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Rumi Hisakata, Shin'ya Nishida, Alan Johnston; Adaptation to texture reveals a local metric underlying perceived size and distance. Journal of Vision 2015;15(12):771. doi: https://doi.org/10.1167/15.12.771.
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© ARVO (1962-2015); The Authors (2016-present)
How the visual system codes metric properties such as size and distance from the information present in the retinal image remains a puzzle. The degree of correlation in the firing of neurons can give some indication of receptive field separation but separation is not coded directly making judging the distance between points by integrating estimates of receptive field separation along a path between them problematic. We need a concept of local spatial scale to resolve this problem. Here we describe a novel and counterintuitive illusion that reveals an internal visual scale against which we determine the spatial properties of objects. In the experiment, observers adapted to dense dot texture and reported on the size of ring that was presented in the same location as the adapting texture as compared to a ring presented in an unadapted field. The perceived size of the ring shrank by approximately 15% after adaptation and the magnitude of the shrinkage depended on the density of texture. Furthermore, we found that this shrinkage not only occurred for geometric figures but also for the perceived distance between two dots. Counterintuitively, the shrinkage coincides with a reduction in apparent density of more sparse dot textures presented in the same adapted location. This new adaptation effect is difficult to explain on a texture or size channel model and shows that the human visual system has a malleable internal metric against which the spatial size or separation of objects is judged and this scale is influenced by adaptation to dense texture. As the underlying scale expands, as revealed though the expanding texture, the apparent size and distance of geometric objects appear compressed. Thus size is coded relative to the metric. This internal metric is an essential first step in processing the geometric properties objects.
Meeting abstract presented at VSS 2015
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