nntrf
artificial neural network for modelling temporal responses
Science Score: 67.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 3 DOI reference(s) in README -
✓Academic publication links
Links to: biorxiv.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (6.4%) to scientific vocabulary
Repository
artificial neural network for modelling temporal responses
Basic Info
Statistics
- Stars: 5
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 3
Metadata Files
README.md
nnTRF - neural network Temporal Response Function
This package is an artificial neural network implementation for temporal responses function modelling of brain signal. It implement the linear time-invariant TRF (mTRF-Toolbox, mTRFpy), the dynamic TRF framework and more!
Installation
You can get the stable release from PyPI:
sh
pip install nntrf
Or get the latest version from this repo:
sh
pip install git+https://github.com/powerfulbean/nnTRF.git
Citing nnTRF
Dou, J., Anderson, A. J., White, A. S., Norman-Haignere, S. V., & Lalor, E. C. (2024). Dynamic modeling of EEG responses to natural speech reveals earlier processing of predictable words. bioRxiv, 2024-08.
@article {Dou2024.08.26.609779,
author = {Dou, Jin and Anderson, Andrew J. and White, Aaron S. and Norman-Haignere, Samuel V. and Lalor, Edmund C.},
title = {Dynamic modeling of EEG responses to natural speech reveals earlier processing of predictable words},
elocation-id = {2024.08.26.609779},
year = {2024},
doi = {10.1101/2024.08.26.609779},
publisher = {Cold Spring Harbor Laboratory},
URL = {https://www.biorxiv.org/content/early/2024/08/26/2024.08.26.609779},
eprint = {https://www.biorxiv.org/content/early/2024/08/26/2024.08.26.609779.full.pdf},
journal = {bioRxiv}
}
Owner
- Name: Jin Dou
- Login: powerfulbean
- Kind: user
- Website: powerfulbean.github.io
- Repositories: 3
- Profile: https://github.com/powerfulbean
Citation (CITATION.cff)
cff-version: 1.2.0
message: If you use this software, please cite the article from preferred-citation.
authors:
- family-names: Dou
given-names: Jin
- family-names: Anderson
given-names: Andrew J.
- family-names: White
given-names: Aaron S.
- family-names: Norman-Haignere
given-names: Samuel V.
- family-names: Lalor
given-names: Edmund C.
title: Dynamic modeling of EEG responses to natural speech reveals earlier processing of predictable words
version: 1.0.0
url: https://www.biorxiv.org/content/early/2024/08/26/2024.08.26.609779
doi: 10.1101/2024.08.26.609779
date-released: '2024-08-26'
preferred-citation:
type: article
authors:
- family-names: Dou
given-names: Jin
- family-names: Anderson
given-names: Andrew J.
- family-names: White
given-names: Aaron S.
- family-names: Norman-Haignere
given-names: Samuel V.
- family-names: Lalor
given-names: Edmund C.
title: Dynamic modeling of EEG responses to natural speech reveals earlier processing of predictable words
doi: 10.1101/2024.08.26.609779
journal: bioRxiv
url: https://www.biorxiv.org/content/early/2024/08/26/2024.08.26.609779
year: '2024'
conference: {}
publisher:
name: Cold Spring Harbor Laboratory
GitHub Events
Total
- Release event: 1
- Watch event: 4
- Push event: 10
- Public event: 1
- Create event: 2
Last Year
- Release event: 1
- Watch event: 4
- Push event: 10
- Public event: 1
- Create event: 2
Packages
- Total packages: 1
-
Total downloads:
- pypi 7 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 3
- Total maintainers: 1
pypi.org: nntrf
- Homepage: https://github.com/powerfulbean/nnTRF
- Documentation: https://nntrf.readthedocs.io/
- License: MIT License
-
Latest release: 1.0.2
published about 1 year ago
Rankings
Maintainers (1)
Dependencies
- actions/checkout v4 composite
- actions/download-artifact v4 composite
- actions/setup-python v5 composite
- actions/upload-artifact v4 composite
- pypa/gh-action-pypi-publish release/v1 composite
- mtrf *
- numpy >=1.20.1
- scikit-fda ==0.7.1
- torch >=1.12.1,<2.0.0