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躯体抑制和树突抑制之间的相互作用促进了位置场的出现和稳定。

The interplay between somatic and dendritic inhibition promotes the emergence and stabilization of place fields.

机构信息

Department of Bioengineering, Imperial College London, London, United Kingdom.

CAPES Foundation, Ministry of Education of Brazil, Brasilia - DF, Brazil.

出版信息

PLoS Comput Biol. 2020 Jul 10;16(7):e1007955. doi: 10.1371/journal.pcbi.1007955. eCollection 2020 Jul.

DOI:10.1371/journal.pcbi.1007955
PMID:32649658
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7386595/
Abstract

During the exploration of novel environments, place fields are rapidly formed in hippocampal CA1 neurons. Place cell firing rate increases in early stages of exploration of novel environments but returns to baseline levels in familiar environments. Although similar in amplitude and width, place fields in familiar environments are more stable than in novel environments. We propose a computational model of the hippocampal CA1 network, which describes the formation, dynamics and stabilization of place fields. We show that although somatic disinhibition is sufficient to form place fields, dendritic inhibition along with synaptic plasticity is necessary for place field stabilization. Our model suggests that place cell stability can be attributed to strong excitatory synaptic weights and strong dendritic inhibition. We show that the interplay between somatic and dendritic inhibition balances the increased excitatory weights, such that place cells return to their baseline firing rate after exploration. Our model suggests that different types of interneurons are essential to unravel the mechanisms underlying place field plasticity. Finally, we predict that artificially induced dendritic events can shift place fields even after place field stabilization.

摘要

在探索新环境时,海马 CA1 神经元中会迅速形成位置场。在探索新环境的早期阶段,位置细胞的放电率会增加,但在熟悉的环境中会恢复到基线水平。尽管幅度和宽度相似,但熟悉环境中的位置场比新环境中的位置场更稳定。我们提出了一个海马 CA1 网络的计算模型,该模型描述了位置场的形成、动态和稳定。我们表明,虽然体细胞去抑制足以形成位置场,但树突抑制以及突触可塑性对于位置场的稳定是必要的。我们的模型表明,位置细胞的稳定性可以归因于强兴奋性突触权重和强树突抑制。我们表明,体细胞和树突抑制之间的相互作用平衡了增加的兴奋性权重,使得位置细胞在探索后恢复到基线放电率。我们的模型表明,不同类型的中间神经元对于揭示位置场可塑性的机制是必不可少的。最后,我们预测,即使在位置场稳定后,人工诱导的树突事件也可以转移位置场。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/149a/7386595/545b8116f397/pcbi.1007955.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/149a/7386595/b4cad392b61f/pcbi.1007955.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/149a/7386595/091eaf9b5282/pcbi.1007955.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/149a/7386595/20193814bc7e/pcbi.1007955.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/149a/7386595/d4a37afb5cae/pcbi.1007955.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/149a/7386595/545b8116f397/pcbi.1007955.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/149a/7386595/b4cad392b61f/pcbi.1007955.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/149a/7386595/091eaf9b5282/pcbi.1007955.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/149a/7386595/20193814bc7e/pcbi.1007955.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/149a/7386595/d4a37afb5cae/pcbi.1007955.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/149a/7386595/545b8116f397/pcbi.1007955.g005.jpg

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