Electroencephalographic Recordings Research Articles

Modeling the cortical response elicited by wrist manipulation via a nonlinear delay differential embedding.

Regarding motor processes, modeling healthy people's brains is essential to understand the brain activity in people with motor impairments. However, little research has been undertaken when external forces disturb limbs, having limited information on physiological pathways. Therefore, in this paper, a nonlinear delay differential embedding model is used to estimate the brain response elicited by externally controlled wrist movement in healthy individuals. The aim is to improve the understanding of the relationship between a controlled wrist movement and the generated cortical activity of healthy people, helping to disclose the underlying mechanisms and physiological relationships involved in the motor event. To evaluate the model, a public database from the Delft University of Technology is used, which contains electroencephalographic recordings of ten healthy subjects while wrist movement was externally provoked by a robotic system. In this work, the cortical response related to movement is identified via Independent Component Analysis and estimated based on a nonlinear delay differential embedding model. After a cross-validation analysis, the model performance reaches 90.21% ± 4.46% Variance Accounted For, and Correlation 95.14% ± 2.31%. The proposed methodology allows to select the model degree, to estimate a general predominant operation mode of the cortical response elicited by wrist movement. The obtained results revealed two facts that had not previously been reported: the movement's acceleration affects the cortical response, and a common delayed activity is shared among subjects. Going forward, identifying biomarkers related to motor tasks could aid in the evaluation of rehabilitation treatments for patients with upper limbs motor impairments.

Depth versus surface: A critical review of subdural and depth electrodes in intracranial electroencephalographic studies.

Intracranial electroencephalographic (IEEG) recording, using subdural electrodes (SDEs) and stereoelectroencephalography (SEEG), plays a pivotal role in localizing the epileptogenic zone (EZ). SDEs, employed for superficial cortical seizure foci localization, provide information on two-dimensional seizure onset and propagation. In contrast, SEEG, with its three-dimensional sampling, allows exploration of deep brain structures, sulcal folds, and bihemispheric networks. SEEG offers the advantages of fewer complications, better tolerability, and coverage of sulci. Although both modalities allow electrical stimulation, SDE mapping can tessellate cortical gyri, providing the opportunity for a tailored resection. With SEEG, both superficial gyri and deep sulci can be stimulated, and there is a lower risk of afterdischarges and stimulation-induced seizures. Most systematic reviews and meta-analyses have addressed the comparative effectiveness of SDEs and SEEG in localizing the EZ and achieving seizure freedom, although discrepancies persist in the literature. The combination of SDEs and SEEG could potentially overcome the limitations inherent to each technique individually, better delineating seizure foci. This review describes the strengths and limitations of SDE and SEEG recordings, highlighting their unique indications in seizure localization, as evidenced by recent publications. Addressing controversies in the perceived usefulness of the two techniques offers insights that can aid in selecting the most suitable IEEG in clinical practice.

Data leakage in deep learning studies of translational EEG

A growing number of studies apply deep neural networks (DNNs) to recordings of human electroencephalography (EEG) to identify a range of disorders. In many studies, EEG recordings are split into segments, and each segment is randomly assigned to the training or test set. As a consequence, data from individual subjects appears in both the training and the test set. Could high test-set accuracy reflect data leakage from subject-specific patterns in the data, rather than patterns that identify a disease? We address this question by testing the performance of DNN classifiers using segment-based holdout (in which segments from one subject can appear in both the training and test set), and comparing this to their performance using subject-based holdout (where all segments from one subject appear exclusively in either the training set or the test set). In two datasets (one classifying Alzheimer's disease, and the other classifying epileptic seizures), we find that performance on previously-unseen subjects is strongly overestimated when models are trained using segment-based holdout. Finally, we survey the literature and find that the majority of translational DNN-EEG studies use segment-based holdout. Most published DNN-EEG studies may dramatically overestimate their classification performance on new subjects.

Altered pattern of theta and gamma oscillation to visual stimuli in patients with post-concussion syndrome.

