Head model and electrical source imaging: a study of 38 epileptic patients

Simulation study on high spatio-temporal resolution acousto-electrophysiological neuroimaging

Objective.Acousto-electrophysiological neuroimaging (AENI) is a technique hypothesized to record electrophysiological activity of the brain with millimeter spatial and sub-millisecond temporal resolution. This improvement is obtained by tagging areas with focused ultrasound (fUS). Due to mechanical vibration with respect to the measuring electrodes, the electrical activity of the marked region will be modulated onto the ultrasonic frequency. The region's electrical activity can subsequently be retrieved via demodulation of the measured signal. In this study, the feasibility of this hypothesized technique is tested.Approach.This is done by calculating the forward electroencephalography response under quasi-static assumptions. The head is simplified as a set of concentric spheres. Two sizes are evaluated representing human and mouse brains. Moreover, feasibility is assessed for wet and dry transcranial, and for cortically placed electrodes. The activity sources are modeled by dipoles, with their current intensity profile drawn from a power-law power spectral density.Results.It is shown that mechanical vibration modulates the endogenous activity onto the ultrasonic frequency. The signal strength depends non-linearly on the alignment between dipole orientation, vibration direction and recording point. The strongest signal is measured when these three dependencies are perfectly aligned. The signal strengths are in the pV-range for a dipole moment of 5 nAm and ultrasonic pressures within Food and Drug Administration (FDA)-limits. The endogenous activity can then be accurately reconstructed via demodulation. Two interference types are investigated: vibrational and static. Depending on the vibrational interference, it is shown that millimeter resolution signal detection is possible also for deep brain regions. Subsequently, successful demodulation depends on the static interference, that at MHz-range has to be sub-picovolt.Significance.Our results show that mechanical vibration is a possible underlying mechanism of acousto-electrophyisological neuroimaging. This paper is a first step towards improved understanding of the conditions under which AENI is feasible.

Electromagnetic source imaging predicts surgical outcome in children with focal cortical dysplasia

OBJECTIVE

To evaluate the diagnostic accuracy of electromagnetic source imaging (EMSI) in localizing spikes and predict surgical outcome in children with drug resistant epilepsy (DRE) due to focal cortical dysplasia (FCD).

METHODS

We retrospectively analyzed magnetoencephalography (MEG) and high-density (HD-EEG) data from 23 children with FCD-associated DRE who underwent intracranial EEG and surgery. We localized spikes using equivalent current dipole (ECD) fitting, dipole clustering, and dynamical statistical parametric mapping (dSPM) on EMSI, electric source imaging (ESI), and magnetic source imaging (MSI). We calculated the distance from the seizure onset zone (DSOZ) and resection (DRES). We estimated receiver operating characteristic (ROC) curves with Youden's index (J) to predict outcome.

RESULTS

EMSI presented shorter DSOZ (15.18 ± 9.06 mm) and DRES (8.56 ± 6.24 mm) compared to ESI (DSOZ: 25.04 ± 16.20 mm, p < 0.009; DRES: 18.88 ± 17.30 mm, p < 0.03) and MSI (DSOZ: 23.37 ± 8.98 mm, p < 0.03; DRES: 15.51 ± 10.11 mm, p < 0.02) for clustering in patients with good outcome. Clustering showed shorter DSOZ and DRES compared to ECD fitting and dSPM (p < 0.05). EMSI had higher performance as outcome predictor (J = 70.63%) compared to ESI (J = 41.27%) and MSI (J = 33.33%) for clustering.

CONCLUSIONS

EMSI provides superior localization and improved predictive performance than individual modalities.

SIGNIFICANCE

EMSI can help the surgical planning and facilitate the localization of epileptogenic foci.

Reliable evaluation of functional connectivity and graph theory measures in source-level EEG: How many electrodes are enough?

OBJECTIVE

Using EEG to characterise functional brain networks through graph theory has gained significant interest in clinical and basic research. However, the minimal requirements for reliable measures remain largely unaddressed. Here, we examined functional connectivity estimates and graph theory metrics obtained from EEG with varying electrode densities.

METHODS

EEG was recorded with 128 electrodes in 33 participants. The high-density EEG data were subsequently subsampled into three sparser montages (64, 32, and 19 electrodes). Four inverse solutions, four measures of functional connectivity, and five graph theory metrics were tested.

RESULTS

The correlation between the results obtained with 128-electrode and the subsampled montages decreased as a function of the number of electrodes. As a result of decreased electrode density, the network metrics became skewed: mean network strength and clustering coefficient were overestimated, while characteristic path length was underestimated.

CONCLUSIONS

Several graph theory metrics were altered when electrode density was reduced. Our results suggest that, for optimal balance between resource demand and result precision, a minimum of 64 electrodes should be utilised when graph theory metrics are used to characterise functional brain networks in source-reconstructed EEG data.

SIGNIFICANCE

Characterisation of functional brain networks derived from low-density EEG warrants careful consideration.

Validating EEG source imaging using intracranial electrical stimulation

Electrical source imaging is used in presurgical epilepsy evaluation and in cognitive neurosciences to localize neuronal sources of brain potentials recorded on EEG. This study evaluates the spatial accuracy of electrical source imaging for known sources, using electrical stimulation potentials recorded on simultaneous stereo-EEG and 37-electrode scalp EEG, and identifies factors determining the localization error. In 11 patients undergoing simultaneous stereo-EEG and 37-electrode scalp EEG recordings, sequential series of 99-110 biphasic pulses (2 ms pulse width) were applied by bipolar electrical stimulation on adjacent contacts of implanted stereo-EEG electrodes. The scalp EEG correlates of stimulation potentials were recorded with a sampling rate of 30 kHz. Electrical source imaging of averaged stimulation potentials was calculated utilizing a dipole source model of peak stimulation potentials based on individual four-compartment finite element method head models with various skull conductivities (range from 0.0413 to 0.001 S/m). Fitted dipoles with a goodness of fit of ≥80% were included in the analysis. The localization error was calculated using the Euclidean distance between the estimated dipoles and the centre point of adjacent stimulating contacts. A total of 3619 stimulation locations, respectively, dipole localizations, were included in the evaluation. Mean localization errors ranged from 10.3 to 26 mm, depending on source depth and selected skull conductivity. The mean localization error increased with an increase in source depth (r(3617) = [0.19], P = 0.000) and decreased with an increase in skull conductivity (r(3617) = [-0.26], P = 0.000). High skull conductivities (0.0413-0.0118 S/m) yielded significantly lower localization errors for all source depths. For superficial sources (<20 mm from the inner skull), all skull conductivities yielded insignificantly different localization errors. However, for deeper sources, in particular >40 mm, high skull conductivities of 0.0413 and 0.0206 S/m yielded significantly lower localization errors. In relation to stimulation locations, the majority of estimated dipoles moved outward-forward-downward to inward-forward-downward with a decrease in source depth and an increase in skull conductivity. Multivariate analysis revealed that an increase in source depth, number of skull holes and white matter volume, while a decrease in skull conductivity independently led to higher localization error. This evaluation of electrical source imaging accuracy using artificial patterns with a high signal-to-noise ratio supports its application in presurgical epilepsy evaluation and cognitive neurosciences. In our artificial potential model, optimizing the selected skull conductivity minimized the localization error. Future studies should examine if this accounts for true neural signals.

