Individual cerebrocerebellar functional network analysis decoding symptomatologic dynamics of postoperative cerebellar mutism syndrome

Ko-Ting Chen, T. Ho, T. Siow, Yu-Chiang Yeh, Sheng-Yao Huang
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引用次数: 1

Abstract

Abstract Introduction Postoperative cerebellar mutism syndrome (pCMS) consists of three types of symptoms (motoric, linguistic, and neurobehavioral) in patients with posterior fossa pathologies. The evolutional mechanism of this high cognitive syndromic complex from cerebellar origin remains unconfirmed. Previous studies analyzing CMS patients mostly focused on the association between structural abnormalities that occur during CMS, of which proximal efferent cerebellar pathway (pECP) injury appears to be the most common pathogenesis. However, structural imaging may not be sensitive enough to determine the dynamic course of CMS, since the symptomatology is primarily an output of cerebral operation. Method We took a network approach in a child during her course of development and recovery of the pCMS. On the other hand, a network neuroscience approach using a mathematical model to extract information from functional imaging to generate interregional connectivity provides abundant evidence that the cerebellum is influential in modulating cerebral functions. Result This study applied a network approach to children with pCMS. An individual cerebrocerebellar functional network analysis using graph theory was then performed to determine the network dynamics during CMS. Cross-validation of clinical neurophysiology and functional neuroscience suggested the critical role of the pECP within CMS from the network analysis. Conclusion The employed approach was therefore useful in determining the complex clinical symptoms using individual functional network analysis, which bridges the gap between structural neuroimaging and clinical neurophysiology.
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个体脑脊髓功能网络分析解码术后小脑缄默症综合征的症状动力学
术后小脑性缄默症(pCMS)由三种类型的症状(运动、语言和神经行为)组成。这种源自小脑的高认知综合征的进化机制仍未得到证实。以往分析CMS患者的研究主要集中在CMS期间发生的结构异常之间的关系,其中近端传出小脑通路(pECP)损伤似乎是最常见的发病机制。然而,结构成像可能不够灵敏,无法确定CMS的动态过程,因为症状主要是脑手术的结果。方法对1例患儿的pCMS发育及恢复过程进行网络分析。另一方面,网络神经科学方法使用数学模型从功能成像中提取信息以产生区域间连接,提供了大量证据表明小脑在调节大脑功能方面具有影响力。结果本研究采用网络方法对pCMS患儿进行研究。然后使用图论进行个体脑小脑功能网络分析,以确定CMS期间的网络动态。临床神经生理学和功能神经科学的交叉验证表明,从网络分析pECP在CMS中的关键作用。结论采用个体功能网络分析方法确定复杂的临床症状,弥补了结构神经影像学与临床神经生理学之间的差距。
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