David C. Van Essen

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 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.

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.

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.

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.

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

This study maps prefrontal cortex circuits in marmosets, revealing distinct local and long-distance projection patterns and their implications for primate brain organization.

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.

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.

The paper shows that high b-value diffusion tensor imaging (DTI) metrics are strongly associated with NODDI metrics in cortical gray matter, but low b-value DTI does not accurately reflect microstructure.

The paper introduces ciftify, a framework to adapt HCP surface-based analysis methods to legacy MR data using CIFTI format.

The paper develops a dynamical circuit model of human cortex incorporating hierarchical heterogeneity to better explain large-scale neural dynamics and functional connectivity.

The paper describes a large-scale retinotopy dataset from the HCP and presents population receptive field analysis results from both individual subjects and group averages.

This paper introduces temporal ICA to remove global structured noise from fMRI data while preserving global neural signals, improving upon traditional global signal regression methods.

This paper compares traditional neuroimaging methods with surface-based approaches, showing traditional methods significantly degrade cortical area localization.

The paper quantifies prefrontal cortex (PFC) size in humans relative to nonhuman primates, finding humans have significantly larger PFC gray and white matter volumes compared to chimpanzees and macaques.

This paper estimates local cortical growth patterns in preterm infants using aMSM, revealing regional and temporal differences in expansion linked to folding and injury detection.

This study examines how the spatial arrangement of brain regions influences functional connectivity and behavioral predictions.

The paper analyzes mouse cortical connectivity using tracer injections and histological markers, revealing high graph density and distinct connectivity profiles compared to macaques.