脉冲时序依赖可塑性

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Spike-timing-dependent plasticity (STDP) is a biological process that adjusts the strength of connections between neurons in the brain. The process adjusts the connection strengths based on the relative timing of a particular neuron's output and input action potentials (or spikes). The STDP process partially explains the activity-dependent development of nervous systems, especially with regard to long-term potentiation and long-term depression.

脉冲时间依赖可塑性(STDP)是一种调节大脑神经元之间连接强度的生物过程。这个过程根据特定神经元输出和输入动作电位(或尖峰)的相对时间来调整连接强度。STDP过程部分解释了神经系统的活动依赖性发育，特别是长期增强和长期抑郁。


Spike-timing-dependent plasticity (STDP) is a biological process that adjusts the strength of connections between neurons in the brain. The process adjusts the connection strengths based on the relative timing of a particular neuron's output and input action potentials (or spikes). The STDP process partially explains the activity-dependent development of nervous systems, especially with regard to long-term potentiation and long-term depression.

电峰时间相关突触可塑性是一种调节大脑神经元之间连接强度的生物学过程。这个过程根据特定神经元输出和输入动作电位(或尖峰)的相对时间来调整连接强度。STDP 过程部分解释了神经系统的活动依赖性发育，特别是关于长时程增强作用和长期抑郁症。

Process

Process

= 进程 =

Under the STDP process, if an input spike to a neuron tends, on average, to occur immediately before that neuron's output spike, then that particular input is made somewhat stronger. If an input spike tends, on average, to occur immediately after an output spike, then that particular input is made somewhat weaker hence: "spike-timing-dependent plasticity". Thus, inputs that might be the cause of the post-synaptic neuron's excitation are made even more likely to contribute in the future, whereas inputs that are not the cause of the post-synaptic spike are made less likely to contribute in the future. The process continues until a subset of the initial set of connections remain, while the influence of all others is reduced to 0. Since a neuron produces an output spike when many of its inputs occur within a brief period, the subset of inputs that remain are those that tended to be correlated in time. In addition, since the inputs that occur before the output are strengthened, the inputs that provide the earliest indication of correlation will eventually become the final input to the neuron.

在STDP过程中，如果一个神经元的输入脉冲平均会在该神经元的输出脉冲之前出现，那么这个特定的输入就会变得更强。平均而言，如果输入峰值倾向于在输出峰值之后立即出现，那么特定的输入就会变得更弱，因此:“峰值时间依赖的可塑性”。因此，可能导致突触后神经元兴奋的输入在未来更有可能发挥作用，而不是导致突触后神经元脉冲的输入则不太可能在未来发挥作用。该过程将继续进行，直到初始连接集的一个子集保留下来，而其他所有连接的影响将减少到0。由于神经元的许多输入在短时间内发生时就会产生输出峰值，因此保留下来的输入子集往往是那些与时间相关的。此外，由于输入发生在输出被加强之前，提供最早相关迹象的输入最终将成为神经元的最终输入。

Under the STDP process, if an input spike to a neuron tends, on average, to occur immediately before that neuron's output spike, then that particular input is made somewhat stronger. If an input spike tends, on average, to occur immediately after an output spike, then that particular input is made somewhat weaker hence: "spike-timing-dependent plasticity". Thus, inputs that might be the cause of the post-synaptic neuron's excitation are made even more likely to contribute in the future, whereas inputs that are not the cause of the post-synaptic spike are made less likely to contribute in the future. The process continues until a subset of the initial set of connections remain, while the influence of all others is reduced to 0. Since a neuron produces an output spike when many of its inputs occur within a brief period, the subset of inputs that remain are those that tended to be correlated in time. In addition, since the inputs that occur before the output are strengthened, the inputs that provide the earliest indication of correlation will eventually become the final input to the neuron.

