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.

Development of webcam-collected and artificial-intelligence-derived social and cognitive performance measures for neurodevelopmental genetic syndromes.

This study focused on the development and initial psychometric evaluation of a set of online, webcam-collected, and artificial intelligence-derived patient performance measures for neurodevelopmental genetic syndromes (NDGS). Initial testing and qualitative input was used to develop four stimulus paradigms capturing social and cognitive processes, including social attention, receptive vocabulary, processing speed, and single-word reading. The paradigms were administered to a sample of 375 participants, including 163 with NDGS, 56 with idiopathic neurodevelopmental disability (NDD), and 156 neurotypical controls. Twelve measures were created from the four stimulus paradigms. Valid completion rates varied from 87 to 100% across measures, with lower but adequate completion rates in participants with intellectual disability. Adequate to excellent internal consistency reliability (α = 0.67 to 0.95) was observed across measures. Test-retest reproducibility at 1-month follow-up and stability at 4-month follow-up was fair to good (r = 0.40-0.73) for 8 of the 12 measures. All gaze-based measures showed evidence of convergent and discriminant validity with parent-report measures of other cognitive and behavioral constructs. Comparisons across NDGS groups revealed distinct patterns of social and cognitive functioning, including people with PTEN mutations showing a less impaired overall pattern and people with SYNGAP1 mutations showing more attentional, processing speed, and social processing difficulties relative to people with NFIX mutations. Webcam-collected performance measures appear to be a reliable and potentially useful method for objective characterization and monitoring of social and cognitive processes in NDGS and idiopathic NDD. Additional validation work, including more detailed convergent and discriminant validity analyses and examination of sensitivity to change, is needed to replicate and extend these observations.

Eye tracking: empirical foundations for a minimal reporting guideline.

In this paper, we present a review of how the various aspects of any study using an eye tracker (such as the instrument, methodology, environment, participant, etc.) affect the quality of the recorded eye-tracking data and the obtained eye-movement and gaze measures. We take this review to represent the empirical foundation for reporting guidelines of any study involving an eye tracker. We compare this empirical foundation to five existing reporting guidelines and to a database of 207 published eye-tracking studies. We find that reporting guidelines vary substantially and do not match with actual reporting practices. We end by deriving a minimal, flexible reporting guideline based on empirical research (Section "An empirically based minimal reporting guideline").

Multilevel hybrid principal components analysis for region-referenced functional electroencephalography data.

Electroencephalography experiments produce region-referenced functional data representing brain signals in the time or the frequency domain collected across the scalp. The data typically also have a multilevel structure with high-dimensional observations collected across multiple experimental conditions or visits. Common analysis approaches reduce the data complexity by collapsing the functional and regional dimensions, where event-related potential (ERP) features or band power are targeted in a pre-specified scalp region. This practice can fail to portray more comprehensive differences in the entire ERP signal or the power spectral density (PSD) across the scalp. Building on the weak separability of the high-dimensional covariance process, the proposed multilevel hybrid principal components analysis (M-HPCA) utilizes dimension reduction tools from both vector and functional principal components analysis to decompose the total variation into between- and within-subject variance. The resulting model components are estimated in a mixed effects modeling framework via a computationally efficient minorization-maximization algorithm coupled with bootstrap. The diverse array of applications of M-HPCA is showcased with two studies of individuals with autism. While ERP responses to match vs mismatch conditions are compared in an audio odd-ball paradigm in the first study, short-term reliability of the PSD across visits is compared in the second. Finite sample properties of the proposed methodology are studied in extensive simulations.

The role of limited salience of speech in selective attention to faces in toddlers with autism spectrum disorders.

