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Related Concept Videos

Purposive Learning01:22

Purposive Learning

E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a bonus...
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Related Experiment Video

Updated: May 27, 2026

Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning
05:33

Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning

Published on: January 29, 2020

Probabilities in implicit learning.

Philip Tseng1, Tzu-Yu Hsu, Ovid J L Tzeng

  • 1Institute of Cognitive Neuroscience, National Central University, 300 Jhongda Road, Jhongli City, Taoyuan County 32001, Taiwan. tsengphilip@gmail.com

Perception
|December 2, 2011
PubMed
Summary
This summary is machine-generated.

The visual system implicitly learns from context, with higher probability contexts improving visual search more effectively. This implicit learning is sensitive to event frequency and temporal aspects, similar to explicit learning.

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Related Experiment Videos

Last Updated: May 27, 2026

Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning
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Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
08:05

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Published on: June 30, 2020

Area of Science:

  • Cognitive Psychology
  • Neuroscience
  • Visual Perception

Background:

  • The visual system excels at learning environmental regularities, including implicit contextual cuing.
  • Contextual cuing facilitates visual search through learned spatial configurations without conscious effort.

Purpose of the Study:

  • To investigate if implicit learning is sensitive to statistical properties, specifically the probability of events.
  • To determine if highly probable events are learned better than less probable ones during implicit learning.

Main Methods:

  • Systematically varying context repetition frequencies to manipulate learning degrees.
  • Measuring search efficiency across different contextual probabilities.

Main Results:

  • Search efficiency increased proportionally with contextual probabilities.
  • Higher probabilities led to greater cuing effects, even with constant exposure.
  • Implicit learning is influenced by both frequency and temporal aspects of context repetition.

Conclusions:

  • The visual system learns both predictive visual contexts and their occurrence probabilities implicitly.
  • Implicit learning's facilitatory effects are modulated by associative strengths, mirroring explicit learning.
  • Statistical properties like probability and temporal factors significantly influence implicit learning in visual search.