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International Conference on Complex Systems (ICCS2006)

Complexity of Human Movement Learning

Gottfried Mayer-Kress
Department of Kinesiology, Penn State University

Yeou-Teh Liu
Sports Science Institute, National Taiwan Normal University

Karl Newell
Department of Kinesiology, Penn State University

     Full text: Not available
     Last modified: March 31, 2006

Human movement is by far the most important channel to communicate and express the complexity of our brain activity. Whereas it has been possible recently to develop electro-magnetic interfaces to the brain (e.g. the thought translation device of Birbaumer’s group) their information transmission rate pales to the rate at which we can communicate our brain-state through coordinated activation of a vast collection of muscles in our body. The most common ones are related to speech but verbal communication only is a fraction of the information flow that we use every day. Eye muscles control gaze direction, facial expression, posture and gestures are other elements of communication that we use in our everyday life.
Our body of work attempts to build a general theoretical framework for using methods from complex systems to model how humans learn intricate coordinated movement patterns. We analyzed classical learning data and conducted a number of learning experiments involving movements at different levels of complexity. Following the complexity paradigm of complex systems of a fitness landscape, we integrate that paradigm with that of Waddington’s epigenetic landscape. This leads to a systematic framework for instructions to participants to seek the minimum of a learning landscape as their task goal.
Here we report the findings from several studies and discuss implications for the future direction of the study of human movement learning.

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