Christopher Andrew Brown

This study externally validates machine learning models for predicting continuous pain intensity from EEG data in healthy individuals, finding limited accuracy despite some classification model success.

This study tests if visual alpha stimulation increases alpha power in chronic musculoskeletal pain patients and reduces pain, finding increased alpha power but no significant pain reduction.

The paper identifies a genetic variant in KCNG4 associated with increased labor pain by altering KV6.4 function in uterine nociceptors.

This study investigates statistical learning impairments in CRPS patients using a hierarchical Bayesian model, finding reduced precision in tactile-spatial predictions compared to healthy controls.

The paper identifies EEG biomarkers of pain catastrophizing by analyzing neural responses to pain cues using machine learning and finds enhanced aversive value encoding in high pain catastrophizers.

The paper identifies altered tactile processing in CRPS patients through somatosensory-evoked potentials, showing variability in cognitive mechanisms and potential biomarkers for clinical use.