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Imaging volumetric dynamics at high speed in mouse and zebrafish brain with confocal light field microscopy

Nature Biotechnology volume 39, pages 74–83 (2021)Cite this article

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Abstract

A detailed understanding of the function of neural networks and how they are supported by a dynamic vascular system requires fast three-dimensional imaging in thick tissues. Here we present confocal light field microscopy, a method that enables fast volumetric imaging in the brain at depths of hundreds of micrometers. It uses a generalized confocal detection scheme that selectively collects fluorescent signals from the in-focus volume and provides optical sectioning capability to improve imaging resolution and sensitivity in thick tissues. We demonstrate recording of whole-brain calcium transients in freely swimming zebrafish larvae and observe behaviorally correlated activities in single neurons during prey capture. Furthermore, in the mouse brain, we detect neural activities at depths of up to 370 μm and track blood cells at 70 Hz over a volume of diameter 800 μm × thickness 150 μm and depth of up to 600 μm.

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Fig. 1: Design and characterization of confocal LFM.
Fig. 2: Whole-brain functional imaging of neural activity in movement-restrained larval zebrafish.
Fig. 3: Tracking and imaging whole-brain neural activity during larval zebrafish’s prey capture behavior.
Fig. 4: Volumetric functional imaging of neural activity in awake mouse brain.
Fig. 5: Imaging and tracking of circulating blood cells in awake mouse brain.

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Data availability

We have no restriction on data availability. Data can be requested from the corresponding author.

Code availability

Custom LabVIEW codes for system control and data acquisition, MATLAB codes for volume reconstruction, system aberration correction, registration of imaging volumes of freely moving larval zebrafish and tracking circulating blood cells can be found in Supplementary Software.

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Acknowledgements

K.W. acknowledges support from National Key R&D Program of China (grant no. 2017YFA0700500), ‘Strategic Priority Research Program’ of the Chinese Academy of Sciences (grant no. XDB32030200), NSFC (grant no. 31871086), International Partnership Program of Chinese Academy of Sciences (grant no. 153D31KYSB20170059), Shanghai Municipal Science and Technology Major Project (grant nos. 2018SHZDZX05 and 18JC1410100). J.D. acknowledges support from Shanghai Municipal Science and Technology Major Project (grant no. 18JC1410100). We thank J. He at the Institute of Neuroscience for his support on zebrafish handling and helpful discussions. We thank the reviewers for their constructive comments and suggestions.

Author information

Author notes

  1. These authors contributed equally: Zhenkun Zhang, Lu Bai, Lin Cong.

Authors and Affiliations

  1. Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China

    Zhenkun Zhang, Lu Bai, Lin Cong, Peng Yu, Tianlei Zhang, Funing Li, Jiulin Du & Kai Wang

  2. University of Chinese Academy of Sciences, Beijing, China

    Zhenkun Zhang, Lu Bai, Peng Yu, Tianlei Zhang, Funing Li, Jiulin Du & Kai Wang

  3. School of Physical Science, University of Science and Technology of China, Hefei, China

    Wanzhuo Shi

  4. Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China

    Jiulin Du & Kai Wang

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Contributions

Z.Z. and L.C. built confocal LFM. Z.Z. wrote the code for image reconstruction. Z.Z. and T.Z. performed zebrafish-related experiments and data analysis. L.B. and P.Y. performed the mouse experiments. L.B. performed data analysis on the mouse calcium imaging. L.B. and W.S. performed data analysis on blood flow in the mouse brain. Z.Z., F.L. and J.D. designed zebrafish behavioral experiments. K.W. conceived and led the project. Z.Z., L.C., L.B. and K.W. wrote the manuscript with input from all authors.

Corresponding author

Correspondence to Kai Wang.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–24, Note 1 and Tables 1–3.

Reporting Summary

Supplementary Video 1

Animated schematics of confocal LFM with fast axial scanning. The excitation laser path and fluorescence imaging light path are in blue and green, respectively. The rotating wheel carrying masks and glass plates is rotated at constant speed. Trigger signals are generated by a trigger laser passing through trigger slits on masks (Supplementary Figs. 1 and 2) to synchronize scanning galvo, laser and camera. Every time a trigger slit on a mask is rotated to the focal spot of the trigger laser, the trigger detector detects a rising edge of laser power, which serves as the trigger signal. Rotation of galvo mirror and rotating wheel are synchronized to ensure the excitation laser sheet always goes through a thin slit in the center of mask. During the scan, fluorescence signals collected by microlenses are spatially filtered by apertures on the same mask before they are imaged on the camera. More detailed descriptions of the system can be found in Fig. 1 and Supplementary Note 1.

Supplementary Video 2

Comparison of confocal LFM and nonconfocal LFM when imaging spontaneous neural activities in restrained larval zebrafish brain. Spontaneous neural activities on a single plane in larval zebrafish brain (Tg(HuC:GCaMP6s), 6 dpf) imaged by confocal LFM with (left) and without (right) confocal mask. Sampling rates were 1 Hz in both conditions.

