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Detection of cellular micromotion by advanced signal processing.
Stephan Rinner1,2, Alberto Trentino1,2, Heike Url3
1Walter Schottky Institut and Physik-Department, Technische Universität München, 85748, Garching, Germany.
Scientific Reports
|November 19, 2020
Summary
Cellular micromotion, tiny cell membrane movements, can signal intercellular communication and neural activity. This study uses advanced signal processing to detect this motion in unlabeled cells from video recordings.
Area of Science:
- Biophysics
- Cell Biology
- Signal Processing
Background:
- Cellular micromotion, occurring at the nanometer to micrometer scale, is a proposed mechanism for intercellular communication.
- It may also serve as a label-free indicator of neural activity.
- Detecting this subtle motion is crucial for understanding cellular dynamics.
Purpose of the Study:
- To explore and apply advanced signal processing techniques for detecting cellular micromotion.
- To analyze video recordings of unlabeled cells for evidence of micromotion.
- To evaluate the efficacy of various signal processing methods in identifying these cellular movements.
Main Methods:
- Spectral filtering of video signals.
- Matched filtering techniques.
- Application of 1D and 3D convolutional neural networks (CNNs) on pixel-wise time-domain data and whole recordings.
Main Results:
- Successful detection of cellular micromotion using the described signal processing methods.
- Demonstration of CNNs' capability in analyzing complex video data for micromotion.
- Validation of signal processing approaches for label-free analysis of cellular dynamics.
Conclusions:
- Advanced signal processing, including CNNs, can effectively detect cellular micromotion in unlabeled cells.
- This technique offers a label-free proxy for studying intercellular signaling and neural activity.
- The findings open new avenues for non-invasive monitoring of cellular dynamics.
