Keywords: Structural Connectivity, Neuroscience, Prematurity
Motivation: Prematurity is associated with heterogeneous cognitive outcomes. How connectomes developed for cognitive functioning remains unclear for preterm adults.
Goal(s): To investigate the developmental trajectories in adults born preterm of different cognitive outcome.
Approach: This study uses unsupervised learning algorithms to define a subgroup of preterm-born adults with generally reduced cognitive function and compared their network properties with control and cognitively higher-performing preterm-born participants.
Results: Significant differences were observed in network measures, including increased global efficiency and clustering coefficient in the higher-performing group, and increased betweenness centrality in the lower-performing group. This stratification cannot be explained by birth weight, gestation age or nutritional history.
Impact: This study suggests compensatory mechanisms leading to a divergent state of structural connectome i.e. 2 or more optimal states of network topologies achieving the same cognitive ability in adults born preterm.
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