Mamah Daniel, Chen Shing Shiun, Gordon Evan, Kandala Sridhar, Barch Deanna M, Harms Michael P
Department of Psychiatry, Washington University Medical School, St Louis, Missouri.
Department of Radiology, Washington University Medical School, St Louis, Missouri.
Biol Psychiatry Glob Open Sci. 2024 Sep 7;4(6):100386. doi: 10.1016/j.bpsgos.2024.100386. eCollection 2024 Nov.
Existing functional connectivity studies of psychosis use population-averaged functional network maps, despite highly variable topographies of these networks across the brain surface. We aimed to define the functional network areas and topographies in the general population and the changes associated with psychotic experiences (PEs) and disorders.
Maps of 8 functional networks were generated using an individual-specific template-matching procedure for each participant from the Human Connectome Project Young Adult cohort ( = 1003) and from a matched case cohort (schizophrenia [SCZ], = 27; bipolar disorder, = 35) scanned identically with the same Connectom scanner. In the Human Connectome Project Young Adult cohort, PEs were estimated based on scores from the Achenbach Self-Report Scale. The relationship of symptoms to the probability of network representation at each cortical vertex was assessed using logistic regression.
In Human Connectome Project Young Adult participants, PE severity on the Achenbach thought problems scale was predicted by increased language network (LAN) and dorsal attention network (DAN) areas and decreased cingulo-opercular network area ( < 0.12). Significant effects were found in SCZ, with a larger DAN and LAN and a smaller frontoparietal network. Network pattern analysis in SCZ showed an increased probability of LAN in the posterior region of the left superior temporal gyrus and of the visual network in the left insula. Regression analyses in SCZ found that mood dysregulation was related to increased DAN surface area.
Those with PEs and SCZ showed abnormal functional network cortical topographies, particularly involving DAN and LAN. Network findings may predict psychosis progression and guide earlier intervention.
尽管精神病的现有功能连接性研究使用的是全人群平均功能网络图谱,但这些网络在整个脑表面的拓扑结构存在很大差异。我们旨在确定普通人群中的功能网络区域和拓扑结构,以及与精神病体验(PEs)和疾病相关的变化。
使用个体特异性模板匹配程序,为人类连接组计划青年成人队列(n = 1003)和匹配的病例队列(精神分裂症[SCZ],n = 27;双相情感障碍,n = 35)中的每位参与者生成8个功能网络的图谱,这些参与者使用相同的连接组扫描仪进行了相同的扫描。在人类连接组计划青年成人队列中,根据阿肯巴克自评量表的得分估计PEs。使用逻辑回归评估症状与每个皮质顶点网络表示概率之间的关系。
在人类连接组计划青年成人参与者中,阿肯巴克思维问题量表上的PE严重程度可通过语言网络(LAN)和背侧注意网络(DAN)区域增加以及扣带-岛盖网络区域减少来预测(P < 0.12)。在SCZ中发现了显著影响,DAN和LAN更大,额顶网络更小。SCZ的网络模式分析显示,左上颞回后部LAN和左岛叶视觉网络的概率增加。SCZ的回归分析发现,情绪调节障碍与DAN表面积增加有关。
有PEs和SCZ的人表现出异常的功能网络皮质拓扑结构,特别是涉及DAN和LAN。网络研究结果可能预测精神病的进展并指导早期干预。