Neural network mapping of gelastic behavior in children with hypothalamus hamartoma  

作　　者：Zhi‑Hao Guo Jian‑Guo Zhang Xiao‑Qiu Shao Wen‑Han Hu Lin Sang Zhong Zheng Chao Zhang Xiu Wang Chun‑De Li Jia‑Jie Mo Kai Zhang 

机构地区：[1]Department of Neurosurgery,Beijing Tiantan Hospital,Capital Medical University,No.119 South 4th Ring West Road,Fengtai District,Beijing 100070,China [2]Department of Neurosurgery,Beijing Neurosurgical Institute,Capital Medical University,Beijing,China [3]Department of Neurology,Beijing Tiantan Hospital,Capital Medical University,Beijing,China [4]Department of Neurosurgery,Beijing Fengtai Hospital,Beijing,China

出　　处：《World Journal of Pediatrics》2024年第7期735-745,共11页世界儿科杂志（英文版）

基　　金：supported by Capital’s Funds for Health Improvement and Research(2022-1-1071,2020-2-1076);the National Natural Science Foundation of China(82071457);the National Key R&D Program of China(2021YFC2401201).

摘　　要：Background Hypothalamus hamartomas(HHs)are rare,congenital,tumor-like,and nonprogressive malformations resulting in drug-resistant epilepsy,mainly affecting children.Gelastic seizures(GS)are an early hallmark of epilepsy with HH.The aim of this study was to explore the disease progression and the underlying physiopathological mechanisms of pathological laughter in HH.Methods We obtained clinical information and metabolic images of 56 HH patients and utilized ictal semiology evaluation to stratify the specimens into GS-only,GS-plus,and no-GS subgroups and then applied contrasted trajectories inference(cTI)to calculate the pseudotime value and evaluate GS progression.Ordinal logistic regression was performed to identify neuroimaging-clinical predictors of GS,and then voxelwise lesion network-symptom mapping(LNSM)was applied to explore GS-associated brain regions.Results cTI inferred the specific metabolism trajectories of GS progression and revealed increased complexity from GS to other seizure types.This was further validated via actual disease duration(Pearson R=0.532,P=0.028).Male sex[odds ratio(OR)=2.611,P=0.013],low age at seizure onset(OR=0.361,P=0.005),high normalized HH metabolism(OR=−1.971,P=0.037)and severe seizure burden(OR=−0.006,P=0.032)were significant neuroimaging clinical predictors.LNSM revealed that the dysfunctional cortico-subcortico-cerebellar network of GS and the somatosensory cortex(S1)represented a negative correlation.Conclusions This study sheds light on the clinical characteristics and progression of GS in children with HH.We identified distinct subtypes of GS and demonstrated the involvement of specific brain regions at the cortical–subcortical–cerebellar level.These valuable results contribute to our understanding of the neural correlates of GS.

关 键 词：Contrasted trajectories inference Gelastic seizure Hypothalamus hamartoma Lesion network-symptom mapping Neural basis 

分 类 号：R72[医药卫生—儿科]