Biologically Plausible Artificial Synaptic Array: Replicating Ebbinghaus' Memory Curve with Selective Attention. Issue 14 (28th February 2021)
- Record Type:
- Journal Article
- Title:
- Biologically Plausible Artificial Synaptic Array: Replicating Ebbinghaus' Memory Curve with Selective Attention. Issue 14 (28th February 2021)
- Main Title:
- Biologically Plausible Artificial Synaptic Array: Replicating Ebbinghaus' Memory Curve with Selective Attention
- Authors:
- Roe, Dong Gue
Kim, Seongchan
Choi, Yoon Young
Woo, Hwije
Kang, Moon Sung
Song, Young Jae
Ahn, Jong‐Hyun
Lee, Yoonmyung
Cho, Jeong Ho - Abstract:
- Abstract: The nature of repetitive learning and oblivion of memory enables humans to effectively manage vast amounts of memory by prioritizing information for long‐term storage. Inspired by the memorization process of the human brain, an artificial synaptic array is presented, which mimics the biological memorization process by replicating Ebbinghaus' forgetting curve. To construct the artificial synaptic array, signal‐transmitting access transistors and artificial synaptic memory transistors are designed using indium–gallium–zinc‐oxide and poly(3‐hexylthiophene), respectively. To secure the desired performance of the access transistor in regulating the input signal to the synaptic transistor, the content of gallium in the access transistor is optimized. In addition, the operation voltage of the synaptic transistor is carefully selected to achieve memory‐state efficiency. Repetitive learning characterizing Ebbinghaus' oblivion curves is realized using an artificial synaptic array with optimized conditions for both transistor components. This successfully demonstrates a biologically plausible memorization process. Furthermore, selective attention for information prioritization in the human brain is mimicked by selectively applying repetitive learning to a synaptic transistor with a high memory state. The demonstrated biologically plausible artificial synaptic array provides great scope for advancement in bioinspired electronics. Abstract : Inspired by the memorization processAbstract: The nature of repetitive learning and oblivion of memory enables humans to effectively manage vast amounts of memory by prioritizing information for long‐term storage. Inspired by the memorization process of the human brain, an artificial synaptic array is presented, which mimics the biological memorization process by replicating Ebbinghaus' forgetting curve. To construct the artificial synaptic array, signal‐transmitting access transistors and artificial synaptic memory transistors are designed using indium–gallium–zinc‐oxide and poly(3‐hexylthiophene), respectively. To secure the desired performance of the access transistor in regulating the input signal to the synaptic transistor, the content of gallium in the access transistor is optimized. In addition, the operation voltage of the synaptic transistor is carefully selected to achieve memory‐state efficiency. Repetitive learning characterizing Ebbinghaus' oblivion curves is realized using an artificial synaptic array with optimized conditions for both transistor components. This successfully demonstrates a biologically plausible memorization process. Furthermore, selective attention for information prioritization in the human brain is mimicked by selectively applying repetitive learning to a synaptic transistor with a high memory state. The demonstrated biologically plausible artificial synaptic array provides great scope for advancement in bioinspired electronics. Abstract : Inspired by the memorization process of the human brain, an artificial synaptic array is developed, which mimics the biological memorization process by replicating Ebbinghaus' forgetting curve. To construct the artificial synaptic array, signal‐transmitting access transistors and artificial synaptic memory transistors are designed using indium–gallium–zinc‐oxide and poly(3‐hexylthiophene), respectively. … (more)
- Is Part Of:
- Advanced materials. Volume 33:Issue 14(2021)
- Journal:
- Advanced materials
- Issue:
- Volume 33:Issue 14(2021)
- Issue Display:
- Volume 33, Issue 14 (2021)
- Year:
- 2021
- Volume:
- 33
- Issue:
- 14
- Issue Sort Value:
- 2021-0033-0014-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2021-02-28
- Subjects:
- artificial synapses -- bioinspiration -- memorization -- multi‐states -- repetitive learning -- synapse arrays
Materials -- Periodicals
Chemical vapor deposition -- Periodicals
620.11 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1521-4095 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/adma.202007782 ↗
- Languages:
- English
- ISSNs:
- 0935-9648
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0696.897800
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 23464.xml