BACKGROUND: Impaired attention to faces of interactive partners is a marker for autism spectrum disorder (ASD) in early childhood. However, it is unclear whether children with ASD avoid faces or find them less salient and whether the phenomenon is linked with the presence of eye contact or speech. METHODS: We investigated the impacts of speech (SP) and direct gaze (DG) on attention to faces in 22-month-old toddlers with ASD (n = 50) and typically developing controls (TD, n = 47) using the Selective Social Attention 2.0 (SSA 2.0) task. The task consisted of four conditions where the presence (+) and absence (-) of DG and SP were systematically manipulated. The severity of autism symptoms, and verbal and nonverbal skills were characterized concurrently with eye tracking at 22.4 (SD = 3.2) months and prospectively at 39.8 (SD = 4.3) months. RESULTS: Toddlers with ASD looked less than TD toddlers at face and mouth regions only when the actress was speaking (direct gaze absence with speech, DG-SP+: d = 0.99, p < .001 for face, d = 0.98, p < .001 for mouth regions; direct gaze present with speech, DG+SP+, d = 1.47, p < .001 for face, d = 1.01, p < .001 for mouth regions). Toddlers with ASD looked less at the eye region only when both gaze and speech cues were present (d = 0.46, p = .03). Salience of the combined DG and SP cues was associated concurrently and prospectively with the severity of autism symptoms, and the association remained significant after controlling for verbal and nonverbal levels. CONCLUSIONS: The study links poor attention to faces with limited salience of audiovisual speech and provides no support for the face avoidance hypothesis in the early stages of ASD. These results are consequential for research on early discriminant and predictive biomarkers as well as identification of novel treatment targets.

Multilevel Differences in Spontaneous Social Attention in Toddlers With Autism Spectrum Disorder.

This study examined the latent structure of spontaneous social attention in 11- to 26-month-olds with autism spectrum disorder (ASD, n = 90) and typically developing (n = 79) controls. Application of the joint and individual variance explained decomposition technique revealed that attention was driven by a condition-independent tuning into the dynamic social scenes construct and context-specific constructs capturing selection of the most relevant social features for processing. Gaze behavior in ASD is characterized by a limited tuning into the social scenes and by a selection of atypical targets for processing. While the former may be due to early disruption of the reward circuitry leading to limited appreciation of the behavioral relevance of social information, the latter may represent secondary deficits reflecting limited knowledge about social partners.

Mixture of autoregressive modeling orders and its implication on single trial EEG classification.

Autoregressive (AR) models are of commonly utilized feature types in Electroencephalogram (EEG) studies due to offering better resolution, smoother spectra and being applicable to short segments of data. Identifying correct AR's modeling order is an open challenge. Lower model orders poorly represent the signal while higher orders increase noise. Conventional methods for estimating modeling order includes Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and Final Prediction Error (FPE). This article assesses the hypothesis that appropriate mixture of multiple AR orders is likely to better represent the true signal compared to any single order. Better spectral representation of underlying EEG patterns can increase utility of AR features in Brain Computer Interface (BCI) systems by increasing timely & correctly responsiveness of such systems to operator's thoughts. Two mechanisms of Evolutionary-based fusion and Ensemble-based mixture are utilized for identifying such appropriate mixture of modeling orders. The classification performance of the resultant AR-mixtures are assessed against several conventional methods utilized by the community including 1) A well-known set of commonly used orders suggested by the literature, 2) conventional order estimation approaches (e.g., AIC, BIC and FPE), 3) blind mixture of AR features originated from a range of well-known orders. Five datasets from BCI competition III that contain 2, 3 and 4 motor imagery tasks are considered for the assessment. The results indicate superiority of Ensemble-based modeling order mixture and evolutionary-based order fusion methods within all datasets.

Infant Social Attention Associated with Elevated Likelihood for Autism Spectrum Disorder: A Multi-Method Comparison.

PURPOSE: The study aimed to compare eye tracking (ET) and manual coding (MC) measures of attention to social and nonsocial information in infants with elevated familial likelihood (EL) of autism spectrum disorder (ASD) and low likelihood of ASD (LL). ET provides a temporally and spatially sensitive tool for measuring gaze allocation. Existing evidence suggests that ET is a promising tool for detecting distinct social attention patterns that may serve as a biomarker for ASD. However, ET is prone to data loss, especially in young EL infants. METHODS: To increase evidence for ET as a viable tool for capturing atypical social attention in EL infants, the current prospective, longitudinal study obtained ET and MC measures of social and nonsocial attention in 25 EL and 47 LL infants at several time points between 3 and 24 months of age. RESULTS: ET data was obtained with a satisfactory success rate of 95.83%, albeit with a higher degree of data loss compared to MC. Infant age and ASD likelihood status did not impact the extent of ET or MC data loss. There was a significant positive association between the ET and MC measures of attention, and separate analyses of attention using ET and AC measures yielded comparable findings. These analyses indicated group differences (EL vs. LL) in age-related change in attention to social vs. nonsocial information. CONCLUSION: Together, the findings support infant ET as a promising approach for identifying very early markers associated with ASD likelihood.

Similar Gap-Overlap Profiles in Children with Fragile X Syndrome and IQ-Matched Autism.

