Atypicality of the N170 Event-Related Potential in Autism Spectrum Disorder: A Meta-analysis

An Event-Related Potential Study on Facial Recognition in Children with and without Autism Spectrum Disorders

Purpose

Facial recognition is very primary and important in individuals' development and the event-related potential based on face recognition such as N170 is considered as the most potential objective marker of autism, the hot and difficult point of current research. We will explore the electrophysiological basis of facial recognition with autism and without autism. Given the link between facial recognition and social impairments, the core symptom of autism, it is also necessary to study the correlation between the P1 and N170 components and the severity of social functioning in autism.

Patients and Methods

In this study, autism and age-matched typically developing children were asked to examine photographs of faces, objects and butterflies and event-related potentials were recorded. The parents or caregivers of the participants were asked to fill out the Vineland Adaptive Behavior Scale. Finally, thirteen children with autism (6.60±2.12years) and ten typically developing (6.65±1.64years) children were included in the experiment.

Results

Children with autism showed slower P1 and N170 latencies than typically developing children. The N170 amplitude for faces was larger than that for objects. Considering age as a covariant, the results primarily remained unchanged and the effect size of age was significant for the P1 and N170 latencies. As for the correlation between ERPs and the severity of social impairment, there were some significant correlations between the P1 and N170 latencies and social functioning.

Conclusion

This result not only suggests the electrophysiological basis of facial recognition but also indicates that the P1 and N170 components could assist in the diagnosis and assessment of autism. Moreover, the results suggest that age should be considered in analyses of the P1 and N170 latencies. Due to a limited number of participants, conducting a multi-center and large-sample study in the future is necessary.

From Dyadic to Higher-Order Interactions: Enhanced Representation of Homotopic Functional Connectivity Through Control of Intervening Variables

Background: The brain's complex functionality emerges from network interactions that go beyond dyadic connections, with higher-order interactions significantly contributing to this complexity. Homotopic functional connectivity (HoFC) is a key neurophysiological characteristic of the human brain, reflecting synchronized activity between corresponding regions in the brain's hemispheres. Materials and Methods: Using resting-state functional magnetic resonance imaging data from the Human Connectome Project, we evaluate dyadic and higher-order interactions of three functional connectivity (FC) parameterizations-bivariate correlation, partial correlation, and tangent space embedding-in their effectiveness at capturing HoFC through the inter-hemispheric analogy test. Results: Higher-order feature vectors are generated through node2vec, a random walk-based node embedding technique applied to FC networks. Our results show that higher-order feature vectors derived from partial correlation most effectively represent HoFC, while tangent space embedding performs best for dyadic interactions. Discussion: These findings validate HoFC and underscore the importance of the FC construction method in capturing intrinsic characteristics of the human brain.

Facial emotion processing hemispheric bias is weakly associated with handedness, autistic traits and biological sex, but not age

BACKGROUND

Right-hemisphere brain regions are strongly implicated in facial emotion processing (FEP), a phenomenon termed right-hemispheric bias. Variability in FEP hemispheric bias is thought to underpin differences in facial emotion recognition ability and has been associated with age, handedness, biological sex, and autistic traits. However, findings from research to date investigating factors associated with FEP hemispheric bias have been inconsistent.

OBJECTIVE

To examine if FEP hemispheric bias can be predicted by individual factors such as age, biological sex, handedness, and autistic traits.

METHODS

427 adults recruited from the general population aged 18-67 years completed the Autism-spectrum Quotient. We also assessed covariates previously linked with FEP hemispheric bias including age, handedness, and biological sex. FEP hemispheric bias was indexed using laterality quotients calculated from a Chimeric Faces Task, where participants indicated which of two identical (but mirrored) half-emotional half-neutral (no emotion) chimeric faces were more emotive.

RESULTS

Linear regression models revealed that (1) handedness predicted FEP hemispheric choice bias, (2) the attention switching Autism-spectrum Quotient subscale predicted FEP hemispheric reaction time bias, and (3) the imagination Autism-spectrum Quotient subscale predicted FEP hemispheric reaction time bias for males, but not females.

CONCLUSIONS

These findings indicate that the relationship between autistic traits and FEP hemispheric bias is nuanced. Additionally, handedness influences hemispheric bias effects during FEP. Future research should endeavour to investigate if FEP hemispheric bias is dependent on the emotion being observed and consider using more direct measures of hemispheric bias.

Social Functioning in Autistic Children with Below-Average vs. Average IQ: Limited Behavioral and Neural Evidence of Group Differences

Despite the relatively high rates of intellectual disability (ID) in autism, research studies and clinical trials commonly exclude autistic participants with below-average IQ. This study aimed to characterize the effect of intellectual ability on social functioning in autistic adolescents assessed using behavioral and neural measures. Caregiver reports and direct standardized behavioral assessments of social abilities along with event-related potential measures of social and nonsocial information processing were obtained in school-age children with autism and ID (n = 41) matched on age, sex, and autism symptom severity to autistic participants with average IQ (n = 41). Full-scale IQ differences did not affect caregiver reports of social functioning in daily life. Group differences were observed only for the direct behavioral assessments of social perception and cognition (NEPSY Memory for Faces delayed, Theory of Mind) as well as social behavior with an unfamiliar friendly confederate, where higher IQ was associated with better performance. Similarly, the impact of IQ on neural responses was limited to a minimal delay in the processing speed of all visual stimuli and the magnitude of differences between social and nonsocial images, but not on incidental memory for the repeated stimuli. The effects of IQ on behavioral or neural responses did not vary based on biological sex. Below-average full-scale IQ in autistic youth affects results of some but not all behavioral or neural measures probing social functioning. Therefore, enrolling participants with a wider range of intellectual ability could be feasible in future studies.

Altered category learning and reduced generalization in autistic adults

Individuals with autism spectrum condition (ASC) are suggested to experience difficulties with categorization and generalization. However, empirical studies have mainly focused on one process at a time, and neglected underlying neural mechanisms. Here, we investigated categorization and generalization at a behavioral and neural level in 38 autistic and 38 neurotypical (NT) adults. By presenting shapes sampled from an artificial multidimensional stimulus space, we investigated (1) behavioral and neural underpinnings of category learning and (2) behavioral generalization of trained categorization to both an extended version of the stimulus space and a novel stimulus space. Our previous findings showed that individuals with autism were slower in category learning. In this study, we demonstrate that this slower learning in autism was not related to differences in applied categorization strategy. In contrast, electroencephalography recordings during training did reveal a reduced amplitude of the N1 component in the right occipital temporal cortex after stimulus presentation in autistic participants, which suggests atypical categorical proficiency. In addition, we observed delayed and higher activation in the frontal regions after receiving (negative) feedback in the autistic group, potentially suggesting more explicit feedback processing or a higher salience of prediction errors in autism. Finally, autistic and NT individuals were able to generalize their learned categorization after training. However, when generalizing to a novel set of shapes, autistic individuals were significantly less accurate. Reduced generalization significantly correlated with increased intolerance to uncertainty scores. This multi-level approach reveals behavioral and neural differences in learning and generalization that could be related to clinical symptoms in autism.

A multimodal neural signature of face processing in autism within the fusiform gyrus

Atypical face processing is commonly reported in autism. Its neural correlates have been explored extensively across single neuroimaging modalities within key regions of the face processing network, such as the fusiform gyrus (FFG). Nonetheless, it is poorly understood how variation in brain anatomy and function jointly impacts face processing and social functioning. Here we leveraged a large multimodal sample to study the cross-modal signature of face processing within the FFG across four imaging modalities (structural magnetic resonance imaging (MRI), resting-state functional magnetic resonance imaging, task-functional magnetic resonance imaging and electroencephalography) in 204 autistic and nonautistic individuals aged 7-30 years (case-control design). We combined two methodological innovations-normative modeling and linked independent component analysis-to integrate individual-level deviations across modalities and assessed how multimodal components differentiated groups and informed social functioning in autism. Groups differed significantly in a multimodal component driven by bilateral resting-state functional MRI, bilateral structure, right task-functional MRI and left electroencephalography loadings in face-selective and retinotopic FFG. Multimodal components outperformed unimodal ones in differentiating groups. In autistic individuals, multimodal components were associated with cognitive and clinical features linked to social, but not nonsocial, functioning. These findings underscore the importance of elucidating multimodal neural associations of social functioning in autism, offering potential for the identification of mechanistic and prognostic biomarkers.

