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Fate of Duplicated Neural Structures.

Luís F Seoane1,2

  • 1Departamento de Biología de Sistemas, Centro Nacional de Biotecnología (CNB), CSIC, C/Darwin 3, 28049 Madrid, Spain.

Entropy (Basel, Switzerland)
|December 8, 2020
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Summary
This summary is machine-generated.

Statistical physics can explain neural circuit evolution. This study explores duplicated circuits, revealing phase transitions that shape complex cognition and brain structures.

Keywords:
brain asymmetrybrain symmetryduplicated neural circuitslateralizationstatistical physics of neural circuits

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Area of Science:

  • Neuroscience
  • Statistical Physics
  • Computational Theory

Background:

  • Statistical physics principles govern matter arrangements based on cost-benefit trade-offs, influencing biological processes and computational limits.
  • Neural circuits are central to cognition and evolution, bridging statistical physics and natural selection.
  • Understanding the statistical physics of neural circuits can predict brain structures under various constraints.

Purpose of the Study:

  • To investigate the statistical physics of neural circuits, focusing on duplicated circuits.
  • To determine how energetic, evolutionary, and computational factors influence neural circuit organization.
  • To explore computational thresholds that may drive neural circuit redundancy.

Main Methods:

  • Analysis of duplicated neural circuits in central nervous systems.
  • Modeling cost-benefit balances for duplicated circuits implementing complex phenotypes.
  • Derivation of phase diagrams and phase-like transitions between single and duplicated circuits.

Main Results:

  • Phase diagrams and transitions were derived, illustrating the conditions favoring single versus duplicated neural circuits.
  • Computational thresholds are identified as potential drivers for neural circuit redundancy.
  • The study suggests these principles constrain evolutionary paths toward complex cognition.

Conclusions:

  • Statistical physics provides a natural framework for understanding neural circuit evolution and organization.
  • Duplicated neural circuits and their transitions are key to understanding the evolution of complex cognition.
  • The derived principles may also inform the internal and input/output connectivity patterns of neural circuits broadly.