A flexible artificial chemosensory neuronal synapse based on chemoreceptive ionogel-gated electrochemical transistor

Abstract

The human olfactory system comprises olfactory receptor neurons, projection neurons, and interneurons that perform remarkably sophisticated functions, including sensing, filtration, memorization, and forgetting of chemical stimuli for perception. Developing an artificial olfactory system that can mimic these functions has proved to be challenging. Herein, inspired by the neuronal network inside the glomerulus of the olfactory bulb, we present an artificial chemosensory neuronal synapse that can sense chemical stimuli and mimic the functions of excitatory and inhibitory neurotransmitter release in the synapses between olfactory receptor neurons, projection neurons, and interneurons. The proposed device is based on a flexible organic electrochemical transistor gated by the potential generated by the interaction of gas molecules with ions in a chemoreceptive ionogel. The combined use of a chemoreceptive ionogel and an organic semiconductor channel allows for a long retentive memory in response to chemical stimuli. Long-term memorization of the excitatory chemical stimulus can be also erased by applying an inhibitory electrical stimulus due to ion dynamics in the chemoresponsive ionogel gate electrolyte. Applying a simple device design, we were able to mimic the excitatory and inhibitory synaptic functions of chemical synapses in the olfactory system, which can further advance the development of artificial neuronal systems for biomimetic chemosensory applications.

Artificial Neuron Devices

“…These systems have potential applications in environmental monitoring and food safety inspections, as well as in the development of medical diagnostic tools. 26,107,108…”

“…The human nervous system is a remarkable biological system that has evolved over millions of years to enable humans to sense, process, and respond to information in a highly efficient and intelligent manner. , Engineers and scientists have been fascinated by the prospect of creating machines and robots that can replicate the biological system for a long time. − Although classical computing systems running on software have been used to mimic biological nervous systems, these systems follow a centralized and sequential approach based on the von Neumann model. , In contrast, biological nervous systems utilize a distributed, parallel, and event-driven approach using neurons and synapses to process information. − These differences lead to classical systems being efficient and accurate for well-defined problems, while biological systems are more compact, fault-tolerant, and power-efficient in complex real-world scenarios. − Therefore, emulating the complex cognition of information interaction and processing mechanisms in biological nervous systems has been a major focus in this field. − The goal is to achieve autonomous functions and problem-solving capabilities, which has inspired the research and development of artificial neural systems. By mimicking the functions of the human nervous system, researchers aim to create artificial neuron devices and systems that can perform tasks with the same level of efficiency and intelligence as humans, thus opening up many new possibilities in research fields such as robotics, healthcare, and artificial intelligence. ,− Additionally, understanding and replicating the mechanisms of the human nervous system can provide researchers with deeper insights into how our own brain and nervous system work, leading to potential development of new treatments for neurological disorders and the development of neuroprosthetics and human augmentation. − …”

“…Artificial visual systems have been developed by integrating optical sensors with synaptic devices. − These systems can implement neuromorphic image processing for the recognition of target objects. − Similarly, acoustic sensors have also been employed to create artificial auditory systems that can recognize and interpret sounds for human–computer interactions. − Olfactory and gustatory sensors have been integrated with synaptic devices to mimic the sense of smell and taste. These systems have potential applications in environmental monitoring and food safety inspections, as well as in the development of medical diagnostic tools. ,, …”

3D-Printed Intrinsically Stretchable Organic Electrochemical Synaptic Transistor Array

“…The increase in synaptic weight (ΔW) plays a crucial role in initiating and maintaining LTP, which is closely associated with learning and memory processes. 41 The change in current reflects the weight of synapses, defined as (I n /I 0 %), representing the strength of neuronal connections. A stronger inhibitory effect is achieved by continuously applying varying numbers of pulses (Figure 4G).…”

Adaptive Memory of a Neuromorphic Transistor with Multi-Sensory Signal Fusion

“…Although considerable efforts have been devoted to the development of various neuromorphic devices, most research and data has been limited to unimodal artificial synapses, such as artificial afferent nerves, artificial nociceptors, chemosensory neuronal synapses, and optoelectronic sensorimotor synapses. − Only a few attempts have been made to mimic the fusion of signals from different perceptions by connecting different sensors with separate synaptic devices . Nevertheless, the implementation of multiple-modal artificial synapses based on a single transistor remains challenging due to their complex structures and fabrication processes.…”