Electrically stimulated hiPSC-derived astrocytes - calcium imaging videos, raw and analysed fluorescence intensity values

Deep brain stimulation (DBS) is an established neuromodulation technique used for various conditions. While it offers symptom relief, the mechanisms underlining its therapeutic effects remain unclear, affecting efficacy and side effects. A key challenge in DBS research is isolating neuron-astrocyte interactions in a complex in vivo environment. To address this, we developed tools to study the effects of DBS on astrocytic calcium dynamics in vitro. We employed human induced pluripotent stem cell (hiPSC)-derived astrocytes cultured on custom glass micro-electrode arrays (MEAs) together with a semi-automated analysis pipeline to extract key calcium dynamics parameters of large data sets. Here, we share calcium imaging videos of hiPSC-derived astrocytes stimulated at 10Hz, 130Hz and stimulated with one electrical pulse. Additionally, we provide the raw fluorescence intensity values of Fluo-4 Calcium indicator in each identified cell and the subsequent data analysed using our custom-made Fluorescence analyser script.

Data analyses were conducted using FIJI ImageJ software (RRID:SCR_002285) and a custom-made Python script we called Fluorescence_analyser. Fluorescence signals (‘F’) from individual astrocytes were extracted by identifying cell bodies through automatic region of interest (ROI) segmentation based on fluorescence intensity, size, and shape using FIJI's ‘Analyze Particles’ function. Fluorescence intensity of each ROI was measured in each video frame using the FIJI ImageJ plugin Time Series Analyzer (RRID:SCR_014269).

Analysis of fluorescence intensity changes over time was performed using our custom-made Fluorescence_analyser script. It automates the acquisition and post-analysis of fluorescence data in a python-based integrated development environment. The results are visualized through various graphs and all calculated data is documented in an Excel file for further use. This automatization enables manual analysis compressing them into a single execution. 

Fluorescence baselines (‘F0’) are computed for each ROI from a 90 second sliding window. Variations in fluorescence intensity were quantified as ΔF/F0, and key parameters such as amplitude, duration, rise slope, and decay slope are calculated for detected significant fluorescence events. Fluorescence_analyser is freely available to download from https://gitedu.hesge.ch/tissue-engineering-lab/estime_fluorescence_analyser and was tested and used on Spyder 6 (https://github.com/spyder-ide/spyder).