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==Connections between neurons==

==Connections between neurons==

{{See also|Synapse}}

{{See also|Synapse}}<nowiki>= = 神经元之间的连接 = =</nowiki>

[[File:Leg Neural Network.jpg|thumb|Proposed organization of motor-semantic neural circuits for action language comprehension. Gray dots represent areas of language comprehension, creating a network for comprehending all language. The semantic circuit of the motor system, particularly the motor representation of the legs (yellow dots), is incorporated when leg-related words are comprehended. Adapted from Shebani et al. (2013)|链接=Special:FilePath/Leg_Neural_Network.jpg]]

 

''请见：突触''[[File:Leg Neural Network.jpg|thumb|Proposed organization of motor-semantic neural circuits for action language comprehension. Gray dots represent areas of language comprehension, creating a network for comprehending all language. The semantic circuit of the motor system, particularly the motor representation of the legs (yellow dots), is incorporated when leg-related words are comprehended. Adapted from Shebani et al. (2013)|链接=Special:FilePath/Leg_Neural_Network.jpg]]

The connections between neurons in the brain are much more complex than those of the [[artificial neuron]]s used in the [[connectionism|connectionist]] neural computing models of [[artificial neural network]]s. The basic kinds of connections between neurons are [[synapse]]s: both [[chemical synapse|chemical]] and [[electrical synapse]]s.

The connections between neurons in the brain are much more complex than those of the [[artificial neuron]]s used in the [[connectionism|connectionist]] neural computing models of [[artificial neural network]]s. The basic kinds of connections between neurons are [[synapse]]s: both [[chemical synapse|chemical]] and [[electrical synapse]]s.

Connections display temporal and spatial characteristics. Temporal characteristics refers to the continuously modified activity-dependent efficacy of synaptic transmission, called [[spike-timing-dependent plasticity]]. It has been observed in several studies that the synaptic efficacy of this transmission can undergo short-term increase (called [[neural facilitation|facilitation]]) or decrease ([[Neural facilitation#Short-term depression|depression]]) according to the activity of the presynaptic neuron. The induction of long-term changes in synaptic efficacy, by [[long-term potentiation]] (LTP) or [[long-term depression|depression]] (LTD), depends strongly on the relative timing of the onset of the [[excitatory postsynaptic potential]] and the postsynaptic action potential. LTP is induced by a series of action potentials which cause a variety of biochemical responses. Eventually, the reactions cause the expression of new receptors on the cellular membranes of the postsynaptic neurons or increase the efficacy of the existing receptors through [[phosphorylation]].

Connections display temporal and spatial characteristics. Temporal characteristics refers to the continuously modified activity-dependent efficacy of synaptic transmission, called [[spike-timing-dependent plasticity]]. It has been observed in several studies that the synaptic efficacy of this transmission can undergo short-term increase (called [[neural facilitation|facilitation]]) or decrease ([[Neural facilitation#Short-term depression|depression]]) according to the activity of the presynaptic neuron. The induction of long-term changes in synaptic efficacy, by [[long-term potentiation]] (LTP) or [[long-term depression|depression]] (LTD), depends strongly on the relative timing of the onset of the [[excitatory postsynaptic potential]] and the postsynaptic action potential. LTP is induced by a series of action potentials which cause a variety of biochemical responses. Eventually, the reactions cause the expression of new receptors on the cellular membranes of the postsynaptic neurons or increase the efficacy of the existing receptors through [[phosphorylation]].

连接表现出时间和空间特征。时间特征是指突触传递的持续修饰的活动依赖的效能，称为splke-timing-dependent plasticity<font color="#ff8000">峰时依赖的可塑性</font>。多项研究发现，根据突触前神经元的活动，这种传递的突触效能可以经历短期的增加(称为<font color="#ff8000">易化facilitation</font>)或减少(<font color="#ff8000">抑制depression</font>)。通过<font color="#ff8000">长期增强long-term potentiation(LTP)</font>或<font color="#ff8000">长期抑制long-term depression(LTD)</font>诱导突触效能的长期变化，在很大程度上取决于<font color="#ff8000">兴奋性突触后电位excitatory postsynaptic potential</font>和突触后动作电位的相对起病时间。LTP是由一系列动作电位引起的各种生化反应引起的。最终这些反应导致突触后神经元细胞膜上表达新的受体或通过<font color="#ff8000">磷酸化phosphorylation</font>增加现有受体的效能。

