Frauke Beyer

The paper investigates associations between retinal nerve fibre layer thickness and brain grey/white matter structure, finding some links but not supporting cardiovascular risk factor associations.

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

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 uses explainable AI to link brain-age prediction models with neuroimaging features of aging, revealing correlations between voxel relevance and structural brain markers.

This study identifies 67 genetic loci associated with head size, finding strong overlaps with cancer pathways and genes, suggesting shared genetic mechanisms between head growth and cancer risk.

This study identifies 25 genetic loci associated with brain age gap and links them to mental and physical health traits using genome-wide data from UK Biobank.

This study investigates structural brain connectivity differences in children with developmental dyscalculia using diffusion tensor imaging and finds reduced white matter coherence and shorter tract lengths in specific brain regions associated with math ability.

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

This paper uses deep learning to estimate brain age from MRI data and identifies structural brain changes associated with aging.

This study shows how estradiol and progesterone levels affect specific brain regions in women's menstrual cycles using MRI.

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.

This study examines the relationship between dietary and serum tyrosine, white matter microstructure, and executive attention in overweight adults, finding sex/gender and age differences.

This study investigates the genetic and environmental factors influencing head motion during MRI, finding no significant single variants and no mediation by physiological or psychological factors.

The paper investigates the relationship between white matter hyperintensities and alpha oscillations in older adults, finding that WMHs are associated with elevated alpha power but not with peak frequency or long-range temporal correlations.

This study assesses the impact of MRI scanner upgrades on grey matter structure measurements in longitudinal designs, finding significant biases that persist despite correction methods.

This study shows weight loss reduces head motion during MRI, suggesting potential biases in neuroimaging outcomes related to obesity.

The paper examines hemispheric asymmetries in EEG and fMRI related to approach and avoidance behavior, finding no significant links to eating behavior or BMI.

This study shows higher BMI correlates with altered hypothalamic microstructure in humans, independent of age, sex, and comorbidities.

The paper identifies 161 genome-wide significant genetic associations for cortical structure traits across 34 brain regions, highlighting key biological pathways and gene functions.

The paper identifies genetic associations with cortical surface area using PCA and GWAS, linking DAAM1 to visual cortex development through mitochondrial pathways and thalamocortical input.

The paper examines how resting heart rate variability (HRV) relates to brain structure and function across different age groups, finding age-dependent changes in functional connectivity.

This study investigates the relationship between blood pressure and grey matter volume in young adults, finding that higher blood pressure correlates with reduced grey matter volume in specific brain regions.

This study examines the relationship between food addiction, obesity, and brain structure in a population-based sample, finding no significant neuroanatomical correlates of food addiction but some associations with BMI and orbitofrontal cortex thickness.

This study predicts brain-age from multimodal imaging data and finds it captures cognitive impairment with robustness to motion and generalizability across datasets.