Modelling trajectories from choice reaching experiments through submovement decomposition
Modelling trajectories from choice reaching experiments through submovement decomposition
复制标题
通过子运动分解从选择到达实验的轨迹建模
DOI：
10.1167/jov.21.9.2711
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发表时间：
2021
影响因子：
1.8
通讯作者：
Heinke D
中科院分区：
文献类型：
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作者：
Heinke D
先前的研究表明，注意选择过程可以影响到达动作。这种效应的关键证据来自于颜色古怪任务中的到达轨迹。这些实验表明，到达曲率的调制与颜色引发有关，即与目标颜色切换的试验相比，颜色重复导致较小的曲率（例如，Song & Nakayama，2008; Moher & Song，2016）。根据这一证据，Heinke及其同事开发了一种受神经学启发的机器人模型，用于颜色启动（Strauss et al.，2015）。关键的是，该模型表明，注意力选择过程很容易泄漏到运动规划造成曲率效应。在这里，我们通过假设到达运动由子运动组成来捕捉这种泄漏效应（例如，Flash & Henis，1991; Friedman，Brown，& Finkbeiner，2013）。子运动被定义为离散的，弹道运动与预定的幅度，方向和持续时间之前，他们的发病。每个子运动都是直线轨迹，但它们的叠加可以创建曲线轨迹。Friedman等（2013）表明，知觉决策过程反映在子运动中。在这项研究中，我们证明了子运动提供了更深入的了解曲率效应。例如，我们发现，开关试验的特点是更多的子运动。因此，子运动分解反映了选择达成任务中的注意选择过程。未来的工作将旨在分析子运动的时间，例如，在什么时间点的子运动，创建弯曲的轨迹发生。这些时间应该反映了注意力选择的时间。
Previous studies have shown that reaching movements can be influenced by attentional selection processes. Critical evidence for this effect stems from reach trajectories in colour-oddity tasks. These experiments showed that the modulation of reach curvature is linked to colour priming—ie, colour repetitions lead to smaller curvatures compared to trials where the target colour switches (eg, Song & Nakayama, 2008; Moher & Song, 2016). Following this evidence, Heinke and colleagues developed a neurologically inspired robotics model for colour priming (Strauss et al., 2015). Critically, the model shows that attentional selection processes easily leak into movement planning causing the curvature effect. Here, we capture this leakage effect through the assumption that reaching movements are composed of submovements (eg, Flash & Henis, 1991; Friedman, Brown, & Finkbeiner, 2013). Submovements are defined as discrete, ballistic movements with predetermined amplitude, direction, and duration prior to their onset. Each submovement is a straight-line trajectory but their superposition can create a curved trajectory. Friedman et al.(2013) showed that perceptual decision-making processes are reflected in submovements. In this research, we demonstrate that submovements provide deeper insights into the curvature effect. For instance, we found that switch trials are characterized by more submovements. Hence, submovement decomposition reflected attentional selection processes in choice reaching tasks. Future work will aim to analyse the timing of submovements eg, at what point of time the submovements which create the curved trajectories occur. These timings should reflect the timing of attentional selection.