BackgroundNeuropsychiatric conditions are heterogeneous and mechanistically diverse, yet predictive modeling studies commonly aggregate features without evaluating prespecified liability architectures. The Pathogenetic Triad (PT) is a multilevel framework proposing that diagnostic outcomes reflect the joint configuration of a trait-related domain, cognitive capacity (CC), and neuropathological burden (NB). In autism, the trait-related domain corresponds to autistic personality (AP). We evaluated this framework using out-of-sample prediction as a structured empirical test of architectural coherence rather than as a purely data-driven exercise in classification.MethodsWe analyzed a case–comparison cohort (n = 42, 21 autistic) with dense multimodal characterization, including behavioral phenotyping, psychometric measures, autonomic physiology, structural MRI morphometry, and magnetoencephalographic indices. AP was indexed by the Autism-Spectrum Quotient, CC by Wechsler’s scales of intelligence, and NB by heart-rate variability as a proxy indicator. This multimodal structure enabled direct comparison of theory-constrained PT models with strength-matched, domain-restricted atheoretical combinations. Predictive discrimination was evaluated using leakage-free nested cross-validation with permutation inference.ResultsAcross multiverse specifications, low-dimensional PT models ranked among the strongest models of comparable size and achieved discrimination broadly comparable to higher-dimensional models within this dataset. Matched comparisons indicated that including all three PT domains was associated with systematic advantages relative to alternatives with similar univariate input strength, consistent with complementary configurational information relating to case status.ConclusionsThese findings provide preliminary evidence supporting the Pathogenetic Triad as a multilevel architecture of autism liability. Although based on a small and demographically restricted cohort, this densely characterized dataset permitted explicit comparison of theory-guided and atheoretical model spaces. The results illustrate how prespecified multilevel frameworks can be operationalized and empirically evaluated in neuropsychiatric samples.
MH-POWER for College Students on the Spectrum
Conditions: College Students on the Autism Spectrum With Mental Health Challenges
Interventions: Behavioral: The MH-POWER program
Sponsors: University of Texas Rio Grande Valley; The American Occupational Therapy Foundation
Recruiting
Interventions: Behavioral: The MH-POWER program
Sponsors: University of Texas Rio Grande Valley; The American Occupational Therapy Foundation
Recruiting
Age-stratified multimodal MRI and machine learning to explore autism-related brain characteristics in youth
PurposeAutism is a common neurodevelopmental condition (NDC) that is characterized by restricted, repetitive behaviors and social communication differences that can impact the daily functioning of individuals. The clinical diagnosis of autism can be challenging, mainly due to its behavioral variability and frequent co-occurrence with other NDCs. This study investigates the ability of machine learning-based classification models trained using multimodal neuroimaging data combined with feature-importance analyses to identify development-specific brain characteristics associated with autism.ApproachA total of 144 participants aged 5 to 18 years with structural MRI (sMRI), diffusion MRI (dMRI), and resting-state functional MRI (rs-fMRI) data available were obtained from the Autism Brain Imaging Data Exchange (ABIDE) database. Radiomic features were extracted from each MRI data modality and used to train support vector machine (SVM) classifiers to identify neuroimaging patterns associated with autism. Single MRI modality classifiers, as well as one combining all three modalities, were trained for comparison purposes. To investigate age-specific effects, the same approach was followed for three age sub-groups: younger children (5–11 years), adolescents (12–18 years), and the entire 5–18 years age cohort. Model performance was evaluated using leave-one-out cross-validation across 30 diagnosis-balanced data splits. Feature-importance analyses were conducted to identify the most important neuroimaging features for classification.ResultsThe classification accuracies of the unimodal models ranged from 68.3% to 75.3% for sMRI, from 69.3% to 77.6% for dMRI, and from 66.3% to 69.9% for rs-fMRI data across age groups. Among all single imaging modalities and age groups, dMRI showed the highest performance with a 77.6% accuracy in younger children (5–11 years). The multimodal approach improved classification performance when compared to the unimodal models in all age groups, achieving accuracies of 78.9%, 76.7%, and 70.5% in the younger, adolescent, and entire age cohorts, respectively. Our findings indicate that multimodal classifiers integrating complementary structural, microstructural, and functional imaging features result in a more comprehensive representation of brain features that strengthens model performance. The most informative brain regions for classification differed between children and adolescents while several diffusion-derived features significantly correlated with social responsiveness scores, emphasizing the clinical importance of studying white and gray matter microstructure in autism.ConclusionsThis study demonstrates the potential of multimodal neuroimaging-based machine learning models to identify development-specific biomarkers associated with autism. The results highlight the value of integrating age-stratified analyses of multimodal neuroimaging to better capture autism-associated developmental brain characteristics. The framework adopted in this study could be extended to explore other NDCs in the future.
