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<p>Miniaturized microscopes or ‘miniscopes’ for neuroimaging in freely behaving animals mostly operate over short durations (&lt;2 h) and image either neuronal activity or cerebral hemodynamics. In contrast, central nervous system (CNS) disease models involving seizures, brain tumors etc. necessitate long-term (&gt;24 h) imaging, remote operation and simultaneous characterization of multiple neurophysiological variables such as neuronal activity, blood flow, blood volume, oxygenation and cellular dynamics (a capability that we call ‘neurosurveillance’). Thus, we developed the ‘CloudScope’, a cloud-based multicontrast miniscope for autonomous neurosurveillance in freely behaving animals. Its cloud-based architecture enables global remote operation and continuous acquisition of multicontrast images over CNS disease model life cycles. We demonstrate CloudScope’s neurosurveillance capabilities in predicting behavior from 24-h neuroimaging data with deep learning (DL), characterizing neurovascular changes during natural behavior, seizure-induced neurovascular disruptions, and in vivo cellular and microvascular phenotyping of brain tumor microenvironments. Finally, CloudScope’s architecture enables ‘time-shared’ imaging, which potentially reduces animal use. Collectively, CloudScope’s neurosurveillance capabilities in conjunction with CNS disease models establish a new paradigm for characterizing their etiology and evolution.</p>

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A cloud-based miniscope for neurosurveillance of brain health and disease in freely behaving animals

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月22日

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  • Janaka Senarathna,
  • Darren Yang,
  • Julia Brill,
  • Subhrajit Das,
  • Shruthi Bare,
  • Yunke Ren,
  • Devorah VanNess,
  • Vu Dinh,
  • Irfaan Karim,
  • Amit K. Banerjee,
  • Nitish V. Thakor,
  • Mingyao Ying,
  • David J. Linden,
  • Arvind P. Pathak

摘要

Miniaturized microscopes or ‘miniscopes’ for neuroimaging in freely behaving animals mostly operate over short durations (<2 h) and image either neuronal activity or cerebral hemodynamics. In contrast, central nervous system (CNS) disease models involving seizures, brain tumors etc. necessitate long-term (>24 h) imaging, remote operation and simultaneous characterization of multiple neurophysiological variables such as neuronal activity, blood flow, blood volume, oxygenation and cellular dynamics (a capability that we call ‘neurosurveillance’). Thus, we developed the ‘CloudScope’, a cloud-based multicontrast miniscope for autonomous neurosurveillance in freely behaving animals. Its cloud-based architecture enables global remote operation and continuous acquisition of multicontrast images over CNS disease model life cycles. We demonstrate CloudScope’s neurosurveillance capabilities in predicting behavior from 24-h neuroimaging data with deep learning (DL), characterizing neurovascular changes during natural behavior, seizure-induced neurovascular disruptions, and in vivo cellular and microvascular phenotyping of brain tumor microenvironments. Finally, CloudScope’s architecture enables ‘time-shared’ imaging, which potentially reduces animal use. Collectively, CloudScope’s neurosurveillance capabilities in conjunction with CNS disease models establish a new paradigm for characterizing their etiology and evolution.