Jan K. Buitelaar

This study analyzes fMRI data from OCD patients and controls to identify age-specific differences in brain activation during inhibitory control and error processing.

The paper develops and evaluates the Regional Vulnerability Index (RVI-ASD) as a neuroimaging biomarker for autism, showing its stability, heritability, and associations with cognition and social outcomes.

This study compares thalamic nucleus volumes across multiple psychiatric and neurological disorders using MRI, finding significant volume reductions in specific regions associated with different conditions.

This study identifies six genome-wide significant risk loci for tic disorders and links genetic risk to specific brain cell types and circuits.

The paper establishes a normative reference for large-scale human brain dynamics using resting-state fMRI data from over 10,000 individuals, revealing systematic reorganization across development and ageing and disorder-specific deviations in mental health conditions.

This study investigates brain age differences in youth with conduct disorder compared to controls, finding accelerated brain maturation in those with adolescence-onset CD.

This study uses longitudinal normative modelling of white matter fractional anisotropy in the EU-AIMS LEAP cohort to show individual deviations in white matter development are linked to clinical variation in autism, with significant cross-sectional and longitudinal brain-behaviour associations.

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.

This study uses genome-wide meta-regression to analyze social behavior across different contexts, ages, and reporters, identifying six genetic loci and showing modest heritability.

The paper identifies neurogenetic substrates of psychopathological procrastination using twin cohort data and neuroimaging analysis, revealing brain disorder characteristics.

The paper investigates neural adaptation to familiar images in autistic adolescents and finds no significant difference in behavioral or neural responses compared to non-autistic adolescents.

This study shows that including zero-phase-delay connectivity improves the reliability and prognostic ability of functional connectivity metrics in neural populations.

The paper conducts GWAS on brain volumes, identifies genetic loci, and develops polygenic scores with cross-ancestry predictive ability and causal links to neuropsychiatric disorders.

The paper examines EEG abnormalities in ASD and controls, finding reduced fE/I in both groups with abnormalities, suggesting inhibition-dominated networks in sensory regions.

The paper evaluates factors affecting brain-age prediction models using structural neuroimaging data from 35,683 individuals, finding optimal model performance with no site harmonization, age-binning, and a sample size of over 1,600.

The paper uses structural equation modeling to identify three genetic factors linked to language/cognition, behavior, and motor development in ASD, revealing novel associations and simplex-specific genetic overlaps.

The paper uses multimodal MRI data to explore brain-behavior relationships, finding some components linked to intoxication and working memory but no significant shared variance between structural and functional organisation.

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.

This paper compares five bioinformatics pipelines for analyzing 16S rRNA gene sequencing data from the gut microbiome, showing how pipeline choice affects downstream statistical results and case-control conclusions.

The paper benchmarks and optimizes a normative modeling framework for brain morphometry across the lifespan using MFPR, showing excellent accuracy and stability.

The paper investigates the relationship between glutamate and GABA gene-sets, autism symptoms, and cortical thickness using data from the EU-AIMS LEAP cohort.

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 shared cortical morphology dimension across six psychiatric conditions using MRI data from 28,546 participants.

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 investigates the association between genetic variation in glutamate and GABA genes and brain structure/chemistry in autism, finding differential involvement in specific brain regions.

The paper examines age-related variations in cortical thickness across different life stages using gene expression data from a large neuroimaging dataset.

The paper investigates genetic overlaps between neuropsychiatric disorders and insulin-related diseases, finding significant genetic correlations and suggesting potential clusters of disorders with divergent pleiotropic effects.

The paper examines hemispheric asymmetry in structural covariance networks in ASD across 43 datasets, finding altered topological features in specific brain regions.

The paper investigates how molecular and connectomic vulnerabilities contribute to cortical abnormalities across multiple brain disorders using MRI data from 47,000 individuals.