"Establishing a Global Neuroscience Information Framework" by Maryann E. Martone

"Establishing a Global Neuroscience Information Framework" by Maryann E. Martone, Professor-in-Residence, Neurosciences; Center for Research in Biological Systems (CRBS); Co-Director, National Center for Microscopy and Imaging Research (NCMIR) Understanding the brain strains the limits of current human ingenuity. Perhaps more than any other organ system, the problem of understanding the brain is fundamentally multiscale, with relevant data derived from spatial and temporal scales spanning many orders of magnitude. Because of the complexity and breadth of these networks, unraveling functional circuits underlying complex behaviors or pinpointing the locus of disease processes, even where the genetic defect is known, has confounded scientists, who by the limitations of experimental methods glimpse only a pinhole view of a vast interconnected landscape. Neuroscientists rely heavily on technological advances to expand our capacity to deal with this enormous complexity. Convergent technological revolutions are producing views of the brain of increasing size, breadth and detail, as we acquire data spanning multiple scales across increasing expanses of brain tissue. With the concomitant increase in computing power, the increased data generation is leading to production of ever more realistic computational models, allowing scientists to probe the consequences of the structural and biochemical complexity in ways not amenable to direct experimentation. Although the amount of data is increasing daily, neuroscience as a whole, with its exceptionally large scope and diverse research community, lacks a coherent community framework for bringing these data together. Because such a framework has not been readily available, each source tends to use its own terminology and is structured, reasonably so, around its own particular data needs. Such customization is a significant barrier to data integration, because it requires considerable human effort to access each resource, understand the context and content of the data, and determine the conditions under which it can be compared to other similar results. The effect of this customization is that much neuroscience data is opaque to modern computational and bioinformatics tools that can operate across vast amounts of data, but require information to be parsed by a machine in order to be accessed and utilized. In this presentation, I will discuss the current landscape of neuroscience resources and our experiences in establishing standards for global neuroscience information exchange through projects like the Neuroscience Information Framework (http://neuinfo.org), the Whole Brain Catalog (http://wholebraincatalog.org) and the Cell Centered Database (http://ccdb.ucsd.edu).