Date of Award
2012
Publisher
North Dakota State University
Document Type
Thesis
Degree Awarded
Master of Science (MS)
Program
Mathematics
Department
Mathematics
College
Science and Mathematics
Faculty Advisor
Cope, Davis
Description
A bifurcation portrait classifies the behavior of a dynamical system and how it transitions between different behaviors. A hybrid dynamical system displays both continuous and discrete dynamics and may display nonsmooth bifurcations. Herein, we analyze a novel hybrid model of a spiking neuron proposed by E.M. Izhikevich [9] that is based on a previous hybrid model with a convex spike-activation function f(x), but modified with a conductance reversal potential term. We analyze the model proposed by Izhikevich and obtain a bifurcation portrait for the continuous dynamics for an arbitrary convex spike activation function f(x). Both subcritical and supercritical Andronov-Hopf bifurcations are possible, and we numerically confirm the presence of a Bautin bifurcation for a particular choice of spike activation function. The model is capable of simulating common cortical neuron types and presents several possibilities for generalizations that may be capable of more complicated behavior.
Recommended Citation
Goodell, Brandon Grae, "Bifurcation Portrait of a Hybrid Spiking Neuron Model" (2012). Mathematics. 15.
https://digitalcommons.ndsu.edu/mathematics/15
Rights
NDSU Policy 190.6.2
Rights Link
https://www.ndsu.edu/fileadmin/policy/190.pdf
Handle Identifier
https://hdl.handle.net/10365/26666