Gabriel Ziegler

This study shows that optimising training difficulty based on individual abilities improves motor task performance and related motor skills in older adults.

This paper introduces an automated method to quantify white matter hyperintensity confluence, showing it correlates with cognitive performance and dementia subtypes beyond volume.

The paper examines how disrupted forward connectivity in the parieto-temporal network relates to memory impairment and AD pathology using fMRI and DCM in a longitudinal study.

This study examines how episodic memory network dysfunction relates to AD biomarkers, neurodegeneration, and cognition using longitudinal fMRI data from the DZNE study.

This paper introduces a quality assessment framework for structural MRI images using tissue classification to identify and mitigate motion artifacts and other quality issues.

The paper links cognitive reserve to brain activity during memory formation, showing it moderates the impact of Alzheimer's pathology on cognitive performance and predicts slower decline.

This paper introduces SMAS, a Bayesian VAE-based AD score from structural MRI data, showing strong correlations with cognitive decline and brain atrophy markers, and outperforming existing measures in predicting AD.

This study shows that adaptive training improves memory precision by reducing neural activity differences between new and familiar experiences, despite increased activity in familiar experiences.

This paper proposes spatial transformation and quality assessment methods for reliably imaging the small noradrenergic locus coeruleus using structural and functional MRI.

The paper investigates effective connectivity patterns during explicit memory encoding in young and older adults, finding reduced inhibitory connectivity in older adults correlates with poorer memory performance.

The paper shows that higher surface folding of the human premotor cortex predicts better long-term learning in a motor task, independent of other structural factors.

The paper introduces a method to estimate local errors in multi-parameter mapping (MPM) neuroimaging data, improving group-level sensitivity by accounting for noise and artefacts.

The paper uses Gaussian process multikernel modeling to predict memory performance and CSF biomarkers in ageing and Alzheimer's disease using MRI and other 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.

The paper introduces and validates a comprehensive fMRI score, FADE-SAME, to quantify memory-related neural activity changes associated with neurocognitive aging.

This study shows that motor skill learning involves coherent waves of myelin plasticity in the corticospinal-hippocampal loop, with spatial and temporal patterns linked to training performance.

This study uses Bayesian model selection to show parametric models better explain fMRI encoding variance than categorical models in young and older adults.

This study uses longitudinal MRI data from Huntington's Disease patients to show complex regional variations in cortical atrophy over time, with some areas showing accelerated atrophy after diagnosis.

This study shows childhood socio-economic disadvantage is linked to reduced myelin growth in adolescence and young adulthood, with some protective effects from parental education and positive parenting.

The paper identifies two modes of brain-behavior covariation in adolescents and young adults using canonical correlation analysis, linking brain connectivity to psychometric, IQ, and demographic data.

The paper links compulsivity and impulsivity to distinct patterns of fronto-striatal myelination during adolescence using longitudinal MRI data.

The paper introduces latent change score models for analyzing developmental changes in brain and behavior using longitudinal data, showing correlated brain-behavior changes and sex differences in cortical thinning.