Abstract

A major challenge in neuroscience is to sample large-scale neuronal activity at high speed and resolution. While calcium (Ca2+) imaging allows high-resolution optical read-out of neuronal activity, it remains challenging to sample large-scale activity at high speed, as most available imaging microscopes provide a trade-off between speed and the size of the acquisition volume. One promising method that avoids the trade-off between the acquisition rate and volume size is light-field microscopy in which the full 3D profile of an object is imaged simultaneously, thereby offering high speed at the cost of reduced spatial resolution. Here we introduce speckle light-field microscopy (speckle LFM), which utilizes speckle-based structured illumination to enhance spatial resolution. Using speckle LFM we demonstrate brain-wide recording of neuronal activity in larval zebrafish at 10 Hz volume rate and at 1.4 times higher resolution compared to conventional light-field microscopy and with suppressed background fluorescence. In addition to improving resolution of spatial structure, we show that the increased resolution reduces spurious signal crosstalk between neighboring neurons.

© 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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2017 (6)

A. Song, A. S. Charles, S. A. Koay, J. L. Gauthier, S. Y. Thiberge, J. W. Pillow, and D. W. Tank, “Volumetric two-photon imaging of neurons using stereoscopy (vTwINS),” Nat. Methods 14, 420–426 (2017).
[Crossref]

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[Crossref]

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[Crossref]

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[Crossref]

L. H. Yeh, L. Tian, and L. Waller, “Structured illumination microscopy with unknown patterns and a statistical prior,” Biomed. Opt. Express 8, 695–711 (2017).
[Crossref]

T. W. Murray, M. Haltmeier, T. Berer, E. Leiss-Holzinger, and P. Burgholzer, “Super-resolution photoacoustic microscopy using blind structured illumination,” Optica 4, 17–22 (2017).
[Crossref]

2016 (7)

K. D. Harris, R. Q. Quiroga, J. Freeman, and S. L. Smith, “Improving data quality in neuronal population recordings,” Nat. Neurosci. 19, 1165–1174 (2016).
[Crossref]

T. Chaigne, J. Gateau, M. Allain, O. Katz, S. Gigan, A. Sentenac, and E. Bossy, “Super-resolution photoacoustic fluctuation imaging with multiple speckle illumination,” Optica 3, 54–57 (2016).
[Crossref]

M. A. Taylor and W. P. Bowen, “Quantum metrology and its application in biology,” Phys. Rep. 615, 1–59 (2016).
[Crossref]

N. C. Pégard, H. Y. Liu, N. Antipa, M. Gerlock, H. Adesnik, and L. Waller, “Compressive light-field microscopy for 3D neural activity recording,” Optica 3, 517–524 (2016).
[Crossref]

B. Hajj, M. El Beheiry, and M. Dahan, “PSF engineering in multifocus microscopy for increased depth volumetric imaging,” Biomed. Opt. Express 7, 726–731 (2016).
[Crossref]

R. Prevedel, A. J. Verhoef, A. J. Pernía-Andrade, S. Weisenburger, B. S. Huang, T. Nöbauer, A. Fernández, J. E. Delcour, P. Golshani, A. Baltuska, and A. Vaziri, “Fast volumetric calcium imaging across multiple cortical layers using sculpted light,” Nat. Methods 13, 1021–1028 (2016).
[Crossref]

W. Yang, J. K. Miller, L. Carrillo-Reid, E. Pnevmatikakis, L. Paninski, R. Yuste, and D. S. Peterka, “Simultaneous multi-plane imaging of neural circuits,” Neuron 89, 269–284 (2016).
[Crossref]

2015 (5)

R. Yuste, “From the neuron doctrine to neural networks,” Nat. Rev. Neurosci. 16, 487–497 (2015).
[Crossref]

R. Tomer, M. Lovett-Barron, I. Kauvar, A. Andalman, V. M. Burns, S. Sankaran, L. Grosenick, M. Broxton, S. Yang, and K. Deisseroth, “SPED light sheet microscopy: fast mapping of biological system structure and function,” Cell 163, 1796–1806 (2015).
[Crossref]

O. E. Olarte, J. Andilla, D. Artigas, and P. Loza-Alvarez, “Decoupled illumination detection in light sheet microscopy for fast volumetric imaging,” Optica 2, 702–705 (2015).
[Crossref]

M. B. Bouchard, V. Voleti, C. S. Mendes, C. Lacefield, W. B. Grueber, R. S. Mann, R. M. Bruno, and E. M. C. Hillman, “Swept confocally-aligned planar excitation (SCAPE) microscopy for high-speed volumetric imaging of behaving organisms,” Nat. Photonics 9, 113–119 (2015).
[Crossref]