Understanding cognitive flexibility in emotional evaluation in autistic males and females: the social context matters

BACKGROUND

Autistic individuals often have difficulty flexibly adjusting their behavior. However, laboratory experiments have yielded inconsistent results, potentially due to various influencing factors, which need to be examined in detail. This study aimed to investigate the hypothesis that the social content of stimuli could play a specific role in some of the flexibility challenges faced by autistic individuals. The second aim was to explore sex differences in this context.

METHODS

We analyzed data from 256 adult participants (124 with autism), matched on age, gender, and sex, who performed an emotional shifting task involving unpredictable shifts between positive and negative stimuli. Additionally, the task included both social and non-social conditions.

RESULTS

Our results revealed a larger switch cost in the social than in the non-social condition, and this was more pronounced in autistic than in non-autistic individuals. Furthermore, we observed that autistic females differed from autistic males in the non-social condition and from non-autistic females in the social condition.

LIMITATIONS

The online nature of the study reduced the control over participant conditions. In addition, further studies are needed to investigate whether these results apply to the broader autism spectrum.

CONCLUSIONS

Building on previous research demonstrating a greater switch cost in autistic than non-autistic individuals for socio-emotional stimuli, our study further extends these findings by highlighting that the social context, rather than the emotional nature of the stimuli alone, may play a significant role in the flexibility challenges faced by autistic individuals. Our findings also contribute to the literature on sex differences in autism.

Where do neurodevelopmental conditions fit in transdiagnostic psychiatric frameworks? Incorporating a new neurodevelopmental spectrum

Features of autism spectrum disorder, attention-deficit/hyperactivity disorder, learning disorders, intellectual disabilities, and communication and motor disorders usually emerge early in life and are associated with atypical neurodevelopment. These "neurodevelopmental conditions" are grouped together in the DSM-5 and ICD-11 to reflect their shared characteristics. Yet, reliance on categorical diagnoses poses significant challenges in both research and clinical settings (e.g., high co-occurrence, arbitrary diagnostic boundaries, high within-disorder heterogeneity). Taking a transdiagnostic dimensional approach provides a useful alternative for addressing these limitations, accounting for shared underpinnings across neurodevelopmental conditions, and characterizing their common co-occurrence and developmental continuity with other psychiatric conditions. Neurodevelopmental features have not been adequately considered in transdiagnostic psychiatric frameworks, although this would have fundamental implications for research and clinical practices. Growing evidence from studies on the structure of neurodevelopmental and other psychiatric conditions indicates that features of neurodevelopmental conditions cluster together, delineating a "neurodevelopmental spectrum" ranging from normative to impairing profiles. Studies on shared genetic underpinnings, overlapping cognitive and neural profiles, and similar developmental course and efficacy of support/treatment strategies indicate the validity of this neurodevelopmental spectrum. Further, characterizing this spectrum alongside other psychiatric dimensions has clinical utility, as it provides a fuller view of an individual's needs and strengths, and greater prognostic utility than diagnostic categories. Based on this compelling body of evidence, we argue that incorporating a new neurodevelopmental spectrum into transdiagnostic frameworks has considerable potential for transforming our understanding, classification, assessment, and clinical practices around neurodevelopmental and other psychiatric conditions.

Reduced spatial frequency differentiation and sex-related specificities in fearful face detection in autism: Insights from EEG and the predictive brain model

Face processing relies on predictive processes driven by low spatial frequencies (LSF) that convey coarse information prior to fine information conveyed by high spatial frequencies. However, autistic individuals might have atypical predictive processes, contributing to facial processing difficulties. This may be more normalized in autistic females, who often exhibit better socio-communicational abilities than males. We hypothesized that autistic females would display a more typical coarse-to-fine processing for socio-emotional stimuli compared to autistic males. To test this hypothesis, we asked adult participants (44 autistic, 51 non-autistic) to detect fearful faces among neutral faces, filtered in two orders: from coarse-to-fine (CtF) and from fine-to-coarse (FtC). Results show lower d' values and longer reaction times for fearful detection in autism compared to non-autistic (NA) individuals, regardless of the filtering order. Both groups presented shorter P100 latency after CtF compared to FtC, and larger amplitude for N170 after FtC compared to CtF. However, autistic participants presented a reduced difference in source activity between CtF and FtC in the fusiform. There was also a more spatially spread activation pattern in autistic females compared to NA females. Finally, females had faster P100 and N170 latencies, as well as larger occipital activation for FtC sequences than males, irrespective of the group. Overall, the results do not suggest impaired predictive processes from LSF in autism despite behavioral differences in fear detection. However, they do indicate reduced brain modulation by spatial frequency in autism. In addition, the findings highlight sex differences that warrant consideration in understanding autistic females.

Impaired inhibitory control when processing real but not cartoon emotional faces in autistic children: Evidence from an event-related potential study

Impaired socioemotional functioning characterizes autistic children, but does weak inhibition control underlie their socioemotional difficulty? This study addressed this question by examining whether and, if so, how inhibition control is affected by face realism and emotional valence in school-age autistic and neurotypical children. Fifty-two autistic and 52 age-matched neurotypical controls aged 10-12 years completed real and cartoon emotional face Go/Nogo tasks while event-related potentials (ERPs) were recorded. The analyses of inhibition-emotion components (i.e., N2, P3, and LPP) and a face-specific N170 revealed that autistic children elicited greater N2 while inhibiting Nogo trials and greater P3/LPP and late LPP for real but not cartoon emotional faces. Moreover, autistic children exhibited a reduced N170 to real face emotions only. Furthermore, correlation results showed that better behavioral inhibition and emotion recognition in autistic children were associated with a reduced N170. These findings suggest that neural mechanisms of inhibitory control in autistic children are less efficient and more disrupted during real face processing, which may affect their age-appropriate socio-emotional development.

Spontaneous instrumental approach-avoidance learning in social contexts in autism

BACKGROUND

Individuals with Autism Spectrum Condition (ASC) are characterized by atypicalities in social interactions, compared to Typically Developing individuals (TD). The social motivation theory posits that these difficulties stem from diminished anticipation, reception, and/or learning from social rewards. Although learning from socioemotional outcomes is core to the theory, studies to date have been sparse and inconsistent. This possibly arises from a combination of theoretical, methodological and sample-related issues. Here, we assessed participants' ability to develop a spontaneous preference for actions that lead to desirable socioemotional outcomes (approaching/avoiding of happy/angry individuals, respectively), in an ecologically valid social scenario. We expected that learning abilities would be impaired in ASC individuals, particularly in response to affiliative social feedback.

METHOD

We ran an online social reinforcement learning task, on two large online cohorts with (n = 274) and without (n = 290) ASC, matched for gender, age and education. Participants had to indicate where they would sit in a waiting room. Each seat was associated with different probabilities of approaching/avoiding emotional individuals. Importantly, the task was implicit, as participants were not instructed to learn, and emotional expressions were never mentioned. We applied both categorical analyses contrasting the ASC and TD groups and dimensional factor analysis on affective questionnaires.

RESULTS

Contrary to our hypothesis, participants showed spontaneous learning from socioemotional outcomes, regardless of their diagnostic group. Yet, when accounting for dimensional variations in autistic traits, as well as depression and anxiety, two main findings emerged among females who failed to develop explicit learning strategies: (1) autism severity in ASC correlated with reduced learning to approach happy individuals; (2) anxiety-depression severity across both ASC and TD participants correlated with reduced learning to approach/avoid happy/angry individuals, respectively.

CONCLUSIONS

Implicit spontaneous learning from socioemotional outcomes is not generally impaired in autism but may be specifically associated with autism severity in females with ASC, when they do not have an explicit strategy for adapting to their social environment. Clinical diagnosis and intervention ought to take into account individual differences in their full complexity, including the presence of co-morbid anxiety and depression, when dealing with social atypicalities in autism.

Coactivation of Autonomic and Central Nervous Systems During Processing of Socially Relevant Information in Autism Spectrum Disorder: A Systematic Review

Body-brain interaction provides a novel approach to understand neurodevelopmental conditions such as autism spectrum disorder (ASD). In this systematic review, we analyse the empirical evidence regarding coexisting differences in autonomic (ANS) and central nervous system (CNS) responses to social stimuli between individuals with ASD and typically developing individuals. Moreover, we review evidence of deviations in body-brain interaction during processing of socially relevant information in ASD. We conducted systematic literature searches in PubMed, Medline, PsychInfo, PsychArticles, and Cinahl databases (until 12.1.2022). Studies were included if individuals with ASD were compared with typically developing individuals, study design included processing of social information, and ANS and CNS activity were measured simultaneously. Out of 1892 studies identified based on the titles and abstracts, only six fulfilled the eligibility criteria to be included in synthesis. The quality of these studies was assessed using a quality assessment checklist. The results indicated that individuals with ASD demonstrate atypicalities in ANS and CNS signalling which, however, are context dependent. There were also indications for altered contribution of ANS-CNS interaction in processing of social information in ASD. However, the findings must be considered in the context of several limitations, such as small sample sizes and high variability in (neuro)physiological measures. Indeed, the methodological choices varied considerably, calling for a need for unified guidelines to improve the interpretability of results. We summarize the current experimentally supported understanding of the role of socially relevant body-brain interaction in ASD. Furthermore, we propose developments for future studies to improve incremental knowledge building across studies of ANS-CNS interaction involving individuals with ASD.

