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.
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.
A preprocessor for the analysis of intra- or extracellular neuronal recordings. NEV2lkit’s main objective is to supply a friendly user interface that links the experimental data to a basic set of routines for analysis, visualization and classification of spikes in a consistent framework. It performs fast unit sorting in single or multiple experiments and allows the extraction of spikes from over large time intervals in continuously recorded data streams.
Treats both fMRI and M/EEG data as first-class citizens. CoSMoMVPA supports all state-of-the-art MVP analysis techniques, including searchlight analyses, classification, correlations, representational similarity analysis, and the time generalization method. It uses a uniform data representation of fMRI data in the volume or on the surface, and of M/EEG data at the sensor and source level. The tool provides a generalized approach to multiple comparison correction across these dimensions using Threshold-Free Cluster Enhancement with state-of-the-art clustering and permutation techniques.
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.
Provides a data acquisition (DAQ) system. MANTA can acquire data from both analog and digital headstages. It facilitates and encourages the addition of new hardware and analysis tools. The tool supports natural visualization of arbitrary 1D, 2D and 3D electrode array geometries, integrates filtering, spike-sorting and denoising for online display, synchronization and communication with a control unit. It allows two modes of acquisition: locally controlled and remotely triggered.
Uses as a simple graphical application designed to help neurophysiologists manage their experimental recording parameters (e.g., number of channels and sampling rate of the acquisition system) and process their data (data filtering, spike extraction, PCA, etc.). NDManager is a part of the Neurosuite, a package designed to help neurophysiologists process and view recorded data in an efficient and user-friendly manner.
Can be used either to improve the output of automatic clustering or to manually cluster raw data. Klusters is a graphical cluster cutting application for manual and semi-automatic spike sorting. It works with a spike waveform file, a feature file and optionally a cluster file produced by an automatic clustering program. After loading the files, Klusters displays an overview of the data. This includes several graphical elements referred to as ‘views’, namely a cluster view, a waveform view and a correlation view. Klusters is a part of the Neurosuite, a package designed to help neurophysiologists process and view recorded data in an efficient and user-friendly manner.
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.
Solves forward problems related to Magneto- and Electro-encephalography (MEG and EEG). OpenMEEG, using symmetric Boundary Element Methods (BEM), is being used for many problems in the field of quasistatic bioelectromagnetics, including Electrical Impedance Tomography (EIT), Intracranial electric potentials, Functional Electrical Stimulation (FES) and Cortical Mapping. This wide range of application domains, as well as its integration into high-level languages makes OpenMEEG particularly valuable for basic and clinical research purposes.
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.
Facilitates the use of advanced deconvolution models and spline regression in event-related brain potentials (ERPs) research. Unfold is programmed in a modular fashion, meaning that intermediate analysis steps can be readily inspected and modified by the user if needed. It is also fully documented, designed to be modular, can employ regularization, can model both linear and nonlinear effects using spline regression,
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.
Deletes the vertical electrooculogram (VEOG) artifacts from the electroencephalography (EEG). FilterBlink subtracts the grand-average of all detected VEOGs from the respective channel from an EEG segment when it shows sufficient correlation with the template. It provides a threshold of similarity between template and EEG segment that allows the user to set the sensitivity and specificity of the filter.
Simplifies clamp control and data acquisition. Henry’s EP Suite includes features for image and spectrographic acquisition, and provides access for protocol editing, inbuilt audio monitor, real-time graphical chart recorder and clamp monitors, real-time steady-state current-voltage monitoring, and sketchpad for runtime comparison.
Provides a method for Heart Rate Variability (HRV) analysis. HRV toolkit is a rigorously validated package of open source including visualization of normal sinus (NN) interval time series, automated outlier removal, and calculation of the basic time- and frequency-domain HRV statistics widely used in the literature.
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