hbMEP
hbMEP is a Python library for hierarchical Bayesian estimation of motor-evoked potential (MEP) size recruitment curves.
Documentation
Read the docs at hbmep.github.io/hbmep/
Citation
Please cite Tyagi et al., 2025 if you find this code useful in your research. The BibTeX entry for the paper is:
@article{tyagi_hierarchical_2025,
title = {Hierarchical {Bayesian} estimation of motor-evoked potential recruitment curves yields accurate and robust estimates},
author = {Tyagi, Vishweshwar and Murray, Lynda M. and Asan, Ahmet S. and Mandigo, Christopher and Virk, Michael S. and Harel, Noam Y. and Carmel, Jason B. and McIntosh, James R.},
journal = {Brain Stimulation},
year = {2025},
doi = {10.1016/j.brs.2025.09.008},
}
License
hbMEP is free software made available under the MIT License. For details see the LICENSE file.
1 maintainer
Metadata
1 maintainer
Release files for hbmep 0.9.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| hbmep-0.9.0.tar.gz | 28.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| hbmep-0.9.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 59.5 kB
Release files / hbmep-0.9.0.tar.gz
| Download URL | hbmep-0.9.0.tar.gz |
|---|---|
| Size | 28.0 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/7.0.0 CPython/3.10.12
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Release files / hbmep-0.9.0-py3-none-any.whl
| Download URL | hbmep-0.9.0-py3-none-any.whl |
|---|---|
| Size | 31.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.10.12
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