Increased functional network segregation in glioma patients post-therapy: a neurological compensatory response or catastrophe for cognition?

Background: The brain operates through networks of interconnected regions, which can be disrupted by glial tumors and their treatment. This study investigates associations between thisaltered functional network topology and cognition in gliomas.

Methods: We studied 50 adult glioma survivors (>1-year post-therapy) and 50 healthy controls. Participants underwent cognitive assessments across six domains and an 8-minute resting-state functional MRI. Based on the BOLD signal, partial correlations were computed among 78 brain regions. From their absolute values, whole-brain and nodal graph metrics were derived and normalized to random graphs. Group differences in whole-brain and nodal graph metrics were assessed with Mann-Whitney U tests and mixed-design ANOVAs respectively. Metrics exhibiting significant intergroup differences were correlated with cognitive scores, with pbonf<.050 indicating significance.

Results: Among controls, 8/78 nodes were identified as hubs. Patients exhibited significantly higher whole-brain clustering, correlating with intelligence (r(98)=-.409,pbonf<.001) and executive functioning (r(98)=.300, pbonf=.014). Lower centrality, higher nodal clustering and assortativity were also observed in patients, particularly in hubs, correlating with language and executive functioning, respectively (all r(98)>.300, pbonf<.050).

Conclusion: Glioma patients commonly experience cognitive deficits alongside post-treatment alterations in functional network topology. Alterations in clustering, assortativity and centralitymay specifically act as compensatory mechanisms, significantly influencing cognitive function.

Cross-disease research has highlighted the importance of functional networks in cognitive functioning. Given that these networks can be disrupted by glial tumors and their treatment, our study examines the relationship between cognitive performance and altered functional network topology using resting-state fMRI in a sizable prospective cohort of 50 glioma survivors and 50 matched healthy controls.

With this study, we reveal significant alterations in the functional network topology and its hubs in glioma survivors, of which specific graph measures appeared to be specifically valuable in predicting executive functioning and language outcomes. These insights underscore the importance of network-based approaches in future research to better understand and address these deficits, certainly given that functional networks and their hubs are understudied in this population.