Pipe-cleaner Model of Neuronal Network Dynamics

preprint2016arXivOpen access

Abstract

We present a functional model of neuronal network connectivity in which the single architectural element is the object commonly known in handicraft circles as a pipe cleaner. We argue that the dual nature of a neuronal circuit - that it be at times highly robust to external manipulation and yet sufficiently flexible to allow for learning and adaptation - is embodied in the pipe cleaner, and thus that a pipe cleaner framework serves as an instructive scaffold in which to examine network dynamics. Regarding the dynamics themselves: as pipe cleaners possess no intrinsic dynamics, in our model we attribute the emergent circuit dynamics to magic. Magic is a strategy that has been largely neglected in the neuroscience community, and may serve as an illuminating comparison to the common physics-based approaches. This model makes predictions that it would be really awesome to test experimentally. Moreover, the relative simplicity of the pipe cleaner - setting aside the fact that it comes in an overwhelming variety of colors - renders it an excellent theoretical building block with which to create simple network models. Also, they are incredibly cheap when bought wholesale on Amazon.

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