ricsinaruto/MEG-group-decode
Train Wavenet-based group-level models on MEG data, and uncover neuroscientifically interpretable information.
This tool helps neuroscientists and cognitive researchers analyze Magnetoencephalography (MEG) data from multiple subjects simultaneously. You provide raw MEG data, and it trains deep learning models to decode brain activity, outputting interpretable features about brain responses. It's designed for researchers seeking to understand group-level neural patterns and the underlying neuroscientific mechanisms.
No commits in the last 6 months.
Use this if you need to train deep learning models on MEG data across a group of subjects and extract meaningful, interpretable insights about brain activity.
Not ideal if you are working with other neuroimaging modalities like fMRI or EEG, or if your primary goal is not group-level analysis and neuroscientific interpretability.
Stars
14
Forks
1
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jan 18, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/ricsinaruto/MEG-group-decode"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
mne-tools/mne-python
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
braindecode/braindecode
Deep learning software to decode EEG, ECG or MEG signals
NeuroTechX/moabb
Mother of All BCI Benchmarks
neuromodulation/py_neuromodulation
Real-time analysis of intracranial neurophysiology recordings.
IoBT-VISTEC/MIN2Net
End-to-End Multi-Task Learning for Subject-Independent Motor Imagery EEG Classification (IEEE...