Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Depth-resolved fiber photometry with a single tapered optical fiber implant

Abstract

Fiber photometry is increasingly utilized to monitor fluorescent sensors of neural activity in the brain. However, most implementations are based on flat-cleaved optical fibers that can only interface with shallow tissue volumes adjacent to the fiber. We exploit modal properties of tapered optical fibers (TFs) to enable light collection over an extent of up to 2 mm of tissue and multisite photometry along the taper. Using a single TF, we simultaneously observed distinct dopamine transients in dorsal and ventral striatum in freely moving mice performing a simple, operant conditioning task. Collection volumes from TFs can also be engineered in both shape and size by microstructuring the nonplanar surface of the taper, to optically target multiple sites not only in the deep brain but, in general, in any biological system or organ in which light collection is beneficial but challenging because of light scattering and absorption.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Light collection from TFs.
Fig. 2: Reconfigurable light collection with TFs.
Fig. 3: Enhanced photometry from genetically stained neural populations.
Fig. 4: In vivo multipoint photometry reveals distinct dopamine responses to locomotion and reward in dorsal and ventral striatum.
Fig. 5: Engineering the light collection volume with microstructured TFs.
Fig. 6: Detection schemes exploiting far-field imaging for depth-resolved fiber photometry.

Similar content being viewed by others

Data availability

Data are available upon reasonable request from the corresponding authors. Data on optical properties of TFs and optical measurements are available from F. Pisano, M.P., M.D.V. and F. Pisanello. Data on in vivo use of tapered fibers are available from B.L.S.

Code availability

Custom code is available upon reasonable request to the corresponding authors. Custom code was used to: (i) extract the ring diameter from far-field measurements and report it in terms of kt in the graph in Fig. 1g; (ii) extract the photometry efficiency field ρ(x,y) from the collection ξ(x,y) and the normalized illumination β(x,y) fields; (iii) control the optical system to compare TF and FF collection in Fig. 3d,e; (iv) perform the in vivo experiments and elaborate the related dataset (Fig. 4 and Supplementary Fig. 6); (v) estimate light collection volumes from optical windows realized along the taper; (vi) to control the optical system to switch light emission and collection between W1 and W2 in Fig. 5m,n; (vii) 3D collection fields (Supplementary Figs. 1 and 7); (viii) perform the geometrical optics-based simulations of light collection with TFs reported in Supplementary Fig. 2; (ix) perform the quantitative estimation of the spatial distribution of the collected signal in Supplementary Fig. 3; (x) evaluate the contribution to integrated signal in Supplementary Fig. 4; (xi) control and extract data for the experiments on the evaluation of modal-mixing influence on the fluorescence signal collected by TFs (Supplementary Fig. 5).

References

  1. Peterka, D. S., Takahashi, H. & Yuste, R. Imaging voltage in neurons. Neuron 69, 9–21 (2011).

    Article  CAS  Google Scholar 

  2. Luo, L., Callaway, E. M. & Svoboda, K. Genetic dissection of neural circuits: a decade of progress. Neuron 98, 256–281 (2018).

    Article  CAS  Google Scholar 

  3. Stroh, A. et al. Making waves: initiation and propagation of corticothalamic Ca2+ waves in vivo. Neuron 77, 1136–1150 (2013).

    Article  CAS  Google Scholar 

  4. Schwalm, M. et al. Cortex-wide BOLD fMRI activity reflects locally-recorded slow oscillation-associated calcium waves. eLife 6, e27602 (2017).

    Article  Google Scholar 

  5. Adelsberger, H., Grienberger, C., Stroh, A. & Konnerth, A. In vivo calcium recordings and channelrhodopsin-2 activation through an optical fiber. Cold Spring Harb. Protoc. 2014, pdb.prot084145 (2014).

    Article  Google Scholar 

  6. Fuhrmann, F. et al. Locomotion, theta oscillations, and the speed-correlated firing of hippocampal neurons are controlled by a medial septal glutamatergic circuit. Neuron 86, 1253–1264 (2015).

