Bermudez, G. | Search bioRxiv

bioRxiv2026

Resting-state Compensatory Remapping in Patients with Brain Tumour Before and After Surgery

Brain tumours invade neural tissue, disrupting the functional organisation of neural networks. This disruption can trigger compensatory neuroplastic mechanisms that help preserve cognitive function despite pathological burden. Resting-state functional connectivity (rs-FC) provides a valuable approach for examining these alterations, yet the scope and trajectory of network-level changes remain unclear. In this study, we used rs-FC to characterise compensatory responses induced by left-hemisphere brain tumours affecting the integrity of the language network. The comparison of connectivity patterns at diagnosis and after surgery allowed us to track the temporal progression of these patterns. Relative to healthy participants, patients showed significant deviations in pre-surgical rs-FC, with widespread changes involving the dorsal attention, sensorimotor, frontoparietal, default mode, and cerebellar networks. These differences persisted post-surgically, with no significant longitudinal modifications. Network-level alterations also influenced topological properties: patients showed increased segregation while preserving global integration relative to controls. These properties changed significantly from pre- to postoperative period, with a postoperative increase in segregation and integration towards a pattern more closely resembling that of healthy controls. Furthermore, preoperative network segregation was identified as a predictor of postoperative cognitive recovery. These findings suggest that brain tumours induce network remapping, affecting functional connectivity far beyond the regions strictly related to the affected region. The observed changes in network topological organisation likely reflect the adaptive role of domain-general networks in facilitating homeostatic processes. Surgical strategies aimed at preserving these changes seem to promote sustained cognitive function, regardless of malignancy grade or lesion extent. Key pointsO_LIPresurgical patients show widespread inter- and intrahemispheric rs-FC alterations, reflecting tumour-driven network remapping. C_LIO_LINetwork integration and segregation show longitudinal recovery, approaching neurotypical topology four months post-surgery. C_LIO_LIPreoperative network segregation predicts postoperative cognitive recovery. C_LI Importance of the StudyBrain tumours disrupt large-scale brain networks, yet the extent, temporal dynamics, and cognitive relevance of these alterations remain poorly understood. Using resting-state functional connectivity, this study provides a longitudinal, network-level characterisation of tumour-induced neuroplasticity in patients with left-hemisphere lesions affecting language-related regions. Compared with prior work focused on local effects or single networks, our results demonstrate widespread inter- and intrahemispheric connectivity changes involving multiple domain-general resting-state networks, highlighting extensive network remapping beyond lesion boundaries. Importantly, we show that postoperative recovery is accompanied by a rebalancing of network integration and segregation toward a neurotypical configuration. Critically, preoperative network segregation emerges as a predictor of postoperative cognitive recovery, identifying a potential biomarker of resilience. These findings have direct translational relevance, suggesting that preserving and supporting large-scale network organisation during surgical planning may promote cognitive outcomes independently of tumour grade or lesion extent.

neuroscience↗

bioRxiv2025

Contralesional grey matter volume as an index of macrostructural plasticity in patients with brain tumors

This research challenges the traditional localizationist view that brain tumors affect only regions directly associated with the lesion, by examining whether they also induce macrostructural alterations in the contralesional hemisphere. We applied Voxel-Based Morphometry, linear regression, and Principal Component Analysis (PCA) to a cohort of 107 adults, including patients with gliomas in the language-dominant left hemisphere and healthy participants. Unlike previous studies, a subset of the clinical population was followed longitudinally for up to four months after oncological treatment, allowing us to describe the temporal progression of structural grey matter changes. Interestingly, a principal component model based on anomaly detection enabled robust differentiation between patients and controls. Patients exhibited significantly greater grey matter volume in the contralesional hemisphere compared to healthy participants, and these structural differences evolved over time, improving the models AUC-ROC metrics. Although exploratory, a correlation analysis revealed that these structural changes were negatively associated with postsurgical cognitive performance. Together with the PCA findings, these results suggest that brain tumors induce extensive and dynamic adaptive mechanisms in the contralateral, unaffected hemisphere, likely reflecting altered patterns of structural covariance rather than simple regional volume increases. Understanding whether these changes could represent potential predictors of postoperative cognitive recovery is crucial for developing comprehensive clinical strategies. Key PointsO_LILeft-hemisphere tumors induce contralesional grey matter increases pre- and post-sugery C_LIO_LIPCA detects altered structural covariance and distinguishes patients from healthy participants C_LIO_LIContralesional grey matter volume changes correlate with postoperative cognitive performance C_LI Importance of the StudyThis study challenges the traditional view that brain tumors cause only localized effects by demonstrating widespread macrostructural alterations in the contralesional hemisphere. We reveal increased grey matter volume and altered patterns of structural covariance outside the tumor region. Longitudinal follow-up after surgery shows these changes are dynamic and evolve over time. Further, we identify moderate associations between contralesional grey matter alterations and cognitive performance, suggesting a link between large-scale neuroplastic responses and functional outcomes. These findings offer new insights into tumor-related neuroplasticity and position structural covariance as a promising marker for tracking brain-wide adaptation in this population. The study has translational relevance for developing predictive tools to monitor recovery and guide personalized rehabilitation.

neuroscience↗