A Signal-Harmonizing Hybrid Neural Pathway Enabled by Bipolar-Chemo-Synapse Spiking Interneuron
To realize human-machine fusion, a hybrid neural pathway operating in the same modality with biological systems becomes imperative, which requires an interneuron unit to encode information in biorecognizable spike sequences and tune the frequency upon excitatory and inhibitory neurotransmitters. Existing artificial interneurons cannot encode information upon different neurotransmitters, and the activation threshold and frequency responsivity do not align with those of biological counterparts, leading to limited success in constructing a signal-harmonizing hybrid neural pathway for neuroprosthetics, neurorehabilitation, and other neuroelectronic applications. Herein, we develop a bipolar-chemosynapse interneuron to encode the spike frequency in a highly bionic paradigm. Bipolar synapses dynamically respond to excitatory and inhibitory neurotransmitters and translate time-series chemical signals into the spike sequence, achieving the lowest activation threshold (6.25 μM) and the highest frequency responsivity (0.55 Hz μM<sup>-1</sup>) to date, close to the biological counterpart. A signal-harmonizing hybrid sensorimotor pathway mediated by excitatory and inhibitory neurotransmitters is constructed for the first time, which encodes upstream mechanical stimuli, modulates the downstream leg swing frequency of a mouse, and balances neural activity accordingly.
Authors
- Yuetong Yang
- Dingding Jiang (ORCID: https://orcid.org/0009-0008-1639-4899)
- Dapeng Wei (ORCID: https://orcid.org/0000-0002-3575-617X)
- Daizong Ji (ORCID: https://orcid.org/0000-0003-2331-5219)
- Shuai Jiang (ORCID: https://orcid.org/0000-0002-0572-4660)
- Enming Song (ORCID: https://orcid.org/0000-0002-2658-904X)
- Changhao Dai (ORCID: https://orcid.org/0000-0002-0696-077X)
- Xinjie Pei
- Bo Chen
- Shen Zhang (ORCID: https://orcid.org/0009-0008-9222-4437)
- Xuejun Wang (ORCID: https://orcid.org/0000-0002-7034-0460)
- Yunqi Liu (ORCID: https://orcid.org/0000-0001-5521-2316)
- Wen-Tao Liu (ORCID: https://orcid.org/0000-0002-8741-6118)
- Yiheng Chen
- Shi Luo
- Derong Kong
Institutions
- Chinese Academy of Sciences (CN)
- Fudan University (CN)
- Integrated Optoelectronics (Norway) (NO)
- Chongqing Institute of Green and Intelligent Technology (CN)
- Pudong Medical Center (CN)
Publication Details
- Journal
- Journal of the American Chemical Society
- Published
- 2025-03-14
- DOI
- https://doi.org/10.1021/jacs.5c00198
- Citations
- 2
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 1.46
Funders
- National Natural Science Foundation of China
- China Postdoctoral Science Foundation