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

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 feature...

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Autores principales: Satary Dizaji, Aslan, Vieira, Bruno Hebling, Khodaei, Mohmmad Reza, Ashrafi, Mahnaz, Parham, Elahe, Hosseinzadeh, Gholam Ali, Salmon, Carlos Ernesto Garrido, Soltanianzadeh, Hamid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Iranian Neuroscience Society 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8114859/
https://www.ncbi.nlm.nih.gov/pubmed/33995924
http://dx.doi.org/10.32598/bcn.12.1.574.1
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author Satary Dizaji, Aslan
Vieira, Bruno Hebling
Khodaei, Mohmmad Reza
Ashrafi, Mahnaz
Parham, Elahe
Hosseinzadeh, Gholam Ali
Salmon, Carlos Ernesto Garrido
Soltanianzadeh, Hamid
author_facet Satary Dizaji, Aslan
Vieira, Bruno Hebling
Khodaei, Mohmmad Reza
Ashrafi, Mahnaz
Parham, Elahe
Hosseinzadeh, Gholam Ali
Salmon, Carlos Ernesto Garrido
Soltanianzadeh, Hamid
author_sort Satary Dizaji, Aslan
collection PubMed
description 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 restingstate 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.
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spelling pubmed-81148592021-05-14 Linking Brain Biology to Intellectual Endowment: A Review on the Associations of Human Intelligence With Neuroimaging Data Satary Dizaji, Aslan Vieira, Bruno Hebling Khodaei, Mohmmad Reza Ashrafi, Mahnaz Parham, Elahe Hosseinzadeh, Gholam Ali Salmon, Carlos Ernesto Garrido Soltanianzadeh, Hamid Basic Clin Neurosci Review Paper 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 restingstate 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. Iranian Neuroscience Society 2021 2021-01-01 /pmc/articles/PMC8114859/ /pubmed/33995924 http://dx.doi.org/10.32598/bcn.12.1.574.1 Text en Copyright© 2021 Iranian Neuroscience Society https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/)
spellingShingle Review Paper
Satary Dizaji, Aslan
Vieira, Bruno Hebling
Khodaei, Mohmmad Reza
Ashrafi, Mahnaz
Parham, Elahe
Hosseinzadeh, Gholam Ali
Salmon, Carlos Ernesto Garrido
Soltanianzadeh, Hamid
Linking Brain Biology to Intellectual Endowment: A Review on the Associations of Human Intelligence With Neuroimaging Data
title Linking Brain Biology to Intellectual Endowment: A Review on the Associations of Human Intelligence With Neuroimaging Data
title_full Linking Brain Biology to Intellectual Endowment: A Review on the Associations of Human Intelligence With Neuroimaging Data
title_fullStr Linking Brain Biology to Intellectual Endowment: A Review on the Associations of Human Intelligence With Neuroimaging Data
title_full_unstemmed Linking Brain Biology to Intellectual Endowment: A Review on the Associations of Human Intelligence With Neuroimaging Data
title_short Linking Brain Biology to Intellectual Endowment: A Review on the Associations of Human Intelligence With Neuroimaging Data
title_sort linking brain biology to intellectual endowment: a review on the associations of human intelligence with neuroimaging data
topic Review Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8114859/
https://www.ncbi.nlm.nih.gov/pubmed/33995924
http://dx.doi.org/10.32598/bcn.12.1.574.1
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