    Article  CAS  Google Scholar 

  7. Simone, K., Füzesi, T., Rosenegger, D., Bains, J. & Murari, K. Open-source, cost-effective system for low-light in vivo fiber photometry. Neurophotonics 5, 025006 (2018).

    Article  Google Scholar 

  8. Muir, J. et al. In vivo fiber photometry reveals signature of future stress susceptibility in nucleus accumbens. Neuropsychopharmacology 43, 255–263 (2018).

    Article  CAS  Google Scholar 

  9. Adelsberger, H., Zainos, A., Alvarez, M., Romo, R. & Konnerth, A. Local domains of motor cortical activity revealed by fiber-optic calcium recordings in behaving nonhuman primates. Proc. Natl Acad. Sci. USA 111, 463–468 (2014).

    Article  CAS  Google Scholar 

  10. Lu, L. et al. Wireless optoelectronic photometers for monitoring neuronal dynamics in the deep brain. Proc. Natl Acad. Sci. USA 115, E1374–E1383 (2018).

    Article  CAS  Google Scholar 

  11. Meng, C. et al. Spectrally Resolved fiber photometry for multi-component analysis of brain circuits. Neuron 98, 707–717.e4 (2018).

    Article  CAS  Google Scholar 

  12. Cui, G. et al. Concurrent activation of striatal direct and indirect pathways during action initiation. Nature 494, 238–242 (2013).

    Article  CAS  Google Scholar 

  13. Markowitz, J. E. et al. The striatum organizes 3D behavior via moment-to-moment action selection. Cell 174, 44–58 (2018).

    Article  CAS  Google Scholar 

  14. Kim, C. K. et al. Simultaneous fast measurement of circuit dynamics at multiple sites across the mammalian brain. Nat. Methods 13, 325–328 (2016).

    Article  Google Scholar 

  15. Gunaydin, L. A. et al. Natural neural projection dynamics underlying social behavior. Cell 157, 1535–1551 (2014).

    Article  CAS  Google Scholar 

  16. Schmid, F. et al. Assessing sensory versus optogenetic network activation by combining (o)fMRI with optical Ca2+ recordings. J. Cereb. Blood Flow. Metab. 36, 1885–1900 (2016).

    Article  CAS  Google Scholar 

  17. Lütcke, H. et al. Optical recording of neuronal activity with a genetically-encoded calcium indicator in anesthetized and freely moving mice. Front. Neural Circuits 4, 9 (2010).

    PubMed  PubMed Central  Google Scholar 

  18. Guo, Q. et al. Multi-channel fiber photometry for population neuronal activity recording. Biomed. Opt. Express 6, 3919 (2015).

    Article  CAS  Google Scholar 

  19. Cui, G. et al. Deep brain optical measurements of cell type–specific neural activity in behaving mice. Nat. Protoc. 9, 1213–1228 (2014).

    Article  CAS  Google Scholar 

  20. Tai, D. C. S., Hooks, D. A., Harvey, J. D., Smaill, B. H. & Soeller, C. Illumination and fluorescence collection volumes for fiber optic probes in tissue. J. Biomed. Opt. 12, 034033 (2007).

    Article  Google Scholar 

  21. Pisanello, M. et al. The three-dimensional signal collection field for fiber photometry in brain tissue. Front. Neurosci. 13, 82 (2019).

    Article  Google Scholar 

  22. Pisanello, F. et al. Dynamic illumination of spatially restricted or large brain volumes via a single tapered optical fiber. Nat. Neurosci. 20, 1180–1188 (2017).

    Article  CAS  Google Scholar 

  23. Park, S. et al. One-step optogenetics with multifunctional flexible polymer fibers. Nat. Neurosci. 20, 612–619 (2017).

    Article  CAS  Google Scholar 

  24. Acker, L., Pino, E. N., Boyden, E. S. & Desimone, R. FEF inactivation with improved optogenetic methods. Proc. Natl Acad. Sci. USA 113, E7297 (2016).

    Article  CAS  Google Scholar 

  25. Pisanello, F. et al. Multipoint-emitting optical fibers for spatially addressable in vivo optogenetics. Neuron 82, 1245–1254 (2014).

