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Visual Statistical Learning TASK
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Visual Statistical Learning (VSL) refers to the ability to implicitly detect and extract regularities or patterns in sequences of visual stimuli over time. In a typical VSL task, participants are exposed to sequences of shapes, symbols, or objects that follow certain probabilistic rules—such as specific transitions being more likely than others. Without explicit instruction or awareness, individuals learn the underlying structure and are later able to predict, categorize, or respond to these patterns more accurately than would be expected by chance. VSL is considered a domain-general learning mechanism that plays a crucial role in cognitive functions such as language acquisition, reading, and object recognition.

Definition contributed by MBryłka
Visual Statistical Learning has been asserted to measure the following CONCEPTS
No concepts assertions have been added.

Phenotypes associated with Visual Statistical Learning

Disorders

No associations have been added.

Traits

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Behaviors

No associations have been added.


IMPLEMENTATIONS of Visual Statistical Learning
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EXTERNAL DATASETS for Visual Statistical Learning
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CONDITIONS

Experimental conditions are the subsets of an experiment that define the relevant experimental manipulation.

CONTRASTS

You must specify conditions before you can define contrasts.


In the Cognitive Atlas, we define a contrast as any function over experimental conditions. The simplest contrast is the indicator value for a specific condition; more complex contrasts include linear or nonlinear functions of the indicator across different experimental conditions.

INDICATORS

No indicators have yet been associated.

An indicator is a specific quantitative or qualitative variable that is recorded for analysis. These may include behavioral variables (such as response time, accuracy, or other measures of performance) or physiological variables (including genetics, psychophysiology, or brain imaging data).

Term BIBLIOGRAPHY