Related Experiment Video
Updated: Jan 8, 2026
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Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
Published on: February 23, 2019
9.1K
Association: one term, five concepts
Thomas F Chartier1, Joël Fagot2, Arnaud Rey1
1Centre de Recherche en Psychologie et Neurosciences, CNRS & Aix-Marseille Université, UMR 7077, Bâtiment 9 Case D, 3 place Victor Hugo, Marseille 13331, France.
Neuroscience and Biobehavioral Reviews
|December 17, 2025
Summary
The term "association" has multiple meanings across mind, brain, and behavior studies. This review identifies five distinct categories of associative links to clarify research and foster interdisciplinary collaboration.
Area of Science:
- Neuroscience
- Psychology
- Computer Science
- Linguistics
Background:
- The term "association" is widely used across disciplines studying mind, brain, and behavior.
- Current usage of "association" lacks clear distinctions, leading to ambiguity.
- This ambiguity hinders clear communication and comparison of findings.
Purpose of the Study:
- To delineate and characterize distinct meanings of "association" in scientific literature.
- To propose a framework of five categories for associative links.
- To improve clarity in research on associations in biological and artificial systems.
Main Methods:
- Comprehensive literature review across neuroscience, psychology, computer science, and linguistics.
- Analysis of the term "association" and its varied applications.
- Development of a categorization system for associative links.
Main Results:
- Identification of five distinct categories of associative links.
- Demonstration of how these categories address issues of polysemy and synonymy.
- Establishment of a descriptive toolset for associationist frameworks.
Conclusions:
- Distinguishing between the five types of associative links enhances research transparency.
- The proposed terminology facilitates interdisciplinary dialogue and collaboration.
- This framework offers improved tools for understanding associations in both natural and artificial systems.
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