Department of Neuroscience (DNS), University of Padova, Padova, Italy.
Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
Hum Brain Mapp. 2021 Dec 15;42(18):6087-6098. doi: 10.1002/hbm.25671. Epub 2021 Sep 29.
Catatonia is a transnosologic psychomotor syndrome with high prevalence in schizophrenia spectrum disorders (SSD). There is mounting neuroimaging evidence that catatonia is associated with aberrant frontoparietal, thalamic and cerebellar regions. Large-scale brain network dynamics in catatonia have not been investigated so far. In this study, resting-state fMRI data from 58 right-handed SSD patients were considered. Catatonic symptoms were examined on the Northoff Catatonia Rating Scale (NCRS). Group spatial independent component analysis was carried out with a multiple analysis of covariance (MANCOVA) approach to estimate and test the underlying intrinsic components (ICs) in SSD patients with (NCRS total score ≥ 3; n = 30) and without (NCRS total score = 0; n = 28) catatonia. Functional network connectivity (FNC) during rest was calculated between pairs of ICs and transient changes in connectivity were estimated using sliding windowing and clustering (to capture both static and dynamic FNC). Catatonic patients showed increased static FNC in cerebellar networks along with decreased low frequency oscillations in basal ganglia (BG) networks. Catatonic patients had reduced state changes and dwelled more in a state characterized by high within-network correlation of the sensorimotor, visual, and default-mode network with respect to noncatatonic patients. Finally, in catatonic patients according to DSM-IV-TR (n = 44), there was a significant correlation between increased within FNC in cortico-striatal state and NCRS motor scores. The data support a neuromechanistic model of catatonia that emphasizes a key role of disrupted sensorimotor network control during distinct functional states.
紧张症是一种具有较高普遍性的跨学科精神运动综合征，存在于精神分裂症谱系障碍（SSD）中。越来越多的神经影像学证据表明，紧张症与异常的额顶叶、丘脑和小脑区域有关。迄今为止，还没有研究过紧张症的大规模大脑网络动力学。在这项研究中，考虑了 58 名右利手 SSD 患者的静息态 fMRI 数据。使用 Northoff 紧张症评定量表（NCRS）检查紧张症症状。采用多元协方差分析（MANCOVA）方法进行组空间独立成分分析，以估计和测试 SSD 患者（NCRS 总分≥3；n=30）和无紧张症（NCRS 总分=0；n=28）的潜在内在成分（ICs）。在休息时，使用滑动窗口和聚类方法计算 IC 之间的功能网络连接（FNC），以估计连接的瞬态变化（以捕获静态和动态 FNC）。紧张症患者的小脑网络中存在静息状态 FNC 增加，而基底节（BG）网络中的低频振荡减少。与非紧张症患者相比，紧张症患者的状态变化减少，更多地处于以感觉运动、视觉和默认模式网络之间的网络内相关性高为特征的状态。最后，在根据 DSM-IV-TR 分类的紧张症患者（n=44）中，皮质-纹状体状态下 FNC 增加与 NCRS 运动评分之间存在显著相关性。这些数据支持紧张症的神经机制模型，该模型强调了在不同功能状态下感觉运动网络控制中断的关键作用。
