Graph theory in paediatric epilepsy: A systematic review

Abstract

Graph theoretical studies have been designed to investigate network topologies during life. Network science and graph theory methods may contribute to a better understanding of brain function, both normal and abnormal, throughout developmental stages. The degree to which childhood epilepsies exert a significant effect on brain network organisation and cognition remains unclear. The hypothesis suggests that the formation of abnormal networks associated with epileptogenesis early in life causes a disruption in normal brain network development and cognition, reflecting abnormalities in later life. Neurological diseases with onset during critical stages of brain maturation, including childhood epilepsy, may threaten this orderly neurodevelopmental process. According to the hypothesis that the formation of abnormal networks associated with epileptogenesis in early life causes a disruption in normal brain network development, it is then mandatory to perform a proper examination of children with new-onset epilepsy early in the disease course and a deep study of their brain network organisation over time. In regards, graph theoretical analysis could add more information. In order to facilitate further development of graph theory in childhood, we performed a systematic review to describe its application in functional dynamic connectivity using electroencephalographic (EEG) analysis, focussing on paediatric epilepsy.

The effects of hemodialysis on the functional brain connectivity in patients with end–stage renal disease: A functional near–infrared spectroscopy study

“…In graph theory, the mean clustering coe cient is de ned as a factor that evaluates how well the connection between neighboring nodes around a node is. (20,21) If the mean clustering coe cient value is high, it means that the connectivity between neighboring nodes is high, suggesting that the segregation of the brain network is high. This suggests that the e ciency of information exchanges in the brain network is high.…”

“…Graph theoretical analysis can quantitatively investigate the e cacy of brain network. (20,21) In this study, we observed changes in functional brain connectivity in patients with ESRD undergoing hemodialysis using graph theory and fNIRS. Furthermore, signi cant changes in the mean clustering coe cient, transitivity, and assortative coe cient were observed.…”

“…Functional connectivity measures were obtained from the connectivity matrix by applying a graph theoretical analysis using BRAPH and MATLAB programs. (19) We calculated the functional connectivity measures, (20,21) including average strength, global e ciency, local e ciency, mean clustering coe cient, transitivity, and assortative coe cient at the pre-, mid-, and post-HD periods in patients with ESRD.…”

Graph Theory-Based Electroencephalographic Connectivity via Phase-Locking Value and Its Association with Ketogenic Diet Responsiveness in Patients with Focal Onset Seizures

“…The extent of integration indicates the ease with which brain regions communicate, which is typically measures in terms of global efficiency [ 18 ]. The belief that seizures are the result of an imbalance between inhibitory and excitatory signals in brain connectivity has prompted many researchers to explore the role of functional connectivity in seizures [ 20 , 21 , 22 , 23 ]. One study using EEG to study fronto-temporal focal epilepsy reported increased functional connectivity (local segregation as well as global integration) in the affected hemisphere [ 22 ].…”

Translational chasm and dialogues in clinical neuroscience

“…Falsaperla et al. ( 2021 ) from Catalania in their systematic review identify the utility of graph theory in aiding the diagnosis of paediatric epilepsy, which has significant clinical implications. Pathological social withdrawal termed ‘Hikikomori’ was originally described in Japan but has since been reported in other countries including non-Asian countries.…”