М. А. Пирадов

This paper evaluates multimodal DTI-TMS metrics to classify chronic ischemic stroke patients into motor recovery groups, finding IC FA ratio and MEP presence as key discriminators.

The paper investigates neural and computational mechanisms of bidding behavior in auctions using model-based neuroimaging and finds directional learning models outperform reinforcement learning in predicting human bidding strategies.

This study optimizes a grid-based TMS mapping algorithm to improve the accuracy of detecting cortical muscle representation changes over time.

This study validates a Russian adaptation of the Coma Recovery Scale-Revised (CRS-R) in patients with chronic disorders of consciousness, showing good reliability, validity, and sensitivity for assessing recovery.