Automatically process entire electrophysiological datasets using MNE-Python.
-
Updated
Jun 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.
Source code of "Machine learning evaluates changes in functional connectivity under a prolonged cognitive load"
A user interface for cloud based medical image storage
Reading Spike2 files for electromiography and preprocessing them
Add a description, image, and links to the mne-python topic page so that developers can more easily learn about it.
To associate your repository with the mne-python topic, visit your repo's landing page and select "manage topics."