创伤后应激障碍静息状态功能连接的数据驱动方法:一项ENIGMA-PGC PTSD研究

IF 3.3 2区 医学 Q1 NEUROIMAGING
Carissa W. Tomas, Jacklynn M. Fitzgerald, C. Lexi Baird, Courtney C. Haswell, Chadi G. Abdallah, Michael Angstadt, Justin T. Baker, Hannah Berg, Jennifer U. Blackford, Josh Cisler, Andrew S. Cotton, Judith K. Daniels, Nicholas D. Davenport, Richard J. Davidson, Terri A. deRoon-Cassini, Seth G. Disner, Wissam El Hage, Negar Fani, Jessie L. Frijling, Evan M. Gordon, Daniel W. Grupe, Xiaofu He, Ryan Herringa, David Hofmann, Ashley A. Huggins, Ahmed Hussain, Jonathan Ipser, Neda Jahanshad, Tanja Jovanovic, Milissa L. Kaufman, Yoojean Kim, Anthony King, Saskia B. J. Koch, Sheri Koopowitz, Amit Lazarov, Lauren A. M. Lebois, Isreal Liberzon, Shmuel Lissek, Antje Manthey, Geoffrey May, Katie A. McLaughlin, Laura Nawijn, Steven M. Nelson, Yuval Neria, Jack B. Nitschke, Bunmi O. Olatunji, Miranda Olff, Matthew Peverill, Yann Quidé, Orren Ravid, Kerry Ressler, Marisa Ross, Lauren E. Salminen, Kelly Sambrook, Chiahao Shih, Anika Sierk, Scott R. Sponheim, Dan J. Stein, Jennifer Stevens, Thomas Straube, Benjamin Suarez-Jimenez, Paul M. Thompson, Nic J. A. van der Wee, Steven J. A. van der Werff, Sanne J. H. van Rooij, Mirjam van Zuiden, Dick J. Veltman, Robert R. J. M. Vermeiren, Henrik Walter, Xin Wang, Hong Xie, Xi Zhu, Sigal Zilcha-Mano, Christine L. Larson, Rajendra Morey
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引用次数: 0

摘要

使用功能性磁共振成像(fMRI),创伤后应激障碍(PTSD)的症状与大脑网络在缺乏给定认知需求或任务时的异常有关,称为静息状态网络。先前的工作主要集中在受先验假设约束的特定区域之间静态功能连接(FC)的中断。然而,动态FC,一种检测大脑网络随时间变化特征的方法,可能为了解PTSD功能障碍背后的网络特性提供更敏感的测量方法。此外,使用数据驱动的分析方法可以揭示其他更大的网络干扰的贡献,而不是由roi或规范网络的假设驱动检查所揭示的。因此,本研究使用群体独立成分分析(ICA)和图论原理来识别、表征并随后比较来自ENIGMA-PGC创伤后应激障碍工作组的创伤暴露个体(N = 1035)的大脑网络动态和周期性连接状态。静态FC和动态FC结果均未显示组间的显著差异。在重复连接状态的停留时间或转换次数方面也没有组间差异。这个具有异质性创伤类型和人口统计学特征的多队列样本比先前的较小的同质创伤队列的文献提供了一个明显更大规模的方法。创伤后应激障碍的异质性,特别是在弥漫性脑网络中,可能无法通过仅评估诊断组来捕获,应进一步开展工作以评估与特定症状特征和创伤类型相关的脑网络动态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Data-Driven Approach to Dynamic Resting State Functional Connectivity in Post-Traumatic Stress Disorder: An ENIGMA-PGC PTSD Study

Data-Driven Approach to Dynamic Resting State Functional Connectivity in Post-Traumatic Stress Disorder: An ENIGMA-PGC PTSD Study

Using functional magnetic resonance imaging (fMRI), symptoms of posttraumatic stress disorder (PTSD) have been associated with aberrations in brain networks in the absence of a given cognitive demand or task, called resting-state networks. Prior work has focused on disruption in the static functional connectivity (FC) among specific regions constrained by a priori hypotheses. However, dynamic FC, an approach that examines brain network characteristics over time, may provide a more sensitive measure to understand the network properties underlying dysfunction in PTSD. Further, using a data-driven analytic approach may reveal the contribution of other larger network disturbances beyond those revealed by hypothesis-driven examinations of ROIs or canonical networks. Therefore, the current study used group independent components analysis (ICA) and graph theory principles to identify, characterize, and subsequently compare brain network dynamics and recurrent connectivity states in a large sample of trauma exposed individuals (N = 1035) with and without PTSD from the ENIGMA-PGC PTSD workgroup. Neither static FC nor dynamic FC results showed robust differences between groups. There were also no group differences in dwell time or number of transitions of recurrent connectivity states. This multi-cohort sample with heterogenous trauma types and demographic features offers a significantly larger scale approach than prior literature with smaller homogenous trauma cohorts. Heterogeneity of PTSD, especially within diffuse brain networks, may not be captured by evaluating only diagnostic groups, further work should be done to evaluate brain network dynamics with respect to specific symptom profiles and trauma types.

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来源期刊
Human Brain Mapping
Human Brain Mapping 医学-核医学
CiteScore
8.30
自引率
6.20%
发文量
401
审稿时长
3-6 weeks
期刊介绍: Human Brain Mapping publishes peer-reviewed basic, clinical, technical, and theoretical research in the interdisciplinary and rapidly expanding field of human brain mapping. The journal features research derived from non-invasive brain imaging modalities used to explore the spatial and temporal organization of the neural systems supporting human behavior. Imaging modalities of interest include positron emission tomography, event-related potentials, electro-and magnetoencephalography, magnetic resonance imaging, and single-photon emission tomography. Brain mapping research in both normal and clinical populations is encouraged. Article formats include Research Articles, Review Articles, Clinical Case Studies, and Technique, as well as Technological Developments, Theoretical Articles, and Synthetic Reviews. Technical advances, such as novel brain imaging methods, analyses for detecting or localizing neural activity, synergistic uses of multiple imaging modalities, and strategies for the design of behavioral paradigms and neural-systems modeling are of particular interest. The journal endorses the propagation of methodological standards and encourages database development in the field of human brain mapping.
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