The Python library Electrophysiology Analysis Toolkit (Elephant) provides tools for the analysis of neuronal activity data, such as spike trains, local field potentials and intracellular data. In addition to providing a platform for sharing analysis codes from different laboratories, Elephant provides a consistent and homogeneous framework for data analysis, built on a modular foundation. The underlying data model is the Neo library, a framework which easily captures a wide range of neuronal data types and methods, including dozens of file formats and network simulation tools. A common data description, as provided by the Neo library, is essential for developing interoperable analysis workflows.

Our offer

  • Explore functional electrophysiological data from heterogeneous sources in a common analytical framework
  • Reference implementations of advanced analytical methods, using the unifying Neo data model
  • Easy to integrate into applications, including graphical analysis tools, network simulation engines, or databases for electrophysiological data
  • Interactive tutorials to illustrate methodologies for data analysis
  • Open-source, community-driven development


Getting started with Elephant and Neo

Elephant, and its complementary data model Neo, are open-source Python libraries available for use offline, and both come pre-installed on the HBP Collaboratory Jupyter Notebooks service for immediate import. The packages are installable from the Python package index, and the sources are found on GitHub. For details, please refer to the install instructions and tutorial sections in the documentation.

Neo and Elephant are EBRAINS components to represent and analyze neuronal activity data from brain simulations and experiment.

Recommended use

Recommended use

Analysis workflows based on Elephant

Elephant is developed in constant, close exchange with scientific applications to ensure that its functionality will continue to be beneficial for the neuroscience community. A growing number of tutorials assist researchers in setting up their analysis workflows.


Elephant Community

Impressions from the 1st Elephant User Workshop 2019, Gif-sur-Yvette, France.

Training for the Elephant community

We offer a growing number of training opportunities for learning how to use Elephant to analyze activity data. The Advanced Neural Data Analysis spring school (ANDA) teaches students and young researchers how to employ the Elephant and Neo libraries to provide data analytics for electrophysiological data. The Elephant User Workshop complements the ANDA course and gives hands-on support for the use of Elephant, Neo and related HBP infrastructures in participants’ research projects. In addition, help from the community is always available through the Neural Ensemble mailing list and EBRAINS support portal.

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