Abstract

The performance of light-field microscopy is improved by selectively illuminating the relevant subvolume of the specimen with a second objective lens. Here we advance this approach to a single-objective geometry, using an oblique one-photon illumination path or two-photon illumination to accomplish selective-volume excitation. The elimination of the second orthogonally oriented objective to selectively excite the volume of interest simplifies specimen mounting; yet, this single-objective approach still reduces the out-of-volume background, resulting in improvements in image contrast, effective resolution, and volume reconstruction quality. We validate our new, to the best of our knowledge, approach through imaging live developing zebrafish, demonstrating the technology’s ability to capture imaging data from large volumes synchronously with high contrast while remaining compatible with standard microscope sample mounting.

© 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

Biological processes often depend on the tight spatiotemporal coordination between cells across tissue-level length scales, extending over hundreds of microns in 3D. The functional understanding of such processes would be greatly aided by imaging tools that offer the combined speed and sensitivity needed to observe 3D cellular dynamics without compromising the normal biology. Light-field microscopy (LFM) is a fast, synchronous 3D imaging technique [13]. Unlike existing volumetric imaging methods that reconstruct a 3D image from intensity information collecting one voxel, one line, or one plane at a time, LFM captures both the two-dimensional (2D) spatial and 2D angular information of light emitted from the sample [Fig. 1(A)], permitting computational reconstruction of the signal from a full volume in just one snapshot. Because spatial resolution must be compromised to capture the angular distribution of the emitting light to yield the extended depth coverage, LFM sacrifices some resolution for its dramatically increased acquisition speed, achieving ${\sim}{{2}}$ orders of magnitude improvement compared to existing methods [15]. While 3D deconvolution can be used to enhance LFM performance [2,3], the out-of-volume fluorescence background, coming from parts of the sample outside the volume of interest (VOI), degrades the image contrast, and resolution. Conventional wide-field illumination excites significant out-of-volume background [Fig. 1(B)], especially for volumes within thick or densely fluorescent samples, precluding LFM’s full potential in intact tissues.

 figure: Fig. 1.

Fig. 1. ASO-SVIM. (A), simplified schematic of LFM. Fluorescence light is collected from the sample volume by an objective lens, separated and filtered from the excitation light by the appropriate dichroic mirror and bandpass filter, and focused by a tube lens at an intermediate image plane where a lenslet array is positioned. The lenslet array refocuses the light onto a camera, so that each position in the 3D sample volume is mapped onto the camera as a unique light intensity pattern. The fluorescence light-field illustrated was captured with point sources located at, above, and below the native focal plane. Such light fields can be reconstructed to full volumes by solving the inverse problem. (B), LFM with conventional wide-field illumination is compatible with standard forms of sample preparation but excites regions outside the VOI. (C), SVIM selectively illuminates the VOI using orthogonal illumination and detection objectives. (D) and (E), ASO-SVIM preferentially excites the VOI and collects the fluorescence using a single-objective lens, providing flexibility in sample mounting similar to traditional microscopy. (D), 1P-ASO-SVIM uses an oblique light sheet, which is scanned in 1D, to define the excitation volume. (E), 2P-ASO-SVIM uses nonlinear excitation of a pulsed near-infrared (NIR) beam that is raster-scanned to define the VOI. In images (A)–(D), 1P excitation is depicted in cyan and, in image (E), 2P excitation is depicted in red; fluorescence emission is depicted in green. See also Supplement 1, Section 1, and Figs. S1–S2.

Download Full Size | PPT Slide | PDF

Inspired by light-sheet microscopy, also known as selective-plane illumination microscopy (SPIM), we recently introduced an improved light-field-based imaging approach, selective-volume illumination microscopy (SVIM), where confining excitation preferentially to the VOI reduces the extraneous out-of-volume background, thereby sharpening the image contrast, reducing unwanted photo damage, and improving the effective resolution in thick specimens [4]. SVIM was implemented with two objective lenses: one to selectively illuminate the VOI, and a second objective, orthogonally aligned, to acquire the fluorescent light field [Fig. 1(C)]. This two-objective geometry requires the sample to be mounted within the mutual intersecting volume defined by the objectives, complicating sample mounting and limiting sample size. Here we implement SVIM in a single-objective geometry, eliminating the need for two orthogonally oriented objectives, greatly simplifying sample mounting and broadening its utility for biological research.

This new technique, termed axial single-objective SVIM (ASO-SVIM), selectively illuminates the sample volume through the same objective used for high-numerical-aperture (NA) detection (Supplement 1, Section 1, and Fig. S1). The VOI is preferentially excited by either one-photon or two-photon processes (1P- or 2P-ASO-SVIM). 1P-ASO-SVIM is accomplished by using a 2D light sheet oriented obliquely to the axial axis [26.5°; Fig. 1(D)], created via a cylindrical lens with an NA of ${\sim}{{0}.\rm{04 {-} 0}.{06}}$, yielding a Gaussian-beam waist of ${\sim}{\rm{4 {-} 6}}\;{\rm{\unicode{x00B5}{\rm m}}}$ and ${\sim}{\rm{150 {-} 230}}\;{\rm{\unicode{x00B5}{\rm m}}}$ confocal parameter; the sample is illuminated by sweeping this oblique sheet in 1D to excite fluorescence within the VOI multiple times within a single camera exposure. 2P-ASO-SVIM is accomplished using a low-NA (${\sim}{{0}.\rm{055 {-} 0}.{08}}$) Gaussian beam that is parallel to the axial axis [Fig. 1(E)], for opto-mechanical simplicity. Two-photon absorption defines the VOI axially (${\sim}{\rm{150 - 230}}\;{\rm{\unicode{x00B5}{\rm m}}}$) via the quadratic dependence of the fluorescence signal on the excitation intensity [4,6]; the beam is raster-scanned in 2D to excite the desired 3D sample volume.

To capture fluorescence light fields emitted from the excited volume, a lenslet array is placed at the native image plane [2]; the foci of the lenslets are imaged onto a camera sensor [Fig. 1(A)]. To enable a direct, quantitative comparison of our technique to more established methods, our microscope is designed to offer seamless switching to SPIM or wide-field LFM modes [Supplement 1, Section 1, Figs. S1 and S2].

We benchmarked the ASO-SVIM performance by measuring the pointspread function with 175 nm fluorescent beads suspended in agarose. After 3D deconvolution [2,3], we obtained volumetric images with the expected maximum resolution, consistent with the optical design: ${2.4}\;{{\pm}}\;{0.3}\;\unicode{x00B5}{\rm m}$ lateral full-width at half-maximum (FWHM), ${5.7}\;{{\pm}}\;{0.2}\;\unicode{x00B5}{\rm m}$ axial FWHM [Supplement 1, Fig. S3(C)]. Due to diffraction and non-uniform sampling of the light-field volume [2,3], the 3D resolution was depth-dependent (varying up to ${\sim}{{46}}\%$ over a $z$ range of ${-}{{50}}$ to 50 µm) [Supplement 1, Fig. S3(B)], and reconstructions contained grid-like artifacts near the native focal plane, as previously reported [2]. To reduce such artifacts in the reconstructions presented here, we applied a low-pass filter in Fourier space ($k$-space), truncating spurious spatial frequencies beyond the resolution limit of the native focal plane (Supplement 1, Section 2, Figs. S4 and S5). The simple process of $k$-space filtering across the nominal focus dampened the artifacts and improved visualization of the 3D reconstructions, without any major loss of 3D resolution or spatial information (Supplement 1, Figs. S5 and S6).

We compared ASO-SVIM with wide-field LFM in imaging the fluorescently-labeled vasculature of the same live larval zebrafish [Fig. 2]. In the comparison, ground-truth images were provided by SPIM, which was recorded as a multi-plane z-stack and deconvolved, thus producing the best image quality at the cost of being slower than the light-field modalities, where the 3D volume was recorded in one snapshot [Supplement, Section 1.6]. ASO-SVIM, using either 1P or 2P excitation, came closer to SPIM than wide-field LFM, producing images with reduced out-of-volume background and higher contrast, [Fig. 2(A)], consistent with results we previously reported for SVIM [4]. This is clearly revealed in an $x {-} z$ slice through the 3D volume [Fig. 2(A), bottom].

 figure: Fig. 2.

Fig. 2. ASO-SVIM improves the contrast and effective resolution in live imaging of zebrafish larvae. (A), top, average-intensity projections (AIPs) of a 100 µm thick 3D image stack from the same transgenic [Tg(kdrl:GFP)] five-day post fertilization (dpf) zebrafish, where the vasculature was fluorescently labeled with green fluorescent protein (GFP), captured by different imaging modalities. Inset: transmitted light image of the zebrafish head, where the dashed red rectangle marks the ${{230}}\;\unicode{x00B5}{\rm m} \times {{600}}\;\unicode{x00B5}{\rm m} \times {{100}}\;\unicode{x00B5} {{\rm{m}}^3}$ volume imaged. (Bottom) cross-sectional ($x {-} z$) views at the location indicated by the dashed yellow line (top left, SPIM panel). The SPIM volume consists of 67 optical sections (exposure time, 355 ms; excitation power at sample, 0.15 mW), collected serially over ${\sim}{{44}}\;{\rm{s}}$; the LFM-based volumes were reconstructed from a single image with an exposure of 355 ms (excitation power, 2P-ASO-SVIM: 525 mW; 1P-ASO-SVIM: 1.5 mW; wide-field LFM: 4 mW). Scale bar, 100 µm. (B), quantification of image contrast versus $z$-depth, showing improvements of 1P-ASO-SVIM and 2 P-ASO-SVIM over wide-field LFM. The image contrast is plotted for each $x {-} y$ slice, normalized by the value of SPIM (blue trace) at $z = - {{50}}\;\unicode{x00B5}{\rm m}$. (C), intensity profiles along the same line for all four modalities (dashed yellow line shown on the $x {-} z$ cut in A; bottom, SPIM). The fluorescence intensities of ASO-SVIM agree more closely with the ground-truth SPIM data than does wide-field LFM. (D), FTs of $x {-} y$ MIPs through the 100 µm thick slabs in (A). The resolution bands (white circles) help show the increased spatial frequency content of ASO-SVIM compared to wide-field LFM, where more signal intensity at larger radial position designates higher resolution captured. (E), average amplitudes along ${k_y}$ direction of the FTs shown in (D), showing that ASO-SVIM frequency spectra fall slower to the experimental noise floor, indicating better effective resolution than wide-field LFM. See also Supplement 1, Fig. S7. (F), enlarged $x {-} y$ slices to highlight single blood vessels, centered at ${\sim}{{86}}\;\unicode{x00B5}{\rm m}$ into the specimen, from the subregion indicated by the dashed yellow box in [(A), top left]. (G), intensity profiles, averaged from the dashed yellow line shown in (F) and from two other similar vessels (Supplement 1, Fig. S8), demonstrate the improvements in effective resolution of ASO-SVIM over wide-field LFM.