连接表现出时间和空间特征。时间特征是指突触传递的持续修饰的活动依赖的效能，称为<font color="#ff8000">峰时依赖的可塑性spike-timing-dependent plasticity</font>。多项研究发现，根据突触前神经元的活动，这种传递的突触效能可以经历短期的增加(称为<font color="#ff8000">易化facilitation</font>)或减少(<font color="#ff8000">抑制depression</font>)。通过<font color="#ff8000">长期增强long-term potentiation(LTP)</font>或<font color="#ff8000">长期抑制long-term depression(LTD)</font>诱导突触效能的长期变化，在很大程度上取决于<font color="#ff8000">兴奋性突触后电位excitatory postsynaptic potential</font>和突触后动作电位的相对起病时间。LTP是由一系列动作电位引起的各种生化反应引起的。最终这些反应导致突触后神经元细胞膜上表达新的受体或通过<font color="#ff8000">磷酸化phosphorylation</font>增加现有受体的效能。

Backpropagating action potentials cannot occur because after an action potential travels down a given segment of the axon, the [[Depolarizing pre-pulse#Hodgkin–Huxley model|m gate]]s on [[voltage-gated sodium channel]]s close, thus blocking any transient opening of the [[Depolarizing pre-pulse#Hodgkin–Huxley model|h gate]] from causing a change in the intracellular sodium ion (Na⁺) concentration, and preventing the generation of an action potential back towards the cell body. In some cells, however, [[neural backpropagation]] does occur through the [[dendrite|dendritic branching]] and may have important effects on synaptic plasticity and computation.

Backpropagating action potentials cannot occur because after an action potential travels down a given segment of the axon, the [[Depolarizing pre-pulse#Hodgkin–Huxley model|m gate]]s on [[voltage-gated sodium channel]]s close, thus blocking any transient opening of the [[Depolarizing pre-pulse#Hodgkin–Huxley model|h gate]] from causing a change in the intracellular sodium ion (Na⁺) concentration, and preventing the generation of an action potential back towards the cell body. In some cells, however, [[neural backpropagation]] does occur through the [[dendrite|dendritic branching]] and may have important effects on synaptic plasticity and computation.

A neuron in the brain requires a single signal to a [[neuromuscular junction]] to stimulate contraction of the postsynaptic muscle cell. In the spinal cord, however, at least 75 [[afferent nerve|afferent]] neurons are required to produce firing. This picture is further complicated by variation in time constant between neurons, as some cells can experience their [[Excitatory postsynaptic potential|EPSPs]] over a wider period of time than others.

A neuron in the brain requires a single signal to a [[neuromuscular junction]] to stimulate contraction of the postsynaptic muscle cell. In the spinal cord, however, at least 75 [[afferent nerve|afferent]] neurons are required to produce firing. This picture is further complicated by variation in time constant between neurons, as some cells can experience their [[Excitatory postsynaptic potential|EPSPs]] over a wider period of time than others.

大脑中的某一神经元需要一个单一的信号到神<font color="#ff8000">经肌肉连接neuromuscular junction</font>，刺激突触后肌肉细胞的收缩。然而，在脊髓中，产生放电需要至少75个<font color="#ff8000">传入神经元afferent nerve</font>。由于神经元之间的时间常数变化，情形变得更加复杂，因为一些细胞会比其他细胞在更长的一段时间内感受到兴奋性突触后电位（EPSPs）。

大脑中的某一神经元需要一个单一的信号到<font color="#ff8000">神经肌肉连接neuromuscular junction</font>，刺激突触后肌肉细胞的收缩。然而，在脊髓中，产生放电需要至少75个<font color="#ff8000">传入神经元afferent nerve</font>。由于神经元之间的时间常数变化，情形变得更加复杂，因为一些细胞会比其他细胞在更长的一段时间内感受到兴奋性突触后电位（EPSPs）。

While in synapses in the [[development of the human brain|developing brain]] synaptic depression has been particularly widely observed it has been speculated that it changes to facilitation in adult brains.

While in synapses in the [[development of the human brain|developing brain]] synaptic depression has been particularly widely observed it has been speculated that it changes to facilitation in adult brains.

