Bioinspired neuron-like electronics

Abstract

As an important application of functional biomaterials, neural probes have contributed substantially to studying the brain. Bioinspired and biomimetic strategies have begun to be applied to the development of neural probes, although these and previous generations of probes have had structural and mechanical dissimilarities from their neuron targets that lead to neuronal loss, neuroinflammatory responses and measurement instabilities. Here, we present a bioinspired design for neural probes—neuron-like electronics (NeuE)—where the key building blocks mimic the subcellular structural features and mechanical properties of neurons. Full three-dimensional mapping of implanted NeuE–brain interfaces highlights the structural indistinguishability and intimate interpenetration of NeuE and neurons. Time-dependent histology and electrophysiology studies further reveal a structurally and functionally stable interface with the neuronal and glial networks shortly following implantation, thus opening opportunities for next-generation brain–machine interfaces. Finally, the NeuE subcellular structural features are shown to facilitate migration of endogenous neural progenitor cells, thus holding promise as an electrically active platform for transplantation-free regenerative medicine.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Design and characterization of NeuE, and 3D mapping of its neural interface.
Fig. 2: Time-dependent 3D histology studies of NeuE–brain interfaces.
Fig. 3: Functional interrogation with NeuE.
Fig. 4: NeuE facilitates migration of NPC-derived newborn neurons.

Code availability

The code used for data analysis is available from the corresponding author upon reasonable request.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

References

  1. 1.

    Ma, X. et al. Tuning crystallization pathways through sequence engineering of biomimetic polymers. Nat. Mater. 16, 767–774 (2017).

    CAS  Article  Google Scholar 

  2. 2.

    Fratzl, P., Kolednik, O., Fischer, F. D. & Dean, M. N. The mechanics of tessellations—bioinspired strategies for fracture resistance. Chem. Soc. Rev. 45, 252–267 (2016).

    CAS  Article  Google Scholar 

  3. 3.

    Green, J. J. & Elisseeff, J. H. Mimicking biological functionality with polymers for biomedical applications. Nature 540, 386–394 (2016).

    CAS  Article  Google Scholar 

  4. 4.

    Sadtler, K. et al. Design, clinical translation and immunological response of biomaterials in regenerative medicine. Nat. Rev. Mater. 1, 16040 (2016).

    CAS  Article  Google Scholar 

  5. 5.

    Chen, R., Canales, A. & Anikeeva, P. Neural recording and modulation technologies. Nat. Rev. Mater. 2, 16093 (2017).

    CAS  Article  Google Scholar 

  6. 6.

    Feiner, R. & Dvir, T. Tissue–electronics interfaces: from implantable devices to engineered tissues. Nat. Rev. Mater. 3, 17076 (2017).

    Article  Google Scholar 

  7. 7.

    Shoffstall, A. J. & Capadona, J. R. Bioinspired materials and systems for neural interfacing. Curr. Opin. Biomed. Eng. 6, 110–119 (2018).

    Article  Google Scholar 

  8. 8.

    Capadona, J. R., Shanmuganathan, K., Tyler, D. J., Rowan, S. J. & Weder, C. Stimuli-responsive polymer nanocomposites inspired by the sea cucumber dermis. Science 319, 1370–1374 (2008).

    CAS  Article  Google Scholar 

  9. 9.

    Smith, D. W. et al. Internal jugular vein compression mitigates traumatic axonal injury in a rat model by reducing the intracranial slosh effect. Neurosurgery 70, 740–746 (2012).

    Article  Google Scholar 

  10. 10.

    Polikov, V. S., Tresco, P. A. & Reichert, W. M. Response of brain tissue to chronically implanted neural electrodes. J. Neurosci. Methods 148, 1–18 (2005).

    Article  Google Scholar 

  11. 11.

    Salatino, J. W., Ludwig, K. A., Kozai, T. D. Y. & Purcell, E. K. Glial responses to implanted electrodes in the brain. Nat. Biomed. Eng. 1, 862–877 (2017).