Autistic traits and event-related potentials in the general population: A scoping review and meta-analysis

BACKGROUND

Differences in short and long-latency Event-Related Potentials (ERPs) can help us infer abnormalities in brain processing, considering early and later stages of stimuli processing across tasks and conditions. In autism research, the adult population remains largely understudied compared to samples at early stages of development. In this context, this scoping review briefly summarises what has been described in community and subclinical adult samples of autism.

METHOD

The current scoping review and meta-analysis includes 50 records (N = 1652) and comprehensively explores short and long-latency ERP amplitudes and their relationship with autistic traits in adult community samples.

RESULTS

This meta-analysis identified, with small to medium effect sizes, distinctive patterns in late ERP amplitudes, indicating enhanced responses to visual stimuli and the opposite patterns to auditory tasks in the included sample. Additionally, a pattern of higher amplitudes was also found for the component P3b in autistic traits.

DISCUSSION

Differential effects in visual and auditory domains are explored in light of the predictive processing framework for Autism. It remains possible that different brain mechanisms operate to explain symptoms related with different sensory modalities. P3b is discussed as a possible component of interest in future studies as it revealed a more robust effect for differentiating severity in the expression of autistic traits in adulthood.

Rodent Models for ASD Biomarker Development

Advances in molecular biology and genetics are increasingly revealing the complex etiology of autism spectrum disorder (ASD). In parallel, a number of biochemical, anatomical, and electrophysiological measures are emerging as potential disease-relevant biomarkers that could inform the diagnosis and clinical management of ASD. Rodent ASD models play a key role in ASD research as essential experimental tools. Nevertheless, there are challenges and limitations to the validity and translational value of rodent models, including genetic relevance and cognitive performance differences between humans and rodents. In this chapter, we begin with a brief history of autism research, followed by prominent examples of disease-relevant mouse models enabled by current knowledge of genetics, molecular biology, and bioinformatics. These ASD-associated rodent models enable quantifiable biomarker development. Finally, we discuss the prospects of ASD biomarker development.

Delineating a Pathway for the Discovery of Functional Connectome Biomarkers of Autism

The promise of individually tailored care for autism has driven efforts to establish biomarkers. This chapter appraises the state of precision-medicine research focused on biomarkers based on the functional brain connectome. This work is grounded on abundant evidence supporting the brain dysconnection model of autism and the advantages of resting-state functional MRI (R-fMRI) for studying the brain in vivo. After considering biomarker requirements of consistency and clinical relevance, we provide a scoping review of R-fMRI studies of individual prediction in autism. In the past 10 years, responding to the availability of open data through the Autism Brain Imaging Data Exchange, machine learning studies have surged. Nearly all have focused on diagnostic label classification. These efforts have shown that autism prediction is feasible using functional connectome markers, with accuracy reported well above chance. In parallel, emerging approaches more directly addressing autism heterogeneity are paving the way for much-needed biomarkers of longitudinal outcome and treatment response. We conclude with key challenges to be addressed by the next generation of studies.

Neural correlates of face processing among preschoolers with fragile X syndrome, autism spectrum disorder, autism siblings, and typical development

The current study examined patterns of event-related potential (ERP) responses during a face processing task in groups of preschoolers uniquely impacted by autism spectrum disorder (ASD), including (1) children with ASD; (2) children with fragile X syndrome (FXS); (3) children with familial risk for ASD, but without a diagnosis (i.e., ASIBs); and (4) a low-risk control (LRC) group. Children with FXS have a high incidence of ASD diagnoses, but there have been no studies of the ERP response to faces in children with FXS and little work focused on children with ASD who have cognitive impairment. The current study examined children's ERP responses to faces and houses in four groups: LRC (N = 28, age = 5.2 years), ASIB (N = 23, age = 5.5 years), FXS (N = 19, age = 5.82 years), and ASD (N = 23, age = 5.5 years). The FXS and ASD groups were characterized by the presence of cognitive impairment. Pictures of upright and inverted faces and houses were presented while recording EEG with a 128-channel system. The N170 occurred at about 200 ms post stimulus onset, was largest on the posterior-lateral electrodes, and was larger for faces than houses. The P1 and N170 ERP components were larger for the FXS group than for the other three groups. The N170 ERP amplitude for the ASD and ASIB groups was smaller than both the LRC and FXS groups, and the LRC and FXS groups had the largest N170 responses on the right side. No difference was found in N170 latency between groups. The similarity of the ASD and ASIB responses suggest a common genetic or environmental origin of the reduced response. Although children with FXS have a high incidence of ASD outcomes, they differed from ASD and ASIB children in this study. Specifically, the children with FXS were hyperresponsive to all stimulus types while the ASD and ASIB groups showed attenuated responses for specific stimuli.

EEG Biomarkers for Autism: Rational, Support, and the Qualification Process

In this chapter, we highlight the advantages, progress, and pending challenges of developing electroencephalography (EEG) and event-related potential (ERP) biomarkers for use in autism spectrum disorder (ASD). We describe reasons why global efforts towards precision treatment in ASD are utilizing EEG indices to quantify biological mechanisms. We overview common sensory processing and attention biomarkers and provide translational examples examining the genetic etiology of autism across animal models and human subgroups. We describe human-specific social biomarkers related to face perception, a complex social cognitive process that may prove informative of autistic social behaviors. Lastly, we discuss outstanding considerations for quantifying EEG biomarkers, the challenges associated with rigor and reproducibility, contexts of future use, and propose opportunities for combinatory multidimensional biomarkers.

A neurophysiological signature of dynamic emotion recognition associated with social communication skills and cortical gamma-aminobutyric acid levels in children

Introduction

Emotion recognition is a core feature of social perception. In particular, perception of dynamic facial emotional expressions is a major feature of the third visual pathway. However, the classical N170 visual evoked signal does not provide a pure correlate of such processing. Indeed, independent component analysis has demonstrated that the N170 component is already active at the time of the P100, and is therefore distorted by early components. Here we implemented, a dynamic face emotional paradigm to isolate a more pure face expression selective N170. We searched for a neural correlate of perception of dynamic facial emotional expressions, by starting with a face baseline from which a facial expression evolved. This allowed for a specific facial expression contrast signal which we aimed to relate with social communication abilities and cortical gamma-aminobutyric acid (GABA) levels.

Methods

We recorded event-related potentials (ERPs) and Magnetic Resonance (MRS) measures in 35 typically developing (TD) children, (10-16 years) sex-matched, during emotion recognition of an avatar morphing/unmorphing from neutral to happy/sad expressions. This task allowed for the elimination of the contribution low-level visual components, in particular the P100, by morphing baseline isoluminant neutral faces into specific expressions, isolating dynamic emotion recognition. Therefore, it was possible to isolate a dynamic face sensitive N170 devoid of interactions with earlier components.

Results

We found delayed N170 and P300, with a hysteresis type of dependence on stimulus trajectory (morphing/unmorphing), with hemispheric lateralization. The delayed N170 is generated by an extrastriate source, which can be related to the third visual pathway specialized in biological motion processing. GABA levels in visual cortex were related with N170 amplitude and latency and predictive of worse social communication performance (SCQ scores). N170 latencies reflected delayed processing speed of emotional expressions and related to worse social communication scores.

Discussion

In sum, we found a specific N170 electrophysiological signature of dynamic face processing related to social communication abilities and cortical GABA levels. These findings have potential clinical significance supporting the hypothesis of a spectrum of social communication abilities and the identification of a specific face-expression sensitive N170 which can potentially be used in the development of diagnostic and intervention tools.

