A Study of How Abnormalities of the CREB Protein Affect a Neuronal System and Its Signals: Modeling and Analysis Using Experimental Data

A. Emadi, A. Abdi
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引用次数: 2

Abstract

It is well understood that the CREB protein is highly involved in neuronal mechanisms underlying memory and learning in mammalian brain, and deficiencies in CREB activity can result in transition to certain pathological conditions. In this paper, we use some published experimental data, along with a neuronal system composed of the Izhikevich neuron model, to characterize how CREB abnormalities can alter neuronal signals and the system behavior. The abnormal data are extracted from intracellular recordings collected from the neurons of transgenic mice expressing VP16-CREB - a constitutively active form of CREB - whereas the normal data are obtained from the wild-type mice neurons. Upon estimating the neuron model parameters from the experimental data, we observe that the model exhibits good fit to both normal and abnormal data, for various synaptic input currents. To study the effect of CREB abnormalities on the considered neuronal system, we use the information theoretic redundancy parameter. It basically measures - for the system output neuron - the amount of spike count information overlap that exists between the states of the stimulus currents injected to the input neurons. Our analysis reveals a noticeable increase in the information redundancy, when CREB behaves abnormally. This finding motivates further exploration of the biological implications of the information redundancy in neuronal systems, and its use as a parameter to model abnormalities in CREB and perhaps other important transcription factors involved in learning and memory.
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CREB蛋白异常如何影响神经元系统及其信号的研究:使用实验数据建模和分析
众所周知,CREB蛋白高度参与哺乳动物大脑记忆和学习的神经元机制,CREB活性的缺乏可导致向某些病理状况的转变。在本文中,我们使用一些已发表的实验数据,以及由Izhikevich神经元模型组成的神经元系统,来表征CREB异常如何改变神经元信号和系统行为。异常数据是从表达VP16-CREB的转基因小鼠神经元的细胞内记录中提取的,VP16-CREB是CREB的组成活性形式,而正常数据是从野生型小鼠神经元中获得的。根据实验数据估计神经元模型参数,我们观察到该模型对各种突触输入电流的正常和异常数据都有很好的拟合。为了研究CREB异常对所考虑的神经元系统的影响,我们使用了信息论冗余参数。对于系统输出神经元来说,它基本上测量的是在注入到输入神经元的刺激电流状态之间存在的尖峰计数信息重叠的数量。我们的分析显示,当CREB行为异常时,信息冗余显著增加。这一发现激发了对神经系统中信息冗余的生物学意义的进一步探索,并将其作为CREB异常模型的参数,以及其他与学习和记忆有关的重要转录因子。
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