Purpose Although many patients with mild traumatic brain injury (mTBI) suffer from post-concussional syndrome(PCS) including abnormal emotional responses, most conventional imaging studies fail to detect any causative brain lesion. We hypothesized that event-related electroencephalography (EEG) recordings with time-frequency analysis would show a distinguishable pattern in mTBI patients with PCS compared with normal healthy controls. Methods EEG signals were collected from a total of 18 subjects: eight mTBI patients with PCS and ten healthy control subjects. The signals were recorded while the subjects were presented with affective visual stimuli, including neutral, pleasant, and unpleasant emotional cues. Event-related spectral perturbation analysis was performed to calculate frontal midline theta activity and posterior midline gamma activity, followed by statistical analysis to identify whether mTBI patients with PCS have distinct patterns of theta or gamma oscillations in response to affective stimuli. Results Compared to the healthy control group, mTBI patients with PCS did not show significant increase in the power of frontal theta activity in response to the pleasant stimuli, indicating less susceptibility towards pleasant cues. Moreover, the patient group showed attenuated gamma oscillatory activity, with no clear alteration in gamma oscillations in response to either pleasant or unpleasant cues. This study demonstrates that mTBI patients with PCS exhibited altered patterns of oscillatory activities in the theta and gamma bands in response to affective visual stimuli compared to the normal control group. Conclusion The current finding implicates that these distinguishable patterns of brain oscillation may represent the mechanism behind various psychiatric symptoms in mTBI patients.

A study of Electroencephalography Findings and its Prognostic Value in Severe COVID-19 Patients Admitted at Intensive Care Unit

A study of Electroencephalography Findings and its Prognostic Value in Severe COVID-19 Patients Admitted at Intensive Care Unit

Exploring the ‘black box’ of anxiety: An ERP study of non-consciously triggered fear generalization

Individuals with anxiety disorders frequently display heightened fear responses, even in situations where there is no imminent danger. We hypothesize that these irrational fear responses are related to automatic processing of fear generalization. The initial automatic detection of stimuli often operates at a non-conscious level. However, whether fear generalization can occur when the cues are not perceived consciously remains unclear. The current study investigated the neurocognitive mechanisms underlying fear conditioning and its non-conscious and conscious generalization using a backward masking paradigm, combined with analysis of event-related potentials from electroencephalographic recordings. Behaviorally, participants showed heightened shock expectancy in response to non-conscious perceived generalization stimuli compared to those perceived consciously. Nonetheless, participants could not consciously distinguish between danger and safe cues in non-conscious trials. Physiologically, danger cues evoked larger frontal N1 amplitudes than safety cues in non-conscious trials, suggesting enhanced attention vigilance towards danger cues in the early sensory processing stage. Meanwhile, when fear generalization was conscious, it was accompanied by a larger P2 amplitude, indicating attention orientation or stimulus evaluation. In addition, fear conditioning was associated with sustained discrimination on P2, P3, and LPP. These findings collectively suggest that non-conscious fear generalization occurs at the neural level, yet additional control conditions are required to confirm this phenomenon on the US expectancy. Thus, non-consciously fear generalization may represent a mechanism that could trigger automatic irrational fear, highlighting the need for further research to explore therapeutic targets in anxiety disorders.

Uncovering spatiotemporal dynamics of the corticothalamic network at ictal onset.

Although the clinical efficacy of deep brain stimulation targeting the anterior nucleus (AN) and centromedian nucleus (CM) of the thalamus has been actively investigated for the treatment of medication-resistant epilepsy, few studies have investigated dynamic ictal changes in corticothalamic connectivity in human electroencephalographic (EEG) recording. This study aims to establish the complex spatiotemporal dynamics of the ictal corticothalamic network associated with various seizure foci. We analyzed 10 patients (aged 2.7-28.1 years) with medication-resistant focal epilepsy who underwent stereotactic EEG evaluation with thalamic sampling. We examined both undirected and directed connectivity, incorporating coherence and spectral Granger causality analysis (GCA) between the diverse seizure foci and thalamic nuclei (AN and CM) at ictal onset. In our analysis of 36 seizures, coherence between seizure onset and thalamic nuclei increased across all frequencies, especially in slower bands (delta, theta, alpha). GCA showed increased information flow from seizure onset to the thalamus across all frequency bands, but outflows from the thalamus were mainly in slower frequencies, particularly delta. In the subgroup analysis based on various seizure foci, the delta coherence showed a more pronounced increase at CM than at AN during frontal lobe seizures. Conversely, in limbic seizures, the delta coherence increase was greater at AN compared to CM. It appears that the delta frequency plays a pivotal role in modulating the corticothalamic network during seizures. Our results underscore the significance of comprehending the spatiotemporal dynamics of the corticothalamic network at ictal onset, and this knowledge could guide personalized responsive neuromodulation treatment strategies.

