Lottman Kristin K, Kraguljac Nina V, White David M, Morgan Charity J, Calhoun Vince D, Butt Allison, Lahti Adrienne C
Department of Biomedical Engineering, University of Alabama at Birmingham , Birmingham, AL , USA.
Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham , Birmingham, AL , USA.
Front Psychiatry. 2017 Feb 6;8:14. doi: 10.3389/fpsyt.2017.00014. eCollection 2017.
Resting-state functional connectivity studies in schizophrenia evaluating average connectivity over the entire experiment have reported aberrant network integration, but findings are variable. Examining time-varying (dynamic) functional connectivity may help explain some inconsistencies. We assessed dynamic network connectivity using resting-state functional MRI in patients with schizophrenia, while unmedicated ( = 34), after 1 week ( = 29) and 6 weeks of treatment with risperidone ( = 24), as well as matched controls at baseline ( = 35) and after 6 weeks ( = 19). After identifying 41 independent components (ICs) comprising resting-state networks, sliding window analysis was performed on IC timecourses using an optimal window size validated with linear support vector machines. Windowed correlation matrices were then clustered into three discrete connectivity states (a relatively sparsely connected state, a relatively abundantly connected state, and an intermediately connected state). In unmedicated patients, static connectivity was increased between five pairs of ICs and decreased between two pairs of ICs when compared to controls, dynamic connectivity showed increased connectivity between the thalamus and somatomotor network in one of the three states. State statistics indicated that, in comparison to controls, unmedicated patients had shorter mean dwell times and fraction of time spent in the sparsely connected state, and longer dwell times and fraction of time spent in the intermediately connected state. Risperidone appeared to normalize mean dwell times after 6 weeks, but not fraction of time. Results suggest that static connectivity abnormalities in schizophrenia may partly be related to altered brain network temporal dynamics rather than consistent dysconnectivity within and between functional networks and demonstrate the importance of implementing complementary data analysis techniques.
在精神分裂症患者中进行的静息态功能连接性研究,评估整个实验过程中的平均连接性,报告了异常的网络整合情况,但结果存在差异。研究随时间变化(动态)的功能连接性可能有助于解释一些不一致之处。我们使用静息态功能磁共振成像评估了精神分裂症患者的动态网络连接性,这些患者在未服药时(n = 34)、服用利培酮1周后(n = 29)和6周后(n = 24),以及在基线时(n = 35)和6周后(n = 19)的匹配对照组。在识别出包含静息态网络的41个独立成分(ICs)后,使用线性支持向量机验证的最佳窗口大小对IC时间序列进行滑动窗口分析。然后将窗口相关矩阵聚类为三种离散的连接状态(相对稀疏连接状态、相对丰富连接状态和中间连接状态)。与对照组相比,未服药患者中五对IC之间的静态连接性增加,两对IC之间的静态连接性降低,动态连接性在三种状态之一中显示丘脑与躯体运动网络之间的连接性增加。状态统计表明,与对照组相比,未服药患者的平均停留时间和在稀疏连接状态下花费的时间比例较短,而在中间连接状态下的停留时间和花费的时间比例较长。利培酮在6周后似乎使平均停留时间恢复正常,但未使时间比例恢复正常。结果表明,精神分裂症中的静态连接性异常可能部分与脑网络时间动态改变有关,而非功能网络内部和之间一致的连接中断,并证明了实施补充数据分析技术的重要性。