Tissue-like Bioelectronic Material Strategies for Personalized Closed-Loop Neuroprostheses
Source abstract
Abstract
Conventional neuroprosthetic interfaces rely on rigid and bulky structures, which limit long-term systemic operations. For chronic applications of neural interfaces targeting regions of the nervous system (brain, spinal cord, and peripheral nerves), maintaining stable electrical performance of alternative devices without physical pressure or secondary damage to nerve tissues is important. Soft neural interfaces based on intrinsically stretchable nanocomposites, functional nanomaterials embedded in a strain-durable polymer matrix, represent ideal platforms due to their spontaneous mechanical modulus matching with biological tissues, enabling a stable device-tissue interface for high-fidelity signaling. A purpose-driven feedback system operating in a closed-loop manner is desirable to supplement artificial bidirectional sensory-motor pathways, as the ultimate goal is to restore sensory and motor functions similar to those of able-bodied individuals. We present recent advancements in material strategies, structural device designs, and monolithic integration of personalized closed-loop neuroprostheses. This includes an overview of soft bioelectronic materials and device platforms featuring high stretchability, conformability, electrical durability and recovery, and tissue adhesion. Strain-gradient bilayer structures combining functional nanocomposite electrodes and tissue-adhesive hydrogel layers have been highlighted as optimal tissue-interfacing form factors. We suggest future directions for monolithically integrated soft neuroprosthetic systems aimed at the personalized treatment of patients with impaired neural function.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Neuroscience and Neural Engineering · Advanced Sensor and Energy Harvesting Materials · Muscle activation and electromyography studies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Electrical and Computer Engineering
Sungkyunkwan University (SKKU)
Center for Neuroscience Imaging Research
Institute for Basic Science (IBS)
Department of Intelligent Precision Healthcare Convergence
SKKU
Department of Biomedical Engineering
Department of Artificial Intelligence System Engineering
Funding
National Research Foundation of Korea · Institute for Basic Science · Korea-US Collaborative Research Fund · Korean Fund for Regenerative Medicine
References (100+)
Show source-provided references
1. 10.1038/s42003-022-04390-w10.1038/s42003-022-04390-w ↗
2. 10.1038/s44222-023-00054-410.1038/s44222-023-00054-4 ↗
3. 10.1016/S2589-7500(24)00222-X10.1016/S2589-7500(24)00222-X ↗
4. 10.1126/scitranslmed.300596810.1126/scitranslmed.3005968 ↗
5. 10.1038/497176a10.1038/497176a ↗
6. 10.1523/JNEUROSCI.1237-24.202410.1523/JNEUROSCI.1237-24.2024 ↗
7. 10.1016/j.copbio.2021.10.00110.1016/j.copbio.2021.10.001 ↗
8. 10.1007/s00415-024-12604-w10.1007/s00415-024-12604-w ↗
9. 10.1038/s41586-020-03180-w10.1038/s41586-020-03180-w ↗
10. 10.1126/scitranslmed.300832510.1126/scitranslmed.3008325 ↗
11. 10.1038/s41591-023-02584-110.1038/s41591-023-02584-1 ↗
12. 10.1038/s41586-018-0649-210.1038/s41586-018-0649-2 ↗
13. 10.1038/s41593-022-01106-510.1038/s41593-022-01106-5 ↗
14. 10.1186/s12984-020-00667-510.1186/s12984-020-00667-5 ↗
15. 10.3389/fnins.2018.0035010.3389/fnins.2018.00350 ↗
16. 10.1038/s41467-024-45190-610.1038/s41467-024-45190-6 ↗
17. 10.1016/j.clinph.2017.12.02710.1016/j.clinph.2017.12.027 ↗
18. 10.1088/1741-2552/aac96410.1088/1741-2552/aac964 ↗
19. 10.1126/scitranslmed.abg646310.1126/scitranslmed.abg6463 ↗
20. 10.1038/s41467-025-58825-z10.1038/s41467-025-58825-z ↗
21. 10.1523/JNEUROSCI.0282-08.200810.1523/JNEUROSCI.0282-08.2008 ↗
22. 10.1073/pnas.241930412210.1073/pnas.2419304122 ↗
23. 10.1016/S0140-6736(17)30601-310.1016/S0140-6736(17)30601-3 ↗
24. 10.1152/physrev.00027.201610.1152/physrev.00027.2016 ↗
25. 10.1126/science.abd038010.1126/science.abd0380 ↗
26. 10.1016/j.wneu.2024.05.10410.1016/j.wneu.2024.05.104 ↗
