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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: dat…
This repository contains the code for the paper "Sentiment-driven statistical causality in multimodal systems", by Ioannis Chalkiadakis, Anna Zaremba, Gareth W. Peters and Michael J. Chantler.
A toolset for evaluating the results and impacts of an educational event, employing cognitive maps as a model for representing cognitive structures or knowledge.