Resting-state EEG recorded with gel-based vs. consumer dry electrodes: spectral characteristics and across-device correlations.

Introduction: Recordings of electroencephalographic (EEG) rhythms and their analyses have been instrumental in basic neuroscience, clinical diagnostics, and the field of brain-computer interfaces (BCIs). While in the past such measurements have been conducted mostly in laboratory settings, recent advancements in dry electrode technology pave way to a broader range of consumer and medical application because of their greater convenience compared to gel-based electrodes. Methods: Here we conducted resting-state EEG recordings in two groups of healthy participants using three dry-electrode devices, the PSBD Headband, the PSBD Headphones and the Muse Headband, and one standard gel electrode-based system, the NVX. We examined signal quality for various spatial and spectral ranges which are essential for cognitive monitoring and consumer applications. Results: Distinctive characteristics of signal quality were found, with the PSBD Headband showing sensitivity in low-frequency ranges and replicating the modulations of delta, theta and alpha power corresponding to the eyes-open and eyes-closed conditions, and the NVX system performing well in capturing high-frequency oscillations. The PSBD Headphones were more prone to low-frequency artifacts compared to the PSBD Headband, yet recorded modulations in the alpha power and had a strong alignment with the NVX at the higher EEG frequencies. The Muse Headband had several limitations in signal quality. Discussion: We suggest that while dry-electrode technology appears to be appropriate for the EEG rhythm-based applications, the potential benefits of these technologies in terms of ease of use and accessibility should be carefully weighed against the capacity of each given system.

Modulations in high-density EEG during the suppression of phantom-limb pain with neurostimulation in upper limb amputees.

Phantom limb pain (PLP) is a distressing and persistent sensation that occurs after the amputation of a limb. While medication-based treatments have limitations and adverse effects, neurostimulation is a promising alternative approach whose mechanism of action needs research, including electroencephalographic (EEG) recordings for the assessment of cortical manifestation of PLP relieving effects. Here we collected and analyzed high-density EEG data in 3 patients (P01, P02, and P03). Peripheral nerve stimulation suppressed PLP in P01 but was ineffective in P02. In contrast, transcutaneous electrical nerve stimulation was effective in P02. In P03, spinal cord stimulation was used to suppress PLP. Changes in EEG oscillatory components were analyzed using spectral analysis and Petrosian fractal dimension. With these methods, changes in EEG spatio-spectral components were found in the theta, alpha, and beta bands in all patients, with these effects being specific to each individual. The changes in the EEG patterns were found for both the periods when PLP level was stationary and the periods when PLP was gradually changing after neurostimulation was turned on or off. Overall, our findings align with the proposed roles of brain rhythms in thalamocortical dysrhythmia or disruption of cortical excitation and inhibition which has been linked to neuropathic pain. The individual differences in the observed effects could be related to the specifics of each patient's treatment and the unique spectral characteristics in each of them. These findings pave the way to the closed-loop systems for PLP management where neurostimulation parameters are adjusted based on EEG-derived markers.

PSIICOS projection optimality for EEG and MEG based functional coupling detection.

Functional connectivity is crucial for cognitive processes in the healthy brain and serves as a marker for a range of neuropathological conditions. Non-invasive exploration of functional coupling using temporally resolved techniques such as MEG allows for a unique opportunity of exploring this fundamental brain mechanism. The indirect nature of MEG measurements complicates the estimation of functional coupling due to the volume conduction and spatial leakage effects. In the previous work (Ossadtchi et al., 2018), we introduced PSIICOS, a method that for the first time allowed us to suppress the volume conduction effect and yet retain information about functional networks whose nodes are coupled with close to zero or zero mutual phase lag. In this paper, we demonstrate analytically that the PSIICOS projection is optimal in achieving a controllable trade-off between suppressing mutual spatial leakage and retaining information about zero- or close to zero-phase coupled networks. We also derive an alternative solution using the regularization-based inverse of the mutual spatial leakage matrix and show its equivalence to the original PSIICOS. We then discuss how PSIICOS solution to the functional connectivity estimation problem can be incorporated into the conventional source estimation framework. Instead of sources, the unknowns are the elementary dyadic networks and their activation time series are formalized by the corresponding source-space cross-spectral coefficients. This view on connectivity estimation as a regression problem opens up new opportunities for formulating a set of principled estimators based on the rich intuition accumulated in the neuroimaging community.

Opposite effects of rapid auditory stimulation on tetanized and non-tetanized tone of adjacent frequency: Mismatch negativity study.