Resting-state EEG power differences in autism spectrum disorder: a systematic review and meta-analysis

Narrative reviews have described various resting-state EEG power differences in autism across all five canonical frequency bands, with increased power for low and high frequencies and reduced power for middle frequencies. However, these differences have yet to be quantified using effect sizes and probed robustly for consistency, which are critical next steps for clinical translation. Following PRISMA guidelines, we conducted a systematic review of published and gray literature on resting-state EEG power in autism. We performed 10 meta-analyses to synthesize and quantify differences in absolute and relative resting-state delta, theta, alpha, beta, and gamma EEG power in autism. We also conducted moderator analyses to determine whether demographic characteristics, methodological details, and risk-of-bias indicators might account for heterogeneous study effect sizes. Our literature search and study selection processes yielded 41 studies involving 1,246 autistic and 1,455 neurotypical individuals. Meta-analytic models of 135 effect sizes demonstrated that autistic individuals exhibited reduced relative alpha (g = -0.35) and increased gamma (absolute: g = 0.37, relative: g = 1.06) power, but similar delta (absolute: g = 0.06, relative: g = 0.10), theta (absolute: g = -0.03, relative: g = -0.15), absolute alpha (g = -0.17), and beta (absolute: g = 0.01, relative: g = 0.08) power. Substantial heterogeneity in effect sizes was observed across all absolute (I2: 36.1-81.9%) and relative (I2: 64.6-84.4%) frequency bands. Moderator analyses revealed that age, biological sex, IQ, referencing scheme, epoch duration, and use of gold-standard autism diagnostic instruments did not moderate study effect sizes. In contrast, resting-state paradigm type (eyes-closed versus eyes-open) moderated absolute beta, relative delta, and relative alpha power effect sizes, and resting-state recording duration moderated relative alpha power effect sizes. These findings support further investigation of resting-state alpha and gamma power as potential biomarkers for autism.

Endophenotype trait domains for advancing gene discovery in autism spectrum disorder

Autism spectrum disorder (ASD) is associated with a diverse range of etiological processes, including both genetic and non-genetic causes. For a plurality of individuals with ASD, it is likely that the primary causes involve multiple common inherited variants that individually account for only small levels of variation in phenotypic outcomes. This genetic landscape creates a major challenge for detecting small but important pathogenic effects associated with ASD. To address similar challenges, separate fields of medicine have identified endophenotypes, or discrete, quantitative traits that reflect genetic likelihood for a particular clinical condition and leveraged the study of these traits to map polygenic mechanisms and advance more personalized therapeutic strategies for complex diseases. Endophenotypes represent a distinct class of biomarkers useful for understanding genetic contributions to psychiatric and developmental disorders because they are embedded within the causal chain between genotype and clinical phenotype, and they are more proximal to the action of the gene(s) than behavioral traits. Despite their demonstrated power for guiding new understanding of complex genetic structures of clinical conditions, few endophenotypes associated with ASD have been identified and integrated into family genetic studies. In this review, we argue that advancing knowledge of the complex pathogenic processes that contribute to ASD can be accelerated by refocusing attention toward identifying endophenotypic traits reflective of inherited mechanisms. This pivot requires renewed emphasis on study designs with measurement of familial co-variation including infant sibling studies, family trio and quad designs, and analysis of monozygotic and dizygotic twin concordance for select trait dimensions. We also emphasize that clarification of endophenotypic traits necessarily will involve integration of transdiagnostic approaches as candidate traits likely reflect liability for multiple clinical conditions and often are agnostic to diagnostic boundaries. Multiple candidate endophenotypes associated with ASD likelihood are described, and we propose a new focus on the analysis of "endophenotype trait domains" (ETDs), or traits measured across multiple levels (e.g., molecular, cellular, neural system, neuropsychological) along the causal pathway from genes to behavior. To inform our central argument for research efforts toward ETD discovery, we first provide a brief review of the concept of endophenotypes and their application to psychiatry. Next, we highlight key criteria for determining the value of candidate endophenotypes, including unique considerations for the study of ASD. Descriptions of different study designs for assessing endophenotypes in ASD research then are offered, including analysis of how select patterns of results may help prioritize candidate traits in future research. We also present multiple candidate ETDs that collectively cover a breadth of clinical phenomena associated with ASD, including social, language/communication, cognitive control, and sensorimotor processes. These ETDs are described because they represent promising targets for gene discovery related to clinical autistic traits, and they serve as models for analysis of separate candidate domains that may inform understanding of inherited etiological processes associated with ASD as well as overlapping neurodevelopmental disorders.

Neural sensitivity to facial identity and facial expression discrimination in adults with autism

The fluent processing of faces can be challenging for autistic individuals. Here, we assessed the neural sensitivity to rapid changes in subtle facial cues in 23 autistic men and 23 age and IQ matched non-autistic (NA) controls using frequency-tagging electroencephalography (EEG). In oddball paradigms examining the automatic and implicit discrimination of facial identity and facial expression, base rate images were presented at 6 Hz, periodically interleaved every fifth image with an oddball image (i.e. 1.2 Hz oddball frequency). These distinctive frequency tags for base rate and oddball stimuli allowed direct and objective quantification of the neural discrimination responses. We found no large differences in the neural sensitivity of participants in both groups, not for facial identity discrimination, nor for facial expression discrimination. Both groups also showed a clear face-inversion effect, with reduced brain responses for inverted versus upright faces. Furthermore, sad faces generally elicited significantly lower neural amplitudes than angry, fearful and happy faces. The only minor group difference is the larger involvement of high-level right-hemisphere visual areas in NA men for facial expression processing. These findings are discussed from a developmental perspective, as they strikingly contrast with robust face processing deficits observed in autistic children using identical EEG paradigms.

Social Knowledge & Performance in Autism: A Critical Review & Recommendations

Autistic social challenges have long been assumed to arise from a lack of social knowledge ("not knowing what to do"), which has undergirded theory and practice in assessment, treatment, and education. However, emerging evidence suggests these differences may be better accounted for by difficulties with social performance ("doing what they may know"). This distinction has important implications for research, practice, policy, and community support of autistic people. This review examines the theoretical and clinical implications and empirical status of the knowledge-performance distinction in autism. Current evidence suggests that social knowledge deficits are neither definitional nor reliably related to outcomes in autism. Prioritizing social knowledge, then, may produce unanticipated, problematic consequences in terms of accuracy of assessment, intervention effectiveness, and promotion of stigma. It may also yield unrealistic expectations around the value of knowledge for autistic people and their families, yielding important ethical considerations. Conversely, recent evidence highlights performance-related factors as being especially promising for better modeling and addressing social challenges in autism. Prioritizing performance, then, may offer new directions for assessment, substantially different intervention opportunities, and novel methods of inclusion and affirmation. This review touches upon each of these domains and implications, integrates these developments with broader models of social competence in youth, and provides direction for future research and practice regarding social competence in autism.

A randomized cross-over trial investigating the neurocognitive effects of acute exercise on face recognition in children with autism spectrum disorder

Difficulties in face recognition contribute to social-cognitive problems in autistic children. Evidence on behavioral interventions targeting this cognitive domain is limited. In non-autistic individuals, a single exercise session is known to elicit temporary benefits for several cognitive functions. Our study investigates whether acute aerobic exercise influences face recognition in autistic children. In a randomized order, 29 participants completed a 20-min moderately-intense cycling bout on an ergometer and a control condition. Before and after each condition, participants categorized Mooney faces and instruments during a computerized cognitive task. Simultaneously, the N170 component of event-related potentials and pupil size were recorded using electroencephalography and eyetracking, respectively. As indicated by a greater increase of reaction time in the exercise compared to the control condition, the results revealed impaired face recognition following aerobic exercise. This effect was accompanied by a lower decrease of the positive N170 amplitude and a trend towards a greater constriction of the pupil size in the exercise compared to the control condition. Our findings highlight the interplay of the physiological state and face recognition in autistic children. Exercise-induced impairments in this social-cognitive ability may be due to an interference with the learning effect that is typically seen for the structural encoding of faces.

