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Abstract: Invasive brain signal recordings generally rely on bioelectrodes implanted on the cortex underneath the dura. Subdural recordings have strong advantages in terms of bandwidth, spatial resolution and signal quality. However, subdural electrodes also have the drawback of compromising the long-term stability of such implants and heighten the risk of infection. Epidurally implanted electrodes might provide a viable alternative to subdural electrodes, offering a compromise between signal quality and invasiveness. Determining the feasibility of epidural electrode implantation for e.g., clinical research, brain–computer interfacing (BCI) and cognitive experiments, requires the characterization of the electrical properties of the dura, and its effect on signal feature detection. In this paper we report measurements of brain signal attenuation by the human dura in vivo. In addition, we use signal detection theory to study how the presence of the dura between the sources and the recording electrodes affects signal power features in motor BCI experiments. For noise levels typical of clinical brain signal recording equipment, we observed no detrimental effects on signal feature detection due to the dura. Subdural recordings were found to be more robust with respect to increased instrumentation noise level as compared to their epidural counterpart nonetheless. Our findings suggest that epidural electrode implantation is a viable alternative to subdural implants from the feature detection viewpoint. [Copyright &y& Elsevier]

Abstract: We investigated how responses of occipital cortex to visual stimuli are modulated by simultaneously presented tactile stimuli. Magnetoencephalography was recorded while subjects performed a simple reaction time task. Presence of a task-irrelevant tactile stimulus leads to faster behavioral responses and earlier and stronger gamma-band synchronization in occipital cortex, irrespective of the relative location of the tactile stimulus. While also other stimulus related responses in occipital cortex were modulated (alpha-band and evoked responses in parieto-occipital region), correlation-analysis revealed induced gamma-band activity to be the best predictor of the faster behavioral response latencies, suggesting a key-role of oscillatory activity for cross-modal integration. [Copyright &y& Elsevier]

Abstract: Language is often perceived together with visual information. This raises the question on how the brain integrates information conveyed in visual and/or linguistic format during spoken language comprehension. In this study we investigated the dynamics of semantic integration of visual and linguistic information by means of time-frequency analysis of the EEG signal. A modified version of the N400 paradigm with either a word or a picture of an object being semantically incongruous with respect to the preceding sentence context was employed. Event-Related Potential (ERP) analysis showed qualitatively similar N400 effects for integration of either word or picture. Time-frequency analysis revealed early specific decreases in alpha and gamma band power for linguistic and visual information respectively. We argue that these reflect a rapid context-based analysis of acoustic (word) or visual (picture) form information. We conclude that although full semantic integration of linguistic and visual information occurs through a common mechanism, early differences in oscillations in specific frequency bands reflect the format of the incoming information and, importantly, an early context-based detection of its congruity with respect to the preceding language context. [Copyright &y& Elsevier]

Abstract: In this paper, we show how ElectroEncephaloGraphic (EEG) and MagnetoEncephaloGraphic (MEG) data can be analyzed statistically using nonparametric techniques. Nonparametric statistical tests offer complete freedom to the user with respect to the test statistic by means of which the experimental conditions are compared. This freedom provides a straightforward way to solve the multiple comparisons problem (MCP) and it allows to incorporate biophysically motivated constraints in the test statistic, which may drastically increase the sensitivity of the statistical test. The paper is written for two audiences: (1) empirical neuroscientists looking for the most appropriate data analysis method, and (2) methodologists interested in the theoretical concepts behind nonparametric statistical tests. For the empirical neuroscientist, a large part of the paper is written in a tutorial-like fashion, enabling neuroscientists to construct their own statistical test, maximizing the sensitivity to the expected effect. And for the methodologist, it is explained why the nonparametric test is formally correct. This means that we formulate a null hypothesis (identical probability distribution in the different experimental conditions) and show that the nonparametric test controls the false alarm rate under this null hypothesis. [Copyright &y& Elsevier]

Objective: We investigated the influence of symmetry assumptions implicit in the derivation and the use of event-related lateralized potentials (ERLs), such as the lateralized readiness potential (LRP). We describe these assumptions and demonstrate several alternative computational methods.Methods: Using analytical methods and forward simulations, we computed the error in the ERL topography that results from deviations in symmetry between homologous brain areas. Based on analytical considerations we show that, for source analysis, the ERL derivation provides no benefits compared to a single subtraction of the two (left-lateralized and right-lateralized) conditions underlying the ERL.Results: Relative errors of 10% in the ERL topography are found if the location of an active region in one hemisphere differs by 10 mm from the symmetric location as compared to the other hemisphere A difference of 30° in orientation results in a relative error of the ERL of 40%. Differences in source strength between hemispheres result in an ERL error that is half the size of the relative strength difference.Conclusions: We estimate that, due to violations of the symmetry assumption underlying the ERL, errors in the ERL topography of 10–40% can be expected. Source analysis does not benefit from the ERL. In topographic mapping and source analysis, the double subtraction of the ERL should be approached with caution and the single subtraction of the ERPs of two lateralized conditions should be first analyzed whenever possible. We suggest that analyses based on the topography of the ERL should only be performed after the assumption of symmetry has been validated. [Copyright &y& Elsevier]

