Biological mimesis based on the WiBIC platform: Modeling of Pavlovian conditioning

抄録

Wireless Brain-Inspired Computing (WiBIC) integrates spiking neural network (SNN) functionality directly into IoT nodes, unifying the concepts of networking in both the IoT and neural domains. Previous studies have shown that WiBIC enables intelligent information processing within the network itself. To extend the applicability of WiBIC, it is essential to show that the network can autonomously generate biologically inspired responses. This paper presents a study on modeling Pavlovian conditioning using the WiBIC platform. We use the Modulated Spike-Timing-Dependent Plasticity (MSTDP) learning rule to facilitate associative learning. For wireless communication within the WiBIC network, we use Asynchronous Pulse Code Multiple Access (APCMA), which effectively emulates the behavior of biological networks. The WiBIC platform was implemented on a Field Programmable Gate Array(FPGA). Experimental results confirm that the implemented system successfully replicates the Pavlovian conditioning process, demonstrating the ability of WiBIC to emulate biological learning mechanisms.