Download Full Size | PPT Slide | PDF

To obtain quantitative measures of the enhanced performance of 1P- and 2P-ASO-SVIM, we calculated the image contrast (defined as the standard deviation of the pixel intensities normalized to the mean intensity) for each $x {-} y$ image plane [Fig. 2(B)]: 1P-ASO-SVIM showed a modest improvement; 2P-ASO-SVIM showed more dramatic improvement over wide-field LFM. The intensity profiles of LFM images [along the dashed yellow line in Fig. 2(A), bottom] documented the improved performance of ASO-SVIM [Fig. 2(C)], as did the Fourier transforms (FTs) of the images [Figs. 2(D) and 2(E)]. Thus, the reduction in background fluorescence substantially boosts the image contrast, as well as effective spatial resolution, both laterally and axially [Figs. 2(D) and 2(E) and Supplement 1, Fig. S7]. The enhanced contrast and effective resolution of the ASO-SVIM modalities are further demonstrated by comparing recorded images of single blood vessels, as well as measurements of the width of these vessels from the line profiles [Figs. 2(F) and 2(G)] and Supplement 1, Fig. S8).

 figure: Fig. 3.

Fig. 3. ASO-SVIM enhances large-scale in vivo recording of neural activity in a ${{320}}\;\unicode{x00B5}{\rm m} \times {{350}}\;\unicode{x00B5}{\rm m} \times \;{{100}}\;\unicode{x00B5} {{\rm{m}}^3}$ volume in larval zebrafish, at 5-dpf, Tg(elavl3:H2b-GCaMP6s). The volumetric rate of 1 Hz sufficiently captured the transient neuronal dynamics, given the relatively slow temporal kinetics of the nuclear-localized calcium indicator GCaMP6s [13]. Excitation power, 2 P-ASO-SVIM, 525 mW; 1 P-ASO-SVIM, 0.4 mW; wide-field LFM, 0.5 mW. (A), MIPs of $x {-} y$ (top) and $x {-} z$ (bottom) brain-wide 100 µm thick volumes of the same zebrafish. These projections depict the standard deviation over a 25 s period for each voxel, highlighting active neurons. Scale bar, 100 µm. See Visualization 1. (B), quantification of the image contrast versus $z$-depth, showing progressive improvements of 1P-ASO-SVIM and 2P-ASO-SVIM over wide-field LFM. The means (center lines) and standard deviations (shadings) are shown. (C), single-neuron signal traces captured by the different modalities, extracted from the 4D datasets shown in (A).

Download Full Size | PPT Slide | PDF

To test ASO-SVIM on a more demanding application, we recorded the activity of large populations of neurons in larval zebrafish. LFM is an attractive technique to meet the neuroimaging challenge of recording the transient firings of a large number of spatially distributed neurons, because it can synchronously capture large volumes; however, the high level of background fluorescence in wide-field LFM has remained an impediment to efforts aimed at capturing brain-wide activity with cellular resolution [3,712]. We previously showed that the improved contrast and effective resolution of SVIM improved brain-wide functional imaging over conventional LFM [4]. We extended the demonstration and analysis to our new ASO-SVIM approach here.

We compared 1P-ASO-SVIM, 2P-ASO-SVIM, and wide-field LFM in imaging the spontaneous brain activity of the same zebrafish larva, labeled with a genetically encoded pan-neuronal fluorescent calcium indicator [Fig. 3]. The reconstructed four-dimensional (4D) recordings are compared by taking the standard deviation along the temporal axis [Fig. 3(A)], to highlight their capability in capturing active neurons, whose transient firings would produce voxels that have large intensity variation in time and thus appear as high-contrast puncta in the resulting projections. We calculated the image contrast of these temporal-standard-deviation projections: 2P-ASO-SVIM achieved the highest contrast, followed by the 1P ASO-SVIM, and then by wide-field LFM [Fig. 3(B)], suggesting that the ASO-SVIM modalities excel in capturing neuronal activity over wide-field LFM.

To quantitatively compare the performance of the different modalities in capturing brain activity at cellular resolution, we identified neurons in the 4D recordings by spot-segmenting the temporal-standard-deviation projections [4]. This standard protocol produced spatial masks corresponding to neurons that were active during the time-lapse. These masks were then applied to the 4D datasets to extract temporal signals that represent single-neuron activity traces [Fig. 3(C)]. The improved contrast of 2P- and 1P-ASO-SVIM allowed us to detect a greater number of active neurons in the brain compared to conventional wide-field illumination [Fig. 3(C)]. 2P-ASO-SVIM captured the largest number of active neurons, due not only to its higher contrast than its 1P counterpart (expanded below) but also because the NIR excitation light is invisible to the fish and thereby significantly reduces the response of the animal’s visual system to the illumination, which would otherwise cloud spontaneous activity [4]. 2P-ASO-SVIM is thus an optimal tool for studies of visually sensitive neural behaviors.

1P- and 2P-ASO-SVIM offer distinct strengths. 1P-ASO-SVIM commands lower laser costs, and offers optical simplicity and exceptionally high volumetric acquisition speed, limited largely by the rate of the camera [4]. However, the 1P excitation volume intersects the sample obliquely and is larger than the desired detection volume [Fig. 1(D)], making 1P-ASO-SVIM less efficient at reducing the background than SVIM (Supplement 1, Section 1.5). Like all forms of linear excitation, visible 1P excitation light increasingly scatters with the depth, resulting in an unavoidable background from outside the VOI. 2P-ASO-SVIM effectively eliminates the background from out-of-volume fluorescence [Fig. 2(A)] due to nonlinear excitation: the quadratic dependence of 2P-excited fluorescence on the laser intensity restricts the excitation volume to near the focus [4,6], resulting in a negligible background, even with single-objective designs. The NIR excitation light is scattered much less than visible wavelengths, allowing a better penetration depth into biological tissue. Through the judicious selection of illumination NA and beam-scanning, it is straightforward to match the 2P excitation volume to the desired VOI (Supplement 1, Section 1). This advantage is partially tempered by the reduced speed of 2P-ASO-SVIM, as the lower 2P excitation cross section yields a lower fluorescence signal for a given laser intensity, which cannot be increased without bounds out of concern for photo damage.

As a final example of the combination of high-contrast, ultrahigh-speed volumetric imaging at cellular resolution, and the sample-mounting flexibility of ASO-SVIM, we imaged a 3D blood flow in nearly the entire larval zebrafish brain, covering a ${{670}}\times {{470}} \times {{200}}\;{\unicode{x00B5}{\rm m}}^3$ volume at ${\sim}{{50}}\;{\rm{Hz}}$ in nine zebrafish mounted in a standard multi-well plate (Supplement 1, Fig. S9, and Visualization 2, Visualization 3 and Visualization 4). Together, our results show that ASO-SVIM offers a convenient middle ground between SPIM and traditional wide-field LFM, offering improved contrast and effective resolution compared to LFM, while outperforming the 3D imaging speed of SPIM by ${\sim}{{2}}$ orders of magnitude, as it requires only a single camera exposure to capture an extended volume. Compared to our earlier form of SVIM [4], ASO-SVIM relaxes steric constraints by using only one objective, easing sample preparation and expanding the application space to multicellular systems that are impractical for a dual-objective design. Improvements of 1P-ASO-SVIM could include a detection objective with a larger NA to enable a larger excitation tilt angle, or a tilted detection path via a tertiary imaging module [1418] that maximizes the effective angle between excitation and detection, to further leverage the strengths of selective illumination (Supplement 1, Section 1.5). To improve the signal rate and hence the imaging speed of 2P-ASO-SVIM, measures that similarly improve the signal rate of multiphoton microscopy could be deployed, such as dispersion compensation [19], resonant scanning, and an optimal laser pulse frequency [20] (Supplement 1, Section 1.3). Finally, the simplicity of ASO-SVIM renders it compatible and synergistic with many recent refinements of LFM [710], and we envision that together they will bring LFM-based imaging techniques into a wide range of biological systems and applications.

Funding

National Science Foundation (1608744, 1650406, 1828793); National Institutes of Health (1R01MH107238-01); Jet Propulsion Laboratory (1632330); Alfred E. Mann Institute, University of Southern California (Fellowship to KKD).

Acknowledgment

The authors acknowledge D. Holland, A. Andreev, and F. Cutrale for discussion and technical assistance.

Disclosures

The authors declare no conflicts of interest.

Data Availability

Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

Supplemental document

See Supplement 1 for supporting content.

