The Mind Research Network, Albuquerque, NM, USA; School of Computer & Information Technology, Shanxi University, Taiyuan, China.
Department of Psychiatry, University of California San Francisco, San Francisco, CA, USA; The Mental Health Service, San Francisco VA Healthcare System, San Francisco, CA, USA.
Neuroimage. 2018 Oct 15;180(Pt B):632-645. doi: 10.1016/j.neuroimage.2017.10.022. Epub 2017 Oct 14.
Individuals at clinical high-risk (CHR) for psychosis are characterized by attenuated psychotic symptoms. Only a minority of CHR individuals convert to full-blown psychosis. Therefore, there is a strong interest in identifying neurobiological abnormalities underlying the psychosis risk syndrome. Dynamic functional connectivity (DFC) captures time-varying connectivity over short time scales, and has the potential to reveal complex brain functional organization. Based on resting-state functional magnetic resonance imaging (fMRI) data from 70 healthy controls (HCs), 53 CHR individuals, and 58 early illness schizophrenia (ESZ) patients, we applied a novel group information guided ICA (GIG-ICA) to estimate inherent connectivity states from DFC, and then investigated group differences. We found that ESZ patients showed more aberrant connectivities and greater alterations than CHR individuals. Results also suggested that disease-related connectivity states occurred in CHR and ESZ groups. Regarding the dominant state with the highest contribution to dynamic connectivity, ESZ patients exhibited greater impairments than CHR individuals primarily in the cerebellum, frontal cortex, thalamus and temporal cortex, while CHR and ESZ populations shared common aberrances mainly in the supplementary motor area, parahippocampal gyrus and postcentral cortex. CHR-specific changes were also found in the connections between the superior frontal gyrus and calcarine cortex in the dominant state. Our findings suggest that CHR individuals generally show an intermediate functional connectivity pattern between HCs and SZ patients but also have unique connectivity alterations.
个体处于精神病高危（CHR）状态的特点是精神病症状减弱。只有少数 CHR 个体转化为完全精神病。因此，人们强烈关注识别精神病风险综合征背后的神经生物学异常。动态功能连接（DFC）捕获短时间尺度上的时变连接，具有揭示复杂大脑功能组织的潜力。基于 70 名健康对照（HCs）、53 名 CHR 个体和 58 名早期精神病精神分裂症（ESZ）患者的静息态功能磁共振成像（fMRI）数据，我们应用一种新的组信息引导独立成分分析（GIG-ICA）从 DFC 中估计固有连接状态，然后研究组间差异。我们发现 ESZ 患者的连接异常和变化比 CHR 个体更明显。结果还表明，与疾病相关的连接状态发生在 CHR 和 ESZ 组中。关于对动态连接贡献最大的主导状态，ESZ 患者的损伤比 CHR 个体更大，主要在小脑、额叶皮层、丘脑和颞叶皮层，而 CHR 和 ESZ 人群在辅助运动区、海马旁回和中央后皮层有共同的异常。在主导状态下，还发现了 CHR 个体之间额上回和距状皮层之间的连接变化。我们的研究结果表明，CHR 个体通常表现出介于 HCs 和 SZ 患者之间的中间功能连接模式，但也有独特的连接改变。
