BrainModels
BrainModels provides standard and canonical brain models (including various neurons, synapses, networks, and intuitive paper examples) which are implemented with BrainPy simulator. Moreover, we welcome your brain model implementations, and publish them through our GitHub homepage. In such a way, once your new model is implemented, it can be easily shared with other BrainPy users.
Currently, we provide the following standard models:
| Neuron Models | Synapse Models | Learning Rules |
|---|---|---|
| Leaky integrate-and-fire model | Alpha Synapse | STDP |
| Exponential integrate-and-fire model | AMPA / NMDA | BCM rule |
| Quadratic integrate-and-fire | GABAA / GABAB | Oja's rule |
| Adaptive Exponential IF model | Exponential Decay Synapse | |
| Adaptive Quadratic IF model | Difference of Two Exponentials | |
| Generalized IF model | Short-term plasticity | |
| Izhikevich model | Gap junction | |
| Hodgkin-Huxley model | Voltage jump | |
| Morris-Lecar model | ||
| Hindmarsh-Rose model |
Installation
Install BrainModels using pip:
> pip install brainmodels
Install from source code:
> pip install git+https://github.com/PKU-NIP-Lab/BrainModels
BrainModels is based on Python (>=3.6), and the following packages need to be installed to use BrainModels:
- brain-py >= 1.1.0
2 maintainers
Metadata
2 maintainers
Release files for brainmodels 0.4.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| brainmodels-0.4.1.tar.gz | 49.2 kB | Without provenance | Details for brainmodels-0.4.1.tar.gz |
Release files / brainmodels-0.4.1.tar.gz
| Download URL | brainmodels-0.4.1.tar.gz |
|---|---|
| Size | 49.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
cee35ec9fceb677fd684af165df20c82cac3b35384cd228fa329b9746896eb7f
|
|
BLAKE2b-256 checksum How to use checksums |
f6d55d65571ae65c1105d40f72123687b17d636d82d3d76ef24eb17a76e2c992
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/3.10.0 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.1 CPython/3.8.11
|
Security for brainmodels 0.4.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
