Matthew Dylan Tisdall

The paper introduces a multimodal MRI dataset to evaluate myelin-sensitive imaging methods across test-retest acquisitions and metrics.

The paper analyzes age-related changes in neurometabolite concentrations in infants using 1H-MRS data from the HBCD study, finding significant increases in some metabolites and decreases in others.

The PMADS Project tracks neurobiological and clinical changes in high-risk individuals across the perinatal period to identify biomarkers linking brain plasticity to PMADs risk.

The paper introduces a longitudinal data resource combining multimodal imaging and cognitive phenotyping to study brain development and EF variation in adolescents.

The paper examines subcortical and limbic volume associations with cortical thinning and neurodegenerative pathologies in postmortem brain MRI data from multiple disease groups.

MR KLEAN improves MRI image quality by denoising k-space data without relying on specific acquisition or reconstruction methods.

The paper introduces an open data resource combining neuroimaging and behavioral measures to study mood and sleep in adolescents and young adults.

The paper characterizes hippocampal subfield border variability using postmortem MRI and histology, finding consistent subfield appearance/disappearance orders and no clear diagnosis-related differences.

This paper develops a multi-modality MRI segmentation model to improve robustness of medial temporal lobe subregion segmentation in poor-quality images.

The paper develops a segmentation protocol for anterior medial temporal lobe regions and integrates it into an automated approach to improve imaging biomarkers for neurodegenerative diseases.

This study evaluates head motion correction methods in diffusion MRI, showing both Eddy and SHORELine perform well but are affected by denoising and sampling schemes.

This study develops a ME-EPI protocol for olfactory task-based fMRI, showing improved BOLD sensitivity over 1E-EPI through signal combination and artifact reduction.

The paper uses multilayer network analysis to explore associations between environmental exposures and brain development in children, finding dense connections within environmental and brain layers but sparse connections between them.

This paper introduces Synth, a field map-less distortion correction method for fMRI data, showing comparable or better performance than field map-based approaches in pediatric and adult datasets.

This study evaluates six compressed sensing diffusion spectrum imaging (CS-DSI) schemes, finding they provide accurate and reliable white matter structure measures with up to 80% reduced scan time compared to full DSI.

This study investigates functional brain network development in children aged 4-10, finding age-related segregation and integration patterns that challenge classical theories of cortical maturation.

The paper investigates whether proxy measures of neural plasticity in the human frontoparietal system predict learning outcomes after short-term training.

This study examines how cerebral blood flow and fMRI fluctuations are coupled in youth, finding age-related decreases, sex differences, and links to executive function.

This study uses joint ex vivo MRI and histology to identify distinct iron-rich gliosis patterns in FTLD-Tau and FTLD-TDP, distinguishing them from other neurodegenerative conditions.

This study creates 3D maps of neurofibrillary tangle burden in the human medial temporal lobe using ex vivo MRI and dense histology, revealing variation along the anterior-posterior axis and widespread NFT distribution.

This paper develops a band-stop filter to correct respiratory artifacts in MRI motion estimates, improving data quality and demonstrating real-time implementation.

The paper presents an ultra-high resolution MRI dataset of an ex vivo human brain and provides it in both native and stereotactic spaces for research and educational use.

The paper develops an automated method to assess structural brain image quality using Euler number and validates its effectiveness in identifying low-quality images and its relationship with cortical thickness and age-related associations.