Cornelia Franziska Hagmann

This paper uses graph convolutional networks to classify neonatal brain connectomes by etiology at voxel-level granularity, achieving higher classification performance than atlas-based methods and a multilayer perceptron baseline.

This study examines structural brain connectome differences in newborns at risk for cognitive developmental delay across multiple etiologies, finding altered network topology features associated with poorer cognitive outcomes.

This study uses diffusion MRI to map thalamic topography across development, showing stable topography but reduced volumes and increased relative volume in CHD infants.

The paper links thalamocortical connectivity in preterm infants to mental developmental outcomes using diffusion MRI.

This study quantifies delayed structural brain connectome maturation in neonates with congenital heart disease compared to healthy controls, showing lower integration and higher segregation.

This study examines the link between early amplitude-integrated EEG (aEEG) and neurodevelopmental outcomes in preterm infants, finding that aEEG measures are not predictive after adjusting for confounders.

This study uses connectomic analysis to show that early high-dose EPO in preterm infants strengthens brain connectivity, particularly in frontal and temporal lobes, and increases network segregation.