Groupwise Structural Parcellation of the Cortex: A Sound Approach Based on Logistic Models

TL;DR

This paper introduces a new, efficient method for groupwise cortical parcellation based on a parsimonious model of extrinsic connectivity, aligning well with known structural and functional brain maps.

Contribution

The authors propose a novel, computationally efficient clustering approach using a logistic model for extrinsic connectivity to achieve accurate groupwise cortical parcellation.

Findings

Parcellations agree with existing structural and functional maps.

Motor and sensory cortex are subdivided consistent with Penfield's homunculus.

Method aligns with Human Connectome Project data.

Abstract

Current theories hold that brain function is highly related to long-range physical connections through axonal bundles, namely extrinsic connectiv-ity. However, obtaining a groupwise cortical parcellation based on extrinsic connectivity remains challenging. Current parcellation methods are compu-tationally expensive; need tuning of several parameters or rely on ad-hoc constraints. Furthermore, none of these methods present a model for the cortical extrinsic connectivity of the cortex. To tackle these problems, we propose a parsimonious model for the extrinsic connectivity and an efficient parceling technique based on clustering of tractograms. Our technique allows the creation of single subject and groupwise parcellations of the whole cortex. The parcellations obtained with our technique are in agreement with structural and functional parcellations in the literature. In particular, the motor and sensory cortex are subdivided in agreement with the human ho-munculus of Penfield. We illustrate this by comparing our resulting parcels with the motor strip mapping included in the Human Connectome Project data.