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Framework for single cell classification

Cell Explorer is a graphical user interface (GUI), standardized pipeline and data structure for exploring and classifying spike sorted single units acquired using extracellular electrodes.

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Cell Explorer

Introduction

The large diversity of cell-types of the brain, provides the means by which circuits perform complex operations. Understanding such diversity is one of the key challenges of modern neuroscience. Neurons have many unique electrophysiological and behavioral features from which parallel cell-type classification can be inferred.

To leverage this, we built the Cell Explorer, a framework for analyzing and characterizing single cells recorded using extracellular electrodes. It can be separated into three components: a standardized yet flexible data structure, a single yet extensive processing script, and a powerful graphical interface. Through the processing, a high dimensional representation is built from electrophysiological and functional features including the spike waveform, spiking statistics, monosynaptic connections, and behavioral spiking dynamics. The user-friendly interactive graphical interface allows for classification and exploration of those features, through a rich set of built-in plots, interaction modes, cell grouping, and filters. Powerful figures can be created for publications. Opto-tagged cells and public access to reference data have been incorporated to help you characterize your data better. The framework is built entirely in MATLAB making it fast and intuitive to implement and incorporate the Cell Explorer into your pipelines and analysis scripts. You can expand it with your metrics, plots, and opto-tagged data.

Data structure Processing pipeline Graphical interface Database

Table of contents

  1. Getting started
    1. Try the Cell Explorer with example data
    2. Tutorials for using the framework with your own data
  2. Reporting bugs, enhancements or questions
  3. Citing the Cell Explorer in your research and publications

Getting started

  1. Clone, fork, or download the repository (cloning is recommended).
  2. Add the local repository to your Matlab setpath.
  3. The pipeline uses CCGHeart.c. to calculate the CCGs. Compiled versions are included for Windows and Mac. If you are using Linux you have to compile the script. In Matlab, go to Cell-Explorer/calc_CellMetrics/CCG/ and run this line:
    mex -O CCGHeart.c
    
  4. The Cell Explorer GUI and pipeline uses a few toolboxes, of which three Matlab toolboxes must be installed manually.
  5. That’s it! Now you can explore the software with below example data or try one of the tutorials.

Try the Cell Explorer with example data

There is an example dataset included in the repository for trying the Cell Explorer. Load the mat-file cell_metrics_batch.mat into Matlab and type:

CellExplorer('metrics',cell_metrics)

Tutorials for using the framework with your own data

We have created a few tutorials to get you started, covering the pipeline and the graphical interface. There is also a tutorial script: CellExplorer_Tutorial.m included with example code for running the pipeline and the GUI on your data.

View tutorials

Reporting bugs, enhancements or questions

Please use the GitHub issues system for reporting bugs, enhancement requests or geneal questions.

Citing the Cell Explorer in your research and publications

Petersen, Peter C, & Buzsáki, György. (2020, April 8). The Cell Explorer: a graphical user interface and a standardized pipeline for exploring and classifying single cells (Version 1.2). Zenodo. http://doi.org/10.5281/zenodo.3604172

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