Analysis Of Event-related Potentials Research Articles

Effects of a Functional Cone Mushroom (Termitomyces fuliginosus) Protein Snack Bar on Cognitive Function in Middle Age: A Randomized Double-Blind Placebo-Controlled Trial

Background: Due to the rising prevalence of cognitive impairment in the middle-aged and elderly population, combined with consumer demand for functional foods to improve health and well-being. Objective: This study aimed to formulate a functional cone mushroom (Termitomyces fuliginosus) (FCM) protein snack bar and evaluate its amino acid profile, phytochemical contents, biological activity and impact on cognitive function. Methods: A total of 26 middle-aged male and female participants were randomized and divided into placebo, FCM1 and FCM2 groups. Continuous consumption was performed for 6 weeks. Demographic data, body composition, cognitive function and memory were evaluated at baseline and at the end of the study period (6 weeks). Results: The event-related potential (ERP) analysis results showed a significant increase in N100 and P300 amplitude at the Fz location in participants who consumed the functional cone mushroom protein snack bar at a dose of 1 g compared to the placebo group (p = 0.015). Additionally, subjects who consumed the functional cone mushroom protein snack bar at a dose of 2 g showed a significantly increased P300 amplitude and percent accuracy of numeric working memory (p = 0.048) compared to those in the placebo group (p = 0.044). The possible underlying mechanism may involve AChE and MAO suppression activity alongside antioxidant activity. Conclusions: These data suggest that FCM can improve cognitive function and memory and may be considered for use in natural supplementation products with possible health benefits.

What guides the judgment of learning: Memory or heuristics? An event-related potential study

Memory monitoring ability is essential for the effectiveness of learning processes. Judgment of Learning (JOL), a metacognitive judgment, is commonly used to measure this ability. An ongoing debate questions whether JOL is an outcome of an inferential or recollective experience, as suggested by different hypotheses regarding the underlying cognitive mechanisms of this judgment. To address this question through a neuroscientific perspective, we aimed to investigate the temporal dynamic of JOL adopting event-related potential (ERP) methodology. Seventy-two young adults participated in an episodic memory task involving word-pairs as stimuli. Their JOLs were obtained through categorical choices in a delayed condition. Additionally, their memory performance was tested in the recognition phase. ERP components were compared for different JOL levels, as well as for the hit responses in the recognition test according to their JOL levels. The analyses showed that JOL processes are observable within an early time window after stimulus presentation, as evidenced by elicitation of the P100, N100, P200, N200, and P300 components across all JOL levels. However, only the amplitude of the N100 varied among these levels. A negative ERP component with 330–500 ms latency was also evident for all JOL levels in the central and parietal electrodes, which did not differ in amplitude. The analyses of the recognition phase ERPs showed that the hit responses did not exhibit a significant difference in the familiarity-related mid-frontal old/new effect (FN400) amplitude; however, those with high level of JOL elicited recollection-related parietal old-new effect with a smaller amplitude. These findings support both hypotheses suggesting that JOL is influenced by heuristics and the retrievability of information.

Evaluating attentional responses to electric vehicle driving noise through event-related potentials: a frequency bands analysis

The advent of electric vehicles (EVs), known for their quieter operation compared to Internal Combustion Engine (ICE) vehicles, has shifted auditory attention towards wind and road noise. This shift is further accentuated by the anticipated future dominance of autonomous vehicles, which is expected to reduce the cognitive demands of driving, potentially heightening sensitivity to external noise and leading to increased annoyance and discomfort. This research investigates the impact of driving noise on selective attention by identifying sounds that significantly disrupt adaptation to driving noise through the analysis of event-related potentials (ERPs). Unlike previous studies that concentrated on the peak high-frequency driving noise fluctuations around 1000 Hz, our study explores a broader spectrum of higher frequencies. By recording brain responses to driving-related auditory stimuli, we detected variations in ERPs across different frequency bands, thereby pinpointing the acoustic characteristics most disruptive to concentration. Our findings aim to contribute towards enhancing driver focus and improving the acoustic comfort inside vehicle cabins.

Temporal and spatial analysis of event-related potentials in response to color saliency differences among various color vision types.

