Fleur Margaret Howells

The paper introduces a scalable toolkit for 3D surface-based brain analysis, demonstrating its utility in mapping subcortical shape variations across 21 international samples.

This study investigates how structural brain alterations in schizophrenia relate to network architecture, finding hub susceptibility and shared epicenters across disease stages and disorders.

This study examines structural brain heterogeneity in schizophrenia using multimodal MRI data from the ENIGMA dataset, finding higher frontotemporal heterogeneity and left parahippocampal homogeneity in patients.

The paper benchmarks and optimizes a normative modeling framework for brain morphometry across the lifespan using MFPR, showing excellent accuracy and stability.

This study investigates how strategic leadership coaching affects cortical arousal and neural circuitry activation in young executives during decision-making tasks, finding increased alpha band activity and wave component amplitudes.

The paper analyzes cortical thickness trajectories in 17,075 individuals to show peak thickness in childhood, steep decline in early adulthood, and slower decline later, with notable exceptions and significant inter-individual variability.

The paper analyzes sex differences in brain structure variability across the lifespan using a large dataset, finding greater male variability in subcortical volumes, cortical surface area, and thickness in most regions.

This study analyzes subcortical volume changes across the lifespan using MRI data from 18,605 individuals, finding age-related declines in some structures and increases in others.

The paper develops deep learning models to assess the quality of subcortical brain shape models from MRI, reducing human rater time by 46-70%.

This work uses machine learning to automate quality control of 3D brain shape models, reducing human workload by 30-70% across multiple datasets and diseases.