A hybrid ambipolar synaptic transistor emulating multiplexed neurotransmission for motivation control and experience-dependent learning

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Abstract

Artificial synapses with full synapse-like functionalities are of crucial importance for the implementation of neuromorphic computing and bioinspired intelligent systems. In particular, the development of artificial synapses with the capability to emulate multiplexed neural transmission is highly desirable, but remains challenging. In this work, we proposed a hybrid ambipolar synaptic transistor that combines two-dimensional (2D) molybdenum disulfide (MoS2) sheet and crystalline one-dimensional (1D) poly(3-hexylthiophene-2,5-diyl) polymer nanowires (P3HT NWs) as dual excitatory channels. Essential synaptic functions, including excitatory postsynaptic current, paired-pulse facilitation, synaptic potentiation and depression, and dynamic filtering were emulated using the synaptic transistor. Benefitting from the dual excitatory channels of the synaptic transistor, the device achieved a fast switch between short-term and long-term memory by altering the charge carriers in the dual channels, i.e., electrons and holes. This emulated the multiplexed neural transmission of different excitatory neurotransmitters, e.g., dopamine and noradrenaline. The plasticity-switchable artificial synapse (PSAS) simulates the task-learning process of individuals under different motivations and the impact of success or failure on task learning and memory, which promises the potential to enable complex functionalities in future neuromorphic intelligent electronics.

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A plasticity-switchable artificial synapse has been proposed to emulate the multiplexed transmission of different neurotransmitters by altering the charge carriers in parallel channels, and simulate the task-learning process of individuals with different motivations.

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Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This work was supported by the National Science Fund for Distinguished Young Scholars of China (No. T2125005), the Tianjin Science Foundation for Distinguished Young Scholars (No. 19JCJQJC61000), and the Shenzhen Science and Technology Project (No. JCYJ20210324121002008).

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    These authors contributed equally to this work.

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