M. A. Taylor, M. Waleed, A. B. Stilgoe, H. Rubinsztein-Dunlop, and W. P. Bowen, “Enhanced optical trapping via structured scattering,” Nat. Photonics 9, 669–673 (2015).
[Crossref]

2014 (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, “Simultaneous whole-animal 3D imaging of neuronal activity using light-field microscopy,” Nat. Methods 11, 727–730 (2014).
[Crossref]

G. Thériault, M. Cottet, A. Castonguay, N. McCarthy, and Y. De Koninck, “Extended two-photon microscopy in live samples with Bessel beams: steadier focus, faster volume scans, and simpler stereoscopic imaging,” Front. Cell. Neurosci. 8, 139 (2014).
[Crossref]

N. Cohen, S. Yang, A. Andalman, M. Broxton, L. Grosenick, K. Deisseroth, M. Horowitz, and M. Levoy, “Enhancing the performance of the light field microscope using wavefront coding,” Opt. Express 22, 24817–24839 (2014).
[Crossref]

2013 (8)

M. Broxton, L. Grosenick, S. Yang, N. Cohen, A. Andalman, K. Deisseroth, and M. Levoy, “Wave optics theory and 3-D deconvolution for the light field microscope,” Opt. Express 21, 25418–25439 (2013).
[Crossref]

S. Abrahamsson, J. Chen, B. Hajj, S. Stallinga, A. Y. Katsov, J. Wisniewski, G. Mizuguchi, P. Soule, F. Mueller, C. D. Darzacq, X. Darzacq, C. Wu, C. I. Bargmann, D. A. Agard, M. Dahan, and M. G. L. Gustafsson, “Fast multicolor 3D imaging using aberration-corrected multifocus microscopy,” Nat. Methods 10, 60–63 (2013).
[Crossref]

S. Quirin, D. S. Peterka, and R. Yuste, “Instantaneous three-dimensional sensing using spatial light modulator illumination with extended depth of field imaging,” Opt. Express 21, 16007–16021 (2013).
[Crossref]

T. Schrödel, R. Prevedel, K. Aumayr, M. Zimmer, and A. Vaziri, “Brain-wide 3D imaging of neuronal activity in Caenorhabditis elegans with sculpted light,” Nat. Methods 10, 1013–1020 (2013).
[Crossref]

M. B. Ahrens, M. B. Orger, D. N. Robson, J. M. Li, and P. J. Keller, “Whole-brain functional imaging at cellular resolution using light-sheet microscopy,” Nat. Methods 10, 413–420 (2013).
[Crossref]

T. Panier, S. Romano, R. Olive, T. Pietri, G. Sumbre, R. Candelier, and G. Debrégeas, “Fast functional imaging of multiple brain regions in intact zebrafish larvae using selective plane illumination microscopy,” Front. Neural Circuits 7, 65 (2013).
[Crossref]

F. O. Fahrbach, F. F. Voigt, B. Schmid, F. Helmchen, and J. Huisken, “Rapid 3D light-sheet microscopy with a tunable lens,” Opt. Express 21, 21010–21026 (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, “Ultrasensitive fluorescent proteins for imaging neuronal activity,” Nature 499, 295–300 (2013).
[Crossref]

2012 (3)

J. Akerboom, T.-W. Chen, T. J. Wardill, L. Tian, J. S. Marvin, S. Mutlu, N. C. Calderón, F. Esposti, B. G. Borghuis, X. R. Sun, A. Gordus, M. B. Orger, R. Portugues, F. Engert, J. J. Macklin, A. Filosa, A. Aggarwal, R. A. Kerr, R. Takagi, S. Kracun, E. Shigetomi, B. S. Khakh, H. Baier, L. Lagnado, S. S.-H. Wang, C. I. Bargmann, B. E. Kimmel, V. Jayaraman, K. L. Svoboda, D. S. Kim, E. R. Schreiter, and L. L. Looger, “Optimization of a GCaMP calcium indicator for neural activity imaging,” J. Neurosci. 32, 13819–13840 (2012).
[Crossref]

E. Mudry, K. Belkebir, J. Girard, J. Savatier, E. Le Moal, C. Nicoletti, M. Allain, and A. Sentenac, “Structured illumination microscopy using unknown speckle patterns,” Nat. Photonics 6, 312–315 (2012).
[Crossref]

A. G. York, S. H. Parekh, D. D. Nogare, R. S. Fischer, K. Temprine, M. Mione, A. B. Chitnis, C. A. Combs, and H. Shroff, “Resolution doubling in live, multicellular organisms via multifocal structured illumination microscopy,” Nat. Methods 9, 749–754 (2012).
[Crossref]

2011 (1)

A. Cheng, J. T. Gonçalves, P. Golshani, K. Arisaka, and C. Portera-Cailliau, “Simultaneous two-photon calcium imaging at different depths with spatiotemporal multiplexing,” Nat. Methods 8, 139–142 (2011).
[Crossref]

