Recording the tactile P300 with the cEEGrid for potential use in a brain-computer interface.

Brain-computer interfaces (BCIs) are scientifically well established, but they rarely arrive in the daily lives of potential end-users. This could be in part because electroencephalography (EEG), a prevalent method to acquire brain activity for BCI operation, is considered too impractical to be applied in daily life of end-users with physical impairment as an assistive device. Hence, miniaturized EEG systems such as the cEEGrid have been developed. While they promise to be a step toward bridging the gap between BCI development, lab demonstrations, and home use, they still require further validation. Encouragingly, the cEEGrid has already demonstrated its ability to record visually and auditorily evoked event-related potentials (ERP), which are important as input signal for many BCIs. With this study, we aimed at evaluating the cEEGrid in the context of a BCI based on tactually evoked ERPs. To compare the cEEGrid with a conventional scalp EEG, we recorded brain activity with both systems simultaneously. Forty healthy participants were recruited to perform a P300 oddball task based on vibrotactile stimulation at four different positions. This tactile paradigm has been shown to be feasible for BCI repeatedly but has never been tested with the cEEGrid. We found distinct P300 deflections in the cEEGrid data, particularly at vertical bipolar channels. With an average of 63%, the cEEGrid classification accuracy was significantly above the chance level (25%) but significantly lower than the 81% reached with the EEG cap. Likewise, the P300 amplitude was significantly lower (cEEGrid R2-R7: 1.87 µV, Cap Cz: 3.53 µV). These results indicate that a tactile BCI using the cEEGrid could potentially be operated, albeit with lower efficiency. Additionally, participants' somatosensory sensitivity was assessed, but no correlation to the accuracy of either EEG system was shown. Our research contributes to the growing amount of literature comparing the cEEGrid to conventional EEG systems and provides first evidence that the tactile P300 can be recorded behind the ear. A BCI based on a thus simplified EEG system might be more readily accepted by potential end-users, provided the accuracy can be substantially increased, e.g., by training and improved classification.

Combining EEG and eye-tracking in virtual reality: Obtaining fixation-onset event-related potentials and event-related spectral perturbations.

Extensive research conducted in controlled laboratory settings has prompted an inquiry into how results can be generalized to real-world situations influenced by the subjects' actions. Virtual reality lends itself ideally to investigating complex situations but requires accurate classification of eye movements, especially when combining it with time-sensitive data such as EEG. We recorded eye-tracking data in virtual reality and classified it into gazes and saccades using a velocity-based classification algorithm, and we cut the continuous data into smaller segments to deal with varying noise levels, as introduced in the REMoDNav algorithm. Furthermore, we corrected for participants' translational movement in virtual reality. Various measures, including visual inspection, event durations, and the velocity and dispersion distributions before and after gaze onset, indicate that we can accurately classify the continuous, free-exploration data. Combining the classified eye-tracking with the EEG data, we generated fixation-onset event-related potentials (ERPs) and event-related spectral perturbations (ERSPs), providing further evidence for the quality of the eye-movement classification and timing of the onset of events. Finally, investigating the correlation between single trials and the average ERP and ERSP identified that fixation-onset ERSPs are less time sensitive, require fewer repetitions of the same behavior, and are potentially better suited to study EEG signatures in naturalistic settings. We modified, designed, and tested an algorithm that allows the combination of EEG and eye-tracking data recorded in virtual reality.

Correcting for ERP latency jitter improves gaze-independent BCI decoding.

OBJECTIVE: Patients suffering from heavy paralysis or Locked-in-Syndrome can regain communication using a Brain-Computer Interface (BCI). Visual event-related potential (ERP) based BCI paradigms exploit visuospatial attention (VSA) to targets laid out on a screen. However, performance drops if the user does not direct their eye gaze at the intended target, harming the utility of this class of BCIs for patients suffering from eye motor deficits. We aim to create an ERP decoder that is less dependent on eye gaze. METHODS: ERP component latency jitter plays a role in covert visuospatial attention (VSA) decoding. We introduce a novel decoder which compensates for these latency effects, termed Woody Classifier-based Latency Estimation (WCBLE). We carried out a BCI experiment recording ERP data in overt and covert visuospatial attention (VSA), and introduce a novel special case of covert VSA termed split VSA, simulating the experience of patients with severely impaired eye motor control. We evaluate WCBLE on this dataset and the BNCI2014-009 dataset, within and across VSA conditions to study the dependency on eye gaze and the variation thereof during the experiment. RESULTS & DISCUSSION: WCBLE outperforms state-of-the-art methods in the VSA conditions of interest in gaze-independent decoding, without reducing overt VSA performance. Results from across-condition evaluation show that WCBLE is more robust to varying VSA conditions throughout a BCI operation session. Together, these results point towards a pathway to achieving gaze independence through suited ERP decoding. Our proposed gaze-independent solution enhances decoding performance in those cases where performing overt VSA is not possible.