PURPOSE: Fragile X syndrome (FXS) is a single-gene disorder characterized by moderate to severe cognitive impairment and a high association with autism spectrum disorder (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD). Atypical visual attention is a feature of FXS, ASD, and ADHD. Thus, studying early attentional patterns in young children with FXS can offer insight into early emerging neurocognitive processes underlying challenges and contribute to our understanding of common and unique features of ASD and ADHD in FXS. METHODS: The present study examined visual attention indexed by the gap-overlap paradigm in children with FXS (n = 39) compared to children with ASD matched on intellectual ability and age (n = 40) and age-matched neurotypical controls (n = 34). The relationship between gap-overlap performance and intellectual ability, ASD, and ADHD across groups was characterized. Saccadic reaction times (RT) were collected across baseline, gap, and overlap conditions. RESULTS: Results indicate no group differences in RT for any conditions. However, RT of the ASD and NT groups became slower throughout the experiment whereas RT of the FXS group did not change, suggesting difficulties in habituation for the FXS group. There was no relationship between RT and intellectual ability, ADHD, or ASD symptoms in the FXS and ASD groups. In the NT group, slower RT was related to elevated ADHD symptoms only. CONCLUSION: Taken together, findings suggest that the social attention differences documented in FXS and ASD may be due to other cognitive factors, such as reward or motivation, rather than oculomotor control of visual attention.

Book-Sharing for Toddlers with Clefts (BOOST): Protocol for a randomized controlled trial of a remote intervention to promote language development in children with cleft palate.

BACKGROUND: Children with cleft palate, with or without cleft lip (CP±L), exhibit language delays on average compared to children without clefts. Interventions to address these disparities are scarce. In this multi-center study, Book Sharing for Toddlers with Clefts (BOOST), we will test a remote, parent-focused intervention to promote language development in children with CP±L. OBJECTIVES: The study will test two primary hypotheses. First, toddlers randomized to BOOST will exhibit better language outcomes than children receiving standard-of-care (SOC). Second, we hypothesize that the BOOST program's effect on language outcomes is mediated by the frequency and quality of parent-child reading interactions. METHODS: The study is a randomized-controlled trial comparing the BOOST group to a SOC comparison group. We will enroll N = 320 English and/or Spanish-speaking children ages 24-32 months with isolated CP±L (n = 160 per group). Both groups will receive children's books, and parents will record and upload videos of themselves reading the books with their children using a smartphone app developed for the study. Parents will also complete surveys asking whether they read to their children on five randomly selected days each week. In addition, the BOOST group will participate in 3 remote dialogic book-sharing intervention sessions via Zoom. We will code book-sharing videos to assess parents' target skill usage and children's expressive language. End-of-study assessments will include measures of child language outcomes (e.g., clinician-administered measures, parent reports, and naturalistic child language samples). RESULTS: Enrollment began in April 2024 and will continue through approximately April 2028. CONCLUSION: The BOOST study will address a critical gap in the literature on interventions to improve language in children with CP±L. The results will inform the care for toddlers with oral clefts and have potential applications for other populations.

Distinct social attention profiles in preschoolers with autism contrasted to fragile X syndrome.

Social attention is a critical skill for learning and development. Social attention difficulties are present in both non-syndromic autism spectrum disorder (nsASD) and fragile X syndrome (FXS), and our understanding of these difficulties is complicated by heterogeneity in both disorders, including co-occurring diagnoses like intellectual disability and social anxiety. Existing research largely utilizes a single index of social attention and rarely includes children with intellectual impairment or uses a cross-syndrome approach. This study investigated whether multi-trait social attention profiles including naturalistic initial eye contact, facial attention, and social scene attention differ in preschool children with nsASD and FXS matched on developmental ability (DQ) and contrasted to neurotypical (NT) controls. The relationship between DQ, ASD severity, and social anxiety and social attention profiles was also examined. Initial eye contact related to social scene attention, implicating that naturalistic social attention is consistent with responses during experimental conditions. Reduced eye contact and lower social scene attention characterized nsASD and FXS. Children with nsASD displayed less facial attention than FXS and NT children, who did not differ. Lower DQ and elevated ASD severity associated with decreased eye contact in nsASD and FXS, and lower DQ was associated with lower social scene attention in FXS. Sex, social anxiety, and age were not associated with social attention. These findings suggest social attention profiles of children with nsASD are highly similar to, yet distinct from, children with FXS. Children with nsASD may present with a global social attention deficit whereas FXS profiles may reflect context-dependent social avoidance.

