Injectable hydrogel bioelectrostimulator for wireless deep brain neuromodulation

1. Fisher, R. S. & Velasco, A. L. Electrical brain stimulation for epilepsy. Nat. Rev. Neurol. 10, 261–270 (2014).

   Google Scholar 

2. Kringelbach, M. L., Jenkinson, N., Owen, S. L. & Aziz, T. Z. Translational principles of deep brain stimulation. Nat. Rev. Neurosci. 8, 623–635 (2007).

   Google Scholar 

3. Cagnan, H., Denison, T., McIntyre, C. & Brown, P. Emerging technologies for improved deep brain stimulation. Nat. Biotechnol. 37, 1024–1033 (2019).

   Google Scholar 

4. Zhang, T. et al. Piezoelectric ultrasound energy–harvesting device for deep brain stimulation and analgesia applications. Sci. Adv. 8, eabk0159 (2022).

   Google Scholar 

5. Singer, A. et al. Magnetoelectric materials for miniature, wireless neural stimulation at therapeutic frequencies. Neuron 107, 631–643 e635 (2020).

   Google Scholar 

6. Wang, Q. et al. Lead-free dual-frequency ultrasound implants for wireless, biphasic deep brain stimulation. Nat. Commun. 15, 4017 (2024).

   Google Scholar 

7. Lozano, A. M. et al. Deep brain stimulation: current challenges and future directions. Nat. Rev. Neurol. 15, 148–160 (2019).

   Google Scholar 

8. Krauss, J. K. et al. Technology of deep brain stimulation: current status and future directions. Nat. Rev. Neurol. 17, 75–87 (2021).

   Google Scholar 

9. Hescham, S. A. et al. Magnetothermal nanoparticle technology alleviates parkinsonian-like symptoms in mice. Nat. Commun. 12, 5569 (2021).

   Google Scholar 

10. Zhang, Y. et al. Transcranial nongenetic neuromodulation via bioinspired vesicle-enabled precise NIR-II optical stimulation. Adv. Mater. 35, e2208601 (2023).

    Google Scholar 

11. Kozielski, K. L. et al. Nonresonant powering of injectable nanoelectrodes enables wireless deep brain stimulation in freely moving mice. Sci. Adv. 7, eabc4189 (2021).

    Google Scholar 

12. Munshi, R. et al. Magnetothermal genetic deep brain stimulation of motor behaviors in awake, freely moving mice. eLife 6, e27069 (2017).

    Google Scholar 

13. Chen, R., Romero, G., Christiansen, M. G., Mohr, A. & Anikeeva, P. Wireless magnetothermal deep brain stimulation. Science 347, 1477–1480 (2015).

    Google Scholar 

14. Wu, X. et al. Tether-free photothermal deep-brain stimulation in freely behaving mice via wide-field illumination in the near-infrared-II window. Nat. Biomed. Eng. 6, 754–770 (2022).

    Google Scholar 

15. Kim, Y. J. et al. Magnetoelectric nanodiscs enable wireless transgene-free neuromodulation. Nat. Nanotechnol. 20, 121–131 (2025).

    Google Scholar 

16. Kim, T. et al. Deep brain stimulation by blood–brain-barrier-crossing piezoelectric nanoparticles generating current and nitric oxide under focused ultrasound. Nat. Biomed. Eng. 7, 149–163 (2023).

    Google Scholar 

17. Jin, S. et al. Instant noninvasive near-infrared deep brain stimulation using optoelectronic nanoparticles without genetic modification. Sci. Adv. 11, eadt4771 (2025).

    Google Scholar 

18. Benfenati, F. & Lanzani, G. Clinical translation of nanoparticles for neural stimulation. Nat. Rev. Mater. 6, 1–4 (2020).

    Google Scholar 

19. Deng, J. et al. Electrical bioadhesive interface for bioelectronics. Nat. Mater. 20, 229–236 (2021).

    Google Scholar 

20. Liu, Y. et al. Soft and elastic hydrogel-based microelectronics for localized low-voltage neuromodulation. Nat. Biomed. Eng. 3, 58–68 (2019).

