Demonstrations from computer vision, such as the recent example of successful navigation without generating any 3D map (Zhu et al, 2016), are likely to have a profound influence on hypotheses about the type of representation that the brain uses to when faced with similar tasks. The goal of work in my lab is to find psychophysical evidence to help discriminate between rival models of 3D vision. The critical division is between models based on 3D coordinate frames and those that use something more like a graph of views. I will present data from our virtual reality lab, where observers move freely and carry out simple tasks such as navigating to remembered locations or making judgements about the size, distance or direction of objects. We often manipulate the scene as participants move, e.g. expanding the world several-fold in all dimensions which participants fail to notice. In all cases, the data are difficult to explain under an assumption that the brain generates a single 3D reconstruction of the scene independent of the task. An alternative is that the brain stores something more like a graph of sensory states linked by actions (or, in fact, 'sensory+motivational' states, which is closely related to the embedding of sensory and goal information that Zhu et al adopt).
Zhu, Mottaghi, Kolve, Lim, Gupta, Fei-Fei, Farhadi (2016) https://arxiv.org/pdf/1609.05143v1.pdf
Andrew Glennerster studied medicine at Cambridge before doing his DPhil in Oxford in Experimental Psychology on human binocular stereopsis. He set up a virtual reality lab in the Physiology department in Oxford where he had Fellowships from the Medical Research Council and the Royal Society. He continues to work on 3D vision in moving observers at the University of Reading where he is a Professor in the School of Psychology and Clinical Language Sciences.