Matthew F. Glasser

DRUMS improves cortical surface alignment by using deep learning with multimodal supervision, outperforming existing methods in accuracy and reproducibility.

The paper describes the iterative creation of harmonized ontologies and 3D frameworks for the basal ganglia across human and non-human primates to enable cross-species comparisons of cellular and molecular data.

This paper introduces a surface-intrinsic framework for hippocampal unfolding that improves alignment accuracy and morphology preservation compared to volumetric methods.

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

This study identifies structural brain differences associated with cognitive performance in middle and late adulthood using data from the Human Connectome Project.

This paper develops a 24-channel 3T RF coil for fMRI in awake monkeys, improving ferumoxytol-weighted functional connectivity estimation and identifying human-like functional networks.

This paper develops a method to compensate for cortical folding effects on cortical thickness, improving its biological interpretability and reducing variability in brain morphology studies.

QuNex Recipes provide a framework for creating executable, human-readable workflows to ensure reproducibility in neuroimaging research.

This paper creates a cross-species spatial transcriptomic atlas of the basal ganglia in human, rhesus macaque, and common marmoset, revealing conserved molecular organization and cell type-specific compartments.

This paper introduces a method to map cortical-layer specific area boundaries in primates using myelin MRI, revealing a 182 area/subarea partition in macaques with high homology to human myelin maps.

The paper investigates the functional organization of the human lateral prefrontal cortex using fMRI, revealing category-biased patches adjacent to domain-general regions.

This paper introduces an automated individual cortical parcellation method using a novel weakly supervised classifier, improving performance over previous models and identifying new atypical language-related brain areas.

The paper develops a processing pipeline for arterial spin labelling MRI data from the Human Connectome Project Lifespan and finds age-related differences in cerebral perfusion and transit times.

This study maps vascular networks in primate brains using ferumoxytol-weighted MRI, revealing regional variations in vascular volume and its relationship with neuronal and receptor densities.

This paper introduces an automated tICA pipeline for fMRI data to remove artifacts and improve signal detection, achieving high accuracy in component classification.

The paper identifies how executive functions are supported by domain-general and task-specific brain networks using high-resolution MRI data from executive tasks.

This paper evaluates individual differences in brain network organization and identifies spatial overlap as indicative of linear additive coupling.

This paper demonstrates a high-performance speech neuroprosthesis that achieves low word error rates and high decoding speeds using intracortical recordings from a person with ALS.

QuNex provides a platform for reproducible neuroimaging analytics, integrating multi-modal tools and enabling scalable, high-throughput processing across species and datasets.

This paper generalises the HCP multimodal cortical parcellation to UK Biobank data using a geometric deep learning framework, improving detection rates across cortical areas.

This paper introduces two empirical methods to correct B1+ transmit field biases in T1w/T2w myelin maps, improving their accuracy for neuroanatomical and statistical analyses.

The paper investigates feedback projections in primate early visual cortex, revealing retinotopic organization and differences in connection strength between ventral and dorsal stream areas.

This paper develops a non-invasive multi-modal neuroimaging pipeline for precise brain targeting in marmosets, revealing significant intersubject variability and creating new population-based templates.

The paper uses high-resolution myelin mapping to show graded variation in cortical myelination rates along the sensorimotor-association axis during adolescence.

The paper identifies domain-general and sensory-biased regions in the human brain using fMRI and WM tasks, showing adjacent regions with different modality preferences.

This paper benchmarks geometric deep learning models for cortical parcellation on the Human Connectome Project data, showing high overlap but variability in specific brain regions.

This paper outlines a multi-site MRI study aiming to establish harmonized imaging biomarkers for brain disorders across the lifespan using standardized protocols and data from healthy and patient subjects.

This paper introduces an algorithm to reduce tractography biases in white matter by modeling fibre density and orientation as a divergence-free vector field, improving cross-modal agreement with functional connectomes.

The paper develops a 24-channel MRI coil and adapts HCP protocols for macaques, enabling high-quality in vivo imaging and preprocessing comparable to human studies.

The paper identifies a domain-general cognitive core in the human cortex using multimodal MRI data from the Human Connectome Project, revealing its anatomical distribution and functional connectivity.