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Swartz Center for Computational Neuroscience's Projects

relica icon relica

A method for estimating the reliability of independent components (Artoni et al. 2014)

sift icon sift

SIFT is an EEGLAB-compatible toolbox for analysis and visualization of multivariate causality and information flow between sources of electrophysiological (EEG/ECoG/MEG) activity. It consists of a suite of command-line functions with an integrated Graphical User Interface for easy access to multiple features. There are currently six modules: data preprocessing, model fitting and connectivity estimation, statistical analysis, visualization, group analysis, and neuronal data simulation.

snap icon snap

Simulation and Neuroscience Application Platform

viewprops icon viewprops

EEGLAB plugin with improved pop_prop and more

zapline-plus icon zapline-plus

Improvements of the ZapLine function to remove line noise from EEG/MEG data. Adds automatic detection of the number of components to remove, and chunks the data into segments to account for nonstationarities.

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