A linear sensorimotor transformation accounts for response range-dependent biases in human heading estimation
Accurate estimation of heading direction from optic flow is a crucial aspect of human spatial perception. Previous studies have shown that humans are typically biased in their estimates of heading directions, but the reported results are inconsistent. While some studies found that humans generally underestimate heading direction (central bias), others find the opposite, an overestimation of heading direction (peripheral bias). We conducted three psychophysical experiments showing that these conflicting findings do not reflect inherent differences in heading perception. Rather we found that they are caused by the different sizes of the response range that participants were allowed to utilize when reporting their estimates. Notably, we show that participants' heading estimates monotonically scale with the size of the response range, leading to underestimation for small and overestimation for large response ranges. Additionally, neither the speed profile of the optic flow pattern nor the response method (mouse vs. keyboard) significantly affected participants' estimates. Furthermore, we derived a Bayesian observer model to quantitatively account for participants' estimation behavior. The model assumes an efficient sensory encoding of heading direction according to the natural prior of freely behaving humans. In addition, the model incorporates a motor stage that linearly maps the percept to the reported estimate with a scaling factor that depends on the size of the response range. This perception-action model accurately predicts participants' estimates both in terms of mean and variance. Our findings underscore that human heading perception follows efficient Bayesian inference; differences in participants' reported estimates can be solely attributed to differences in linear mapping from percept to probe response.