A task-general connectivity model reveals variation in convergence of cortical inputs to functional regions of the cerebellum.
A task-general connectivity model reveals variation in convergence of cortical inputs to functional regions of the cerebellum.
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DOI：
10.7554/elife.81511
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发表时间：
2023-04-21
期刊：
影响因子：
7.7
通讯作者：
Diedrichsen J
中科院分区：
文献类型：
--
作者：
King M;Shahshahani L;Ivry RB;Diedrichsen J
虽然静息态功能磁共振成像研究提供了人类新皮层和小脑之间的连接的一个广泛的图片，皮层输入到小脑电路的收敛程度仍然未知。小脑的每个区域是接受来自单个皮质区的输入，还是接受来自多个皮质区的汇聚输入？在这里，我们使用基于任务的功能磁共振成像数据来建立一系列的皮质-小脑连接模型，每个模型都允许不同程度的收敛。我们比较了这些模型预测小脑活动模式的能力，为新的任务集。允许某种程度的收敛的模型提供了最好的预测，认为多个皮层输入到单个小脑体素的收敛。重要的是，小脑的聚合程度各不相同，在与语言、工作记忆和社会认知相关的区域观察到的聚合程度最高。这些发现表明，小脑的功能分区支持运动和认知功能的方式存在重要差异。
While resting-state fMRI studies have provided a broad picture of the connectivity between human neocortex and cerebellum, the degree of convergence of cortical inputs onto cerebellar circuits remains unknown. Does each cerebellar region receive input from a single cortical area or convergent inputs from multiple cortical areas? Here, we use task-based fMRI data to build a range of cortico-cerebellar connectivity models, each allowing for a different degree of convergence. We compared these models by their ability to predict cerebellar activity patterns for novel Task Sets. Models that allow some degree of convergence provided the best predictions, arguing for convergence of multiple cortical inputs onto single cerebellar voxels. Importantly, the degree of convergence varied across the cerebellum with the highest convergence observed in areas linked to language, working memory, and social cognition. These findings suggest important differences in the way that functional subdivisions of the cerebellum support motor and cognitive function.