Ischemic heart disease (IHD) is the leading cause of morbidity and mortality worldwide. 1It begins with myocardial infarction (MI), which results from obstruction of coronary artery blood flow and leaves dependent cardiomyocytes ischemic due to a mismatch between oxygen supply and demand. Although revascularization and medical management have dramatically reduced acute mortality from MI, surviving patients frequently develop chronic symptomatic heart failure. In adults, cardiomyocyte proliferative potential is limited, and to date, no consequential cardiac regeneration has been demonstrated. Instead, therapeutic efforts have focused on protecting the non-dead but still injured and ischemic borderzone cardiomyocytes (BZ) in the region immediately adjacent to the infarct zone (IZ). BZ are thought to be biologically distinct from the distant well-perfused remote zone cardiomyocytes (RZ), yet surprisingly little is known about their cellular and molecular biology due to technology limitation. In Chapter 1, we developed methods for performing high throughput single nuclei cardiomyocyte transcriptional profiling and use them to transcriptionally define BZ from RZ. We hypothesize that BZ and RZ will exhibit distinct transcriptional signatures that can be revealed by unbiased clustering. To validate the marker genes that best define cardiomyocytes from each territory, we employed a recently developed method for spatially resolved transcriptomics known as Visium 10x, a grid based method ( low resolution) and multiplexed RNA fluorescence in situ hybridization (mFISH) to show that the BZ can be functionally defined by gene expression patterns. Macrophages contribute to diverse physiologic and pathogenic functions across myocardial tissue. They are critical players in the pathophysiological processes induced by myocardial infarction such as removing dead cells near BZ, patrolling local tissue microenvironments, and mounting innate and adaptive anti-pathogen. Morphologic evidence suggests that macrophages are arranged as networks of cells and there is evidence that they communicate with cardiomyocytes to influence cardiac conduction 2. However, existing methods for studying communication between macrophages include transfer of microinjected or scrape loaded membrane impermeant dyes, fluorescence recovery after photobleaching, or measurement of electrical conductance via patch clamping are destructive with low temporal resolution 3. For the next chapter, we developed a transgenic tool to provide a non-destructive assay that infer cell communication with high temporal resolution. We leveraged high resolution imaging with a using tissue-specific genetically encoded calcium indicator (GECI) mice reporter (GCAMP5 fl) animal in which is calcium dependent green-fluorescence protein (GFP) specifically in (Csf1rCre) macrophages. Calcium represents an attractive indicator of cell communication in cells because it is a dynamic second messenger influenced by multiple signaling pathways. In non-communicating populations of cells, calcium dynamics are not necessarily correlated. We reasoned that non-destructive monitoring of calcium dynamics in a population of cells and detection of their spatiotemporal correlations could be used to infer cell communication, even if the molecular stimuli, mediators, and mechanisms were unknown. In order to infer cell communication, we create a computational pipeline called ‘Excess Synchrony’ which automatically preprocess GECI fluorescence time-series measured by time-lapse imaging or intravital microscopy, detect peaks with single cell resolution, and infer cell communication from the synchrony of single cell calcium transients.