Global diversity in individualized cortical network topography

Area of Science:

• Neuroscience
• Human Brain Imaging
• Population Neuroscience

Background:

• Individualized cortical network topography (ICNT) shows significant variation, particularly in association networks.
• Previous ICNT research primarily focused on Western populations, leaving the influence of non-Western populations understudied.

Purpose of the Study:

• To investigate how ICNT differs between White American and Han Chinese populations.
• To determine if ethnicity-related ICNT variations can be used for ethnicity identification.
• To explore the relationship between ethnic ICNT diversity and cortical organization properties.

Main Methods:

• Utilized a multisession hierarchical Bayesian model to define individualized functional networks.
• Analyzed data from White American and Han Chinese participants in the Human Connectome Project.
• Employed support vector machine and generalized additive models for classification and validation.

Main Results:

• Significant differences in the size and spatial topography of individualized functional networks were observed between White American and Han Chinese groups, especially in heteromodal association cortex.
• Ethnicity was identified with 74% accuracy using ICNT, with heteromodal networks being key predictors.
• Spatial heterogeneity in ICNT ethnic diversity correlated with evolutionary expansion, myelination, and cerebral blood flow.

Conclusions:

• ICNT exhibits ethnic variations, particularly in heteromodal association networks.
• ICNT diversity can serve as a biomarker for ethnicity.
• Findings emphasize the critical need for more diverse global neuroimaging datasets for comprehensive brain research.