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	<title>神经回路 - 版本历史</title>
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	<updated>2026-11-03T14:03:32Z</updated>
	<subtitle>本wiki的该页面的版本历史</subtitle>
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		<title>2022年6月26日 (日) 11:05 薄荷</title>
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		<updated>2022-06-26T11:05:55Z</updated>

		<summary type="html">&lt;p&gt;&lt;/p&gt;
&lt;a href=&quot;https://wiki.swarma.org/index.php?title=%E7%A5%9E%E7%BB%8F%E5%9B%9E%E8%B7%AF&amp;amp;diff=32570&amp;amp;oldid=30758&quot;&gt;显示更改&lt;/a&gt;</summary>
		<author><name>薄荷</name></author>
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		<title>2022年4月29日 (五) 00:14 Glh20100487</title>
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		<updated>2022-04-29T00:14:48Z</updated>

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&lt;table class=&quot;diff diff-contentalign-left diff-editfont-monospace&quot; data-mw=&quot;interface&quot;&gt;
				&lt;col class=&quot;diff-marker&quot; /&gt;
				&lt;col class=&quot;diff-content&quot; /&gt;
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				&lt;col class=&quot;diff-content&quot; /&gt;
				&lt;tr class=&quot;diff-title&quot; lang=&quot;zh-Hans-CN&quot;&gt;
				&lt;td colspan=&quot;2&quot; style=&quot;background-color: #fff; color: #202122; text-align: center;&quot;&gt;←上一版本&lt;/td&gt;
				&lt;td colspan=&quot;2&quot; style=&quot;background-color: #fff; color: #202122; text-align: center;&quot;&gt;2022年4月29日 (五) 00:14的版本&lt;/td&gt;
				&lt;/tr&gt;&lt;tr&gt;&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot; id=&quot;mw-diff-left-l7&quot; &gt;第7行：&lt;/td&gt;
&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot;&gt;第7行：&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;神经回路neural circuit&amp;lt;/font&amp;gt;由一群&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;神经元neuron&amp;lt;/font&amp;gt;构成，通过&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;突触synapse&amp;lt;/font&amp;gt;相互连接，被激活时，就可以执行某种特定功能。&amp;lt;ref name=&amp;quot;Neuro&amp;quot; /&amp;gt; 神经回路彼此再连接，形成&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;大尺度脑网络large scale brain networks&amp;lt;/font&amp;gt;。&amp;lt;ref name=&amp;quot;CEI&amp;quot; /&amp;gt; &amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;生物神经网络Biological neural network&amp;lt;/font&amp;gt;启发了&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;人工神经网络artificial neural network&amp;lt;/font&amp;gt;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。&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;神经回路neural circuit&amp;lt;/font&amp;gt;由一群&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;神经元neuron&amp;lt;/font&amp;gt;构成，通过&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;突触synapse&amp;lt;/font&amp;gt;相互连接，被激活时，就可以执行某种特定功能。&amp;lt;ref name=&amp;quot;Neuro&amp;quot; /&amp;gt; 神经回路彼此再连接，形成&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;大尺度脑网络large scale brain networks&amp;lt;/font&amp;gt;。&amp;lt;ref name=&amp;quot;CEI&amp;quot; /&amp;gt; &amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;生物神经网络Biological neural network&amp;lt;/font&amp;gt;启发了&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;人工神经网络artificial neural network&amp;lt;/font&amp;gt;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。&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;文件：Blausen 0657 Multipolar Neuron &lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;Anatomy of a multipolar neuron &lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;多极神经元的解剖学&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;==Early study==&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;==Early study==&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot; id=&quot;mw-diff-left-l13&quot; &gt;第13行：&lt;/td&gt;
&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot;&gt;第19行：&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;= = 早期研究 = = 对神经网络的早期研究见于&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;赫伯特 · 斯宾塞Herbert Spencer&amp;lt;/font&amp;gt;的《心理学原理》第三版(1872)、&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;西奥多 · 梅纳特Theodor Meynert&amp;lt;/font&amp;gt;的《精神病学》(1884)、&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;威廉 · 詹姆斯William James&amp;lt;/font&amp;gt;的《心理学原理》(1890)和&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;西格蒙德 · 弗洛伊德Sigmund Freud&amp;lt;/font&amp;gt;的《科学心理学计划》(1895)。&amp;lt;ref name=&amp;quot;:0&amp;quot; /&amp;gt; 1949年，&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;赫布Hebb&amp;lt;/font&amp;gt;在其理论（即&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;赫布理论Hebbian theory&amp;lt;/font&amp;gt;）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&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;信号传递signal transmission&amp;lt;/font&amp;gt;。1959年，&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;神经科学家neuroscientist&amp;lt;/font&amp;gt;, &amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;沃伦·麦卡洛克Warren Sturgis&amp;lt;/font&amp;gt;和 &amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;沃尔特·皮茨Walter Pitts&amp;lt;/font&amp;gt; 发表了关于神经网络处理的第一部著作。&amp;lt;ref name=&amp;quot;:1&amp;quot; /&amp;gt; 他们从理论上证明了人工神经元网络可以实现&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;逻辑logical&amp;lt;/font&amp;gt;、&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;算术arithmetic&amp;lt;/font&amp;gt;和&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;符号功能symbolic&amp;lt;/font&amp;gt;。