Serena Jane Counsell

This paper validates a motion correction technique, DISORDER, for pediatric brain morphometry, showing improved reliability for motion-degraded scans compared to conventional MPRAGE.

This study examines dynamic functional connectivity in neonatal brains using fMRI and links it to neurodevelopmental outcomes in early childhood.

This study uses MRI to compare brain volumes in neonates with Down syndrome to a control group, finding reduced whole brain volume in DS infants.

The paper introduces a deep learning pipeline for automated fetal brain segmentation and volumetry, showing reduced need for manual refinement and agreement with manual segmentations in clinical cases.

This study identifies behavioral subgroups in very preterm children using integrated similarity networks and links them to neonatal brain structure and function differences.

This study uses diffusion MRI to track thalamocortical pathway maturation in human fetal brains, identifying key neurobiological changes in the second to third trimester.

The paper uses network analysis to compare cognitive and behavioral trait interactions between very preterm and full-term children, finding distinct topological differences in their networks.

The paper examines how functional brain centrality develops in neonates and how preterm birth affects it, finding age-related changes and regional differences but no direct link to 18-month neurodevelopmental outcomes.

This paper uses machine learning to predict neonatal brain age and clinical risk from structural connectomes, finding thalamocortical connections are key predictors of developmental outcomes.

This study examines how gestational age at birth affects structural brain development in healthy term-born infants and links these changes to neurodevelopmental outcomes at 18 months.

This study examines how preterm birth affects cortical development in infants at term-equivalent age using MRI, finding altered microstructure and morphology with individual variability.

This paper develops a multi-channel 4D atlas of neonatal brain development combining structural and diffusion MRI data, showing microstructural differences between term and preterm infants.

The paper analyzes neonatal functional MRI data to study functional connectivity in term and preterm infants, finding age-related maturation and preterm birth-related disruptions in brain networks.

The paper develops normative brain volumetric development curves for term-born infants and compares preterm infants to these curves, identifying individual deviations linked to clinical factors and neurocognitive outcomes.

The paper optimizes multi-shell diffusion MRI acquisition parameters using a data-driven approach, resulting in a specific protocol for neonatal imaging.

This study examines ADHD symptoms in very preterm children, finding higher rates of subthreshold ADHD and associations with cognitive and socio-demographic factors.

This paper introduces a method for fetal diffusion MRI reconstruction with intensity correction, enabling detailed analysis of brain connectivity and microstructure in-utero.

The paper investigates microstructural cortex development in neonates with congenital heart disease and finds impaired oxygen delivery correlates with abnormal microstructure.

This paper develops a segmentation method for myelin-like signals on T2-weighted MRI to estimate gestational age in preterm infants using manual annotations and an expectation-maximization framework.

The paper finds that genetic risk for neuropsychiatric diseases is linked to reduced deep grey matter volume in preterm infants, suggesting a mechanism for how early adversity interacts with genetic vulnerability.

The paper examines how brain network properties at birth predict language skills and shows that syntactic abilities are affected by preterm birth.

The paper introduces a fully automated pipeline for neonatal cortical surface reconstruction from MRI, achieving high accuracy in 85% of cases.