REFERENCES

1. M. Levoy, R. Ng, A. Adams, M. Footer, and M. Horowitz, in ACM SIGGRAPH (ACM, 2006), pp. 924–934.

2. M. Broxton, L. Grosenick, S. Yang, N. Cohen, A. Andalman, K. Deisseroth, and M. Levoy, Opt. Express 21, 25418 (2013). [CrossRef]  

3. R. Prevedel, Y. G. Yoon, M. Hoffmann, N. Pak, G. Wetzstein, S. Kato, T. Schrödel, R. Raskar, M. Zimmer, E. S. Boyden, and A. Vaziri, Nat. Methods 11, 727 (2014). [CrossRef]  

4. T. V. Truong, D. B. Holland, S. Madaan, A. Andreev, K. Keomanee-Dizon, J. V. Troll, D. E. S. Koo, M. J. McFall-Ngai, and S. E. Fraser, Commun. Biol. 3, 1 (2020). [CrossRef]  

5. N. Wagner, N. Norlin, J. Gierten, G. de Medeiros, B. Balázs, J. Wittbrodt, L. Hufnagel, and R. Prevedel, Nat. Methods 16, 497 (2019). [CrossRef]  

6. T. V. Truong, W. Supatto, D. S. Koos, J. M. Choi, and S. E. Fraser, Nat. Methods 8, 757 (2011). [CrossRef]  

7. N. C. Pégard, H. Y. Liu, N. Antipa, M. Gerlock, H. Adesnik, and L. Waller, Optica 3, 517 (2016). [CrossRef]  

8. L. Cong, Z. Wang, Y. Chai, W. Hang, C. Shang, W. Yang, L. Bai, J. Du, K. Wang, and Q. Wen, eLife 6, e28158 (2017). [CrossRef]  

9. T. Nöbauer, O. Skocek, A. J. Pernía-Andrade, L. Weilguny, F. M. Traub, M. I. Molodtsov, and A. Vaziri, Nat. Methods 14, 811 (2017). [CrossRef]  

10. O. Skocek, T. Nöbauer, L. Weilguny, F. M. Traub, C. N. Xia, M. I. Molodtsov, A. Grama, M. Yamagata, D. Aharoni, D. D. Cox, P. Golshani, and A. Vaziri, Nat. Methods 15, 429 (2018). [CrossRef]  

11. S. Aimon, T. Katsuki, T. Jia, L. Grosenick, M. Broxton, K. Deisseroth, T. J. Sejnowski, and R. J. Greenspan, PLoS Biol. 17, e2006732 (2019). [CrossRef]  

12. Q. Lin, J. Manley, M. Helmreich, F. Schlumm, J. M. Li, D. N. Robson, F. Engert, A. Schier, T. Nöbauer, and A. Vaziri, Cell 180, 536 (2020). [CrossRef]  

13. T. W. Chen, T. J. Wardill, Y. Sun, S. R. Pulver, S. L. Renninger, A. Baohan, E. R. Schreiter, R. A. Kerr, M. B. Orger, V. Jayaraman, L. L. Logger, K. Svoboda, and D. S. Kim, Nature 499, 295 (2013). [CrossRef]  

14. C. Dunsby, Opt. Express 16, 20306 (2008). [CrossRef]  

15. M. Kumar, S. Kishore, J. Nasenbeny, D. L. McLean, and Y. Kozorovitskiy, Opt. Express 26, 13027 (2018). [CrossRef]  

16. V. Voleti, K. B. Patel, W. Li, C. P. Campos, S. Bharadwaj, H. Yu, C. Ford, M. J. Casper, R. W. Yan, W. Liang, C. Wen, K. D. Kimura, K. L. Targof, and E. M. C. Hillman, Nat. Methods 16, 1054 (2019). [CrossRef]  

17. B. Yang, X. Chen, Y. Wang, S. Feng, V. Pessino, N. Stuurman, N. H. Cho, K. W. Cheng, S. J. Lord, L. Xu, D. Xie, R. D. Mullins, M. D. Leonetti, and B. Huang, Nat. Methods 16, 501 (2019). [CrossRef]  

18. E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020). [CrossRef]  

19. V. Chauhan, P. Bowlan, J. Cohen, and R. Trebino, J. Opt. Soc. Am. B 27, 619 (2010). [CrossRef]  

20. V. Maioli, A. Boniface, P. Mahou, J. F. Ortas, L. Abdeladim, E. Beaurepaire, and W. Supatto, Biomed. Opt. Express 11, 6012 (2020). [CrossRef]  

References

  • View by:
  • |
  • |
  • |

  1. M. Levoy, R. Ng, A. Adams, M. Footer, and M. Horowitz, in ACM SIGGRAPH (ACM, 2006), pp. 924–934.
  2. M. Broxton, L. Grosenick, S. Yang, N. Cohen, A. Andalman, K. Deisseroth, and M. Levoy, Opt. Express 21, 25418 (2013).
    [Crossref]
  3. R. Prevedel, Y. G. Yoon, M. Hoffmann, N. Pak, G. Wetzstein, S. Kato, T. Schrödel, R. Raskar, M. Zimmer, E. S. Boyden, and A. Vaziri, Nat. Methods 11, 727 (2014).
    [Crossref]
  4. T. V. Truong, D. B. Holland, S. Madaan, A. Andreev, K. Keomanee-Dizon, J. V. Troll, D. E. S. Koo, M. J. McFall-Ngai, and S. E. Fraser, Commun. Biol. 3, 1 (2020).
    [Crossref]
  5. N. Wagner, N. Norlin, J. Gierten, G. de Medeiros, B. Balázs, J. Wittbrodt, L. Hufnagel, and R. Prevedel, Nat. Methods 16, 497 (2019).
    [Crossref]
  6. T. V. Truong, W. Supatto, D. S. Koos, J. M. Choi, and S. E. Fraser, Nat. Methods 8, 757 (2011).
    [Crossref]
  7. N. C. Pégard, H. Y. Liu, N. Antipa, M. Gerlock, H. Adesnik, and L. Waller, Optica 3, 517 (2016).
    [Crossref]
  8. L. Cong, Z. Wang, Y. Chai, W. Hang, C. Shang, W. Yang, L. Bai, J. Du, K. Wang, and Q. Wen, eLife 6, e28158 (2017).
    [Crossref]
  9. T. Nöbauer, O. Skocek, A. J. Pernía-Andrade, L. Weilguny, F. M. Traub, M. I. Molodtsov, and A. Vaziri, Nat. Methods 14, 811 (2017).
    [Crossref]
  10. O. Skocek, T. Nöbauer, L. Weilguny, F. M. Traub, C. N. Xia, M. I. Molodtsov, A. Grama, M. Yamagata, D. Aharoni, D. D. Cox, P. Golshani, and A. Vaziri, Nat. Methods 15, 429 (2018).
    [Crossref]
  11. S. Aimon, T. Katsuki, T. Jia, L. Grosenick, M. Broxton, K. Deisseroth, T. J. Sejnowski, and R. J. Greenspan, PLoS Biol. 17, e2006732 (2019).
    [Crossref]
  12. Q. Lin, J. Manley, M. Helmreich, F. Schlumm, J. M. Li, D. N. Robson, F. Engert, A. Schier, T. Nöbauer, and A. Vaziri, Cell 180, 536 (2020).
    [Crossref]
  13. T. W. Chen, T. J. Wardill, Y. Sun, S. R. Pulver, S. L. Renninger, A. Baohan, E. R. Schreiter, R. A. Kerr, M. B. Orger, V. Jayaraman, L. L. Logger, K. Svoboda, and D. S. Kim, Nature 499, 295 (2013).
    [Crossref]
  14. C. Dunsby, Opt. Express 16, 20306 (2008).
    [Crossref]
  15. M. Kumar, S. Kishore, J. Nasenbeny, D. L. McLean, and Y. Kozorovitskiy, Opt. Express 26, 13027 (2018).
    [Crossref]
  16. V. Voleti, K. B. Patel, W. Li, C. P. Campos, S. Bharadwaj, H. Yu, C. Ford, M. J. Casper, R. W. Yan, W. Liang, C. Wen, K. D. Kimura, K. L. Targof, and E. M. C. Hillman, Nat. Methods 16, 1054 (2019).
    [Crossref]
  17. B. Yang, X. Chen, Y. Wang, S. Feng, V. Pessino, N. Stuurman, N. H. Cho, K. W. Cheng, S. J. Lord, L. Xu, D. Xie, R. D. Mullins, M. D. Leonetti, and B. Huang, Nat. Methods 16, 501 (2019).
    [Crossref]
  18. E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
    [Crossref]
  19. V. Chauhan, P. Bowlan, J. Cohen, and R. Trebino, J. Opt. Soc. Am. B 27, 619 (2010).
    [Crossref]
  20. V. Maioli, A. Boniface, P. Mahou, J. F. Ortas, L. Abdeladim, E. Beaurepaire, and W. Supatto, Biomed. Opt. Express 11, 6012 (2020).
    [Crossref]

2020 (4)

T. V. Truong, D. B. Holland, S. Madaan, A. Andreev, K. Keomanee-Dizon, J. V. Troll, D. E. S. Koo, M. J. McFall-Ngai, and S. E. Fraser, Commun. Biol. 3, 1 (2020).
[Crossref]

Q. Lin, J. Manley, M. Helmreich, F. Schlumm, J. M. Li, D. N. Robson, F. Engert, A. Schier, T. Nöbauer, and A. Vaziri, Cell 180, 536 (2020).
[Crossref]

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

V. Maioli, A. Boniface, P. Mahou, J. F. Ortas, L. Abdeladim, E. Beaurepaire, and W. Supatto, Biomed. Opt. Express 11, 6012 (2020).
[Crossref]

2019 (4)

V. Voleti, K. B. Patel, W. Li, C. P. Campos, S. Bharadwaj, H. Yu, C. Ford, M. J. Casper, R. W. Yan, W. Liang, C. Wen, K. D. Kimura, K. L. Targof, and E. M. C. Hillman, Nat. Methods 16, 1054 (2019).
[Crossref]

B. Yang, X. Chen, Y. Wang, S. Feng, V. Pessino, N. Stuurman, N. H. Cho, K. W. Cheng, S. J. Lord, L. Xu, D. Xie, R. D. Mullins, M. D. Leonetti, and B. Huang, Nat. Methods 16, 501 (2019).
[Crossref]

S. Aimon, T. Katsuki, T. Jia, L. Grosenick, M. Broxton, K. Deisseroth, T. J. Sejnowski, and R. J. Greenspan, PLoS Biol. 17, e2006732 (2019).
[Crossref]

N. Wagner, N. Norlin, J. Gierten, G. de Medeiros, B. Balázs, J. Wittbrodt, L. Hufnagel, and R. Prevedel, Nat. Methods 16, 497 (2019).
[Crossref]

