Literature DB >> 27123677

Observers' cognitive states modulate how visual inputs relate to gaze control.

Omid Kardan1, John M Henderson2, Grigori Yourganov3, Marc G Berman1.   

Abstract

Previous research has shown that eye-movements change depending on both the visual features of our environment, and the viewer's top-down knowledge. One important question that is unclear is the degree to which the visual goals of the viewer modulate how visual features of scenes guide eye-movements. Here, we propose a systematic framework to investigate this question. In our study, participants performed 3 different visual tasks on 135 scenes: search, memorization, and aesthetic judgment, while their eye-movements were tracked. Canonical correlation analyses showed that eye-movements were reliably more related to low-level visual features at fixations during the visual search task compared to the aesthetic judgment and scene memorization tasks. Different visual features also had different relevance to eye-movements between tasks. This modulation of the relationship between visual features and eye-movements by task was also demonstrated with classification analyses, where classifiers were trained to predict the viewing task based on eye movements and visual features at fixations. Feature loadings showed that the visual features at fixations could signal task differences independent of temporal and spatial properties of eye-movements. When classifying across participants, edge density and saliency at fixations were as important as eye-movements in the successful prediction of task, with entropy and hue also being significant, but with smaller effect sizes. When classifying within participants, brightness and saturation were also significant contributors. Canonical correlation and classification results, together with a test of moderation versus mediation, suggest that the cognitive state of the observer moderates the relationship between stimulus-driven visual features and eye-movements. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Entities:  

Mesh:

Year:  2016        PMID: 27123677     DOI: 10.1037/xhp0000224

Source DB:  PubMed          Journal:  J Exp Psychol Hum Percept Perform        ISSN: 0096-1523            Impact factor:   3.332


  6 in total

1.  A Generative Model of Cognitive State from Task and Eye Movements.

Authors:  W Joseph MacInnes; Amelia R Hunt; Alasdair D F Clarke; Michael D Dodd
Journal:  Cognit Comput       Date:  2018-05-09       Impact factor: 5.418

2.  Predicting eye-movement characteristics across multiple tasks from working memory and executive control.

Authors:  Steven G Luke; Emily S Darowski; Shawn D Gale
Journal:  Mem Cognit       Date:  2018-07

3.  Image Feature Types and Their Predictions of Aesthetic Preference and Naturalness.

Authors:  Frank F Ibarra; Omid Kardan; MaryCarol R Hunter; Hiroki P Kotabe; Francisco A C Meyer; Marc G Berman
Journal:  Front Psychol       Date:  2017-04-28

4.  OSIEshort: A small stimulus set can reliably estimate individual differences in semantic salience.

Authors:  Marcel Linka; Benjamin de Haas
Journal:  J Vis       Date:  2020-09-02       Impact factor: 2.240

5.  Cultural and Developmental Influences on Overt Visual Attention to Videos.

Authors:  Omid Kardan; Laura Shneidman; Sheila Krogh-Jespersen; Suzanne Gaskins; Marc G Berman; Amanda Woodward
Journal:  Sci Rep       Date:  2017-09-12       Impact factor: 4.379

6.  Overt attentional correlates of memorability of scene images and their relationships to scene semantics.

Authors:  Muxuan Lyu; Kyoung Whan Choe; Omid Kardan; Hiroki P Kotabe; John M Henderson; Marc G Berman
Journal:  J Vis       Date:  2020-09-02       Impact factor: 2.240

  6 in total

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