Resting Frontal Gamma Power is Associated with Both Expressive Language and Non-verbal Cognitive Abilities in Young Autistic Children.

Previous research links resting frontal gamma power to key developmental outcomes in young neurotypical (NT) children and infants at risk for language impairment. However, it remains unclear whether gamma power is specifically associated with language or with more general cognitive abilities among young children diagnosedwith autism spectrum disorder (ASD). The current study evaluates differences in resting frontal gamma power between young autistic and NT children and tests whether gamma power is uniquely associated with individual differences in expressive language, receptive language and non-verbal cognitive abilities in autistic and NT children. Participants included 48 autistic children and 58 age- and sex-matched NT children (ages 22-60months). Baseline electroencephalography (EEG) recordings were acquired from each participant. Children also completed the Mullen Scales of Early Learning (MSEL). We found thatfrontal gamma power at rest did not differ between autistic and NT children. Among autistic children, reduced frontal gamma power was significantly associated with both higher expressive language skills and higher non-verbal cognitive skills, controlling for age and sex. The interaction between frontal gamma power and diagnostic status no longer explained unique variance in expressive language skills after controlling for variance associated with non-verbal cognitive skills across autistic and NT children. Together, these findings suggest that reduced gamma power is associated with both better expressive language and non-verbal cognitive skills among young autistic children. Moreover, associations between high frequency neural activity and cognition are not specific to verbal abilities but reflect neural mechanisms associated with general higher-order cognitive abilities in ASD.

The Ultra-Long-Term Sleep study: Design, rationale, data stability and user perspective.

Sleep deprivation and poor sleep quality are significant societal challenges that negatively impact individuals' health. The interaction between subjective sleep quality, objective sleep measures, physical and cognitive performance, and their day-to-day variations remains poorly understood. Our year-long study of 20 healthy individuals, using subcutaneous electroencephalography, aimed to elucidate these interactions, assessing data stability and participant satisfaction, usability, well-being and adherence. In the study, 25 participants were fitted with a minimally invasive subcutaneous electroencephalography lead, with 20 completing the year of subcutaneous electroencephalography recording. Signal stability was measured using covariance of variation. Participant satisfaction, usability and well-being were measured with questionnaires: Perceived Ease of Use questionnaire, System Usability Scale, Headache questionnaire, Major Depression Inventory, World Health Organization 5-item Well-Being Index, and interviews. The subcutaneous electroencephalography signals remained stable for the entire year, with an average participant adherence rate of 91%. Participants rated their satisfaction with the subcutaneous electroencephalography device as easy to use with minimal or no discomfort. The System Usability Scale score was high at 86.3 ± 10.1, and interviews highlighted that participants understood how to use the subcutaneous electroencephalography device and described a period of acclimatization to sleeping with the device. This study provides compelling evidence for the feasibility of longitudinal sleep monitoring during everyday life utilizing subcutaneous electroencephalography in healthy subjects, showcasing excellent signal stability, adherence and user experience. The amassed subcutaneous electroencephalography data constitutes the largest dataset of its kind, and is poised to significantly advance our understanding of day-to-day variations in normal sleep and provide key insights into subjective and objective sleep quality.

