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

Higher Mental Functions of the Brain: Language

Higher Mental Functions of the Brain: Language

Language is a system of communication that allows the expression of thoughts, ideas, and feelings. The brain processes language in both hemispheres.
Language formation and comprehension take place in the dominant hemisphere. The dominant hemisphere is responsible for understanding the meaning of spoken, written, or sign language, as well as the ability to communicate. For most people, the left hemisphere is the dominant one. The right hemisphere, then, gives tone and emotional context to the...

Language and Cognition

Language and Cognition

Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.

Elaborative Rehearsals

Elaborative Rehearsals

Elaborative rehearsal is a crucial cognitive strategy that strengthens information encoding in long-term memory by making meaningful connections between new data and pre-existing knowledge. This approach contrasts with maintenance rehearsal, which involves simple repetition without delving into the significance of the information. While maintenance rehearsal might temporarily keep information active in short-term memory, it is less effective for long-term retention.
The effectiveness of...

Decision Making

Decision Making

Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...

Components of Language

Components of Language

Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs. “eh”). Phonemes combine to...

You might also read

Related Articles

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

Sort by

Same author

Circular inference in visual cortical hierarchies in schizophrenia.

Psychiatry and clinical neurosciences·2026

Same author

Cerebellar Transcranial Alternating Current Stimulation in the Theta Band Prevents Recall of the Initial Fear Association After Extinction Training.

Human brain mapping·2026

Same author

Patient-reported satisfaction with thermal water-based cosmetic products in breast cancer patients undergoing chemotherapy: a feasibility study.

Cancer treatment and research communications·2026

Same author

What Is New in the German S3 Guideline on Gastric Cancer: Diagnosis, Staging, and Treatment.

Oncology research and treatment·2026

Same author

RGD Modification of Poly(2-oxazoline) Cryogels: Investigation of Material Properties and Cellular Adhesion.

Macromolecular bioscience·2026

Same author

A computational model of canonical cortical microcircuits for dynamic Bayesian inference and control as inference.

Neuroscience research·2025

Search research articles

Related Experiment Video

Updated: Jun 16, 2026

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Published on: December 23, 2025

A computational neural model of goal-directed utterance selection.

Michael Klein¹, Hans Kamp, Guenther Palm

¹Centre for Language and Speech Technology, Radboud University of Nijmegen, Postbus 9103, 6500 HD Nijmegen, The Netherlands. Michael.Q.Klein@gmail.com

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

|February 2, 2010

Summary

This study introduces a computational framework for understanding language use, employing Markov Decision Processes to model how agents learn to communicate effectively for achieving goals. It demonstrates agents can learn to strategically decide when to speak, whom to address, and what to say.

Related Experiment Videos

Last Updated: Jun 16, 2026

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Published on: December 23, 2025

Area of Science:

Computational linguistics
Cognitive science
Artificial intelligence

Background:

Human communication is often driven by extralinguistic goals, such as influencing others' actions or beliefs.
A computational foundation for understanding goal-directed language use has been previously lacking.

Purpose of the Study:

To propose a computational foundation for goal-directed language use.
To model how agents can learn the strategic aspects of communication.

Main Methods:

Utilizing Markov Decision Processes (MDPs) for modeling language use.
Incorporating internal models (next-state transition functions) and reinforcement learning for value function estimation.
Testing the cognitive architecture in multi-agent game simulations with competent agents.

Main Results:

Agents learned to predict context-dependent effects of utterances through interaction.
The cognitive architecture successfully modeled the acquisition of communicative capabilities.
Agents demonstrated the ability to decide when to speak, whom to address, and what to say to achieve goals.

Conclusions:

The proposed computational architecture provides a foundation for understanding goal-directed language use.
This framework can account for learning strategic communication behaviors in artificial agents.
The integration of action selection mechanisms offers a neurobiologically plausible approach to language pragmatics.