Preliminary observations on the associations between sensory processing abnormalities and event-related potentials in adults with autism spectrum disorder.

Aim: Autism spectrum disorder (ASD) is a neurodevelopmental disorder that is thought to involve a variety of neurophysiological characteristics. Event-related potentials (ERPs) reflect cognitive functions in the brain's cognitive processing. In this study, we investigated differences in P300 and N100 of ERPs between ASD and typically developing groups and focused on the relationship between the components of ERPs and measures of autistic traits and sensory processing characteristics. Methods: ERPs were measured in 96 subjects in the ASD group and 62 subjects in the age- and sex-adjusted typically developing group. Correlations between each component and the scores of the Autism-Spectrum Quotient Japanese version (AQ-J) and the Adolescent and Adult Sensory Profile (AASP) were also evaluated. Results: The ASD group showed a significant decrease in the amplitude of N100 at C3. Furthermore, a negative correlation was found between lower amplitude at C3 of N100 and low registered sensory scores in both groups. Conclusion: Our findings imply that the N100 amplitude at C3 could be a potential indicator for examining the neurophysiological traits of ASD; however, these results should be interpreted with caution due to their preliminary nature. These tentative insights into sensory processing anomalies may be discernible in specific subsets of the ASD population, providing a foundation for future investigative pathways.

Post-stroke aphasia rehabilitation using an adapted visual P300 brain-computer interface training: improvement over time, but specificity remains undetermined.

Introduction: This study aimed to evaluate the efficacy of visual P300 brain-computer interface use to support rehabilitation of chronic language production deficits commonly experienced by individuals with a left-sided stroke resulting in post-stroke aphasia. Methods: The study involved twelve participants, but five dropped out. Additionally, data points were missing for three participants in the remaining sample of seven participants. The participants underwent four assessments-a baseline, pre-assessment, post-assessment, and follow-up assessment. Between the pre-and post-assessment, the participants underwent at least 14 sessions of visual spelling using a brain-computer interface. The study aimed to investigate the impact of this intervention on attention, language production, and language comprehension and to determine whether there were any potential effects on quality of life and well-being. Results: None of the participants showed a consistent improvement in attention. All participants showed an improvement in spontaneous speech production, and three participants experienced a reduction in aphasia severity. We found an improvement in subjective quality of life and daily functioning. However, we cannot rule out the possibility of unspecific effects causing or at least contributing to these results. Conclusion: Due to challenges in assessing the patient population, resulting in a small sample size and missing data points, the results of using visual P300 brain-computer interfaces for chronic post-stroke aphasia rehabilitation are preliminary. Thus, we cannot decisively judge the potential of this approach.

Evaluation of Different Types of Stimuli in an Event-Related Potential-Based Brain-Computer Interface Speller under Rapid Serial Visual Presentation.

Rapid serial visual presentation (RSVP) is currently a suitable gaze-independent paradigm for controlling visual brain-computer interfaces (BCIs) based on event-related potentials (ERPs), especially for users with limited eye movement control. However, unlike gaze-dependent paradigms, gaze-independent ones have received less attention concerning the specific choice of visual stimuli that are used. In gaze-dependent BCIs, images of faces-particularly those tinted red-have been shown to be effective stimuli. This study aims to evaluate whether the colour of faces used as visual stimuli influences ERP-BCI performance under RSVP. Fifteen participants tested four conditions that varied only in the visual stimulus used: grey letters (GL), red famous faces with letters (RFF), green famous faces with letters (GFF), and blue famous faces with letters (BFF). The results indicated significant accuracy differences only between the GL and GFF conditions, unlike prior gaze-dependent studies. Additionally, GL achieved higher comfort ratings compared with other face-related conditions. This study highlights that the choice of stimulus type impacts both performance and user comfort, suggesting implications for future ERP-BCI designs for users requiring gaze-independent systems.

