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Source Information Flow Toolbox

RRID:SCR_002561 RRID Copied

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Source Information Flow Toolbox (RRID:SCR_002561)

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Resource Information

URL: http://sccn.ucsd.edu/wiki/SIFT

Proper Citation: Source Information Flow Toolbox (RRID:SCR_002561)

Description: A GUI-enabled EEGLAB plugin for modeling and visualizing dynamical interactions between electrophysiological signals (EEG, ECoG, MEG, etc), preferably after transforming signals into the source domain. The toolbox consists of four modules: (1) Data Preprocessing, (2) Model Fitting and Connectivity Estimation, (3) Statistical Analysis, (4) Visualization, with a fifth Group Analysis module in development. Module 2 currently includes several adaptive multivariate autoregressive modeling (AMVAR) algorithms, including segmentation AMVAR and Kalman filtering. This subsequently allows the user to validate the model and estimate (in the time-frequency domain) a wide range of multivariate Granger-causal and coherence measures published to date. Module 3 includes routines for parametric and non-parametric significance testing. Module 4 contains routines for interactive visualization of dynamical interactions across time, frequency and anatomical source location.

Abbreviations: SIFT

Resource Type: image analysis software, software application, segmentation software, software toolkit, data visualization software, data processing software, software resource

Keywords: connectivity analysis, directed transfer analysis, eeg, meg, electrocorticography, granger causality, partial directed coherence

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This resource

is listed by	NeuroImaging Tools and Resources Collaboratory (NITRC)
is related to	EEGLAB
has parent organization	Swartz Center for Computational Neuroscience

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