    Article  CAS  Google Scholar 

  26. Pisano, F. et al. Focused ion beam nanomachining of tapered optical fibers for patterned light delivery.Microelectron. Eng. 195, 41–49 (2018).

    Article  CAS  Google Scholar 

  27. Pisanello, M. et al. Tailoring light delivery for optogenetics by modal demultiplexing in tapered optical fibers. Sci. Rep. 8, 4467 (2018).

    Article  Google Scholar 

  28. Pisanello, M. et al. Modal demultiplexing properties of tapered and nanostructured optical fibers for in vivo optogenetic control of neural activity. Biomed. Opt. Express 6, 4014 (2015).

    Article  CAS  Google Scholar 

  29. Klaus, A. et al. The spatiotemporal organization of the striatum encodes action space. Neuron 95, 1171–1180 (2017).

    Article  CAS  Google Scholar 

  30. Patriarchi, T. et al. Ultrafast neuronal imaging of dopamine dynamics with designed genetically encoded sensors. Science 360, 1420 (2018).

    Article  CAS  Google Scholar 

  31. Howe, M. W. & Dombeck, D. A. Rapid signalling in distinct dopaminergic axons during locomotion and reward. Nature 535, 505–510 (2016).

    Article  CAS  Google Scholar 

  32. Coddington, L. T. & Dudman, J. T. Emergence of reward expectation signals in identified dopamine neurons. Nat. Neurosci. 21, 1563–1573 (2018).

    Article  CAS  Google Scholar 

  33. da Silva, J. A., Tecuapetla, F., Paixão, V. & Costa, R. M. Dopamine neuron activity before action initiation gates and invigorates future movements. Nature 554, 244–248 (2018).

    Article  Google Scholar 

  34. Rizzo, A. et al. Laser micromachining of tapered optical fibers for spatially selective control of neural activity. Microelectron. Eng. 192, 88–95 (2018).

    Article  CAS  Google Scholar 

  35. Tanese, D. et al. Imaging membrane potential changes from dendritic spines using computer-generated holography. Neurophotonics 4, 031211 (2017).

    Article  Google Scholar 

  36. Wang, T. et al. Three-photon imaging of mouse brain structure and function through the intact skull. Nat. Methods 15, 789–792 (2018).

    Article  Google Scholar 

  37. Preibisch, S., Saalfeld, S. & Tomancak, P. Globally optimal stitching of tiled 3D microscopic image acquisitions. Bioinformatics 25, 1463–1465 (2009).

    Article  CAS  Google Scholar 

  38. Sileo, L., Pisanello, M., De Vittorio, M. & Pisanello, F. Fabrication of multipoint light emitting optical fibers for optogenetics. Proc. SPIE 9305, 93052O (2015).

    Article  Google Scholar 

Download references

Acknowledgements

F. Pisano, E.M., A.B., M.B., B.S. and F. Pisanello acknowledge funding from the European Research Council under the European Union’s Horizon 2020 research and innovation program (#677683); M. Pisanello and M.D.V. acknowledge funding from the European Research Council under the European Union’s Horizon 2020 research and innovation program (#692943). L.S., M.D.V. and B.L.S. are funded by the US National Institutes of Health (U01NS094190). M. Pisanello, L.S., F. Pisanello, M.D.V., B.L.S. are funded by the US National Institutes of Health (1UF1NS108177-01).

Author information

Authors and Affiliations

Authors

Contributions

F. Pisano and M.P. equally contributed to this work. F. Pisano, M.P., A.B., M.B., B.L.S. and F. Pisanello developed the optical systems for the characterization of TFs. F. Pisano, M.P., E.M, A.B., M.B. and B.S. performed optical characterization of TF and ex vivo experiments. F. Pisano, M.P. and A.B. analyzed the data from ex vivo experiments. J.L. and S.J.L. developed the in vivo scanning TF photometry system, performed the in vivo experiment and analyzed the in vivo data. F. Pisano, L.S. fabricated the microstructured TFs. M.H. and F. Pisanello performed preliminary experiments. F. Pisano, M.P, J.L, S.J.L, B.L.S., M.D.V. and F. Pisanello wrote the manuscript and prepared the figures with contributions from all authors. M.D.V., B.L.S. and F. Pisanello conceived the study and jointly supervised the work.

