Patrick Berg

Guidelines for using human event-related potentials to study cognition: recording standards and publication criteria.

Event-related potentials (ERPs) recorded from the human scalp can provide important information about how the human brain normally processes information and about how this processing may go awry in neurological or psychiatric disorders. Scientists using or studying ERPs must strive to overcome the many technical problems that can occur in the recording and analysis of these potentials. The methods and the results of these ERP studies must be published in a way that allows other scientists to understand exactly what was done so that they can, if necessary, replicate the experiments. The data must then be analyzed and presented in a way that allows different studies to be compared readily. This paper presents guidelines for recording ERPs and criteria for publishing the results.

Artifact correction of the ongoing EEG using spatial filters based on artifact and brain signal topographies.

Summary Review and analysis of continuous EEG recordings may be impeded by physiological artifacts such as blinks, eye movements, or cardiac activity. Spatial filters based on artifact and brain signal topographies can remove artifacts completely without distortion of relevant brain activity. The authors describe the basic principle of artifact correction by spatial filtering and they review different approaches to estimate artifact and brain signal topographies. The main focus is on the preselection approach, which is fast enough to be applied while paging through the segments of a digital EEG recording. Examples of real EEG segments, containing epileptic seizure activity or interictal spikes contaminated by artifacts, show that spatial filtering by preselection can be a useful tool during EEG review. Advantages and disadvantages of the different spatial filter approaches are discussed.

BESA Source Coherence: A New Method to Study Cortical Oscillatory Coupling

This paper introduces source coherence, a new method for the analysis of cortical coherence using noninvasive EEG and MEG data. Brain electrical source analysis (BESA) is applied to create a discrete multiple source model. This model is used as a source montage to transform the recorded data from sensor level into brain source space. This provides source waveforms of the modeled brain regions as a direct measure for their activities on a single trial basis. The source waveforms are transformed into time-frequency space using complex demodulation. Magnitude-squared coherence between the brain sources reveals oscillatory coupling between sources. This procedure allows one to separate the time-frequency content of different brain regions even if their activities severely overlap at the surface. Thus, source coherence overcomes problems of localization and interpretation that are inherent to coherence analysis at sensor level. The principle of source coherence is illustrated using an EEG recording of an error-related negativity as an example. In this experiment the subject performed a visuo-motor task. Source coherence analysis revealed dynamical linking between posterior and central areas within the gamma-band around the time of button press at a post-stimulus latency of 200-300 ms.

Ocular artifacts in EEG and event-related potentials I: Scalp topography

SummaryThe ocular artifacts that contaminate the EEG derive from the potential difference between the cornea and the fundus of the eye. This corneofundal or corneoretinal potential can be considered as an equivalent dipole with its positive pole directed toward the cornea. The cornea shows a steady DC potential of approximately +13 mV relative to the forehead. Blink potentials are caused by the eyelids sliding down over the positively charged cornea. The artifacts from eye-movements result from changes in orientation of the corneo-fundal potential. The scalp-distribution of the ocular artifacts can be described in terms of propagation factors — the fraction of the EOG signal at periocular electrodes that is recorded at a particular scalp location. These factors vary with the location of the scalp electrode. Propagation factors for blinks and upward eye-movements are significantly different.

A fast method for forward computation of multiple-shell spherical head models

Using a combination of 3 suitably located dipoles in a homogeneous sphere, the scalp potential due to a dipole source in a 4-shell spherical head model can be approximated with a high degree of precision and a more than 30-fold increase in computing speed. Magnitudes and locations of the 3 equivalent dipoles can be fitted in a homogeneous sphere to data generated from a source at one location in a 4-shell head model. The resulting parameters are used to compute scalp potentials for sources at other locations and orientations. Residual variance measures showed close agreement between the new approximation and a standard 4-shell computation method. Further tests of the method used scalp data from 500 randomly selected pairs of sources generated by the standard 4-shell computation and fitted using, for forward computations, the new approximation and the single-shell Ary-corrected head model. Errors with the new approximation were marginally larger than with the standard computation, but sources were located within 0.5 mm and 0.6 degrees of the original position in 99% of the fits. 99% error limits for the Ary model were up to 18 mm and 25 degrees and depended on the head model parameters.

Use of prior knowledge in brain electromagnetic source analysis.

