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.
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.
Assists in visualizing results of processing steps and final outputs. MNE-Python is a scripting-based package with many visualization capabilities. It covers multiple methods of data preprocessing, source localization, statistical analysis, and estimation of functional connectivity between distributed brain regions. It offers some unique capabilities, in a coherent package facilitating the combination of standard and advanced techniques in a single environment.
Interfaces standard electrophysiology data sources and collates various analysis and simulation tools. FIND allows concise review of methods and algorithms, and opens possibilities for enhancements. It offers feature for the unified data import, representation and storage allowing for a standardized interfacing, independently of the experimental hardware and software used. This tool provides effective means of quality management.
Analyzes and visualizes electrophysiological data. Stimfit is a free analysis environment for cellular neurophysiology. This tool can number and clarify the activity of single neurons and communication between neurons. It contains algorithms to characterize the kinetics of presynaptic action potentials. This software uses several typical formats for biomedical signals, including those most commonly used in cellular electrophysiology.
Analyzes, browses and analyzes data from electrophysiology experiments or neural simulations. Spyke Viewer is built on an object model for electrophysiology data: the Neo library. This software furnishes a central graphic user interface from which independently developed analysis can be executed. It provides a flexible plugin architecture that permits creation of new plugins to allow extensibility.
Permits to visualize electrodes implantation on image data and prepares database for group studies. IntrAnat Electrodes allows users to search across patients according to a variety of anatomical and functional criteria. It uses established research neuroimaging toolboxes such as BrainVisa, Freesurfer, SPM and ANTs to recycle optimal and validated image analysis processes.
Visualizes cortical activations on a three-dimensional (3D) model of a brain surface. NeuralAct provides researchers working with Electrocorticography (ECoG) the means to observe the activity on models of the cortex. It includes a model of a pial cortical surface in the Talairach coordinate space derived from the AFNI SUMA package. This method is robust and easy to use, and should therefore benefit a wide range of researchers in cortical surface areas.
Provides general purpose data acquisition. Ephus is an open-source, flexible software package that includes functionality for a wide variety of applications ranging from traditional in vitro electrophysiology to highly customized circuit mapping and in vivo behavioral protocols. It offers a collection of both application-specific tools, such as those for electrophysiology, scanning and mapping, video imaging, as well as common (shared) tools for data binding, configuration switching, and experimental timing.
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.
Creates 3D PDF documents for biomedical publications. MeVisLab aims to facilitate the generation of U3D files by reducing the number of necessary tools to only one application in the field of biomedical image processing. It allows users to build sophisticated applications with graphical user interfaces that hide the underlying platform and do not require substantial programming knowledge. This tool permits simple assembling of image processing networks.
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.
Assists users in providing heart rate variability analysis. RHRV provides utility functions for importing heart rate time series data, analyzing their variability, and plotting and/or exporting the analysis results. It uses a custom data structure to store all information related to digital recordings from a polysomnograph. It also includes functions for loading ASCII or WFDB formatted files.
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.
Provides a toolbox for electrophysiological data analysis. NeoAnalysis is based on the Neo package to standardize electrophysiological data. This software is composed of six main modules that: (1) converts recording files different data acquiring systems to standardized format (HDF5); (2) detects spikes the raw signals; (3) sorts offline spike; (4) filters analog signals; (5) analyzes data at the population level and (6) displays data and analysis results.
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.
Allows users to inspect and mark multi-channel digitized contents with no constraint concerning marking periods of data in subsets of channels. The EyeBallGUI interface simplifies users the management and the annotation of their experiments. Its flexibility allows the retention of more good quality bio-signal data and it facilitates marking of multi-channel bio-signals for other purposes not readily supported by existing toolboxes.
Allows users to identify cortical spreading depolarizations (CSDs) using electroencephalography (EEG) signals. This algorithm intends to detect different types of CSD waves, including narrow and complex patterns of CSD, using HD-EEG under specific conditions. Its analysis aims at being noninvasive and automated. This approach was tested on simulated electroencephalography (EEG) signals.
Offers a digital imaging and communications in medicine (DICOM) solution. OsiriX is an image processing software that provides displaying, reviewing, interpreting and post-processing image files. It supports DICOM standard for a complete integration in a workflow environment and in a picture archiving and communication system (PACS).