    Article  Google Scholar 

  12. 12.

    Kozai, T. D. Y. et al. Ultrasmall implantable composite microelectrodes with bioactive surfaces for chronic neural interfaces. Nat. Mater. 11, 1065–1073 (2012).

    CAS  Article  Google Scholar 

  13. 13.

    Charkhkar, H. et al. Chronic intracortical neural recordings using microelectrode arrays coated with PEDOT–TFB. Acta Biomater. 32, 57–67 (2016).

    CAS  Article  Google Scholar 

  14. 14.

    Bedell, H. W. et al. Targeting CD14 on blood derived cells improves intracortical microelectrode performance. Biomaterials 163, 163–173 (2018).

    CAS  Article  Google Scholar 

  15. 15.

    Arati, S., Subramaniam, D. R. & Jit, M. Long-term changes in the material properties of brain tissue at the implant–tissue interface. J. Neural Eng. 10, 066001 (2013).

    Article  Google Scholar 

  16. 16.

    Liu, J. et al. Syringe-injectable electronics. Nat. Nanotechnol. 10, 629–636 (2015).

    CAS  Article  Google Scholar 

  17. 17.

    Fu, T.-M. et al. Stable long-term chronic brain mapping at the single-neuron level. Nat. Methods 13, 875–882 (2016).

    CAS  Article  Google Scholar 

  18. 18.

    Zhou, T. et al. Syringe-injectable mesh electronics integrate seamlessly with minimal chronic immune response in the brain. Proc. Natl Acad. Sci. USA 114, 5894–5899 (2017).

    CAS  Article  Google Scholar 

  19. 19.

    Canales, A. et al. Multifunctional fibers for simultaneous optical, electrical and chemical interrogation of neural circuits in vivo. Nat. Biotechnol. 33, 277–284 (2015).

    CAS  Article  Google Scholar 

  20. 20.

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

    CAS  Article  Google Scholar 

  21. 21.

    Minev, I. R. et al. Electronic dura mater for long-term multimodal neural interfaces. Science 347, 159–163 (2015).

    CAS  Article  Google Scholar 

  22. 22.

    Luan, L. et al. Ultraflexible nanoelectronic probes form reliable, glial scar–free neural integration.Sci. Adv. 3, e1601966 (2017).

    Article  Google Scholar 

  23. 23.

    Garcia, J., Pena, J., McHugh, S. & Jerusalem, A. A model of the spatially dependent mechanical properties of the axon during its growth. Comput. Model. Eng. Sci. 87, 411–432 (2012).

    Google Scholar 

  24. 24.

    Wang, S. S.-H. et al. Functional trade-offs in white matter axonal scaling. J. Neurosci. 28, 4047–4056 (2008).

    CAS  Article  Google Scholar 

  25. 25.

    Fu, T.-M., Hong, G., Viveros, R. D., Zhou, T. & Lieber, C. M. Highly scalable multichannel mesh electronics for stable chronic brain electrophysiology. Proc. Natl Acad. Sci. USA 114, E10046–E10055 (2017).

    CAS  Article  Google Scholar 

  26. 26.

    Jun, J. J. et al. Fully integrated silicon probes for high-density recording of neural activity. Nature 551, 232–236 (2017).

    CAS  Article  Google Scholar 

  27. 27.

    Hong, G. S. et al. Syringe injectable electronics: precise targeted delivery with quantitative input/output connectivity. Nano Lett. 15, 6979–6984 (2015).

    Article  Google Scholar 

  28. 28.

    Feng, G. et al. Imaging neuronal subsets in transgenic mice expressing multiple spectral variants of GFP. Neuron 28, 41–51 (2000).

    CAS  Article  Google Scholar 

  29. 29.

    Zhuo, L. et al. Live astrocytes visualized by green fluorescent protein in transgenic mice. Dev. Biol. 187, 36–42 (1997).

