The influence of skull parameters in a realastically shaped head model on the accuracy of EEG dipole localization

Magnetic resonance imaging (MRI) provides the means for the generation of head models with a high geometrical detail. Errors in the generation of realistically shaped models are likely to be made, due to the identification of the different anatomical structures. The poorly conducting skull layer plays a special role, since it is known to have a large effect on the scalp potentials and is difficult to distinguish in MRI. If source localisation is applied to EEG, then the systematic errors in the parameters of the reconstructed sources are partly due to the misspecifications of the head model. - In this paper, the influence of certain head model parameters on the systematic errors of reconstructed dipole sources is investigated. Variations in the skull conductivity and thickness, as well as local variations in the skull thickness, are considered. In order to do so, the sensitivity measure is introduced, which specifies the amount of change of a dipole parameter due to a specific model variation. Sensitivity maps are constructed for layers of dipoles underneath the brain surface. The maps of dipole sensitivities show the local distribution of the systematic errors to be expected. The computations are performed by means of a derivative method, which utilizes a linearization of the forward problem

A validation study for a consumer-grade auditory-visual stimulation device

Self-care and improving one’s well-being has been growing rapidly in recent years for manifold reasons (e.g. higher workload, corona pandemic). Consumer-grade noninvasive stimulation devices are therefore on the rise to counteract the occurrence of mood disorders and burn-out symptoms. Here, we aim at investigating the impact of dynamically varying auditory-visual stimulation patterns on neural entrainment patterns and resonance phenomena. Twenty-two healthy volunteers (11 female, 25.4 ± 5.1 years, one dropout, seven in control group) participated in the study. EEG data (64 channel; equidistant layout) were acquired preand during stimulation for each volunteer. Visual and auditory stimuli were presented via a headset (ATUM, Neuro- Bright; https://www.neurobright.co.uk/). Presentation patterns (frequency, intensity, spatial distribution) varied within a presentation session but were kept constant across all volunteers. Stimulus intensity was adjusted to individual comfort levels. Individual alpha peak frequencies (iAPF) were calculated via the power spectral density with 50% overlapping 10s epochs from pre-stimulation segments. For both, the study and the control group, a time-frequency representation was calculated for the pre- and during-stimulation segments. From this, power values were determined for different frequency-bands (iAPF, stimulation frequencies and second harmonics of the latter). Statistical analyses focused on contrasting the power values between pre- and during stimulation. Mean iAPF values were 10.25 ± 0.99Hz for the study and 10.63 ± 1.21Hz for the control group respectively. Both, power values at the stimulation frequencies and their second harmonics differed significantly between pre- and during stimulation (p stim =0.001; p harm =0.001) in the study group. No such difference was found for the control group (pstim=0.352; pharm=0.237). Further, neither the study nor the control group showed significant iAPF power differences (p study =0.035; p control =0.352; alpha*=0.008). Our results suggest that lightweight, portable auditory-visual presentation devices represent an effective tool for generating entrainment and resonance effects at home. Further analyses will focus on the investigation of individual differences driving such modulatory effect

A high-density 256-channel cap for dry electroencephalography

High-density electroencephalography (HD-EEG) is currently limited to laboratory environments since state-of-the-art electrode caps require skilled staff and extensive preparation. We propose and evaluate a 256-channel cap with dry multipin electrodes for HD-EEG. We describe the designs of the dry electrodes made from polyurethane and coated with Ag/AgCl. We compare in a study with 30 volunteers the novel dry HD-EEG cap to a conventional gel-based cap for electrode-skin impedances, resting state EEG, and visual evoked potentials (VEP). We perform wearing tests with eight electrodes mimicking cap applications on real human and artificial skin. Average impedances below 900 k[Ohm] for 252 out of 256 dry electrodes enables recording with state-of-the-art EEG amplifiers. For the dry EEG cap, we obtained a channel reliability of 84% and a reduction of the preparation time of 69%. After exclusion of an average of 16% (dry) and 3% (gel-based) bad channels, resting state EEG, alpha activity, and pattern reversal VEP can be recorded with less than 5% significant differences in all compared signal characteristics metrics. Volunteers reported wearing comfort of 3.6 ± 1.5 and 4.0 ± 1.8 for the dry and 2.5 ± 1.0 and 3.0 ± 1.1 for the gel-based cap prior and after the EEG recordings, respectively (scale 1-10). Wearing tests indicated that up to 3,200 applications are possible for the dry electrodes. The 256-channel HD-EEG dry electrode cap overcomes the principal limitations of HD-EEG regarding preparation complexity and allows rapid application by not medically trained persons, enabling new use cases for HD-EEG

