Our submission for 2nd place to the MEG decoding competition https://www.kaggle.com/c/decoding-the-human-brain
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Updated
Aug 2, 2014 - Python
Our submission for 2nd place to the MEG decoding competition https://www.kaggle.com/c/decoding-the-human-brain
MNE-CAMCAN for processing the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) MEG dataset using MNE-Python
Temporal Representational Similarity Analysis in Python
Superimpose a set of protein structures and report a RSMD matrix, in CSV and Mega-compatible formats, using Pymol as a module
Python software to design current-carrying coils inside magnetically shielded cylinders to generate arbitrary static magnetic field profiles.
This repository provides analysis code to analyze spatial mixing in electrophysiological data through lead field and spatial pattern coefficients.
Contextual Minimum-Norm Estimates (CMNE): A Deep Learning Method for Source Estimation in Neuronal Networks
Brain state classification of MEG (Magnetoencephalography) data
GUI for easy MEG to BIDS conversion
A runner for the MNE BIDS Pipeline.
Apply Maxwell filtering on MEG signals recorded with Elketa (or MEGIN or Neuromag) machine using MNE Python.
Simple GUI that implements Scorepochs algorithm and provides graphical support to aid M/EEG experts during epoch selection procedure.
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