Konrad Wagstyl

The paper evaluates SynthSeg's performance on developmental MRI scans and finds that rescaling to adult brain sizes improves segmentation accuracy in infants and children.

The paper maps mesoscopic vascular networks in the human brain using the BigBrain dataset, revealing non-uniform vascular density related to cortical areas.

The paper quantifies sex differences in human cortical volume by separating contributions from surface area and thickness, and links these to genetic and hormonal factors using neuroimaging data.

This paper presents a normative framework for brain asymmetry across the lifespan using a large neuroimaging dataset, revealing distinct spatial patterns and providing tools for clinical and research applications.

The paper identifies three conserved spatiomolecular gradients in the adult human brain that align with developmental axes and predict functional territories.

The paper constructs a sulcal phenotype network from MRI scans to identify two clusters of sulci related to developmental timing and gene expression gradients.

This study identifies 928 genes associated with brain weight variation across three datasets and links them to neurodevelopmental processes and brain function.

This paper integrates multiscale cortical biology by generating spatially dense gene expression maps from postmortem data, revealing transcriptional zones linked to microstructure and neuroimaging features.

The paper quantifies how laminar thickness patterns in the human cortex correlate with processing hierarchy, showing developmental and functional relationships.

The paper provides a high-resolution T2* MRI dataset of the human brain at 7 Tesla, revealing cortical substructures and consistent depth-dependent T2* values across subjects.

The paper identifies new cortical gene expression components linked to neurodevelopment and finds associations with autism and schizophrenia across multiple data types.

BigBrainWarp simplifies integration of BigBrain histology with neuroimaging by providing tools for registration and cytoarchitectural feature access.

LayNii is a software suite designed for analyzing layer-specific functional MRI data with SNR and coverage constraints, offering tools for layerification, smoothing, and artifact mitigation.

The paper identifies a natural axis of transmitter receptor distribution in the human cerebral cortex that reflects laminar differentiation and functional organization.

The paper extends the CIVET pipeline for human MRI to process macaque brains, using the NMT template and anatomical parcellations, and reports results on 126 macaques.

This study improves MEG source inversion by using white matter surface locations and correspondence-based orientation estimation, showing better performance in evoked response fitting.

The paper presents a 3D laminar atlas of the human cerebral cortex using a convolutional neural network and uses it to analyze thickness gradients in sensory and motor cortices.

The paper links genetic risks to spatial brain vulnerabilities in neurodevelopmental disorders using neuroimaging and gene expression data.

The paper investigates age-related changes in cortical myeloarchitecture during adolescence using longitudinal MRI data and identifies two distinct developmental processes.

The paper identifies a dissociation between microstructural and functional gradients in transmodal brain networks using histological and MRI data.

The paper introduces morphometric similarity networks to map cortical organization and shows they predict cognitive variation across individuals.