在 STDP 过程中，如果一个神经元的输入尖峰平均来说发生在该神经元的输出尖峰之前，那么这个特定的输入就会变得更强。平均而言，如果一个输入峰值趋向于在一个输出峰值之后立即出现，那么这个特定的输入就会变得更弱，因此称为“电峰时间相关突触可塑性”。因此，可能是引起突触后神经元兴奋的输入在未来更有可能起作用，而不是引起突触后尖峰的输入在未来更不可能起作用。这个过程一直持续下去，直到初始连接集的一个子集保留下来，而其他所有连接的影响力都减少到0。由于当一个神经元的许多输入信号在短时间内发生时，它就会产生一个输出尖峰，所以剩下的输入信号的子集就是那些倾向于在时间上相关的信号。此外，由于输出之前的输入增强，提供相关性最早指示的输入最终将成为神经元的最终输入。

History

In 1973, M. M. Taylor[1] suggested that if synapses were strengthened for which a presynaptic spike occurred just before a postsynaptic spike more often than the reverse (Hebbian learning), while with the opposite timing or in the absence of a closely timed presynaptic spike, synapses were weakened (anti-Hebbian learning), the result would be an informationally efficient recoding of input patterns. This proposal apparently passed unnoticed in the neuroscientific community, and subsequent experimentation was conceived independently of these early suggestions.

1973年，M. M. Taylor提出，如果突触在突触前脉冲出现在突触后脉冲之前的情况下得到加强，而在相反的时间或没有突触前脉冲的情况下，突触被削弱(抗Hebbian学习)，其结果将是对输入模式进行高效的信息编码。这一提议显然没有引起神经科学界的注意，随后的实验设想独立于这些早期的建议。

In 1973, M. M. Taylor suggested that if synapses were strengthened for which a presynaptic spike occurred just before a postsynaptic spike more often than the reverse (Hebbian learning), while with the opposite timing or in the absence of a closely timed presynaptic spike, synapses were weakened (anti-Hebbian learning), the result would be an informationally efficient recoding of input patterns. This proposal apparently passed unnoticed in the neuroscientific community, and subsequent experimentation was conceived independently of these early suggestions.

在1973年，m. m. 泰勒提出，如果突触得到加强，突触前尖峰出现的频率比突触后尖峰出现的频率高(Hebbian 学习) ，而相反的时间或没有紧密定时的突触前尖峰，突触减弱(anti-Hebbian 学习) ，其结果将是信息有效地重新编码输入模式。这个提议显然没有被神经科学界注意到，随后的实验也是独立于这些早期的建议而构想的。

Early experiments on associative plasticity were carried out by W. B. Levy and O. Steward in 1983[2] and examined the effect of relative timing of pre- and postsynaptic action potentials at millisecond level on plasticity. Bruce McNaughton contributed much to this area, too. In studies on neuromuscular synapses carried out by Y. Dan and Mu-ming Poo in 1992,[3] and on the hippocampus by D. Debanne, B. Gähwiler, and S. Thompson in 1994,[4] showed that asynchronous pairing of postsynaptic and synaptic activity induced long-term synaptic depression. However, STDP was more definitively demonstrated by Henry Markram in his postdoc period till 1993 in Bert Sakmann's lab (SFN and Phys Soc abstracts in 1994–1995) which was only published in 1997.[5] C. Bell and co-workers also found a form of STDP in the cerebellum. Henry Markram used dual patch clamping techniques to repetitively activate pre-synaptic neurons 10 milliseconds before activating the post-synaptic target neurons, and found the strength of the synapse increased. When the activation order was reversed so that the pre-synaptic neuron was activated 10 milliseconds after its post-synaptic target neuron, the strength of the pre-to-post synaptic connection decreased. Further work, by Guoqiang Bi, Li Zhang, and Huizhong Tao in Mu-Ming Poo's lab in 1998,[6] continued the mapping of the entire time course relating pre- and post-synaptic activity and synaptic change, to show that in their preparation synapses that are activated within 5-20 ms before a postsynaptic spike are strengthened, and those that are activated within a similar time window after the spike are weakened. This phenomenon has been observed in various other preparations, with some variation in the time-window relevant for plasticity. Several reasons for timing-dependent plasticity have been suggested. For example, STDP might provide a substrate for Hebbian learning during development,[7][8] or, as suggested by Taylor[1] in 1973, the associated Hebbian and anti-Hebbian learning rules might create informationally efficient coding in bundles of related neurons. Works from Y. Dan's lab advanced to study STDP in in vivo systems.[9]

