Tomko Matus, Benuskova Lubica, Jedlicka Peter
Centre of Biosciences, Institute of Molecular Physiology and Genetics, Slovak Academy of Sciences, Dubravska cesta 9, Bratislava, 840 05, Slovakia.
Faculty of Medicine, Institute of Medical Physics and Biophysics, Comenius University Bratislava, Bratislava, Slovakia.
J Comput Neurosci. 2024 May;52(2):125-131. doi: 10.1007/s10827-024-00868-0. Epub 2024 Mar 12.
Long-term potentiation (LTP) is a synaptic mechanism involved in learning and memory. Experiments have shown that dendritic sodium spikes (Na-dSpikes) are required for LTP in the distal apical dendrites of CA1 pyramidal cells. On the other hand, LTP in perisomatic dendrites can be induced by synaptic input patterns that can be both subthreshold and suprathreshold for Na-dSpikes. It is unclear whether these results can be explained by one unifying plasticity mechanism. Here, we show in biophysically and morphologically realistic compartmental models of the CA1 pyramidal cell that these forms of LTP can be fully accounted for by a simple plasticity rule. We call it the voltage-based Event-Timing-Dependent Plasticity (ETDP) rule. The presynaptic event is the presynaptic spike or release of glutamate. The postsynaptic event is the local depolarization that exceeds a certain plasticity threshold. Our model reproduced the experimentally observed LTP in a variety of protocols, including local pharmacological inhibition of dendritic spikes by tetrodotoxin (TTX). In summary, we have provided a validation of the voltage-based ETDP, suggesting that this simple plasticity rule can be used to model even complex spatiotemporal patterns of long-term synaptic plasticity in neuronal dendrites.
长时程增强(LTP)是一种参与学习和记忆的突触机制。实验表明,树突状钠峰电位(Na-峰电位)是CA1锥体细胞远端顶端树突中LTP所必需的。另一方面,胞体周围树突中的LTP可由对Na-峰电位既可以是阈下也可以是阈上的突触输入模式诱导产生。目前尚不清楚这些结果是否可以用一种统一的可塑性机制来解释。在这里,我们在CA1锥体细胞的生物物理和形态学逼真的房室模型中表明,这些形式的LTP可以通过一个简单的可塑性规则得到充分解释。我们将其称为基于电压的事件时间依赖性可塑性(ETDP)规则。突触前事件是突触前峰电位或谷氨酸的释放。突触后事件是超过某个可塑性阈值的局部去极化。我们的模型在各种实验方案中重现了实验观察到的LTP,包括用河豚毒素(TTX)对树突峰电位进行局部药理学抑制。总之,我们对基于电压的ETDP进行了验证,表明这个简单的可塑性规则可用于模拟神经元树突中甚至复杂的长期突触可塑性时空模式。