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Selectionist and evolutionary approaches to brain function: a critical appraisal.

Chrisantha Fernando1, Eörs Szathmáry, Phil Husbands

  • 1School of Electronic Engineering and Computer Science, Queen Mary, University of London London, UK.

Frontiers in Computational Neuroscience
|May 5, 2012
PubMed
Summary

Many brain theories claim Darwinian principles, but most lack true evolutionary replicators. This study explores generalized selectionist frameworks and proposes models for genuine Darwinian evolutionary units in the brain.

Keywords:
Darwinian neurodynamicsIzhikevich spiking networkscausal inferencehill-climbersneural Darwinismneuronal group selectionneuronal replicator hypothesisprice equation

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Area of Science:

  • Neuroscience
  • Evolutionary Biology
  • Computational Neuroscience

Background:

  • Several theories propose Darwinian mechanisms for brain dynamics and function, including neuronal group selection and synaptic selection.
  • These theories often employ selectionist principles but may not meet the strict criteria for true Darwinian evolution, such as the presence of replicators with hereditary variation.

Purpose of the Study:

  • To critically evaluate existing Darwinian-inspired theories of brain function.
  • To explore generalized selectionist frameworks and their relation to evolutionary algorithms.
  • To propose and analyze models of true Darwinian evolutionary units within the brain.

Main Methods:

  • Review and analysis of prominent theories of Darwinian brain function (e.g., Edelman, Changeux, Seung, Loewenstein, Adam, Calvin).
  • Comparison with generalized selectionist frameworks, including Price's covariance formulation, Bayesian models, and reinforcement learning.
  • Classification of search algorithms to highlight the role of Darwinian replicators.
  • Development and analysis of novel models for neuronal replicators based on connectivity and activity copying.

Main Results:

  • Most proposed brain mechanisms are selectionist but not truly Darwinian due to the absence of identifiable replicators with information transfer and hereditary variation.
  • Generalized selectionist frameworks, including Bayesian models and reinforcement learning, align with selection dynamics.
  • Darwinian replicators, defined by multiplication, heredity, and variability, represent a powerful search mechanism, especially in sparse search spaces.
  • Parallel competitive search with information transfer can be more efficient than search without it.

Conclusions:

  • True Darwinian evolutionary units in the brain, based on neuronal connectivity and activity copying, are theoretically plausible but challenging to identify.
  • The study provides a framework for understanding and modeling Darwinian processes in the brain, offering potential for future research.