2018 (2)

O. Skocek, T. Nöbauer, L. Weilguny, F. M. Traub, C. N. Xia, M. I. Molodtsov, A. Grama, M. Yamagata, D. Aharoni, D. D. Cox, P. Golshani, and A. Vaziri, Nat. Methods 15, 429 (2018).
[Crossref]

M. Kumar, S. Kishore, J. Nasenbeny, D. L. McLean, and Y. Kozorovitskiy, Opt. Express 26, 13027 (2018).
[Crossref]

2017 (2)

L. Cong, Z. Wang, Y. Chai, W. Hang, C. Shang, W. Yang, L. Bai, J. Du, K. Wang, and Q. Wen, eLife 6, e28158 (2017).
[Crossref]

T. Nöbauer, O. Skocek, A. J. Pernía-Andrade, L. Weilguny, F. M. Traub, M. I. Molodtsov, and A. Vaziri, Nat. Methods 14, 811 (2017).
[Crossref]

2016 (1)

2014 (1)

R. Prevedel, Y. G. Yoon, M. Hoffmann, N. Pak, G. Wetzstein, S. Kato, T. Schrödel, R. Raskar, M. Zimmer, E. S. Boyden, and A. Vaziri, Nat. Methods 11, 727 (2014).
[Crossref]

2013 (2)

M. Broxton, L. Grosenick, S. Yang, N. Cohen, A. Andalman, K. Deisseroth, and M. Levoy, Opt. Express 21, 25418 (2013).
[Crossref]

T. W. Chen, T. J. Wardill, Y. Sun, S. R. Pulver, S. L. Renninger, A. Baohan, E. R. Schreiter, R. A. Kerr, M. B. Orger, V. Jayaraman, L. L. Logger, K. Svoboda, and D. S. Kim, Nature 499, 295 (2013).
[Crossref]

2011 (1)

T. V. Truong, W. Supatto, D. S. Koos, J. M. Choi, and S. E. Fraser, Nat. Methods 8, 757 (2011).
[Crossref]

2010 (1)

2008 (1)

Abdeladim, L.

Adams, A.

M. Levoy, R. Ng, A. Adams, M. Footer, and M. Horowitz, in ACM SIGGRAPH (ACM, 2006), pp. 924–934.

Adesnik, H.

Aharoni, D.

O. Skocek, T. Nöbauer, L. Weilguny, F. M. Traub, C. N. Xia, M. I. Molodtsov, A. Grama, M. Yamagata, D. Aharoni, D. D. Cox, P. Golshani, and A. Vaziri, Nat. Methods 15, 429 (2018).
[Crossref]

Aimon, S.

S. Aimon, T. Katsuki, T. Jia, L. Grosenick, M. Broxton, K. Deisseroth, T. J. Sejnowski, and R. J. Greenspan, PLoS Biol. 17, e2006732 (2019).
[Crossref]

Andalman, A.

Andreev, A.

T. V. Truong, D. B. Holland, S. Madaan, A. Andreev, K. Keomanee-Dizon, J. V. Troll, D. E. S. Koo, M. J. McFall-Ngai, and S. E. Fraser, Commun. Biol. 3, 1 (2020).
[Crossref]

Antipa, N.

Arteaga, C. L.

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

Azarova, E. V.

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

Bai, L.

L. Cong, Z. Wang, Y. Chai, W. Hang, C. Shang, W. Yang, L. Bai, J. Du, K. Wang, and Q. Wen, eLife 6, e28158 (2017).
[Crossref]

Balázs, B.

N. Wagner, N. Norlin, J. Gierten, G. de Medeiros, B. Balázs, J. Wittbrodt, L. Hufnagel, and R. Prevedel, Nat. Methods 16, 497 (2019).
[Crossref]

Baohan, A.

T. W. Chen, T. J. Wardill, Y. Sun, S. R. Pulver, S. L. Renninger, A. Baohan, E. R. Schreiter, R. A. Kerr, M. B. Orger, V. Jayaraman, L. L. Logger, K. Svoboda, and D. S. Kim, Nature 499, 295 (2013).
[Crossref]

Beaurepaire, E.

Bharadwaj, S.

V. Voleti, K. B. Patel, W. Li, C. P. Campos, S. Bharadwaj, H. Yu, C. Ford, M. J. Casper, R. W. Yan, W. Liang, C. Wen, K. D. Kimura, K. L. Targof, and E. M. C. Hillman, Nat. Methods 16, 1054 (2019).
[Crossref]

Boniface, A.

Bowlan, P.

Boyden, E. S.

R. Prevedel, Y. G. Yoon, M. Hoffmann, N. Pak, G. Wetzstein, S. Kato, T. Schrödel, R. Raskar, M. Zimmer, E. S. Boyden, and A. Vaziri, Nat. Methods 11, 727 (2014).
[Crossref]

Broadbent, D.

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

Broxton, M.

S. Aimon, T. Katsuki, T. Jia, L. Grosenick, M. Broxton, K. Deisseroth, T. J. Sejnowski, and R. J. Greenspan, PLoS Biol. 17, e2006732 (2019).
[Crossref]

M. Broxton, L. Grosenick, S. Yang, N. Cohen, A. Andalman, K. Deisseroth, and M. Levoy, Opt. Express 21, 25418 (2013).
[Crossref]

Campos, C. P.

V. Voleti, K. B. Patel, W. Li, C. P. Campos, S. Bharadwaj, H. Yu, C. Ford, M. J. Casper, R. W. Yan, W. Liang, C. Wen, K. D. Kimura, K. L. Targof, and E. M. C. Hillman, Nat. Methods 16, 1054 (2019).
[Crossref]

Carisey, A. F.

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

Casper, M. J.

V. Voleti, K. B. Patel, W. Li, C. P. Campos, S. Bharadwaj, H. Yu, C. Ford, M. J. Casper, R. W. Yan, W. Liang, C. Wen, K. D. Kimura, K. L. Targof, and E. M. C. Hillman, Nat. Methods 16, 1054 (2019).
[Crossref]

Chai, Y.

L. Cong, Z. Wang, Y. Chai, W. Hang, C. Shang, W. Yang, L. Bai, J. Du, K. Wang, and Q. Wen, eLife 6, e28158 (2017).
[Crossref]

Chang, B. J.

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

Chauhan, V.

Chen, T. W.

T. W. Chen, T. J. Wardill, Y. Sun, S. R. Pulver, S. L. Renninger, A. Baohan, E. R. Schreiter, R. A. Kerr, M. B. Orger, V. Jayaraman, L. L. Logger, K. Svoboda, and D. S. Kim, Nature 499, 295 (2013).
[Crossref]

Chen, X.

B. Yang, X. Chen, Y. Wang, S. Feng, V. Pessino, N. Stuurman, N. H. Cho, K. W. Cheng, S. J. Lord, L. Xu, D. Xie, R. D. Mullins, M. D. Leonetti, and B. Huang, Nat. Methods 16, 501 (2019).
[Crossref]

Cheng, K. W.

B. Yang, X. Chen, Y. Wang, S. Feng, V. Pessino, N. Stuurman, N. H. Cho, K. W. Cheng, S. J. Lord, L. Xu, D. Xie, R. D. Mullins, M. D. Leonetti, and B. Huang, Nat. Methods 16, 501 (2019).
[Crossref]

Cho, N. H.

B. Yang, X. Chen, Y. Wang, S. Feng, V. Pessino, N. Stuurman, N. H. Cho, K. W. Cheng, S. J. Lord, L. Xu, D. Xie, R. D. Mullins, M. D. Leonetti, and B. Huang, Nat. Methods 16, 501 (2019).
[Crossref]

Choi, J. M.

T. V. Truong, W. Supatto, D. S. Koos, J. M. Choi, and S. E. Fraser, Nat. Methods 8, 757 (2011).
[Crossref]

Cohen, J.

Cohen, N.

Cong, L.

L. Cong, Z. Wang, Y. Chai, W. Hang, C. Shang, W. Yang, L. Bai, J. Du, K. Wang, and Q. Wen, eLife 6, e28158 (2017).
[Crossref]

Cox, D. D.

O. Skocek, T. Nöbauer, L. Weilguny, F. M. Traub, C. N. Xia, M. I. Molodtsov, A. Grama, M. Yamagata, D. Aharoni, D. D. Cox, P. Golshani, and A. Vaziri, Nat. Methods 15, 429 (2018).
[Crossref]

de Medeiros, G.

N. Wagner, N. Norlin, J. Gierten, G. de Medeiros, B. Balázs, J. Wittbrodt, L. Hufnagel, and R. Prevedel, Nat. Methods 16, 497 (2019).
[Crossref]

Dean, K. M.

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

Deisseroth, K.

S. Aimon, T. Katsuki, T. Jia, L. Grosenick, M. Broxton, K. Deisseroth, T. J. Sejnowski, and R. J. Greenspan, PLoS Biol. 17, e2006732 (2019).
[Crossref]

M. Broxton, L. Grosenick, S. Yang, N. Cohen, A. Andalman, K. Deisseroth, and M. Levoy, Opt. Express 21, 25418 (2013).
[Crossref]

Doubrovinski, K.

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

Du, J.

L. Cong, Z. Wang, Y. Chai, W. Hang, C. Shang, W. Yang, L. Bai, J. Du, K. Wang, and Q. Wen, eLife 6, e28158 (2017).
[Crossref]

Dunsby, C.

Engert, F.

Q. Lin, J. Manley, M. Helmreich, F. Schlumm, J. M. Li, D. N. Robson, F. Engert, A. Schier, T. Nöbauer, and A. Vaziri, Cell 180, 536 (2020).
[Crossref]

Feng, S.

B. Yang, X. Chen, Y. Wang, S. Feng, V. Pessino, N. Stuurman, N. H. Cho, K. W. Cheng, S. J. Lord, L. Xu, D. Xie, R. D. Mullins, M. D. Leonetti, and B. Huang, Nat. Methods 16, 501 (2019).
[Crossref]

Fiolka, R. P.

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

Footer, M.