27. 10.1038/s44222-024-00239-510.1038/s44222-024-00239-5 ↗
28. 10.3389/fnins.2021.74946510.3389/fnins.2021.749465 ↗
29. 10.1007/s00586-008-0729-310.1007/s00586-008-0729-3 ↗
30. 10.1038/s41593-018-0262-610.1038/s41593-018-0262-6 ↗
31. 10.1038/s41467-018-05282-610.1038/s41467-018-05282-6 ↗
32. 10.1038/nature2011810.1038/nature20118 ↗
33. 10.1038/ncomms423710.1038/ncomms4237 ↗
34. 10.1002/adma.20220186410.1002/adma.202201864 ↗
35. 10.1126/scitranslmed.aay468210.1126/scitranslmed.aay4682 ↗
36. 10.1002/brx2.4710.1002/brx2.47 ↗
37. 10.1038/s41928-022-00913-910.1038/s41928-022-00913-9 ↗
38. 10.1038/s41467-024-45768-010.1038/s41467-024-45768-0 ↗
39. 10.1038/s41928-023-01074-z10.1038/s41928-023-01074-z ↗
40. 10.1126/sciadv.adt604110.1126/sciadv.adt6041 ↗
41. 10.1002/adfm.20240356210.1002/adfm.202403562 ↗
42. 10.3389/fnins.2016.0031210.3389/fnins.2016.00312 ↗
43. 10.1021/acsmaterialslett.1c0043810.1021/acsmaterialslett.1c00438 ↗
44. 10.1016/j.matt.2021.02.00110.1016/j.matt.2021.02.001 ↗
45. 10.1016/j.bios.2024.11647210.1016/j.bios.2024.116472 ↗
46. 10.1039/D2MH01125E10.1039/D2MH01125E ↗
47. 10.1038/s41467-023-40191-310.1038/s41467-023-40191-3 ↗
48. 10.1039/D3NR05488H10.1039/D3NR05488H ↗
49. 10.1038/s44222-024-00194-110.1038/s44222-024-00194-1 ↗
50. 10.1021/acs.nanolett.4c0116310.1021/acs.nanolett.4c01163 ↗
51. 10.1038/s41467-024-47223-610.1038/s41467-024-47223-6 ↗
52. 10.1038/s41565-022-01160-x10.1038/s41565-022-01160-x ↗
53. 10.1021/acs.jpcc.5b0662910.1021/acs.jpcc.5b06629 ↗
54. 10.1038/s41591-020-0792-910.1038/s41591-020-0792-9 ↗
55. 10.1038/s41598-024-53719-410.1038/s41598-024-53719-4 ↗
56. 10.1038/s41565-024-01658-610.1038/s41565-024-01658-6 ↗
57. 10.1126/science.abh435710.1126/science.abh4357 ↗
58. 10.1126/sciadv.abl551110.1126/sciadv.abl5511 ↗
59. 10.1016/j.bios.2019.11191910.1016/j.bios.2019.111919 ↗
60. 10.1016/j.trechm.2024.02.00210.1016/j.trechm.2024.02.002 ↗
61. 10.1016/j.cej.2023.14525110.1016/j.cej.2023.145251 ↗
62. 10.1038/nature2549410.1038/nature25494 ↗
63. 10.1038/s41467-017-01824-610.1038/s41467-017-01824-6 ↗
64. 10.3390/nano903037410.3390/nano9030374 ↗
65. 10.1002/adma.20240793110.1002/adma.202407931 ↗
66. 10.1038/s41586-023-06660-x10.1038/s41586-023-06660-x ↗
67. 10.1002/marc.20210032410.1002/marc.202100324 ↗
68. 10.1016/j.heliyon.2024.e3703010.1016/j.heliyon.2024.e37030 ↗
69. 10.1038/s41467-022-30648-210.1038/s41467-022-30648-2 ↗
70. 10.1002/smtd.20220131810.1002/smtd.202201318 ↗
71. 10.1002/adma.20230340110.1002/adma.202303401 ↗
72. 10.1002/smll.20240221410.1002/smll.202402214 ↗
73. 10.1002/adfm.20231090810.1002/adfm.202310908 ↗
74. 10.1038/s41467-023-37948-110.1038/s41467-023-37948-1 ↗
75. 10.1126/sciadv.160207610.1126/sciadv.1602076 ↗
76. 10.1126/sciadv.adi772410.1126/sciadv.adi7724 ↗
77. 10.1038/s41467-022-29773-910.1038/s41467-022-29773-9 ↗
78. 10.1126/sciadv.adg860210.1126/sciadv.adg8602 ↗
79. 10.1126/sciadv.adf057510.1126/sciadv.adf0575 ↗
80. 10.1126/science.abo663110.1126/science.abo6631 ↗
81. 10.1016/j.matt.2020.03.01610.1016/j.matt.2020.03.016 ↗
82. 10.1002/adma.20220415910.1002/adma.202204159 ↗
83. 10.1038/ncomms198010.1038/ncomms1980 ↗
84. 10.1038/s41528-024-00299-y10.1038/s41528-024-00299-y ↗
85. 10.1126/science.120615710.1126/science.1206157 ↗
86. 10.1016/j.cossms.2015.01.00210.1016/j.cossms.2015.01.002 ↗
87. 10.1126/science.115436710.1126/science.1154367 ↗
88. 10.1038/ncomms1589410.1038/ncomms15894 ↗
89. 10.1039/C8CS00706C10.1039/C8CS00706C ↗
90. 10.1038/nmat490410.1038/nmat4904 ↗
91. 10.1021/acsnano.9b0016010.1021/acsnano.9b00160 ↗
92. 10.1038/s41467-022-32966-x10.1038/s41467-022-32966-x ↗
93. 10.1038/s41928-023-00932-010.1038/s41928-023-00932-0 ↗
94. 10.1126/sciadv.aaw106610.1126/sciadv.aaw1066 ↗
95. 10.1038/s41928-018-0189-710.1038/s41928-018-0189-7 ↗
96. 10.1038/nature1240110.1038/nature12401 ↗
97. 10.1038/nnano.2012.20610.1038/nnano.2012.206 ↗
98. 10.1038/s41565-018-0226-810.1038/s41565-018-0226-8 ↗
99. 10.1038/s41928-025-01389-z10.1038/s41928-025-01389-z ↗
100. 10.1002/adma.20130568210.1002/adma.201305682 ↗