Emergent features break the rules of crowding.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
15 01 2020
Historique:
received: 07 10 2019
accepted: 27 12 2019
entrez: 17 1 2020
pubmed: 17 1 2020
medline: 17 1 2020
Statut: epublish

Résumé

Crowding is the deleterious influence of surrounding objects (flankers) on target identification. A central rule of crowding is that it is stronger when the target and the flankers are similar. Here, we show in three experiments how emergent features break this rule. Observers identified targets with various emergent features consisting of a pair of adjacent chevrons either pointing in opposite ('Diamonds' and 'Xs'), or the same (both up or down) directions. Targets were flanked by Diamonds or Xs, resulting in conditions with different levels of target-flanker similarity. Despite high target-flanker similarity, Diamonds were identified better than Xs when flanked by Diamonds. Participants' judgments of target conspicuity, however, showed that Diamonds were not perceived to stand out more strongly from X than Diamond flankers. Next, we asked observers to indicate whether all presented items were identical. We found superior performance with all Diamonds compared to all Xs, indicating that display uniformity judgments benefitted from the emergent features of Diamonds. Our results showed that emergent features and the information content of the entire display strongly modulated crowding. We suggest that conventional crowding rules only hold when target and flankers are artificially constrained to be mutually independent.

Identifiants

pubmed: 31941984
doi: 10.1038/s41598-019-57277-y
pii: 10.1038/s41598-019-57277-y
pmc: PMC6962356
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

406

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Auteurs

Natalia Melnik (N)

Institute of Psychology, University of Bern, Bern, 3012, Switzerland. natalia.melnik@psy.unibe.ch.

Daniel R Coates (DR)

Institute of Psychology, University of Bern, Bern, 3012, Switzerland.
College of Optometry, University of Houston, Houston, Texas, 77204, USA.

Bilge Sayim (B)

Institute of Psychology, University of Bern, Bern, 3012, Switzerland.
SCALab - Sciences Cognitives et Sciences Affectives, CNRS, UMR 9193, University of Lille, Lille, 59000, France.

Classifications MeSH