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相关概念视频

Neuroplasticity01:01

Neuroplasticity

259
Neuroplasticity reflects the brain's remarkable capacity to adapt and evolve, responding dynamically to learning, experiences, or injury by reorganizing its neural circuitry. This reorganization involves creating new neural connections and refining old ones through a series of biological processes that contribute to the brain's lifelong development and adaptability.
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Long-term Potentiation01:35

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.
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Integration of Synaptic Events01:28

Integration of Synaptic Events

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Synaptic integration mainly includes the summation of graded potentials. Graded potentials, regardless of their type, cause subtle alterations in membrane voltage, resulting in either depolarization or hyperpolarization. These incremental changes, when combined or summed, can propel the neuron toward its threshold. Consider, for example, a membrane experiencing a +15 mV shift, causing it to depolarize from -70 mV to -55 mV. In this scenario, graded potentials govern the membrane's ability...
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Neural Circuits01:25

Neural Circuits

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Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
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The Synapse02:47

The Synapse

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Neurons communicate with one another by passing on their electrical signals to other neurons. A synapse is the location where two neurons meet to exchange signals. At the synapse, the neuron that sends the signal is called the presynaptic cell, while the neuron that receives the message is called the postsynaptic cell. Note that most neurons can be both presynaptic and postsynaptic, as they both transmit and receive information.
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Synaptic Signaling01:09

Synaptic Signaling

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Neurons communicate at synapses, or junctions, to excite or inhibit the activity of other neurons or target cells, such as muscles. Synapses may be chemical or electrical.
Most synapses are chemical, meaning an electrical impulse or action potential spurs the release of chemical messengers called neurotransmitters. The neuron sending the signal is called the presynaptic neuron, and the neuron receiving the signal is the postsynaptic neuron.
The presynaptic neuron fires an action potential that...
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相关实验视频

Updated: May 22, 2025

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond
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模块化合成突触表现出复杂的多层次可塑性

Xingji Liu1, Yao Ni1, Zujun Wang2

  • 1School of Integrated Circuits, Guangdong University of Technology, Guangzhou, 510006, China.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
|May 20, 2025
PubMed
概括

研究人员开发了一种人工突触 (HRAS),可以精确地控制通道电荷,模拟双神经递质的作用. 这一突破使得多层次的可塑性和时空计算能够实现安全的信息处理和增强的神经网络.

关键词:
生物启发的加密应用.双神经递质神经递质.侧向调制是一种侧向调制.时间空间的属性.突触晶体管的突触晶体管是什么

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科学领域:

  • 材料科学 材料科学 材料科学
  • 神经科学是一个神经科学.
  • 计算机工程 计算机工程

背景情况:

  • 人工突触对于开发神经形态计算系统至关重要.
  • 现有的人工突触模型往往缺乏复杂性来模仿复杂的神经过程,如侧向抑制和多层次可塑性.

研究的目的:

  • 开发一种新型的人工突触,能够模拟双神经递质的多层次协调作用.
  • 在多层次的尺度上实现横向抑制/增强和短期/长期可塑性之间的复杂相互作用.
  • 探索这种人工突触在生物灵感计算和安全信息处理中的应用.

主要方法:

  • 开发一个不对称的双门异构接口调节的人工突触 (HRAS).
  • 使用印锡氧化物 (ITZO) 双接口通道,由主门和侧门调节.
  • 采用介电合和离子效应来精确控制通道电荷.

主要成果:

  • 该HRAS装置成功模拟了双神经递质的多层次协调作用.
  • 首次实现了多层次的横向抑制/增强和短期/长期可塑性.
  • 在模拟频率依赖的图像过和动态视觉持久性方面展示了HRAS能力.
  • 提出了一种基于HRAS的双门输入神经网络架构,具有增强的识别能力.

结论:

  • 开发的HRAS提供了一个多功能设备级平台,通过利用时空属性来安全处理信息.
  • 基于HRAS的新型神经网络架构显示了先进的生物启发计算应用的前景.
  • 这项工作代表了创造更复杂和功能更强的人工突触装置的重大进步.