NEURONpyxl: fast, flexible, Python-integrated simulation of biophysical neural networks with complex plastic synapses.

Dickman U, Thomas PJ, Chiel HJ, Byrne JH, Neveu CL

DOI: 10.3389/fncom.2026.1771884
Published: 2026
Container: Frontiers in computational neuroscience
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3389/fncom.2026.1771884,
  title = {NEURONpyxl: fast, flexible, Python-integrated simulation of biophysical neural networks with complex plastic synapses.},
  author = {Dickman U and Thomas PJ and Chiel HJ and Byrne JH and Neveu CL},
  year = {2026},
  journal = {Frontiers in computational neuroscience},
  doi = {10.3389/fncom.2026.1771884},
  url = {https://doi.org/10.3389/fncom.2026.1771884}
}

RIS

TY  - JOUR
TI  - NEURONpyxl: fast, flexible, Python-integrated simulation of biophysical neural networks with complex plastic synapses.
AU  - Dickman U
AU  - Thomas PJ
AU  - Chiel HJ
AU  - Byrne JH
AU  - Neveu CL
PY  - 2026
JO  - Frontiers in computational neuroscience
DO  - 10.3389/fncom.2026.1771884
UR  - https://doi.org/10.3389/fncom.2026.1771884
ER  -

APA

U, D., PJ, T., HJ, C., JH, B., & CL, N. (2026). NEURONpyxl: fast, flexible, Python-integrated simulation of biophysical neural networks with complex plastic synapses.. Frontiers in computational neuroscience. https://doi.org/10.3389/fncom.2026.1771884

Source records

pubmed · retrieved 2026-09-25T07:40:21.541Z