1983年，W. B. Levy和O. Steward对联想可塑性进行了早期实验，研究了毫秒级突触前和突触后动作电位的相对时间对可塑性的影响。布鲁斯·麦克诺顿(Bruce McNaughton)也对这一领域做出了很大贡献。1992年Y. Dan和Mu-ming Poo对神经肌肉突触的研究，以及1994年D. Debanne, B. Gähwiler和S. Thompson对海马的研究表明，突触后和突触活动的异步配对会导致长期的突触抑制。然而，STDP由Henry Markram在他的博士后期间，直到1993年在Bert Sakmann的实验室(SFN和Phys Soc abstracts in 1994-1995)更明确地证明，直到1997年才发表。C. Bell和他的同事还在小脑中发现了STDP的一种形式。Henry Markram使用双重膜片箝位技术，在激活突触后目标神经元10毫秒前重复激活突触前神经元，发现突触的强度增加了。当激活顺序颠倒过来，使突触前神经元在突触后目标神经元10毫秒后被激活，突触前-突触后连接的强度下降。进一步的工作,通过提供Bi,李,和汇众道浦慕明的实验室在1998年,持续整个时间进程的映射相关预处理和突触后活动和突触变化,表明在他们准备中激活突触前5 - 20 ms突触后得到加强,而那些在峰值后类似时间窗内被激活的细胞则减弱了。这一现象已在各种其他准备中观察到，在与可塑性相关的时间窗口中有一些变化。人们提出了几个时间依赖性可塑性的原因。例如，STDP可能在发育过程中为Hebbian学习提供了一个底物，或者，正如Taylor在1973年提出的，相关的Hebbian和anti-Hebbian学习规则可能在相关神经元束中创造出高效的信息编码。来自Y. Dan实验室的工作进展到在体内系统中研究STDP。

Early experiments on associative plasticity were carried out by W. B. Levy and O. Steward in 1983 and examined the effect of relative timing of pre- and postsynaptic action potentials at millisecond level on plasticity. Bruce McNaughton contributed much to this area, too. In studies on neuromuscular synapses carried out by Y. Dan and Mu-ming Poo in 1992, and on the hippocampus by D. Debanne, B. Gähwiler, and S. Thompson in 1994, showed that asynchronous pairing of postsynaptic and synaptic activity induced long-term synaptic depression. However, STDP was more definitively demonstrated by Henry Markram in his postdoc period till 1993 in Bert Sakmann's lab (SFN and Phys Soc abstracts in 1994–1995) which was only published in 1997. C. Bell and co-workers also found a form of STDP in the cerebellum. Henry Markram used dual patch clamping techniques to repetitively activate pre-synaptic neurons 10 milliseconds before activating the post-synaptic target neurons, and found the strength of the synapse increased. When the activation order was reversed so that the pre-synaptic neuron was activated 10 milliseconds after its post-synaptic target neuron, the strength of the pre-to-post synaptic connection decreased. Further work, by Guoqiang Bi, Li Zhang, and Huizhong Tao in Mu-Ming Poo's lab in 1998, continued the mapping of the entire time course relating pre- and post-synaptic activity and synaptic change, to show that in their preparation synapses that are activated within 5-20 ms before a postsynaptic spike are strengthened, and those that are activated within a similar time window after the spike are weakened. This phenomenon has been observed in various other preparations, with some variation in the time-window relevant for plasticity. Several reasons for timing-dependent plasticity have been suggested. For example, STDP might provide a substrate for Hebbian learning during development, or, as suggested by Taylor in 1973, the associated Hebbian and anti-Hebbian learning rules might create informationally efficient coding in bundles of related neurons. Works from Y. Dan's lab advanced to study STDP in in vivo systems.