2009 (3)

T. Dertinger, R. Colyer, G. Iyer, S. Weiss, and J. Enderlein, “Fast, background-free, 3D super-resolution optical fluctuation imaging (SOFI),” Proc. Natl. Acad. Sci. USA 106, 22287–22292 (2009).
[Crossref]

M. Levoy, Z. Zhang, and I. McDowall, “Recording and controlling the 4D light field in a microscope using microlens arrays,” J. Microsc. 235, 144–162 (2009).
[Crossref]

J. W. Tay, M. A. Taylor, and W. P. Bowen, “Sagnac-interferometer-based characterization of spatial light modulators,” Appl. Opt. 48, 2236–2242 (2009).
[Crossref]

2008 (3)

M. G. L. Gustafsson, L. Shao, P. M. Carlton, C. R. Wang, I. N. Golubovskaya, W. Z. Cande, D. A. Agard, and J. W. Sedat, “Three-dimensional resolution doubling in wide-field fluorescence microscopy by structured illumination,” Biophys. J. 94, 4957–4970 (2008).
[Crossref]

A. Gatti, D. Magatti, and F. Ferri, “Three-dimensional coherence of light speckles: theory,” Phys. Rev. A 78, 063806 (2008).
[Crossref]

G. D. Reddy, K. Kelleher, R. Fink, and P. Saggau, “Three-dimensional random access multiphoton microscopy for functional imaging of neuronal activity,” Nat. Neurosci. 11, 713–720 (2008).
[Crossref]

2006 (2)

M. Levoy, R. Ng, A. Adams, M. Footer, and M. Horowitz, “Light field microscopy,” ACM Trans. Graph. 25, 924 (2006).
[Crossref]

S. Shoham, D. H. O’Connor, and R. Segev, “How silent is the brain: is there a “dark matter” problem in neuroscience?” J. Comp. Physiol. A 192, 777–784 (2006).
[Crossref]

2005 (2)

2004 (1)

J. Huisken, J. Swoger, F. Del Bene, J. Wittbrodt, and E. H. Stelzer, “Optical sectioning deep inside live embryos by selective plane illumination microscopy,” Science 305, 1007–1009 (2004).
[Crossref]

2000 (1)

M. G. Gustafsson, “Surpassing the lateral resolution limit by a factor of two using structured illumination microscopy,” J. Microsc. 198, 82–87 (2000).
[Crossref]

1999 (1)

R. Heintzmann and C. Cremer, “Laterally modulated excitation microscopy: improvement of resolution by using a diffraction grating,” Proc. SPIE 3568, 185–196 (1999).
[Crossref]

1990 (1)

W. Denk, J. H. Strickler, and W. W. Webb, “Two-photon laser scanning fluorescence microscopy,” Science 248, 73–76 (1990).
[Crossref]

Abrahamsson, S.

S. Abrahamsson, J. Chen, B. Hajj, S. Stallinga, A. Y. Katsov, J. Wisniewski, G. Mizuguchi, P. Soule, F. Mueller, C. D. Darzacq, X. Darzacq, C. Wu, C. I. Bargmann, D. A. Agard, M. Dahan, and M. G. L. Gustafsson, “Fast multicolor 3D imaging using aberration-corrected multifocus microscopy,” Nat. Methods 10, 60–63 (2013).
[Crossref]

Adams, A.

M. Levoy, R. Ng, A. Adams, M. Footer, and M. Horowitz, “Light field microscopy,” ACM Trans. Graph. 25, 924 (2006).
[Crossref]

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Figures (5)

