journal article·2025-02Open access

In Vivo Neurodynamics Mapping via High‐Speed Two‐Photon Fluorescence Lifetime Volumetric Projection Microscopy

Yanping Li, Xiangcong Xu, Chao Zhang, Xuefeng Sun, Sisi Zhou, Xuan Li, Jiaqing Guo, Rui Hu, Junle Qu, Liwei Liu

Advanced Science· Volume 12· Issue 7

Abstract

Abstract Monitoring the morphological and biochemical information of neurons and glial cells at high temporal resolution in three‐dimensional (3D) volumes of in vivo is pivotal for understanding their structure and function, and quantifying the brain microenvironment. Conventional two‐photon fluorescence lifetime volumetric imaging speed faces the acquisition speed challenges of slow serial focal tomographic scanning, complex post‐processing procedures for lifetime images, and inherent trade‐offs among contrast, signal‐to‐noise ratio, and speed. This study presents a two‐photon fluorescence lifetime volumetric projection microscopy using an axially elongated Bessel focus and instant frequency‐domain fluorescence lifetime technique, and integrating with a convolutional network to enhance the imaging speed for in vivo neurodynamics mapping. The proposed method is validated by monitoring intracellular Ca2+ concentration throughout whole volume, tracking microglia movement and microenvironmental changes following thermal injury in the zebrafish brain, analyzing structural and functional variations of gap junctions in astrocyte networks, and measuring the Ca2+ concentration in neurons in mouse brains. This innovative methodology enables quantitative in vivo visualization of neurodynamics and the cellular processes and interactions in the brain.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Advanced Fluorescence Microscopy Techniques · Photoacoustic and Ultrasonic Imaging · Neuroinflammation and Neurodegeneration Mechanisms

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

State Key Laboratory of Radio Frequency Heterogeneous Integration & Key Laboratory of Optoelectronic Devices and Systems College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen 518060 China

Funding

National Natural Science Foundation of China · China Postdoctoral Science Foundation · Science and Technology Planning Project of Shenzen Municipality

References (64)

