Event-related Potential Data Research Articles

Mechanism of cognitive processing for acupuncture action on generalized anxiety with naturally occurring consecutive partial sleep deprivation in early adulthood: a randomized controlled study and evaluation of event-related potentials

IntroductionGeneralized anxiety disorder (GAD) is a common mental disorder that often begins in adolescence or early adulthood and is characterized by widespread and persistent anxiety. Partial sleep deprivation (PSD) is an important risk factor for GAD development and a common comorbidity. Adolescence is a period of rapid brain and nervous system development, and during this time, the occurrence of GAD can lead to neurocognitive deficits, such as impaired attention, cognitive control, and attention bias, that significantly affect cognitive function. However, relatively little research has been conducted on GAD comorbid with PSD in early adulthood compared with other psychiatric disorders. Clinical studies have demonstrated the effectiveness of acupuncture in treating GAD and sleep disorders, but the mechanism of how acupuncture modulates neurocognitive processing in patients with GAD comorbid with PSD has not been clarified.Methods/designIn this randomized clinical trial, a total of 56 participants diagnosed with GAD comorbid with naturally occurring PSD and 28 healthy controls (HCs) will be recruited. The participants diagnosed with GAD comorbid with PSD will be randomly assigned to either the acupuncture group or the sham acupuncture group at a 1:1 ratio. The primary outcome measure is the Hamilton Anxiety Rating Scale (HAMA). Secondary outcome measures are the Sleep Deprivation Index (SDI), the Self-Assessment Scale for Anxiety (SAS), the Epworth Sleepiness Scale (ESS), and the State-Trait Anxiety Inventory (STAI). Additionally, three psychological paradigms (the attentional network test, psychomotor vigilance test, and emotional face Go/No-go) and event-related potential (ERP) data. Healthy volunteers will not undergo acupuncture but will instead participate in baseline assessments for the scales, mental paradigms, and ERP data. Acupuncture and sham acupuncture interventions will be conducted for 30 min, three times a week, over a 2-week period. Evaluations will be performed at zero weeks (baseline), 1 week, and 2 weeks, with the data enumerator, outcome assessor, and participant blinded to the treatment assignment.DiscussionThis study contributes to the exploration of the effects of acupuncture on improving anxiety symptoms and cognitive functions in individuals with comorbid GAD and PSD.Trial registrationClinicalTrials.gov, ChiCTR2400082221. Registered March 25, 2024.

Electrophysiological evidence of nonspatial inhibition of return affecting audiovisual integration.

The present study endeavored to investigate the potential neural underpinnings of disparities in audiovisual integration (AVI) between valid and invalid targets, modulated by nonspatial inhibition of return (IOR). Concurrently, we sought to delineate the distinct roles subserved by Chinese character primes and color block primes throughout this process. We employed a prime-neutral cue-target paradigm, wherein 25 college students participated in the experiment. Behavioral measures encompassed the reaction time, IOR effect, multisensory response enhancement, and race model analysis. Besides, we examined the N200, N400, and P300 components elicited by the target stimulus presentation in a time-locked fashion to investigate the neural underpinnings of AVI disparities in the context of valid and invalid targets. Behavioral analyses unveiled a significant attenuation of AVI for valid targets, with this effect being particularly pronounced in trials involving Chinese character primes. Intriguingly, event-related potential (ERP) data evinced AVI within the N400 and P300 components. Moreover, the novelty of this study resides in identifying the P300 component as the principal neural correlate underpinning the attenuation of AVI arising from nonspatial IOR-a finding that was not replicated when employing color block primes. This research furnishes novel ERP evidence that elucidates the mechanisms through which nonspatial IOR modulates AVI. This contributes significantly to a broader understanding of the cognitive processes underpinning multisensory perception and attentional dynamics. These insights not only corroborate the late attention theory and the coactivation model but also lend credence to the context-updating hypothesis. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Exploring Attention Bias Mechanisms in Sub-Threshold Depression: ERP Insights into Biased Orientation and Disengagement.

