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Related Concept Videos

Observational Learning01:12

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Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
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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...
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Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Can you relate this to the phrase "Hindsight is 20/20" now? 
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Related Experiment Video

Updated: Jan 17, 2026

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
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Prior beliefs modulate rule-based learning in dynamic probabilistic environments: Insights from a hierarchical

Weiwei Zhang1, Linyan Liu1, John W Schwieter2

  • 1Institute of Psychological and Brain Science, Liaoning Normal University, Dalian 116029, China; Key Laboratory of Brain and Cognitive Neuroscience, Dalian, Liaoning Province 116029, China.

Behavioural Brain Research
|September 14, 2025
PubMed
Summary

Humans show symbolic flexibility, adapting learning strategies for language and math rules in changing environments. Prior beliefs influence learning speed and brain activity, highlighting neural adaptability.

Keywords:
Prior beliefProbabilistic environmentsRight caudate nucleusRule learningSymbol flexibility

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Area of Science:

  • Cognitive Neuroscience
  • Decision Making
  • Symbolic Learning

Background:

  • Humans utilize diverse rules for decision-making.
  • Symbolic flexibility allows effective acquisition of different symbol associations.
  • Uncertainty exists regarding symbol flexibility in dynamic environments for language and non-language rules.

Purpose of the Study:

  • To investigate symbol flexibility in dynamic environments for language and non-language rules.
  • To examine how prior beliefs and environmental uncertainty shape learning.
  • To identify neural correlates of rule-specific learning.

Main Methods:

  • Integration of a probabilistic reversal learning task and a picture-word matching task.
  • Creation of dynamic environments with varying reward probabilities.
  • Computational modeling of behavioral and fMRI data.

Main Results:

  • Individuals demonstrated symbol flexibility, learning distinct symbol systems with divergent patterns.
  • Increased prior belief value led to faster non-language rule learning but slower language rule learning.
  • The right caudate nucleus showed rule-specific activation patterns influenced by probability and rule type.

Conclusions:

  • Prior beliefs dynamically shape learning strategies across rule types and environmental uncertainties.
  • Neural and behavioral adaptability underlies symbol flexibility.
  • Symbol flexibility is maintained in dynamic environments for both language and non-language rules.