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{{short description|Network or circuit of neurons}}

{{short description|Network or circuit of neurons}}

{{About||neural networks in computers|artificial neural network|projections from one region of the nervous system to another|neural pathway}}关于 计算机中使用的神经网络，请见人工神经网络。关于神经系统中一处神经元与另一处神经元之间的连接通路，请见神经通路。[[File:Blausen 0657 MultipolarNeuron.png|thumb|300px|Anatomy of a [[multipolar neuron]] |链接=Special:FilePath/Blausen_0657_MultipolarNeuron.png]]

{{About||neural networks in computers|artificial neural network|projections from one region of the nervous system to another|neural pathway}}关于计算机中使用的神经网络，请见<font color="#ff8000">人工神经网络artificial neural network</font>。关于神经系统中一处神经元与另一处神经元之间的连接通路，请见<font color="#ff8000">神经通路neural pathway</font>。[[File:Blausen 0657 MultipolarNeuron.png|thumb|300px|Anatomy of a [[multipolar neuron]] |链接=Special:FilePath/Blausen_0657_MultipolarNeuron.png]]

A '''neural circuit''' is a population of [[neuron]]s interconnected by [[synapse]]s to carry out a specific function when activated.<ref name="Neuro">{{cite book |last1=Purves |first1=Dale |title=Neuroscience |date=2011 |publisher=Sinauer |location=Sunderland, Mass. |isbn=9780878936953 |page=507 |edition= 5th}}</ref> Neural circuits interconnect to one another to form [[large scale brain networks]].<ref name="CEI">{{cite web |title=Neural Circuits {{!}} Centre of Excellence for Integrative Brain Function |url=https://www.brainfunction.edu.au/research/research-themes/neural-circuits/ |website=Centre of Excellence for Integrative Brain Function |access-date=4 June 2018 |language=en-AU |date=13 June 2016}}</ref> Biological [[neural network]]s have inspired the design of [[artificial neural network]]s, but artificial neural networks are usually not strict copies of their biological counterparts.

A '''neural circuit''' is a population of [[neuron]]s interconnected by [[synapse]]s to carry out a specific function when activated.<ref name="Neuro">{{cite book |last1=Purves |first1=Dale |title=Neuroscience |date=2011 |publisher=Sinauer |location=Sunderland, Mass. |isbn=9780878936953 |page=507 |edition= 5th}}</ref> Neural circuits interconnect to one another to form [[large scale brain networks]].<ref name="CEI">{{cite web |title=Neural Circuits {{!}} Centre of Excellence for Integrative Brain Function |url=https://www.brainfunction.edu.au/research/research-themes/neural-circuits/ |website=Centre of Excellence for Integrative Brain Function |access-date=4 June 2018 |language=en-AU |date=13 June 2016}}</ref> Biological [[neural network]]s have inspired the design of [[artificial neural network]]s, but artificial neural networks are usually not strict copies of their biological counterparts.

A neural circuit is a population of neurons interconnected by synapses to carry out a specific function when activated. Neural circuits interconnect to one another to form large scale brain networks. Biological neural networks have inspired the design of artificial neural networks, but artificial neural networks are usually not strict copies of their biological counterparts.

<font color="#ff8000">神经回路neural circuit</font>由一群<font color="#ff8000">神经元neuron</font>构成，通过突触synapse<font color="#ff8000"></font>相互连接，被激活时，就可以执行某种特定功能。<ref name="Neuro" /> 神经回路彼此再连接，形成大尺度脑网络large scale brain networks<font color="#ff8000"></font>。<ref name="CEI" /> 生物神经网络Biological neural network<font color="#ff8000"></font>启发了人工神经网络artificial neural network<font color="#ff8000"></font>的设计，但人工神经网络通常不是机械地复制生物神经网络。

 

 

==Early study==

==Early study==

= = 早期研究 = = 对神经网络的早期研究见于赫伯特 · 斯宾塞的《心理学原理》第三版(1872)、西奥多 · 梅纳特的《精神病学》(1884)、威廉 · 詹姆斯的《心理学原理》(1890)和西格蒙德 · 弗洛伊德的《科学心理学计划》(1895)。1949年，赫布在其理论（即赫布理论）中提出了神经元学习的第一定律。赫布理论认为，配对中突触前神经元和突触后神经元的活动可以充分改变突触连接的动态特性，即要么促进，要么抑制信号传递。1959年，神经科学家，沃伦·麦卡洛克和 Walter Pitts 发表了关于神经网络处理的第一部著作。他们从理论上证明了人工神经元网络可以实现逻辑、算术和符号功能。生物神经元的简化模型由此建立起来，现在通常被称为感知器或人工神经元。这些简单的模型解释了神经加成作用(即突触后膜上的电位将在细胞体中加成)。后来的模型也提供了兴奋性和抑制性突触传递。

