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Related Concept Videos

Entropy Change in Reversible Processes01:10

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In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
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Entropy02:39

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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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Entropy01:18

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The first law of thermodynamics is quantitatively formulated via an equation relating the internal energy of a system, the heat exchanged by it, and the work done on it. A quantitative formulation of the second law of thermodynamics leads to defining a state function, the entropy.
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Entropy and the Second Law of Thermodynamics01:20

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The second law of thermodynamics can be stated quantitatively using the concept of entropy. Entropy is the measure of disorder of the system.
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Entropy within the Cell01:22

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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...
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Organization of the Brain01:30

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The brain is an integral component of the nervous system and serves as the center for processing sensory inputs, making decisions, and directing bodily actions. This complex organ is organized into three primary sections: the hindbrain, midbrain, and forebrain, each responsible for a range of vital functions.
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Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
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Transitions in Brain Evolution: Space, Time and Entropy.

Kate J Jeffery1, Carlo Rovelli2

  • 1Institute of Behavioural Neuroscience, Department of Experimental Psychology, University College London, 26 Bedford Way, London WC1H 0AP, UK.

Trends in Neurosciences
|May 17, 2020
PubMed
Summary
This summary is machine-generated.

Evolutionary biology explains brain complexity through entropy. Brains, by representing space and time, accelerate entropy growth, but complex life

Keywords:
braincomplexityentropyevolutionfree energyspacestate space

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Area of Science:

  • Evolutionary biology
  • Thermodynamics
  • Neuroscience

Background:

  • Brains present an explanatory challenge due to the common association of entropy with disorder.
  • Evolutionary processes, including the development of complex structures like brains, can be understood as facilitating entropy growth.
  • The thermodynamic principles governing life's complexity and persistence are not fully elucidated.

Purpose of the Study:

  • To propose a framework for understanding brain evolution within the context of entropy and thermodynamics.
  • To explore how evolutionary transitions, particularly the development of brains, influence an organism's interaction with its environment and state space.
  • To investigate the thermodynamic underpinnings of complex life's persistence.

Main Methods:

  • Conceptual analysis integrating principles of evolution, thermodynamics, and neuroscience.
  • Exploration of how increased reach in space and time, facilitated by evolutionary innovations, allows for greater entropy production.
  • Examination of brain evolution as a key transition enabling enhanced representation and processing of spatio-temporal information.

Main Results:

  • Evolutionary transitions, especially brain development, extend organisms' influence in space and time, opening new pathways for entropy increase.
  • Brain evolution significantly enhances the capacity for spatio-temporal representation, thereby accelerating entropy production.
  • Certain evolutionary pathways may lead to 'dead-ends' in the state space, indicating that the persistence of complex life is not guaranteed by thermodynamics.

Conclusions:

  • Brain evolution is an entropic process that enhances an organism's ability to generate entropy by expanding its reach in space and time.
  • The complexity of brains is thermodynamically advantageous by enabling sophisticated spatio-temporal representation and processing.
  • The long-term persistence of complex life is contingent on navigating evolutionary pathways that avoid thermodynamic limitations.