&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;生物神经元的简化模型models of biological neurons&amp;lt;/font&amp;gt;由此建立起来，现在通常被称为&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;感知器perceptrons&amp;lt;/font&amp;gt;或&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;人工神经元artificial neurons&amp;lt;/font&amp;gt;。这些简单的模型解释了&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;神经加成作用neural summation&amp;lt;/font&amp;gt;(即突触后膜上的电位将在&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;细胞体cell body&amp;lt;/font&amp;gt;中加成)。后来的模型也提供了兴奋性和抑制性突触传递。&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;= = 早期研究 = = 对神经网络的早期研究见于&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;赫伯特 · 斯宾塞Herbert Spencer&amp;lt;/font&amp;gt;的《心理学原理》第三版(1872)、&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;西奥多 · 梅纳特Theodor Meynert&amp;lt;/font&amp;gt;的《精神病学》(1884)、&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;威廉 · 詹姆斯William James&amp;lt;/font&amp;gt;的《心理学原理》(1890)和&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;西格蒙德 · 弗洛伊德Sigmund Freud&amp;lt;/font&amp;gt;的《科学心理学计划》(1895)。&amp;lt;ref name=&amp;quot;:0&amp;quot; /&amp;gt; 1949年，&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;赫布Hebb&amp;lt;/font&amp;gt;在其理论（即&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;赫布理论Hebbian theory&amp;lt;/font&amp;gt;）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&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;信号传递signal transmission&amp;lt;/font&amp;gt;。1959年，&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;神经科学家neuroscientist&amp;lt;/font&amp;gt;, &amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;沃伦·麦卡洛克Warren Sturgis&amp;lt;/font&amp;gt;和 &amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;沃尔特·皮茨Walter Pitts&amp;lt;/font&amp;gt; 发表了关于神经网络处理的第一部著作。&amp;lt;ref name=&amp;quot;:1&amp;quot; /&amp;gt; 他们从理论上证明了人工神经元网络可以实现&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;逻辑logical&amp;lt;/font&amp;gt;、&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;算术arithmetic&amp;lt;/font&amp;gt;和&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;符号功能symbolic&amp;lt;/font&amp;gt;。&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;生物神经元的简化模型models of biological neurons&amp;lt;/font&amp;gt;由此建立起来，现在通常被称为&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;感知器perceptrons&amp;lt;/font&amp;gt;或&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;人工神经元artificial neurons&amp;lt;/font&amp;gt;。这些简单的模型解释了&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;神经加成作用neural summation&amp;lt;/font&amp;gt;(即突触后膜上的电位将在&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;细胞体cell body&amp;lt;/font&amp;gt;中加成)。后来的模型也提供了兴奋性和抑制性突触传递。&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;文件：Cajal actxinter&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;From &amp;quot;Texture of the [[Nervous System]] of Man and the [[Vertebrates]]&amp;quot; by [[Santiago Ramón y Cajal]]. The figure illustrates the diversity of neuronal morphologies in the [[auditory cortex]].&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;摘自Santiago Ramón y Cajal的《人类和脊椎动物的神经系统结构》。这幅图说明了听觉皮层神经元形态的多样性。&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;==Connections between neurons==&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;==Connections between neurons==&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot; id=&quot;mw-diff-left-l22&quot; &gt;第22行：&lt;/td&gt;
&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot;&gt;第34行：&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;大脑神经元之间的连接比&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;人工神经元artificial neuron&amp;lt;/font&amp;gt;之间的连接要复杂得多，人工神经元常用于人工&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;神经网络中的连接计算模型connectionist neural computing model&amp;lt;/font&amp;gt;。大脑神经元之间的基本连接是&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;突触synapse&amp;lt;/font&amp;gt;,包括：&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;化学突触chemical synapse&amp;lt;/font&amp;gt;和&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;电突触electrical synapse&amp;lt;/font&amp;gt;。&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;大脑神经元之间的连接比&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;人工神经元artificial neuron&amp;lt;/font&amp;gt;之间的连接要复杂得多，人工神经元常用于人工&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;神经网络中的连接计算模型connectionist neural computing model&amp;lt;/font&amp;gt;。大脑神经元之间的基本连接是&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;突触synapse&amp;lt;/font&amp;gt;,包括：&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;化学突触chemical synapse&amp;lt;/font&amp;gt;和&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;电突触electrical synapse&amp;lt;/font&amp;gt;。&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;文件:Leg Neural Network&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;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)&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;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)&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot; id=&quot;mw-diff-left-l62&quot; &gt;第62行：&lt;/td&gt;
