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

Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

234
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...
234
Feedback control systems01:26

Feedback control systems

541
Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
541
Open and closed-loop control systems01:17

Open and closed-loop control systems

1.3K
Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal...
1.3K
Classification of Systems-I01:26

Classification of Systems-I

388
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
388
Relation between Mathematical Equations and Block Diagrams01:20

Relation between Mathematical Equations and Block Diagrams

2.5K
In a spring-mass-damper system, the second-order differential equation describes the dynamic behavior of the system. When transformed into the Laplace domain under zero initial conditions, this equation can be effectively analyzed and manipulated. The transformation into the Laplace domain converts differential equations into algebraic equations, simplifying the process of isolating the output.
2.5K
Network Function of a Circuit01:25

Network Function of a Circuit

454
Frequency response analysis in electrical circuits provides vital insights into a circuit's behavior as the frequency of the input signal changes. The transfer function, a mathematical tool, is instrumental in understanding this behavior. It defines the relationship between phasor output and input and comes in four types: voltage gain, current gain, transfer impedance, and transfer admittance. The critical components of the transfer function are the poles and zeros.
454

You might also read

Related Articles

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

Sort by
Same author

Continuous developmental changes in word recognition and language learning across early childhood.

eLife·2026
Same author

Old age is perceived to begin later: cross-European differences and the role of macro-level factors for the historical change in the perceived onset of old age.

The journals of gerontology. Series B, Psychological sciences and social sciences·2026
Same author

Adolescents' perceptions of media messages and their preventive health behaviors: a longitudinal study.

Pediatric research·2026
Same author

Time-Related Considerations for Modeling Event-Based Data Collected via Ecological Momentary Assessment.

Advances in methods and practices in psychological science·2026
Same author

Smartphone use among adolescents during school hours: High-intensity objective observations across different instructional contexts.

Child development·2026
Same author

Risk Communication in Real Time: Examining Individuals' Smartphone Use During the 2021 Texas Winter Disaster With Mobile Sensing.

Risk analysis : an official publication of the Society for Risk Analysis·2026

Related Experiment Video

Updated: Nov 8, 2025

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.4K

Describing and Controlling Multivariate Nonlinear Dynamics: A Boolean Network Approach.

Xiao Yang1, Nilam Ram1, Peter C M Molenaar2

  • 1Stanford University, Stanford, CA, USA.

Multivariate Behavioral Research
|April 20, 2021
PubMed
Summary
This summary is machine-generated.

We present a Boolean network method for modeling complex nonlinear dynamics using binary data. This approach helps understand and control psychological systems, like emotion regulation in children.

Keywords:
Boolean networknetwork controlnonlinear dynamicspsychological systems

More Related Videos

Designing and Implementing Nervous System Simulations on LEGO Robots
10:34

Designing and Implementing Nervous System Simulations on LEGO Robots

Published on: May 25, 2013

15.3K
Gene Digital Circuits Based on CRISPR-Cas Systems and Anti-CRISPR Proteins
10:46

Gene Digital Circuits Based on CRISPR-Cas Systems and Anti-CRISPR Proteins

Published on: October 18, 2022

2.0K

Related Experiment Videos

Last Updated: Nov 8, 2025

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.4K
Designing and Implementing Nervous System Simulations on LEGO Robots
10:34

Designing and Implementing Nervous System Simulations on LEGO Robots

Published on: May 25, 2013

15.3K
Gene Digital Circuits Based on CRISPR-Cas Systems and Anti-CRISPR Proteins
10:46

Gene Digital Circuits Based on CRISPR-Cas Systems and Anti-CRISPR Proteins

Published on: October 18, 2022

2.0K

Area of Science:

  • Computational Psychology
  • Dynamical Systems Theory
  • Network Science

Background:

  • Nonlinear dynamics in multivariate psychological systems are complex to model.
  • Binary time-series data are often available in psychological studies.
  • Controlling psychological dynamics requires understanding system attractors.

Purpose of the Study:

  • To introduce and demonstrate a novel Boolean network method for modeling and controlling nonlinear dynamics in psychological systems.
  • To apply the Boolean network method to understand emotion regulation dynamics in children.
  • To design network control strategies for guiding psychological systems toward desired states.

Main Methods:

  • Developed a three-step Boolean network method: inferring temporal relations as Boolean functions, extracting attractors, and designing network control.
  • Applied the method to binary time-series data from a study on children's anger regulation (N=120, T=480s).
  • Identified heterogeneous emotion regulation dynamics and control strategies across individuals.

Main Results:

  • The Boolean network method successfully described nonlinear dynamics in children's emotion regulation.
  • Identified 22 distinct Boolean networks representing heterogeneous emotion regulation dynamics.
  • Demonstrated heterogeneous control strategies for directing children toward desired 'anger OFF' attractors.

Conclusions:

  • The Boolean network method offers a novel approach to describing nonlinear dynamics in multivariate psychological systems.
  • This method has the potential to inform the design of interventions for guiding psychological systems toward specific goals.
  • The study highlights individual differences in emotion regulation dynamics and control strategies.