Elephant – Open-Source Tool for the Analysis of Electrophysiological Data Sets

The need for reproducible research has become a topic of intense discussion in the neurosciences. Reproducibility is based on building well-defined workflows leading to documented, traceable analysis steps. In recent years software tools (e.g., Neurotools [1], spykeutils [2], OpenElectrophy [3]) have been developed to analyze electrophysiological data. However, many tools tend to specialize in particular types of analysis and do not use a common data model, forcing the user to rely on multiple tools during an analysis. Often the code base of such tools is not written in a modular way, which complicates the combination and comparison of different analysis methods.Here we introduce the Electrophysiology Analysis Toolkit (Elephant) as a community-centered initiative (http://neuralensemble.org/elephant/). Elephant is an easy-to-use, open source Python toolkit, that offers a broad range of functions for analyzing multi-scale data of brain dynamics from experiments and brain simulations. The focus is the analysis of electrical activity, ranging from single unit or massively parallel spike train data to population signals such as the local field potentials. The scope of the library covers analysis methods for time series data (e.g., signal processing, spectral analysis), spike trains (e.g., spike train correlation, spike pattern analysis) and methods for relating both signal types (e.g., spike-triggered averaging). In the context of hypothesis testing, utility modules for the generation of realizations of stochastic processes and of surrogate signals are implemented.We chose to use Neo [4] as the underlying data model. This guarantees compatibility within the toolkit, but also provides access to various file I/O modules to access data in both open and proprietary formats. We demonstrate the usage of Elephant in the form of use cases, and outline how to parallelize analyses using the toolkit. In particular, we illustrate the use of Elephant and the task-system on the Unified Portal (UP) [5] of the Human Brain Project which will be the central platform for collaboration by managing complex analysis workflows in a provenance-tracked fashion. Using the web interface of the UP, neuroscientists can launch either generic analysis scripts made available to the community to analyze their data, or alternatively upload and run custom-tailored analysis programs based on Neo and Elephant. The collaborative nature of the portal will enable scientists to easily share and reproduce an analysis inside or even outside their collaborative groups on the UP. Elephant is released on the python package index PyPI [6], and documentation is available at [7]. Please feel free to contribute your analysis tools into Elephant![1] http://neuralensemble.org/NeuroTools/[2] http://spykeutils.readthedocs.org/en/0.4.1/[3] http://neuralensemble.org/OpenElectrophy/[4] Garcia et al. (2014) Front. Neuroinform 8:10, doi:10.3389/fninf.2014.00010[5] https://developer.humanbrainproject.eu/docs/Unified%20Portal/latest/[6] https://pypi.python.org/pypi/elephant[7] http://elephant.readthedocs.org/en/latest/index.ht