Individuals with depression may have alterations in attention that begin at the sub-threshold stage. This study explored attention bias from the perspectives of early attention orientation and late attention disengagement in individuals with sub-threshold depression (SD) and healthy control (HC) individuals using a cue-target paradigm and event-related potentials (ERPs). The study enrolled 46 participants, comprising 23 males and 23 females, with 25 individuals in the SD group and 21 in the HC group, exceeding the calculated sample size requirement. The data were analyzed from two aspects. Behavioral data showed that SD individuals had difficulty in attention disengagement and that the time of attention transfer was delayed. Analysis of ERP data revealed that, regardless of the attributes of the emotional stimulus, the cue information promoted participants' response to the target stimulus. While SD individuals did show directional acceleration of attention to the emotional stimulus, no significant negative attention bias was observed. Taken together, these findings suggest that SD individuals do not show specific directional acceleration of attention to negative stimuli in the early stage of attention processing, although there may be attention avoidance.

Emotion perception through the nose: how olfactory emotional cues modulate the perception of neutral facial expressions in affective disorders

Humans can decode emotional states from the body odors of the conspecifics and this type of emotional communication is particularly relevant in conditions in which social interactions are impaired, as in depression and social anxiety. The present study aimed to explore how body odors collected in happiness and fearful conditions modulate the subjective ratings, the psychophysiological response and the neural processing of neutral faces in individuals with depressive symptoms, social anxiety symptoms, and healthy controls (N = 22 per group). To this aim, electrocardiogram (ECG) and HD-EEG were recorded continuously. Heart Rate Variability (HRV) was extracted from the ECG as a measure of vagal tone, event-related potentials (ERPs) and event-related spectral perturbations (ERPSs) were extracted from the EEG. The results revealed that the HRV increased during the fear and happiness body odors conditions compared to clean air, but no group differences emerged. For ERPs data, repeated measure ANOVA did not show any significant effects. However, the ERPSs analyses revealed a late increase in delta power and a reduced beta power both at an early and a late stage of stimulus processing in response to the neutral faces presented with the emotional body odors, regardless of the presence of depressive or social anxiety symptoms. The current research offers new insights, demonstrating that emotional chemosignals serve as potent environmental cues. This represents a substantial advancement in comprehending the impact of emotional chemosignals in both individuals with and without affective disorders.

Exploring the Influence of Object, Subject, and Context on Aesthetic Evaluation through Computational Aesthetics and Neuroaesthetics

Background: In recent years, computational aesthetics and neuroaesthetics have provided novel insights into understanding beauty. Building upon the findings of traditional aesthetics, this study aims to combine these two research methods to explore an interdisciplinary approach to studying aesthetics. Method: Abstract artworks were used as experimental materials. Based on traditional aesthetics and in combination, features of composition, tone, and texture were selected. Computational aesthetic methods were then employed to correspond these features to physical quantities: blank space, gray histogram, Gray Level Co-occurrence Matrix (GLCM), Local Binary Pattern (LBP), and Gabor filters. An electroencephalogram (EEG) experiment was carried out, in which participants conducted aesthetic evaluations of the experimental materials in different contexts (genuine, fake), and their EEG data were recorded to analyze the impact of various feature classes in the aesthetic evaluation process. Finally, a Support Vector Machines (SVMs) was utilized to model the feature data, Event-Related Potentials (ERPs), context data, and subjective aesthetic evaluation data. Result: Behavioral data revealed higher aesthetic ratings in the genuine context. ERP data indicated that genuine contexts elicited more negative deflections in the prefrontal lobes between 200 and 1000 ms. Class II compositions demonstrated more positive deflections in the parietal lobes at 50–120 ms, while Class I tones evoked more positive amplitudes in the occipital lobes at 200–300 ms. Gabor features showed significant variations in the parieto-occipital area at an early stage. Class II LBP elicited a prefrontal negative wave with a larger amplitude. The results of the SVM models indicated that the model incorporating aesthetic subject and context data (ACC = 0.76866) outperforms the model using only parameters of the aesthetic object (ACC = 0.68657). Conclusion: A positive context tends to provide participants with a more positive aesthetic experience, but abstract artworks may not respond to this positivity. During aesthetic evaluation, the ERP data activated by different features show a trend from global to local. The SVM model based on multimodal data fusion effectively predicts aesthetics, further demonstrating the feasibility of the combined research approach of computational aesthetics and neuroaesthetics.

