ElectroMagnetoEncephalography Software: Overview and Integration with Other EEG/MEG Toolboxes
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paper_title: Keep it simple: a case for using classical minimum norm estimation in the analysis of EEG and MEG data

paper_content:

The present study aims at finding the optimal inverse solution for the bioelectromagnetic inverse problem in the absence of reliable a priori information about the generating sources. Three approaches to tackle this problem are compared theoretically: the maximum-likelihood approach, the minimum norm approach, and the resolution optimization approach. It is shown that in all three of these frameworks, it is possible to make use of the same kind of a priori information if available, and the same solutions are obtained if the same a priori information is implemented. In particular, they all yield the minimum norm pseudoinverse (MNP) in the complete absence of such information. This indicates that the properties of the MNP, and in particular, its limitations like the inability to localize sources in depth, are not specific to this method but are fundamental limitations of the recording modalities. The minimum norm solution provides the amount of information that is actually present in the data themselves, and is therefore optimally suited to investigate the general resolution and accuracy limits of EEG and MEG measurement configurations. Furthermore, this strongly suggests that the classical minimum norm solution is a valuable method whenever no reliable a priori information about source generators is available, that is, when complex cognitive tasks are employed or when very noisy data (e.g., single-trial data) are analyzed. For that purpose, an efficient and practical implementation of this method will be suggested and illustrated with simulations using a realistic head geometry.
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paper_title: A new method for off-line removal of ocular artifact

paper_content:

Abstract A new off-line procedure for dealing with ocular artifacts in ERP recording is described. The procedure (EMPC) uses EOG and EEG records for individual trials in an experimental session to estimate a propagation factor which describes the relationship between the EOG and EEG traces. The propagation factor is computed after stimulus-linkes variability in both traces has been removed. Different propagation factors are computed for blinks and eye movements. Tests are presented which demonstrate the validity and reliability of the procedure. ERPs derived from trials corrected by EMCP are more similar to a ‘true’ ERP than are ERPs derived from either uncorrected or randomly corrected trials. The procedure also reduces the difference between ERPs which are based on trials with different degrees of EOG variance. Furthermore, variability at each time point, across trials, is reduced following correction. The propagation factor decreases from frontal to parietal electrodes, and is larger for saccades than blinks. It is more consistent within experimental sessions than between sessions. The major advantage of the procedure is that it permits retention of all trials in an ERP experiment, irrespective of ocular artifact. Thus, studies of populations characterized by a high degree of artifact, and those requiring eye movements as part of the experimental task, are made possible. Furthermore, there is no need to require subjects to restrict eye movement activity. In comparison to procedures suggested by others, EMCP also has the advantage that separate correction factors are computed for blinks and movements and that these factors are based on data from the experimental session itself rather than from a separate calibration session.
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paper_title: The polar average reference effect: a bias in estimating the head surface integral in EEG recording

paper_content:

A reference-independent measure of potential is helpful for studying the multichannel EEG. The potentials integrated over the surface of the body is a constant, i.e. inactive across time, regardless of the activity and distribution of brain electric sources. Therefore, the average reference, the mean of all recording channels at each time point, may be used to approximate an inactive reference. However, this approximation is valid only with accurate spatial sampling of the scalp fields. Accurate sampling requires a sufficient electrode density and full coverage of the head’s surface. If electrodes are concentrated in one region of the surface, such as just on the scalp, then the average is biased toward that region. Differences from the average will then be smaller in the center of the region, e.g. the vertex, than at the periphery. In this paper, we illustrate how this polar average reference effect (PARE) may be created by both the inadequate density and the uneven distribution of EEG electrodes. The greater the coverage of the surface of the volume conductor, the more the average reference approaches the ideal inactive reference. q 1999 Elsevier Science Ireland Ltd. All rights reserved.
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paper_title: Statistical control of artifacts in dense array EEG/MEG studies

paper_content:

With the advent of dense sensor arrays (64-256 channels) in electroencephalography and magnetoencephalography studies, the probability increases that some recording channels are contaminated by artifact. If all channels are required to be artifact free, the number of acceptable trials may be unacceptably low. Precise artifact screening is necessary for accurate spatial mapping, for current density measures, for source analysis, and for accurate temporal analysis based on single-trial methods. Precise screening presents a number of problems given the large datasets. We propose a procedure for statistical correction of artifacts in dense array studies (SCADS), which (1) detects individual channel artifacts using the recording reference, (2) detects global artifacts using the average reference, (3) replaces artifact-contaminated sensors with spherical interpolation statistically weighted on the basis of all sensors, and (4) computes the variance of the signal across trials to document the stability of the averaged waveform. Examples from 128-channel recordings and from numerical simulations illustrate the importance of careful artifact review in the avoidance of analysis errors.
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paper_title: Interpreting magnetic fields of the brain: minimum norm estimates

paper_content:

