Chris Rorden

The paper ablates attention heads in vision-language models to study picture naming accuracy, finding that head removal disrupts naming but does not confirm the head computes the behavior.

This study shows that different analysis methods greatly affect the accuracy of lesion-symptom mapping, with specific designs improving sensitivity and specificity.

This study maps the neurotransmitter architecture of the human language network and identifies neurochemical disruptions in post-stroke aphasia, suggesting potential for personalized pharmacological strategies.

This study benchmarks predictive models for long-term stroke outcomes using a global consortium, revealing mechanistic diversity and key predictors across motor, cognitive, and emotional domains.

This study investigates the neural separation of verbal working memory and syntactic comprehension, finding distinct brain networks associated with each function.

Neurodesk provides a portable and reproducible neuroimaging analysis platform using software containers to enable accessible and flexible data analysis pipelines.

The paper introduces FMRI quality control tools in AFNI, providing systematic, in-depth, and interactive QC features for preprocessing pipelines.

This study uses resting-state fMRI and graph theory to examine how disruptions in the dual-stream speech processing model relate to aphasia impairments in stroke patients.

The paper proposes using the second derivative (DoG) for edge detection in MRI coregistration, improving alignment quality by generating closed surfaces and reducing intensity dependency.

This study investigates the neural basis of speech processing by analyzing lesion data from 158 individuals with brain damage, identifying key regions involved in syllable discrimination and word comprehension.

The paper maps structural white matter disconnections in apraxia by analyzing diffusion tensor imaging data from stroke patients, identifying key fronto-temporo-parietal and subcortical networks involved.

This study uses multivariate lesion-mapping to identify a brain network associated with spatial neglect and attention in right brain damaged patients, showing benefits over univariate methods.

This study examines word error patterns in connected speech and object naming after left hemisphere stroke, finding distinct neural substrates for different types of paraphasias.

The paper updates the Lead-DBS pipeline for DBS imaging and connectomics, demonstrating its application on clinical data and comparing preprocessing strategies.

The paper describes an automated processing and quality control pipeline for brain imaging data from the first 10,000 UK Biobank participants.