Abstract

During natural vision, our brains are constantly exposed to complex, but regularly structured, environments. Real-world scenes are defined by typical part-whole relationships, where the meaning of the whole scene emerges from configurations of localized information present in individual parts of the scene. Such typical part-whole relationships suggest that information from individual scene parts is not processed independently, but that there are mutual influences between the parts and the whole during scene analysis. Here, we review recent research that used a straightforward, but effective approach to study such mutual influences: By dissecting scenes into multiple arbitrary pieces, these studies provide new insights into how the processing of whole scenes is shaped by their constituent parts and, conversely, how the processing of individual parts is determined by their role within the whole scene. We highlight three facets of this research: First, we discuss studies demonstrating that the spatial configuration of multiple scene parts has a profound impact on the neural processing of the whole scene. Second, we review work showing that cortical responses to individual scene parts are shaped by the context in which these parts typically appear within the environment. Third, we discuss studies demonstrating that missing scene parts are interpolated from the surrounding scene context. Bridging these findings, we argue that efficient scene processing relies on an active use of the scene's part-whole structure, where the visual brain matches scene inputs with internal models of what the world should look like.

Highlights

  • The ability to efficiently parse visual environments is critical for successful human behavior

  • We will discuss studies showing that when parts of a scene are missing, the visual brain uses typical part–whole structure to “fill in” information that is currently absent. Synthesizing these findings, we argue that the mutual influences between the whole scene and its constituent parts are well captured by a framework of scene processing in which the visual system actively matches visual inputs with internal models of the world

  • The recent findings establish that parts and wholes substantially influence each other during scene processing, which suggests that the efficiency of real-world scene vision lends itself to the exploitation of typical distributions of information across the environment

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Summary

INTRODUCTION

The ability to efficiently parse visual environments is critical for successful human behavior. We will discuss studies showing that when parts of a scene are missing, the visual brain uses typical part–whole structure to “fill in” information that is currently absent Synthesizing these findings, we argue that the mutual influences between the whole scene and its constituent parts are well captured by a framework of scene processing in which the visual system actively matches visual inputs with internal models of the world. The inversion effects indicate that scene-selective responses are fundamentally sensitive to the part–whole structure of scenes that we frequently experience in the world, rather than only to visual differences between intact and jumbled scenes These results reveal a strong sensitivity to scene structure for typically oriented scenes, it is unclear whether they index a richer representation of upright and structured scenes. This suggests that the scene structure available in intact and upright scenes facilitates the rapid readout of meaningful category information from the scene

Journal of Cognitive Neuroscience
CONCLUSION AND OUTLOOK
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