Preserved but not functional: growth biology shapes connectivity resilience in meningioma and glioma
Brain tumors disrupt neural connectivity, but the nature of this disruption depends on tumor growth biology. Here, we analyze pre-operative structural connectivity (SC), functional connectivity (FC), and generalized effective connectivity (GEC) in 14 meningioma patients, 10 glioma patients, and 10 matched controls to characterize how extra-axial and intra-axial tumors differentially affect brain networks. We introduce FC resilience, the relative preservation of functional connectivity in structurally damaged regions, and find that meningioma patients exhibit significantly higher FC resilience than glioma patients, with SC-dominant damage and preserved neural activity in damaged regions. Glioma patients show balanced SC-FC damage and degraded neural activity, consistent with infiltrative destruction of both white matter and neural substrate. Connectivity damage is not localized to the tumor vicinity and is non-randomly distributed across functional networks, with distinct propagation patterns: glioma SC damage clusters along white matter pathways, while meningioma SC damage preferentially targets Limbic and Default networks. Network topology analysis reveals that more segregated functional and effective connectivity, particularly higher modularity, predicts FC resilience in meningioma patients but not in glioma patients, while structural connectivity topology shows no predictive value. Non-equilibrium dynamics, quantified via the Fluctuation-Dissipation Theorem, are elevated in damaged regions of meningioma patients, serving as a dynamical marker of structural damage rather than an independent compensatory mechanism. Clinically, higher FC resilience in glioma patients is associated with worse cognitive outcomes, suggesting that preserved FC without an intact neural substrate does not reflect genuine functional preservation. These findings demonstrate that the interpretation of functional connectivity resilience depends fundamentally on tumor type and its underlying growth biology.