Real-time cortical dynamics during motor inhibition

The inhibition of action is a fundamental executive mechanism of human behaviour that involve a complex neural network. In spite of the progresses made so far, many questions regarding the brain dynamics occurring during action inhibition are still unsolved. Here, we used a novel approach optimized to investigate real-time effective brain dynamics, which combines transcranial magnetic stimulation (TMS) with simultaneous electroencephalographic (EEG) recordings. 22 healthy volunteers performed a motor Go/NoGo task during TMS of the hand-hotspot of the primary motor cortex (M1) and whole-scalp EEG recordings. We reconstructed source-based real-time spatiotemporal dynamics of cortical activity and cortico-cortical connectivity throughout the task. Our results showed a task-dependent bi-directional change in theta/gamma supplementary motor cortex (SMA) and M1 connectivity that, when participants were instructed to inhibit their response, resulted in an increase of a specific TMS-evoked EEG potential (N100), likely due to a GABA-mediated inhibition. Interestingly, these changes were linearly related to reaction times, when participants were asked to produce a motor response. In addition, TMS perturbation revealed a task-dependent long-lasting modulation of SMA–M1 natural frequencies, i.e. alpha/beta activity. Some of these results are shared by animal models and shed new light on the physiological mechanisms of motor inhibition in humans.

Stimulus Complexity Can Enhance Art Appreciation: Phenomenological and Psychophysiological Evidence for the Pleasure-Interest Model of Aesthetic Liking.

We tested predictions deriving from the "Pleasure-Interest Model of Aesthetic Liking" (PIA Model), whereby aesthetic preferences arise from two fluency-based processes: an initial automatic, percept-driven default process and a subsequent perceiver-driven reflective process. One key trigger for reflective processing is stimulus complexity. Moreover, if meaning can be derived from such complexity, then this can engender increased interest and elevated liking. Experiment 1 involved graffiti street-art images, pre-normed to elicit low, moderate and high levels of interest. Subjective reports indicated a predicted enhancement in liking across increasing interest levels. Electroencephalography (EEG) recordings during image viewing revealed different patterns of alpha power in temporal brain regions across interest levels. Experiment 2 enforced a brief initial image-viewing stage and a subsequent reflective image-viewing stage. Differences in alpha power arose in most EEG channels between the initial and deliberative viewing stages. A linear increase in aesthetic liking was again seen across interest levels, with different patterns of alpha activity in temporal and occipital regions across these levels. Overall, the phenomenological data support the PIA Model, while the physiological data suggest that enhanced aesthetic liking might be associated with "flow-feelings" indexed by alpha activity in brain regions linked to visual attention and reducing distraction.

Transcranial direct current stimulation alters cerebrospinal fluid-interstitial fluid exchange in mouse brain

BackgroundTranscranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique that has gained prominence recently. Clinical studies have explored tDCS as an adjunct to neurologic disease rehabilitation, with evidence suggesting its potential in modulating brain clearance mechanisms. The glymphatic system, a proposed brain waste clearance system, posits that cerebrospinal fluid-interstitial fluid (CSF-ISF) exchange aids in efficient metabolic waste removal. While some studies have linked tDCS to astrocytes inositol trisphosphate (IP3)/Ca2+ signaling, the impact of tDCS on CSF-ISF exchange dynamics remains unclear. HypothesistDCS influences the dynamics of CSF-ISF exchange through astrocytic IP3/Ca2+ signaling. MethodsIn this study, we administered tDCS (0.1mA for 10 minutes) to C57BL/6 mice anesthetized with ketamine-xylazine (KX). The anode was positioned on the cranial bone above the cortex, and the cathode was inserted into the neck. Following tDCS, we directly assessed brain fluid dynamics by injecting biotinylated dextran amine (BDA) as a CSF tracer into the cisterna magna (CM). The brain was then extracted after either 30 or 60 minutes and fixed. After 24 hours, the sectioned brain slices were stained with Alexa 594-conjugated streptavidin (SA) to visualize BDA using immunohistochemistry. We conducted Electroencephalography (EEG) recordings and aquaporin 4 (AQP4)/CD31 immunostaining to investigate the underlying mechanisms of tDCS. Additionally, we monitored the efflux of Evans blue, injected into the cisterna magna, using cervical lymph node imaging. The experiments were subsequently repeated with inositol trisphosphate receptor type 2 (IP3R2)-knockout mice. ResultsPost-tDCS, we observed an increased CSF tracer influx, indicating a modulation of CSF-ISF exchange by tDCS. Additionally, tDCS appeared to enhance the brain's metabolic waste efflux. EEG recordings showed an increase in delta wave post-tDCS. But no significant change in AQP4 expression was detected 30 minutes post-tDCS. ConclusionOur findings suggest that tDCS augments the glymphatic system's influx and efflux. Through astrocyte IP3/Ca2+ signaling, tDCS was found to modify the delta wave, which correlates positively with brain clearance. This study underscores the potential of tDCS in modulating brain metabolic waste clearance.

