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Related Concept Videos

Homeostatic Imbalance01:10

Homeostatic Imbalance

Homeostasis is the maintenance of a stable internal environment within the body, which is crucial for the proper functioning of cells, tissues, organs, and organ systems. The body has various control mechanisms that work together to regulate various physiological parameters such as temperature, blood pressure, pH balance, and fluid balance, to name a few. These control mechanisms are based on feedback loops that can be either positive or negative.
However, sometimes these feedback loops fail,...
Positive and Negative Feedback Loops01:18

Positive and Negative Feedback Loops

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:
Control Systems01:10

Control Systems

Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
At the heart...
Entropy within the Cell01:22

Entropy within the Cell

A living cell's primary tasks of obtaining, transforming, and using energy to do work may seem simple. However, the second law of thermodynamics explains why these tasks are harder than they appear. None of the energy transfers in the universe are completely efficient. In every energy transfer, some amount of energy is lost in a form that is unusable. In most cases, this form is heat energy. Thermodynamically, heat energy is defined as the energy transferred from one system to another that is...
What is Homeostasis?01:16

What is Homeostasis?

Maintaining homeostasis requires that the body continuously maintain its internal conditions. Each physiological condition has a particular set point, from body temperature to blood pressure to levels of certain nutrients. A set point is the physiological value around which the normal range fluctuates. A normal range is a restricted set of values that is optimally healthful and stable. For example, the set point for normal human body temperature is approximately 37°C (98.6°F). Physiological...
Entropy02:39

Entropy

Salt particles that have dissolved in water never spontaneously come back together in solution to reform solid particles. Moreover, a gas that has expanded in a vacuum remains dispersed and never spontaneously reassembles. The unidirectional nature of these phenomena is the result of a thermodynamic state function called entropy (S). Entropy is the measure of the extent to which the energy is dispersed throughout a system, or in other words, it is proportional to the degree of disorder of a...

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Related Experiment Video

Updated: Jun 8, 2026

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

Self-organized chaos through polyhomeostatic optimization.

D Markovic1, Claudius Gros

  • 1Institute for Theoretical Physics, Johann Wolfgang Goethe University, Frankfurt am Main, Germany.

Physical Review Letters
|September 28, 2010
PubMed
Summary
This summary is machine-generated.

Polyhomeostatic control adapts neural networks to target firing rate distributions, unlike traditional homeostasis. This adaptation leads to chaotic bursting behavior by destabilizing network attractors.

Related Experiment Videos

Last Updated: Jun 8, 2026

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

Area of Science:

  • Computational Neuroscience
  • Dynamical Systems Theory
  • Information Theory

Background:

  • Homeostatic regulation stabilizes systems at a steady state.
  • Polyhomeostatic control aims for target behavioral distributions, not just stability.
  • Neural networks are fundamental to understanding complex behaviors.

Purpose of the Study:

  • To investigate polyhomeostatic control in individual and network models of firing-rate neurons.
  • To explore adaptation mechanisms that maximize information entropy in neural firing rates.
  • To analyze the impact of polyhomeostatic adaptation on network dynamics and stability.

Main Methods:

  • Modeling individual and networks of firing-rate neurons.
  • Implementing adaptation rules to achieve target firing rate distributions.
  • Analyzing network dynamics using concepts from dynamical systems theory, including attractors.
  • Simulating Hopfield-like network setups to observe emergent behaviors.

Main Results:

  • Finite polyhomeostatic adaptation rates disrupt all attractors in Hopfield-like networks.
  • This disruption results in intermittently bursting neuronal activity.
  • The networks exhibit self-organized chaos as a consequence of adaptation.
  • Information entropy maximization is achieved through these dynamic changes.

Conclusions:

  • Polyhomeostatic control fundamentally alters network dynamics, moving away from stable states.
  • Intermittent bursting and self-organized chaos are key emergent behaviors.
  • Understanding polyhomeostasis is crucial for comprehending adaptive behaviors in biological and artificial systems.