Bogdan Draganski

Dose-dependent myelin g-ratio alterations in the white matter of 16p11.2 copy number variations

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.

White Matter Microstructure Fingerprint of Cerebral Small Vessel Disease

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

Multiscale reorganization of brain and behavior under large-scale electrical perturbation

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

Beta-burst dynamics in the motor cortex are reshaped through sensorimotor refinement

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.

Mid-level visual features engage V4 to support sparse object recognition under uncertainty

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.

Using rare genetic mutations to revisit structural brain asymmetry

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.

Is there a neural common factor for visual illusions?

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

Subcortical brain alterations in carriers of genomic copy number variants

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

Statistical analyses of motion-corrupted MRI relaxometry data

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

Rare CNVs and phenome-wide profiling: a tale of brain-structural divergence and phenotypical convergence

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.

Mind the gap: performance metric evaluation in brain-age prediction

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

Restoring statistical validity in group analyses of motion-corrupted MRI data

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.

Neuropsychiatric copy number variants exert shared effects on human brain structure

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

Leveraging biobank-scale rare and common variant analyses to identify ASPHD1 as the main driver of reproductive traits in the 16p11.2 locus

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

Simultaneous Estimation of Population Receptive Field and Hemodynamic Parameters from Single Point BOLD Responses using Metropolis-Hastings Sampling

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.

Controlling motion artefact levels in MR images by suspending data acquisition during periods of head motion

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.

Multiple Linear Regression: Bayesian Inference for Distributed and Big Data in the Medical Informatics Platform of the Human Brain Project

Convex Optimized Population Receptive Field (CO-pRF) Mapping

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