Pipe-cleaner Model of Neuronal Network Dynamics

TL;DR

This paper introduces a novel neuronal network model using pipe cleaners as a metaphor, emphasizing robustness and flexibility, and proposes magic as a new way to understand emergent dynamics, offering a simple and testable framework.

Contribution

It presents a unique pipe cleaner-based model of neuronal networks and introduces the concept of magic to explain emergent circuit dynamics, contrasting physics-based approaches.

Findings

Predicts testable neural circuit behaviors

Highlights robustness and flexibility of the pipe cleaner analogy

Proposes magic as a new explanatory strategy

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.