1. Motor Control Theory
Chapter 5 – slide set 4

2. The crucial relationship is:
From the last slide set…
Between the order parameter(s), control parameter(s) and stability…
For the baby stepping:
Order parameter = step reflex; control parameters = fat weight, muscle strength, environment
Energy efficiency is the overall guide to the circumstances under which the step is more or less stable

3. The crucial relationship is:
So where does the step part of the movement come from?
Remember the idea of interacting parts of a system (from the water example)?
Here the interacting parts are muscles, and their connections
When innervated as a whole, the babies muscles resolve themselves into a kick

4. The crucial relationship is:
…and the dynamics of the CNS adapting to the most energy efficient solution to the problem (given enough time and experience)
Leads to many “local solutions”
Learning progresses by de-stabilizing these in favor of more effective solutions
Think of developing bad habits in sport, and trying to get out of them – the longer they have persisted, the more stable they are and the harder they are to break

5. Relating to humans – another example – running and walking (see link below)
Order Parameter
Control parameter
Attractor state B A C

6. But really – how does it apply to humans??? Another example:
In-phase:
Faster and faster…
Kelso & Scholtz, 1985

7. But really – how does it apply to humans??? Another example:
In-phase:
Faster and faster…
Kelso & Scholtz, 1985
Kelso & Scholtz, 1985

8. But really – how does it apply to humans??? Another example:
Anti-phase:
Faster and faster…
Kelso & Scholtz, 1985
Kelso & Scholtz, 1985

9. But really – how does it apply to humans??? Another example:
Anti-phase:
Faster and faster…
Kelso & Scholtz, 1985
Kelso & Scholtz, 1985

10. But really – how does it apply to humans???
Stability and attractors
The in-phase and out-of-phase states in the Kelso example are attractor states for the movement
Perturbing the movement when it is in a stable attractor region will result in a quick return to stability (in-phase)
Difference between jt. Angles
Coordination
Stability
Variation in jt. Angles (arbitrary units)

11. But really – how does it apply to humans???
Stability and attractors
Perturbing the movement when it is close to a region of instability will result in either a longer period of instability followed by a resumption of the original state, or a new attractor state
When close to a period of transition, the movement will exhibit critical fluctuations
the movement will be more ‘wobbly,’ less stable
Difference between jt. Angles
Coordination
Stability
Variation in jt. Angles (arbitrary units)

12. Exploring the coordination of movement using synergetics
Define system and joint motions used to perform task
Scale a parameter within the task and identify the slowest “moving” relationships of joint motions (order parameter)
Scan the dynamics of the slow moving relationships
Identify the preferred and non-preferred patterns
Choose a potential control parameter
Determine the relative stability of the patterns within a phase transition experiment
Mathematically model your system
Test the model

13. Properties of DST Attractor states are characterized by
optimal energy efficiency
Stability
Self-organization
Motor development example:
The emergence of the shape of the step wasn’t dictated by the brain, but emerged as a consequence of the interplay amongst a whole range of variables.

14. Properties of DST Coordinative structures
Partial solution to the degrees of freedom problem
joint or limb components ‘linked’ to each other during movement
become sensitive to the movements of other parts
they become one structure for the purposes of coordination
Kelso et al. (1984) – jaw movements
Arytunyen et al. (1980) – pistol shooting

15. Properties of DST Perception-action coupling
Rather than the brain specifying behavior, the environment specifies behavior (such as timing) – that is it constrains the movement in an important way
There are many examples of this:
Long-jump (Lee, Lishman & Thomson, 1982)
Control of braking (Lee, 1976)
Catching (Savelsburgh, Whiting & Bootsma, 1992)

16. Perception-action coupling - examples

17. Perception-action coupling - examples

18. “Embodied cognition” in artificial intelligence
Other thoughts...
“Embodied cognition” in artificial intelligence

19. Other thoughts...
Pictures from Thelen’s (and Ulrich’s) early research – stepping and kicking

20. Other thoughts...
Pictures from Thelen’s (and Ulrich’s) early research – “walking” on a treadmill

21. Other thoughts...
Data from Thelen et al. 1993: two children showing very different approaches to reaching for an object. However...

22. by the end of the first year, the movements are very similar
...by the end of the first year, the movements are very similar. What does that say about the search for coordination?

23. Other thoughts...
Schematic from Thelen et al. 2001: the “A not B” problem. A truly complex and adaptive case of modeling order and control parameters...see next slide

24. Other thoughts...
Excerpt from Spencer et al (2006): the “A not B” problem. A list of control parameters in the task. And another comment on embodied cognition. DST doesn't only deal with movement.