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模拟活体中放电型加压素细胞的尖峰活动。

Modelling the in vivo spike activity of phasically-firing vasopressin cells.

机构信息

Institute of Integrated Micro and Nano Systems, University of Edinburgh, Edinburgh, UK.

出版信息

J Neuroendocrinol. 2010 Dec;22(12):1290-300. doi: 10.1111/j.1365-2826.2010.02080.x.

DOI:10.1111/j.1365-2826.2010.02080.x
PMID:21083630
Abstract

A minimalist model of magnocellular vasopressin neurones was developed to examine the hypothesis that their phasic behaviour is the product of intrinsic voltage- and activity-dependent intracellular mechanisms that create a bistable dynamical system. The model can closely match a range of phasic behaviours recorded in vasopressin cells in vivo, as well as reproduce the three archetypal behaviours of vasopressin cells (continuous firing, sparse sporadic firing and phasic firing) by varying one of the fourteen model parameters. In addition, the mean and standard deviation of burst and silence periods can be matched by varying a further two parameters. In the model, the long-term behaviour (phasic characteristics) of cells is largely independent of the short-term behaviour (interspike intervals).

摘要

开发了一个简化的大细胞加压素神经元模型,以检验其假设,即它们的脉冲行为是内在电压和活动依赖性细胞内机制的产物,这些机制创建了一个双稳态动力学系统。该模型可以很好地匹配体内加压素细胞记录的一系列脉冲行为,并且通过改变 14 个模型参数中的一个,还可以再现加压素细胞的三种典型行为(连续放电、稀疏散发性放电和脉冲放电)。此外,通过进一步改变两个参数,可以匹配爆发和静止期的平均值和标准偏差。在该模型中,细胞的长期行为(脉冲特征)在很大程度上独立于短期行为(脉冲间隔)。

相似文献

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Modelling the in vivo spike activity of phasically-firing vasopressin cells.模拟活体中放电型加压素细胞的尖峰活动。
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引用本文的文献

1
Phasic spiking in vasopressin neurons: How and Why.血管加压素神经元的相位尖峰:如何及为何。
J Neuroendocrinol. 2021 Nov;33(11):e13042. doi: 10.1111/jne.13042. Epub 2021 Nov 8.
2
Spike patterning in oxytocin neurons: Capturing physiological behaviour with Hodgkin-Huxley and integrate-and-fire models.催产素神经元中的尖峰模式:用霍奇金-赫胥黎模型和积分发放模型捕捉生理行为。
PLoS One. 2017 Jul 6;12(7):e0180368. doi: 10.1371/journal.pone.0180368. eCollection 2017.
3
Information coding in vasopressin neurons--the role of asynchronous bistable burst firing.
血管加压素神经元中的信息编码——异步双稳爆发式放电的作用。
Biosystems. 2013 May;112(2):85-93. doi: 10.1016/j.biosystems.2013.03.010. Epub 2013 Mar 14.
4
Models of electrical activity: calibration and prediction testing on the same cell.电活动模型:同一细胞的校准和预测测试。
Biophys J. 2012 Nov 7;103(9):2021-32. doi: 10.1016/j.bpj.2012.09.034.
5
Phasic firing in vasopressin cells: understanding its functional significance through computational models.血管加压素细胞的相位性放电:通过计算模型理解其功能意义。
PLoS Comput Biol. 2012;8(10):e1002740. doi: 10.1371/journal.pcbi.1002740. Epub 2012 Oct 18.
6
Quantitative prediction of vasopressin secretion using a computational population model of rat magnocellular neurons.使用大鼠大细胞神经元计算群体模型对血管加压素分泌进行定量预测。
J Comput Neurosci. 2012 Dec;33(3):533-45. doi: 10.1007/s10827-012-0399-3. Epub 2012 Jun 12.