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Package to calculate and classify ICAs using MEGNET deep learning architecture

Project description

MEGNET

megnet-tests

This repository is a fork of the code listed below in the original code reference. This repository adds an automated processing wrapper and python package installation around the original codebase. The current codebase utilizes mne python to preprocess the data, generate the infomax ICA components (n=20), circular topography maps, and timeseries outputs. The architecture of neural net has been preserved, however, the weights have been reset to uniform distribution and retrained using repository data from MEGIN, CTF, 4D, and KIT systems.

Install

conda create -n megnet 'mne>=1.6' 'python<3.14'
conda activate megnet
pip install MEGnet-neuro

Post install initalization (downloading huggingface model weights)

megnet_init

Original Code Repository

https://github.com/DeepLearningForPrecisionHealthLab/MegNET_2020
Manuscript available: https://pubmed.ncbi.nlm.nih.gov/34274419/
DOI: https://doi.org/10.1016/j.neuroimage.2021.118402
PMID: 34274419

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