Predicting Antidepressant Treatment Response Using Functional Brain Controllability Analysis-Reference-Cited by-同舟云学术

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Predicting Antidepressant Treatment Response Using Functional Brain Controllability Analysis

Published:2023-03-01 Issue:2 Volume:13 Page:107-116
ISSN:2158-0014
Container-title:Brain Connectivity
language:en
Short-container-title:Brain Connectivity

Author:

Fang Feng¹,Godlewska Beata²³,Selvaraj Sudhakar⁴,Zhang Yingchun¹^ORCID

Affiliation:

1. Department of Biomedical Engineering, University of Houston, Houston, Texas, USA.

2. Department of Psychiatry, Medical Sciences Division, University of Oxford, United Kingdom.

3. Oxford Health NHS Foundation Trust, Oxford, United Kingdom.

4. Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, The McGovern Medical School of UT Health Houston, Houston, Texas, USA.

Publisher

Mary Ann Liebert Inc

Subject

General Neuroscience

Link

https://www.liebertpub.com/doi/pdf/10.1089/brain.2022.0027

Reference70 articles.

1. Treatment-resistant depression: therapeutic trends, challenges, and future directions

2. Biomarkers of ketamine’s antidepressant effect: a clinical review of genetics, functional connectivity, and neurophysiology

3. Data-driven control of complex networks

4. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Distinct MRI-based functional and structural connectivity for antidepressant response prediction in major depressive disorder;Clinical Neurophysiology;2024-04

2. Neurophysiological Biomarkers;Biomarkers in Neuropsychiatry;2023

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