On the nature and use of models in network neuroscience.

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TitleOn the nature and use of models in network neuroscience.
Publication TypeJournal Article
Year of Publication2018
AuthorsBassett, DS, Zurn, P, Gold, JI
JournalNat Rev Neurosci
Volume19
Issue9
Pagination566-578
Date Published2018 Sep
ISSN1471-0048
Abstract

Network theory provides an intuitively appealing framework for studying relationships among interconnected brain mechanisms and their relevance to behaviour. As the space of its applications grows, so does the diversity of meanings of the term network model. This diversity can cause confusion, complicate efforts to assess model validity and efficacy, and hamper interdisciplinary collaboration. In this Review, we examine the field of network neuroscience, focusing on organizing principles that can help overcome these challenges. First, we describe the fundamental goals in constructing network models. Second, we review the most common forms of network models, which can be described parsimoniously along the following three primary dimensions: from data representations to first-principles theory; from biophysical realism to functional phenomenology; and from elementary descriptions to coarse-grained approximations. Third, we draw on biology, philosophy and other disciplines to establish validation principles for these models. We close with a discussion of opportunities to bridge model types and point to exciting frontiers for future pursuits.

DOI10.1038/s41583-018-0038-8
Alternate JournalNat. Rev. Neurosci.
PubMed ID30002509
PubMed Central IDPMC6466618
Grant ListR01 EY015260 / EY / NEI NIH HHS / United States
R01 NS099348 / NS / NINDS NIH HHS / United States
R01 DC009209 / DC / NIDCD NIH HHS / United States
R21 MH106799 / MH / NIMH NIH HHS / United States
RF1 MH116920 / MH / NIMH NIH HHS / United States
R01 MH113550 / MH / NIMH NIH HHS / United States
R01 HD086888 / HD / NICHD NIH HHS / United States
R01 MH115557 / MH / NIMH NIH HHS / United States