KEYWORDS: Neurons, Stochastic processes, Interference (communication), Performance modeling, Mathematical modeling, Systems modeling, Signal detection, Solids, Particles, Signal to noise ratio
We study the response time of a neuron in the transient regime of
FitzHugh-Nagumo model, in the presence of a suprathreshold signal
and noise sources. In the deterministic regime we find that the
activation time of the neuron has a minimum as a function of the
signal driving frequency. In the stochastic regime we consider two
cases: (a) the fast variable of the model is noisy, and (b)
the slow variable, that is the recovery variable, is subjected to
fluctuations. In both cases we find two noise-induced effects,
namely the resonant activation-like and the noise enhanced
stability phenomena. The role of these noise-induced effects is
analyzed. The first one produces suppression of noises, while the
second one delays the neuron response. Finally, the role of the
phase of the driving signal on the transient dynamics of the
neuron is analyzed.
The response of a noisy FitzHugh-Nagumo (FHN) neuron-like model to
weak periodic forcing is analyzed. The mean activation time is
investigated as a function of noise intensity and of the parameters of the external signal. It is shown by numerical simulation that there exists a frequency range within which the phenomenon of resonant activation occurs; resonant activation is also observed in coupled FHN elements. The mean activation time with small noise intensity is compared with the theoretical results.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.