Unifying Long-Term Plasticity Rules for Excitatory Synapses by Modeling Dendrites of Cortical Pyramidal Neurons

被引:36
|
作者
Ebner, Christian [1 ,2 ,3 ,4 ]
Clopath, Claudia [5 ]
Jedlicka, Peter [1 ,6 ,7 ]
Cuntz, Hermann [1 ,2 ]
机构
[1] Frankfurt Inst Adv Studies, D-60438 Frankfurt, Germany
[2] Max Planck Gesell, Ernst Strungmann Inst ESI Neurosci Cooperat, D-60528 Frankfurt, Germany
[3] Charite Univ Med Berlin, NeuroCure Cluster Excellence, D-10117 Berlin, Germany
[4] Humboldt Univ, Inst Biol, D-10117 Berlin, Germany
[5] Imperial Coll London, Bioengn Dept, Computat Neurosci Lab, London SW7 2AZ, England
[6] Goethe Univ Frankfurt, Neurosci Ctr, Inst Clin Neuroanat, D-60528 Frankfurt, Germany
[7] Justus Liebig Univ, Fac Med, ICAR3R Interdisciplinary Ctr 3Rs Anim Res, D-35392 Giessen, Germany
来源
CELL REPORTS | 2019年 / 29卷 / 13期
基金
英国生物技术与生命科学研究理事会; 英国工程与自然科学研究理事会; 英国惠康基金;
关键词
TIMING-DEPENDENT PLASTICITY; SYNAPTIC PLASTICITY; CELLULAR MECHANISM; NMDA; COINCIDENCE; CALMODULIN; DEPRESSION; SPIKES; POTENTIATION; SENSITIVITY;
D O I
10.1016/j.celrep.2019.11.068
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
A large number of experiments have indicated that precise spike times, firing rates, and synapse locations crucially determine the dynamics of long-term plasticity induction in excitatory synapses. However, it remains unknown how plasticity mechanisms of synapses distributed along dendritic trees cooperate to produce the wide spectrum of outcomes for various plasticity protocols. Here, we propose a four-pathway plasticity framework that is well grounded in experimental evidence and apply it to a biophysically realistic cortical pyramidal neuron model. We show in computer simulations that several seemingly contradictory experimental landmark studies are consistent with one unifying set of mechanisms when considering the effects of signal propagation in dendritic trees with respect to synapse location. Our model identifies specific spatiotemporal contributions of dendritic and axo-somatic spikes as well as of subthreshold activation of synaptic clusters, providing a unified parsimonious explanation not only for rate and timing dependence but also for location dependence of synaptic changes.
引用
收藏
页码:4295 / +
页数:19
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