Abstract

Understanding the mechanisms of perception, cognition, and behavior requires instruments that are capable of recording and controlling the electrical activity of many neurons simultaneously and at high speeds. All-optical approaches are particularly promising since they are minimally invasive and potentially scalable to experiments interrogating thousands or millions of neurons. Conventional light-field microscopy provides a single-shot 3D fluorescence capture method with good light efficiency and fast speed, but suffers from low spatial resolution and significant image degradation due to scattering in deep layers of brain tissue. Here, we propose a new compressive light-field microscopy method to address both problems, offering a path toward measurement of individual neuron activity across large volumes of tissue. The technique relies on spatial and temporal sparsity of fluorescence signals, allowing one to identify and localize each neuron in a 3D volume, with scattering and aberration effects naturally included and without ever reconstructing a volume image. Experimental results on live zebrafish track the activity of an estimated 800+ neural structures at 100 Hz sampling rate.

© 2016 Optical Society of America

Full Article  |  PDF Article
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References

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2016 (1)

E. Pnevmatikakis, D. Soudry, Y. Gao, T. A. Machado, J. Merel, D. Pfau, T. Reardon, Y. Mu, C. Lacefield, W. Yang, M. Ahrens, R. Bruno, T. M. Jessell, D. Peterka, R. Yuste, and L. Paninski, “Simultaneous denoising, deconvolution, and demixing of calcium imaging data,” Neuron 89, 285–299 (2016).
[Crossref]

2015 (4)

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).

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).

C. K. Kim, A. Miri, L. C. Leung, A. Berndt, P. Mourrain, D. W. Tank, and R. D. Burdine, “Prolonged, brain-wide expression of nuclear-localized gcamp3 for functional circuit mapping,” Front. Neural Circuits 8, 00138 (2014).

2013 (4)

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).

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).

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).

A. Bègue, E. Papagiakoumou, B. Leshem, R. Conti, L. Enke, D. Oron, and V. Emiliani, “Two-photon excitation in scattering media by spatiotemporally shaped beams and their application in optogenetic stimulation,” Biomed. Opt. Express 4, 2869–2879 (2013).

2012 (3)

G. Katona, G. Szalay, P. Maak, A. Kaszas, M. Veress, D. Hillier, B. Chiovini, E. S. Vizi, B. Roska, and B. Rozsa, “Fast two-photon in vivo imaging with three-dimensional random-access scanning in large tissue volumes,” Nat. Methods 9, 201–208 (2012).

E. Baumgart and U. Kubitscheck, “Scanned light sheet microscopy with confocal slit detection,” Opt. Express 20, 21805–21814 (2012).

L. Waller, G. Situ, and J. W. Fleischer, “Phase-space measurement and coherence synthesis of optical beams,” Nat. Photonics 6, 474–479 (2012).

2010 (1)

H. Meyer, V. Wimmer, M. Oberlaender, C. De Kock, B. Sakmann, and M. Helmstaedter, “Number and laminar distribution of neurons in a thalamocortical projection column of rat vibrissal cortex,” Cereb. Cortex 20, 2277–2286 (2010).

2009 (1)

S. A. Vavasis, “On the complexity of nonnegative matrix factorization,” SIAM J. Optim. 20, 1364–1377 (2009).

2008 (1)

P. Keller, A. Schmidt, J. Wittbrodt, and E. Stelzer, “Reconstruction of zebrafish early embryonic development by scanned light sheet microscopy,” Science 322, 1065–1069 (2008).
[Crossref]

2007 (1)

H. Kim, “Sparse non-negative matrix factorizations via alternating non-negativity-constrained least squares for microarray data analysis,” Bioinformatics 23, 1495–1502 (2007).
[Crossref]

2006 (1)

M. Levoy, R. Ng, A. Adams, M. Footer, and M. Horowitz, “Light field microscopy,” ACM Trans. Graph. 25, 924–934 (2006).
[Crossref]

2003 (1)

C. Petersen, A. Grinvald, and B. Sakmann, “Spatiotemporal dynamics of sensory responses in layer 2/3 of rat barrel cortex measured in vivo by voltage-sensitive dye imaging combined with whole-cell voltage recordings and neuron reconstructions,” J. Neurosci. 23, 1298–1309 (2003).

