title: Large-scale extraction of brain connectivity from the neuroscientific literature.
abstract: BACKGROUND
  In neuroscience, as in many other scientific domains, the primary form of knowledge dissemination is through published articles. One challenge for modern neuroinformatics is finding methods to make the knowledge from the tremendous backlog of publications accessible for search, analysis and the integration of such data into computational models. A key example of this is metascale brain connectivity, where results are not reported in a normalized repository. Instead, these experimental results are published in natural language, scattered among individual scientific publications. This lack of normalization and centralization hinders the large-scale integration of brain connectivity results. In this article, we present text-mining models to extract and aggregate brain connectivity results from 13.2 million PubMed abstracts and 630 216 full-text publications related to neuroscience. The brain regions are identified with three different named entity recognizers (NERs) and then normalized against two atlases: the Allen Brain Atlas (ABA) and the atlas from the Brain Architecture Management System (BAMS). We then use three different extractors to assess inter-region connectivity.
  
  
  RESULTS
  NERs and connectivity extractors are evaluated against a manually annotated corpus. The complete in litero extraction models are also evaluated against in vivo connectivity data from ABA with an estimated precision of 78%. The resulting database contains over 4 million brain region mentions and over 100 000 (ABA) and 122 000 (BAMS) potential brain region connections. This database drastically accelerates connectivity literature review, by providing a centralized repository of connectivity data to neuroscientists.
authors.affiliation: Blue Brain Project, Brain Mind Institute and School of Computer and Communication Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
authors.forename: Renaud
authors.initials: R
authors.lastname: Richardet
authors.affiliation: Blue Brain Project, Brain Mind Institute and School of Computer and Communication Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
authors.forename: Jean-Cédric
authors.initials: JC
authors.lastname: Chappelier
authors.affiliation: Blue Brain Project, Brain Mind Institute and School of Computer and Communication Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
authors.forename: Martin
authors.initials: M
authors.lastname: Telefont
authors.affiliation: Blue Brain Project, Brain Mind Institute and School of Computer and Communication Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
authors.forename: Sean
authors.initials: S
authors.lastname: Hill
mesh_terms: D000818:Animals; D001185:Artificial Intelligence; D001271:Atlases as Topic; D001921:Brain / Q000033:anatomy & histology* / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D057225:Data Mining / Q000379:methods*; D016208:Databases, Factual; D051379:Mice; D009445:Neuroanatomy; D010506:Periodicals as Topic; D012984:Software; D009626:Terminology as Topic