McConnell Brain Imaging Centre, Department of Biomedical Engineering, Faculty of Medicine, School of Computer Science, The Neuro-Montreal Neurological Institute (MNI), McGill University, Montreal, Quebec, Canada.
Mila-Quebec Artificial Intelligence Institute, Montreal, Quebec, Canada.
J Neurophysiol. 2024 Sep 1;132(3):849-869. doi: 10.1152/jn.00164.2024. Epub 2024 Jul 25.
The human cerebellum is increasingly recognized to be involved in nonmotor and higher-order cognitive functions. Yet, its ties with the entire cerebral cortex have not been holistically studied in a whole brain exploration with a unified analytical framework. Here, we characterized dissociable cortical-cerebellar structural covariation patterns based on regional gray matter volume (GMV) across the brain in = 38,527 UK Biobank participants. Our results invigorate previous observations in that important shares of cortical-cerebellar structural covariation are described as ) a dissociation between the higher-level cognitive system and lower-level sensorimotor system and ) an anticorrelation between the visual-attention system and advanced associative networks within the cerebellum. We also discovered a novel pattern of ipsilateral, rather than contralateral, cerebral-cerebellar associations. Furthermore, phenome-wide association assays revealed key phenotypes, including cognitive phenotypes, lifestyle, physical properties, and blood assays, associated with each decomposed covariation pattern, helping to understand their real-world implications. This systems neuroscience view paves the way for future studies to explore the implications of these structural covariations, potentially illuminating new pathways in our understanding of neurological and cognitive disorders. Cerebellum's association with the entire cerebral cortex has not been holistically studied in a unified way. Here, we conjointly characterize the population-level cortical-cerebellar structural covariation patterns leveraging ∼40,000 UK Biobank participants whole brain structural scans and ∼1,000 phenotypes. We revitalize the previous hypothesis of an anticorrelation between the visual-attention system and advanced associative networks within the cerebellum. We also discovered a novel ipsilateral cerebral-cerebellar associations. Phenome-wide association (PheWAS) revealed real-world implications of the structural covariation patterns.
人类小脑越来越被认为参与非运动和更高阶的认知功能。然而，在使用统一分析框架对整个大脑进行的全脑探索中，其与整个大脑皮层的联系尚未得到全面研究。在这里，我们在 38527 名英国生物库参与者中，基于大脑中区域灰质体积（GMV）的特征描述了可分离的皮质-小脑结构协变模式。我们的结果激发了以前的观察结果，即重要的皮质-小脑结构协变份额被描述为）高级认知系统与低级感觉运动系统之间的分离和）小脑内视觉注意系统与高级联想网络之间的负相关。我们还发现了同侧而不是对侧大脑-小脑关联的新模式。此外，表型全基因组关联分析揭示了关键的表型，包括认知表型、生活方式、身体特征和血液检测，与每个分解的协变模式相关，有助于理解它们在现实世界中的意义。这种系统神经科学观点为未来研究探索这些结构协变的意义铺平了道路，可能为我们理解神经和认知障碍提供新的途径。小脑与整个大脑皮层的联系尚未以统一的方式进行整体研究。在这里，我们利用约 40000 名英国生物库参与者的全脑结构扫描和约 1000 种表型，共同描述了皮质-小脑结构协变模式的人群水平特征。我们振兴了小脑内视觉注意系统与高级联想网络之间存在负相关的先前假设。我们还发现了一种新的同侧大脑-小脑关联。表型全基因组关联分析（PheWAS）揭示了结构协变模式的现实意义。
