Combined Electrophysiological and Behavioral Evidence for the Suppression of Salient Distractors

Gaspelin, Nicholas; Luck, Steven J.

doi:10.1162/jocn_a_01279

Cited by 196 publications

(352 citation statements)

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“…A lower probability of reporting probes embedded within singleton distractors has been taken as evidence in support of the signal suppression hypothesis. 94,95 Yet, the same pattern of behavioral results can be explained by reactive suppression in the sense that attention is first captured by the singleton distractor (if only for the briefest moment) and subsequently immediately suppressed. 96 To bypass the ambiguities of behavioral evidence, researchers have turned to two event-related potentials in the electrophysiological (EEG) signal: the N2pc and the Pd.…”

Section: First Trial Last Trialmentioning

confidence: 84%

“…To bypass the ambiguities of behavioral evidence, researchers have turned to two event‐related potentials in the electrophysiological (EEG) signal: the N2pc and the Pd. These typically occur around 200 ms poststimulus onset, and reflect attentional selection and suppression, respectively. The Pd, a transient positivity contralateral to the distractor, is especially relevant as its amplitude inversely scales with behavioral measures of distractor interference .…”

Section: Postdistractor Inhibition: Preattentive and Reactive Inhibitionmentioning

confidence: 99%

“…10,105 Although in many cases the Pd follows the N2pc 76,102,[106][107][108] or N1pc 104 in the ERP waveform as predicted by the ignoring paradox, growing evidence indicates that salient distractors can also be inhibited (as evidenced by a Pd) in the absence of any neural evidence for attentional selection (e.g., the absence of an N2pc). 10 Notably, in the majority of these studies, the experimental design allowed for statistical learning, either because the target and distractor identities were fixed (i.e., same color/shape) across trials, 94,101,109,110 or because there was a high probability distractor location. 85 This suggests that experience with distracting information is necessary for preattentive suppression of distracting information.…”

Section: First Trial Last Trialmentioning

confidence: 99%

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Inhibition in selective attention

Moorselaar

Slagter

2020

Annals of the New York Academy of Sciences

139

124

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Our ability to focus on goal‐relevant aspects of the environment is critically dependent on our ability to ignore or inhibit distracting information. One perspective is that distractor inhibition is under similar voluntary control as attentional facilitation of target processing. However, a rapidly growing body of research shows that distractor inhibition often relies on prior experience with the distracting information or other mechanisms that need not rely on active representation in working memory. Yet, how and when these different forms of inhibition are neurally implemented remains largely unclear. Here, we review findings from recent behavioral and neuroimaging studies to address this outstanding question. We specifically explore how experience with distracting information may change the processing of that information in the context of current predictive processing views of perception: by modulating a distractor's representation already in anticipation of the distractor, or after integration of top‐down and bottom‐up sensory signals. We also outline directions for future research necessary to enhance our understanding of how the brain filters out distracting information.

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Section: First Trial Last Trialmentioning

confidence: 84%

Section: Postdistractor Inhibition: Preattentive and Reactive Inhibitionmentioning

confidence: 99%

Section: First Trial Last Trialmentioning

confidence: 99%

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Inhibition in selective attention

Moorselaar

Slagter

2020

Annals of the New York Academy of Sciences

139

124

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“…In addition, we evaluated how location learning affected later-stage target and distractor processing, as reflected in the lateralized ERP components, the N2pc and the Pd, respectively. Whereas the N2pc is thought to reflect attentional selection (Eimer, 2014;Luck, 2012;, the Pd is selectively elicited by distracting visual input and linked to distractor inhibition (Gaspelin & Luck, 2018a;Hickey, Di Lollo, & McDonald, 2009).…”

Section: Event-related Potential (Erp) Analysismentioning

confidence: 99%

Learning what is irrelevant or relevant: Expectations facilitate distractor inhibition and target facilitation through distinct neural mechanisms

Moorselaar

Slagter

2019

Preprint

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It is well known that attention can facilitate performance by top-down biasing processing of task-relevant information in advance. Recent findings from behavioral studies suggest that distractor inhibition is not under similar direct control, but strongly dependent on expectations derived from previous experience. Yet, how expectations about distracting information influence distractor inhibition at the neural level remains unclear. The current study addressed this outstanding question in three experiments in which search displays with repeating distractor or target locations across trials allowed observers to learn which location to selectively suppress or boost. Behavioral findings demonstrated that both distractor and target location learning resulted in more efficient search, as indexed by faster response times. Crucially, benefits of distractor learning were observed without target location foreknowledge, unaffected by the number of possible target locations, and could not be explained by priming alone. To determine how distractor location expectations facilitated performance, we applied a spatial encoding model to EEG data to reconstruct activity in neural populations tuned to the distractor or target location. Target location learning increased neural tuning to the target location in advance, indicative of preparatory biasing. This sensitivity increased after target presentation. By contrast, distractor expectations did not change preparatory spatial tuning. Instead, distractor expectations reduced distractor-specific processing, as reflected in the disappearance of the Pd ERP component, a neural marker of distractor inhibition, and decreased decoding accuracy. These findings suggest that the brain may no longer process expected distractors as distractors, once it has learned they can safely be ignored. Significance statementWe constantly try hard to ignore conspicuous events that distract us from our current goals. Surprisingly, and in contrast to dominant attention theories, ignoring distracting, but irrelevant events does not seem to be as flexible as is focusing our attention on those same aspects. Instead, distractor suppression appears to strongly rely on learned, context-dependent expectations. Here, we investigated how learning about upcoming distractors changes distractor processing and directly contrasted the underlying neural dynamics to target learning. We show that while target learning enhanced anticipatory sensory tuning, distractor learning only modulated reactive suppressive processing. These results suggest that expected distractors may no longer be considered distractors by the brain once it has learned that they can safely be ignored.

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“…The p values for the permutation tests were estimated using the following formula with 1 1,000 permutations 64 In Experiments 2 and 3, we fitted the CDA amplitudes to a power-law model. The 5…”

Section: Erp Datamentioning

confidence: 99%

Electrophysiological correlates of the flexible allocation of visual working memory resources

Salahub

Lockhart

Dube

et al. 2019

Preprint

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1Visual working memory is a brief, capacity-limited store of visual information that is involved in 2 a large number of cognitive functions. To guide one's behavior effectively, one must efficiently 3 allocate these limited memory resources across memory items. Previous research has suggested 4 that items are either stored in memory or completely blocked from memory access. However, 5 recent behavioral work proposes that memory resources can be flexibly split across items based 6 on their level of task importance. Here, we investigated the electrophysiological correlates of 7 flexible resource allocation by manipulating the distribution of resources amongst systematically 8 lateralized memory items. We examined the contralateral delay activity (CDA), a waveform 9 typically associated with the number of items held in memory. Across three experiments, we 10 found that, in addition to memory load, the CDA flexibly tracks memory resource allocation. 11This allocation occurred as early as attentional selection, as indicated by the N2pc. Additionally, 12CDA amplitude was better-described when fit with a continuous model predicted by load and 13 resources together than when fit with either alone. Our findings show that electrophysiological 14 markers of attentional selection and memory maintenance not only track memory load, but also 15 the proportion of memory resources those items receive. 16

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Combined Electrophysiological and Behavioral Evidence for the Suppression of Salient Distractors

Cited by 196 publications

References 50 publications

Inhibition in selective attention

Inhibition in selective attention

Learning what is irrelevant or relevant: Expectations facilitate distractor inhibition and target facilitation through distinct neural mechanisms

Electrophysiological correlates of the flexible allocation of visual working memory resources

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