Suppr超能文献

体内膜电位动力学预测的峰值阈值适应性。

Spike-threshold adaptation predicted by membrane potential dynamics in vivo.

作者信息

Fontaine Bertrand, Peña José Luis, Brette Romain

机构信息

Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York, United States of America.

Laboratoire Psychologie de la Perception, CNRS and Université Paris Descartes, Paris, France; Département d'Etudes Cognitives, Ecole Normale Supérieure, Paris, France; Sorbonne Universités, UPMC Univ. Paris 06, UMR_S 968, Institut de la Vision, Paris, France; INSERM, U968, Paris, France; CNRS, UMR_7210, Paris, France.

出版信息

PLoS Comput Biol. 2014 Apr 10;10(4):e1003560. doi: 10.1371/journal.pcbi.1003560. eCollection 2014 Apr.

Abstract

Neurons encode information in sequences of spikes, which are triggered when their membrane potential crosses a threshold. In vivo, the spiking threshold displays large variability suggesting that threshold dynamics have a profound influence on how the combined input of a neuron is encoded in the spiking. Threshold variability could be explained by adaptation to the membrane potential. However, it could also be the case that most threshold variability reflects noise and processes other than threshold adaptation. Here, we investigated threshold variation in auditory neurons responses recorded in vivo in barn owls. We found that spike threshold is quantitatively predicted by a model in which the threshold adapts, tracking the membrane potential at a short timescale. As a result, in these neurons, slow voltage fluctuations do not contribute to spiking because they are filtered by threshold adaptation. More importantly, these neurons can only respond to input spikes arriving together on a millisecond timescale. These results demonstrate that fast adaptation to the membrane potential captures spike threshold variability in vivo.

摘要

神经元通过一系列的尖峰脉冲来编码信息,当它们的膜电位超过阈值时就会触发尖峰脉冲。在体内,尖峰阈值表现出很大的变异性,这表明阈值动态对神经元的综合输入如何在尖峰脉冲中编码有着深远的影响。阈值变异性可以通过对膜电位的适应来解释。然而,也有可能大多数阈值变异性反映的是噪声以及除阈值适应之外的其他过程。在这里,我们研究了仓鸮体内记录的听觉神经元反应中的阈值变化。我们发现,尖峰阈值可以通过一个模型进行定量预测,在该模型中,阈值会适应并在短时间尺度上跟踪膜电位。因此,在这些神经元中,缓慢的电压波动不会导致尖峰脉冲,因为它们被阈值适应过滤掉了。更重要的是,这些神经元只能对在毫秒时间尺度上一起到达的输入尖峰做出反应。这些结果表明,对膜电位的快速适应捕捉了体内尖峰阈值的变异性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dd2/3983065/e40f7c40047d/pcbi.1003560.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