Center for Psychosocial Medicine, Department of General Psychiatry, University of Heidelberg, Germany.
Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
Prog Neuropsychopharmacol Biol Psychiatry. 2019 Jul 13;93:114-121. doi: 10.1016/j.pnpbp.2019.03.007. Epub 2019 Mar 16.
There is accumulating neuroimaging evidence for both structural and functional abnormalities in schizophrenia patients with persistent auditory verbal hallucinations (AVH). So far, the direct interrelationships between altered structural and functional changes underlying AVH are unknown. Recently, it has become possible to reveal hidden patterns of neural dysfunction not sufficiently captured by separate analysis of these two modalities. A data-driven fusion method called parallel independent component analysis (p-ICA) is able to identify maximally independent components of each imaging modality as well as the link between them. In the present study, we utilized p-ICA to study covarying components among gray matter volume maps computed from structural MRI (sMRI) and fractional amplitude of low-frequency fluctuations (fALFF) maps computed from resting-state functional MRI (rs-fMRI) data of 15 schizophrenia patients with AVH, 16 non-hallucinating schizophrenia patients (nAVH), and 19 healthy controls (HC). We found a significant correlation (r = 0.548, n = 50, p < .001) between a sMRI component and a rs-fMRI component, which was significantly different between the AVH and non AVH group (nAVH). The rs-fMRI component comprised temporal cortex and cortical midline regions, the sMRI component included predominantly fronto-temporo-parietal regions. Distinct clinical features, as measured by the Psychotic Symptoms Rating Scale (PSYRATS), were associated with two different modality specific rs-fMRI components. There was a significant correlation between a predominantly parietal resting-state network and the physical dimension of PSYRATS and the posterior cingulate/temporal cortex network and the emotional dimension of PSYRATS. These data suggest AVH-specific interrelationships between intrinsic network activity and GMV, together with modality-specific associations with distinct symptom dimensions of AVH.
目前有越来越多的神经影像学证据表明，持续性幻听（AVH）的精神分裂症患者存在结构和功能异常。迄今为止，尚不清楚这些异常的结构和功能改变之间的直接相互关系。最近，人们已经能够揭示隐藏的神经功能障碍模式，而这些模式单凭对这两种模态的单独分析是无法充分捕捉到的。一种名为并行独立成分分析（p-ICA）的数据驱动融合方法能够识别每个成像模态的最大独立成分以及它们之间的联系。在本研究中，我们利用 p-ICA 研究了 15 名有幻听的精神分裂症患者、16 名无幻听的精神分裂症患者（nAVH）和 19 名健康对照者（HC）的结构磁共振成像（sMRI）计算的灰质体积图与静息态功能磁共振成像（rs-fMRI）计算的低频振幅（fALFF）图之间的协变成分。我们发现 sMRI 成分和 rs-fMRI 成分之间存在显著相关性（r=0.548，n=50，p<0.001），并且这种相关性在 AVH 组和 nAVH 组之间存在显著差异（nAVH）。rs-fMRI 成分包括颞叶皮层和皮质中线区域，sMRI 成分主要包括额颞顶叶区域。通过精神病症状评定量表（PSYRATS）测量的不同临床特征与两个不同模态的特定 rs-fMRI 成分相关。主要与顶叶静息态网络相关的成分与 PSYRATS 的物理维度之间存在显著相关性，而与后扣带回/颞叶皮层网络相关的成分与 PSYRATS 的情感维度之间存在显著相关性。这些数据表明，AVH 具有特异性的内在网络活动与 GMV 之间的相互关系，以及与 AVH 不同症状维度的特定模态相关联。
