Motor Synergies: A Concept in Motor Control

1. Motor Synergies:A Concept in Motor Control Marieke Rohde CCNR – Centre for Cognitive Neuroscience and Robotics Workshop on the Dynamical Systems approach to Life and CognitionUniversity of Sussex, 8 and 9 March 2005

2. Structure • Motor Synergies • Directional Pointing • Linear Synergies in Human Directional Pointing • Evolutionary Robotics Example • Conclusions

3. 1.) Motor Synergies

4. Nicholas Bernstein • Nicolas Bernstein (1967, but really 1935) • Physiology of Activity, Biomechanics • Degrees of Freedom Problem

5. The Degrees of Freedom Problem • The “Cartesian Puppeteer” has to control a countless number of motor units. DoF 2600 26 7

6. Motor Equivalence and Context-Conditioned Variability • Motor Equivalence • Redundancy through many degrees of freedom • Context-Conditioned Variability: • Anatomical (role of a muscle is context dependent) • Mechanical (command sent to muscles is ignorant against motion/nonmuscular forces) • Physiological (the spinal cord is not just a relay station)

7. The Solution • Systematic relationships between actuators (constraints) can reduce the degrees of freedom to form functional motor units (e.g. wheel position in a car)  Motor Synergies! • Skill Acquisition • First freezing degrees of freedom • Then freeing them and exploiting passive dynamics

8. Biological Evidence for Synergies • Systematicities in kinetics/kinematics: • Different types of gaits • Shooting • Breathing (Overview: Tuller et. Al. 1982) • Linear relation between shoulder and elbow torque (Gottlieb et. Al. 1999) • Complex behaviour as composition of synergies • Frog EMG data can be explained as linear combination of 7 linear synergies (Saltiel et. Al. 2001) Synergy between elbow and shoulder joint in a skilled marksperson

9. Problems with Motor Control through Synergy Control • The reminder of the homunculus • How does it work? • Acquisition and maintenance of synergies: • What is a good synergy? • What mechanism controls their development? • Combination of synergies: • Who deals with non-linearities? • Weiss, P. and M. Jeannerod (1998): • “Motor coordination is not the goal but a means to achieve the goal of an action”

10. …there’s no problem. Still, the observed phenomena require explanation. If there’s no homunculus…

11. Evolutionary Robotics • Things we can ask ourselves: • What does it imply if we have non-redundant models? • What does it imply if we do not have context-conditioned variability? • Things we can investigate: • More degrees of freedom • Anatomical, mechanical, physiological context dependence • Motor synergies in the absence of a homunculus • Impact of these factors on • Behaviour • Evolvability • The “phylogenetic learning” process

12. 2.) Directional Pointing

13. Linear Synergies in Human Directional Pointing • Gottlieb et. Al. 1997: • Directional Pointing in the sagittal plane • Linear relation: • Systematic variation of scaling constant with pointing direction • Linear synergies as an outcome of learning? • Zaal et. Al. 1999: • Linear Synergies are not learned, they constrain learning Hand trajectories for pointing Direction against scaling constant Pre-reaching period

14. Simulated Robotic Arm Proprioceptive (joint angle) + Directional Inputs Fitness: Position at endpoint Motor control: “Garden CTRNNs” with two motor neurons per degree of freedom “Split Brain CTRNNs” with separate controllers for joints Linear Synergy networks with just one motor output and evolved scaling function (RBFNs) 2 vs. 4 degrees of freedom for all of the above 2 goals vs. up to 6 goals (additional goal once it has a certain level) Most severe simplifications: Hand of 4 degrees model is squashed between two planes No gravity Experiments (Work in Progress) Screenshot of the simulated arm

15. Results • Performance • DoFs: 4 twice as good as 2 • Linear synergy are much better than CTRNNs (even linear linear synergies are comparable) • Split brains are not a lot worse than ordinary CTRNNs • How do they solve the problems? • 2 DoF’s: Frequently just use one joint • 4 DoF’s: exploit the invisible planes. • Linear Synergy: use different techniques, look a bit smoother • Split brains: Independence of joints very obvious

16. Results • Phylogeny • CTRNNs freeze degrees of freedom at first and then include them. • Networks use passive dynamics straight away. • Synergies • No linear synergies in any CTRNN controllers.

