Аннотация:Network neuroscience explores the brain's connectome, demonstrating that dynamicneural networks support cognitive functions. This study investigates how distinctcognitive abilities—working memory and cognitive inhibitory control—are supportedby unique brain network configurations constructed by estimating whole-brain networksusing mutual information. The study involved 195 participants who completedthe Sternberg Item Recognition task and Flanker tasks while undergoing electroencephalographyrecording. A mixed-effects linear model analyzed the influence of networkmetrics on cognitive performance, considering individual differences and taskspecificdynamics. The findings indicate that working memory and cognitive inhibitorycontrol are associated with different network attributes, with working memoryrelying on distributed networks and cognitive inhibitory control on more segregatedones. Our analysis suggests that both strong and weak connections contribute tocognitive processes, with weak connections potentially leading to a more stable andsupport networks of memory and cognitive inhibitory control. The findings indirectlysupport the network neuroscience theory of intelligence, suggesting different functionaltopology of networks inherent to various cognitive functions. Nevertheless,we propose that understanding individual variations in cognitive abilities requires recognizingboth shared and unique processes within the brain's network dynamics.