Electrophysiological correlates of distance and direction processing during cognitive map retrieval: A source analysis

Introduction

The cognitive map is an internal representation of the environment and allows us to navigate through familiar environments. It preserves the distances and directions between landmarks which help us orient ourselves in our surroundings. The aim of our task was to understand the role played by theta waves in the cognitive map and especially how the cognitive map is recalled and how the manipulation of distances and directions occurs within the cognitive map.

Method

In order to investigate the neural correlates of the cognitive map, we used the Cognitive Map Recall Test, in which 33 participants had to estimate distances and directions between familiar landmarks tailored to their own knowledge. We examined the role of theta waves in the cognitive map, as well as the brain regions that generated them. To that aim, we performed electroencephalographic source imaging while focusing on frequency spectral analysis.

Results

We observed increases of theta amplitude in the frontal, temporal, parahippocampal gyri and temporal poles during the recall of the cognitive map. We also found increases of theta amplitude in the temporal pole and retrosplenial cortex during manipulation of directions. Overall, direction processing induces higher theta amplitude than distance processing, especially in the temporal lobe, and higher theta amplitude during recall compared to manipulation, except in the retrosplenial cortex where this pattern was reversed.

Discussion

We reveal the role of theta waves as a marker of directional processing in the retrosplenial cortex and the temporal poles during the manipulation of spatial information. Increases in theta waves in frontal, parahippocampal, temporal and temporal pole regions appear to be markers of working memory and cognitive map recall. Therefore, our Cognitive Map Recall Test could be useful for testing directional difficulties in patients. Our work also shows that there are two distinct parts to the cognitive map test: recall and manipulation of spatial information. This is often considered as two similar processes in the literature, but our work demonstrates that these processes could be different, with theta waves from different brain regions contributing to either recall or manipulation; this should be considered in future studies.

Resting state EEG power spectrum and functional connectivity in autism: a cross-sectional analysis

BACKGROUND

Understanding the development of the neuronal circuitry underlying autism spectrum disorder (ASD) is critical to shed light into its etiology and for the development of treatment options. Resting state EEG provides a window into spontaneous local and long-range neuronal synchronization and has been investigated in many ASD studies, but results are inconsistent. Unbiased investigation in large and comprehensive samples focusing on replicability is needed.

METHODS

We quantified resting state EEG alpha peak metrics, power spectrum (PS, 2-32 Hz) and functional connectivity (FC) in 411 children, adolescents and adults (n = 212 ASD, n = 199 neurotypicals [NT], all with IQ > 75). We performed analyses in source-space using individual head models derived from the participants' MRIs. We tested for differences in mean and variance between the ASD and NT groups for both PS and FC using linear mixed effects models accounting for age, sex, IQ and site effects. Then, we used machine learning to assess whether a multivariate combination of EEG features could better separate ASD and NT participants. All analyses were embedded within a train-validation approach (70%-30% split).

RESULTS

In the training dataset, we found an interaction between age and group for the reactivity to eye opening (p = .042 uncorrected), and a significant but weak multivariate ASD vs. NT classification performance for PS and FC (sensitivity 0.52-0.62, specificity 0.59-0.73). None of these findings replicated significantly in the validation dataset, although the effect size in the validation dataset overlapped with the prediction interval from the training dataset.

LIMITATIONS

The statistical power to detect weak effects-of the magnitude of those found in the training dataset-in the validation dataset is small, and we cannot fully conclude on the reproducibility of the training dataset's effects.

CONCLUSIONS

This suggests that PS and FC values in ASD and NT have a strong overlap, and that differences between both groups (in both mean and variance) have, at best, a small effect size. Larger studies would be needed to investigate and replicate such potential effects.

A Graph Fourier Transform Based Bidirectional Long Short-Term Memory Neural Network for Electrophysiological Source Imaging

Electrophysiological source imaging (ESI) refers to the process of reconstructing underlying activated sources on the cortex given the brain signal measured by Electroencephalography (EEG) or Magnetoencephalography (MEG). Due to the ill-posed nature of ESI, solving ESI requires the design of neurophysiologically plausible regularization or priors to guarantee a unique solution. Recovering focally extended sources is more challenging, and traditionally uses a total variation regularization to promote spatial continuity of the activated sources. In this paper, we propose to use graph Fourier transform (GFT) based bidirectional long-short term memory (BiLSTM) neural network to solve the ESI problem. The GFT delineates the 3D source space into spatially high, medium and low frequency subspaces spanned by corresponding eigenvectors. The low frequency components can naturally serve as a spatially low-band pass filter to reconstruct extended areas of source activation. The BiLSTM is adopted to learn the mapping relationship between the projection of low-frequency graph space and the recorded EEG. Numerical results show the proposed GFT-BiLSTM outperforms other benchmark algorithms in synthetic data under varied signal-to-noise ratios (SNRs). Real data experiments also demonstrate its capability of localizing the epileptogenic zone of epilepsy patients with good accuracy.

Distinct spatio-temporal and spectral brain patterns for different thermal stimuli perception

Understanding the human brain's perception of different thermal sensations has sparked the interest of many neuroscientists. The identification of distinct brain patterns when processing thermal stimuli has several clinical applications, such as phantom-limb pain prediction, as well as increasing the sense of embodiment when interacting with neurorehabilitation devices. Notwithstanding the remarkable number of studies that have touched upon this research topic, understanding how the human brain processes different thermal stimuli has remained elusive. More importantly, very intense thermal stimuli perception dynamics, their related cortical activations, as well as their decoding using effective features are still not fully understood. In this study, using electroencephalography (EEG) recorded from three healthy human subjects, we identified spatial, temporal, and spectral patterns of brain responses to different thermal stimulations ranging from extremely cold and hot stimuli (very intense), moderately cold and hot stimuli (intense), to a warm stimulus (innocuous). Our results show that very intense thermal stimuli elicit a decrease in alpha power compared to intense and innocuous stimulations. Spatio-temporal analysis reveals that in the first 400 ms post-stimulus, brain activity increases in the prefrontal and central brain areas for very intense stimulations, whereas for intense stimulation, high activity of the parietal area was observed post-500 ms. Based on these identified EEG patterns, we successfully classified the different thermal stimulations with an average test accuracy of 84% across all subjects. En route to understanding the underlying cortical activity, we source localized the EEG signal for each of the five thermal stimuli conditions. Our findings reveal that very intense stimuli were anticipated and induced early activation (before 400 ms) of the anterior cingulate cortex (ACC). Moreover, activation of the pre-frontal cortex, somatosensory, central, and parietal areas, was observed in the first 400 ms post-stimulation for very intense conditions and starting 500 ms post-stimuli for intense conditions. Overall, despite the small sample size, this work presents novel findings and a first comprehensive approach to explore, analyze, and classify EEG-brain activity changes evoked by five different thermal stimuli, which could lead to a better understanding of thermal stimuli processing in the brain and could, therefore, pave the way for developing a real-time withdrawal reaction system when interacting with prosthetic limbs. We underpin this last point by benchmarking our EEG results with a demonstration of a real-time withdrawal reaction of a robotic prosthesis using a human-like artificial skin.

