CNSC-10. THE COMPLEX RELATIONSHIP BETWEEN NEURONAL ACTIVITY AND FUNCTIONAL NETWORK PROPERTIES IN GLIOMA PATIENTS

Abstract

Abstract BACKGROUND Glioma is associated with pathologically high peritumoral neuronal activity, which associates with faster tumor progression. Concurrently, glioma patients have local and widespread disturbances of the functional brain network as measured with magnetoencephalography (MEG), such as higher network clustering (the extent to which regions connected to a particular area are also connected to each other) and locally altered integrative connectivity (for instance assessed with a centrality measure). How local neuronal activity and nodal network properties relate to each other has yet to be investigated. METHODS We obtained eyes-closed resting-state MEG in 95 de novo glioma patients and 57 matched healthy controls (HCs). The offset of the power spectrum was calculated for 210 cortical atlas regions as a proxy for neuronal activity. Regional clustering coefficient (CC) and eigenvector centrality (EC) were calculated in the delta, theta and alpha bands. Offset and network values were then averaged across peritumoral regions, contralateral homologue regions and all non-peritumoral regions. Linear mixed models were used to relate nodal CC and EC to local offset in patients and HCs. RESULTS The peritumoral area was significantly more active than the non-peritumoral homologue in patients, and showed pathologically high activity in comparison to HCs. However, patients’ functional network was disturbed globally, showing higher clustering and lower centrality than HCs. Whereas high activity related to high centrality in HCs and patients alike, high activity seemed to relate to low clustering in non-peritumoral regions in patients, but not HCs. CONCLUSION We find that the relationship between neuronal activity and functional network properties is disturbed in a complex manner in glioma patients. Our results further underline the importance of investigating how local activity may impact global network topology in order to understand how neuron-glioma interactions shape brain functioning.