    Google Scholar 

21. Chong, J. et al. Highly conductive tissue-like hydrogel interface through template-directed assembly. Nat. Commun. 14, 2206 (2023).

    Google Scholar 

22. Liu, Y. et al. Morphing electronics enable neuromodulation in growing tissue. Nat. Biotechnol. 38, 1031–1036 (2020).

    Google Scholar 

23. Inoue, A., Yuk, H., Lu, B. & Zhao, X. Strong adhesion of wet conducting polymers on diverse substrates. Sci. Adv. 6, eaay5394 (2020).

    Google Scholar 

24. Zhang, J. et al. Engineering electrodes with robust conducting hydrogel coating for neural recording and modulation. Adv. Mater. 35, e2209324 (2023).

    Google Scholar 

25. Cheng, S., Zhu, R. & Xu, X. Hydrogels for next generation neural interfaces. Commun. Mater. 5, 99 (2024).

    Google Scholar 

26. Li, J. et al. PEDOT:PSS-based bioelectronics for brain monitoring and modulation. Microsyst. Nanoeng. 11, 87 (2025).

    Google Scholar 

27. Li, W., Li, Y., Song, Z., Wang, Y.-X. & Hu, W. PEDOT-based stretchable optoelectronic materials and devices for bioelectronic interfaces. Chem. Soc. Rev. 53, 10575–10603 (2024).

    Google Scholar 

28. Strakosas, X. et al. Metabolite-induced in vivo fabrication of substrate-free organic bioelectronics. Science 379, 795–802 (2023).

    Google Scholar 

29. Wang, Y. et al. Dopant-enabled supramolecular approach for controlled synthesis of nanostructured conductive polymer hydrogels. Nano Lett. 15, 7736–7741 (2015).

    Google Scholar 

30. Wang, Z., Chen, Z., Ma, Z. & Han, H. Label-free mode based on ferrocene/PEDOT:PSS–PPy for molecularly imprinted electrochemically ultrasensitive detection of amino acids. Anal. Chem. 96, 14298–14305 (2024).

    Google Scholar 

31. Setka, M. et al. Raman and XPS studies of ammonia sensitive polypyrrole nanorods and nanoparticles. Sci. Rep. 9, 8465 (2019).

    Google Scholar 

32. Boehler, C., Carli, S., Fadiga, L., Stieglitz, T. & Asplund, M. Tutorial: guidelines for standardized performance tests for electrodes intended for neural interfaces and bioelectronics. Nat. Protoc. 15, 3557–3578 (2020).

    Google Scholar 

33. Kohn, P., Schroter, K. & Thurn-Albrecht, T. Interfacial polarization and field-induced orientation in nanostructured soft-ion conductors. Phys. Rev. Lett. 102, 216101 (2009).

    Google Scholar 

34. Erfani, R., Marefat, F., Sodagar, A. M. & Mohseni, P. Modeling and characterization of capacitive elements with tissue as dielectric material for wireless powering of neural implants. IEEE Trans. Neural Syst. Rehab. Eng. 26, 1093–1099 (2018).

    Google Scholar 

35. Huang, L. & Hu, A. P. Defining the mutual coupling of capacitive power transfer for wireless power transfer. Electron. Lett. 51, 1806–1807 (2015).

    Google Scholar 

36. Theodoridis, M. P. Effective capacitive power transfer. IEEE Trans. Power Electron. 27, 4906–4913 (2012).

    Google Scholar 

37. Wang, Z. et al. SAR and temperature: simulations and comparison to regulatory limits for MRI. J. Magn. Reson. Imaging 26, 437–441 (2007).

    Google Scholar 

38. Xicoy, H., Wieringa, B. & Martens, G. J. The SH-SY5Y cell line in Parkinson’s disease research: a systematic review. Mol. Neurodegener. 12, 10 (2017).

