Self-motion sensitivity to visual yaw rotations in humans

Abstract

While moving through the environment, humans use vision to discriminate different self-motion intensities and to control their actions (e.g. maintaining balance or controlling a vehicle). How the intensity of visual stimuli affects self-motion perception is an open, yet important, question. In this study, we investigate the human ability to discriminate perceived velocities of visually induced illusory self-motion (vection) around the vertical (yaw) axis. Stimuli, generated using a projection screen (70 × 90 deg field of view), consist of a natural virtual environment (360 deg panoramic colour picture of a forest) rotating at constant velocity. Participants control stimulus duration to allow for a complete vection illusion to occur in every single trial. In a two-interval forced-choice task, participants discriminate a reference motion from a comparison motion, adjusted after every presentation, by indicating which rotation feels stronger. Motion sensitivity is measured as the smallest perceivable change in stimulus intensity (differential threshold) for eight participants at five rotation velocities (5, 15, 30, 45 and 60 deg/s). Differential thresholds for circular vection increase with stimulus velocity, following a trend well described by a power law with an exponent of 0.64. The time necessary for complete vection to arise is slightly but significantly longer for the first stimulus presentation (average 11.56 s) than for the second (9.13 s) and does not depend on stimulus velocity. Results suggest that lower differential thresholds (higher sensitivity) are associated with smaller rotations, because they occur more frequently during everyday experience. Moreover, results also suggest that vection is facilitated by a recent exposure, possibly related to visual motion after-effect.

Human discrimination of head-centred visual–inertial yaw rotations

“…While a large group of important studies focused on measuring the smallest perceivable motion intensity (absolute threshold) and its dependency on motion direction and frequency (cf. Guedry 1974 ), only few studies addressed how the smallest perceivable change in motion intensity (differential threshold, DT) depends on the intensity of the supra-threshold motion (Zaichik et al 1999 ; Mallery et al 2010 ; Naseri and Grant 2012 ; Nesti et al 2014a , 2015 ). DTs for different intensities of combined visual and inertial motion cues have (to the best of our knowledge) not been investigated yet, as previous studies focused on how visual and inertial sensory cues independently contribute to the discrimination of self-motion.…”

“…For example during locomotion, head rotation velocities can range from 0 to 400 °/s and even higher (Grossman et al 1988 ). Recent studies investigated human DTs for different motion intensities (Zaichik et al 1999 ; Mallery et al 2010 ; Naseri and Grant 2012 ; Nesti et al 2014a , 2015 ). This is commonly done by presenting a participant with two consecutive motion stimuli and iteratively adjusting their difference in motion intensity until discrimination performance converges to a specific, statistically derived level of accuracy (Gescheider 1997 ).…”

“…in darkness) for head-centred yaw rotations, forward–backward translations and vertical translations, respectively. Moreover, Nesti et al ( 2015 ) measured DTs for yaw self-motion perception as evoked by a purely visual stimulation (vection). These studies have shown that DTs can be described well by a power function of the general form Δ S = k * S a , where Δ S is the DT, S is the stimulus intensity and k and a are free parameters that depend on the type of motion investigated.…”

“…We then compare DTs measured for inertial motion cues (inertial-only condition) and visual–inertial motion cues (visual–inertial condition) with DTs measured for visual motion cues (visual-only condition). The latter data were collected in a previous experiment on vection during constant visual yaw rotations conducted in our laboratory (Nesti et al 2015 ). The present study is therefore designed to facilitate comparison of the data with Nesti et al ( 2015 ) and to allow testing of an MLI model that predicts the variance of the bimodal (visual–inertial) estimate based on the variance of the unimodal (visual-only and inertial-only) estimates.…”

Modelling visual-vestibular integration and behavioural adaptation in the driving simulator

“…Here, σ vis = 0.5 • /s was used, loosely based on Nesti et al (2015), who found that humans could discriminate between visual rotation stimuli of about 5 • /s, at which yaw rates typically peak in the present slalom task, if they were different by 1 • /s. The 0.5 • /s noise level gives 75 % correct direction classification, by a drift diffusion model such as in the intermittent control framework used here, of a 1 • /s stimuli if presented during 10 s, a similar duration of presentation as in Nesti et al (2015).…”