4.6 Article

Impaired Functional Homotopy and Topological Properties Within the Default Mode Network of Children With Generalized Tonic-Clonic Seizures: A Resting-State fMRI Study

期刊

FRONTIERS IN NEUROSCIENCE
卷 16, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fnins.2022.833837

关键词

generalized tonic-clonic seizure children; default-mode network; voxel-mirrored homotopic connectivity; graph theory; support vector machine

资金

  1. National Natural Science Foundation of China [81601483]
  2. Medical Science and Technology Research Foundation of Guangdong Province [A2021076]
  3. Key-Ares Research and Development Program of Guangdong Province [2020B1111100001]
  4. Administration of Traditional Chinese Medicine of Guangdong Province [20221099]
  5. China Scholarship Council [201906785005]
  6. Huang Zhendong Research Fund for Traditional Chinese Medicine of Jinan University

向作者/读者索取更多资源

This study examined the interhemispheric functional connectivity and topological organization within the default-mode network (DMN) in children with generalized tonic-clonic seizures (GTCS). The results showed significant changes in connectivity and organization in the DMN of GTCS patients. Decreased homotopic coordination in the DMN can be used as an effective biomarker to reflect seizure effects and distinguish children with GTCS from typically developing children.
IntroductionThe aim of the present study was to examine interhemispheric functional connectivity (FC) and topological organization within the default-mode network (DMN) in children with generalized tonic-clonic seizures (GTCS). MethodsResting-state functional MRI was collected in 24 children with GTCS and 34 age-matched typically developing children (TDC). Between-group differences in interhemispheric FC were examined by an automated voxel-mirrored homotopic connectivity (VMHC) method. The topological properties within the DMN were also analyzed using graph theoretical approaches. Consistent results were detected and the VMHC values were extracted as features in machine learning for subject classification. ResultsChildren with GTCS showed a significant decrease in VMHC in the DMN, including the hippocampal formation (HF), lateral temporal cortex (LTC), and angular and middle frontal gyrus. Although the patients exhibited efficient small-world properties of the DMN similar to the TDC, significant changes in regional topological organization were found in the patients, involving the areas of the bilateral temporal parietal junction, bilateral LTC, left temporal pole, and HF. Within the DMN, disrupted interhemispheric FC was found between the bilateral HF and LTC, which was consistent with the VMHC results. The VMHC values in bilateral HF and LTC were significantly correlated with clinical information in patients. Support vector machine analysis using average VMHC information in the bilateral HF and LTC as features achieved a correct classification rate of 89.34% for the classification. ConclusionThese results indicate that decreased homotopic coordination in the DMN can be used as an effective biomarker to reflect seizure effects and to distinguish children with GTCSs from TDC.

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