Sex Differences on the ADOS-2.

The sex difference in the prevalence of autism spectrum disorder (ASD) may be magnified by sex differences on diagnostic measures. The current study compared autistic males and females on items on the gold-standard diagnostic measure, the Autism Diagnostic Observation Schedule, Second Edition (ADOS-2). In a sample of 8-to-17-year old autistic individuals from research (n = 229) and clinical settings (n = 238), females were less likely to show atypicalities on most items related to social-communication behaviors and on total and subscale scores. When controlling for overall intensity of symptomatology, no sex differences survived statistical corrections. Diagnostic criteria and/or gold-standard assessments may be less sensitive to female presentations of ASD and/or autistic females may exhibit fewer or less intense behaviors characteristic of ASD.

Remote, tablet-based assessment of gaze following: a nationwide infant twin study.

Introduction: Much of our understanding of infant psychological development relies on an in-person, laboratory-based assessment. This limits research generalizability, scalability, and equity in access. One solution is the development of new, remotely deployed assessment tools that do not require real-time experimenter supervision. Methods: The current nationwide (Sweden) infant twin study assessed participants remotely via their caregiver's tablets (N = 104, ages 3 to 17 months). To anchor our findings in previous research, we used a gaze-following task where experimental and age effects are well established. Results: Closely mimicking results from conventional eye tracking, we found that a full head movement elicited more gaze following than isolated eye movements. Furthermore, predictably, we found that older infants followed gaze more frequently than younger infants. Finally, while we found no indication of genetic contributions to gaze-following accuracy, the latency to disengage from the gaze cue and orient toward a target was significantly more similar in monozygotic twins than in dizygotic twins, an indicative of heritability. Discussion: Together, these results highlight the potential of remote assessment of infants' psychological development, which can improve generalizability, inclusion, and scalability in developmental research.

A functional model for studying common trends across trial time in eye tracking experiments.

Eye tracking (ET) experiments commonly record the continuous trajectory of a subject's gaze on a two-dimensional screen throughout repeated presentations of stimuli (referred to as trials). Even though the continuous path of gaze is recorded during each trial, commonly derived outcomes for analysis collapse the data into simple summaries, such as looking times in regions of interest, latency to looking at stimuli, number of stimuli viewed, number of fixations or fixation length. In order to retain information in trial time, we utilize functional data analysis (FDA) for the first time in literature in the analysis of ET data. More specifically, novel functional outcomes for ET data, referred to as viewing profiles, are introduced that capture the common gazing trends across trial time which are lost in traditional data summaries. Mean and variation of the proposed functional outcomes across subjects are then modeled using functional principal components analysis. Applications to data from a visual exploration paradigm conducted by the Autism Biomarkers Consortium for Clinical Trials showcase the novel insights gained from the proposed FDA approach, including significant group differences between children diagnosed with autism and their typically developing peers in their consistency of looking at faces early on in trial time.

Attention Allocation During Exploration of Visual Arrays in ASD: Results from the ABC-CT Feasibility Study.

Visual exploration paradigms involving object arrays have been used to examine salience of social stimuli such as faces in ASD. Recent work suggests performance on these paradigms may associate with clinical features of ASD. We evaluate metrics from a visual exploration paradigm in 4-to-11-year-old children with ASD (n = 23; 18 males) and typical development (TD; n = 23; 13 males). Presented with arrays containing faces and nonsocial stimuli, children with ASD looked less at (p = 0.002) and showed fewer fixations to (p = 0.022) faces than TD children, and spent less time looking at each object on average (p = 0.004). Attention to the screen and faces correlated positively with social and cognitive skills in the ASD group (ps < .05). This work furthers our understanding of objective measures of visual exploration in ASD and its potential for quantifying features of ASD.

Concomitant medication use in children with autism spectrum disorder: Data from the Autism Biomarkers Consortium for Clinical Trials.

