11C-UCB-J PET imaging is consistent with lower synaptic density in autistic adults.

The neural bases of autism are poorly understood at the molecular level, but evidence from animal models, genetics, post-mortem studies, and single-gene disorders implicate synaptopathology. Here, we use positron emission tomography (PET) to assess the density of synapses with synaptic vesicle glycoprotein 2A (SV2A) in autistic adults using 11C-UCB-J. Twelve autistic (mean (SD) age 25 (4) years; six males), and twenty demographically matched non-autistic individuals (26 (3) years; eleven males) participated in a 11C-UCB-J PET scan. Binding potential, BPND, was the primary outcome measure and computed with the centrum semiovale as the reference region. Partial volume correction with Iterative Yang was applied to control for possible volumetric differences. Mixed-model statistics were calculated for between-group differences. Relationships to clinical characteristics were evaluated based on clinician ratings of autistic features. Whole cortex synaptic density was 17% lower in the autism group (p = 0.01). All brain regions in autism had lower 11C-UCB-J BPND compared to non-autistic participants. This effect was evident in all brain regions implicated in autism. Significant differences were observed across multiple individual regions, including the prefrontal cortex (-15%, p = 0.02), with differences most pronounced in gray matter (p < 0.0001). Synaptic density was significantly associated with clinical measures across the whole cortex (r = 0.67, p = 0.02) and multiple regions (rs = -0.58 to -0.82, ps = 0.05 to <0.01). The first in vivo investigation of synaptic density in autism with PET reveals pervasive and large-scale lower density in the cortex and across multiple brain areas. Synaptic density also correlated with clinical features, such that a greater number of autistic features were associated with lower synaptic density. These results indicate that brain-wide synaptic density may represent an as-yet-undiscovered molecular basis for the clinical phenotype of autism and associated pervasive alterations across a diversity of neural processes.

Clinician-caregiver informant discrepancy is associated with sex, diagnosis age, and intervention use among autistic children.

LAY ABSTRACT: In some cases, a clinician's perceptions of a child's autism-related behaviors are not the same as the child's caregiver's perceptions. Identifying how these discrepancies relate to the characteristics of the child is critical for ensuring that diagnosis procedures are unbiased and suitable for all children. This study examined whether discrepancies between clinician and caregiver reports of autism features related to the child's sex at birth. We also explored how the discrepancies related to the age at which the child received their autism diagnosis and how much intervention they received. We found that clinicians rated autism features higher than caregivers for boys and rated autism features lower than caregivers for girls. In addition, lower clinician relative to parent ratings was related to being diagnosed at an older age and receiving less intervention. These findings suggest that there is more to learn about the presentation of autism-related behaviors in girls. When caregiver and clinician ratings of autism features do not align, it may be important to consider caregivers' ratings to obtain a more accurate picture of the child's autism features and the support they may need.

Widespread Associations between Behavioral Metrics and Brain Microstructure in ASD.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication and repetitive behaviors. A diagnosis of ASD is provided by a clinician following cognitive and behavioral evaluations, but there is currently no biomarker associating these metrics with neurological changes. Our lab has previously found that g-ratio, the proportion of axon width to myelin diameter, and axonal conduction velocity, which is associated with the capacity of an axon to carry information, are both decreased in ASD individuals. By associating these differences with performance on cognitive and behavioral tests, we can evaluate which tests most reveal changes in the brain. Analyzing 273 participants (148 with ASD) ages 8-to-17 (49% female) through an NIH-sponsored Autism Centers of Excellence (ACE) network (Grant#: MH100028), we observe widespread associations between behavioral and cognitive evaluations of autism and between behavioral and microstructural metrics. Analyzing data from all participants, conduction velocity but not g-ratio was significantly associated with many behavioral metrics. However, this pattern was reversed when looking solely at ASD participants. This reversal may suggest that the mechanism underlying differences between autistic and non-autistic individuals may be distinct from the mechanism underlying ASD behavioral severity. Two additional machine learning cluster analyses applied to neuroimaging data reinforce the association between neuroimaging and behavioral metrics and suggest that age-related maturation of brain metrics may drive changes in ASD behavior. By associating neuroimaging metrics with ASD, it may be possible to measure and identify individuals at high risk of ASD before behavioral tests can detect them.

