Researchers in the field of Coordination Dynamics aim to identify general laws of pattern formation in human movements rather than searching for a locus of movement pattern generation. This approach is inspired by ideas borne by the theory of Dynamic Systems and Self-organization. Over the last two decades a rhythmic movement paradigm has been the dominant experimental task constraint in this field, because, among other reasons, it allows a rather simple mathematical description of the movement system’s dynamics in terms of its phase. Another virtue is that it allows only few dynamic phenomena such as a small number of stationary phase states, transitions in between those and phase drift. Within this paradigm many effects have been successfully investigated including learning, attention, symmetry breaking, perception-action coupling, bimanual interference and many more [Zanone et al., 2000; Zaal & Bootsma, 2000; Temprado et al., 2002] (see [Jirsa & Kelso, 2004] for an overview of the current state-of-the-art).

Despite the obvious successes of the rhythmic coordination paradigm, it remains somewhat unsatisfactory that the scientific knowledge gained under this paradigm has not been transferred to the general field of movement sciences. At a recent symposium (NASPSPA 2001, St. Louis) on Schema-theory (with Richard Schmidt, Karl Newell, David Sherwood and Tim Lee), the major shortcoming of the Dynamical Systems approach has been referred to as the limitation to rhythmic movements. The main objective of this proposal is to overcome the limitation of the Dynamical Systems approach to a particular movement type and develop a theoretical foundation of coordination dynamics for arbitrary movements. The rhythmic movement paradigm shall be included as a subset in a wider class of movement phenomena including discrete movement tasks, the interference of multiple simultaneous movements, as well as the interaction between movements and environmental stimuli.

Viktor Jirsa (November 9th, 2005)

On the Neural Basis of Bimanual Coordination

Phase transitions of emergent spatiotemporal temporal patterns have been observed in the dynamics of effectors (fingers) associated with rhythmic bimanual coordination. Neural control of the effectors involves a crosstalk between various functional elements mediated via the underlying connectivity. In the current project we will develop a theoretical framework to understand the laws of coordination dynamics between the functional elements at the neural level for stable and unstable patterns of behavior. We perform EEG studies and search for the neural signatures of unimanual and bimanual coordination. The overarching goal of this project is to obtain theoretical constraints which identify candidate connection topologies and neural activation patterns, thereby capturing a lower dimensional dynamics of brain patterns which can be quantified and seek first experimental evidence.

In a general scenario any effector of behavior has an underlying neural control. The information processing occurs at several functional elements which connects the effectors and involves a degree of crosstalk and time delay. In this project, we investigate the several connection topologies under which the functional elements in the neural level influences the behavior for example a rhythmic motor task. We seek a lower dimensional description of the laws of structure and dynamics under varying connection scenarios between the effectors and establish a operational framework to quantify these laws.

Contact: Arpan Banerjee

References:

1. Dynamics of multifrequency coordination using parametric driving: theory and experiment Collins G. Assisi, Viktor K. Jirsa, J. A. Scott Kelso, Biological Cybernetics, Volume 93, Issue 1, Jul 2005
2. The excitator as a minimal model for the coordination dynamics of discrete and rhythmic movement VK Jirsa, JA Kelso - J Mot Behav, 2005
3. Local and global stabilization of coordination by sensory information PW Fink, VK Jirsa, P Foo, JAS Kelso - Experimental Brain Research, 2000
4. Recruitment of degrees of freedom stabilizes coordination PW Fink, JAS Kelso, VK Jirsa, GC de Guzman - J Exp Psychol Hum Percept Perform, 2000
5. The HKB model revisited: how varying the degree of symmetry controls dynamics A Fuchs, VK Jirsa - Human Movement Science, 2000
6. Connecting Cortical And Behavioral Dynamics: Bimanual Coordination VK Jirsa, A Fuchs, JAS Kelso - Neural Computation, 1998