Abstract
Voltage imaging with cellular specificity has been made possible by advances in genetically encoded voltage indicators. However, the kilohertz rates required for voltage imaging lead to weak signals. Moreover, out-of-focus fluorescence and tissue scattering produce background that both undermines the signal-to-noise ratio and induces crosstalk between cells, making reliable in vivo imaging in densely labeled tissue highly challenging. We describe a microscope that combines the distinct advantages of targeted illumination and confocal gating while also maximizing signal detection efficiency. The resulting benefits in signal-to-noise ratio and crosstalk reduction are quantified experimentally and theoretically. Our microscope provides a versatile solution for enabling high-fidelity in vivo voltage imaging at large scales and penetration depths, which we demonstrate across a wide range of imaging conditions and different genetically encoded voltage indicator classes.
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Data availability
Data underlying the results presented in this study are available at https://doi.org/10.5281/zenodo.10682544 (ref. 55). Source data are provided with this paper.
Code availability
All relevant code for data processing is available at https://doi.org/10.5281/zenodo.10682544 (ref. 55) (Creative Commons Attribution 4.0 International License).
References
Kim, T. H. & Schnitzer, M. J. Fluorescence imaging of large-scale neural ensemble dynamics. Cell 185, 9–41 (2022).
Lin, M. Z. & Schnitzer, M. J. Genetically encoded indicators of neuronal activity. Nat. Neurosci. 19, 1142–1153 (2016).
Sabatini, B. L. & Tian, L. Imaging neurotransmitter and neuromodulator dynamics in vivo with genetically encoded indicators. Neuron 108, 17–32 (2020).
Huang, L. et al. Relationship between simultaneously recorded spiking activity and fluorescence signal in GCaMP6 transgenic mice. eLife 10, e51675 (2021).
Knöpfel, T. & Song, C. Optical voltage imaging in neurons: moving from technology development to practical tool. Nat. Rev. Neurosci. 20, 719–727 (2019).
Gong, Y. et al. High-speed recording of neural spikes in awake mice and flies with a fluorescent voltage sensor. Science 350, 1361–1366 (2015).
Piatkevich, K. D. et al. A robotic multidimensional directed evolution approach applied to fluorescent voltage reporters. Nat. Chem. Biol. 14, 352–360 (2018).
Piatkevich, K. D. et al. Population imaging of neural activity in awake behaving mice. Nature 574, 413–417 (2019).
Adam, Y. et al. Voltage imaging and optogenetics reveal behaviour-dependent changes in hippocampal dynamics. Nature 569, 413–417 (2019).
Villette, V. et al. Ultrafast two-photon imaging of a high-gain voltage indicator in awake behaving mice. Cell 179, 1590–1608 (2019).
Kannan, M. et al. Dual-polarity voltage imaging of the concurrent dynamics of multiple neuron types. Science 378, eabm8797 (2022).
Tian, H. et al. Video-based pooled screening yields improved far-red genetically encoded voltage indicators. Nat. Methods 20, 1082–1094 (2023).
Abdelfattah, A. S. et al. Sensitivity optimization of a rhodopsin-based fluorescent voltage indicator. Neuron 111, 1547–1563.e9 (2023).
Liu, Z. et al. Sustained deep-tissue voltage recording using a fast indicator evolved for two-photon microscopy. Cell 185, 3408–3425 (2022).
Lim, S. T., Antonucci, D. E., Scannevin, R. H. & Trimmer, J. S. A novel targeting signal for proximal clustering of the Kv2.1 K+ channel in hippocampal neurons. Neuron 25, 385–397 (2000).
Quicke, P. et al. Single-neuron level one-photon voltage imaging with sparsely targeted genetically encoded voltage indicators. Front. Cell. Neurosci. 13, 39 (2019).
Fan, L. Z. et al. All-optical electrophysiology reveals the role of lateral inhibition in sensory processing in cortical layer 1. Cell 180, 521–535 (2020).