    CAS  Article  Google Scholar 

  30. 30.

    Chung, K. et al. Structural and molecular interrogation of intact biological systems. Nature 497, 332–337 (2013).

    CAS  Article  Google Scholar 

  31. 31.

    Yang, B. et al. Single-cell phenotyping within transparent intact tissue through whole-body clearing. Cell 158, 945–958 (2014).

    CAS  Article  Google Scholar 

  32. 32.

    Saxena, T. & Bellamkonda, R. V. A sensor web for neurons. Nat. Mater. 14, 1190–1191 (2015).

    CAS  Article  Google Scholar 

  33. 33.

    Igarashi, K. M., Lu, L., Colgin, L. L., Moser, M.-B. & Moser, E. I. Coordination of entorhinal–hippocampal ensemble activity during associative learning. Nature 510, 143–147 (2014).

    CAS  Article  Google Scholar 

  34. 34.

    Jackson, A. & Fetz, E. E. Compact movable microwire array for long-term chronic unit recording in cerebral cortex of primates. J. Neurophysiol. 98, 3109–3118 (2007).

    Article  Google Scholar 

  35. 35.

    Dickey, A. S., Suminski, A., Amit, Y. & Hatsopoulos, N. G. Single-unit stability using chronically implanted multielectrode arrays. J. Neurophysiol. 102, 1331–1339 (2009).

    Article  Google Scholar 

  36. 36.

    Quiroga, R. Q., Nadasdy, Z. & Ben-Shaul, Y. Unsupervised spike detection and sorting with wavelets and superparamagnetic clustering. Neural Comput. 16, 1661–1687 (2004).

    Article  Google Scholar 

  37. 37.

    Schmitzer-Torbert, N., Jackson, J., Henze, D., Harris, K. & Redish, A. D. Quantitative measures of cluster quality for use in extracellular recordings. Neuroscience 131, 1–11 (2005).

    CAS  Article  Google Scholar 

  38. 38.

    Schmitzer-Torbert, N. & Redish, A. D. Neuronal activity in the rodent dorsal striatum in sequential navigation: separation of spatial and reward responses on the multiple T task. J. Neurophysiol. 91, 2259–2272 (2004).

    Article  Google Scholar 

  39. 39.

    Spratley, J. P. F., Ward, M. C. L. & Hall, P. S. Bending characteristics of SU-8. IET Micro Nano Lett. 2, 20–23 (2007).

    CAS  Article  Google Scholar 

  40. 40.

    Jog, M. S. et al. Tetrode technology: advances in implantable hardware, neuroimaging, and data analysis techniques. J. Neurosci. Methods 117, 141–152 (2002).

    CAS  Article  Google Scholar 

  41. 41.

    Buzsáki, G. et al. Tools for probing local circuits: high-density silicon probes combined with optogenetics. Neuron 86, 92–105 (2015).

    Article  Google Scholar 

  42. 42.

    Weiler, S. et al. High-yield in vitro recordings from neurons functionally characterized in vivo. Nat. Protoc. 13, 1275–1293 (2018).

    CAS  Article  Google Scholar 

  43. 43.

    Cossell, L. et al. Functional organization of excitatory synaptic strength in primary visual cortex. Nature 518, 399–403 (2015).

    CAS  Article  Google Scholar 

  44. 44.

    Liu, X. et al. Optogenetic stimulation of a hippocampal engram activates fear memory recall. Nature 484, 381–385 (2012).

    CAS  Article  Google Scholar 

  45. 45.

    Gonçalves, J. T., Schafer, S. T. & Gage, F. H. Adult neurogenesis in the hippocampus: from stem cells to behavior. Cell 167, 897–914 (2016).

    Article  Google Scholar 

  46. 46.

    Ming, G.-l & Song, H. Adult neurogenesis in the mammalian central nervous system. Annu. Rev. Neurosci. 28, 223–250 (2005).