EEG source imaging concordance with intracranial EEG and epileptologist review in focal epilepsy

EEG source imaging is becoming widely used for the evaluation of medically refractory focal epilepsy. The validity of EEG source imaging has been established in several studies comparing source imaging to the surgical resection cavity and subsequent seizure freedom. We present a cohort of 87 patients and compare EEG source imaging of both ictal and interictal scalp EEG to the seizure onset zone on intracranial EEG. Concordance of EEG source imaging with intracranial EEG was determined on a sublobar level and was quantified by measuring the distance between the source imaging result and the centroid of the active seizure onset zone electrodes. The EEG source imaging results of a subgroup of 26 patients with high density 76-channel EEG were compared with the localization of three experienced epileptologists. Of 87 patients, 95% had at least one analysis concordant with intracranial EEG and 74% had complete concordance. There was a higher rate of complete concordance in temporal lobe epilepsy compared to extratemporal (89.3 and 62.8%, respectively, P = 0.015). Of the total 282 analyses performed on this cohort, higher concordance was also seen in temporal discharges (95%) compared to extratemporal (77%) (P = 0.0012), but no difference was seen comparing high-density EEG with standard (32-channel) EEG. Subgroup analysis of ictal waveforms showed greater concordance for ictal spiking, compared with rhythmic activity, paroxysmal fast activity, or obscured onset. Median distances from the dipole and maximum distributed source to a centroid of seizure onset zone electrodes were 30.0 and 32.5 mm, respectively, and the median distances from dipole and maximum distributed source to nearest seizure onset zone electrode were 22.8 and 21.7, respectively. There were significantly shorter distances in ictal spiking. There were shorter distances in patients with Engel Class 1 outcome from surgical resection compared to patients with worse outcomes. For the subgroup of 26 high-density EEG patients, EEG source localization had a significantly higher concordance (92% versus 65%), sensitivity (57% versus 35%) and positive predictive value (60% versus 36%) compared with epileptologist localization. Our study demonstrates good concordance between ictal and interictal source imaging and intracranial EEG. Temporal lobe discharges have higher concordance rates than extratemporal discharges. Importantly, this study shows that source imaging has greater agreement with intracranial EEG than visual review alone, supporting its role in surgical planning.

Linear distributed inverse solutions for interictal EEG source localisation

OBJECTIVE

To compare the spatial accuracy of 6 linear distributed inverse solutions for EEG source localisation of interictal epileptic discharges: Minimum Norm, Weighted Minimum Norm, Low-Resolution Electromagnetic Tomography (LORETA), Local Autoregressive Average (LAURA), Standardised LORETA, and Exact LORETA.

METHODS

Spatial accuracy was assessed clinically by retrospectively comparing the maximum source of averaged interictal discharges to the resected brain area in 30 patients with successful epilepsy surgery, based on 204-channel EEG. Additionally, localisation errors of the inverse solutions were assessed in computer simulations, with different levels of noise added to the signal in both sensor space and source space.

RESULTS

In the clinical evaluations, the source maximum was located inside the resected brain area in 50-57% of patients when using LORETA or LAURA, while all other inverse solutions performed significantly worse (17-30%; corrected p < 0.01). In the simulation studies, when noise levels exceeded 10%, LORETA and LAURA had substantially smaller localisation errors than the other inverse solutions.

CONCLUSIONS

LORETA and LAURA provided the highest spatial accuracy both in clinical and simulated data, alongside with a comparably high robustness towards noise.

SIGNIFICANCE

Among the different linear inverse solution algorithms tested, LORETA and LAURA might be preferred for interictal EEG source localisation.

The Influence of the Head Model Conductor on the Source Localization of Auditory Evoked Potentials

The accuracy of EEG source analysis reconstruction improves when a realistic head volume conductor is modeled. In this study we investigated how the progressively more complex head representations influence the spatial localization of auditory-evoked potentials (AEPs). Fourteen young-adult participants with normal hearing performed the AEP task. Individualized head models were obtained from structural MRI and diffusion-weighted imaging scans collected in a separate session. AEPs were elicited by 1 k Hz and 4 k Hz tone bursts during a passive-listening tetanizing paradigm. We compared the amplitude of the N1 and P2 components before and after 4 min of tetanic-stimulation with 1 k Hz sounds. Current density reconstruction values of both components were investigated in the primary auditory cortex and adjacent areas. Furthermore, we compared the signal topography and magnitude obtained with 10 different head models on the EEG forward solution. Starting from the simplest model (scalp, skull, brain), we investigated the influence of modeling the CSF, distinguishing between GM and WM conductors, and including anisotropic WM values. We localized the activity of AEPs within the primary auditory cortex, but not in adjacent areas. The inclusion of the CSF compartment had the strongest influence on the source reconstruction, whereas white matter anisotropy led to a smaller improvement. We conclude that individualized realistic head models provide the best solution for the forward solution when modeling the CSF conductor.

Improving surgical outcome with electric source imaging and high field magnetic resonance imaging

While most patients with focal epilepsy present with clear structural abnormalities on standard, 1.5 or 3 T MRI, some patients are MRI-negative. For those, quantitative MRI techniques, such as volumetry, voxel-based morphometry, and relaxation time measurements can aid in finding the epileptogenic focus. High-field MRI, just recently approved for clinical use by the FDA, increases the resolution and, in several publications, was shown to improve the detection of focal cortical dysplasias and mild cortical malformations. For those cases without any tissue abnormality in neuroimaging, even at 7 T, scalp EEG alone is insufficient to delimitate the epileptogenic zone. They may benefit from the use of high-density EEG, in which the increased number of electrodes helps improve spatial sampling. The spatial resolution of even low-density EEG can benefit from electric source imaging techniques, which map the source of the recorded abnormal activity, such as interictal epileptiform discharges, focal slowing, and ictal rhythm. These EEG techniques help localize the irritative, functional deficit, and seizure-onset zone, to better estimate the epileptogenic zone. Combining those technologies allows several drug-resistant cases to be submitted to surgery, increasing the odds of seizure freedom and providing a must needed hope for patients with epilepsy.

Advances in Electrical Source Imaging: A Review of the Current Approaches, Applications and Challenges

Brain source localization has been consistently implemented over the recent years to elucidate complex brain operations, pairing the high temporal resolution of the EEG with the high spatial estimation of the estimated sources. This review paper aims to present the basic principles of Electrical source imaging (ESI) in the context of the recent progress for solving the forward and the inverse problems, and highlight the advantages and limitations of the different approaches. As such, a synthesis of the current state-of-the-art methodological aspects is provided, offering a complete overview of the present advances with regard to the ESI solutions. Moreover, the new dimensions for the analysis of the brain processes are indicated in terms of clinical and cognitive ESI applications, while the prevailing challenges and limitations are thoroughly discussed, providing insights for future approaches that could help to alleviate methodological and technical shortcomings.

Source imaging of seizure onset predicts surgical outcome in pediatric epilepsy

Objective:

To assess whether ictal electric source imaging (ESI) on low-density scalp EEG can approximate the seizure onset zone (SOZ) location and predict surgical outcome in children with refractory epilepsy undergoing surgery.

