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相关概念视频

Long-term Potentiation01:25

Long-term Potentiation

2.8K
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...
2.8K
Observational Learning01:12

Observational Learning

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Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
231
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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Associative Learning01:27

Associative Learning

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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...
462
Long-Term Memory01:18

Long-Term Memory

222
Long-term memory is a relatively permanent type of memory, capable of storing vast amounts of information over extended periods. Its storage capacity is generally considered unlimited.
Long-term memory can be categorized into two primary types: explicit and implicit memory. Explicit memory, also known as declarative memory, involves the conscious recollection of information that we deliberately try to remember, recall, and articulate. This type of memory encompasses specific facts, events, and...
222
Higher Mental Functions of Brain: Learning and Memory01:26

Higher Mental Functions of Brain: Learning and Memory

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Memory is one of the most vital higher mental functions of the brain. Memory is closely related to learning because it enables us to retain information and experiences from our past to use them in our present life. It also helps us to remember facts, events, and skills, such as riding a bike or swimming. There are two types of memory — declarative memory, which involves memorizing facts or events, and procedural memory, which enables us to remember how to do something like writing or...
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相关实验视频

Updated: Jul 27, 2025

Investigating Long-term Synaptic Plasticity in Interlamellar Hippocampus CA1 by Electrophysiological Field Recording
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学习皮层层次结构与时间赫比安更新.

Pau Vilimelis Aceituno1,2, Matilde Tristany Farinha1, Reinhard Loidl1

  • 1Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland.

Frontiers in computational neuroscience
|June 9, 2023
PubMed
概括

研究人员提出了一种生物可信的学习机制,用于人工神经网络 (ANN),使用微分赫比安更新. 这种方法可以在深度学习框架中实现层次学习,模仿哺乳动物的智力.

关键词:
反向传播反向传播.皮质层次的层次结构.信用指派 信用指派 信用指派 信用指派深度学习是一种深度学习.不同的希伯语学习 希伯语学习尖的时间依赖的可塑性.突触性可塑性 突触性可塑性目标传播的传播目标.

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Simultaneous Long-term Recordings at Two Neuronal Processing Stages in Behaving Honeybees
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Simultaneous Long-term Recordings at Two Neuronal Processing Stages in Behaving Honeybees

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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: Jul 27, 2025

Investigating Long-term Synaptic Plasticity in Interlamellar Hippocampus CA1 by Electrophysiological Field Recording
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Investigating Long-term Synaptic Plasticity in Interlamellar Hippocampus CA1 by Electrophysiological Field Recording

Published on: August 11, 2019

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Simultaneous Long-term Recordings at Two Neuronal Processing Stages in Behaving Honeybees
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Simultaneous Long-term Recordings at Two Neuronal Processing Stages in Behaving Honeybees

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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

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科学领域:

  • 计算神经科学是一种神经科学.
  • 人工智能的人工智能
  • 机器学习 机器学习

背景情况:

  • 哺乳动物的智能依赖于层次感官处理,从低级特征到高级对象识别.
  • 人工神经网络 (ANN) 呈现出类似的等级结构,但通常使用生物学上不合理的训练算法,如反向传播.
  • 在生物学上存在可信的替代方案,但用于误差计算信号的神经元比较的明确机制仍然难以捉摸.

研究的目的:

  • 为深度学习中神经元误差计算和权重更新提出一个生物学上可信的机制.
  • 通过比较神经元分隔活动来证明如何计算局部错误信号.
  • 证明这种机制支持监督层次学习.

主要方法:

  • 引入了一种新的学习规则,将顶点反对 postsynaptic 发射速率的影响与差异 Hebbian 更新相结合.
  • 制定并证明了权重更新对最小化推理延迟和自上而下的反的等价性.
  • 在基于反的深度学习框架中验证了差异的Hebbian更新,例如预测编码和平衡传播.

主要成果:

  • 证明,拟议的微分赫比安更新规则最大限度地减少了推断延迟和上下反要求.
  • 表明这种学习机制在其他生物学上可信的深度学习框架内是有效的.
  • 在ANN中建立了时间Hebbian学习和监督层次学习之间的联系.

结论:

  • 这项工作消除了对生物可信的深度学习模型的关键要求.
  • 提出了一种新的学习机制,将时间赫比亚学习规则与监督等级学习相结合.
  • 为生物学神经网络如何实现复杂的学习和智能提供了潜在的解释.