Intracellular calcium is a convenient measurable indicator of astroglial signaling and active involvement in information processing and regulatory pathways in the CNS. Many laboratories are rapidly accumulating astrocyte calcium imaging data in different modalities, with a global trend towards behaving animal experiments. This creates a demand for astrocyte-oriented data processing and analysis frameworks. Current best performing algorithms for analysis of calcium imaging data are neuron-oriented and rely on stationary, stable, separable spatial sources prior. Astrocytes are less predictable with regards to spatial or temporal characteristics of their calcium activity, displaying patterns from spatially confined microdomains to spreading events to large-scale waves. I will present our in-the-making approach to denoising and description of astrocytic calcium imaging data, addressing event-oriented, continuous, and network-level features in ex vivo and in vivo settings. Further insights into physical principles and molecular mechanisms underlying astroglial calcium dynamics may come from mathematical modeling. I will describe our spatially extended modeling framework, which can be employed to this end, and will present patterns of calcium dynamics simulated with this model set.
