A systems approach to investigating the roles of cellular mechanisms for tuning of neural computation in the entorhinal cortex

科学中最具挑战性的问题之一是了解大脑中神经细胞表达的分子如何使思想和行动发生。无论是对大脑如何工作的学术理解，还是对致力于开发治疗神经和精神疾病的疗法的行业来说，这都是至关重要的。分子的合成和细胞的组装在大脑和身体的其他器官中是相似的，但大脑的不同之处在于它有能力执行相当复杂的计算。这些计算依赖于神经细胞膜中的离子通道产生的电信号。膜离子通道是连接基因表达和电信号的重要分子纽带。明确解释神经细胞膜离子通道的计算模型将使基因表达、电信号和大脑功能之间建立直接联系。我们建议开发定量和预测模型，最终解释基因表达如何决定在大脑中进行的计算。我们将重点关注大脑中一个叫做内嗅觉皮质的子区域。这个地区的组织方式使其成为一个非常有吸引力的典范。在探索过程中，该区域上端的神经细胞以相对较高的分辨率编码动物的位置，分辨率约为30厘米。位于该区域内逐渐向下的神经细胞也编码动物的位置，但分辨率逐渐降低。重要的是，当这些神经细胞的输入被激活时，产生的电信号遵循类似的组织。在内嗅觉皮质的上部，电信号非常短暂。在逐渐变低的位置，这些信号的持续时间会增加。这种电信号的组织可能是由于在不同位置的神经细胞膜上发现的离子通道的差异。我们将首先开发简单的计算机模型，内嗅皮层中的神经细胞。然后，我们将把不同神经细胞中离子通道沿着内侧嗅觉皮质自上而下的轴线的组织数据纳入到这些模型中。我们将使用这些模型来预测神经元将如何对可用于简单计算的信号做出反应，以及如果缺少特定的离子通道分子，这些反应会发生什么。然后，我们将从真实的神经细胞进行记录，并研究它们对同等输入信号的反应。这些实验将在神经细胞上重复，在神经细胞中，特定的离子通道分子或编码它们的基因已经被选择性地阻断。通过将实验结果与模型预测进行比较，我们将能够改进和提高模型的预测能力，同时还可以确定模型可能尚未解释的功能，因此需要进一步研究。最后，我们将使用经过验证的模型来预测特定离子通道分子在不同空间分辨率下编码动物位置的作用。本研究所产生的模型和实验结果将在几个领域中有所裨益和应用。1)通过建立基因、电信号和神经细胞计算之间的基本联系，这项研究将对理解健康的大脑非常重要。这将为进一步研究特定基因如何影响大脑功能奠定关键基础。2)内侧内嗅皮质和膜离子通道是药物发现的重要靶点。我们建立的计算模型将使制药或生物技术公司能够对开发中的潜在治疗策略进行干燥的实验室测试。3)在拟议的工作中发现的原理可能会刺激未来基于生物的计算设备的设计。

One of the most challenging problems in science is to understand how the molecules expressed by nerve cells in the brain enable thoughts and actions to take place. This is of fundamental importance, both for academic understanding of how brains work, and for industries aiming to develop therapies that treat neurological and psychiatric disorders. Synthesis of molecules and assembly of cells is similar in the brain and other organs of the body, but the brain is distinguished by its ability to perform computations of considerable complexity. These computations rely upon electrical signals generated by ion channels found in the membrane of nerve cells. Membrane ion channels are the critical molecular link between gene expression and electrical signaling. Computational models that explicitly account for a neuron's membrane ion channels will enable direct links to be established between gene expression, electrical signaling and brain function. We propose to develop quantitative and predictive models that will ultimately account for how gene expression determines the computations carried out in the brain. We will focus on a sub-region of the brain called the entorhinal cortex. This region is organized in a way that makes it a very attractive model. During exploration, nerve cells at the upper end of this region encode an animal's location at a relatively high resolution of approximately 30 cm. Nerve cells located progressively lower down within this region also encode an animals location, but at progressively lower resolution. Importantly, the electrical signals generated when inputs to these nerve cells are activated follow a similar organization. In the upper part of the entorhinal cortex, the electrical signals are very brief. At progressively lower locations, the duration of these signals increases. This organization of electrical signals is probably dues to differences between the ion channels found in the membrane of nerve cells at different locations. We will first develop simple computer models nerve cells in the entorhinal cortex. We will then incorporate into these models data about the organization of ion channels in different nerve cells along the top-to-bottom axis of the medial entorhinal cortex. We will use these models to predict how the neurons will respond to signals that can be used for simple computations, and what happens to these responses if specific ion channel molecules are absent. We will then record from real nerve cells and study their responses to equivalent input signals. These experiments will be repeated on nerve cells in which specific ion channel molecules, or the genes that encode them, have been selectively blocked. By comparison of the experimental results with the model predictions we will be able to refine and improve the predictive power of the models, while also identifying functions that the model may not yet explain and that will therefore require further investigation. Finally, we will use the validated model to predict the roles of specific ion channel molecules in encoding of an animals location at different spatial resolutions. The models and experimental results generated by this study will be of benefit and application in several areas. 1) By establishing basic links between genes, electrical signaling and computation by nerve cells, the study will be important for understanding the healthy brain. It will form a key foundation for further investigations of how specific genes influences brain function. 2) The medial entorhinal cortex and the membrane ion channels that we will focus on are important targets for drug discovery. The computational models that we build will enable dry lab testing of potential therapeutic strategies in development by pharmaceutical or biotechnology companies. 3) The principles uncovered during the proposed work may stimulate future design of biologically based computational devices.