SummaryUsing multichannel measurements of EEG and/or MEG, macroscopic source activities can be estimated in the human brain using brain electric source analysis (BESA, Scherg 1990). If a discrete number of brain areas is active, functional brain images which depict the locations and orientations of equivalent dipole sources as well as the dynamics of the local macroscopic currents can be obtained from such data - in principle -without external knowledge. However, given a certain number of sources or ‘neural masses’ (Freeman 1975) which contribute to an event related response (ERP), it can be difficult to find the correct solution due to background noise in the data and distortions from the head model. Prior knowledge based on anatomy and physiology can be useful to constrain spatial or temporal parameters of the model and to define better cost functions for fitting locations and orientations. An analysis of the auditory evoked N100 complex and of the auditory mismatch negativity (MMN) is presented which illustrates the use of spatial constraints. Also, the use of a modified cost function is demonstrated which limits source currents in certain time intervals.

Optimizing principal components analysis of event-related potentials: Matrix type, factor loading weighting, extraction, and rotations

OBJECTIVE Given conflicting recommendations in the literature, this report seeks to present a standard protocol for applying principal components analysis (PCA) to event-related potential (ERP) datasets. METHODS The effects of a covariance versus a correlation matrix, Kaiser normalization vs. covariance loadings, truncated versus unrestricted solutions, and Varimax versus Promax rotations were tested on 100 simulation datasets. Also, whether the effects of these parameters are mediated by component size was examined. RESULTS Parameters were evaluated according to time course reconstruction, source localization results, and misallocation of ANOVA effects. Correlation matrices resulted in dramatic misallocation of variance. The Promax rotation yielded much more accurate results than Varimax rotation. Covariance loadings were inferior to Kaiser Normalization and unweighted loadings. CONCLUSIONS Based on the current simulation of two components, the evidence supports the use of a covariance matrix, Kaiser normalization, and Promax rotation. When these parameters are used, unrestricted solutions did not materially improve the results. We argue against their use. Results also suggest that optimized PCA procedures can measurably improve source localization results. SIGNIFICANCE Continued development of PCA procedures can improve the results when PCA is applied to ERP datasets.

Dipole models of eye movements and blinks

Average EOGs were recorded from 4 subjects for vertical and horizontal eye movements of 15 degrees away from and back to a central fixation point, and for eyeblinks while looking at the fixation point. Using spatio-temporal dipole modelling, several alternative dipole models of the electrical activity of the eyes were compared. A reasonable fit was only obtained if the equivalent dipoles were allowed to take up different locations and orientations depending on the type of eye activity. It appears that (a) the equivalent ocular dipole is located away from the axis of rotation of the eyeball, (b) eyelid movements contribute to a change in location of the dipole in vertical eye movements and blinks, and (c) some of the apparent dipole movement is due to inadequacy of the 3-shell spherical head model near to the eyes. Consequences of the results for eye-artifact correction are discussed.

Advanced tools for digital EEG review: Virtual source montages, whole-head mapping, correlation, and phase analysis

Summary Digital EEG allows one to combine recorded EEG channels into new montages without the need to record new data. Using spherical splines, voltages can be estimated at any point on the head. This allows one to generate various montages with the recorded or virtual electrodes at standardized locations, to interpolate bad electrodes, and to generate topographic maps over the whole head. Simulations of EEG activity originating in various brain regions are used to illustrate the effects of known generators on various montages and on whole-head maps. Some properties of spatial filters are introduced, and it is shown how they can be used to develop source montages with signals that estimate the activity in specific brain regions. The usefulness and validity of a source montage designed to focus on temporal lobe activity is illustrated with simulations and examples of temporal lobe spikes and seizures. Additional tools such as cross-correlation among channels, fast Fourier transform, and phase maps are described. These tools are useful in estimating time lags between source channels and in interpreting propagating spike and seizure activity. In combination, these tools help to analyze and to enhance activities that may be hard to detect from the background scalp EEG in traditional montages.

Ocular artifacts in recording EEGs and event-related potentials. II: Source dipoles and source components.

SummaryThe source dipoles for blinks point radially whereas the source dipoles for saccades point tangentially, in the direction of the eye movement. This indicates that blink potentials are not generated by eye movements but by the eyelid sliding down over the positively charged cornea. Dipole source dipole analysis shows that the “rider artifact” at the onset of upward and lateral saccades is caused by the eyelid as it lags a little behind the eyes at the beginning of the movement. Dipole source analysis allows both the EEG and the EOG to be modeled simultaneously and EOG generators to be distinguished from nearby EEG generators. Ocular source components can be calculated from a principal component analysis of EEG and EOG recordings during blinks and saccades. The effectiveness of propagation factors, source dipoles and source components in removing ocular artifacts from EEG samples was assessed. The most effective correction procedure uses source components.