SAM: A Unified Self-Adaptive Multicompartmental Spiking Neuron Model for Learning With Working Memory.

Yang S, Gao T, Wang J, Deng B, Azghadi MR, Lei T, Linares-Barranco B

Open source

DOI: 10.3389/fnins.2022.850945
Published: 2022
Container: Frontiers in neuroscience
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3389/fnins.2022.850945,
  title = {SAM: A Unified Self-Adaptive Multicompartmental Spiking Neuron Model for Learning With Working Memory.},
  author = {Yang S and Gao T and Wang J and Deng B and Azghadi MR and Lei T and Linares-Barranco B},
  year = {2022},
  journal = {Frontiers in neuroscience},
  doi = {10.3389/fnins.2022.850945},
  url = {https://doi.org/10.3389/fnins.2022.850945}
}

RIS

TY  - JOUR
TI  - SAM: A Unified Self-Adaptive Multicompartmental Spiking Neuron Model for Learning With Working Memory.
AU  - Yang S
AU  - Gao T
AU  - Wang J
AU  - Deng B
AU  - Azghadi MR
AU  - Lei T
AU  - Linares-Barranco B
PY  - 2022
JO  - Frontiers in neuroscience
DO  - 10.3389/fnins.2022.850945
UR  - https://doi.org/10.3389/fnins.2022.850945
ER  -

APA

S, Y., T, G., J, W., B, D., MR, A., T, L., & B, L. (2022). SAM: A Unified Self-Adaptive Multicompartmental Spiking Neuron Model for Learning With Working Memory.. Frontiers in neuroscience. https://doi.org/10.3389/fnins.2022.850945

Source records

pubmed · retrieved 2026-09-25T16:28:43.599Z
europe-pmc · retrieved 2026-09-25T16:28:43.625Z
doaj · retrieved 2026-09-25T16:28:43.610Z