Towards ASSR-based hearing assessment using natural sounds

Objective. The auditory steady-state response (ASSR) allows estimation of hearing thresholds. The ASSR can be estimated from electroencephalography (EEG) recordings from electrodes positioned on both the scalp and within the ear (ear-EEG). Ear-EEG can potentially be integrated into hearing aids, which would enable automatic fitting of the hearing device in daily life. The conventional stimuli for ASSR-based hearing assessment, such as pure tones and chirps, are monotonous and tiresome, making them inconvenient for repeated use in everyday situations. In this study we investigate the use of natural speech sounds for ASSR estimation. Approach. EEG was recorded from 22 normal hearing subjects from both scalp and ear electrodes. Subjects were stimulated monaurally with 180 min of speech stimulus modified by applying a 40 Hz amplitude modulation (AM) to an octave frequency sub-band centered at 1 kHz. Each 50 ms sub-interval in the AM sub-band was scaled to match one of 10 pre-defined levels (0–45 dB sensation level, 5 dB steps). The apparent latency for the ASSR was estimated as the maximum average cross-correlation between the envelope of the AM sub-band and the recorded EEG and was used to align the EEG signal with the audio signal. The EEG was then split up into sub-epochs of 50 ms length and sorted according to the stimulation level. ASSR was estimated for each level for both scalp- and ear-EEG. Main results. Significant ASSRs with increasing amplitude as a function of presentation level were recorded from both scalp and ear electrode configurations. Significance. Utilizing natural sounds in ASSR estimation offers the potential for electrophysiological hearing assessment that are more comfortable and less fatiguing compared to existing ASSR methods. Combined with ear-EEG, this approach may allow convenient hearing threshold estimation in everyday life, utilizing ambient sounds. Additionally, it may facilitate both initial fitting and subsequent adjustments of hearing aids outside of clinical settings.

A personalized earbud for non-invasive long-term EEG monitoring

Objective. The primary objective of this study was to evaluate the reliability, comfort, and performance of a custom-fit, non-invasive long-term electrophysiologic headphone, known as Aware Hearable, for the ambulatory recording of brain activities. These recordings play a crucial role in diagnosing neurological disorders such as epilepsy and in studying neural dynamics during daily activities. Approach. The study uses commercial manufacturing processes common to the hearing aid industry, such as 3D scanning, computer-aided design modeling, and 3D printing. These processes enable the creation of the Aware Hearable with a personalized, custom-fit, thereby ensuring complete and consistent contact with the inner surfaces of the ear for high-quality data recordings. Additionally, the study employs a machine learning data analysis approach to validate the recordings produced by Aware Hearable, by comparing them to the gold standard intracranial electroencephalography recordings in epilepsy patients. Main results. The results indicate the potential of Aware Hearable to expedite the diagnosis of epilepsy by enabling extended periods of ambulatory recording. Significance. This offers significant reductions in burden to patients and their families. Furthermore, the device’s utility may extend to a broader spectrum, making it suitable for other applications involving neurophysiological recordings in real-world settings.

