Natalie J. Forde

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

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.

This paper develops lifespan normative models of white matter fractional anisotropy using diffusion MRI data and applies them to identify white matter deviations in early psychosis.

This paper introduces a normative modelling approach to detect diffusion MRI artefacts and processing errors using UK Biobank data, outperforming traditional visual and quantitative QC methods.

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.

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

The paper examines associations between externalizing/internalizing behaviors and cortico-amygdalar connectivity in children with NDDs and TDC, finding no significant linear relationships.

The paper integrates brain imaging and behavioral data to identify transdiagnostic subgroups in children with ASD, ADHD, or OCD, finding stable groups based on cortical thickness and inattention symptoms.

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

The paper examines sex differences in brain structure variability across the lifespan, finding greater regional variability in males and age-by-sex interactions in variability patterns.