Abnormal Modular Organization of Functional Networks in Cognitively Impaired Children with Frontal Lobe Epilepsy

M. J. Vaessen, H. M. H. Braakman, J. S. Heerink, J. F. A. Jansen, M. H. J. A. Debeij-van Hall, P. A. M. Hofman, A. P. Aldenkamp, W. H. Backes*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


Many children with frontal lobe epilepsy (FLE) have significant cognitive comorbidity, for which the underlying mechanism has not yet been unraveled, but is likely related to disturbed cerebral network integrity. Using resting-state fMRI, we investigated whether cerebral network characteristics are associated with epilepsy and cognitive comorbidity. We included 37 children with FLE and 41 healthy age-matched controls. Cognitive performance was determined by means of a computerized visual searching task. A connectivity matrix for 82 cortical and subcortical brain regions was generated for each subject by calculating the inter-regional correlation of the fMRI time signals. From the connectivity matrix, graph metrics were calculated and the anatomical configuration of aberrant connections and modular organization was investigated. Both patients and controls displayed efficiently organized networks. However, FLE patients displayed a higher modularity, implying that subnetworks are less interconnected. Impaired cognition was associated with higher modularity scores and abnormal modular organization of the brain, which was mainly expressed as a decrease in long-range and an increase in interhemispheric connectivity in patients. We showed that network modularity analysis provides a sensitive marker for cognitive impairment in FLE and suggest that abnormally interconnected functional subnetworks of the brain might underlie the cognitive problems in children with FLE.
Original languageEnglish
Pages (from-to)1997-2006
JournalCerebral Cortex
Issue number8
Publication statusPublished - Aug 2013


  • cognitive impairment
  • epilepsy
  • functional MRI
  • functional reorganization
  • neural networks


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