GluN2B-NMDAR亚基对突触可塑性的贡献:CA3-CA1突触的现象学模型。

IF 2.8 4区 医学 Q2 NEUROSCIENCES
Justinas J Dainauskas, Hélène Marie, Michele Migliore, Ausra Saudargiene
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引用次数: 1

摘要

突触可塑性被认为是学习和记忆的关键机制。我们建立了基于n -甲基-d -天冬氨酸(NMDA)受体的现象学电位依赖性突触可塑性模型,研究海马CA1锥体神经元上CA3-CA1突触的突触修饰。该模型结合了GluN2A-NMDA和GluN2B-NMDA受体亚基功能,并解释了突触强度依赖于突触后NMDA受体组成和功能,而没有明确模拟NMDA受体介导的细胞内钙,这是突触可塑性的局部触发因素。我们将该模型嵌入到海马CA1锥体细胞的双室模型中,并通过高频和低频刺激的spike- time -dependent synaptic plasticity (STDP)实验数据对其进行验证。该模型预测了在GluN2B-NMDA受体功能减退的情况下,CA1锥体神经元详细室室模型顶端树突上形成的突触学习规则的改变,并可用于海马体网络,以模拟健康和疾病中的学习。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

GluN2B-NMDAR subunit contribution on synaptic plasticity: A phenomenological model for CA3-CA1 synapses.

GluN2B-NMDAR subunit contribution on synaptic plasticity: A phenomenological model for CA3-CA1 synapses.

GluN2B-NMDAR subunit contribution on synaptic plasticity: A phenomenological model for CA3-CA1 synapses.

GluN2B-NMDAR subunit contribution on synaptic plasticity: A phenomenological model for CA3-CA1 synapses.

Synaptic plasticity is believed to be a key mechanism underlying learning and memory. We developed a phenomenological N-methyl-D-aspartate (NMDA) receptor-based voltage-dependent synaptic plasticity model for synaptic modifications at hippocampal CA3-CA1 synapses on a hippocampal CA1 pyramidal neuron. The model incorporates the GluN2A-NMDA and GluN2B-NMDA receptor subunit-based functions and accounts for the synaptic strength dependence on the postsynaptic NMDA receptor composition and functioning without explicitly modeling the NMDA receptor-mediated intracellular calcium, a local trigger of synaptic plasticity. We embedded the model into a two-compartmental model of a hippocampal CA1 pyramidal cell and validated it against experimental data of spike-timing-dependent synaptic plasticity (STDP), high and low-frequency stimulation. The developed model predicts altered learning rules in synapses formed on the apical dendrites of the detailed compartmental model of CA1 pyramidal neuron in the presence of the GluN2B-NMDA receptor hypofunction and can be used in hippocampal networks to model learning in health and disease.

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来源期刊
CiteScore
7.10
自引率
2.70%
发文量
74
审稿时长
14 weeks
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