Welcome to the repository for the Source Information Flow Toolbox (SIFT)
Developed and Maintained by: Tim Mullen (SCCN, INC, UCSD)
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.
Methods currently implemented include:
- Preprocessing routines
- Time-varying (adaptive) multivariate autoregessive modeling
- granger causality
- directed transfer function (DTF, dDTF)
- partial directed coherence (PDC, GPDC, PDCF, RPDC)
- multiple and partial coherence
- event-related spectral perturbation (ERSP)
- and many other measures...
- Bootstrap/resampling and analytical statistics
- single-condition (test for absence of information flow)
- between-condition (test for condition A = condition B)
- event-related (difference from baseline))
- A suite of programs for interactive visualization of information flow dynamics across time and frequency (with optional 3D visualization in MRI-coregistered source-space).
SIFT releases can be downloaded below. For installation and startup instructions please refer to [Chapter 6.1 of the SIFT Manual](Chapter 6.1. System Requirements).
|TIP: You can also install SIFT using the EEGLAB Extension Manager.|
|Compatibility Warning: If you are using Matlab R2013a or later, please use SIFT 0.9.8-alpha or a later version. Please note that SIFT has only been tested with Matlab R2009a through R2013b. Some features of the software may not be compatible with earlier/later versions of Matlab.|
Please note that the SIFT datastructures created using alpha versions of SIFT (release 0.9.8-alpha or earlier) are not fully compatible with release 1.0-beta (or later) versions of SIFT.
You may use the function hlp_upgradeAlphaToBeta() (included with SIFT beta release 1.33) to upgrade datasets created in SIFT 0.9.8-alpha or earlier to beta-compatible versions. No data will be deleted in this conversion.
SIFT 1.4.1 *NEW*
Sample data for the tutorial (143 Mb)
70-page SIFT manual. It gives both SIFT methods theory and a practical guide to using SIFT using downloadable sample data. An updated web version is also available below. NOTE: The practical guide applies to alpha releases of SIFT. A tutorial for version 1.0-beta or later is available here
Sample slides from the 15th International EEGLAB Workshop in Beijing, China (June 16, 2012): SIFT Lecture: Theory and Applications
If you use SIFT for a paper or talk PLEASE don't forget to mention you used SIFT (provide the URL to this wiki) and include the following citation(s):
Delorme, A., Mullen, T., Kothe, C., et al "EEGLAB, SIFT, NFT, BCILAB, and ERICA: New Tools for Advanced EEG Processing", Computational Intelligence and Neuroscience, vol. 2011, Article ID 130714, 12 pages, 2011 pdf
SIFT Online Handbook and User Manual
A video-lecture on the (very) basic theory and application of SIFT to modeling distributed brain dynamics in EEG is available here