Automated rejection and repair of epochs in M/EEG.
Project description
This repository hosts code to automatically reject trials and repair sensors for M/EEG data.
The documentation can be found under the following links:
for the stable release
for the latest (development) version
Dependencies
These are the dependencies to use autoreject:
Python (>=3.5)
numpy (>=1.8)
matplotlib (>=1.3)
scipy (>=0.16)
mne-python (>=0.14)
scikit-learn (>=0.18)
joblib
Two optional dependencies are tqdm (for nice progressbars) and h5py (for IO).
Cite
If you use this code in your project, please cite:
Mainak Jas, Denis Engemann, Federico Raimondo, Yousra Bekhti, and Alexandre Gramfort, "Automated rejection and repair of bad trials in MEG/EEG." In 6th International Workshop on Pattern Recognition in Neuroimaging (PRNI). 2016. Mainak Jas, Denis Engemann, Yousra Bekhti, Federico Raimondo, and Alexandre Gramfort. 2017. Autoreject: Automated artifact rejection for MEG and EEG data. NeuroImage, 159, 417-429.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
autoreject-0.2.1.tar.gz
(34.6 kB
view hashes)
Built Distribution
autoreject-0.2.1-py3-none-any.whl
(24.8 kB
view hashes)
Close
Hashes for autoreject-0.2.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 44eeb0e9624336fc2d1c3eebd5c29f08c693a1c640e4e8f4670b66b0ffd2e06d |
|
MD5 | d21ead86dc1ede181dbd568a19f13acf |
|
BLAKE2b-256 | d49f0e5357c97eb878939081d4b9541f9daac4a525f0b4cb34dcc534a861c97b |