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Identifying Neural Patterns of Functional Dyspepsia Using Multivariate Pattern Analysis: A Resting-State fMRI Study

BACKGROUND: Previous imaging studies on functional dyspepsia (FD) have focused on abnormal brain functions during special tasks, while few studies concentrated on the resting-state abnormalities of FD patients, which might be potentially valuable to provide us with direct information about the neura...

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Autores principales: Liu, Peng, Qin, Wei, Wang, Jingjing, Zeng, Fang, Zhou, Guangyu, Wen, Haixia, von Deneen, Karen M., Liang, Fanrong, Gong, Qiyong, Tian, Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3709912/
https://www.ncbi.nlm.nih.gov/pubmed/23874543
http://dx.doi.org/10.1371/journal.pone.0068205
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author Liu, Peng
Qin, Wei
Wang, Jingjing
Zeng, Fang
Zhou, Guangyu
Wen, Haixia
von Deneen, Karen M.
Liang, Fanrong
Gong, Qiyong
Tian, Jie
author_facet Liu, Peng
Qin, Wei
Wang, Jingjing
Zeng, Fang
Zhou, Guangyu
Wen, Haixia
von Deneen, Karen M.
Liang, Fanrong
Gong, Qiyong
Tian, Jie
author_sort Liu, Peng
collection PubMed
description BACKGROUND: Previous imaging studies on functional dyspepsia (FD) have focused on abnormal brain functions during special tasks, while few studies concentrated on the resting-state abnormalities of FD patients, which might be potentially valuable to provide us with direct information about the neural basis of FD. The main purpose of the current study was thereby to characterize the distinct patterns of resting-state function between FD patients and healthy controls (HCs). METHODOLOGY/PRINCIPAL FINDINGS: Thirty FD patients and thirty HCs were enrolled and experienced 5-mintue resting-state scanning. Based on the support vector machine (SVM), we applied multivariate pattern analysis (MVPA) to investigate the differences of resting-state function mapped by regional homogeneity (ReHo). A classifier was designed by using the principal component analysis and the linear SVM. Permutation test was then employed to identify the significant contribution to the final discrimination. The results displayed that the mean classifier accuracy was 86.67%, and highly discriminative brain regions mainly included the prefrontal cortex (PFC), orbitofrontal cortex (OFC), supplementary motor area (SMA), temporal pole (TP), insula, anterior/middle cingulate cortex (ACC/MCC), thalamus, hippocampus (HIPP)/parahippocamus (ParaHIPP) and cerebellum. Correlation analysis revealed significant correlations between ReHo values in certain regions of interest (ROI) and the FD symptom severity and/or duration, including the positive correlations between the dmPFC, pACC and the symptom severity; whereas, the positive correlations between the MCC, OFC, insula, TP and FD duration. CONCLUSIONS: These findings indicated that significantly distinct patterns existed between FD patients and HCs during the resting-state, which could expand our understanding of the neural basis of FD. Meanwhile, our results possibly showed potential feasibility of functional magnetic resonance imaging diagnostic assay for FD.
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spelling pubmed-37099122013-07-19 Identifying Neural Patterns of Functional Dyspepsia Using Multivariate Pattern Analysis: A Resting-State fMRI Study Liu, Peng Qin, Wei Wang, Jingjing Zeng, Fang Zhou, Guangyu Wen, Haixia von Deneen, Karen M. Liang, Fanrong Gong, Qiyong Tian, Jie PLoS One Research Article BACKGROUND: Previous imaging studies on functional dyspepsia (FD) have focused on abnormal brain functions during special tasks, while few studies concentrated on the resting-state abnormalities of FD patients, which might be potentially valuable to provide us with direct information about the neural basis of FD. The main purpose of the current study was thereby to characterize the distinct patterns of resting-state function between FD patients and healthy controls (HCs). METHODOLOGY/PRINCIPAL FINDINGS: Thirty FD patients and thirty HCs were enrolled and experienced 5-mintue resting-state scanning. Based on the support vector machine (SVM), we applied multivariate pattern analysis (MVPA) to investigate the differences of resting-state function mapped by regional homogeneity (ReHo). A classifier was designed by using the principal component analysis and the linear SVM. Permutation test was then employed to identify the significant contribution to the final discrimination. The results displayed that the mean classifier accuracy was 86.67%, and highly discriminative brain regions mainly included the prefrontal cortex (PFC), orbitofrontal cortex (OFC), supplementary motor area (SMA), temporal pole (TP), insula, anterior/middle cingulate cortex (ACC/MCC), thalamus, hippocampus (HIPP)/parahippocamus (ParaHIPP) and cerebellum. Correlation analysis revealed significant correlations between ReHo values in certain regions of interest (ROI) and the FD symptom severity and/or duration, including the positive correlations between the dmPFC, pACC and the symptom severity; whereas, the positive correlations between the MCC, OFC, insula, TP and FD duration. CONCLUSIONS: These findings indicated that significantly distinct patterns existed between FD patients and HCs during the resting-state, which could expand our understanding of the neural basis of FD. Meanwhile, our results possibly showed potential feasibility of functional magnetic resonance imaging diagnostic assay for FD. Public Library of Science 2013-07-12 /pmc/articles/PMC3709912/ /pubmed/23874543 http://dx.doi.org/10.1371/journal.pone.0068205 Text en © 2013 Liu et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Liu, Peng
Qin, Wei
Wang, Jingjing
Zeng, Fang
Zhou, Guangyu
Wen, Haixia
von Deneen, Karen M.
Liang, Fanrong
Gong, Qiyong
Tian, Jie
Identifying Neural Patterns of Functional Dyspepsia Using Multivariate Pattern Analysis: A Resting-State fMRI Study
title Identifying Neural Patterns of Functional Dyspepsia Using Multivariate Pattern Analysis: A Resting-State fMRI Study
title_full Identifying Neural Patterns of Functional Dyspepsia Using Multivariate Pattern Analysis: A Resting-State fMRI Study
title_fullStr Identifying Neural Patterns of Functional Dyspepsia Using Multivariate Pattern Analysis: A Resting-State fMRI Study
title_full_unstemmed Identifying Neural Patterns of Functional Dyspepsia Using Multivariate Pattern Analysis: A Resting-State fMRI Study
title_short Identifying Neural Patterns of Functional Dyspepsia Using Multivariate Pattern Analysis: A Resting-State fMRI Study
title_sort identifying neural patterns of functional dyspepsia using multivariate pattern analysis: a resting-state fmri study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3709912/
https://www.ncbi.nlm.nih.gov/pubmed/23874543
http://dx.doi.org/10.1371/journal.pone.0068205
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