Electrophys Feature Extraction Library¶
The Electrophys Feature Extract Library (eFEL) allows neuroscientists to automatically extract eFeatures from time series data recorded from neurons (both in vitro and in silico). Examples are the action potential width and amplitude in voltage traces recorded during whole-cell patch clamp experiments. The user of the library provides a set of traces and selects the eFeatures to be calculated. The library will then extract the requested eFeatures and return the values to the user.
The core of the library is written in C++, and a Python wrapper is included. You can automatically compile and install the library as a Python module.
The source code of the eFEL is located on github: BlueBrain/eFEL
- Installation
- Examples
- Quick start
- How to set the settings
- Parallel efeature extraction using multiprocessing/scoop
- DEAP optimisation
- Reading different file formats
- Loading NWB files using Neo
- Use of eFEL on the models downloaded from the Neocortical Microcircuit Portal
- Extracting features from SONATA Network simulations
- Extracellular Features Extraction for MEA Data
- Voltage clamp trace and eFEL
- eFeature descriptions
- Python API
- Changelog
- Developer’s Guide