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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).
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Background: Non-uniqueness of Parameters in...
References
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Marder E, Goaillard JM (2006) Variability, compensation and homeostasis in neuron and network function. Nat Rev Neurosci 7:563–574
Marder E, Taylor AL (2011) Multiple models to capture the variability in biological neurons and networks. Nat Neurosci 14:133–138
Waddington CH (1957) The strategy of the genes; a discussion of some aspects of theoretical biology. Allen & Unwin, London
Wagner A (2005) Robustness and evolvability in living systems. Princeton University Press, Princeton, Woodstock
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Goaillard, JM. (2022). Neuronal Parameter Non-uniqueness. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-0716-1006-0_171
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DOI: https://doi.org/10.1007/978-1-0716-1006-0_171
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