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Readout of fluorescence functional signals through highly scattering tissue

Abstract

Fluorescence is a powerful means to probe information processing in the mammalian brain1. However, neuronal tissues are highly heterogeneous and thus opaque to light. A wide set of non-invasive or invasive techniques for scattered light rejection, optical sectioning or localized excitation have been developed, but non-invasive optical recording of activity through a highly scattering layer beyond the ballistic regime is impossible as yet. Here, we show that functional signals from fluorescent time-varying sources located below a highly scattering bone tissue can be retrieved efficiently by exploiting matrix factorization algorithms to demix this information from temporal sequences of low-contrast fluorescence speckle patterns.

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Fig. 1: Schematic of hardware set-up and operation of the fluorescence activity recording through a highly scattering sample.
Fig. 2: Temporal activity recording.
Fig. 3: Multiple depth recording.

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Data availability

The data that support the plots within this paper and other findings of this study are available from the corresponding author upon reasonable request.

Code availability

Analysis scripts are available at https://github.com/laboGigan/SpeckledNeuronsAnalysis. Hardware control scripts are available at https://github.com/laboGigan/SpeckledNeuronsControl.

References

  1. Helmchen, F. & Konnerth, A. Imaging in Neuroscience: A Laboratory Manual (Cold Spring Harbor Laboratory Press, 2011).

  2. Boyden, E. S., Zhang, F., Bamberg, E., Nagel, G. & Deisseroth, K. Millisecond-timescale, genetically targeted optical control of neural activity. Nat. Neurosci. 8, 1263–1268 (2005).

    Article  Google Scholar 

  3. Chen, T.-W. et al. Ultrasensitive fluorescent proteins for imaging neuronal activity. Nature 499, 295–300 (2013).

    Article  ADS  Google Scholar 

  4. Livet, J. et al. Transgenic strategies for combinatorial expression of fluorescent proteins in the nervous system. Nature 450, 56–62 (2007).

    Article  ADS  Google Scholar 

  5. Weisenburger, S. & Vaziri, A. A guide to emerging technologies for large-scale and whole-brain optical imaging of neuronal activity. Annu. Rev. Neurosci. 41, 431–452 (2018).

    Article  Google Scholar 

  6. Prevedel, R. et al. Fast volumetric calcium imaging across multiple cortical layers using sculpted light. Nat. Methods 13, 1021–1028 (2016).

    Article  Google Scholar 

  7. Iyer, V., Hoogland, T. M. & Saggau, P. Fast functional imaging of single neurons using random-access multiphoton (RAMP) microscopy. J. Neurophysiol. 95, 535–545 (2006).

    Article  Google Scholar 

  8. Katona, G. et al. Fast two-photon in vivo imaging with three-dimensional random-access scanning in large tissue volumes. Nat. Methods 9, 201–208 (2012).

    Article  Google Scholar 

  9. Grewe, B. F., Langer, D., Kasper, H., Kampa, B. M. & Helmchen, F. High-speed in vivo calcium imaging reveals neuronal network activity with near-millisecond precision. Nat. Methods 7, 399–405 (2010).

    Article  Google Scholar 

  10. Bovetti, S. et al. Simultaneous high-speed imaging and optogenetic inhibition in the intact mouse brain. Sci. Rep. 7, 40041 (2017).

    Article  ADS  Google Scholar 

  11. Nikolenko, V. SLM microscopy: scanless two-photon imaging and photostimulation using spatial light modulators. Front. Neural Circuits 2, 5 (2008).

    Article  Google Scholar 

  12. Zhou, P. et al. Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data. eLife 7, e28728 (2018).

    Article  Google Scholar 

  13. Nöbauer, T. et al. Video rate volumetric Ca2+ imaging across cortex using seeded iterative demixing (SID) microscopy. Nat. Methods 14, 811–818 (2017).

    Article  Google Scholar 

  14. Pégard, N. C. et al. Compressive light-field microscopy for 3D neural activity recording. Optica 3, 517–524 (2016).

    Article  ADS  Google Scholar 

  15. Horstmeyer, R., Ruan, H. & Yang, C. Guidestar-assisted wavefront-shaping methods for focusing light into biological tissue. Nat. Photon. 9, 563–571 (2015).

    Article  ADS  Google Scholar 

  16. Rotter, S. & Gigan, S. Light fields in complex media: mesoscopic scattering meets wave control. Rev. Mod. Phys. 89, 015005 (2017).

    Article  ADS  Google Scholar 

  17. Katz, O., Heidmann, P., Fink, M. & Gigan, S. Non-invasive single-shot imaging through scattering layers and around corners via speckle correlations. Nat. Photon. 8, 784–790 (2014).

    Article  ADS  Google Scholar 

  18. Hofer, M., Soeller, C., Brasselet, S. & Bertolotti, J. Wide field fluorescence epi-microscopy behind a scattering medium enabled by speckle correlations. Opt. Express 26, 9866–9881 (2018).