&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot;&gt;第76行：&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;神经回路的典型例子是&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;海马体hippocampus&amp;lt;/font&amp;gt;中的&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;三突触回路trisynaptic circuit&amp;lt;/font&amp;gt;。另一个是连接&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;下丘脑hypothalamus&amp;lt;/font&amp;gt;和&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;边缘叶limbic lobe&amp;lt;/font&amp;gt;的&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;帕佩兹回路Papez circuit&amp;lt;/font&amp;gt;。在&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;皮层-基底神经节-丘脑-皮层环路cortico-basal ganglia-thalamo-cortical loop&amp;lt;/font&amp;gt;中有几个神经回路。这些回路在皮层、&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;基底神经节basal ganglia&amp;lt;/font&amp;gt;、丘脑之间传递信息，并将信息传回皮层。基底神经节内最大的结构，&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;纹状体striatum&amp;lt;/font&amp;gt;，被认为有自己的内部微电路。&amp;lt;ref name=&amp;quot;Stocco&amp;quot; /&amp;gt;&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;神经回路的典型例子是&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;海马体hippocampus&amp;lt;/font&amp;gt;中的&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;三突触回路trisynaptic circuit&amp;lt;/font&amp;gt;。另一个是连接&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;下丘脑hypothalamus&amp;lt;/font&amp;gt;和&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;边缘叶limbic lobe&amp;lt;/font&amp;gt;的&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;帕佩兹回路Papez circuit&amp;lt;/font&amp;gt;。在&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;皮层-基底神经节-丘脑-皮层环路cortico-basal ganglia-thalamo-cortical loop&amp;lt;/font&amp;gt;中有几个神经回路。这些回路在皮层、&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;基底神经节basal ganglia&amp;lt;/font&amp;gt;、丘脑之间传递信息，并将信息传回皮层。基底神经节内最大的结构，&amp;lt;font color=&amp;quot;#ff8000&amp;quot;&amp;gt;纹状体striatum&amp;lt;/font&amp;gt;，被认为有自己的内部微电路。&amp;lt;ref name=&amp;quot;Stocco&amp;quot; /&amp;gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;文件：Model of Cerebellar Perceptron&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;Model of a neural circuit in the [[cerebellum]]&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;小脑神经回路模型&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;Neural circuits in the [[spinal cord]] called [[central pattern generator]]s are responsible for controlling motor instructions involved in rhythmic behaviours. Rhythmic behaviours include walking, [[urination]], and [[ejaculation]]. The central pattern generators are made up of different groups of [[spinal interneuron]]s.&amp;lt;ref name=&amp;quot;Guertin&amp;quot;&amp;gt;{{cite journal |last1=Guertin |first1=PA |title=Central pattern generator for locomotion: anatomical, physiological, and pathophysiological considerations. |journal=Frontiers in Neurology |date=2012 |volume=3 |pages=183 |doi=10.3389/fneur.2012.00183 |pmid=23403923|pmc=3567435 }}&amp;lt;/ref&amp;gt;&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;Neural circuits in the [[spinal cord]] called [[central pattern generator]]s are responsible for controlling motor instructions involved in rhythmic behaviours. Rhythmic behaviours include walking, [[urination]], and [[ejaculation]]. The central pattern generators are made up of different groups of [[spinal interneuron]]s.&amp;lt;ref name=&amp;quot;Guertin&amp;quot;&amp;gt;{{cite journal |last1=Guertin |first1=PA |title=Central pattern generator for locomotion: anatomical, physiological, and pathophysiological considerations. |journal=Frontiers in Neurology |date=2012 |volume=3 |pages=183 |doi=10.3389/fneur.2012.00183 |pmid=23403923|pmc=3567435 }}&amp;lt;/ref&amp;gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot; id=&quot;mw-diff-left-l123&quot; &gt;第123行：&lt;/td&gt;
&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot;&gt;第145行：&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;*[[Pulse-coupled networks]]&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;*[[Pulse-coupled networks]]&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;*[[Systems neuroscience]]&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;*[[Systems neuroscience]]&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt; &lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;请见&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;* 反馈&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;* 反馈&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;* 人脑区域分布列表&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;* 人脑区域分布列表&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot; id=&quot;mw-diff-left-l137&quot; &gt;第137行：&lt;/td&gt;
&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot;&gt;第159行：&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;==Further reading==&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;==Further reading==&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;*[http://www.scholarpedia.org/article/Intrinsic_plasticity Intrinsic plasticity] Robert H. Cudmore, Niraj S. Desai [[Scholarpedia]] 3(2):1363. [[doi:10.4249/scholarpedia.1363]]&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;*[http://www.scholarpedia.org/article/Intrinsic_plasticity Intrinsic plasticity] Robert H. Cudmore, Niraj S. Desai [[Scholarpedia]] 3(2):1363. [[doi:10.4249/scholarpedia.1363]]&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;del style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;&lt;/del&gt;&lt;/div&gt;&lt;/td&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;del style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;*Intrinsic plasticity Robert H. Cudmore, Niraj S. Desai Scholarpedia 3(2):1363. doi:10.4249/scholarpedia.1363&lt;/del&gt;&lt;/div&gt;&lt;/td&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;=&amp;lt;nowiki&amp;gt;= 进一步阅读 = =&amp;lt;/nowiki&amp;gt;=  &lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;=&amp;lt;nowiki&amp;gt;= 进一步阅读 = =&amp;lt;/nowiki&amp;gt;=  &lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;* 内在可塑性 罗伯特 · &lt;del class=&quot;diffchange diffchange-inline&quot;&gt;h &lt;/del&gt;· 卡德莫尔，尼拉杰 · &lt;del class=&quot;diffchange diffchange-inline&quot;&gt;s &lt;/del&gt;· &lt;del class=&quot;diffchange diffchange-inline&quot;&gt;德赛奖学金百科全书3&lt;/del&gt;(2) : 1363. doi: 10.4249/Scholarpedia. 1363&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;* 内在可塑性 罗伯特 · &lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;H &lt;/ins&gt;· 卡德莫尔，尼拉杰 · &lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;S &lt;/ins&gt;· &lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;德赛 奖学金百科全书3&lt;/ins&gt;(2) : 1363. doi: 10.4249/Scholarpedia. 1363&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;==External links==&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;==External links==&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot; id=&quot;mw-diff-left-l151&quot; &gt;第151行：&lt;/td&gt;
