bioRxiv · 10.64898/2026.10.18.759043
NeuroPilot: Longitudinal intravital neural imaging across scales and modalities through an agentic platform
Abstract
Longitudinal intravital imaging is essential for understanding how neural populations evolve across behavioral states, yet converting large-scale recordings into biological insight remains a fundamental challenge because neural signals are degraded by noise, non-rigid motion, and heterogeneous recording conditions. Here we introduce NeuroPilot, an agentic framework that transforms neural imaging analysis into a closed-loop, context-aware process, integrating a multimodal large language model with callable computational imaging modules to adaptively coordinate workflows from raw recordings to population-level readouts. Across heterogeneous imaging and experimental regimes, NeuroPilot restores motion-degraded recordings and supports consistent neural signal recovery, detection, and tracking in challenging deep-brain, freely moving, and longitudinal settings. These enable neuronal population tracking across spinal stimulation paradigms, deep-brain imaging, and continuous 24-hour mPFC recordings aligned with spontaneous sleep-wake behavior. By converting heterogeneous intravital recordings into stable population activity maps, NeuroPilot supports behavioral decoding and reveals structured neural dynamics across behavioral states and transitions. NeuroPilot establishes a scalable agentic paradigm for neural imaging analysis, expanding experimental access to the measurement, visualization, and interpretation of neural population activity.
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Zhang, G., Luo, Y., Ju, F., Liu, D., Zhang, D., Guo, C., Han, J., Qiu, S., Wang, T., Wang, J., Ma, M., Li, B., Jiang, Y., Wei, P., Liu, X., Chi, N., Li, Z.. 2026-10-19. NeuroPilot: Longitudinal intravital neural imaging across scales and modalities through an agentic platform. https://doi.org/10.64898/2026.10.18.759043
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