Adam Naples

Autistic individuals with intellectual disability (ASD+ID) and profound autism are rarely studied in neuroscience research due to barriers including communication challenges, sensory sensitivities, anxiety, and elevated behavioral support needs. Consequently, biomarker development in autism fails to include the portion of the autistic population with highest support needs and greatest potential to benefit from treatments derived from imminent advances in personalized medicine. Here we present a multimodal, participant-centered protocol for simultaneous electroencephalography (EEG) and eye-tracking (ET) acquisition to advance clinical trial readiness research in this underserved population. The protocol combines individualized behavioral supports and an adaptive EEG-ET acquisition platform. Pre-visit caregiver interviews informed participant-specific research plans, including customized visual supports, reinforcement strategies, and EEG net desensitization procedures. A gaze-contingent stimulus presentation system used participant-preferred videos to support attention to experimental stimuli and behavior consistent with data acquisition (e.g., refraining from movement) while dynamically adapting stimulus delivery based on visual engagement with the assay and real-time assessment of data quality. By quantifying attended trials in real time and prioritizing unattended stimulus classes, the paradigm maximizes acquisition efficiency to minimize participant burden. This approach was utilized to deploy candidate biomarkers with demonstrated replicability in the Autism Biomarkers Consortium for Clinical Trials (ABC-CT): the N170 event-related potential to faces, resting-state EEG, and visual attention to human faces (measured with ET). Feasibility was evaluated in 76 children with ASD+ID (M age = 8.76 years; IQ = 32.4) and a small comparison sample of 8 children with intellectual disability without autism (M age = 8.91 years; IQ = 45.9). Usable EEG data (>7 minutes) were acquired in 61% (ASD+ID) and 88% (ID) of participants, respectively. Sufficient ET data were obtained from 67% (ASD+ID) and 63% (ID) of participants, respectively. Findings demonstrate the feasibility of inclusive biomarker acquisition and provide a framework for expanding participation of individuals with ASD+ID and profound autism in neuroscience research. Ongoing research seeks to evaluate this approach in larger samples and to demonstrate feasibility in multisite research studies.

Autism is a common neurodevelopmental condition with considerable between-person variability and unknown biological etiology. Diagnosis of autism in adults relies on measurement of performance (e.g., clinician rating of social behavior, standardized assessment of cognition) and self-report of autism features. Our prior work revealed a strong relationship between clinician ratings of social function in autism and in vivo measures of synaptic density as measured by [ ¹¹ C]UCB-J PET (Matuskey et al., 2025). However, it is not understood how the measured aspects of the autism phenotype index underlying biology. Here, in a sample of 12 autistic adults, we address this question by relating synaptic density imaging to a range of performance measures, such as cognition and face recognition, in contrast to self-report measures. Our results identify a dissociation between these measurement types in that synaptic density correlates strongly with measures of performance but shows virtually no relationship with self-report. These findings suggest that, while self-report and performance measures share variance in characterizing phenotypes in autism, they diverge when mapping onto the underlying biology. Results suggest that higher synaptic density may index a general mechanism that facilitates social and cognitive performance across a range of tasks. These data also indicate that performance and self-report measures are not interchangeable in capturing brain-behavior correspondences in autism, a finding that can guide measure selection in future biomarker studies and clinical research.

Reduced social attention (SA) is a hallmark feature of autism that is foundational to social communication and interaction. However, emerging evidence suggests that reduced SA may not be uniformly expressed across the autism spectrum. Sex and cognitive ability (IQ) have been identified as relevant stratification variables, potentially moderating SA in autistic children. We examined differential patterns of SA stratified by sex and cognitive ability in a large, longitudinal sample of autistic and neurotypical (NT) children (ages 6–11 years) from the Autism Biomarkers Consortium for Clinical Trials (ABC‐CT), examining SA across four measurement timepoints (Baseline, 6 weeks, 6 months, and 4 years). SA was measured using the oculomotor index of gaze to human faces (OMI) derived from standardized eye‐tracking (ET) assays, with children stratified by sex (male, female) and IQ (IQ ≥ 85, IQ < 85). Linear mixed‐effects models were used to evaluate the effects of sex, IQ, and timepoint on SA, with additional analyses assessing the stability and clinical associations of OMI. Autistic females did not exhibit lower OMI scores compared to autistic males; however, relative to sex‐matched NT children, autistic females showed approximately twice the reduction in OMI observed in autistic males. Likewise, the reduction in OMI associated with autism (i.e., ASD < NT) was larger in autistic children with below‐average IQ than in those with average or above‐average IQ. These differences were relatively stable across measurement timepoints, and OMI was more strongly associated with clinical features like face memory and adaptive behavior in autistic males and the average or above‐average IQ autism subgroup. While reduced SA is a general feature of autism, its expression is stratified by sex and cognitive ability. These findings highlight the importance of subgroup stratification to better understand heterogeneity in autism and improve the utility of SA as a therapeutic biomarker.

