Skip to main content

Collection of neuron models for the NEURON simulator

Project description

dbbs-models

Collection of neuron models for the NEURON simulator.

Citations

If you use our models for any scientific works you're required to cite the following papers:

Granule cell model

Masoli, S., Tognolina, M., Laforenza, U., Moccia, F., and D’Angelo, E. (2020). Parameter tuning differentiates granule cell subtypes enriching transmission properties at the cerebellum input stage. Commun. Biol. 3, 222. doi:10.1038/s42003-020-0953-x.

Golgi cell model

Masoli, S., Ottaviani, A., Casali, S., and D’Angelo, E. (2020). Cerebellar Golgi cell models predict dendritic processing and mechanisms of synaptic plasticity. PLoS Comput. Biol. 16, 1–27. doi:10.1371/journal.pcbi.1007937.

Stellate cell model

Rizza, M. F., Locatelli, F., Masoli, S., Sánchez-Ponce, D., Muñoz, A., Prestori, F., et al. (2021). Stellate cell computational modeling predicts signal filtering in the molecular layer circuit of cerebellum. Sci. Rep. 11, 3873. doi:10.1038/s41598-021-83209-w.

Purkinje cell model

Masoli, S., Solinas, S., and D’Angelo, E. (2015). Action potential processing in a detailed Purkinje cell model reveals a critical role for axonal compartmentalization. Front. Cell. Neurosci. 9, 1–22. doi:10.3389/fncel.2015.00047.

Masoli, S., and D’Angelo, E. (2017). Synaptic Activation of a Detailed Purkinje Cell Model Predicts Voltage-Dependent Control of Burst-Pause Responses in Active Dendrites. Front. Cell. Neurosci. 11, 1–18. doi:10.3389/fncel.2017.00278.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

dbbs_models-2.0.0-py3-none-any.whl (372.3 kB view details)

Uploaded Python 3

File details

Details for the file dbbs_models-2.0.0-py3-none-any.whl.

File metadata

  • Download URL: dbbs_models-2.0.0-py3-none-any.whl
  • Upload date:
  • Size: 372.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.6.0 importlib_metadata/4.8.2 pkginfo/1.8.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.7

File hashes

Hashes for dbbs_models-2.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 85a2aa74d081f78c0883dda2940dad37974164dbc06103aaa687d3a39f976b52
MD5 9ee4c5ed443d138200fff66b28db8164
BLAKE2b-256 6aabda13a2ced41f63d7eff07415563a4740be278a72c6947a5a96fc435d6722

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page