Visual Search Task
Version: v1 (current)
A classic attention paradigm measuring the efficiency of finding targets among distractors based on feature similarity.
Overview
Visual Search tasks present participants with arrays of items and ask them to locate a target among distractors. Search efficiency depends on whether the target "pops out" due to a unique feature (feature search: fast, parallel) or requires scrutiny of individual items (conjunction search: slow, serial). The relationship between response time and set size (number of items) reveals the underlying search strategy.
Feature searches (e.g., red circle among green circles) produce flat RT slopes (~5ms/item), indicating parallel processing. Conjunction searches (e.g., red circle among red squares and green circles) produce steep slopes (~20-40ms/item), indicating serial, attention-demanding search. This dissociation has been central to attention theories for decades.
Researchers use visual search to study attention, perception, working memory, and aging. Clinical applications include measuring attentional capacity in ADHD, neglect, and visual processing disorders.
Scientific Background
Classic Findings:
- Feature vs. Conjunction: Feature searches are efficient (parallel); conjunction searches are inefficient (serial)
- Set Size Effect: RT increases linearly with number of distractors in conjunction search
- Pop-Out: Targets with unique features are detected in <5ms/item regardless of set size
- Target-Present vs. Target-Absent: Absent trials show steeper slopes (~2x present slopes in serial search)
- Guidance: Partial information can guide attention to reduce effective set size
Search Types:
- Feature Search: Single dimension difference (color, shape, orientation)
- Conjunction Search: Target defined by combination of features
- Spatial Configuration: Targets defined by unique spatial arrangement
Seminal Papers:
- Treisman & Gelade (1980): Feature Integration Theory
- Wolfe (1994): Guided Search model
- Duncan & Humphreys (1989): Visual search and stimulus similarity
Why Researchers Use This Task
- Attention Research: Distinguish parallel vs. serial processing mechanisms
- Visual Processing: Study preattentive vs. attentive vision
- Clinical Assessment: Measure attentional capacity and visual processing speed
- Aging Studies: Track age-related slowing in visual search
- Interface Design: Test visibility of targets in complex displays (e.g., medical imaging)
Current Implementation Status
Fully Implemented:
- ✅ Feature search (single-dimension differences)
- ✅ Conjunction search (two-dimension combinations)
- ✅ Configurable set sizes (4, 8, 12, 16, etc.)
- ✅ Target-present and target-absent trials
- ✅ RT slope calculation by set size
- ✅ Practice trials with feedback
Partially Implemented:
- ⚠️ Limited to color and shape features (no orientation, size, motion)
- ⚠️ Fixed spatial layouts (random positions)
Not Yet Implemented:
- ❌ Contextual cueing (repeated configurations)
- ❌ Eye-tracking integration for scan paths
- ❌ Custom feature dimensions
Configuration Parameters
Display Options
| Parameter | Type | Default | Description |
|---|---|---|---|
| Item Font Size (px) | number | 48 | Font size of each search item (range 8-200) |
| Grid Columns | number | 6 | Number of columns in the search grid (range 2-20) |
| Grid Rows | number | 6 | Number of rows in the search grid (range 2-20) |
| Time-based mode | boolean | false | When enabled, trials auto-advance on the per-trial stimulus timeout; otherwise the trial is self-paced |
| Practice enabled | boolean | true | Whether a practice phase runs before the main trials |
Trial Spreadsheet
Trials (and practice trials) are defined row-by-row in a spreadsheet rather than as global parameters. Each row has the following columns:
| Column | Type | Default | Description |
|---|---|---|---|
| Set Size | number | 4 | Number of items shown (clamped to 1-50, and to grid capacity) |
| Target Present | checkbox | false | Whether the target is present on this trial |
| Target Feature | text | T | Character used for the target |
| Distractor Feature | text | L | Character used for the distractors |
| Search Type | dropdown | feature | feature or conjunction |
| Block | text | (empty) | Optional block label |
| Fixation (ms) | number | 500 | Pre-display fixation cross duration |
| Stimulus (ms) | number | 0 | Search display duration (0 = until response) |
The default main set ships with 12 rows (set sizes 8 and 12, feature and conjunction, target present/absent); the default practice set ships with 4 rows (set sizes 4 and 6).