早期的联想可塑性实验是由 w。利维和 o。在1983年，Steward 博士和他的同事们研究了在毫秒级别上突触前和突触后动作电位的相对计时对可塑性的影响。布鲁斯 · 麦克诺顿对这个领域也做出了很大的贡献。在1992年由 y. Dan 和 Mu-ming Poo 进行的神经肌肉突触研究中，以及1994年由 d. Debanne，b. Gähwiler 和 s. Thompson 进行的海马研究中，发现突触后活动和突触活动的异步配对导致了长期突触抑制。然而，亨利 · 马克拉姆在1993年之前的博士后时期，在伯特 · 萨克曼的实验室(1994-1995年的 SFN 和 Phys Soc 文摘)更明确地证明了 STDP，该文摘直到1997年才出版。贝尔和他的同事们也在小脑中发现了一种 STDP。亨利 · 马克拉姆使用双膜片钳技术，在激活突触后目标神经元前10毫秒重复激活突触前神经元，发现突触的强度增加了。当激活顺序发生逆转，突触前神经元在目标神经元突触后10毫秒被激活时，突触前-突触后连接的强度降低。1998年，蒲慕明实验室的毕、张和陶做了进一步的研究，他们继续绘制了整个时间过程中突触前和突触后活动和突触变化的图谱，以显示在突触后尖峰出现之前5-20毫秒内被激活的突触，以及那些在尖峰出现后在相似时间窗内被激活的突触被削弱了。这种现象已经在许多其他的制剂中观察到，在与塑性有关的时间窗中有一些变化。提出了定时塑性的几个原因。例如，STDP 可能在开发过程中为 Hebbian 的学习提供一个基础，或者，正如 Taylor 在1973年提出的，相关的 Hebbian 和 anti-Hebbian 学习规则可能在相关神经元的捆绑中创建信息高效的编码。丹的实验室致力于研究体内系统中的 STDP。

Mechanisms

Mechanisms

= 机制 =

Postsynaptic NMDA receptors are highly sensitive to the membrane potential (see coincidence detection in neurobiology). Due to their high permeability for calcium, they generate a local chemical signal that is largest when the back-propagating action potential in the dendrite arrives shortly after the synapse was active (pre-post spiking). Large postsynaptic calcium transients are known to trigger synaptic potentiation (Long-term potentiation). The mechanism for spike-timing-dependent depression is less well understood, but often involves either postsynaptic voltage-dependent calcium entry/mGluR activation, or retrograde endocannabinoids and presynaptic NMDARs.[10]

突触后NMDA受体对膜电位高度敏感(见神经生物学中的偶合检测)。由于它们对钙的高渗透性，当突触激活后不久树突的反向传播动作电位到达时，它们产生的局部化学信号最大(前-后尖峰)。大的突触后钙瞬变被认为是触发突触电位(长期电位)。脉冲时间依赖性抑郁的机制还不太清楚，但通常涉及突触后电压依赖性钙离子输入/mGluR激活，或逆行性内源性大麻素和突触前NMDARs。

Postsynaptic NMDA receptors are highly sensitive to the membrane potential (see coincidence detection in neurobiology). Due to their high permeability for calcium, they generate a local chemical signal that is largest when the back-propagating action potential in the dendrite arrives shortly after the synapse was active (pre-post spiking). Large postsynaptic calcium transients are known to trigger synaptic potentiation (Long-term potentiation). The mechanism for spike-timing-dependent depression is less well understood, but often involves either postsynaptic voltage-dependent calcium entry/mGluR activation, or retrograde endocannabinoids and presynaptic NMDARs.

突触后 NMDA 受体对膜电位高度敏感(见神经生物学中的重合检测)。由于它们对钙的高渗透性，它们产生的局部化学信号是最大的，当树突的反向传播动作电位到达后不久，突触是活跃的(前后尖峰)。大量突触后钙瞬变已知触发突触电位(长时程增强作用)。刺激时序依赖性抑郁的机制尚不清楚，但通常涉及突触后电压依赖性钙通道/mGluR 激活，或者是逆行内源性大麻素和突触前 nmdar。

