Space and feature-based attention operate both independently and interactively within latent components of perceptual decision making

Guangsheng LIANG, John E. POQUIZ, Miranda SCOLARI*

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

2 Citations (Scopus)

Abstract

Top-down visual attention filters undesired stimuli while selected information is afforded the lion’s share of limited cognitive resources. Multiple selection mechanisms can be deployed simultaneously, but how unique influences of each combine to facilitate behavior remains unclear. Previously, we failed to observe an additive perceptual benefit when both space-based attention (SBA) and feature-based attention (FBA) were cued in a sparse display (Liang & Scolari, 2020): FBA was restricted to higher order decision-making processes when combined with a valid spatial cue, whereas SBA additionally facilitated target enhancement. Here, we introduced a series of design modifications across three experiments to elicit both attention mechanisms within signal enhancement while also investigating the impacts on decision making. First, we found that when highly reliable spatial and feature cues made unique contributions to search (experiment 1), or when each cue component was moderately reliable (experiments 2a and 2b), both mechanisms were deployed independently to resolve the target. However, the same manipulations produced interactive attention effects within other latent decision-making components that depended on the probability of the integrated cueing object. Time spent before evidence accumulation was reduced and responses were more conservative for the most likely pre-cue combination—even when it included an invalid component. These data indicate that selection mechanisms operate on sensory signals invariably in an independent manner, whereas a higher-order dependency occurs outside of signal enhancement.

Original languageEnglish
Article number12
JournalJournal of Vision
Volume23
Issue number1
Early online dateJan 2023
DOIs
Publication statusPublished - Jan 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2023 The Authors

Keywords

  • Drift diffusion model
  • Feature-based attention
  • Perceptual decision making
  • Space-based attention

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