Neurophysiological effects of cognitive behavioral therapy in social anxiety: An ERP study using a dot-probe task

BackgroundSocial anxious individuals show attention bias towards emotional stimuli, this phenomenon is considered to be an important cause of anxiety generation and maintenance. Cognitive-behavioral therapy (CBT) is a standard psychotherapy for social anxiety disorder. CBT decreases attention biases by correcting the maladaptive beliefs of socially anxious individuals, but it is not clear whether CBT alters neurophysiological features of socially anxious individuals at early automatic and/or late cognitive strategy stage of attentional processing. MethodTo address this knowledge gap, we collected pre-treatment event-related potential data of 22 socially anxious individuals while they performed a dot-probe task. These participants then received eight weeks of CBT, and post-treatment ERP data were collected after completion of CBT treatment. We also included 29 healthy controls and compared them with individuals with social anxiety to determine the neural mechanisms underlying the effectiveness of CBT. ResultsParticipants’ social anxiety level was significantly alleviated with CBT. ERP results revealed that (1) compared to pre-treatment phase, P1 amplitudes induced by probes significantly decreased at post-treatment phase, whereas P3 amplitudes increased at post-treatment phase; the P1 amplitudes induced by probes following happy-neutral face pairs in socially anxious individuals after treatment was significantly different with that in healthy controls; (2) amplitude of components elicited by face pairs did not change significantly between pre-treatment and post-treatment phases; (3) changes of Liebowitz Social Anxiety Scale were positively correlated with changes of P1 amplitude, and negatively correlated with changes of N1 amplitude. LimitationsOur sample was university students and lacked randomization, which limits the generalizability of the results. ConclusionThe present results demonstrated that CBT may adjust cognitive strategies in the later stage of attentional processing, indicating by changed ERPs appeared in probe-presenting stage for social anxiety.

The influence of task-irrelevant color perception on flanker task performance: Insights from behavioral and ERP data

Perception of color as a task-relevant stimulus can affect cognition and behavior in the flanker task; however, it remains unclear whether it has the same impact when it is a task-irrelevant stimulus dimension. To this end, we applied four-letter flanker tasks with or without colored (red/blue) to 23 healthy young adults, while recording the event-related potentials (ERPs) and behavioral performance. The flanker task included four kinds of color types: non-color letter (NC), all color letter (AC), flanker color letter (FC), and target color letter (TC), each flanker task included congruent and incongruent conditions. The behavioral data demonstrated the classic conflict effect across all color types of flanker tasks in both reaction times (RTs) and accuracy, the significant interaction and main effect of color type factors were only observed in accuracy. The ERP results showed significant interaction between conflict factor (congruent, incongruent) and color type (NC, AC, FC, and TC), and the color type factor enhanced the fronto-central P2 (180–200 ms), descended the fronto-centro-parietal N2b (260–320 ms), and increased the fronto-central P3b (360–520 ms). The fronto-central P2 and the fronto-central P3b were larger for TC than NC, AC, and FC in the congruent condition, while the fronto-central P3b was smaller for NC than AC, FC, and TC in the incongruent condition. Furthermore, the fronto-centro-parietal N2b was decreased successively in NC, AC, FC, and TC in both congruent and incongruent conditions. Overall, our findings suggested that the task-irrelevant stimuli dimension of color can capture some attentional resources and is affected by the location of color (target/flanker) and the type of task trial (congruent/incongruent) in the flanker task.

Maternal emotion regulation abilities affect adolescent depressive symptoms by mediating their emotion regulation ability: An ERP study

Adolescents with major depressive disorder (MDD) experience significant difficulties in emotion regulation. This study aimed to explore emotion regulation in adolescents with depression using an emotion regulation paradigm combined with event-related potentials (ERP) while investigating the relationship between maternal emotion regulation and adolescent depressive symptoms through a mediation model. Overall, 38 healthy controls (HC) and 57 adolescents with depression (MDD) rated the pictures they saw according to aversive reappraisal (reappraisal of an aversive picture or down-regulate aversive emotions), aversive watch, and neutral conditions. Adolescents with depression gave more negative ratings to aversive images, and the emotional regulation success index (ERSI) of adolescents with depression was lower than that of healthy individuals. ERP data revealed an elevation in late positive potential (LPP) amplitude during the aversive reappraisal and aversive watch conditions compared with that in the neutral condition in the MDD group. Compared with the HC group, adolescents with depression showed larger LPP amplitudes under aversive watch conditions. The aversive reappraisal condition evoked a larger LPP than that in the other conditions in the HC group in the late time windows. The ΔLPP (separating the variability in the ERP wave associated with emotion regulation) was larger in the HC group than in the MDD group. Mediation analysis revealed that maternal emotion regulation influenced adolescent depression levels through its effect on the adolescent’s emotion regulation. These findings provide important insights into the emotion regulation process in adolescents with depression and offer suggestions for clinical interventions.

