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Intrinsic fluctuations in arousal shape the dynamic organization of the mouse brain large-scale networks
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Intrinsic fluctuations in arousal shape the dynamic organization of the mouse brain large-scale networks
Par Jean Charles Mariani - Istituto Italiano di Tecnologia, Genoa, Italy
Le 7 Octobre 2025 à 11h00 - Laboratoire Jean Perrin - Campus Jussieu - T 22-32- 4e et. - P407
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Résumé
Despite decades of applications in both clinical and preclinical settings, the exact nature of large-scale functional connectivity (FC) and resting-state network (RSN) activity remains debated. It has recently been suggested that FC, as probed with fMRI in humans, may reflect a dominant traveling wave synchronized with intrinsic arousal fluctuations. According to this model, whole-brain fMRI network activity would thus be constrained to a low-dimensional space defined by arousal. However, whether and how this model generalizes to different species and brain states remains unclear. Here, we used concurrent functional ultrasound imaging (fUSI) and pupillometry in lightly sedated mice to investigate how intrinsic fluctuations in arousal propagate and affect the functional architecture of mouse brain networks. In contrast to prevailing models in humans, we found that intrinsic whole-brain fUSI activity can be described as the sum of robust infraslow (0.04–0.1 Hz) local stationary hemodynamic waves, superimposed onto ultraslow (<0.03 Hz), arousal-driven traveling waves. Importantly, these faster fluctuations extended across homotopic, anatomically interconnected areas, matching well-characterized RSN topographies. These observations suggest that interareal synchronization and FC in low-arousal states primarily reflect transient hemodynamic phase-locking, rather than mere differences in the individual phase of signals. These findings also support an updated conceptual framework whereby large-scale intrinsic network activity and FC reflect weakly coupled pseudo-oscillators, allowing arousal-driven and local regional activity to independently coexist across dissociable temporal scales. According to this updated model, the dimensionality of brain dynamics in low-arousal states is increased by the independent contribution of standing hemodynamic waves.
