Vision at a glance: The role of attention in processing object-to-object categorical relations

Research output: Contribution to journalArticlepeer-review


When viewing a scene at a glance, the visual and categorical relations between objects in the scene are extracted rapidly. In the present study, the involvement of spatial attention in the processing of such relations was investigated. Participants performed a category detection task (e.g., “is there an animal”) on briefly flashed object pairs. In one condition, visual attention spanned both stimuli, and in another, attention was focused on a single object while its counterpart object served as a task-irrelevant distractor. The results showed that when participants attended to both objects, a categorical relation effect was obtained (Exp. 1). Namely, latencies were shorter to objects from the same category than to those from different superordinate categories (e.g., clothes, vehicles), even if categories were not prioritized by the task demands. Focusing attention on only one of two stimuli, however, largely eliminated this effect (Exp. 2). Some relational processing was seen when categories were narrowed to the basic level and were highly distinct from each other (Exp. 3), implying that categorical relational processing necessitates attention, unless the unattended input is highly predictable. Critically, when a prioritized (to-be-detected) object category, positioned in a distractor’s location, differed from an attended object, a robust distraction effect was consistently observed, regardless of category homogeneity and/or of response conflict factors (Exp. 4). This finding suggests that object relations that involve stimuli that are highly relevant to the task settings may survive attentional deprivation at the distractor location. The involvement of spatial attention in object-to-object categorical processing is most critical in situations that include wide categories that are irrelevant to one’s current goals.

Original languageEnglish
Pages (from-to)671-688
Number of pages18
JournalAttention, Perception, and Psychophysics
Issue number2
StatePublished - 1 Feb 2020

Bibliographical note

Funding Information:
I thank S. Yakim, A. Izoutcheev, M. Shachar, and T. Nave for their assistance in experiment programming and data collection. This research was supported by the Israel Science Foundation (grant no. 1622/15) to N.G. 1 According to power computations, to achieve a power of .9 under the assumption of a categorical relation effect of d = 0.8 (alpha = .05), a sample of 19 participants was required. Since there were three target categories in Experiment 1B, and to allow for full target counterbalancing across participants, a sample of 21 participants was chosen for both studies of Experiment 1, as well as for the following experiments (aside from Exp. 4, in which a slightly larger sample was required, due to a change in counterbalancing requirements). In addition to these a priori power computations, a post-hoc computation of the achieved power was conducted for the categorical relation effect among the nontarget trials of Experiment 1 (see below). The power computation yielded an actual power of .98 in Experiment 1A, and a power of .93 in Experiment 1B. All power computations were conducted using the G*Power 3.1.3 software (Faul, Erdfelder, Lang, & Buchner, 2007 ). 2 A Bayes factor was computed, representing the likelihood ratio of the data under the assumption of the presence of a categorical relation effect (referred to as the BF; see Dienes, 2011 ; Jeffreys, 1961 ). According to widely accepted benchmarks, BF values of 10 or greater indicate a strong effect, 3 < BF < 10 suggests a moderate effect, 0.33 < BF < 3 implies an inconclusive result, and BF < 0.33 indicates the absence of an effect (i.e., clear support for H0). Cohen’s d effect size, computed for all contrasts, is defined as the standardized mean difference between the two conditions. According to common rules of thumb, d values of 0.2, 0.5, and 0.8 stand for small, medium, and large effects, respectively (see J. Cohen, 1988 ). All statistical analyses were conducted using the JASP software (version 3 To allow for full counterbalancing of all possible combinations of pair targets, a sample of 24 participants was chosen.


  • Categorical processing
  • Contingent attention capture
  • Focused attention
  • Object recognition
  • Object–object associations
  • Perceptual categorization and identification
  • Task relevance
  • Visual attention


Dive into the research topics of 'Vision at a glance: The role of attention in processing object-to-object categorical relations'. Together they form a unique fingerprint.

Cite this