Behavioral dynamics and neural grounding of a dynamic field theory of multi-object tracking.
Behavioral dynamics and neural grounding of a dynamic field theory of multi-object tracking.
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DOI：
10.1142/s0219635212500227
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发表时间：
2012-09
影响因子：
1.8
通讯作者：
Perone S
中科院分区：
文献类型：
--
作者：
Spencer JP;Barich K;Goldberg J;Perone S
动态跟踪环境中移动对象的能力对于与本地环境进行高效交互至关重要。在这里，我们在多目标跟踪(MOT)任务的背景下考察了这种能力。已经提出了几种理论来解释人们如何跟踪运动对象；然而，这些先前的理论中只有一种是在实时过程模型中实现的，并且对象跟踪理论与使用ERPs和fMRI的日益增长的神经文献之间没有直接联系。在此，我们提出了一个建立在空间认知动态场理论基础上的目标跟踪神经过程模型。仿真表明，我们的动态场模型捕获了最近的行为数据，考察了速度和跟踪持续时间对MOT性能的影响。此外，我们表明，具有相同轨迹和参数的相同模型可以解释最近的ERP结果，该结果探索了人们如何将注意力资源分配给目标而不是分心者。我们通过将这一新的目标跟踪理论与其他最近的报道进行比较来得出结论，并讨论了如何在未来的工作中有效地探索该理论的神经基础。
The ability to dynamically track moving objects in the environment is crucial for efficient interaction with the local surrounds. Here, we examined this ability in the context of the multi-object tracking (MOT) task. Several theories have been proposed to explain how people track moving objects; however, only one of these previous theories is implemented in a real-time process model, and there has been no direct contact between theories of object tracking and the growing neural literature using ERPs and fMRI. Here, we present a neural process model of object tracking that builds from a Dynamic Field Theory of spatial cognition. Simulations reveal that our dynamic field model captures recent behavioral data examining the impact of speed and tracking duration on MOT performance. Moreover, we show that the same model with the same trajectories and parameters can shed light on recent ERP results probing how people distribute attentional resources to targets vs. distractors. We conclude by comparing this new theory of object tracking to other recent accounts, and discuss how the neural grounding of the theory might be effectively explored in future work.