Connectivity and dysconnectivity: A brief history of functional connectivity research in schizophrenia and future directions

Eva Mennigen, Barnaly Rashid, Vince D. Calhoun

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

In this chapter, we delve into clinical applications of functional connectivity (FC) analyses using the example of schizophrenia. Schizophrenia is not only one of the most common psychiatric disorders but also one of the most debilitating ones. Further, its diverse clinical symptoms and neurodevelopmental aspects suggest involvement of various brain areas and networks, which renders it as a distinguished brain disorder to apply FC analyses to better understand the underlying disease pathophysiology.After presenting an overview on schizophrenia itself, we summarize the most commonly implemented FC approaches applied in schizophrenia research: graph theory, seed-based, and independent component analysis (ICA) approaches. We discuss findings from these approaches and highlight possible future directions of schizophrenia research. Despite the evident mathematical differences between these approaches, some commonalities are noticed: an anatomical overlap across studies, distinct patterns of dysconnectivity, and less flexible brain connectivity in patients with schizophrenia.

Original languageEnglish (US)
Title of host publicationConnectomics
Subtitle of host publicationApplications to Neuroimaging
PublisherElsevier
Pages123-154
Number of pages32
ISBN (Electronic)9780128138397
ISBN (Print)9780128138380
DOIs
StatePublished - Sep 12 2018
Externally publishedYes

Keywords

  • Connectivity
  • Dysconnectivity
  • Graph theory
  • Independent component analysis
  • Schizophrenia

ASJC Scopus subject areas

  • Computer Science(all)

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