Spike-contrast is a novel, time-scale-independent, and multivariate measure of spike train synchrony, as described in the following peer-reviewed publication:

Ciba, M., Isomura, T., Jimbo, Y., Bahmer, A., & Thielemann, C. (2018). Spike-contrast: A novel time-scale independent and multivariate measure of spike train synchrony. Journal of Neuroscience Methods, 293, 136–143. DOI: 10.1016/j.jneumeth.2017.09.008 Link to the publication

Spike-contrast was developed to address challenges in measuring spike train synchrony, offering a robust tool that is independent of time scale and capable of analyzing multivariate spike data. It provides a single synchrony value but also a synchrony curve (synchrony as function of the time scale). The measure has applications in neuroscience, including studies of neural coding and network dynamics.

This repository hosts the MATLAB and Python implementations of the Spike-contrast algorithm. Below, we provide details about the respective implementations.

• Description: This is the original MATLAB implementation used in the publication.
• Status: This code is no longer actively maintained or updated.
• Usage: Researchers may use this version for reproducing the results presented in the publication.
• Limitations: For new applications, consider using the up-to-date Python implementation described below.

• Description: This is the original Python implementation of Spike-contrast.

• Status: While this version is functional, it may be outdated.

• Current Version: The most up-to-date Python implementation is integrated into the Elephant Python library.

• Documentation: Detailed documentation and usage examples are available in Elephant's official documentation.

  • Spike-contrast in Elephant

1. Clone the Repository:

   git clone https://github.com/yourusername/spike-contrast.git cd spike-contrast

2. MATLAB Usage: Open the .m files in MATLAB and follow the provided examples.

3. Python Usage: Run the .py files in your Python environment, or use the Elephant library for the latest implementation.

   To install Elephant:

   pip install elephant

4. Further Information: Refer to the publication for theoretical details and performance analysis of the Spike-contrast measure.

This project is distributed under the MIT License. See the LICENSE file for more details.

If you use Spike-contrast in your research, please cite the original publication: Ciba, M., Isomura, T., Jimbo, Y., Bahmer, A., & Thielemann, C. (2018). Spike-contrast: A novel time scale independent and multivariate measure of spike train synchrony. Journal of neuroscience methods, 293, 136-143. DOI: 10.1016/j.jneumeth.2017.09.008

For inquiries or issues related to this repository, please contact:

Manuel Ciba

manuel.ciba@th-ab.de

or

BioMEMS lab (University of Applied Sciences Aschaffenburg)

biomems.lab.thab@gmail.com