From Hebbian rule to STDP

From Hebbian rule to STDP

= From Hebbian rule to STDP = =

According to the Hebbian rule, synapses increase their efficiency if the synapse persistently takes part in firing the postsynaptic target neuron. Similarly, the efficiency of synapses decreases when the firing of their presynaptic targets is persistently independent of firing their postsynaptic ones. These principles are often simplified in the mnemonics: those who fire together, wire together; and those who fire out of sync, lose their link. However, if two neurons fire exactly at the same time, then one cannot have caused, or taken part in firing the other. Instead, to take part in firing the postsynaptic neuron, the presynaptic neuron needs to fire just before the postsynaptic neuron. Experiments that stimulated two connected neurons with varying interstimulus asynchrony confirmed the importance of temporal relation implicit in Hebb's principle: for the synapse to be potentiated or depressed, the presynaptic neuron has to fire just before or just after the postsynaptic neuron, respectively.[11] In addition, it has become evident that the presynaptic neural firing needs to consistently predict the postsynaptic firing for synaptic plasticity to occur robustly,[12] mirroring at a synaptic level what is known about the importance of contingency in classical conditioning, where zero contingency procedures prevent the association between two stimuli.

根据Hebbian规则，如果突触持续参与突触后目标神经元的放电，突触的效率就会提高。类似地，当突触前目标的发射持续独立于突触后目标的发射时，突触的效率会降低。这些原则通常在记忆法中被简化了:那些一起开火的，连接在一起的;而那些不同步的人，会失去联系。然而，如果两个神经元完全同时放电，那么其中一个神经元就不可能引起或参与另一个神经元的放电。相反，为了参与刺激突触后神经元，突触前神经元需要在突触后神经元之前刺激。用不同刺激间异步方式刺激两个连接的神经元的实验证实了赫布原理中隐含的时间关系的重要性:为了增强或抑制突触，突触前神经元必须分别在突触后神经元之前或之后发出信号。此外，很明显的是，突触前神经放电需要一致地预测突触后放电，才能稳健地发生突触可塑性，在突触水平上反映出已知的经典条件反射中偶然性的重要性，零偶然性程序防止两个刺激之间的联系。

According to the Hebbian rule, synapses increase their efficiency if the synapse persistently takes part in firing the postsynaptic target neuron. Similarly, the efficiency of synapses decreases when the firing of their presynaptic targets is persistently independent of firing their postsynaptic ones. These principles are often simplified in the mnemonics: those who fire together, wire together; and those who fire out of sync, lose their link. However, if two neurons fire exactly at the same time, then one cannot have caused, or taken part in firing the other. Instead, to take part in firing the postsynaptic neuron, the presynaptic neuron needs to fire just before the postsynaptic neuron. Experiments that stimulated two connected neurons with varying interstimulus asynchrony confirmed the importance of temporal relation implicit in Hebb's principle: for the synapse to be potentiated or depressed, the presynaptic neuron has to fire just before or just after the postsynaptic neuron, respectively. In addition, it has become evident that the presynaptic neural firing needs to consistently predict the postsynaptic firing for synaptic plasticity to occur robustly, mirroring at a synaptic level what is known about the importance of contingency in classical conditioning, where zero contingency procedures prevent the association between two stimuli.

根据赫布定律，如果突触持续参与触发突触后靶神经元，突触的效率就会提高。类似地，当突触前目标的激活持续独立于突触后目标的激活时，突触的效率降低。这些原则在记忆法中经常被简化: 那些一起开火的人，连接在一起; 而那些不同步开火的人，失去了他们之间的联系。然而，如果两个神经元同时激活，那么一个神经元就不可能引发或参与激活另一个神经元。相反，为了参与刺激突触后神经元，突触前神经元需要在突触后神经元之前刺激。刺激两个连接的神经元的实验证实了 Hebb 原理中时间关系的重要性: 要使突触增强或抑制，突触前神经元必须分别在突触后神经元之前或之后触发。此外，已经很明显的是突触前神经放电需要持续稳定地预测突触后放电发生的突触可塑性，在突触水平上反映了已知的经典条件反射的重要性，在那里零突变程序阻止了两个刺激之间的联系。