<font color="#ff8000">脊髓spinal cord</font>中的神经回路称为<font color="#ff8000">中央模式发生器central pattern generator</font>，负责控制与节律性行为有关的运动指令。节律性行为包括行走、<font color="#ff8000">排尿urination</font>和<font color="#ff8000">射精ejaculation</font>。中枢模式发生器由不同组的<font color="#ff8000">脊髓中间神经元spinal interneuron</font>组成。<ref name="Guertin" />

<font color="#ff8000">脊髓spinal cord</font>中的神经回路称为<font color="#ff8000">中央模式发生器central pattern generator</font>，负责控制与节律性行为有关的运动指令。节律性行为包括行走、<font color="#ff8000">排尿urination</font>和<font color="#ff8000">射精ejaculation</font>。中枢模式发生器由不同组的<font color="#ff8000">脊髓中间神经元spinal interneuron</font>组成。<ref name="Guertin" />

There are four principal types of neural circuits that are responsible for a broad scope of neural functions. These circuits are a '''diverging circuit''', a '''converging circuit''', a '''reverberating circuit''', and a '''parallel after-discharge circuit'''.<ref name="Saladin">{{cite book |last1=Saladin |first1=K |title=Human anatomy |publisher=McGraw-Hill |isbn=9780071222075 |page=364 |edition=3rd}}</ref>

There are four principal types of neural circuits that are responsible for a broad scope of neural functions. These circuits are a '''diverging circuit''', a '''converging circuit''', a '''reverberating circuit''', and a '''parallel after-discharge circuit'''.<ref name="Saladin">{{cite book |last1=Saladin |first1=K |title=Human anatomy |publisher=McGraw-Hill |isbn=9780071222075 |page=364 |edition=3rd}}</ref>

{{See also|Neuropsychology|Cognitive neuropsychology}}

{{See also|Neuropsychology|Cognitive neuropsychology}}

研究方法

研究方法

Different [[neuroimaging]] techniques have been developed to investigate the activity of neural circuits and networks. The use of "brain scanners" or functional neuroimaging to investigate the structure or function of the brain is common, either as simply a way of better assessing brain injury with high-resolution pictures, or by examining the relative activations of different brain areas. Such technologies may include [[functional magnetic resonance imaging]] (fMRI), [[brain positron emission tomography]] (brain PET), and [[computed axial tomography]] (CAT) scans. [[Functional neuroimaging]] uses specific brain imaging technologies to take scans from the brain, usually when a person is doing a particular task, in an attempt to understand how the activation of particular brain areas is related to the task. In functional neuroimaging, especially fMRI, which measures [[hemodynamic response|hemodynamic activity]] (using [[Blood-oxygen-level dependent imaging|BOLD-contrast imaging]]) which is closely linked to neural activity, PET, and [[electroencephalography]] (EEG) is used.

Different [[neuroimaging]] techniques have been developed to investigate the activity of neural circuits and networks. The use of "brain scanners" or functional neuroimaging to investigate the structure or function of the brain is common, either as simply a way of better assessing brain injury with high-resolution pictures, or by examining the relative activations of different brain areas. Such technologies may include [[functional magnetic resonance imaging]] (fMRI), [[brain positron emission tomography]] (brain PET), and [[computed axial tomography]] (CAT) scans. [[Functional neuroimaging]] uses specific brain imaging technologies to take scans from the brain, usually when a person is doing a particular task, in an attempt to understand how the activation of particular brain areas is related to the task. In functional neuroimaging, especially fMRI, which measures [[hemodynamic response|hemodynamic activity]] (using [[Blood-oxygen-level dependent imaging|BOLD-contrast imaging]]) which is closely linked to neural activity, PET, and [[electroencephalography]] (EEG) is used.