Our study describes the effects of sensory tetanization on neurophysiological and behavioral measures in humans linking cellular studies of long-term potentiation with high-level brain processes. Rapid (every 75ms) presentation of pure tone (1020 Hz, 50ms) for 2 minutes was preceded and followed by oddball blocks that contained the same stimulus presented as deviant (probability of 5-10%) interspersed with standard (80-90%) and deviant tones (5-10%) of adjacent frequencies (1000 and 980Hz, respectively). Mismatch negativity (MMN) component in response to tetanized tone (1020Hz), while being similar to MMN for non-tetanized tone before tetanization, became larger than that after tetanization, pointing to the increase in cortical differentiation of these tones. However, this differentiation was partially due to the MMN decrease after tetanization for tones adjacent to tetanized frequency, suggesting the influence of lateral inhibition to this effect. Although MMN correlated with tone discriminability in a psychophysical task, the behavioral improvement after tetanization was not statistically detectable. To conclude, short-term auditory tetanization affects cortical representation of tones that are not limited to the tetanized stimuli.

An experimental paradigm for studying EEG correlates of olfactory discrimination.

Electroencephalography (EEG) correlates of olfaction are of fundamental and practical interest for many reasons. In the field of neural technologies, olfactory-based brain-computer interfaces (BCIs) represent an approach that could be useful for neurorehabilitation of anosmia, dysosmia and hyposmia. While the idea of a BCI that decodes neural responses to different odors and/or enables odor-based neurofeedback is appealing, the results of previous EEG investigations into the olfactory domain are rather inconsistent, particularly when non-primary processing of olfactory signals is concerned. Here we developed an experimental paradigm where EEG recordings are conducted while a participant executes an olfaction-based instructed-delay task. We utilized an olfactory display and a sensor of respiration to deliver odors in a strictly controlled fashion. We showed that with this approach spatial and spectral EEG properties could be analyzed to assess neural processing of olfactory stimuli and their conversion into a motor response. We conclude that EEG recordings are suitable for detecting active processing of odors. As such they could be integrated in a BCI that strives to rehabilitate olfactory disabilities or uses odors for hedonistic purposes.

Exoskeleton gait training with spinal cord neuromodulation.

Neuromodulating the locomotor network through spinal cord electrical stimulation (SCES) is effective for restoring function in individuals with gait deficits. However, SCES alone has limited effectiveness without concurrent locomotor function training that enhances activity-dependent plasticity of spinal neuronal networks by sensory feedback. This mini review discusses recent developments in using combined interventions, such as SCES added to exoskeleton gait training (EGT). To develop personalized therapies, it is crucial to assess the state of spinal circuitry through a physiologically relevant approach that identifies individual characteristics of spinal cord function to develop person-specific SCES and EGT. The existing literature suggests that combining SCES and EGT to activate the locomotor network can have a synergistic rehabilitative effect on restoring walking abilities, somatic sensation, and cardiovascular and bladder function in paralyzed individuals.

The global prevalence of autism spectrum disorder: A three-level meta-analysis.

Autism spectrum disorder (ASD) is one the most disabling developmental disorders, imposing an extremely high economic burden. Obtaining as accurate prevalence estimates as possible is crucial to guide governments in planning policies for identification and intervention for individuals with ASD and their relatives. The precision of prevalence estimates can be heightened by summative analyses of the data collected around the world. To that end, we conducted a three-level mixed-effects meta-analysis. A systematic search of the Web of Science, PubMed, EMBASE, and PsycINFO databases from 2000 up to 13 July 2020 was performed, and reference lists of previous reviews and existing databases of prevalence studies were screened. Overall, 79 studies were included in the analysis of ASD and 59-in the analysis of previously existing relevant diagnoses: 30 for Autistic Disorder (AD), 15 for Asperger Syndrome (AS), and 14 for Atypical Autism (AA) and Pervasive Developmental Disorder - Not Otherwise Specified (PDD-NOS); these research reports covered the period from 1994 to 2019. Pooled prevalence estimates were 0.72% (95% CI = 0.61-0.85) for ASD, 0.25% (95% CI = 0.18-0.33) for AD, 0.13% (95% CI = 0.07-0.20) for AS, and 0.18% (95% CI = 0.10-0.28) for the combined group of AA and PDD-NOS. Estimates were higher (1) for the studies that used records-review surveillance rather than other designs; (2) in North America compared with other geographical regions; and (3) in high-income compared with lower-income countries. The highest prevalence estimates were registered in the USA. There was an increase in autism prevalence estimates over time. The prevalence was also significantly higher for children aged between 6 and 12 years compared to children under the age of 5 and over the age of 13 years. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019131525, identifier CRD42019131525.

Data-driven approach for the delineation of the irritative zone in epilepsy in MEG.

