A Practical Guide to Tuning Spiking Neuronal Dynamics for Computational Neuroscience and NeuroAI Research

Abstract

In this work, we examine and study the fundamental elements of spiking neural networks (SNNs) as well as how to tune them. Concretely, we focus on two different foundational neuronal units utilized in SNNs -- the leaky integrate-and-fire (LIF) and the resonate-and-fire (RAF) neuron. We explore key equations as well as how hyperparameter value settings affect model behavior. Beyond hyperparameters, we study and discuss other important design elements of SNNs -- the choice of input encoding, the construction of a neural assembly, and the setup for excitatory-inhibitory populations -- and how these impact neuronal dynamics.

Expanded Version