Spatiotemporal Eye Movement Dynamics Reveal Altered Face Prioritization in Early Visual Processing Among Autistic Children.

BACKGROUND: Reduced social attention - looking at faces - is one of the most common manifestations of social difficulty in autism central to social development. Although reduced social attention is well-characterized in autism, qualitative differences in how social attention unfolds across time remains unknown. METHODS: We used a computational modeling (i.e., hidden Markov modeling) approach to assess and compare the spatiotemporal dynamics of social attention in a large, well-characterized sample of autistic (n = 280) and neurotypical (n = 120) children (ages 6-11) that completed three social eye-tracking assays across three longitudinal time points (Baseline, 6 weeks, 24 weeks). RESULTS: Our analysis supported the existence of two common eye movement patterns that emerged across three ET assays. A focused pattern was characterized by small face regions of interest, which had high probability of capturing fixations early in visual processing. In contrast, an exploratory pattern was characterized by larger face regions of interest, with lower initial probability of fixation, and more non-social regions of interest. In the context of social perception, autistic children showed significantly more exploratory eye movement patterns than neurotypical children across all social perception assays and all three longitudinal time points. Eye movement patterns were associated with clinical features of autism, including adaptive function, face recognition, and autism symptom severity. CONCLUSIONS: Decreased likelihood of precisely looking to faces early in social visual processing may be an important feature of autism that was associated with autism-related symptomology and may reflect less visual sensitivity to face information.

Central and peripheral physiological responses to decision making in hoarding disorder.

Individuals with hoarding disorder (HD) have difficulty parting with personal possessions, which leads to the accumulation of excessive clutter. According to a proposed biphasic neurobiological model, HD is characterized by blunted central and peripheral nervous system activity at rest and during neutral (non-discarding) decisions, and exaggerated activity during decision-making about discarding personal possessions. Here, we compared the error-related negativity (ERN) and psychophysiological responses (skin conductance, heart rate and heart rate variability, and end tidal CO2) during neutral and discarding-related decisions in 26 individuals with HD, 37 control participants with anxiety disorders, and 28 healthy control participants without psychiatric diagnoses. We also compared alpha asymmetry between the HD and control groups during a baseline resting phase. Participants completed a series of Go/No Go decision-making tasks, one involving choosing certain shapes (neutral task) and the other involving choosing images of newspapers to imaginally "discard" (discarding task). While all participants showed expected increased frontal negativity to commission of an error, contrary to hypotheses, there were no group differences in the ERN or any psychophysiological measures. Alpha asymmetry at rest also did not differ between groups. The findings suggest that the ERN and psychophysiological responses may not differ in individuals with HD during simulated discarding decisions relative to control participants, although the null results may be explained by methodological challenges in using Go/No Go tasks as discarding tasks. Future replication and extension of these results will be needed using ecologically valid discarding tasks.

Parsing evoked and induced gamma response differences in Autism: A visual evoked potential study.

OBJECTIVE: Electroencephalography (EEG) measures of visual evoked potentials (VEPs) provide a targeted approach for investigating neural circuit dynamics. This study separately analyses phase-locked (evoked) and non-phase-locked (induced) gamma responses within the VEP to comprehensively investigate circuit differences in autism. METHODS: We analyzed VEP data from 237 autistic and 114 typically developing (TD) children aged 6-11, collected through the Autism Biomarkers Consortium for Clinical Trials (ABC-CT). Evoked and induced gamma (30-90 Hz) responses were separately quantified using a wavelet-based time-frequency analysis, and group differences were evaluated using a permutation-based clustering procedure. RESULTS: Autistic children exhibited reduced evoked gamma power but increased induced gamma power compared to TD peers. Group differences in induced responses showed the most prominent effect size and remained statistically significant after excluding outliers. CONCLUSIONS: Our study corroborates recent research indicating diminished evoked gamma responses in children with autism. Additionally, we observed a pronounced increase in induced power. Building upon existing ABC-CT findings, these results highlight the potential to detect variations in gamma-related neural activity, despite the absence of significant group differences in time-domain VEP components. SIGNIFICANCE: The contrasting patterns of decreased evoked and increased induced gamma activity in autistic children suggest that a combination of different EEG metrics may provide a clearer characterization of autism-related circuitry than individual markers alone.

