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Antidepressant Effects of Electroconvulsive Therapy Unrelated to the Brain's Functional Network Connectivity alterations at an Individual Level

BACKGROUND: Electroconvulsive therapy (ECT) can alleviate the symptoms of treatment-resistant depression (TRD). Functional network connectivity (FNC) is a newly developed method to investigate the brain's functional connectivity patterns. The first aim of this study was to investigate FNC alter...

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Autores principales: Chen, Guang-Dong, Ji, Feng, Li, Gong-Ying, Lyu, Bo-Xuan, Hu, Wei, Zhuo, Chuan-Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5324377/
https://www.ncbi.nlm.nih.gov/pubmed/28218214
http://dx.doi.org/10.4103/0366-6999.199845
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author Chen, Guang-Dong
Ji, Feng
Li, Gong-Ying
Lyu, Bo-Xuan
Hu, Wei
Zhuo, Chuan-Jun
author_facet Chen, Guang-Dong
Ji, Feng
Li, Gong-Ying
Lyu, Bo-Xuan
Hu, Wei
Zhuo, Chuan-Jun
author_sort Chen, Guang-Dong
collection PubMed
description BACKGROUND: Electroconvulsive therapy (ECT) can alleviate the symptoms of treatment-resistant depression (TRD). Functional network connectivity (FNC) is a newly developed method to investigate the brain's functional connectivity patterns. The first aim of this study was to investigate FNC alterations between TRD patients and healthy controls. The second aim was to explore the relationship between the ECT treatment response and pre-ECT treatment FNC alterations in individual TRD patients. METHODS: This study included 82 TRD patients and 41 controls. Patients were screened at baseline and after 2 weeks of treatment with a combination of ECT and antidepressants. Group information guided-independent component analysis (GIG-ICA) was used to compute subject-specific functional networks (FNs). Grassmann manifold and step-wise forward component selection using support vector machines were adopted to perform the FNC measure and extract the functional networks' connectivity patterns (FCP). Pearson's correlation analysis was used to calculate the correlations between the FCP and ECT response. RESULTS: A total of 82 TRD patients in the ECT group were successfully treated. On an average, 8.50 ± 2.00 ECT sessions were conducted. After ECT treatment, only 42 TRD patients had an improved response to ECT (the Hamilton scores reduction rate was more than 50%), response rate 51%. 8 FNs (anterior and posterior default mode network, bilateral frontoparietal network, audio network, visual network, dorsal attention network, and sensorimotor network) were obtained using GIG-ICA. We did not found that FCPs were significantly different between TRD patients and healthy controls. Moreover, the baseline FCP was unrelated to the ECT treatment response. CONCLUSIONS: The FNC was not significantly different between the TRD patients and healthy controls, and the baseline FCP was unrelated to the ECT treatment response. These findings will necessitate that we modify the experimental scheme to explore the mechanisms underlying ECT's effects on depression and explore the specific predictors of the effects of ECT based on the pre-ECT treatment magnetic resonance imaging.
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spelling pubmed-53243772017-03-01 Antidepressant Effects of Electroconvulsive Therapy Unrelated to the Brain's Functional Network Connectivity alterations at an Individual Level Chen, Guang-Dong Ji, Feng Li, Gong-Ying Lyu, Bo-Xuan Hu, Wei Zhuo, Chuan-Jun Chin Med J (Engl) Original Article BACKGROUND: Electroconvulsive therapy (ECT) can alleviate the symptoms of treatment-resistant depression (TRD). Functional network connectivity (FNC) is a newly developed method to investigate the brain's functional connectivity patterns. The first aim of this study was to investigate FNC alterations between TRD patients and healthy controls. The second aim was to explore the relationship between the ECT treatment response and pre-ECT treatment FNC alterations in individual TRD patients. METHODS: This study included 82 TRD patients and 41 controls. Patients were screened at baseline and after 2 weeks of treatment with a combination of ECT and antidepressants. Group information guided-independent component analysis (GIG-ICA) was used to compute subject-specific functional networks (FNs). Grassmann manifold and step-wise forward component selection using support vector machines were adopted to perform the FNC measure and extract the functional networks' connectivity patterns (FCP). Pearson's correlation analysis was used to calculate the correlations between the FCP and ECT response. RESULTS: A total of 82 TRD patients in the ECT group were successfully treated. On an average, 8.50 ± 2.00 ECT sessions were conducted. After ECT treatment, only 42 TRD patients had an improved response to ECT (the Hamilton scores reduction rate was more than 50%), response rate 51%. 8 FNs (anterior and posterior default mode network, bilateral frontoparietal network, audio network, visual network, dorsal attention network, and sensorimotor network) were obtained using GIG-ICA. We did not found that FCPs were significantly different between TRD patients and healthy controls. Moreover, the baseline FCP was unrelated to the ECT treatment response. CONCLUSIONS: The FNC was not significantly different between the TRD patients and healthy controls, and the baseline FCP was unrelated to the ECT treatment response. These findings will necessitate that we modify the experimental scheme to explore the mechanisms underlying ECT's effects on depression and explore the specific predictors of the effects of ECT based on the pre-ECT treatment magnetic resonance imaging. Medknow Publications & Media Pvt Ltd 2017-02-20 /pmc/articles/PMC5324377/ /pubmed/28218214 http://dx.doi.org/10.4103/0366-6999.199845 Text en Copyright: © 2017 Chinese Medical Journal http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.
spellingShingle Original Article
Chen, Guang-Dong
Ji, Feng
Li, Gong-Ying
Lyu, Bo-Xuan
Hu, Wei
Zhuo, Chuan-Jun
Antidepressant Effects of Electroconvulsive Therapy Unrelated to the Brain's Functional Network Connectivity alterations at an Individual Level
title Antidepressant Effects of Electroconvulsive Therapy Unrelated to the Brain's Functional Network Connectivity alterations at an Individual Level
title_full Antidepressant Effects of Electroconvulsive Therapy Unrelated to the Brain's Functional Network Connectivity alterations at an Individual Level
title_fullStr Antidepressant Effects of Electroconvulsive Therapy Unrelated to the Brain's Functional Network Connectivity alterations at an Individual Level
title_full_unstemmed Antidepressant Effects of Electroconvulsive Therapy Unrelated to the Brain's Functional Network Connectivity alterations at an Individual Level
title_short Antidepressant Effects of Electroconvulsive Therapy Unrelated to the Brain's Functional Network Connectivity alterations at an Individual Level
title_sort antidepressant effects of electroconvulsive therapy unrelated to the brain's functional network connectivity alterations at an individual level
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5324377/
https://www.ncbi.nlm.nih.gov/pubmed/28218214
http://dx.doi.org/10.4103/0366-6999.199845
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