Self-association enhances early attentional selection through automatic prioritization of socially salient signals

Meike Scheller* (Corresponding Author), Jan Tünnermann, Katja Fredriksson, Huilin Fang, Jie Sui* (Corresponding Author)

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

Efficiently processing self-related information is critical for cognition, yet the earliest mechanisms enabling this self-prioritization remain unclear. By combining a temporal order judgement task with computational modelling based on the Theory of Visual Attention (TVA), we show how mere, arbitrary associations with the self can fundamentally alter attentional selection of sensory information into short-term memory/awareness, by enhancing the attentional weights and processing capacity devoted to encoding socially loaded information. This self-prioritization in attentional selection occurs automatically at early perceptual stages but reduces when active social decoding is required. Importantly, the processing benefits obtained from attentional selection via self-relatedness and via physical salience were additive, suggesting that social and perceptual salience captured attention via separate mechanisms. Furthermore, intra-individual correlations revealed an ‘obligatory’ self-prioritization effect, whereby self-relatedness overpowered the contribution of perceptual salience in guiding attentional selection. Together, our findings provide evidence for the influence of self-relatedness during earlier, automatic stages of attentional section at the gateway to perception, distinct from later post-attentive processing stages.
Original languageEnglish
JournaleLife
Early online date27 Dec 2024
DOIs
Publication statusE-pub ahead of print - 27 Dec 2024

Funding

The study was supported by grants from the Leverhulme Foundation (REF RPG-2019-010) and the Institutional Research Leave Award (CF10831-27) to JS.

FundersFunder number
The Leverhulme TrustRPG-2019-010
Institutional Research Leave AwardCF10831-27

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