    Google Scholar 

39. Limousin, P. & Foltynie, T. Long-term outcomes of deep brain stimulation in Parkinson disease. Nat. Rev. Neurol. 15, 234–242 (2019).

    Google Scholar 

40. Florence, G., Sameshima, K., Fonoff, E. T. & Hamani, C. Deep brain stimulation: more complex than the inhibition of cells and excitation of fibers. Neuroscientist 22, 332–345 (2015).

    Google Scholar 

41. Herrington, T. M., Cheng, J. J. & Eskandar, E. N. Mechanisms of deep brain stimulation. J. Neurophysiol. 115, 19–38 (2015).

    Google Scholar 

42. Prasad, A. et al. Comprehensive characterization and failure modes of tungsten microwire arrays in chronic neural implants. J. Neural Eng. 9, 056015 (2012).

    Google Scholar 

43. Yuk, H., Lu, B. & Zhao, X. Hydrogel bioelectronics. Chem. Soc. Rev. 48, 1642–1667 (2019).

    Google Scholar 

44. Shi, L. H. et al. High-frequency stimulation of the subthalamic nucleus reverses limb-use asymmetry in rats with unilateral 6-hydroxydopamine lesions. Brain Res. 1013, 98–106 (2004).

    Google Scholar 

45. Chen, J. et al. Non-Faradaic optoelectrodes for safe electrical neuromodulation. Nat. Commun. 15, 405 (2024).

    Google Scholar 

46. Palasz, E. et al. BDNF as a promising therapeutic agent in Parkinson’s disease. Int. J. Mol. Sci. 21, 1170 (2020).

    Google Scholar 

47. Wu, N., Sun, X., Zhou, C., Yan, J. & Cheng, C. Neuroblasts migration under control of reactive astrocyte-derived BDNF: a promising therapy in late neurogenesis after traumatic brain injury. Stem Cell Res. Ther. 14, 2 (2023).

    Google Scholar 

48. Burciu, R. G. et al. Functional MRI of disease progression in Parkinson disease and atypical Parkinsonian syndromes. Neurology 87, 709–717 (2016).

    Google Scholar 

49. Tessitore, A., Cirillo, M. & De Micco, R. Functional connectivity signatures of Parkinson’s disease. J. Parkinsons Dis. 9, 637–652 (2019).

    Google Scholar 

50. Zhao, S. et al. Full activation pattern mapping by simultaneous deep brain stimulation and fMRI with graphene fiber electrodes. Nat. Commun. 11, 1788 (2020).

    Google Scholar 

51. Driscoll, N. et al. MXene-infused bioelectronic interfaces for multiscale electrophysiology and stimulation. Sci. Transl. Med. 13, eabf8629 (2021).

    Google Scholar 

52. Boutet, A. et al. Predicting optimal deep brain stimulation parameters for Parkinson’s disease using functional MRI and machine learning. Nat. Commun. 12, 3043 (2021).

    Google Scholar 

53. Subramanian, L. et al. Real-time functional magnetic resonance imaging neurofeedback for treatment of Parkinson’s disease. J. Neurosci. 31, 16309–16317 (2011).

    Google Scholar 

54. Filippi, M., Sarasso, E. & Agosta, F. Resting-state functional MRI in Parkinsonian syndromes. Mov. Disord. Clin. Pract. 6, 104–117 (2019).

    Google Scholar 

55. Pelled, G., Bergman, H., Ben-Hur, T. & Goelman, G. Manganese-enhanced MRI in a rat model of Parkinson’s disease. J. Magn. Reson. Imaging 26, 863–870 (2007).

    Google Scholar 

56. Nyatega, C. O., Qiang, L., Adamu, M. J. & Kawuwa, H. B. Gray matter, white matter and cerebrospinal fluid abnormalities in Parkinson’s disease: a voxel-based morphometry study. Front. Psychiatry 13, 1027907 (2022).