Candidate biomarkers in psychiatric disorders: state of the field

The field of psychiatry is hampered by a lack of robust, reliable and valid biomarkers that can aid in objectively diagnosing patients and providing individualized treatment recommendations. Here we review and critically evaluate the evidence for the most promising biomarkers in the psychiatric neuroscience literature for autism spectrum disorder, schizophrenia, anxiety disorders and post-traumatic stress disorder, major depression and bipolar disorder, and substance use disorders. Candidate biomarkers reviewed include various neuroimaging, genetic, molecular and peripheral assays, for the purposes of determining susceptibility or presence of illness, and predicting treatment response or safety. This review highlights a critical gap in the biomarker validation process. An enormous societal investment over the past 50 years has identified numerous candidate biomarkers. However, to date, the overwhelming majority of these measures have not been proven sufficiently reliable, valid and useful to be adopted clinically. It is time to consider whether strategic investments might break this impasse, focusing on a limited number of promising candidates to advance through a process of definitive testing for a specific indication. Some promising candidates for definitive testing include the N170 signal, an event-related brain potential measured using electroencephalography, for subgroup identification within autism spectrum disorder; striatal resting-state functional magnetic resonance imaging (fMRI) measures, such as the striatal connectivity index (SCI) and the functional striatal abnormalities (FSA) index, for prediction of treatment response in schizophrenia; error-related negativity (ERN), an electrophysiological index, for prediction of first onset of generalized anxiety disorder, and resting-state and structural brain connectomic measures for prediction of treatment response in social anxiety disorder. Alternate forms of classification may be useful for conceptualizing and testing potential biomarkers. Collaborative efforts allowing the inclusion of biosystems beyond genetics and neuroimaging are needed, and online remote acquisition of selected measures in a naturalistic setting using mobile health tools may significantly advance the field. Setting specific benchmarks for well-defined target application, along with development of appropriate funding and partnership mechanisms, would also be crucial. Finally, it should never be forgotten that, for a biomarker to be actionable, it will need to be clinically predictive at the individual level and viable in clinical settings.

EEG frequency tagging evidence of intact social interaction recognition in adults with autism

To explain the social difficulties in autism, many studies have been conducted on social stimuli processing. However, this research has mostly used basic social stimuli (e.g., eyes, faces, hands, single agent), not resembling the complexity of what we encounter in our daily social lives and what people with autism experience difficulties with. Third-party social interactions are complex stimuli that we come across often and are also highly relevant for social functioning. Interestingly, the existing behavioral studies point to altered social interaction processing in autism. However, it is not clear whether this is due to altered recognition or altered interpretation of social interactions. Here, we specifically investigated the recognition of social interaction in adults with and without autism. More precisely, we measured neural responses to social scenes depicting either social interaction or not with an electroencephalogram frequency tagging task and compared these responses between adults with and without autism (N = 61). The results revealed an enhanced response to social scenes with interaction, replicating previous findings in a neurotypical sample. Crucially, this effect was found in both groups, with no difference between them. This suggests that social interaction recognition is not atypical in adults with autism. Taken together with the previous behavioral evidence, our study thus suggests that individuals with autism are able to recognize social interactions, but that they might not extract the same information from those interactions or that they might use the extracted information differently.

Face processing in young adults with autism and ADHD: An event related potentials study

Background

Atypicalities in perception and interpretation of faces and emotional facial expressions have been reported in both autism and attention-deficit/hyperactivity disorder (ADHD) during childhood and adulthood. Investigation of face processing during young adulthood (18 to 25 years), a transition period to full-fledged adulthood, could provide important information on the adult outcomes of autism and ADHD.

Methods

In this study, we investigated event-related potentials (ERPs) related to visual face processing in autism, ADHD, and co-occurring autism and ADHD in a large sample of young adults (N = 566). The groups were based on the Diagnostic Interview for ADHD in Adults 2.0 (DIVA-2) and the Autism Diagnostic Observation Schedule-2 (ADOS-2). We analyzed ERPs from two passive viewing tasks previously used in childhood investigations: (1) upright and inverted faces with direct or averted gaze; (2) faces expressing different emotions.

Results

Across both tasks, we consistently found lower amplitude and longer latency of N170 in participants with autism compared to those without. Longer P1 latencies and smaller P3 amplitudes in response to emotional expressions and longer P3 latencies for upright faces were also characteristic to the autistic group. Those with ADHD had longer N170 latencies, specific to the face-gaze task. Individuals with both autism and ADHD showed additional alterations in gaze modulation and a lack of the face inversion effect indexed by a delayed N170.

Conclusion

Alterations in N170 for autistic young adults is largely consistent with studies on autistic adults, and some studies in autistic children. These findings suggest that there are identifiable and measurable socio-functional atypicalities in young adults with autism.

Predictability modulates neural response to eye contact in ASD

BACKGROUND

Deficits in establishing and maintaining eye-contact are early and persistent vulnerabilities of autism spectrum disorder (ASD), and the neural bases of these deficits remain elusive. A promising hypothesis is that social features of autism may reflect difficulties in making predictions about the social world under conditions of uncertainty. However, no research in ASD has examined how predictability impacts the neural processing of eye-contact in naturalistic interpersonal interactions.

METHOD

We used eye tracking to facilitate an interactive social simulation wherein onscreen faces would establish eye-contact when the participant looked at them. In Experiment One, receipt of eye-contact was unpredictable; in Experiment Two, receipt of eye-contact was predictable. Neural response to eye-contact was measured via the N170 and P300 event-related potentials (ERPs). Experiment One included 23 ASD and 46 typically developing (TD) adult participants. Experiment Two included 25 ASD and 43 TD adult participants.

RESULTS

When receipt of eye-contact was unpredictable, individuals with ASD showed increased N170 and increased, but non-specific, P300 responses. The magnitude of the N170 responses correlated with measures of sensory and anxiety symptomology, such that increased response to eye-contact was associated with increased symptomology. However, when receipt of eye-contact was predictable, individuals with ASD, relative to controls, exhibited slower N170s and no differences in the amplitude of N170 or P300.

LIMITATIONS

Our ASD sample was composed of adults with IQ > 70 and included only four autistic women. Thus, further research is needed to evaluate how these results generalize across the spectrum of age, sex, and cognitive ability. Additionally, as analyses were exploratory, some findings failed to survive false-discovery rate adjustment.

CONCLUSIONS

Neural response to eye-contact in ASD ranged from attenuated to hypersensitive depending on the predictability of the social context. These findings suggest that the vulnerabilities in eye-contact during social interactions in ASD may arise from differences in anticipation and expectation of eye-contact in addition to the perception of gaze alone.

Understanding the nature of face processing in early autism: A prospective study

Dimensional approaches to psychopathology interrogate the core neurocognitive domains interacting at the individual level to shape diagnostic symptoms. Embedding this approach in prospective longitudinal studies could transform our understanding of the mechanisms underlying neurodevelopmental disorders. Such designs require us to move beyond traditional group comparisons and determine which domain-specific alterations apply at the level of the individual, and whether they vary across distinct phenotypic subgroups. As a proof of principle, this study examines how the domain of face processing contributes to the emergence of autism spectrum disorder (ASD). We used an event-related potentials (ERPs) task in a cohort of 8-month-old infants with (n = 148) and without (n = 68) an older sibling with ASD, and combined traditional case-control comparisons with machine-learning techniques for prediction of social traits and ASD diagnosis at 36 months, and Bayesian hierarchical clustering for stratification into subgroups. A broad profile of alterations in the time-course of neural processing of faces in infancy was predictive of later ASD, with a strong convergence in ERP features predicting social traits and diagnosis. We identified two main subgroups in ASD, defined by distinct patterns of neural responses to faces, which differed on later sensory sensitivity. Taken together, our findings suggest that individual differences between infants contribute to the diffuse pattern of alterations predictive of ASD in the first year of life. Moving from group-level comparisons to pattern recognition and stratification can help to understand and reduce heterogeneity in clinical cohorts, and improve our understanding of the mechanisms that lead to later neurodevelopmental outcomes. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Modern Biomarkers for Autism Spectrum Disorder: Future Directions

Autism spectrum disorder is an increasingly prevalent neurodevelopmental disorder in the world today, with an estimated 2% of the population being affected in the USA. A major complicating factor in diagnosing, treating, and understanding autism spectrum disorder is that defining the disorder is solely based on the observation of behavior. Thus, recent research has focused on identifying specific biological abnormalities in autism spectrum disorder that can provide clues to diagnosis and treatment. Biomarkers are an objective way to identify and measure biological abnormalities for diagnostic purposes as well as to measure changes resulting from treatment. This current opinion paper discusses the state of research of various biomarkers currently in development for autism spectrum disorder. The types of biomarkers identified include prenatal history, genetics, neurological including neuroimaging, neurophysiologic, and visual attention, metabolic including abnormalities in mitochondrial, folate, trans-methylation, and trans-sulfuration pathways, immune including autoantibodies and cytokine dysregulation, autonomic nervous system, and nutritional. Many of these biomarkers have promising preliminary evidence for prenatal and post-natal pre-symptomatic risk assessment, confirmation of diagnosis, subtyping, and treatment response. However, most biomarkers have not undergone validation studies and most studies do not investigate biomarkers with clinically relevant comparison groups. Although the field of biomarker research in autism spectrum disorder is promising, it appears that it is currently in the early stages of development.