Neurocognitive performance of badminton players at different competitive levels in visuospatial attention tasks.

Visuospatial attention (VSA) is a cognitive function that enables athletes, particularly those engaged in open-skill sports, to allocate attentional resources efficiently to the appropriate target and in the appropriate direction. Studies have indicated that expert players exhibit superior cognitive performance to that of novices. However, no study has investigated differences in VSA performance among elite, expert, and intermediate badminton players or the potential neurophysiological mechanisms underlying such differences. Accordingly, the present study explored neuropsychological and neurophysiological parameters during VSA tasks among badminton players of varying competitive levels. The study included 54 participants and divided them into three groups according to their competition records: elite (n = 18), expert (n = 18), and intermediate (n = 18). Their neuropsychological performance and brain event-related potentials (ERPs) during the Posner cueing paradigm were collected. Although the three groups did not differ in their accuracy rates, ERP N2 amplitudes, or N2 or P3 latencies, the elite and expert groups exhibited notably faster reaction times and more pronounced P3 amplitudes than did the intermediate group during the cognitive task. However, we did not observe these between-group differences when we controlled for the covariate training years. Additionally, the elite and expert groups exhibited comparable neurocognitive performance. These findings indicate that badminton players' competitive levels influence their VSA. However, the beneficial effects on neuropsychological and neurophysiological performance could stabilize after a certain level of badminton competence is reached. Year of training could also be a major factor influencing badminton players' neurocognitive performance in VSA tasks.

Effects of attentional instructions on the behavioral and neural mechanisms of speech auditory feedback control.

The present study investigated how instructions for paying attention to auditory feedback may affect speech error detection and sensorimotor control. Electroencephalography (EEG) and speech signals were recorded from 21 neurologically intact adult subjects while they produced the speech vowel sound /a/ and received randomized ±100 cents pitch-shift alterations in their real-time auditory feedback. Subjects were instructed to pay attention to their auditory feedback and press a button to indicate whether they detected a pitch-shift stimulus during trials. Data for this group was compared with 22 matched subjects who completed the same speech task under altered auditory feedback condition without attentional instructions. Results revealed a significantly smaller magnitude of speech compensations in the attentional-instruction vs. no-instruction group and a positive linear association between the magnitude of compensations and P2 event-related potential (ERP) amplitudes. In addition, we found that the amplitude of P2 ERP component was significantly larger in the attentional-instruction vs. no-instruction group. Source localization analysis showed that this effect was accounted for by significantly stronger neural activities in the right hemisphere insula, precentral gyrus, postcentral gyrus, transverse temporal gyrus, and superior temporal gyrus in the attentional-instruction group. These findings suggest that attentional instructions may enhance speech auditory feedback error detection, and subsequently improve sensorimotor control via generating more stable speech outputs (i.e., smaller compensations) in response to pitch-shift alterations. Our data are informative for advancing theoretical models and motivating targeted interventions with a focus on the role of attentional instructions for improving treatment outcomes in patients with motor speech disorders.

Effects of 6-Month Combined Physical Exercise and Cognitive Training on Neuropsychological and Neurophysiological Function in Older Adults with Subjective Cognitive Decline: A Randomized Controlled Trial.

Background: Multidomain intervention may delay or ameliorate cognitive decline in older adults at risk of Alzheimer's disease, particularly in the memory and inhibitory functions. However, no study systematically investigates the changes of brain function in cognitively-normal elderly with subjective cognitive decline (SCD) when they receive multidomain intervention. Objective: We aimed to examine whether a multidomain intervention could improve neuropsychological function and neurophysiological activities related to memory and inhibitory function in SCD subjects. Methods: Eight clusters with a total of 50 community-dwelling SCD older adults were single-blind, randomized into intervention group, which received physical and cognitive training, or control group, which received treatment as usual. For the neuropsychological function, a composite Z score from six cognitive tests was calculated and compared between two groups. For the neurophysiological activities, event-related potentials (ERPs) of memory function, including mismatch negativity (MMN) and memory-P3, as well as ERPs of inhibitory function, including sensory gating (SG) and inhibition-P3, were measured. Assessments were performed at baseline (T1), end of the intervention (T2), and 6 months after T2 (T3). Results: For the neuropsychological function, the effect was not observed after the intervention. For the neurophysiological activities, improved MMN responses of ΔT2-T1 were observed in the intervention group versus the control group. The multidomain intervention produced a sustained effect on memory-P3 latencies of ΔT3-T1. However, there were no significant differences in changes of SG and inhibition-P3 between intervention and control groups. Conclusions: While not impactful on neuropsychological function, multidomain intervention enhances specific neurophysiological activities associated with memory function.

