Department of Psychiatry, University of Rochester Medical Center, 601 Elmwood Ave, Rochester, NY 14642, USA; Department of Neuroscience, University of Rochester Medical Center, 601 Elmwood Ave, Rochester, NY 14642, USA; Center for Visual Science, University of Rochester, 601 Elmwood Ave, Rochester, NY 14642, USA; Department of Brain & Cognitive Science, University of Rochester, 358 Meliora Hall, P.O. Box 270268, Rochester, NY 14627, USA.
Center for Visual Science, University of Rochester, 601 Elmwood Ave, Rochester, NY 14642, USA; Department of Brain & Cognitive Science, University of Rochester, 358 Meliora Hall, P.O. Box 270268, Rochester, NY 14627, USA.
Neuroimage Clin. 2024;43:103630. doi: 10.1016/j.nicl.2024.103630. Epub 2024 Jun 9.
Past work has shown that people with schizophrenia exhibit more cross-subject heterogeneity in their functional connectivity patterns. However, it remains unclear whether specific brain networks are implicated, whether common confounds could explain the results, or whether task activations might also be more heterogeneous. Unambiguously establishing the existence and extent of functional heterogeneity constitutes a first step toward understanding why it emerges and what it means clinically.
We first leveraged data from the HCP Early Psychosis project. Functional connectivity (FC) was extracted from 718 parcels via principal components regression. Networks were defined via a brain network partition (Ji et al., 2019). We also examined an independent data set with controls, later-stage schizophrenia patients, and ADHD patients during rest and during a working memory task. We quantified heterogeneity by averaging the Pearson correlation distance of each subject's FC or task activity pattern to that of every other subject of the same cohort.
Affective and non-affective early psychosis patients exhibited more cross-subject whole-brain heterogeneity than healthy controls (ps < 0.001, Hedges' g > 0.74). Increased heterogeneity could be found in up to seven networks. In-scanner motion, medication, nicotine, and comorbidities could not explain the results. Later-stage schizophrenia patients exhibited heterogeneous connectivity patterns and task activations compared to ADHD and control subjects. Interestingly, individual connection weights, parcel-wise task activations, and network averages thereof were not more variable in patients, suggesting that heterogeneity becomes most obvious over large-scale patterns.
Whole-brain cross-subject functional heterogeneity characterizes psychosis during rest and task. Developmental and pathophysiological consequences are discussed.
过去的研究表明,精神分裂症患者的功能连接模式表现出更多的跨个体异质性。然而,目前尚不清楚是否涉及特定的大脑网络,是否常见的混杂因素可以解释结果,或者任务激活是否也更加多样化。明确建立功能异质性的存在和程度是理解其产生原因和临床意义的第一步。
我们首先利用 HCP 早期精神病项目的数据。通过主成分回归从 718 个区提取功能连接(FC)。通过脑网络分区(Ji 等人,2019 年)定义网络。我们还检查了一个具有对照、晚期精神分裂症患者和 ADHD 患者的独立数据集,在休息和工作记忆任务期间进行。我们通过平均每个受试者的 FC 或任务活动模式与同一队列中每个其他受试者的 Pearson 相关距离来量化异质性。
情感和非情感早期精神病患者的全脑跨个体异质性高于健康对照组(ps<0.001,Hedges' g>0.74)。多达七个网络可以发现增加的异质性。在扫描仪内运动、药物、尼古丁和合并症不能解释结果。与 ADHD 和对照组相比,晚期精神分裂症患者表现出连接模式和任务激活的异质性。有趣的是,个体连接权重、区组任务激活以及网络平均值在患者中并没有更高的可变性,这表明异质性在大尺度模式中最为明显。
全脑跨个体功能异质性特征描述了休息和任务期间的精神病。讨论了发展和病理生理学后果。