Abstract:
:Statistical properties of spike trains as well as other neurophysiological data suggest a number of mathematical models of neurons. These models range from entirely descriptive ones to those deduced from the properties of the real neurons. One of them, the diffusion leaky integrate-and-fire neuronal model, which is based on the Ornstein-Uhlenbeck (OU) stochastic process that is restricted by an absorbing barrier, can describe a wide range of neuronal activity in terms of its parameters. These parameters are readily associated with known physiological mechanisms. The other model is descriptive, Gamma renewal process, and its parameters only reflect the observed experimental data or assumed theoretical properties. Both of these commonly used models are related here. We show under which conditions the Gamma model is an output from the diffusion OU model. In some cases, we can see that the Gamma distribution is unrealistic to be achieved for the employed parameters of the OU process.
journal_name
Biol Cybernjournal_title
Biological cyberneticsauthors
Lansky P,Sacerdote L,Zucca Cdoi
10.1007/s00422-016-0690-xsubject
Has Abstractpub_date
2016-06-01 00:00:00pages
193-200issue
2-3eissn
0340-1200issn
1432-0770pii
10.1007/s00422-016-0690-xjournal_volume
110pub_type
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