Does Transcranial Direct Current Stimulation Affect Potential P300-Related Events in Vascular Dementia? Considerations from a Pilot Study.

Vascular dementia, the second most common type of dementia, currently lacks a definitive cure. In the pursuit of therapies aimed at slowing its progression and alleviating symptoms, transcranial direct current stimulation (tDCS) emerges as a promising approach, characterized by its non-invasive nature and the ability to promote brain plasticity. In this study, the primary objective was to investigate the effects of a two-week cycle of tDCS on the dorsolateral prefrontal cortex (DLPFC) and neurophysiological functioning in thirty patients diagnosed with vascular dementia. Each participant was assigned to one of two groups: the experimental group, which received anodal tDCS to stimulate DPCFL, and the control group, which received sham tDCS. Neurophysiological functions were assessed before and after tDCS using P300 event-related potentials (ERPs), while neuropsychological function was evaluated through a Mini-Mental State Examination (MMSE). The results showed a reduction in P300 latency, indicating a faster cognitive process; an increase in P300 amplitude, suggesting a stronger neural response to cognitive stimuli; and a significant improvement in MMSE scores compared to the control group, indicating an overall enhancement in cognitive functions. These findings suggest that tDCS could represent a promising therapeutic option for improving both neurophysiological and cognitive aspects in patients with vascular dementia.

An auto-segmented multi-time window dual-scale neural network for brain-computer interfaces based on event-related potentials.

Objective.Event-related potentials (ERPs) are cerebral responses to cognitive processes, also referred to as cognitive potentials. Accurately decoding ERPs can help to advance research on brain-computer interfaces (BCIs). The spatial pattern of ERP varies with time. In recent years, convolutional neural networks (CNNs) have shown promising results in electroencephalography (EEG) classification, specifically for ERP-based BCIs.Approach.This study proposes an auto-segmented multi-time window dual-scale neural network (AWDSNet). The combination of a multi-window design and a lightweight base network gives AWDSNet good performance at an acceptable cost of computing. For each individual, we create a time window set by calculating the correlation of signedR-squared values, which enables us to determine the length and number of windows automatically. The signal data are segmented based on the obtained window sets in sub-plus-global mode. Then, the multi-window data are fed into a dual-scale CNN model, where the sizes of the convolution kernels are determined by the window sizes. The use of dual-scale spatiotemporal convolution focuses on feature details while also having a large enough receptive length, and the grouping parallelism undermines the increase in the number of parameters that come with dual scaling.Main results.We evaluated the performance of AWDSNet on a public dataset and a self-collected dataset. A comparison was made with four popular methods including EEGNet, DeepConvNet, EEG-Inception, and PPNN. The experimental results show that AWDSNet has excellent classification performance with acceptable computational complexity.Significance.These results indicate that AWDSNet has great potential for applications in ERP decoding.

Probing a neural unreliability account of auditory sensory processing atypicalities in Rett Syndrome.

