Personal Income Performance Correlates with Brain Structural Network Modularity but Not Intelligence Quotient

Area of Science:

• Neuroscience
• Brain Imaging
• Graph Theory

Background:

• Brain structural connectivity is increasingly studied using diffusion tensor imaging (DTI) and graph theory.
• Understanding the neural basis of socioeconomic factors like personal income (PI) is crucial.

Purpose of the Study:

• To investigate the association between brain structural connectivity and personal income (PI) in adults.
• To explore the relationship between brain network organization, intelligence quotient (IQ), and PI performance.

Main Methods:

• Utilized diffusion tensor imaging (DTI) and tract-based spatial statistics (TBSS) on 55 male subjects.
• Applied brain graph techniques to analyze structural connectivity and generate graph metrics.
• Assessed full-scale IQ (FSIQ) using the Wechsler Adult Intelligence Scale and calculated PI performance score.

Main Results:

• Brain network modularity positively correlated with PI performance score (p=0.003) and negatively with FSIQ (p=0.04).
• No significant correlation was found between IQ indices and PI performance.
• TBSS revealed greater axial and mean diffusivities in high-performance groups, linked to modular brain organization.

Conclusions:

• Personal income performance is strongly associated with a modular brain structural connectivity, indicating efficient, rapid processing networks.
• The lack of correlation between performance and IQ suggests that decision-making networks, rather than academic reasoning, may be more influential in PI.
• Findings imply that specialized brain network organization, not general intelligence, may underpin financial success.