&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot;&gt;第171行：&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;*[http://nba.uth.tmc.edu/neuroscience/s1/introduction.html Introduction to Neurons and Neuronal Networks], ''Neuroscience Online'' (electronic neuroscience textbook)&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;*[http://nba.uth.tmc.edu/neuroscience/s1/introduction.html Introduction to Neurons and Neuronal Networks], ''Neuroscience Online'' (electronic neuroscience textbook)&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;*[http://www.gfai.de/~heinz/publications/NI/index.htm Delaying Pulse Networks (Wave Interference Networks)]&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;*[http://www.gfai.de/~heinz/publications/NI/index.htm Delaying Pulse Networks (Wave Interference Networks)]&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;外部链接&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;*&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;Comparison of Neural Networks in the Brain and Artificial Neural Networks&lt;/del&gt;&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;* &lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;脑内神经网络与人工神经网络的比较&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;*&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;Lecture notes at MIT OpenCourseWare&lt;/del&gt;&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;* &lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;麻省理工学院公开课程讲稿&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;*&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;Computation in the Brain&lt;/del&gt;&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;* &lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;大脑中的计算&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;*&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;Biological Neural Network Toolbox - A free Matlab toolbox for simulating networks of several different types of neurons&lt;/del&gt;&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;* &lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;一种自由的Matlab工具箱，用于模拟几种不同类型的神经元的网络&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;*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.&lt;/del&gt;&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;* wormweb. org: &lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;线虫神经网络的交互式可视化—— 一种具有302个神经元的线虫，它是唯一一种完整的神经网络被发现的生物。使用这个网站浏览网络，并搜索任何两个神经元之间的路径。&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;*Introduction to Neurons and Neuronal Networks, Neuroscience Online (electronic neuroscience textbook)&lt;/del&gt;&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;* &lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;《神经元与神经元网络概论》，''神经科学在线''&lt;/ins&gt;(&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;神经科学电子教材&lt;/ins&gt;)&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;* Delaying Pulse Networks (Wave Interference Networks)&lt;/del&gt;&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;* 延迟脉冲网络(波干扰网络)&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt; &lt;/div&gt;&lt;/td&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;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 &lt;/del&gt;&lt;/div&gt;&lt;/td&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;*wormweb. org: &lt;del class=&quot;diffchange diffchange-inline&quot;&gt;秀丽隐杆线虫神经网络的交互式可视化，一种有302个神经元的线虫，是唯一一种神经网络已经被发现的生物体。使用此网站浏览通过网络和搜索路径之间的任何2个神经元。&lt;/del&gt;&lt;/div&gt;&lt;/td&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;*&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;神经元和神经元网络介绍，神经科学在线&lt;/del&gt;(&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;电子神经科学教科书&lt;/del&gt;)&lt;/div&gt;&lt;/td&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;*延迟脉冲网络(波干扰网络)&lt;/div&gt;&lt;/td&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;{{nervous_system}}&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;{{nervous_system}}&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;/table&gt;</summary>
		<author><name>Glh20100487</name></author>
	</entry>
	<entry>
		<id>https://wiki.swarma.org/index.php?title=%E7%A5%9E%E7%BB%8F%E5%9B%9E%E8%B7%AF&amp;diff=30741&amp;oldid=prev</id>
		<title>2022年4月28日 (四) 01:57 Glh20100487</title>
		<link rel="alternate" type="text/html" href="https://wiki.swarma.org/index.php?title=%E7%A5%9E%E7%BB%8F%E5%9B%9E%E8%B7%AF&amp;diff=30741&amp;oldid=prev"/>
		<updated>2022-04-28T01:57:34Z</updated>

		<summary type="html">&lt;p&gt;&lt;/p&gt;
&lt;a href=&quot;https://wiki.swarma.org/index.php?title=%E7%A5%9E%E7%BB%8F%E5%9B%9E%E8%B7%AF&amp;amp;diff=30741&amp;amp;oldid=30740&quot;&gt;显示更改&lt;/a&gt;</summary>
		<author><name>Glh20100487</name></author>
	</entry>
	<entry>
		<id>https://wiki.swarma.org/index.php?title=%E7%A5%9E%E7%BB%8F%E5%9B%9E%E8%B7%AF&amp;diff=30740&amp;oldid=prev</id>
		<title>2022年4月28日 (四) 01:40 Glh20100487</title>