In 1972, Barlow announced the ''single neuron revolution'': "our perceptions are caused by the activity of a rather small number of neurons selected from a very large population of predominantly silent cells."<ref name="Barlow1972">{{cite journal |last1=Barlow|first1=HB|title=Single units and sensation: a neuron doctrine for perceptual psychology? |journal=Perception|date=December 1, 1972|volume=1|issue=4 |pages=371-394|doi=10.1068/p010371|pmid=4377168}}</ref> This approach was stimulated by the idea of [[grandmother cell]] put forward two years earlier. Barlow formulated "five dogmas" of neuron doctrine.  Recent studies of '[[grandmother cell]]' and sparse coding phenomena develop and modify these ideas.<ref name="QuianQuiroga2005">{{cite journal |last1=Quian Quiroga|first1=R|last2=Reddy|first2=L|last3=Kreiman|first3=G|last4=Koch|first4=C|last5=Fried|first5=I|title=Invariant visual representation by single neurons in the human brain|journal=Nature|date=Jun 23, 2005|volume=435|issue=7045|pages=1102-1107|doi=10.1038/nature03687|doi-access=free|pmid=15973409}}</ref> The single cell experiments  used intracranial electrodes in the medial temporal lobe (the hippocampus and surrounding cortex). Modern development of [[concentration of measure]] theory (stochastic separation theorems) with applications to [[artificial neural networks]] give mathematical background to unexpected effectiveness of small neural ensembles in high-dimensional brain.<ref name=":2">{{cite journal |last1= Gorban|first1= Alexander N.|last2= Makarov|first2= Valeri A.|last3= Tyukin |first3= Ivan Y.|date= July 2019|title= The unreasonable effectiveness of small neural ensembles in high-dimensional brain|journal= Physics of Life Reviews|volume= 29 |pages= 55–88|doi= 10.1016/j.plrev.2018.09.005|doi-access=free|pmid= 30366739|arxiv= 1809.07656}}</ref>

In 1972, Barlow announced the ''single neuron revolution'': "our perceptions are caused by the activity of a rather small number of neurons selected from a very large population of predominantly silent cells."<ref name="Barlow1972">{{cite journal |last1=Barlow|first1=HB|title=Single units and sensation: a neuron doctrine for perceptual psychology? |journal=Perception|date=December 1, 1972|volume=1|issue=4 |pages=371-394|doi=10.1068/p010371|pmid=4377168}}</ref> This approach was stimulated by the idea of [[grandmother cell]] put forward two years earlier. Barlow formulated "five dogmas" of neuron doctrine.  Recent studies of '[[grandmother cell]]' and sparse coding phenomena develop and modify these ideas.<ref name="QuianQuiroga2005">{{cite journal |last1=Quian Quiroga|first1=R|last2=Reddy|first2=L|last3=Kreiman|first3=G|last4=Koch|first4=C|last5=Fried|first5=I|title=Invariant visual representation by single neurons in the human brain|journal=Nature|date=Jun 23, 2005|volume=435|issue=7045|pages=1102-1107|doi=10.1038/nature03687|doi-access=free|pmid=15973409}}</ref> The single cell experiments  used intracranial electrodes in the medial temporal lobe (the hippocampus and surrounding cortex). Modern development of [[concentration of measure]] theory (stochastic separation theorems) with applications to [[artificial neural networks]] give mathematical background to unexpected effectiveness of small neural ensembles in high-dimensional brain.<ref name=":2">{{cite journal |last1= Gorban|first1= Alexander N.|last2= Makarov|first2= Valeri A.|last3= Tyukin |first3= Ivan Y.|date= July 2019|title= The unreasonable effectiveness of small neural ensembles in high-dimensional brain|journal= Physics of Life Reviews|volume= 29 |pages= 55–88|doi= 10.1016/j.plrev.2018.09.005|doi-access=free|pmid= 30366739|arxiv= 1809.07656}}</ref>

在<font color="#ff8000">神经生物学neurobiology</font>中，连接主义方法和单细胞方法之间的现代平衡已经通过长时间的讨论实现。1972年，巴洛宣布了“单一神经元革命”：“我们的感知是由从大量沉默细胞中选择的少量神经元的活动引起的。‘’<ref name="Barlow1972" /> 这种方法是受到两年前提出的<font color="#ff8000">祖母细胞grandmother cell</font>的启发。巴洛提出了神经元学说的“五大信条”。最近对“<font color="#ff8000">祖母细胞grandmother cell</font>”和稀疏编码现象的研究进一步完善了这些观点。<ref name="QuianQuiroga2005" />单细胞实验使用位于内侧颞叶(海马和周围皮层)的颅内电极。<font color="#ff8000">度量集中concentration of measure</font>理论(随机分离定理)的现代发展及其在人工神经网络artificial neural networks中的应用为高维大脑中小型神经系统集成的意想不到的有效性提供了数学背景。<ref name=":2" />

