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Processes continuous and event-related EEG (electro-encephalography) and MEG (magneto-encephalography). EEGLAB also processes other electrophysiological data incorporating independent component analysis (ICA), time/frequency analysis, artifact rejection, event-related statistics, and several useful modes of visualization of the averaged and single-trial data. EEGLAB provides an interactive graphic user interface (GUI) allowing users to flexibly and interactively process their high-density EEG and other dynamic brain data using ICA and/or time/frequency analysis, as well as standard averaging methods.
Uses as a viewer for continuously recorded signals, spiking activity, and behavioral events. NeuroScope is an advanced viewer for electrophysiological and behavioral data with limited editing capabilities. NeuroScope displays the data in a trace view (electrophysiological signals) and optionally a position view (position tracking) combined in a display. NeuroScope is a part of the Neurosuite, a package designed to help neurophysiologists process and view recorded data in an efficient and user-friendly manner.
A software package running under MATLAB and allowing for analysis and visualization of functional brain networks from M/EEG recordings. The main objective of this tool is to cover the complete processing framework from the M/EEG pre-processing to the identification of the functional brain networks. EEGNET includes mainly the calculation of the functional connectivity between scalp M/EEG signals as well between reconstructed brain sources obtained from the solution of the inverse problem. It also includes the characterization of the brain networks by computing the network measures proposed in the field of graph theory. EEGNET provides user-friendly interactive 2D /3D brain networks visualization.
eConnectome / Electrophysiological Connectome
A MATLAB-based toolbox, eConnectome (electrophysiological connectome), for mapping and imaging functional connectivity at both the scalp and cortical levels from the electroencephalogram (EEG), as well as from the electrocorticogram (ECoG). Graphical user interfaces were designed for interactive and intuitive use of the toolbox. Major functions of eConnectome include EEG/ECoG preprocessing, scalp spatial mapping, cortical source estimation, connectivity analysis, and visualization. Granger causality measures such as directed transfer function and adaptive directed transfer function were implemented to estimate the directional interactions of brain functional networks, over the scalp and cortical sensor spaces. Cortical current density inverse imaging was implemented using a generic realistic geometry brain-head model from scalp EEGs. Granger causality could be further estimated over the cortical source domain from the inversely reconstructed cortical source signals as derived from the scalp EEG.
Allows visualization and processing of electrophysiological signals. AnyWave is composed of several components: a visualization component that is the graphic user interface; another is a montage manager for editing user-defined montage; events can be handled by the markers manager component; the process manager exploits optional signal processing algorithm modules and finally a component deals with the plugin compatibility. It supports plugin modularity with the possibility to add plugins to add new features such as compatibility with other formats.
ECoG ClusterFlow
Allows neuroscientists to investigate the major cluster evolution patterns over space and time. ECoG ClusterFlow is a hierarchical multi-scale approach that supports the exploration, comparison and analysis of time-varying community evolution patterns at varying temporal granularity. It provides (i) an overview that summarizes the overall changes in cluster evolution, where users explore salient dynamic patterns; and (ii) a hierarchical glyph-based timeline visualization for exploring the dynamic spatial organizational changes of the clusters that uses data aggregation and small multiples methods.
A Matlab-based software for the visualization of multi-channel biomedical signals, particularly for the electroencephalography (EEG). BioSigPlot is designed for researchers on both engineering and medicine who should collaborate, visualize and analyze signals. It aims to provide a highly customizable interface for signal processing experimentation in order to plot several kinds of signals while integrating the common tools for physician. The main advantages compared to other existing programs are the multi-dataset displaying, the synchronization with video and the online processing.
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