Multichannel detection of evoked responses using critical values corrected by a parametric bootstrap: Frequency-domain cholesky correction

Multivariate Objective Response Detection (MORD) techniques aim to detect evoked responses in multichannel electroencephalographic (EEG) recordings. They provide enhanced statistical power, allowing the detection of small signals in shorter or noisy recordings. However, the correlation between the signals in multichannel recordings can lead to false positive rates greater than the nominal significance level of the tests. To address this, we propose a parametric bootstrap approach that adjusts the critical values based on the correlation between EEG channels in the time domain, a method called time-domain Cholesky correction (TDCC). In that first approach, we assumed that correlation (or, more precisely, coherence) is constant across all frequency bands. However, this is unlikely to hold true, as signal-to-noise ratios (where the signal is the evoked response and noise all other signal components) may vary across frequencies. Thus, in the current work, we propose an alternative parametric bootstrap method for estimating the critical values of MORD techniques based on the correlation in the frequency domain (FDCC, frequency-domain Cholesky-corrected critical values). The proposed methods are evaluated using simulated data and an auditory steady-state response (ASSR) database in the 40 Hz range. The proposed method controlled the false positive rate well, with increased sensitivity compared to single-channel methods. When compared to TDCC, FDCC achieved similar performance but with the advantage of being, on average, 27 times faster in terms of computational time required to estimate the critical values.

The Role of the Motor System in L1 and L2 Action Verb Processing for Chinese Learners of English: Evidence from Mu Rhythm Desynchronization.

The nature of semantic representation has long been a key question in linguistic research. The Embodied Cognition theory challenges the traditional view of language representation, stating that semantic information stems from the sensory-motor cortex, which is activated automatically during semantic processing. However, most of the evidence comes from monolingual studies; it remains unclear whether second-language (L2) comprehension involves different semantic representations or mirrors the pattern seen in first-language (L1) processing. Therefore, the present study investigated the role of the sensory-motor system in language processing via making Electroencephalography (EEG) recordings during the processing of L1 and L2 action verbs. The results showed that L1 (Chinese) action verbs generated higher mu-event-related desynchronization (ERD) than L1 abstract verbs in the early processing stage (250 ms after verb presentation), and the same phenomenon was also observed for L2 (English). The results also indicated that language modulated the processing of action verbs, with L1 action verbs eliciting stronger ERD than L2 action verbs. These results demonstrate that the sensory-motor cortex plays a crucial role in comprehending both L1 and L2 action verbs.

Multiscale neuro-inspired models for interpretation of EEG signals in patients with epilepsy

ObjectiveThe aim is to gain insight into the pathophysiological mechanisms underlying interictal epileptiform discharges observed in electroencephalographic (EEG) and stereo-EEG (SEEG, depth electrodes) recordings performed during pre-surgical evaluation of patients with drug-resistant epilepsy. MethodsWe developed novel neuro-inspired computational models of the human cerebral cortex at three different levels of description: i) microscale (detailed neuron models), ii) mesoscale (neuronal mass models) and iii) macroscale (whole brain models). Although conceptually different, micro- and mesoscale models share some similar features, such as the typology of neurons (pyramidal cells and three types of interneurons), their spatial arrangement in cortical layers, and their synaptic connectivity (excitatory and inhibitory). The whole brain model consists of a large-scale network of interconnected neuronal masses, with connectivity based on the human connectome. ResultsFor these three levels of description, the fine-tuning of free parameters and the quantitative comparison with real data allowed us to reproduce interictal epileptiform discharges with a high degree of fidelity and to formulate hypotheses about the cell- and network-related mechanisms underlying the generation of fast ripples and SEEG-recorded epileptic spikes and spike-waves. ConclusionsThe proposed models provide valuable insights into the pathophysiological mechanisms underlying the generation of epileptic events. The knowledge gained from these models effectively complements the clinical analysis of SEEG data collected during the evaluation of patients with epilepsy. SignificanceThese models are likely to play a key role in the mechanistic interpretation of epileptiform activity.

