Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Cognitive Learning01:21

Cognitive Learning

1.4K
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...
1.4K
Associative Learning01:27

Associative Learning

1.5K
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...
1.5K
Purposive Learning01:22

Purposive Learning

542
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...
542
Higher Mental Functions of Brain: Learning and Memory01:26

Higher Mental Functions of Brain: Learning and Memory

2.2K
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...
2.2K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Identifying networks within an fMRI multivariate searchlight analysis.

Neuropsychologia·2026
Same author

Mechanisms of semantic composition in older adults: control, semantic processing, and imagery.

Frontiers in psychology·2026
Same author

Reduced dependence on sensorimotor processing in the brain is associated with higher math skills in adults.

Cerebral cortex (New York, N.Y. : 1991)·2026
Same author

Meta-analytic evidence for fast mapping in healthy adults.

Learning & memory (Cold Spring Harbor, N.Y.)·2026
Same author

Seeking cognitive and neural specificity in occipitotemporal cortex.

Cognitive neuroscience·2025
Same author

The Neural Consequences of Semantic Composition.

Journal of cognitive neuroscience·2025

Related Experiment Video

Updated: Feb 22, 2026

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
08:05

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Published on: June 30, 2020

8.1K

Variation across individuals and items determine learning outcomes from fast mapping.

Marc N Coutanche1, Griffin E Koch1

  • 1Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA.

Neuropsychologia
|October 1, 2017
PubMed
Summary

Fast mapping word learning is influenced by foil typicality and memory system use. Atypical foils cause competition, typical foils facilitate, especially for semantic memory users.

Keywords:
CortexFast mappingHippocampusLearningMemoryWords

More Related Videos

Using MazeSuite and Functional Near Infrared Spectroscopy to Study Learning in Spatial Navigation
20:12

Using MazeSuite and Functional Near Infrared Spectroscopy to Study Learning in Spatial Navigation

Published on: October 8, 2011

31.1K
A Within-Subject Experimental Design using an Object Location Task in Rats
09:28

A Within-Subject Experimental Design using an Object Location Task in Rats

Published on: May 6, 2021

5.3K

Related Experiment Videos

Last Updated: Feb 22, 2026

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
08:05

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Published on: June 30, 2020

8.1K
Using MazeSuite and Functional Near Infrared Spectroscopy to Study Learning in Spatial Navigation
20:12

Using MazeSuite and Functional Near Infrared Spectroscopy to Study Learning in Spatial Navigation

Published on: October 8, 2011

31.1K
A Within-Subject Experimental Design using an Object Location Task in Rats
09:28

A Within-Subject Experimental Design using an Object Location Task in Rats

Published on: May 6, 2021

5.3K

Area of Science:

  • Cognitive Psychology
  • Neuroscience
  • Linguistics

Background:

  • Fast mapping enables rapid word learning in adults, but its underlying mechanisms remain unclear.
  • Existing research highlights neurobiological and behavioral markers associated with fast mapping, such as quick lexical integration.
  • Understanding factors that modulate fast mapping outcomes is crucial for elucidating its cognitive underpinnings.

Purpose of the Study:

  • To investigate how the typicality of learning items (foils) and individual memory system preferences affect fast mapping outcomes.
  • To examine the relationship between foil typicality, lexical competition, and recognition performance in adult learners.
  • To determine if semantic memory plays a distinct role in modulating fast mapping effects.

Main Methods:

  • Ninety participants learned new words using a fast mapping approach with systematically varied foil typicality.
  • The Survey of Autobiographical Memory (SAM) was used to assess individual reliance on semantic, episodic, and spatial memory.
  • Lexical competition and recognition performance were quantified to measure learning outcomes.
  • An independent dataset was used to replicate the relationship between foil typicality and lexical competition.

Main Results:

  • Foil typicality significantly influenced lexical competition after fast mapping; atypical foils led to competition, while typical foils led to facilitation.
  • Individual differences in memory system employment modulated these effects, particularly for participants with a strong semantic memory preference.
  • The observed relationship between foil atypicality and lexical competition was replicated in an independent dataset.
  • These effects were specific to fast mapping and not observed with other learning approaches.

Conclusions:

  • The semantic properties of foils used in fast mapping critically influence subsequent lexical integration and competition.
  • Individual reliance on semantic memory plays a key role in how learners process and integrate newly acquired words.
  • Findings suggest that optimizing foil characteristics and considering learner memory profiles can enhance fast mapping efficiency.