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Electrophysiology-Tutorial-for-Neuroscience

Version 1.2 (4.83 MB) by Shubo Chakrabarti
This is a tutorial for key data analysis steps used by neuroscientists - filtering, spike extraction, PCA, clustering, and spectral analysis
5.0
(3)

440 Downloads

Updated 5 Aug 2021

From GitHub

View License on GitHub

This tutorial shows how neuroscientists can use MATLAB to analyze neural signals. This includes best practices on
1. reading in diverse neural data
2. representing time-series data
3. filtering, smoothing, resampling data
4. clustering waveforms using PCA and Gaussian mixture models
5. frequency domain and time-frequency analyses
For those new to programming, several steps can be achieved with the MATLAB Signal Analyzer App - a click-and-point interface that generates code.
For mid-level programmers, this tutorial can be the starting point for more complicated signal processing and analysis workflows
For experts, this is a good tutorial for teaching the basics of neural signal analyses
To run this Live Script check if you have a MATLAB license from your school or university. If not, you can download a free trial for 30 days.
For a Japanese language version, check this entry

Cite As

Shubo Chakrabarti (2023). Electrophysiology-Tutorial-for-Neuroscience (https://github.com/bat365-Teaching-Resources/Electrophysiology-Tutorial-for-Neuroscience/releases/tag/v1.2), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2020b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
1.2

See release notes for this release on GitHub: https://github.com/bat365-Teaching-Resources/Electrophysiology-Tutorial-for-Neuroscience/releases/tag/v1.2
1.1

See release notes for this release on GitHub: https://github.com/bat365-Teaching-Resources/Electrophysiology-Tutorial-for-Neuroscience/releases/tag/v1.1
1.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.