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Bifurcations, Neural Population Models and

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Definition

In neural population models (NPMs), as in dynamical systems in general, smooth changes in system parameters, for example, coupling strength, input levels, and time constants, may result in sudden qualitative changes in system dynamics, such as the occurrence or disappearance of oscillatory or chaotic behavior. Such phenomena are referred to as bifurcations and are interesting because they may account for switching phenomena, which are common in both brain signals and organisms’ behavior.

Detailed Description

Depending on their particular parameter set, NPMs experience different asymptotic dynamic behaviors characterized by constant output, harmonic (i.e., sinusoidal) or nonharmonic oscillations, which can be periodic or quasiperiodic (i.e., the signal repeats itself approximately, but not exactly), and even chaotic behavior (Frascoli et al. 2011; Spiegler et al. 2010, 2011). The transitions in parameter space between these qualitatively different states are called...

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Correspondence to Thomas R. Knösche .

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Knösche, T.R. (2014). Bifurcations, Neural Population Models and. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7320-6_53-2

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  • DOI: https://doi.org/10.1007/978-1-4614-7320-6_53-2

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  • Online ISBN: 978-1-4614-7320-6

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Chapter history

  1. Latest

    Bifurcations, Neural Population Models and
    Published:
    30 July 2014

    DOI: https://doi.org/10.1007/978-1-4614-7320-6_53-2

  2. Original

    Bifurcations, Neural Population Models and
    Published:
    07 February 2014

    DOI: https://doi.org/10.1007/978-1-4614-7320-6_53-1