4.8 Article

Restickable Oxide Neuromorphic Transistors with Spike-Timing-Dependent Plasticity and Pavlovian Associative Learning Activities

期刊

ADVANCED FUNCTIONAL MATERIALS
卷 28, 期 44, 页码 -

出版社

WILEY-V C H VERLAG GMBH
DOI: 10.1002/adfm.201804025

关键词

flexible electronics; neuromorphic transistors; Pavlovian associative learning; spike-timing-dependent plasticity

资金

  1. Zhejiang Provincial Natural Science Foundation of China [LR18F040002]
  2. Ningbo Science and Technology Innovation Team [2016B10005]
  3. National Natural Science Foundation of China [11474293]
  4. Youth Innovation Promotion Association CAS
  5. Key Research Program of Frontier Sciences, Chinese Academy of Sciences [QYZDB-SSW-JSC047]
  6. CAS Interdisciplinary Innovation Team

向作者/读者索取更多资源

In neural system, both spike-timing-dependent plasticity (STDP) and conditioned reflex are vital synaptic learning mechanisms to regulate advanced neural activities, being associated with temporally coupled stimuli. Thus, realization of STDP and conditioned reflex on a single solid-state device may open up new opportunities for neuromorphic engineering. Here, restickable chitosan-gated oxide neuromorphic transistors are fabricated on polyimide tape. Based on protonic electrochemical doping/de-doping processes at indium-tin-oxide/chitosan interfaces, four types of STDP learning rules are successfully demonstrated, including Hebbian STDP, anti-Hebbian STDP, symmetrical STDP, and visual STDP. Trained with Hebbian STDP, Pavlovian associative learning and extinction behaviors are demonstrated successfully on a single-oxide neuromorphic transistor. No complex device circuits are needed. It is interesting to note here that the devices can be pasted on different holders with different curvature radii without degrading the transistor performances and STDP learning rules. Moreover, the proposed oxide neuromorphic transistors can be dissolved in deionized water easily. The results here indicate potential applications of the proposed restickable oxide neuromorphic transistors in flexible neuromorphic cognitive platforms.

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