Tag: Autism

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Regulating Together for Intellectual Disability: A Group Behavioral Therapy for for Emotion Dysregulation in Autism and Intellectual Disability

Conditions: Autism; Intellectual Disabilities With Other Behavioral Symptoms; Intellectual Disability

Interventions: Behavioral: Regulating Together group therapy

Sponsors: Children’s Mercy Hospital Kansas City; National Institutes of Health (NIH); National Center for Advancing Translational Sciences (NCATS); Frontiers Clinical & Translational Science Institute

Recruiting
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<![CDATA[After FDA’s new warning, experts stress controlled data show acetaminophen in pregnancy isn’t tied to autism or ADHD; confounding fuels scares.]]>
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The Sentinel Phenotype: a theoretical bioenergetic and neurobiological framework for high-fidelity predictive systems (HEPOE Theory)

The HEPOE Theory (High Entropy Predictive Organization Efficiency) proposes a novel conceptual framework for understanding Giftedness (HA/G), moving beyond academic performance-based models toward a biophysical and neuroscientific foundation. Through a theoretical synthesis grounded in the Free Energy Principle and Biological Thermodynamics, the gifted individual is redefined as a “Sentinel”: a high-fidelity sampling system specialized in the early detection of isomorphy and the reduction of systemic entropy. This framework reinterprets Charles Spearman’s general intelligence (g) as a macroscopic manifestation of hardware efficiency, where reasoning ability is proposed to be fundamentally constrained by working-memory capacity and the metabolic economy of ATP resynthesis. We hypothesize that the hardware operates under an “open sensory gating” regime and low latent inhibition, leading to high metabolic costs and chronic allostatic load. The paper introduces the original concept of Predictive Moral Injury to conceptualize the potential somatic damage resulting from the early perception of ethical-systemic collapses within low-resolution environments. The HEPOE Unification Matrix integrates decades of classical literature and proposes a rigorous differential diagnosis against the pathologization of ASD, ADHD, and PTSD. It hypothesizes that the Sentinel’s exhaustion is not a dysfunction, but a logistical byproduct of high predictive performance under entropy-saturated conditions.
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Marmoset models for the study of autism spectrum disorders

Neurological and psychiatric disorders are a highly prevalent source of global disability. For the majority of these conditions, including autism spectrum disorder (ASD), disease-modifying treatments remain unavailable, and existing pharmacological interventions are largely palliative.

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New Study Identifies Different Biological Subtypes of Autism

Research findings help explain why symptoms present so differently from one child to the next, and why individualized supports and interventions are essential.

Autism can look very different from person to person. One child might differ from another in how they learn, process sensory information, and experience social and communication challenges. Scientists have long suspected these differences stem from distinct biology, but proving it has been challenging — until now.

A recent study published in Nature Neuroscience has identified two biological subtypes of autism linked to different pathways in the brain.

Researchers from the Child Mind Institute, the Istituto Italiano di Tecnologia, and other international partners analyzed brain connection patterns in nearly 2,000 individuals, including 940 autistic people from the Autism Brain Imaging Data Exchange (ABIDE). By combining human brain-imaging datasets with complementary biological data, they identified two consistent patterns in how different brain regions communicate.

One subtype showed reduced communication, or hypoconnectivity, among brain regions linked to pathways that help brain cells send signals to one another. The other showed increased communication, or hyperconnectivity, among brain regions linked to pathways associated with the immune system. The two subtypes exhibited differences in functional brain structure and modest differences on standardized autism assessments, with the hyperconnectivity subtype scoring moderately higher on autism severity measures.

These findings give scientists the first empirically biology-based framework for understanding autism’s complexities over time. This type of work could move the field closer to more precise, personalized approaches to medicine and care. However, this does not mean autism can now be divided into just two categories, nor does it create a new diagnostic framework. Autism is complex, and these two subtypes are likely part of a much larger picture.

The study also highlights the importance of open science. Through shared datasets like ABIDE, researchers can tackle questions too large for a single lab to answer alone.

Read the Full Paper

The post New Study Identifies Different Biological Subtypes of Autism appeared first on Child Mind Institute.

