| Autor: |
Nusbaum F; Health Systemic Process (P2S), UR 4129, Université Claude Bernard-Lyon 1, Université de Lyon, Lyon, France., Hannoun S; Medical Imaging Sciences Program, Division of Health Professions, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon., Barile B; CREATIS, CNRS UMR 5220, INSERM U1294, Université Claude Bernard-Lyon1, INSA-Lyon, Université de Lyon, Villeurbanne, France., Suprano I; CREATIS, CNRS UMR 5220, INSERM U1294, Université Claude Bernard-Lyon1, INSA-Lyon, Université de Lyon, Villeurbanne, France., Mouchet S; Service de Psychiatrie Légale - Pôle Santé Mentale des Détenus et Psychiatrie Légale, Centre Hospitalier le Vinatier, Bron, France., Sappey-Marinier D; CREATIS, CNRS UMR 5220, INSERM U1294, Université Claude Bernard-Lyon1, INSA-Lyon, Université de Lyon, Villeurbanne, France.; CERMEP-Imagerie du Vivant, Université de Lyon, Bron, France. |
| Abstrakt: |
Introduction: This study aims to use diffusion tensor imaging (DTI) in conjunction with brain graph techniques to define brain structural connectivity and investigate its association with personal income (PI) in individuals of various ages and intelligence quotients (IQ). Methods: MRI examinations were performed on 55 male subjects (mean age: 40.1 ± 9.4 years). Graph data and metrics were generated, and DTI images were analyzed using tract-based spatial statistics (TBSS). All subjects underwent the Wechsler Adult Intelligence Scale for a reliable estimation of the full-scale IQ (FSIQ), which includes verbal comprehension index, perceptual reasoning index, working memory index, and processing speed index. The performance score was defined as the monthly PI normalized by the age of the subject. Results: The analysis of global graph metrics showed that modularity correlated positively with performance score ( p = 0.003) and negatively with FSIQ ( p = 0.04) and processing speed index ( p = 0.005). No significant correlations were found between IQ indices and performance scores. Regional analysis of graph metrics showed modularity differences between right and left networks in sub-cortical ( p = 0.001) and frontal ( p = 0.044) networks. TBSS analysis showed greater axial and mean diffusivities in the high-performance group in correlation with their modular brain organization. Conclusion: This study showed that PI performance is strongly correlated with a modular organization of brain structural connectivity, which implies short and rapid networks, providing automatic and unconscious brain processing. Additionally, the lack of correlation between performance and IQ suggests a reduced role of academic reasoning skills in performance to the advantage of high uncertainty decision-making networks. |
