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

Storage01:23

Storage

142
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...
142
The Representativeness Heuristic02:13

The Representativeness Heuristic

16.4K
The representative heuristic describes a biased way of thinking, in which you unintentionally stereotype someone or something. For example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.
16.4K
Associative Learning01:27

Associative Learning

628
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...
628
Protein Networks02:26

Protein Networks

4.1K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.1K
Deductive Reasoning01:16

Deductive Reasoning

60.8K
Deductive reasoning, or deduction, is the type of logic used in hypothesis-based science. In deductive reasoning, the pattern of thinking moves in the opposite direction as compared to inductive reasoning, which means that it uses a general principle or law to predict specific results. From those general principles, a scientist can deduce and predict the specific results that would be valid as long as the general principles are valid.
For example, a researcher can deduce specific predictions...
60.8K
Natural and Artificial Concepts01:24

Natural and Artificial Concepts

284
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...
284

You might also read

Related Articles

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

Sort by
Same author

Beyond analogy: Pragmatic constraints on metaphor production and comprehension.

Journal of experimental psychology. General·2026
Same author

Advancing with age: Older adults excel in comprehension of novel metaphors.

Psychology and aging·2024
Same author

Zero-shot visual reasoning through probabilistic analogical mapping.

Nature communications·2023
Same author

Aesthetic preferences for prototypical movements in human actions.

Cognitive research: principles and implications·2023
Same author

Emergent analogical reasoning in large language models.

Nature human behaviour·2023
Same author

In situ bidirectional human-robot value alignment.

Science robotics·2022
Same journal

Perception and action as one: Re-integrating research on human action through event files.

Psychological review·2026
Same journal

Associative learning explains "intuitive statistics" in animals.

Psychological review·2026
Same journal

A reciprocal model of practice and skill: Navigating between dropout and expertise.

Psychological review·2026
Same journal

The relative psychometric function: A general analysis framework for relating psychological processes.

Psychological review·2026
Same journal

A taxonomy of discriminatory behavior.

Psychological review·2026
Same journal

Extreme-value signal detection theory for recognition memory: The parametric road not taken.

Psychological review·2026
See all related articles

Related Experiment Video

Updated: Sep 27, 2025

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.2K

Probabilistic analogical mapping with semantic relation networks.

Hongjing Lu1, Nicholas Ichien1, Keith J Holyoak1

  • 1Department of Psychology.

Psychological Review
|April 7, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a computational model for analogical reasoning, explaining how humans map concepts across different domains. The model successfully predicts human performance in analogy tasks, highlighting the importance of semantic representations.

More Related Videos

A Semantic Priming Event-related Potential ERP Task to Study Lexico-semantic and Visuo-semantic Processing in Autism Spectrum Disorder
08:17

A Semantic Priming Event-related Potential ERP Task to Study Lexico-semantic and Visuo-semantic Processing in Autism Spectrum Disorder

Published on: April 12, 2018

10.7K
Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

629

Related Experiment Videos

Last Updated: Sep 27, 2025

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.2K
A Semantic Priming Event-related Potential ERP Task to Study Lexico-semantic and Visuo-semantic Processing in Autism Spectrum Disorder
08:17

A Semantic Priming Event-related Potential ERP Task to Study Lexico-semantic and Visuo-semantic Processing in Autism Spectrum Disorder

Published on: April 12, 2018

10.7K
Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

629

Area of Science:

  • Cognitive Science
  • Computational Neuroscience
  • Artificial Intelligence

Background:

  • Flexible analogical reasoning in humans relies on identifying and mapping relations between concepts across different domains.
  • Previous models focused on learning semantic relations from word embeddings, but lacked a robust mechanism for cross-domain concept mapping.

Purpose of the Study:

  • To develop a novel computational model for analogical mapping between two analogs.
  • To validate the model's predictions against human performance in both novel and classic analogy tasks.
  • To explore the model's potential for analog retrieval.

Main Methods:

  • Developed a Bayesian framework for probabilistic graph matching.
  • Constructed semantic relation networks from distributed representations of concepts and their relations.
  • Compared model predictions with human behavioral data from adults and children on multi-relational mapping tasks.

Main Results:

  • The computational model accurately accounts for a wide range of human analogical mapping phenomena.
  • The model demonstrates success in tasks requiring the integration of multiple relational comparisons.
  • The approach shows promise for extension to analog retrieval.

Conclusions:

  • Human-like analogical mapping can emerge from comparison mechanisms applied to rich semantic representations.
  • The model provides a computational account for how humans bridge conceptual gaps in analogical reasoning.
  • This work advances our understanding of the cognitive underpinnings of flexible reasoning.