1994 (1)

R. Tibshirani, “Regression shrinkage and selection via the lasso,” J. R. Stat. Soc. Ser. B 58, 267–288 (1994).

1990 (1)

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

1951 (1)

M. Lax, “Multiple scattering of waves,” Rev. Mod. Phys. 23, 287–310 (1951).
[Crossref]

Adams, A.

M. Levoy, R. Ng, A. Adams, M. Footer, and M. Horowitz, “Light field microscopy,” ACM Trans. Graph. 25, 924–934 (2006).
[Crossref]

M. Levoy, R. Ng, A. Adams, M. Footer, and M. Horowitz, “Light field microscopy,” in ACM SIGGRAPH 2006 Papers, Boston, Massachusetts (ACM, 2006), pp. 924–934.

Ahrens, M.

E. Pnevmatikakis, D. Soudry, Y. Gao, T. A. Machado, J. Merel, D. Pfau, T. Reardon, Y. Mu, C. Lacefield, W. Yang, M. Ahrens, R. Bruno, T. M. Jessell, D. Peterka, R. Yuste, and L. Paninski, “Simultaneous denoising, deconvolution, and demixing of calcium imaging data,” Neuron 89, 285–299 (2016).
[Crossref]

Allen, W. E.

Andalman, A.

Andalman, A. S.

Aumayr, K.

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).

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, “Ultrasensitive fluorescent proteins for imaging neuronal activity,” Nature 499, 295–300 (2013).

Baumgart, E.

Bègue, A.

Berndt, A.

C. K. Kim, A. Miri, L. C. Leung, A. Berndt, P. Mourrain, D. W. Tank, and R. D. Burdine, “Prolonged, brain-wide expression of nuclear-localized gcamp3 for functional circuit mapping,” Front. Neural Circuits 8, 00138 (2014).

Bouchard, M. B.

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

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

Broxton, M.

Bruno, R.

E. Pnevmatikakis, D. Soudry, Y. Gao, T. A. Machado, J. Merel, D. Pfau, T. Reardon, Y. Mu, C. Lacefield, W. Yang, M. Ahrens, R. Bruno, T. M. Jessell, D. Peterka, R. Yuste, and L. Paninski, “Simultaneous denoising, deconvolution, and demixing of calcium imaging data,” Neuron 89, 285–299 (2016).
[Crossref]

Bruno, R. M.

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

Burdine, R. D.

C. K. Kim, A. Miri, L. C. Leung, A. Berndt, P. Mourrain, D. W. Tank, and R. D. Burdine, “Prolonged, brain-wide expression of nuclear-localized gcamp3 for functional circuit mapping,” Front. Neural Circuits 8, 00138 (2014).

Carroll, E.

C. S. Oldfield, A. R. Huth, M. Chavez, E. Carroll, A. Prendergast, T. Qu, A. Hoagland, C. Wyart, and E. Y. Isacoff, University of California, Berkeley, Berkeley, CA 94720 and CNRS-UMR-7225, 75005 Paris, France, are preparing a paper to be called “Experience shapes hunting behavior by increasing the impact of information transfer from visual to motor areas.”

Chavez, M.

C. S. Oldfield, A. R. Huth, M. Chavez, E. Carroll, A. Prendergast, T. Qu, A. Hoagland, C. Wyart, and E. Y. Isacoff, University of California, Berkeley, Berkeley, CA 94720 and CNRS-UMR-7225, 75005 Paris, France, are preparing a paper to be called “Experience shapes hunting behavior by increasing the impact of information transfer from visual to motor areas.”

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, “Ultrasensitive fluorescent proteins for imaging neuronal activity,” Nature 499, 295–300 (2013).

Chiovini, B.

