Begonia—A Two-Photon Imaging Analysis Pipeline for Astrocytic Ca2+ Signals

• Main Authors: Daniel M. Bjørnstad, Knut S. Åbjørsbråten, Eivind Hennestad, Céline Cunen, Gudmund Horn Hermansen, Laura Bojarskaite, Klas H. Pettersen, Koen Vervaeke, Rune Enger
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2021-05-01
• Series: Frontiers in Cellular Neuroscience
• Subjects: two-photon (2P); image analysis; calcium imaging; ROA analysis; astrocyte
• Online Access: https://www.frontiersin.org/articles/10.3389/fncel.2021.681066/full

Imaging the intact brain of awake behaving mice without the dampening effects of anesthesia, has revealed an exceedingly rich repertoire of astrocytic Ca2+ signals. Analyzing and interpreting such complex signals pose many challenges. Traditional analyses of fluorescent changes typically rely on manually outlined static region-of-interests, but such analyses fail to capture the intricate spatiotemporal patterns of astrocytic Ca2+ dynamics. Moreover, all astrocytic Ca2+ imaging data obtained from awake behaving mice need to be interpreted in light of the complex behavioral patterns of the animal. Hence processing multimodal data, including animal behavior metrics, stimulation timings, and electrophysiological signals is needed to interpret astrocytic Ca2+ signals. Managing and incorporating these data types into a coherent analysis pipeline is challenging and time-consuming, especially if research protocols change or new data types are added. Here, we introduce Begonia, a MATLAB-based data management and analysis toolbox tailored for the analyses of astrocytic Ca2+ signals in conjunction with behavioral data. The analysis suite includes an automatic, event-based algorithm with few input parameters that can capture a high level of spatiotemporal complexity of astrocytic Ca2+ signals. The toolbox enables the experimentalist to quantify astrocytic Ca2+ signals in a precise and unbiased way and combine them with other types of time series data.