Methods:

We examined 35 children with refractory epilepsy. We dichotomized surgical outcome into seizure- and non-seizure-free. We identified ictal onsets recorded with scalp and intracranial EEG and localized them using equivalent current dipoles and standardized low-resolution magnetic tomography (sLORETA). We estimated the localization accuracy of scalp EEG as distance of scalp dipoles from intracranial dipoles. We also calculated the distances of scalp dipoles from resection, as well as their resection percentage and compared between seizure-free and non-seizure-free patients. We built receiver operating characteristic curves to test whether resection percentage predicted outcome.

Results:

Resection distance was lower in seizure-free patients for both dipoles (p = 0.006) and sLORETA (p = 0.04). Resection percentage predicted outcome with a sensitivity of 57.1% (95% CI, 34–78.2%), a specificity of 85.7% (95% CI, 57.2–98.2%) and an accuracy of 68.6% (95% CI, 50.7–83.5%) (p = 0.01).

Conclusion:

Ictal ESI performed on low-density scalp EEG can delineate the SOZ and predict outcome.

Significance:

Such an application may increase the number of children who are referred for epilepsy surgery and improve their outcome.

A review of magnetoencephalography use in pediatric epilepsy: an update on best practice

Introduction: Magnetoencephalography (MEG) is a noninvasive technique that is used for presurgical evaluation of children with drug-resistant epilepsy (DRE).Areas covered: The contributions of MEG for localizing the epileptogenic zone are discussed, in particular in extra-temporal lobe epilepsy and focal cortical dysplasia, which are common in children, as well as in difficult to localize epilepsy such as operculo-insular epilepsy. Further, the authors review current evidence on MEG for mapping eloquent cortex, its performance, application in clinical practice, and potential challenges.Expert opinion: MEG could change the clinical management of children with DRE by directing placement of intracranial electrodes thereby enhancing their yield. With improved identification of a circumscribed epileptogenic zone, MEG could render more patients as suitable candidates for epilepsy surgery and increase utilization of surgery.

Reconfiguration of Electroencephalography Microstate Networks after Breath-Focused, Digital Meditation Training

Sustained attention and working memory were improved in young adults after they engaged in a recently developed, closed-loop, digital meditation practice. Whether this type of meditation also has a sustained effect on dominant resting-state networks is currently unknown. In this study, we examined the resting brain states before and after a period of breath-focused, digital meditation training versus placebo using an electroencephalography (EEG) microstate approach. We found topographical changes in postmeditation rest, compared with baseline rest, selectively for participants who were actively involved in the meditation training and not in participants who engaged with an active, expectancy-match, placebo control paradigm. Our results suggest a reorganization of brain network connectivity after 6 weeks of intensive meditation training in brain areas, mainly including the right insula, the superior temporal gyrus, the superior parietal lobule, and the superior frontal gyrus bilaterally. These findings provide an opening for the development of a novel noninvasive treatment of neuropathological states by low-cost, breath-focused, digital meditation practice, which can be monitored by the EEG microstate approach.

Violence Exposure Is Associated With Atypical Appraisal of Threat Among Women: An EEG Study

Introduction

The present study investigates the association of lifetime interpersonal violence (IPV) exposure, related posttraumatic stress disorder (IPV-PTSD), and appraisal of the degree of threat posed by facial avatars.

Methods

We recorded self-rated responses and high-density electroencephalography (HD-EEG) among women, 16 of whom with lifetime IPV-PTSD and 14 with no PTSD, during a face-evaluation task that displayed male face avatars varying in their degree of threat as rated along dimensions of dominance and trustworthiness.

Results

The study found a significant association between lifetime IPV exposure, under-estimation of dominance, and over-estimation of trustworthiness. Characterization of EEG microstates supported that lifetime IPV-PTSD modulates emotional appraisal, specifically in encoding and decoding processing associated with N170 and LPP evoked potentials. EEG source localization demonstrated an overactivation of the limbic system, in particular the parahippocampal gyrus, in response to non-threatening avatars. Additionally, dysfunctional involvement of attention-related processing anterior prefrontal cortex (aPFC) was found in response to relatively trustworthy avatars in IPV-PTSD individuals compared with non-PTSD controls.

Discussion

This study showed that IPV exposure and related PTSD modulate individuals' evaluation of facial characteristics suggesting threat. Atypical processing of these avatar characteristics was marked by group differences in brain regions linked to facial processing, emotion regulation, and memory.

High-density Electric Source Imaging of interictal epileptic discharges: How many electrodes and which time point?

OBJECTIVE

To assess the value of caudal EEG electrodes over cheeks and neck for high-density electric source imaging (ESI) in presurgical epilepsy evaluation, and to identify the best time point during averaged interictal epileptic discharges (IEDs) for optimal ESI accuracy.

METHODS

We retrospectively examined presurgical 257-channel EEG recordings of 45 patients with pharmacoresistant focal epilepsy. By stepwise removal of cheek and neck electrodes, averaged IEDs were downsampled to 219, 204, and 156 EEG channels. Additionally, ESI at the IED's half-rise was compared to other time points. The respective sources of maximum activity were compared to the resected brain area and postsurgical outcome.

RESULTS

Caudal channels had disproportionately more artefacts. In 30 patients with favourable outcome, the 204-channel array yielded the most accurate results with ESI maxima < 10 mm from the resection in 67% and inside affected sublobes in 83%. Neither in temporal nor in extratemporal cases did the full 257-channel setup improve ESI accuracy. ESI was most accurate at 50% of the IED's rising phase.

CONCLUSION

Information from cheeks and neck electrodes did not improve high-density ESI accuracy, probably due to higher artefact load and suboptimal biophysical modelling.

SIGNIFICANCE

Very caudal EEG electrodes should be used for ESI with caution.

Functional connectivity of the irritative zone identified by electrical source imaging, and EEG-correlated fMRI analyses

•

The irritative zone differs on Electrical Source Imaging (ESI) and EEG-fMRI.

•

Findings differ in functional connectivity and show low temporal correlation.

•

ESI and EEG-fMRI reveal distinct aspects of the irritative zone.

•

The differences may reflect differences in temporal resolution of the techniques.

Objective

The irritative zone - the area generating epileptic spikes - can be studied non-invasively during the interictal period using Electrical Source Imaging (ESI) and simultaneous electroencephalography-functional magnetic resonance imaging (EEG-fMRI). Although the techniques yield results which may overlap spatially, differences in spatial localization of the irritative zone within the same patient are consistently observed. To investigate this discrepancy, we used Blood Oxygenation Level Dependent (BOLD) functional connectivity measures to examine the underlying relationship between ESI and EEG-fMRI findings.

Methods

Fifteen patients (age 20–54), who underwent presurgical epilepsy investigation, were scanned using a single-session resting-state EEG-fMRI protocol. Structural MRI was used to obtain the electrode localisation of a high-density 64-channel EEG cap. Electrical generators of interictal epileptiform discharges were obtained using a distributed local autoregressive average (LAURA) algorithm as implemented in Cartool EEG software. BOLD activations were obtained using both spike-related and voltage-map EEG-fMRI analysis. The global maxima of each method were used to investigate the temporal relationship of BOLD time courses and to assess the spatial similarity using the Dice similarity index between functional connectivity maps.