Effectiveness of a Virtual Reality Social Skills Intervention in Autism
Conditions: Autism Spectrum Disorder High-Functioning; Young Adults
Interventions: Behavioral: MyRakan Autism
Sponsors: National University of Malaysia; Ministry of Higher Education, Malaysia
Completed
Interventions: Behavioral: MyRakan Autism
Sponsors: National University of Malaysia; Ministry of Higher Education, Malaysia
Completed
The burden of care, parenting stress, and navigating welfare services: parents’ everyday experiences of young children with autism spectrum disorder
BackgroundParenting a child with autism spectrum disorder (ASD) is demanding and affects all aspects of life, yet parents’ experiences during the child’s early years remain underexplored, especially from Scandinavian countries. This study examined parents’ experiences in a Scandinavian context characterized by strong parental involvement of both parents, extensive preschool coverage, and comprehensive welfare systems. Our aim was to explore how parents of preschool children experience everyday parenting and how these experiences shape parenting stress and family life.Materials and MethodsThirteen individual semi-structured interviews were conducted with mothers and fathers of children with ASD aged three to five. This study is part of the “Enabling Parents of Children with Autism Spectrum Disorders – A Randomized Controlled Study on Parenting Programs”, registered at Clinical-Trials.gov (ID: NCT05750095). Data were analyzed using Systematic Text Condensation, a descriptive and exploratory cross-case thematic approach.ResultsThree main categories were identified: “Everyday family life”, “Family and social networks”, and “Meeting the system in daily life”. Parents described continuous adaptation to their child’s needs; everyday life required continuous follow-up while managing concerns of siblings and the child’s safety. Experiences of participation and isolation coexisted, and parents frequently fostered understanding and acceptance of ASD while seeking practical and emotional support in everyday life. Preschool services and support were important. In their interactions with welfare services, parents often encounter bureaucratic complexity when seeking competence, stability, and flexibility.ConclusionParenting a young child with ASD is a dynamic process involving ongoing tasks, adaptation, and learning, strongly shaped by both the child’s needs and the coherence of the surrounding support systems. When services are fragmented, insufficient, or uncoordinated, the parental burden and stress increases, whereas moments of mastery and support foster resilience, underscoring the need for competent, flexible, and family−adapted services.
A Two-Part Intervention to Target Cardiovascular Health
Conditions: Autism; Adverse Childhood Experience; Stress; Cardiovascular (CV) Risk
Interventions: Behavioral: Lifestyle Medicine; Behavioral: Cognitive Behavioral Therapy (CBT); Behavioral: Lifestyle Medicine with CBT Group
Sponsors: University of California, Los Angeles; Health Resources and Services Administration (HRSA)
Not yet recruiting
Interventions: Behavioral: Lifestyle Medicine; Behavioral: Cognitive Behavioral Therapy (CBT); Behavioral: Lifestyle Medicine with CBT Group
Sponsors: University of California, Los Angeles; Health Resources and Services Administration (HRSA)
Not yet recruiting
Some parents see a villain in ‘Toy Story 5.’ Others see a lifeline.
