Replicable, Transdiagnostic Behavioral and Neural Correlates of Sensory Over-responsivity
Luo, H.; Kim, A. W.; Gurnett, C. A.; Abbacchi, A. M.; Constantino, J. N.; Luby, J. L.; Perino, M. T.; Barch, D. M.; Sylvester, C. M.; Camacho, M. C.; Schwarzlose, R. F.
Show abstract
ObjectiveSensory over-responsivity (SOR), characterized by strong negative reactions to typically innocuous stimuli, is considered a symptom of autism spectrum disorder. However, SOR also affects 15-20% of children overall, including a majority of children with common psychiatric conditions. Despite its prevalence, the clinical specificity and neurobiological bases of SOR remain poorly understood. Our study aims to determine the specific clinical significance of SOR across diverse child samples and establish whether SOR is associated with distinct patterns of functional connectivity (FC). MethodWe analyzed data from 15,728 children (ages 6-17.9 years) across five datasets: three community samples, including the Adolescent Brain Cognitive Development [ABCD] and Healthy Brain Network [HBN] studies, and two autism-enriched samples. Bivariate and multivariate models examined associations between SOR and symptoms of anxiety, attention-deficit/hyperactivity disorder, depression, conduct disorder, and oppositional defiant disorder, as well as autistic traits. Analysis of resting-state functional MRI (fMRI) data from the ABCD study tested brain-wide and circuit-specific FC correlates of mild SOR, replication of effects in an independent ABCD subsample, as well as extension to severe SOR in ABCD. ResultsMultivariate analyses revealed that SOR is associated with a remarkably consistent transdiagnostic profile: greater levels of both autistic traits and anxiety symptoms and, in community samples, lower levels of conduct disorder symptoms. Across samples, SOR is not reliably associated with symptoms of any other analyzed psychiatric conditions. SOR is associated with both brain-wide and circuit-specific resting-state functional connectivity (FC) patterns that replicate across independent subsamples and highlight FC differences between cingulo-parietal network and bilateral caudate nucleus. ConclusionOur results demonstrate that SOR may constitute a transdiagnostic latent trait with both specific clinical risk and protection, and with replicable neural correlates that implicate specific cortico-subcortical circuits. These findings advance our understanding of the neurobiology and clinical relevance of SOR. They may also inform clinical practice and future research aimed at understanding and supporting individuals with sensory challenges.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Examining Differences in the Genetic and Functional Architecture of ADHD Diagnosed in Childhood and Adulthood 94%
- Dynamic Resting-State Network Markers of Disruptive Behavior Problems in Youth 93%
- No support for oxytocin modulation of reward-related brain function in autism: evidence from a randomized controlled trial 93%
Similar papers in this journal
- Brain structure and function show distinct relations with genetic predispositions to mental health and cognition 95%
- Longitudinal development of thalamocortical functional connectivity in 22q11.2 deletion syndrome 93%
- Auditory and Visual Thalamocortical Connectivity Alterations in Unmedicated People with Schizophrenia: An Individualized Sensory Thalamic Localization and Resting-State Functional Connectivity Study 93%
Similar papers in this journal
- Connectome-wide mega-analysis reveals robust patterns of atypical functional connectivity in autism 95%
- Reconciling Dimensional and Categorical Models of Autism Heterogeneity: a Brain Connectomics & Behavioral Study 94%
- GWAS of Over 427,000 Individuals Establishes GABAergic and Synaptic Molecular Pathways as Key for Cognitive Executive Functions 94%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.