Laser & Optoelectronics Progress, Volume. 62, Issue 18, 1817010(2025)

Event-Driven Microscopy: New Frontiers of Intravital Bioimaging (Invited)

Chenhui Yu1,2, Guanyi Zhu1,2, and Fei He1,2,3、*
Author Affiliations
  • 1Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800, China
  • 2University of Chinese Academy of Sciences, Beijing 100049, China
  • 3Zhangjiang Laboratory, Shanghai 201210, China
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    Figures & Tables(8)
    Imaging parameters and biological samples. (a) Trade-offs between various imaging parameters and biological specimens; (b) spatiotemporal scale distribution of different experimental targets, including neurons, cells, and tissues
    Comparison of the working principles of conventional optical microscope and event-driven microscope. (a) Structure of early conventional optical microscope; (b) workflow of event-driven microscope
    Evolution of event-driven microscopy
    Event-driven mode-switching microscopy systems for imaging mitosis in cells. (a) Imaging workflow of Micropilot[36]; (b) Micropilot low-resolution confocal imaging of HeLa cells undergoing mitosis[36]; (c) high-resolution confocal imaging by Micropilot showing two-color 3D time-lapse sequences of HeLa cells in mitosis[36]; (d) imaging workflow of NanoJ-Fluidics[37]; (e) example of a rounding mitotic HeLa cell during live-cell imaging[37]; (f) NanoJ-Fluidics imaging of fixed cells undergoing mitosis[37]
    Working principle and application of event camera. (a) Trajectory of a moving ball in the xy-plane; (b) schematic of event camera capturing the ball's motion trajectory with high temporal resolution; (c) output images from conventional frame-based image sensor determined by frame rate; (d) schematic comparison of responses from sCMOS and event camera (top: intensity curve emitted during fluorophore blinking; middle: signal returned by an ideal camera with a 30 ms exposure time; bottom: signal returned by an ideal event camera)[44]; (e) SMLM images acquired by sCMOS and event camera[44]
    etSTED imaging of neuronal activity[39]. (a) Schematic of synaptic vesicle dynamics during calcium signaling; (b) experimental timeline for a wide-field frame; (c) maximum projection analysis image from wide-field imaging detecting local calcium signals; (d) magnified views at two detected event locations; (e) 2.5 Hz etSTED time series; (f) synaptic vesicle cluster analysis; (g) schematic of endosomal vesicle interaction processes; (h) timeline schematic for a wide-field image; (i) tracking of vesicle movement in wide-field imaging; (j) magnified views of two representative events showing two tracked vesicles approaching each other; (k) triggered 2.8 Hz STED time series showing endosomal vesicle dynamics
    Tracking cancer cell migration using DDM and application of smartLLSM in the study of immune responses and nanomedicine. (a) Schematic of DDM applied for live feedback imaging of migratory subpopulations[41]; UMAP space colored by mean speed (b) and meandering index (c), revealing distinct migratory phenotypes[41]; (d) cells migrating at different speeds under low magnification (top) and rapidly migrating cells imaged under high magnification (bottom)[41]; (e) schematic of the smartLLSM imaging workflow[42]; (f) inverted fluorescence microscopy imaging of different CTL sample categories[42]; (g) representative maximum intensity projections and schematic diagrams of CTL synapses with lysosomal granules concentrated at the front, middle, and back[42]; (h) inverted fluorescence microscopy imaging of different sample categories of cells at various mitotic stages[42]; (i) maximum intensity projections of prometaphase and metaphase cells under control and 5 nmol/L paclitaxel treatment conditions[42]; (j) violin plot of metaphase plate angle for control and 5 nmol/L paclitaxel-treated cells in prometaphase and metaphase[42]
    • Table 1. Summary of event-driven illumination imaging system

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      Table 1. Summary of event-driven illumination imaging system

      MethodImaging modeRef.
      Controlled light-exposure based on electronic circuit and AOMConfocal microscopy29
      Adaptive illumination based on feedback circuit and EOMTwo-photon microscopy30
      Adaptive SIM enabled by DMDSIM31
      DyMIN based on FPGA and AOMSTED nanoscopy32
      Real time feedback system based on FPGA data-acquisition cardRESOLFT nanoscopy33
      Adaptive excitation source based on AWG and fiber-integrated EOMLaser scanning multiphoton microscopy34
      Learned adaptive multiphoton illumination based on physics-based machine learning modelMultiphoton microscopy35
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    Chenhui Yu, Guanyi Zhu, Fei He. Event-Driven Microscopy: New Frontiers of Intravital Bioimaging (Invited)[J]. Laser & Optoelectronics Progress, 2025, 62(18): 1817010

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    Paper Information

    Category: Medical Optics and Biotechnology

    Received: May. 7, 2025

    Accepted: Jul. 1, 2025

    Published Online: Sep. 11, 2025

    The Author Email: Fei He (hefei@siom.ac.cn)

    DOI:10.3788/LOP251160

    CSTR:32186.14.LOP251160

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