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Record W4312213268 · doi:10.1101/2022.12.23.521791

Exogenous attention interferes with endogenous attention processing via lateralized alpha power

2022· preprint· en· W4312213268 on OpenAlexafffund
Mathieu Landry, Jason da Silva Castanheira, Amir Raz, Sylvain Baillet, Jérôme Sackur

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersCanadian Institutes of Health ResearchNational Institutes of HealthHealth CanadaCanada First Research Excellence FundAgence Nationale de la RechercheNatural Sciences and Engineering Research Council of CanadaFondation Brain CanadaMcGill University
KeywordsEndogenyPsychologyVisual spatial attentionCognitive psychologyN2pcAttentional controlNeuroscienceCognitionVisual attention

Abstract

fetched live from OpenAlex

Abstract Current theories of attention differentiate exogenous (bottom-up) from endogenous (top-down) orienting of visuospatial attention. While both forms of attentional processing engage different processes, endogenous and exogenous attention are thought to share processing resources, as shown by recent empirical evidence of their functional interactions. Here, we aim to uncover the neurobiological basis of how salient events that drive exogenous attention disrupts endogenous attention processes. We hypothesize that interference from exogenous attention over endogenous attention involves alpha-band activity, a neural marker of visuospatial attention. To test this hypothesis, we contrast the effects of endogenous attention across two experimental conditions: a single cueing condition where endogenous attention is engaged in isolation, and a double cueing condition where endogenous attention is concurrently engaged with exogenous attention. Our results are consistent with previous work and show that the concurrent engagement of exogenous attention interferes with endogenous attention processes. Importantly, we evaluate our main hypothesis using a moderated mediation model. We found that changes in alpha-band activity mediate the relationship between endogenous attention and its benefits on task performance, and that the interference of exogenous attention on endogenous attention occurs via the moderation of this indirect effect. Altogether, our results substantiate a model of attention, whereby top-down and bottom-up attentional processes compete for shared neurophysiological resources. This model accounts for the observed patterns of interference between exogenous and endogenous attention. Significance Statement Scientists differentiate top-down and bottom-up visuospatial attention processes. While bottom-up attention is rapidly engaged by emerging demands from the environment, top-down attention reflects slow voluntary shifts of attention. Several lines of research substantiate the idea that top-down and bottom-up attentional processes involve distinct brain systems. An increasing number of studies, however, argue that both attention systems share brain processing resources. The current study examines how salient visual events that engage bottom-up processes interfere with top-down processes. Using neurophysiological recordings and multivariate pattern classification techniques, the researchers show that both top-down and bottom-up attention processes do share brain resources expressed via alpha-band neurophysiological activity (8-12 Hz). The results further demonstrate that the interference patterns observed over brain activity in the alpha-band between both attention systems explains, in part, the interference between top-down and bottom-up attention at the behavioural level. The authors conclude by proposing a model of visuospatial attention whereby the dynamics between both attention systems are determined by their competition for limited brain processing resources.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.073
GPT teacher head0.287
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2022
Admission routes2
Has abstractyes

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