Functional Connectivity in Brain Tumor Dynamics

Functional connectivity refers to the temporal correlation of neural activity between distinct brain regions, offering insight into how tumours disrupt or co-opt existing networks. In patients with intra-axial lesions such as gliomas, slow tumour growth permits progressive plastic adaptation within both local and distant circuits. Resting-state and task-based functional MRI, along with electrophysiological methods, have revealed altered connectivity within language, motor and default networks, often accompanied by compensatory recruitment of homologous contralateral regions. Graph-theoretical approaches quantify these changes by characterising hubs, efficiency and modular organisation, thereby linking alterations in network topology to clinical symptoms, seizure propensity and cognitive outcomes. Advances in multimodal imaging have shown that peri-tumoural regions may exhibit a “penumbra” of suppressed complexity, while more remote areas can demonstrate hyperconnectivity. Tumour genetics, location and grade modulate these patterns, influencing both the extent of reorganisation and the risk–benefit profile of surgical resection. An improved understanding of global and focal connectivity shifts informs preoperative mapping, prediction of functional preservation and design of personalised therapeutic strategies.

Research from Nature Portfolio

Analyses in patients with frontal lobe gliomas have demonstrated that the posterior default mode network undergoes both intra- and cross-hemispheric alterations. In contrast to healthy controls, individuals harbouring tumours exhibit reduced connectivity strength between posterior cingulate and temporal-parietal junction regions in both hemispheres. Simultaneously, correlation coefficients between connectivity pairs increase, suggesting network reconfiguration. Subgroup analyses reveal that lesions in the dominant hemisphere produce more pronounced connectivity loss, and the degree of disruption correlates with histological grade. These findings underscore that focal lesions exert widespread effects on large-scale networks, challenging the notion of purely local tumour impact and highlighting the importance of assessing bilateral network integrity in surgical planning.

Functional Connectivity in Brain Tumor Dynamics publication trend

The graph below shows the total number of articles in functional connectivity in brain tumor dynamics across all publications each year (not limited to Nature Index journals).

Technical terms

Functional connectivity: Statistical dependence between neurophysiological signals in distinct brain regions, reflecting coordinated activity.

Resting-state fMRI: Imaging technique measuring spontaneous brain activity fluctuations to infer network architecture in the absence of a specific task.

Graph theory: Mathematical framework describing brain networks as nodes (regions) and edges (connections) to quantify properties such as efficiency and centrality.

Default mode network (DMN): A set of interconnected regions active during rest and implicated in self-referential processing and baseline brain function.

Nodal efficiency: A graph-theoretical metric indicating how efficiently information is exchanged between a given node and all other nodes in the network.

References

1. Alteration of the Intra- and Cross- Hemisphere Posterior Default Mode Network in Frontal Lobe Glioma Patients. Scientific Reports (2016).
2. Global Effects of Focal Brain Tumors on Functional Complexity and Network Robustness: A Prospective Cohort Study. Neurosurgery (2018).
3. A speech fluency brain network derived from gliomas. Brain Communications (2024).
4. Longitudinal Evaluation of Brain Plasticity in Low-Grade Gliomas: fMRI and Graph-Theory Provide Insights on Language Reorganization. Cancers (2023).
5. Effect of tumor genetics, pathology, and location on fMRI of language reorganization in brain tumor patients. European Radiology (2023).
6. Functional Mapping before and after Low-Grade Glioma Surgery: A New Way to Decipher Various Spatiotemporal Patterns of Individual Neuroplastic Potential in Brain Tumor Patients. Cancers (2020).