Relative Average Look Duration and its Association with Neurophysiological Activity in Young Children with Autism Spectrum Disorder

Increased observation of predictable visual stimuli in children with potential autism spectrum disorder

Children with autism spectrum disorder (ASD) often exhibit social communication impairments and restricted, repetitive behaviors (RRB). Previous studies have shown that children with ASD prefer observing repetitive movements over random movements, reflecting RRB symptoms, but the developmental timeline of this preference remains unclear. New evidence suggests that children with ASD may develop predictive processing abilities for repeated behaviors, providing insight into how they recognize and respond to predictable patterns. This study employed a preferential-looking paradigm to examine whether children with potential ASD demonstrated longer observation durations for predictable movements compared to typically developing (TD) children. Participants were presented with pairs of stimuli featuring predictable and unpredictable movements, which they freely observed side-by-side. Results showed that children with potential ASD spent significantly more time observing predictable movements, particularly during the latter part of the stimulus presentation. These findings suggest that a gradual increase in attention to predictable movements may reflect difficulties in learning cause-and-effect relationships between movement trajectories and the anticipation of complete shapes. This study highlights the potential utility of predictable movement stimuli as a behavioral marker for early ASD screening. It underscores the essential need for further research into predictive processing in children with ASD.

Model selection to achieve reproducible associations between resting state EEG features and autism

A concern in the field of autism electroencephalography (EEG) biomarker discovery is their lack of reproducibility. In the present study, we considered the problem of learning reproducible associations between multiple features of resting state (RS) neural activity and autism, using EEG data collected during a RS paradigm from 36 to 96 month-old children diagnosed with autism (N = 224) and neurotypical children (N = 69). Specifically, EEG spectral power and functional connectivity features were used as inputs to a regularized generalized linear model trained to predict diagnostic group (autism versus neurotypical). To evaluate our model, we proposed a procedure that quantified both the predictive generalization and reproducibility of learned associations produced by the model. When prioritizing both model predictive performance and reproducibility of associations, a highly reproducible profile of associations emerged. This profile revealed a distinct pattern of increased gamma power and connectivity in occipital and posterior midline regions associated with an autism diagnosis. Conversely, model selection based on predictive performance alone resulted in non-robust associations. Finally, we built a custom machine learning model that further empirically improved robustness of learned associations. Our results highlight the need for model selection criteria that maximize the scientific utility provided by reproducibility instead of predictive performance.

EEG decoding for effects of visual joint attention training on ASD patients with interpretable and lightweight convolutional neural network

Visual joint attention, the ability to track gaze and recognize intent, plays a key role in the development of social and language skills in health humans, which is performed abnormally hard in autism spectrum disorder (ASD). The traditional convolutional neural network, EEGnet, is an effective model for decoding technology, but few studies have utilized this model to address attentional training in ASD patients. In this study, EEGNet was used to decode the P300 signal elicited by training and the saliency map method was used to visualize the cognitive properties of ASD patients during visual attention. The results showed that in the spatial distribution, the parietal lobe was the main region of classification contribution, especially for Pz electrode. In the temporal information, the time period from 300 to 500 ms produced the greatest contribution to the electroencephalogram (EEG) classification, especially around 300 ms. After training for ASD patients, the gradient contribution was significantly enhanced at 300 ms, which was effective only in social scenarios. Meanwhile, with the increase of joint attention training, the P300 latency of ASD patients gradually shifted forward in social scenarios, but this phenomenon was not obvious in non-social scenarios. Our results indicated that joint attention training could improve the cognitive ability and responsiveness of social characteristics in ASD patients.

