Susan J. Goodbody

Papers

Total Citations

721

H-Index

About

Susan J. Goodbody is a pioneering researcher in motor control and computational neuroscience, whose work has fundamentally shaped our understanding of how the brain predicts and learns from movement. Her key research areas include sensorimotor integration, predictive motor learning, and internal models of action. Goodbody’s most influential contribution is her landmark 1998 paper, “Predicting the Consequences of Our Own Actions,” which has garnered 384 citations and established a foundational framework for how efference copies and internal models enable us to anticipate the sensory outcomes of self-generated movements. In a second highly cited work (224 citations), she demonstrated how the motor system generalizes learning across different movement durations and amplitudes using robotic interfaces, revealing the brain’s remarkable flexibility. Her 1999 study on predictive motor learning of temporal delays (113 citations) further illuminated anticipatory grip force control, showing how the nervous system compensates for delays to prevent object slippage during bimanual actions. Goodbody’s research has had lasting impact on robotics, rehabilitation, and our understanding of motor disorders, making her a central figure in the field of human motor control.