在<font color="#ff8000">神经生物学neurobiology</font>中，连接主义方法和单细胞方法之间的现代平衡已经通过长时间的讨论实现。1972年，巴洛宣布了“单一神经元革命”：“我们的感知是由从大量沉默细胞中选择的少量神经元的活动引起的。‘’<ref name="Barlow1972" /> 这种方法是受到两年前提出的<font color="#ff8000">祖母细胞grandmother cell</font>的启发。巴洛提出了神经元学说的“五大信条”。最近对“<font color="#ff8000">祖母细胞grandmother cell</font>”和稀疏编码现象的研究进一步完善了这些观点。<ref name="QuianQuiroga2005" />单细胞实验使用位于内侧颞叶(海马和周围皮层)的颅内电极。<font color="#ff8000">度量集中concentration of measure</font>理论(随机分离定理)的现代发展及其在<font color="#ff8000">人工神经网络artificial neural networks</font>中的应用为高维大脑中小型神经系统集成的意想不到的有效性提供了数学背景。<ref name=":2" />

==Clinical significance==

==Clinical significance==

在某些情况下，当<font color="#ff8000">基底神经节basal ganglia</font>受累时，神经环路会变成病理性的，继而引起问题，如<font color="#ff8000">帕金森病Parkinson's disease</font>。<ref name="French" /> <font color="#ff8000">帕佩兹回路Papez circuit</font>发生问题也会导致包括帕金森氏症在内的一系列<font color="#ff8000">神经退行性疾病neurodegenerative disorders</font>。

在某些情况下，当<font color="#ff8000">基底神经节basal ganglia</font>受累时，神经环路会变成病理性的，继而引起问题，如<font color="#ff8000">帕金森病Parkinson's disease</font>。<ref name="French" /> <font color="#ff8000">帕佩兹回路Papez circuit</font>发生问题也会导致包括帕金森氏症在内的一系列<font color="#ff8000">神经退行性疾病neurodegenerative disorders</font>。

==See also ==

==See also==

*[[Feedback]]

*[[Feedback]]

*[[List of regions in the human brain]]

*[[List of regions in the human brain]]

*[[Systems neuroscience]]

*[[Systems neuroscience]]

*Feedback

* 反馈

*List of regions in the human brain

* 人脑区域分布列表

*Network science

* 神经编码

*Neural coding

* 神经工程

*Neural engineering

* 神经震荡

*Neural oscillation

* 脉冲耦合神经网络

*Pulse-coupled networks

* 系统神经科学

 

==References==

==References==

=<nowiki>= 进一步阅读 = =</nowiki>=  

=<nowiki>= 进一步阅读 = =</nowiki>=  

*内在可塑性罗伯特 · h · 卡德莫尔，尼拉杰 · s · 德赛奖学金百科全书3(2) : 1363. doi: 10.4249/Scholarpedia. 1363

* 内在可塑性 罗伯特 · h · 卡德莫尔，尼拉杰 · s · 德赛奖学金百科全书3(2) : 1363. doi: 10.4249/Scholarpedia. 1363

==External links==

==External links==

*[http://www.gfai.de/~heinz/publications/NI/index.htm Delaying Pulse Networks (Wave Interference Networks)]

*[http://www.gfai.de/~heinz/publications/NI/index.htm Delaying Pulse Networks (Wave Interference Networks)]

* Comparison of Neural Networks in the Brain and Artificial Neural Networks

*Comparison of Neural Networks in the Brain and Artificial Neural Networks

*Lecture notes at MIT OpenCourseWare

*Lecture notes at MIT OpenCourseWare

*Computation in the Brain

*Computation in the Brain

*WormWeb.org: Interactive Visualization of the C. elegans Neural Network - C. elegans, a nematode with 302 neurons, is the only organism for whom the entire neural network has been uncovered.  Use this site to browse through the network and to search for paths between any 2 neurons.

*WormWeb.org: Interactive Visualization of the C. elegans Neural Network - C. elegans, a nematode with 302 neurons, is the only organism for whom the entire neural network has been uncovered.  Use this site to browse through the network and to search for paths between any 2 neurons.

*Introduction to Neurons and Neuronal Networks, Neuroscience Online (electronic neuroscience textbook)

*Introduction to Neurons and Neuronal Networks, Neuroscience Online (electronic neuroscience textbook)

*Delaying Pulse Networks (Wave Interference Networks)

* Delaying Pulse Networks (Wave Interference Networks)

生物神经网络工具箱-一个免费的 Matlab 工具箱，用于模拟几种不同类型神经元的网络  

生物神经网络工具箱-一个免费的 Matlab 工具箱，用于模拟几种不同类型神经元的网络