= = 早期研究 = = 对神经网络的早期研究见于赫伯特 · 斯宾塞的《心理学原理》第三版(1872)、西奥多 · 梅纳特的《精神病学》(1884)、威廉 · 詹姆斯的《心理学原理》(1890)和西格蒙德 · 弗洛伊德的《科学心理学计划》(1895)。1949年，赫布在其理论（即赫布理论）中提出了神经元学习的第一定律。赫布理论认为，配对中突触前神经元和突触后神经元的活动可以充分改变突触连接的动态特性，即要么促进，要么抑制信号传递。1959年，神经科学家，沃伦·麦卡洛克和 Walter Pitts 发表了关于神经网络处理的第一部著作。他们从理论上证明了人工神经元网络可以实现逻辑、算术和符号功能。生物神经元的简化模型由此建立起来，现在通常被称为感知器或人工神经元。这些简单的模型解释了神经加成作用(即突触后膜上的电位将在细胞体中加成)。后来的模型也提供了兴奋性和抑制性突触传递。

==Connections between neurons ==

==Connections between neurons==

{{See also|Synapse}}

{{See also|Synapse}}

[[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]]

[[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]]

虽然在发育状态的脑突触中，突触抑制已经被广泛观察到，但据推测，它在成人大脑中改变为易化。

虽然在发育状态的脑突触中，突触抑制已经被广泛观察到，但据推测，它在成人大脑中改变为易化。

== Circuitry ==

==Circuitry==

[[File:Model of Cerebellar Perceptron.jpg|thumb|Model of a neural circuit in the [[cerebellum]]|链接=Special:FilePath/Model_of_Cerebellar_Perceptron.jpg]]

[[File:Model of Cerebellar Perceptron.jpg|thumb|Model of a neural circuit in the [[cerebellum]]|链接=Special:FilePath/Model_of_Cerebellar_Perceptron.jpg]]

An example of a neural circuit is the [[trisynaptic circuit]] in the [[hippocampus]]. Another is the [[Papez circuit]] linking the [[hypothalamus]] to the [[limbic lobe]]. There are several neural circuits in the [[cortico-basal ganglia-thalamo-cortical loop]]. These circuits carry information between the cortex, [[basal ganglia]], thalamus, and back to the cortex. The largest structure within the basal ganglia, the [[striatum]], is seen as having its own internal microcircuitry.<ref name="Stocco">{{cite journal |last1=Stocco |first1=Andrea |last2=Lebiere |first2=Christian |last3=Anderson |first3=John R. |title=Conditional Routing of Information to the Cortex: A Model of the Basal Ganglia's Role in Cognitive Coordination |journal=Psychological Review |volume=117 |issue=2 |pages=541–74 |year=2010 |pmid=20438237 |doi=10.1037/a0019077 |pmc=3064519}}</ref>

An example of a neural circuit is the [[trisynaptic circuit]] in the [[hippocampus]]. Another is the [[Papez circuit]] linking the [[hypothalamus]] to the [[limbic lobe]]. There are several neural circuits in the [[cortico-basal ganglia-thalamo-cortical loop]]. These circuits carry information between the cortex, [[basal ganglia]], thalamus, and back to the cortex. The largest structure within the basal ganglia, the [[striatum]], is seen as having its own internal microcircuitry.<ref name="Stocco">{{cite journal |last1=Stocco |first1=Andrea |last2=Lebiere |first2=Christian |last3=Anderson |first3=John R. |title=Conditional Routing of Information to the Cortex: A Model of the Basal Ganglia's Role in Cognitive Coordination |journal=Psychological Review |volume=117 |issue=2 |pages=541–74 |year=2010 |pmid=20438237 |doi=10.1037/a0019077 |pmc=3064519}}</ref>

神经编码神经工程神经震荡脉冲耦合神经网络系统神经科学

神经编码神经工程神经震荡脉冲耦合神经网络系统神经科学

==References==

== References==

{{Reflist}}

{{Reflist}}

*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==

*[https://web.archive.org/web/20040807104201/http://www.his.sunderland.ac.uk/ps/worksh2/denham.pdf Comparison of Neural Networks in the Brain and Artificial Neural Networks]

*[https://web.archive.org/web/20040807104201/http://www.his.sunderland.ac.uk/ps/worksh2/denham.pdf Comparison of Neural Networks in the Brain and Artificial Neural Networks]

*[https://web.archive.org/web/20051024152350/http://ocw.mit.edu/OcwWeb/Brain-and-Cognitive-Sciences/9-95-AResearch-Topics-in-NeuroscienceJanuary--IAP-2003/LectureNotes/ Lecture notes at MIT OpenCourseWare]

*[https://web.archive.org/web/20051024152350/http://ocw.mit.edu/OcwWeb/Brain-and-Cognitive-Sciences/9-95-AResearch-Topics-in-NeuroscienceJanuary--IAP-2003/LectureNotes/ Lecture notes at MIT OpenCourseWare]

*Computation in the Brain

*Computation in the Brain

*Biological Neural Network Toolbox - A free Matlab toolbox for simulating networks of several different types of neurons

*Biological Neural Network Toolbox - A free Matlab toolbox for simulating networks of several different types of 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.

*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