Background: Social anhedonia, indicating reduced pleasure from social interaction, is heightened in autistic youth and associated with increased internalizing symptoms transdiagnostically. The stability of social anhedonia over time and its longitudinal impact on internalizing symptoms in autism have never been examined. Methods: Participants were 276 autistic children (M_age = 8.60, SD_age = 1.65; 211 male) with IQ ≥ 60 (M_IQ = 96.74, SD_IQ = 18.19). Autism severity was measured using the Autism Diagnostic Observation Schedule, Second Edition. Caregivers completed the Child and Adolescent Symptom Inventory, Fifth Edition (CASI-5) at baseline, 6 weeks, and 6 months. The CASI-5 includes a social anhedonia subscale derived from relevant items across domains. ICC (Intraclass Correlation Coefficient) analysis assessed stability, while cross-lagged panel models examined associations among social anhedonia, depression, and social anxiety across time. Results: At baseline, social anhedonia correlated with autism severity, as well as parent-reported social anxiety and depression. Social anhedonia showed relative stability (ICC = 0.763) over 6 months, with a significant decline between baseline and 6 weeks (β = −0.52, p < .001). Cross-lagged models revealed a bidirectional relationship between social anhedonia and depression over time, while social anxiety displayed concurrent, but not predictive, associations across time. Conclusions: Social anhedonia demonstrated stability over 6 months, suggesting that it may be a relatively stable characteristic in autistic children. Concurrent relationships were observed between social anhedonia and depression, as well as social anxiety and attention-deficit/hyperactivity disorder. Only depression demonstrated a bidirectional longitudinal association with social anhedonia. This bidirectional relationship aligns with developmental models linking early negative social experiences to subsequent internalizing symptoms in autistic children, underscoring the clinical significance of social anhedonia assessment in this population.

It has not previously been possible to investigate the fundamental relationship between axonal structure – which dictates action potential transmission – and human neuronal function in vivo . Here, we introduce a novel metric of axonal signal speed, estimated axonal latency (EAL), derived from the relationship between axonal diameter, myelination, and length measured via MRI. We validate EAL along two pathways of the face processing network by relating it to N170 latency, an electrophysiological marker of face processing speed measured via EEG. Our results show that EAL along these pathways predicts N170 latency specifically during face processing. Moreover, we demonstrate that individuals with and without autism rely upon different pathways, potentially providing a structural account for autism-related face processing differences. By establishing this relationship between EEG-based electrical function and MRI-based axonal microstructure, we provide a non-invasive, spatially detailed estimate of neuronal processing speed that can inform our understanding of brain function, development, and disorder. Teaser: Estimated axonal latency is a non-invasive, spatially detailed measure of neuronal speed to inform brain function and disorder.

Autism and social anxiety (SA) share behavioral features like reduced eye contact, variable social attention, and differences in social interactions. However, the impact of the co-occurrence of these conditions (e.g., autism with co-occurring SA) on social attention remains unknown. Therefore, we evaluated whether the degree of SA characteristics in autistic youth modulated (e.g., amplified or lessened) a core hallmark feature of autism: social attention, or looking at faces. Fifty-four autistic and 35 non-autistic children and adolescents completed a gaze-contingent eye-tracking (ET) paradigm, in which faces dynamically expressed happy or fearful expressions contingent on participant eye contact. SA characteristics were assessed via standardized self- and parent-report measures. Social attention was measured by calculating the average percent looking time at the face and eye regions of each emotional expression. Autistic participants looked less at faces than non-autistic participants, and higher self-report SA was associated with less looking at eyes in both autistic and non-autistic participants. SA features affect social attention similarly in autistic and non-autistic youth, highlighting the importance of considering co-occurring psychiatric characteristics when assessing social attention and eye contact in autistic individuals.

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.

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.