17. 3.) Conclusions

18. Conclusions: Evolutionary Robotics • Redundant degrees of freedom can facilitate evolving a controller, in spite of the much bigger search space and lead to a better solution • Learning under the constraint of linear synergy reshapes the search space and can lead to a very quick and successful evolution of different strategies (Careful with bias through model selection).

19. Conclusions: Synergies • A question we cannot answer (yet) is: Why are there linear synergies? • The acquisition of synergies: • Learning is not necessarily building up linear synergies. • The fact that the constraint of linear synergy boosts evolution suggests its suitability for developmental processes. • CTRNNs freeze and free DoFs. • Some kind of synergy gives CTRNNs an advantage over split brain CTRNNs. • The concept of synergy: • It is very useful to explain behaviour in abstract terms. • Particularly, if more complex behaviour is investigated. • Thinking in terms of synergies raises different questions • You just have to be clear about your relation to the Homunculus idea.

20. Future Research • Input models: • Make more CTRNN friendly • Visual inputs • Get rid of the invisible planes • Evolve constraints for lifetime development • Use synergies in a larger context (co-evolution of car and driver) • Investigate other forms of context conditioned variability

21. Any questions?

22. References • Arbib, M. A. (1981):  Perceptual Structures and Distributed Motor Control.  In: V. B. Brooks (ed.): Handbook of Physiology. Section 2: The Nervous System. Vol. II, Motor Control, Part 1. American Physiological Society, 1449-1480. • Bernstein, N. (1967): The Coordination and Regulation of Movements. Oxford: Pergamon. • Berthouze, L. and M. Lungarella (2004): Motor Skill Acquisition Under Environmental Perturbations: On the Necessity of Alternate Freezing and Freeing of Degrees of Freedom. Adaptive Behavior, 12(1). • Gottlieb, G. L., Q. Song, G. L. Almeida, D. Hong, and D. Corcos (1997): Directional Control of Planar Human Arm Movement. Journal of Neurophysiology 78:2985-2998. • Grossberg, S. and Paine, R.W.(2000): A Neural Model of Corticocerebellar Interactions During Attentive Imitation and Predictive Learning of Sequential Handwriting Movements. Neural Networks, 13, 999-1046. • Morasso, P., F.A. Mussa Ivaldi and C. Ruggiero (1983): How a discontinuous mechanism can produce continuous patterns in trajectory formation and handwriting. Acta Psychologica 54. pp. 83-98.

23. References • Sporns, O., and G.M. Edelman (1993): Solving Bernstein's problem: A proposal for the development of coordinated movement by selection. Child Dev. 64:960-981. • Saltiel, P., K. Wyler-Duda, A. d'Avella, M.C.Tresch and Bizzi, E. (2001): Muscle Synergies Encoded Within the Spinal Cord: Evidence From Focal Intraspinal NMDA Iontophoresis in the Frog. J. Neurophysiol., 85: 605-619. • Tuller, B., H. Fitch and M. Turvey (1982): The Bernstein Perspective: II. The Concept of Muscle Linkage or Coordinative Structure. in: S. Kelso (ed.): Human Motor Behavior. An Introduction. Hillsdale: Lawrence Erlbaum. • Turvey, M., H. Fitch and B. Tuller (1982): The Bernstein Perspective: I. The Problems of Degrees of Freedom and Context-Conditioned Variability. in: S. Kelso (ed.): Human Motor Behavior. An Introduction. Hillsdale: Lawrence Erlbaum. • Weiss, P. and M. Jeannerod (1998): Getting a Grasp on Coordination. News Physiol. Sci. 13. 70-75. • Zaal, F., Daigle, K., Gottlieb, G.L., Thelen, E. (1999): An unlearned principle for controlling natural movements. Journal of Neurophysiology, 82:255-259.