GliaNeurosciencePeer-reviewed journal article
Deciphering spatio-temporal fluorescence changes using multi-threshold event detection (MTED)
Franziska E. MülleriD, Volodymyr CherkasiD, Gebhard StopperiD, Laura C. CaudaliD, Laura StopperiD, Frank KirchhoffiD, Christian HennebergeriD, Evgeni G. PonimaskiniD, André ZeugiD
Abstract
Recent achievements in indicator optimization and imaging techniques promote the exploration of Ca2+ activity patterns as a main second messenger in many organs. Astrocytes are important regulators of brain activity and well known for their Ca2+-dependent modulation of neurons. However, standardized methods to analyze and interpret Ca2+ activity recordings are missing and hindering global comparisons. Here, we present a biophysics-based concept to analyze Ca2+signals, which includes multiple thresholds and provides the experimenter with a comprehensive toolbox for a differentiated and in-depth characterization of Ca2+ signals. We analyzed various ex vivo and in vivo imaging datasets and verify the validity of our multi-threshold event detection (MTED) algorithm across Ca2+ indicators, imaging setups, and model systems from primary cell culture to awake, head-fixed mice. Applying our MTED concept enables standardized analysis and advances research using optical readouts of cellular activity to decrypt brain function. It allowed us to obtain new insights into the complex dependence of Ca2+activity patterns on temperature and neuronal activity. Highlights[->] We present a robust pixel-based algorithm to analyze multidimensional fluorescence data. [->]Automated multiple-threshold analysis accurately quantifies changes in fluorescence across magnitudes. [->]It characterizes the complexity of dynamic and overlapping activity patterns of Ca2+ activity of astrocytes in vitro, in situ, and in vivo. [->]Its application provides quantitative parameters how temperature and neuronal activity determine astrocytic Ca2+ activity.
- organism: mouse
- assay: imaging
- research focus: cell type annotation
- research focus: differential expression
- research focus: trajectory inference
- research focus: cell-cell communication
- approach: statistical model
- Citations
- 9
- FWCI
- 0.69
- Field percentile
- top 39%
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