A common genetic variant in the Neurexin family member CNTNAP2 is related to language but not communication skills in youth with Autism Spectrum Disorder.

One of the candidate genes related to language variability in individuals with Autism Spectrum Disorder (ASD) is the contactin-associated protein-like 2 gene (CNTNAP2), a member of the Neurexin family. However, due to the different assessment tools used, it is unknown whether the polymorphisms of the CNTNAP2 gene are linked to structural language skills or more general communication abilities. A total of 302 youth aged 7 to 18 years participated in the present study: 131 verbal youth with ASD (62 female), 130 typically developing (TD) youth (64 female), and 41 unaffected siblings (US) of youth with ASD (25 female). Blood samples were collected to obtain genomic DNA and processed by the Rutgers University Cell and Data Repository or using standard protocols (Gentra Puregene Blood DNA extraction kit; Qiagen). Language and verbal communication skills were screened with the Clinical Evaluation of Language Fundamental-4 (CELF-4) and Vineland-II Communication domain, subsequently. The results showed that the polymorphism of CNTNAP2 (SNP rs2710102) was related to structural language abilities, such that participants carrying the A-allele had lower language skills in comparison to the G-allele homozygotes. No relationship was found between the polymorphism of CNTNAP2 and more general communication abilities. Although the study revealed genetic mechanisms that are associated with CELF-4 measures but not Vineland-II in youth with ASD, follow-up studies are needed that will include measures of language and communication that are less correlated to each other as well as will include a group of minimally and/or non-verbal individuals with ASD.

Modeling intra-individual inter-trial EEG response variability in autism.

Autism spectrum disorder (autism) is a prevalent neurodevelopmental condition characterized by early emerging impairments in social behavior and communication. EEG represents a powerful and non-invasive tool for examining functional brain differences in autism. Recent EEG evidence suggests that greater intra-individual trial-to-trial variability across EEG responses in stimulus-related tasks may characterize brain differences in autism. Traditional analysis of EEG data largely focuses on mean trends of the trial-averaged data, where trial-level analysis is rarely performed due to low neural signal to noise ratio. We propose to use nonlinear (shape-invariant) mixed effects (NLME) models to study intra-individual inter-trial EEG response variability using trial-level EEG data. By providing more precise metrics of response variability, this approach could enrich our understanding of neural disparities in autism and potentially aid the identification of objective markers. The proposed multilevel NLME models quantify variability in the signal's interpretable and widely recognized features (e.g., latency and amplitude) while also regularizing estimation based on noisy trial-level data. Even though NLME models have been studied for more than three decades, existing methods cannot scale up to large data sets. We propose computationally feasible estimation and inference methods via the use of a novel minorization-maximization (MM) algorithm. Extensive simulations are conducted to show the efficacy of the proposed procedures. Applications to data from a large national consortium find that children with autism have larger intra-individual inter-trial variability in P1 latency in a visual evoked potential (VEP) task, compared to their neurotypical peers.

The relationship between gamma-band neural oscillations and language skills in youth with Autism Spectrum Disorder and their first-degree relatives.

