4.1 Article

A reduction for spiking integrate-and-fire network dynamics ranging from homogeneity to synchrony

Journal

JOURNAL OF COMPUTATIONAL NEUROSCIENCE
Volume 38, Issue 2, Pages 355-404

Publisher

SPRINGER
DOI: 10.1007/s10827-014-0543-3

Keywords

Coarse grain; Ensemble average; Integrate and fire; Spiking network

Funding

  1. NSF [DMS-1162548]
  2. Direct For Mathematical & Physical Scien
  3. Division Of Mathematical Sciences [1200004] Funding Source: National Science Foundation

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In this paper we provide a general methodology for systematically reducing the dynamics of a class of integrate-and-fire networks down to an augmented 4-dimensional system of ordinary-differential-equations. The class of integrate-and-fire networks we focus on are homogeneously-structured, strongly coupled, and fluctuation-driven. Our reduction succeeds where most current firing-rate and population-dynamics models fail because we account for the emergence of 'multiple-firing-events' involving the semi-synchronous firing of many neurons. These multiple-firing-events are largely responsible for the fluctuations generated by the network and, as a result, our reduction faithfully describes many dynamic regimes ranging from homogeneous to synchronous. Our reduction is based on first principles, and provides an analyzable link between the integrate-and-fire network parameters and the relatively low-dimensional dynamics underlying the 4-dimensional augmented ODE.

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