Alessandro Nesti

To successfully perform daily activities such as maintaining posture or running, humans need to be sensitive to self-motion over a large range of motion intensities. How the intensity of the motion stimuli affects self-motion perception is an open, yet important, question. We conducted an experimental campaign to investigate how the human ability to discriminate self-motion depends on motion intensity for upward and downward translations in darkness and for horizontal head-centred rotations in presence of visual-only, inertial-only and visual-inertial motion stimuli. We found that differential thresholds, i.e. the smallest detectable change in stimulus intensity, increase with stimulus intensity following a trend well-described by a power function [1,2]. Moreover, combining visual and inertial stimuli does not lead to improved self-motion sensitivity over the investigated range of yaw rotations. We further observed that the time necessary for a visual-only stimulus to evoke a compelling self-motion illusion is independent from stimulus intensity and facilitated by recent exposure [2].

Figure: Differential thresholds for head centered yaw rotations.

Figure: Inside of the cabin of the MPI CyberMotion Simulator. In a driving experiment, the driver steers a virtual car through a curve using a forcefeedback steering wheel.

In driving simulation, simulator tilt is used to reproduce linear acceleration. In order to feel realistic, this tilt is performed at a rate below the tilt-rate detection threshold, which is usually assumed constant. However, it is known that many factors affect the threshold, like visual information, simulator motion in additional directions, or active vehicle control. We investigated the effect of these factors on roll-rate detection threshold during simulated curve driving [3]. Results showed that roll-rate perception in vehicle simulation is affected by the presence of motion in additional directions. Moreover, an active control task seems to increase the detection threshold, i.e. impair motion sensitivity, but with large individual differences. We hypothesize that this is related to the level of immersion during the task.

3. WABS: PERCEPTION-BASED MOTION SIMULATION

Within the project WABS ("Wahrnehmungsbasierte Bewegungssimulation") we developed an alternative approach to motion cueing. Motion cueing is the process of converting a desired physical motion (e.g. from a vehicle model) into commands that are sent to the motion simulator. This conversion is done by a so-called Motion Cueing Algorithm (MCA).The WABS project is based on the idea that motion cueing can be improved by including novel insights in human self-motion perception, obtained from fundamental motion perception studies, in the MCAs. This "perception-based motion cueing" approach allows for exploiting the limitations and ambiguities of the human perceptual system.

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To expand our simulator fleet, we acquired and installed a new motion simulator consisting of a hexapod motion system. I supported the acquisition process and developed the software interface, including the experimental framework that was used for several research projects (from September 2015 onwards).

Figure: Artistic representation of the graphical user interface (GUI), the software and the motion simulator

While moving through the environment, our central nervous system accumulates sensory information over time to provide an estimate of our self-motion, allowing for completing crucial tasks such as maintaining balance. However, little is known on how the duration of the motion stimuli influences our performances in a self-motion discrimination task. We studied the human ability to discriminate intensities of sinusoidal (0.5 Hz) self-rotations around the vertical axis (yaw) for four different stimulus durations (1, 2, 3 and 5 s) in darkness. We found that discrimination performances increase with stimulus duration [4], suggesting that the central nervous system accumulates sensory information on self-motion over time. Observed trends in differential thresholds are consistent with predictions based on a drift diffusion model with leaky integration of sensory evidence.

Figure: Experimentally measured DTs (red circles) are well described by a DDM that includes a leaky integration term (blue line).

The fundamental research question of how physical and perceived stimuli are related to each other fascinates neuroscientists since the seminal works of Weber and, later on, of Fechner and Stevens. In the research field of self-motion perception, important steps towards this goal have been recently achieved through a series of studies that quantified the human ability to discriminate self-movements for a wide range of motion intensities [1], [2]. However, this does not yet allow to univocally define the “psychophysical function” relating physical and perceived motion intensity, since changes in discrimination performances can be due to nonlinearities and/or to stimulus-dependent noisein the perceptual process. In this project we combine a “Magnitude Estimation” (ME) task and a “Magnitude Discrimination” (MD) task to gain insight into both the shape and the noise of the psychophysical function. In the ME task, 10 participants experience several 1s long linear translations of different intensities (0 – 2 m/s²) and assign them a numerical estimate that reflects the intensity of the evoked motion sensation. In the MD task, the smallest detectable change between two lateral translations of different intensity (Differential Threshold, DT) will be measured for 10 participants. Preliminary analyses show that both magnitude estimates and DTs increase with motion intensity, and that measured DTs are overall smaller than predictions based on magnitude estimates alone.