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Neuronal Parameter Non-uniqueness

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Encyclopedia of Computational Neuroscience

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Synonyms

Degeneracy; Distributed robustness; Neutral space

Definition

Parameter non-uniqueness refers to the ability of biological systems to generate a similar (or even identical) functional output using vastly different solutions in the properties of their underlying components. As such, parameter non-uniqueness is tightly linked to the notion of degeneracy but also to the notion of neutral space, which refers to regions of a parameter space where variations in the parameters’ values have no effect (therefore, the term neutral) on the system’s output (function/phenotype) (Wagner 2005).

Methodologically, however, parameter non-uniqueness means that the dynamics of a biological system such as the neuron might not be captured by modeling a unique set of parameters but rather by modeling a population of models covering the biological neutral space of solutions (non-unique sets of parameters) (Marder and Taylor 2011).

Detailed Description

Background: Non-uniqueness of Parameters in...

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References

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  • Wagner A (2005) Robustness and evolvability in living systems. Woodstock, Princeton University Press, Princeton

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Author information

Authors and Affiliations

  1. Inserm, UMR_S 1072, 13015, Marseille, France

    Jean-Marc Goaillard

  2. Aix-Marseille Université, UNIS, 13015, Marseille, France

    Jean-Marc Goaillard

Authors
  1. Jean-Marc Goaillard
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Corresponding author

Correspondence to Jean-Marc Goaillard .

Editor information

Editors and Affiliations

  1. Atlanta, Georgia, USA

    Dieter Jaeger

  2. Department of Biomedical Engineering, Florida International University, Miami, Florida, USA

    Ranu Jung

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© 2014 Springer Science+Business Media New York

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Goaillard, JM. (2014). Neuronal Parameter Non-uniqueness. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7320-6_171-1

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  • DOI: https://doi.org/10.1007/978-1-4614-7320-6_171-1

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  • Publisher Name: Springer, New York, NY

  • Online ISBN: 978-1-4614-7320-6

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