Learning the environment as compatible forces and motions
Event details
| Date | 12.12.2016 |
| Hour | 16:30 › 17:30 |
| Speaker | Prof. F. A. Mussa-Ivaldi, Rehabilitation Institute of Chicago, USA. |
| Location | |
| Category | Conferences - Seminars |
The goal of recovering the desired behavior against external perturbations can be achieved by feedback mechanisms. When the environment is unpredictable, the maintenance of a desired motion or a desired contact force by feedback mechanisms can be accomplished by shifting the interface impedance toward two opposing limits. In motion control, random forces are counteracted by high position feedback gains, resulting in high contact impedance. In force control, random motions are compensated by high force feedback gains, resulting in low contact impedance.
The possibility to shift impedance toward high or low values is constrained by the passive mechanics of muscles and bones and by the long transmission delays of neural feedback. However, when the environment acts upon us in a predictable way, our brain may form internal representations of the external mechanics and modify the feedforward commands accordingly. This leads to an adaptive response that has been extensively investigated in the generation of movements against predictable force fields.
I will consider this issue in a theoretical framework that extends the concept of internal models and unifies the approach to the motor learning of forces and motions. In this framework, the brain generates a vast spectrum of interactive behaviors by combining two independent processes. One is competent to control movements in free space and the other is competent to control contact forces against rigid constraints. Free space and rigid constraints are singularities at the boundaries of a continuum of mechanical impedance. Within this continuum, forces and motions occur in "compatible pairs" connected by the equations of Newtonian dynamics. The force applied to an object determines its motion. Conversely, inverse dynamics determine a unique force trajectory from a movement trajectory. In this perspective, motor learning is a process that leads to representing the environment dynamics through the discovery of compatible force/motion pairs.
Bio: Ferdinando A. (Sandro) Mussa-Ivaldi was born in Torino, Italy. He has a degree (Laurea) in physics from the University of Torino, Torino, Italy, in 1978, and the Ph.D. degree in biomedical engineering from the Politecnico of Milano, Milan, Italy, 1987. He is a Professor of Physiology, Physical Medicine and Rehabilitation and Biomedical Engineering at Northwestern University. He is founder and Director of the Robotics Laboratory of the Rehabilitation Institute of Chicago. His areas of interest and expertise include robotics, neurobiology of the sensory-motor system and computational neuroscience. Among his scientific achievements are the first measurement of human arm multi-joint impedance, the development of a technique for investigating the mechanisms of motor learning through the application of deterministic force fields, the discovery of a family of integrable generalized inverses for redundant kinematic chains, the discovery of functional modules within the spinal cord that generate a discrete family of force-fields, the development of a theoretical framework for the representation, generation and learning of arm movements and the development of the first neurorobotic system in which a neural preparation in vitro—the brainstem of a lamprey—controls the behavior of a mobile-robot through a closed-loop interaction.
In the last two decades, he has worked toward understanding the mechanisms of motor learning and how these mechanisms can be used to help people recover from disability. He investigates motor learning, not merely as a mechanism to improve particular skills, but as a means for the brain to adapt the control a body that changes in a variable environment. Recently, he has developed the concept of the body–machine interface as an instrument to facilitate the reorganization of movement to control devices such as wheelchairs and computers. He is the author of over 150 full-length publications. Dr. Mussa-Ivaldi is a member of the Society for Neuroscience and of the Society for the Neural Control of Movement.
The possibility to shift impedance toward high or low values is constrained by the passive mechanics of muscles and bones and by the long transmission delays of neural feedback. However, when the environment acts upon us in a predictable way, our brain may form internal representations of the external mechanics and modify the feedforward commands accordingly. This leads to an adaptive response that has been extensively investigated in the generation of movements against predictable force fields.
I will consider this issue in a theoretical framework that extends the concept of internal models and unifies the approach to the motor learning of forces and motions. In this framework, the brain generates a vast spectrum of interactive behaviors by combining two independent processes. One is competent to control movements in free space and the other is competent to control contact forces against rigid constraints. Free space and rigid constraints are singularities at the boundaries of a continuum of mechanical impedance. Within this continuum, forces and motions occur in "compatible pairs" connected by the equations of Newtonian dynamics. The force applied to an object determines its motion. Conversely, inverse dynamics determine a unique force trajectory from a movement trajectory. In this perspective, motor learning is a process that leads to representing the environment dynamics through the discovery of compatible force/motion pairs.
Bio: Ferdinando A. (Sandro) Mussa-Ivaldi was born in Torino, Italy. He has a degree (Laurea) in physics from the University of Torino, Torino, Italy, in 1978, and the Ph.D. degree in biomedical engineering from the Politecnico of Milano, Milan, Italy, 1987. He is a Professor of Physiology, Physical Medicine and Rehabilitation and Biomedical Engineering at Northwestern University. He is founder and Director of the Robotics Laboratory of the Rehabilitation Institute of Chicago. His areas of interest and expertise include robotics, neurobiology of the sensory-motor system and computational neuroscience. Among his scientific achievements are the first measurement of human arm multi-joint impedance, the development of a technique for investigating the mechanisms of motor learning through the application of deterministic force fields, the discovery of a family of integrable generalized inverses for redundant kinematic chains, the discovery of functional modules within the spinal cord that generate a discrete family of force-fields, the development of a theoretical framework for the representation, generation and learning of arm movements and the development of the first neurorobotic system in which a neural preparation in vitro—the brainstem of a lamprey—controls the behavior of a mobile-robot through a closed-loop interaction.
In the last two decades, he has worked toward understanding the mechanisms of motor learning and how these mechanisms can be used to help people recover from disability. He investigates motor learning, not merely as a mechanism to improve particular skills, but as a means for the brain to adapt the control a body that changes in a variable environment. Recently, he has developed the concept of the body–machine interface as an instrument to facilitate the reorganization of movement to control devices such as wheelchairs and computers. He is the author of over 150 full-length publications. Dr. Mussa-Ivaldi is a member of the Society for Neuroscience and of the Society for the Neural Control of Movement.
Practical information
- Informed public
- Free
Organizer
- Prof. S. Micera