Using network analytics, we sought to determine whether neighborhood disadvantage was associated with disruptions to the intrinsic cognitive networks of persons with Juvenile Myoclonic Epilepsy (JME). 62 participants with JME were categorized into high (n = 18) and low (n = 44) disadvantaged groups using the Area Deprivation Index and compared to 44 controls as to the network properties of their cognitive networks. The networks were interrogated using test metrics from a comprehensive neuropsychological test battery that assessed intellectual ability, language, visouperception/construction, learning and memory, executive function, and speed-dependent abilities. Network analyses demonstrated graded increases in overall connectivity and association strength across groups (controls < low-disadvantage JME< high-disadvantage JME), with the high-disadvantage JME group showing the greatest number of positive correlations and strongest inter-test associations. Community structure differed across groups, with reduced modularity and less differentiated cognitive networks in JME, particularly in the high-disadvantage group, suggesting over-integration and reduced network segregation. Regression analyses identified antiseizure medication load as a significant predictor of global efficiency in low-disadvantage JME only, with no significant clinical seizure predictors observed in the high-disadvantage JME group. The results indicate that structural (neighborhood) disadvantage is associated with detectable adverse effects on the underlying cognitive networks of persons with JME. While the cognitive status of JME has long been known to be adversely affected, the results reported here demonstrate that fundamental shifts in underlying cognitive network properties are associated with disadvantage, characterized by an abnormally highly integrated and less modular (differentiated) network structure.
Garcia‐Ramos et al. (Thu,) studied this question.