The HBP aims to make it easier for scientists to organise and access the huge volumes of heterogeneous data, knowledge and tools produced by the international neuroscience community. The Project shares this goal with the International Neuroinformatics Coordinating Facility (INCF) and with other projects such as the Allen Institute's Brain Atlas projects (

The Neuroinformatics Platform contributes to these efforts by offering a new range of tools designed for the construction of multi-level brain atlases, and for the analysis and interpretation of large volumes of structural and functional data. The HBP will use these tools to develop detailed multi-level atlases of rodent and human brains. The atlases will bring together data from the literature, and from ongoing research, and will provide a single source of annotated, high-quality data. In addition, the Platform will be support for Predictive Neuroinformatics, which involves mining large volumes of data and analysing activity data in order to identify patterns and relationships between data from different levels of biological organisation. This makes it possible to predict parameters where experimental data is not yet available, and to test and calibrate model implementations. If this strategy is systematically applied, it has the potential to significanlty increase the amount of information that can be extracted from experimental data, rapidly fill gaps in our current knowledge, and accelerate the generation of data required for brain modelling.

The objective for the Ramp-Up Phase was to launch the first functional version of the Neuroinformatics Platform, and to populate it with data, models and ontologies for ion channels, cell types, synapse types and microcircuits. data and models are palced in the data space, and annotated with ontologies from the Brainpedia. Initial tools and workflows for analysis of electron microscopy data and local field potential data will be deployed. A core service for tracking the provenance of data and models throughout the workflows ensures reproducibility and appropriate attribution. In addition, initial Predictive Neuroinformatics efforts targeting the prediction of fine scale and long range connectivity from DTI imaging data have been completed.

In SGA1, SP5 aims to:

  • Establish standard software for federated active data repositories with a focus on European data producing sites;
  • Launch strategic data repositories in key member states;
  • Integrate key data sets from SP1, the literature and community data repositories;
  • Curate key datasets and ontologies required for atlases and brain modelling;
  • Integrate Allen Institute datasets containing whole brain gene expression, single cell morphologies, electrophysiology, transcriptome and mesoscale brain connectivity;
  • Provide an initial data mining infrastructure for extracting key modelling parameters of whole rodent brain models;
  • Use predictive neuroscience approaches to predict additional parameters and constraints for a whole rodent brain model;
  • Establish initial human atlas and human brain atlas analytics capabilities.

What People are Saying

  • One of the core goals of the Human Brain Project is to integrate our full understanding of the human brain – to know what we know – and the Neuroinformatics subproject is really about aggregating, federating, bringing together all of that data, making it accessible and telling us what we know. How much can that actually inform us about the missing data and how do we make use of it to build models.

    Prof. Sean Hill, Blue Brain Project, Ecole Polytechnique Fédérale de Lausanne,
    co-leader of the Neuroinformatics subproject