BACKGROUND: Most children with Autism Spectrum Disorder (ASD) have co-occurring language impairments and some of these autism-specific language difficulties are also present in their non-autistic first-degree relatives. One of the possible neural mechanisms associated with variability in language functioning is alterations in cortical gamma-band oscillations, hypothesized to be related to neural excitation and inhibition balance. METHODS: We used a high-density 128-channel electroencephalography (EEG) to register brain response to speech stimuli in a large sex-balanced sample of participants: 125 youth with ASD, 121 typically developing (TD) youth, and 40 unaffected siblings (US) of youth with ASD. Language skills were assessed with Clinical Evaluation of Language Fundamentals. RESULTS: First, during speech processing, we identified significantly elevated gamma power in ASD participants compared to TD controls. Second, across all youth, higher gamma power was associated with lower language skills. Finally, the US group demonstrated an intermediate profile in both language and gamma power, with nonverbal IQ mediating the relationship between gamma power and language skills. LIMITATIONS: We only focused on one of the possible neural contributors to variability in language functioning. Also, the US group consisted of a smaller number of participants in comparison to the ASD or TD groups. Finally, due to the timing issue in EEG system we have provided only non-phase-locked analysis. CONCLUSIONS: Autistic youth showed elevated gamma power, suggesting higher excitation in the brain in response to speech stimuli and elevated gamma power was related to lower language skills. The US group showed an intermediate pattern of gamma activity, suggesting that the broader autism phenotype extends to neural profiles.

Conduction velocity, G-ratio, and extracellular water as microstructural characteristics of autism spectrum disorder.

The neuronal differences contributing to the etiology of autism spectrum disorder (ASD) are still not well defined. Previous studies have suggested that myelin and axons are disrupted during development in ASD. By combining structural and diffusion MRI techniques, myelin and axons can be assessed using extracellular water, aggregate g-ratio, and a new approach to calculating axonal conduction velocity termed aggregate conduction velocity, which is related to the capacity of the axon to carry information. In this study, several innovative cellular microstructural methods, as measured from magnetic resonance imaging (MRI), are combined to characterize differences between ASD and typically developing adolescent participants in a large cohort. We first examine the relationship between each metric, including microstructural measurements of axonal and intracellular diffusion and the T1w/T2w ratio. We then demonstrate the sensitivity of these metrics by characterizing differences between ASD and neurotypical participants, finding widespread increases in extracellular water in the cortex and decreases in aggregate g-ratio and aggregate conduction velocity throughout the cortex, subcortex, and white matter skeleton. We finally provide evidence that these microstructural differences are associated with higher scores on the Social Communication Questionnaire (SCQ) a commonly used diagnostic tool to assess ASD. This study is the first to reveal that ASD involves MRI-measurable in vivo differences of myelin and axonal development with implications for neuronal and behavioral function. We also introduce a novel formulation for calculating aggregate conduction velocity, that is highly sensitive to these changes. We conclude that ASD may be characterized by otherwise intact structural connectivity but that functional connectivity may be attenuated by network properties affecting neural transmission speed. This effect may explain the putative reliance on local connectivity in contrast to more distal connectivity observed in ASD.

Autistic Individuals Do Not Alter Visual Processing Strategy During Encoding Versus Recognition of Faces: A Hidden Markov Modeling Approach.

PURPOSE: Visual face recognition-the ability to encode, discriminate, and recognize the faces of others-is fundamentally supported by eye movements and is a common source of difficulty for autistic individuals. We aimed to evaluate how visual processing strategies (i.e., eye movement patterns) directly support encoding and recognition of faces in autistic and neurotypical (NT) individuals. METHODS: We used a hidden Markov modeling approach to evaluate the spatiotemporal dynamics of eye movements in autistic (n = 15) and neurotypical (NT) adolescents (n = 17) during a face identity recognition task. RESULTS: We discovered distinct eye movement patterns among all participants, which included a focused and exploratory strategy. When evaluating change in visual processing strategy across encoding and recognition phases, autistic individuals did not shift their eye movement patterns like their NT peers, who shifted to a more exploratory visual processing strategy during recognition. CONCLUSION: These findings suggest that autistic individuals do not modulate their visual processing strategy across encoding and recognition of faces, which may be an indicator of less efficient face processing.

Support vector machine prediction of individual Autism Diagnostic Observation Schedule (ADOS) scores based on neural responses during live eye-to-eye contact.

