Real-Time Embedded Simulation Platform for Hippocampal Traveling Waves of Electric Field Conduction

Abstract

The investigation of hippocampal traveling waves has gained significant importance in comprehending and treating neural disorders such as epilepsy, as well as unraveling the neural mechanisms underlying memory and cognition. Recently, it has been discovered through both in vivo and in vitro experiments that hippocampal traveling waves are typically characterized by the coexistence of fast and slow waves. However, electrophysiological experiments face limitations in terms of cost, reproducibility, and ethical considerations, which hinder the exploration of the mechanisms behind these traveling waves. Model-based real-time virtual simulations can serve as a reliable alternative to pre-experiments on hippocampal preparations. In this paper, we propose a real-time simulation method for traveling waves of electric field conduction on a 2D plane by implementing a hippocampal network model on a multi-core parallel embedded computing platform (MPEP). A numerical model, reproducing both NMDA-dependent fast waves and Ca-dependent slow waves, is optimized for deployment on this platform. A multi-core parallel scheduling policy is employed to address the conflict between model complexity and limited physical resources. With the support of a graphical user interface (GUI), users can rapidly construct large-scale models and monitor the progress of real simulations. Experimental results using MPEP with four computing boards and one routing board demonstrate that a hippocampal network with a 200 × 16 pyramidal neuron array can execute real-time generation of both fast and slow traveling waves with total power consumption below 500 mW. This study presents a real-time virtual simulation strategy as an efficient alternative to electrophysiological experiments for future research on hippocampal traveling waves.

Keywords

• traveling waves
• hippocampal network
• electric field
• real-time simulation
• embedded system