		<link rel="alternate" type="text/html" href="https://wiki.swarma.org/index.php?title=%E7%A5%9E%E7%BB%8F%E5%9B%9E%E8%B7%AF&amp;diff=30740&amp;oldid=prev"/>
		<updated>2022-04-28T01:40:03Z</updated>

		<summary type="html">&lt;p&gt;&lt;/p&gt;
&lt;a href=&quot;https://wiki.swarma.org/index.php?title=%E7%A5%9E%E7%BB%8F%E5%9B%9E%E8%B7%AF&amp;amp;diff=30740&amp;amp;oldid=30739&quot;&gt;显示更改&lt;/a&gt;</summary>
		<author><name>Glh20100487</name></author>
	</entry>
	<entry>
		<id>https://wiki.swarma.org/index.php?title=%E7%A5%9E%E7%BB%8F%E5%9B%9E%E8%B7%AF&amp;diff=30739&amp;oldid=prev</id>
		<title>2022年4月28日 (四) 01:18 Glh20100487</title>
		<link rel="alternate" type="text/html" href="https://wiki.swarma.org/index.php?title=%E7%A5%9E%E7%BB%8F%E5%9B%9E%E8%B7%AF&amp;diff=30739&amp;oldid=prev"/>
		<updated>2022-04-28T01:18:46Z</updated>

		<summary type="html">&lt;p&gt;&lt;/p&gt;
&lt;a href=&quot;https://wiki.swarma.org/index.php?title=%E7%A5%9E%E7%BB%8F%E5%9B%9E%E8%B7%AF&amp;amp;diff=30739&amp;amp;oldid=30734&quot;&gt;显示更改&lt;/a&gt;</summary>
		<author><name>Glh20100487</name></author>
	</entry>
	<entry>
		<id>https://wiki.swarma.org/index.php?title=%E7%A5%9E%E7%BB%8F%E5%9B%9E%E8%B7%AF&amp;diff=30734&amp;oldid=prev</id>
		<title>2022年4月27日 (三) 01:07 Glh20100487</title>
		<link rel="alternate" type="text/html" href="https://wiki.swarma.org/index.php?title=%E7%A5%9E%E7%BB%8F%E5%9B%9E%E8%B7%AF&amp;diff=30734&amp;oldid=prev"/>
		<updated>2022-04-27T01:07:50Z</updated>

		<summary type="html">&lt;p&gt;&lt;/p&gt;
&lt;table class=&quot;diff diff-contentalign-left diff-editfont-monospace&quot; data-mw=&quot;interface&quot;&gt;
				&lt;col class=&quot;diff-marker&quot; /&gt;
				&lt;col class=&quot;diff-content&quot; /&gt;
				&lt;col class=&quot;diff-marker&quot; /&gt;
				&lt;col class=&quot;diff-content&quot; /&gt;
				&lt;tr class=&quot;diff-title&quot; lang=&quot;zh-Hans-CN&quot;&gt;
				&lt;td colspan=&quot;2&quot; style=&quot;background-color: #fff; color: #202122; text-align: center;&quot;&gt;←上一版本&lt;/td&gt;
				&lt;td colspan=&quot;2&quot; style=&quot;background-color: #fff; color: #202122; text-align: center;&quot;&gt;2022年4月27日 (三) 01:07的版本&lt;/td&gt;
				&lt;/tr&gt;&lt;tr&gt;&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot; id=&quot;mw-diff-left-l53&quot; &gt;第53行：&lt;/td&gt;
&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot;&gt;第53行：&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;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.&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;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.&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;虽然在发育状态的脑developing &lt;del class=&quot;diffchange diffchange-inline&quot;&gt;brain突触中，突触抑制已经被广泛观察到，但能够推断的是，它在成人大脑中得到完善。&lt;/del&gt;&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;虽然在发育状态的脑developing &lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;brain突触中，突触抑制已经被广泛观察到，但能够推断的是，它在成人大脑中转变成易化。&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;==Circuitry==&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;==Circuitry==&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot; id=&quot;mw-diff-left-l88&quot; &gt;第88行：&lt;/td&gt;
&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot;&gt;第88行：&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;In a parallel after-discharge circuit, a neuron inputs to several chains of neurons. Each chain is made up of a different number of neurons but their signals converge onto one output neuron. Each synapse in the circuit acts to delay the signal by about 0.5 msec so that the more synapses there are will produce a longer delay to the output neuron. After the input has stopped, the output will go on firing for some time. This type of circuit does not have a feedback loop as does the reverberating circuit. Continued firing after the stimulus has stopped is called ''after-discharge''. This circuit type is found in the [[reflex arc]]s of certain [[reflex]]es.&amp;lt;ref name=&amp;quot;Saladin&amp;quot; /&amp;gt;&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;In a parallel after-discharge circuit, a neuron inputs to several chains of neurons. Each chain is made up of a different number of neurons but their signals converge onto one output neuron. Each synapse in the circuit acts to delay the signal by about 0.5 msec so that the more synapses there are will produce a longer delay to the output neuron. After the input has stopped, the output will go on firing for some time. This type of circuit does not have a feedback loop as does the reverberating circuit. Continued firing after the stimulus has stopped is called ''after-discharge''. This circuit type is found in the [[reflex arc]]s of certain [[reflex]]es.&amp;lt;ref name=&amp;quot;Saladin&amp;quot; /&amp;gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;在并联的后放电回路中，一个神经元输入到几个神经元链。每个链由不同数量的神经元组成，但是它们的信号会聚到一个输出神经元上。电路中每一个突触都会将信号延迟0.&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;5毫秒左右，因此，突触越多，输出神经元的延迟时间就越长。在输入停止之后，输出将持续一段时间。这种类型的电路不像混响电路那样有反馈回路。刺激停止后的持续放电称为后放电。这种回路类型存在于某些反射reflex的反射弧reflex &lt;/del&gt;arc中。&amp;lt;ref name=&amp;quot;Saladin&amp;quot; /&amp;gt;&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;在并联的后放电回路中，一个神经元输入到几个神经元链。每个链由不同数量的神经元组成，但是它们的信号会聚到一个输出神经元上。电路中每一个突触都会将信号延迟0.&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;5毫秒左右，因此，突触越多，输出神经元的延迟时间就越长。在输入停止之后，输出将持续一段时间。这种类型的电路不像反射电路那样有反馈回路。刺激停止后的持续放电称为后放电。这种回路类型存在于某些反射reflex的反射弧reflex &lt;/ins&gt;arc中。&amp;lt;ref name=&amp;quot;Saladin&amp;quot; /&amp;gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;==Study methods==&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;==Study methods==&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;{{See also|Neuropsychology|Cognitive neuropsychology}}&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;{{See also|Neuropsychology|Cognitive neuropsychology}}&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;/table&gt;</summary>
