Simon Baron‐Cohen

The paper identifies a mid-gestational molecular mechanism linking cortical size and ADHD through genetic and single-cell RNA sequencing analyses.

The paper identifies polygenic hierarchies in macroscale brain structural organisation using genome-wide association studies of imaging-derived phenotypes.

The paper identifies cell-type-specific DNA methylation differences in autism, revealing female-specific X chromosome alterations in microglia.

The paper examines how environmental factors influence brain structure, cognition, and mental health in adolescents using the ABCD dataset, finding that advantageous environments correlate with better developmental outcomes.

This study compares mono- and bi-allelic NRXN1 mutations in iPSC-derived neurons, showing bi-allelic mutations cause more severe molecular, synaptic, and functional impairments.

This study analyzes a large MRI dataset to model age-related brain volume changes and sex differences from prenatal to postnatal development.

The paper introduces dGAMLSS, a distributed algorithm for fitting GAMLSS models to construct population reference charts without sharing patient data.

The paper introduces a multiscale resource integrating genetics, brain imaging, and clinical data from autistic individuals and their relatives to explore genetic and neurobiological patterns in autism.

The paper shows that neonatal brain volumes and birth factors predict developmental and socioemotional outcomes in toddlers.

This study identifies cell-type-specific DNA methylation dynamics in the human cortex across development, highlighting prenatal periods as critical for epigenomic plasticity and linking changes to neurodevelopmental disorders.

This study identifies two ASD subgroups with distinct brain morphology using cross-cultural datasets, highlighting key brain regions associated with subgroup characteristics and autistic traits.

This study performs a GWAS on functional brain network metrics and finds genetic overlap with brain structure and autism.

The paper develops predictive models for intellectual disability in autistic children by integrating genetic variants and developmental milestones, achieving an AUC ROC of 0.65 and identifying 10% of ID cases.

This study examines uncertainty processing in humans using computational models and neurochemical data, finding links between neurotransmitter levels and prediction errors in reversal learning.

The paper examines sex differences in brain structure at birth in newborns, finding larger brain volumes in males and specific regional differences in gray and white matter volumes between sexes.

This study investigates the impact of NRXN1 intronic deletions on early cortical development using hiPSCs, finding altered isoform expression and dendritic morphology.

The paper introduces a longitudinal dataset of school-age children and adolescents in China, detailing its design, sampling, and neuroimaging measurements.

The paper maps functional connectivity patterns in the somatosensory cortex during rest and emotional tasks in ASD and neurotypical individuals, linking them to adaptive functioning skills.

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 maps the odds ratio for autism associated with rare LoF variants in autism-associated genes and shows sub-diagnostic effects in undiagnosed individuals.

GWAS of 2,347 neuroimaging phenotypes identifies genetic loci and structures related to cortical development, cellular processes, and neurodevelopmental disorders.

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 introduces brain charts as a standardized resource for benchmarking brain morphology across the human lifespan using MRI data from a large and diverse cohort.

The paper investigates sex differences in autism using resting-state fMRI data, finding significant effects in brain connectivity and replicating some findings in independent samples.

This paper optimizes Airy-beam light sheet microscopy to image 3D structures in hiPSC-derived human cortical spheroids, enabling high-resolution analysis of neurodevelopmental processes.

The paper identifies structural covariation alterations in autism using VBM and links these patterns to core autism symptoms through canonical correlation analysis.

This study uses sequential Bayesian analysis to examine if face-specific neural responses relate to cognitive empathy or age, finding no significant associations.

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.