Human color vision exhibits significant diversity that cannot be fully explained by categorical classifications. Understanding how individuals with different color vision phenotypes perceive, recognize, and react to the same physical stimuli provides valuable insights into sensory characteristics. This study aimed to identify behavioral and neural differences between different color visions, primarily classified as typical trichromats and anomalous trichromats, in response to two chromatic stimuli, blue-green and red, during an attention-demanding oddball task. We analyzed the P3 component of event-related potentials (ERPs), associated with attention, and conducted a broad spatiotemporal exploration of neural differences. Behavioral responses were also analyzed to complement neural data. Participants included typical trichromats (n = 13) and anomalous trichromats (n = 5), and the chromatic stimuli were presented in an oddball paradigm. Typical trichromats exhibited faster potentiation from the occipital to parietal regions in response to the more salient red stimulus, particularly in the area overlapping with the P3 component. In contrast, anomalous trichromats revealed faster potentiation to the expected more salient blue-green stimulus in the occipital to parietal regions, with no other significant neural differences between stimuli. Comparisons between the color vision types showed no significant overall neural differences. The large variability in red-green sensitivity among anomalous trichromats, along with neural variability not fully explained by this sensitivity, likely contributed to the absence of clear neural distinctions based on color saliency. While reaction times were influenced by red-green sensitivity, neural signals showed ambiguity regarding saliency differences. These findings suggest that factors beyond red-green sensitivity influenced neural activity related to color perception and cognition in minority color vision phenotypes. Further research with larger sample sizes is needed to more comprehensively explore these neural dynamics and their broader implications.

Threatening an Illusory Limb: An Event-related Potential Study of the Rubber Hand Illusion.

The rubber hand illusion (RHI) is a well-established method for studying body ownership: Given adequate concordance of visual, sensory, and proprioceptive stimuli, the individual experiences a rubber hand as his or her own. To study the effects of a threat to the rubber hand. We created a typical RHI paradigm but added threatening pain: Both the real hand of an individual and the rubber hand were stroked with a brush, either synchronously (RHI-inducing condition) or asynchronously (control condition), but only the rubber hand was then pricked with a needle to create a threatening pain condition. Event-related potentials (ERPs) were recorded in a group of 23 typically-developed individuals. ERP effects were source-localized using low-resolution electromagnetic tomography. The individuals consistently reported experience of the RHI during the experiment when the brush strokes were applied synchronously to both the real hand and the rubber hand. ERP analysis revealed that synchronous brush stroking gave rise to higher amplitude of frontal ERPs in the 100-200 ms range than asynchronous brush stroking, which was interpreted as reflecting the RHI. In the threatening pain condition, ERPs showed a greater positivity at frontocentral electrodes, source localized in the supplementary motor area (SMA). SMA activation could reflect a control mechanism over reflexive motor activity, facilitating a possible threat-related response. Further studies should address ERP effects and the extent of the RHI to standard and threat stimuli in a correlative fashion to further elucidate the functional significance of the neurophysiological findings.

Brain Evoked Response Qualification Using Multi-Set Consensus Clustering: Toward Single-Trial EEG Analysis.

In event-related potential (ERP) analysis, it is commonly assumed that individual trials from a subject share similar properties and originate from comparable neural sources, allowing reliable interpretation of group-averages. Nevertheless, traditional group-level ERP analysis methods, including cluster analysis, often overlook critical information about individual subjects' neural processes due to using fixed measurement intervals derived from averaging. We developed a multi-set consensus clustering pipeline to examine cognitive processes at the individual subject level. Initially, consensus clustering from diverse methods was applied to single-trial EEG epochs of individual subjects. Subsequently, a second level of consensus clustering was performed across the trials of each subject. A newly modified time window determination method was then employed to identify individual subjects' ERP(s) of interest. We validated our method with simulated data for ERP components N2 and P3, and real data from a visual oddball task to confirm the P3 component. Our findings revealed that estimated time windows for individual subjects provide precise ERP identification compared to fixed time windows across all subjects. Additionally, Monte Carlo simulations with synthetic single-trial data demonstrated stable scores for the N2 and P3 components, confirming the reliability of our method. The proposed method enhances the examination of brain-evoked responses at the individual subject level by considering single-trial EEG data, thereby extracting mutual information relevant to the neural process. This approach offers a significant improvement over conventional ERP analysis, which relies on the averaging mechanism and fixed measurement interval.

