Bio-Inspired Neuromorphic Circuit Design of Nonassociative Learning for Multisensory Enhancement and Depression

The capability of unisensory and multisensory information processing is crucial for bio-inspired intelligent systems. Based on biological nonassociative learning (NAL) and multisensory integration (MSI) mechanisms, a bio-inspired memristor-based neuromorphic circuit is proposed, which bridges multiple unisensory channels with a multisensory mutual associative memory (MMAM) unit. Inspired by the gill-withdrawal reflex in Aplysia, unisensory channels are capable of NAL processes, including habituation, sensitization, dishabituation, and spontaneous recovery, providing adaptation to innocuous stimuli and sensitivity to noxious stimuli. In light of the response enhancement and depression in the superior colliculus under multisensory cues, the MMAM unit enables the interaction between multiple sensory stimuli, thereby facilitating multisensory enhancement and depression, collectively known as MSI. By leveraging the proposed circuit, the artificial nociceptor and semantic satiation are mimicked. Furthermore, circuit performance analyses demonstrate the robustness and device tolerance. By further incorporating visual, auditory, tactile, olfactory, and gustatory sensors and scaling up the circuit, the neuromorphic system is promising for intelligent robot platforms with enhanced environmental perception and cognition capabilities.