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相关概念视频

Neural Circuits01:25

Neural Circuits

2.6K
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...
2.6K
Integration of Synaptic Events01:28

Integration of Synaptic Events

3.4K
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 to...
3.4K
Associative Learning01:27

Associative Learning

1.2K
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
1.2K
Overview of Synapses01:25

Overview of Synapses

4.7K
A synapse is a specialized structure where two neurons connect, allowing them to pass an electrical or chemical signal to another neuron. It is the point of communication between neurons. The term "synapse" is derived from the Greek word "synapsis," which means "conjunction." The entire process of neural communication revolves around the synapse. When activated, a neuron releases chemicals known as neurotransmitters into the synapse. These neurotransmitters cross the synapse and bind to...
4.7K
Electrical Synapses01:28

Electrical Synapses

10.1K
Electrical synapses found in all nervous systems play important and unique roles. In these synapses, the presynaptic and postsynaptic membranes are very close together (3.5 nm) and are actually physically connected by channel proteins forming gap junctions.
Gap junctions allow the current to pass directly from one cell to the next. In contrast, in the chemical synapse, the neurotransmitters carry the information through the synaptic cleft from one neuron to the next. They consist of two...
10.1K
Chemical Synapses01:26

Chemical Synapses

4.3K
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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相关实验视频

Updated: Jan 11, 2026

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

Published on: March 2, 2015

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混合功能3D人工突触用于卷积和强化学习.

Jiseong Im1, Jangsaeng Kim2,3, Jonghyun Ko1

  • 1Department of Electrical and Computer Engineering and Inter-university Semiconductor Research Center, Seoul National University, Seoul 08826, Republic of Korea.

Science advances
|November 14, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种新的3D闪存架构,用于高效的卷积操作,增强内存计算 (CIM) 系统. 新设计提高了可靠性和能源效率,用于诸如自动驾驶等应用.

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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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相关实验视频

Last Updated: Jan 11, 2026

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

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

Published on: March 2, 2015

10.8K
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

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科学领域:

  • 计算机工程 计算机工程
  • 材料科学 材料科学 材料科学
  • 人工智能的人工智能

背景情况:

  • 传统的二维内存计算 (CIM) 系统在神经网络中表现出色,但在卷积神经网络 (CNN) 中效率低下.
  • 需要更高效的CIM架构来支持复杂的AI任务.
  • 垂直堆叠的3D闪存为新的计算范式提供了潜力.

研究的目的:

  • 开发一个3D内存计算架构,以实现高效的卷积和强化学习.
  • 为了减少面积的开销,并提高卷积操作中的能源效率.
  • 为了证明3D卷积块 (3D CB) 和3D完全连接块 (3D FCB) 的协同集成.

主要方法:

  • 设计了一个新的3D卷积块 (3D CB),利用垂直堆叠的3D闪存.
  • 开发了一个兼容的3D完全连接块 (3D FCB),结构修改最小.
  • 在单个晶圆上集成3D CB和3D FCB,提供完整的系统.

主要成果:

  • 3D CB显著减少了空头面积,并提高了卷积的可靠性和能源效率.
  • 3D CB和3D FCB展示了与无协同集成的独特功能.
  • 综合系统实现了高效率的自动驾驶的精确和一致的路径规划.

结论:

  • 拟议的3D CIM架构可以实现高效的卷积和强化学习.
  • 这一进步为下一代内存计算技术铺平了道路.
  • 该系统对节能自动驾驶应用非常有希望.