Automatically process entire electrophysiological datasets using MNE-Python.
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Updated
Sep 20, 2024 - Python
Automatically process entire electrophysiological datasets using MNE-Python.
Connectivity algorithms that leverage the MNE-Python API.
A framework for boosting the implementation of stimulus-response research code in the field of cognitive science and neuroscience
MEG sensor-space and source-space analysis using mne-python
Preprocessing and encoding analysis pipelines associated with published neuroscientific research paper.
Repository with neurophysiological and statistical pipelines for auditory cognitive neuroscience research article in preparation.
Automated rejection and repair of bad trials/sensors in M/EEG
Realtime data analysis with MNE-Python
Representational Similarity Analysis on MEG and EEG data
Estimate/compute high-frequency oscillations (HFOs) from iEEG data that are BIDS and MNE compatible using a scikit-learn-style API.
A Brain Computer Interface for Electroencephalogram data learning and prediction. Implementaton of Common Spatial Patterns algorithm from scratch.
A simple open source Python package for I/O between Cartool and Python
BrainVision EEG data classification using the MNE, Keras and the scikit-learn libraries.
Neuropycon package of functions for electrophysiology analysis, can be used from graphpype and nipype
A U-Net for approximating the MEG inverse problem
A runner for the MNE BIDS Pipeline.
A user interface for cloud based medical image storage
This is my pipeline for preprocessing and processing EEG data in Python.
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.
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