Brain Research in the Digital Age Mark H. Ellisman
University of San Diego, USA
University of San Diego, USA
Abstract: A grand goal in neuroscience research is to understand how the interplay of structural, chemical and electrical signals in nervous tissue gives rise to behavior. We are rapidly approaching this horizon as neuroscientists make use of an increasingly powerful arsenal of instruments and tools for obtaining data, from the level of molecules to nervous systems, and engage in the arduous and challenging process of adapting and assembling neuroscience data at all scales of resolution and across disciplines into computerized databases. A consolidated strategy for integrating neuroscience data has been to provide a multi-scale structural or spatial scaffold on which existing and accruing elements of neuroscience knowledge can be located and relationships explored from any network-linked computer. Similarly, efforts to integrate multi-scale microscopy data from different imaging methods using a common spatial framework are hampered by incomplete descriptions of the microanatomy of nervous systems. While some spatial and temporal scales are well studied and described, there are many domains where current methods have provided only sparse descriptions. Multi-scale imaging activities currently providing data to populate this brain information scaffold will be highlighted, with particular reference to those emerging with capabilities to facilitate mapping at a resolution of one nm to 10's of µm - a dimensional range that encompasses macromolecular complexes, organelles, and multi-component structures such as synapses and cellular interactions in the context of the complex organization of the brain. This effort also provides multi-scale structural frameworks for construction of models being used to test hypotheses not amenable to direct experimental analysis using software tools that allow for computational simulation of microphysiological properties of nervous systems.
