Journal
HUMAN BRAIN MAPPING
Volume 39, Issue 7, Pages 2764-2776Publisher
WILEY
DOI: 10.1002/hbm.24038
Keywords
correspondence analysis; meta-analysis; multivariate; Neurosynth; recommendation engine; semantic analysis
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The functional neuroimaging literature has become increasingly complex and thus difficult to navigate. This complexity arises from the rate at which new studies are published and from the terminology that varies widely from study-to-study and even more so from discipline-to-discipline. One way to investigate and manage this problem is to build a semantic space that maps the different vocabulary used in functional neuroimaging literature. Such a semantic space will also help identify the primary research domains of neuroimaging and their most commonly reported brain regions. In this work, we analyzed the multivariate semantic structure of abstracts in Neurosynth and found that there are six primary domains of the functional neuroimaging literature, each with their own preferred reported brain regions. Our analyses also highlight possible semantic sources of reported brain regions within and across domains because some research topics (e.g., memory disorders, substance use disorder) use heterogeneous terminology. Furthermore, we highlight the growth and decline of the primary domains over time. Finally, we note that our techniques and results form the basis of a recommendation engine that could help readers better navigate the neuroimaging literature.
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