LAY ABSTRACT: Children with autism spectrum disorder are prescribed a variety of medications that affect the central nervous system (psychotropic medications) to address behavior and mood. In clinical trials, individuals taking concomitant psychotropic medications often are excluded to maintain homogeneity of the sample and prevent contamination of biomarkers or clinical endpoints. However, this choice may significantly diminish the clinical representativeness of the sample. In a recent multisite study designed to identify biomarkers and behavioral endpoints for clinical trials (the Autism Biomarkers Consortium for Clinical Trials), school-age children with autism spectrum disorder were enrolled without excluding for medications, thus providing a unique opportunity to examine characteristics of psychotropic medication use in a research cohort and to guide future decisions on medication-related inclusion criteria. The aims of the current analysis were (1) to quantify the frequency and type of psychotropic medications reported in school-age children enrolled in the ABC-CT and (2) to examine behavioral features of children with autism spectrum disorder based on medication classes. Of the 280 children with autism spectrum disorder in the cohort, 42.5% were taking psychotropic medications, with polypharmacy in half of these children. The most commonly reported psychotropic medications included melatonin, stimulants, selective serotonin reuptake inhibitors, alpha agonists, and antipsychotics. Descriptive analysis showed that children taking antipsychotics displayed a trend toward greater overall impairment. Our findings suggest that exclusion of children taking concomitant psychotropic medications in trials could limit the clinical representativeness of the study population, perhaps even excluding children who may most benefit from new treatment options.

The Autism Biomarkers Consortium for Clinical Trials: Initial Evaluation of a Battery of Candidate EEG Biomarkers.

OBJECTIVE: Numerous candidate EEG biomarkers have been put forward for use in clinical research on autism spectrum disorder (ASD), but biomarker development has been hindered by limited attention to the psychometric properties of derived variables, inconsistent results across small studies, and variable methodology. The authors evaluated the basic psychometric properties of a battery of EEG assays for their potential suitability as biomarkers in clinical trials. METHODS: This was a large, multisite, naturalistic study in 6- to 11-year-old children who either had an ASD diagnosis (N=280) or were typically developing (N=119). The authors evaluated an EEG battery composed of well-studied assays of resting-state activity, face perception (faces task), biological motion perception, and visual evoked potentials (VEPs). Biomarker psychometrics were evaluated in terms of acquisition rates, construct performance, and 6-week stability. Preliminary evaluation of use was explored through group discrimination and phenotypic correlations. RESULTS: Three assays (resting state, faces task, and VEP) show promise in terms of acquisition rates and construct performance. Six-week stability values in the ASD group were moderate (intraclass correlations ≥0.66) for the faces task latency of the P1 and N170, the VEP amplitude of N1 and P1, and resting alpha power. Group discrimination and phenotype correlations were primarily observed for the faces task P1 and N170. CONCLUSIONS: In the context of a large-scale, rigorous evaluation of candidate EEG biomarkers for use in ASD clinical trials, neural response to faces emerged as a promising biomarker for continued evaluation. Resting-state activity and VEP yielded mixed results. The study's biological motion perception assay failed to display construct performance. The results provide information about EEG biomarker performance that is relevant for the next stage of biomarker development efforts focused on context of use.

Evaluation of clinical assessments of social abilities for use in autism clinical trials by the autism biomarkers consortium for clinical trials.

Clinical trials in autism spectrum disorder (ASD) often rely on clinician rating scales and parent surveys to measure autism-related features and social behaviors. To aid in the selection of these assessments for future clinical trials, the Autism Biomarkers Consortium for Clinical Trials (ABC-CT) directly compared eight common instruments with respect to acquisition rates, sensitivity to group differences, equivalence across demographic sub-groups, convergent validity, and stability over a 6-week period. The sample included 280 children diagnosed with ASD (65 girls) and 119 neurotypical children (36 girls) aged from 6 to 11 years. Full scale IQ for ASD ranged from 60 to 150 and for neurotypical ranged from 86 to 150. Instruments measured clinician global assessment and autism-related behaviors, social communication abilities, adaptive function, and social withdrawal behavior. For each instrument, we examined only the scales that measured social or communication functioning. Data acquisition rates were at least 97.5% at T1 and 95.7% at T2. All scales distinguished diagnostic groups. Some scales significantly differed by participant and/or family demographic characteristics. Within the ASD group, most clinical instruments exhibited weak (≥ |0.1|) to moderate (≥ |0.4|) intercorrelations. Short-term stability was moderate (ICC: 0.5-0.75) to excellent (ICC: >0.9) within the ASD group. Variations in the degree of stability may inform viability for different contexts of use, such as identifying clinical subgroups for trials versus serving as a modifiable clinical outcome. All instruments were evaluated in terms of their advantages and potential concerns for use in clinical trials.

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.