Statistics of natural movements are reflected in motor errors.
Humans use their arms to engage in a wide variety of motor tasks during everyday life. However, little is known about the statistics of these natural arm movements. Studies of the sensory system have shown that the statistics of sensory inputs are key to determining sensory processing. We hypothesized that the statistics of natural everyday movements may, in a similar way, influence motor performance as measured in laboratory-based tasks. We developed a portable motion-tracking system that could be worn by subjects as they went about their daily routine outside of a laboratory setting. We found that the well-documented symmetry bias is reflected in the relative incidence of movements made during everyday tasks. Specifically, symmetric and antisymmetric movements are predominant at low frequencies, whereas only symmetric movements are predominant at high frequencies. Moreover, the statistics of natural movements, that is, their relative incidence, correlated with subjects' performance on a laboratory-based phase-tracking task. These results provide a link between natural movement statistics and motor performance and confirm that the symmetry bias documented in laboratory studies is a natural feature of human movement.
Howard
Ian S
IS
Computational and Biological Learning Laboratory, Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, UK. ish22@cam.ac.uk
Ingram
James N
JN
Körding
Konrad P
KP
Wolpert
Daniel M
DM
D001132:Arm / Q000502:physiology; D004550:Elbow / Q000294:innervation; D005246:Feedback / Q000502:physiology*; D006801:Humans; D008297:Male; D015233:Models, Statistical; D009068:Movement / Q000502:physiology*; D011597:Psychomotor Performance / Q000502:physiology*; D016059:Range of Motion, Articular / Q000502:physiology*