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急性功能状态变化阶段内的动态功能-结构耦合:来自一项抑郁症识别研究的证据。

Dynamic functional-structural coupling within acute functional state change phases: Evidence from a depression recognition study.

作者信息

Bi Kun, Hua Lingling, Wei Maobin, Qin Jiaolong, Lu Qing, Yao Zhijian

机构信息

Key Laboratory of Child Development and Learning Science, Research Centre for Learning Science, Southeast University, Nanjing 210096, China.

Department of Psychiatry, Nanjing Brain Hospital, Nanjing Medical University, Nanjing 210029, China.

出版信息

J Affect Disord. 2016 Feb;191:145-55. doi: 10.1016/j.jad.2015.11.041. Epub 2015 Dec 2.

Abstract

BACKGROUND

Dynamic functional-structural connectivity (FC-SC) coupling might reflect the flexibility by which SC relates to functional connectivity (FC). However, during the dynamic acute state change phases of FC, the relationship between FC and SC may be distinctive and embody the abnormality inherent in depression. This study investigated the depression-related inter-network FC-SC coupling within particular dynamic acute state change phases of FC.

METHODS

Magnetoencephalography (MEG) and diffusion tensor imaging (DTI) data were collected from 26 depressive patients (13 women) and 26 age-matched controls (13 women). We constructed functional brain networks based on MEG data and structural networks from DTI data. The dynamic connectivity regression algorithm was used to identify the state change points of a time series of inter-network FC. The time period of FC that contained change points were partitioned into types of dynamic phases (acute rising phase, acute falling phase,acute rising and falling phase and abrupt FC variation phase) to explore the inter-network FC-SC coupling. The selected FC-SC couplings were then fed into the support vector machine (SVM) for depression recognition.

RESULTS

The best discrimination accuracy was 82.7% (P=0.0069) with FC-SC couplings, particularly in the acute rising phase of FC. Within the FC phases of interest, the significant discriminative network pair was related to the salience network vs ventral attention network (SN-VAN) (P=0.0126) during the early rising phase (70-170ms).

LIMITATIONS

This study suffers from a small sample size, and the individual acute length of the state change phases was not considered.

CONCLUSIONS

The increased values of significant discriminative vectors of FC-SC coupling in depression suggested that the capacity to process negative emotion might be more directly related to the SC abnormally and be indicative of more stringent and less dynamic brain function in SN-VAN, especially in the acute rising phase of FC. We demonstrated that depressive brain dysfunctions could be better characterized by reduced FC-SC coupling flexibility in this particular phase.

摘要

背景

动态功能-结构连接性(FC-SC)耦合可能反映了结构连接(SC)与功能连接(FC)相关的灵活性。然而,在FC的动态急性状态变化阶段,FC与SC之间的关系可能是独特的,并体现出抑郁症固有的异常。本研究调查了在FC特定动态急性状态变化阶段内与抑郁症相关的网络间FC-SC耦合。

方法

收集了26名抑郁症患者(13名女性)和26名年龄匹配的对照者(13名女性)的脑磁图(MEG)和扩散张量成像(DTI)数据。我们基于MEG数据构建了功能性脑网络,并从DTI数据构建了结构网络。使用动态连接回归算法来识别网络间FC时间序列的状态变化点。将包含变化点的FC时间段划分为动态阶段类型(急性上升阶段、急性下降阶段、急性上升和下降阶段以及FC突然变化阶段),以探索网络间FC-SC耦合。然后将选定的FC-SC耦合输入支持向量机(SVM)进行抑郁症识别。

结果

FC-SC耦合的最佳辨别准确率为82.7%(P = 0.0069),特别是在FC的急性上升阶段。在感兴趣的FC阶段内,显著的辨别性网络对在早期上升阶段(70 - 170毫秒)与突显网络与腹侧注意网络(SN-VAN)相关(P = 0.0126)。

局限性

本研究样本量较小,且未考虑状态变化阶段的个体急性时长。

结论

抑郁症中FC-SC耦合显著辨别向量值的增加表明,处理负面情绪的能力可能更直接地与SC异常相关,并表明SN-VAN中脑功能更严格且动态性更低,特别是在FC的急性上升阶段。我们证明,在这个特定阶段,抑郁症脑功能障碍可以通过降低的FC-SC耦合灵活性更好地表征。

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