Fig. 1.
Fig. 1. Speckle light-field microscopy. (a) Experimental schematic. The LFM is constructed with a microlens array placed in the primary image plane of the fluorescence microscope, which then projects onto the chip of a sCMOS camera via a 1:1 image relay (not shown). Controlled speckle illumination is introduced by imaging an SLM with a random phase mask onto the objective back-focal plane. (b) In speckle LFM, the fluorescent objects (grey disks) are illuminated with a sequence of independent speckle patterns (blue), and the resulting fluorescence is recorded. (c) The workflow of speckle and linear LFM, with example data from closely spaced fluorescent beads. The light-field images are extracted by taking the (i) variance and (ii) mean of the recorded data, for speckle and linear LFM, respectively. The use of variance offers sharper points and lower background. The source volume is then reconstructed using the PSF squared in speckle LFM (iii), or (iv) the PSF in linear LFM (see Section 2). In this example, the beads are resolved with speckle LFM but unresolved with linear LFM. (v) The square root of the speckle LFM reconstruction is then taken to renormalize it to a linear scaling with source brightness. Renormalization is not needed for linear LFM. Scale bars 2 μm.
Fig. 2.
Fig. 2. Monte Carlo simulation of speckle LFM detection statistics. (a) An example showing how the signal is calculated for speckle imaging; pseudo-random speckle illumination (blue) is incident on fluorophores for which the brightness can vary. (b) The resulting fluorescence (green) is the product of the fluorophore brightness and illumination. As the fluorophore brightness increases, both the mean and variance of the recorded signal increase. (c) and (d) We compare two configurations, one in which the sample is illuminated by a completely random sequence of speckle patterns, and another with a repeating pattern of 10 pseudo-random speckle patterns. We see that both (c) in the absence of shot noise, and (d) with shot noise included, the repeating pattern (blue) leads to a signal closely representing the ground truth (dashed line), while random fluctuations in the illumination introduce severe noise when using completely random speckle (light green). (e) The dependence of SNR on the mean number of photons included in each reconstruction. When using random speckle (light green), the random illumination statistics dominate the noise and preclude any improvement from increasing the intensity. A repeating pattern, however, improves consistently with photon number as expected for a shot-noise-limited measurement (blue). (f) Trade-off between SNR and reconstruction frame rate. The volume imaging rate can be increased by calculating the variance with smaller bin size, but at cost of SNR. If the intensity is fixed (blue), there is a dramatic loss of SNR with increasing image rate. Even if the illumination is increased to maintain fixed photon number in each bin (orange dashed), increasing the frame rate leads to diminishing SNR.
Fig. 3.
Fig. 3. Brain-wide recording of neural activity in larval zebrafish. (a) 3D projection of the standard deviation in time of the recorded movie, which thus highlights the active neurons. (b) and (c) Zoom-in on a single slice at z=12  μm above the focal plane. The speckle LFM reconstruction (b) shows sharper features and more resolvable spots than the similar linear LFM data (c). (d) Brain-wide activity recorded using speckle LFM in this fish. The activity is mostly spontaneous, though increased activity is visible around 270–278 s, following a tail movement. (e) Two example ROIs from the areas indicated in (b) and (c) were selected, and their activity plotted in (f). The dynamics recorded with speckle LFM (blue) closely agrees with the linear LFM (orange) at most times. However, some transients that are observed on both ROIs with linear LFM are observed only on ROI 2 (i, ii, iv) or ROI 1 (iii) with speckle LFM. This is due to the lower spatial resolution of linear LFM partially mixing the signals. Scale bars in (a) 50 μm, (b, c) 10 μm, (e) 4 μm.
Fig. 4.
Fig. 4. Quantification of resolution from pairwise mutual information. (a) Pairwise mutual information of ROIs as a function of lateral separation. Data is shown for two axial slices, with solid and dashed lines 24 and 84 μm above the focus, respectively. In all cases the mutual information is highest for closely spaced ROIs which cannot be completely resolved and plateaus at large separation. We define the onset of crosstalk to be the separation at which the average mutual information increases by 0.4 bits (dotted line), which provides a quantitative measure of the achievable resolution in vivo. (b) Estimated resolution in vivo. The resolution estimated from mutual information (points) is compared to the theoretically predicted resolution of the LFM (lines). Speckle LFM surpasses the resolution of linear LFM at all depths. The arrows indicate the data points extracted from the example data shown in (a). At some depths (36  μm, 24  μm, and 12 μm) crosstalk was not statistically observable using speckle LFM; these data points are therefore omitted. The spike of poor resolution at z=0 is known as the artifact plane and is a well-known feature of the conventional LFM deconvolution method [25,27].
Fig. 5.
Fig. 5. Speckle LFM imaging of neural activity in a mouse. 3D volumes imaged with (a)–(c) speckle LFM and (d)–(f) linear LFM, with example planes shown at (a) and (d) 80 μm, (b) and (e) 120 μm, and (c) and (f) 170 μm depth below the brain surface. This data includes a strong fluorescent background which is effectively suppressed in the speckle LFM data, allowing individual cells to be resolved which cannot be clearly distinguished from background with linear LFM. (g) Time traces from 10 example ROIs as indicated in (a)–(f). Solid lines: speckle LFM, dotted lines: linear LFM. Similar to results from fish, speckle LFM suppresses background and thereby increases the amplitude of ΔF/F. Scale bars 50 μm.

Equations (6)

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A(R)=μ(r)I(r)H(R,r)dr,
A(R)=I(r)μ(r)H(R,r)dr,
Var(A(R))=A2A2=C(r1,r2)μ(r1)μ(r2)H(R,r1)H(R,r2)dr1dr2,
C(r1,r2)=I(r1)I(r2)I(r1)I(r2),
C(r1,r2)I(r1)2  δ(r1r2),
Var(A(R))I(r)2μ2(r)H2(R,r)dr.

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