Role in hippocampal learning

Role in hippocampal learning

= 在海马学习中的作用 =

For the most efficient STDP, the presynaptic and postsynaptic signal has to be separated by approximately a dozen of milliseconds. However, events happening within a couple of minutes can typically be linked together by the hippocampus as episodic memories. To resolve this contradiction, a mechanism relying on the theta waves and the phase precession has been proposed: Representations of different memory entities (such as a place, face, person etc.) are repeated on each theta cycle at a given theta phase during the episode to be remembered. Expected, ongoing, and completed entities have early, intermediate and late theta phases, respectively. In the CA3 region of the hippocampus, the recurrent network turns entities with neighboring theta phases into coincident ones thereby allowing STDP to link them together. Experimentally detectable memory sequences are created this way by reinforcing the connection between subsequent (neighboring) representations. [13]

对于最有效的STDP，突触前和突触后信号必须被间隔大约12毫秒。然而，在几分钟内发生的事件通常可以被海马体联系在一起作为情景记忆。为了解决这一矛盾，人们提出了一种依赖于θ波和相位进动的机制:不同记忆实体(如一个地方、脸、人等)的表征在要记忆的情节中，在给定的θ相位的每个θ循环上重复。预期的、正在进行的和完成的实体分别有早期、中期和后期的θ阶段。在海马体的CA3区域，循环网络将相邻的θ相位的实体转化为一致的，从而允许STDP将它们连接在一起。实验上可检测到的记忆序列是通过加强后续(邻近)表示之间的联系而创建的。

For the most efficient STDP, the presynaptic and postsynaptic signal has to be separated by approximately a dozen of milliseconds. However, events happening within a couple of minutes can typically be linked together by the hippocampus as episodic memories. To resolve this contradiction, a mechanism relying on the theta waves and the phase precession has been proposed: Representations of different memory entities (such as a place, face, person etc.) are repeated on each theta cycle at a given theta phase during the episode to be remembered. Expected, ongoing, and completed entities have early, intermediate and late theta phases, respectively. In the CA3 region of the hippocampus, the recurrent network turns entities with neighboring theta phases into coincident ones thereby allowing STDP to link them together. Experimentally detectable memory sequences are created this way by reinforcing the connection between subsequent (neighboring) representations.

对于最有效的 STDP，突触前和突触后信号必须被大约12毫秒分开。然而，在几分钟内发生的事件通常可以通过海马体联系在一起，形成情景记忆。为了解决这一矛盾，提出了一种依赖于 θ 波和相进动的机制: 不同记忆实体(如地点、面孔、人等)的表征在每个 θ 周期的某个给定的 θ 阶段重复出现，以便被记住。预期的、正在进行的和已完成的实体分别有早期、中期和晚期 theta 阶段。在海马的 ca3区域，循环网络将具有相邻 θ 相位的实体转变为相同的实体，从而使 STDP 将它们连接在一起。通过加强后续(相邻)表示之间的联系，实验可检测的存储序列就是这样产生的。

Uses in artificial neural networks

The concept of STDP has been shown to be a proven learning algorithm for forward-connected artificial neural networks in pattern recognition. Recognising traffic,[14] sound or movement using Dynamic Vision Sensor (DVS) cameras has been an area of research.[15][16] Correct classifications with a high degree of accuracy with only minimal learning time has been shown. It was shown that a spiking neuron trained with STDP learns a linear model of a dynamic system with minimal least square error.[17]

STDP的概念已被证明是一种有效的模式识别前向连接人工神经网络的学习算法。利用动态视觉传感器(DVS)摄像机识别交通、声音或运动已经成为一个研究领域。正确的分类与高度的准确性，只有最少的学习时间已被显示。结果表明，STDP训练的脉冲神经元能够以最小二乘误差学习动态系统的线性模型。

The concept of STDP has been shown to be a proven learning algorithm for forward-connected artificial neural networks in pattern recognition. Recognising traffic, sound or movement using Dynamic Vision Sensor (DVS) cameras has been an area of research. Correct classifications with a high degree of accuracy with only minimal learning time has been shown. It was shown that a spiking neuron trained with STDP learns a linear model of a dynamic system with minimal least square error.

