Topic: mne-python Goto Github
Some thing interesting about mne-python
Some thing interesting about mne-python
mne-python,Source code of "Machine learning evaluates changes in functional connectivity under a prolonged cognitive load"
User: 5a7man
mne-python,This is my pipeline for preprocessing and processing EEG data in Python.
User: adiaslow
mne-python,MNE-preprocessing is a python repository to reduce artifacts based on basic and unanimous approaches step by step from electroencephalographic (EEG) raw data.
User: aghaderi
mne-python,The main objective of this project is to recognise positive, negative and neutral emotions (CNN). Creating artificial signals using generative adversarial networks (GANs)
User: albertopad
mne-python,Analyze and manipulate EEG data using PyEEGLab.
User: alessiozanga
mne-python,Introduction to EEG analysis course using MNE-Python
User: alexenge
Home Page: https://alexenge.github.io/intro-to-eeg/
mne-python,tutorial and practice of EEG (Electroencephalogram) analysis, filtering, data I/O via MNE-Python (Minimum Norm Estimation)
User: atsukoba
mne-python,Automated rejection and repair of bad trials/sensors in M/EEG
Organization: autoreject
Home Page: https://autoreject.github.io
mne-python,NeuroIDBench: An Open-Source Benchmark Framework for the Standardization of Methodology in Brainwave-based Authentication Research
User: avichaurasia
Home Page: https://arxiv.org/abs/2402.08656
mne-python,Predicting Cognitive Workload in Flight Simulations using EEG Spectral and Connectivity Features: Repository for Research Code and Results
User: basverkennis
mne-python,EEG signals can be used to detect the mental state of a person which can have applications in machine learning. This repo gives an introduction to EEG signal analysis using MNE python library and describes the setup, the data preprocessing, data visualization and segmentation into epochs.
User: coderjolly
mne-python,Reading Spike2 files for electromiography and preprocessing them
User: dantoniosara
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).
User: edw4rdyao
mne-python,Quick guide and tutorial to scientific data python programming
User: faturita
mne-python,BrainVision EEG data classification using the MNE, Keras and the scikit-learn libraries.
User: fkupilik
mne-python,A simple open source Python package for I/O between Cartool and Python
Organization: functional-brain-mapping-laboratory
mne-python,A runner for the MNE BIDS Pipeline.
User: hoechenberger
mne-python,MNE-Python extension for VS Code
User: hoechenberger
mne-python,
User: jasmainak
Home Page: https://jasmainak.github.io/mne-workshop-brown/
mne-python,A U-Net for approximating the MEG inverse problem
User: jjlatval
mne-python,group sequential tests for neuroimaging
User: john-veillette
mne-python,[DEPRECATED: use MNE-Python] Python module to stream and analyze EEG data in real-time
User: kaczmarj
mne-python,Research in the area of Brain-Computer interfaces.
User: livankrekh
mne-python,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
User: lukethehecker
mne-python,laura: Local Auto-Regressive Average: A linear solution to the M/EEG inverse problem
User: lukethehecker
mne-python,Extracting power bands (theta, delta, alpha, beta bands) from the EEG signal using MNE and YASA Python
User: manishthilagar
mne-python,Materials and source code for my MSc thesis: "Studying Network Variants With Electroencephalography"
User: mccarthy-m-g
mne-python,Automatically process entire electrophysiological datasets using MNE-Python.
Organization: mne-tools
Home Page: https://mne.tools/mne-bids-pipeline/
mne-python,Connectivity algorithms that leverage the MNE-Python API.
Organization: mne-tools
Home Page: https://mne.tools/mne-connectivity/dev/index.html
mne-python,Repository for mne docker images
Organization: mne-tools
Home Page: http://mne.tools/mne-docker/
mne-python,Estimate/compute high-frequency oscillations (HFOs) from iEEG data that are BIDS and MNE compatible using a scikit-learn-style API.
Organization: mne-tools
Home Page: http://mne.tools/mne-hfo/
mne-python,Realtime data analysis with MNE-Python
Organization: mne-tools
Home Page: https://mne.tools/mne-realtime/
mne-python,Introduction to processing of EEG data using Python on a remote cluster
User: neurohazardous
mne-python, Neuropycon package of functions for electrophysiology analysis, can be used from graphpype and nipype
Organization: neuropycon
Home Page: http://neuropycon.github.io/ephypype
mne-python,
Organization: nirlab-tau
Home Page: https://nirlab-tau.github.io/sleepeegpy/
mne-python,Preprocessing Pipelines for EEG (MNE-python), fMRI (nipype), MEG (MNE-python/autoreject) data
User: nmningmei
mne-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.
User: phuycke
Home Page: https://doi.org/10.1111/ejn.15320
mne-python,A framework for boosting the implementation of stimulus-response research code in the field of cognitive science and neuroscience
User: powerfulbean
mne-python,Wrapper for MNE that makes fNIRS data analysis easier
User: pulkitgoyal56
Home Page: https://drive.google.com/file/d/1Wp6imXUvrWWXFJgtis9uWp8zWZlRckwU/view
mne-python,EEG Motor Imagery Classification Using CNN, Transformer, and MLP
User: reshalfahsi
mne-python,Sparsity enables subcortical source estimation, Krishnaswamy et al, PNAS 2017
User: sherazkhan
Home Page: https://www.pnas.org/content/114/48/E10465.full
mne-python,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 Representation. Front. Neurosci. 12. https://doi.org/10.3389/fnins.2018.00006 and Andersen, L. M. Group Analysis in FieldTrip of Time-Frequency Responses: A Pipeline for Reproducibility at Every Step of Processing, Going From Individual Sensor Space Representations to an Across-Group Source Space Representation. Front. Neurosci. 12, (2018). https://10.3389/fnins.2018.00261
User: ualsbombe
mne-python,Representational Similarity Analysis on MEG and EEG data
User: wmvanvliet
Home Page: https://users.aalto.fi/~vanvlm1/mne-rsa
mne-python,A beginner's guide to analyze MEG data using MNE-Python
User: yh-luo
mne-python,The python codes for the Analyzing Neural Time Series Data, Mike X Cohen (2012) MIT Press
User: yujingoto
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