DOI: https://doi.org/10.21203/rs.3.rs-1052526/v1
Cognitive dysfunction related to opioid use disorder (OUD) requires investigation of the interconnected network of cognitive domains through behavioral experiments and graph data modeling. Here, we conducted n-back, selective and divided attention, and Wisconsin card sorting tests and then reconstructed the interactive cognitive network of subscales or domains for opioid users and non-users to identify the most central cognitive functions and their connections using graph model analysis. Then, each network was analyzed topologically based on the betweenness and closeness centrality measures. Results from the opioid users’ network show that in the divided attention module, the reaction time and the number of commission errors were the most central subscales of cognitive function. Whereas in non-users, the number of correct responses and commission errors were the most central cognitive measure. These findings corroborate that opioid users show impaired divided attention as higher reaction time and errors in performing the tasks. Divided attention is the most central cognitive function in both OUD subjects and non-users, although differences were observed between the subscales of the two groups. Therefore, divided attention is a promising target for future cognitive therapies, treatments and rehabilitation as its improvement may lead to an enhancement of overall cognitive domain performance.