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

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.

Visual and vestibular perceptual thresholds each demonstrate better precision at specific frequencies and also exhibit optimal integration

“…Variations in threshold across frequencies indicate different filtering, i.e., that responses to different cues depend on current and past inputs being weighted differently. As with many other motion threshold studies (Benson et al 1986(Benson et al , 1989Butler et al 2010;Crane 2012a;Grabherr et al 2008;Haburcakova et al 2012;Kolev et al 1996;Roditi andCrane 2012a, 2012b;Soyka et al 2011;Valko et al 2012;Zupan and Merfeld 2008), motion stimuli were single cycles of sinusoidal acceleration with frequency f. Figure 2 shows the corresponding cosine bell velocity and sigmoidal displacement and demonstrates how the amplitudes of the three co-vary for a given frequency. While not a primary objective of this study, when compared across frequencies, this approach is sometimes used to separate the contributions of position, velocity, acceleration and higher-derivate cues.…”

“…A Gaussian cumulative distribution psychometric function defined by two parameters, sigma and bias, was fit to the data of each block, using a maximum likelihood fit (MATLAB Statistics Toolbox version 7.0) determined using a generalized linear model and probit link function (Haburcakova et al 2012;Zupan and Merfeld 2008). The Gaussian distribution was chosen (Wichmann and Hill 2001), as in every similar study of which we are aware (e.g., Butler et al 2010;MacNeilage et al 2010;Roditi and Crane 2012b;Soyka et al 2011), because it correctly fits the second-order statistics (i.e., variance of the underlying distribution). Although a logistic distribution may also provide an appropriate fit, the differences between the logistic and Gaussian distributions are small (Dobson and Barnett 2008) and inconsequential, and the most appropriate distribution cannot be determined without extensive data collection.…”

Directional Asymmetries and Age Effects in Human Self-Motion Perception

“…There have been several prior studies that have established vestibular perceptual thresholds of healthy humans (Walsh 1961;Clark 1967;Gundry 1978;Melvill Jones and Young 1978;Gianna et al 1996;Grabherr et al 2008;MacNeilage et al 2010;Mallery et al 2010;Soyka et al 2011). However, these studies have not provided two important details: possible effects of aging and possible directional asymmetries.…”

“…Vestibular reflexes including the VOR (Stefansson and Imoto 1986;Tian et al 2001), spinal reflexes (Liaw et al 2009), and VEMP (Nguyen et al 2010) also decline with age. Most prior studies of motion perception have focused on a population under age 40 (Walsh 1961;Benson et al 1986Grabherr et al 2008;MacNeilage et al 2010;Mallery et al 2010;Soyka et al 2011), but when older subjects were included, advanced age was associated with higher perceptual thresholds in fore-aft motion (Kingma 2005).…”

The MPI CyberMotion Simulator: A Novel Research Platform to Investigate Human Control Behavior

“…First of all, the simulator serves as an experimental platform for basic research into motion perception. For example, measurements of thresholds in response to different motion shapes can enhance our understanding of self-motion perception [17]. Also, the large motion range of the simulator allows for performing path integration experiments in three dimensions, such that assessments can be made as to whether path integration is similar between horizontal and vertical planes [18].…”