Impaired cognitive flexibility in major depressive disorder: Evidences from spatial-temporal ERPs analysis

BackgroundMajor Depressive Disorder (MDD) may exhibit impairments in cognitive flexibility. This study investigated whether the cognitive flexibility deficits in MDD are evident across general stimuli or specific to emotional stimuli, while exploring the underlying neuropsychological mechanism. MethodsA total of 41 MDD patients and 42 healthy controls (HCs) were recruited. Event-related potentials (ERPs) were recorded when participants performed a non-emotional and an emotional task switching paradigm (N-ETSP and ETSP), both of which assessed cognitive flexibility. Microstate and source localization analysis were applied to reflect brain activity among different brain areas during task switching. ResultsIn the N-ETSP, MDD group showed larger P3 difference wave (Pd3) amplitudes and longer P2 difference wave (Pd2) latencies. In the ETSP, MDD group displayed smaller N2 difference wave (Nd2) amplitudes and larger Pd3 amplitudes. The comparison of sLORETA images of emotional switch task and emotional repeat task showed that MDD group had increased activation in the precentral gyrus in microstate2 of the P2 time window and had reduced activation in the middle occipital gyrus in microstate3 of the N2 time window. LimitationsThe cross-sectional design failed to capture dynamic changes in cognitive flexibility in MDD. ConclusionsMDD demonstrated impaired cognitive flexibility respond to both non-emotional and emotional stimuli, with greater impairment for negative emotional stimuli. These deficits are evident in abnormal ERPs component during the early attention stage and the later task preparation stage. Furthermore, abnormal emotional switching cost in MDD appears to be related to early abnormal perceptual control in the parietal-occipital cortex.

Memorization-Based Training and Testing Paradigm for Robust Vocal Identity Recognition in Expressive Speech Using Event-Related Potentials Analysis.

Recognizing familiar speakers from vocal streams is a fundamental aspect of human verbal communication. However, it remains unclear how listeners can still discern the speaker's identity in expressive speech. This study develops a memorization-based individual speaker identity recognition approach and an accompanying electroencephalogram (EEG) data analysis pipeline, which monitors how listeners recognize familiar speakers and tell unfamiliar ones apart. EEG data captures online cognitive processes during new versus old speaker distinction based on voice, offering a real-time measure of brain activity, overcoming limits of reaction times and accuracy measurements. The paradigm comprises three steps: listeners establish associations between three voices and their names (training); listeners indicate the name corresponding to a voice from three candidates (checking); listeners distinguish between three old and three new speaker voices in a two-alternative forced-choice task (testing). The speech prosody in testing was either confident or doubtful. EEG data were collected using a 64-channel EEG system, followed by preprocessing and imported into RStudio for ERP and statistical analysis and MATLAB for brain topography. Results showed an enlarged late positive component (LPC) was elicited in the old-talker compared to the new-talker condition in the 400-850 ms window in the Pz and other wider range of electrodes in both prosodies. Yet, the old/new effect was robust in central and posterior electrodes for doubtful prosody perception, whereas the anterior, central, and posterior electrodes are for confident prosody condition. This study proposes that this experiment design can serve as a reference for investigating speaker-specific cue-binding effects in various scenarios (e.g., anaphoric expression) and pathologies in patients like phonagnosia.

Employing Siamese Networks as Quantitative Biomarker for Assessing the Effect of Dolphin-Assisted Therapy on Pediatric Cerebral Palsy.