M. Levoy, R. Ng, A. Adams, M. Footer, and M. Horowitz, in ACM SIGGRAPH (ACM, 2006), pp. 924–934.

Ford, C.

V. Voleti, K. B. Patel, W. Li, C. P. Campos, S. Bharadwaj, H. Yu, C. Ford, M. J. Casper, R. W. Yan, W. Liang, C. Wen, K. D. Kimura, K. L. Targof, and E. M. C. Hillman, Nat. Methods 16, 1054 (2019).
[Crossref]

Fraser, S. E.

T. V. Truong, D. B. Holland, S. Madaan, A. Andreev, K. Keomanee-Dizon, J. V. Troll, D. E. S. Koo, M. J. McFall-Ngai, and S. E. Fraser, Commun. Biol. 3, 1 (2020).
[Crossref]

T. V. Truong, W. Supatto, D. S. Koos, J. M. Choi, and S. E. Fraser, Nat. Methods 8, 757 (2011).
[Crossref]

Gerlock, M.

Gierten, J.

N. Wagner, N. Norlin, J. Gierten, G. de Medeiros, B. Balázs, J. Wittbrodt, L. Hufnagel, and R. Prevedel, Nat. Methods 16, 497 (2019).
[Crossref]

Golshani, P.

O. Skocek, T. Nöbauer, L. Weilguny, F. M. Traub, C. N. Xia, M. I. Molodtsov, A. Grama, M. Yamagata, D. Aharoni, D. D. Cox, P. Golshani, and A. Vaziri, Nat. Methods 15, 429 (2018).
[Crossref]

Grama, A.

O. Skocek, T. Nöbauer, L. Weilguny, F. M. Traub, C. N. Xia, M. I. Molodtsov, A. Grama, M. Yamagata, D. Aharoni, D. D. Cox, P. Golshani, and A. Vaziri, Nat. Methods 15, 429 (2018).
[Crossref]

Greenspan, R. J.

S. Aimon, T. Katsuki, T. Jia, L. Grosenick, M. Broxton, K. Deisseroth, T. J. Sejnowski, and R. J. Greenspan, PLoS Biol. 17, e2006732 (2019).
[Crossref]

Grosenick, L.

S. Aimon, T. Katsuki, T. Jia, L. Grosenick, M. Broxton, K. Deisseroth, T. J. Sejnowski, and R. J. Greenspan, PLoS Biol. 17, e2006732 (2019).
[Crossref]

M. Broxton, L. Grosenick, S. Yang, N. Cohen, A. Andalman, K. Deisseroth, and M. Levoy, Opt. Express 21, 25418 (2013).
[Crossref]

Hang, W.

L. Cong, Z. Wang, Y. Chai, W. Hang, C. Shang, W. Yang, L. Bai, J. Du, K. Wang, and Q. Wen, eLife 6, e28158 (2017).
[Crossref]

Hanker, A. B.

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

Helmreich, M.

Q. Lin, J. Manley, M. Helmreich, F. Schlumm, J. M. Li, D. N. Robson, F. Engert, A. Schier, T. Nöbauer, and A. Vaziri, Cell 180, 536 (2020).
[Crossref]

Hillman, E. M. C.

V. Voleti, K. B. Patel, W. Li, C. P. Campos, S. Bharadwaj, H. Yu, C. Ford, M. J. Casper, R. W. Yan, W. Liang, C. Wen, K. D. Kimura, K. L. Targof, and E. M. C. Hillman, Nat. Methods 16, 1054 (2019).
[Crossref]

Hoffmann, M.

R. Prevedel, Y. G. Yoon, M. Hoffmann, N. Pak, G. Wetzstein, S. Kato, T. Schrödel, R. Raskar, M. Zimmer, E. S. Boyden, and A. Vaziri, Nat. Methods 11, 727 (2014).
[Crossref]

Holland, D. B.

T. V. Truong, D. B. Holland, S. Madaan, A. Andreev, K. Keomanee-Dizon, J. V. Troll, D. E. S. Koo, M. J. McFall-Ngai, and S. E. Fraser, Commun. Biol. 3, 1 (2020).
[Crossref]

Horowitz, M.

M. Levoy, R. Ng, A. Adams, M. Footer, and M. Horowitz, in ACM SIGGRAPH (ACM, 2006), pp. 924–934.

Huang, B.

B. Yang, X. Chen, Y. Wang, S. Feng, V. Pessino, N. Stuurman, N. H. Cho, K. W. Cheng, S. J. Lord, L. Xu, D. Xie, R. D. Mullins, M. D. Leonetti, and B. Huang, Nat. Methods 16, 501 (2019).
[Crossref]

Hufnagel, L.

N. Wagner, N. Norlin, J. Gierten, G. de Medeiros, B. Balázs, J. Wittbrodt, L. Hufnagel, and R. Prevedel, Nat. Methods 16, 497 (2019).
[Crossref]

Huh, J.

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

Jayaraman, V.

T. W. Chen, T. J. Wardill, Y. Sun, S. R. Pulver, S. L. Renninger, A. Baohan, E. R. Schreiter, R. A. Kerr, M. B. Orger, V. Jayaraman, L. L. Logger, K. Svoboda, and D. S. Kim, Nature 499, 295 (2013).
[Crossref]

Jia, T.

S. Aimon, T. Katsuki, T. Jia, L. Grosenick, M. Broxton, K. Deisseroth, T. J. Sejnowski, and R. J. Greenspan, PLoS Biol. 17, e2006732 (2019).
[Crossref]

Ju, R. J.

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

Kato, S.

R. Prevedel, Y. G. Yoon, M. Hoffmann, N. Pak, G. Wetzstein, S. Kato, T. Schrödel, R. Raskar, M. Zimmer, E. S. Boyden, and A. Vaziri, Nat. Methods 11, 727 (2014).
[Crossref]

Katsuki, T.

S. Aimon, T. Katsuki, T. Jia, L. Grosenick, M. Broxton, K. Deisseroth, T. J. Sejnowski, and R. J. Greenspan, PLoS Biol. 17, e2006732 (2019).
[Crossref]

Keomanee-Dizon, K.

T. V. Truong, D. B. Holland, S. Madaan, A. Andreev, K. Keomanee-Dizon, J. V. Troll, D. E. S. Koo, M. J. McFall-Ngai, and S. E. Fraser, Commun. Biol. 3, 1 (2020).
[Crossref]

Kerr, R. A.

T. W. Chen, T. J. Wardill, Y. Sun, S. R. Pulver, S. L. Renninger, A. Baohan, E. R. Schreiter, R. A. Kerr, M. B. Orger, V. Jayaraman, L. L. Logger, K. Svoboda, and D. S. Kim, Nature 499, 295 (2013).
[Crossref]

Kim, D. S.

T. W. Chen, T. J. Wardill, Y. Sun, S. R. Pulver, S. L. Renninger, A. Baohan, E. R. Schreiter, R. A. Kerr, M. B. Orger, V. Jayaraman, L. L. Logger, K. Svoboda, and D. S. Kim, Nature 499, 295 (2013).
[Crossref]

Kimura, K. D.

V. Voleti, K. B. Patel, W. Li, C. P. Campos, S. Bharadwaj, H. Yu, C. Ford, M. J. Casper, R. W. Yan, W. Liang, C. Wen, K. D. Kimura, K. L. Targof, and E. M. C. Hillman, Nat. Methods 16, 1054 (2019).
[Crossref]

Kishore, S.

Kobayashi, Y.

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

Koo, D. E. S.

T. V. Truong, D. B. Holland, S. Madaan, A. Andreev, K. Keomanee-Dizon, J. V. Troll, D. E. S. Koo, M. J. McFall-Ngai, and S. E. Fraser, Commun. Biol. 3, 1 (2020).
[Crossref]

Koos, D. S.

T. V. Truong, W. Supatto, D. S. Koos, J. M. Choi, and S. E. Fraser, Nat. Methods 8, 757 (2011).
[Crossref]

Kozorovitskiy, Y.

Kruithoff, R.

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

Kumar, M.

Lee, K. M.

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

Leonetti, M. D.

B. Yang, X. Chen, Y. Wang, S. Feng, V. Pessino, N. Stuurman, N. H. Cho, K. W. Cheng, S. J. Lord, L. Xu, D. Xie, R. D. Mullins, M. D. Leonetti, and B. Huang, Nat. Methods 16, 501 (2019).
[Crossref]

Levoy, M.

M. Broxton, L. Grosenick, S. Yang, N. Cohen, A. Andalman, K. Deisseroth, and M. Levoy, Opt. Express 21, 25418 (2013).
[Crossref]

M. Levoy, R. Ng, A. Adams, M. Footer, and M. Horowitz, in ACM SIGGRAPH (ACM, 2006), pp. 924–934.

Li, J. M.

Q. Lin, J. Manley, M. Helmreich, F. Schlumm, J. M. Li, D. N. Robson, F. Engert, A. Schier, T. Nöbauer, and A. Vaziri, Cell 180, 536 (2020).
[Crossref]

Li, W.

V. Voleti, K. B. Patel, W. Li, C. P. Campos, S. Bharadwaj, H. Yu, C. Ford, M. J. Casper, R. W. Yan, W. Liang, C. Wen, K. D. Kimura, K. L. Targof, and E. M. C. Hillman, Nat. Methods 16, 1054 (2019).
[Crossref]

Liang, W.

V. Voleti, K. B. Patel, W. Li, C. P. Campos, S. Bharadwaj, H. Yu, C. Ford, M. J. Casper, R. W. Yan, W. Liang, C. Wen, K. D. Kimura, K. L. Targof, and E. M. C. Hillman, Nat. Methods 16, 1054 (2019).
[Crossref]

Lin, Q.

Q. Lin, J. Manley, M. Helmreich, F. Schlumm, J. M. Li, D. N. Robson, F. Engert, A. Schier, T. Nöbauer, and A. Vaziri, Cell 180, 536 (2020).
[Crossref]

Liu, H. Y.

Logger, L. L.

