Visual Search Task
Introduction
The visual search task investigates how we find target objects in complex scenes using vision. Related research began in the late 1970s with the work of Anne Treisman. A key finding is that when a target is defined by a single feature — for example, a red triangle among green triangles — it is detected in parallel and seems to "pop out": reaction time stays nearly flat as the number of items grows. This version runs both a feature-search and a conjunction-search condition so you can compare the two search modes directly.
When the target is defined by a combination of features — for example, a red circle among red squares and green circles — search typically becomes effortful and serial: reaction time grows roughly linearly with set size, and this increase is called the "search slope". This is an educational adaptation of the Treisman & Gelade (1980) paradigm with simplified geometric stimuli and web-adapted set sizes (8, 16, 24); it is intended for self-exploration, not research or clinical use.
Experiment Entry
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Frequently Asked Questions
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What is the Visual Search task?
Each round shows a grid of colored shapes. In the feature condition you look for a red triangle among green triangles; in the conjunction condition you look for a red circle among red squares and green circles. Press the space bar (or click the display) as soon as you find the target; if there is none, simply wait. The experiment compares reaction times across set sizes 8, 16, and 24 in both conditions.
How is my performance calculated?
For each condition and set size, the average reaction time of correct target-present trials is computed, and a straight line (least-squares slope in ms per item) is fitted to those averages. Responses faster than 150 ms and incorrect trials are excluded from the reaction-time averages; target-absent accuracy is reported separately.
What do my search times indicate?
The slope of reaction time against set size is the key measure. A near-zero slope in the feature condition indicates parallel, pop-out search; a clearly positive slope in the conjunction condition indicates serial attentional checking of items, following the logic of feature-integration theory.
Why do some targets pop out?
When a target differs in a single feature such as color or shape, it is found equally fast at any set size, because early vision detects elementary features everywhere at once. That is why the red triangle among green triangles feels effortless.
What makes real-world search slow?
Clutter, low contrast between target and distractors, and feature conjunctions — the same factors that make radiology, security screening, and icon search demanding.
Is this the original Treisman & Gelade experiment?
No. It is an educational, web-based adaptation: the stimuli are simplified geometric shapes, set sizes are reduced to 8, 16, and 24, and the session is shortened. It is suitable for self-exploration and demonstration, not for research-grade or clinical measurement.
References
- Treisman, A. M., & Gelade, G. (1980). A feature-integration theory of attention. Cognitive Psychology, 12(1), 97-136. 10.1016/0010-0285(80)90005-5
- Wolfe, J. M. (1998). Visual search. In H. Pashler (Ed.), Attention (pp. 13-73). Psychology Press.
- Wolfe, J. M. (1994). Guided Search 2.0: A revised model of visual search. Psychonomic Bulletin & Review, 1(2), 202-238. 10.3758/BF03200774
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Further Reading
- Treisman, A. (1977). Focussed attention in the perception and retrieval of multidimensional stimuli. Perception and Psychophysics, 9, 40-50.
- Treisman, A., & Gelade, G. (1980). A feature integration theory of attention. Cognitive Psychology, 12, 97-136.
About This Experiment
This experiment is an educational adaptation for demonstration purposes. It is not a clinical diagnostic tool. Results reflect your performance in this specific session and should not be interpreted as an assessment of your cognitive abilities.
Data Privacy
Your experiment data is processed and stored locally in your browser. No data is uploaded to any server unless you explicitly export it.
