4.5 Article

MNEflow: Neural networks for EEG/MEG decoding and interpretation

Journal

SOFTWAREX
Volume 17, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.softx.2021.100951

Keywords

Neural networks; Electroencephalography; Magnetoencephalography; Tensorflow; Machine learning

Funding

  1. European Research Council [678578]
  2. European Research Council (ERC) [678578] Funding Source: European Research Council (ERC)

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MNEflow is a Python package that applies deep neural networks to EEG and MEG measurements. It includes Tensorflow implementations of popular CNN models for EEG-MEG data and introduces a flexible pipeline for preprocessing, validation, and model interpretation. The software aims to save time and computational resources in analyzing EEG and MEG data.
MNEflow is a Python package for applying deep neural networks to multichannel electroencephalograpic (EEG) and magnetoencephalographic (MEG) measurements. This software comprises Tensorflow-based implementations of several popular convolutional neural network (CNN) models for EEG-MEG data and introduces a flexible pipeline enabling easy application of the most common preprocessing, validation, and model interpretation approaches. The software aims to save time and computational resources required for applying neural networks to the analysis of EEG and MEG data. (C) 2021 The Authors. Published by Elsevier B.V.

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