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

Language and Cognition01:27

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.
Language Development01:22

Language Development

Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
The critical period for language acquisition suggests that the ability to acquire language is at its peak early in life. As people age, this proficiency decreases. Language development begins very...
Modeling with Differential Equations01:25

Modeling with Differential Equations

Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...
Components of Language01:24

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...
Population Growth00:57

Population Growth

Population size is dynamic, increasing with birth rates and immigration, and decreasing with death rates and emigration. In ideal conditions with unlimited resources, populations can increase exponentially, which plots as a J-shaped growth rate curve of population size against time. This type of curve is characteristic of newly-introduced invasive species, or populations that have suffered catastrophic declines and are rebounding.However, realistic environmental conditions limit the number of...
Exponential Equations for Modeling Growth01:26

Exponential Equations for Modeling Growth

Exponential models are essential for describing rapid, multiplicative changes in natural systems, such as population growth. When a population doubles at regular intervals, the process can be modeled using a suitable base. For instance, a bacterial culture that doubles every three hours follows the model n(t)=n0⋅2t/3, where n(t) is the population at the time t.A more general model uses the natural base e, especially for continuous growth. This takes the form n(t)=n0⋅ert, where r is the relative...

You might also read

Related Articles

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

Sort by
Same author

Rivastigmine Templates with Antioxidant Motifs-A Medicinal Chemist's Toolbox Towards New Multipotent AD Drugs.

Antioxidants (Basel, Switzerland)·2025
Same author

Attention-sensitive communication in 13-month-old infants from urban and rural areas in Mozambique: Influence of the recipient's behaviour and lifestyle.

Infant behavior & development·2025
Same author

Innovative Multilumen Stent System for Pulmonary Flow Adjustment in Congenital Heart Disease and Dilated Cardiomyopathy.

JACC. Basic to translational science·2023
Same author

Exploring How People with Expressive Aphasia Interact with and Perceive a Social Robot.

International journal of social robotics·2022
Same author

Localized absence of myocardium mimicking a contained left ventricular rupture.

European heart journal open·2022
Same author

The impact of age and sex on in-hospital outcomes in acute type A aortic dissection surgery.

Journal of thoracic disease·2022

Related Experiment Video

Updated: Jun 18, 2026

The (Spatial) Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition
05:15

The (Spatial) Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition

Published on: February 19, 2018

Modeling interactions between language evolution and demography.

Paul Vogt1

  • 1Tilburg Center for Creative Computing, Tilburg University, P.O. Box 90153, Tilburg, The Netherlands.

Human Biology
|December 1, 2009
PubMed
Summary
This summary is machine-generated.

This review classifies models of language evolution and demographic processes into analytical, agent-based analytical, and agent-based cognitive approaches. Agent-based cognitive models offer the most detailed simulations for understanding complex sociocognitive interactions.

More Related Videos

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
20:36

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Published on: July 4, 2007

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment
06:48

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Published on: June 25, 2019

Related Experiment Videos

Last Updated: Jun 18, 2026

The (Spatial) Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition
05:15

The (Spatial) Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition

Published on: February 19, 2018

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
20:36

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Published on: July 4, 2007

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment
06:48

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Published on: June 25, 2019

Area of Science:

  • Computational Linguistics
  • Evolutionary Biology
  • Social Sciences

Background:

  • Understanding the interplay between language evolution and demographic processes is crucial for linguistics and social sciences.
  • Various modeling approaches exist, each with distinct capabilities in simulating these complex interactions.

Purpose of the Study:

  • To review and classify existing models that integrate language evolution and demographic processes.
  • To provide a guideline for selecting appropriate modeling approaches based on research questions and desired simulation complexity.

Main Methods:

  • Classification of models into three categories: analytical modeling, agent-based analytical modeling, and agent-based cognitive modeling.
  • Comparative analysis of the complexity and realism of interactions handled by each modeling approach.

Main Results:

  • Analytical models are suitable for high-level demographic and language evolution processes.
  • Agent-based analytical models effectively simulate social dynamics without deep cognitive detail.
  • Agent-based cognitive models provide the most detailed and realistic simulations of sociocognitive mechanisms in language evolution.

Conclusions:

  • The choice of modeling approach significantly impacts the scope and depth of insights into language evolution and demography.
  • Agent-based cognitive modeling is recommended for studies requiring intricate simulation of sociocognitive factors.
  • This review guides researchers in selecting the most effective modeling strategy for their specific research objectives.