		<author><name>Glh20100487</name></author>
	</entry>
	<entry>
		<id>https://wiki.swarma.org/index.php?title=%E7%A5%9E%E7%BB%8F%E5%9B%9E%E8%B7%AF&amp;diff=30733&amp;oldid=prev</id>
		<title>2022年4月27日 (三) 00:59 Glh20100487</title>
		<link rel="alternate" type="text/html" href="https://wiki.swarma.org/index.php?title=%E7%A5%9E%E7%BB%8F%E5%9B%9E%E8%B7%AF&amp;diff=30733&amp;oldid=prev"/>
		<updated>2022-04-27T00:59:07Z</updated>

		<summary type="html">&lt;p&gt;&lt;/p&gt;
&lt;table class=&quot;diff diff-contentalign-left diff-editfont-monospace&quot; data-mw=&quot;interface&quot;&gt;
				&lt;col class=&quot;diff-marker&quot; /&gt;
				&lt;col class=&quot;diff-content&quot; /&gt;
				&lt;col class=&quot;diff-marker&quot; /&gt;
				&lt;col class=&quot;diff-content&quot; /&gt;
				&lt;tr class=&quot;diff-title&quot; lang=&quot;zh-Hans-CN&quot;&gt;
				&lt;td colspan=&quot;2&quot; style=&quot;background-color: #fff; color: #202122; text-align: center;&quot;&gt;←上一版本&lt;/td&gt;
				&lt;td colspan=&quot;2&quot; style=&quot;background-color: #fff; color: #202122; text-align: center;&quot;&gt;2022年4月27日 (三) 00:59的版本&lt;/td&gt;
				&lt;/tr&gt;&lt;tr&gt;&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot; id=&quot;mw-diff-left-l12&quot; &gt;第12行：&lt;/td&gt;
&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot;&gt;第12行：&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;Early treatments of neural [[Biological network|networks]] can be found in [[Herbert Spencer]]'s ''Principles of Psychology'', 3rd edition (1872), [[Theodor Meynert]]'s ''[[Psychiatry]]'' (1884), [[William James]]' ''Principles of [[Psychology]]'' (1890), and [[Sigmund Freud]]'s Project for a Scientific Psychology (composed 1895).&amp;lt;ref name=&amp;quot;:0&amp;quot;&amp;gt;{{cite web |url=http://psych.stanford.edu/~jlm/papers/ThomasMcCIPCambEncy.pdf |title=Connectionist models of cognition |author1=Michael S. C. Thomas |author2=James L. McClelland |publisher=[[Stanford University]] |access-date=2015-08-31 |archive-url=https://web.archive.org/web/20150906120214/http://psych.stanford.edu/~jlm/papers/ThomasMcCIPCambEncy.pdf |archive-date=2015-09-06 |url-status=dead }}&amp;lt;/ref&amp;gt; The first rule of neuronal learning was described by [[Donald Olding Hebb|Hebb]] in 1949, in the [[Hebbian theory]]. Thus, Hebbian pairing of pre-synaptic and post-synaptic activity can substantially alter the dynamic characteristics of the synaptic connection and therefore either facilitate or inhibit [[neurotransmission|signal transmission]]. In 1959, the [[neuroscientist]]s, [[Warren Sturgis McCulloch]] and [[Walter Pitts]] published the first works on the processing of neural networks.&amp;lt;ref name=&amp;quot;:1&amp;quot;&amp;gt;{{citation | title = What the frog's eye tells the frog's brain. |author1=J. Y. Lettvin |author2=H. R. Maturana |author3=W. S. McCulloch |author4=W. H. Pitts | year = 1959 | work = Proc. Inst. Radio Engr. | issue = 47 | pages = 1940–1951 }}&amp;lt;/ref&amp;gt; They showed theoretically that networks of artificial neurons could [[implementation|implement]] [[logic]]al, [[arithmetic]], and [[symbol]]ic functions. Simplified [[Biological neuron model|models of biological neurons]] were set up, now usually called [[perceptrons]] or [[artificial neurons]]. These simple models accounted for [[Summation (Neurophysiology)|neural summation]] (i.e., potentials at the post-synaptic membrane will summate in the [[cell body]]). Later models also provided for excitatory and inhibitory synaptic transmission.&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;Early treatments of neural [[Biological network|networks]] can be found in [[Herbert Spencer]]'s ''Principles of Psychology'', 3rd edition (1872), [[Theodor Meynert]]'s ''[[Psychiatry]]'' (1884), [[William James]]' ''Principles of [[Psychology]]'' (1890), and [[Sigmund Freud]]'s Project for a Scientific Psychology (composed 1895).&amp;lt;ref name=&amp;quot;:0&amp;quot;&amp;gt;{{cite web |url=http://psych.stanford.edu/~jlm/papers/ThomasMcCIPCambEncy.pdf |title=Connectionist models of cognition |author1=Michael S. C. Thomas |author2=James L. McClelland |publisher=[[Stanford University]] |access-date=2015-08-31 |archive-url=https://web.archive.org/web/20150906120214/http://psych.stanford.edu/~jlm/papers/ThomasMcCIPCambEncy.pdf |archive-date=2015-09-06 |url-status=dead }}&amp;lt;/ref&amp;gt; The first rule of neuronal learning was described by [[Donald Olding Hebb|Hebb]] in 1949, in the [[Hebbian theory]]. Thus, Hebbian pairing of pre-synaptic and post-synaptic activity can substantially alter the dynamic characteristics of the synaptic connection and therefore either facilitate or inhibit [[neurotransmission|signal transmission]]. In 1959, the [[neuroscientist]]s, [[Warren Sturgis McCulloch]] and [[Walter Pitts]] published the first works on the processing of neural networks.&amp;lt;ref name=&amp;quot;:1&amp;quot;&amp;gt;{{citation | title = What the frog's eye tells the frog's brain. |author1=J. Y. Lettvin |author2=H. R. Maturana |author3=W. S. McCulloch |author4=W. H. Pitts | year = 1959 | work = Proc. Inst. Radio Engr. | issue = 47 | pages = 1940–1951 }}&amp;lt;/ref&amp;gt; They showed theoretically that networks of artificial neurons could [[implementation|implement]] [[logic]]al, [[arithmetic]], and [[symbol]]ic functions. Simplified [[Biological neuron model|models of biological neurons]] were set up, now usually called [[perceptrons]] or [[artificial neurons]]. These simple models accounted for [[Summation (Neurophysiology)|neural summation]] (i.e., potentials at the post-synaptic membrane will summate in the [[cell body]]). Later models also provided for excitatory and inhibitory synaptic transmission.