The analysis software for EEG/ERP research Analyzer 2: The analysis software for EEG/ERP researchBrainVision Analyzer started in 1997 and is used in thousands of research labs. Scientists u...

Easy to use multifunctional recording software BrainVision Recorder is a multifunctional recording software designed to provide our amplifier customers with an extremely versatile and eas...

The best EEG signal processing for EEG and MEG data BESA is the most widely used software for source analysis and dipole localization in EEG and MEG research. BESA Research has been develop...

BCI EEG with OpenVibe OpenViBE is a complete program for Brain-Computer Interface and neuroscience research developed by the Inria research Institute. OpenViBE is a complete program fo...

BCI Frameworks - EEGLAB EEGLAB is an interactive Matlab toolbox for processing continuous and event-related EEG, MEG and other electrophysiological data incorporating independent component...

Brain-Computer Interfaces (BCI) and Real Time Neurosciences EEG data acquisition systems, brain signals, and study/feedback paradigms. Matlab scripts can be executed in real-time from ...

EEG BCI OpenVibe for BrainProducts OpenViBE is a complete program for Brain-Computer Interface and neuroscience research developed initially by the Inria research Institute, available imme...

EEG RDA Clients - Recorder RDA (Remote Data Access) Clients allow you to remotely access BrainVision Recorder for transferring data from BrainVision Recorder to other programs located o...

Event-Related Spectral Perturbation (ERD/ERS) The ERD_ERS value is in the range from [100 %, +100%] and describes the spectral change of activity at sampling time t relative to the activi...

Coherence: correlation in frequency domain In BESA Research, the coherence dialog box is part of the ERP module. Use 'ERP/Coherence' in the main window to open the dialog box. It defines ...

Beamforming The BESA beamformer is a modified version of the linearly constrained minimum variance vector beamformer in the time-frequency domain as described in Gross et al., "Dynamic ima...

Complex Demodulation Time-frequency transforms are obtained in a very fast implementation based on complex demodulation. Apart from source channels, intracranial channels, and scalp chan...

Source coherence From the single trials, time-frequency displays are generated by averaging spectral density amplitude or power over trials. Source coherence is calculated by averagin...

Covariance (Noise Regularization) Two methods to estimate the channel noise correlation matrix CN are provided by BESA Research: Use baseline or Use 15% lowest values. In each case, the a...

CSD and CSD Map (Current Source Density or EEG voltage) The surface Laplacian operator (second spatial derivative of the voltage distribution in tissue) calculates the volume current flow ...

DC Detrend (default in BESA) BESA Research uses settings provided in the initialization file BESA.ini whenever BESA Research is started or a new file is opened for the first time. The for...

FFT (Fast Fourier Transform) The Fast Fourier Transformation (FFT) can be applied to a marked region, the data displayed on the screen, over a larger time range in the data between two ma...

FFT Inverse (n/a BESA) Individual FEM model BESA Research provides head models that are based either on multi-shell spherical head models, standardized realistic head models using finite...

Grand Average The Event-Related Potentials (ERP) module provides many features that assist you with the analysis of event-related and evoked potentials and fields. These features, which a...

ICA ICA analysis allows decomposing EEG/MEG data into independent components. The method behind ICA analysis is the extended ICA algorithm (Lee TW et al. Independent component analysis us...

Inverse ICA The option Define as Artifact Topography opens the �Select Topographies� tab of the Artifact Correction Dialog (analogous to pressing Artifact / Select). In this tab, the ...

LORETA - for source analysis LORETA ("Low Resolution Electromagnetic Tomography") is a distributed inverse method of the family of weighted minimum norm methods. LORETA was suggested by R...

LRP (Lateralized Readiness Potential) The Contingent Negative Variation (CNV) and the Lateralized Readiness Potential (LRP) can be used as indicators for premotor and motor preparation dur...

MATLAB, BESA inbuilt interface to MATLAB / EEGLAB BESA Research has menu items "Send to MATLAB..." at various locations that allow to send data as structures to Matlab. After sending the ...

MR Correction - for detecting and correcting MR scanner artifacts during combined EEG-fMRI measurements When combining EEG and fMRI data: You will simply open the EEG data file in BESA Rese...

Ocular Correction (Subspace projection-SSP, regression algorithm) This approach has been commonly applied in the literature. SSP does not contrast artifacts and brain activity. Rather, the ...

Ocular Correction ICA (based on ICA) ICA analysis allows decomposing EEG/MEG data into independent components. ICA decomposition is performed on the current screen and can be started from...

PCA (Principal Component Analysis) This method estimates the brain activity from the data currently displayed on the screen. The data is scanned in specified time intervals. Those segment...

Phase diagram The phase diagram option is used to analyze phase differences between coherent channels. This can give an insight into a possible coupling of brain regions which may be nece...

Segmentation It is possible to create new trigger events from any of the recorded channels. This is achieved by defining parameters that characterize the features of the event. After the ...

t-Tests (paired and unpaired) BESA Statistics provides optimized, user-guided workflows for cross-subject analysis of EEG / MEG data. The statistical method used is parameter-free permuta...

Artifact rejection The Artifact Rejection transform allows you to search the data set for physical artifacts following segmentation and to remove or mark segments with artifacts. To mark a...

EEG Average Brain Products The Average transform is used for averaging previously segmented data. Prerequisites for use The transform is typically used after 1. Filtering (optional), 2. Se...

