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Related Concept Videos

Real-World Application of Classical Conditioning01:15

Real-World Application of Classical Conditioning

Classical conditioning not only includes the initial pairing of stimuli but also extends to more complex forms, such as higher-order conditioning. Higher-order conditioning involves creating associations beyond the primary conditioned stimulus, resulting in a chain of conditioned responses.
Higher-order, or second-order, conditioning occurs when a neutral stimulus becomes associated with an already established conditioned stimulus through repeated pairings. For instance, if a dog has been...
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Generalization, Discrimination, and Extinction01:24

Generalization, Discrimination, and Extinction

Generalization, discrimination, and extinction are key concepts in operant conditioning that influence how behaviors are learned and maintained.
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Reinforcement Schedules01:24

Reinforcement Schedules

Positive reinforcement is a powerful method for teaching new behaviors to both animals and humans. B.F. Skinner demonstrated this with his experiments using rats in a Skinner box. When a rat pressed a lever, it received a food pellet. This immediate reward encouraged the rat to repeat the behavior. This method, where a reward follows every instance of the behavior, is known as continuous reinforcement. It is highly effective for establishing new behaviors quickly.
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Timing and Consequences on Behavior01:08

Timing and Consequences on Behavior

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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: Jun 11, 2026

A Fully Automated and Highly Versatile System for Testing Multi-cognitive Functions and Recording Neuronal Activities in Rodents
09:13

A Fully Automated and Highly Versatile System for Testing Multi-cognitive Functions and Recording Neuronal Activities in Rodents

Published on: May 3, 2012

Neural systems implicated in delayed and probabilistic reinforcement.

Rudolf N Cardinal1

  • 1Department of Experimental Psychology, University of Cambridge, Downing Street, Cambridge, UK. Rudolf.Cardinal@pobox.com

Neural Networks : the Official Journal of the International Neural Network Society
|August 30, 2006
PubMed
Summary
This summary is machine-generated.

Agents face challenges learning and choosing with uncertain or delayed rewards. Individual differences in delay and uncertainty sensitivity link to impulsivity and risk-taking behaviors.

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Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents
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Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Behavioral Economics

Background:

  • Agents must learn and make choices based on uncertain or delayed rewards.
  • These processes occur in both implicit (stimulus-response) and explicit (action-outcome-value) representational systems.
  • Individual differences in sensitivity to delay and uncertainty are linked to impulsivity and risk-taking.

Purpose of the Study:

  • To review theoretical problems in learning and choice under delayed/uncertain reinforcement.
  • To examine the relationship between learning and choice processes with delayed/uncertain reinforcement.
  • To explore the neurobiological underpinnings of delay and uncertainty discounting.

Main Methods:

  • Theoretical review of learning and decision-making under uncertainty and delay.
  • Examination of individual differences in sensitivity to reward timing and probability.
  • Analysis of the roles of specific neuromodulators and brain structures.

Main Results:

  • Learning and choice under delayed/uncertain reinforcement are related but dissociable.
  • Neuromodulators (serotonin, dopamine, noradrenaline) and specific brain regions are implicated in discounting.
  • Key structures include nucleus accumbens, orbitofrontal cortex, amygdala, and prefrontal cortex.

Conclusions:

  • Understanding delay and uncertainty discounting is crucial for explaining impulsivity and risk-taking.
  • Neuromodulatory systems and interconnected brain structures mediate these complex decision-making processes.
  • Further research is needed to fully elucidate the mechanisms underlying these phenomena.