Name: Christoph Dinh
Type: User
Company: Harvard Medical School, MIT, MGH - Martinos Center
Bio: Postdoctoral research fellow focusing on data analysis, machine learning, real-time data processing and software architecture
Twitter: christophdinh
Location: Boston, USA
Blog: http://www.mne-cpp.org
Christoph Dinh's Projects
Training and evaluation pipeline for MEG and EEG brain signal encoding and decoding using deep learning. Code for our paper "Decoding speech perception from non-invasive brain recordings" published in Nature Machine Intelligence, 2023.
Contextual Minimum-Norm Estimates (CMNE): A Deep Learning Method for Source Estimation in Neuronal Networks
For evaluating spatial fidelity of M/EEG source estimates
RAP-MUSIC CUDA implementation
Tal group processing code
Koma is a framework to efficiently simulate Magnetic Resonance Imaging (MRI) acquisitions. The main focus of this package is to simulate general scenarios that could arise in pulse sequence development.
Applications for MEG and EEG Data Acquisition, Analysis & Visualization
Minimal MNE-CPP test data set
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
Deprecated qt3d Version 1.0 (use this only for the old MNE-CPP Disp3D implementation)
ScanHub combines multimodal data acquisition and complex data processing in one cloud platform.
Self-Organizing Feature Map Tutorial
MATLAB Source Localization Toolbox