Suppr超能文献

突触强度、短期可塑性和输入同步如何促进神经元尖峰输出。

How synaptic strength, short-term plasticity, and input synchrony contribute to neuronal spike output.

机构信息

Institute of Neuroinformatics, University of Zürich and ETH Zürich, Zürich, Switzerland.

Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts, United States of America.

出版信息

PLoS Comput Biol. 2023 Apr 17;19(4):e1011046. doi: 10.1371/journal.pcbi.1011046. eCollection 2023 Apr.

Abstract

Neurons integrate from thousands of synapses whose strengths span an order of magnitude. Intriguingly, in mouse neocortex, the few 'strong' synapses are formed between similarly tuned cells, suggesting they determine spiking output. This raises the question of how other computational primitives, including 'background' activity from the many 'weak' synapses, short-term plasticity, and temporal factors contribute to spiking. We used paired recordings and extracellular stimulation experiments to map excitatory postsynaptic potential (EPSP) amplitudes and paired-pulse ratios of synaptic connections formed between pyramidal neurons in layer 2/3 (L2/3) of barrel cortex. While net short-term plasticity was weak, strong synaptic connections were exclusively depressing. Importantly, we found no evidence for clustering of synaptic properties on individual neurons. Instead, EPSPs and paired-pulse ratios of connections converging onto the same cells spanned the full range observed across L2/3, which critically constrains theoretical models of cortical filtering. To investigate how different computational primitives of synaptic information processing interact to shape spiking, we developed a computational model of a pyramidal neuron in the excitatory L2/3 circuitry, which was constrained by our experiments and published in vivo data. We found that strong synapses were substantially depressed during ongoing activation and their ability to evoke correlated spiking primarily depended on their high temporal synchrony and high firing rates observed in vivo. However, despite this depression, their larger EPSP amplitudes strongly amplified information transfer and responsiveness. Thus, our results contribute to a nuanced framework of how cortical neurons exploit synergies between temporal coding, synaptic properties, and noise to transform synaptic inputs into spikes.

摘要

神经元整合来自数千个突触的信息,这些突触的强度跨度为一个数量级。有趣的是,在小鼠新皮层中,少数“强”突触形成于具有相似调谐的细胞之间,这表明它们决定了放电输出。这就提出了一个问题,即其他计算基元(包括来自许多“弱”突触的“背景”活动、短期可塑性和时间因素)如何有助于放电。我们使用成对记录和细胞外刺激实验,绘制了桶状皮层 2/3 层(L2/3)中锥体神经元之间形成的兴奋性突触后电位(EPSP)幅度和突触连接的成对脉冲比。虽然净短期可塑性较弱,但强突触连接是完全抑制性的。重要的是,我们没有发现单个神经元上突触特性聚类的证据。相反,汇聚到同一细胞的连接的 EPSP 和成对脉冲比跨越了 L2/3 中观察到的整个范围,这对皮层滤波的理论模型具有关键限制。为了研究突触信息处理的不同计算基元如何相互作用以形成放电,我们开发了一个兴奋性 L2/3 电路中锥体神经元的计算模型,该模型受到我们实验和已发表的体内数据的限制。我们发现,在持续激活期间,强突触被显著抑制,它们引发相关放电的能力主要取决于它们在体内观察到的高时间同步性和高 firing rate。然而,尽管存在这种抑制,它们更大的 EPSP 幅度强烈放大了信息传递和响应性。因此,我们的研究结果为皮质神经元如何利用时间编码、突触特性和噪声之间的协同作用将突触输入转化为尖峰提供了一个细致的框架。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9931/10153727/d6002fc74c05/pcbi.1011046.g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验