A recent publication in the Lancet was dedicated to clinical recommendations to support autistic females at birth. Because more males than females are diagnosed with autism, their needs are often misunderstood, misinterpreted, or just ignored. Researchers, clinicians, scientists, parents and self-advocates from around the world joined together to identify those needs and propose solutions that can be implemented in everyday care. Listen to this week’s podcast episode to learn more, or read the article in its entirety at the link below.
Everyone who has looked for support for autism spectrum disorder is familiar with waitlists. Waitlists for evaluation, diagnosis, intervention, consultations and referrals. These waitlists prevent important opportunities for services and many groups developing technologies, policies, and approaches to reduce the waitlists or work around them. On this week’s podcast, we talk to Dr. Sharief Taraman from Cognoa to hear about their recent study on the scope of the problem on waitlists, what causes them, and how digital therapeutics may help them.
In recognition of September 26th, this week’s podcast episode explores one of the more dangerous issues in autism: wandering. But it’s really not wandering in the traditional sense. Wandering in autism mostly means running off, bolting, deliberately with intent and without permission. Obviously this leads to some very dangerous situations for people on the spectrum. How can it be mitigated or understood? Some behavioral therapies are helpful, but new technologies have allowed for more options to bring back loved ones that have run off unexpectedly. Finally, the community needs to be better aware of possible stressors or triggers that trigger a wandering episode and work together with families to prevent running off. This problem is not caused by one thing, and the community needs multiple solutions to keep kids and adults safe.
Can biomarkers that measure things like visual social attention be a good proxy for an in person behavioral diagnosis? Why would this be important? This week’s podcast explores two new studies the the Journal of the American Medical Association that show a simple device called EarliPoint can be used to shorten the wait times to receive a diagnostic evaluation. Currently autism can be diagnosed at 18 months but most families do not get into an appointment until 4-5 years of age. That can change. Families were able to easily complete it, it predicted things like not just a diagnosis but behavioral features and cognitive ability. It’s been deployed in 6 speciality centers, been approved by the FDA, and hopefully coming to a clinic near you soon.
Understanding the neural processes underpinning individual differences in early language development is of increasing interest, as it is known to vary in typical development and to be quite heterogeneous in neurodevelopmental conditions. However, few studies to date have tested whether early brain measures are indicative of the developmental trajectory of language, as opposed to language outcomes at specific ages. We combined recordings from two longitudinal studies, including typically developing infants without a family history of autism, and infants with increased likelihood of developing autism (infant-siblings) (N = 191). Electroencephalograms (EEG) were recorded at 6 months, and behavioral assessments at 6, 12, 18, 24 and 36 months of age. Using a growth curve model, we tested whether absolute EEG spectral power at 6 months was associated with concurrent language abilities, and developmental change in language between 6 and 36 months. We found evidence of an association between 6-month alpha-band power and concurrent, but not developmental change in, expressive language ability in both infant-siblings and control infants. The observed association between 6-month alpha-band power and 6-month expressive language was not moderated by group status, suggesting some continuity in neural mechanisms.
Best practice for the assessment of autism spectrum disorder (ASD) symptom severity relies on clinician ratings of the Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2), but the association of these ratings with objective measures of children’s social gaze and smiling is unknown. Sixty-six preschool-age children (49 boys, M = 39.97 months, SD = 10.58) with suspected ASD (61 confirmed ASD) were administered the ADOS-2 and provided social affect calibrated severity scores (SA CSS). Children’s social gaze and smiling during the ADOS-2, captured with a camera contained in eyeglasses worn by the examiner and parent, were obtained via a computer vision processing pipeline. Children who gazed more at their parents (p = .04) and whose gaze at their parents involved more smiling (p = .02) received lower social affect severity scores, indicating fewer social affect symptoms, adjusted R2 = .15, p = .003.
Keywords: Autism diagnostic observation schedule; Autism spectrum disorder; Objective measurement; Smiling; Social gaze.
This week’s podcast explores new evidence that exercise produces longer term improvements in coordination and motor skills. Parents can play a big role in how these skills are developed over time. Physical exercise also has different effects on the brain in typically developing people than those with a diagnosis.
