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

You might also read

Related Articles

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

Sort by
Same author

Digital phenotyping of affect and stress in emerging adults.

Frontiers in digital health·2026
Same author

Synaptic Plasticity as a Function of the Temporal Derivative.

bioRxiv : the preprint server for biology·2026
Same author

Genetic and Environmental Associations Between Processing Speed and Executive Functions Across Adolescence and Established Adulthood.

Behavior genetics·2026
Same author

Cognitive dispersion in established adulthood: etiology and implications for cognitive aging.

Innovation in aging·2026
Same author

Adolescent music engagement is associated with less alcohol consumption and substance experimentation 5-11 years later: A genetically informative study.

Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors·2026
Same author

Relationships Between Polygenic Scores for Psychopathology and Observed Psychopathology Are Mediated by Cognitive Control and Reward Sensitivity Pathways: Insights From the ABCD Study.

Biological psychiatry global open science·2026

Related Experiment Video

Updated: Apr 30, 2026

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
09:01

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

Published on: May 7, 2014

9.5K

A neural network model of individual differences in task switching abilities.

Seth A Herd1, Randall C O'Reilly1, Tom E Hazy1

  • 1Department of Psychology and Neuroscience, University of Colorado Boulder, 345 UCB, Boulder, CO 80309, USA.

Neuropsychologia
|May 6, 2014
PubMed
Summary

This study uses a neural network model to explore individual differences in cognitive control and task switching. Findings suggest task switching variations relate to goal representation persistence, while common executive functions depend on prefrontal cortex representation strength.

Keywords:
Computational modelExecutive controlGeneticsSet shifting

More Related Videos

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks
06:57

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks

Published on: August 9, 2016

10.5K
New Variations for Strategy Set-shifting in the Rat
09:45

New Variations for Strategy Set-shifting in the Rat

Published on: January 23, 2017

7.7K

Related Experiment Videos

Last Updated: Apr 30, 2026

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
09:01

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

Published on: May 7, 2014

9.5K
Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks
06:57

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks

Published on: August 9, 2016

10.5K
New Variations for Strategy Set-shifting in the Rat
09:45

New Variations for Strategy Set-shifting in the Rat

Published on: January 23, 2017

7.7K

Area of Science:

  • Cognitive Neuroscience
  • Computational Psychiatry
  • Neuroscience

Background:

  • Individual differences in executive functions (EF) are not fully explained by current computational models.
  • Task switching abilities are separable from other EF abilities, like response inhibition.
  • The Unity/Diversity model proposes distinct 'Shifting-Specific' and 'Common EF' components.

Purpose of the Study:

  • Investigate brain mechanisms behind individual differences in cognitive control during task switching.
  • Test hypotheses about neural underpinnings of 'Shifting-Specific' and 'Common EF'.
  • Explain the separability of task switching from other executive functions.

Main Methods:

  • Adapted a Prefrontal cortex, Basal ganglia Working Memory (PBWM) neural network model.
  • Simulated task switching and Stroop task performance.
  • Manipulated parameters to model individual differences.

Main Results:

  • Task switching variation linked to automatic goal representation persistence.
  • 'Common EF' variation linked to prefrontal cortex (PFC) representation strength.
  • Increased PFC signal-to-noise ratio reduced Stroop interference but increased switch costs.

Conclusions:

  • Individual differences in task switching and common EF have distinct neural bases.
  • A stability-flexibility tradeoff in PFC function explains opposing correlations with other variables.
  • Neural network models can elucidate complex executive function interactions and individual variability.