Max Planck Institute for Dynamics and Self-Organization -- Department for Nonlinear Dynamics and Network Dynamics Group
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BCCN AG-Seminar

Tuesday, 13.01.2009 17 c.t.

Variability and stability in motor learning

by Prof. Dr. Dagmar Sternad
from Departments of Biology, Electrical & Computer Engineering, and Physics, Northeastern University, Boston, USA

Contact person: Katja Fiedler


Seminarraum Haus 2, 4. Stock (Bunsenstr.)


Variability is a ubiquitous characteristic in even highly skilled performance and can serve as a useful window into the determinants of skill acquisition and control. Variability is specifically informative when a task is redundant, i.e., the same result can be obtained in many different ways. My colleagues and I have developed a novel analysis technique that parses observed variability into three components: tolerance, noise and covariation. In three experiments we examined questions of: What aspects of variability decrease with practice? Are actors sensitive to their intrinsic noise in selecting strategies? How can variability or its components be manipulated by interventions? For all experiments a throwing task served as our model system. Using a virtual set-up, subjects threw a pendular projectile in a simulated concentric force field to hit a target. The movement was experimentally constrained such that only two variables, angle and velocity of ball release, fully determined the projectile's trajectory and thereby the accuracy of the throw. While leaving the task redundant, this simplification facilitated analysis and decomposition of variability.


Bernstein Lecture

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