Brain networks, structural realism, and local approaches to the scientific realism debate

Karen Yan*, Jonathon Hricko

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

We examine recent work in cognitive neuroscience that investigates brain networks. Brain networks are characterized by the ways in which brain regions are functionally and anatomically connected to one another. Cognitive neuroscientists use various noninvasive techniques (e.g., fMRI) to investigate these networks. They represent them formally as graphs. And they use various graph theoretic techniques to analyze them further. We distinguish between knowledge of the graph theoretic structure of such networks (structural knowledge) and knowledge of what instantiates that structure (nonstructural knowledge). And we argue that this work provides structural knowledge of brain networks. We explore the significance of this conclusion for the scientific realism debate. We argue that our conclusion should not be understood as an instance of a global structural realist claim regarding the structure of the unobservable part of the world, but instead, as a local structural realist attitude towards brain networks in particular. And we argue that various local approaches to the realism debate, i.e., approaches that restrict realist commitments to particular theories and/or entities, are problematic insofar as they don't allow for the possibility of such a local structural realist attitude.

Keywords

  • Brain networks
  • Cognitive neuroscience
  • Graph theory
  • Local approaches
  • Structural realism

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