Theta resting EEG in TPJ/pSTS is associated with individual differences in the feeling of being looked at

Examining resting state functional connectivity and frequency power analysis in adults who stutter compared to adults who do not stutter

Introduction

Stuttering is a speech disorder characterized by impaired connections between brain regions involved in speech production. This study aimed to investigate functional connectivity and frequency power during rest in adults who stutter (AWS) compared to fluent adults (AWNS) in the dorsolateral prefrontal cortex (DLPFC), dorsolateral frontal cortex (DLFC), supplementary motor area (SMA), motor speech, angular gyrus (AG), and inferior temporal gyrus (ITG).

Materials and methods

Fifteen AWS (3 females, 12 males) and fifteen age- and sex-matched AWNS (3 females, 12 males) participated in this study. All participants were native Persian speakers. Stuttering severity in the AWS group was assessed using the Persian version of the Stuttering Severity Instrument Fourth Edition (SSI-4). Resting-state electroencephalography (EEG) was recorded for 5 min while participants sat comfortably with their eyes open. We analyzed frequency band power across various frequency bands and investigated functional connectivity within the specified speech region.

Results

Significant between-group differences were found in band powers including alpha, beta, delta, theta, and gamma, specifically in the premotor, SMA, motor speech, and frontal regions. AWS also showed increased coherence between the right motor speech region compared to controls. We demonstrate that the proposed hierarchical false discovery rate (FDR) method is the most effective for both simulations and experimental data. In the expected regions, this method revealed significant synchrony effects at an acceptable error rate of 5%.

Conclusion

The results highlight disrupted functional connectivity in AWS at resting state, particularly in speech-related and associated areas. Given the complex neurological basis of developmental stuttering, robust neural markers are closely linked to this phenomenon. These markers include imbalanced activity within brain regions associated with speech and motor functions, coupled with impaired functional connectivity between these regions. The cortico-basal ganglia-thalamo-cortical system governs the dynamic interplay between cortical regions, with SMA as a key cortical site. It is hypothesized that the aberrant resting state functional connectivity will impact the language planning and motor execution necessary for fluent speech. Examining resting-state metrics as biomarkers could further elucidate the neural underpinnings of stuttering and guide intervention.

Autistic traits modulate the influence of face masks on gaze perception

Detecting when others are looking at us is a crucial social skill. Accordingly, a range of gaze angles is perceived as self-directed; this is termed the "cone of direct gaze" (CoDG). Multiple cues, such as nose and head orientation, are integrated during gaze perception. Thus, occluding the lower portion of the face, such as with face masks during the COVID-19 pandemic, may influence how gaze is perceived. Individual differences in the prioritisation of eye-region and non-eye-region cues may modulate the influence of face masks on gaze perception. Autistic individuals, who may be more reliant on non-eye-region directional cues during gaze perception, might be differentially affected by face masks. In the present study, we compared the CoDG when viewing masked and unmasked faces (N = 157) and measured self-reported autistic traits. The CoDG was wider for masked compared to unmasked faces, suggesting that reduced reliability of lower face cues increases the range of gaze angles perceived as self-directed. Additionally, autistic traits positively predicted the magnitude of CoDG difference between masked and unmasked faces. This study provides crucial insights into the effect of face masks on gaze perception, and how they may affect autistic individuals to a greater extent.

Autism-Related Differences in Cortical Activation When Observing, Producing, and Imitating Communicative Gestures: An fNIRS Study

Children with autism spectrum disorder (ASD) have difficulties in gestural communication during social interactions. However, the neural mechanisms involved in naturalistic gestural communication remain poorly understood. In this study, cortical activation patterns associated with gestural communication were examined in thirty-two children with and without ASD (mean age: 11.0 years, SE: 0.6 years). Functional near-infrared spectroscopy (fNIRS) was used to record cortical activation while children produced, observed, or imitated communicative gestures. Children with ASD demonstrated more spatial and temporal errors when performing and imitating communicative gestures. Although both typically developing (TD) children and children with ASD showed left-lateralized cortical activation during gesture production, children with ASD showed hyperactivation in the middle/inferior frontal gyrus (MIFG) during observation and imitation, and hypoactivation in the middle/superior temporal gyrus (MSTG) during gesture production compared to their TD peers. More importantly, children with ASD exhibited greater MSTG activation during imitation than during gesture production, suggesting that imitation could be an effective intervention strategy to engage cortical regions crucial for processing and producing gestures. Our study provides valuable insights into the neural mechanisms underlying gestural communication difficulties in ASD, while also identifying potential neurobiomarkers that could serve as objective measures for evaluating intervention effectiveness in children with ASD.

