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首页> 外文期刊>Journal of vision >An object-tracking model that combines position and speed explains spatial and temporal responses in a timing task
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An object-tracking model that combines position and speed explains spatial and temporal responses in a timing task

机译:结合位置和速度的对象跟踪模型解释了计时任务中的空间和时间响应

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摘要

Many tasks require synchronizing our actions with particular moments along the path of moving targets. However, it is controversial whether we base these actions on spatial or temporal information, and whether using either can enhance our performance. We addressed these questions with a coincidence timing task. A target varying in speed and motion duration approached a goal. Participants stopped the target and were rewarded according to its proximity to the goal. Results showed larger reward for responses temporally (rather than spatially) equidistant to the goal across speeds, and this pattern was promoted by longer motion durations. We used a Kalman filter to simulate time and space-based responses, where modeled speed uncertainty depended on motion duration and positional uncertainty on target speed. The comparison between simulated and observed responses revealed that a single position-tracking mechanism could account for both spatial and temporal patterns, providing a unified computational explanation.
机译:许多任务需要使我们的动作与移动目标路径上的特定时刻保持同步。但是,是否将这些动作基于空间或时间信息,以及是否使用两者都可以提高我们的性能,都存在争议。我们通过巧合的定时任务解决了这些问题。速度和运动持续时间不同的目标已接近目标。参与者停止了目标,并根据其与目标的接近程度获得了奖励。结果表明,在速度上在时间上(而不是在空间上)与目标等距的响应具有更大的回报,并且这种模式是通过较长的运动时间来促进的。我们使用卡尔曼滤波器来模拟基于时间和空间的响应,其中建模的速度不确定性取决于运动持续时间以及目标速度上的位置不确定性。模拟和观察到的响应之间的比较表明,单个位置跟踪机制可以说明空间和时间模式,从而提供了统一的计算解释。

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