Age-Related Differences in the Effects of Linguistic and Nonlinguistic Masking on Semantic Processing: Evidence From the N400 Component in Young and Middle-Aged Listeners.

The purpose of this study was to determine if there are age-related differences in semantic processing with linguistic and nonlinguistic masking, as measured by the N400. Sixteen young (19-31 years) and 16 middle-aged (41-57 years) adults with relatively normal hearing sensitivity were asked to determine whether word pairs were semantically related or unrelated in three listening conditions: quiet, forward, and reverse two-talker speech competition at 0 dB SNR. Behavioral data (accuracies and reaction times) and auditory event-related potential data (N400 amplitudes and latencies) were analyzed using separate mixed design multivariate analysis of variances. Mean N400 amplitudes for semantically related word pairs were similar between young and middle-aged adults. Although neither group showed N400 amplitude differences between masker types, N400 amplitude was significantly greater in the presence of linguistic and nonlinguistic masking than in quiet. In contrast, mean N400 amplitudes for semantically unrelated words were significantly more negative for young adults and not significantly different among listening conditions. Our findings illustrated age-related differences during a semantic processing task, as indexed by the N400, that may not be evident in suprathreshold speech repetition/recognition tasks or behavioral data. Additionally, N400 amplitudes indicated that linguistic masking effects were equivalent to nonlinguistic masking effects on semantic processing.

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. Approach. 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. Main results. 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. Significance. 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.

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.

Processing of visual hapaxes in picture naming task: An event-related potential study

Object recognition and visual categorization are typically swift and seemingly effortless tasks that involve numerous underlying processes. In our investigation, we utilized a picture naming task to explore the processing of rarely encountered objects (visual hapaxes) in comparison to common objects. Our aim was to determine the stage at which these rare objects are classified as unnamable. Contrary to our expectations and in contrast to some prior research on event-related potentials (ERPs) with novel and atypical objects, no differences between conditions were observed in the late time windows corresponding to the P300 or N400 components. However, distinctive patterns between hapaxes and common objects surfaced in three early time windows, corresponding to the posterior N1 and P2 waves, as well as a widespread N2 wave. According to the ERP data, the differentiation between hapaxes and common objects occurs within the first 380 ms of the processing line, involving only limited and indirect top-down influence.

Exploring the neuropsychological basis of behavioral contagion during learning about another agent's social preferences: Evidence from an ERP study.

Social contagion is a pervasive phenomenon and an important social influence that involves the rapid dissemination (propagation) of behaviors, attitudes, emotions, or ideas from one person to another, often without conscious reflection or rational thought. This phenomenon is closely related to conformity, by which a person changes his/her original ideas and attitude and imitates certain behavior of others. Although some behavioral research has been carried out on contagion and conformity, there is very little neuropsychological understanding of these phenomena. Existing research on social influence and conformity has predominantly focused on tasks like mental rotation or rating tasks involving facial expressions, with fewer studies exploring risk preferences and temporal discounting. However, there is a notable gap in the literature when it comes to examining social influence and conformity using other‑regarding preference models derived from heterodox economics. To address this research gap, the present study investigates the neuropsychological underpinnings of social contagion by utilizing event‑related potentials (ERPs) recorded while subjects engage in mini‑dictator games. The behavioral analysis revealed that contagion had an impact on the participants' preferences, leading to a change in their choices. We observed a P300 component in the midline and right posterior during the time window of 200‑350 ms after stimulus onset, which showed a significant increase in mean amplitude when participants observed others' behavior, compared to when they made decisions based on their own preferences. Moreover, the lack of late positive potential in the time window of 500‑650 ms suggests that the presence of P300 may indicate difficulty in making decisions. In summary, by analyzing both behavioral and ERP data, this study may provide a more comprehensive understanding of the cognitive and neural processes that drive conformity and contagion behavior. Our analysis has the potential to inform policymakers in developing effective interventions for promoting positive social behaviors and reducing negative ones.

