Gabriel González‐Escamilla

The paper describes the OpenNeuroPET initiative, which develops standards and open-source tools to standardize and share PET neuroimaging data, enhancing reproducibility and collaboration.

The paper identifies oligodendrocyte subtype changes in Parkinson's disease across species, linking them to disease progression and clinical outcomes.

The paper uses single-cell spatial transcriptomics to analyze brain samples from neurodegenerative diseases and COVID-19, identifying disease-specific transcriptional patterns and microenvironmental changes.

This study identifies tyrosine receptor signalling as linked to choroid plexus enlargement and CSF dynamics in MS neuroinflammation.

The paper curates and provides analysis-ready diffusion MRI data for pediatric brain white-matter research, including automated quality control using a trained neural network.

This study investigates how subthalamic nucleus activity modulates action adaptation in Parkinson's patients during a force adaptation task, finding that reduced beta activity correlates with better adaptation.

This study uses cortical network analysis to predict deep brain stimulation outcomes in dystonia patients, finding that grey matter atrophy patterns can predict response with 88% accuracy.

The paper analyzes dynamic network responses to threat, showing that community reorganization and flexibility drive physiological responses.

This study uses TMS-EEG to examine dmPFC excitability during fear processing and links it to structural brain properties.