Visual Search in Sport and Ergonomics: Its Relationship to Selective Attention and Performer Expertise

1988 ◽  
Vol 1 (4) ◽  
pp. 205-235 ◽  
Author(s):  
Bruce Abernethy
Keyword(s):  
Visual Search ◽  
Selective Attention

scholarly journals Visual Search Without Selective Attention: A Cognitive Architecture Account

2018 ◽  
Vol 11 (1) ◽  
pp. 222-239 ◽  
Author(s):  
David E. Kieras
Keyword(s):  
Visual Search ◽  
Selective Attention ◽  
Cognitive Architecture

Selective attention modulates implicit learning

2001 ◽  
Vol 54 (4) ◽  
pp. 1105-1124 ◽  
Author(s):  
Yuhong Jiang ◽  
Marvin M. Chun
Keyword(s):  
Visual Search ◽  
Selective Attention ◽  
Implicit Learning ◽  
Target Location ◽  
Spatial Configuration ◽  
Contextual Cueing ◽  
Predictive Information

The effect of selective attention on implicit learning was tested in four experiments using the “contextual cueing” paradigm (Chun & Jiang, 1998, 1999). Observers performed visual search through items presented in an attended colour (e.g., red) and an ignored colour (e.g., green). When the spatial configuration of items in the attended colour was invariant and was consistently paired with a target location, visual search was facilitated, showing contextual cueing (Experiments 1, 3, and 4). In contrast, repeating and pairing the configuration of the ignored items with the target location resulted in no contextual cueing (Experiments 2 and 4). We conclude that implicit learning is robust only when relevant, predictive information is selectively attended.

An interactive constraint-based system for selective attention in visual search

1997 ◽  
pp. 431-440 ◽  
Author(s):  
R. Cucchiara ◽  
E. Lamma ◽  
P. Mello ◽  
M. Milano
Keyword(s):  
Visual Search ◽  
Selective Attention

MODELING VISUAL SEARCH: EVOLVING THE SELECTIVE ATTENTION FOR IDENTIFICATION MODEL (SAIM)

2004 ◽  
Author(s):  
DIETMAR HEINKE ◽  
GLYN W. HUMPHREYS ◽  
CLAIRE L. TWEED
Keyword(s):  
Visual Search ◽  
Selective Attention ◽  
Identification Model

scholarly journals Efficient Attentional Selection Predicts Distractor Devaluation: Event-related Potential Evidence for a Direct Link between Attention and Emotion

2007 ◽  
Vol 19 (8) ◽  
pp. 1316-1322 ◽  
Author(s):  
Monika Kiss ◽  
Brian A. Goolsby ◽  
Jane E. Raymond ◽  
Kimron L. Shapiro ◽  
Laetitia Silvert ◽  
...  
Keyword(s):  
Visual Search ◽  
Selective Attention ◽  
Search Task ◽  
Visual Search Task ◽  
Emotional Responses ◽  
Event Related Potential ◽  
Behavioral Measures ◽  
Affective Evaluation ◽  
Evaluative Judgments ◽  
Attentional Selectivity

Links between attention and emotion were investigated by obtaining electrophysiological measures of attentional selectivity together with behavioral measures of affective evaluation. Participants were asked to rate faces that had just been presented as targets or distractors in a visual search task. Distractors were rated as less trustworthy than targets. To study the association between the efficiency of selective attention during visual search and subsequent emotional responses, the N2pc component was quantified as a function of evaluative judgments. Evaluation of distractor faces (but not target faces) covaried with selective attention. On trials where distractors were later judged negatively, the N2pc emerged earlier, demonstrating that attention was strongly biased toward target events, and distractors were effectively inhibited. When previous distractors were judged positively, the N2pc was delayed, indicating unfocused attention to the target and less distractor suppression. Variations in attentional selectivity across trials can predict subsequent emotional responses, strongly suggesting that attention is closely associated with subsequent affective evaluation.

Visual Search Strategy, Selective Attention, and Expertise in Soccer

1998 ◽  
Vol 69 (2) ◽  
pp. 111-128 ◽  
Author(s):  
A. M. Williams ◽  
K. Davids
Keyword(s):  
Visual Search ◽  
Selective Attention ◽  
Search Strategy

scholarly journals SELECTIVE ATTENTION IN AGE-ASSOCIATED MEMORY IMPAIRMENT: AN ERP STUDY IN VISUAL SEARCH

2017 ◽  
Vol 1 (suppl_1) ◽  
pp. 477-478
Author(s):  
A. Bujn ◽  
L. Lorenzo-López ◽  
A. Maseda ◽  
R. López-López ◽  
C. Diego-Diez ◽  
...  
Keyword(s):  
Visual Search ◽  
Selective Attention ◽  
Memory Impairment

The Impact of Age on Visual Search Performance

1993 ◽  
Vol 37 (2) ◽  
pp. 172-176 ◽  
Author(s):  
P. Manivannan ◽  
Sara Czaja ◽  
Colin Drury ◽  
Chi Ming Ip
Keyword(s):  
Visual Search ◽  
Reaction Time ◽  
Selective Attention ◽  
Search Task ◽  
Visual Search Task ◽  
Age Groups ◽  
Search Performance ◽  
Performance Effect ◽  
Age Related ◽  
The Impact

Visual search is an important component of many real world tasks such as industrial inspection and driving. Several studies have shown that age has an impact on visual search performance. In general older people demonstrate poorer performance on such tasks as compared to younger people. However, there is controversy regarding the source of the age-performance effect. The objective of this study was to examine the relationship between component abilities and visual search performance, in order to identify the locus of age-related performance differences. Six abilities including reaction time, working memory, selective attention and spatial localization were identified as important components of visual search performance. Thirty-two subjects ranging in age from 18 - 84 years, categorized in three different age groups (young, middle, and older) participated in the study. Their component abilities were measured and they performed a visual search task. The visual search task varied in complexity in terms of type of targets detected. Significant relationships were found between some of the component skills and search performance. Significant age effects were also observed. A model was developed using hierarchical multiple linear regression to explain the variance in search performance. Results indicated that reaction time, selective attention, and age were important predictors of search performance with reaction time and selective attention accounting for most of the variance.

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