Prediction of mild cognitive impairment using EEG signal and BiLSTM network

Mild cognitive impairment (MCI) is a cognitive disease that primarily affects elderly persons. Patients with MCI have impairments in one or more cognitive areas, such as memory, attention, language, and problem-solving. The risk of Alzheimer’s disease development is 10 times higher among individuals who meet the MCI diagnosis than in those who do not have such a diagnosis. Identifying the primary neurophysiological variations between those who are suffering from cognitive impairment and those who are ageing normally may provide helpful techniques to assess the effectiveness of therapies. Event-related Potentials (ERPs) are utilized to investigate the processing of sensory, cognitive, and motor information in the brain. ERPs enable excellent temporal resolution of underlying brain activity. ERP data is complex due to the temporal variation that occurs in the time domain. It is actually a type of electroencephalography (EEG) signal that is time-locked to a specific event or behavior. To remove artifacts from the data, this work utilizes Independent component analysis, finite impulse response filter, and fast Fourier transformation as preprocessing techniques. The bidirectional long short-term memory network is utilized to retain the spatial relationships between the ERP data while learning changes in temporal information for a long time. This network performed well both in modeling and information extraction from the signals. To validate the model performance, the proposed framework is tested on two benchmark datasets. The proposed framework achieved a state-of-the-art accuracy of 96.03% on the SJTU Emotion EEG Dataset dataset and 97.31% on the Chung–Ang University Hospital EEG dataset for the classification tasks.

How variable are the classic ERP effects during sentence processing? A systematic resampling analysis of the N400 and P600 effects

Although event-related potential (ERP) research on language processing has capitalized on key, theoretically influential components such as the N400 and P600, their measurement properties—especially the variability in their temporal and spatial parameters—have rarely been examined. The current study examined the measurement properties of the N400 and P600 effects elicited by semantic and syntactic anomalies, respectively, during sentence processing. We used a bootstrap resampling procedure to randomly draw many thousands of resamples varying in sample size and stimulus count from a larger sample of 187 participants and 40 stimulus sentences of each type per condition. Our resampling investigation focused on three issues: (a) statistical power; (b) variability in the magnitudes of the effects; and (c) variability in the temporal and spatial profiles of the effects. At the level of grand averages, the N400 and P600 effects were both robust and substantial. However, across resamples, there was a high degree of variability in effect magnitudes, onset times, and scalp distributions, which may be greater than is currently appreciated in the literature, especially for the P600 effects. These results provide a useful basis for designing future studies using these two well-established ERP components. At the same time, the results also highlight challenges that need to be addressed in future research (e.g., how best to analyze the ERP data without engaging in such questionable research practices as p-hacking).

A study of ERPs acquired during handwritten and printed Chinese character processing in a lexical decision task

The aim of this study was to investigate the time course differences in brain processing between handwritten and printed Chinese characters. Behavioural and event-related potential (ERP) data were collected from twenty participants as they performed a lexical decision task in which Chinese handwritten and printed characters served as stimuli. The findings indicated that N1 reflects orthographic regularity during the early processing stage; N400 and the late positive component (LPC) data revealed that reading handwritten words evoke greater ERP amplitudes during the late processing stage. Although handwritten characters evoke greater ERP amplitudes, this did not result in more efficient behavioural outcomes. Therefore, it appears that the greater ERP amplitudes observed in the handwriting task corresponded to deeper meaning comprehension, which is also more challenging for semantic integration.

Two-Hour Nicotine Withdrawal Improves Inhibitory Control Dysfunction in Male Smokers: Evidence from a Smoking-Cued Go/No-Go Task ERP Study.

Nicotine withdrawal is a multifaceted physiological and psychological process that can induce a spectrum of mood disturbances. Gaining a more nuanced understanding of how pure nicotine withdrawal influences cognitive control functions may provide valuable insights for the enhancement of smoking cessation programs. This study investigated changes in inhibitory control function in smokers after 2-hour nicotine withdrawal using the event-related potential (ERP) technique. 28 nicotine dependence (ND) patients and 28 health controls (HCs) completed a smoking-cued Go/No-go task containing two different types of picture stimuli, smoking-cued and neutral picture stimuli. We analyzed the behavioral and ERP data using a mixed model Repeated Measure Analysis of Variance (ANOVA). No-go trials accuracy rate (ACC) at baseline (time 1) was lower in the ND group compared to HCs with smoking-cued stimuli, and No-go trials ACC after 2-hour nicotine withdrawal (time 2) was not lower in the ND group compared to HCs. When confronted with smoking-cued stimuli, the No-go trials ACC was higher in time 2 than in time 1 in the ND group. For the ERP component, the No-go N2 amplitudes in the ND group with smoking-cued stimuli were lower than that of HCs, whereas after 2-hour nicotine withdrawal, the ND group's No-go N2 amplitudes higher than that at time 1, and did not differ from that of HCs. No-go P3 amplitudes were not significantly different between the two groups. Evidenced from ERP data, ND patients have an inhibitory control dysfunction in the face of smoking cues, which is mainly manifested in the early stage of response inhibition rather than in the late stage. Two-hour nicotine withdrawal improves inhibitory control dysfunction in ND patients. The No-go N2 component is an important and sensitive neuroelectrophysiological indicator of inhibitory control function in ND patients.