G. Katona, G. Szalay, P. Maak, A. Kaszas, M. Veress, D. Hillier, B. Chiovini, E. S. Vizi, B. Roska, and B. Rozsa, “Fast two-photon in vivo imaging with three-dimensional random-access scanning in large tissue volumes,” Nat. Methods 9, 201–208 (2012).

Cohen, N.

Conti, R.

De Kock, C.

H. Meyer, V. Wimmer, M. Oberlaender, C. De Kock, B. Sakmann, and M. Helmstaedter, “Number and laminar distribution of neurons in a thalamocortical projection column of rat vibrissal cortex,” Cereb. Cortex 20, 2277–2286 (2010).

Deisseroth, K.

Denk, W.

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

Emiliani, V.

Enke, L.

Fleischer, J.

C.-H. Lu, S. Muenzel, and J. Fleischer, “High-resolution light-field microscopy,” in Computational Optical Sensing and Imaging, OSA Technical Digest (online) (Optical Society of America, 2013), paper CTh3B.2.

Fleischer, J. W.

L. Waller, G. Situ, and J. W. Fleischer, “Phase-space measurement and coherence synthesis of optical beams,” Nat. Photonics 6, 474–479 (2012).

Footer, M.

M. Levoy, R. Ng, A. Adams, M. Footer, and M. Horowitz, “Light field microscopy,” ACM Trans. Graph. 25, 924–934 (2006).
[Crossref]

M. Levoy, R. Ng, A. Adams, M. Footer, and M. Horowitz, “Light field microscopy,” in ACM SIGGRAPH 2006 Papers, Boston, Massachusetts (ACM, 2006), pp. 924–934.

Gao, Y.

E. Pnevmatikakis, D. Soudry, Y. Gao, T. A. Machado, J. Merel, D. Pfau, T. Reardon, Y. Mu, C. Lacefield, W. Yang, M. Ahrens, R. Bruno, T. M. Jessell, D. Peterka, R. Yuste, and L. Paninski, “Simultaneous denoising, deconvolution, and demixing of calcium imaging data,” Neuron 89, 285–299 (2016).
[Crossref]

Grinvald, A.

C. Petersen, A. Grinvald, and B. Sakmann, “Spatiotemporal dynamics of sensory responses in layer 2/3 of rat barrel cortex measured in vivo by voltage-sensitive dye imaging combined with whole-cell voltage recordings and neuron reconstructions,” J. Neurosci. 23, 1298–1309 (2003).

Grosenick, L.

Grueber, W. B.

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

Hanrahan, P.

M. Levoy and P. Hanrahan, “Light field rendering,” in Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques, New York (ACM, 1996), pp. 31–42.

Helmstaedter, M.

H. Meyer, V. Wimmer, M. Oberlaender, C. De Kock, B. Sakmann, and M. Helmstaedter, “Number and laminar distribution of neurons in a thalamocortical projection column of rat vibrissal cortex,” Cereb. Cortex 20, 2277–2286 (2010).

Hillier, D.

G. Katona, G. Szalay, P. Maak, A. Kaszas, M. Veress, D. Hillier, B. Chiovini, E. S. Vizi, B. Roska, and B. Rozsa, “Fast two-photon in vivo imaging with three-dimensional random-access scanning in large tissue volumes,” Nat. Methods 9, 201–208 (2012).

Hillman, E. M.

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

Hoagland, A.

C. S. Oldfield, A. R. Huth, M. Chavez, E. Carroll, A. Prendergast, T. Qu, A. Hoagland, C. Wyart, and E. Y. Isacoff, University of California, Berkeley, Berkeley, CA 94720 and CNRS-UMR-7225, 75005 Paris, France, are preparing a paper to be called “Experience shapes hunting behavior by increasing the impact of information transfer from visual to motor areas.”

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

Horowitz, M.

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).

