What is Clarinet?

Clarinet is a MATLAB® app designed to analyze electrophysiology experiments.

Developed for neuroscience research, Clarinet allows you to analyze neuronal signals acquired with a variety of intracellular and extracellular recording techniques.

Clarinet can display your recorded epochs in a 2D or 3D cartesian space. Search epochs that meets specific conditions, process them using a pipeline of epoch processors and then export data for further processing/plotting with your favorite data analysis tools.

Clarinet is designed from the beginning to be the perfect companion of Symphony, the data acquisition suite developed in Fred Rieke's Lab at the University of Washington. Import automatically data saved with either Symphony (version 1 or 2), taking full advantage during analysis of the dynamic data structure that makes Symphony shine.

Create your analysis pipeline by using built-in epoch processors or create your own, combine multiple processors into a pipeline and use it process many epochs at once.

Creating a custom epoch processor is as easy as writing a simple matlab function. Clarinet will dynamically load new epoch processors, letting end-users change parameters and processing epochs without having to write code.

Clarinet can search your data based on many conditions according to multiple criteria, this allows you to always find the specific data and create rich queries even in large databases. Searching condition include numerical or string operators (including regular expressions).

Whether your workstation uses Microsoft Windows, macOS or Linux, Clarinet can run on your computer since it relies only on core Matlab functions.

Clarinet is licensed under GNU General Public License v3. This strong copyleft license ensures you will always have the right to obtain, view and modify Clarinet's source code to review its functionality and improve its features.

We strongly believe that software developed for data analysis in scientific research must be open source, to ensure the highest level of reproducibility of your science.