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Facilitating stochastic resonance as a pre-emphasis method for neural spike detection
Cihan Berk Güngör1,2, Hakan Töreyin2
1Department of Electrical and Computer Engineering, University of California - San Diego, San Diego, CA, United States of America.
Journal of Neural Engineering
|September 18, 2020
Summary
This study introduces a novel pre-emphasis method using stochastic resonance (SR) to enhance neural spike detection in extracellular recordings. The technique significantly improves signal-to-noise ratio and outperforms existing methods, enabling more neurons to be monitored.
Area of Science:
- Neuroscience
- Signal Processing
- Biophysics
Background:
- Extracellular neural recordings are crucial for understanding brain activity.
- Detecting neural spikes in noisy single-channel recordings remains a challenge.
- Current methods often struggle with low signal-to-noise ratios and high false detection rates.
Purpose of the Study:
- To develop a novel pre-emphasis method to increase the number of detectable neural spikes in single-channel extracellular recordings.
- To leverage stochastic resonance (SR) for improved neural signal detection.
- To enhance the monitoring capacity of single-channel neural interfaces.
Main Methods:
- A pre-emphasis method using an overdamped Brownian particle in a monostable potential was proposed.
- The method utilizes stochastic resonance (SR) by introducing band-pass-filtered noisy extracellular recordings.
- Spike detection was performed by applying a threshold to the Brownian particle's x-position output.
- Performance was evaluated using synthetic datasets with varying noise intensities and compared against state-of-the-art methods.
Main Results:
- The stochastic resonance (SR)-based spike detection improved the signal-to-noise ratio by up to 7.35 dB on a synthetic intracellular dataset.
- The proposed method outperformed state-of-the-art pre-emphasis techniques in false positive and false negative rates across 15 out of 16 synthetic extracellular datasets.
- Achieved 100% sensitivity and positive predictivity values in seven of the evaluated recordings.
Conclusions:
- The proposed stochastic resonance (SR)-based pre-emphasis method effectively enhances neural spike detection in noisy extracellular recordings.
- This technique offers a significant improvement over existing methods, particularly in reducing false positives and negatives.
- The method holds substantial potential for increasing the number of neurons that can be monitored using single-channel extracellular recordings, advancing neural interface capabilities.