Xiao, S. et al. Large-scale voltage imaging in behaving mice using targeted illumination. iScience 24, 103263 (2021).
Weber, T. D., Moya, M. V., Kilic, K., Mertz, J. & Economo, M. N. High-speed multiplane confocal microscopy for voltage imaging in densely labeled neuronal populations. Nat. Neurosci. 26, 1642–1650 (2023).
Li, B. et al. Two-photon voltage imaging of spontaneous activity from multiple neurons reveals network activity in brain tissue. iScience 23, 101363 (2020).
Wu, J. et al. Kilohertz two-photon fluorescence microscopy imaging of neural activity in vivo. Nat. Methods 17, 287–290 (2020).
Platisa, J. et al. High-speed low-light in vivo two-photon voltage imaging of large neuronal populations. Nat. Methods 20, 1095–1103 (2023).
Quirin, S., Jackson, J., Peterka, D. S. & Yuste, R. Simultaneous imaging of neural activity in three dimensions. Front. Neural Circuits 8, 29 (2014).
Ducros, M., Houssen, Y. G., Bradley, J., de Sars, V. & Charpak, S. Encoded multisite two-photon microscopy. Proc. Natl Acad. Sci. USA 110, 13138–13143 (2013).
Pawley, J. Handbook of Biological Confocal Microscopy Vol. 236 (Springer Science & Business Media, 2006).
Saleh, B. E. & Teich, M. C. Fundamentals of Photonics (John Wiley & Sons, 2019).
Geng, Q., Gu, C., Cheng, J. & Chen, S.-c Digital micromirror device-based two-photon microscopy for three-dimensional and random-access imaging. Optica 4, 674–677 (2017).
Hoffmann, M., Papadopoulos, I. N. & Judkewitz, B. Kilohertz binary phase modulator for pulsed laser sources using a digital micromirror device. Optics Lett. 43, 22–25 (2018).
Polishchuk, G. & Sokol’skiĭ, M. Correction of the image tilt in optical systems. J. Optical Technol. 75, 432–436 (2008).
Wilt, B. A., Fitzgerald, J. E. & Schnitzer, M. J. Photon shot noise limits on optical detection of neuronal spikes and estimation of spike timing. Biophys. J. 104, 51–62 (2013).
Pnevmatikakis, E. A. et al. Simultaneous denoising, deconvolution and demixing of calcium imaging data. Neuron 89, 285–299 (2016).
Giovannucci, A. et al. CaImAn an open source tool for scalable calcium imaging data analysis. eLife 8, e38173 (2019).
Cai, C. et al. Volpy: automated and scalable analysis pipelines for voltage imaging datasets. PLoS Comput. Biol. 17, e1008806 (2021).
Einstein, M. C., Polack, P.-O., Tran, D. T. & Golshani, P. Visually evoked 3–5 Hz membrane potential oscillations reduce the responsiveness of visual cortex neurons in awake behaving mice. J. Neurosci. 37, 5084–5098 (2017).
Nestvogel, D. B. & McCormick, D. A. Visual thalamocortical mechanisms of waking state-dependent activity and alpha oscillations. Neuron 110, 120–138 (2022).
Senzai, Y., Fernandez-Ruiz, A. & Buzsáki, G. Layer-specific physiological features and interlaminar interactions in the primary visual cortex of the mouse. Neuron 101, 500–513 (2019).
Cruikshank, S. J. et al. Thalamic control of layer 1 circuits in prefrontal cortex. J. Neurosci. 32, 17813–17823 (2012).
Rubio-Garrido, P., Pérez-de Manzo, F., Porrero, C., Galazo, M. J. & Clascá, F. Thalamic input to distal apical dendrites in neocortical layer 1 is massive and highly convergent. Cereb. Cortex 19, 2380–2395 (2009).
Abdelfattah, A. S. et al. Bright and photostable chemigenetic indicators for extended in vivo voltage imaging. Science 365, 699–704 (2019).
