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.
Some smaller changes, e.g. dead links and minor annoyances when running in batch mode.
"Abort instead of looping forever when covariance matrices don't converge" "fixes" an infinite loop when the resulting covariance matrices aren't positive definite and can't be fixed, aborting with an error after 10000 tries instead. This isn't ideal, but still better than coming back from the weekend, taking a look at the HPC cluster and seeing some jobs cancelled after taking 100% CPU time until the time limit was reached.
(to be merged after #6).
Some smaller changes, e.g. dead links and minor annoyances when running in batch mode.
"Abort instead of looping forever when covariance matrices don't converge" "fixes" an infinite loop when the resulting covariance matrices aren't positive definite and can't be fixed, aborting with an error after 10000 tries instead. This isn't ideal, but still better than coming back from the weekend, taking a look at the HPC cluster and seeing some jobs cancelled after taking 100% CPU time until the time limit was reached.