Hebbian plasticity means that if the firing of two neurons is correlated, then their connection is strengthened. Conversely, uncorrelated firing causes a decrease in synaptic strength. Spike-timing-dependent plasticity (STDP) represents one instantiation of Hebbian plasticity. Under STDP, synaptic changes depend on the relative timing of the pre- and post-synaptic firing. By inducing pre- and post-synaptic firing at different relative times the STDP curves of many neurons have been determined, and it has been found that there are different curves for different neuron types or synaptic sites. Biophysically, strengthening (long-term potentiation, LTP) or weakening (long-term depression, LTD) of glutamatergic synapses depends on the post-synaptic influx of calcium (Ca²⁺): weak influx leads to LTD, while strong, transient influx causes LTP. The voltage-dependent NMDA receptors are the main source of Ca²⁺ influx, but they will only open if a post-synaptic depolarisation coincides with pre-synaptic neurotransmitter release. Here we present a computational mechanism for Ca²⁺-dependent plasticity in which the interplay between the pre-synaptic neurotransmitter release and the post-synaptic membrane potential leads to distinct Ca²⁺ time-courses, which in turn lead to the change in synaptic strength. It is shown that the model complies with classic STDP results, as well as with results obtained with triplets of spikes. Furthermore, the model is capable of displaying different shapes of STDP curves, as observed in different experimental studies.

中文翻译：

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钙流入依赖的可塑性模型表现出多个STDP曲线。

赫比的可塑性意味着，如果两个神经元的激发相关，那么它们的联系就会增强。相反，不相关的射击会导致突触强度降低。依赖于尖峰时间的可塑性（STDP）代表了Hebbian可塑性的一种实例。在STDP下，突触的变化取决于突触前和突触后发射的相对时间。通过在不同的相对时间诱导突触前和突触后放电，已经确定了许多神经元的STDP曲线，并且发现对于不同的神经元类型或突触部位有不同的曲线。从生物学上讲，谷氨酸能突触的增强（长期增强，LTP）或减弱（长期抑制，LTD）取决于突触后钙的流入（Ca ²⁺）：弱流入会导致LTD，而强而短暂的流入会导致LTP。电压依赖性NMDA受体是C a ²⁺大量涌入的主要来源，但是只有在突触后去极化与突触前神经递质释放同时发生时，它们才会打开。在这里，我们介绍了一种依赖于C a ^2+的可塑性的计算机制，其中突触前神经递质释放与突触后膜电位之间的相互作用导致截然不同的C a ²⁺时间过程，从而导致突触强度的变化。结果表明，该模型符合经典的STDP结果以及三重峰的结果。此外，如在不同的实验研究中所观察到的，该模型能够显示不同形状的STDP曲线。