Amber N. V. Ruigrok

This study examines subcortical structural differences in autism using MRI data, finding localized shape variations rather than volumetric differences, with age-related patterns observed.

The paper identifies patterns of neural variability in autism using fMRI across tasks, finding greater global connectivity deviations and similar spatial patterns in autistic individuals compared to controls.

The paper identifies a multimodal brain pattern associated with autism by integrating gray and white matter morphology data and linking it to clinical symptoms.

This study identifies genetic correlates of phenotypic heterogeneity in autism by analyzing common and de novo variants across core features and co-occurring disabilities.

The paper identifies atypical brain asymmetry in autism as a potential neurophenotype for stratification, showing individualized patterns linked to symptom severity and language delay.

The paper shows that the Hurst exponent from fMRI BOLD signals indexes synaptic excitation-inhibition ratio, revealing sex-specific E:I imbalance in autistic mice medial prefrontal cortex.

This study examines the boundary sharpness coefficient (BSC) as a measure of cortical microstructure in ASD, finding age, sex, and regional differences in BSC that correlate with clinical measures.

The paper investigates how prenatal androgens affect functional connectivity in social brain networks, finding sex-specific impacts on adolescent males.

The paper identifies 5 distinct subgroups within autism spectrum conditions using clustering analysis on cognitive datasets, revealing varying levels of mentalizing impairments.

This paper shows that removing non-BOLD artifacts using ME-ICA improves effect size and statistical power in mentalizing task-fMRI, particularly in cerebellar regions.