M. Levoy, R. Ng, A. Adams, M. Footer, and M. Horowitz, “Light field microscopy,” ACM Trans. Graph. 25, 924–934 (2006).
[Crossref]

M. Levoy, R. Ng, A. Adams, M. Footer, and M. Horowitz, “Light field microscopy,” in ACM SIGGRAPH 2006 Papers, Boston, Massachusetts (ACM, 2006), pp. 924–934.

Huth, A. R.

C. S. Oldfield, A. R. Huth, M. Chavez, E. Carroll, A. Prendergast, T. Qu, A. Hoagland, C. Wyart, and E. Y. Isacoff, University of California, Berkeley, Berkeley, CA 94720 and CNRS-UMR-7225, 75005 Paris, France, are preparing a paper to be called “Experience shapes hunting behavior by increasing the impact of information transfer from visual to motor areas.”

Isacoff, E. Y.

C. S. Oldfield, A. R. Huth, M. Chavez, E. Carroll, A. Prendergast, T. Qu, A. Hoagland, C. Wyart, and E. Y. Isacoff, University of California, Berkeley, Berkeley, CA 94720 and CNRS-UMR-7225, 75005 Paris, France, are preparing a paper to be called “Experience shapes hunting behavior by increasing the impact of information transfer from visual to motor areas.”

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, “Ultrasensitive fluorescent proteins for imaging neuronal activity,” Nature 499, 295–300 (2013).

Jessell, T. M.

E. Pnevmatikakis, D. Soudry, Y. Gao, T. A. Machado, J. Merel, D. Pfau, T. Reardon, Y. Mu, C. Lacefield, W. Yang, M. Ahrens, R. Bruno, T. M. Jessell, D. Peterka, R. Yuste, and L. Paninski, “Simultaneous denoising, deconvolution, and demixing of calcium imaging data,” Neuron 89, 285–299 (2016).
[Crossref]

Jonas, E.

Kaszas, A.

G. Katona, G. Szalay, P. Maak, A. Kaszas, M. Veress, D. Hillier, B. Chiovini, E. S. Vizi, B. Roska, and B. Rozsa, “Fast two-photon in vivo imaging with three-dimensional random-access scanning in large tissue volumes,” Nat. Methods 9, 201–208 (2012).

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

Katona, G.

G. Katona, G. Szalay, P. Maak, A. Kaszas, M. Veress, D. Hillier, B. Chiovini, E. S. Vizi, B. Roska, and B. Rozsa, “Fast two-photon in vivo imaging with three-dimensional random-access scanning in large tissue volumes,” Nat. Methods 9, 201–208 (2012).

Kauvar, I.

Keller, P.

P. Keller, A. Schmidt, J. Wittbrodt, and E. Stelzer, “Reconstruction of zebrafish early embryonic development by scanned light sheet microscopy,” Science 322, 1065–1069 (2008).
[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, “Ultrasensitive fluorescent proteins for imaging neuronal activity,” Nature 499, 295–300 (2013).

Kim, C. K.

S. J. Yang, W. E. Allen, I. Kauvar, A. S. Andalman, N. P. Young, C. K. Kim, J. H. Marshel, G. Wetzstein, and K. Deisseroth, “Extended field-of-view and increased-signal 3D holographic illumination with time-division multiplexing,” Opt. Express 23, 32573–32581 (2015).

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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).

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C. K. Kim, A. Miri, L. C. Leung, A. Berndt, P. Mourrain, D. W. Tank, and R. D. Burdine, “Prolonged, brain-wide expression of nuclear-localized gcamp3 for functional circuit mapping,” Front. Neural Circuits 8, 00138 (2014).

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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).

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G. Katona, G. Szalay, P. Maak, A. Kaszas, M. Veress, D. Hillier, B. Chiovini, E. S. Vizi, B. Roska, and B. Rozsa, “Fast two-photon in vivo imaging with three-dimensional random-access scanning in large tissue volumes,” Nat. Methods 9, 201–208 (2012).