This study explores the potential of using a Siamese Network as a biomarker for assessing the effectiveness of Dolphin-Assisted Therapy (DAT) in children with Spastic Cerebral Palsy (SCP). The problem statement revolves around the need for objective measures to evaluate the impact of DAT on patients with SCP, considering the subjective nature of traditional assessment methods. The methodology involves training a Siamese network, a type of neural network designed to compare similarities between inputs, using data collected from SCP patients undergoing DAT sessions. The study employed Event-Related Potential (ERP) and Fast Fourier Transform (FFT) analyses to examine cerebral activity and brain rhythms, proposing the use of SNN to compare electroencephalographic (EEG) signals of children with cerebral palsy before and after Dolphin-Assisted Therapy. Testing on samples from four children yielded a high average similarity index of 0.9150, indicating consistent similarity metrics before and after therapy. The network is trained to learn patterns and similarities between pre- and post-therapy evaluations, in order to identify biomarkers indicative of therapy effectiveness. Notably, the Siamese Network's architecture ensures that comparisons are made within the same feature space, allowing for more accurate assessments. The results of the study demonstrate promising findings, indicating different patterns in the output of the Siamese Network that correlate with improvements in symptoms of SCP post-DAT. Confirming these observations will require large, longitudinal studies but such findings would suggest that the Siamese Network could have utility as a biomarker in monitoring treatment responses for children with SCP who undergo DAT and offer them more objective as well as quantifiable manners of assessing therapeutic interventions. Great discrepancies in neuronal voltage perturbations, 7.9825 dB on average at the specific samples compared to the whole dataset (6.2838 dB), imply a noted deviation from resting activity. These findings indicate that Dolphin-Assisted Therapy activates particular brain regions specifically during the intervention.

Dorsal Anterior Cingulate Cortex Coordinates Contextual Mental Imagery for Single-Beat Manipulation during Rhythmic Sensorimotor Synchronization.

Flexible pulse-by-pulse regulation of sensorimotor synchronization is crucial for voluntarily showing rhythmic behaviors synchronously with external cueing; however, the underpinning neurophysiological mechanisms remain unclear. We hypothesized that the dorsal anterior cingulate cortex (dACC) plays a key role by coordinating both proactive and reactive motor outcomes based on contextual mental imagery. To test our hypothesis, a missing-oddball task in finger-tapping paradigms was conducted in 33 healthy young volunteers. The dynamic properties of the dACC were evaluated by event-related deep-brain activity (ER-DBA), supported by event-related potential (ERP) analysis and behavioral evaluation based on signal detection theory. We found that ER-DBA activation/deactivation reflected a strategic choice of motor control modality in accordance with mental imagery. Reverse ERP traces, as omission responses, confirmed that the imagery was contextual. We found that mental imagery was updated only by environmental changes via perceptual evidence and response-based abductive reasoning. Moreover, stable on-pulse tapping was achievable by maintaining proactive control while creating an imagery of syncopated rhythms from simple beat trains, whereas accuracy was degraded with frequent erroneous tapping for missing pulses. We conclude that the dACC voluntarily regulates rhythmic sensorimotor synchronization by utilizing contextual mental imagery based on experience and by creating novel rhythms.

Neuromechanical proficiency in elite performance decision-making: An event-related potential (ERP) analysis

This research focuses intensively on the neural mechanisms of action selection responses in elite athletes during high-stakes decision-making. It emphasizes the neuromechanical dimensions of these processes, contrasting the responses of expert and novice players within a theoretical framework of neural information processing in high-performance contexts. Utilizing advanced EEG technologies, including event-related potential (ERP) analysis, the study captures a comprehensive view of both behavioral and neurophysiological data. The central aim is to unravel the intricate neural underpinnings that distinguish elite athletes in their decision-making strategies. Key findings highlight: (1) Enhanced accuracy and swifter reaction times in elite athletes during the action selection phase; (2) Significant neurophysiological differences, marked by pronounced N1 peak amplitudes with prolonged latencies, reduced P2 peak amplitudes with stable latencies, decreased P3 peak amplitudes with reduced latencies, and increased average PSW amplitudes. These discoveries significantly advance our understanding of the neural foundations of expert decision-making in high-performance sports. This study not only sheds light on the cognitive and neural dynamics of elite sports performance but also provides a foundation for developing training and performance enhancement techniques in various high-stakes domains.

