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Related Concept Videos

Cognitive Learning01:21

Cognitive Learning

Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
Higher Mental Functions of Brain: Learning and Memory01:26

Higher Mental Functions of Brain: Learning and Memory

Memory is one of the most vital higher mental functions of the brain. Memory is closely related to learning because it enables us to retain information and experiences from our past to use them in our present life. It also helps us to remember facts, events, and skills, such as riding a bike or swimming. There are two types of memory — declarative memory, which involves memorizing facts or events, and procedural memory, which enables us to remember how to do something like writing or playing an...
Associative Learning01:27

Associative Learning

Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
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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Related Experiment Video

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Investigating the Neural Mechanisms of Aware and Unaware Fear Memory with fMRI
12:51

Investigating the Neural Mechanisms of Aware and Unaware Fear Memory with fMRI

Published on: October 6, 2011

Experience-dependent changes in human brain activation during contingency learning.

M W Schlund1, D Ortu

  • 1Department of Behavior Analysis, University of North Texas, Denton, TX 76203, USA. Michael.Schlund@unt.edu

Neuroscience
|October 15, 2009
PubMed
Summary

Learning to adapt involves understanding cues linked to rewards. This study used fMRI to show how brain activity in frontal and limbic regions changes during positive reinforcement learning, revealing key neural processes.

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Last Updated: Jun 19, 2026

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Area of Science:

  • Neuroscience
  • Cognitive Psychology
  • Neuroimaging

Background:

  • Adaptation to changing environments relies on learning response-reinforcer contingencies.
  • Understanding the neural basis of contingency learning is crucial for cognitive science.

Purpose of the Study:

  • To investigate brain activation changes in frontal and limbic regions during positive reinforcement learning using functional magnetic resonance imaging (fMRI).
  • To characterize the neural dynamics associated with the development of contingency control.

Main Methods:

  • Functional magnetic resonance imaging (fMRI) was employed to monitor brain activity.
  • Participants underwent nine reinforcement learning trials while behavioral data (accuracy, reaction time) were recorded.
  • Analysis focused on identifying linear and non-linear changes in brain activation patterns.

Main Results:

  • Contingency learning was associated with linear increases or inverted-U shaped activation changes in superior, medial, orbitofrontal cortex (OFC), amygdala, insula, and medial temporal lobe.
  • Parietal, occipital, and cerebellar regions showed linear decreases or U-shaped activation changes.
  • A positive correlation was observed between changes in OFC and amygdala activation, though individual variability was significant.

Conclusions:

  • Linear increases in OFC activation suggest its role in developing contingency control, even with stable behavior.
  • Individual differences in OFC-amygdala coupling highlight the need to explore subject variability in contingency learning.
  • Further research should refine experimental designs to better understand individual neural sensitivities and control for extraneous variables.