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E. Pnevmatikakis, D. Soudry, Y. Gao, T. A. Machado, J. Merel, D. Pfau, T. Reardon, Y. Mu, C. Lacefield, W. Yang, M. Ahrens, R. Bruno, T. M. Jessell, D. Peterka, R. Yuste, and L. Paninski, “Simultaneous denoising, deconvolution, and demixing of calcium imaging data,” Neuron 89, 285–299 (2016).
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E. Pnevmatikakis, D. Soudry, Y. Gao, T. A. Machado, J. Merel, D. Pfau, T. Reardon, Y. Mu, C. Lacefield, W. Yang, M. Ahrens, R. Bruno, T. M. Jessell, D. Peterka, R. Yuste, and L. Paninski, “Simultaneous denoising, deconvolution, and demixing of calcium imaging data,” Neuron 89, 285–299 (2016).
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C. K. Kim, A. Miri, L. C. Leung, A. Berndt, P. Mourrain, D. W. Tank, and R. D. Burdine, “Prolonged, brain-wide expression of nuclear-localized gcamp3 for functional circuit mapping,” Front. Neural Circuits 8, 00138 (2014).

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E. Pnevmatikakis, D. Soudry, Y. Gao, T. A. Machado, J. Merel, D. Pfau, T. Reardon, Y. Mu, C. Lacefield, W. Yang, M. Ahrens, R. Bruno, T. M. Jessell, D. Peterka, R. Yuste, and L. Paninski, “Simultaneous denoising, deconvolution, and demixing of calcium imaging data,” Neuron 89, 285–299 (2016).
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H. Meyer, V. Wimmer, M. Oberlaender, C. De Kock, B. Sakmann, and M. Helmstaedter, “Number and laminar distribution of neurons in a thalamocortical projection column of rat vibrissal cortex,” Cereb. Cortex 20, 2277–2286 (2010).

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C. S. Oldfield, A. R. Huth, M. Chavez, E. Carroll, A. Prendergast, T. Qu, A. Hoagland, C. Wyart, and E. Y. Isacoff, University of California, Berkeley, Berkeley, CA 94720 and CNRS-UMR-7225, 75005 Paris, France, are preparing a paper to be called “Experience shapes hunting behavior by increasing the impact of information transfer from visual to motor areas.”

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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).

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

Paninski, L.

E. Pnevmatikakis, D. Soudry, Y. Gao, T. A. Machado, J. Merel, D. Pfau, T. Reardon, Y. Mu, C. Lacefield, W. Yang, M. Ahrens, R. Bruno, T. M. Jessell, D. Peterka, R. Yuste, and L. Paninski, “Simultaneous denoising, deconvolution, and demixing of calcium imaging data,” Neuron 89, 285–299 (2016).
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Peterka, D.

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E. Pnevmatikakis, D. Soudry, Y. Gao, T. A. Machado, J. Merel, D. Pfau, T. Reardon, Y. Mu, C. Lacefield, W. Yang, M. Ahrens, R. Bruno, T. M. Jessell, D. Peterka, R. Yuste, and L. Paninski, “Simultaneous denoising, deconvolution, and demixing of calcium imaging data,” Neuron 89, 285–299 (2016).
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E. Pnevmatikakis, D. Soudry, Y. Gao, T. A. Machado, J. Merel, D. Pfau, T. Reardon, Y. Mu, C. Lacefield, W. Yang, M. Ahrens, R. Bruno, T. M. Jessell, D. Peterka, R. Yuste, and L. Paninski, “Simultaneous denoising, deconvolution, and demixing of calcium imaging data,” Neuron 89, 285–299 (2016).
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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).

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).

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C. S. Oldfield, A. R. Huth, M. Chavez, E. Carroll, A. Prendergast, T. Qu, A. Hoagland, C. Wyart, and E. Y. Isacoff, University of California, Berkeley, Berkeley, CA 94720 and CNRS-UMR-7225, 75005 Paris, France, are preparing a paper to be called “Experience shapes hunting behavior by increasing the impact of information transfer from visual to motor areas.”

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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).

