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Ruu Harn Cheng, Dirk Walther, Soojin Park; Concavity and convexity of conjoint surfaces underlie neural and behavioral categorization of scenes and objects. Journal of Vision 2018;18(10):140. doi: 10.1167/18.10.140.
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Scene recognition and object recognition are crucial for humans to interact with the world. Places and objects are processed differently and even in anatomically separate brain regions. However, little is known about how the brain triages visual input into the scene versus object processing stream. Places are often characterized by concave boundaries that enclose the local environment, whereas objects are typically encountered as individual entities bounded by convex conjoint surfaces. In this study, we ask whether concavity and convexity of conjoint surfaces might differentiate between scenes and objects. We hypothesize that visual cues of concavity would selectively activate scene-selective processes whereas cues of convexity would selectively activate object-selective processes. In Experiment 1, we created artificial images that vary parametrically in the angle at which two planar surfaces conjoin. There were seven stimulus conditions: three concave, three convex and one flat condition. Planar surfaces in the concave conditions converge in depth, whereas those in the convex conditions diverge in depth. Participants (N=13) viewed stimuli in blocks of 12s while performing a one-back repetition detection task in the fMRI scanner. We measured the univariate response of a scene-selective area (parahippocampal place area; PPA) and an object-selective area (lateral occipital complex; LOC). Consistent with our hypothesis, PPA is sensitive to changes in concavity but not convexity of conjoint surfaces. Conversely, LOC shows an overall greater response to convex than concave conditions. In Experiment 2, we created line drawings of the stimuli from Experiment 1 and asked 100 participants to behaviorally categorize these line drawings as scenes or objects. Consistent with our neural finding, participants categorized line drawings in concave conditions as scenes and those in convex conditions as objects. Together, our results show that concavity and convexity of conjoint surfaces underlie both neural and behavioral categorization of scenes and objects.
Meeting abstract presented at VSS 2018
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