Results

ESI, voltage-map and spike-related EEG-fMRI methods identified peaks in 15 (100%), 13 (67%) and 8 (53%) of the 15 patients, respectively. For all methods, maxima were localised within the same lobe, but differed in sub-lobar localisation, with a median distance of 22.8 mm between the highest peak for each method. The functional connectivity analysis showed that the temporal correlation between maxima only explained 38% of the variance between the time course of the BOLD response at the maxima. The mean Dice similarity index between seed-voxel functional connectivity maps showed poor spatial agreement.

Significance

Non-invasive methods for the localisation of the irritative zone have distinct spatial and temporal sensitivity to different aspects of the local cortical network involved in the generation of interictal epileptiform discharges.

Ictal EEG source localization in focal epilepsy: Review and future perspectives

Electroencephalographic (EEG) source imaging localizes the generators of neural activity in the brain. During presurgical epilepsy evaluation, EEG source imaging of interictal epileptiform discharges is an established tool to estimate the irritative zone. However, the origin of interictal activity can be partly or fully discordant with the origin of seizures. Therefore, source imaging based on ictal EEG data to determine the seizure onset zone can provide precious clinical information. In this descriptive review, we address the importance of localizing the seizure onset zone based on noninvasive EEG recordings as a complementary analysis that might reduce the burden of the presurgical evaluation. We identify three major challenges (low signal-to-noise ratio of the ictal EEG data, spread of ictal activity in the brain, and validation of the developed methods) and discuss practical solutions. We provide an extensive overview of the existing clinical studies to illustrate the potential clinical utility of EEG-based localization of the seizure onset zone. Finally, we conclude with future perspectives and the needs for translating ictal EEG source imaging into clinical practice.

Error and post-error processing in children with attention-deficit/hyperactivity disorder: An electrical neuroimaging study

OBJECTIVE

Inaccurate and inconsistent response styles in attention-deficit/hyperactivity disorder (ADHD) have been observed in a wide variety of cognitive tasks, in line with regulatory deficit models of ADHD. Event-related potential (ERP) studies of error processing have provided evidence for these models, but are limited in specificity. We aimed to improve the isolation, localization and identification of error (self-monitoring and adaptive control) and post-error (implementation of cognitive control) processing in ADHD.

METHODS

ERPs were obtained for 46 ADHD and 51 typically developing (TD) children using the stop-signal task. Response-locked error (Ne and Pe) and stimulus-locked post-error (N2) components were compared between groups. Ne/Pe were corrected for preceding stimulus overlap and group differences were localized.

RESULTS

Ne was intact, while Pe amplitude was markedly reduced in children with ADHD (ηp² = 0.14). Pe differences were localized in the dorsal posterior/midcingulate (BA31/24) cortex. While the TD group showed increased N2 amplitude in post-error trials (ηp² = 0.24), localized in the left ventrolateral prefrontal cortex (VLPFC) and angular gyrus, the ADHD group did not.

CONCLUSIONS

Self-regulation deficits in ADHD are associated with later stages of error processing and subsequent implementation of cognitive control.

SIGNIFICANCE

We contribute to the literature by further specifying error processing deficits in ADHD.

Connectome spectral analysis to track EEG task dynamics on a subsecond scale

We present an approach for tracking fast spatiotemporal cortical dynamics in which we combine white matter connectivity data with source-projected electroencephalographic (EEG) data. We employ the mathematical framework of graph signal processing in order to derive the Fourier modes of the brain structural connectivity graph, or "network harmonics". These network harmonics are naturally ordered by smoothness. Smoothness in this context can be understood as the amount of variation along the cortex, leading to a multi-scale representation of brain connectivity. We demonstrate that network harmonics provide a sparse representation of the EEG signal, where, at certain times, the smoothest 15 network harmonics capture 90% of the signal power. This suggests that network harmonics are functionally meaningful, which we demonstrate by using them as a basis for the functional EEG data recorded from a face detection task. There, only 13 network harmonics are sufficient to track the large-scale cortical activity during the processing of the stimuli with a 50 ​ms resolution, reproducing well-known activity in the fusiform face area as well as revealing co-activation patterns in somatosensory/motor and frontal cortices that an unconstrained ROI-by-ROI analysis fails to capture. The proposed approach is simple and fast, provides a means of integration of multimodal datasets, and is tied to a theoretical framework in mathematics and physics. Thus, network harmonics point towards promising research directions both theoretically - for example in exploring the relationship between structure and function in the brain - and practically - for example for network tracking in different tasks and groups of individuals, such as patients.

EEG Source Imaging (ESI) utility in clinical practice

Epilepsy surgery is an important treatment modality for medically refractory focal epilepsy. The outcome of surgery usually depends on the localization accuracy of the epileptogenic zone (EZ) during pre-surgical evaluation. Good localization can be achieved with various electrophysiological and neuroimaging approaches. However, each approach has its own merits and limitations. Electroencephalography (EEG) Source Imaging (ESI) is an emerging model-based computational technique to localize cortical sources of electrical activity within the brain volume, three-dimensionally. ESI based pre-surgical evaluation gives an overall clinical yield of 73-91%, depending on choice of head model, inverse solution and EEG electrode density. It is a cost effective, non-invasive method which provides valuable additional information in presurgical evaluation due to its high localizing value specifically in MRI-negative cases, extra or basal temporal lobe epilepsy, multifocal lesions such as tuberous sclerosis or cases with multiple hypotheses. Unfortunately, less than 1% of surgical centers in developing countries use this method as a part of pre-surgical evaluation. This review promotes ESI as a useful clinical tool especially for patients with lesion-negative MRI to determine EZ cost-effectively with high accuracy under the optimized conditions.

Decoding of Pain Perception using EEG Signals for a Real-Time Reflex System in Prostheses: A Case Study

In recent times, we have witnessed a push towards restoring sensory perception to upper-limb amputees, which includes the whole spectrum from gentle touch to noxious stimuli. These are essential components for body protection as well as for restoring the sense of embodiment. Notwithstanding the considerable advances that have been made in designing suitable sensors and restoring tactile perceptions, pain perception dynamics and its decoding using effective bio-markers, are still not fully understood. Here, using electroencephalography (EEG) recordings, we identified and validated a spatio-temporal signature of brain activity during innocuous, moderately more intense, and noxious stimulation of an amputee's phantom limb using transcutaneous nerve stimulation (TENS). Based on the spatio-temporal EEG features, we developed a system for detecting pain perception and reaction in the brain, which successfully classified three different stimulation conditions with a test accuracy of 94.66%, and we investigated the cortical activity in response to sensory stimuli in these conditions. Our findings suggest that the noxious stimulation activates the pre-motor cortex with the highest activation shown in the central cortex (Cz electrode) between 450 ms and 750 ms post-stimulation, whereas the highest activation for the moderately intense stimulation was found in the parietal lobe (P2, P4, and P6 electrodes). Further, we localized the cortical sources and observed early strong activation of the anterior cingulate cortex (ACC) corresponding to the noxious stimulus condition. Moreover, activation of the posterior cingulate cortex (PCC) was observed during the noxious sensation. Overall, although this is a single case study, this work presents a novel approach and a first attempt to analyze and classify neural activity when restoring sensory perception to amputees, which could chart a route ahead for designing a real-time pain reaction system in upper-limb prostheses.