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E. Pnevmatikakis, D. Soudry, Y. Gao, T. A. Machado, J. Merel, D. Pfau, T. Reardon, Y. Mu, C. Lacefield, W. Yang, M. Ahrens, R. Bruno, T. M. Jessell, D. Peterka, R. Yuste, and L. Paninski, “Simultaneous denoising, deconvolution, and demixing of calcium imaging data,” Neuron 89, 285–299 (2016).
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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).

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G. Katona, G. Szalay, P. Maak, A. Kaszas, M. Veress, D. Hillier, B. Chiovini, E. S. Vizi, B. Roska, and B. Rozsa, “Fast two-photon in vivo imaging with three-dimensional random-access scanning in large tissue volumes,” Nat. Methods 9, 201–208 (2012).

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G. Katona, G. Szalay, P. Maak, A. Kaszas, M. Veress, D. Hillier, B. Chiovini, E. S. Vizi, B. Roska, and B. Rozsa, “Fast two-photon in vivo imaging with three-dimensional random-access scanning in large tissue volumes,” Nat. Methods 9, 201–208 (2012).

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H. Meyer, V. Wimmer, M. Oberlaender, C. De Kock, B. Sakmann, and M. Helmstaedter, “Number and laminar distribution of neurons in a thalamocortical projection column of rat vibrissal cortex,” Cereb. Cortex 20, 2277–2286 (2010).

C. Petersen, A. Grinvald, and B. Sakmann, “Spatiotemporal dynamics of sensory responses in layer 2/3 of rat barrel cortex measured in vivo by voltage-sensitive dye imaging combined with whole-cell voltage recordings and neuron reconstructions,” J. Neurosci. 23, 1298–1309 (2003).

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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).

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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).

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).

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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, “Ultrasensitive fluorescent proteins for imaging neuronal activity,” Nature 499, 295–300 (2013).

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G. Katona, G. Szalay, P. Maak, A. Kaszas, M. Veress, D. Hillier, B. Chiovini, E. S. Vizi, B. Roska, and B. Rozsa, “Fast two-photon in vivo imaging with three-dimensional random-access scanning in large tissue volumes,” Nat. Methods 9, 201–208 (2012).

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C. K. Kim, A. Miri, L. C. Leung, A. Berndt, P. Mourrain, D. W. Tank, and R. D. Burdine, “Prolonged, brain-wide expression of nuclear-localized gcamp3 for functional circuit mapping,” Front. Neural Circuits 8, 00138 (2014).

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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).

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G. Katona, G. Szalay, P. Maak, A. Kaszas, M. Veress, D. Hillier, B. Chiovini, E. S. Vizi, B. Roska, and B. Rozsa, “Fast two-photon in vivo imaging with three-dimensional random-access scanning in large tissue volumes,” Nat. Methods 9, 201–208 (2012).

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

Waller, L.

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, “Ultrasensitive fluorescent proteins for imaging neuronal activity,” Nature 499, 295–300 (2013).

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S. J. Yang, W. E. Allen, I. Kauvar, A. S. Andalman, N. P. Young, C. K. Kim, J. H. Marshel, G. Wetzstein, and K. Deisseroth, “Extended field-of-view and increased-signal 3D holographic illumination with time-division multiplexing,” Opt. Express 23, 32573–32581 (2015).

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).

Wimmer, V.

H. Meyer, V. Wimmer, M. Oberlaender, C. De Kock, B. Sakmann, and M. Helmstaedter, “Number and laminar distribution of neurons in a thalamocortical projection column of rat vibrissal cortex,” Cereb. Cortex 20, 2277–2286 (2010).

Wittbrodt, J.

P. Keller, A. Schmidt, J. Wittbrodt, and E. Stelzer, “Reconstruction of zebrafish early embryonic development by scanned light sheet microscopy,” Science 322, 1065–1069 (2008).
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Wyart, C.

