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arl-eegmodels

This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow

burst_detection

bycycle

Cycle-by-cycle analysis of neural oscillations.

deepeeg

Deep Learning with Tensor Flow for EEG MNE Epoch Objects

dev_burst_analysis

Analysis code for Rayson, et al "Detection and Analysis of Cortical Beta Bursts in Developmental EEG Data"

ecogfog

codes to analyze ecog data in the fog project

eeg-classification

This project was a joint effort with the neurology labs at UNL and UCD Anschutz to use deep learning to classify EEG data.

eeg-pytorch

EEG motor-imagery data analysis using MNE and Pytorch

eeglearn-pytorch

fooof

Parameterizing neural power spectra into periodic & aperiodic components.

icn_bursts

a python toolbox for beta burst research based on mne

introduction_to_statistical_learning_summary_python

Summary of each chapter of the book- Introduction of Statistical Learning (ISL), along with Python code & data.

jackson_2019

Analysis code used to create figures in Jackson et al, 2019

mne-codes

Youtube codes

mne-python

MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python

mne_workshop_amsterdam

Materials for workshops on the open neural time series analysis toolbox MNE-Python

neuroscience_tutorials

Some tutorials for students of neuroscience

yasa

YASA (Yet Another Spindle Algorithm): a Python package to analyze polysomnographic sleep recordings.

youtube-tutorials