Linking Brain Biology to Intellectual Endowment: A Review on the Associations of Human Intelligence With Neuroimaging Data

Autor(es)

Dizaji, Aslan ^[1] ; Vieira, Bruno Hebling ^[2] ; Khodaei, Mohmmad Reza ^[1] ; Ashrafi, Mahnaz ^[1] ; Parham, Elahe ^[1] ; Hossein-Zadeh, Gholam Ali ^{[1, 3]} ; Garrido Salmon, Carlos Ernesto ^[2] ; Zadeh, Hamid Soltanian ^{[1, 3, 4]}

Afiliação do(s) autor(es)

^[1] Univ Tehran, Coll Engn, Control & Intelligent Proc Ctr Frrellence CIPCE, Sch Elect & Comp Engn, Tehran - Iran

^[2] Univ Sao Paulo, Dept Phys, Inbrain Lab, FFCLRP, Ribeirao Preto - Brazil

^[3] Inst Res Fundamental Sci IPM, Sch Cognit Sci, Tehran - Iran

^[4] Henry Ford Hlth Syst, Radiol Image Anal Lab, Detroit, MI - USA

• Tipo de documento: Artigo de Revisão
• Fonte: BASIC AND CLINICAL NEUROSCIENCE; v. 12, n. 1, p. 1-27, JAN-FEB 2021.
• Citações Web of Science: 0

Resumo

Human intelligence has always been a fascinating subject for scientists. Since the inception of Spearman's general intelligence in the early 1900s, there has been significant progress towards characterizing different aspects of intelligence and its relationship with structural and functional features of the brain. In recent years, the invention of sophisticated brain imaging devices using Diffusion-Weighted Imaging (DWI) and functional Magnetic Resonance Imaging (fMRI) has allowed researchers to test hypotheses about neural correlates of intelligence in humans. This review summarizes recent findings on the associations of human intelligence with neuroimaging data. To this end, first, we review the literature that has related brain morphometry to intelligence. Next, we elaborate on the applications of DWI and resting-state fMRI on the investigation of intelligence. Then, we provide a survey of literature that has used multimodal DWI-fMRI to shed light on intelligence. Finally, we discuss the state-of-the-art of individualized prediction of intelligence from neuroimaging data and point out future strategies. Future studies hold promising outcomes for machine learning-based predictive frameworks using neuroimaging features to estimate human intelligence. (AU)

• Processo FAPESP: 18/11881-1 - Predição de capacidades intelectuais por aprendizado de máquina a partir de neuroimagem por ressonância magnética
• Beneficiário: Bruno Hebling Vieira
• Modalidade de apoio: Bolsas no Brasil - Doutorado
• Processo FAPESP: 17/02752-0 - Predição do desempenho em testes de inteligência a partir das conectividades estruturais e funcionais do cérebro humano
• Beneficiário: Carlos Ernesto Garrido Salmon
• Modalidade de apoio: Auxílio à Pesquisa - Regular