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

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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.