Tools for the analysis of electro-physiological datasets, including EEG.
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Updated
Nov 2, 2017 - Python
Tools for the analysis of electro-physiological datasets, including EEG.
This repository provides analysis code to analyze intracranial electrophysiological data with data-driven spatial filters.
Functions for preprocessing timeseries data stored in the NWB format
In this research project we used a shift-invariant k-means algorithm to learn a preictal and interictal codebook of prototypical waveforms that can be used to summarize the occurrence of recurrent waveforms and to classify between preictal and interictal segments. We use the common spatial patterns (CSP) method to spatially filter the multichann…
Backend scripts for the XNAT edf-fif-et importer plugin.
Time series analysis codes used in the company's data science projects.
A Python Toolbox for Multimode Neural Data Representation Analysis - A Representational Analysis Toolbox for Neuroscience, including Neural Pattern Similarity (NPS), Representational Similarity Analysis (RSA), Spatiotemporal Pattern Similarity (STPS) & Inter-Subject Correlation (ISC)
Package to analyze EEG, ECoG and other electrophysiology formats. It allows for visualization of the results and for a GUI that can be used to score sleep stages.
Parameterizing neural power spectra into periodic & aperiodic components.
Systems Neuroscience Computing in Python: user-friendly analysis of large-scale electrophysiology data
Deep learning software to decode EEG, ECG or MEG signals
Real-time analysis of intracranial neurophysiology recordings.
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
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