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Ideal observer analysis for continuous tracking experiments

机译:用于连续跟踪实验的理想观察者分析

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摘要

Continuous tracking is a newly developed technique that allows fast and efficient data acquisition by asking participants to “track” a stimulus varying in some property (usually position in space). Tracking is a promising paradigm for the investigation of dynamic features of perception and could be particularly well suited for testing ecologically relevant situations difficult to study with classical psychophysical paradigms. The high rate of data collection may be useful in studies on clinical populations and children, who are unable to undergo long testing sessions. In this study, we designed tracking experiments with two novel stimulus features, numerosity and size, proving the feasibility of the technique outside standard object tracking. We went on to develop an ideal observer model that characterizes the results in terms of efficiency of conversion of stimulus strength into responses, and identification of early and late noise sources. Our ideal observer closely modeled results from human participants, providing a generalized framework for the interpretation of tracking data. The proposed model allows to use the tracking paradigm in various perceptual domains, and to study the divergence of human participants from ideal behavior.
机译:连续跟踪是一种新开发的技术,它通过要求参与者 “跟踪” 在某些属性(通常在空间中的位置)变化的刺激来实现快速有效的数据采集。跟踪是研究感知动态特征的一种很有前途的范式,可能特别适合于测试经典心理物理学范式难以研究的生态相关情况。高数据收集率可能有助于对无法进行长时间测试的临床人群和儿童的研究。在这项研究中,我们设计了具有两个新刺激特征(数量和大小)的跟踪实验,证明了该技术在标准对象跟踪之外的可行性。我们继续开发了一个理想的观察者模型,该模型根据刺激强度转化为响应的效率以及识别早期和晚期噪声源来表征结果。我们理想的观察者对人类参与者的结果进行了密切建模,为跟踪数据的解释提供了一个通用框架。所提出的模型允许在各种感知领域使用跟踪范式,并研究人类参与者与理想行为的差异。

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