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Related Concept Videos

Concepts and Prototypes01:24

Concepts and Prototypes

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The human nervous system handles vast amounts of information by translating sensory stimuli into neural impulses, which the brain processes, creating thoughts expressed through language or stored as memories. The brain also synthesizes information from emotions and memories, which significantly influence thoughts and behaviors. This intricate process creates a comprehensive mental picture.
The brain organizes this information using concepts, which are mental categories grouping linguistic data,...
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Higher Mental Functions of Brain: Learning and Memory01:26

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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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Cognitive Learning01:21

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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.
Tolman introduced the idea that behavior is influenced by...
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Storage01:23

Storage

310
A schema is a mental framework that helps individuals organize and interpret information. Schemata, formed from previous experiences, influence how we process new information: how we encode it, the inferences we make, and how we retrieve it. For instance, a schema for what a typical classroom looks like might include desks, a teacher's desk, a whiteboard, and students in such an environment. This expectation helps us quickly understand and navigate new classrooms without needing to analyze...
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Natural and Artificial Concepts01:24

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In psychology, concepts can be divided into two categories: natural and artificial. Natural concepts are formed through direct or indirect experiences. For example, consider the concept of snow. If you live in a place with regular snowfall, such as Essex Junction, Vermont, you know snow through direct experiences. You’ve seen it fall, touched it, shoveled it, and played in it. You recognize its texture, appearance, and even its smell. In contrast, if you live on an island like Saint...
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Understanding Self-Concept01:20

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The self-concept encompasses individuals' beliefs about themselves, structured through cognitive frameworks known as self-schemas. These schemas function as mental representations of specific traits or behaviors, influencing how self-relevant information is perceived, processed, and remembered. For example, individuals who are schematic for body weight are more likely to interpret routine experiences—such as dining out or shopping—through the lens of that trait. Conversely, those...
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Brain Mechanisms of Concept Learning.

Dagmar Zeithamova1, Michael L Mack2, Kurt Braunlich3

  • 1Department of Psychology and Institute of Neuroscience, University of Oregon, Eugene, Oregon 97403, dasa@uoregon.edu mack@psych.utoronto.ca.

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience
|October 18, 2019
PubMed
Summary
This summary is machine-generated.

Concept learning builds organized knowledge by identifying similarities and differences in experiences. This review explores how brain systems, including the hippocampus and prefrontal cortex, support flexible concept learning.

Keywords:
categorizationcomputational modelingfMRIhippocampusparietal cortexprefrontal cortex

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Area of Science:

  • Cognitive Neuroscience
  • Computational Neuroscience

Background:

  • Concept learning is crucial for cognition, enabling organized knowledge acquisition.
  • Prior research often focused on dissociating brain systems involved in concept learning.

Purpose of the Study:

  • To review recent advances in understanding the neural basis of concept learning.
  • To examine computational and neural approaches to concept learning theories.
  • To detail the roles of specific brain regions in concept learning.

Main Methods:

  • Review of recent research combining computational modeling with neural measures.
  • Analysis of studies investigating specific computations and representations in concept learning.
  • Detailed discussion of brain regions like the hippocampus and prefrontal cortex.

Main Results:

  • Novel analytical approaches reveal specific computational roles in concept learning.
  • Engagement of the hippocampus, ventromedial, and lateral prefrontal cortices is modulated by experience coherence and learning goals.
  • Lateral parietal cortex also plays a role in concept learning.

Conclusions:

  • Flexible concept learning arises from the interaction of multiple brain systems (learning, memory, attention, perception, reward).
  • This mechanism adapts to diverse category structures and integrates motivational states.
  • Concept learning offers a valuable model for studying neural dynamics in complex behaviors.