C. S. Oldfield, A. R. Huth, M. Chavez, E. Carroll, A. Prendergast, T. Qu, A. Hoagland, C. Wyart, and E. Y. Isacoff, University of California, Berkeley, Berkeley, CA 94720 and CNRS-UMR-7225, 75005 Paris, France, are preparing a paper to be called “Experience shapes hunting behavior by increasing the impact of information transfer from visual to motor areas.”

Yang, S.

Yang, S. J.

Yang, W.

E. Pnevmatikakis, D. Soudry, Y. Gao, T. A. Machado, J. Merel, D. Pfau, T. Reardon, Y. Mu, C. Lacefield, W. Yang, M. Ahrens, R. Bruno, T. M. Jessell, D. Peterka, R. Yuste, and L. Paninski, “Simultaneous denoising, deconvolution, and demixing of calcium imaging data,” Neuron 89, 285–299 (2016).
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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).

Young, N. P.

Yuste, R.

E. Pnevmatikakis, D. Soudry, Y. Gao, T. A. Machado, J. Merel, D. Pfau, T. Reardon, Y. Mu, C. Lacefield, W. Yang, M. Ahrens, R. Bruno, T. M. Jessell, D. Peterka, R. Yuste, and L. Paninski, “Simultaneous denoising, deconvolution, and demixing of calcium imaging data,” Neuron 89, 285–299 (2016).
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Zhong, J.

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

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).

ACM Trans. Graph. (1)

M. Levoy, R. Ng, A. Adams, M. Footer, and M. Horowitz, “Light field microscopy,” ACM Trans. Graph. 25, 924–934 (2006).
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Bioinformatics (1)

H. Kim, “Sparse non-negative matrix factorizations via alternating non-negativity-constrained least squares for microarray data analysis,” Bioinformatics 23, 1495–1502 (2007).
[Crossref]

Biomed. Opt. Express (1)

Cereb. Cortex (1)

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Supplementary Material (6)

NameDescription
» Supplement 1: PDF (4319 KB)      Supplemental document
» Visualization 1: MP4 (2038 KB)      Light-field refocusing.
» Visualization 2: MP4 (5817 KB)      Threshold-based detection.
» Visualization 3: MP4 (6942 KB)      Independent component extraction guarantees sparse spatial components.
» Visualization 4: MP4 (18244 KB)      Video reconstruction of the 3D activity.
» Visualization 5: MP4 (12298 KB)      When the zebrafish returns to rest, the dictionary becomes valid again (residual error drops).

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Figures (6)

Fig. 1.
Fig. 1.

Experimental setup and post-processing steps for samples tagged with engineered fluorescent proteins to track brain activity. A fluorescence microscope is fitted with a microlens array for light-field data acquisition. A training video of sparse frames is acquired or computed by ICA. (Step 1) Training: light-field measurements are processed to separate and identify individual calcium sources (neural structures) by their 3D position. The extracted “light-field signature” represents the measurement (including scattering and aberrations) that would be made if only that corresponding neural structure was active. (Step 2) Subsequent data frames are decomposed as a linear positive combination of the light-field signatures in the dictionary. The coefficients of this decomposition represent a quantitative measure of calcium-induced fluorescence in each identified neuron.

Fig. 2.
Fig. 2.

Extracting light-field signatures and 3D positions of individual neural structures. (a) One of the 40 sparse light-field components. (b) Light-field slice along the red dashed line. Each distinct structure prescribes a line in the space-angle plot, whose position and tilt indicates lateral position and depth, respectively. Individual neural structures are distinguished and localized—shown here as different colors. (c) Overlay of extracted light-field signatures for multiple neural structures, each with a different color. (d) Estimated 3D positions for each of the neurons in this component.

Fig. 3.
Fig. 3.

Single-shot experimental detection and 3D localization of sparsely distributed fluorescent beads, with and without scattering, as compared to two-photon microscopy scanned images. (a) Single-shot light-field measurement and several space-angle slices (along the red lines) without scattering. (b) Dataset recorded after placing a 100 μm slice of wild-type mouse brain tissue directly above the beads so as to introduce realistic scattering conditions without displacing the volume of interest. (c) 2D intensity images become blurred by scattering. (d) and (e) Comparison of localization capabilities for two-photon and our light-field microscopy, with and without scattering. (d) Estimated source positions are projected onto the x , y plane for visualization and (e) shown in 3D.