Neurophysiology of hypokinetic movement’s disorders: New insights in daily clinical practice

Hypokinetic movement disorders encompass a group of clinically similar diseases that present challenges in discrimination during neurological examinations. Characterizing a specific hypokinetic disorder is necessary for the diagnosis and treatment in daily clinical practice. Neurophysiological tools, such as electromyography (EMG) combined with accelerometry, motor-evoked potentials (MEPs), electroencephalographic recording (EEG), Bereitschaftspotential (BP), auditory-evoked cognitive potential (P300), blink reflex (BR), and R2 blink reflex recovery cycle (R2BRRC), are useful in the differential diagnosis of movement disorders due to the common clinical features. However, neurophysiological assessments of movement disorders, especially hypokinetic diseases, are currently underutilized in clinical practice as compared to a few decades ago. This review aims to summarize practical insights gleaned from reported studies over the past 5 years (i.e., 2019 – 2023) regarding neurophysiological assessments of hypokinetic movement disorders, emphasizing the importance of their routine application. In particular, the methodology of the electrophysiologic evaluations pertaining to hypokinetic movement disorders is assessed. Moreover, a practical approach for the differential diagnosis of similar movement disorder syndromes based on specific neurophysiological features is proposed. Collectively, this review of the most recent neurophysiological implications in hypokinetic movement disorders highlights the practicality of these methods. Despite the advancement of other diagnostic techniques (e.g., neuroradiological methods), neurophysiological assessments may be a promising tool for clinical diagnoses, due to their high accuracy and ability to categorize and manage movement disorders (e.g., hypokinetic movement disorders) in daily clinical practice.

Stationary stable cross-correlation pattern and task specific deviations in unresponsive wakefulness syndrome as well as clinically healthy subjects.

Brain dynamics is highly non-stationary, permanently subject to ever-changing external conditions and continuously monitoring and adjusting internal control mechanisms. Finding stationary structures in this system, as has been done recently, is therefore of great importance for understanding fundamental dynamic trade relationships. Here we analyse electroencephalographic recordings (EEG) of 13 subjects with unresponsive wakefulness syndrome (UWS) during rest and while being influenced by different acoustic stimuli. We compare the results with a control group under the same experimental conditions and with clinically healthy subjects during overnight sleep. The main objective of this study is to investigate whether a stationary correlation pattern is also present in the UWS group, and if so, to what extent this structure resembles the one found in healthy subjects. Furthermore, we extract transient dynamical features via specific deviations from the stationary interrelation pattern. We find that (i) the UWS group is more heterogeneous than the two groups of healthy subjects, (ii) also the EEGs of the UWS group contain a stationary cross-correlation pattern, although it is less pronounced and shows less similarity to that found for healthy subjects and (iii) deviations from the stationary pattern are notably larger for the UWS than for the two groups of healthy subjects. The results suggest that the nervous system of subjects with UWS receive external stimuli but show an overreaching reaction to them, which may disturb opportune information processing.

Differences in attentional function between experienced mindfulness meditators and non-meditators.

Attentional enhancement has often been identified as the central cognitive mechanism underlying the benefits of mindfulness meditation. However, the extent to which this enhancement is observable in the neural processes underlying long-term meditation is unclear. This current study aimed to examine differences in attentional performance between meditators and controls (non-meditators) using a visual oddball task with concurrent electroencephalography (EEG) recordings. Thirty-four participants were recruited, including 16 meditators and 18 healthy controls, who were non-meditators. The participants completed a visual oddball task, using visual stimuli, and EEG recording. Self-reports revealed that meditators had higher mindful attention scores than did the control group. The behavioral results showed that the meditators demonstrated faster reaction times than the non-meditators did. Neural findings indicated a higher P2 amplitude in the meditators than in the controls. The meditators demonstrated a significantly higher P3 in the target trials than in the distractor trials, which was not observed in the controls. Additionally, the time-frequency analysis demonstrated that the delta and theta powers in the meditators were significantly higher than those in the controls. The study suggests the meditators exhibited greater attentional performance than the controls did, as revealed by EEG and behavioral measures. This study extends previous research on the effects of mindfulness meditation on attention and adds to our understanding of the effects of long-term mindfulness meditation.