低维放电率模型预测的神经元群体中强直性和相位性放电之间转换的解释机制
Mechanisms explaining transitions between tonic and phasic firing in neuronal populations as predicted by a low dimensional firing rate model
摘要:
在神经元群体中实验观察到的几种放电模式已经成功地与动物行为相关联。群体爆发,在此被认为是一段时间的高放电率,随后是一段时间的静止,通常是在行为期间的神经元组中观察到的。单细胞爆发的生物物理膜电位模型至少涉及三个方程。扩展这样的模型来研究神经元群体的集体行为涉及数千个方程,并且在计算上可能非常昂贵。出于这个原因,低维人口模型,捕捉生物物理方面的网络是必要的。\noindent本论文使用一个放电率模型来研究触发和停止紧张性和相位性群体放电之间的转换的机制。这些机制是通过二维系统捕获的,该系统可以潜在地扩展到包括神经系统的不同区域之间的相互作用,并且具有少量的方程。在啮齿类动物中脑多巴胺能神经元的典型行为被用来作为一个例子来说明和解释我们的结果。\noindent这里提出的模型可以用作研究神经元网络之间相互作用的构建块。这种理论方法可能有助于了解和理解调节群体爆发性放电的因素,以及它如何调节行为的不同方面。
英文摘要:
Several firing patterns experimentally observed in neural populations have been successfully correlated to animal behavior. Population bursting, hereby regarded as a period of high firing rate followed by a period of quiescence, is typically observed in groups of neurons during behavior. Biophysical membrane-potential models of single cell bursting involve at least three equations. Extending such models to study the collective behavior of neural populations involves thousands of equations and can be very expensive computationally. For this reason, low dimensional population models that capture biophysical aspects of networks are needed. \noindent The present paper uses a firing-rate model to study mechanisms that trigger and stop transitions between tonic and phasic population firing. These mechanisms are captured through a two-dimensional system, which can potentially be extended to include interactions between different areas of the nervous system with a small number of equations. The typical behavior of midbrain dopaminergic neurons in the rodent is used as an example to illustrate and interpret our results. \noindent The model presented here can be used as a building block to study interactions between networks of neurons. This theoretical approach may help contextualize and understand the factors involved in regulating burst firing in populations and how it may modulate distinct aspects of behavior.
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