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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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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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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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Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
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Energy Consumption and Entropy Production in a Stochastic Formulation of BCM Learning.

Gastone Castellani1, Leon N Cooper2, Luciana Renata De Oliveira3

  • 1Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy.

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|December 28, 2020
PubMed
Summary

The BCM theory of synaptic plasticity has two formulations. The newer formulation, in a nonequilibrium steady state, exhibits enhanced plasticity and lower entropy production compared to the original rule.

Keywords:
chemical master equationnon-equilibrium thermodynamicssynaptic plasticity

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Area of Science:

  • Computational Neuroscience
  • Statistical Physics
  • Thermodynamics

Background:

  • Previous studies introduced a stochastic description of the BCM theory of synaptic plasticity.
  • The BCM theory has two formulations: original (threshold based on squared activity) and newer (threshold based on averaged squared activity).

Purpose of the Study:

  • To explore the statistical properties and thermodynamic behavior of the two BCM plasticity rules.
  • To introduce a continuous parameterization between the two BCM rules and analyze their differences.

Main Methods:

  • Stochastic description and chemical master equation approach.
  • Analysis of risk/energy functions and Jacobian matrix eigenvalues.
  • Thermodynamic interpretation using open systems, entropy production, and energy consumption.

Main Results:

  • The newer BCM rule, unlike the original, does not satisfy detailed balance and exists in a nonequilibrium steady state (NESS).
  • A continuous parameterization between the rules reveals a minimum related to Jacobian eigenvalues.
  • The newer NESS rule demonstrates higher synaptic plasticity with lower entropy production and energy consumption.

Conclusions:

  • The newer BCM formulation offers a more plastic and thermodynamically efficient model of synaptic plasticity.
  • The study provides a framework for understanding synaptic plasticity within open thermodynamic systems.