Distractor effects during processing of words under load

Brand-D’Abrescia, Muriele; Lavie, Nilli

doi:10.3758/bf03193105

Cited by 27 publications

(26 citation statements)

References 19 publications

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“…Interestingly, different models of distractor inhibition predict different patterns of results. If distractor suppression and target enhancement are dependent on common neural mechanisms (e.g., Dalton, Lavie, & Spence, 2009;Brand-DʼAbrescia & Lavie, 2007;Lavie & De Fockert, 2005), then the same WME conditions that delay attention-related enhancement of a subsequent target would also delay attention-related suppression. Other models of distractor suppression, however, propose that it may proceed independently from target enhancement if target and distractor processing are dependent on different neural systems (e.g., Park, Kim, & Chun, 2007;Kim, Kim, & Chun, 2005).…”

Section: Discussionmentioning

confidence: 99%

Working Memory Encoding Delays Top–Down Attention to Visual Cortex

Scalf

Dux

Marois

2011

Journal of Cognitive Neuroscience

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Section: Discussionmentioning

confidence: 99%

Working Memory Encoding Delays Top–Down Attention to Visual Cortex

Scalf

Dux

Marois

2011

Journal of Cognitive Neuroscience

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“…In the third group (see Fig. 1C), PL is increased by making it more difficult to discriminate among the possible targets (Bahrami, Carmel, Walsh, Rees, & Lavie, 2008;Brand-D'Abrescia & Lavie, 2007;Cartwright-Finch & Lavie, 2007;Couperus, 2001;Handy & Mangun, 2000;Taya, Adams, Graf, & Lavie, 2009). In the fourth group (see Fig.…”

Section: Perceptual Loadmentioning

confidence: 99%

Identifying visual targets amongst interfering distractors: Sorting out the roles of perceptual load, dilution, and attentional zoom

Cave

Chen

2016

Atten Percept Psychophys

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Visual selection is imperfect; whenever a complex array of objects is processed, representations of multiple objects are likely to be active simultaneously. A full account of attentional processing must explain how these representations affect one another and how they interact to produce a response. Evidence on these interactions comes from measures of distractor interference and from dilution of distractor effects by other nontargets. Based on these data, different principles have been proposed to help understand target-distractor interactions, including accounts based on perceptual load and on dilution among nontargets. We review evidence from a number of experiments, including some using Yantis and Jonides's (Journal of Experimental Psychology: Human Perception and Performance, 10, 601-621, 1984, Journal of Experimental Psychology: Human Perception and Performance, 16, 121-134, 1990) methods for preventing abrupt onsets, which can disrupt spatial attention. The results underscore spatial constraints on the allocation of attention to include targets and exclude distractors. Selection is most effective when a single region can be selected that includes all possible target locations and excludes possible distractor locations. This region can be expanded or contracted as needed for the task, as suggested by C. W. Eriksen and St. James's (Perception & Psychophysics, 40, 225-240, 1986) zoom lens model. This attentional zoom setting is probably affected by a number of factors, including the number of nontargets, the similarity among stimulus elements, the discriminability of the possible targets, and the discrimination difficulty of a concurrent task. A narrower attentional zoom setting that excludes a distractor will prevent interference from that distractor. Interference from a distractor will be diluted by nontargets, but only if they are within the attentional zoom region.

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“…Although evidence from numerous studies provides support for perceptual load theory (e.g., Bahrami, Carmel, Walsh, Rees, & Lavie, 2008;Brand-D'Abrescia & Lavie, 2007;Cartwright-Finch & Lavie 2007;Forster & Lavie, 2007;Lavie, 1995Lavie, , 2006Lavie & de Fockert, 2003;Lavie & Fox, 2000;Lavie & Robertson, 2001;Lavie et al, 2004;Muggleton, Lamb, Walsh, & Lavie, 2008), reported data are inconsistent with predictions of this theory. Using a name classification task, Lavie et al investigated the effect of perceptual load (set size) on the level of interference from a face distractor.…”

Section: Introductionmentioning

confidence: 96%

Interference from familiar natural distractors is not eliminated by high perceptual load

Chunhong

Chen

2009

Psychological Research

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A crucial prediction of perceptual load theory is that high perceptual load can eliminate interference from distractors. However, Lavie et al. (Psychol Sci 14:510-515, 2003) found that high perceptual load did not eliminate interference when the distractor was a face. The current experiments examined the interaction between familiarity and perceptual load in modulating interference in a name search task. The data reveal that high perceptual load eliminated the interference effect for unfamiliar distractors that were faces or objects, but did not eliminate the interference for familiar distractors that were faces or objects. Based on these results, we proposed that the processing of familiar and natural stimuli may be immune to the effect of perceptual load.

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Distractor effects during processing of words under load

Cited by 27 publications

References 19 publications

Working Memory Encoding Delays Top–Down Attention to Visual Cortex

Working Memory Encoding Delays Top–Down Attention to Visual Cortex

Identifying visual targets amongst interfering distractors: Sorting out the roles of perceptual load, dilution, and attentional zoom

Interference from familiar natural distractors is not eliminated by high perceptual load

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