Face masks have a limited effect on the feeling of being looked at

Introduction

Wearing face masks has been promoted as an effective measure to reduce the spread of COVID-19. Because face masks cover a major part of the face, they have detrimental effects on various aspects of social cognition. Yet, a highly important feature of the face is not occluded by face masks: the eyes. The eyes play an important role in social interactions: knowing where another person is looking is of central importance when interacting with others. Recent research has reported an attentional shift toward the eye region as a consequence of the widespread exposure to face masks. However, no study has yet investigated the influence of face masks on the perception of eye gaze direction. Here we investigated whether face masks have an effect on the feeling of being looked at. Assuming an attentional shift toward the eyes, we might expect more accurate gaze perception in faces wearing face masks.

Methods

Sixty-five participants decided for a series of realistic avatar faces whether each face was making eye contact or not. Half of the faces wore face masks, the other half did not. For each participant and separately for each condition (mask vs. no mask), we calculated the cone of direct gaze (CoDG), a commonly used measure to quantify the range of gaze angles within which an observer assumes mutual gaze.

Results

Contrary to our expectations, results show that mutual gaze is not recognized more accurately in masked faces. Rather, the CoDG was, on average, slightly wider for faces wearing masks compared to faces without masks.

Discussion

Notwithstanding the relatively small effect of face mask, these findings potentially have implications on our social interactions. If we inadvertently feel looked at by an onlooker, we may react inappropriately by reciprocating the alleged approach orientation.

The Effect of Time Window Length on EEG-Based Emotion Recognition

Various lengths of time window have been used in feature extraction for electroencephalogram (EEG) signal processing in previous studies. However, the effect of time window length on feature extraction for the downstream tasks such as emotion recognition has not been well examined. To this end, we investigate the effect of different time window (TW) lengths on human emotion recognition to find the optimal TW length for extracting electroencephalogram (EEG) emotion signals. Both power spectral density (PSD) features and differential entropy (DE) features are used to evaluate the effectiveness of different TW lengths based on the SJTU emotion EEG dataset (SEED). Different lengths of TW are then processed with an EEG feature-processing approach, namely experiment-level batch normalization (ELBN). The processed features are used to perform emotion recognition tasks in the six classifiers, the results of which are then compared with the results without ELBN. The recognition accuracies indicate that a 2-s TW length has the best performance on emotion recognition and is the most suitable to be used in EEG feature extraction for emotion recognition. The deployment of ELBN in the 2-s TW can further improve the emotion recognition performances by 21.63% and 5.04% when using an SVM based on PSD and DE features, respectively. These results provide a solid reference for the selection of TW length in analyzing EEG signals for applications in intelligent systems.

An adversarial discriminative temporal convolutional network for EEG-based cross-domain emotion recognition

Domain adaptation (DA) tackles the problem where data from the source domain and target domain have different underlying distributions. In cross-domain (cross-subject or cross-dataset) emotion recognition based on EEG signals, traditional classification methods lack domain adaptation capabilities and have low performance. To address this problem, we proposed a novel domain adaptation strategy called adversarial discriminative-temporal convolutional networks (AD-TCNs) in this study, which can ensure the invariance of the representation of feature graphs in different domains and fill in the differences between different domains. For EEG data with specific temporal attributes, the temporal model TCN is used as the feature encoder. In the cross-subject experiment, our AD-TCN method achieved the highest accuracies of the valence and arousal dimensions in both the DREAMER and DEAP datasets. In the cross-dataset experiment, two of the eight task groups showed accuracies of 62.65% and 62.36%. Compared with the state-of-the-art performance in the same protocol, experimental results demonstrated that our method is an effective extension to realize EEG-based cross-domain emotion recognition.

The Cone of Direct Gaze: A Stable Trait

Direct eye gaze is a potent stimulus in social interactions and is often associated with interest and approach orientation. Yet, there is remarkable variability in the range of gaze lines that people accept as being direct. A measure that is frequently used to quantify the range of gaze angles within which an observer assumes mutual gaze is the cone of direct gaze (CoDG). While individual differences in CoDG have often been examined, studies that systematically investigate the stability of an observers' CoDG over time are scarce. In two experiments, we measured the CoDG using an established paradigm and repeated the measurement after 5 min and/or after 1 week. We found high inter-individual variation, but high agreement within participants (ICCs between 0.649 and 0.855). We conclude that the CoDG can be seen as a rather stable measure, much like a personality trait.

