Wallace H. Coulter Department of Biomedical Engineering at Georgia Institute of Technology and Emory University, Atlanta, GA, United States of America; Department of Electrical and Computer Engineering at Georgia Institute of Technology, Atlanta, GA, United States of America; Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United States of America.
Departments of Psychiatry and Neuroscience, Yale University, School of Medicine, New Haven, CT, United States of America; Olin Neuropsychiatry Research Center, Hartford, CT, United States of America.
Schizophr Res. 2021 Feb;228:103-111. doi: 10.1016/j.schres.2020.11.055. Epub 2021 Jan 9.
Although visual processing impairments have been explored in schizophrenia (SZ), their underlying neurobiology of the visual processing impairments has not been widely studied. Also, while some research has hinted at differences in information transfer and flow in SZ, there are few investigations of the dynamics of functional connectivity within visual networks. In this study, we analyzed resting-state fMRI data of the visual sensory network (VSN) in 160 healthy control (HC) subjects and 151 SZ subjects. We estimated 9 independent components within the VSN. Then, we calculated the dynamic functional network connectivity (dFNC) using the Pearson correlation. Next, using k-means clustering, we partitioned the dFNCs into five distinct states, and then we calculated the portion of time each subject spent in each state, which we termed the occupancy rate (OCR). Using OCR, we compared HC with SZ subjects and investigated the link between OCR and visual learning in SZ subjects. Besides, we compared the VSN functional connectivity of SZ and HC subjects in each state. We found that this network is indeed highly dynamic. Each state represents a unique connectivity pattern of fluctuations in VSN FNC, and all states showed significant disruption in SZ. Overall, HC showed stronger connectivity within the VSN in states. SZ subjects spent more time in a state in which the connectivity between the middle temporal gyrus and other regions of VNS is highly negative. Besides, OCR in a state with strong positive connectivity between the middle temporal gyrus and other regions correlated significantly with visual learning scores in SZ.
尽管精神分裂症 (SZ) 中已经探索了视觉处理障碍，但它们的视觉处理障碍的潜在神经生物学尚未得到广泛研究。此外，虽然一些研究暗示了 SZ 中信息传递和流动的差异，但很少有研究调查视觉网络内功能连接的动态。在这项研究中，我们分析了 160 名健康对照 (HC) 受试者和 151 名 SZ 受试者的静息状态 fMRI 数据。我们在 VSN 中估计了 9 个独立成分。然后，我们使用 Pearson 相关系数计算动态功能网络连接 (dFNC)。接下来，使用 k-均值聚类，我们将 dFNC 分为五个不同的状态，然后计算每个状态每个受试者花费的时间比例，我们称之为占用率 (OCR)。使用 OCR，我们比较了 HC 和 SZ 受试者，并研究了 OCR 与 SZ 受试者视觉学习之间的关系。此外，我们比较了每个状态下 SZ 和 HC 受试者的 VSN 功能连接。我们发现这个网络确实是高度动态的。每个状态代表 VSN FNC 波动的独特连接模式，所有状态在 SZ 中都显示出明显的中断。总体而言，HC 在状态下显示出更强的 VSN 内连接。SZ 受试者在连接高度负相关的状态下花费更多的时间。此外，中间颞叶与 VNS 其他区域之间具有强正连接的状态中的 OCR 与 SZ 中的视觉学习得分显著相关。