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Progenitor diversity during formation of the mammalian neocortex

Mammalian neocortical development follows a precise spatiotemporal sequence to generate the organized structure responsible for higher-order cognition and behavior. Increasing evidence suggests that diversification of neural stem and progenitor cells during prenatal development is a key step in the emergence of the intricate circuitry and functional architecture of the cerebral cortex. This review discusses novel findings with an emphasis on mechanisms and consequences of cell lineage variation during normal and altered brain development, including focus on neurodevelopmental disorders such as autism spectrum disorders and Down syndrome.
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A bibliometric analysis of neuroimaging studies on cognitive control in autism spectrum disorder (2000–2025)

ObjectiveThis study aims to systematically analyze neuroimaging research on cognitive control in Autism spectrum disorder (ASD) from 2000 to 2025 using bibliometric methods, in order to reveal the evolutionary trajectory, core knowledge base, research hotspots, and future frontiers of the field.MethodsA search was conducted on the Web of Science Core Collection and Scopus databases, resulting in the inclusion of 1,581 relevant articles. VOSviewer and the Bibliometrix package in R were utilized to conduct a comprehensive visualization and quantitative analysis of annual publication volume, country/institution/author collaboration networks, keyword co-occurrence, document co-citation, and thematic evolution.Results(1) The volume of research literature showed exponential growth, with an annual growth rate of 21.61%, entering a period of rapid development particularly after 2012, which is closely related to the popularization of functional magnetic resonance imaging (fMRI) technology. (2) “Functional connectivity,” “executive function,” and “default mode network” were the most central keywords. “Functional connectivity” rapidly became a hub connecting various themes after 2010, marking a paradigm shift from “functional localization” to “brain network dysregulation.” (3) The “Triple network model” proposed by Menon was the most cited document, laying the core theoretical foundation for understanding ASD as a disorder of large-scale brain network dysfunction. (4) “Transdiagnostic” research has emerged as a new hotspot, while “multimodal imaging,” “machine learning,” and “dynamic connectivity” represent highly promising future directions.ConclusionOver the past two decades, neuroimaging research on cognitive control in ASD has undergone a profound paradigm shift: from focusing on abnormal activation in isolated brain regions to exploring the static and dynamic dysregulation of large-scale brain networks. The research perspective has also expanded from a single-disorder model to a transdiagnostic framework that includes comparisons with other neurodevelopmental disorders (e.g., ADHD). Future research should focus on the fusion of multimodal data, the application of computational psychiatry methods, and the translation of basic research findings into personalized clinical interventions.
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Factors influencing the sensory profile in patients with autism spectrum disorder from 16 months to 14 years: results of an observational study

IntroductionSensory processing abnormalities represent a high-impact clinical feature in individuals with Autism Spectrum Disorder (ASD). Sensory alterations can be classified by modality and behavioral responses to stimuli. The literature presents conflicting results regarding the association between the sensory profile and other clinical elements. Therefore, this study aimed to characterize the clinical variables that influence sensory anomalies in subjects with ASD.MethodsThis single-center retrospective observational study selected 159 subjects with a confirmed ASD diagnosis, aged 16 months to 14 years. Data collected included clinical assessments (developmental profile, intelligence quotient, adaptive profile and autistic symptom severity) and sensory evaluations using the Sensory Profile-2. A Bayesian cumulative logit model was implemented to assess the impact of clinical variables on sensory profiles.ResultsThe analysis identifies adaptive functioning as the most consistent predictor of sensory outcomes, where higher functioning correlates with a reduction in atypical patterns, particularly sensory sensitivity. Conversely, autism severity and sex generally showed no significant impact, though higher cognitive functioning was specifically linked to increased sensory avoiding behaviors. Furthermore, the Bayesian analysis revealed a modifying effect of age on the sensory profile, characterized by a non-monotonic trend clustered around two distinct age peaks. The preschool period is characterized by a predominance of sensory seeking behaviors and auditory processing challenges, whereas the 8-to-12-year developmental window marks a significant shift toward hypersensitivity and avoidant patterns, particularly within the visual and oral modalities.DiscussionOverall, the analysis revealed that the adaptive profile has a significant impact on the sensory profile, consistent with existing literature. Age emerged as a key modifying factor with a non-monotonic trajectory, contrasting with previous studies that typically highlight either improvement or stability over time. Study main limitations include its retrospective and non-longitudinal nature. Therefore, further prospective longitudinal studies are necessary to explore these dynamic associations between the sensory profile and other clinical variables over time.