Inhibitory Control Network Connectivity and Social Adjustment After Pediatric Brain Tumour Treatment
Katie Wade Alonso, Laura Ferlanti, Fatma Al-Rubeye, Michael Zara, Julie Tseng, Eden Cohen, Suzanne Laughlin, Donald J MabbottAbstract
Background
Risk factors for poor social adjustment after brain tumour treatment are not well established. Prior work implicates age, sex, treatment factors, and inhibitory control performance. However, it’s unknown whether functional and structural brain connectivity within inhibitory control networks can help explain social outcomes after treatment.
Methods
Using magnetoencephalography, the Go/No-Go task, diffusion-weighted imaging, and the Pediatric Quality of Life (PedsQL) questionnaire, we quantified differences in inhibitory control, supporting brain connectivity, and social adjustment between children treated for brain tumours (n = 15) and typically developing controls (TDC; n = 11).
Results
Relative to TDC, children treated for brain tumours showed significantly (1) reduced low gamma neural communication between networks important for inhibitory control, indexed by lower weighted phase lag indices (wPLI); (2) disrupted white matter microstructure between these networks, indexed by lower intra-axonal and higher extra-axonal diffusivity metrics; and (3) lower parent-reported social adjustment based on the PedsQL. In robust regressions across participants, poorer social adjustment was associated with female sex, more treatments and complications, reduced low gamma wPLI underlying inhibitory control within key networks, and more diffuse white matter damage. Groups did not significantly differ in Go/No-Go performance, and performance was not related to social outcomes.
Conclusions
These findings suggest that both specific perturbations to functional connectivity within inhibitory control networks and broad damage to structural connectivity contribute to social difficulties after brain tumour treatment. These results provide preliminary evidence that measures of network connectivity could inform approaches for identifying children at greatest risk of social difficulties and guiding prioritization of supports.