Visual target detection in a distracting background relies on neural encoding of both visual targets and background

Luo, Cheng; Ding, Nai

doi:10.1016/j.neuroimage.2020.116870

Cited by 6 publications

(12 citation statements)

References 85 publications

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“…Therefore, the subsequent ERP analysis were conducted using the central centro-parietal electrodes (Cz, CPz, Pz, CP1, CP2). The choice of the central centro-parietal EEG electrodes in this study was consistent with that of previous ERP study on visual target detection (Luo and Ding, 2020).…”

Section: Erp Analysissupporting

confidence: 77%

“…The stimulus set for practicing was constructed by randomly selecting 20 patches from each type and randomly rotating each patch by 0, 90, 180, or 270 degrees once. In the testing phase, we employed the oddball paradigm commonly used in previous target detection studies (O'Connell et al, 2012;Luo and Ding, 2020) and constructed the stimulus set for testing using one random rotation of the remaining target patches and three random rotations of the remaining non-target patches, so the ratio of the number of target to non-target patches was 1:3 (600:1800).…”

Section: Stimulimentioning

confidence: 99%

“…Visual objects processing relies on the neural encoding of visual information from both target and background (Luo and Ding, 2020). The background surrounding a visual object has a significant impact on target detection and identification performance (Naber et al, 2012), even more so than the semantic category of the object itself (Hagen and Laeng, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…On the flip side, the visual background may be accompanied by task-irrelevant interferences, which often inevitably reduces the task performance (Theeuwes, 2004). Specifically, in visual target detection, the presence of a salient task-irrelevant background increased the false alarm rate and slowed down the speed for decision-making (Luo and Ding, 2020). In visual target classification, the performance for classify objects embedded in complex backgrounds (especially in semantically inconsistent backgrounds) was significantly lower than that for isolated objects (Davenport and Potter, 2004), which may be attributed to the increased difficulty of target-background splitting in complex scenes (Torralbo and Beck, 2008;Prass et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…Most previous studies have used synthetic or curated visual stimuli to investigate the top-down and bottom-up attentions in visual processing, such as embedding natural (Sun et al, 2011;Prass et al, 2013;Hagen and Laeng, 2016) or artificial (Smout et al, 2019;Luo and Ding, 2020) objects into different natural or artificial scenes, or adjusting images to various resolutions (Torralba, 2009;Barenholtz, 2014). Although these synthetic and curated stimuli can introduce a controlled amount of variation or difficulty to the task and allow the investigation of neural coding in relation to these factors (Cadieu et al, 2014), they are difficult to expose or maintain the contextual effects in real world, thus inevitably strips away the effects of some unknown but crucial factors in the native background.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

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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Section: Erp Analysissupporting

confidence: 77%

Section: Stimulimentioning

confidence: 99%