Attenuated conflict self-referential information facilitating conflict resolution

Self-referential information can reduce the congruency effect by acting as a signal to enhance cognitive control. However, it cannot be denied that self-referential information can attract and hold attention. To investigate this issue, the study used a revised Stroop task and recorded behavioral and electrophysiological data from thirty-three participants. We combined event-related potential (ERP) and multivariate pattern analysis (MVPA) to examine the neural correlates of self-referential processing and conflict processing. In the behavioral results, self-referential information reduced the congruency effect. Specifically, self-reference stimuli elicited smaller N2 amplitude than non-self-reference stimuli, indicating that self-referential information was promptly identified and reduced top-down cognitive resource consumption. Self-referential information could be reliably decoded from ERP signals in the early-to-mid stage. Moreover, self-reference conditions exhibited earlier congruency decoding than non-self-reference conditions, facilitating conflict monitoring. In the late stage, under the incongruent condition, self-reference stimuli elicited smaller sustained potential amplitude than non-self-reference stimuli, indicating that cognitive control in the self-reference condition required fewer cognitive resources for conflict resolution. Together, these findings revealed that self-referential information was identified and facilitated conflict monitoring, leading to more effective conflict resolution.

Blunted stimulus-preceding negativity during reward anticipation in major depressive disorder

BackgroundReward processing dysfunction is a core characteristic of major depressive disorder (MDD), yet event-related potential (ERP) research in MDD has predominantly focused on reward receipt as opposed to anticipation. The stimulus-preceding negativity (SPN) ERP reflects anticipatory brain processing. This study examines whether individuals with MDD exhibit deficits during reward anticipation as evidenced by altered SPN amplitude. MethodsWe assessed prefeedback-SPN amplitudes during a monetary incentive delay (MID) task in individuals with MDD (n = 142, 99 with comorbid anxiety disorders [MDD + ANX]) compared to Controls (n = 37). A mixed analysis of variance was performed on prefeedback-SPN amplitude and behavioral measures, with group (MDD, MDD + ANX, Control) as the between-subjects factor, and feedback (gain, loss) and electrode (F3, F4, Fz, C3, C4, Cz, P3, P4, Pz) as within-subjects factors. ResultsA group main effect revealed faster reaction times for the Control group than MDD and MDD + ANX groups. A group x feedback interaction indicated that the MDD subgroup had smaller prefeedback-SPN amplitudes than MDD + ANX and Control groups when anticipating gain feedback. Additionally, individuals with current MDD, irrespective of past MDD and comorbid anxiety, exhibited smaller SPN amplitudes than Controls prior to gain feedback. LimitationsThe MID paradigm, designed for functional magnetic resonance imaging (fMRI) data acquisition, lacks optimization for ERP analysis. Moreover, the clinical groups included more females than the Control group. ConclusionsReduced resource allocation to reward anticipation may differentiate MDD from MDD + ANX and Control groups. Further investigation of the neural mechanisms of distinct MDD phenotypes is warranted.

The time course of semantic ambiguity in visual word recognition: behavioral and ERP evidence for the lexical-semantic effect.

Homonyms are words with multiple, unrelated meanings that share a single form and pronunciation. These words provide valuable insights into how semantic representation is retrieved and selected independently of orthography and phonology. This study aims to investigate the temporal dynamics of lexical and semantic processing in the visual recognition of Korean words. Specifically, we examine how homonyms and unambiguous words are processed differently during a lexical decision task (LDT) with EEG recording, considering the effects of word frequency and the number of meanings (NOMs). Participants performed a lexical decision task where they were required to determine if a visually presented stimulus was a valid Korean word. We compared the behavioral responses and event-related potentials (ERPs) evoked by homonyms and unambiguous words, each possessing either high or low word frequency. Both subjective and objective NOMs were measured and manipulated, while controlling for the subjective balance of individual frequencies of meanings to control for confounding from the relatedness of meaning (ROM). For ERP analysis, a non-parametric cluster-based permutation test was employed in addition to the two time windows of interest (i.e., N400 and P600). Behavioral results indicated a marginally significant interaction between word frequency and semantic ambiguity along with a main effect of word frequency, showing faster and more accurate responses for high-frequency words. An ambiguity advantage was observed only for low-frequency words, with no significant effect found for high-frequency words. ERP results revealed that lexical-semantic interactions were reflected in the modulations of the N400 and P600 components. High-frequency homonyms elicited an enhanced N400 amplitude, while low-frequency homonyms showed a reduced P600 amplitude. The findings suggest that the activation of semantic information occurs simultaneously with lexical processing, rather than during post-lexical or decision-making processes. Furthermore, considering balanced homonyms were employed in this study, inhibitory competition may arise from the high-frequency individual meanings of high-frequency words. In contrast, in low-frequency words, a facilitative effect may arise from gains in global semantic activation or semantic feedback to the orthographic level.

