Attention scales according to inferred real-world object size

Collegio, Andrew; Nah, Joseph; Scotti, Paul S.; Shomstein, Sarah

doi:10.1038/s41562-018-0485-2

Cited by 35 publications

(18 citation statements)

References 37 publications

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“…Second, preparatory activity may be situationally invariant [19] . For example, preparatory activity may reflect a canonical (e.g., real-world) size of the target object, rather than its predicted -and variable -retinal image size [20,21] . Third, preparatory activity may incorporate the expected retinal size of the target object given the current viewing distance (i.e., more distant objects will produce a smaller retinal image).…”

Section: Introductionmentioning

confidence: 99%

Preparatory attention incorporates contextual expectations

Gayet

2021

Preprint

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Humans are remarkably proficient at finding objects within a complex visual world. Current theories of attentional selection propose that this ability is mediated by target-specific preparatory activity in visual cortex, biasing visual processing in favor of the target object. In real-world situations, however, the retinal image that any object will produce is unknown in advance; its size, for instance, varies dramatically with the object's distance from the observer. Using fMRI, we show that preparatory activity is systematically modulated by expectations derived from scene context. Human participants searched for objects at different distances in scenes. Activity patterns in object-selective cortex during search preparation (while no objects were presented), resembled activity patterns evoked by viewing targets object in isolation. Crucially, this preparatory activity was modulated by distance, reflecting the predicted retinal image of the object at each distance. These findings reconcile current theories of attentional selection with the challenges of real-world vision.

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Section: Introductionmentioning

confidence: 99%

Preparatory attention incorporates contextual expectations

Gayet

2021

Preprint

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“…Therefore, although a real car and a toy car share similar visual appearances, actions on these two objects are completely different ( 8 ). Further, the feature of objects’ real-world size also provides important information for high-level cognitive processes, such as attention ( 33 ), numerical perceptions ( 34 ), and semantic knowledge ( 35 ). In short, our finding that the feature of objects’ real-world size served as an axis of object space thus may greatly expand our understanding of object recognition from the angle of vision for perception to a novel viewpoint of vision for action.…”

Section: Discussionmentioning

confidence: 99%

Real-world size of objects serves as an axis of object space

Huang

Song

Liu

2021

Preprint

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Our mind can represent various objects from the physical world metaphorically into an abstract and complex high-dimensional object space, with a finite number of orthogonal axes encoding critical object features. Previous fMRI studies have shown that the middle fusiform sulcus in the ventral temporal cortex separates the real-world small-size map from the large-size map. Here we asked whether the feature of objects' real-world size constructed an axis of object space with deep convolutional neural networks (DCNNs) based on three criteria of sensitivity, independence and necessity that are impractical to be examined altogether with traditional approaches. A principal component analysis on features extracted by the DCNNs showed that objects' real-world size was encoded by an independent component, and the removal of this component significantly impaired DCNN's performance in recognizing objects. By manipulating stimuli, we found that the shape and texture of objects, rather than retina size, co-occurrence and task demands, accounted for the representation of the real-world size in the DCNNs. A follow-up fMRI experiment on humans further demonstrated that the shape, but not the texture, was used to infer the real-world size of objects in humans. In short, with both computational modeling and empirical human experiments, our study provided the first evidence supporting the feature of objects' real-world size as an axis of object space, and devised a novel paradigm for future exploring the structure of object space.

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“…When examining familiar landmarks, Epstein et al (2007) found that the PPA responds more strongly to landmarks than to other types objects, suggesting the space around the landmark is represented. More recently, researchers found a connection between an object and the space surrounding it (Collegio et al, 2019;Mullally & Maguire, 2011, 2013. Mullally and Maguire (2013) demonstrated that certain objects (referred to as space-defining objects) evoked depictions of the surrounding three-dimensional space (e.g., oak bed) when they were either viewed or imagined in isolation.…”

Section: Navigationmentioning

confidence: 99%

Scene Perception

Castelhano

Williams

2021

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Visual cognitive processes have traditionally been examined with simplified stimuli, but generalization of these processes to the real world is not always straightforward. Using images, computer-generated images, and virtual environments, researchers have examined processing of visual information in the real world.Although referred to as scene perception, this research field encompasses many aspects of scene processing. Beyond the perception of visual features, scene processing is fundamentally influenced and constrained by semantic information as well as spatial layout and spatial associations with objects. In this Element, we will present recent advances in how scene processing occurs within a few seconds of exposure, how scene information is retained in the long term, and how different tasks affect attention in scene processing.By considering the characteristics of real-world scenes, as well as different time windows of processing, we can develop a fuller appreciation of the research that falls under the wider umbrella of scene processing.

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Attention scales according to inferred real-world object size

Cited by 35 publications

References 37 publications

Preparatory attention incorporates contextual expectations

Preparatory attention incorporates contextual expectations

Real-world size of objects serves as an axis of object space

Scene Perception

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