Subject-specific segregation of functional territories based on deep phenotyping

Area of Science:

• Neuroscience
• Cognitive Neuroscience
• Neuroimaging

Background:

• Functional magnetic resonance imaging (fMRI) traditionally analyzes group-average brain maps from single tasks.
• Recent efforts aim for systematic spatial representations of multiple mental functions.
• Individualized brain mapping requires high-resolution data and robust analytical methods.

Purpose of the Study:

• To investigate the feasibility of individual brain mapping using the high-resolution Individual Brain Charting (IBC) task-fMRI dataset.
• To validate the reproducibility of IBC brain maps against large-scale datasets.
• To assess the consistency and predictive power of spatial components across tasks and participants.

Main Methods:

• Utilized the Individual Brain Charting (IBC) dataset, a high-resolution task-fMRI dataset.
• Verified IBC brain map reproducibility with existing large-scale datasets.
• Inferred and mapped elementary spatial components across multiple tasks within and across participants.
• Employed contrast accumulation for fine functional characterization of brain regions.

Main Results:

• IBC brain maps successfully reproduced findings from previous large-scale datasets.
• Elementary spatial components showed consistent mapping within and across participants.
• Topographic information from individual contrast maps predicted contrasts from other tasks.
• Contrast accumulation enabled detailed functional characterization of the language network, generalizing across participants.

Conclusions:

• Individual brain mapping using task-fMRI is feasible and reliable.
• The IBC dataset supports consistent and predictive mapping of cognitive functions.
• This approach enhances the fine-grained functional characterization of brain regions and networks.