Abstract
A stimulus-response system and conscious response enable humans to respond effectively to environmental changes and external stimuli. This paper presents an artificial stimulus-response system that is inspired by human conscious response and is capable of emulating it. The system is composed of an artificial visual receptor, artificial synapse, artificial neuron circuits, and actuator. By incorporating these artificial nervous components, a series of conscious response processes that markedly reduces response time as a result of learning from repeated stimuli are demonstrated. The proposed artificial stimulus-response system offers the promise of a new research field that would aid the development of artificial intelligence-based organs for patients with neurological disorders.
Highlights
Humans can recognize various stimuli and have a sophisticated reaction system to respond to them
The InP quantum dot (QD) layer in the artificial visual receptor (AVR) is coated onto graphene, and this layer converts a light stimulus into an electrical signal by the photogating effect (36)
For fabrication of the artificial synapse (AS), poly(vinylidene fluoride-trifluoroethylene) [P(VDF-TrFE)] and an ion gel {a mixture of poly(vinylidene fluoride-co-hexafluoropropylene) [P(VDF-HFP)] and 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([EMIM][TFSI]) ionic liquid} are coated to form the retentive electric double layer (EDL), which controls the synaptic connections through a learning process
Summary
Humans can recognize various stimuli and have a sophisticated reaction system to respond to them. Lee group (9) invented an artificial afferent nervous system comprising pressure sensors, an organic ring oscillator, and a synaptic transistor They demonstrated that the artificial nerve could be made compatible with living beings by being connected to the nerve of a cockroach and subsequent actuation of a leg muscle by stimulation. Conscious responses are those that require a learning process by the cerebral cortex, such as an athlete’s starting reaction or catching a flying ball This type of response can be controlled by learning from repeated stimuli and responses, and this learning modulates the synaptic connections and thereby optimizes the response (18–22, 24). Lee group (11) successfully realized light-interactive actuation using an optoelectronic sensorimotor synapse and a neuromuscular system These systems performed signal transmission based on unconscious response, but they did not completely mimic the biological stimulus-response system with conscious response. Simulation of the human stimulus-response system requires integration of neurons capable of conscious responses, stimulus detection, actuation, and control of synaptic connection strengthened by a learning process
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