The adage: 'all data is spatial'is especially pertinent in the field of neuroscience, since neuronal data must be indexed by the neuroanatomical location of phenomena or entities under study. Brain atlases are very widely used as laboratory tools, being some of the most highly cited publications in science. This proposal seeks to use brain atlases as a method for indexing data from the literature in a neuroinformatics system. This data includes both textual and graphical information, ranging from highly detailed maps constructed from vector- based spatial primitives, histological photographs and drawings, to textual reports of experimental findings in the literature (which we will analyze on a large scale). These data represent a significant scientific investment that are currently locked away in previously published journal articles (and the detailed data-sets and drawings from researchers that were used to write the articles). A prototype that summarizes the last fifteen years' output of one of the world's most prominent neuroanatomy laboratories is immediately available. This project will develop a collaborative environment to enable neuroscientists to use these valuable maps within the community as a whole by contributing data to a shared system with an open-source system (called 'NeuARt II') that permits querying, overlaying, viewing and annotating such data in an integrated manner. We will also use Natural Language Processing (NLP) techniques to index neuroanatomical references in large numbers of journal articles to be accessible within our infrastructure. As an initial text corpus, we over 110,000 documents taken from last 35 years of published information from the primary neuroanatomical literature. We will construct a neuroanatomical interface that conceptually resembles the 'Google Maps'system, permitting users to use an intuitive spatial interface to browse large amounts of biomedical data in spatial register. The proposed infrastructure will also provide new opportunities to compare and synthesize the anatomical components of neuroscience data multiple modalities (physiological, behavioral, clinical, genetic, molecular, etc.).
Given the scope of the use of neuroanatomical maps from the rat and mouse in the study of neurobiological disease, we expect our research impact scientists working in almost all subfields of the subject. Our collaborators who form the early adopters of this approach are neuroendocrinology researchers studying the mechanisms of stress and anxiety disorders which are estimated to affect 19.1 million people in the USA, costing $42 billion in health care costs per year (source: Anxiety Disorders Association of America). A better understanding of the neuronal mechanisms underlying these disorders could lead to new, effective therapies and treatments.
|Burns, Gully A P C; Turner, Jessica A (2013) Modeling functional Magnetic Resonance Imaging (fMRI) experimental variables in the Ontology of Experimental Variables and Values (OoEVV). Neuroimage 82:662-70|
|Ramakrishnan, Cartic; Patnia, Abhishek; Hovy, Eduard et al. (2012) Layout-aware text extraction from full-text PDF of scientific articles. Source Code Biol Med 7:7|
|Russ, Thomas A; Ramakrishnan, Cartic; Hovy, Eduard H et al. (2011) Knowledge engineering tools for reasoning with scientific observations and interpretations: a neural connectivity use case. BMC Bioinformatics 12:351|
|Tallis, Marcelo; Thompson, Richard; Russ, Thomas A et al. (2011) Knowledge synthesis with maps of neural connectivity. Front Neuroinform 5:24|