Keyboard Shortcuts
Researchers can customize the keyboard bindings used during the task:
| Parameter | Type | Default | Description |
|---|---|---|---|
| Show keyboard hint | boolean | True | Display an on-screen hint showing the configured keys |
| Present key | key | P | Key for "target present" response |
| Present action label | text | "Target present" | Label shown in the keyboard hint |
| Absent key | key | A | Key for "target absent" response |
| Absent action label | text | "Target absent" | Label shown in the keyboard hint |
Data Output
Markers and Responses
The task records high-resolution timestamps in two separate collections:
Markers (stimulus_shown):
{
"type": "stimulus_shown",
"ts": "2024-01-01T00:00:01.000Z",
"hr": 1234.56,
"data": {
"trial_index": 1,
"stimulus_id": "visual_search_0_1",
"set_size": 8,
"target_present": true,
"search_type": "feature",
"expected_response": "present",
"block": "main",
"is_practice": false
}
}
Response Data:
{
"trial_index": 1,
"stimulus_id": "visual_search_0_1",
"source": "keyboard",
"raw_key": "p",
"set_size": 8,
"target_present": true,
"search_type": "feature",
"expected_response": "present",
"response_value": "present",
"response_correct": true,
"latency_ms": 485,
"block": "main",
"is_practice": false
}
Summary Artifact
A JSON file (visual_search_summary_<taskIndex>.json) with aggregated statistics including RT x set size slopes:
{
"task_kind": "visual_search",
"task_index": 0,
"total_trials": 40,
"overall": {
"total": 40,
"valid_responses": 38,
"correct": 35,
"accuracy": 0.921,
"mean_rt_ms": 1245,
"mean_correct_rt_ms": 1198,
"timeouts": 2
},
"breakdowns": {
"target_presence": {
"present": { "total": 20, "accuracy": 0.95, "mean_correct_rt_ms": 1050 },
"absent": { "total": 20, "accuracy": 0.89, "mean_correct_rt_ms": 1350 }
},
"search_type": {
"feature": { "total": 20, "accuracy": 0.98, "mean_correct_rt_ms": 850 },
"conjunction": { "total": 20, "accuracy": 0.86, "mean_correct_rt_ms": 1550 }
},
"set_size": {
"4": { "present": 900, "absent": 1100 },
"8": { "present": 1100, "absent": 1500 },
"16": { "present": 1400, "absent": 2200 }
}
},
"trials": [ /* per-trial data */ ]
}
When practice is enabled, an additional practice object (with its own total_trials, overall, breakdowns.target_presence, and trials) is appended.
Key metrics:
breakdowns.target_presence: Performance split by target-present vs. target-absent trialsbreakdowns.search_type: Performance split by feature vs. conjunction searchbreakdowns.set_size: Mean RT by set size for present and absent correct trials (for slope analysis)response_correct: Whether participant correctly identified target presence/absence
Example Research Configurations
Feature Search (Efficient)
Target: Red circle
Distractors: Green circles
Set Sizes: 4, 8, 12, 16
Expected: Flat slopes (<10ms/item), high accuracy
Conjunction Search (Inefficient)
Target: Red circle
Distractors: Red squares AND green circles
Set Sizes: 4, 8, 12, 16
Expected: Steep slopes (20-40ms/item present, 40-80ms/item absent)
Aging Comparison
Search: Both feature and conjunction
Set Sizes: 4, 8, 12 (smaller range for older adults)
Analysis: Compare slopes between age groups
Participant Experience
- Instructions: "A grid of letters will appear. Decide whether the target letter (shown at the top) is present or absent. Press P for present, A for absent."
- Practice: Try searches with feedback (default 4 trials, mixed set sizes)
- Main Trials: For each trial:
- Fixation point (500ms)
- "Target: X" header appears above the grid showing the current trial's target letter (driven by the
target_featurecolumn, defaults toT) - Search display appears with multiple items
- Scan for target as quickly as possible
- Respond present/absent
- Completion: See overall accuracy and average RT
All keyboard bindings are configurable by the researcher in the study configuration. The keys listed above are the defaults.
Design Recommendations
General Guidelines
- Set Size Range: Use 4-16 items for adults; 4-8 for children/clinical
- Target Presence: Balance present/absent (50/50) to prevent bias
- Trials per Condition: 10-15 trials per set size for stable slope estimates
- Feature Selection: Use highly discriminable features (avoid subtle color differences)
Designing Efficient (Feature) Search
- Single feature difference: color, shape, orientation, or size
- Large perceptual difference (red vs. green, not red vs. orange)
- Homogeneous distractors (all same)
Designing Inefficient (Conjunction) Search
- Target defined by 2+ features (red circle = red + circle)
- Each feature also present in distractors separately
- Requires checking feature combinations
Population-Specific Adaptations
Children (8+ years):
- Smaller set sizes (4, 6, 8)
- Larger items (60px)
- Simpler features (shape > color for young children)
- Fewer trials
Older Adults (65+):
- Larger items and spacing
- Fewer set sizes (4, 8, 12)
- Generous time limits
- Expect overall slowing but similar slope patterns
Clinical Populations:
- Neglect: Watch for left-right asymmetry in search
- ADHD: May show increased RT variability
- Visual processing disorders: Consider feature discriminability
Common Issues and Solutions
| Issue | Solution |
|---|---|
| No set size effect in conjunction search | Ensure target truly requires conjunction (check distractor types) |
| Set size effect in feature search | Target may not be sufficiently distinct; increase feature salience |
| High error rate on absent trials | Give more practice; emphasize accuracy over speed |
| Response bias (favoring present) | Balance target presence; provide accuracy feedback |
| Items overlap | Increase minimum spacing or reduce item size |
References
- Treisman, A. M., & Gelade, G. (1980). A feature-integration theory of attention. Cognitive Psychology, 12(1), 97-136.
- Wolfe, J. M. (1994). Guided Search 2.0: A revised model of visual search. Psychonomic Bulletin & Review, 1(2), 202-238.
- Duncan, J., & Humphreys, G. W. (1989). Visual search and stimulus similarity. Psychological Review, 96(3), 433-458.
- Wolfe, J. M., & Horowitz, T. S. (2017). Five factors that guide attention in visual search. Nature Human Behaviour, 1(3), 0058.
See Also
- Attentional Blink - Temporal attention limits
- Posner Cueing - Spatial attention orienting