Spike Response Fitting and Prediction of a Single Neuron Model

Conductance based detail biological models of neurons are able to predict various forms of spiking patterns with great accuracy, but the computational resources required to simulate large network of such neurons are still incomprehensible. As an alternative various simplified spiking models of neurons have been proposed. These models achieve computational efficiency through dynamical system techniques such as linearization, bifurcation analysis etc. Although, these simplifications have enabled researchers with large scale network simulations, but they require multiple parameters to be fitted and optimized for specific simulation requirements such as spiking behavior, site of action potential initiation etc. It is known that cortical pyramidal neurons are independently capable of generating action potential from various segments of the cell structure such as the soma, apical and basal dendrites, axon hillock, axon initial segment etc. These action potentials interact with each other due to antidromic and orthodromic propagation and may affect the overall cortical dynamics. Furthermore, the Axon Initial Segment was shown as the preferred site of action potential initiation. The result presented in this study focuses on the analysis, fitting and prediction of spikes generated during Action Potential Initiation at Axon Initial Segment (AIS). The Adaptive Exponential Integrate and Fire (AdEx) model was implemented for the purpose in the NEURON simulator and fitted to a biologically accurate neuron model. The study also verifies the shape of individual fitted action potential generated at the AIS and modifies the generic model for more efficient simulation.