T. W. Chen, T. J. Wardill, Y. Sun, S. R. Pulver, S. L. Renninger, A. Baohan, E. R. Schreiter, R. A. Kerr, M. B. Orger, V. Jayaraman, L. L. Logger, K. Svoboda, and D. S. Kim, Nature 499, 295 (2013).
[Crossref]

Lord, S. J.

B. Yang, X. Chen, Y. Wang, S. Feng, V. Pessino, N. Stuurman, N. H. Cho, K. W. Cheng, S. J. Lord, L. Xu, D. Xie, R. D. Mullins, M. D. Leonetti, and B. Huang, Nat. Methods 16, 501 (2019).
[Crossref]

Madaan, S.

T. V. Truong, D. B. Holland, S. Madaan, A. Andreev, K. Keomanee-Dizon, J. V. Troll, D. E. S. Koo, M. J. McFall-Ngai, and S. E. Fraser, Commun. Biol. 3, 1 (2020).
[Crossref]

Mahou, P.

Maioli, V.

Manley, J.

Q. Lin, J. Manley, M. Helmreich, F. Schlumm, J. M. Li, D. N. Robson, F. Engert, A. Schier, T. Nöbauer, and A. Vaziri, Cell 180, 536 (2020).
[Crossref]

Marín, A.

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

McFall-Ngai, M. J.

T. V. Truong, D. B. Holland, S. Madaan, A. Andreev, K. Keomanee-Dizon, J. V. Troll, D. E. S. Koo, M. J. McFall-Ngai, and S. E. Fraser, Commun. Biol. 3, 1 (2020).
[Crossref]

McLean, D. L.

Millett-Sikking, A.

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

Molodtsov, M. I.

O. Skocek, T. Nöbauer, L. Weilguny, F. M. Traub, C. N. Xia, M. I. Molodtsov, A. Grama, M. Yamagata, D. Aharoni, D. D. Cox, P. Golshani, and A. Vaziri, Nat. Methods 15, 429 (2018).
[Crossref]

T. Nöbauer, O. Skocek, A. J. Pernía-Andrade, L. Weilguny, F. M. Traub, M. I. Molodtsov, and A. Vaziri, Nat. Methods 14, 811 (2017).
[Crossref]

Mullins, R. D.

B. Yang, X. Chen, Y. Wang, S. Feng, V. Pessino, N. Stuurman, N. H. Cho, K. W. Cheng, S. J. Lord, L. Xu, D. Xie, R. D. Mullins, M. D. Leonetti, and B. Huang, Nat. Methods 16, 501 (2019).
[Crossref]

Nasenbeny, J.

Ng, R.

M. Levoy, R. Ng, A. Adams, M. Footer, and M. Horowitz, in ACM SIGGRAPH (ACM, 2006), pp. 924–934.

Nöbauer, T.

Q. Lin, J. Manley, M. Helmreich, F. Schlumm, J. M. Li, D. N. Robson, F. Engert, A. Schier, T. Nöbauer, and A. Vaziri, Cell 180, 536 (2020).
[Crossref]

O. Skocek, T. Nöbauer, L. Weilguny, F. M. Traub, C. N. Xia, M. I. Molodtsov, A. Grama, M. Yamagata, D. Aharoni, D. D. Cox, P. Golshani, and A. Vaziri, Nat. Methods 15, 429 (2018).
[Crossref]

T. Nöbauer, O. Skocek, A. J. Pernía-Andrade, L. Weilguny, F. M. Traub, M. I. Molodtsov, and A. Vaziri, Nat. Methods 14, 811 (2017).
[Crossref]

Norlin, N.

N. Wagner, N. Norlin, J. Gierten, G. de Medeiros, B. Balázs, J. Wittbrodt, L. Hufnagel, and R. Prevedel, Nat. Methods 16, 497 (2019).
[Crossref]

Orger, M. B.

T. W. Chen, T. J. Wardill, Y. Sun, S. R. Pulver, S. L. Renninger, A. Baohan, E. R. Schreiter, R. A. Kerr, M. B. Orger, V. Jayaraman, L. L. Logger, K. Svoboda, and D. S. Kim, Nature 499, 295 (2013).
[Crossref]

Ortas, J. F.

Pak, N.

R. Prevedel, Y. G. Yoon, M. Hoffmann, N. Pak, G. Wetzstein, S. Kato, T. Schrödel, R. Raskar, M. Zimmer, E. S. Boyden, and A. Vaziri, Nat. Methods 11, 727 (2014).
[Crossref]

Patel, K. B.

V. Voleti, K. B. Patel, W. Li, C. P. Campos, S. Bharadwaj, H. Yu, C. Ford, M. J. Casper, R. W. Yan, W. Liang, C. Wen, K. D. Kimura, K. L. Targof, and E. M. C. Hillman, Nat. Methods 16, 1054 (2019).
[Crossref]

Pégard, N. C.

Pernía-Andrade, A. J.

T. Nöbauer, O. Skocek, A. J. Pernía-Andrade, L. Weilguny, F. M. Traub, M. I. Molodtsov, and A. Vaziri, Nat. Methods 14, 811 (2017).
[Crossref]

Pessino, V.

B. Yang, X. Chen, Y. Wang, S. Feng, V. Pessino, N. Stuurman, N. H. Cho, K. W. Cheng, S. J. Lord, L. Xu, D. Xie, R. D. Mullins, M. D. Leonetti, and B. Huang, Nat. Methods 16, 501 (2019).
[Crossref]

Pohlkamp, T.

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

Prevedel, R.

N. Wagner, N. Norlin, J. Gierten, G. de Medeiros, B. Balázs, J. Wittbrodt, L. Hufnagel, and R. Prevedel, Nat. Methods 16, 497 (2019).
[Crossref]

R. Prevedel, Y. G. Yoon, M. Hoffmann, N. Pak, G. Wetzstein, S. Kato, T. Schrödel, R. Raskar, M. Zimmer, E. S. Boyden, and A. Vaziri, Nat. Methods 11, 727 (2014).
[Crossref]

Pulver, S. R.

T. W. Chen, T. J. Wardill, Y. Sun, S. R. Pulver, S. L. Renninger, A. Baohan, E. R. Schreiter, R. A. Kerr, M. B. Orger, V. Jayaraman, L. L. Logger, K. Svoboda, and D. S. Kim, Nature 499, 295 (2013).
[Crossref]

Raskar, R.

R. Prevedel, Y. G. Yoon, M. Hoffmann, N. Pak, G. Wetzstein, S. Kato, T. Schrödel, R. Raskar, M. Zimmer, E. S. Boyden, and A. Vaziri, Nat. Methods 11, 727 (2014).
[Crossref]

Renninger, S. L.

T. W. Chen, T. J. Wardill, Y. Sun, S. R. Pulver, S. L. Renninger, A. Baohan, E. R. Schreiter, R. A. Kerr, M. B. Orger, V. Jayaraman, L. L. Logger, K. Svoboda, and D. S. Kim, Nature 499, 295 (2013).
[Crossref]

Robson, D. N.

Q. Lin, J. Manley, M. Helmreich, F. Schlumm, J. M. Li, D. N. Robson, F. Engert, A. Schier, T. Nöbauer, and A. Vaziri, Cell 180, 536 (2020).
[Crossref]

Sapoznik, E.

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

Schier, A.

Q. Lin, J. Manley, M. Helmreich, F. Schlumm, J. M. Li, D. N. Robson, F. Engert, A. Schier, T. Nöbauer, and A. Vaziri, Cell 180, 536 (2020).
[Crossref]

Schlumm, F.

Q. Lin, J. Manley, M. Helmreich, F. Schlumm, J. M. Li, D. N. Robson, F. Engert, A. Schier, T. Nöbauer, and A. Vaziri, Cell 180, 536 (2020).
[Crossref]

Schmidt, J. C.

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

Schreiter, E. R.

T. W. Chen, T. J. Wardill, Y. Sun, S. R. Pulver, S. L. Renninger, A. Baohan, E. R. Schreiter, R. A. Kerr, M. B. Orger, V. Jayaraman, L. L. Logger, K. Svoboda, and D. S. Kim, Nature 499, 295 (2013).
[Crossref]

Schrödel, T.

R. Prevedel, Y. G. Yoon, M. Hoffmann, N. Pak, G. Wetzstein, S. Kato, T. Schrödel, R. Raskar, M. Zimmer, E. S. Boyden, and A. Vaziri, Nat. Methods 11, 727 (2014).
[Crossref]

Sejnowski, T. J.

S. Aimon, T. Katsuki, T. Jia, L. Grosenick, M. Broxton, K. Deisseroth, T. J. Sejnowski, and R. J. Greenspan, PLoS Biol. 17, e2006732 (2019).
[Crossref]

Shang, C.

L. Cong, Z. Wang, Y. Chai, W. Hang, C. Shang, W. Yang, L. Bai, J. Du, K. Wang, and Q. Wen, eLife 6, e28158 (2017).
[Crossref]

Shepherd, D. P.

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

Skocek, O.

O. Skocek, T. Nöbauer, L. Weilguny, F. M. Traub, C. N. Xia, M. I. Molodtsov, A. Grama, M. Yamagata, D. Aharoni, D. D. Cox, P. Golshani, and A. Vaziri, Nat. Methods 15, 429 (2018).
[Crossref]

T. Nöbauer, O. Skocek, A. J. Pernía-Andrade, L. Weilguny, F. M. Traub, M. I. Molodtsov, and A. Vaziri, Nat. Methods 14, 811 (2017).
[Crossref]

Stehbens, S. J.

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

Stuurman, N.

B. Yang, X. Chen, Y. Wang, S. Feng, V. Pessino, N. Stuurman, N. H. Cho, K. W. Cheng, S. J. Lord, L. Xu, D. Xie, R. D. Mullins, M. D. Leonetti, and B. Huang, Nat. Methods 16, 501 (2019).
[Crossref]

Sun, Y.

T. W. Chen, T. J. Wardill, Y. Sun, S. R. Pulver, S. L. Renninger, A. Baohan, E. R. Schreiter, R. A. Kerr, M. B. Orger, V. Jayaraman, L. L. Logger, K. Svoboda, and D. S. Kim, Nature 499, 295 (2013).
[Crossref]

Supatto, W.