Changing concepts in presurgical assessment for epilepsy surgery

Candidates for epilepsy surgery must undergo presurgical evaluation to establish whether and how surgical treatment can stop seizures without causing neurological deficits. Various techniques, including MRI, PET, single-photon emission CT, video-EEG, magnetoencephalography and invasive EEG, aim to identify the diseased brain tissue and the involved network. Recent technical and methodological developments, encompassing both advances in existing techniques and new combinations of technologies, are enhancing the ability to define the optimal resection strategy. Multimodal interpretation and predictive computer models are expected to aid surgical planning and patient counselling, and multimodal intraoperative guidance is likely to increase surgical precision. In this Review, we discuss how the knowledge derived from these new approaches is challenging our way of thinking about surgery to stop focal seizures. In particular, we highlight the importance of looking beyond the EEG seizure onset zone and considering focal epilepsy as a brain network disease in which long-range connections need to be taken into account. We also explore how new diagnostic techniques are revealing essential information in the brain that was previously hidden from view.

Visual analysis of high density EEG: As good as electrical source imaging?

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Visual analysis of HD-EEG is an excellent tool to explore the epileptogenic focus.

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ESI remains the gold standard for presurgical evaluation of the cortical source.

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ESI at 50% slope/ESI at peak discordance could predict worse surgical outcome.

Objective

In this study, we sought to determine whether visual analysis of high density EEG (HD-EEG) would provide similar localizing information comparable to electrical source imaging (ESI).

Methods

HD-EEG (256 electrodes) recordings from 20 patients suffering from unifocal, drug-resistant epilepsy (13 women, mean age 29.1 ± 2.62 years, 11 with temporal lobe epilepsy) were examined. In the visual analysis condition, we identified the 5 contacts with maximal spike amplitude and determined their localization with respect to the underlying cortex. ESI was computed using the LAURA algorithm of the averaged spikes in the patient’s individual MRI. We considered the localization “correct” if all 5 contacts were concordant with the resection volume underneath or if ESI was located within the resection as determined by the postoperative MRI.

Results

Twelve patients were postoperatively seizure-free (Engel Class IA), while the remaining eight were in class IB to IV. Visual analysis and ESI showed sensitivity of 58% and 75%, specificity of 75% and 87%, and accuracy of 65% and 80%, respectively. In 70% of cases, visual analysis and ESI provided concordant results.

Conclusions

Localization of the electrodes with maximal spike amplitude provides very good estimation of the localization of the underlying source. However, ESI has a higher accuracy and adds 3D information; therefore, it should remain the tool of choice for presurgical evaluation.

Significance

The present study proposes the possibility to analyze HD-EEG visually, in tandem with ESI or alone, if ESI is not accessible.

L-Dopa Modulation of Brain Connectivity in Parkinson's Disease Patients: A Pilot EEG-fMRI Study

Studies of functional neurosurgery and electroencephalography in Parkinson's disease have demonstrated abnormally synchronous activity between basal ganglia and motor cortex. Functional neuroimaging studies investigated brain dysfunction during motor task or resting state and primarily have shown altered patterns of activation and connectivity for motor areas. L-dopa administration relatively normalized these functional alterations. The aim of this pilot study was to examine the effects of L-dopa administration on functional connectivity in early-stage PD, as revealed by simultaneous recording of functional magnetic resonance imaging (fMRI) and electroencephalographic (EEG) data. Six patients with diagnosis of probable PD underwent EEG-fMRI acquisitions (1.5 T MR scanner and 64-channel cap) before and immediately after the intake of L-dopa. Regions of interest in the primary motor and sensorimotor regions were used for resting state fMRI analysis. From the EEG data, weighted partial directed coherence was computed in the inverse space after the removal of gradient and cardioballistic artifacts. fMRI results showed that the intake of L-dopa increased functional connectivity within the sensorimotor network, and between motor areas and both attention and default mode networks. EEG connectivity among regions of the motor network did not change significantly, while regions of the default mode network showed a strong tendency to increase their outflow toward the rest of the brain. This pilot study provided a first insight into the potentiality of simultaneous EEG-fMRI acquisitions in PD patients, showing for both techniques the analogous direction of increased connectivity after L-dopa intake, mainly involving motor, dorsal attention and default mode networks.

Influence of Head Tissue Conductivity Uncertainties on EEG Dipole Reconstruction

Reliable EEG source analysis depends on sufficiently detailed and accurate head models. In this study, we investigate how uncertainties inherent to the experimentally determined conductivity values of the different conductive compartments influence the results of EEG source analysis. In a single source scenario, the superficial and focal somatosensory P20/N20 component, we analyze the influence of varying conductivities on dipole reconstructions using a generalized polynomial chaos (gPC) approach. We find that in particular the conductivity uncertainties for skin and skull have a significant influence on the EEG inverse solution, leading to variations in source localization by several centimeters. The conductivity uncertainties for gray and white matter were found to have little influence on the source localization, but a strong influence on the strength and orientation of the reconstructed source, respectively. As the CSF conductivity is most accurately determined of all conductivities in a realistic head model, CSF conductivity uncertainties had a negligible influence on the source reconstruction. This small uncertainty is a further benefit of distinguishing the CSF in realistic volume conductor models.

The human sensorimotor cortex fosters muscle synergies through cortico-synergy coherence

In neuromotor control, the dimensionality of complex muscular activation patterns is effectively reduced through the emergence of muscle synergies. Muscle synergies are tailored to task-specific biomechanical needs. Traditionally, they are considered as low-dimensional neural output of the spinal cord and as such their coherent cortico-muscular pathways have remained underexplored in humans. We investigated whether muscle synergies have a higher-order origin, especially, whether they are manifest in the cortical motor network. We focused on cortical muscle synergy representations involved in balance control and examined changes in cortico-synergy coherence accompanying short-term balance training. We acquired electromyography and electro-encephalography and reconstructed cortical source activity using adaptive spatial filters. The latter were based on three muscle synergies decomposed from the activity of nine unilateral leg muscles using non-negative matrix factorization. The corresponding cortico-synergy coherence displayed phase-locked activity at the Piper rhythm, i.e., cortico-spinal synchronization around 40 Hz. Our study revealed the presence of muscle synergies in the motor cortex, in particular, in the paracentral lobule, known for the representation of lower extremities. We conclude that neural oscillations synchronize between the motor cortex and spinal motor neuron pools signifying muscle synergies. The corresponding cortico-synergy coherence around the Piper rhythm decreases with training-induced balance improvement.

