Because of the fast expansion of artificial intelligence, development and applications of neuromorphic systems attract extensive interest. In this paper, a highly interconnected neuromorphic architecture (HINA) based on flexible self-supported multiterminal organic transistors is proposed. Au electrodes, poly(3-hexylthiophene) active channels, and ion-conducting membranes were combined to fabricate organic neuromorphic devices. Especially, freestanding ion-conducting membranes were used as gate dielectrics as well as support substrates. Basic neuromorphic behavior and four forms of spike-timing-dependent plasticity were emulated. The fabricated neuromorphic device showed excellent electrical stability and mechanical flexibility after 1000 bends. Most importantly, the device structure is interconnected in a way similar to the neural architecture of the human brain and realizes not only the structure of the multigate but also characteristics of the global gate. Dynamic processes of memorizing and forgetting were incorporated into the global gate matrix simulation. Pavlov's learning rule was also simulated by taking advantage of the multigate array. Realization of HINAs would open a new path for flexible and sophisticated neural networks.
Keywords: Pavlov’s learning rule; STDP; flexible neuromorphic devices; highly interconnected architectures; memorizing and forgetting; self-supported multiterminal organic transistors.