The Time-Course of Ultrarapid Categorization: The Influence of Scene Congruency and Top-Down Processing

Vanmarcke, Steven; Calders, Filip; Wagemans, Johan

doi:10.1177/2041669516673384

Cited by 16 publications

(10 citation statements)

References 79 publications

(145 reference statements)

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“…In turn, the higher scrutiny used for Sure level responses moves this threshold to higher representational nodes (which potentially requires different or more detailed visual information) leading to more time to detect targets. This line of explanation also fits with the hypothesis of flexible use of spatial frequency information, which suggests that different spatial scales are linked to specific stimulus types or in this case stimulus types or representational hubs (Mack & Palmeri, 2015;Mermillod, Guyader, & Chauvin, 2005;Oliva & Schyns, 1997;Vanmarcke, Calders, & Wagemans, 2016). Here, we expand previous findings by providing evidence that this flexibility also applies to different response certainties.…”

Section: Discussionsupporting

confidence: 88%

Flexibility of emerging face categorization at different levels of abstraction

Santo

Wagemans

2021

Journal of Vision

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Categorization of visual stimuli at different levels of abstraction relies on the encoding of relevant diagnostic features present at different spatial scales. We used the Eidolon Factory, an image-manipulation algorithm that introduces random disarray fields across spatial scales, to study how such a process flexibly combines perceptual information to perform successful categorization depending on task demands. Images of animal faces, human faces, and everyday objects were disarrayed coherently (random fields correlated) or incoherently (random fields randomized) to create a family of 50 eidolons per stimulus image with increasing disarray. Participants (N = 243) viewed each family of eidolons in a smooth sequence from maximum disarray to no disarray and performed a category verification task either at the superordinate (any face type) or basic (human face only) levels at two levels of uncertainty: participants in one group used their gut feeling to respond, whereas another group had to be sure of their decision. When participants used their gut feeling to respond, we observed a superordinate-level advantage. When they were sure of their response, we observed a basic-level advantage. Coherently disarrayed sequences impaired target detection compared to incoherently disarrayed sequences for both levels of response certainty. Furthermore, participants' sensitivity in the Any Face condition increased when they observed coherently disarrayed sequences and had to be sure of their response. These results suggest that the visual system does not strictly adhere to feedforward processing but flexibly adjusts to the relevant perceptual information depending on task context.

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Section: Discussionsupporting

confidence: 88%

Flexibility of emerging face categorization at different levels of abstraction

Santo

Wagemans

2021

Journal of Vision

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“…Using a forced-choice saccadic task, Wu et al ( 2014 ) found that humans can accurately perform superordinate level categorization at 120 ms, while the accuracy of basic level categorization is around chance-level. Although Mack and Palmeri ( 2015 ) challenged the rapid presentation paradigm for studying the processing order of categorization levels, studies done by Poncet and Fabre-Thorpe ( 2014 ) and Vanmarcke et al ( 2016 ) showed that the advantage of superordinate level is not affected by the stimulus duration (25–500 ms) and diversity. Also, Praß et al ( 2013 ) showed that the background context and animacy have no effect on the superordinate level advantage.…”

Section: Introductionmentioning

confidence: 99%

Object Categorization in Finer Levels Relies More on Higher Spatial Frequencies and Takes Longer

Ashtiani¹,

Kheradpisheh²,

Masquelier³

et al. 2017

Front. Psychol.

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The human visual system contains a hierarchical sequence of modules that take part in visual perception at different levels of abstraction, i.e., superordinate, basic, and subordinate levels. One important question is to identify the “entry” level at which the visual representation is commenced in the process of object recognition. For a long time, it was believed that the basic level had a temporal advantage over two others. This claim has been challenged recently. Here we used a series of psychophysics experiments, based on a rapid presentation paradigm, as well as two computational models, with bandpass filtered images of five object classes to study the processing order of the categorization levels. In these experiments, we investigated the type of visual information required for categorizing objects in each level by varying the spatial frequency bands of the input image. The results of our psychophysics experiments and computational models are consistent. They indicate that the different spatial frequency information had different effects on object categorization in each level. In the absence of high frequency information, subordinate and basic level categorization are performed less accurately, while the superordinate level is performed well. This means that low frequency information is sufficient for superordinate level, but not for the basic and subordinate levels. These finer levels rely more on high frequency information, which appears to take longer to be processed, leading to longer reaction times. Finally, to avoid the ceiling effect, we evaluated the robustness of the results by adding different amounts of noise to the input images and repeating the experiments. As expected, the categorization accuracy decreased and the reaction time increased significantly, but the trends were the same. This shows that our results are not due to a ceiling effect. The compatibility between our psychophysical and computational results suggests that the temporal advantage of the superordinate (resp. basic) level to basic (resp. subordinate) level is mainly due to the computational constraints (the visual system processes higher spatial frequencies more slowly, and categorization in finer levels depends more on these higher spatial frequencies).

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“…The achievement of meaningful contextual processing relies on the separation of target and background (Vanmarcke et al, 2016). Complex native scenes may provide more attention-guiding cues, but salient scene contents also increases the difficulty to target-background separation, so its negative effect on target processing may overwhelm the positive effect of incremented semantic cues.…”

Section: Discussionmentioning

confidence: 99%

How Native Background Affects Human Performance in Real-World Visual Object Detection: An Event-Related Potential Study

et al. 2021

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Visual processing refers to the process of perceiving, analyzing, synthesizing, manipulating, transforming, and thinking of visual objects. It is modulated by both stimulus-driven and goal-directed factors and manifested in neural activities that extend from visual cortex to high-level cognitive areas. Extensive body of studies have investigated the neural mechanisms of visual object processing using synthetic or curated visual stimuli. However, synthetic or curated images generally do not accurately reflect the semantic links between objects and their backgrounds, and previous studies have not provided answers to the question of how the native background affects visual target detection. The current study bridged this gap by constructing a stimulus set of natural scenes with two levels of complexity and modulating participants' attention to actively or passively attend to the background contents. Behaviorally, the decision time was elongated when the background was complex or when the participants' attention was distracted from the detection task, and the object detection accuracy was decreased when the background was complex. The results of event-related potentials (ERP) analysis explicated the effects of scene complexity and attentional state on the brain responses in occipital and centro-parietal areas, which were suggested to be associated with varied attentional cueing and sensory evidence accumulation effects in different experimental conditions. Our results implied that efficient visual processing of real-world objects may involve a competition process between context and distractors that co-exist in the native background, and extensive attentional cues and fine-grained but semantically irrelevant scene information were perhaps detrimental to real-world object detection.

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The Time-Course of Ultrarapid Categorization: The Influence of Scene Congruency and Top-Down Processing

Cited by 16 publications

References 79 publications

Flexibility of emerging face categorization at different levels of abstraction

Flexibility of emerging face categorization at different levels of abstraction

Object Categorization in Finer Levels Relies More on Higher Spatial Frequencies and Takes Longer

How Native Background Affects Human Performance in Real-World Visual Object Detection: An Event-Related Potential Study

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