Intrinsic plasticity of silicon nanowire neurotransistors for dynamic memory and learning functions

被引:0
|
作者
Eunhye Baek
Nikhil Ranjan Das
Carlo Vittorio Cannistraci
Taiuk Rim
Gilbert Santiago Cañón Bermúdez
Khrystyna Nych
Hyeonsu Cho
Kihyun Kim
Chang-Ki Baek
Denys Makarov
Ronald Tetzlaff
Leon Chua
Larysa Baraban
Gianaurelio Cuniberti
机构
[1] TU Dresden,Institute for Materials Science and Max Bergmann Center of Biomaterials
[2] TU Dresden,Center for Advancing Electronics Dresden
[3] Tsinghua University,Center for Brain
[4] University of Calcutta,Inspired Computing Research (CBICR), Beijing Innovation Center for Future Chip
[5] TU Dresden,Department of Radio Physics and Electronics
[6] Tsinghua University,Biomedical Cybernetics Group, Biotechnology Center (BIOTEC), Center for Molecular and Cellular Bioengineering (CMCB), Center for Systems Biology Dresden (CSBD), Cluster of Excellence Physics of Life (PoL)
[7] Pohang University of Science and Technology,Center for Complex Network Intelligence (CCNI), Tsinghua Laboratory of Brain and Intelligence
[8] Helmholtz-Zentrum Dresden-Rossendorf e.V.,Department of Creative IT Engineering
[9] Jeonbuk National University,Institute of Ion Beam Physics and Materials Research
[10] Technische Universität Dresden,Division of Electronic Engineering
[11] EECS Department,Chair of Fundamentals of Electrical Engineering
[12] Helmholtz-Zentrum Dresden-Rossendorf e.V.,University of California
来源
Nature Electronics | 2020年 / 3卷
关键词
D O I
暂无
中图分类号
学科分类号
摘要
Neuromorphic architectures merge learning and memory functions within a single unit cell and in a neuron-like fashion. Research in the field has been mainly focused on the plasticity of artificial synapses. However, the intrinsic plasticity of the neuronal membrane is also important in the implementation of neuromorphic information processing. Here we report a neurotransistor made from a silicon nanowire transistor coated by an ion-doped sol–gel silicate film that can emulate the intrinsic plasticity of the neuronal membrane. The neurotransistors are manufactured using a conventional complementary metal–oxide–semiconductor process on an 8-inch (200 mm) silicon-on-insulator wafer. Mobile ions allow the film to act as a pseudo-gate that generates memory and allows the neurotransistor to display plasticity. We show that multiple pulsed input signals of the neurotransistor are non-linearly processed by sigmoidal transformation into the output current, which resembles the functioning of a neuronal membrane. The output response is governed by the input signal history, which is stored as ionic states within the silicate film, and thereby provides the neurotransistor with learning capabilities.
引用
收藏
页码:398 / 408
页数:10
相关论文
共 50 条
  • [41] Silicon nanowire arrays as learning chemical vapour classifiers
    Niskanen, A. O.
    Colli, A.
    White, R.
    Li, H. W.
    Spigone, E.
    Kivioja, J. M.
    NANOTECHNOLOGY, 2011, 22 (29)
  • [42] More than synaptic plasticity: role of nonsynaptic plasticity in learning and memory
    Mozzachiodi, Riccardo
    Byrne, John H.
    TRENDS IN NEUROSCIENCES, 2010, 33 (01) : 17 - 26
  • [43] Microglia regulation of synaptic plasticity and learning and memory
    Jessica Cornell
    Shelbi Salinas
    Hou-Yuan Huang
    Miou Zhou
    Neural Regeneration Research, 2022, 17 (04) : 705 - 716
  • [44] A role for tau in learning, memory and synaptic plasticity
    Biundo, Fabrizio
    Del Prete, Dolores
    Zhang, Hong
    Arancio, Ottavio
    D'Adamio, Luciano
    SCIENTIFIC REPORTS, 2018, 8
  • [45] Myelin plasticity: sculpting circuits in learning and memory
    Wendy Xin
    Jonah R. Chan
    Nature Reviews Neuroscience, 2020, 21 : 682 - 694
  • [46] Learning, Memory & Plasticity: A Systems Level Approach
    Hager, A.
    CANADIAN JOURNAL OF EXPERIMENTAL PSYCHOLOGY-REVUE CANADIENNE DE PSYCHOLOGIE EXPERIMENTALE, 2012, 66 (04): : 314 - 314
  • [47] A role for tau in learning, memory and synaptic plasticity
    Fabrizio Biundo
    Dolores Del Prete
    Hong Zhang
    Ottavio Arancio
    Luciano D’Adamio
    Scientific Reports, 8
  • [48] Adaptation, perceptual learning, and plasticity of brain functions
    Horton, Jonathan C.
    Fahle, Manfred
    Mulder, Theo
    Trauzettel-Klosinski, Susanne
    GRAEFES ARCHIVE FOR CLINICAL AND EXPERIMENTAL OPHTHALMOLOGY, 2017, 255 (03) : 435 - 447
  • [49] Myelin plasticity: sculpting circuits in learning and memory
    Xin, Wendy
    Chan, Jonah R.
    NATURE REVIEWS NEUROSCIENCE, 2020, 21 (12) : 682 - 694
  • [50] Microglia regulation of synaptic plasticity and learning and memory
    Cornell, Jessica
    Salinas, Shelbi
    Huang, Hou-Yuan
    Zhou, Miou
    NEURAL REGENERATION RESEARCH, 2022, 17 (04) : 705 - 716