Social difficulties during interactions with others are central to autism spectrum disorder (ASD). Understanding the links between these social difficulties and their underlying neural processes is a primary aim focused on improved diagnosis and treatment. In keeping with this goal, we have developed a multivariate classification method based on neural data acquired by functional near infrared spectroscopy, fNIRS, during live eye-to-eye contact with adults who were either typically developed (TD) or individuals with ASD. The ASD diagnosis was based on the gold-standard Autism Diagnostic Observation Schedule (ADOS) which also provides an index of symptom severity. Using a nested cross-validation method, a support vector machine (SVM) was trained to discriminate between ASD and TD groups based on the neural responses during eye-to-eye contact. ADOS scores were not applied in the classification training. To test the hypothesis that SVM identifies neural activity patterns related to one of the neural mechanisms underlying the behavioral symptoms of ASD, we determined the correlation coefficient between the SVM scores and the individual ADOS scores. Consistent with the hypothesis, the correlation between observed and predicted ADOS scores was 0.72 (p < 0.002). Findings suggest that multivariate classification methods combined with the live interaction paradigm of eye-to-eye contact provide a promising approach to link neural processes and social difficulties in individuals with ASD.

Conduction Velocity, G-ratio, and Extracellular Water as Microstructural Characteristics of Autism Spectrum Disorder.

The neuronal differences contributing to the etiology of autism spectrum disorder (ASD) are still not well defined. Previous studies have suggested that myelin and axons are disrupted during development in ASD. By combining structural and diffusion MRI techniques, myelin and axons can be assessed using extracellular water, aggregate g-ratio, and a novel metric termed aggregate conduction velocity, which is related to the capacity of the axon to carry information. In this study, several innovative cellular microstructural methods, as measured from magnetic resonance imaging (MRI), are combined to characterize differences between ASD and typically developing adolescent participants in a large cohort. We first examine the relationship between each metric, including microstructural measurements of axonal and intracellular diffusion and the T1w/T2w ratio. We then demonstrate the sensitivity of these metrics by characterizing differences between ASD and neurotypical participants, finding widespread increases in extracellular water in the cortex and decreases in aggregate g-ratio and aggregate conduction velocity throughout the cortex, subcortex, and white matter skeleton. We finally provide evidence that these microstructural differences are associated with higher scores on the Social Communication Questionnaire (SCQ) a commonly used diagnostic tool to assess ASD. This study is the first to reveal that ASD involves MRI-measurable in vivo differences of myelin and axonal development with implications for neuronal and behavioral function. We also introduce a novel neuroimaging metric, aggregate conduction velocity, that is highly sensitive to these changes. We conclude that ASD may be characterized by otherwise intact structural connectivity but that functional connectivity may be attenuated by network properties affecting neural transmission speed. This effect may explain the putative reliance on local connectivity in contrast to more distal connectivity observed in ASD.

Frontal EEG alpha asymmetry in youth with autism: Sex differences and social-emotional correlates.

In youth broadly, EEG frontal alpha asymmetry (FAA) associates with affective style and vulnerability to psychopathology, with relatively stronger right activity predicting risk for internalizing and externalizing behaviors. In autistic youth, FAA has been related to ASD diagnostic features and to internalizing symptoms. Among our large, rigorously characterized, sex-balanced participant group, we attempted to replicate findings suggestive of altered FAA in youth with an ASD diagnosis, examining group differences and impact of sex assigned at birth. Second, we examined relations between FAA and behavioral variables (ASD features, internalizing, and externalizing) within autistic youth, examining effects by sex. Third, we explored whether the relation between FAA, autism features, and mental health was informed by maternal depression history. In our sample, FAA did not differ by diagnosis, age, or sex. However, youth with ASD had lower total frontal alpha power than youth without ASD. For autistic females, FAA and bilateral frontal alpha power correlated with social communication features, but not with internalizing or externalizing symptoms. For autistic males, EEG markers correlated with social communication features, and with externalizing behaviors. Exploratory analyses by sex revealed further associations between youth FAA, behavioral indices, and maternal depression history. In summary, findings suggest that individual differences in FAA may correspond to social-emotional and mental health behaviors, with different patterns of association for females and males with ASD. Longitudinal consideration of individual differences across levels of analysis (e.g., biomarkers, family factors, and environmental influences) will be essential to parsing out models of risk and resilience among autistic youth.