    Google Scholar 

57. Yang, K. et al. White matter changes in Parkinson’s disease. NPJ Parkinsons Dis. 9, 150 (2023).

    Google Scholar 

58. Zhai, H. et al. Voxel-based morphometry of grey matter structures in Parkinson’s disease with wearing-off. Brain Imaging Behav. 17, 725–737 (2023).

    Google Scholar 

59. Gillies, G. E., Murray, H. E., Dexter, D. & McArthur, S. Sex dimorphisms in the neuroprotective effects of estrogen in an animal model of Parkinson’s disease. Pharmacol. Biochem. Behav. 78, 513–522 (2004).

    Google Scholar 

60. Gillies, G. E., Pienaar, I. S., Vohra, S. & Qamhawi, Z. Sex differences in Parkinson’s disease. Front. Neuroendocrinol. 35, 370–384 (2014).

    Google Scholar 

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Author notes

1. These authors contributed equally: Ming Yang, Wenliang Liu, Ping Chen, Zhuang Liu, Renyuan Sun.

Authors and Affiliations

1. National Engineering Research Center for Nanomedicine, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China

   Ming Yang, Wenliang Liu, Ping Chen, Renyuan Sun, Chuan Gao, Jiahui She, Chong Ma, Dingke Zhang, Zhikun Li, Nanxi Yi & Zhiqiang Luo

2. Department of Neurology, Songjiang Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China

   Zhuang Liu & Jie Wang

3. Department of Electrical and Computer Engineering, University of Illinois, Urbana-Champaign, Urbana, IL, USA

   Baochun Xu & Cunjiang Yu

4. Department of Pediatric Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

   Qiong Wang, Jiexiong Feng & Zhiqiang Luo

5. Stem cells and Tissue Engineering Manufacture Center, School of Life Science, Hubei University, Wuhan, China

   Bingqing Xue & Donghui Zhang

6. Department of Materials Science and Engineering, University of Illinois, Urbana-Champaign, Urbana, IL, USA

   Cunjiang Yu

7. Department of Mechanical Science and Engineering, University of Illinois, Urbana-Champaign, Urbana, IL, USA

   Cunjiang Yu

8. Department of Bioengineering, Materials Research Laboratory, Beckman Institute for Advanced Science and Technology, Nick Holonyak Micro and Nanotechnology Laboratory, University of Illinois, Urbana-Champaign, Urbana, IL, USA

   Cunjiang Yu

9. Shanghai Key Laboratory of Emotions and Affective Disorders, Songjiang Research Institute, Songjiang Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China

   Jie Wang

10. Research Center for Intelligent Fiber Devices and Equipment, State Key Laboratory of New Textile Materials and Advanced Processing, Huazhong University of Science and Technology, Wuhan, China

    Zhiqiang Luo

Contributions

Zhiqiang Luo, J.W., and C.Y. supervised the project. M.Y., W.L., P.C., Zhuang Liu, and R.S. designed the ICH and experiments. M.Y., W.L., P.C., N.Y., and Zhikun Li conducted fabrication and testing of materials. M.Y., W.L., Q.W., Bingqing Xue, and Dingke Zhang conducted the in vitro experiments. M.Y., R.S., C.G., and J.S conducted the in vivo rat experiments. M.Y. and Zhuang Liu conducted MRI experiments. M.Y., W.L., P.C., Zhuang Liu, R.S., C.Y., J.W., and Zhiqiang Luo prepared the manuscript. M.Y., W.L., Zhuang Liu, R.S., and Baochun Xu processed the data and drew the figures. C.M., C.G., Donghui Zhang, and J.F. polished the manuscript. All authors discussed and agreed with the final version.

Corresponding authors

Correspondence to Cunjiang Yu, Jie Wang or Zhiqiang Luo.

Competing interests

The authors declare no competing interests.

Peer review information

Nature Communications thanks Hossein Montazerian, Daniel Simon, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. A peer review file is available.

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