Bump attractors and waves in networks of leaky integrate-and-fire neurons
D. Avitabile, J. L. Davis, K. C. A. Wedgwood

TL;DR
This paper explores the relationship between bump attractors and traveling waves in networks of leaky integrate-and-fire neurons, revealing how complex spatiotemporal patterns can be constructed and analyzed through a novel voltage mapping operator.
Contribution
It introduces an analytical framework linking bump attractors and waves, enabling construction and stability analysis of localized traveling waves with arbitrary spike counts.
Findings
Waves are determined by firing sets and can be constructed with arbitrary spikes.
Higher spike counts lead to slower waves and bump-like profiles.
Unstable waves coexist with stable homogeneous states, influencing bump dynamics.
Abstract
Bump attractors are wandering localised patterns observed in in vivo experiments of spatially-extended neurobiological networks. They are important for the brain's navigational system and specific memory tasks. A bump attractor is characterised by a core in which neurons fire frequently, while those away from the core do not fire. We uncover a relationship between bump attractors and travelling waves in a classical network of excitable, leaky integrate-and-fire neurons. This relationship bears strong similarities to the one between complex spatiotemporal patterns and waves at the onset of pipe turbulence. Waves in the spiking network are determined by a firing set, that is, the collection of times at which neurons reach a threshold and fire as the wave propagates. We define and study analytical properties of the voltage mapping, an operator transforming a solution's firing set into its…
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Taxonomy
TopicsNeural dynamics and brain function · Nonlinear Dynamics and Pattern Formation · stochastic dynamics and bifurcation