Prefrontal Cortex Responses to Social Video Stimuli in Young Children with and without Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder affecting individuals worldwide and characterized by deficits in social interaction along with the presence of restricted interest and repetitive behaviors. Despite decades of behavioral research, little is known about the brain mechanisms that influence social behaviors among children with ASD. This, in part, is due to limitations of traditional imaging techniques specifically targeting pediatric populations. As a portable and scalable optical brain monitoring technology, functional near infrared spectroscopy (fNIRS) provides a measure of cerebral hemodynamics related to sensory, motor, or cognitive function. Here, we utilized fNIRS to investigate the prefrontal cortex (PFC) activity of young children with ASD and with typical development while they watched social and nonsocial video clips. The PFC activity of ASD children was significantly higher for social stimuli at medial PFC, which is implicated in social cognition/processing. Moreover, this activity was also consistently correlated with clinical measures, and higher activation of the same brain area only during social video viewing was associated with more ASD symptoms. This is the first study to implement a neuroergonomics approach to investigate cognitive load in response to realistic, complex, and dynamic audiovisual social stimuli for young children with and without autism. Our results further confirm that new generation of portable fNIRS neuroimaging can be used for ecologically valid measurements of the brain function of toddlers and preschool children with ASD.

Digitally Diagnosing Multiple Developmental Delays Using Crowdsourcing Fused With Machine Learning: Protocol for a Human-in-the-Loop Machine Learning Study

BACKGROUND

A considerable number of minors in the United States are diagnosed with developmental or psychiatric conditions, potentially influenced by underdiagnosis factors such as cost, distance, and clinician availability. Despite the potential of digital phenotyping tools with machine learning (ML) approaches to expedite diagnoses and enhance diagnostic services for pediatric psychiatric conditions, existing methods face limitations because they use a limited set of social features for prediction tasks and focus on a single binary prediction, resulting in uncertain accuracies.

OBJECTIVE

This study aims to propose the development of a gamified web system for data collection, followed by a fusion of novel crowdsourcing algorithms with ML behavioral feature extraction approaches to simultaneously predict diagnoses of autism spectrum disorder and attention-deficit/hyperactivity disorder in a precise and specific manner.

METHODS

The proposed pipeline will consist of (1) gamified web applications to curate videos of social interactions adaptively based on the needs of the diagnostic system, (2) behavioral feature extraction techniques consisting of automated ML methods and novel crowdsourcing algorithms, and (3) the development of ML models that classify several conditions simultaneously and that adaptively request additional information based on uncertainties about the data.

RESULTS

A preliminary version of the web interface has been implemented, and a prior feature selection method has highlighted a core set of behavioral features that can be targeted through the proposed gamified approach.

CONCLUSIONS

The prospect for high reward stems from the possibility of creating the first artificial intelligence-powered tool that can identify complex social behaviors well enough to distinguish conditions with nuanced differentiators such as autism spectrum disorder and attention-deficit/hyperactivity disorder.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/52205.

Altered theta-beta ratio in infancy associates with family history of ADHD and later ADHD-relevant temperamental traits

BACKGROUND

Uncovering the neural mechanisms that underlie symptoms of attention deficit hyperactivity disorder (ADHD) requires studying brain development prior to the emergence of behavioural difficulties. One new approach to this is prospective studies of infants with an elevated likelihood of developing ADHD.

METHODS

We used a prospective design to examine an oscillatory electroencephalography profile that has been widely studied in both children and adults with ADHD - the balance between lower and higher frequencies operationalised as the theta-beta ratio (TBR). In the present study, we examined TBR in 136 10-month-old infants (72 male and 64 female) with/without an elevated likelihood of developing ADHD and/or a comparison disorder (Autism Spectrum Disorder; ASD).

RESULTS

Infants with a first-degree relative with ADHD demonstrated lower TBR than infants without a first-degree relative with ADHD. Further, lower TBR at 10 months was positively associated with temperament dimensions conceptually related to ADHD at 2 years. TBR was not altered in infants with a family history of ASD.

CONCLUSIONS

This is the first demonstration that alterations in TBR are present prior to behavioural symptoms of ADHD. However, these alterations manifest differently than those sometimes observed in older children with an ADHD diagnosis. Importantly, altered TBR was not seen in infants at elevated likelihood of developing ASD, suggesting a degree of specificity to ADHD. Taken together, these findings demonstrate that there are brain changes associated with a family history of ADHD observable in the first year of life.