The authors have applied estimation theory to the problem of determining primary current distributions from measured neuromagnetic fields. In this procedure, essentially nothing is assumed about the source currents, except that they are spatially restricted to a certain region. Simulation experiments show that the results can describe the structure of the current flow fairly well. By increasing the number of measurements, the estimate can be made more localised. The current distributions may be also used as an interpolation and an extrapolation for the measured field patterns.
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paper_title: Electromagnetic brain mapping

paper_content:

There has been tremendous advances in our ability to produce images of human brain function. Applications of functional brain imaging extend from improving our understanding of the basic mechanisms of cognitive processes to better characterization of pathologies that impair normal function. Magnetoencephalography (MEG) and electroencephalography (EEG) (MEG/EEG) localize neural electrical activity using noninvasive measurements of external electromagnetic signals. Among the available functional imaging techniques, MEG and EEG uniquely have temporal resolutions below 100 ms. This temporal precision allows us to explore the timing of basic neural processes at the level of cell assemblies. MEG/EEG source localization draws on a wide range of signal processing techniques including digital filtering, three-dimensional image analysis, array signal processing, image modeling and reconstruction, and, blind source separation and phase synchrony estimation. We describe the underlying models currently used in MEG/EEG source estimation and describe the various signal processing steps required to compute these sources. In particular we describe methods for computing the forward fields for known source distributions and parametric and imaging-based approaches to the inverse problem.
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paper_title: Keep it simple: a case for using classical minimum norm estimation in the analysis of EEG and MEG data

paper_content:

The present study aims at finding the optimal inverse solution for the bioelectromagnetic inverse problem in the absence of reliable a priori information about the generating sources. Three approaches to tackle this problem are compared theoretically: the maximum-likelihood approach, the minimum norm approach, and the resolution optimization approach. It is shown that in all three of these frameworks, it is possible to make use of the same kind of a priori information if available, and the same solutions are obtained if the same a priori information is implemented. In particular, they all yield the minimum norm pseudoinverse (MNP) in the complete absence of such information. This indicates that the properties of the MNP, and in particular, its limitations like the inability to localize sources in depth, are not specific to this method but are fundamental limitations of the recording modalities. The minimum norm solution provides the amount of information that is actually present in the data themselves, and is therefore optimally suited to investigate the general resolution and accuracy limits of EEG and MEG measurement configurations. Furthermore, this strongly suggests that the classical minimum norm solution is a valuable method whenever no reliable a priori information about source generators is available, that is, when complex cognitive tasks are employed or when very noisy data (e.g., single-trial data) are analyzed. For that purpose, an efficient and practical implementation of this method will be suggested and illustrated with simulations using a realistic head geometry.
---
paper_title: Mapping EEG-potentials on the surface of the brain: A strategy for uncovering cortical sources

paper_content:

This paper describes a uniform method for calculating the interpolation of scalp EEG potential distribution, the current source density (CSD), the cortical potential distribution (cortical mapping) and the CSD of the cortical potential distribution. It will be shown that interpolation and deblurring methods such as CSD or cortical mapping are not independent of the inverse problem in potential theory. Not only the resolution but also the accuracy of these techniques, especially those of deblurring, depend greatly on the spatial sampling rate (i.e., the number of electrodes). Using examples from simulated and real (64 channels) data it can be shown that the application of more than 100 EEG channels is not only favourable but necessary to guarantee a reasonable accuracy in the calculations of CSD or cortical mapping. Likewise, it can be shown that using more than 250 electrodes does not improve the resolution.
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paper_title: EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis

paper_content:

We have developed a toolbox and graphic user interface, EEGLAB, running under the cross-platform MATLAB environment (The Mathworks, Inc.) for processing collections of single-trial and/or averaged EEG data of any number of channels. Available functions include EEG data, channel and event information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multi-trial ERP-image plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), Independent Component Analysis (ICA) and time/frequency decompositions including channel and component cross-coherence supported by bootstrap statistical methods based on data resampling. EEGLAB functions are organized into three layers. Top-layer functions allow users to interact with the data through the graphic interface without needing to use MATLAB syntax. Menu options allow users to tune the behavior of EEGLAB to available memory. Middle-layer functions allow users to customize data processing using command history and interactive 'pop' functions. Experienced MATLAB users can use EEGLAB data structures and stand-alone signal processing functions to write custom and/or batch analysis scripts. Extensive function help and tutorial information are included. A 'plug-in' facility allows easy incorporation of new EEG modules into the main menu. EEGLAB is freely available (http://www.sccn.ucsd.edu/eeglab/) under the GNU public license for noncommercial use and open source development, together with sample data, user tutorial and extensive documentation.
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paper_title: Oscillatory γ-Band (30–70 Hz) Activity Induced by a Visual Search Task in Humans

paper_content:

