Automated rejection and repair of bad trials/sensors in M/EEG
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Updated
Apr 7, 2024 - Python
Automated rejection and repair of bad trials/sensors in M/EEG
Automatically process entire electrophysiological datasets using MNE-Python.
Connectivity algorithms that leverage the MNE-Python API.
Analyze and manipulate EEG data using PyEEGLab.
Representational Similarity Analysis on MEG and EEG data
Realtime data analysis with MNE-Python
A research repository of deep learning on electroencephalographic (EEG) for Motor imagery(MI), including eeg data processing(visualization & analysis), papers(research and summary), deep learning models(reproduction and experiments).
EEG inverse solution with artificial neural networks. This package works with MNE-Python data structures for easy integration into your MNE-based M/EEG code
[DEPRECATED: use MNE-Python] Python module to stream and analyze EEG data in real-time
Neuropycon package of functions for electrophysiology analysis, can be used from graphpype and nipype
Preprocessing Pipelines for EEG (MNE-python), fMRI (nipype), MEG (MNE-python/autoreject) data
Analysis scripts for group analysis of MEG data in both Python and MATLAB associated with Andersen, L.M., 2018. Group Analysis in MNE-Python of Evoked Responses from a Tactile Stimulation Paradigm: A Pipeline for Reproducibility at Every Step of Processing, Going from Individual Sensor Space Representations to an across-Group Source Space Repres…
Quick guide and tutorial to scientific data python programming
MNE-preprocessing is a python repository to reduce artifacts based on basic and unanimous approaches step by step from electroencephalographic (EEG) raw data.
EEG Motor Imagery Classification Using CNN, Transformer, and MLP
Estimate/compute high-frequency oscillations (HFOs) from iEEG data that are BIDS and MNE compatible using a scikit-learn-style API.
BrainVision EEG data classification using the MNE, Keras and the scikit-learn libraries.
A beginner's guide to analyze MEG data using MNE-Python
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