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Related Concept Videos

Higher Mental Functions of Brain: Learning and Memory01:26

Higher Mental Functions of Brain: Learning and Memory

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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...
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Associative Learning01:27

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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...
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Observational Learning01:12

Observational Learning

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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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Purposive Learning01:22

Purposive 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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Introduction to Learning01:18

Introduction to Learning

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Learning is the process of acquiring knowledge or skills through practice or experience, leading to long-lasting behavioral changes. This acquisition occurs through interaction with the environment and requires practice or experience. For instance, mastering a skill such as surfing requires considerable practice and experience, highlighting the essential role of repeated interactions with the environment in learning.
In contrast to learned behaviors, unlearned behaviors such as crying, sexual...
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Cognitive Learning01:21

Cognitive Learning

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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.
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Updated: Nov 1, 2025

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
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Adaptive learning is structure learning in time.

Linda Q Yu1, Robert C Wilson2, Matthew R Nassar1

  • 1Carney Institute for Brain Sciences, Brown University, 164 Angell Street, Providence, RI, 02912, USA.

Neuroscience and Biobehavioral Reviews
|June 18, 2021
PubMed
Summary
This summary is machine-generated.

Humans learn flexibly by combining information sources and adapting to new data. This adaptive learning optimizes decision-making by inferring context and transferring knowledge across situations.

Keywords:
Adaptive learningBayesian inferenceEvent segmentationGrid codeReversal learningStructure learning

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Area of Science:

  • Cognitive Psychology
  • Neuroscience
  • Machine Learning

Background:

  • Humans exhibit flexible information use, integrating multiple sources over time to inform decisions.
  • Individuals rationally adjust information reliance based on environmental statistics and personal uncertainty.
  • Knowledge transfer across different situations highlights sophisticated learning capabilities.

Purpose of the Study:

  • To review psychological and neural mechanisms of adaptive and structure learning.
  • To outline how humans pool relevant information, demarcate contexts, and prevent interference.
  • To provide a unified view of how the brain uses temporal structure for optimized learning.

Main Methods:

  • Review of psychological and neural mechanisms.
  • Analysis of information pooling, context demarcation, and interference prevention.
  • Examination through the lens of optimal inference.

Main Results:

  • Flexible learning relies on inferring context to guide information integration and separation.
  • The brain exploits temporal structure to optimize learning through adaptive strategies.
  • A unified multi-system view bridges concepts from multiple fields.

Conclusions:

  • Optimal inference provides a framework for understanding flexible and adaptive learning.
  • The brain employs sophisticated mechanisms to manage information across different contexts.
  • Understanding these processes offers insights into human learning and decision-making.