A model of temporal scaling correctly predicts that motor timing improves with speed
Humans can perform complex motor movements at varying speeds. Here, the authors show that a recurrent neural network can be trained to exhibit temporal scaling obeying Weber’s law as well as validate a prediction of the model of improved precision of movements at faster speeds.
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2018
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/1735b53621ec48ce80e9bab83c18ff20 |
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