Variation in Reported Human Head Tissue Electrical Conductivity Values

Electromagnetic source characterisation requires accurate volume conductor models representing head geometry and the electrical conductivity field. Head tissue conductivity is often assumed from previous literature, however, despite extensive research, measurements are inconsistent. A meta-analysis of reported human head electrical conductivity values was therefore conducted to determine significant variation and subsequent influential factors. Of 3121 identified publications spanning three databases, 56 papers were included in data extraction. Conductivity values were categorised according to tissue type, and recorded alongside methodology, measurement condition, current frequency, tissue temperature, participant pathology and age. We found variation in electrical conductivity of the whole-skull, the spongiform layer of the skull, isotropic, perpendicularly- and parallelly-oriented white matter (WM) and the brain-to-skull-conductivity ratio (BSCR) could be significantly attributed to a combination of differences in methodology and demographics. This large variation should be acknowledged, and care should be taken when creating volume conductor models, ideally constructing them on an individual basis, rather than assuming them from the literature. When personalised models are unavailable, it is suggested weighted average means from the current meta-analysis are used. Assigning conductivity as: 0.41 S/m for the scalp, 0.02 S/m for the whole skull, or when better modelled as a three-layer skull 0.048 S/m for the spongiform layer, 0.007 S/m for the inner compact and 0.005 S/m for the outer compact, as well as 1.71 S/m for the CSF, 0.47 S/m for the grey matter, 0.22 S/m for WM and 50.4 for the BSCR.

EEG Source Imaging: A Practical Review of the Analysis Steps

The electroencephalogram (EEG) is one of the oldest technologies to measure neuronal activity of the human brain. It has its undisputed value in clinical diagnosis, particularly (but not exclusively) in the identification of epilepsy and sleep disorders and in the evaluation of dysfunctions in sensory transmission pathways. With the advancement of digital technologies, the analysis of EEG has moved from pure visual inspection of amplitude and frequency modulations over time to a comprehensive exploration of the temporal and spatial characteristics of the recorded signals. Today, EEG is accepted as a powerful tool to capture brain function with the unique advantage of measuring neuronal processes in the time frame in which these processes occur, namely in the sub-second range. However, it is generally stated that EEG suffers from a poor spatial resolution that makes it difficult to infer to the location of the brain areas generating the neuronal activity measured on the scalp. This statement has challenged a whole community of biomedical engineers to offer solutions to localize more precisely and more reliably the generators of the EEG activity. High-density EEG systems combined with precise information of the head anatomy and sophisticated source localization algorithms now exist that convert the EEG to a true neuroimaging modality. With these tools in hand and with the fact that EEG still remains versatile, inexpensive and portable, electrical neuroimaging has become a widely used technology to study the functions of the pathological and healthy human brain. However, several steps are needed to pass from the recording of the EEG to 3-dimensional images of neuronal activity. This review explains these different steps and illustrates them in a comprehensive analysis pipeline integrated in a stand-alone freely available academic software: Cartool. The information about how the different steps are performed in Cartool is only meant as a suggestion. Other EEG source imaging software may apply similar or different approaches to the different steps.

Electrical Neuroimaging of Music Processing in Pianists With and Without True Absolute Pitch

True absolute pitch (AP), labeling of pitches with semitone precision without a reference, is classically studied using isolated tones. However, AP is acquired and has its function within complex dynamic musical contexts. Here we examined event-related brain responses and underlying cerebral sources to endings of short expressive string quartets, investigating a homogeneous population of young highly trained pianists with half of them possessing true-AP. The pieces ended regularly or contained harmonic transgressions at closure that participants appraised. Given the millisecond precision of ERP analyses, this experimental plan allowed examining whether AP alters music processing at an early perceptual, or later cognitive level, or both, and which cerebral sources underlie differences with non-AP musicians. We also investigated the impact of AP on general auditory cognition. Remarkably, harmonic transgression sensitivity did not differ between AP and non-AP participants, and differences for auditory cognition were only marginal. The key finding of this study is the involvement of a microstate peaking around 60 ms after musical closure, characterizing AP participants. Concurring sources were estimated in secondary auditory areas, comprising the planum temporale, all transgression conditions collapsed. These results suggest that AP is not a panacea to become a proficient musician, but a rare perceptual feature.

Electroencephalography, magnetoencephalography and source localization: their value in epilepsy

PURPOSE OF REVIEW

Source localization of cerebral activity using electroencephalography (EEG) or magnetoencephalography (MEG) can reveal noninvasively the generators of the abnormal signals recorded in epilepsy, such as interictal epileptic discharges (IEDs) and seizures. Here, we review recent progress showcasing the usefulness of these techniques in treating patients with drug-resistant epilepsy.

RECENT FINDINGS

The source localization of IEDs by high-density EEG and MEG has now been proved in large patient cohorts to be accurate and clinically relevant, with positive and negative predictive values rivaling those of structural MRI. Localizing seizure onsets is an emerging technique that seems to perform similarly well to the localization of interictal spikes, although there remain questions regarding the processing of signals for reliable results. The localization of somatosensory cortex using EEG/MEG is well established. The localization of language cortex is less reliable, although progress has been made regarding hemispheric lateralization. Source localization is also able to reveal how epilepsy alters the dynamics of neuronal activity in the large-scale networks that underlie cerebral function.

SUMMARY

Given the high performance of EEG/MEG source localization, these tools should find a place similar to that of established techniques like MRI in the assessment of patients for epilepsy surgery.

Subcortical electrophysiological activity is detectable with high-density EEG source imaging

Subcortical neuronal activity is highly relevant for mediating communication in large-scale brain networks. While electroencephalographic (EEG) recordings provide appropriate temporal resolution and coverage to study whole brain dynamics, the feasibility to detect subcortical signals is a matter of debate. Here, we investigate if scalp EEG can detect and correctly localize signals recorded with intracranial electrodes placed in the centromedial thalamus, and in the nucleus accumbens. Externalization of deep brain stimulation (DBS) electrodes, placed in these regions, provides the unique opportunity to record subcortical activity simultaneously with high-density (256 channel) scalp EEG. In three patients during rest with eyes closed, we found significant correlation between alpha envelopes derived from intracranial and EEG source reconstructed signals. Highest correlation was found for source signals in close proximity to the actual recording sites, given by the DBS electrode locations. Therefore, we present direct evidence that scalp EEG indeed can sense subcortical signals.

Electroencephalography (EEG) allows the measurement of electrical signals associated with brain activity, but it is unclear if EEG can accurately measure subcortical activity. Here, the authors show that source dynamics, reconstructed from scalp EEG, correlate with activity recorded from human thalamus and nucleus accumbens.

Assessing the localization accuracy and clinical utility of electric and magnetic source imaging in children with epilepsy

OBJECTIVE

To evaluate the accuracy and clinical utility of conventional 21-channel EEG (conv-EEG), 72-channel high-density EEG (HD-EEG) and 306-channel MEG in localizing interictal epileptiform discharges (IEDs).

METHODS

Twenty-four children who underwent epilepsy surgery were studied. IEDs on conv-EEG, HD-EEG, MEG and intracranial EEG (iEEG) were localized using equivalent current dipoles and dynamical statistical parametric mapping (dSPM). We compared the localization error (E_Loc) with respect to the ground-truth Irritative Zone (IZ), defined by iEEG sources, between non-invasive modalities and the distance from resection (D_res) between good- (Engel 1) and poor-outcomes. For each patient, we estimated the resection percentage of IED sources and tested whether it predicted outcome.

RESULTS

MEG presented lower E_Loc than HD-EEG and conv-EEG. For all modalities, D_res was shorter in good-outcome than poor-outcome patients, but only the resection percentage of the ground-truth IZ and MEG-IZ predicted surgical outcome.

