Literature DB >> 28656774

Emulating Bilingual Synaptic Response Using a Junction-Based Artificial Synaptic Device.

He Tian1, Xi Cao2, Yujun Xie3, Xiaodong Yan1, Andrew Kostelec4, Don DiMarzio4, Cheng Chang5, Li-Dong Zhao5, Wei Wu1, Jesse Tice4, Judy J Cha3, Jing Guo2, Han Wang1.   

Abstract

Excitatory and inhibitory postsynaptic potentials are the two fundamental categories of synaptic responses underlying the diverse functionalities of the mammalian nervous system. Recent advances in neuroscience have revealed the co-release of both glutamate and GABA neurotransmitters from a single axon terminal in neurons at the ventral tegmental area that can result in the reconfiguration of the postsynaptic potentials between excitatory and inhibitory effects. The ability to mimic such features of the biological synapses in semiconductor devices, which is lacking in the conventional field effect transistor-type and memristor-type artificial synaptic devices, can enhance the functionalities and versatility of neuromorphic electronic systems in performing tasks such as image recognition, learning, and cognition. Here, we demonstrate an artificial synaptic device concept, an ambipolar junction synaptic devices, which utilizes the tunable electronic properties of the heterojunction between two layered semiconductor materials black phosphorus and tin selenide to mimic the different states of the synaptic connection and, hence, realize the dynamic reconfigurability between excitatory and inhibitory postsynaptic effects. The resulting device relies only on the electrical biases at either the presynaptic or the postsynaptic terminal to facilitate such dynamic reconfigurability. It is distinctively different from the conventional heterosynaptic device in terms of both its operational characteristics and biological equivalence. Key properties of the synapses such as potentiation and depression and spike-timing-dependent plasticity are mimicked in the device for both the excitatory and inhibitory response modes. The device offers reconfiguration properties with the potential to enable useful functionalities in hardware-based artificial neural network.

Entities:  

Keywords:  artificial synaptic device; black phosphorus; reconfigurability; tin selenide; two-dimensional heterojunctions

Mesh:

Substances:

Year:  2017        PMID: 28656774     DOI: 10.1021/acsnano.7b03033

Source DB:  PubMed          Journal:  ACS Nano        ISSN: 1936-0851            Impact factor:   15.881


  6 in total

1.  Rectifying Resistive Memory Devices as Dynamic Complementary Artificial Synapses.

Authors:  Dan Berco
Journal:  Front Neurosci       Date:  2018-10-22       Impact factor: 4.677

2.  Ultralow Power Wearable Heterosynapse with Photoelectric Synergistic Modulation.

Authors:  Tian-Yu Wang; Jia-Lin Meng; Zhen-Yu He; Lin Chen; Hao Zhu; Qing-Qing Sun; Shi-Jin Ding; Peng Zhou; David Wei Zhang
Journal:  Adv Sci (Weinh)       Date:  2020-03-16       Impact factor: 16.806

3.  In-sensor reservoir computing for language learning via two-dimensional memristors.

Authors:  Linfeng Sun; Zhongrui Wang; Jinbao Jiang; Yeji Kim; Bomin Joo; Shoujun Zheng; Seungyeon Lee; Woo Jong Yu; Bai-Sun Kong; Heejun Yang
Journal:  Sci Adv       Date:  2021-05-14       Impact factor: 14.136

4.  Flexible synaptic floating gate devices with dual electrical modulation based on ambipolar black phosphorus.

Authors:  Xiong Xiong; Xin Wang; Qianlan Hu; Xuefei Li; Yanqing Wu
Journal:  iScience       Date:  2022-02-18

5.  Rectifying optoelectronic memory based on WSe2/graphene heterostructures.

Authors:  Sung Hyun Kim; Myung Uk Park; ChangJun Lee; Sum-Gyun Yi; Myeongjin Kim; Yongsuk Choi; Jeong Ho Cho; Kyung-Hwa Yoo
Journal:  Nanoscale Adv       Date:  2021-07-20

6.  Two-Dimensional Perovskite-Gated AlGaN/GaN High-Electron-Mobility-Transistor for Neuromorphic Vision Sensor.

Authors:  Xitong Hong; Yulong Huang; Qianlei Tian; Sen Zhang; Chang Liu; Liming Wang; Kai Zhang; Jia Sun; Lei Liao; Xuming Zou
Journal:  Adv Sci (Weinh)       Date:  2022-07-22       Impact factor: 17.521

  6 in total

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