Rare targets are less susceptible to attention capture once detection has begun

Hon, Nicholas; Ng, Gavin; Chan, Gerald

doi:10.3758/s13423-015-0921-5

Cited by 3 publications

(3 citation statements)

References 29 publications

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“…Much of the work on this target probability effect has focused on unearthing its locus, with several proposals implicating perceptual (Dykes & Pascal, 1981;Jabar & Anderson, 2015;Lau & Huang, 2010;Menneer, Donnelly, Godwin, & Cave, 2010) and response stages (Fleck & Mitroff, 2007). Recently, though, the effect has been demonstrated to have an attentional locus (Hon, Ng, & Chan, 2016;Hon & Tan, 2013), with lower probability targets being disproportionately affected by attentional manipulations even when response and perceptual considerations were held constant. In many studies of the target probability effect, observers are not informed beforehand of the probability values used.…”

Section: Introductionmentioning

confidence: 99%

Learning in the Target Prevalence Effect

Hon

Jabar

2018

Perception

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Rare or low prevalence targets are detected less well than counterparts that occur with higher probability. It stands to reason, though, that before such a deficit is apparent, information about a given target's probability of occurrence must be apprehended. In this study, we investigated how much target experience is necessary for target probabilities to be fully acquired and established within mental task representations. A central finding was that different target probability values required approximately the same amount of target sampling to learn. This was true whether learning about target probabilities from a naive start-point (Experiment 1) or when recalibrating from one probability value to another (Experiment 2). We discuss these findings in relation to how mental task representations are modified when new task-relevant information is received and the attentional consequences of such changes.

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Section: Introductionmentioning

confidence: 99%

Learning in the Target Prevalence Effect

Hon

Jabar

2018

Perception

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“…Selective attention makes modalities generate attention demands, and RSE will be affected by these attention demands (Pollmann & Zaidel, 1999). Studies have shown that the unimodal target probability can change attention demands (Hon et al, 2016; Hon & Tan, 2013), which may explain why MRE varies with unimodal target probabilities in modal-based selective attention. Overall, the modality dominance with modal-based selective attention and unimodal target probability manipulation can induce significant RSE.…”

Section: Discussionmentioning

confidence: 99%

Modal-based attention modulates the redundant-signals effect: Role of unimodal target probability

Wang

Xing

et al. 2022

Perception

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Multisensory integration includes two behavioral manifestations: the modality dominance effect and the redundant-signals effect (RSE). RSE is a multisensory improvement effect in which individuals respond more quickly and accurately to bimodal audiovisual (AV) targets than to unimodal auditory (A) or visual (V) targets. Previous studies have confirmed that RSE is the product of modality interactions between different modalities. The goal of this study was to systematically investigate the effects of the modality dominance manipulated by modal-based attention and unimodal target probability on RSE. The results showed that when paying attention to both the A and V modalities (Exp. 1), RSE was not significantly different between unimodal target probabilities. When selectively paying attention to the A modality (Exp. 2A), RSE was also not significantly different between unimodal target probabilities. However, when selectively paying attention to the V modality (Exp. 2B), the magnitude of RSE showed a significant decreasing trend with the increasing probability of V targets. Our study is the first to reveal that the unimodal target probability significantly modulates RSE in visual selective attention, and this modulatory effect of the unimodal target probability on RSE is opposite to the modulatory effect on the modality dominance effect.

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“…Although questionable, we decided to include less noise stimuli in the NVA condition than target words in the VA condition to minimize the allocation of attention to word stimuli in the NVA condition. Indeed, it has been suggested that low-probability targets involve more attentional demands and are less sensitive to attentional capture compared with high-probability targets (Hon, Ng, & Chan, 2016;Hon & Tan, 2013).…”

Section: Experimental Paradigmmentioning

confidence: 99%

Tracking the Effects of Top–Down Attention on Word Discrimination Using Frequency-tagged Neuromagnetic Responses

Niesen

Ghinst

Bourguignon

et al. 2020

Journal of Cognitive Neuroscience

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Discrimination of words from nonspeech sounds is essential in communication. Still, how selective attention can influence this early step of speech processing remains elusive. To answer that question, brain activity was recorded with magnetoencephalography in 12 healthy adults while they listened to two sequences of auditory stimuli presented at 2.17 Hz, consisting of successions of one randomized word (tagging frequency = 0.54 Hz) and three acoustically matched nonverbal stimuli. Participants were instructed to focus their attention on the occurrence of a predefined word in the verbal attention condition and on a nonverbal stimulus in the nonverbal attention condition. Steady-state neuromagnetic responses were identified with spectral analysis at sensor and source levels. Significant sensor responses peaked at 0.54 and 2.17 Hz in both conditions. Sources at 0.54 Hz were reconstructed in supratemporal auditory cortex, left superior temporal gyrus (STG), left middle temporal gyrus, and left inferior frontal gyrus. Sources at 2.17 Hz were reconstructed in supratemporal auditory cortex and STG. Crucially, source strength in the left STG at 0.54 Hz was significantly higher in verbal attention than in nonverbal attention condition. This study demonstrates speech-sensitive responses at primary auditory and speech-related neocortical areas. Critically, it highlights that, during word discrimination, top–down attention modulates activity within the left STG. This area therefore appears to play a crucial role in selective verbal attentional processes for this early step of speech processing.

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Rare targets are less susceptible to attention capture once detection has begun

Cited by 3 publications

References 29 publications

Learning in the Target Prevalence Effect

Learning in the Target Prevalence Effect

Modal-based attention modulates the redundant-signals effect: Role of unimodal target probability

Tracking the Effects of Top–Down Attention on Word Discrimination Using Frequency-tagged Neuromagnetic Responses

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