Automatically process entire electrophysiological datasets using MNE-Python.
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Updated
Sep 3, 2024 - Python
Automatically process entire electrophysiological datasets using MNE-Python.
Automated rejection and repair of bad trials/sensors in M/EEG
Connectivity algorithms that leverage the MNE-Python API.
Analyze and manipulate EEG data using PyEEGLab.
Realtime data analysis with MNE-Python
Estimate/compute high-frequency oscillations (HFOs) from iEEG data that are BIDS and MNE compatible using a scikit-learn-style API.
[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
Representational Similarity Analysis on MEG and EEG data
A simple open source Python package for I/O between Cartool and Python
A U-Net for approximating the MEG inverse problem
BrainVision EEG data classification using the MNE, Keras and the scikit-learn libraries.
MEG sensor-space and source-space analysis using mne-python
This is my pipeline for preprocessing and processing EEG data in Python.
A runner for the MNE BIDS Pipeline.
A user interface for cloud based medical image storage
Directory used to store the code used for the paper titled "Theta and alpha power across fast and slow timescales in cognitive control" by Pieter Huycke, Pieter Verbeke, C. Nico Boehler and Tom Verguts.
Repository with neurophysiological and statistical pipelines for auditory cognitive neuroscience research article in preparation.
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