NeuroPilot: Longitudinal intravital neural imaging across scales and modalities through an agentic platform
- 1College of Future Information Technology, Fudan University, Shanghai 200433, China
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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BibTeX
@misc{zhang2026neuropilot,
title = {{NeuroPilot: Longitudinal intravital neural imaging across scales and modalities through an agentic platform}},
author = {G. Zhang and Y. Luo and F. Ju and D. Liu and D. Zhang and C. Guo and J. Han and S. Qiu and T. Wang and J. Wang and M. Ma and B. Li and Y. Jiang and P. Wei and X. Liu and N. Chi and Z. Li},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.18.759043},
url = {https://www.biorxiv.org/content/10.64898/2026.10.18.759043v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - NeuroPilot: Longitudinal intravital neural imaging across scales and modalities through an agentic platform
AU - G. Zhang
AU - Y. Luo
AU - F. Ju
AU - D. Liu
AU - D. Zhang
AU - C. Guo
AU - J. Han
AU - S. Qiu
AU - T. Wang
AU - J. Wang
AU - M. Ma
AU - B. Li
AU - Y. Jiang
AU - P. Wei
AU - X. Liu
AU - N. Chi
AU - Z. Li
PY - 2026
DA - 2026/10/18
PB - bioRxiv
DO - 10.64898/2026.10.18.759043
UR - https://www.biorxiv.org/content/10.64898/2026.10.18.759043v1
AB - 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.
ER -