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可卡因成瘾相关的默认模式网络功能连接的可重复大脑区域异常:不同模型阶数的组独立成分分析研究。

Cocaine addiction related reproducible brain regions of abnormal default-mode network functional connectivity: a group ICA study with different model orders.

机构信息

Department of Computer Science and Engineering, Korea University, Anam-dong, Seongbuk-ku, Seoul 136-713, Republic of Korea.

出版信息

Neurosci Lett. 2013 Aug 26;548:110-4. doi: 10.1016/j.neulet.2013.05.029. Epub 2013 May 22.

Abstract

Model order selection in group independent component analysis (ICA) has a significant effect on the obtained components. This study investigated the reproducible brain regions of abnormal default-mode network (DMN) functional connectivity related with cocaine addiction through different model order settings in group ICA. Resting-state fMRI data from 24 cocaine addicts and 24 healthy controls were temporally concatenated and processed by group ICA using model orders of 10, 20, 30, 40, and 50, respectively. For each model order, the group ICA approach was repeated 100 times using the ICASSO toolbox and after clustering the obtained components, centrotype-based anterior and posterior DMN components were selected for further analysis. Individual DMN components were obtained through back-reconstruction and converted to z-score maps. A whole brain mixed effects factorial ANOVA was performed to explore the differences in resting-state DMN functional connectivity between cocaine addicts and healthy controls. The hippocampus, which showed decreased functional connectivity in cocaine addicts for all the tested model orders, might be considered as a reproducible abnormal region in DMN associated with cocaine addiction. This finding suggests that using group ICA to examine the functional connectivity of the hippocampus in the resting-state DMN may provide an additional insight potentially relevant for cocaine-related diagnoses and treatments.

摘要

在组独立成分分析(ICA)中,模型阶数的选择对得到的成分有显著影响。本研究通过组 ICA 中不同的模型阶数设置,探讨了与可卡因成瘾相关的异常默认模式网络(DMN)功能连接的可重复脑区。将 24 名可卡因成瘾者和 24 名健康对照者的静息态 fMRI 数据按时间串联,并分别使用模型阶数为 10、20、30、40 和 50 的组 ICA 进行处理。对于每个模型阶数,使用 ICASSO 工具箱重复进行 100 次组 ICA 处理,并在对获得的成分进行聚类后,选择基于 centroid 的前侧和后侧 DMN 成分进行进一步分析。通过后向重构获得个体 DMN 成分,并将其转换为 z 分数图。采用全脑混合效应因子方差分析,探讨可卡因成瘾者和健康对照组之间静息态 DMN 功能连接的差异。对于所有测试的模型阶数,可卡因成瘾者的海马体功能连接均减弱,这可能被认为是与可卡因成瘾相关的 DMN 中可重复的异常区域。这一发现表明,使用组 ICA 来检查静息态 DMN 中海马体的功能连接,可能为与可卡因相关的诊断和治疗提供潜在相关的额外见解。

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