A Dynamic Multi-Scale Convolution Model for Face Recognition Using Event-Related Potentials.

With the development of data mining technology, the analysis of event-related potential (ERP) data has evolved from statistical analysis of time-domain features to data-driven techniques based on supervised and unsupervised learning. However, there are still many challenges in understanding the relationship between ERP components and the representation of familiar and unfamiliar faces. To address this, this paper proposes a model based on Dynamic Multi-Scale Convolution for group recognition of familiar and unfamiliar faces. This approach uses generated weight masks for cross-subject familiar/unfamiliar face recognition using a multi-scale model. The model employs a variable-length filter generator to dynamically determine the optimal filter length for time-series samples, thereby capturing features at different time scales. Comparative experiments are conducted to evaluate the model's performance against SOTA models. The results demonstrate that our model achieves impressive outcomes, with a balanced accuracy rate of 93.20% and an F1 score of 88.54%, outperforming the methods used for comparison. The ERP data extracted from different time regions in the model can also provide data-driven technical support for research based on the representation of different ERP components.

Identification of Methamphetamine Abusers Can Be Supported by EEG-Based Wavelet Transform and BiLSTM Networks

Methamphetamine (MA) is a neurological drug, which is harmful to the overall brain cognitive function when abused. Based on this property of MA, people can be divided into those with MA abuse and healthy people. However, few studies to date have investigated automatic detection of MA abusers based on the neural activity. For this reason, the purpose of this research was to investigate the difference in the neural activity between MA abusers and healthy persons and accordingly discriminate MA abusers. First, we performed event-related potential (ERP) analysis to determine the time range of P300. Then, the wavelet coefficients of the P300 component were extracted as the main features, along with the time and frequency domain features within the selected P300 range to classify. To optimize the feature set, F_score was used to remove features below the average score. Finally, a Bidirectional Long Short-term Memory (BiLSTM) network was performed for classification. The experimental result showed that the detection accuracy of BiLSTM could reach 83.85%. In conclusion, the P300 component of EEG signals of MA abusers is different from that in normal persons. Based on this difference, this study proposes a novel way for the prevention and diagnosis of MA abuse.

The relationship between frontal alpha asymmetry and behavioral and brain activity indices of reactive inhibitory control.

Reactive inhibitory control plays an important role in phenotype of different diseases/different phases of a disease. One candidate electrophysiological marker of inhibitory control is frontal alpha asymmetry (FAA). FAA reflects the relative difference in contralateral frontal brain activity. However, the relationship between FAA and potential behavioral/brain activity indices of reactive inhibitory control is not yet clear. We assessed the relationship between resting-state FAA and indicators of reactive inhibitory control. Additionally, we investigated the effect of modulation of FAA via transcranial direct current stimulation (tDCS). We implemented a randomized sham-controlled design with 65 healthy humans (Mage = 23.93, SDage = 6.08; 46 female). Before and after 2-mA anodal tDCS of the right frontal site (with the cathode at the contralateral site) for 20 min, we collected EEG data and reactive inhibitory performance in neutral and food-reward conditions, using the stop signal task (SST). There was no support for the effect of tDCS on FAA or any indices of reactive inhibitory control. Our correlation analysis revealed an association between inhibitory brain activity in the food-reward condition and (pre-tDCS) asymmetry. Higher right relative to left frontal brain activity was correlated with reduced early-onset inhibitory activity and, in contrast, linked with higher late-onset inhibitory control in the food-reward condition. Similarly, event-related potential analyses showed reduced early-onset and enhanced late-onset inhibitory brain activity over time, particularly in the food-reward condition. These results suggest that there can be a dissociation regarding the lateralization of frontal brain activity and early- and late-onset inhibitory brain activity.NEW & NOTEWORTHY This research reveals dissociation between baseline frontal alpha asymmetry and the timing of reactive inhibitory brain activities in food-reward contexts. Whereas inhibitory control performance decreases over time in a stop signal task, electrophysiological indices show reduced early- and heightened late-onset inhibitory brain activity, especially in the reward condition. Additionally, greater right frontal activity correlates with reduced early-onset and increased late-onset inhibitory brain activity.

