Cargando…

Aberrant Resting-State Brain Function in Adolescent Depression

To explore the changes of brain function and conduct clinical differential diagnosis based on support vector machine (SVM) in adolescent patients with depression. A total of 24 adolescent patients with depression according to CCMD-3 and DSM-5 and 23 gender, education level, body mass index, and age...

Descripción completa

Detalles Bibliográficos
Autores principales: Mao, Ning, Che, Kaili, Chu, Tongpeng, Li, Yuna, Wang, Qinglin, Liu, Meijie, Ma, Heng, Wang, Zhongyi, Lin, Fan, Wang, Bin, Ji, Haixia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7396538/
https://www.ncbi.nlm.nih.gov/pubmed/32903315
http://dx.doi.org/10.3389/fpsyg.2020.01784
_version_ 1783565604990484480
author Mao, Ning
Che, Kaili
Chu, Tongpeng
Li, Yuna
Wang, Qinglin
Liu, Meijie
Ma, Heng
Wang, Zhongyi
Lin, Fan
Wang, Bin
Ji, Haixia
author_facet Mao, Ning
Che, Kaili
Chu, Tongpeng
Li, Yuna
Wang, Qinglin
Liu, Meijie
Ma, Heng
Wang, Zhongyi
Lin, Fan
Wang, Bin
Ji, Haixia
author_sort Mao, Ning
collection PubMed
description To explore the changes of brain function and conduct clinical differential diagnosis based on support vector machine (SVM) in adolescent patients with depression. A total of 24 adolescent patients with depression according to CCMD-3 and DSM-5 and 23 gender, education level, body mass index, and age matched healthy controls were assessed with 17-item Hamilton Depression Rating Scale (HAMD). HAMD scores were requested from ≥17 of patients. Three−dimensional T1 and resting-state functional magnetic resonance imaging data were acquired from all participants. The data were analyzed using SPM 12 and REST1.8. Two-sample t-test was conducted to compare regional homogeneity (ReHo) values among the groups of participants. Finally, based on SVM classification, clinical differential diagnosis of the patients was carried out. The receiver operator characteristic (ROC) curve were used to confirm the performance of the SVM model. An increase ReHo values were observed in the lingual gyrus, middle occipital gyrus, postcentral gyrus, and precentral gyrus, whereas a decrease in ReHo was found in vermis compared with the control group. The SVM model showed good performance in classification prediction of adolescent depression, with an area under curve (AUC) of 0.778 [95% confidence interval (CI), 0.661–0.797]. The changes in the spontaneous neural activity of these regions may play an important role in the neuropathological mechanism of adolescent depression and may provide promising markers for clinical evaluation.
format Online
Article
Text
id pubmed-7396538
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-73965382020-09-03 Aberrant Resting-State Brain Function in Adolescent Depression Mao, Ning Che, Kaili Chu, Tongpeng Li, Yuna Wang, Qinglin Liu, Meijie Ma, Heng Wang, Zhongyi Lin, Fan Wang, Bin Ji, Haixia Front Psychol Psychology To explore the changes of brain function and conduct clinical differential diagnosis based on support vector machine (SVM) in adolescent patients with depression. A total of 24 adolescent patients with depression according to CCMD-3 and DSM-5 and 23 gender, education level, body mass index, and age matched healthy controls were assessed with 17-item Hamilton Depression Rating Scale (HAMD). HAMD scores were requested from ≥17 of patients. Three−dimensional T1 and resting-state functional magnetic resonance imaging data were acquired from all participants. The data were analyzed using SPM 12 and REST1.8. Two-sample t-test was conducted to compare regional homogeneity (ReHo) values among the groups of participants. Finally, based on SVM classification, clinical differential diagnosis of the patients was carried out. The receiver operator characteristic (ROC) curve were used to confirm the performance of the SVM model. An increase ReHo values were observed in the lingual gyrus, middle occipital gyrus, postcentral gyrus, and precentral gyrus, whereas a decrease in ReHo was found in vermis compared with the control group. The SVM model showed good performance in classification prediction of adolescent depression, with an area under curve (AUC) of 0.778 [95% confidence interval (CI), 0.661–0.797]. The changes in the spontaneous neural activity of these regions may play an important role in the neuropathological mechanism of adolescent depression and may provide promising markers for clinical evaluation. Frontiers Media S.A. 2020-07-21 /pmc/articles/PMC7396538/ /pubmed/32903315 http://dx.doi.org/10.3389/fpsyg.2020.01784 Text en Copyright © 2020 Mao, Che, Chu, Li, Wang, Liu, Ma, Wang, Lin, Wang and Ji. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Mao, Ning
Che, Kaili
Chu, Tongpeng
Li, Yuna
Wang, Qinglin
Liu, Meijie
Ma, Heng
Wang, Zhongyi
Lin, Fan
Wang, Bin
Ji, Haixia
Aberrant Resting-State Brain Function in Adolescent Depression
title Aberrant Resting-State Brain Function in Adolescent Depression
title_full Aberrant Resting-State Brain Function in Adolescent Depression
title_fullStr Aberrant Resting-State Brain Function in Adolescent Depression
title_full_unstemmed Aberrant Resting-State Brain Function in Adolescent Depression
title_short Aberrant Resting-State Brain Function in Adolescent Depression
title_sort aberrant resting-state brain function in adolescent depression
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7396538/
https://www.ncbi.nlm.nih.gov/pubmed/32903315
http://dx.doi.org/10.3389/fpsyg.2020.01784
work_keys_str_mv AT maoning aberrantrestingstatebrainfunctioninadolescentdepression
AT chekaili aberrantrestingstatebrainfunctioninadolescentdepression
AT chutongpeng aberrantrestingstatebrainfunctioninadolescentdepression
AT liyuna aberrantrestingstatebrainfunctioninadolescentdepression
AT wangqinglin aberrantrestingstatebrainfunctioninadolescentdepression
AT liumeijie aberrantrestingstatebrainfunctioninadolescentdepression
AT maheng aberrantrestingstatebrainfunctioninadolescentdepression
AT wangzhongyi aberrantrestingstatebrainfunctioninadolescentdepression
AT linfan aberrantrestingstatebrainfunctioninadolescentdepression
AT wangbin aberrantrestingstatebrainfunctioninadolescentdepression
AT jihaixia aberrantrestingstatebrainfunctioninadolescentdepression