Seminar Details
2023-05-02 (14h) : Understanding human motor control and adaptation through stochastic feedback control
At Euler building (room A.002)
Organized by Mathematical Engineering
Speaker :
Kalidindi, Hari Teja
Abstract :
Humans display flexible motor control in a wide range of contexts, which is supported by distributed computations in the nervous system. Stochastic optimal feedback control models have been used to capture many features of human motor behavior and related neural information processing (to an extent), but their use has been limited to well-practiced movement repertoires, where human behavior is observed to be close to optimal. However, when the conditions under which humans act change, they must adapt their control responses to suit the new context. Although adaptive behavior involves optimizing one's actions to new contexts, researchers have surprisingly avoided using optimal feedback control models to explain motor adaptation until very recently. In my presentation, I will discuss how stochastic feedback control is used in neuroscience and our work on human motor control and adaptation, which is based on predictions from this theory. Overall, my presentation will demonstrate the importance of considering stochastic feedback control in our understanding of human motor control and adaptation and how it can shed light on how the nervous system produces movements.