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Joshua B Julian, Alex T Keinath, Jack Ryan, Roy H Hamilton, Isabel A Muzzio, Russell A Epstein; Mechanisms for encoding navigational boundaries in the mammalian brain. Journal of Vision 2016;16(12):8. doi: 10.1167/16.12.8.
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© ARVO (1962-2015); The Authors (2016-present)
Thirty years of research suggests that environmental boundaries exert powerful control over navigational behavior, often to the exclusion of other navigationally-relevant cues, such as objects or visual surface textures. Here we present findings from experiments in mice and humans demonstrating the existence of specialized mechanisms for processing boundaries during navigation. In the first study, we examined the navigational behavior of disoriented mice trained to locate rewards in two chambers with geometrically identical boundaries, distinguishable based on the visual textures along one wall. We observed that although visual textures were used to identify the chambers, those very same cues were not used to disambiguate facing directions within a chamber. Rather, recovery of facing directions relied exclusively on boundary geometry. These results provide evidence for dissociable processes for representing boundaries and other visual cues. In a second line of work, we tested whether the human visual system contains neural regions specialized for processing of boundaries. Specifically, we tested the prediction that the Occipital Place Area (OPA) might play a critical role in boundary-based navigation, by extracting boundary information from visual scenes. To do so, we used transcranial magnetic stimulation (TMS) to interrupt processing in the OPA during a navigation task that required participants to learn object locations relative to boundaries and non-boundary cues. We found that TMS of the OPA impaired learning of locations relative to boundaries, but not relative to landmark objects or large-scale visual textures. Taken together, these results provide evidence for dedicated neural circuitry for representing boundary information.
Meeting abstract presented at VSS 2016
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