Visual Statistical Learning

Overview

Source: Laboratory of Jonathan Flombaum—Johns Hopkins University

The visual environment contains massive amounts of information involving the relations between objects in space and time; certain objects are more likely to appear in the vicinity of other objects. Learning these regularities can support a wide array of visual processing, including object recognition. Unsurprisingly, then, humans appear to learn these regularities automatically, quickly, and without conscious awareness. The name for this type of implicit learning is visual statistical learning. In the laboratory, it is studied with an incidental-encoding paradigm: participants observe a stream of nonsense objects and complete a cover-task, a task unrelated to the underlying statistical structure in the stream. But statistical structure is present, and subsequent to a short exposure period—as short as 10 min in some experiments—a familiarity test reveals the extent of learning by the participants.

This video will demonstrate standard methods for inducing and testing visual statistical learning.

Procedure

1. Generate a set of nonsense objects and arrange them into a triplet structure.

Often visual statistical learning is studied with simple objects like the set below. Generate a set of objects, and then group them into triplets (Figure 1).

Figure 1. Sample stimuli grouped into triplets for visual statistical learning. In the learning segment of an experiment, triplets will appear in random order,

Results

Because each familiarity test includes one triplet and one foil (a randomly generated non-triplet), chance performance overall is 50%. Score each trial in terms of whether the participant chose the triplet or the foil as more familiar, and selecting triplets more than half of the time constitutes a demonstration of statistical learning. After testing 10-20 participants, average together the rate of choosing the familiar triplet among all the participants. A simple bar graph is a good way to visualize the main effect (

Application and Summary

Visual statistical learning has been utilized as a starting point for investigating a variety of issues in learning, perception, and memory. These include the influence and necessity of attention for learning, the brain areas involved in implicit visual memory and object recognition, as well as differences and similarities in learning about spatial vs. temporal structure. Visual statistical learning is also thought to be an example of a broader class of statistical learning mechanisms, including auditory statistical, whi