Takasaki, K., Abbasi-Asl, R. & Waters, J. Superficial bound of the depth limit of two-photon imaging in mouse brain. eNeuro 7, 0255-19.2019 (2020).
Mohammed, A. I. et al. An integrative approach for analyzing hundreds of neurons in task performing mice using wide-field calcium imaging. Sci. Rep. 6, 20986 (2016).
Jung, J. C., Mehta, A. D., Aksay, E., Stepnoski, R. & Schnitzer, M. J. In vivo mammalian brain imaging using one- and two-photon fluorescence microendoscopy. J. Neurophysiol. 92, 3121–3133 (2004).
Andermann, M. L. et al. Chronic cellular imaging of entire cortical columns in awake mice using microprisms. Neuron 80, 900–913 (2013).
Larkum, M. E., Petro, L. S., Sachdev, R. N. & Muckli, L. A perspective on cortical layering and layer-spanning neuronal elements. Front. Neuroanatomy https://doi.org/10.3389/fnana.2018.00056 (2018).
Zhang, Y. et al. Fast and sensitive GCaMP calcium indicators for imaging neural populations. Nature 615, 884–891 (2023).
Marvin, J. S. et al. Stability, affinity and chromatic variants of the glutamate sensor iGluSnFR. Nat. Methods 15, 936–939 (2018).
Shain, W. J., Vickers, N. A., Goldberg, B. B., Bifano, T. & Mertz, J. Extended depth-of-field microscopy with a high-speed deformable mirror. Optics Lett. 42, 995–998 (2017).
Xiao, S., Tseng, H.-A., Gritton, H., Han, X. & Mertz, J. Video-rate volumetric neuronal imaging using 3D targeted illumination. Sci. Rep. 8, 7921 (2018).
Kim, T. H. et al. Long-term optical access to an estimated one million neurons in the live mouse cortex. Cell Rep. 17, 3385–3394 (2016).
Kılıç, K. et al. Chronic cranial windows for long term multimodal neurovascular imaging in mice. Front. Physiol. 11, 612678 (2021).
Padfield, D. Masked object registration in the Fourier domain. IEEE Trans. Image Proc. 21, 2706–2718 (2011).
Heintzmann, R., Relich, P. K., Nieuwenhuizen, R. P., Lidke, K. A. & Rieger, B. Calibrating photon counts from a single image. Preprint at https://doi.org/10.48550/arXiv.1611.05654 (2016).
Lachaux, J. P., Rodriguez, E., Martinerie, J. & Varela, F. J. Measuring phase synchrony in brain signals. Human Brain Mapping 8, 194–208 (1999).
Aydore, S., Pantazis, D. & Leahy, R. M. A note on the phase locking value and its properties. NeuroImage 74, 231–244 (2013).
Xiao, S. et al. Source code and data for manuscript “Large-scale deep tissue voltage imaging with targeted illumination confocal microscopyˮ. Zenodo https://doi.org/10.5281/zenodo.10682544 (2024).
Acknowledgements
We thank members of the Han and Economo laboratories for their assistance in imaging experiments. This work was supported by the National Institutes of Health grant nos. R34NS127098 (S.X. and J.M.), R01MH122971 (K.K., E.L., R.M., C.R., E.B., D.S. and X.H.), RF1MH126882 (W.J.C. and M.N.E.) and F32MH129149 (M.V.M.), and National Science Foundation grant no. 2002971-DIOS (X.H.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
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S.X., X.H. and J.M. conceived the project. S.X. designed and built the TICO microscope. W.J.C., K.K., M.V.M., R.A.M., E.B. and D.S. prepared experimental animals. S.X. performed imaging experiments with assistance from W.J.C., K.K., M.V.M., C.R., E.B. and D.S. S.X. and E.L. analyzed the data. S.X. wrote the manuscript with contributions from W.J.C., E.L. and R.M. M.N.E., X.H. and J.M. edited the manuscript. All authors reviewed the manuscript. M.N.E., X.H. and J.M. supervised the project.
