An Ultrasensitive Biomimetic Optic Afferent Nervous System with Circadian Learnability
Source abstract
Abstract
Abstract The optic afferent nervous system (OANS) plays a significant role in generating vision and circadian behaviors based on light detection and signals from the endocrine system. However, the bionic simulation of this photochemically mediated behavior is still a challenge for neuromorphic devices. Herein, stimuli of neurotransmitters at ultralow concentrations and illumination are coupled to artificial synapses with the aid of biofunctionalized heterojunction and tunneling to successfully simulate a circadian neural response. Furthermore, the mechanisms underlying the photosensitive synaptic current in response to stimuli are described. Interestingly, this OANS is demonstrated to be capable of mimicking normal and abnormal circadian learnability by combining the measured synaptic current with a three‐layer spike neural network. Strong theoretical and experimental evidence, as well as applications, are provided for the proposed biomimetic OANS to demonstrate that it can reproduce biological circadian behavior, thus establishing it as a promising candidate for future neuromorphic intelligent robots.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Memory and Neural Computing · Photoreceptor and optogenetics research · Neuroscience and Neural Engineering
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
College of Electronic Information and Optical Engineering Nankai University Tianjin 300071 P. R. China
Key Laboratory of Brain‐Like Neuromorphic Devices and Systems of Hebei Province College of Electron and Information Engineering Hebei University Baoding 071002 P. R. China
Funding
National Natural Science Foundation of China
References (49)
Show source-provided references
1. 10.1038/s41551-019-0446-810.1038/s41551-019-0446-8 ↗
2. 10.1038/s41467-020-15105-210.1038/s41467-020-15105-2 ↗
3. 10.1126/science.aao009810.1126/science.aao0098 ↗
4. 10.1002/adma.20190643310.1002/adma.201906433 ↗
5. 10.1097/WNO.000000000000062910.1097/WNO.0000000000000629 ↗
6. 10.1038/s41586-020-2285-x10.1038/s41586-020-2285-x ↗
7. 10.1038/s41398-020-0694-010.1038/s41398-020-0694-0 ↗
8. 10.1002/hup.96410.1002/hup.964 ↗
9. 10.1038/s41580-019-0179-210.1038/s41580-019-0179-2 ↗
10. 10.1002/adma.20210011910.1002/adma.202100119 ↗
11. 10.3389/fncir.2013.0000910.3389/fncir.2013.00009 ↗
12. 10.1038/nn.338710.1038/nn.3387 ↗
13. 10.1016/j.neuron.2010.09.00610.1016/j.neuron.2010.09.006 ↗
14. 10.1126/sciadv.170016010.1126/sciadv.1700160 ↗
15. 10.1021/acsnano.1c0467610.1021/acsnano.1c04676 ↗
16. 10.1016/j.matt.2022.02.02010.1016/j.matt.2022.02.020 ↗
17. 10.34133/2022/985184310.34133/2022/9851843 ↗
18. 10.1038/s41467-022-34448-610.1038/s41467-022-34448-6 ↗
19. 10.1007/s00441000034310.1007/s004410000343 ↗
20. 10.1080/0968768001002876210.1080/09687680010028762 ↗
21. 10.3390/app921471910.3390/app9214719 ↗
22. 10.1002/adfm.20210430410.1002/adfm.202104304 ↗
23. 10.1038/s41563-020-0703-y10.1038/s41563-020-0703-y ↗
24. 10.1002/pol.2021050210.1002/pol.20210502 ↗
25. Sun F. · Adv. Mater. · 2020 · 5
26. 10.1002/adfm.20200723210.1002/adfm.202007232 ↗
27. 10.1002/smll.20190010710.1002/smll.201900107 ↗
28. 10.1016/j.nanoen.2022.10748610.1016/j.nanoen.2022.107486 ↗
29. 10.1021/acsnano.1c0024810.1021/acsnano.1c00248 ↗
30. 10.1021/acsnano.7b0746010.1021/acsnano.7b07460 ↗
31. 10.1021/acsnano.1c0992510.1021/acsnano.1c09925 ↗
32. 10.1103/PhysRevResearch.2.01204210.1103/PhysRevResearch.2.012042 ↗
33. 10.1002/adfm.20170532010.1002/adfm.201705320 ↗
34. 10.1002/adma.20200209210.1002/adma.202002092 ↗
35. 10.1039/C8NR05336G10.1039/C8NR05336G ↗
36. 10.1039/C6TC04261A10.1039/C6TC04261A ↗
37. 10.1103/PhysRev.102.146410.1103/PhysRev.102.1464 ↗
38. 10.1103/PhysRevLett.97.02680110.1103/PhysRevLett.97.026801 ↗
39. 10.1038/nn73510.1038/nn735 ↗
40. 10.1038/s41467-018-07572-510.1038/s41467-018-07572-5 ↗
41. 10.1021/acsnano.0c0892110.1021/acsnano.0c08921 ↗
42. 10.1016/j.nanoen.2020.10545310.1016/j.nanoen.2020.105453 ↗
43. 10.1038/s41593-020-0640-810.1038/s41593-020-0640-8 ↗
44. 10.1177/033310241985181510.1177/0333102419851815 ↗
45. 10.1038/s41569-019-0167-410.1038/s41569-019-0167-4 ↗
46. 10.1002/adfm.20160200510.1002/adfm.201602005 ↗
47. 10.7567/JJAP.57.06510310.7567/JJAP.57.065103 ↗
48. 10.1016/j.aca.2017.11.00810.1016/j.aca.2017.11.008 ↗
49. 10.1038/s41467-020-17215-310.1038/s41467-020-17215-3 ↗