Time/space regularization of the inward continuation problem in EEG using the Boundary Element Method

The inward continuation problem in EEG consists in the computation of the cortical potential distribution from the measured potential distribution on the scalp. Although unique this inverse problem is ill-posed. That is, low-level noise in the scalp potential data or a small error in the geometrical data can lead to unbounded errors in the solution. Regularization techniques have to be used to minimize these effects. The inverse problem is solved in two steps. First Tikhonov regularization is applied yielding a solution of the potential on the inside of the skull surface for every timestep. Than the solution of the first step is used for Twomey regularization. At each moment in time a new solution is found by using as a priori estimate the average of the first solution one timestep prior and one timestep after. This combination of spatial (Tikhonov) and temporal (Twomey) regularization improves the solution and smoothes the solution in space and time. Both simulations and the application to EEG data of a Median Nerve stimulation experiment yield encouraging results. Further comparative studies have to be carried out to evaluate the application of time/space regularization of the inward continuation problem in EEG

Spatiotemporal phase slip patterns for visual evoked potentials, covert object naming tasks, and insight moments extracted from 256 channel EEG recordings

Funding Information: A portion of this work was funded by grants from the Landspitali Research Fund and the Icelandic Research Fund (RANNIS), Grant Number: 174236-051, Modeling of Cranial Muscle Artefacts in EEG Data. UG was funded by German Research Foundation, Grant Number: GR 5251/1-1. Publisher Copyright: Copyright © 2023 Ramon, Graichen, Gargiulo, Zanow, Knösche and Haueisen.Phase slips arise from state transitions of the coordinated activity of cortical neurons which can be extracted from the EEG data. The phase slip rates (PSRs) were studied from the high-density (256 channel) EEG data, sampled at 16.384 kHz, of five adult subjects during covert visual object naming tasks. Artifact-free data from 29 trials were averaged for each subject. The analysis was performed to look for phase slips in the theta (4–7 Hz), alpha (7–12 Hz), beta (12–30 Hz), and low gamma (30–49 Hz) bands. The phase was calculated with the Hilbert transform, then unwrapped and detrended to look for phase slip rates in a 1.0 ms wide stepping window with a step size of 0.06 ms. The spatiotemporal plots of the PSRs were made by using a montage layout of 256 equidistant electrode positions. The spatiotemporal profiles of EEG and PSRs during the stimulus and the first second of the post-stimulus period were examined in detail to study the visual evoked potentials and different stages of visual object recognition in the visual, language, and memory areas. It was found that the activity areas of PSRs were different as compared with EEG activity areas during the stimulus and post-stimulus periods. Different stages of the insight moments during the covert object naming tasks were examined from PSRs and it was found to be about 512 ± 21 ms for the ‘Eureka’ moment. Overall, these results indicate that information about the cortical phase transitions can be derived from the measured EEG data and can be used in a complementary fashion to study the cognitive behavior of the brain.Peer reviewe

Proficient brain for optimal performance: the MAP model perspective

Background. The main goal of the present study was to explore theta and alpha event-related desynchronization/synchronization (ERD/ERS) activity during shooting performance. We adopted the idiosyncratic framework of the multi-action plan (MAP) model to investigate different processing modes underpinning four types of performance. In particular, we were interested in examining the neural activity associated with optimal-automated (Type 1) and optimal-controlled (Type 2) performances. Methods. Ten elite shooters (6 male and 4 female) with extensive international experience participated in the study. ERD/ERS analysis was used to investigate cortical dynamics during performance. A 4 × 3 (performance types × time) repeated measures analysis of variance was performed to test the differences among the four types of performance during the three seconds preceding the shots for theta, low alpha, and high alpha frequency bands. The dependent variables were the ERD/ERS percentages in each frequency band (i.e., theta, low alpha, high alpha) for each electrode site across the scalp. This analysis was conducted on 120 shots for each participant in three different frequency bands and the individual data were then averaged. Results. We found ERS to be mainly associated with optimal-automatic performance, in agreement with the “neural efficiency hypothesis.” We also observed more ERD as related to optimal-controlled performance in conditions of “neural adaptability” and proficient use of cortical resources. Discussion. These findings are congruent with the MAP conceptualization of four performance states, in which unique psychophysiological states underlie distinct performance-related experiences. From an applied point of view, our findings suggest that the MAP model can be used as a framework to develop performance enhancement strategies based on cognitive and neurofeedback technique