Learning-Dependent Changes in Brain Responses While Learning to Break Camouflage: A Human fMRI Study

Streeb, Nicole; Chen, Xin; Hegdé, Jay

doi:10.1167/12.9.1131

Cited by 2 publications

(9 citation statements)

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“…This issue is highly significant in real-world situations. For instance, our finding that naive subjects, regardless of whether or not they have any a priori aptitude for visual pattern recognition, can be trained to detect camouflaged targets even upon a very brief viewing (Chen & Hegdé, 2012a ); also see (Chen & Hegdé, 2012b ; Streeb et al, 2012 ) is potentially applicable to real-world combat situations. However, merely being able to judge, no matter how accurately, that the given combat scene contains a target is not very useful to a sniper under real-world combat conditions if he/she is unable to also accurately tell where the target is.…”

Section: Significancementioning

confidence: 94%

“…The localization issue is also significant from a more purely scientific point of view, especially given the fact that expert subjects perform our camouflage-breaking task accurately even when there is no physical target to localize, i.e., when the scene did not contain a physical target object, but simply had the overall statistical properties of images that did [see Fig. 4 of (Chen & Hegdé, 2012a ); also see (Chen & Hegdé, 2012b ; Streeb et al, 2012 )]. Similar findings have been reported in breast cancer screening, where expert radiologists can accurately distinguish mammograms with versus without a lesion even when there is no visible lesion to localize (Brennan et al, 2018 ; Evans et al, 2016 ).…”

Section: Significancementioning

confidence: 96%

“…Subjects were provided feedback after their response, which served to implicitly and retroactively label the image as one in which the target was present or absent. Importantly, subjects were not told what to learn or what the target object was, nor shown the target in isolation (Chen & Hegdé, 2012b ; Streeb et al, 2012 ). Over several hundred trials (depending on the subject), the subjects’ performance improved to highly significant levels.…”

Section: Significancementioning

confidence: 99%

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Expert camouflage-breakers can accurately localize search targets

et al. 2021

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Camouflage-breaking is a special case of visual search where an object of interest, or target, can be hard to distinguish from the background even when in plain view. We have previously shown that naive, non-professional subjects can be trained using a deep learning paradigm to accurately perform a camouflage-breaking task in which they report whether or not a given camouflage scene contains a target. But it remains unclear whether such expert subjects can actually detect the target in this task, or just vaguely sense that the two classes of images are somehow different, without being able to find the target per se. Here, we show that when subjects break camouflage, they can also localize the camouflaged target accurately, even though they had received no specific training in localizing the target. The localization was significantly accurate when the subjects viewed the scene as briefly as 50 ms, but more so when the subjects were able to freely view the scenes. The accuracy and precision of target localization by expert subjects in the camouflage-breaking task were statistically indistinguishable from the accuracy and precision of target localization by naive subjects during a conventional visual search where the target ‘pops out’, i.e., is readily visible to the untrained eye. Together, these results indicate that when expert camouflage-breakers detect a camouflaged target, they can also localize it accurately.

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Section: Significancementioning

confidence: 94%

Section: Significancementioning

confidence: 96%

Section: Significancementioning

confidence: 99%

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Expert camouflage-breakers can accurately localize search targets

et al. 2021

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“…That is, once the subjects learn what the background ‘looks like’, they can tell if there is an object in a given scene that does not ‘belong’ in the scene. A second, interrelated property is that the improvement in camouflage-breaking performance transfers very well across the targets , but poorly across backgrounds [ 27 , 29 ]. Thus, when the subjects are trained to a criterion using images in which both the target and background had a given type of texture (e.g., ‘foliage’, see Figure 1 ) and their camouflage-breaking performance is tested using the same background texture (i.e., ‘trained texture’), their performance remains high.…”

Section: Experiments 1: Characterization Of the Relationship Between ...mentioning

confidence: 99%

“…In our previous studies on perceptual learning that used a two-alternative forced choice (2AFC) task paradigm, we reported that prior to camouflage training, a majority of the subject’s incorrect responses are attributable to false alarms (or false positives), where the subjects mistake image regions with high visual saliency for targets [ 27 , 28 , 29 , 37 ]. During successful camouflage training, the proportion of false alarms tends to decrease systematically, thus contributing to the improvement in performance as measured by d’ [ 27 , 28 , 29 , 37 ].…”

Section: Experiments 1: Characterization Of the Relationship Between ...mentioning

confidence: 99%

Satisfaction of Search Can Be Ameliorated by Perceptual Learning: A Proof-of-Principle Study

Park

Branch

Hegdé

2022

Vision

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When searching a visual image that contains multiple target objects of interest, human subjects often show a satisfaction of search (SOS) effect, whereby if the subjects find one target, they are less likely to find additional targets in the image. Reducing SOS or, equivalently, subsequent search miss (SSM), is of great significance in many real-world situations where it is of paramount importance to find all targets in a given image, not just one. However, studies have shown that even highly trained and experienced subjects, such as expert radiologists, are subject to SOS. Here, using the detection of camouflaged objects (or camouflage-breaking) as an illustrative case, we demonstrate that when naïve subjects are trained to detect camouflaged objects more effectively, it has the side effect of reducing subjects’ SOS. We tested subjects in the SOS task before and after they were trained in camouflage-breaking. During SOS testing, subjects viewed naturalistic scenes that contained zero, one, or two targets, depending on the image. As expected, before camouflage-training, subjects showed a strong SOS effect, whereby if they had found a target with relatively high visual saliency in a given image, they were less likely to have also found a lower-saliency target when one existed in the image. Subjects were then trained in the camouflage-breaking task to criterion using non-SOS images, i.e., camouflage images that contained zero or one target. Surprisingly, the trained subjects no longer showed significant levels of SOS. This reduction was specific to the particular background texture in which the subjects received camouflage training; subjects continued to show significant SOS when tested using a different background texture in which they did not receive camouflage training. A separate experiment showed that the reduction in SOS was not attributable to non-specific exposure or practice effects. Together, our results demonstrate that perceptual expertise can, in principle, reduce SOS, even when the perceptual training does not specifically target SOS reduction.

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Learning-Dependent Changes in Brain Responses While Learning to Break Camouflage: A Human fMRI Study

Cited by 2 publications

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Expert camouflage-breakers can accurately localize search targets

Expert camouflage-breakers can accurately localize search targets

Satisfaction of Search Can Be Ameliorated by Perceptual Learning: A Proof-of-Principle Study

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