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预测水平平面任意平移加速度曲线的方向检测阈值。

Predicting direction detection thresholds for arbitrary translational acceleration profiles in the horizontal plane.

机构信息

Department of Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Spemannstraße 38, 72076, Tübingen, Germany.

出版信息

Exp Brain Res. 2011 Mar;209(1):95-107. doi: 10.1007/s00221-010-2523-9. Epub 2011 Jan 14.

Abstract

In previous research, direction detection thresholds have been measured and successfully modeled by exposing participants to sinusoidal acceleration profiles of different durations. In this paper, we present measurements that reveal differences in thresholds depending not only on the duration of the profile, but also on the actual time course of the acceleration. The measurements are further explained by a model based on a transfer function, which is able to predict direction detection thresholds for all types of acceleration profiles. In order to quantify a participant's ability to detect the direction of motion in the horizontal plane, a four-alternative forced-choice task was implemented. Three types of acceleration profiles (sinusoidal, trapezoidal and triangular) were tested for three different durations (1.5, 2.36 and 5.86 s). To the best of our knowledge, this is the first study which varies both quantities (profile and duration) in a systematic way within a single experiment. The lowest thresholds were found for trapezoidal profiles and the highest for triangular profiles. Simulations for frequencies lower than the ones actually measured predict a change from this behavior: Sinusoidal profiles are predicted to yield the highest thresholds at low frequencies. This qualitative prediction is only possible with a model that is able to predict thresholds for different types of acceleration profiles. Our modeling approach represents an important advancement, because it allows for a more general and accurate description of perceptual thresholds for simple and complex translational motions.

摘要

在之前的研究中,通过让参与者暴露于不同时长的正弦加速轮廓,已经测量并成功地对方向检测阈值进行建模。在本文中,我们提出的测量结果表明,阈值不仅取决于轮廓的时长,还取决于加速度的实际时间进程。该模型基于传递函数,能够预测所有类型的加速度轮廓的方向检测阈值,进一步解释了这些测量结果。为了量化参与者在水平面上检测运动方向的能力,我们实施了一个四择一的强制选择任务。对三种类型的加速度轮廓(正弦、梯形和三角形)进行了三种不同时长(1.5、2.36 和 5.86 秒)的测试。据我们所知,这是第一个在单个实验中系统地改变这两个量(轮廓和时长)的研究。梯形轮廓的阈值最低,三角形轮廓的阈值最高。低于实际测量频率的模拟预测会发生这种行为的变化:在低频下,正弦轮廓预计会产生最高的阈值。只有能够预测不同类型的加速度轮廓的阈值的模型才能实现这种定性预测。我们的建模方法是一个重要的进展,因为它允许对简单和复杂平移运动的感知阈值进行更一般和准确的描述。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef15/3035781/ee1b9175d6c6/221_2010_2523_Fig1_HTML.jpg

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