Perception, not muscle homology, makes coordination more stable

Arianne Azmoodah1 & Andrew D Wilson1*

Psychology, Leeds Beckett University, Leeds UK

*Corresponding Author

A.D.Wilson@leedsbeckett.ac.uk

Web: https://cognitioninaction.wordpress.com; Twitter: @PsychScientists

Coordinated rhythmic movements exhibit a characteristic pattern of stability, where 0° is most stable, 180° is stable but less so, and nothing else is stable without some training. This pattern is thought to be affected by two constraints. The first constraint is egocentric; when the coordination requires the use of homologous muscle groups at the same time, movements are more stable. The second constraint is allocentric; when the coordination involves motion in the same direction at the same time, movements are more stable. Previous work has shown that net movement stability emerges as these constraints play out in real time (Swinnen et al, 1997).

Previous work has relied on Lissajous feedback displays which transform the two movements being coordinated into a single, integrated motion. This feedback does not preserve the allocentric information unless the hands and their relative direction can be viewed as well. This disrupts the standard stability pattern (Kovacs et al, 2009). Wilson et al (2010) developed and tested coordination feedback displays, in which the movements of each limb are represented by a dot on a screen, preserving both constraints. These displays enabled us to test an ecological, perception-action model of coordination dynamics (Bingham, 2001, 2004a,b; Snapp-Childs et al, 2011) as well as provide real-time feedback that drives learning without transforming that dynamic (e.g. Wilson et al, 2010).

Stability is typically measured the standard deviation of relative phase (SDΨ). However, the variability of a coordination is not independent of the intended relative phase, and you cannot interpret SDΨ without accounting for performed relative phase. For example, if I am untrained and try to perform 90° I will quickly lose this coordination and get stuck at 0°, which I will then do with low variability. The resulting SDΨ is not, therefore, a valid measure of the stability of the target coordination (Wilson et al, 2005a,b; Snapp-Childs et al, 2011). My recent work has advocated for a new measure, proportion-time-on-target +/- 20° (PTT20). This summarises the stability of the requested coordination and has proven itself valid, highly effective and sensitive.

Here we tested 24 participants and had them move joysticks (covered so they were out of view) to produce either 0° or 180° in either Lissajous or coordination displays using either homologous or non-homologous muscles. We assessed stability with SDΨ and PTT20. With SDΨ, both egocentric and allocentric constraints both seemed to be playing a role in movement stability. With PTT20, vision dominated and muscle homology made no contribution. These results show that muscle homology may lead to more consistent coordinated movements (SDΨ) but not necessarily coordinated movements more stable at a target phase, which is best measured with PTT20. A pre-registered replication is currently underway to improve the evidence for this claim.

Uncovering the mechanisms governing coordination dynamics requires methods that account for the perception-action nature of those dynamics (coordination feedback) and measures that validly

assess the behaviour of interest (PTT20). This will all be discussed in the broader context of the ecological approach to coordinated rhythmic movement (see Golonka & Wilson, 2012).

References

Bingham, G.P. (2001). A perceptually driven dynamical model of rhythmic limb movement and bimanual coordination. Proceedings of the 23rd Annual Conference of the Cognitive Science Society, (pp. 75-79). Hillsdale, N.J., LEA Publishers.

Bingham, G.P. (2004). A perceptually driven dynamical model of bimanual rhythmic movement (and phase perception). Ecological Psychology, 16(1),45-53.

Bingham, G.P. (2004). Another timing variable composed of state variables: Phase perception and phase driven oscillators. In H. Hecht & G.J.P. Savelsbergh (Eds.) Theories of Time-to-Contact. Boston: MIT Press.

Golonka, S., & Wilson, A. D. (2012). Gibson’s ecological approach – a model for the benefits of a theory driven psychology. Avant, 3(2), 40-53.

Kovacs, A. J., Buchanan, J. J., & Shea, C. H. (2009). Using scanning trials to assess intrinsic coordination dynamics. Neuroscience letters, 455(3), 162-167.

Snapp-Childs, W., Wilson, A. D., & Bingham, G. P. (2011). The stability of rhythmic movement coordination depends on relative speed: The Bingham model supported. Experimental Brain Research, 215, 89-100.

Swinnen, S. P., Jardin, K., Meulenbroek, R., Dounskaia, N., & Hofkens-Van Den Brandt, M. (1997). Egocentric and allocentric constraints in the expression of patterns of interlimb coordination. Journal of Cognitive Neuroscience, 9(3), 348-377.

Wilson, A. D., Collins, D. R., & Bingham, G. P. (2005a) Perceptual coupling in rhythmic movement coordination – Stable perception leads to stable action. Experimental Brain Research, 164, 517-528.

Wilson, A. D., Collins, D. R., & Bingham, G. P. (2005b) Human movement coordination implicates relative direction as the information for relative phase. Experimental Brain Research, 165, 351-361.

Wilson, A. D., Snapp-Childs, W., Coates, R., & Bingham, G. P. (2010). Learning a coordinated rhythmic movement with task-appropriate coordination feedback. Experimental Brain Research, 205(4), 513-520.