Oswaldo Baffa

This paper uses machine learning to predict TMS stimulation sites using tractography and myographic responses, showing improved performance in some subjects.

This paper characterizes an open-source electronic-robotic mTMS platform that improves the accuracy and automation of brain stimulation targeting.

This study investigates how the orientation of TMS-induced electric fields affects short-interval intracortical inhibition and facilitation in the motor cortex, finding optimal orientations for maximizing MEP suppression and facilitation.

This study examines coactivation and overlapping of cortical motor representations for forearm and hand muscles using nTMS, finding high overlap and stronger stimulation intensity effects on size than topography.

This paper develops an electronic TMS transducer for precise E-field orientation control and validates a model of neuronal excitability orientation selectivity.