In the present study, we investigated whether the perception of heading of linear self-motion can be explained by Maximum Likelihood Integration (MLI) of visual and non-visual sensory cues. MLI predicts smaller variance for multisensory judgments compared to unisensory judgments. Nine participants were exposed to visual, inertial, or visuala??inertial motion conditions in a moving base simulator, capable of accelerating along a horizontal linear track with variable heading. Visual random-dot motion stimuli were projected on a display with a 40?° horizontal ?? 32?° vertical field of view (FoV). All motion profiles consisted of a raised cosine bell in velocity. Stimulus heading was varied between 0 and 20?°. After each stimulus, participants indicated whether perceived self-motion was straight-ahead or not. We fitted cumulative normal distribution functions to the data as a psychometric model and compared this model to a nested model in which the slope of the multisensory condition was subject to the MLI hypothesis. Based on likelihood ratio tests, the MLI model had to be rejected. It seems that the imprecise inertial estimate was weighed relatively more than the precise visual estimate, compared to the MLI predictions. Possibly, this can be attributed to low realism of the visual stimulus. The present results concur with other findings of overweighing of inertial cues in synthetic environments.
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