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Statistical Properties Demand as Much Attention as Object Features
Author(s) -
Liqiang Huang
Publication year - 2015
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0131191
Subject(s) - object (grammar) , orientation (vector space) , task (project management) , computer science , feature (linguistics) , property (philosophy) , set (abstract data type) , statistical analysis , artificial intelligence , cognitive psychology , pattern recognition (psychology) , psychology , statistics , mathematics , engineering , linguistics , philosophy , epistemology , programming language , geometry , systems engineering
Recent studies have argued that the statistical properties of a set of visual items can be extracted with little or even no cost. In the present study, observers ( N = 188) performed a color task and an orientation task, and the attention effect was measured as the advantage of pre-cueing one of the two tasks. The color and orientation tasks required participants to report either an object feature or the mean of a 4×4 array (i.e., statistical property). The pre-cueing advantages were approximately equal regardless of the nature of the tasks (object features vs. statistical properties), providing evidence that statistical properties are not perceived with zero cost, but demand as much attention as object features.

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