    CAS  Article  Google Scholar 

  47. 47.

    Reza, M. et al. In vivo migration of endogenous brain progenitor cells guided by an injectable peptide amphiphile biomaterial. J. Tissue Eng. Regen. Med. 12, e2123–e2133 (2018).

    Article  Google Scholar 

  48. 48.

    James, C. B. et al. Failure mode analysis of silicon-based intracortical microelectrode arrays in non-human primates. J. Neural Eng. 10, 066014 (2013).

    Article  Google Scholar 

  49. 49.

    Rozenberg, B. Kinetics, thermodynamics and mechanism of reactions of epoxy oligomers with amines. Adv. Polym. Sci. 75, 113–165 (1986).

    Article  Google Scholar 

  50. 50.

    Schuhmann, T. G., Yao, J., Hong, G., Fu, T.-M. & Lieber, C. M. Syringe-injectable electronics with a plug-and-play input/output interface. Nano Lett. 17, 5836–5842 (2017).

    CAS  Article  Google Scholar 

  51. 51.

    Schuhmann, T. G. et al. Syringe-injectable mesh electronics for stable chronic rodent electrophysiology. J. Vis. Exp. 137, e58003 (2018).

    Google Scholar 

  52. 52.

    Murray, E. et al. Simple, scalable proteomic imaging for high-dimensional profiling of intact systems. Cell 163, 1500–1514 (2015).

    CAS  Article  Google Scholar 

Download references

Acknowledgements

The authors thank D. Richardson and S. Terclavers for help with image acquisition, data handling and critical discussion, and J. Huang for assistance with recording instrumentation. This work is supported by the National Institute on Drug Abuse of the National Institutes of Health (1R21DA043985-01), a NIH Director’s Pioneer Award (1DP1EB025835-01) and the Air Force Office of Scientific Research (FA9550-14-1-0136) (to C.M.L.), the Simmons Awards (to X.Y.) and an American Heart Association Postdoctoral Fellowship (16POST27250219) and NIH Pathway to Independence Award (1K99AG056636-02) (to G.H.). This work was performed in part at the Harvard Center for Biological Imaging (HCBI) and Harvard University Center for Nanoscale Systems (CNS), a member of the National Nanotechnology Coordinated Infrastructure Network (NNCI) supported by the National Science Foundation.

Author information

Affiliations

Authors

Contributions

X.Y. and C.M.L. designed the experiments. X.Y., T.Z., T.J.Z., G.H., Y.Z., R.D.V., T.-M.F. and T.G. performed the experiments. X.Y., T.Z., T.J.Z. and C.M.L. analysed the data. X.Y. and C.M.L. wrote the paper. All authors discussed the results, revised or commented on the manuscript.

Corresponding author

Correspondence to Charles M. Lieber.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

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

Supplementary information

Supplementary Information

Supplementary Notes, Supplementary Figures 1–21, Supplementary Tables 1–3, Supplementary Video Legends 1–3, Supplementary References

Reporting Summary

Supplementary Video 1

Full 3D NeuE/neuron interface—360°-rotation video of the full 3D NeuE/neuron interface shown in Fig. 1d. Green and red colours represent neurons and NeuE, respectively.

Supplementary Video 2

Structurally indistinguishable NeuE/neuron interface—video showing depth-coding structures corresponding to Fig. 1f(II), highlighting structural indistinguishability between neuron neurites and NeuE neurite-like interconnects.

Supplementary Video 3

Junction between neuron neurites and NeuE neurite-like interconnect—video showing channel-coding and depth-coding structures corresponding to Fig. 1f(III),(IV), highlighting closely contacted junction between neuron neurites and NeuE neurite-like interconnect.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Yang, X., Zhou, T., Zwang, T.J. et al. Bioinspired neuron-like electronics. Nat. Mater. 18, 510–517 (2019). https://doi.org/10.1038/s41563-019-0292-9

Download citation

Further reading

Search

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