    Article  ADS  Google Scholar 

  19. Chang, J. & Wetzstein, G. Single-shot speckle correlation fluorescence microscopy in thick scattering tissue with image reconstruction priors. J. Biophotonics 11, e201700224 (2018).

    Article  Google Scholar 

  20. Stern, G. & Katz, O. Noninvasive focusing through scattering layers using speckle correlations. Opt. Letters 44, 143–146 (2019).

    Article  ADS  Google Scholar 

  21. Xu, X. et al. Imaging of objects through a thin scattering layer using a spectrally and spatially separated reference. Opt. Express 26, 15073–15083 (2018).

    Article  ADS  Google Scholar 

  22. Judkewitz, B., Horstmeyer, R., Vellekoop, I. M., Papadopoulos, I. N. & Yang, C. Translation correlations in anisotropically scattering media. Nat. Phys. 11, 684–689 (2015).

    Article  Google Scholar 

  23. Hong, G. & Lieber, C. M. Novel electrode technologies for neural recordings. Nat. Rev. Neurosci. 20, 330–345 (2019).

    Article  Google Scholar 

  24. Lin, M. Z. & Schnitzer, M. J. Genetically encoded indicators of neuronal activity. Nat. Neurosci. 19, 1142–1153 (2016).

    Article  Google Scholar 

  25. Deneux, T. et al. Accurate spike estimation from noisy calcium signals for ultrafast three-dimensional imaging of large neuronal populations in vivo. Nat. Commun. 7, 12190 (2016).

    Article  ADS  Google Scholar 

  26. Soleimanzad, H., Gurden, H. & Pain, F. Optical properties of mice skull bone in the 455 to 705 nm range. J. Biomed. Opt. 22, 010503 (2017).

    Article  Google Scholar 

  27. Goodman, J. W. Speckle Phenomena in Optics: Theory and Applications (Roberts & Company, 2007).

  28. Comon, P. & Jutten, C. Handbook of Blind Source Separation (Academic Press, 2010).

  29. Mukamel, E. A., Nimmerjahn, A. & Schnitzer, M. J. Automated analysis of cellular signals from large-scale calcium imaging data. Neuron 63, 747–760 (2009).

    Article  Google Scholar 

  30. Diego Andilla, F. & Hamprecht, F. A. Sparse space-time deconvolution for calcium image analysis. In Advances in Neural Information Processing Systems 27 (eds Ghahramani, Z. et al.) 64–72 (Curran Associates, 2014).

  31. Maruyama, R. et al. Detecting cells using non-negative matrix factorization on calcium imaging data. Neural Netw. 55, 11–19 (2014).

    Article  Google Scholar 

  32. Pnevmatikakis, E. et al. Simultaneous denoising, deconvolution and demixing of calcium imaging data. Neuron 89, 285–299 (2016).

    Article  Google Scholar 

  33. Mertz, J. & Barankov, R. Imaging luminous objects through a single optical fiber. In Proceedings of Optics in the Life Sciences (2015) BT2A.1 (Optical Society of America, 2015).

  34. Saade, A. et al. Random projections through multiple optical scattering: approximating kernels at the speed of light. In 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 6215–6219 (IEEE, 2016).

  35. Rahimi, A. & Recht, B. Random features for large-scale kernel machines. In Proceeedings of Advances in Neural Information Processing Systems 20 (eds Platt, J. C. et al.) 1177–1184 (Curran Associates, 2008).

  36. Mahoney, M. in Foundations and Trends in Machine Learning Vol. 3, 123–224 (Now Publishers, 2011).

  37. Boniface, A., Blochet, B., Dong, J. & Gigan, S. Noninvasive light focusing in scattering media using speckle variance optimization. Optica 6, 1381–1385 (2019).

    Article  ADS  Google Scholar 

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Acknowledgements

We thank L. Bourdieu for providing biological samples and for numerous discussions, and F. Niwa for the cultured neurons. We also thank A. Vaziri and T. Nöbauer for useful suggestions, S. Leedumrongwatthanakun, J. Dong and A. Boniface for constructive comments, and B. Rauer and F. Soldevila for comments on the manuscript. This work was funded by the European Research Council (ERC; H2020, SMARTIES-724473). S.G. is a member of the Institut Universitaire de France.

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C.M. performed the experiment and analysed the data. S.G. and C.M. conceived the project and wrote the manuscript. S.G. supervised the project.

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Correspondence to Sylvain Gigan.

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The authors declare no competing interests.

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Supplementary Information

Supplementary methods and Figs. 1–13.

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Moretti, C., Gigan, S. Readout of fluorescence functional signals through highly scattering tissue. Nat. Photonics 14, 361–364 (2020). https://doi.org/10.1038/s41566-020-0612-2

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