Following initial learning, information stored in memory undergoes a time- and experience-dependent evolution. Currently, the nature of this evolution at the neuronal ensemble level remains largely unknown. To obtain insight into this dynamic process there is a need to follow memory-associated neuronal representations in large populations of single cells over long periods of time. However, until recently it has been nearly technically impossible to obtain the requisite data. In my postdoctoral work I have developed an experimental system that enables such investigation by longitudinally imaging neuronal activity in more than 1,000 neurons simultaneously in the hippocampus of freely behaving rodents over the course of months. To enable high-speed imaging at cellular resolution in deep brain structures, my system combines four recent technical advances: (i) miniaturized head-mounted fluorescence microscopes for use in freely behaving mice; (ii) microendoscope probes, for high-resolution imaging of cells in deep brain structures pertinent to long-term memory; (iii) a chronic mouse preparation that permits longitudinal imaging over months of individual neurons lying deep in the brain; (iv) genetically encoded Ca2+ indicators to report neuronal activity. To investigate the principles of neural coding of long-term memory and their underlying biological mechanisms, my lab will combine this imaging methodology with genetic tools for manipulating neuronal activity in specific hippocampal cell types, and novel computational methods for analyzing data from large-scale neuronal populations. This proposal aims to determine how hippocampal place coding evolves as a function of learning and passage of time, and how adult neurogenesis shapes hippocampal information processing. Our results may have profound implications to our understanding of long-term memory and to the study of brain disorders, such as Alzheimer disease and age-related memory loss.