The Selective Social Attention task in children with autism spectrum disorder: Results from the Autism Biomarkers Consortium for Clinical Trials (ABC-CT) feasibility study.

The Selective Social Attention (SSA) task is a brief eye-tracking task involving experimental conditions varying along socio-communicative axes. Traditionally the SSA has been used to probe socially-specific attentional patterns in infants and toddlers who develop autism spectrum disorder (ASD). This current work extends these findings to preschool and school-age children. Children 4- to 12-years-old with ASD (N = 23) and a typically-developing comparison group (TD; N = 25) completed the SSA task as well as standardized clinical assessments. Linear mixed models examined group and condition effects on two outcome variables: percent of time spent looking at the scene relative to scene presentation time (%Valid), and percent of time looking at the face relative to time spent looking at the scene (%Face). Age and IQ were included as covariates. Outcome variables' relationships to clinical data were assessed via correlation analysis. The ASD group, compared to the TD group, looked less at the scene and focused less on the actress' face during the most socially-engaging experimental conditions. Additionally, within the ASD group, %Face negatively correlated with SRS total T-scores with a particularly strong negative correlation with the Autistic Mannerism subscale T-score. These results highlight the extensibility of the SSA to older children with ASD, including replication of between-group differences previously seen in infants and toddlers, as well as its ability to capture meaningful clinical variation within the autism spectrum across a wide developmental span inclusive of preschool and school-aged children. The properties suggest that the SSA may have broad potential as a biomarker for ASD.

Systematic review: emotion dysregulation and challenging behavior interventions for children and adolescents on the autism spectrum with graded key evidence-based strategy recommendations.

Challenging behavior, such as aggression, is highly prevalent in children and adolescents on the autism spectrum and can have a devastating impact. Previous reviews of challenging behavior interventions did not include interventions targeting emotion dysregulation, a common cause of challenging behavior. We reviewed emotion dysregulation and challenging behavior interventions for preschoolers to adolescents to determine which evidence-based strategies have the most empirical support for reducing/preventing emotion dysregulation/challenging behavior. We reviewed 95 studies, including 29 group and 66 single case designs. We excluded non-behavioral/psychosocial interventions and those targeting internalizing symptoms only. We applied a coding system to identify discrete strategies based on autism practice guidelines with the addition of strategies common in childhood mental health disorders, and an evidence grading system. Strategies with the highest quality evidence (multiple randomized controlled trials with low bias risk) were Parent-Implemented Intervention, Emotion Regulation Training, Reinforcement, Visual Supports, Cognitive Behavioral/Instructional Strategies and Antecedent-Based Interventions. Regarding outcomes, most studies included challenging behavior measures, while few included emotion dysregulation measures. This review highlights the importance of teaching emotion regulation skills explicitly, positively reinforcing replacement/alternative behaviors, using visuals and metacognition, addressing stressors proactively, and involving parents. It also calls for more rigorously designed studies and for including emotion dysregulation as an outcome/mediator in future trials.

Modeling idiopathic autism in forebrain organoids reveals an imbalance of excitatory cortical neuron subtypes during early neurogenesis.

Idiopathic autism spectrum disorder (ASD) is highly heterogeneous, and it remains unclear how convergent biological processes in affected individuals may give rise to symptoms. Here, using cortical organoids and single-cell transcriptomics, we modeled alterations in the forebrain development between boys with idiopathic ASD and their unaffected fathers in 13 families. Transcriptomic changes suggest that ASD pathogenesis in macrocephalic and normocephalic probands involves an opposite disruption of the balance between excitatory neurons of the dorsal cortical plate and other lineages such as early-generated neurons from the putative preplate. The imbalance stemmed from divergent expression of transcription factors driving cell fate during early cortical development. While we did not find genomic variants in probands that explained the observed transcriptomic alterations, a significant overlap between altered transcripts and reported ASD risk genes affected by rare variants suggests a degree of gene convergence between rare forms of ASD and the developmental transcriptome in idiopathic ASD.