Shorter average look durations to dynamic social stimuli are associated with higher levels of autism symptoms in young autistic children

LAY ABSTRACT

Many studies of autism look at the differences in how autistic research participants look at certain types of images. These studies often focus on where research participants are looking within the image, but that does not tell us everything about how much they are paying attention. It could be useful to know more about how well autistic research participants can focus on an image with people in it, because those who can look at images of people for longer duration without stopping may be able to easily learn other skills that help them to interact with people. We measured how long autistic research participants watched the video without breaking their attention. The video sometimes had a person speaking, and at other times had toys moving and making sounds. We measured the typical amount of time autistic research participants could look at the video before they looked away. We found that research participants with more severe autism tended to look at the video for shorter amounts of time. The ability to focus without stopping may be related to social skills in autistic people.

Early development of social attention in toddlers at high familial risk for autism spectrum disorder

The present study explored the early development of social attention of toddlers at high familial risk (HR) for autism spectrum disorder (ASD). Eighteen HR toddlers and twenty-two toddlers at low familial risk for ASD (LR) between 11 and 24 months were asked to watch paired social and non-social videos. We found that: (1) the initial social preference in HR group decreased with age, but not in LR group; (2) both groups showed significant social habituation across trials, but HR group habituated slightly slower as age increased. These findings suggest that atypical social attention could be an early characteristic of toddlers at high familial risk for ASD.

Joint Analysis of Eye Blinks and Brain Activity to Investigate Attentional Demand during a Visual Search Task

In several fields, the need for a joint analysis of brain activity and eye activity to investigate the association between brain mechanisms and manifest behavior has been felt. In this work, two levels of attentional demand, elicited through a conjunction search task, have been modelled in terms of eye blinks, brain activity, and brain network features. Moreover, the association between endogenous neural mechanisms underlying attentional demand and eye blinks, without imposing a time-locked structure to the analysis, has been investigated. The analysis revealed statistically significant spatial and spectral modulations of the recorded brain activity according to the different levels of attentional demand, and a significant reduction in the number of eye blinks when a higher amount of attentional investment was required. Besides, the integration of information coming from high-density electroencephalography (EEG), brain source localization, and connectivity estimation allowed us to merge spectral and causal information between brain areas, characterizing a comprehensive model of neurophysiological processes behind attentional demand. The analysis of the association between eye and brain-related parameters revealed a statistically significant high correlation (R > 0.7) of eye blink rate with anterofrontal brain activity at 8 Hz, centroparietal brain activity at 12 Hz, and a significant moderate correlation with the participation of right Intra Parietal Sulcus in alpha band (R = -0.62). Due to these findings, this work suggests the possibility of using eye blinks measured from one sensor placed on the forehead as an unobtrusive measure correlating with neural mechanisms underpinning attentional demand.

A Phase II Randomized Clinical Trial of the Safety and Efficacy of Intravenous Umbilical Cord Blood Infusion for Treatment of Children with Autism Spectrum Disorder

OBJECTIVE

To evaluate whether umbilical cord blood (CB) infusion is safe and associated with improved social and communication abilities in children with autism spectrum disorder (ASD).

STUDY DESIGN

This prospective, randomized, placebo-controlled, double-blind study included 180 children with ASD, aged 2-7 years, who received a single intravenous autologous (n = 56) or allogeneic (n = 63) CB infusion vs placebo (n = 61) and were evaluated at 6 months postinfusion.

RESULTS

CB infusion was safe and well tolerated. Analysis of the entire sample showed no evidence that CB was associated with improvements in the primary outcome, social communication (Vineland Adaptive Behavior Scales-3 [VABS-3] Socialization Domain), or the secondary outcomes, autism symptoms (Pervasive Developmental Disorder Behavior Inventory) and vocabulary (Expressive One-Word Picture Vocabulary Test). There was also no overall evidence of differential effects by type of CB infused. In a subanalysis of children without intellectual disability (ID), allogeneic, but not autologous, CB was associated with improvement in a larger percentage of children on the clinician-rated Clinical Global Impression-Improvement scale, but the OR for improvement was not significant. Children without ID treated with CB showed significant improvements in communication skills (VABS-3 Communication Domain), and exploratory measures including attention to toys and sustained attention (eye-tracking) and increased alpha and beta electroencephalographic power.

CONCLUSIONS

Overall, a single infusion of CB was not associated with improved socialization skills or reduced autism symptoms. More research is warranted to determine whether CB infusion is an effective treatment for some children with ASD.