Spatiotemporal Modulation of Plasticity in Multi‐Terminal Tactile Synaptic Transistor. (17th October 2022)
- Record Type:
- Journal Article
- Title:
- Spatiotemporal Modulation of Plasticity in Multi‐Terminal Tactile Synaptic Transistor. (17th October 2022)
- Main Title:
- Spatiotemporal Modulation of Plasticity in Multi‐Terminal Tactile Synaptic Transistor
- Authors:
- Mo, Wen‐Ai
Ding, Guanglong
Nie, Zihao
Feng, Zihao
Zhou, Kui
Chen, Ruo‐Si
Xie, Peng
Shang, Gang
Han, Su‐Ting
Zhou, Ye - Abstract:
- Abstract: Neuromorphic system based on artificial synaptic devices is considered as a potential candidate to realize the in‐memory computing and parallel processing of data for overcoming the von Neumann bottleneck. However, to fully imitate the complicated functions of the biological neural networks at the hardware level is still a challenging task. In this work, a multi‐terminal MoS2 synaptic transistor is developed, which not only simulates various biological synaptic behaviors, including paired pulse facilitation (PPF), excitatory/inhibitory post‐synaptic current (EPSC/IPSC), spike‐rate‐dependent plasticity (SRDP), and spike‐timing‐dependent plasticity (STDP), but also can independently mimic the parallel signal processing and transmissions in biological multipolar neurons. By combining the multi‐terminal MoS2 synaptic transistor with the micro‐structured polydimethylsiloxane (PDMS) pressure sensors, an intelligent tactile recognition system is built up, which can realize the spatiotemporal recognition of touch position. Furthermore, with sensor selection, the spatiotemporal modulation of synaptic plasticity and the human learning and forgetting behaviors to the knowledge with different difficulty degrees can be mimicked. This work provides a novel interconnection scheme for simulating signal transmission and processing among neurons, showing broad application prospects of the multi‐terminal MoS2 synaptic transistor in intelligent human–computer interaction and bionicAbstract: Neuromorphic system based on artificial synaptic devices is considered as a potential candidate to realize the in‐memory computing and parallel processing of data for overcoming the von Neumann bottleneck. However, to fully imitate the complicated functions of the biological neural networks at the hardware level is still a challenging task. In this work, a multi‐terminal MoS2 synaptic transistor is developed, which not only simulates various biological synaptic behaviors, including paired pulse facilitation (PPF), excitatory/inhibitory post‐synaptic current (EPSC/IPSC), spike‐rate‐dependent plasticity (SRDP), and spike‐timing‐dependent plasticity (STDP), but also can independently mimic the parallel signal processing and transmissions in biological multipolar neurons. By combining the multi‐terminal MoS2 synaptic transistor with the micro‐structured polydimethylsiloxane (PDMS) pressure sensors, an intelligent tactile recognition system is built up, which can realize the spatiotemporal recognition of touch position. Furthermore, with sensor selection, the spatiotemporal modulation of synaptic plasticity and the human learning and forgetting behaviors to the knowledge with different difficulty degrees can be mimicked. This work provides a novel interconnection scheme for simulating signal transmission and processing among neurons, showing broad application prospects of the multi‐terminal MoS2 synaptic transistor in intelligent human–computer interaction and bionic neuromorphic perception systems. Abstract : A multi‐terminal MoS2 synaptic transistor has been designed to mimic the parallel signal transmission behaviors of biological multipolar neurons. With the combination of micro‐structured pressure sensors, an intelligent tactile recognition system is built up to realize spatiotemporal tactile recognition and modulation of synaptic plasticity. The system can also emulate the human learning and forgetting behaviors with various degrees of difficulty. … (more)
- Is Part Of:
- Advanced Electronic Materials. Volume 9:Number 1(2023)
- Journal:
- Advanced Electronic Materials
- Issue:
- Volume 9:Number 1(2023)
- Issue Display:
- Volume 9, Issue 1 (2023)
- Year:
- 2023
- Volume:
- 9
- Issue:
- 1
- Issue Sort Value:
- 2023-0009-0001-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2022-10-17
- Subjects:
- artificial synapses -- memory -- pressure sensors -- tactile recognition -- transistors
Materials -- Electric properties -- Periodicals
Materials science -- Periodicals
Magnetic materials -- Periodicals
Electronic apparatus and appliances -- Periodicals
537 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2199-160X ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/aelm.202200733 ↗
- Languages:
- English
- ISSNs:
- 2199-160X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0696.848400
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24994.xml