| Full text | |
| Author(s): |
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]
Total Authors: 8
|
| Affiliation: | [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
Total Affiliations: 4
|
| Document type: | Review article |
| Source: | BASIC AND CLINICAL NEUROSCIENCE; v. 12, n. 1, p. 1-27, JAN-FEB 2021. |
| Web of Science Citations: | 0 |
| Abstract | |
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) | |
| FAPESP's process: | 18/11881-1 - Machine learning prediction of intellectual abilities from magnetic resonance neuroimaging |
| Grantee: | Bruno Hebling Vieira |
| Support Opportunities: | Scholarships in Brazil - Doctorate |
| FAPESP's process: | 17/02752-0 - Prediction of human intelligence through neuroimaging features |
| Grantee: | Carlos Ernesto Garrido Salmon |
| Support Opportunities: | Regular Research Grants |