| Autor: |
Gori, Julien, Rioul, Olivier |
| Rok vydání: |
2018 |
| Předmět: |
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| Zdroj: |
Biological Cybernetics (2020), 114(6), 621-641 |
| Druh dokumentu: |
Working Paper |
| DOI: |
10.1007/s00422-020-00853-7 |
| Popis: |
Trajectories in human aimed movements are inherently variable. Using the concept of positional variance profiles, such trajectories are shown to be decomposable into two phases: In a first phase, the variance of the limb position over many trajectories increases rapidly; in a second phase, it then decreases steadily. A new theoretical model, where the aiming task is seen as a Shannon-like communication problem, is developed to describe the second phase: Information is transmitted from a source (determined by the position at the end of the first phase), to a destination (the movement's end-point) over a channel perturbed by Gaussian noise, with the presence of a noiseless feedback link. Information-theoretic considerations show that the positional variance decreases exponentially with a rate equal to the channel capacity C. Two existing datasets for simple pointing tasks are re-analyzed and observations on real data confirm our model. The first phase has constant duration and C is found constant across instructions and task parameters, which thus characterizes the participant's performance. Our model provides a clear understanding of the speed-accuracy tradeoff in aimed movements: Since the participant's capacity is fixed, a higher prescribed accuracy necessarily requires a longer second phase resulting in an increased overall movement time. The well-known Fitts' law is also recovered using this approach. |
| Databáze: |
arXiv |
| Externí odkaz: |
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