Bio-plausible reconfigurable spiking neuron for neuromorphic computing
Biological neurons use diverse temporal expressions of spikes to achieve efficient communication and modulation of neural activities. Nonetheless, existing neuromorphic computing systems mainly use simplified neuron models with limited spiking behaviors due to high cost of emulating these biological spike patterns. Here, we propose a compact reconfigurable neuron design using the intrinsic dynamics of a NbO<sub>2</sub>-based spiking unit and excellent tunability in an electrochemical memory (ECRAM) to emulate the fast-slow dynamics in a bio-plausible neuron. The resistance of the ECRAM was effective in tuning the temporal dynamics of the membrane potential, contributing to flexible reconfiguration of various bio-plausible firing modes, such as phasic and burst spiking, and exhibiting adaptive spiking behaviors in changing environment. We used the bio-plausible neuron model to build spiking neural networks with bursting neurons and demonstrated improved classification accuracies over simplified models, showing great promises for use in more bio-plausible neuromorphic computing systems.
Authors
- Y. F. Liu (ORCID: https://orcid.org/0009-0002-7974-520X)
- Enhui He (ORCID: https://orcid.org/0000-0002-7870-5284)
- Peng Lin (ORCID: https://orcid.org/0000-0002-0679-8063)
- Huajin Tang (ORCID: https://orcid.org/0000-0002-9857-1543)
- Xiao Yu (ORCID: https://orcid.org/0009-0009-2292-6588)
- Qian Zheng (ORCID: https://orcid.org/0000-0003-3968-3622)
- Bihua Zhang
- Gang Pan (ORCID: https://orcid.org/0000-0002-4049-6181)
- Wei Kong (ORCID: https://orcid.org/0000-0002-7965-4407)
- Hao Jiang (ORCID: https://orcid.org/0000-0002-2110-0057)
- Jiayi Zhao (ORCID: https://orcid.org/0009-0007-0682-8676)
- De Ma (ORCID: https://orcid.org/0000-0001-8700-938X)
- Peng Chen (ORCID: https://orcid.org/0000-0001-7550-6522)
- Huaze Zhu (ORCID: https://orcid.org/0009-0009-0115-6748)
- Xiaofei Jin (ORCID: https://orcid.org/0009-0008-6334-8676)
- Xumeng Zhang (ORCID: https://orcid.org/0000-0002-3828-151X)
- Wenju Huo
Institutions
- Zhejiang University of Science and Technology (CN)
- Fudan University (CN)
- Westlake University (CN)
- Zhejiang Lab (CN)
- Zhejiang University (CN)
Publication Details
- Journal
- Science Advances
- Published
- 2025-02-05
- DOI
- https://doi.org/10.1126/sciadv.adr6733
- Citations
- 31
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 22.64
Funders
- Fundamental Research Funds for the Central Universities
- Natural Science Foundation of Zhejiang Province