BACKGROUND: In the search for objective tools to quantify neural function in Rett Syndrome (RTT), which are crucial in the evaluation of therapeutic efficacy in clinical trials, recordings of sensory-perceptual functioning using event-related potential (ERP) approaches have emerged as potentially powerful tools. Considerable work points to highly anomalous auditory evoked potentials (AEPs) in RTT. However, an assumption of the typical signal-averaging method used to derive these measures is "stationarity" of the underlying responses - i.e. neural responses to each input are highly stereotyped. An alternate possibility is that responses to repeated stimuli are highly variable in RTT. If so, this will significantly impact the validity of assumptions about underlying neural dysfunction, and likely lead to overestimation of underlying neuropathology. To assess this possibility, analyses at the single-trial level assessing signal-to-noise ratios (SNR), inter-trial variability (ITV) and inter-trial phase coherence (ITPC) are necessary. METHODS: AEPs were recorded to simple 100 Hz tones from 18 RTT and 27 age-matched controls (Ages: 6-22 years). We applied standard AEP averaging, as well as measures of neuronal reliability at the single-trial level (i.e. SNR, ITV, ITPC). To separate signal-carrying components from non-neural noise sources, we also applied a denoising source separation (DSS) algorithm and then repeated the reliability measures. RESULTS: Substantially increased ITV, lower SNRs, and reduced ITPC were observed in auditory responses of RTT participants, supporting a "neural unreliability" account. Application of the DSS technique made it clear that non-neural noise sources contribute to overestimation of the extent of processing deficits in RTT. Post-DSS, ITV measures were substantially reduced, so much so that pre-DSS ITV differences between RTT and TD populations were no longer detected. In the case of SNR and ITPC, DSS substantially improved these estimates in the RTT population, but robust differences between RTT and TD were still fully evident. CONCLUSIONS: To accurately represent the degree of neural dysfunction in RTT using the ERP technique, a consideration of response reliability at the single-trial level is highly advised. Non-neural sources of noise lead to overestimation of the degree of pathological processing in RTT, and denoising source separation techniques during signal processing substantially ameliorate this issue.

Potentiation of the muscarinic acetylcholine receptor 1 modulates neurophysiological features in a mouse model of Rett syndrome.

Rett syndrome (RTT) is a neurodevelopmental disorder primarily caused by mutations in the X chromosome-linked gene Methyl-CpG Binding Protein 2 (MECP2). Restoring MeCP2 expression after disease onset in a mouse model of RTT reverses phenotypes, providing hope for development of treatments for RTT. Translatable biomarkers of improvement and treatment responses have the potential to accelerate both preclinical and clinical evaluation of targeted therapies in RTT. Studies in people with and mouse models of RTT have identified neurophysiological features, such as auditory event-related potentials, that correlate with disease severity, suggesting that they could be useful as biomarkers of disease improvement or early treatment response. We recently demonstrated that treatment of RTT mice with a positive allosteric modulator (PAM) of muscarinic acetylcholine subtype 1 receptor (M1) improved phenotypes, suggesting that modulation of M1 activity is a potential therapy in RTT. To evaluate whether neurophysiological features could be useful biomarkers to assess the effects of M1 PAM treatment, we acutely administered the M1 PAM VU0486846 (VU846) at doses of 1, 3, 10 and 30 â€‹mg/kg in wildtype and RTT mice. This resulted in an inverted U-shaped dose response with maximal improvement of AEP features at 3 â€‹mg/kg but with no marked effect on basal EEG power or epileptiform discharges in RTT mice and no significant changes in wildtype mice. These findings suggest that M1 potentiation can improve neural circuit synchrony to auditory stimuli in RTT mice and that neurophysiological features have potential as pharmacodynamic or treatment-responsive biomarkers for preclinical and clinical evaluation of putative therapies in RTT.

Unsupervised separation of nonlinearly mixed event-related potentials using manifold clustering and non-negative matrix factorization.

Event-related potentials (ERPs) can quantify brain responses to reveal the neural mechanisms of sensory perception. However, ERPs often reflect nonlinear mixture responses to multiple sources of sensory stimuli, and an accurate separation of the response to each stimulus remains a challenge. This study aimed to separate the ERP into nonlinearly mixed source components specific to individual stimuli. We developed an unsupervised learning method based on clustering of manifold structures of mixture signals combined with channel optimization for signal source reconstruction using non-negative matrix factorization (NMF). Specifically, we first implemented manifold learning based on Local Tangent Space Alignment (LTSA) to extract the spatial manifold structure of multi-resolution sub-signals separated via wavelet packet transform. We then used fuzzy entropy to extract the dynamical process of the manifold structures and performed a k-means clustering to separate different sources. Lastly, we used NMF to obtain the optimal contributions of multiple channels to ensure accurate source reconstructions. We evaluated our developed approach using a simulated ERP dataset with known ground truth of two components of ERP mixture signals. Our results show that the correlation coefficient between the reconstructed source signal and the true source signal was 92.8 % and that the separation accuracy in ERP amplitude was 91.6 %. The results show that our unsupervised separation approach can accurately separate ERP signals from nonlinear mixture source components. The outcomes provide a promising way to isolate brain responses to multiple stimulus sources during multisensory perception.