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Nature Methods thanks Darcy Peterka and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available. Primary Handling Editor: Nina Vogt, in collaboration with the Nature Methods team.
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Extended data
Extended Data Fig. 1 Principle and schematic of TICO microscope.
(a-c) Design principle of TICO microscope: (a) conventional strategy for incorporation a DMD into a confocal microscope; (b) bypassing DMD in the detection path to avoid fluorescence loss; (c) inserting a wedge prism in front of the DMD corrects for both image plane tilt and 1D magnification change caused by the DMD, restoring confocality between excitation and detection beams. (d) Detailed schematic of TICO microscope. DM, dichromatic mirror. Em, emission filter. Ex, excitation filter. PBS, polarizing beam splitter. λ/2, half-wave plate. λ/4, quarter-wave plate. Galvo, galvanometric scanner. DMD, digital micromirror device. Obj, objective.
Extended Data Fig. 2 Optical performance characterization of TICO microscope.
(a) Fluorescence image of a single layer of 1 μm fluorescent beads acquired by projecting a 7.9 μm checkerboard pattern on the DMD. Note that over the full FOV of 1.16 × 0.325 mm the top left and bottom right corner are clipped due to the smaller DMD chip size. The FOV without clipping is 880 × 325 μm, indicated by the red rectangle. Scale bar, 50 μm. (b) Confocal image of 100 nm fluorescent beads over the FOV. Slit size was set to 14 μm. Scale bar, 50 μm. (c) FWHM values of PSFs across different lateral positions across the FOV. Scale bar, 50 μm. For each group from left to right, n = 92, 106, 123, 121, 124, 82 beads from 1 FOV. Box plots same as Fig. 2(e). (d) Example PSFs from the red rectangular regions shown in (b). Scale bar, 5 μm. (e) Optical sectioning profiles measured with different slit widths 2vd. Data obtained by axially translating a single layer of 1 μm fluorescent beads and measuring the integrated intensity as a function of defocus without targeted illumination. a.u., arbitrary unit. (f) Thickness of optical sections measured at a threshold of 50% or 90% of the maximum intensity.
Extended Data Fig. 3 High-speed voltage imaging at 1 kHz frame rate.
(a) Confocal image of Voltron2 fluorescence over a FOV of 880 × 325 μm. Scale bar, 50 μm. (b) Averaged Voltron2 fluorescence image with 42 targeted neurons. Scale bar, 50 μm. (c) Fluorescence traces of spiking neurons over a 30 s recording. (d,e) Zoomed-in fluorescence traces over the rectangular labeled regions in (c).
Extended Data Fig. 4 High-speed voltage imaging at 2 kHz and 4 kHz frame rates.
(a) Confocal image of Voltron2 fluorescence. Scale bar, 50 μm. (b) Averaged Voltron2 fluorescence image with 14 neurons targeted within the FOV. Scale bar, 50 μm. (c) Voltron fluorescence traces of 5 active neurons over a 10 s recording. Recording speed 2 kHz. (d,e) Zoomed-in fluorescence traces over the rectangular labeled regions in (c). (f) Confocal image of GFP fluorescence. Scale bar, 20 μm. (g) Averaged somArchon fluorescence image with 4 neurons targeted within the FOV. Scale bar, 20 μm. (h) SomArchon fluorescence traces of 2 active neurons over a 10 s recording. Recording speed 4 kHz. (i,j) Zoomed-in fluorescence traces over the rectangular labeled regions in (h).
Extended Data Fig. 5 Large-scale imaging of Voltron2 fluorescence from 57 cells invivo.
(a) Averaged Voltron2 fluorescence image from TICO microscope with 57 cells targeted. Scale bar, 50 μm. (b) Complete 20 min recording of Voltron2 fluorescence from 57 cells. (c) Raw fluorescence traces from 2 selected cells.
