Bogdan Draganski

This study investigates how 16p11.2 copy number variations affect white matter structure by analyzing axonal and myelin volume and g-ratio across different cohorts.

The paper analyzes white matter microstructure in cerebral small vessel disease using multimodal imaging metrics and identifies associations with cardiovascular risk factors.

The paper identifies multiscale principles of brain reorganization under electrical perturbation by integrating neuroimaging, connectomics, and transcriptomics data from 148 experiments.

The paper examines how beta-band burst dynamics in the motor cortex change with motor skill learning under adaptive and non-adaptive training conditions, showing reorganization of burst features with practice.

This study shows that mid-level visual features, specifically curve segments, enable better object recognition under uncertainty by engaging V4, offering advantages over phosphene-like dots in cortical prostheses.

The paper investigates how rare genetic mutations affect brain asymmetry by analyzing CNVs in a cohort of individuals and linking genetic alterations to brain structure and function.

The paper re-evaluates the correlation between visual illusion susceptibility and neural measures, finding no significant correlations at the perceptual or neural levels.

This study examines subcortical brain alterations in CNV carriers across multiple neuropsychiatric disorders, finding shared and distinct patterns of structural changes.

This paper introduces QUIQI, a method to restore homoscedasticity in MRI relaxometry data by using weighted least squares, improving statistical analysis robustness.

The paper investigates how eight rare CNVs affect brain structure and phenotypes across 534 carriers, finding structural divergence and phenotypic convergence despite different genetic origins.

This study evaluates performance metrics in brain-age prediction across datasets, showing variability based on age range, sample size, and age-bias correction.

The paper introduces a data-driven method to restore statistical validity in MRI group analyses by assigning image weights based on quality indices, improving performance across brain regions despite motion effects.

The paper examines the effects of neuropsychiatric CNVs on brain structure using neuroimaging data and identifies shared anatomical patterns across multiple CNVs.

The paper identifies ASPHD1 as a key driver of reproductive traits in the 16p11.2 locus using biobank data, Mendelian randomization, and animal models.

This paper introduces a Bayesian approach using MCMC sampling to estimate population receptive fields and hemodynamic parameters from single-point BOLD responses, showing high performance and validity.

This paper presents a framework to suspend MRI data acquisition during predicted head motion to reduce artefacts, achieving improved data quality with minimal scan time increase.

This paper introduces CO-pRF, a convex optimization framework for pRF mapping that improves speed and reliability compared to traditional nonlinear methods.