Two recent papers suggest that a childhood diagnosis of ASD is important for adulthood quality of life and well being. But another one points out that it isn’t the only thing, or even the primary factor, involved in improved quality of life and well-being as autistic adults age. There are others, like comorbid mental health problems, demographic factors like gender and current age. These studies were conducted by autistic researchers and did an amazing thing – one tried to replicate the other. The media got the point of these findings wrong (shocker) so today’s #ASFpodcast explains what they mean.
The disparity in diagnosis between Black kids and white kids is narrowing, but not by luck or coincidence. Based on previous research, clinicians are altering their professional training and their outreach to make sure more Black families are diagnosed and receive interventions. On today’s podcast, we highlight a recent study that focused on different ways to lower the age of diagnosis and improve access to early intervention in Black families. This intervention improved cognitive outcomes in Black kids.
Literature examining emotional regulation in infants with autism spectrum disorder (ASD) has focused on parent report. We examined behavioral and physiological responses during an emotion-evoking task designed to elicit emotional states in infants. Infants at an increased likelihood for ASD (IL; have an older sibling with ASD; 96 not classified; 29 classified with ASD at age two) and low likelihood (LL; no family history of ASD; n = 61) completed the task at 6, 12, and 18 months. The main findings were (1) the IL-ASD group displayed higher levels of negative affect during toy removal and negative tasks compared to the IL non-ASD and LL groups, respectively, (2) the IL-ASD group spent more time looking at the baseline task compared to the other two groups, and (3) the IL-ASD group showed a greater increase in heart rate from baseline during the toy removal and negative tasks compared to the LL group. These results suggest that IL children who are classified as ASD at 24 months show differences in affect, gaze, and heart rate during an emotion-evoking task, with potential implications for understanding mechanisms related to emerging ASD.
Keywords: ASD; affect; autism; baby sibling; gaze; heart rate; physiology.
Background: Fragile X syndrome (FXS) is the most prevalent form of inherited intellectual disability and is commonly associated with autism. Previous studies have linked the structural and functional alterations in FXS with impaired sensory processing and sensory hypersensitivity, which may hinder the early development of cognitive functions such as language comprehension. In this study, we compared the P1 response of the auditory evoked potential and its habituation to repeated auditory stimuli in male children (2-7 years old) with and without FXS, and examined their association with clinical measures in these two groups.
Methods: We collected high-density electroencephalography (EEG) data in an auditory oddball paradigm from 12 male children with FXS and 11 age- and sex-matched typically developing (TD) children. After standardized EEG pre-processing, we conducted a spatial principal component (PC) analysis and identified two major PCs-a frontal PC and a temporal PC. Within each PC, we compared the P1 amplitude and inter-trial phase coherence (ITPC) between the two groups, and performed a series of linear regression analysis to study the association between these EEG measures and several clinical measures, including assessment scores for language abilities, non-verbal skills, and sensory hypersensitivity.
Results: At the temporal PC, both early and late standard stimuli evoked a larger P1 response in FXS compared to TD participants. For temporal ITPC, the TD group showed greater habituation than the FXS group. However, neither group showed significant habituation of the frontal or temporal P1 response. Despite lack of habituation, exploratory analysis of brain-behavior associations observed that within the FXS group, reduced frontal P1 response to late standard stimuli, and increased frontal P1 habituation were both associated with better language scores.
Conclusion: We identified P1 amplitude and ITPC in the temporal region as a contrasting EEG phenotype between the FXS and the TD groups. However, only frontal P1 response and habituation were associated with language measures. Larger longitudinal studies are required to determine whether these EEG measures could be used as biomarkers for language development in patients with FXS.
Keywords: EEG; ERP; Fragile X syndrome; autism; language; neural habituation; phase coherence.
On this week’s podcast, we conduct an interview with Michelle Hughes, PhD, epidemiologist with the CDC, who answers all of our questions about how many people have autism, how they are counted, what has changed since the last count and why the CDC are counting more kids than they were 10 years ago.
You can read more about her here: https://www.linkedin.com/in/michellemergler/
Here is a link to the 8 year old counting study: https://pubmed.ncbi.nlm.nih.gov/36952288/
Here is the follow up to when they turned 16: https://pubmed.ncbi.nlm.nih.gov/36849336/