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相关概念视频

Neural Circuits01:25

Neural Circuits

1.1K
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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Synaptic Signaling01:09

Synaptic Signaling

5.5K
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...
5.5K
The Synapse02:47

The Synapse

124.5K
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.
124.5K

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相关实验视频

Updated: Jun 13, 2025

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond
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Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond

Published on: June 24, 2015

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非同步的数值尖端神经膜系统具有局部同步.

Hongyan Zhang1, Yuzhen Zhao1, Xiyu Liu1

  • 1Business School, Shandong Normal University, Jinan, 25000, Shandong, P. R. China.

International journal of neural systems
|September 10, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的尖端神经P系统 (SN P系统) 与局部同步的神经元集,增强计算能力. 新系统的有效性与膜计算中的现有模型相美.

关键词:
数字刺神经膜系统的神经膜系统.全球异步膜系统当地同步 地方同步

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Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments
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Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
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Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

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相关实验视频

Last Updated: Jun 13, 2025

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond
08:08

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond

Published on: June 24, 2015

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Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments
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Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments

Published on: November 12, 2019

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Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
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Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

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科学领域:

  • 膜计算技术的使用
  • 计算神经科学是一种神经科学.
  • 人工神经网络的人工神经网络

背景情况:

  • 尖端神经P系统 (SN P系统) 是第三代神经网络模型,自2006年以来在膜计算中得到广泛研究.
  • 全球异步数值尖端神经P系统 (ANSN P系统) 提供了更广泛的适应性.
  • 生物神经科学揭示了一些神经元社区同步运作.

研究的目的:

  • 为了研究一个新的全球异步尖端神经P系统 (ANSN P系统),集成本地同步神经元集.
  • 探索局部同步如何影响计算属性,例如减少值依赖和增强控制不确定性.
  • 评估新系统作为生成器和接受器的计算能力.

主要方法:

  • 设计和分析一种新的ANSN P系统,包括局部同步神经元集.
  • 在生成模式下检查ADD,SUB和FIN模块.
  • 在接受模式下分析INPUT和ADD模块.

主要成果:

  • 新的ANSN P系统在生成和接受模式中展示了计算能力.
  • 与现有的SNP系统进行比较,考虑神经元数量和每个神经元的规则,显示了可比的有效性.
  • 局部同步神经元集的结合增强了控制的不确定性,并减少了值依赖.

结论:

  • 拟议的ANSN P系统与局部同步神经元集是膜计算中的可行和有效模型.
  • 这个模型为在异步计算框架中整合同步行为提供了一个新的视角.
  • 该系统的性能至少与现有的SNP系统一样有效,为进一步研究铺平了道路.