A generalizable connectome-based marker of in-scan sustained attention in neurodiverse youth.

Difficulty with attention is an important symptom in many conditions in psychiatry, including neurodiverse conditions such as autism. There is a need to better understand the neurobiological correlates of attention and leverage these findings in healthcare settings. Nevertheless, it remains unclear if it is possible to build dimensional predictive models of attentional state in a sample that includes participants with neurodiverse conditions. Here, we use 5 datasets to identify and validate functional connectome-based markers of attention. In dataset 1, we use connectome-based predictive modeling and observe successful prediction of performance on an in-scan sustained attention task in a sample of youth, including participants with a neurodiverse condition. The predictions are not driven by confounds, such as head motion. In dataset 2, we find that the attention network model defined in dataset 1 generalizes to predict in-scan attention in a separate sample of neurotypical participants performing the same attention task. In datasets 3-5, we use connectome-based identification and longitudinal scans to probe the stability of the attention network across months to years in individual participants. Our results help elucidate the brain correlates of attentional state in youth and support the further development of predictive dimensional models of other clinically relevant phenotypes.

Engaging the disability community in informatics research: rationales and practical steps.

As the informatics community grows in its ability to address health disparities, there is an opportunity to expand our impact by focusing on the disability community as a health disparity population. Although informaticians have primarily catered design efforts to one disability at a time, digital health technologies can be enhanced by approaching disability from a more holistic framework, simultaneously accounting for multiple forms of disability and the ways disability intersects with other forms of identity. The urgency of moving toward this more holistic approach is grounded in ethical, legal, and design-related rationales. Shaped by our research and advocacy with the disability community, we offer a set of guidelines for effective engagement. We argue that such engagement is critical to creating digital health technologies which more fully meet the needs of all disabled individuals.

Elevated symptoms of executive dysfunction predict lower adaptive functioning in 3-year-olds with autism spectrum disorder.

Executive functioning (EF) deficits co-occur frequently with autism spectrum disorder (ASD) and have a long-term detrimental impact on quality of life of children and their families. Timely identification of risk for EF vulnerabilities may hasten access to early intervention and alleviate their long-term consequences. This study examines (1) if EF deficits are elevated in toddlers with ASD compared to nonautistic siblings of children with ASD, typically developing (TYP) toddlers, and toddlers with atypical developmental presentation; and (2) if EF deficits have a detrimental effect on adaptive functioning in ASD. Participants were recruited between September 2014 and October 2019 and included 73 toddlers with ASD, 33 nonautistic siblings of children with ASD, 35 toddlers with atypical development, and 28 TYP toddlers matched on chronological age (M = 39.01 months, SD = 3.11). EF deficits were measured using the BRIEF-P; adaptive skills were measured using the VABS-II. Whenever appropriate, analyses were controlled for MSEL verbal and nonverbal developmental quotient, ADOS-2 autism severity scores, and sex. Analyses revealed that toddlers with ASD exhibited elevated BRIEF-P scores across all domains compared to each of the three comparison groups. Higher BRIEF-P scores were associated with lower adaptive social, communication, and daily living skills while controlling for symptom severity, verbal and nonverbal functioning, and sex. In conclusion, marked vulnerabilities in EF are already present in 3-year-old toddlers with ASD and are predictive of the level of adaptive functioning in ASD. EF vulnerabilities in toddlers should be targeted for intervention to improve long-term outcomes in ASD. LAY SUMMARY: Many children with autism experience vulnerabilities in executive functioning (EF), which may include challenges with inhibition, working memory, cognitive flexibility, and planning. The study shows that these vulnerabilities can already be detected at age three and that their presence is linked with lower social, communication, and daily living skills. Screening children with ASD for EF challenges and helping those who have difficulties may improve their long-term outcomes.

Understanding the experiences of self-injurious behavior in autism spectrum disorder: Implications for monitoring technology design.

OBJECTIVE: Monitoring technology may assist in managing self-injurious behavior (SIB), a pervasive concern in autism spectrum disorder (ASD). Affiliated stakeholder perspectives should be considered to design effective and accepted SIB monitoring methods. We examined caregiver experiences to generate design guidance for SIB monitoring technology. MATERIALS AND METHODS: Twenty-three educators and 16 parents of individuals with ASD and SIB completed interviews or focus groups to discuss needs related to monitoring SIB and associated technology use. RESULTS: Qualitative content analysis of participant responses revealed 7 main themes associated with SIB and technology: triggers, emotional responses, SIB characteristics, management approaches, caregiver impact, child/student impact, and sensory/technology preferences. DISCUSSION: The derived themes indicated areas of emphasis for design at the intersection of monitoring and SIB. Systems design at this intersection should consider the range of manifestations of and management approaches for SIB. It should also attend to interactions among children with SIB, their caregivers, and the technology. Design should prioritize the transferability of physical technology and behavioral data as well as the safety, durability, and sensory implications of technology. CONCLUSIONS: The collected stakeholder perspectives provide preliminary groundwork for an SIB monitoring system responsive to needs as articulated by caregivers. Technology design based on this groundwork should follow an iterative process that meaningfully engages caregivers and individuals with SIB in naturalistic settings.

Low-motion fMRI data can be obtained in pediatric participants undergoing a 60-minute scan protocol.

Performing functional magnetic resonance imaging (fMRI) scans of children can be a difficult task, as participants tend to move while being scanned. Head motion represents a significant confound in fMRI connectivity analyses. One approach to limit motion has been to use shorter MRI protocols, though this reduces the reliability of results. Hence, there is a need to implement methods to achieve high-quality, low-motion data while not sacrificing data quantity. Here we show that by using a mock scan protocol prior to a scan, in conjunction with other in-scan steps (weighted blanket and incentive system), it is possible to achieve low-motion fMRI data in pediatric participants (age range: 7-17 years old) undergoing a 60 min MRI session. We also observe that motion is low during the MRI protocol in a separate replication group of participants, including some with autism spectrum disorder. Collectively, the results indicate it is possible to conduct long scan protocols in difficult-to-scan populations and still achieve high-quality data, thus potentially allowing more reliable fMRI findings.