Willingness valued more than ability in partner choice: Insights into behavioral and ERP data.

In human cooperation, people prefer to choose partners with high willingness and ability-while both are valued by partners, individuals often prioritize willingness. Two event-related potential (ERP) experiments were conducted to discern the neural processes underpinning this preference. In the first experiment, participants made a choice between two potential partners and received feedback on the selected partner's willingness to cooperate. This was followed by feedback on the partner's task performance (ability) or a gambling outcome. In contrast, the second experiment first provided feedback on ability, then presented feedback on willingness or a gambling outcome. This study revealed that a potential partner's willingness trait significantly influences individuals' emotional evaluations and monetary allocations than the ability trait. Electrophysiological data indicated that low-willingness feedback elicited a diminished feedback-related negative (FRN) and an amplified P3 compared to high-willingness feedback. In contrast, no such difference was discernible between high- and low-ability feedback. Moreover, the P3 difference from high versus low willingness was considerably more pronounced than that from gambling outcomes, whereas the difference wave between high and low ability paralleled gambling outcomes. These findings bolster the novel finding that partner willingness may provide more substantial social rewards than ability. Furthermore, this study provides the first ERP evidence of willingness and ability trait perceptions in partner choice decisions.

Impaired implicit emotion regulation in patients with panic disorder: An event-related potential study on affect labeling.

Panic disorder (PD) involves emotion dysregulation, but its underlying mechanisms remain poorly understood. Previous research suggests that implicit emotion regulation may play a central role in PD-related emotion dysregulation and symptom maintenance. However, there is a lack of studies exploring the neural mechanisms of implicit emotion regulation in PD using neurophysiological indicators. To study the neural mechanisms of implicit emotion regulation in PD with event-related potentials (ERP). A total of 25 PD patients and 20 healthy controls (HC) underwent clinical eva-luations. The study utilized a case-control design with random sampling, selecting participants for the case group from March to December 2018. Participants performed an affect labeling task, using affect labeling as the experimental condition and gender labeling as the control condition. ERP and behavioral data were recorded to compare the late positive potential (LPP) within and between the groups. Both PD and HC groups showed longer reaction times and decreased accuracy under the affect labeling. In the HC group, late LPP amplitudes exhibited a dynamic pattern of initial increase followed by decrease. Importantly, a significant group × condition interaction effect was observed. Simple effect analysis revealed a reduction in the differences of late LPP amplitudes between the affect labeling and gender labeling conditions in the PD group compared to the HC group. Furthermore, among PD patients under the affect labeling, the late LPP was negatively correlated with disease severity, symptom frequency, and intensity. PD patients demonstrate abnormalities in implicit emotion regulation, hampering their ability to mobilize cognitive resources for downregulating negative emotions. The late LPP amplitude in response to affect labeling may serve as a potentially valuable clinical indicator of PD severity.

Auditory event-related potential differentiates girls with Rett syndrome from their typically-developing peers with high accuracy: Machine learning study

Rett Syndrome (RTT) is a rare neurodevelopmental disorder caused by mutation in the MECP2 gene. No cures are still available, but several clinical trials are ongoing. Here we examine neurophysiological correlates of auditory processing for ability to differentiate patients with RTT from typically developing (TD) peers applying standard machine learning (ML) methods and pipelines. Capitalized on the available event-related potential (ERP) data recorded in response to tone presented at different rates (stimulus onset asynchrony 900, 1800 and 3600 ms) from 24 patients with RTT and 27 their TD peer. We considered the most common ML models that are widely used for classification tasks. These include both linear models (logistic regression, support-vector machine with linear kernel) and tree-based nonlinear models (random forest, gradient boosting). Based on these methods we were able to differentiate RTT from TD children with high accuracy (with up to 0.94 ROC-AUC score), which was evidently higher at the fastest presentation rate. Importance analysis and perturbation importance pointed out that the most important feature for classification is P2-N2 peak-to-peak amplitude, consistently across the approaches and blocks with different presentation rate. The results suggest the unique pattern of ERP characteristics for RTT and points to features of importance. The results might be relevant for establishing outcome measures for clinical trials.