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

Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

812
A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of...
812
Information Processing Approach01:30

Information Processing Approach

207
The information-processing theory of cognitive development centers on fundamental mental processes, including attention, memory, and problem-solving skills. Researchers in this field examine how cognitive abilities, such as working memory, evolve and influence children's overall development. Studies indicate that children with stronger working memory tend to excel in reading comprehension, math, and problem-solving compared to peers with less efficient memory skills. Low working memory is...
207
Population Growth00:57

Population Growth

26.0K
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.
26.0K
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

806
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
806
Cognitive Development During Adulthood01:30

Cognitive Development During Adulthood

360
Cognitive development continues throughout adulthood, undergoing significant shifts across early, middle, and late stages. Individual transition occurs from adolescent idealism to pragmatic and adaptable thinking in early adulthood. During this period, individuals learn to integrate personal beliefs with the recognition that other perspectives are equally valid. Exposure to the complexities of modern society, diverse experiences, and higher education contribute to this adaptive thought process,...
360
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

115
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
115

You might also read

Related Articles

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

Sort by
Same author

A folk taxonomy of magic.

Cognition·2026
Same author

A reporting checklist for large language models in behavioural science.

Nature human behaviour·2026
Same author

Resolving Feynman's restaurant problem reveals optimal solutions and human strategies.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Considering Psychological Mechanisms Can Change the Interpretation of Bayesian Models.

Topics in cognitive science·2026
Same author

Aha! moments correspond to metacognitive prediction errors.

Cognition·2026
Same author

Whither symbols in the era of advanced neural networks?

Trends in cognitive sciences·2026
Same journal

An Introduction to Rational Constructivism in Cognitive Development.

Topics in cognitive science·2026
Same journal

Fungal Memory and Minimal Cognition.

Topics in cognitive science·2026
Same journal

Limits to Language Prediction: Findings From Diverse Populations.

Topics in cognitive science·2026
Same journal

There Is More Than Meets the Eye: The Dual Role of Perception in Shaping Color Lexicons.

Topics in cognitive science·2026
Same journal

Inference and Imagination.

Topics in cognitive science·2026
Same journal

Gesture Use Across Different Concepts: Focusing on Cross-Linguistic Diversity.

Topics in cognitive science·2026
See all related articles

Related Experiment Video

Updated: Oct 6, 2025

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
09:23

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Published on: August 16, 2017

8.2K

Overcoming Individual Limitations Through Distributed Computation: Rational Information Accumulation in

Mathew D Hardy1, Peaks M Krafft2, Bill Thompson1,3

  • 1Department of Psychology, Princeton University.

Topics in Cognitive Science
|January 15, 2022
PubMed
Summary
This summary is machine-generated.

Social learning in multigenerational networks enables groups to solve complex problems. This distributed Bayesian inference allows individuals to leverage past experiences with minimal cognitive load, enhancing collective intelligence.

Keywords:
Bayesian inferenceCollective intelligenceCultural evolutionDistributed computationGroup rationalitySocial learning

More Related Videos

Author Spotlight: Automated Lifespan Monitoring – Discovering Aging Dynamics with the Lifespan Machine
08:53

Author Spotlight: Automated Lifespan Monitoring – Discovering Aging Dynamics with the Lifespan Machine

Published on: January 26, 2024

1.2K
The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

9.5K

Related Experiment Videos

Last Updated: Oct 6, 2025

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
09:23

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Published on: August 16, 2017

8.2K
Author Spotlight: Automated Lifespan Monitoring – Discovering Aging Dynamics with the Lifespan Machine
08:53

Author Spotlight: Automated Lifespan Monitoring – Discovering Aging Dynamics with the Lifespan Machine

Published on: January 26, 2024

1.2K
The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

9.5K

Area of Science:

  • Cognitive Science
  • Social Networks
  • Collective Intelligence

Background:

  • Human intelligence is characterized by social interaction, which helps overcome cognitive limitations.
  • Computational problems often exceed individual time and cognitive resource constraints.
  • Social networks facilitate information accumulation across generations.

Purpose of the Study:

  • To demonstrate how information accumulation in social networks arises from distributed Bayesian inference.
  • To provide a population-level rationality criterion extending individual rationality analyses.
  • To investigate how individuals benefit from prior generations' experience with low cognitive effort.

Main Methods:

  • Developed a model of distributed Bayesian inference in multigenerational social networks.
  • Conducted two controlled behavioral experiments with social transmission structures matching the model.
  • Participants engaged in categorization tasks requiring reliance on and contribution to accumulated knowledge.

Main Results:

  • Microsocieties successfully accumulated distributed information across individuals and time.
  • Group-level distributed computation pooled information and resources effectively.
  • Individuals performed complex tasks effectively by leveraging collective knowledge.

Conclusions:

  • Distributed computation in social groups allows limited individuals to tackle complex problems.
  • Multigenerational social networks facilitate efficient information accumulation through Bayesian inference.
  • This framework offers a new perspective on population rationality and collective problem-solving.