Development of peak alpha frequency reflects a distinct trajectory of neural maturation in autistic children.

Electroencephalographic peak alpha frequency (PAF) is a marker of neural maturation that increases with age throughout childhood. Distinct maturation of PAF is observed in children with autism spectrum disorder such that PAF does not increase with age and is instead positively associated with cognitive ability. The current study clarifies and extends previous findings by characterizing the effects of age and cognitive ability on PAF between diagnostic groups in a sample of children and adolescents with and without autism spectrum disorder. Resting EEG data and behavioral measures were collected from 45 autistic children and 34 neurotypical controls aged 8 to 18 years. Utilizing generalized additive models to account for nonlinear relations, we examined differences in the joint effect of age and nonverbal IQ by diagnosis as well as bivariate relations between age, nonverbal IQ, and PAF across diagnostic groups. Age was positively associated with PAF among neurotypical children but not among autistic children. In contrast, nonverbal IQ but not age was positively associated with PAF among autistic children. Models accounting for nonlinear relations revealed different developmental trajectories as a function of age and cognitive ability based on diagnostic status. Results align with prior evidence indicating that typical age-related increases in PAF are absent in autistic children and that PAF instead increases with cognitive ability in these children. Findings suggest the potential of PAF to index distinct trajectories of neural maturation in autistic children.

Investigating the Face Inversion Effect in Autism Across Behavioral and Neural Measures of Face Processing: A Systematic Review and Bayesian Meta-Analysis.

Importance: Face processing is foundational to human social cognition, is central to the hallmark features of autism spectrum disorder (ASD), and shapes neural systems and social behavior. Highly efficient and specialized, the face processing system is sensitive to inversion, demonstrated by reduced accuracy in recognition and altered neural response to inverted faces. Understanding at which mechanistic level the autistic face processing system may be particularly different, as measured by the face inversion effect, will improve overall understanding of brain functioning in autism. Objective: To synthesize data from the extant literature to determine differences of the face processing system in ASD, as measured by the face inversion effect, across multiple mechanistic levels. Data Sources: Systematic searches were conducted in the MEDLINE, Embase, Web of Science, and PubMed databases from inception to August 11, 2022. Study Selection: Original research that reported performance-based measures of face recognition to upright and inverted faces in ASD and neurotypical samples were included for quantitative synthesis. All studies were screened by at least 2 reviewers. Data Extraction and Synthesis: This systematic review and meta-analysis was conducted according to the 2020 Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. Multiple effect sizes were extracted from studies to maximize information gain and statistical precision and used a random-effects, multilevel modeling framework to account for statistical dependencies within study samples. Main Outcomes and Measures: Effect sizes were calculated as a standardized mean change score between ASD and neurotypical samples (ie, Hedges g). The primary outcome measure was performance difference between upright and inverted faces during face recognition tasks. Measurement modality, psychological construct, recognition demand, sample age, sample sex distribution, and study quality assessment scores were assessed as moderators. Results: Of 1768 screened articles, 122 effect sizes from 38 empirical articles representing data from 1764 individual participants (899 ASD individuals and 865 neurotypical individuals) were included in the meta-analysis. Overall, face recognition performance differences between upright and inverted faces were reduced in autistic individuals compared with neurotypical individuals (g = -0.41; SE = 0.11; 95% credible interval [CrI], -0.63 to -0.18). However, there was considerable heterogeneity among effect sizes, which were explored with moderator analysis. The attenuated face inversion effect in autistic individuals was more prominent in emotion compared with identity recognition (b = 0.46; SE = 0.26; 95% CrI, -0.08 to 0.95) and in behavioral compared with electrophysiological measures (b = 0.23; SE = 0.24; 95% CrI, -0.25 to 0.70). Conclusions and Relevance: This study found that on average, face recognition in autism is less impacted by inversion. These findings suggest less specialization or expertise of the face processing system in autism, particularly in recognizing emotion from faces as measured in behavioral paradigms.