Experimental Brain Research

, Volume 215, Issue 3–4, pp 269–283 | Cite as

Two classes of movements in motor control

  • Elizabeth B. TorresEmail author
Research Article


This work investigated whether fundamental differences emerged between segments of complex movement sequences performed at different instructed speeds. To this end, we tested 5 novices and 1 karate expert as they performed beginner’s martial arts routines. We found that if one blindly took these segments and separated them according to the variability of trajectory parameters, one could unambiguously group two classes of movements between the same two space regions: one type that remained quite conserved despite speed changes and another type that changed with speed level. These groups corresponded to functionally different movements (strike segments explicitly directed to a set of goals and spontaneously retracting segments supplementing the goals). The curvature of the goal-directed segments remained quite conserved despite speed changes, yet the supplemental movements spanned families of trajectories with different curvature according to the speed. Likewise, the values of the hand’s peak velocity across trials were more variable in supplemental segments, and for each participant, there were different statistical signatures of variability between the two movement classes. This dichotomy between coexisting movement classes of our natural actions calls for a theoretical characterization. The present experimental results strongly suggest that two separate sets of principles may govern these movement classes in complex natural behaviors, since under different dynamics the hand did not describe a unique family of trajectories between the same two points in the 3D space.


Goal-directed movements Supplemental movements Speeds Blind classification Kinesthetic sense Martial arts Maximum velocity 



We thank Uri Yarmush, our Psychology undergraduate martial arts expert who performed, instructed, and supervised the routines in these motor experiments. We thank Prof. Jorge V. José for technical guidance on Statistical Mechanics and Dr. Robert W. Isenhower for useful comments. This work was funded by the NSF Cyber-Enabled Discovery and Innovation Type I (Idea) grant # 0941587 to EBT “A novel quantitative framework to study lack of social interactions in Autism Spectrum Disorders” and by the New Jersey Governor’s Council for Medical Research and Treatment of Autism grant # 10-403-SCH-E-0 “Perceptual Motor Anticipation in ASD”.


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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  1. 1.Psychology Department (Busch Campus)Rutgers UniversityPiscatawayUSA
  2. 2.Cognitive ScienceRutgers UniversityPiscatawayUSA
  3. 3.Computational Biomedicine Imaging and Modeling, Computer ScienceRutgers UniversityPiscatawayUSA
  4. 4.Medical School (Neurology)Indiana UniversityBloomingtonUSA

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