Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Implicit Memories

Implicit Memories

Implicit memories, also known as non-declarative memories, are long-term memories that function outside of conscious awareness. These memories influence behavior and skills without explicit knowledge. This type of memory is evident in tasks like playing tennis, snowboarding, and texting. Implicit memory has three subsystems: procedural memory, conditioning, and priming. This type of memory is essential in various activities, from everyday tasks to specialized skills.
One key aspect of implicit...

Implicit Personality Theories

Implicit Personality Theories

Implicit personality theory explains how individuals make assumptions about the relationships between personality traits, behaviors, and character types. When people learn that someone possesses a particular trait, they tend to infer the presence of other related characteristics, forming a cohesive impression. This cognitive shortcut plays a crucial role in social interactions and interpersonal judgments.Central Traits and Their InfluenceSolomon Asch's seminal 1946 study highlighted the power...

Explicit Memories

Explicit Memories

Explicit memories, also known as declarative memories, are consciously remembered, recalled, and reported. Studying for a chemistry exam involves material that will become part of explicit memory. There are two types of explicit memory: episodic and semantic.
Episodic memory contains information about personally experienced events and is reported as a story. An example of episodic memory is recalling a birthday celebration. This type of memory includes the what, where, and when of an event, as...

Attitudes

Attitudes

Attitude is our evaluation of a person, an idea, or an object. We have attitudes for many things ranging from products that we might pick up in the supermarket to people around the world to political policies. Typically, attitudes are favorable or unfavorable: positive or negative (Eagly & Chaiken, 1993). And, they have three components: an affective component (feelings), a behavioral component (the effect of the attitude on behavior), and a cognitive component (belief and knowledge;...

The Representativeness Heuristic

The Representativeness Heuristic

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.

Nonconscious Mimicry

Nonconscious Mimicry

Nonconscious mimicry occurs when individuals alter their mannerisms to match the behaviors and expressions of those nearby, without intention.

You might also read

Related Articles

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

Sort by

Same author

CODE beyond FAIR: a roadmap for reusable research software.

Scientific data·2026

Same author

Social hierarchy influences monkeys' risky decisions.

Communications biology·2026

Same author

Stop treating code like an afterthought: record, share and value it.

Nature·2025

Same author

A dynamical computational model of theta generation in hippocampal circuits to study theta-gamma oscillations during neurostimulation.

eLife·2024

Same author

Computational benefits of structural plasticity, illustrated in songbirds.

Neuroscience and biobehavioral reviews·2021

Same author

Sustainable computational science: the ReScience initiative.

PeerJ. Computer science·2021

Same journal

Exploiting audio-visual modalities in videos: Object detection via multi-stage bilateral coupling network.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

Reliability-aware modality completion with cross-modal distillation for federated learning with missing modalities.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

IGFD-Net: Illumination-guided frequency decoupling for polarization image fusion.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

Multiple-Strategies dung beetle optimizer and its applications in engineering optimization and bankruptcy prediction.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

Aggregating global-scale pixel-wise forgery cues within a graph.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

Finite-Time intermittent control for secure synchronization of Neutral-Type stochastic delayed neural networks under aperiodic DoS attacks.

Neural networks : the official journal of the International Neural Network Society·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 25, 2026

Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning

Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning

Published on: January 29, 2020

Implicit and explicit representations.

Nicolas P Rougier¹

¹INRIA Nancy - Grand Est, 615, Rue du Jardin Botanique, 54 600 Villers-Lès-Nancy, France. Nicolas.Rougier@loria.fr

Neural Networks : the Official Journal of the International Neural Network Society

|February 11, 2009

Summary

This summary is machine-generated.

This study introduces a computational framework to understand grounded representations, exploring the difference between implicit and explicit representations in cognitive science. It addresses the symbol grounding problem, moving beyond mere token processing for higher brain functions.

More Related Videos

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation

Published on: March 1, 2017

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses

Published on: January 7, 2019

Related Experiment Videos

Last Updated: Jun 25, 2026

Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning

Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning

Published on: January 29, 2020

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation

Published on: March 1, 2017

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses

Published on: January 7, 2019

Area of Science:

Cognitive Science
Computational Neuroscience
Artificial Intelligence

Background:

The symbol grounding problem, a significant challenge in cognitive science, questions how symbols acquire meaning beyond arbitrary tokens.
Understanding how symbols connect to real-world referents is crucial for explaining higher brain functions like language and cognition.

Purpose of the Study:

To present a novel computational framework for investigating the nature of grounded representations.
To elucidate the distinction between implicit and explicit representations within this framework.

Main Methods:

Development of a computational framework to model symbol grounding.
Introduction of two distinct models to differentiate between implicit and explicit representations.

Main Results:

The proposed framework offers a new perspective on how symbols become meaningful.
The models highlight key differences in how implicit and explicit representations function.

Conclusions:

The computational framework provides a valuable tool for advancing research on grounded representations.
Further exploration of implicit and explicit representations can deepen our understanding of cognition and language.