EEG Band Rejection (Filter) The Band Rejection transform can be used to filter interference signals of constant frequency out of the EEG signal. These interference signals may be due to th...

EEG Baseline Correction You can use the Baseline Correction transform to adjust the baseline of every segment. Correction is generally performed before averaging. An interval in a segment ...

Cardioballistic artifacts CB Correction for detecting and correcting cardioballistic artifacts The CB Correction transform allows the detection of pulse beats and the correction of cardiob...

EEG Coherence Analyzer You can use the Coherence transform to calculate coherence-related measures between two channels or signals, which yield a channel pair. All these measures are based...

EEG Complex Demodulation The Complex Demodulation transform continuously transforms the EEG signal by means of mathematical methods in such a way that the resulting signal consists only of...

EEG Covariance The Covariance transform can be used as a preliminary step for various forms of coherence calculation. In contrast to the Coherence transform, the data output by the Covaria...

EEG Cross Correlation The Cross Correlation transform enables you to calculate the cross correlation between two channels in a segmented EEG. It is a statistical measure of the dependency ...

CSD and CSD Map (Current Source Density) Analyzer The CSD transform computes an estimate of the surface Laplacian based on the EEG voltage values across the scalp electrodes that have vali...

EEG DC Detrend Analyzer The DC Detrend transform calculates the DC trend from the EEG signal. The average voltage is calculated for each prestimulus interval of the specified marker type....

ERS / ERD (Event-Related Synchronization / Desynchronization) The ERS/ERD transform can be used to analyze the event-related course of individual frequency bands in the EEG. Prerequisites ...

FFT (Fast Fourier Transform) Analyzer The Fourier transform converts data from the time domain into the frequency domain. In other words, the resulting data indicates the extent to which t...

FFT Inverse Analyzer The FFT Inverse transform allows to convert data back from the frequency domain into the time domain. This procedure might be particularly useful whenever you intend t...

EEG Grand Average BrainVision The Grand Average transform allows you to generate one or more grand averages based on a number of different averages. Grand Average is a secondary transform....

ICA Independent Component Analysis The ICA transform is used to split the EEG signals up into independent components using information theory methods. It is assumed here that EEG signals a...

Inverse ICA Analysis The Inverse ICA transform is used to apply the inverse of an ICA matrix directly to the ICA node or to its subnodes (child nodes). The transform makes it possible to r...

EEG IIR Filter - Zero Phase Shift Butterworth Filters The Infinite Impulse Response (IIR) Filters transform allows you to filter or attenuate undesired frequency (spectral) components tha...

EEG Level Trigger The Level Trigger transform allows you to set threshold markers on one or more channels if voltage limits are violated. These markers can be used as a basis for segmentat...

EEG Linear Derivation The Linear Derivation transform allows you to create new channels from linear combinations of existing channels. The new channels are calculated from coefficients tha...

LORETA - for EEG source analysis Low Resolution Electromagnetic Tomography (LORETA) provides a three-dimensional distribution of brain electrical activity (the current density field). LORE...

EEG LRP (Lateralized Readiness Potential) You can use the LRP transform to calculate the lateralized readiness potential (LRP) from two data sets (e.g. movements of the left and right hand...

MATLAB, inbuilt interface to MATLAB / EEGLAB The MATLAB transform allows data to be exported from the Analyzer to MATLAB, processed there and then reimported into the Analyzer. In this wa...

EEG MR Correction - for detecting and correcting MR scanner artifacts The MR Correction transform allows the detection and correction of artifacts that occur during combined EEG-fMRI measu...

EEG Ocular Correction (based on a regression algorithm) The Ocular Correction transform eliminates or at least reduces the effect of eye movements on the EEG. The Gratton & Coles metho...

EEG Ocular Correction ICA (based on ICA) The Ocular Correction ICA transform allows ocular artifacts in the EEG to be corrected. This is an ICA-based correction process using a simplified ...

PCA (Principal Component Analysis) On the one hand, a principal component analysis is used to reduce the data volume. On the other, it makes it possible to extract hypothetical variables w...

EEG Peak Detection The Peak Detection transform is used to detect and mark peaks. Peaks are local minima and maxima within an averaged EEG. The transform allows you to specify peaks in a t...

EEG Raw Data Inspection The Raw Data Inspection transform allows you to check the raw EEG data set for physical artifacts. The inspection can be carried out manually, semi automatically or...

Rectify transform EEG data The Rectify transform rectifies EEG data. In other words, positive values remain the same, while negative values are converted to positive. ...

EEG RMS / GFP (Root Mean Square and Global Field Power) The RMS/GFP transform allows you to determine the overall activity of selected channels. ...

EEG Segmentation Segmentation refers to the subdivision of the EEG into different segments (epochs). Segmentation can be based on a number of different criteria. In the Analyzer, the subd...

EEG Topographic Interpolation The Topographic Interpolation transform allows you to obtain virtual EEG channel values on the basis of real existing values. The background to topographic in...

EEG t-Tests (paired and unpaired) It is often not possible to estimate reliably on the basis of two EEG curves � the grand averages of two groups or two experimental conditions, for exa...

Wavelets EEG The Wavelets transform is used to perform a spectral analysis of EEG signals. Unlike the FFT, which calculates the entire frequency spectrum for a given interval, the Wavelets...