Illustration by Andrea Navas-Olive

The large diversity of neuron types provides the means by which cortical circuits perform complex operations. Neuron can be described by biophysical and molecular characteristics, afferent inputs, and neuron targets. To quantify, visualize, and standardize those features, we developed the open-source, MATLAB-based framework CellExplorer. It consists of three components: a processing module, a flexible data structure, and a powerful graphical interface. The processing module calculates standardized physiological metrics, performs neuron-type classification, finds putative monosynaptic connections, and saves them to a standardized, yet flexible, machine-readable format. The graphical interface makes it possible to explore the computed features at the speed of a mouse click. The framework allows users to process, curate, and relate their data to a growing public collection of neurons. CellExplorer can link genetically identified cell types to physiological properties of neurons collected across laboratories and potentially lead to interlaboratory standards of single-cell metrics.


  • An open-source framework for single-cell characterization and visualization
  • A processing module that calculates a set of standardized physiological metrics
  • A graphical interface to explore computed features at the speed of a mouse click

Peter C. Petersen*, Joshua H. Siegle, Nicholas A. Steinmetz, Sara Mahallati, György Buzsáki*. “CellExplorer: A framework for visualizing and characterizing single neurons”. *corresponding author. Neuron, September 29, 2021. [website] [github] [pdf] [link]