Encoding perceptual ensembles during visual search in peripheral vision

• Published in: Journal of Vision
• Main Authors: Tanrikulu, Ömer Daglar, Chetverikov, Andrey, Kristjánsson, Árni
• Other Authors: Faculty of Psychology, Health Sciences
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2020
• Subjects: Ensemble perception; Peripheral vision; Priming of pop-out; Summary statistics; Visual search; Ophthalmology; Sensory Systems; Iceland
• Online Access: https://hdl.handle.net/20.500.11815/3436; https://doi.org/10.1167/JOV.20.8.20

Funding Information: The authors thank Sabrina Hansmann-Roth for valuable feedback on the data analysis and the interpretation of the data. ODT and AK were supported by grant IRF #173947-052 from the Icelandic Research Fund, and by a grant from the Research Fund of the University of Iceland. AC is supported by Radboud Excellence Fellowship. Publisher Copyright: © The Authors. Observers can learn complex statistical properties of visual ensembles, such as their probability distributions. Even though ensemble encoding is considered critical for peripheral vision, whether observers learn such distributions in the periphery has not been studied. Here, we used a visual search task to investigate how the shape of distractor distributions influences search performance and ensemble encoding in peripheral and central vision. Observers looked for an oddly oriented bar among distractors taken from either uniform or Gaussian orientation distributions with the same mean and range. The search arrays were either presented in the foveal or peripheral visual fields. The repetition and role reversal effects on search times revealed observers' internal model of distractor distributions. Our results showed that the shape of the distractor distribution influenced search times only in foveal, but not in peripheral search. However, role reversal effects revealed that the shape of the distractor distribution could be encoded peripherally depending on the interitem spacing in the search array. Our results suggest that, although peripheral vision might rely heavily on summary statistical representations of feature distributions, it can also encode information about the distributions themselves. Peer reviewed