The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, China; Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany; Faculty of Psychology, Southwest University, Chongqing 400715, China.
McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, United States; Massachusetts General Hospital and Harvard Medical School, Boston, United States.
Neuroimage Clin. 2022;36:103176. doi: 10.1016/j.nicl.2022.103176. Epub 2022 Aug 29.
High co-morbidity and substantial overlap across psychiatric disorders encourage a transition in psychiatry research from categorical to dimensional approaches that integrate neuroscience and psychopathology. Converging evidence suggests that the cerebellum is involved in a wide range of cognitive functions and mental disorders. An important question thus centers on the extent to which cerebellar function can be linked to transdiagnostic dimensions of psychopathology. To address this question, we used a multivariate data-driven statistical technique (partial least squares) to identify latent dimensions linking human cerebellar connectome as assessed by functional MRI to a large set of clinical, cognitive, and trait measures across 198 participants, including healthy controls (n = 92) as well as patients diagnosed with attention-deficit/hyperactivity disorder (n = 35), bipolar disorder (n = 36), and schizophrenia (n = 35). Macroscale spatial gradients of connectivity at voxel level were used to characterize cerebellar connectome properties, which provide a low-dimensional representation of cerebellar connectivity, i.e., a sensorimotor-supramodal hierarchical organization. This multivariate analysis revealed significant correlated patterns of cerebellar connectivity gradients and behavioral measures that could be represented into four latent dimensions: general psychopathology, impulsivity and mood, internalizing symptoms and executive dysfunction. Each dimension was associated with a unique spatial pattern of cerebellar connectivity gradients across all participants. Multiple control analyses and 10-fold cross-validation confirmed the robustness and generalizability of the yielded four dimensions. These findings highlight the relevance of cerebellar connectivity as a necessity for the study and classification of transdiagnostic dimensions of psychopathology and call on researcher to pay more attention to the role of cerebellum in the dimensions of psychopathology, not just within the cerebral cortex.
高共病率和精神障碍之间的大量重叠促使精神病学研究从分类方法向整合神经科学和精神病理学的维度方法转变。越来越多的证据表明,小脑参与了广泛的认知功能和精神障碍。因此,一个重要的问题是小脑功能与精神病理学的跨诊断维度之间的联系程度。为了解决这个问题,我们使用了一种多变量数据驱动的统计技术(偏最小二乘法),根据 198 名参与者的大量临床、认知和特质测量数据,包括健康对照者(n=92)、注意力缺陷多动障碍患者(n=35)、双相情感障碍患者(n=36)和精神分裂症患者(n=35),来识别将人类小脑连接组(由功能磁共振成像评估)与大样本的临床、认知和特质测量数据联系起来的潜在维度。利用体素水平的连接宏观空间梯度来描述小脑连接组的特征,为小脑连接提供了一个低维表示,即感觉运动-超模态层次组织。这种多变量分析揭示了小脑连接梯度和行为测量之间存在显著的相关模式,可以将其表示为四个潜在维度:一般精神病理学、冲动性和情绪、内化症状和执行功能。每个维度都与所有参与者的小脑连接梯度的独特空间模式相关。多项对照分析和 10 倍交叉验证证实了所产生的四个维度的稳健性和可推广性。这些发现强调了小脑连接的重要性,这是研究和分类精神病理学跨诊断维度的必要条件,并呼吁研究人员更加关注小脑在精神病理学维度中的作用,而不仅仅是在大脑皮层中。