CONCLUSIONS

MEG localizes the IZ more accurately than conv-EEG and HD-EEG. MSI may help the presurgical evaluation in terms of patient's outcome prediction. The promising clinical value of ESI for both conv-EEG and HD-EEG prompts the use of higher-density EEG-systems to possibly achieve MEG performance.

SIGNIFICANCE

Localizing the IZ non-invasively with MSI/ESI facilitates presurgical evaluation and surgical prognosis assessment.

EEG recording during an emotional face-matching task in children of mothers with interpersonal violence-related posttraumatic stress disorder

The aim of this study was to examine the effects of maternal interpersonal violence-related posttraumatic disorder (IPV-PTSD) on child appraisal of emotion, as measured by high-density electroencephalography (HD-EEG) during an Emotional Face-matching Task (EFMT). We recorded HD-EEG in 47 children of mothers with and without IPV-PTSD during an Emotional Face-matching Task (EFMT). Mothers and children each performed the EFMT. Behavioral results demonstrated that both mothers who were directly exposed to violent events, and their children, presented attentional bias toward negative emotions when processing facial stimuli. EEG findings confirmed differences in emotion appraisal between children of IPV-PTSD mothers and non-PTSD controls at scalp-level and in terms of source localization upon which children of IPV-PTSD mothers demonstrated decreased activation of the right dorsolateral prefrontal cortex (dlPFC) in response to angry and fearful faces as compared to non-PTSD children with respect to the N170 component. Our study, to our knowledge, is the first to show that maternal IPV-PTSD significantly affects a mother's own and her child's neural activity in response to facial expressions of negative emotion. These findings are potentially important to the development and study of effective interventions to interrupt intergenerational cycles of violence and trauma.

Electromagnetic source imaging in presurgical workup of patients with epilepsy: A prospective study

Objective

To determine the diagnostic accuracy and clinical utility of electromagnetic source imaging (EMSI) in presurgical evaluation of patients with epilepsy.

Methods

We prospectively recorded magnetoencephalography (MEG) simultaneously with EEG and performed EMSI, comprising electric source imaging, magnetic source imaging, and analysis of combined MEG-EEG datasets, using 2 different software packages. As reference standard for irritative zone (IZ) and seizure onset zone (SOZ), we used intracranial recordings and for localization accuracy, outcome 1 year after operation.

Results

We included 141 consecutive patients. EMSI showed localized epileptiform discharges in 94 patients (67%). Most of the epileptiform discharge clusters (72%) were identified by both modalities, 15% only by EEG, and 14% only by MEG. Agreement was substantial between inverse solutions and moderate between software packages. EMSI provided new information that changed the management plan in 34% of the patients, and these changes were useful in 80%. Depending on the method, EMSI had a concordance of 53% to 89% with IZ and 35% to 73% with SOZ. Localization accuracy of EMSI was between 44% and 57%, which was not significantly different from MRI (49%–76%) and PET (54%–85%). Combined EMSI achieved significantly higher odds ratio compared to electric source imaging and magnetic source imaging.

Conclusion

EMSI has accuracy similar to established imaging methods and provides clinically useful, new information in 34% of the patients.

Classification of evidence

This study provides Class IV evidence that EMSI had a concordance of 53%–89% and 35%–73% (depending on analysis) for the localization of epileptic focus as compared with intracranial recordings—IZ and SOZ, respectively.

Face and gaze perception in borderline personality disorder: An electrical neuroimaging study

Humans are sensitive to gaze direction from early life, and gaze has social and affective values. Borderline personality disorder (BPD) is a clinical condition characterized by emotional dysregulation and enhanced sensitivity to affective and social cues. In this study we wanted to investigate the temporal-spatial dynamics of spontaneous gaze processing in BPD. We used a 2-back-working-memory task, in which neutral faces with direct and averted gaze were presented. Gaze was used as an emotional modulator of event-related-potentials to faces. High density EEG data were acquired in 19 females with BPD and 19 healthy women, and analyzed with a spatio-temporal microstates analysis approach. Independently of gaze direction, BPD patients showed altered N170 and P200 topographies for neutral faces. Source localization revealed that the anterior cingulate and other prefrontal regions were abnormally activated during the N170 component related to face encoding, while middle temporal deactivations were observed during the P200 component. Post-task affective ratings showed that BPD patients had difficulty to disambiguate neutral gaze. This study provides first evidence for an early neural bias toward neutral faces in BPD independent of gaze direction and also suggests the importance of considering basic aspects of social cognition in identifying biological risk factors of BPD.

Electrical Neuroimaging of Music Processing Reveals Mid-Latency Changes with Level of Musical Expertise

This original research focused on the effect of musical training intensity on cerebral and behavioral processing of complex music using high-density event-related potential (ERP) approaches. Recently we have been able to show progressive changes with training in gray and white matter, and higher order brain functioning using (f)MRI [(functional) Magnetic Resonance Imaging], as well as changes in musical and general cognitive functioning. The current study investigated the same population of non-musicians, amateur pianists and expert pianists using spatio-temporal ERP analysis, by means of microstate analysis, and ERP source imaging. The stimuli consisted of complex musical compositions containing three levels of transgression of musical syntax at closure that participants appraised. ERP waveforms, microstates and underlying brain sources revealed gradual differences according to musical expertise in a 300–500 ms window after the onset of the terminal chords of the pieces. Within this time-window, processing seemed to concern context-based memory updating, indicated by a P3b-like component or microstate for which underlying sources were localized in the right middle temporal gyrus, anterior cingulate and right parahippocampal areas. Given that the 3 expertise groups were carefully matched for demographic factors, these results provide evidence of the progressive impact of training on brain and behavior.

Reproducibility of EEG-MEG fusion source analysis of interictal spikes: Relevance in presurgical evaluation of epilepsy

Fusion of electroencephalography (EEG) and magnetoencephalography (MEG) data using maximum entropy on the mean method (MEM-fusion) takes advantage of the complementarities between EEG and MEG to improve localization accuracy. Simulation studies demonstrated MEM-fusion to be robust especially in noisy conditions such as single spike source localizations (SSSL). Our objective was to assess the reliability of SSSL using MEM-fusion on clinical data. We proposed to cluster SSSL results to find the most reliable and consistent source map from the reconstructed sources, the so-called consensus map. Thirty-four types of interictal epileptic discharges (IEDs) were analyzed from 26 patients with well-defined epileptogenic focus. SSSLs were performed on EEG, MEG, and fusion data and consensus maps were estimated using hierarchical clustering. Qualitative (spike-to-spike reproducibility rate, SSR) and quantitative (localization error and spatial dispersion) assessments were performed using the epileptogenic focus as clinical reference. Fusion SSSL provided significantly better results than EEG or MEG alone. Fusion found at least one cluster concordant with the clinical reference in all cases. This concordant cluster was always the one involving the highest number of spikes. Fusion yielded highest reproducibility (SSR EEG = 55%, MEG = 71%, fusion = 90%) and lowest localization error. Also, using only few channels from either modality (21EEG + 272MEG or 54EEG + 25MEG) was sufficient to reach accurate fusion. MEM-fusion with consensus map approach provides an objective way of finding the most reliable and concordant generators of IEDs. We, therefore, suggest the pertinence of SSSL using MEM-fusion as a valuable clinical tool for presurgical evaluation of epilepsy.