Toward a dynamical systems analysis of neuromodulation

Chris Buckley, Seth Bullock, Netta Cohen

    Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)


    This work presents some first steps toward a more thorough understanding of the control systems employed in evolutionary robotics. In order to choose an appropriate architecture or to construct an effective novel control system we need insights into what makes control systems successful, robust, evolvable, etc. Here we present analysis intended to shed light on this type of question as it applies to a novel class of artificial neural networks that include a neuromodulatory mechanism: GasNets. We begin by instantiating a particular GasNet subcircuit responsible for tuneable pattern generation and thought to underpin the attractive property of “temporal adaptivity”. Rather than work within the GasNet formalism, we develop an extension of the well-known FitzHugh-Nagumo equations. The continuous nature of our model allows us to conduct a thorough dynamical systems analysis and to draw parallels between this subcircuit and beating/bursting phenomena reported in the neuroscience literature. We then proceed to explore the effects of different types of parameter modulation on the system dynamics. We conclude that while there are key differences between the gain modulation used in the GasNet and alternative schemes (including threshold modulation of more traditional synaptic input), both approaches are able to produce tuneable pattern generation. While it appears, at least in this study, that the GasNet’s gain modulation may not be crucial to pattern generation , we go on to suggest some possible advantages it could confer.
    Original languageUndefined/Unknown
    Title of host publicationProceedings of the Eighth International Conference on Simulation of Adaptive Behavior (SAB 2004)
    EditorsStefan Schaal, Auke Jan Ijspeert, Aude Billard, Sethu Vijayakumar, John Hallam, Jean-Arcady Meyer
    PublisherMassachusetts Institute of Technology (MIT) Press
    Number of pages10
    Publication statusPublished - 2004

    Bibliographical note

    [Won best paper prize].

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