PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
March 23, 2026Virtual Reality1 citationsOpen Access

Beyond flatland: naturalistic three-dimensional stimuli and visual working memory processing

View Full Paper
GSGilad SchriftTel Aviv UniversitySLS. LandoTel Aviv UniversityRLRoy LuriaTel Aviv University

Key Points

  • This research examines how three-dimensional stimuli impact visual working memory performance compared to two-dimensional stimuli.
  • Experiment utilized a virtual reality change detection task with both 2D and 3D stimuli.
  • Participants' response times and accuracy were measured under varying memory loads.
  • Performance across different dimensionality was compared.
  • Response times increased more significantly for 3D stimuli at higher memory loads.
  • Accuracy remained similar between 2D and 3D stimuli.
  • 3D stimuli enhanced visual perception but introduced processing costs.

Abstract

Abstract Visual working memory (VWM) enables the temporary storage and manipulation of visual information, yet its limited capacity makes it sensitive to the amount and structure of the information it must retain. The vast majority of previous VWM research has used two-dimensional stimuli, while real-world visual perception incorporates depth-related spatial cues which may affect performance. Prior work suggests that depth could enhance VWM performance by enabling perceptual enrichment and better individuation, but may also introduce additional cognitive processing costs and impair performance. Here, we directly tested how dimensionality influences VWM under different memory loads using a virtual reality adaptation of the change detection task, enabling the presentation of ecologically valid, real-world 2D and 3D objects. While accuracy was comparable across stimulus dimensionality, response times for 3D stimuli showed larger increases at higher memory loads. These results suggest that even though 3D stimuli may enrich perceptual input, they introduce processing costs that become more apparent under high memory load, possibly demanding additional neural resources associated with depth processing.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Schrift et al. (2026) studied this question.

synapsesocial.com/papers/69c08b9fa48f6b84677f930dhttps://doi.org/10.1007/s10055-026-01343-0
Ask AI
Helpful
Bookmark
Share
View Full Paper