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Behavioral Dynamics and Neural Grounding of a Dynamic Field Theory of Multi-Object Tracking

机译:多对象跟踪动态场理论的行为动态与神经接地

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摘要

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.
机译:动态跟踪环境中移动物体的能力对于与本地环境进行有效交互至关重要。在这里,我们在多对象跟踪(MOT)任务的上下文中检查了此功能。已经提出了几种理论来解释人们如何跟踪运动物体。但是,这些先前的理论中只有一种是在实时过程模型中实现的,并且对象跟踪的理论与使用ERPs和fMRI的神经文献的发展之间没有直接联系。在这里,我们介绍了基于空间认知的动态场理论建立的对象跟踪的神经过程模型。仿真表明,我们的动态字段模型捕获了最新的行为数据,检查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阐明最近的ERP结果,该结果探讨了人们如何将注意力资源分配给目标与干扰者。我们通过将这种新的对象跟踪理论与最近的其他研究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。

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