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Updated: Dec 29, 2025
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Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond
Published on: June 24, 2015
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A novel method for quantifying periodicity and time delay in dynamic neural networks using unstable subaction
Julian Sorensen1, Nick J Spencer2
1Cyber Sensing and Shaping, Cyber and Electronic Warfare Division, Defence, Science, and Technology Group, Edinburgh, South Australia, Australia.
Journal of Neurophysiology
|January 30, 2020
Summary
We developed new methods to analyze unstable electrical signals in neural networks. These techniques accurately determine signal periodicity and time delays, enabling directional analysis of signal propagation.
Area of Science:
- Neuroscience
- Signal Processing
- Biophysics
Background:
- Analyzing electrical signal propagation in neural networks typically relies on stable action potential waveforms.
- Unstable signal waveforms complicate the correlation of synchronization and time lags between recording sites.
Purpose of the Study:
- To present novel techniques for determining the periodicity of electrical signals at individual sites.
- To introduce analytical methods for jointly determining periodicity and time delay between two independent recording sites.
Main Methods:
- Developed techniques for individual site periodicity estimation.
- Created analytical methods for joint periodicity and time delay determination using cross-correlation function properties.
- Applied methods to analyze signal propagation directionality in neural networks.
Main Results:
- Successfully determined signal periodicity for individual sites.
- Enabled joint estimation of periodicity and time delay for dual sites.
- Allowed for the determination of excitation spread directionality along neural networks.
Conclusions:
- The novel techniques accurately analyze electrical signal propagation even with unstable waveforms.
- These methods are applicable to various biological systems with dynamic signal variability.
- The approach offers a robust solution for synchronicity and time delay determination in signal processing.
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