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Reconfigurable nanophotonic silicon probes for sub-millisecond deep-brain optical stimulation

Nature Biomedical Engineering volume 4, pages 223–231 (2020)Cite this article

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Abstract

The use of nanophotonics to rapidly and precisely reconfigure light beams for the optical stimulation of neurons in vivo has remained elusive. Here we report the design and fabrication of an implantable silicon-based probe that can switch and route multiple optical beams to stimulate identified sets of neurons across cortical layers and simultaneously record the produced spike patterns. Each switch in the device consists of a silicon nitride waveguide structure that can be rapidly (<20 μs) reconfigured by electrically tuning the phase of light. By using an eight-beam probe, we show in anaesthetized mice that small groups of single neurons can be independently stimulated to produce multineuron spike patterns at sub-millisecond precision. We also show that a probe integrating co-fabricated electrical recording sites can simultaneously optically stimulate and electrically measure deep-brain neural activity. The technology is scalable, and it allows for beam focusing and steering and for structured illumination via beam shaping. The high-bandwidth optical-stimulation capacity of the device might facilitate the probing of the spatiotemporal neural codes underlying behaviour.

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Fig. 1: Schematic of an implantable probe based on reconfigurable nanophotonics operating in the visible spectral range for optogenetic neuromodulation.
Fig. 2: Nanophotonic switch operating in the visible spectral range with high extinction ratio and short switching time.
Fig. 3: Spatial optical patterns generated by the probe to demonstrate dynamic reconfiguration of highly collimated beams.
Fig. 4: In vivo demonstration of a nanoprobe driving multiple individual neurons with precisely timed spike patterns.
Fig. 5: In vivo demonstration of a fully integrated nanophotonic probe with Pt recording sites.

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Data availability

The main data supporting the results in this study are available within the paper and its Supplementary Information. The raw and analysed datasets generated during the study are too large to be publicly shared, but they are available for research purposes from the corresponding authors on reasonable request.

Code availability

The code packages MClust 3.5 and CellBase R2013a are openly available at http://redishlab.neuroscience.umn.edu/mclust/MClust.html and https://github.com/hangyabalazs/CellBase.

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Acknowledgements

This work was supported by the National Science Foundation Brain EAGER (grant no. 1611090) and was performed in part at the Cornell NanoScale Facility, a member of the National Nanotechnology Coordinated Infrastructure, which is supported by the National Science Foundation (grant no. ECCS-1542081). Back-end fabrication processing was done in part at the Advanced Science Research Center NanoFabrication Facility at the Graduate Center of the City University of New York. A.M. was funded by a National Science Foundation Graduate Research Fellowship (grant no. DGE-1144153). X.J. acknowledges the China Scholarship Council for financial support.

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Author notes

  1. These authors contributed equally: Aseema Mohanty, Qian Li.

Authors and Affiliations

  1. Department of Electrical Engineering, Columbia University, New York, NY, USA

    Aseema Mohanty, Mohammad Amin Tadayon, Samantha P. Roberts, Gaurang R. Bhatt, Euijae Shim, Xingchen Ji, Jaime Cardenas, Steven A. Miller & Michal Lipson

  2. School of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA

    Aseema Mohanty & Xingchen Ji

  3. Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, NY, USA

    Qian Li & Adam Kepecs

  4. Department of Neuroscience, Washington University in St. Louis, St. Louis, MO, USA

    Qian Li & Adam Kepecs

  5. Institute of Optics, University of Rochester, Rochester, NY, USA

    Jaime Cardenas

  6. Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA

    Adam Kepecs

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Contributions

A.M. designed and tested the performance of the nanophotonic probe. Q.L. performed the animal surgery, histological analysis and electrophysiology data analysis. A.M. and Q.L. developed and conducted the in vivo electrophysiology experiment with the assistance of M.A.T. and S.P.R. A.M. fabricated the nanophotonic probe with the assistance of X.J. and J.C. S.P.R. developed and fabricated the integrated recording electrode process. E.S. and G.R.B. assisted with back-end fabrication processing and electrical packaging, respectively. A.M. and M.A.T. developed the fibre packaging for in vivo experiments. S.A.M. developed the software interface for optical characterization. A.M., Q.L., M.A.T., A.K. and M.L. designed the experiment and discussed the results. A.M., Q.L. and M.A.T. designed and built the experimental setup. A.K. and M.L. supervised the project. A.M., Q.L., A.K. and M.L. prepared the manuscript. M.A.T., S.P.R., G.R.B., E.S., X.J., J.C. and S.A.M. edited the manuscript.

Corresponding authors

Correspondence to Adam Kepecs or Michal Lipson.

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Competing interests

A.M., Q.L., M.A.T., X.J., A.K. and M.L. are listed as inventors in a patent application related to this work, filed by Columbia University. The remaining authors declare no competing interests.

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Supplementary Video 1

Independent illumination of eight spots with low cross-talk.

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Mohanty, A., Li, Q., Tadayon, M.A. et al. Reconfigurable nanophotonic silicon probes for sub-millisecond deep-brain optical stimulation. Nat Biomed Eng 4, 223–231 (2020). https://doi.org/10.1038/s41551-020-0516-y

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