Resting state EEG power spectrum and functional connectivity in autism: a cross-sectional analysis

BACKGROUND

Understanding the development of the neuronal circuitry underlying autism spectrum disorder (ASD) is critical to shed light into its etiology and for the development of treatment options. Resting state EEG provides a window into spontaneous local and long-range neuronal synchronization and has been investigated in many ASD studies, but results are inconsistent. Unbiased investigation in large and comprehensive samples focusing on replicability is needed.

METHODS

We quantified resting state EEG alpha peak metrics, power spectrum (PS, 2-32 Hz) and functional connectivity (FC) in 411 children, adolescents and adults (n = 212 ASD, n = 199 neurotypicals [NT], all with IQ > 75). We performed analyses in source-space using individual head models derived from the participants' MRIs. We tested for differences in mean and variance between the ASD and NT groups for both PS and FC using linear mixed effects models accounting for age, sex, IQ and site effects. Then, we used machine learning to assess whether a multivariate combination of EEG features could better separate ASD and NT participants. All analyses were embedded within a train-validation approach (70%-30% split).

RESULTS

In the training dataset, we found an interaction between age and group for the reactivity to eye opening (p = .042 uncorrected), and a significant but weak multivariate ASD vs. NT classification performance for PS and FC (sensitivity 0.52-0.62, specificity 0.59-0.73). None of these findings replicated significantly in the validation dataset, although the effect size in the validation dataset overlapped with the prediction interval from the training dataset.

LIMITATIONS

The statistical power to detect weak effects-of the magnitude of those found in the training dataset-in the validation dataset is small, and we cannot fully conclude on the reproducibility of the training dataset's effects.

CONCLUSIONS

This suggests that PS and FC values in ASD and NT have a strong overlap, and that differences between both groups (in both mean and variance) have, at best, a small effect size. Larger studies would be needed to investigate and replicate such potential effects.

Identifying Age Based Maturation in the ERP Response to Faces in Children With Autism: Implications for Developing Biomarkers for Use in Clinical Trials

Recent proposals have suggested the potential for neural biomarkers to improve clinical trial processes in neurodevelopmental conditions; however, few efforts have identified whether chronological age-based adjustments will be necessary (as used in standardized behavioral assessments). Event-related potentials (ERPs) demonstrate early differences in the processing of faces vs. objects in the visual processing system by 4 years of age and age-based improvement (decreases in latency) through adolescence. Additionally, face processing has been proposed to be related to social skills as well as autistic social-communication traits. While previous reports suggest delayed latency in individuals with autism spectrum disorder (ASD), extensive individual and age based heterogeneity exists. In this report, we utilize a sample of 252 children with ASD and 118 children with typical development (TD), to assess the N170 and P100 ERP component latencies (N170L and P100L, respectively), to upright faces, the face specificity effect (difference between face and object processing), and the inversion effect (difference between face upright and inverted processing) in relation to age. First, linear mixed models (LMMs) were fitted with fixed effect of age at testing and random effect of participant, using all available data points to characterize general age-based development in the TD and ASD groups. Second, LMM models using only the TD group were used to calculate age-based residuals in both groups. The purpose of residualization was to assess how much variation in ASD participants could be accounted for by chronological age-related changes. Our data demonstrate that the N170L and P100L responses to upright faces appeared to follow a roughly linear relationship with age. In the ASD group, the distribution of the age-adjusted residual values suggest that ASD participants were more likely to demonstrate slower latencies than would be expected for a TD child of the same age, similar to what has been identified using unadjusted values. Lastly, using age-adjusted values for stratification, we found that children who demonstrated slowed age-adjusted N170L had lower verbal and non-verbal IQ and worse face memory. These data suggest that age must be considered in assessing the N170L and P100L response to upright faces as well, and these adjusted values may be used to stratify children within the autism spectrum.

Effectiveness of virtual reality and computerized training programs for enhancing emotion recognition in people with autism spectrum disorder: a systematic review and meta-analysis

Background: People with autism spectrum disorder (ASD) have difficulties recognizing emotions. Studies showed that virtual reality (VR) and computerized training programs might be used as potential tools for enhancing emotion recognition in such people. However, some inconsistencies were observed between the studies. Objective: In the current systematic review and meta-analysis, the potential of computerized and VR training programs were evaluated for enhancing emotion recognition in people with ASD. Method: Using PRISMA guidelines and a PICO model, eligible studies were retrieved and the pooled effect size was calculated. Results: This meta-analysis obtained the pooled effect of Cohen's d = 0.69 (95% CI: [0.49, 0.89]) that showed the positive effect of VR and computerized training on emotion recognition in people with ASD. The effectiveness was confirmed for different types of study design, and for both children and adults, while it was larger for non-VR computerized programs compared with VR counterparts. Conclusion-Due to the small sample size of this study and the substantial heterogeneity between studies, the outcomes should be considered with caution in practice. However, these outcomes can be considered for optimizing suitable computerized applications or as the hypothesis for future studies.

Sex differences in automatic emotion regulation in adolescents with autism spectrum disorder

Autism may be underdiagnosed in females because their social difficulties are often less noticeable. This study explored sex differences in automatic facial emotion processing in 45 adolescents with autism spectrum disorder (22 female, 23 male), age 10-16 years, performing active target detection task and Go/NoGo tasks where faces with positive and negative emotional expressions served as irrelevant distractors. The combined sample demonstrated more accurate performance on the target detection (response initiation) than the Go/NoGo task (response inhibition), replicating findings previously reported in typical participants. Females exhibited greater difficulty than males with response initiation in the target detection task, especially in the context of angry faces, while males found withholding a response in the Go/NoGo block with happy faces more challenging. Electrophysiological data revealed no sex differences or emotion discrimination effects during the early perceptual processing of faces indexed by the occipitotemporal N170. Autistic males demonstrated increased frontal N2 and parietal P3 amplitudes compared to females, suggesting greater neural resource allocation to automatic emotion regulation processes. The associations between standardized behavioral measures (autism severity, theory of mind skills) and brain responses also varied by sex: more adaptive social functioning was related to the speed of perceptual processing (N170 latency) in females and the extent of deliberate attention allocation (P3 amplitudes) in males. Together, these findings suggest that males and females with autism may rely on different strategies for social functioning and highlight the importance of considering sex differences in autism. LAY SUMMARY: Females with autism may exhibit less noticeable social difficulties than males. This study demonstrates that autistic females are more successful than males at inhibiting behavioral responses in emotional contexts, while males are more likely to initiate a response. At the neural level, social functioning in females is related to the speed of automatic perceptual processing of facial cues, and in males, to the extent of active attention allocation to the stimuli. These findings highlight the importance of considering sex differences in autism diagnosis and treatment selection.

Autism Spectrum Disorder and Clinical High Risk for Psychosis: A Systematic Review and Meta-analysis

Psychotic experiences can occur in autism spectrum disorders (ASD). Some of the ASD individuals with these experiences may fulfil Clinical High-Risk for Psychosis (CHR-P) criteria. A systematic literature search was performed to review the information on ASD and CHR-P. A meta-analysis of the proportion of CHR-P in ASD was conducted. The systematic review included 13 studies. The mean age of ASD individuals across the included studies was 11.09 years. The Attenuated Psychosis Syndrome subgroup was the most frequently reported. Four studies were meta-analysed, showing that 11.6% of CHR-P individuals have an ASD diagnosis. Symptoms of prodromal psychosis may be present in individuals with ASD. The transition from CHR-P to psychosis is not affected by ASD.

