imaging Institute, Cleveland Clinic, Cleveland, OH, United States

Synopsis

Keywords: Functional Connectivity, fMRI (resting state), Parcellation, Cohesion, DCBC

Motivation: Cohesive parcellation provides optimal connectivity-based parcels for downstream brain modeling, but at the cost of high parcel count, making comparisons to traditional parcellations difficult.

Goal(s): We aim to fairly compare parcellations across a wide array of parcel sizes and counts.

Approach: rsfMRI of 18 healthy subjects were parcellated based on cohesion and evaluated with the distance-controlled boundary coefficient (DCBC), an unbiased metric that incorporates spatial features of parcels in addition to connectivity.

Results: Cohesive parcellation compared favorably to traditional parcellations based on DCBC of rsfMRI.

Impact: Using an unbiased metric (DCBC), we show that the utility of connectivity-based cohesive parcellation is not simply due to high parcel count.

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