Neuroscientific research produces huge volumes of heterogeneous data, which can be difficult to navigate through, and in most cases are not available for further analysis. The aim of the Neuroinformatics Platform is to integrate heterogeneous experimental data. focusing on rodent and human studies from other HBP Subprojects and community resources, in a database - the KnowledgeGraph - amd make the data available for analytic, predictive, and modelling efforts.

One of the HBP's key objectives is to build computational brain models based on experimental data from the human and rodent brain. To this end, the Neuroinformatics Platform (NIP) offers tools and services to:

  • ingest data and metadata into a database, the KnowledgeGraph, which will be the main resource for integration of a wide range of data from the brain
  • assign positions in standard atlas space to data, thereby connecting data in the KnowledgeGraph to reference atlases for the mouse, rat, or human brain
  • query, view, and analyse data discovered through the KnowledgeGraph
  • organise scientific projects, facilitate interaction and collaboration and provide web-accessible storage through the HBP Collaboratory

In the Ramp-Up Phase, we delivered key components towards a new infrastructure for neuroscience research. New atlases for the human and rodent brain were developed together with a suite of tools to register experimental data to the atlases, and view and analyse data. For the human atlas (BigBrain), we achieved new brain region parcellations, important improvements of the 3D reconstruction of the template, and quantitative cell measures. We integrated the rodent atlases into new work flows from experiment to data and metadata storage and spatial registration / anchoring of experimental data to the atlases. A broad range of data types have already been integrated in the atlases. We developed advanced functions for structural data analyses in the EspINA toolkit, for Predictive Neuroinformatics in the SynapseGenerator and other tool kits, and for electrophysiology data analysis in the Elephant toolkit. SP5's tools and resources are either available through the NIP or through the Collaboratory.

Building on the data and metadata managed through the KnowledgeGraph, the Neuroinformatics Platform Subproject will work closely with the other HBP Platforms in SGA1 to:

  • produce multi-level atlases of experimental data from the human and rodent brain with analytics capabilities, making it easier to integrate, navigate and mine the data
  • integrate crucial data sets from community data repositories, and launch strategic repositories
  • establish analytics pipelines for structural data, from electron microscopy to whole brain imaging, aimed at producing derived data for theory and modelling
  • establish analytics pipelines for activity data, from cellular, network and ensemble level, up to large scales, also aimed at producing derived data for theory and modelling

 

Publication highlights:

Amunts, K., Hawrylycz, M.J., Van Essen, D.C., Van Horn, J.D., Harel, N., Poline, J.B., De Martino, F., Bjaalie, J.G., Dehaene-Lambertz, G., Dehaene, S., Valdes-Sosa, P., Thirion, B., Zilles, K., Hill, S.L., Abrams, M.B., Tass, P.A., Vanduffel, W., Evans, A.C., & Eickhoff, S.B. (2014). Interoperable atlases of the human brain. Neuroimage, 99:525-532.

Amunts, K., Lepage, C., Borgeat, L., Mohlberg, H., Dickscheid, T., Rousseau, M.É., Bludau, S., Bazin, P.L., Lewis, L.B., Oros-Peusquens, A.M., Shah, N.J., Lippert, T., Zilles, K., & Evans, A.C. (2013). BigBrain: an ultrahigh-resolution 3D human brain model. Science, 340:1472-1475.

Grillner, S. (2014). Megascience efforts and the brain. Neuron, 82:1209-1211.

Papp, E.A., Leergaard, T.B., Calabrese, E., Johnson, G.A., & Bjaalie, J.G. (2014). Waxholm Space atlas of the Sprague Dawley rat brain. Neuroimage, 97:374-386.

Tiesinga, P., Bakker, R., Hill, S., & Bjaalie, J.G. (2015). Feeding the human brain model. Current Opinion in Neurobiology, 32:107-114.