Disrupted dynamics of transient brain states in patients with brain tumors: a co-activation pattern analysis of resting-state fMRI.

backgroundBrain tumors impair brain function both locally and across distant regions by disrupting network connectivity, contributing to cognitive deficits and triggering compensatory plasticity. Traditional resting-state fMRI methods average brain activity over time, missing transient, dynamic events critical to cognition. Co-Activation Pattern (CAP) analysis captures these brief brain states, enabling quantification of state engagement and duration. PURPOSE: To investigate alterations in transient brain states in patients with brain tumors using CAP analysis of resting-state fMRI, and to assess whether these changes reflect modified engagement of cognitive states compared to healthy controls. MATERIALS AND

methodsThis retrospective cross-sectional study included 106 patients with left-hemispheric brain tumors (72 high-grade gliomas, 19 low-grade gliomas, 15 metastases; mean age 61.15 ± 8.95 years; 43 women) and 100 age-matched healthy controls. Resting-state fMRI data were analyzed using a seed-free clustering method (TbCAPs toolbox) to extract CAPs. CAPs were first identified in controls and then matched to patients via spatial similarity. Each CAP was assigned to a canonical brain network using the GIFT toolbox. Dynamic metrics computed included: persistence (duration of a CAP), transitions (switching frequency), in-degree, and out-degree. Group comparisons used two-tailed t-tests with Benjamini-Hochberg correction (p < 0.05).

resultsSix CAPs were identified. Compared to controls, patients showed significantly increased transitions, in-degree, and out-degree, and decreased persistence in CAPs linked to the default mode and executive control networks (all p < 0.01), suggesting more frequent but less stable engagement. Visuospatial network CAPs demonstrated lower transition, in/out-degree and persistence in patients (p < 0.05). No significant differences were observed among tumor types.

conclusionPatients with brain tumors display altered CAP dynamics involving higher-order cognitive networks and perceptual networks. These alterations may reflect the combined effects of tumor-related network damage and potential adaptive reorganization, with potential implications for functional preoperative planning and prognosis. However, in the absence of direct clinical or neuropsychological correlations, these interpretations remain hypothesis-generating. The findings are also limited by the retrospective cross-sectional design preventing causal or longitudinal interpretation, and the restriction to left-hemispheric tumors. Future studies integrating CAP dynamics with cognitive and clinical outcomes will be necessary to determine whether these changes reflect compensatory functional reorganization in brain tumor patients.