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运用有效连接映射网络成瘾障碍:一项频谱动态因果建模研究。

Mapping Internet gaming disorder using effective connectivity: A spectral dynamic causal modeling study.

机构信息

Department of Psychology, Zhejiang Normal University, Jinhua, China.

Department of Physics, Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China.

出版信息

Addict Behav. 2019 Mar;90:62-70. doi: 10.1016/j.addbeh.2018.10.019. Epub 2018 Oct 16.

Abstract

OBJECTS

Understanding the neural basis underlying Internet gaming disorder (IGD) is essential for the diagnosis and treatment of this type of behavioural addiction. Aberrant resting-state functional connectivity (rsFC) of the default mode network (DMN) has been reported in individuals with IGD. Since rsFC is not a directional analysis, the effective connectivity within the DMN in IGD remains unclear. Here, we employed spectral dynamic causal modeling (spDCM) to explore this issue.

METHODS

Resting state fMRI data were collected from 64 IGD (age: 22.6 ± 2.2) and 63 well-matched recreational Internet game users (RGU, age: 23.1 ± 2.5). Voxel-based mean time series data extracted from the 4 brain regions within the DMN (medial prefrontal cortex, mPFC; posterior cingulate cortex, PCC; bilateral inferior parietal lobule, left IPL/right IPL) of two groups during the resting state were used for the spDCM analysis.

RESULTS

Compared with RGU, IGD showed reduced effective connectivity from the mPFC to the PCC and from the left IPL to the mPFC, with reduced self-connection in the PCC and the left IPL.

CONCLUSIONS

The spDCM could distinguish the changes in the functional architecture between two groups more precisely than rsFC. Our findings suggest that the decreased excitatory connectivity from the mPFC to the PCC may be a crucial biomarker for IGD. Future brain-based intervention should pay attention to dysregulation in the IPL-mPFC-PCC circuits.

摘要

目的

理解网络成瘾障碍(IGD)的神经基础对于这种行为成瘾的诊断和治疗至关重要。已有研究报道,IGD 个体的默认模式网络(DMN)静息态功能连接(rsFC)异常。由于 rsFC 不是一种有向分析,因此 IGD 中 DMN 的有效连接尚不清楚。在这里,我们采用谱动态因果建模(spDCM)来探讨这个问题。

方法

从 64 名 IGD(年龄:22.6±2.2)和 63 名匹配良好的娱乐性网络游戏使用者(RGU,年龄:23.1±2.5)中采集静息态 fMRI 数据。从 DMN(内侧前额叶皮质,mPFC;后扣带回皮质,PCC;双侧顶下小叶,左 IPL/右 IPL)内的 4 个脑区提取两组在静息状态下的基于体素的平均时间序列数据,用于 spDCM 分析。

结果

与 RGU 相比,IGD 显示出从 mPFC 到 PCC 的有效连接减少,从左 IPL 到 mPFC 的有效连接减少,PCC 和左 IPL 的自连接减少。

结论

spDCM 比 rsFC 更能准确地区分两组之间功能结构的变化。我们的研究结果表明,mPFC 到 PCC 的兴奋性连接减少可能是 IGD 的一个关键生物标志物。未来基于大脑的干预措施应注意 IPL-mPFC-PCC 回路的失调。

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