&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;= = 早期研究 = = 对神经网络的早期研究见于赫伯特 · 斯宾塞Herbert Spencer的《心理学原理》第三版(1872)、西奥多 · 梅纳特Theodor Meynert的《精神病学》(1884)、威廉 · 詹姆斯William James的《心理学原理》(1890)和西格蒙德 · 弗洛伊德Sigmund Freud的《科学心理学计划》(1895)。&amp;lt;ref name=&amp;quot;:0&amp;quot; /&amp;gt; 1949年，赫布Hebb在其理论（即赫布理论Hebbian theory）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signal &lt;del class=&quot;diffchange diffchange-inline&quot;&gt;transmission。1959年，神经科学家，沃伦·麦卡洛克Warren &lt;/del&gt;Sturgis和 沃尔特·皮茨Walter Pitts 发表了关于神经网络处理的第一部著作。&amp;lt;ref name=&amp;quot;:1&amp;quot; /&amp;gt; &lt;del class=&quot;diffchange diffchange-inline&quot;&gt;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models &lt;/del&gt;of biological neurons由此建立起来，现在通常被称为感知器perceptrons或人工神经元artificial neurons。这些简单的模型解释了神经加成作用neural summation(&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;即突触后膜上的电位将在细胞体中加成&lt;/del&gt;)。后来的模型也提供了兴奋性和抑制性突触传递。&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;= = 早期研究 = = 对神经网络的早期研究见于赫伯特 · 斯宾塞Herbert Spencer的《心理学原理》第三版(1872)、西奥多 · 梅纳特Theodor Meynert的《精神病学》(1884)、威廉 · 詹姆斯William James的《心理学原理》(1890)和西格蒙德 · 弗洛伊德Sigmund Freud的《科学心理学计划》(1895)。&amp;lt;ref name=&amp;quot;:0&amp;quot; /&amp;gt; 1949年，赫布Hebb在其理论（即赫布理论Hebbian theory）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signal &lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;transmission。1959年，神经科学家neuroscientist, 沃伦·麦卡洛克Warren &lt;/ins&gt;Sturgis和 沃尔特·皮茨Walter Pitts 发表了关于神经网络处理的第一部著作。&amp;lt;ref name=&amp;quot;:1&amp;quot; /&amp;gt; &lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;他们从理论上证明了人工神经元网络可以实现逻辑logical、算术arithmetic和符号功能symbolic。生物神经元的简化模型models &lt;/ins&gt;of biological neurons由此建立起来，现在通常被称为感知器perceptrons或人工神经元artificial neurons。这些简单的模型解释了神经加成作用neural summation(&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;即突触后膜上的电位将在细胞体cell body中加成&lt;/ins&gt;)。后来的模型也提供了兴奋性和抑制性突触传递。&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;==Connections between neurons==&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;==Connections between neurons==&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot; id=&quot;mw-diff-left-l33&quot; &gt;第33行：&lt;/td&gt;
&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot;&gt;第33行：&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;One principle by which neurons work is [[Summation (neurophysiology)|neural summation]] – [[postsynaptic potential|potentials]] at the [[Chemical synapse|postsynaptic membrane]] will sum up in the cell body. If the [[depolarization]] of the neuron at the [[axon hillock]] goes above threshold an action potential will occur that travels down the [[axon]] to the terminal endings to transmit a signal to other neurons. Excitatory and inhibitory synaptic transmission is realized mostly by [[excitatory postsynaptic potentials]] (EPSPs), and [[inhibitory postsynaptic potentials]] (IPSPs).&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;One principle by which neurons work is [[Summation (neurophysiology)|neural summation]] – [[postsynaptic potential|potentials]] at the [[Chemical synapse|postsynaptic membrane]] will sum up in the cell body. If the [[depolarization]] of the neuron at the [[axon hillock]] goes above threshold an action potential will occur that travels down the [[axon]] to the terminal endings to transmit a signal to other neurons. Excitatory and inhibitory synaptic transmission is realized mostly by [[excitatory postsynaptic potentials]] (EPSPs), and [[inhibitory postsynaptic potentials]] (IPSPs).&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;神经元工作的其中一个原理是神经加成——突触后膜上的电位将在细胞体中进行加成。如果神经元在轴突丘处的去极化超过阈值，就会发生动作电位，动作电位沿着轴突向下传递到末端，将信号传递给其他神经元。兴奋性和抑制性突触传递主要通过兴奋性突触后电位&lt;/del&gt;(EPSPs)&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;和抑制性突触后电位&lt;/del&gt;(IPSPs)实现。&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;神经元工作的其中一个原理是神经加成neural summation——突触后膜postsynaptic membrane上的电位potentials将在细胞体中进行加成。如果神经元在轴突丘axon hillock处的去极化depolarization超过阈值，就会发生动作电位，动作电位沿着轴突向下传递到末端，将信号传递给其他神经元。兴奋性和抑制性突触传递主要通过兴奋性突触后电位exciatory postsynaptic potentials&lt;/ins&gt;(EPSPs)&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;和抑制性突触后电位inhibitory postsynaptic potentials&lt;/ins&gt;(IPSPs)实现。&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;On the [[electrophysiology|electrophysiological]] level, there are various phenomena which alter the response characteristics of individual synapses (called [[synaptic plasticity]]) and individual neurons ([[intrinsic plasticity]]). These are often divided into short-term plasticity and long-term plasticity. Long-term synaptic plasticity is often contended to be the most likely [[memory]] substrate. Usually, the term &amp;quot;[[neuroplasticity]]&amp;quot; refers to changes in the brain that are caused by activity or experience.&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;On the [[electrophysiology|electrophysiological]] level, there are various phenomena which alter the response characteristics of individual synapses (called [[synaptic plasticity]]) and individual neurons ([[intrinsic plasticity]]). These are often divided into short-term plasticity and long-term plasticity. Long-term synaptic plasticity is often contended to be the most likely [[memory]] substrate. Usually, the term &amp;quot;[[neuroplasticity]]&amp;quot; refers to changes in the brain that are caused by activity or experience.