An enormously complex part of the brain, the neocortex, is thought to give us the ability to generate conscious thought, develop language and perform complicated perception and spatial reasoning tasks. Understanding how the neocortex is built is key to understanding how our brain functions. Here, we propose to develop novel computational and experimental tools to help us understand how electrical activity and genetic circuits are coupled to generate the different cell types in this complex organ. While one might imagine an exceptionally elaborate network of genes giving rise to the brain, several reprogramming experiments suggest that just a handful developmentally important key factors control specific fate choices.
We aim to discover these sets of factors to build a coarse road map of the key gene expression events leading to the neocortex, and over lay on this map the expression patterns of all the other genes. We will do so using the data that has the spatial and temporal expression pattern of every mouse gene during the course of the development of the mouse brain from mid gestation to adult. We will develop a novel computational paradigm to analyze this data and extract the rules governing the construction of the neocortex. We will test these rules directly in an in vitro directed differentiation system, focusing on the pyramidal neurons. To enable such tests, we are developing ground-breaking imaging technologies to both measure and perturb gene expression and electrical activity in thousands of single cells as they differentiate in vitro from stem cells to post-mitotic pyramidal neurons. We will measure dynamics of candidate factors predicted by our computational analysis as well as calcium and electrical activity in single cells by using multiple fluorescent reporters. By analyzing these single cell time-series expression and activity data using a Bayesian statistical analysis and directly perturbing the dynamics of expression of specific genes and e
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