Supplementary Video 3

3D volumetric imaging of larval zebrafish brain. MIP in time of the calcium responses on flash light stimuli in a larval zebrafish brain (Tg(HuC:GCaMP6s), 5 dpf). The larval zebrafish is movement-restrained. Five imaging volumes obtained sequentially from five different mask–glass plate combinations were stitched together to cover an entire imaging depth of ~200 μm. The same data are shown in Fig. 2b–d and Supplementary Video 4.

Supplementary Video 4

Whole-brain functional imaging in larval zebrafish under light stimulation. Larval zebrafish (Tg(HuC:GCaMP6s), 5 dpf) with pan-neuronal labeling of cytosol-localized GCamp6s was imaged by confocal LFM at a 6-Hz volume rate. A flash of light was applied at time window of 0–4 s. The same data are shown in Fig. 2b–d and Supplementary Video 3.

Supplementary Video 5

Whole-brain functional imaging of a freely swimming larval zebrafish during prey capture behavior. Confocal LFM imaging of a freely swimming larval zebrafish expressing cytosol-localized, pan-neuronal GCaMP6s (Tg(HuC:GCaMP6s), 8 dpf). Left, behavioral recording of the zebrafish and paramecia. Right, MIPs of reconstructed volumes obtained in five different sets of masks and glass plates focusing at different depths. The raw reconstructions and registration of them in top views are displayed in the top and middle rows, respectively. Shown in the bottom row are the MIPs in the y–z view of registered results. At 15.03 s, the zebrafish larva initiated hunting, identified by the converging eyes onto the paramecium marked in blue and a J-turn to align its heading direction. It successfully ate the paramecium indicated in orange at 15.72 s. Video plays four times slower than real time. Scale bar, 100 µm. The same data are shown in Fig. 3.

Supplementary Video 6

Unbiased volumetric reconstruction of active neural structures in an awake mouse brain imaged by confocal LFM. Volumetric rendering of spontaneously active neural structures imaged by confocal LFM in an awake mouse brain. Neurons in mouse brain were densely labeled with cytosol-localized GCamp6. The displayed images are standard deviations of unbiased volumetric reconstruction time series with 1,600 time points. Detailed description of data processing can be found in the Methods. Three volumes were captured at the indicated different depths in different sessions. The same data are shown in Fig. 4a–e.

Supplementary Video 7

Active neural structures extracted by CNMF-E on each z plane independently in an imaging volume captured by confocal LFM. Volumetric rendering of time series of neural activities on their corresponding spatial footprints extracted by CNMF-E. The CNMF-E was separately applied on each z plane within the reconstructed volume (Methods). The imaging volume was from 100 to 200 μm below the cortical surface. The spatial footprints of the same neuron at different z planes showed highly correlated temporal traces, which validated the CNMF-E extraction results. The same data are shown in Fig. 4a–e.

Supplementary Video 8

Imaging circulating blood cells in an awake mouse brain by confocal LFM. Imaging circulating blood cells in awake mouse brain in six volumes starting from the cortex surface to 650 μm below at 70 Hz volume rate. Circulating cells labeled with red fluorescent dye are in red. Presumed blood vessels, as found by averaging over time images of labeled blood cells, are in green. Blood cells circulating as deep as 600 μm below the cortex surface can be imaged by confocal LFM.

Supplementary Video 9

Imaging circulating blood cells in an awake mouse brain over extended period of time. Volumetric imaging of circulating blood cells 100–250 μm below the mouse cortex surface over entire imaging session (1,260 frames in 18 s). These data are the same as in the second volume in Supplementary Video 8 but with more time points.

Supplementary Video 10

Analysis of instantaneous speeds of circulating cells in blood vessels. By tracking single cells in blood vessels, their speeds can be inferred. The skeletons of blood vessels are colored based on the average speeds of circulating blood cells in them over the entire imaging session (1,260 frames in 18 s). The change in brightness of each blood vessel skeleton indicates the change of instantaneous speeds of cells in it. This analysis was carried on an imaging volume covering ~100–250 μm below mouse cortex surface (same as in Supplementary Video 9). The skeletons of blood vessels in the volume were projected in the z direction for display.

Supplementary Software 1

MATLAB and LabVIEW source codes for system control, confocal LFM 3D reconstruction, system aberration calibration, 3D registration of zebrafish imaging data, analysis of circulating blood cells and example data for doing 3D reconstruction.

Supplementary Data 1

Design files for several key elements in confocal LFM.

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Zhang, Z., Bai, L., Cong, L. et al. Imaging volumetric dynamics at high speed in mouse and zebrafish brain with confocal light field microscopy. Nat Biotechnol 39, 74–83 (2021). https://doi.org/10.1038/s41587-020-0628-7

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