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相关概念视频

MOS Capacitor01:25

MOS Capacitor

747
A Metal-Oxide-Semiconductor (MOS) capacitor is a fundamental structure used extensively in semiconductor device technology, particularly in the fabrication of integrated circuits and MOSFETs (metal-oxide-semiconductor field-effect transistors). The MOS capacitor consists of three layers: a metal gate, a dielectric oxide, and a semiconductor substrate.
The metal gate is typically made from highly conductive materials such as aluminum or polysilicon. Beneath the metal gate lies a thin layer of...
747
Chemical Synapses01:26

Chemical Synapses

8.8K
Chemical synapses are specialized sites between two neurons or between a neuron and a non-neuronal cell like a muscle, glandular or sensory cell.
Because chemical synapses depend on the release of neurotransmitter molecules from synaptic vesicles to pass on their signal, there is an approximately one millisecond delay between when the axon potential reaches the presynaptic terminal and when the neurotransmitter leads to opening of postsynaptic ion channels. Additionally, this signaling is...
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Ligand-Gated Ion Channel Receptor: Gating Mechanism01:30

Ligand-Gated Ion Channel Receptor: Gating Mechanism

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Ligand-gated ion channels are transmembrane proteins that play a vital role in intercellular communication and functions of the nervous system. They allow the influx of ions across the membrane once the neurotransmitter binds, allowing the subsequent transmission of electrical excitation across the neurons. Other ligand-gated ion channels, like the γ-aminobutyric acid (GABA) receptor, permit anions like chloride into the cells on the binding of the GABA molecule. Their entry into the cell...
2.2K
Long-term Potentiation01:25

Long-term Potentiation

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Long-term potentiation, or LTP, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTP is the process of synaptic strengthening that occurs over time between pre and postsynaptic neuronal connections. The synaptic strengthening of LTP works in opposition to the synaptic weakening of long-term depression (LTD) and together are the main mechanisms that underlie learning and memory.
Hebbian LTP
LTP can occur when...
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相关实验视频

Updated: Jun 18, 2025

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
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Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Published on: March 9, 2019

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混合CMOS-Memristor突触电路用于实现基于离子的可塑性模型.

Jae Gwang Lim1,2, Sung-Jae Park1,3, Sang Min Lee1,3

  • 1Center for Semiconductor Technology, Korea Institute of Science and Technology, Seoul, 02792, South Korea.

Scientific reports
|August 2, 2024
PubMed
概括

这项研究介绍了一种新的CMOS-memristor混合突触电路,能够模拟用于节能神经形态计算的多种尖峰时间依赖可塑性 (STDP) 规则. 该电路成功展示了关联式学习,为可扩展的大脑启发的AI铺平了道路.

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A Method for Growing Bio-memristors from Slime Mold
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Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond
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相关实验视频

Last Updated: Jun 18, 2025

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
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Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Published on: March 9, 2019

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A Method for Growing Bio-memristors from Slime Mold
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科学领域:

  • 神经形态工程的神经形态工程
  • 人工智能的人工智能
  • 材料科学 材料科学 材料科学

背景情况:

  • 神经形态计算的目标是节能大数据处理,尖端神经网络 (SNN) 和生物可信的学习规则是关键方法.
  • 现有的SNN硬件经常实现标准的尖峰时机依赖可塑性 (STDP),但很少捕捉到生物大脑中观察到的多样化的STDP规则.

研究的目的:

  • 提出和设计一个CMOS-memristor混合突触电路,用于硬件实现基于离子的可塑性模型.
  • 使用这种混合电路模拟各种STDP曲线,超越标准STDP实现.
  • 证明电路在神经网络操作中的能力,特别是关联式学习.

主要方法:

  • 开发了一种CMOS-memristor混合突触电路,利用memristors进行模拟非挥发性内存.
  • 设计了四个子块的电路,利用memristor属性来模拟可塑性.
  • 采用H桥电路结构和PWM调制用于重量变化.
  • 实施了基于离子的可塑性模型,以实现多种STDP曲线.

主要成果:

  • 在单个CMOS-memristor混合电路中成功模拟了各种STDP曲线.
  • 演示了一个简单的神经网络操作,用于协会学习 (帕夫洛维安调节).
  • 用memristor的非挥发性和模拟性来利用高效的突触重量更新.

结论:

  • 拟议的CMOS-memristor混合突触电路有效地模拟了各种STDP规则,解决了当前SNN硬件中的差距.
  • 这种电路有助于开发出更具生物现实的神经形态系统.
  • 该设计显示了可扩展的神经形态计算应用程序的前景,因为它具有大规模集成的潜力.