Bayesian estimation of group event-related potential components (BEGEP): testing a model for synthetic and real datasets

Objective. The spatial resolution of event-related potentials (ERPs) recorded on the head surface is quite low, since the sensors located on the scalp register mixtures of signals from several cortical sources. Bayesian models for multi-channel ERPs obtained from a group of subjects under multiple task conditions can aid in recovering signals from these sources. Approach. This study introduces a novel model that captures several important characteristics of ERP, including person-to-person variability in the magnitude and latency of source signals. Furthermore, the model takes into account that ERP noise, the main source of which is the background electroencephalogram, has the following properties: it is spatially correlated, spatially heterogeneous, and varies over time and from person to person. Bayesian inference algorithms have been developed to estimate the parameters of this model, and their performance has been evaluated through extensive experiments using synthetic data and real ERPs records in a large number of subjects (N = 351). Main results. The signal estimates obtained using these algorithms were compared with the results of the analysis of ERPs by conventional methods. This comparison showed that the use of this model is suitable for the analysis of ERPs and helps to reveal some features of source signals that are difficult to observe in their mixture signals recorded on the scalp. Significance. This study shown that the proposed method is a potentially useful tool for analyzing ERPs collected from groups of subjects in various cognitive neuroscience experiments.

Effects of natural sound on human stress recovery based on EEG techniques

Natural sounds are an essential part of a restorative environment. Although numerous studies have established the positive impact of natural sounds on human health and well-being, few have examined the differences between natural sounds on human stress recovery. This study examined the impact of natural sounds on stress recovery by comparing a silent environment (control group) with three experimental groups exposed to flowing water sound, birdsong, and wind sounds. The investigation entailed the assessment of subjective assessments and EEG signals from 30 subjects (12 males and 18 females). The subjective evaluations indicated that the PRS scores for the sounds of flowing water and birdsong were superior to those of the silent environment. The EEG results revealed that EEG-α activity was more pronounced in response to natural sounds than the silent environment, with birdsong evoking the most significant EEG-α activity. Wind sounds increased the mental stress of the subjects. Conversely, birdsong and flowing water sound were beneficial for alleviating mental stress. Additionally, the analysis of event-related potentials (ERP) demonstrated that natural sounds elicited higher P300 amplitudes in central and parietal lobe sensors and had little effect on the frontal region. The study also demonstrated the correlation between EEG and subjective stress evaluations, providing insights into stress reduction theories and offering practical suggestions for optimizing the acoustic environment in urban settings.

Global Field Time-Frequency Representation-Based Discriminative Similarity Analysis of Passive Auditory ERPs for Diagnosis of Disorders of Consciousness.

Behavioural diagnosis of patients with disorders of consciousness (DOC) is challenging and prone to inaccuracies. Consequently, there have been increased efforts to develop bedside assessment based on EEG and event-related potentials (ERPs) that are more sensitive to the neural factors supporting conscious awareness. However, individual detection of residual consciousness using these techniques is less established. Here, we hypothesize that the cross-state similarity (defined as the similarity between healthy and impaired conscious states) of passive brain responses to auditory stimuli can index the level of awareness in individual DOC patients. To this end, we introduce the global field time-frequency representation-based discriminative similarity analysis (GFTFR-DSA). This method quantifies the average cross-state similarity index between an individual patient and our constructed healthy templates using the GFTFR as an EEG feature. We demonstrate that the proposed GFTFR feature exhibits superior within-group consistency in 34 healthy controls over traditional EEG features such as temporal waveforms. Second, we observed the GFTFR-based similarity index was significantly higher in patients with a minimally conscious state (MCS, 40 patients) than those with unresponsive wakefulness syndrome (UWS, 54 patients), supporting our hypothesis. Finally, applying a linear support vector machine classifier for individual MCS/UWS classification, the model achieved a balanced accuracy and F1 score of 0.77. Overall, our findings indicate that combining discriminative and interpretable markers, along with automatic machine learning algorithms, is effective for the differential diagnosis in patients with DOC. Importantly, this approach can, in principle, be transferred into any ERP of interest to better inform DOC diagnoses.