FieldTrip is a MATLAB software toolbox for magnetoencephalography (MEG) and electroencephalography (EEG) analysis. [1] It is developed at the Donders Institute for Brain, Cognition and Behaviour at the Radboud University Nijmegen, together with collaborating institutes. The development of FieldTrip is supported by funding from the BrainGain, Human Connectome and ChildBrain projects. The FieldTrip software is released as open source under the GNU General Public License.
The toolbox includes algorithms for simple and advanced analysis of MEG, EEG, and invasive electrophysiological data, such as time-frequency analysis, source reconstruction using dipoles, distributed sources, beamformers, and non-parametric statistical testing. It supports the data formats of major MEG systems (CTF, Neuromag, BTi) and most popular EEG systems, as well as of spike and fNIRS data by external collaborators. FieldTrip contains high-level functions that can be used to construct an analysis protocol in MATLAB. Though it contains some graphical user interface elements (mostly concerned with results visualization), it is mainly targeted towards batch-scripting of the formerly mentioned analysis protocols.
MATLAB is a proprietary multi-paradigm programming language and numeric computing environment developed by MathWorks. MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages.
GNU Octave is software featuring a high-level programming language, primarily intended for numerical computations. Octave helps in solving linear and nonlinear problems numerically, and for performing other numerical experiments using a language that is mostly compatible with MATLAB. It may also be used as a batch-oriented language. Since it is part of the GNU Project, it is free software under the terms of the GNU General Public License.
Scilab is a free and open-source, cross-platform numerical computational package and a high-level, numerically oriented programming language. It can be used for signal processing, statistical analysis, image enhancement, fluid dynamics simulations, numerical optimization, and modeling, simulation of explicit and implicit dynamical systems and symbolic manipulations.
Magnetoencephalography (MEG) is a functional neuroimaging technique for mapping brain activity by recording magnetic fields produced by electrical currents occurring naturally in the brain, using very sensitive magnetometers. Arrays of SQUIDs are currently the most common magnetometer, while the SERF magnetometer is being investigated for future machines. Applications of MEG include basic research into perceptual and cognitive brain processes, localizing regions affected by pathology before surgical removal, determining the function of various parts of the brain, and neurofeedback. This can be applied in a clinical setting to find locations of abnormalities as well as in an experimental setting to simply measure brain activity.
An event-related potential (ERP) is the measured brain response that is the direct result of a specific sensory, cognitive, or motor event. More formally, it is any stereotyped electrophysiological response to a stimulus. The study of the brain in this way provides a noninvasive means of evaluating brain functioning.
Euler is a free and open-source numerical software package. It contains a matrix language, a graphical notebook style interface, and a plot window. Euler is designed for higher level math such as calculus, optimization, and statistics.
EEGLAB is a MATLAB toolbox distributed under the free BSD license for processing data from electroencephalography (EEG), magnetoencephalography (MEG), and other electrophysiological signals. Along with all the basic processing tools, EEGLAB implements independent component analysis (ICA), time/frequency analysis, artifact rejection, and several modes of data visualization. EEGLAB allows users to import their electrophysiological data in about 20 binary file formats, preprocess the data, visualize activity in single trials, and perform ICA. Artifactual ICA components may be subtracted from the data. Alternatively, ICA components representing brain activity may be further processed and analyzed. EEGLAB also allows users to group data from several subjects, and to cluster their independent components.
The Donders Centre for Cognitive Neuroimaging is one of the four centers which together comprise the Donders Institute. It is located at the campus of the Radboud University Nijmegen and maintains strong ties with the Max Planck Institute for Psycholinguistics. It is named after the Dutch ophthalmologist Franciscus Donders, who was the first scientist to use differences in reaction times to infer differences in cognitive processing.
Chronux is an open-source software package developed for the loading, visualization and analysis of a variety of modalities / formats of neurobiological time series data. Usage of this tool enables neuroscientists to perform a variety of analysis on multichannel electrophysiological data such as LFP, EEG, MEG, Neuronal spike times and also on spatiotemporal data such as FMRI and dynamic optical imaging data. The software consists of a set of MATLAB routines interfaced with C libraries that can be used to perform the tasks that constitute a typical study of neurobiological data. These include local regression and smoothing, spike sorting and spectral analysis - including multitaper spectral analysis, a powerful nonparametric method to estimate power spectrum. The package also includes some GUIs for time series visualization and analysis. Chronux is GNU GPL v2 licensed.
Electroencephalography (EEG) is an electrophysiological monitoring method to record electrical activity on the scalp that has been shown to represent the macroscopic activity of the surface layer of the brain underneath. It is typically non-invasive, with the electrodes placed along the scalp. Electrocorticography, involving invasive electrodes, is sometimes called intracranial EEG.
Electrophysiological techniques for clinical diagnosis will discuss the techniques borrowed from electrophysiology used in the clinical diagnosis of subjects. There are many processes that occur in the body which produce electrical signals that can be detected. Depending on the location and the source of these signals, distinct methods and techniques have been developed to properly target them.
The following outline is provided as an overview of and topical guide to brain mapping:
The Neurophysiological Biomarker Toolbox (NBT) is an open source MATLAB toolbox for the computation and integration of neurophysiological biomarkers. The NBT toolbox has so far been used in seven peer-reviewed research articles, and has a broad user base of more than 1000 users. The NBT toolbox provides unique features for analysis of resting-state EEG or MEG recordings. NBT offers a pipeline from data storage to statistics including artifact rejection, signal visualization, biomarker computation, statistical testing, and biomarker databasing. NBT allows for easy implementation of new biomarkers, and incorporates an online wiki that aims at facilitating collaboration among NBT users including extensive help and tutorials. The standardised way of data storage and analysis that NBT proposes allow different research projects to merge, compare, or share their data and biomarker algorithms.
A field trip is a journey by a group of people to a place away from their normal environment, usually for education, personal enrichment, or research purposes.
Corticomuscular Coherence relates to the synchrony in the neural activity of brain's cortical areas and muscle. The neural activities are picked up by electrophysiological recordings from the brain and muscle (EMG). It is a method to study the neural control of movement.
Corticocortical coherence is referred to the synchrony in the neural activity of different cortical brain areas. The neural activities are picked up by electrophysiological recordings from the brain. It is a method to study the brain's neural communication and function at rest or during functional tasks.
EEG analysis is exploiting mathematical signal analysis methods and computer technology to extract information from electroencephalography (EEG) signals. The targets of EEG analysis are to help researchers gain a better understanding of the brain; assist physicians in diagnosis and treatment choices; and to boost brain-computer interface (BCI) technology. There are many ways to roughly categorize EEG analysis methods. If a mathematical model is exploited to fit the sampled EEG signals, the method can be categorized as parametric, otherwise, it is a non-parametric method. Traditionally, most EEG analysis methods fall into four categories: time domain, frequency domain, time-frequency domain, and nonlinear methods. There are also later methods including deep neural networks (DNNs).