Literature DB >> 27559719

Visual reinforcement shapes eye movements in visual search.

Céline Paeye, Alexander C Schütz, Karl R Gegenfurtner.   

Abstract

We use eye movements to gain information about our visual environment; this information can indirectly be used to affect the environment. Whereas eye movements are affected by explicit rewards such as points or money, it is not clear whether the information gained by finding a hidden target has a similar reward value. Here we tested whether finding a visual target can reinforce eye movements in visual search performed in a noise background, which conforms to natural scene statistics and contains a large number of possible target locations. First we tested whether presenting the target more often in one specific quadrant would modify eye movement search behavior. Surprisingly, participants did not learn to search for the target more often in high probability areas. Presumably, participants could not learn the reward structure of the environment. In two subsequent experiments we used a gaze-contingent display to gain full control over the reinforcement schedule. The target was presented more often after saccades into a specific quadrant or a specific direction. The proportions of saccades meeting the reinforcement criteria increased considerably, and participants matched their search behavior to the relative reinforcement rates of targets. Reinforcement learning seems to serve as the mechanism to optimize search behavior with respect to the statistics of the task.

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Year:  2016        PMID: 27559719     DOI: 10.1167/16.10.15

Source DB:  PubMed          Journal:  J Vis        ISSN: 1534-7362            Impact factor:   2.240


  3 in total

Review 1.  Eye movement characteristics in schizophrenia: A recent update with clinical implications.

Authors:  Kentaro Morita; Kenichiro Miura; Kiyoto Kasai; Ryota Hashimoto
Journal:  Neuropsychopharmacol Rep       Date:  2019-11-27

2.  Saccade Landing Point Prediction Based on Fine-Grained Learning Method.

Authors:  Aythami Morales; Francisco M Costela; Russell L Woods
Journal:  IEEE Access       Date:  2021-04-01       Impact factor: 3.367

3.  Predicting task performance from biomarkers of mental fatigue in global brain activity.

Authors:  Lin Yao; Jonathan L Baker; Nicholas D Schiff; Keith P Purpura; Mahsa Shoaran
Journal:  J Neural Eng       Date:  2021-03-08       Impact factor: 5.379

  3 in total

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