The reliable identification of the irritative zone (IZ) is a prerequisite for the correct clinical evaluation of medically refractory patients affected by epilepsy. Given the complexity of MEG data, visual analysis of epileptiform neurophysiological activity is highly time consuming and might leave clinically relevant information undetected. We recorded and analyzed the interictal activity from seven patients affected by epilepsy (Vectorview Neuromag), who successfully underwent epilepsy surgery (Engel > = II). We visually marked and localized characteristic epileptiform activity (VIS). We implemented a two-stage pipeline for the detection of interictal spikes and the delineation of the IZ. First, we detected candidate events from peaky ICA components, and then clustered events around spatio-temporal patterns identified by convolutional sparse coding. We used the average of clustered events to create IZ maps computed at the amplitude peak (PEAK), and at the 50% of the peak ascending slope (SLOPE). We validated our approach by computing the distance of the estimated IZ (VIS, SLOPE and PEAK) from the border of the surgically resected area (RA). We identified 25 spatiotemporal patterns mimicking the underlying interictal activity (3.6 clusters/patient). Each cluster was populated on average by 22.1 [15.0-31.0] spikes. The predicted IZ maps had an average distance from the resection margin of 8.4 ± 9.3 mm for visual analysis, 12.0 ± 16.5 mm for SLOPE and 22.7 ±. 16.4 mm for PEAK. The consideration of the source spread at the ascending slope provided an IZ closer to RA and resembled the analysis of an expert observer. We validated here the performance of a data-driven approach for the automated detection of interictal spikes and delineation of the IZ. This computational framework provides the basis for reproducible and bias-free analysis of MEG recordings in epilepsy.

Fast parametric curve matching (FPCM) for automatic spike detection.

Objective. Epilepsy is a widely spread neurological disease, whose treatment often requires resection of the pathological cortical tissue. Interictal spike analysis observed in the non-invasively collected EEG or MEG data offers an attractive way to localize epileptogenic cortical structures for surgery planning purposes. Interictal spike detection in lengthy multichannel data is a daunting task that is still often performed manually. This frequently limits such an analysis to a small portion of the data which renders the appropriate risks of missing the potentially epileptogenic region. While a plethora of automatic spike detection techniques have been developed each with its own assumptions and limitations, none of them is ideal and the best results are achieved when the output of several automatic spike detectors are combined. This is especially true in the low signal-to-noise ratio conditions. To this end we propose a novel biomimetic approach for automatic spike detection based on a constrained mixed spline machinery that we dub as fast parametric curve matching (FPCM).Approach. Using the peak-wave shape parametrization, the constrained parametric morphological model is constructed and convolved with the observed multichannel data to efficiently determine mixed spline parameters corresponding to each time-point in the dataset. Then the logical predicates that directly map to verbalized text-book like descriptions of the expected interictal event morphology allow us to accomplish the spike detection task.Main results. The results of simulations mimicking typical low SNR scenarios show the robustness and high receiver operating characteristic AUC values of the FPCM method as compared to the spike detection performed using more conventional approaches such as wavelet decomposition, template matching or simple amplitude thresholding. Applied to the real MEG and EEG data from the human patients and to rat ECoG data, the FPCM technique demonstrates reliable detection of the interictal events and localization of epileptogenic zones concordant with independent conclusions made by the epileptologist.Significance. Since the FPCM is computationally light, tolerant to high amplitude artifacts and flexible to accommodate verbalized descriptions of an arbitrary target morphology, it is likely to complement the existing arsenal of means for analysis of noisy interictal datasets.

Generalization of sustained neurophysiological effects of short-term auditory 13-Hz stimulation to neighbouring frequency representation in humans.

A fuller understanding of the effects of auditory tetanization in humans would inform better language and sensory learning paradigms; however, there are still unanswered questions. Here, we probe sustained changes in the event-related potentials (ERPs) to 1020- and 980-Hz tones following a rapid presentation of 1020-Hz tone (every 75 ms, 13.3 Hz, tetanization). Consistent with some previous studies, we revealed the increase in the P2 ERP component after tetanization. Contrary to some other studies, we did not observe the expected N1 increase after tetanization even in the identical experimental sequence. We detected a significant N1 decrease after tetanization. Expanding previous research, we showed that P2 increase and N1 decrease are not specific to the stimulus type (tetanized 1020 Hz and non-tetanized 980 Hz), suggesting the generalizability of tetanization effect to the not-stimulated auditory tones, at least to those of the neighbouring frequency. The ERPs' tetanization effects were observed for at least 30 min-the most prolonged interval examined, consistent with the duration of long-term potentiation, LTP. In addition, the tetanization effects were detectable in the blocks where the participants watched muted videos, an experimental setting that can be easily used in children and other challenging groups. Thus, auditory 13-Hz stimulation affects brain processing of tones including those of neighbouring frequencies.