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Automated Analysis of Dynamic Ca2+ Signals in Image Sequences
Published on: June 16, 2014
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CADENCE - Neuroinformatics Tool for Supervised Calcium Events Detection.
Nikolay Aseyev1, Anastasia Borodinova2, Svetlana Pavlova2
1Institute of Higher Nervous Activity and Neurophysiology of RAS, Moscow, Russia. aseyev@ihna.ru.
Neuroinformatics
|July 1, 2024
Summary
CADENCE is a new Python tool for detecting calcium events in neuronal imaging data. This open-source software aids researchers in analyzing neuronal activity by inferring calcium events from fluorescence data.
Area of Science:
- Neuroscience
- Bioinformatics
- Computational Biology
Background:
- Calcium imaging is crucial for studying neuronal ensembles.
- Existing tools often provide relative fluorescence (ΔF/F) but lack detailed calcium event analysis.
- Researchers need to infer calcium events from ΔF/F curves for further analysis.
Purpose of the Study:
- To introduce CADENCE, an open-source Python tool for supervised calcium event detection.
- To provide a user-friendly graphic interface for analyzing calcium imaging data.
- To facilitate the creation of raster representations of calcium events for downstream analysis.
Main Methods:
- CADENCE is written in Python 3 and features a Qt6 graphical user interface.
- It employs supervised learning for detecting calcium events.
- The tool processes movie data from calcium imaging instruments.
Main Results:
- CADENCE enables supervised detection of calcium events from fluorescence data.
- The tool assists in converting raw imaging data into meaningful event timelines.
- It generates raster representations of neuronal activity.
Conclusions:
- CADENCE offers a valuable neuroinformatics solution for detailed calcium event analysis.
- The open-source nature of CADENCE promotes accessibility and collaboration in neuroscience research.
- This tool supports advanced analyses by providing structured calcium event data.
