Groupwise structural parcellation of the whole cortex: A logistic random effects model based approach

Area of Science:

• Neuroscience
• Computational Biology
• Brain Imaging Analysis

Background:

• Brain function is linked to long-range physical connections (extrinsic connectivity) via axonal bundles.
• Existing groupwise cortical parcellation methods based on extrinsic connectivity are computationally intensive and require parameter tuning or constraints.
• A comprehensive model for cortical extrinsic connectivity is lacking.

Purpose of the Study:

• To develop a parsimonious model for cortical extrinsic connectivity.
• To introduce an efficient parceling technique for creating single-subject and groupwise cortical parcellations.
• To validate the parcellations against existing structural and functional data.

Main Methods:

• Proposed a parsimonious model for extrinsic connectivity.
• Developed an efficient parceling technique based on clustering of tractograms.
• Compared resulting parcellations with structural/functional atlases and Human Connectome Project data.

Main Results:

• Successfully created single-subject and groupwise parcellations of the whole cortex.
• Parcellations demonstrated agreement with established structural and functional atlases.
• Motor and sensory cortex subdivisions accurately reflected the human homunculus and Human Connectome Project motor strip mapping.

Conclusions:

• The proposed technique offers an efficient and effective method for cortical parcellation based on extrinsic connectivity.
• The model and technique provide a valuable tool for neuroscience research, enabling more precise brain mapping.
• The findings support the link between extrinsic connectivity and functional brain organization.