Developing a Screening Tool for Areas of Abnormal Central Vision Using Visual Stimuli With Natural Scene Statistics

Rekha Srinivasan, Andrew Turpin, Allison M McKendrick

Research output: Contribution to journalArticlepeer-review


PURPOSE: Previous studies show that some visual field (VF) defects are detectable from visual search behavior; for example, when watching video. Here, we developed and tested a VF testing approach that measures the number of fixations to find targets on a background with spatial frequency content similar to natural scenes.

METHODS: Twenty-one older controls and 20 people with glaucoma participated. Participants searched for a Gabor (6 c/°) that appeared in one of 25 possible locations within a 15° (visual angle) 1/f noise background (RMS contrast: 0.20). Procedure performance was assessed by calculating sensitivity and specificity for different combinations of control performance limits (p = 95%, 98%, 99%), number of target locations with fixations outside control performance limits (k = 0 to 25) and number of repeated target presentations (n = 1 to 20).

RESULTS: Controls made a median of two to three fixations (twenty-fifth to seventy-fifth percentile: two to four) to locate the target depending on location. A VF was flagged "abnormal" when the number of fixations was greater than the p = 99% for k = 3 or more locations with n = 2 repeated presentations, giving 85% sensitivity and 95.2% specificity. The median test time for controls was 85.71 (twenty-fifth to seventy-fifth percentile: 66.49-113.53) seconds.

CONCLUSION: Our prototype test demonstrated effective and efficient screening of abnormal areas in central vision.

TRANSLATIONAL RELEVANCE: Visual search behavior can be used to detect central vision loss and may produce results that relate well to performance in natural visual environments.

Original languageEnglish
Article number34
Number of pages12
JournalTranslational vision science & technology
Issue number2
Publication statusPublished - 1 Feb 2022
Externally publishedYes


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