Corresponding authors

Correspondence to Filippo Pisano, Massimo De Vittorio, Bernardo L. Sabatini or Ferruccio Pisanello.

Ethics declarations

Competing interests

L.S., M.D.V., B.L.S. and F. Pisanello are founders and hold private equity in OptogeniX, a company that develops, produces and sells technologies to deliver light into the brain. Tapered fibers commercially available from OptogeniX were used as tools in the research.

Additional information

Peer review information Nina Vogt was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Integrated supplementary information

Supplementary Figure 1 Data on collection fields of tapered optical fibers.

a) Collection length for a typical fiber with NA=0.22 (black dots), NA=0.39 (red squares) and NA=0.66 (green triangles) TFs as a function of the taper angle. The collection length is calculated as the distance from the tip at which the collection intensity drops to 10% of its maximum value. Error bars represent fabrication tolerances, expressed as twice the distance between the collection length and the distance from the tip at which the collection intensity approaches the noise level, defined as 5% of the collection maximum. b) Comparison of number of photons collected from a two-photon fluorescence spot raster-scanned in a PBS:fluorescein solution (pixel dwell time 3.2 µs) for a FF (inset) and TF with NA 0.39; the isoline in the FF inset shows the maximum number of photons collected by the TF; scale bar 500 µm. c) Isometric lines of photons collection for a NA=0.39 TF in a PBS:Fluorescein solution (30 µM); the color bar shows the number of photons per pixel (dwell time 3.2 µs); isolines are drawn at 10, 20, 50, and 100 photons; scale bar is 500 µm. d) Volumetric collection field obtained from a z-stack for a TF NA=0.66 in solution; isometric collection surfaces are drawn as fractions of the maximum collected signal (10%, 20%, 40%, 60% and 80%). The ξ(x,y) field is symmetrical around the waveguide axis. Collection experiments producing similar results were repeated independently more than 10 times.

Supplementary Figure 2 Geometrical optics-based simulation of light collection with tapered optical fibers.

a) Definitions for the geometrical optics-based simulation of light collection from a NA=0.39 TF immersed in a uniform medium. b) Rays path and angular definitions implementing the simulation. c) Example of a simulated collection field ξSIM(x,y,z). Collection intensity in arbitrary units is shown as a color map with the scale bar representing 400 µm. Details on how these calculations were performed are given in paragraph 1 of the Supplementary note.

Supplementary Figure 3 Quantitative estimation of the spatial distribution of the collected signal.

a),b) Representative isolines resulting from the segmentation of collection ξ(x,y) and photometry efficiency ρ(x,y) fields for flat and tapered fibers, respectively. c) Collection volumes for different thresholds, for both FFs and TFs, for collection ξ(x,y,z) and photometry efficiency ρ(x,y,z) fields. d) Distribution of number of counts for increasing levels of signal, for both FFs and TFs, for collection ξ(x,y,z) and photometry efficiency ρ(x,y,z) fields. e) Depth of the center of gravity of the collected signal as a function of threshold counts, for both FFs and TFs, for collection ξ(x,y,z) and photometry efficiency ρ(x,y,z) fields. Details on how these calculations were performed are given in paragraph 2 of the Supplementary note. Experiments with similar results were repeated independently 3 times.

Supplementary Figure 4 Relative contribution of tissue volumes to the total integrated signal collected with a FF and a TF.

This plot was extracted from light collection diagrams ξ(x,y) shown in Supplementary Fig. 3. We imposed threshold values tn on the counts registered by the detector. Volumes were calculated as described in Supplementary Fig. 3. For a given threshold tn the contribution to the integrated signal was calculated as \({\mathrm{C}}\left( {{\mathrm{t}}_{\mathrm{n}}} \right) = \mathop {\sum }\limits_{\mathrm{i}} {\mathrm{\xi }}({\mathrm{x}}_{\mathrm{i}},{\mathrm{y}}_{\mathrm{i}},0)\) for all {xi,yi} so that ξ(xi,yi,0)>tn. The relative contribution in percent was obtained by dividing C(tn)/C(t=20). To obtain similar relative contributions, thresholds were set as: T={875, 620, 500, 300, 200, 115} for TFs and T={2600, 1650, 1200, 600, 320, 100} for FFs. Experiments with similar results were repeated independently 3 times.

