| چکیده انگلیسی مقاله |
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. |
| کلیدواژههای انگلیسی مقاله |
Human intelligence, Brain networks, Structural connectivity, Functional connectivity, Morphometry, DTI, functional Magnetic Resonance Imaging (fMRI), Intelligence predictio |
| نویسندگان مقاله |
| Aslan Dizaji
Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.
| Bruno Hebling Vieira
Inbrain Lab, Department of Physics, FFCLRP, University of São Paulo, Ribeirao Preto, Brazil.
| Mohmmad Reza Khodaei
Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.
| Mahnaz Ashrafi
Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.
| Elahe Parham
Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.
| Gholam Ali Hossein-Zadeh
Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.
| Carlos Ernesto Garrido Salmon
Inbrain Lab, Department of Physics, FFCLRP, University of São Paulo, Ribeirao Preto, Brazil.
| Hamid Soltanian Zadeh
Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.
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