&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;在电生理层面上，存在着改变个体突触&lt;/del&gt;(&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;突触可塑性&lt;/del&gt;)和个体神经元(&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;内禀可塑性&lt;/del&gt;)&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;的反应特征的各种现象。这些可塑性通常分为短期可塑性和长期可塑性。长期突触可塑性通常被认为是最有可能的记忆底物。通常来说，“神经可塑性”指的是由活动或经历引起的大脑变化。&lt;/del&gt;&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;在电生理electrophysiological层面上，存在着改变个体突触&lt;/ins&gt;(&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;突触可塑性synaptic plasticity&lt;/ins&gt;)和个体神经元(&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;内禀可塑性intrinsic plasticity&lt;/ins&gt;)&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;的反应特征的各种现象。这些可塑性通常分为短期可塑性和长期可塑性。长期突触可塑性通常被认为是最有可能的记忆memory底物。通常来说，“神经可塑性neuroplasticity”指的是由活动或经历引起的大脑变化。&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;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]].&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;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，称为峰时依赖的可塑性。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&lt;/del&gt;(&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;称为易化&lt;/del&gt;)或减少(&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;抑制&lt;/del&gt;)&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;。通过长期增强&lt;/del&gt;(LTP)&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;或抑制&lt;/del&gt;(LTD)&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;诱导突触效能的长期变化，在很大程度上取决于兴奋性突触后电位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磷酸化增加现有受体的效能。&lt;/del&gt;&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;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]].&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt; &lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;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，称为峰时依赖的可塑性splke-timing-dependent plasticity。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&lt;/ins&gt;(&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;称为易化facilitation&lt;/ins&gt;)或减少(&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;抑制depression&lt;/ins&gt;)&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;。通过长期增强long-term potentiation&lt;/ins&gt;(LTP)&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;或抑制depression&lt;/ins&gt;(LTD)&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;诱导突触效能的长期变化，在很大程度上取决于兴奋性突触后电位excitatory postsynaptic potential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磷酸化phosphorylation增加现有受体的效能。&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;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&amp;lt;sup&amp;gt;+&amp;lt;/sup&amp;gt;) 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.&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;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&amp;lt;sup&amp;gt;+&amp;lt;/sup&amp;gt;) 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.&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;反向传播的动作电位是不可能发生的，因为当动作电位沿着轴突的某一特定节段传递之后，电压门控钠通道上的m门关闭，从而阻止h门的任何瞬态打开，以免引起细胞内钠离子浓度的变化。并阻止动作电位的产生回到细胞体内。然而，在某些细胞中，神经反向传播确实通过树突分支发生，并可能对突触可塑性和计算产生重要影响。&lt;/del&gt;&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;反向传播的动作电位是不可能发生的，因为当动作电位沿着轴突的某一特定节段传递之后，电压门控钠通道voltage-gated sodium上的m门m gate关闭，从而阻止h门h gate的任何瞬态打开，以免引起细胞内钠离子浓度的变化。并阻止动作电位的产生回到细胞体内。然而，在某些细胞中，神经反向传播neural backpropagation确实通过树突分支dendritic branching发生，并可能对突触可塑性和计算产生重要影响。&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;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.&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;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.&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;/table&gt;</summary>
		<author><name>Glh20100487</name></author>
	</entry>
	<entry>
		<id>https://wiki.swarma.org/index.php?title=%E7%A5%9E%E7%BB%8F%E5%9B%9E%E8%B7%AF&amp;diff=30732&amp;oldid=prev</id>
		<title>2022年4月27日 (三) 00:28 Glh20100487</title>
		<link rel="alternate" type="text/html" href="https://wiki.swarma.org/index.php?title=%E7%A5%9E%E7%BB%8F%E5%9B%9E%E8%B7%AF&amp;diff=30732&amp;oldid=prev"/>
		<updated>2022-04-27T00:28:48Z</updated>

		<summary type="html">&lt;p&gt;&lt;/p&gt;
&lt;a href=&quot;https://wiki.swarma.org/index.php?title=%E7%A5%9E%E7%BB%8F%E5%9B%9E%E8%B7%AF&amp;amp;diff=30732&amp;amp;oldid=30699&quot;&gt;显示更改&lt;/a&gt;</summary>
		<author><name>Glh20100487</name></author>
	</entry>
	<entry>
		<id>https://wiki.swarma.org/index.php?title=%E7%A5%9E%E7%BB%8F%E5%9B%9E%E8%B7%AF&amp;diff=30699&amp;oldid=prev</id>
		<title>2022年4月25日 (一) 02:46 Glh20100487</title>
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		<updated>2022-04-25T02:46:15Z</updated>

		<summary type="html">&lt;p&gt;&lt;/p&gt;
&lt;a href=&quot;https://wiki.swarma.org/index.php?title=%E7%A5%9E%E7%BB%8F%E5%9B%9E%E8%B7%AF&amp;amp;diff=30699&amp;amp;oldid=30698&quot;&gt;显示更改&lt;/a&gt;</summary>
		<author><name>Glh20100487</name></author>
	</entry>
	<entry>
		<id>https://wiki.swarma.org/index.php?title=%E7%A5%9E%E7%BB%8F%E5%9B%9E%E8%B7%AF&amp;diff=30698&amp;oldid=prev</id>
		<title>2022年4月25日 (一) 02:43 Glh20100487</title>
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		<updated>2022-04-25T02:43:09Z</updated>

		<summary type="html">&lt;p&gt;&lt;/p&gt;
&lt;a href=&quot;https://wiki.swarma.org/index.php?title=%E7%A5%9E%E7%BB%8F%E5%9B%9E%E8%B7%AF&amp;amp;diff=30698&amp;amp;oldid=30697&quot;&gt;显示更改&lt;/a&gt;</summary>
		<author><name>Glh20100487</name></author>
	</entry>
</feed>