Integrated computational and imaging framework to understand astrocyte calcium dynamics

Astrocytes, the most numerous glial cells, play important roles in the brain functions. Astrocytic activity and their relationships with behaviors remain largely unexplored. Unlike their counterparts, neurons, astrocytes are not electrically excitable and therefore cannot be studied using conventional electrophysiological methods. Advances in optical imaging techniques and genetically encoded calcium indicators, which change their fluorescence properties upon binding to calcium ions, have enabled the observation of intracellular calcium concentrations in astrocytes as a means to measure their excitability. However, studies have revealed a striking spatiotemporal diversity and complexity in the calcium signals of astrocytes. Deciphering calcium signaling in astrocytes is both a significant challenge and an urgent need. Here, we propose an integrated computational and imaging framework that enables: 1) the generation of realistic astrocyte imaging data that depict the calcium signals observed in microscopy; and 2) the validation of model output by tuning model parameters, which can be used for interpreting experimental results. In this poster, we present our preliminary results for simulating astrocytic morphology and calcium dynamics in an integrated computational framework.