Conner James Black, associate director of the Autism Center at the Child Mind Institute, encourages families to have two separate devices: one for communication and another for entertainment, rather than using one for both.
The post Some parents see a villain in ‘Toy Story 5.’ Others see a lifeline. appeared first on Child Mind Institute.
Module-specific diagnostic accuracy of ADOS-2 in real-world clinical referral populations: an updated systematic review and HSROC meta-analysis
BackgroundThe Autism Diagnostic Observation Schedule, Second Edition (ADOS-2), is widely used in the diagnostic evaluation of autism spectrum disorder (ASD); however, its diagnostic performance in real-world clinical referral populations remains heterogeneous, particularly across modules and clinical contexts. This systematic review and meta-analysis evaluated the module-specific diagnostic accuracy of ADOS-2 using hierarchical meta-analytic modeling and examined sources of heterogeneity in updated evidence clinical studies.MethodsA systematic search of PubMed/MEDLINE, Scopus, and Web of Science was conducted from January 2021 to February 2026, with additional screening of reference lists. Studies were included if they evaluated ADOS-2 diagnostic accuracy in real-world clinical referral populations, used DSM- or ICD-based clinical best-estimate diagnosis as the reference standard, and reported extractable 2×2 data. Diagnostic accuracy was pooled using a hierarchical summary receiver operating characteristic (HSROC) model with a bivariate random-effects approach. Module-specific analyses (Toddler Module, Modules 1–2, Module 3, Module 4) and meta-regression were performed to examine heterogeneity.ResultsTen studies were included in the qualitative synthesis, and six provided extractable 2×2 data for quantitative pooling. Overall pooled sensitivity was 0.88 (95% CI: 0.83–0.92) and pooled specificity was 0.74 (95% CI: 0.68–0.80), with an HSROC AUC of 0.86. The Toddler Module showed the highest diagnostic performance (sensitivity 0.92; specificity 0.88; AUC 0.94), whereas specificity decreased in Modules 3 and 4. Meta-regression identified module level, psychiatric referral setting, and adult samples as significant contributors to reduced specificity. No significant publication bias was detected.ConclusionsADOS-2 demonstrates high overall sensitivity but variable specificity across modules in real-world clinical referral populations. Reduced specificity was more commonly observed in higher ADOS-2 modules, which are typically administered to verbally fluent adolescents and adults with greater psychiatric complexity.
The Download: Europe’s heat wave hits the grid, and IBM’s chip targets Moore’s Law
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.
Europe’s extreme heat is shutting down power plants
Europe is in the middle of a record-breaking heat wave, and the grid is being pushed to its limits as people turn to fans and air-conditioning to try to stay cool. But some power plants won’t be online to help handle the load.
The main source of stress is increased demand, largely driven by cooling. And the challenges are only expected to worsen as climate change brings more frequent and intense heat waves.
Find out how rising temperatures are stretching power supplies—and how utilities can adapt.
—Casey Crownhart
What Europe’s heat wave means for the power grid
Grid planning in the age of climate change generally means that we need a lot more supply, and quickly. But one interesting facet to this challenge is that in some places, seasonal patterns are shifting, compounding the difficulty of meeting demand.
Europe has historically seen its grid peak in the winter when electric heating is widespread. So some planned outages happen in the spring and into the summer, which is affecting the supply right now. But a growing need for air-conditioning will alter the balance.
Read the full story on how climate change is reshaping electricity demand.
—Casey Crownhart
This story is from The Spark, our weekly newsletter giving you the inside track on all things climate. Sign up to receive it in your inbox every Wednesday.
IBM unveils chip technology that could help extend Moore’s Law another decade
IBM has built a new prototype chip with around 100 billion transistors on an area the size of a fingernail. That’s twice the density of the company’s previous state-of-the-art technology announced in 2021. And the design could pave the way for faster and more energy-efficient computers for years to come.
