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Machine learning prediction of intellectual abilities from magnetic resonance neuroimaging

Grant number: 18/11881-1
Support type:Scholarships in Brazil - Doctorate
Effective date (Start): April 01, 2019
Effective date (End): November 30, 2021
Field of knowledge:Biological Sciences - Biophysics - Biophysics of Processes and Systems
Principal researcher:Carlos Ernesto Garrido Salmon
Grantee:Bruno Hebling Vieira
Home Institution: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto (FFCLRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil

Abstract

Intelligence encompasses several cognitive capabilities that allow the individual to gather information from and act on its environment. It is known that these cognitive processes are centered in the brain and, comparing the human brain to the brain of other animals less proficient at diverse cognitive processes usual to humans, it is possible to infer that neuroanatomical and neurophysiological divergences are, somehow, associated to differences in cognitive abilities. In another scale, these divergences are also noticed between human individuals, where there exists a correlation between intracranial volume and intelligence quotients, for example. Knowing that, it is possible to employ neuroimaging, more specifically anatomical and functional magnetic resonance imaging, to uncover correlates of intelligence in humans. Alternatively, it is also possible to derive models to predict, with machine learning, intelligence quotients in subjects from their neuroimaging data. In this project, we propose the use of both methodologies to uncover relationships between intelligence and brain morphometric and connectivity features in a large sample of healthy subjects. (AU)

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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
VIEIRA, BRUNO HEBLING; HIAR, NATHALIA HANNA; CARDOSO, GEORGE C.. Uncertainty Reduction in Logistic Growth Regression Using Surrogate Systems Carrying Capacities: a COVID-19 Case Study. Brazilian Journal of Physics, v. 52, n. 1, . (18/11881-1)
DIZAJI, ASLAN; VIEIRA, BRUNO HEBLING; KHODAEI, MOHMMAD REZA; ASHRAFI, MAHNAZ; PARHAM, ELAHE; HOSSEIN-ZADEH, GHOLAM ALI; GARRIDO SALMON, CARLOS ERNESTO; ZADEH, HAMID SOLTANIAN. Linking Brain Biology to Intellectual Endowment: A Review on the Associations of Human Intelligence With Neuroimaging Data. BASIC AND CLINICAL NEUROSCIENCE, v. 12, n. 1, p. 1-27, . (18/11881-1, 17/02752-0)
VIEIRA, BRUNO HEBLING; DUBOIS, JULIEN; CALHOUN, VINCE D.; SALMON, CARLOS ERNESTO GARRIDO. A deep learning based approach identifies regions more relevant than resting-state networks to the prediction of general intelligence from resting-state fMRI. Human Brain Mapping, v. 42, n. 18, . (18/11881-1, 17/02752-0)

Please report errors in scientific publications list by writing to: cdi@fapesp.br.