Ross D. Markello

The paper introduces netneurotools, a Python toolkit developed by trainees to streamline brain imaging workflows by integrating diverse data types and addressing interoperability challenges.

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

This study uses fMRI and manifold learning to show how cortical activity patterns change during sensorimotor adaptation, revealing contraction and expansion in specific brain regions.

Neurotransmitter receptor/transporter PET maps (19 targets, 1239 healthy participants) align with connectomes, explain MEG power, and track cognitive gradients and cortical thinning in 13 disorders.

Neuromaps provides a software package to standardize and compare brain maps across different coordinate systems, enabling comprehensive annotation analysis of the human brain.

The paper examines the relationship between gene expression and neurotransmitter receptor/transporter density in the human brain using PET and autoradiography, finding poor spatial correspondence except for four specific receptors.

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

The paper maps interspecies differences in subcortical anatomy between humans and chimpanzees, linking heritability, morphology, and behavioral correlates.

The paper develops the abagen toolbox to standardize imaging transcriptomics workflows and shows that methodological variability significantly affects research outcomes using the Allen Human Brain Atlas.

The paper examines how lifestyle and reproductive factors interact with cortical thickness in healthy adults, finding sex-specific patterns linked to brain ageing.

This study evaluates ten spatial null models for neuroimaging data, finding that naive models have high false positive rates while spatially-constrained models are more conservative but still variable.

This paper integrates multimodal data from Parkinson's disease patients using similarity network fusion to identify continuous phenotypic axes that better capture patient heterogeneity than discrete biotypes.

The paper identifies two topographic gradients of intrinsic brain dynamics across the neocortex, linked to cognitive and functional processing patterns.

The paper maps gene expression patterns to functional activation patterns in the cortex, identifying a gradient separating affective and cognitive domains and linking it to cognitive performance.

This study links tissue volume loss in schizophrenia to structural and functional connectivity, finding that 25-35% of regional deformation variance is explained by these factors.

The paper examines structure-function relationships in the neocortex, finding that structural and functional networks diverge in higher-order areas.

The paper uses resting-state fMRI to identify distinct functional networks in human basal forebrain nuclei, aligning with anatomical regions and showing unique projection patterns.