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Studies on human finger tapping neural networks by phase transition curves

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Abstract

Generally, the phase resetting experiments can be used to investigate the behaviors of the stable biological oscillators (e.g. circadian rhythms, biochemical oscillators, pacemaker neurons, bursting neurons). Winfree found that there are two types of phase transition curves (PTC) in the phase resetting experiments of biochemical oscillations. The one is the curve with an average slope of unity (Type 1) and is obtained for the small magnitude of perturbation. The other curve is that with a zero average slope (Type 0) and is obtained for the large magnitude of perturbation. Previously, we explained these results mathematically by the homotopy theory. In this paper, some properties of the human finger tapping neural network are studied psychologically using PTC on the basis of above theoretical results: assuming that an oscillatory neural network controls the human finger tapping, we performed two kinds of phase resetting experiments on the finger tapping. In the first experiment, we showed that the PTC was available to estimate the degree of functional interaction between the finger tapping neural network and that which controls another task. Three tasks (rapid key-pushing, rapid voicing and pattern discrimination) were chosen as the perturbation of the phase resetting experiment. Analyzing shapes of PTCs, it was found that the interaction with the key-pushing network was the largest, and that with the pattern recognition network was the smallest of the three. In the second experiment, we modified the first task as perturbation of the phase resetting experiments to investigate further the interactions between the left and the right hand motor systems. Consequently the following results were revealed. First, shapes of PTCs are very different according as subject's experiences of finger tapping. Second, the type of PTC for some subjects changes from Type 0 to Type 1 by learning. Third, the PTC tends to become Type 0 for shorter tapping periods. Fourth, neither changes of motor loads (the necessary force to push the key) nor an alternation of the tapping hand and the key-pushing hand affects the shape of PTCs.

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Yamanishi, Ji., Kawato, M. & Suzuki, R. Studies on human finger tapping neural networks by phase transition curves. Biol. Cybernetics 33, 199–208 (1979). https://doi.org/10.1007/BF00337409

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