Extended Data Fig. 6 Large-scale imaging of somArchon fluorescence from 37 cells near the visual cortex.
(a) Confocal image of GFP fluorescence. Yellow square indicates actual somArchon imaging FOV shown in (b). Scale bar, 50 μm. (b) SomArchon fluorescence image with 37 cells targeted. Scale bar, 50 μm. (c) SomArchon fluorescence traces of 37 cells over a continuous 30 s recording. Recording speed 775 Hz, imaging depth 100 μm. (d,e) Zoomed-in fluorescence traces of active neurons during 1 s and 25 s of the recording.
Extended Data Fig. 7 Observation of highly synchronized 3 - 5 Hz membrane oscillations in L1 interneurons.
(a) Confocal image of GFP fluorescence over the imaging FOV. Scale bar, 50 μm. (b) SomArchon fluorescence traces for all the neurons labeled in (a). Scale bar, 50 μm. (c,d) Zoomed-in fluorescence traces (top panel) of two selective neurons and their corresponding power spectra (bottom panel).
Extended Data Fig. 8 Analysis of voltage traces recorded from the animal in Extended Data Fig. 7, Supplementary Fig. 16.
(a) Frequency-resolved Vm power averaged from time periods with high delta population Vm power (> 2 standard deviation, S.D.; red trace) and low Vm power (< 2 S.D.; blue trace). Within 2 - 5 Hz frequency range (black box), most neurons showed significant Vm delta power modulation (paired student t-test, ***p = 3.27e−12, n = 99 neurons with average spike rate ≥ 1 Hz, 8 FOVs from 1 mouse). Solid line, mean; shaded area, ± 1 S.D. (b) Firing rate modulation of neurons from periods of high Vm delta power relative to periods of low Vm delta power. Paired student t-test, **p = 0.009, n = 99 neurons with average spike rate ≥ 1 Hz, 8 FOVs from 1 mouse. Box plots same as Fig. 2(e). (c) Frequency-resolved spike-Vm phase locking for all neurons. Solid line, mean; shaded area, ± 1 S.D. (d) Frequency-resolved spike-Vm phase locking between neuron pairs. Red trace, neuron pairs with separation distances between 50 - 150 μm; blue trace, neuron pairs with separation distances > 350 μm. Solid line, mean; shaded area, ± 1 S.D. (e-g) Polar plots of spike phase distribution relative to the 3-5 Hz Vm oscillations within individual neurons (e), and between neuron pairs across separation distances in the range 50 - 150 μm (f) and > 350 μm (g).
Extended Data Fig. 9 Additional datasets for in vivo imaging of Voltron2 fluorescence at depths greater than 200 μm.
Imaging depths from (a) to (d) are 220, 270, 300, and 300 μm. Left column, averaged Voltron2 fluorescence image. Scale bars are 50 μm. Middle column, Voltron2 fluorescence traces from corresponding labeled neurons over 60 s recordings. Right column, zoomed-in fluorescence traces of active neurons during 2 s clips.
Extended Data Fig. 10 Side-on voltage imaging across multiple cortical layers with an implanted microprism.
Voltron2 fluorescence traces of all 25 neurons across layer 1 to 5 over the complete 45 s recording.
Supplementary information
Supplementary Information
Supplementary Notes 1–5, Figs. 1–19 and Tables 1–3.
Supplementary Table 4
Statistical data for Supplementary Fig. 6.
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Source Data Fig. 2
Statistical source data and statistical testing results.
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Xiao, S., Cunningham, W.J., Kondabolu, K. et al. Large-scale deep tissue voltage imaging with targeted-illumination confocal microscopy. Nat Methods 21, 1094–1102 (2024). https://doi.org/10.1038/s41592-024-02275-w
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DOI: https://doi.org/10.1038/s41592-024-02275-w