Svoboda, K.

T. W. Chen, T. J. Wardill, Y. Sun, S. R. Pulver, S. L. Renninger, A. Baohan, E. R. Schreiter, R. A. Kerr, M. B. Orger, V. Jayaraman, L. L. Logger, K. Svoboda, and D. S. Kim, Nature 499, 295 (2013).
[Crossref]

Targof, K. L.

V. Voleti, K. B. Patel, W. Li, C. P. Campos, S. Bharadwaj, H. Yu, C. Ford, M. J. Casper, R. W. Yan, W. Liang, C. Wen, K. D. Kimura, K. L. Targof, and E. M. C. Hillman, Nat. Methods 16, 1054 (2019).
[Crossref]

Tata, P. R.

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

Traub, F. M.

O. Skocek, T. Nöbauer, L. Weilguny, F. M. Traub, C. N. Xia, M. I. Molodtsov, A. Grama, M. Yamagata, D. Aharoni, D. D. Cox, P. Golshani, and A. Vaziri, Nat. Methods 15, 429 (2018).
[Crossref]

T. Nöbauer, O. Skocek, A. J. Pernía-Andrade, L. Weilguny, F. M. Traub, M. I. Molodtsov, and A. Vaziri, Nat. Methods 14, 811 (2017).
[Crossref]

Trebino, R.

Troll, J. V.

T. V. Truong, D. B. Holland, S. Madaan, A. Andreev, K. Keomanee-Dizon, J. V. Troll, D. E. S. Koo, M. J. McFall-Ngai, and S. E. Fraser, Commun. Biol. 3, 1 (2020).
[Crossref]

Truong, T. V.

T. V. Truong, D. B. Holland, S. Madaan, A. Andreev, K. Keomanee-Dizon, J. V. Troll, D. E. S. Koo, M. J. McFall-Ngai, and S. E. Fraser, Commun. Biol. 3, 1 (2020).
[Crossref]

T. V. Truong, W. Supatto, D. S. Koos, J. M. Choi, and S. E. Fraser, Nat. Methods 8, 757 (2011).
[Crossref]

Vaziri, A.

Q. Lin, J. Manley, M. Helmreich, F. Schlumm, J. M. Li, D. N. Robson, F. Engert, A. Schier, T. Nöbauer, and A. Vaziri, Cell 180, 536 (2020).
[Crossref]

O. Skocek, T. Nöbauer, L. Weilguny, F. M. Traub, C. N. Xia, M. I. Molodtsov, A. Grama, M. Yamagata, D. Aharoni, D. D. Cox, P. Golshani, and A. Vaziri, Nat. Methods 15, 429 (2018).
[Crossref]

T. Nöbauer, O. Skocek, A. J. Pernía-Andrade, L. Weilguny, F. M. Traub, M. I. Molodtsov, and A. Vaziri, Nat. Methods 14, 811 (2017).
[Crossref]

R. Prevedel, Y. G. Yoon, M. Hoffmann, N. Pak, G. Wetzstein, S. Kato, T. Schrödel, R. Raskar, M. Zimmer, E. S. Boyden, and A. Vaziri, Nat. Methods 11, 727 (2014).
[Crossref]

Voleti, V.

V. Voleti, K. B. Patel, W. Li, C. P. Campos, S. Bharadwaj, H. Yu, C. Ford, M. J. Casper, R. W. Yan, W. Liang, C. Wen, K. D. Kimura, K. L. Targof, and E. M. C. Hillman, Nat. Methods 16, 1054 (2019).
[Crossref]

Wagner, N.

N. Wagner, N. Norlin, J. Gierten, G. de Medeiros, B. Balázs, J. Wittbrodt, L. Hufnagel, and R. Prevedel, Nat. Methods 16, 497 (2019).
[Crossref]

Waller, L.

Wang, K.

L. Cong, Z. Wang, Y. Chai, W. Hang, C. Shang, W. Yang, L. Bai, J. Du, K. Wang, and Q. Wen, eLife 6, e28158 (2017).
[Crossref]

Wang, Y.

B. Yang, X. Chen, Y. Wang, S. Feng, V. Pessino, N. Stuurman, N. H. Cho, K. W. Cheng, S. J. Lord, L. Xu, D. Xie, R. D. Mullins, M. D. Leonetti, and B. Huang, Nat. Methods 16, 501 (2019).
[Crossref]

Wang, Z.

L. Cong, Z. Wang, Y. Chai, W. Hang, C. Shang, W. Yang, L. Bai, J. Du, K. Wang, and Q. Wen, eLife 6, e28158 (2017).
[Crossref]

Wardill, T. J.

T. W. Chen, T. J. Wardill, Y. Sun, S. R. Pulver, S. L. Renninger, A. Baohan, E. R. Schreiter, R. A. Kerr, M. B. Orger, V. Jayaraman, L. L. Logger, K. Svoboda, and D. S. Kim, Nature 499, 295 (2013).
[Crossref]

Weilguny, L.

O. Skocek, T. Nöbauer, L. Weilguny, F. M. Traub, C. N. Xia, M. I. Molodtsov, A. Grama, M. Yamagata, D. Aharoni, D. D. Cox, P. Golshani, and A. Vaziri, Nat. Methods 15, 429 (2018).
[Crossref]

T. Nöbauer, O. Skocek, A. J. Pernía-Andrade, L. Weilguny, F. M. Traub, M. I. Molodtsov, and A. Vaziri, Nat. Methods 14, 811 (2017).
[Crossref]

Welf, E. S.

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

Wen, C.

V. Voleti, K. B. Patel, W. Li, C. P. Campos, S. Bharadwaj, H. Yu, C. Ford, M. J. Casper, R. W. Yan, W. Liang, C. Wen, K. D. Kimura, K. L. Targof, and E. M. C. Hillman, Nat. Methods 16, 1054 (2019).
[Crossref]

Wen, Q.

L. Cong, Z. Wang, Y. Chai, W. Hang, C. Shang, W. Yang, L. Bai, J. Du, K. Wang, and Q. Wen, eLife 6, e28158 (2017).
[Crossref]

Wetzstein, G.

R. Prevedel, Y. G. Yoon, M. Hoffmann, N. Pak, G. Wetzstein, S. Kato, T. Schrödel, R. Raskar, M. Zimmer, E. S. Boyden, and A. Vaziri, Nat. Methods 11, 727 (2014).
[Crossref]

Wittbrodt, J.

N. Wagner, N. Norlin, J. Gierten, G. de Medeiros, B. Balázs, J. Wittbrodt, L. Hufnagel, and R. Prevedel, Nat. Methods 16, 497 (2019).
[Crossref]

Xia, C. N.

O. Skocek, T. Nöbauer, L. Weilguny, F. M. Traub, C. N. Xia, M. I. Molodtsov, A. Grama, M. Yamagata, D. Aharoni, D. D. Cox, P. Golshani, and A. Vaziri, Nat. Methods 15, 429 (2018).
[Crossref]

Xie, D.

B. Yang, X. Chen, Y. Wang, S. Feng, V. Pessino, N. Stuurman, N. H. Cho, K. W. Cheng, S. J. Lord, L. Xu, D. Xie, R. D. Mullins, M. D. Leonetti, and B. Huang, Nat. Methods 16, 501 (2019).
[Crossref]

Xu, L.

B. Yang, X. Chen, Y. Wang, S. Feng, V. Pessino, N. Stuurman, N. H. Cho, K. W. Cheng, S. J. Lord, L. Xu, D. Xie, R. D. Mullins, M. D. Leonetti, and B. Huang, Nat. Methods 16, 501 (2019).
[Crossref]

Yamagata, M.

O. Skocek, T. Nöbauer, L. Weilguny, F. M. Traub, C. N. Xia, M. I. Molodtsov, A. Grama, M. Yamagata, D. Aharoni, D. D. Cox, P. Golshani, and A. Vaziri, Nat. Methods 15, 429 (2018).
[Crossref]

Yan, R. W.

V. Voleti, K. B. Patel, W. Li, C. P. Campos, S. Bharadwaj, H. Yu, C. Ford, M. J. Casper, R. W. Yan, W. Liang, C. Wen, K. D. Kimura, K. L. Targof, and E. M. C. Hillman, Nat. Methods 16, 1054 (2019).
[Crossref]

Yang, B.

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

B. Yang, X. Chen, Y. Wang, S. Feng, V. Pessino, N. Stuurman, N. H. Cho, K. W. Cheng, S. J. Lord, L. Xu, D. Xie, R. D. Mullins, M. D. Leonetti, and B. Huang, Nat. Methods 16, 501 (2019).
[Crossref]

Yang, S.

Yang, W.

L. Cong, Z. Wang, Y. Chai, W. Hang, C. Shang, W. Yang, L. Bai, J. Du, K. Wang, and Q. Wen, eLife 6, e28158 (2017).
[Crossref]

Yoon, Y. G.

R. Prevedel, Y. G. Yoon, M. Hoffmann, N. Pak, G. Wetzstein, S. Kato, T. Schrödel, R. Raskar, M. Zimmer, E. S. Boyden, and A. Vaziri, Nat. Methods 11, 727 (2014).
[Crossref]

York, A. G.

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

Yu, H.

V. Voleti, K. B. Patel, W. Li, C. P. Campos, S. Bharadwaj, H. Yu, C. Ford, M. J. Casper, R. W. Yan, W. Liang, C. Wen, K. D. Kimura, K. L. Targof, and E. M. C. Hillman, Nat. Methods 16, 1054 (2019).
[Crossref]

Zimmer, M.

