Abstract
We present a theoretical and computational work, aiming at the estimation of firing rate based excitatory and inhibitory neural network from realistic stimulus-response data. The stimulus and response recordings are taken from a previous study which performs a measurement on the H1 neurons of the order Diptera flies. The parameter estimation is performed by maximum likelihood method. As the stimulus-response data is a single recording of 20 minutes, it is segmented and individual segments are superimposed on each other to increase the statistical content of information. The true values of the model parameters are unknown as we are not using synthetic data. Because of this fact, two sample Kolmogorov-Smirnov test is applied to compare the interspiking intervals of the recorded and model responses. Estimation and analysis results are presented in tabular and graphical forms. In addition, a comparison with previous research employing a modified Fitzhugh-Nagumo model is made.
Highlights
Compartmental neural modeling is appeared after the development of the well known Hodgkin-Huxley model [23] in 1952
This was a highly nonlinear fourth order differential equation aiming at the description of quantitative features such as membrane potentials and ion channel conductances Following that, simpler models such as Fitzhugh-Nagumo [18], MorrisLecar [35] and Hindmarsh-Rose [22] models appeared
We attempt to estimate the parameters of an firing rate based neural network model representing excitatory and inhibitory behaviors
Summary
The compartmental models may involve single or multiple subsystems and are relatively complicated. They are used when one needs to simulate one or more biophysical features of realistic neurons. Compartmental neural modeling is appeared after the development of the well known Hodgkin-Huxley model [23] in 1952. This was a highly nonlinear fourth order differential equation aiming at the description of quantitative features such as membrane potentials and ion channel conductances Following that, simpler models such as Fitzhugh-Nagumo [18], MorrisLecar [35] and Hindmarsh-Rose [22] models appeared.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Journal of Scientific Technology and Engineering Research
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
