Research Question: What changes in gene expression underlie learning and memory?
Interdisciplinary Approach: This project combines gene expression profiling using a novel high-throughput technique (single-cell RNA sequencing), computational analysis, and current theories of the cellular organization of a brain structure important in learning and memory to understand the mechanisms underlying learning.
Potential Implications of Research: The results will deepen our understanding of the molecular basis of learning and memory.
Learning and memory depend on long-lasting changes in the structure and function of the nervous system, which are in part induced by changes in gene expression. However, the full complement of gene expression changes underlying learning and memory is still poorly understood. Further complicating the issue is the fact that the nervous system is made up of many different neuronal cell types, each specialized to perform a specific task in the brain. Whether these different cell types use similar or distinct mechanisms during learning is not known.
Using the mouse neocortex as a model system, we will compare the gene expression changes induced by experience across different neuronal cell types. The neocortex is a brain structure that plays an important role in learning and memory in both mice and humans, making it well-suited for these studies. The experiments take advantage of recently developed high-throughput techniques that now allow the gene expression profiles of hundreds to thousands of individual neurons to be sampled simultaneously (as noted in Figure 1).
Combining these approaches with further advances in the computational analysis of these data, will uncover new cellular mechanisms involved in learning, and will determine whether these cellular pathways are shared across different cell types or whether different types of neurons tap into distinct cellular mechanisms during learning. In addition, the time course of the gene expression changes will be assessed and compared across neuronal cell types.
These high-throughput approaches will generate a comprehensive view of the genes engaged by learning and will identify common mechanisms that may be suitable for targeted therapeutic interventions to improve learning. Furthermore, this project will shed light on the diversity of neuronal responses to learning and address whether or not any interventions must be targeted to specific neuronal types.