The coherent representation of an object in the visual system has been suggested to be achieved by the synchronization in the γ-band (30–70 Hz) of a distributed neuronal assembly. Here we measure variations of high-frequency activity on the human scalp. The experiment is designed to allow the comparison of two different perceptions of the same picture. In the first condition, an apparently meaningless picture that contained a hidden Dalmatian, a neutral stimulus, and a target stimulus (twirled blobs) are presented. After the subject has been trained to perceive the hidden dog and its mirror image, the second part of the recordings is performed (condition 2). The same neutral stimulus is presented, intermixed with the picture of the dog and its mirror image (target stimulus). Early (95 msec) phase-locked (or stimulus-locked) γ-band oscillations do not vary with stimulus type but can be subdivided into an anterior component (38 Hz) and a posterior component (35 Hz). Non-phase-locked γ-band oscillations appear with a latency jitter around 280 msec after stimulus onset and disappear in averaged data. They increase in amplitude in response to both target stimuli. They also globally increase in the second condition compared with the first one. It is suggested that this γ-band energy increase reflects both bottom-up (binding of elementary features) and top-down (search for the hidden dog) activation of the same neural assembly coding for the Dalmatian. The relationships between high- and low-frequency components of the response are discussed, and a possible functional role of each component is suggested.
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paper_title: Difference formulas for the surface Laplacian on a triangulated surface

paper_content:

Abstract Different approximating expressions for the surface Laplacian operator on a triangulated surface are derived. They are evaluated on a triangulated spherical surface for which the analytical expression of the surface Laplacian is known. It is shown that in order to obtain accurate results, due care has to be taken of irregularities present in the triangulation grid. If this is done, the approximation will equal the performance of an expression based on least squares which can be derived. Next the different approximations obtained are used as a regularization operator in the solution of an ill-posed inverse problem in electrical volume conduction. It is shown that in this application a crude approximation to the surface Laplacian suffices.
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paper_title: Spherical splines for scalp potential and current density mapping

paper_content:

Abstract Description of mapping methods using spherical splines, both to interpolate scalp potentials (SPs), and to approximate scalp current densities (SCDs). Compared to a previously published method using thin plate splines, the advantages are a very simple derivation of the SCD approximation, faster computing times, and greater accuracy in areas with few electrodes.
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paper_title: EEG oscillations and wavelet analysis

paper_content:

Electroencephalographic recordings are analyzed in an event-related fashion when we want to gain insights into the relation of the electroencephalogram (EEG) and experimental events. The standard analysis method is to focus on event-related potentials (ERPs) by averaging. However, another approach is to concentrate on eventrelated oscillations (EROs). This chapter will introduce the notion of EEG oscillations and a method suited to analyze the temporal and spatial characteristics of EROs at the same time, namely the wavelet analysis. At first an introduction to oscillatory EEG activity will be given, followed by details of the wavelet analysis. Some general prerequisites of recording EROs will be reviewed and finally, recently introduced wavelet-based methods for studying dynamical interrelations between brain signals will be discussed.
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paper_title: Mapping EEG-potentials on the surface of the brain: A strategy for uncovering cortical sources

paper_content:

This paper describes a uniform method for calculating the interpolation of scalp EEG potential distribution, the current source density (CSD), the cortical potential distribution (cortical mapping) and the CSD of the cortical potential distribution. It will be shown that interpolation and deblurring methods such as CSD or cortical mapping are not independent of the inverse problem in potential theory. Not only the resolution but also the accuracy of these techniques, especially those of deblurring, depend greatly on the spatial sampling rate (i.e., the number of electrodes). Using examples from simulated and real (64 channels) data it can be shown that the application of more than 100 EEG channels is not only favourable but necessary to guarantee a reasonable accuracy in the calculations of CSD or cortical mapping. Likewise, it can be shown that using more than 250 electrodes does not improve the resolution.
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paper_title: Event-Related EEG Time-Frequency Analysis: An Overview of Measures and An Analysis of Early Gamma Band Phase Locking in Schizophrenia

paper_content:

