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Data analysis and visualisation

Data analysis provides methods and workflows to reveal hidden dynamics and extract characteristic statistical features from simulations and experiments. These toolboxes help computational neuroscientists analyse neuronal dynamics simulations and validate models against experimental evidence. Visualisation gives scientists a powerful tool for interactive data analysis, from an overview to deep insights. EBRAINS offers access to interactive tools for visualising models and simulation results from the cellular to the network level.

Popular data analysis tools

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The Python library Electrophysiology Analysis Toolkit (Elephant) provides tools for analysing 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. This framework 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 the Neo library provides, is essential for developing interoperable analysis workflows.

Modelling and simulationData analysis and visualisationValidation and inference


NeuroScheme is a tool that allows users to navigate through circuit data at different levels of abstraction using schematic representations for a fast and precise interpretation of data. It also allows filtering, sorting and selections at the different levels of abstraction. Finally it can be coupled with realistic visualization or other applications using the ZeroEQ event library developed in WP 7.3. This application allows analyses based on a side-by-side comparison using its multi-panel views, and it also provides focus-and-context. Its different layouts enable arranging data in different ways: grid, 3D, camera-based, scatterplot-based or circular. It provides editing capabilities, to create a scene from scratch or to modify an existing one.

Modelling and simulationCellular level simulationData analysis and visualisation


NEST is a simulator for spiking neural network models that focuses on the dynamics, size and structure of neural systems, rather than on the exact morphology of individual neurons. It is ideal for networks of any size, including models of information processing (e.g. in the visual or auditory cortex of mammals), models of network activity dynamics (e.g. laminar cortical networks or balanced random networks) and models of learning and plasticity. NEST is openly available for download.

Modelling and simulationNetwork level simulationData analysis and visualisation

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