Fig. 4.
Fig. 4.

Neural activity tracking in the telencephalon of a five-day-old live zebrafish restrained in agarose. (a) Light-field signatures were extracted for 802 neural structures and 10 s of spontaneous activity was recorded at 100 Hz. (b) The normalized change of fluorescence, d F / F , is displayed for each neuron as a function of time. Motion is quantified by digitally tracking the first moment of the 2D image, with visible motion artifacts at t = 1.9    s , t = 4.9    s , and t = 9    s . (c) For each identified neuron, the position in 3D space is estimated, with color showing time-averaged fluorescence activity across both telencephalic lobes of the fore-brain.

Fig. 5.
Fig. 5.

(a) Modified experimental setup for spatial resolution measurements. Slices of mouse brain tissue with varying thickness are placed above an artificial source (created by a second microscope objective) that is intended to mimic the fluorescence in an active neuron. The artificial source can be precisely positioned at any location in 3D space. Comparison of distinguishability for light-field data versus 2D fluorescence data. Measurements for two source positions are displayed simultaneously with red and green color maps, for separation (b) in the ( x , y ) plane and (c) along the z axis. (d) Distinguishability of the two captured images as a function of separation distance between two sources. Light-field measurements outperform 2D fluorescence in the lateral plane and (e) along the optical axis. (f) We use our algorithm to estimate the position of the source through a 300 μm slice for controlled source displacements along the ( y ) axis in strong scattering.

Fig. 6.
Fig. 6.

Spatial resolution analysis for our method, according to the minimal distance between two sources required for correct identification as separate neurons (a) in the lateral ( x , y ) plane and (b) along the optical axis through a given depth of mouse brain tissue. Fluorescence microscopy (green) and light-field microscopy (blue) are compared on the same scale and show a tenfold difference in performance along all axes. (c) Estimated maximum resolvable neuron density as a function of depth in mouse brain tissue, as compared to typical neuron density observed in the mouse barrel cortex.

Equations (16)

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I ( u , t ) = j = 1 N I j ( u ) a j ( t ) ,
min c > 0 ( r i I ( u , t ) I ^ ( u , t ) 2 + μ r i c ( r i , t ) ) ,
I ^ ( u , t ) = r i I ^ i ( u , t ) = r i c ( r i , t ) A ( r i , u x , u y ) ,
A ( r i , u x , u y ) = z 0 2 π z i 2 e z 0 2 z i 2 ( ( x i x ) 2 + ( y i y ) 2 + z i 2 ( θ x 2 + θ y 2 ) ) ,
I j ( u ) = 1 a j ( t ) I ^ j ( u , t ) I ^ ( u , t ) I ( u , t ) , with    a j ( t ) = I ^ j ( u , t ) I ^ ( u , t ) I ( u , t ) d u .
I j ( u ) d u = 1 , and j = 1 N I j ( u ) a j ( t ) = I ( u , t ) .
I ( u , t ) = n = 1 N k I ( n ) ( u ) f n ( t ) ,
I = ST ,
S i , k = I ( k ) ( u ( i ) ) ,
T k , j = f k ( j δ t ) .
min S i , k > 0 , T k , j > 0 ( I ST 2 + λ 1 k , j | T k , j | ) ,
min a 1 a n > 0 I ( u , t ) j = 1 N a j I j ( u ) 2 .
( d F F 0 ) i ( t ) = a i ( t ) ( 1 / T ) t = 0 T a i ( t ) d t 1 ,
N V δ x δ y δ z .
D ( I 1 , I 2 ) = 1 I 1 ( u ) I 2 ( u ) d u I 1 2 ( u ) d u I 2 2 ( u ) d u .
D ( I 1 , I 2 ) > 1 SNR .

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