An increasing number of schizophrenia studies have been examining electroencephalography (EEG) data using time-frequency analysis, documenting illness-related abnormalities in neuronal oscillations and their synchronization, particularly in the gamma band. In this article, we review common methods of spectral decomposition of EEG, time-frequency analyses, types of measures that separately quantify magnitude and phase information from the EEG, and the influence of parameter choices on the analysis results. We then compare the degree of phase locking (ie, phase-locking factor) of the gamma band (36–50 Hz) response evoked about 50 milliseconds following the presentation of standard tones in 22 healthy controls and 21 medicated patients with schizophrenia. These tones were presented as part of an auditory oddball task performed by subjects while EEG was recorded from their scalps. The results showed prominent gamma band phase locking at frontal electrodes between 20 and 60 milliseconds following tone onset in healthy controls that was significantly reduced in patients with schizophrenia (P 5 .03). The finding suggests that the early-evoked gamma band response to auditory stimuli is deficiently synchronized in schizophrenia. We discuss the results in terms of pathophysiological mechanisms compromising event-related gamma phase synchrony in schizophrenia and further attempt to reconcile this finding with prior studies that failed to find this effect.
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paper_title: The polar average reference effect: a bias in estimating the head surface integral in EEG recording

paper_content:

A reference-independent measure of potential is helpful for studying the multichannel EEG. The potentials integrated over the surface of the body is a constant, i.e. inactive across time, regardless of the activity and distribution of brain electric sources. Therefore, the average reference, the mean of all recording channels at each time point, may be used to approximate an inactive reference. However, this approximation is valid only with accurate spatial sampling of the scalp fields. Accurate sampling requires a sufficient electrode density and full coverage of the head’s surface. If electrodes are concentrated in one region of the surface, such as just on the scalp, then the average is biased toward that region. Differences from the average will then be smaller in the center of the region, e.g. the vertex, than at the periphery. In this paper, we illustrate how this polar average reference effect (PARE) may be created by both the inadequate density and the uneven distribution of EEG electrodes. The greater the coverage of the surface of the volume conductor, the more the average reference approaches the ideal inactive reference. q 1999 Elsevier Science Ireland Ltd. All rights reserved.
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Title: ElectroMagnetoEncephalography Software: Overview and Integration with Other EEG/MEG Toolboxes

Section 1: Introduction
Description 1: Introduce the EMEGS software, its purpose, and the structure of the paper.

Section 2: Main Field of Software Application
Description 2: Describe the primary applications of EMEGS in academic and research settings, including the distinction between basic and expert modes.

Section 3: Availability, License, and Support
Description 3: Provide details on how to access EMEGS, its licensing under GNU GPL, and the available support and documentation.

Section 4: System Requirements
Description 4: Outline the system requirements for running EMEGS, including necessary software and hardware specifications.

Section 5: Features and Implementation
Description 5: Provide an overview of the features offered by EMEGS and how various tasks are implemented in the software.

Section 6: Preprocessing
Description 6: Detail the preprocessing steps in EMEGS to prepare raw EEG or MEG data for analysis.

Section 7: Artifact Detection and Averaging
Description 7: Explain the process of artifact detection, sensor interpolation, and averaging in EMEGS.

Section 8: Interpolation, Current Source Density, and Source Localization
Description 8: Discuss the methods used in EMEGS for interpolation, current source density calculation, and source localization.

Section 9: Statistical and Exploratory Analysis of Evoked Brain Signals
Description 9: Describe the statistical and exploratory analysis capabilities within EMEGS for analyzing evoked brain signals.

Section 10: Data Display and Visualization
Description 10: Explain the various data visualization tools and techniques provided by EMEGS.

Section 11: Generation of Synthetic Data
Description 11: Discuss how synthetic EEG/MEG data can be generated in EMEGS for educational and testing purposes.

Section 12: Extending EMEGS Capabilities: Exemplified Time Frequency Analysis Using FieldTrip
Description 12: Describe the integration of EMEGS with FieldTrip for time-frequency analysis and how it extends the software’s capabilities.

Section 13: Future Directions
Description 13: Provide insights into the future development plans for EMEGS and potential new features.

Section 14: Conclusion
Description 14: Summarize the key points of the paper and the advantages of using EMEGS for EEG/MEG data analysis.

Section 15: Appendix A - EMEGS Analysis Tutorial
Description 15: Provide brief analysis tutorials to illustrate the EMEGS processing facilities.

Section 16: Appendix B - EMEGS Plug-ins
Description 16: Explain the plug-in facility in EMEGS and how users can create and integrate their own analysis functions.