Assessing atypical brain functional connectivity development: An approach based on generative adversarial networks.

Autor:	Dos Santos PMN; Center of Mathematics, Computing, and Cognition, Universidade Federal do ABC, São Bernardo do Campo, Santo André, Brazil., Mendes SL; Center of Mathematics, Computing, and Cognition, Universidade Federal do ABC, São Bernardo do Campo, Santo André, Brazil., Biazoli C; Center of Mathematics, Computing, and Cognition, Universidade Federal do ABC, São Bernardo do Campo, Santo André, Brazil., Gadelha A; Laboratory of Integrative Neuroscience, Universidade Federal de São Paulo, São Paulo, Brazil.; National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil., Salum GA; National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil.; Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Federal University of Rio Grande do Sul, Porto Alegre, Brazil., Miguel EC; National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil.; Department of Psychiatry, School of Medicine, University of São Paulo, São Paulo, Brazil., Rohde LA; National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil.; Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Federal University of Rio Grande do Sul, Porto Alegre, Brazil.; UniEduK, Jaguariúna, Brazil., Sato JR; Center of Mathematics, Computing, and Cognition, Universidade Federal do ABC, São Bernardo do Campo, Santo André, Brazil.; Laboratory of Integrative Neuroscience, Universidade Federal de São Paulo, São Paulo, Brazil.; National Institute of Developmental Psychiatry for Children and Adolescents (CNPq), São Paulo, Brazil.; Big Data, Hospital Israelita Albert Einstein, São Paulo, Brazil.
Jazyk:	angličtina
Zdroj:	Frontiers in neuroscience [Front Neurosci] 2023 Jan 09; Vol. 16, pp. 1025492. Date of Electronic Publication: 2023 Jan 09 (Print Publication: 2022).
DOI:	10.3389/fnins.2022.1025492
Abstrakt:	Generative Adversarial Networks (GANs) are promising analytical tools in machine learning applications. Characterizing atypical neurodevelopmental processes might be useful in establishing diagnostic and prognostic biomarkers of psychiatric disorders. In this article, we investigate the potential of GANs models combined with functional connectivity (FC) measures to build a predictive neurotypicality score 3-years after scanning. We used a ROI-to-ROI analysis of resting-state functional magnetic resonance imaging (fMRI) data from a community-based cohort of children and adolescents (377 neurotypical and 126 atypical participants). Models were trained on data from neurotypical participants, capturing their sample variability of FC. The discriminator subnetwork of each GAN model discriminated between the learned neurotypical functional connectivity pattern and atypical or unrelated patterns. Discriminator models were combined in ensembles, improving discrimination performance. Explanations for the model's predictions are provided using the LIME (Local Interpretable Model-Agnostic) algorithm and local hubs are identified in light of these explanations. Our findings suggest this approach is a promising strategy to build potential biomarkers based on functional connectivity. Competing Interests: LAR has received grant or research support from, served as a consultant to, and served on the speakers’ bureau of Abbott, Aché, Bial, Medice, Novartis/Sandoz, Pfizer/Upjohn, and Shire/Takeda in the last three years. The ADHD and Juvenile Bipolar Disorder Outpatient Programs chaired by LAR have received unrestricted educational and research support from the following pharmaceutical companies in the last three years: Novartis/Sandoz and Shire/Takeda. LAR has received authorship royalties from Oxford Press and ArtMed. All of these are outside of the study. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The handling editor declared a past co-authorship with the author JS. (Copyright © 2023 Dos Santos, Mendes, Biazoli, Gadelha, Salum, Miguel, Rohde and Sato.)
Databáze:	MEDLINE
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