Abstract
Posterior fossa syndrome (PFS) consists of three types of symptom (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 PFS patients mostly focused on the association between structural abnormalities that occur during PFS, 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 PFS, since the symptomatology is primarily an output of cerebral operation. 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. This study applied a network approach to children with PFS. Scaling of each symptom domain was used to quantify the dynamics of the syndrome. An individual cerebrocerebellar functional network analysis was then performed to determine the network dynamics during PFS. Cross-validation of clinical neurophysiology and functional neuroscience suggested the critical role of the pECP within PFS from the network analysis. 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.
Functional Network Analysis Reveals Extended Gliomagenesis Pathway Maps and Three Novel MYC-Interacting Genes in Human Gliomas
