{
  "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.",
  "abstract_shown": true,
  "affiliations": [
    "College of Future Information Technology, Fudan University, Shanghai 200433, China"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 17,
  "authors": [
    {
      "name": "G. Zhang"
    },
    {
      "name": "Y. Luo"
    },
    {
      "name": "F. Ju"
    },
    {
      "name": "D. Liu"
    },
    {
      "name": "D. Zhang"
    },
    {
      "name": "C. Guo"
    },
    {
      "name": "J. Han"
    },
    {
      "name": "S. Qiu"
    },
    {
      "name": "T. Wang"
    },
    {
      "name": "J. Wang"
    },
    {
      "name": "M. Ma"
    },
    {
      "affs": [
        0
      ],
      "name": "B. Li"
    },
    {
      "name": "Y. Jiang"
    },
    {
      "name": "P. Wei"
    },
    {
      "name": "X. Liu"
    },
    {
      "name": "N. Chi"
    },
    {
      "affs": [
        0
      ],
      "name": "Z. Li"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/deyzbc35t8ngh.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.18.759043",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.18.759043v1.full",
  "id": "deyzbc35t8ngh",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.18.759043v1",
  "language": null,
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "neuroscience"
    ],
    [
      "openalex",
      "2805|Neural dynamics and brain function"
    ]
  ],
  "openalex": "W7222964250",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.18.759043v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-18",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/deyzbc35t8ngh.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:28:36Z",
      "native_id": "10.64898/2026.10.18.759043",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.18.759043v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:neuroscience",
      "subfield": "neuroscience"
    }
  ],
  "title": "NeuroPilot: Longitudinal intravital neural imaging across scales and modalities through an agentic platform",
  "title_text": "NeuroPilot: Longitudinal intravital neural imaging across scales and modalities through an agentic platform",
  "type": "preprint",
  "updated_at": "2026-10-30T12:28:36Z",
  "url": "https://research.draconitic.com/paper/deyzbc35t8ngh",
  "venue": "bioRxiv",
  "versions": []
}