在人工神经网络中的应用已被证明是前向连接人工神经网络在模式识别中的一种行之有效的学习算法。使用动态视觉传感器(DVS)摄像机识别交通、声音或运动一直是研究领域。正确的分类具有高度的准确性和只有最小的学习时间已经显示。结果表明，经过 STDP 训练的脉冲神经元学习动态系统的线性模型，其最小二乘误差最小。

A general approach, replicated from the core biological principles, is to apply a window function (Δw) to each synapse in a network. The window function will increase the weight (and therefore the connection) of a synapse when the parent neuron fires just before the child neuron, but will decrease otherwise.[18]

从核心生物学原理复制而来的一种通用方法是将窗口函数(Δw)应用到网络中的每个突触上。当父神经元在子神经元之前触发时，窗口函数会增加突触的权重(因此也会增加突触的连接)，但反之则会减少。

A general approach, replicated from the core biological principles, is to apply a window function (Δw) to each synapse in a network. The window function will increase the weight (and therefore the connection) of a synapse when the parent neuron fires just before the child neuron, but will decrease otherwise.

从核心生物学原理复制出来的一个通用方法是对网络中的每个突触应用一个窗口函数(δw)。当父神经元在子神经元之前触发时，窗口函数将增加突触的重量(因此也会增加突触的连接) ，但是否则会减少。

Several variations of the window function have been proposed to allow for a range of learning speeds and classification accuracy.[19]

窗口函数的几个变化已被提出，以允许一个范围的学习速度和分类精度。

Several variations of the window function have been proposed to allow for a range of learning speeds and classification accuracy.