Modulation of brain function and antidepressant effects by transcranial alternating current stimulation in patients with major depressive disorder: Evidence from ERP.

Transcranial alternating current stimulation (tACS) is an emerging non-invasive neuromodulation treatment for major depressive disorder (MDD), but its mechanism remains unclear. Therefore, we evaluated the effects of tACS on event-related potentials (ERP) based on a randomized controlled study. All patients were divided into two groups to receive either 20 sessions 77.5Hz-tACS or 20 sessions of sham stimulation during 4 weeks. The Hamilton Depression Rating Scale for Depression -17 item (HAMD-17) and ERP during face-word Stroop task were recorded before and after the treatment (the fourth weekend). Our findings indicate a significant alleviation of depressive symptoms after tACS. For the behavioral performance, sham group showed a significant decrease in reaction time to the sad incongruent condition and an increase in accuracy to the happy condition. The active group showed an increase in accuracy to the incongruent condition. ERP analysis revealed that tACS significantly shortened the latency of P2 to incongruent condition, decreased the amplitude and prolonged the latency of N2 to negative condition. These ERP alterations suggest a potential rectification of negative bias and enhancement of cognitive functioning in patients with MDD, offering insights into the antidepressant mechanisms of tACS.

From lab to life: assessing the impact of real-world interactions on the operation of rapid serial visual presentation-based brain-computer interfaces.

Objective.Brain-computer interfaces (BCI) have been extensively researched in controlled lab settings where the P300 event-related potential (ERP), elicited in the rapid serial visual presentation (RSVP) paradigm, has shown promising potential. However, deploying BCIs outside of laboratory settings is challenging due to the presence of contaminating artifacts that often occur as a result of activities such as talking, head movements, and body movements. These artifacts can severely contaminate the measured EEG signals and consequently impede detection of the P300 ERP. Our goal is to assess the impact of these real-world noise factors on the performance of a RSVP-BCI, specifically focusing on single-trial P300 detection.Approach.In this study, we examine the impact of movement activity on the performance of a P300-based RSVP-BCI application designed to allow users to search images at high speed. Using machine learning, we assessed P300 detection performance using both EEG data captured in optimal recording conditions (e.g. where participants were instructed to refrain from moving) and a variety of conditions where the participant intentionally produced movements to contaminate the EEG recording.Main results.The results, presented as area under the receiver operating characteristic curve (ROC-AUC) scores, provide insight into the significant impact of noise on single-trial P300 detection. Notably, there is a reduction in classifier detection accuracy when intentionally contaminated RSVP trials are used for training and testing, when compared to using non-intentionally contaminated RSVP trials.Significance.Our findings underscore the necessity of addressing and mitigating noise in EEG recordings to facilitate the use of BCIs in real-world settings, thus extending the reach of EEG technology beyond the confines of the laboratory.

Differences in visuospatial cognition among table tennis players of different skill levels: an event-related potential study.

This study aimed to examine the influence of sport skill levels on behavioural and neuroelectric performance in visuospatial attention and memory visuospatial tasks were administered to 54 participants, including 18 elite and 18 amateur table tennis players and 18 nonathletes, while event-related potentials were recorded. In all the visuospatial attention and memory conditions, table tennis players displayed faster reaction times than nonathletes, regardless of skill level, although there was no difference in accuracy between groups. In addition, regardless of task conditions, both player groups had a greater P3 amplitude than nonathletes, and elite players exhibited a greater P3 amplitude than amateurs players. The results of this study indicate that table tennis players, irrespective of their skill level, exhibit enhanced visuospatial capabilities. Notably, athletes at the elite level appear to benefit from an augmented allocation of attentional resources when engaging in visuospatial tasks.

Using Event-Related Potentials to Evidence the Visual and Semantic Impact: A Pilot Study with N400 Effect and Food Packaging.