• We tested a 3D scanner as an affordable and fast electrode digitizer. • The accuracy of the 3D scanned electrode positions is higher than template positions. • EEG source models improve with 3D scanned electrode positions. In this study, we evaluated the use of a structured-light 3D scanner for EEG electrode digitization. We tested its accuracy, robustness and evaluated its practical feasibility. Furthermore, we assessed how 3D scanning of EEG electrode positions affects the accuracy of EEG volume conduction models and source localization. To assess the improvement in electrode positions and source results, we compared the electrode positions both at the scalp level and by quantifying source model accuracy between the 3D scanner, generic template, and cap-specific electrode positions. The use of the 3D scanner significantly improves the accuracy of EEG electrode positions to a median error of 9.4 mm and maximal error of 32.8 mm, relative to the custom (median error of 10.9 mm, maximal error 39.1 mm) and manufacturer's template positions (median error of 13.8 mm, maximal error 57.0 mm). The relative difference measure (RDM) of the EEG source model averaged over the brain improves from 0.18 to 0.11. The dipole localization error averaged over the brain improves from 11.4 mm to 7.0 mm. A structured-light 3D scanner improves the electrode position accuracy and thereby the EEG source model accuracy. It is more affordable than systems currently used for this, and allows for robust and fast digitization. Therefore, we consider it a cost and time-efficient way to improve EEG source reconstruction. [ABSTRACT FROM AUTHOR]

• An IFCN Workgroup supplies recommendations on EEG frequency and topographical analysis for research. • EEG recording, visualization, and extraction/interpretation best features are proposed. • Pros and cons for clinical research of those features are discussed in light of controversies. In 1999, the International Federation of Clinical Neurophysiology (IFCN) published "IFCN Guidelines for topographic and frequency analysis of EEGs and EPs" (Nuwer et al., 1999). Here a Workgroup of IFCN experts presents unanimous recommendations on the following procedures relevant for the topographic and frequency analysis of resting state EEGs (rsEEGs) in clinical research defined as neurophysiological experimental studies carried out in neurological and psychiatric patients: (1) recording of rsEEGs (environmental conditions and instructions to participants; montage of the EEG electrodes; recording settings); (2) digital storage of rsEEG and control data; (3) computerized visualization of rsEEGs and control data (identification of artifacts and neuropathological rsEEG waveforms); (4) extraction of "synchronization" features based on frequency analysis (band-pass filtering and computation of rsEEG amplitude/power density spectrum); (5) extraction of "connectivity" features based on frequency analysis (linear and nonlinear measures); (6) extraction of "topographic" features (topographic mapping; cortical source mapping; estimation of scalp current density and dura surface potential; cortical connectivity mapping), and (7) statistical analysis and neurophysiological interpretation of those rsEEG features. As core outcomes, the IFCN Workgroup endorsed the use of the most promising "synchronization" and "connectivity" features for clinical research, carefully considering the limitations discussed in this paper. The Workgroup also encourages more experimental (i.e. simulation studies) and clinical research within international initiatives (i.e., shared software platforms and databases) facing the open controversies about electrode montages and linear vs. nonlinear and electrode vs. source levels of those analyses. [ABSTRACT FROM AUTHOR]

Abstract: Objective: Investigate the effectiveness and frequency dependence of central drive transmission via the α-motoneuron pool to the muscle. Methods: We describe a model for the simulation of α-motoneuron firing and the EMG signal as response to central drive input. The transfer in the frequency domain is investigated. Coherence between stochastical central input and EMG is also evaluated. Results: The transmission of central rhythmicities to the EMG signal relates to the spectral content of the latter. Coherence between central input to the α-motoneuron pool and the EMG signal is significant whereby the coupling strength hardly depends on the frequency in a range from 1 to 100Hz. Common central input to pairs of α-motoneurons strongly increases the coherence levels. The often-used rectification of the EMG signal introduces a clear frequency dependence. Conclusions: Oscillatory phenomena are strongly transmitted via the α-motoneuron pool. The motoneuron firing frequencies do play a role in the transmission gain, but do not influence the coherence levels. Rectification of the EMG signal enhances the transmission gain, but lowers coherence and introduces a strong frequency dependency. We think that it should be avoided. Significance: Our findings show that rhythmicities are translated into α-motoneuron activity without strong non-linearities. [ABSTRACT FROM AUTHOR]

Abstract: We used simultaneously recorded EEG and fMRI to investigate in which areas the BOLD signal correlates with frontal theta power changes, while subjects were quietly lying resting in the scanner with their eyes open. To obtain a reliable estimate of frontal theta power we applied ICA on band-pass filtered (2–9 Hz) EEG data. For each subject we selected the component that best matched the mid-frontal scalp topography associated with the frontal theta rhythm. We applied a time-frequency analysis on this component and used the time course of the frequency bin with the highest overall power to form a regressor that modeled spontaneous fluctuations in frontal theta power. No significant positive BOLD correlations with this regressor were observed. Extensive negative correlations were observed in the areas that together form the default mode network. We conclude that frontal theta activity can be seen as an EEG index of default mode network activity. [Copyright &y& Elsevier]

To understand spatial summation of pain processing in the brain, we investigated the cerebral evoked responses to non-painful and painful contact heat stimulation (70 °C/s fast onset; intensity 2,4,6, corresponding to the individual''s non-, slight and moderate pain) comparing one (1s) vs. two spots (2s) in 11 subjects while electroencephalographic signals were recorded. Significant spatial summation effects were shown only for the pain levels. For moderate pain, global field power examination isolated two peak activations for the vertex (Cz) N550 and P750 components. The single dipole modelling identified as likely the supplementary motor area, SMA area-6 source for N550, and posterior cingulate area-23 for P750. These source components showed a significantly faster (41.2 ms) latency and a shift in location from dorsal to ventral SMA of N550 toward cingulate area-31 between the 1s and 2s conditions. The temporal and spatial shift during spatial summation may reflect speeding up of the limbic affective reaction and prefrontal cognitive preparation in impending aversion and is deemed essential for integration of bodily sensations, such as pain. [Copyright &y& Elsevier]