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

Working Memory01:24

Working Memory

1.3K
Working memory refers to a combination of components, including short-term memory and attention, that allow an individual to hold information temporarily as we perform cognitive tasks. It is an essential cognitive function that enables the execution of complex tasks such as problem-solving, comprehension, and reasoning. Unlike short-term memory, which simply involves the storage of information for a brief period, working memory involves the active manipulation and processing of this...
1.3K

You might also read

Related Articles

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

Sort by
Same author

A review and evaluation of doubly robust approaches for estimating average treatment effects.

Behavior research methods·2026
Same author

Dynamical Cardiovascular Synchrony in Patient-caregiver Dyads Affected by Cancer: An Application of the Coupled Linear Oscillator Model.

Biopsychosocial science and medicine·2026
Same author

Eating away the Boredom? An Experimental and Ecological Momentary Assessment of State Boredom and Snack Consumption.

Psychological reports·2026
Same author

Estimating the reliability of round-robin judgments with social relations confirmatory factor analyses.

The British journal of mathematical and statistical psychology·2026
Same author

Enhancing Two-Stage Estimation in Differential Equation Models: A Bias-Correction Method via Stochastic Approximation.

Psychometrika·2026
Same author

Estimating Trends With Differential Item Functioning: A Comparison of Five IRT-Based Approaches.

Educational and psychological measurement·2026
Same journal

Adverse and positive childhood experiences in relation to adolescent mental health: sequential indirect associations.

Frontiers in psychology·2026
Same journal

Personality profiles and usage experience are associated with trust and dependence on generative AI: a latent profile analysis.

Frontiers in psychology·2026
Same journal

Editorial: Promoting replicability: empowering method and applied researchers in driving reliable results.

Frontiers in psychology·2026
Same journal

The mediating roles of the challenge appraisal in the relationship between the coach-athlete relationship and adolescent athletes' burnout.

Frontiers in psychology·2026
Same journal

Unpacking GenAI-enabled deep learning engagement: role perceptions, human-GenAI synergy strategies, and underlying mechanisms.

Frontiers in psychology·2026
Same journal

Violence exposure and cyberbullying among Chinese adolescents: the mediating role of moral disengagement.

Frontiers in psychology·2026
See all related articles

Related Experiment Video

Updated: Apr 26, 2026

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

14.2K

Dynamical systems analysis applied to working memory data.

Fidan Gasimova1, Alexander Robitzsch2, Oliver Wilhelm1

  • 1Department of Psychology, Ulm University Ulm, Germany.

Frontiers in Psychology
|July 30, 2014
PubMed
Summary
This summary is machine-generated.

This study reveals cyclical patterns in weekly working memory capacity (WMC) among 9th graders. Individual differences in WMC oscillation frequency are linked to initial performance and learning pace.

Keywords:
B-spline imputationdynamical systems analysisintensive longitudinal dataintraindividual variabilitysimulation study

More Related Videos

Assessing Working Memory in Children: The Comprehensive Assessment Battery for Children – Working Memory (CABC-WM)
09:05

Assessing Working Memory in Children: The Comprehensive Assessment Battery for Children – Working Memory (CABC-WM)

Published on: June 12, 2017

31.1K
A Cognitive Paradigm to Investigate Interference in Working Memory by Distractions and Interruptions
10:38

A Cognitive Paradigm to Investigate Interference in Working Memory by Distractions and Interruptions

Published on: July 16, 2015

12.7K

Related Experiment Videos

Last Updated: Apr 26, 2026

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

14.2K
Assessing Working Memory in Children: The Comprehensive Assessment Battery for Children – Working Memory (CABC-WM)
09:05

Assessing Working Memory in Children: The Comprehensive Assessment Battery for Children – Working Memory (CABC-WM)

Published on: June 12, 2017

31.1K
A Cognitive Paradigm to Investigate Interference in Working Memory by Distractions and Interruptions
10:38

A Cognitive Paradigm to Investigate Interference in Working Memory by Distractions and Interruptions

Published on: July 16, 2015

12.7K

Area of Science:

  • Cognitive Psychology
  • Developmental Neuroscience
  • Data Science

Background:

  • Working memory capacity (WMC) is crucial for cognitive functions.
  • Understanding longitudinal variability in WMC is essential for educational and clinical applications.
  • Previous research has not fully captured the dynamic, cyclical nature of WMC fluctuations.

Purpose of the Study:

  • To investigate weekly fluctuations in working memory capacity (WMC) over two years in adolescents.
  • To model the cyclical patterns of WMC variability using dynamical systems analysis.
  • To explore individual differences in WMC oscillation parameters.

Main Methods:

  • Longitudinal study of 112 9th graders over 2 years.
  • Dynamical system analysis employing a second-order linear differential equation.
  • B-spline imputation for handling missing data and multilevel modeling for individual differences.

Main Results:

  • A significant negative frequency parameter indicates cyclical patterns in weekly memory updating performance.
  • Higher initial WMC and slower improvement correlate with a slower oscillation frequency.
  • Simulation results highlight B-spline knot count as more influential than embedding dimensions for imputation accuracy.

Conclusions:

  • Weekly WMC exhibits predictable cyclical patterns influenced by individual learning trajectories.
  • Dynamical systems analysis provides a robust framework for studying cognitive variability.
  • Methodological choices, like B-spline imputation, significantly impact the accuracy of longitudinal cognitive data analysis.