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

Cell Signaling Feedback Loops01:07

Cell Signaling Feedback Loops

8.1K
Positive and negative feedback loops are crucial for regulating biological signaling systems. These feedback loops are processes that connect output signals to their inputs.
Negative feedback loops
Most signaling systems have negative feedback loops that can perform different functions such as output limiter, and adaptation.
Output limiter
Upon receiving an input signal, the cellular response rapidly increases until a threshold is reached. Beyond this threshold, a negative feedback loop...
8.1K
Feedback control systems01:26

Feedback control systems

816
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...
816
Positive and Negative Feedback Loops01:18

Positive and Negative Feedback Loops

26.6K
Animal organs and organ systems constantly adjust to internal and external changes through a process called homeostasis ("steady state"). Examples of these changes include regulation of the level of glucose or calcium in the blood or internal responses to external temperatures. Homeostasis requires  maintaining an internal dynamic equilibrium:
26.6K
Effects of feedback01:24

Effects of feedback

1.2K
Feedback in control systems plays a critical role in shaping various operational parameters, extending beyond simple error reduction to influence stability, bandwidth, gain, impedance, and sensitivity. Understanding these effects requires examining a basic feedback system characterized by defined input, output, error, and feedback signals.
Feedback significantly modifies the gain of a control system. The gain of a system without feedback is altered by a factor of one plus GH, where G represents...
1.2K
Classification of Systems-II01:31

Classification of Systems-II

585
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
585
Positive Regulator Molecules01:45

Positive Regulator Molecules

137.4K
To consistently produce healthy cells, the cell cycle—the process that generates daughter cells—must be precisely regulated.
137.4K

You might also read

Related Articles

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

Sort by
Same author

Effects of confinement on supercooled tetrahedral liquids.

The Journal of chemical physics·2019
Same author

Effects of the bond polarity on the structural and dynamical properties of silica-like liquids.

The Journal of chemical physics·2018
Same author

Biodiversity and ecosystem functioning in evolving food webs.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences·2016
Same author

3D replicon distributions arise from stochastic initiation and domino-like DNA replication progression.

Nature communications·2016
Same author

The influence of dispersal on a predator-prey system with two habitats.

Journal of theoretical biology·2016
Same author

Evolutionary food web model based on body masses gives realistic networks with permanent species turnover.

Scientific reports·2015

Related Experiment Video

Updated: Apr 20, 2026

Studying Cell Cycle-regulated Gene Expression by Two Complementary Cell Synchronization Protocols
12:02

Studying Cell Cycle-regulated Gene Expression by Two Complementary Cell Synchronization Protocols

Published on: June 6, 2017

28.8K

Single generation cycles and delayed feedback cycles are not separate phenomena.

T Pfaff1, A Brechtel1, B Drossel1

  • 1Institute of Condensed Matter Physics, Hochschulstraße 6, 64289 Darmstadt, Germany.

Theoretical Population Biology
|December 3, 2014
PubMed
Summary

This study shows that population cycles, including single-generation and delayed-feedback cycles, can emerge from a single model. Varying competition parameters generates diverse cycle periods and even chaos, challenging distinct classifications.

Keywords:
Delay differential equationDelayed feedback cyclesGeneration cyclesSingle generation cyclesStructured population model

More Related Videos

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
07:59

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Published on: June 9, 2023

2.1K
Continuous Measurement of Biological Noise in Escherichia Coli Using Time-lapse Microscopy
08:25

Continuous Measurement of Biological Noise in Escherichia Coli Using Time-lapse Microscopy

Published on: April 27, 2021

4.3K

Related Experiment Videos

Last Updated: Apr 20, 2026

Studying Cell Cycle-regulated Gene Expression by Two Complementary Cell Synchronization Protocols
12:02

Studying Cell Cycle-regulated Gene Expression by Two Complementary Cell Synchronization Protocols

Published on: June 6, 2017

28.8K
Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
07:59

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Published on: June 9, 2023

2.1K
Continuous Measurement of Biological Noise in Escherichia Coli Using Time-lapse Microscopy
08:25

Continuous Measurement of Biological Noise in Escherichia Coli Using Time-lapse Microscopy

Published on: April 27, 2021

4.3K

Area of Science:

  • Ecology
  • Mathematical Biology
  • Population Dynamics

Background:

  • Generation cycles are population oscillations occurring over one or few species generation times.
  • Previous models distinguished single-generation cycles (1-2 generation times) from delayed-feedback cycles (2-4 generation times).

Purpose of the Study:

  • To investigate a simplified model for generation cycles using a delay-differential equation.
  • To explore the relationship between single-generation and delayed-feedback cycles by decoupling maturation time and competition delay.

Main Methods:

  • Formulated a single delay-differential equation for adult population density.
  • Modeled recruitment based on juvenile phase competition intensity.
  • Varied model parameters, particularly those affecting inter-cohort competition duration.

Main Results:

  • Single-generation and delayed-feedback cycles were found to occur within the same model version.
  • A gradual transition between cycle types was observed with parameter variation.
  • Cycle periods were not confined to specific intervals and could include chaos.
  • Inter-cohort competition parameters influenced cycle period and stability.

Conclusions:

  • A clear distinction between different types of generation cycles is not supported by this model.
  • Life-cycle features, especially during the juvenile stage and maturation, are crucial for density-limited population dynamics.
  • The model demonstrates that diverse population dynamics, including chaotic behavior, can arise from simple mechanisms.