一些窗函数的变化已经被提出，以允许一个范围的学习速度和分类的准确性。

See also

See also

= 参见 =

  • Synaptic plasticity
  • Didactic organisation


  • Synaptic plasticity
  • Didactic organisation

References

  1. ↑ 1.0 1.1 Taylor MM (1973). "The Problem of Stimulus Structure in the Behavioural Theory of Perception". South African Journal of Psychology. 3: 23–45.
  2. ↑ Levy WB, Steward O (April 1983). "Temporal contiguity requirements for long-term associative potentiation/depression in the hippocampus". Neuroscience. 8 (4): 791–7. CiteSeerX 10.1.1.365.5814. doi:10.1016/0306-4522(83)90010-6. PMID 6306504. S2CID 16184572. [1]
  3. ↑ Dan Y, Poo MM (1992). "Hebbian depression of isolated neuromuscular synapses in vitro". Science. 256 (5063): 1570–73. Bibcode:1992Sci...256.1570D. doi:10.1126/science.1317971. PMID 1317971.
  4. ↑ Debanne D, Gähwiler B, Thompson S (1994). "Asynchronous pre- and postsynaptic activity induces associative long-term depression in area CA1 of the rat hippocampus in vitro". Proceedings of the National Academy of Sciences of the United States of America. 91 (3): 1148–52. Bibcode:1994PNAS...91.1148D. doi:10.1073/pnas.91.3.1148. PMC 521471. PMID 7905631.
  5. ↑ Markram H, Lübke J, Frotscher M, Sakmann B (January 1997). "Regulation of synaptic efficacy by coincidence of postsynaptic APs and EPSPs" (PDF). Science. 275 (5297): 213–5. doi:10.1126/science.275.5297.213. PMID 8985014. S2CID 46640132.
  6. ↑ Bi GQ, Poo MM (15 December 1998). "Synaptic modifications in cultured hippocampal neurons: dependence on spike timing, synaptic strength, and postsynaptic cell type". Journal of Neuroscience. 18 (24): 10464–72. doi:10.1523/JNEUROSCI.18-24-10464.1998. PMC 6793365. PMID 9852584.
  7. ↑ Gerstner W, Kempter R, van Hemmen JL, Wagner H (September 1996). "A neuronal learning rule for sub-millisecond temporal coding". Nature. 383 (6595): 76–78. Bibcode:1996Natur.383...76G. doi:10.1038/383076a0. PMID 8779718. S2CID 4319500.
  8. ↑ Song S, Miller KD, Abbott LF (September 2000). "Competitive Hebbian learning through spike-timing-dependent synaptic plasticity". Nature Neuroscience. 3 (9): 919–26. doi:10.1038/78829. PMID 10966623. S2CID 9530143.
  9. ↑ Meliza CD, Dan Y (2006), "Receptive-field modification in rat visual cortex induced by paired visual stimulation and single-cell spiking", Neuron, 49 (2): 183–189, doi:10.1016/j.neuron.2005.12.009, PMID 16423693
  10. ↑ Sjöström, Per Jesper; Turrigiano, Gina G; Nelson, Sacha B (2003-08-14). "Neocortical LTD via Coincident Activation of Presynaptic NMDA and Cannabinoid Receptors". Neuron (in English). 39 (4): 641–654. doi:10.1016/S0896-6273(03)00476-8. PMID 12925278. S2CID 9111561.
  11. ↑ Caporale N.; Dan Y. (2008). "Spike timing-dependent plasticity: a Hebbian learning rule". Annual Review of Neuroscience. 31: 25–46. doi:10.1146/annurev.neuro.31.060407.125639. PMID 18275283.
  12. ↑ Bauer E. P.; LeDoux J. E.; Nader K. (2001). "Fear conditioning and LTP in the lateral amygdala are sensitive to the same stimulus contingencies". Nature Neuroscience. 4 (7): 687–688. doi:10.1038/89465. PMID 11426221. S2CID 33130204.
  13. ↑ Kovács KA (September 2020). "Episodic Memories: How do the Hippocampus and the Entorhinal Ring Attractors Cooperate to Create Them?". Frontiers in Systems Neuroscience. 14: 68. doi:10.3389/fnsys.2020.559186. PMC 7511719. PMID 33013334.
  14. ↑ Bichler, Olivier; Querlioz, Damien; Thorpe, Simon J.; Bourgoin, Jean-Philippe; Gamrat, Christian (22 Feb 2012). "Extraction of temporally correlated features from dynamic vision sensors with spike-timing-dependent plasticity". Neural Networks. 32: 339–348. doi:10.1016/j.neunet.2012.02.022. PMID 22386501.
  15. ↑ Thorpe, Simon J. (2012). "Spike-Based Image Processing: Can We Reproduce Biological Vision in Hardware?". In Fusiello, Andrea; Murino, Vittorio; Cucchiara, Rita. Lecture Notes in Computer Science. 7583. Springer Berlin Heidelberg. pp. 516–521. doi:10.1007/978-3-642-33863-2_53. ISBN 978-3-642-33862-5. 
  16. ↑ O'Connor, Peter; Neil, Daniel; Liu, Shih-Chii; Delbruck, Tobi; Pfeiffer, Michael (2013). "Real-time classification and sensor fusion with a spiking deep belief network". Frontiers in Neuroscience. 7: 178. doi:10.3389/fnins.2013.00178. PMC 3792559. PMID 24115919.
  17. ↑ Suri, Roland E. (2004). "A computational framework for cortical learning" (PDF). Biological Cybernetics (in English). 90 (6): 400–9. doi:10.1007/s00422-004-0487-1. hdl:20.500.11850/64482. ISSN 0340-1200. PMID 15316786. S2CID 2745163.
  18. ↑ Ratanamahatana, Chotirat Ann; Keogh, Eamonn (22 April 2004). "Making Time-series Classification More Accurate Using Learned Constraints". Proceedings of the 2004 SIAM International Conference on Data Mining: 11–22. doi:10.1137/1.9781611972740.2. {{cite journal}}: |access-date= requires |url= (help)
  19. ↑ Ratanamahatana, Chotirat Ann; Keogh, Eamonn (22 April 2004). "Making Time-series Classification More Accurate Using Learned Constraints". Proceedings of the 2004 SIAM International Conference on Data Mining: 11–22. doi:10.1137/1.9781611972740.2. {{cite journal}}: |access-date= requires |url= (help)

Further reading

Further reading

= 进一步阅读 =


External links

  • Spike-timing dependent plasticity - Scholarpedia

= 外部链接 =

  • 依赖于脉冲时间的可塑性-学者百科


Category:Neuroplasticity Category:Memory

类别: 神经可塑性类别: 记忆


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