Show source-provided references
1. 10.1038/nn.435810.1038/nn.4358 ↗
2. 10.1038/s43586-022-00147-110.1038/s43586-022-00147-1 ↗
3. 10.1523/JNEUROSCI.1527-18.201910.1523/JNEUROSCI.1527-18.2019 ↗
4. 10.1038/nmeth.430510.1038/nmeth.4305 ↗
5. 10.1088/2050-6120/ab880810.1088/2050-6120/ab8808 ↗
6. 10.1038/nprot.2011.36410.1038/nprot.2011.364 ↗
7. 10.1038/ncomms171410.1038/ncomms1714 ↗
8. 10.1002/advs.20210437910.1002/advs.202104379 ↗
9. 10.1038/nbt89910.1038/nbt899 ↗
10. 10.1038/nphoton.2012.30710.1038/nphoton.2012.307 ↗
11. 10.1002/jnr.2443310.1002/jnr.24433 ↗
12. 10.1016/j.neuron.2015.09.04310.1016/j.neuron.2015.09.043 ↗
13. 10.1038/nprot.2017.15410.1038/nprot.2017.154 ↗
14. 10.1126/science.adf972510.1126/science.adf9725 ↗
15. 10.1038/s41592-021-01108-410.1038/s41592-021-01108-4 ↗
16. 10.1364/OPTICA.5.00129010.1364/OPTICA.5.001290 ↗
17. 10.1364/OPTICA.42687010.1364/OPTICA.426870 ↗
18. 10.1002/jemt.1042110.1002/jemt.10421 ↗
19. 10.1364/BOE.9.00344910.1364/BOE.9.003449 ↗
20. 10.1364/OE.24.00689910.1364/OE.24.006899 ↗
21. 10.1117/1.JBO.17.12.12602010.1117/1.JBO.17.12.126020 ↗
22. 10.1038/nmeth.383610.1038/nmeth.3836 ↗
23. 10.1038/s41467-020-19851-110.1038/s41467-020-19851-1 ↗
24. 10.1038/s41467-023-36889-z10.1038/s41467-023-36889-z ↗
25. 10.1038/s41467-022-35733-010.1038/s41467-022-35733-0 ↗
26. 10.1038/s41592-024-02309-310.1038/s41592-024-02309-3 ↗
27. 10.1038/nn.451610.1038/nn.4516 ↗
28. 10.1038/nmeth.422610.1038/nmeth.4226 ↗
29. 10.1364/OPTICA.44828710.1364/OPTICA.448287 ↗
30. 10.3389/fbinf.2023.133541310.3389/fbinf.2023.1335413 ↗
31. 10.1038/s41592-019-0458-z10.1038/s41592-019-0458-z ↗
32. 10.1038/3504606710.1038/35046067 ↗
33. 10.1038/nn.292910.1038/nn.2929 ↗
34. 10.1038/nn86710.1038/nn867 ↗
35. 10.1523/JNEUROSCI.0946-06.200610.1523/JNEUROSCI.0946-06.2006 ↗
36. 10.1042/bj266023510.1042/bj2660235 ↗
37. 10.1126/science.111064710.1126/science.1110647 ↗
38. 10.1038/nn147210.1038/nn1472 ↗
39. 10.1038/nn199710.1038/nn1997 ↗
40. 10.1038/nri.2017.12510.1038/nri.2017.125 ↗
41. 10.1126/sciadv.abd116010.1126/sciadv.abd1160 ↗
42. 10.1016/j.devcel.2012.04.01210.1016/j.devcel.2012.04.012 ↗
43. 10.1039/b902341k10.1039/b902341k ↗
44. 10.1016/j.neuroscience.2018.11.01010.1016/j.neuroscience.2018.11.010 ↗
45. 10.1038/nn.390610.1038/nn.3906 ↗
46. 10.1016/j.neuron.2018.03.05010.1016/j.neuron.2018.03.050 ↗
47. 10.1038/s41583-020-0361-810.1038/s41583-020-0361-8 ↗
48. 10.1523/JNEUROSCI.5100-07.200810.1523/JNEUROSCI.5100-07.2008 ↗
49. 10.3389/fnmol.2019.0002310.3389/fnmol.2019.00023 ↗
50. 10.1038/s41596-018-0026-510.1038/s41596-018-0026-5 ↗
51. 10.1117/1.JBO.29.1.01650110.1117/1.JBO.29.1.016501 ↗
52. 10.1002/lpor.20230063410.1002/lpor.202300634 ↗
53. 10.1364/OL.46308710.1364/OL.463087 ↗
54. 10.1038/s41377-024-01498-y10.1038/s41377-024-01498-y ↗
55. Lin S. · Laser Photonics Rev. · 2024 · 18
56. 10.1038/s41467-024-48502-y10.1038/s41467-024-48502-y ↗
57. 10.1364/BOE.39393110.1364/BOE.393931 ↗
58. 10.1103/PhysRevLett.113.13390210.1103/PhysRevLett.113.133902 ↗
59. 10.1038/nphoton.2016.25210.1038/nphoton.2016.252 ↗
60. 10.1186/s43074-023-00117-010.1186/s43074-023-00117-0 ↗
61. O.Ronneberger P.Fischer T.Brox inMedical Image Computing and Computer‐Assisted Intervention–MICCAI 2015 (Eds:N.Navab J.Hornegger W. M.Wells A. F.Frangi) Springer Cham2015 pp.234–241.10.1007/978-3-319-24574-4_28 ↗
62. S.Woo J.Park J.‐Y.Lee I. S.Kweon inProc. of the European Conf. on Computer Vision (ECCV) (Eds:V.Ferrari M.Hebert C.Sminchisescu Y.Weiss) Springer Cham2018 pp.3–19.
63. X.Zhang Q.Chen R.Ng V.Koltun inProc. of the IEEE/CVF Conf. on Computer Vision and Pattern Recognition IEEE Long Beach CA2019 pp.3762–3770.
64. C.Ledig L.Theis F.Huszár J.Caballero A.Cunningham A.Acosta A.Aitken A.Tejani J.Totz Z.Wang inProc. of the IEEE Conf. on Computer Vision and Pattern Recognition IEEE Honolulu Hawaii2017 pp.4681–4690.