Pinging the brain to reveal the hidden attentional priority map using encephalography

Duncan, Dock; Moorselaar, Dirk van; Theeuwes, Jan

doi:10.1101/2022.08.23.504931

Cited by 7 publications

(1 citation statement)

References 117 publications

(253 reference statements)

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“…These latent/silent/quiescent changes (Stokes, 2015) in response to expected distractors can be more difficult to measure using common methods in psychological science, such as EEG oscillations, ERPs, or fMRI BOLD that have spatial and temporal resolutions that are orders of magnitude coarser than the synaptic scale. Nevertheless, changes at the synaptic level can be inferred through clever indirect measures (Duncan et al, 2022). In electrophysiological studies, the PD ERP component is often taken to indicate the presence of proactive suppression when it occurs around 100-200 ms (in non-human primate electrophysiology see: Cosman et al, 2018; in human ERPs, see: Gaspelin & Luck, 2018;Sawaki & Luck, 2010;Stilwell et al, 2022).…”

Section: Timingmentioning

confidence: 99%

Terms of debate: Consensus definitions to guide the scientific discourse on visual distraction

Liesefeld¹,

Lamy²,

Gaspelin³

et al. 2023

Preprint

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Hypothesis-driven research rests on clearly articulated scientific theories. The building blocks for communicating these theories are scientific terms. Obviously, communication – and thus, scientific progress – is hampered if the meaning of these terms varies idiosyncratically across (sub)fields and even across individual researchers within the same subfield. We have formed an international group of experts representing various theoretical stances with the goal to homogenize the use of the terms that are most relevant to the field of visual distraction in visual search. Our discussions revealed striking heterogeneity and we had to invest much time and effort to increase our mutual understanding of each other’s use of central terms, which turned out to be strongly related to our respective theoretical positions. We present the outcomes of these discussions in a glossary and provide some context in several essays. Specifically, we explicate how central terms are used in the distraction literature and consensually sharpen their definitions in order to enable communication across theoretical standpoints. Where applicable, we also explain how the respective constructs can be measured. We believe that this novel type of adversarial collaboration can serve as a model for other fields of psychological research that strive to build a solid groundwork for theorizing and communicating by establishing a common language. For the field of visual distraction, the present paper should facilitate communication across theoretical standpoints and may serve as an introduction and reference text for newcomers.

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Section: Timingmentioning

confidence: 99%

Terms of debate: Consensus definitions to guide the scientific discourse on visual distraction

Liesefeld¹,

Lamy²,

Gaspelin³

et al. 2023

Preprint

View full text Add to dashboard Cite

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Statistical learning of distractor locations is dependent on task context

Waard

Moorselaar

Bogaerts

et al. 2023

Sci Rep

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Through statistical learning, humans can learn to suppress visual areas that often contain distractors. Recent findings suggest that this form of learned suppression is insensitive to context, putting into question its real-life relevance. The current study presents a different picture: we show context-dependent learning of distractor-based regularities. Unlike previous studies which typically used background cues to differentiate contexts, the current study manipulated task context. Specifically, the task alternated from block to block between a compound search and a detection task. In both tasks, participants searched for a unique shape, while ignoring a uniquely colored distractor item. Crucially, a different high-probability distractor location was assigned to each task context in the training blocks, and all distractor locations were made equiprobable in the testing blocks. In a control experiment, participants only performed a compound search task such that the contexts were made indistinguishable, but the high-probability locations changed in exactly the same way as in the main experiment. We analyzed response times for different distractor locations and show that participants can learn to suppress a location in a context-dependent way, but suppression from previous task contexts lingers unless a new high-probability location is introduced.

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The Electrophysiological Markers of Statistically Learned Attentional Enhancement: Evidence for a Saliency Based Mechanism

Duncan

Moorselaar

Theeuwes

2023

Preprint

Self Cite

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It has been well established that attention can be sharpened through the process of statistical learning, whereby visual search is optimally adapted to the spatial probabilities of a target in visual fields. Specifically, attentional processing becomes more efficient when targets appear at high relatively to low probability locations. Statistically learned attentional enhancement has been shown to differ behaviorally from the more well studied top-down and bottom-up forms of attention; and while the electrophysiological characteristics of top-down and bottom-up attention have been well explored, relatively little work has been done to characterize the electrophysiological correlates of statistically learned attentional enhancement. In the current study, EEG data was collected while participants performed the additional singleton task with an unbalanced target distribution. Encephalographic data was then analyzed for two well-known correlates of attentional processing; alpha lateralization and the N2pc component. Our results showed that statistically learned attentional enhancement is not characterized by alpha lateralization, thereby differentiating it from top-down enhancement. Yet targets at high probability locations did reliably produce larger N2pc amplitudes, a known marker of increased bottom-up capture due to higher target-distractor contrasts. These results support an interpretation of the probability cuing effects where the improved processing of targets at expected locations is mediated by a saliency-based mechanism; boosting the salience of targets appearing at high-probability locations relative to those at low-probability locations.

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Pinging the brain to reveal the hidden attentional priority map using encephalography

Cited by 7 publications

References 117 publications

Terms of debate: Consensus definitions to guide the scientific discourse on visual distraction

Terms of debate: Consensus definitions to guide the scientific discourse on visual distraction

Statistical learning of distractor locations is dependent on task context

The Electrophysiological Markers of Statistically Learned Attentional Enhancement: Evidence for a Saliency Based Mechanism

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