Recent research has characterized the anatomical connectivity of the cortico-cerebellar system – a large and important fibre system in the primate brain. Within this system, there are reciprocal projections between the prefrontal cortex and Crus II of the cerebellar cortex, which both play important roles in the acquisition and execution of cognitive skills. Here, we propose that this system also plays a particular role in sustaining skilled cognitive performance in patients with Relapsing-Remitting Multiple Sclerosis (RRMS), in whom advancing neuropathology causes increasingly inefficient information processing. We scanned RRMS patients and closely matched healthy subjects while they performed the Paced Auditory Serial Addition Test (PASAT), a demanding test of information processing speed, and a control task. This enabled us to localize differences between conditions that change as a function of group (group-by-condition interactions). Hemodynamic activity in some patient populations with CNS pathology are not well understood and may be atypical, so we avoided analysis strategies that rely exclusively on models of hemodynamic activity derived from the healthy brain, using instead an approach that combined a ‘model-free’ analysis technique (Tensor Independent Component Analysis, TICA) that was relatively free of such assumptions, with a post-hoc ‘model-based’ approach (General Linear Model, GLM). Our results showed group-by-condition interactions in cerebellar cortical Crus II. We suggest that this area may have in role maintaining performance in working memory tasks by compensating for inefficient data transfer associated with white matter lesions in MS.

中文翻译：

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复发缓解型多发性硬化症 (RRMS) 中的小脑信息处理。

最近的研究表征了皮质-小脑系统的解剖学连通性——灵长类动物大脑中一个大而重要的纤维系统。在这个系统中，前额叶皮层和小脑皮层的小腿 II 之间存在相互投射，它们在认知技能的获得和执行中都起着重要的作用。在这里，我们建议该系统在维持复发缓解型多发性硬化症 (RRMS) 患者的熟练认知能力方面也发挥着特殊作用，在这些患者中，神经病理学的进步导致信息处理效率越来越低。我们扫描了 RRMS 患者和密切匹配的健康受试者，同时他们执行了节奏听觉连续加法测试 (PASAT)，这是一项对信息处理速度的苛刻测试，以及一项控制任务。这使我们能够定位随组（逐组条件交互）而变化的条件之间的差异。某些中枢神经系统病变患者人群的血流动力学活动尚不清楚，可能是非典型的，因此我们避免了仅依赖于源自健康大脑的血流动力学活动模型的分析策略，而是使用结合“无模型”分析的方法技术（张量独立分量分析，TICA）相对没有此类假设，采用事后“基于模型”的方法（通用线性模型，GLM）。我们的结果显示了小脑皮质 Crus II 中的逐组相互作用。