Packaging design is pivotal in motivating consumer decisions, as a key communication tool from creation to purchase. Currently, the interpretation and evaluation of packaging's impact are shifting toward non-traditional methods. This pilot study evaluated the packaging perception of York Ham and Turkey Breast products. The event-related potential (ERP) technique, the methodology priming words (positive and negative), and target images (original and modified packaging) were applied. A total of 23 participants were sampled using a 32-channels scalp elastic electrode cap and viewed 200 trials of word-image matching. Participants responded whether the images and adjectives matched or not, using the two groups of images. The results demonstrate an N400 effect in the parietal area. This region was observed to show evidence of cognitive processing related to congruency or incongruency, by contrasting the priming and target of this study. The evaluation positioned the York Ham packaging as the best rated. The findings show a relevant contribution to ERPs and research related to the food packaging perception.

The prediction potential indexes the meaning and communicative function of upcoming utterances.

Prediction has a fundamental role in language processing. However, predictions can be made at different levels, and it is not always clear whether speech sounds, morphemes, words, meanings, or communicative functions are anticipated during dialogues. Previous studies reported specific brain signatures of communicative pragmatic function, in particular enhanced brain responses immediately after encountering an utterance used to request an object from a partner, but relatively smaller ones when the same utterance was used for naming the object. The present experiment now investigates whether similar neuropragmatic signatures emerge in recipients before the onset of upcoming utterances carrying different predictable communicative functions. Trials started with a context question and object pictures displayed on the screen, raising the participant's expectation that words from a specific semantic category (food or tool) would subsequently be used to either name or request one of the objects. Already 600 msec before utterance onset, a larger prediction potential was observed when a request was anticipated relative to naming expectation. As this result is congruent with the neurophysiological difference previously observed right after the critical utterance, the anticipatory brain activity may index predictions about the social-communicative function of upcoming utterances. In addition, we also found that the predictable semantic category of the upcoming word was likewise reflected in the anticipatory brain potential. Thus, the neurophysiological characteristics of the prediction potential can capture different types of upcoming linguistic information, including semantic and pragmatic aspects of an upcoming utterance and communicative action.

Study Protocol: Global Research Initiative on the Neurophysiology of Schizophrenia (GRINS) project.

BACKGROUND: Objective and quantifiable markers are crucial for developing novel therapeutics for mental disorders by 1) stratifying clinically similar patients with different underlying neurobiological deficits and 2) objectively tracking disease trajectory and treatment response. Schizophrenia is often confounded with other psychiatric disorders, especially bipolar disorder, if based on cross-sectional symptoms. Awake and sleep EEG have shown promise in identifying neurophysiological differences as biomarkers for schizophrenia. However, most previous studies, while useful, were conducted in European and American populations, had small sample sizes, and utilized varying analytic methods, limiting comprehensive analyses or generalizability to diverse human populations. Furthermore, the extent to which wake and sleep neurophysiology metrics correlate with each other and with symptom severity or cognitive impairment remains unresolved. Moreover, how these neurophysiological markers compare across psychiatric conditions is not well characterized. The utility of biomarkers in clinical trials and practice would be significantly advanced by well-powered transdiagnostic studies. The Global Research Initiative on the Neurophysiology of Schizophrenia (GRINS) project aims to address these questions through a large, multi-center cohort study involving East Asian populations. To promote transparency and reproducibility, we describe the protocol for the GRINS project. METHODS: The research procedure consists of an initial screening interview followed by three subsequent sessions: an introductory interview, an evaluation visit, and an overnight neurophysiological recording session. Data from multiple domains, including demographic and clinical characteristics, behavioral performance (cognitive tasks, motor sequence tasks), and neurophysiological metrics (both awake and sleep electroencephalography), are collected by research groups specialized in each domain. CONCLUSION: Pilot results from the GRINS project demonstrate the feasibility of this study protocol and highlight the importance of such research, as well as its potential to study a broader range of patients with psychiatric conditions. Through GRINS, we are generating a valuable dataset across multiple domains to identify neurophysiological markers of schizophrenia individually and in combination. By applying this protocol to related mental disorders often confounded with each other, we can gather information that offers insight into the neurophysiological characteristics and underlying mechanisms of these severe conditions, informing objective diagnosis, stratification for clinical research, and ultimately, the development of better-targeted treatment matching in the clinic.