Multimodal Evidence of Atypical Processing of Eye Gaze and Facial Emotion in Children With Autistic Traits

According to the shared signal hypothesis (SSH) the impact of facial expressions on emotion processing partially depends on whether the gaze is directed toward or away from the observer. In autism spectrum disorder (ASD) several aspects of face processing have been found to be atypical, including attention to eye gaze and the identification of emotional expressions. However, there is little research on how gaze direction affects emotional expression processing in typically developing (TD) individuals and in those with ASD. This question is investigated here in two multimodal experiments. Experiment 1 required processing eye gaze direction while faces differed in emotional expression. Forty-seven children (aged 9-12 years) participated. Their Autism Diagnostic Observation Schedule (ADOS) scores ranged from 0 to 6 in the experiment. Event-related potentials (ERPs) were sensitive to gaze direction and emotion, but emotion processing did not depend on gaze direction. However, for angry faces the gaze direction effect on the N170 amplitude, as typically observed in TD individuals, diminished with increasing ADOS score. For neutral expressions this correlation was not significant. Experiment 2 required explicit emotion classifications in a facial emotion composite task while eye gaze was manipulated incidentally. A group of 22 children with ASD was compared to a propensity score-matched group of TD children (mean age = 13 years). The same comparison was carried out for a subgroup of nine children with ASD who were less trained in social cognition, according to clinician's report. The ASD group performed overall worse in emotion recognition than the TD group, independently of emotion or gaze direction. However, for disgust expressions, eye tracking data revealed that TD children fixated relatively longer on the eyes of the stimulus face with a direct gaze as compared with averted gaze. In children with ASD we observed no such modulation of fixation behavior as a function of gaze direction. Overall, the present findings from ERPs and eye tracking confirm the hypothesis of an impaired sensitivity to gaze direction in children with ASD or elevated autistic traits, at least for specific emotions. Therefore, we conclude that multimodal investigations of the interaction between emotional processing and stimulus gaze direction are promising to understand the characteristics of individuals differing along the autism trait dimension.

EEG as a translational biomarker and outcome measure in fragile X syndrome

Targeted treatments for fragile X syndrome (FXS) have frequently failed to show efficacy in clinical testing, despite success at the preclinical stages. This has highlighted the need for more effective translational outcome measures. EEG differences observed in FXS, including exaggerated N1 ERP amplitudes, increased resting gamma power and reduced gamma phase-locking in the sensory cortices, have been suggested as potential biomarkers of the syndrome. These abnormalities are thought to reflect cortical hyper excitability resulting from an excitatory (glutamate) and inhibitory (GABAergic) imbalance in FXS, which has been the target of several pharmaceutical remediation studies. EEG differences observed in humans also show similarities to those seen in laboratory models of FXS, which may allow for greater translational equivalence and better predict clinical success of putative therapeutics. There is some evidence from clinical trials showing that treatment related changes in EEG may be associated with clinical improvements, but these require replication and extension to other medications. Although the use of EEG characteristics as biomarkers is still in the early phases, and further research is needed to establish its utility in clinical trials, the current research is promising and signals the emergence of an effective translational biomarker.

Looking Back at the Next 40 Years of ASD Neuroscience Research

During the last 40 years, neuroscience has become one of the most central and most productive approaches to investigating autism. In this commentary, we assemble a group of established investigators and trainees to review key advances and anticipated developments in neuroscience research across five modalities most commonly employed in autism research: magnetic resonance imaging, functional near infrared spectroscopy, positron emission tomography, electroencephalography, and transcranial magnetic stimulation. Broadly, neuroscience research has provided important insights into brain systems involved in autism but not yet mechanistic understanding. Methodological advancements are expected to proffer deeper understanding of neural circuitry associated with function and dysfunction during the next 40 years.

Investigating Changes in Reward-Related Neural Correlates After PEERS Intervention in Adolescents With ASD: Preliminary Evidence of a "Precision Medicine" Approach

Background: The Social Motivation Hypothesis proposes that individuals with autism spectrum disorder (ASD) experience social interactions as less rewarding than their neurotypical (TD) peers, which may lead to reduced social initiation. Existing studies of the brain's reward system in individuals with ASD report varied findings for anticipation of and response to social rewards. Given discrepant findings, the anticipation of and response to social rewards should be further evaluated, particularly in the context of intervention outcome. We hypothesized that individual characteristics may help predict neural changes from pre- to post-intervention. Methods: Thirteen adolescents with ASD received the Program for the Education and Enrichment of Relational Skills (PEERS) intervention for 16 weeks; reward-related EEG was collected before and after intervention. Fourteen TD adolescents were tested at two timepoints but did not receive intervention. Event-related potentials were calculated to measure anticipation of (stimulus-preceding negativity; SPN) and response to (reward-related positivity; RewP) social and non-social rewards. Additionally, measures of social responsiveness, social skills, and intervention-engagement were collected. Group differences were analyzed as well as individual differences using prediction models. Result: Parent-reported social responsiveness and social skills improved in adolescents with ASD after participation in PEERS. ASD adolescents displayed marginally decreased anticipation of social rewards at post-intervention compared to pre-intervention. Regression models demonstrated that older adolescents and those with lower parent-reported social motivation prior to participation in PEERS displayed marginally increased social reward anticipation (more robust SPN) from pre- to post-intervention. Participants who displayed more parent-reported social motivation before intervention and were more actively engaged in the PEERS intervention evidenced increased social reward processing (more robust RewP) from pre- to post-intervention. Conclusion: Findings suggest that there may be differences in saliency between wanting/anticipating social rewards vs. liking/responding to social rewards in individuals with ASD. Our findings support the hypothesis that identification of individual differences may predict which adolescents are poised to benefit the most from particular interventions. As such, reported findings set the stage for the advancement of "precision medicine." This investigation is a critical step forward in our ability to understand and predict individual response to interventions in individuals with ASD.

The meaning of significant mean group differences for biomarker discovery

Over the past decade, biomarker discovery has become a key goal in psychiatry to aid in the more reliable diagnosis and prognosis of heterogeneous psychiatric conditions and the development of tailored therapies. Nevertheless, the prevailing statistical approach is still the mean group comparison between "cases" and "controls," which tends to ignore within-group variability. In this educational article, we used empirical data simulations to investigate how effect size, sample size, and the shape of distributions impact the interpretation of mean group differences for biomarker discovery. We then applied these statistical criteria to evaluate biomarker discovery in one area of psychiatric research-autism research. Across the most influential areas of autism research, effect size estimates ranged from small (d = 0.21, anatomical structure) to medium (d = 0.36 electrophysiology, d = 0.5, eye-tracking) to large (d = 1.1 theory of mind). We show that in normal distributions, this translates to approximately 45% to 63% of cases performing within 1 standard deviation (SD) of the typical range, i.e., they do not have a deficit/atypicality in a statistical sense. For a measure to have diagnostic utility as defined by 80% sensitivity and 80% specificity, Cohen's d of 1.66 is required, with still 40% of cases falling within 1 SD. However, in both normal and nonnormal distributions, 1 (skewness) or 2 (platykurtic, bimodal) biologically plausible subgroups may exist despite small or even nonsignificant mean group differences. This conclusion drastically contrasts the way mean group differences are frequently reported. Over 95% of studies omitted the "on average" when summarising their findings in their abstracts ("autistic people have deficits in X"), which can be misleading as it implies that the group-level difference applies to all individuals in that group. We outline practical approaches and steps for researchers to explore mean group comparisons for the discovery of stratification biomarkers.

Modeling temporal dynamics of face processing in youth and adults

A hierarchical model of temporal dynamics was examined in adults (n = 34) and youth (n = 46) across the stages of face processing during the perception of static and dynamic faces. Three ERP components (P100, N170, N250) and spectral power in the mu range were extracted, corresponding to cognitive stages of face processing: low-level vision processing, structural encoding, higher-order processing, and action understanding. Youth and adults exhibited similar yet distinct patterns of hierarchical temporal dynamics such that earlier cognitive stages predicted later stages, directly and indirectly. However, latent factors indicated unique profiles related to behavioral performance for adults and youth and age as a continuous factor. The application of path analysis to electrophysiological data can yield novel insights into the cortical dynamics of social information processing.

Brief Report: Preliminary Evidence of the N170 as a Biomarker of Response to Treatment in Autism Spectrum Disorder

Background: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by primary difficulties in social function. Individuals with ASD display slowed neural processing of faces, as indexed by the latency of the N170, a face-sensitive event-related potential. Currently, there are no objective biomarkers of ASD useful in clinical care or research. Efficacy of behavioral treatment is currently evaluated through subjective clinical impressions. To explore whether the N170 might have utility as an objective index of treatment response, we examined N170 before and after receipt of an empirically validated behavioral treatment in children with ASD. Method: Electroencephalography (EEG) data were obtained on a preliminary cohort of preschool-aged children with ASD before and after a 16-week course of PRT and in a subset of participants in waitlist control (16-weeks before the start of PRT) and follow-up (16-weeks after the end of PRT). EEG was recorded while participants viewed computer-generated faces with neutral and fearful affect. Results: Significant reductions in N170 latency to faces were observed following 16 weeks of PRT intervention. Change in N170 latency was not observed in the waitlist-control condition. Conclusions: This exploratory study offers suggestive evidence that N170 latency may index response to behavioral treatment. Future, more rigorous, studies in larger samples are indicated to evaluate whether the N170 may be useful as a biomarker of treatment response.