Supplementary Figure 5 Site-selective illumination and modal-mixing influence on the collected signal.

a) Site selective illumination with a TF inserted in the cortex of a brain slice uniformly stained with fluorescein. b) Site selective illumination with a TF inserted in the striatum of a fixed brain slice from Thy1-ChR2-EYFP mouse. c) Optical setup used to assess resilience of fluorimetry performances to movement induced artifact. The far field ring produced by fluorescence light collected at a specific diameter is imaged on a sCMOS camera. The ring radius h is a direct measurement of the of the transversal component kt of the wave-vector guided into the fiber following the set of equations \(h = \frac{{f_1 \cdot f_3}}{{f_2}} \cdot \tan \theta ,\) \(k_{\mathrm{t}} = \frac{{2\pi }}{\lambda } \cdot \sin \theta ,\)where θ is the output angle from the fiber and fi the focal of the i-th lens in the imaging system (Fig. 1f). d) Comparison of the variation of intensity (left) and ring diameter (right) when performing photometry with steady or shaken fibers. Experiments were conducted with two different input angles. The experiment was repeated independently, with similar results, 5 times.

Supplementary Figure 6 Average dLight photometry signals from all trials shown separately for individual mice.

Signals from the dorsal site are shown in red; signals from the ventral site are shown in blue. Shaded areas represent the standard error on the mean of the trial averages.Mouse 1: N=37 trials for rewarded entry. N=435 trials for unrewarded entry. N=52 trials for movement initiation. Mouse 2: N=52 trials for rewarded entry. N=481 trials for unrewarded entry. N=50 trials for movement initiation. Mouse 3: N=54 trials for rewarded entry. N=418 trials for unrewarded entry. N=48 trials for movement initiation. Mouse 4: N=36 trials for rewarded entry. N=198 trials for unrewarded entry. N=52 trials for movement initiation.

Supplementary Figure 7 Further data on collection and emission from optical windows opened on the taper edge.

a) 3D maps of light collection obtained from windows of different sizes in a PBS:fluorescein solution (30 µM); isosurfaces of collection are drawn as fraction of the maximum number of collected photons (10%, 20%,40%,60%,80) b) Example of a z-stack acquired simultaneously by the µscope PMT and the fiber PMT. Scale bar is 10 µm.). The experiment was repeated independently, with similar results, 3 times. c) (Left) SEM image of a micro-structured TF with two optical windows at different taper diameters; (Right) The two optical windows are independently addressed by manipulating the input angle to stimulate fluroescence in a confined region of the surrounding medium (PBS:fluoresceince 30 µM). The experiment was independently repeated 3 times with similar results.

Supplementary Figure 8 Collection of fluorescence from a source at the same distance from the first emission diameter of TF and the facet of a FF.

Schematic representation of the distance between a fluorescence source and the optically active surface collecting light for a FF (left) and a TF (right).

Supplementary information

Supplementary Information

Supplementary Figures 1–8, Supplementary Note

Reporting Summary

Supplementary Video 1

Resilience of depth selective fiber photometry on fiber perturbations. The Video shows how perturbation of the patch fiber do not significantly alter the optical signal emitted and collected by a TF. Measurements are shown at two different input angles. Quantitative data are reported in Supplementary Figure 5.

Supplementary Video 2

Represenative fiber perturbation. The Video shows representative fiber movements used to evaluate how perturbation of the patch fiber alter the optical signal emitted and collected by TFs, shown in Supplementary Video 1

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pisano, F., Pisanello, M., Lee, S.J. et al. Depth-resolved fiber photometry with a single tapered optical fiber implant. Nat Methods 16, 1185–1192 (2019). https://doi.org/10.1038/s41592-019-0581-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41592-019-0581-x

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing