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Dynamics of the semantic priming shift: behavioral experiments and cortical network model

Identifying type I excitability using dynamics of stochastic neural firing patterns

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Identifying type I excitability using dynamics of stochastic neural firing patterns

Content Provider	Springer Nature Link
Author	Jia, Bing Gu, Huaguang
Copyright Year	2012
Abstract	The stochastic firing patterns are simulated near saddle-node bifurcation on an invariant cycle corresponding to type I excitability in stochastic Morris–Lecar model. In absence of external periodic signal, the stochastic firing manifests continuous distribution in ISI histogram (ISIH), whose amplitude at first increases sharply and then decreases exponentially. In presence of the external periodic signal, stochastic firing patterns appear as two cases of integer multiple firing with multiple discrete peaks in ISIH. One manifests perfect exponential decay in all peaks and the other imperfect exponential decay except a lower first peak. These stochastic firing patterns simulated with or without external periodic signal can be demonstrated in the experiments on rat hippocampal CA1 pyramidal neurons. The exponential decay laws in the multiple peaks are also acquired using probability analysis method. The perfect decay law is determined by the independent characteristic within the firing while the imperfect decay law is from the inhibitory effect. In addition, the stochastic firing patterns corresponding to type I excitability are compared to those of type II excitability. The results not only reveal the dynamics of stochastic firing patterns with or without external signal corresponding to type I excitability, but also provide practical indicators to availably identify type I excitability.
Starting Page	485
Ending Page	497
Page Count	13
File Format	PDF
ISSN	18714080
Journal	Cognitive Neurodynamics
Volume Number	6
Issue Number	6
e-ISSN	18714099
Language	English
Publisher	Springer Netherlands
Publisher Date	2012-06-14
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Neural firing pattern Excitability Type I excitability Stochastic process Integer multiple firing Saddle-node bifurcation on an invariant cycle Neurosciences Cognitive Psychology Biochemistry Biomedicine general Computer Science Artificial Intelligence (incl. Robotics)
Content Type	Text
Resource Type	Article
Subject	Cognitive Neuroscience

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Identifying type I excitability using dynamics of stochastic neural firing patterns.

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