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相关概念视频

The Synapse02:47

The Synapse

125.3K
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.
125.3K
Synaptic Signaling01:09

Synaptic Signaling

5.6K
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...
5.6K
Neuronal Communication01:28

Neuronal Communication

966
Neurons, the fundamental units of the brain and nervous system, communicate through complex electrochemical signals that underpin all cognitive and bodily functions. This communication is primarily facilitated by a process involving the generation and propagation of an action potential along the axon of the neuron. When the internal electrical charge of a neuron surpasses a certain threshold, an action potential is triggered. This rapid change in voltage travels swiftly along the axon to the...
966
Chemical Synapses01:26

Chemical Synapses

8.9K
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...
8.9K
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
The Role of Ion Channels in Neuronal Computation01:19

The Role of Ion Channels in Neuronal Computation

3.2K
A postsynaptic neuron usually receives numerous impulses from several other presynaptic neurons. The axon hillock of the postsynaptic neuron integrates all these signals and determines the likelihood of firing an action potential.
Sometimes a single EPSP is strong enough to induce an action potential in the postsynaptic neuron. However, multiple presynaptic inputs must often create EPSPs around the same time for the postsynaptic neuron to be sufficiently depolarized to fire an action potential....
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相关实验视频

Updated: Jul 10, 2025

3D Modeling of Dendritic Spines with Synaptic Plasticity
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3D Modeling of Dendritic Spines with Synaptic Plasticity

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远程行动:跨树突异突突触修饰的理论机制.

Sahil Moza1

  • 1Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138 sahilmoza@fas.harvard.edu.

eNeuro
|November 20, 2023
PubMed
概括

神经元树突中的不对称电压衰减允许不同的学习路径. 这种机制使等级性的异突突触可塑性成为可能,影响神经元如何处理和存储信息.

科学领域:

  • 神经科学是一个神经科学.
  • 计算神经科学是一种神经科学.
  • 突触性可塑性 突触性可塑性

背景情况:

  • 树突对神经元计算至关重要,并集成突触输入.
  • 突触可塑性,即突触随时间增强或减弱的能力,是学习和记忆的基础.
  • 异突突触可塑性涉及非直接刺激的突触的变化.

研究的目的:

  • 为了研究在树突树枝中不对称电压减弱的作用.
  • 探索这种现象是如何支持层次性的异突突触可塑性的.
  • 了解神经网络的计算影响.

主要方法:

  • 神经元树突结构的计算建模.
  • 模拟突触输入模式和由此产生的电压动态.
  • 基于模拟的树突活动的可塑性诱导规则的分析.

主要成果:

  • 观察到不对称的电压减弱会在树突中产生不同的电压域.
  • 这些域对各种突触的突触可塑性诱导有不同的影响.
  • 这些发现证明了对异突突触可塑性进行层次控制的机制.

结论:

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  • 树突电压减弱为实现等级计算提供了基板.
  • 这种机制允许神经元表现出复杂的,依赖输入的可塑性.
  • 这项研究提供了关于神经回路中学习和记忆的生物物理基础的见解.