MarsAtlas: A cortical parcellation atlas for functional mapping

Area of Science:

• Neuroimaging
• Computational Neuroscience
• Anatomical Atlasing

Background:

• Developing anatomical brain atlases is crucial for analyzing functional neuroimaging data.
• Existing atlases may not optimally capture functional network organization.

Purpose of the Study:

• To present and validate MarsAtlas, a novel cortical parcellation model based on macroanatomy.
• To assess MarsAtlas's utility in mapping visuomotor functional networks using MEG data.

Main Methods:

• Utilized the HIP-HOP cortical parameterization method to create an orthogonal coordinate system based on sulci.
• Developed MarsAtlas, a parcellation scheme aligned with anatomical landmarks and directional fields.
• Analyzed magnetoencephalography (MEG) data from a visuomotor task, estimating high-gamma activity (HGA).

Main Results:

• Both MarsAtlas and Talairach atlases identified increased HGA in sensorimotor, fronto-parietal, and medial prefrontal areas during visuomotor tasks.
• MarsAtlas provided enhanced functional insights along dorsolateral and rostrocaudal axes.
• MarsAtlas demonstrated an increase in statistical significance compared to the Talairach atlas.

Conclusions:

• MarsAtlas is a valid anatomical atlas for functional mapping of the human cortex.
• MarsAtlas offers a potential framework for integrating functional data from diverse neuroimaging techniques (MEG, intracranial EEG, fMRI).