In the last fifteen years, transistors have been shrunk close to their limits. They can’t get smaller without their function deteriorating. IBM’s new chip resolves this with an approach familiar to urban planners: building up.
Here’s how the strategy is bringing new hope to the technology industry.
—Sophia Chen
The must-reads
I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.
1 Anthropic says Alibaba “illicitly” extracted Claude’s capabilities
It claims the Chinese firm ran a “brazen” campaign to access the model. (BBC)
+ It says it’s the “largest known distillation attack” on the company. (CNBC)
+ The technique trains a weaker model on a stronger one’s outputs. (FT $)
+ Anthropic previously accused other Chinese rivals of using it. (CNN)
+ But it’s still feuding with the White House. (MIT Technology Review)
2 NASA has detected possible chemical signatures of ancient life on Mars
The Perseverance rover spotted complex carbon on rocks. (New Scientist $)
+ The molecules are typically associated with dead organisms. (Guardian)
+ The US has lost its lead in the hunt for alien life. (MIT Technology Review)
3 The EU has joined a US pact to stop relying on Chinese AI
Much of the rest of the world seems to still be a battleground for control. (FT $)
+ China is expanding its AI push in the Global South to counter the US. (The Wire China)
+ Chinese AI experts are freaking out about the AI arms race. (Wired $)
4 OpenAI and Broadcom have unveiled their first jointly designed AI chip
Jalapeño is built to power large-scale AI systems like ChatGPT. (NYT $)
+ It’s part of OpenAI’s push to “build the full stack.” (CNBC)
5 A new report shows ICE has built a vast hi-tech surveillance system
It includes facial recognition, drones, and data scraping.(Guardian)
+ Is the Pentagon allowed to surveil citizens with AI? (MIT Technology Review)
6 Electronics can now be printed onto living tissue
Which could enable smart implants and ingestible diagnostics. (The Economist $)
7 The data center boom is sparking a third wave of inflation
Demand for memory chips is pushing prices higher.(WSJ $)
8 Companies are scrambling to curb spending on AI token “chewing”
Accenture data shows non-technical staff are draining budgets. (404 Media)
9 Claude Design is creating a bland wave of website uniformity
The AI tool is homogenizing the internet’s aesthetic. (The New Yorker $)
10 Elon Musk has lost his trillionaire status
Thanks to SpaceX stock coming back to Earth. (Business Insider)
Quote of the day
“Tom Brown is not being a weirdo like Dario and can actually engage.”
—A person directly familiar with calls between the Trump administration and Anthropic tells Wired that they’ve improved since cofounder Tom Brown replaced CEO Dario Amodei in the talks.
One More Thing
TONY LUONG
The quest to learn if our brain’s mutations affect mental health
For years, scientists searching for the roots of conditions like schizophrenia, autism, and Alzheimer’s have focused on single genes. But the real source may lie in a more complex genetic puzzle inside the brain.
Mike McConnell has spent decades exploring the idea that neurons do not all share identical DNA, and that these differences could help explain psychiatric disease. His work has contributed to evidence that brain cells can form a “genetic mosaic,” with mutations that vary across the brain.
Discover how this could reshape our understanding of mental illness.
—Roxanne Khamsi
We can still have nice things
A place for comfort, fun, and distraction to brighten up your day. (Got any ideas? Drop me a line.)
+ This classical reimagining of the Super Mario soundtrack is exquisite.
+ At long last, we can calculate the fuel efficiency of launching our enemies into the Sun.
+ Before CGI, explosions were an art form. This compilation of classic practical effects is pure action-movie nostalgia.
+ Cambridge botanists lovingly recreated a 336-year-old garden to honor the “father of natural history.” (Big thanks to reader Peter Ryan for the find!)
<![CDATA[Phase 2 IRIS finds ML-004 misses social communication goals in autism, but notably reduces irritability in teens.]]>