P01.10.B The relation between executive functioning and MEG multilayer network centrality in glioma patients

Abstract

Abstract Background Many patients with glioma suffer from deficits in executive functioning (EF), regardless of tumor location and size. While some patients experience improving EF after tumor resection, others deteriorate over time. This variability in cognitive trajectories is still poorly understood, but neuroscientific approaches that view the brain as a network may bear correlative and predictive value in this respect. Particularly integrative network connectivity of the fronto-parietal network are crucial for EF, but studies so far have only investigated isolated neural frequency bands of interest. Here, we synergize fronto-parietal network connectivity across frequency bands and test its explanatory power for EF at diagnosis and 1 year after tumor resection. Material and Methods Patients with diffuse glioma (n=37) underwent neuropsychological assessments, including three tests for EF, and resting-state magnetoencephalography (MEG) at both time points. Patients’ EF performance was standardized to z-scores using validated norm scores, adjusting for age, sex and education. MEG was source-reconstructed using patients’ MRI in combination with a beamformer approach and time series were filtered into six classical frequency bands. Band-specific functional connectivity between 78 cortical regions was estimated, after which an interconnected multilayer, multi-frequency network was created per patient. Multilayer centrality was then calculated as a measure of integrative network connectivity per region, and averaged over all fronto-parietal network regions to yield a single value reflecting integrative, multi-frequency network connectivity per patient at each time point. Results At diagnosis, eight patients had z-scores <-1.5, indicating clinically relevant cognitive deficits. Preoperatively, poorer performance on the Concept Shifting Task was associated with lower multilayer centrality (p=.017), while improving performance on this task from diagnosis to 1 year after resection was associated with an increase in multilayer centrality (p=.022). Multilayer centrality at diagnosis did not significantly predict EF at follow-up. Conclusion Our results establish a significant relationship between poorer and decreasing EF with lower and decreasing multilayer, multi-frequency integrative connectivity of the fronto-parietal network in glioma patients. Studies with larger and more homogeneous samples may further explore the relevance of this multilayer approach in understanding and particularly predicting postoperative decline in EF in these patients, as our sample was characterized by large heterogeneity in cognitively relevant patient and tumor characteristics.