R. Prevedel, Y. G. Yoon, M. Hoffmann, N. Pak, G. Wetzstein, S. Kato, T. Schrödel, R. Raskar, M. Zimmer, E. S. Boyden, and A. Vaziri, Nat. Methods 11, 727 (2014).
[Crossref]

Biomed. Opt. Express (1)

Cell (1)

Q. Lin, J. Manley, M. Helmreich, F. Schlumm, J. M. Li, D. N. Robson, F. Engert, A. Schier, T. Nöbauer, and A. Vaziri, Cell 180, 536 (2020).
[Crossref]

Commun. Biol. (1)

T. V. Truong, D. B. Holland, S. Madaan, A. Andreev, K. Keomanee-Dizon, J. V. Troll, D. E. S. Koo, M. J. McFall-Ngai, and S. E. Fraser, Commun. Biol. 3, 1 (2020).
[Crossref]

eLife (2)

L. Cong, Z. Wang, Y. Chai, W. Hang, C. Shang, W. Yang, L. Bai, J. Du, K. Wang, and Q. Wen, eLife 6, e28158 (2017).
[Crossref]

E. Sapoznik, B. J. Chang, J. Huh, R. J. Ju, E. V. Azarova, T. Pohlkamp, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K. M. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, Y. Kobayashi, P. R. Tata, R. Kruithoff, K. Doubrovinski, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, eLife 9, e57681 (2020).
[Crossref]

J. Opt. Soc. Am. B (1)

Nat. Methods (7)

R. Prevedel, Y. G. Yoon, M. Hoffmann, N. Pak, G. Wetzstein, S. Kato, T. Schrödel, R. Raskar, M. Zimmer, E. S. Boyden, and A. Vaziri, Nat. Methods 11, 727 (2014).
[Crossref]

T. Nöbauer, O. Skocek, A. J. Pernía-Andrade, L. Weilguny, F. M. Traub, M. I. Molodtsov, and A. Vaziri, Nat. Methods 14, 811 (2017).
[Crossref]

O. Skocek, T. Nöbauer, L. Weilguny, F. M. Traub, C. N. Xia, M. I. Molodtsov, A. Grama, M. Yamagata, D. Aharoni, D. D. Cox, P. Golshani, and A. Vaziri, Nat. Methods 15, 429 (2018).
[Crossref]

N. Wagner, N. Norlin, J. Gierten, G. de Medeiros, B. Balázs, J. Wittbrodt, L. Hufnagel, and R. Prevedel, Nat. Methods 16, 497 (2019).
[Crossref]

T. V. Truong, W. Supatto, D. S. Koos, J. M. Choi, and S. E. Fraser, Nat. Methods 8, 757 (2011).
[Crossref]

V. Voleti, K. B. Patel, W. Li, C. P. Campos, S. Bharadwaj, H. Yu, C. Ford, M. J. Casper, R. W. Yan, W. Liang, C. Wen, K. D. Kimura, K. L. Targof, and E. M. C. Hillman, Nat. Methods 16, 1054 (2019).
[Crossref]

B. Yang, X. Chen, Y. Wang, S. Feng, V. Pessino, N. Stuurman, N. H. Cho, K. W. Cheng, S. J. Lord, L. Xu, D. Xie, R. D. Mullins, M. D. Leonetti, and B. Huang, Nat. Methods 16, 501 (2019).
[Crossref]

Nature (1)

T. W. Chen, T. J. Wardill, Y. Sun, S. R. Pulver, S. L. Renninger, A. Baohan, E. R. Schreiter, R. A. Kerr, M. B. Orger, V. Jayaraman, L. L. Logger, K. Svoboda, and D. S. Kim, Nature 499, 295 (2013).
[Crossref]

Opt. Express (3)

Optica (1)

PLoS Biol. (1)

S. Aimon, T. Katsuki, T. Jia, L. Grosenick, M. Broxton, K. Deisseroth, T. J. Sejnowski, and R. J. Greenspan, PLoS Biol. 17, e2006732 (2019).
[Crossref]

Other (1)

M. Levoy, R. Ng, A. Adams, M. Footer, and M. Horowitz, in ACM SIGGRAPH (ACM, 2006), pp. 924–934.

Supplementary Material (5)

NameDescription
» Supplement 1       Supplementary material
» Visualization 1       Fluorescence light-field (left) and 3D reconstructed maximum-intensity projections along the indicated directions (right) of a time-lapse recording of brain-wide neural activity in a 5-dpf transgenic zebrafish.
» Visualization 2       Maximum-intensity projections of nine 5-dpf zebrafish, with fluorescent labels in both the blood cells [Tg(gata1:dsRed)] and endocardium [Tg(kdrl:eGFP)], represented in magenta and grayscale, respectively.
» Visualization 3       1P-ASO-SVIM imaging of blood cells [Tg(gata1:dsRed)] flowing across the entire brain of a 5-dpf zebrafish. Cellular resolution imaging was performed over a 670- by 470- by 200-µm volume at ~50 Hz.
» Visualization 4       Volumetric view of whole-brain blood flow, with red blood cell tracks color-coded in time. Same dataset as presented in Visualization 3.

Data Availability

Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

Cited By

OSA participates in Crossref's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (3)

Fig. 1.
Fig. 1. ASO-SVIM. (A), simplified schematic of LFM. Fluorescence light is collected from the sample volume by an objective lens, separated and filtered from the excitation light by the appropriate dichroic mirror and bandpass filter, and focused by a tube lens at an intermediate image plane where a lenslet array is positioned. The lenslet array refocuses the light onto a camera, so that each position in the 3D sample volume is mapped onto the camera as a unique light intensity pattern. The fluorescence light-field illustrated was captured with point sources located at, above, and below the native focal plane. Such light fields can be reconstructed to full volumes by solving the inverse problem. (B), LFM with conventional wide-field illumination is compatible with standard forms of sample preparation but excites regions outside the VOI. (C), SVIM selectively illuminates the VOI using orthogonal illumination and detection objectives. (D) and (E), ASO-SVIM preferentially excites the VOI and collects the fluorescence using a single-objective lens, providing flexibility in sample mounting similar to traditional microscopy. (D), 1P-ASO-SVIM uses an oblique light sheet, which is scanned in 1D, to define the excitation volume. (E), 2P-ASO-SVIM uses nonlinear excitation of a pulsed near-infrared (NIR) beam that is raster-scanned to define the VOI. In images (A)–(D), 1P excitation is depicted in cyan and, in image (E), 2P excitation is depicted in red; fluorescence emission is depicted in green. See also Supplement 1, Section 1, and Figs. S1–S2.
Fig. 2.
Fig. 2. ASO-SVIM improves the contrast and effective resolution in live imaging of zebrafish larvae. (A), top, average-intensity projections (AIPs) of a 100 µm thick 3D image stack from the same transgenic [Tg(kdrl:GFP)] five-day post fertilization (dpf) zebrafish, where the vasculature was fluorescently labeled with green fluorescent protein (GFP), captured by different imaging modalities. Inset: transmitted light image of the zebrafish head, where the dashed red rectangle marks the ${{230}}\;\unicode{x00B5}{\rm m} \times {{600}}\;\unicode{x00B5}{\rm m} \times {{100}}\;\unicode{x00B5} {{\rm{m}}^3}$ volume imaged. (Bottom) cross-sectional ($x {-} z$) views at the location indicated by the dashed yellow line (top left, SPIM panel). The SPIM volume consists of 67 optical sections (exposure time, 355 ms; excitation power at sample, 0.15 mW), collected serially over ${\sim}{{44}}\;{\rm{s}}$; the LFM-based volumes were reconstructed from a single image with an exposure of 355 ms (excitation power, 2P-ASO-SVIM: 525 mW; 1P-ASO-SVIM: 1.5 mW; wide-field LFM: 4 mW). Scale bar, 100 µm. (B), quantification of image contrast versus $z$-depth, showing improvements of 1P-ASO-SVIM and 2 P-ASO-SVIM over wide-field LFM. The image contrast is plotted for each $x {-} y$ slice, normalized by the value of SPIM (blue trace) at $z = - {{50}}\;\unicode{x00B5}{\rm m}$. (C), intensity profiles along the same line for all four modalities (dashed yellow line shown on the $x {-} z$ cut in A; bottom, SPIM). The fluorescence intensities of ASO-SVIM agree more closely with the ground-truth SPIM data than does wide-field LFM. (D), FTs of $x {-} y$ MIPs through the 100 µm thick slabs in (A). The resolution bands (white circles) help show the increased spatial frequency content of ASO-SVIM compared to wide-field LFM, where more signal intensity at larger radial position designates higher resolution captured. (E), average amplitudes along ${k_y}$ direction of the FTs shown in (D), showing that ASO-SVIM frequency spectra fall slower to the experimental noise floor, indicating better effective resolution than wide-field LFM. See also Supplement 1, Fig. S7. (F), enlarged $x {-} y$ slices to highlight single blood vessels, centered at ${\sim}{{86}}\;\unicode{x00B5}{\rm m}$ into the specimen, from the subregion indicated by the dashed yellow box in [(A), top left]. (G), intensity profiles, averaged from the dashed yellow line shown in (F) and from two other similar vessels (Supplement 1, Fig. S8), demonstrate the improvements in effective resolution of ASO-SVIM over wide-field LFM.
Fig. 3.
Fig. 3. ASO-SVIM enhances large-scale in vivo recording of neural activity in a ${{320}}\;\unicode{x00B5}{\rm m} \times {{350}}\;\unicode{x00B5}{\rm m} \times \;{{100}}\;\unicode{x00B5} {{\rm{m}}^3}$ volume in larval zebrafish, at 5-dpf, Tg(elavl3:H2b-GCaMP6s). The volumetric rate of 1 Hz sufficiently captured the transient neuronal dynamics, given the relatively slow temporal kinetics of the nuclear-localized calcium indicator GCaMP6s [13]. Excitation power, 2 P-ASO-SVIM, 525 mW; 1 P-ASO-SVIM, 0.4 mW; wide-field LFM, 0.5 mW. (A), MIPs of $x {-} y$ (top) and $x {-} z$ (bottom) brain-wide 100 µm thick volumes of the same zebrafish. These projections depict the standard deviation over a 25 s period for each voxel, highlighting active neurons. Scale bar, 100 µm. See Visualization 1. (B), quantification of the image contrast versus $z$-depth, showing progressive improvements of 1P-ASO-SVIM and 2P-ASO-SVIM over wide-field LFM. The means (center lines) and standard deviations (shadings) are shown. (C), single-neuron signal traces captured by the different modalities, extracted from the 4D datasets shown in (A).