Temporal dynamics of resting EEG networks are associated with prosociality

As prosociality is key to facing many of our societies' global challenges (such as fighting a global pandemic), we need to better understand why some individuals are more prosocial than others. The present study takes a neural trait approach, examining whether the temporal dynamics of resting EEG networks are associated with inter-individual differences in prosociality. In two experimental sessions, we collected 55 healthy males' resting EEG, their self-reported prosocial concern and values, and their incentivized prosocial behavior across different reward domains (money, time) and social contexts (collective, individual). By means of EEG microstate analysis we identified the temporal coverage of four canonical resting networks (microstates A, B, C, and D) and their mutual communication in order to examine their association with an aggregated index of prosociality. Participants with a higher coverage of microstate A and more transitions from microstate C to A were more prosocial. Our study demonstrates that temporal dynamics of intrinsic brain networks can be linked to complex social behavior. On the basis of previous findings on links of microstate A with sensory processing, our findings suggest that participants with a tendency to engage in bottom-up processing during rest behave more prosocially than others.

Theta resting EEG in the right TPJ is associated with individual differences in implicit intergroup bias

Why are some people more biased than others in their implicit evaluations during social interaction? The dispositional determinants of individual differences in implicit intergroup bias are poorly understood. Here, we explored whether such variability might be explained by stable neural traits. For that purpose, we used the source-localized resting electroencephalograms of 83 members of naturalistic social groups to explain their bias in an in-/outgroup implicit association test. Lower levels of resting theta current density in the right temporo-parietal junction (TPJ) were associated with stronger implicit intergroup bias and explained unique variability in bias beyond relevant personality questionnaires. These findings demonstrate the added value of the neural trait approach in predicting inter-individual differences in implicit social cognition. Given that low levels of resting theta current density during wakefulness likely reflect increased cortical activation, our results suggest that individuals with an efficiently working right TPJ possess capacities to mediate specific cognitive processes that predispose them towards stronger implicit intergroup bias. As the human species has evolved living in distinct social groups, the capacity to quickly differentiate friend from foe became highly adaptive and might thus constitute an essential part of human nature.

Neural traits characterize unconditional cooperators, conditional cooperators, and noncooperators in group-based cooperation

Contributing to and maintaining public goods are important for a functioning society. In reality, however, we see large variations in contribution behavior. While some individuals are not cooperative, others are highly so. Still others cooperate only to the extent they believe others will. Although these distinct behavioral types clearly have a divergent social impact, the sources of heterogeneity are poorly understood. We used source‐localized resting electroencephalography in combination with a model‐free clustering approach to participants' behavior in the Public Goods Game to explain heterogeneity. Findings revealed that compared to noncooperators, both conditional cooperators and unconditional cooperators are characterized by higher baseline activation in the right temporo‐parietal junction, an area involved in social cognition. Interestingly, conditional cooperators were further characterized by higher baseline activation in the left lateral prefrontal cortex, an area involved in behavioral control. Our findings suggest that conditional cooperators' better capacities for behavioral control enable them to control their propensity to cooperate and thus to minimize the risk of exploitation by noncooperators.

Connectome-based model predicts individual differences in propensity to trust

Trust constitutes a fundamental basis of human society and plays a pivotal role in almost every aspect of human relationships. Although enormous interest exists in determining the neuropsychological underpinnings of a person's propensity to trust utilizing task-based fMRI; however, little progress has been made in predicting its variations by task-free fMRI based on whole-brain resting-state functional connectivity (RSFC). Here, we combined a one-shot trust game with a connectome-based predictive modeling approach to predict propensity to trust from whole-brain RSFC. We demonstrated that individual variations in the propensity to trust were primarily predicted by RSFC rooted in the functional integration of distributed key nodes-caudate, amygdala, lateral prefrontal cortex, temporal-parietal junction, and the temporal pole-which are part of domain-general large-scale networks essential for the motivational, affective, and cognitive aspects of trust. We showed, further, that the identified brain-behavior associations were only evident for trust but not altruistic preferences and that propensity to trust (and its underlying neural underpinnings) were modulated according to the extent to which a person emphasizes general social preferences (i.e., horizontal collectivism) rather than general risk preferences (i.e., trait impulsiveness). In conclusion, the employed data-driven approach enables to predict propensity to trust from RSFC and highlights its potential use as an objective neuromarker of trust impairment in mental disorders.

The Role of Eye Gaze During Natural Social Interactions in Typical and Autistic People

Social interactions involve complex exchanges of a variety of social signals, such as gaze, facial expressions, speech and gestures. Focusing on the dual function of eye gaze, this review explores how the presence of an audience, communicative purpose and temporal dynamics of gaze allow interacting partners to achieve successful communication. First, we focus on how being watched modulates social cognition and behavior. We then show that the study of interpersonal gaze processing, particularly gaze temporal dynamics, can provide valuable understanding of social behavior in real interactions. We propose that the Interpersonal Gaze Processing model, which combines both sensing and signaling functions of eye gaze, provides a framework to make sense of gaze patterns in live interactions. Finally, we discuss how autistic individuals process the belief in being watched and interpersonal dynamics of gaze, and suggest that systematic manipulation of factors modulating gaze signaling can reveal which aspects of social eye gaze are challenging in autism.