Predicting the retinotopic organization of human visual cortex from anatomy using geometric deep learning.

Ribeiro, Fernanda L; Bollmann, Steffen; Puckett, Alexander M

Ribeiro, Fernanda L; Bollmann, Steffen; Puckett, Alexander M.

Afiliação

Ribeiro FL; School of Psychology, The University of Queensland, Saint Lucia, Brisbane, QLD 4072, Australia; Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia. Electronic address: fernanda.ribeiro@uq.edu.au.
Bollmann S; School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, QLD 4072, Australia.
Puckett AM; School of Psychology, The University of Queensland, Saint Lucia, Brisbane, QLD 4072, Australia; Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia.

Neuroimage ; 244: 118624, 2021 12 01.

Article em En | MEDLINE | ID: mdl-34607019

Assuntos

Aprendizado Profundo; Córtex Visual/diagnóstico por imagem; Adulto; Feminino; Humanos; Individualidade; Imageamento por Ressonância Magnética; Masculino; Redes Neurais de Computação; Neurônios; Adulto Jovem

Palavras-chave

Cortical surface; High-resolution fMRI; Machine learning; Manifold; Vision; Visual hierarchy

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Adult / Female / Humans / Male Idioma: En Ano de publicação: 2021 Tipo de documento: Article

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