Action Potential Parameters and Spiking Behavior of Cortical Neurons: A Statistical Analysis for Designing Spiking Neural Networks

Abstract

Cortical neurons exhibit several spiking dynamics both in in-vivo and in-vitro experiments. Neural spikes or action potentials (APs) are also observed in various shapes and forms. Statistical correlation between action potential parameters and associated spiking behaviour of a neuron is discussed in this paper. Three fundamental parameters width, height and energy of an AP along with spiking frequency and inter spike interval (ISI) are extracted for 91 human cortical neurons selected from Allen Institute for Brain Science (AIBS) database. It has been shown that neurons firing narrow, short and low energy APs have higher spiking frequency compared to the neurons with wide and taller APs. For a rise in excitation, it has been presented that information gain for neurons firing wider spikes is less compared to information gain for neurons firing narrow spikes. It has been shown that neurons with low spiking frequency and high spiking frequency dissipate energy of similar order for total spiking activity for similar excitation. Implications of the statistical inferences drawn are explained for a computational model of a spiking neuron. Effect of changing AP width on the overall dynamics of a spiking neural network is also highlighted. Key findings of this study will be useful for designing spiking neural networks for various cognitive applications.