Dysfunctional large-scale brain networks in drug-naïve depersonalization-derealization disorder patients.

IF 3.4 2区 医学 Q2 PSYCHIATRY
Sisi Zheng, Mingkang Song, Nan Song, Hong Zhu, Xue Li, Dongqing Yin, Shanshan Liu, Yan Zhao, Meng Fang, Yanzhe Ning, Hongxiao Jia
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引用次数: 0

Abstract

Background: Depersonalization-Derealization Disorder (DPRD) presents challenges in understanding its neurobiological underpinnings. Several neuroimaging studies have revealed altered brain function and structure in DPRD. However, the knowledge about large-scale dysfunctional brain networks in DPRD remains unknown.

Methods: A total of 47 drug-naïve DPRD patients and 49 healthy controls (HCs) were recruited and underwent resting-state functional scanning. After constructing large-scale brain networks, we calculated within-and between-network functional connectivity (FC) using the Schaefer and Tian atlas. The Support Vector Machine (SVM) model was employed to classify DPRD patients and provide features for DPRD patients concerning the dysfunctional large-scale brain networks. Finally, the correlation analysis was performed between altered functional connectivity of large-scale brain networks and scores of clinical assessments in DPRD patients.

Results: Compared to HCs, we found significantly decreased FCs, within-networks across four brain networks and between-networks involving 18 pairs of brain networks in DPRD patients. Moreover, our results revealed a satisfactory classification accuracy (80%) of these decreased FCs for correctly identifying DPRD patients. Notably, a significant negative correlation was observed between the 'Self' factor of the CDS and the FC within the somatosensory-motor network.

Conclusion: Overall, disrupted FC of large-scale brain networks may contribute to understanding neurobiological underpinnings in DPRD. Our findings may provide potential targets for therapeutic interventions.

drug-naïve去人格化-现实感障碍患者的功能失调大尺度脑网络。
背景:人格解体障碍(DPRD)在理解其神经生物学基础方面提出了挑战。一些神经影像学研究已经发现了DPRD的脑功能和结构的改变。然而,关于DPRD中大规模功能失调的脑网络的知识仍然未知。方法:共招募47例drug-naïve DPRD患者和49例健康对照(hc),进行静息状态功能扫描。在构建大规模脑网络后,我们使用Schaefer和Tian图谱计算了网络内和网络间的功能连接(FC)。采用支持向量机(SVM)模型对DPRD患者进行分类,为DPRD患者提供有关大尺度脑网络功能失调的特征。最后,对大尺度脑网络功能连通性的改变与DPRD患者的临床评估评分进行相关性分析。结果:与hc相比,我们发现在DPRD患者中,四个脑网络内的FCs和涉及18对脑网络的网络之间的FCs显著减少。此外,我们的结果显示,这些降低的FCs在正确识别DPRD患者方面具有令人满意的分类准确性(80%)。值得注意的是,在体感运动网络中,CDS的“自我”因子与FC之间存在显著的负相关。结论:总的来说,大规模脑网络的FC中断可能有助于理解DPRD的神经生物学基础。我们的发现可能为治疗干预提供潜在的靶点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
BMC Psychiatry
BMC Psychiatry 医学-精神病学
CiteScore
5.90
自引率
4.50%
发文量
716
审稿时长
3-6 weeks
期刊介绍: BMC Psychiatry is an open access, peer-reviewed journal that considers articles on all aspects of the prevention, diagnosis and management of psychiatric disorders, as well as related molecular genetics, pathophysiology, and epidemiology.
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