Susan Whitfield

HARMONY harmonizes neuroimaging data from multiple cohorts to study brain-behavior associations in anxious misery disorders, showing increased statistical power in pooled analyses.

This paper introduces mRBM-HBP, a Bayesian framework that integrates resting-state and task fMRI to improve cortical parcellation accuracy and individual specificity.

The paper examines DMN hyperconnectivity in psychosis risk individuals and links two distinct connectivity patterns to specific symptom clusters.

The paper examines how specific lifetime stressor characteristics and brain network connectivity predict anxiety and depression symptoms in adolescents.

The paper uses connectome predictive modeling to identify neural correlates of trait mindfulness subscales in resting-state fMRI data from three samples.

This review evaluates EEG and fMRI studies on mindfulness-based neurofeedback, finding mixed evidence for brain changes and mental health benefits, with limitations in control groups and transfer effects.

The paper replicates and extends a brain system for allostasis and interoception using 7 Tesla fMRI, finding high agreement with animal tract-tracing studies.

This study uses mindfulness-based fMRI neurofeedback to target DMN hyperconnectivity in adolescents with affective disorder history, showing reduced within-DMN connectivity and increased state mindfulness.

The paper predicts exercise adherence in older adults using brain structure and function, along with other measures, showing multimodal models have the highest predictive power.

This study investigates cerebello-cerebral functional connectivity in MDD using resting-state fMRI, finding increased connectivity in the DMN-related cerebellar ROI and between ROI1 and angular gyrus.

The paper examines how brain network coupling in children relates to cognitive performance, finding environment-dependent patterns in the relationship between lateral frontoparietal and default mode networks.

This study improves automated white-matter tractography in lower-quality diffusion MRI data by training on high-quality Connectom data and manually annotated pathways.

The paper examines resting-state fMRI data from high-risk individuals to determine if abnormal functional connectivity in the dentate nuclei precedes psychosis onset.

The paper develops a functional brain network model to predict stimulus-independent, task-unrelated thought across different populations and contexts.

The paper predicts future changes in sedentary behavior using resting state functional connectivity and baseline measures in older adults.

The paper compares resting state functional connectivity in jazz improvisers, classical musicians, and non-musicians, finding distinct connectivity patterns associated with musical training and improvisation.

This paper identifies three functional territories in the human dentate nucleus using resting-state MRI, showing their unique contributions to default-mode, salience-motor, and visual brain networks.

The paper examines how beta and gamma frequency bands mediate different aspects of cortical resting-state network maturation from age 7 to 29.