The N170 event-related potential reflects delayed neural response to faces when visual attention is directed to the eyes in youths with ASD

Atypical neural response to faces is thought to contribute to social deficits in autism spectrum disorder (ASD). Compared to typically developing (TD) controls, individuals with ASD exhibit delayed brain responses to upright faces at a face-sensitive event-related potential (ERP), the N170. Given observed differences in patterns of visual attention to faces, it is not known whether slowed neural processing may simply reflect atypical looking to faces. The present study manipulated visual attention to facial features to examine whether directed attention to the eyes normalizes N170 latency in ASD. ERPs were recorded in 30 children and adolescents with ASD as well as 26 TD children and adolescents. Results replicated prior findings of shorter N170 latency to the eye region of the face in TD individuals. In contrast, those with ASD did not demonstrate modulation of N170 latency by point of regard to the face. Group differences in latency were most pronounced when attention was directed to the eyes. Results suggest that well-replicated findings of N170 delays in ASD do not simply reflect atypical patterns of visual engagement with experimental stimuli. These findings add to a body of evidence indicating that N170 delays are a promising marker of atypical neural response to social information in ASD. LAY SUMMARY: This study looks at how children's and adolescents' brains respond when looking at different parts of a face. Typically developing children and adolescents processed eyes faster than other parts of the face, whereas this pattern was not seen in ASD. Children and adolescents with ASD processed eyes more slowly than typically developing children. These findings suggest that observed inefficiencies in face processing in ASD are not simply reflective of failure to attend to the eyes.

Emotional visual mismatch negativity: a joint investigation of social and non-social dimensions in adults with autism

Unusual behaviors and brain activity to socio-emotional stimuli have been reported in Autism Spectrum Disorder (ASD). Atypical reactivity to change and intolerance of uncertainty are also present, but little is known on their possible impact on facial expression processing in autism. The visual mismatch negativity (vMMN) is an electrophysiological response automatically elicited by changing events such as deviant emotional faces presented among regular neutral faces. While vMMN has been found altered in ASD in response to low-level changes in simple stimuli, no study has investigated this response to visual social stimuli. Here two deviant expressions were presented, neutral and angry, embedded in a sequence of repetitive neutral stimuli. vMMN peak analyses were performed for latency and amplitude in early and late time windows. The ASD group presented smaller amplitude of the late vMMN to both neutral and emotional deviants compared to the typically developed adults (TD) group, and only the TD group presented a sustained activity related to emotional change (i.e., angry deviant). Source reconstruction of the vMMNs further revealed that any change processing elicited a reduced activity in ASD group compared to TD in the saliency network, while the specific processing emotional change elicited activity in the temporal region and in the insula. This study confirms atypical change processing in ASD and points to a specific difficulty in the processing of emotional changes, potentially playing a crucial role in social interaction deficits. Nevertheless, these results require to be further replicated with a greater sample size and generalized to other emotional expressions.

Facial Expression Processing Across the Autism-Psychosis Spectra: A Review of Neural Findings and Associations With Adverse Childhood Events

Autism spectrum disorder (ASD) and primary psychosis are classified as distinct neurodevelopmental disorders, yet they display overlapping epidemiological, environmental, and genetic components as well as endophenotypic similarities. For instance, both disorders are characterized by impairments in facial expression processing, a crucial skill for effective social communication, and both disorders display an increased prevalence of adverse childhood events (ACE). This narrative review provides a brief summary of findings from neuroimaging studies investigating facial expression processing in ASD and primary psychosis with a focus on the commonalities and differences between these disorders. Individuals with ASD and primary psychosis activate the same brain regions as healthy controls during facial expression processing, albeit to a different extent. Overall, both groups display altered activation in the fusiform gyrus and amygdala as well as altered connectivity among the broader face processing network, probably indicating reduced facial expression processing abilities. Furthermore, delayed or reduced N170 responses have been reported in ASD and primary psychosis, but the significance of these findings is questioned, and alternative frequency-tagging electroencephalography (EEG) measures are currently explored to capture facial expression processing impairments more selectively. Face perception is an innate process, but it is also guided by visual learning and social experiences. Extreme environmental factors, such as adverse childhood events, can disrupt normative development and alter facial expression processing. ACE are hypothesized to induce altered neural facial expression processing, in particular a hyperactive amygdala response toward negative expressions. Future studies should account for the comorbidity among ASD, primary psychosis, and ACE when assessing facial expression processing in these clinical groups, as it may explain some of the inconsistencies and confound reported in the field.

The N170 event-related potential differentiates congruent and incongruent gaze responses in gaze leading

To facilitate social interactions, humans need to process the responses that other people make to their actions, including eye movements that could establish joint attention. Here, we investigated the neurophysiological correlates of the processing of observed gaze responses following the participants’ own eye movement. These observed gaze responses could either establish, or fail to establish, joint attention. We implemented a gaze leading paradigm in which participants made a saccade from an on-screen face to an object, followed by the on-screen face either making a congruent or incongruent gaze shift. An N170 event-related potential was elicited by the peripherally located gaze shift stimulus. Critically, the N170 was greater for joint attention than non-joint gaze both when task-irrelevant (Experiment 1) and task-relevant (Experiment 2). These data suggest for the first time that the neurocognitive system responsible for structural encoding of face stimuli is affected by the establishment of participant-initiated joint attention.

Computer data simulator to assess the accuracy of estimates of visual N2/N2pc event-related potential components

OBJECTIVE

Event-related potentials (ERPs) evoked by visual stimulations comprise several components, with different amplitudes and latencies. Among them, the N2 and N2pc components have been demonstrated to be a measure of subjects' allocation of visual attention to possible targets and to be involved in the suppression of irrelevant items. Unfortunately, the N2 and N2pc components have smaller amplitudes compared with those of the background electroencephalogram (EEG), and their measurement requires employing techniques such as conventional averaging, which in turn necessitates several sweeps to provide acceptable estimates. In visual search studies, the number of sweeps (Nswp) used to extrapolate reliable estimates of N2/N2pc components has always been somehow arbitrary, with studies using 50-500 sweeps. In-silico studies relying on synthetic data providing a close-to-realistic fit to the variability of the visual N2 component and background EEG signals are therefore needed to go beyond arbitrary choices in this context.

APPROACH

In the present work, we sought to take a step in this direction by developing a simulator of ERP variations in the N2 time range based on real experimental data while monitoring variations in the estimation accuracy of N2/N2pc components as a function of two factors, i.e. signal-to-noise ratio (SNR) and number of averaged sweeps.

MAIN RESULTS

The results revealed that both Nswp and SNR had a strong impact on the accuracy of N2/N2pc estimates. Critically, the present simulation showed that, for a given level of SNR, a non-arbitrary Nswp could be parametrically determined, after which no additional significant improvements in noise suppression and N2/N2pc accuracy estimation were observed.

SIGNIFICANCE

The present simulator is thought to provide investigators with quantitative guidelines for designing experimental protocols aimed at improving the detection accuracy of N2/N2pc components. The parameters of the simulator can be tuned, adapted, or integrated to fit other ERP modulations.

Evidence of an Own-Age Bias in Facial Emotion Recognition for Adolescents With and Without Autism Spectrum Disorder

A common interpretation of the face-processing deficits associated with autism spectrum disorder (ASD) is that they arise from a failure to develop normative levels of perceptual expertise. One indicator of perceptual expertise for faces is the own-age bias, operationalized as a processing advantage for faces of one's own age, presumably due to more frequent contact and experience. This effect is especially evident in domains of face recognition memory but less commonly investigated in social-emotional expertise (e.g., facial emotion recognition; FER), where individuals with ASD have shown consistent deficits. In the present study, we investigated whether a FER task would elicit an own-age bias for individuals with and without ASD and explored how the magnitude of an own-age bias may differ as a function of ASD status and symptoms. Ninety-two adolescents (63 male) between the ages of 11 and 14 years completed the child- and adult-face subtests of a standardized FER task. Overall FER accuracy was found to differ by ASD severity, reflecting poorer performance for those with increased symptoms. Results also indicated that an own-age bias was evident, reflecting greater FER performance for child compared to adult faces, for all adolescents regardless of ASD status or symptoms. However, the strength of the observed own-age bias did not differ by ASD status or severity. Findings suggest that face processing abilities of adolescents with ASD may be influenced by experience with specific categories of stimuli, similar to their typically developing peers.