The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, PR China; MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, PR China.
School of Public Affairs and Administration, University of Electronic Science and Technology of China, Chengdu, China.
Prog Neuropsychopharmacol Biol Psychiatry. 2020 Jun 8;100:109889. doi: 10.1016/j.pnpbp.2020.109889. Epub 2020 Feb 14.
Major depressive disorder (MDD) is a ubiquitous mental illness with heterogeneous symptoms, however, the pathophysiology mechanisms are still not fully understood. Clinical and preclinical studies suggested that depression could cause disturbances in sensory perception systems, disruptions in auditory and visual functions may serve as an essential clinical features underlying MDD.
The current study investigated the abnormal intrinsic connectivity within and between visual and auditory networks in 95 MDD patients and 97 age-, gender-, education level-matched healthy controls (HCs) by using resting-state functional magnetic resonance imaging (fMRI). One auditory network (AN) and three visual components including visual component 1 (VC1), VC2, and VC3 were identified by using independent component analysis method based on the fMRI networks during the resting state with the largest spatial correlations, combining with brain regions and specific network templates.
We found that MDD could be characterized by the following disrupted network model relative to HCs: (i) reduced within-network connectivity in the AN, VC2, and VC3; (ii) reduced between-network connectivity between the AN and the VC3. Furthermore, aberrant functional connectivity (FC) within the visual network was linked to the clinical symptoms.
Overall, our results demonstrated that abnormalities of FC in perception systems including intrinsic visual and auditory networks may explain neurobiological mechanisms underlying MDD and could serve as a potential effective biomarker.
重度抑郁症（MDD）是一种普遍存在的精神疾病，具有异质的症状，但病理生理学机制仍未完全理解。临床和临床前研究表明，抑郁症可能导致感觉感知系统紊乱，听觉和视觉功能障碍可能是 MDD 的重要临床特征。
本研究通过静息态功能磁共振成像（fMRI），对 95 名 MDD 患者和 97 名年龄、性别、教育程度匹配的健康对照（HC）进行了视觉和听觉网络内和网络间的异常内在连通性研究。通过独立成分分析方法，基于静息状态下 fMRI 网络，确定了一个听觉网络（AN）和三个视觉成分，包括视觉成分 1（VC1）、VC2 和 VC3，这些成分与脑区和特定的网络模板具有最大的空间相关性。
我们发现 MDD 与 HCs 相比，可以用以下破坏的网络模型来描述：（i）AN、VC2 和 VC3 内网络连接减少；（ii）AN 与 VC3 之间的网络间连接减少。此外，视觉网络内的异常功能连接（FC）与临床症状有关。
总的来说，我们的研究结果表明，包括内在视觉和听觉网络在内的感知系统的 FC 异常可能解释了 MDD 的神经生物学机制，并可能成为潜在的有效生物标志物。
