Phenotype network and brain structural covariance network of anxiety

Je Yeon Yun, Yong Ku Kim

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Network-based approach for psychological phenotypes assumes the dynamical interactions among the psychiatric symptoms, psychological characteristics, and neurocognitive performances arise, as they coexist, propagate, and inhibit other components within the network of mental phenomena. For differential types of dataset from which the phenotype network is to be estimated, a Gaussian graphical model, an Ising model, a directed acyclic graph, or an intraindividual covariance network could be used. Accordingly, these network-based approaches for anxiety-related psychological phenomena have been helpful in quantitative and pictorial understanding of qualitative dynamics among the diverse psychological phenomena as well as mind-environment interactions. Brain structural covariance refers to the correlative patterns of diverse brain morphological features among differential brain regions comprising the brain, as calculated per participant or across the participants. These covarying patterns of brain morphology partly overlap with longitudinal patterns of brain cortical maturation and also with propagating pattern of brain morphological changes such as cortical thinning and brain volume reduction in patients diagnosed with neurologic or psychiatric disorders along the trajectory of disease progression. Previous studies that used the brain structural covariance network could show neural correlates of specific anxiety disorder such as panic disorder and also elucidate the neural underpinning of anxiety symptom severity in diverse psychiatric and neurologic disorder patients.

Original languageEnglish
Title of host publicationAdvances in Experimental Medicine and Biology
PublisherSpringer
Pages21-34
Number of pages14
DOIs
Publication statusPublished - 2020 Jan 1

Publication series

NameAdvances in Experimental Medicine and Biology
Volume1191
ISSN (Print)0065-2598
ISSN (Electronic)2214-8019

Keywords

  • Anxiety disorder
  • Brain magnetic resonance imaging
  • Directed acyclic network
  • Gaussian graphical model
  • Ising model
  • Phenotype network
  • Structural covariance network

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)

Cite this

Yun, J. Y., & Kim, Y. K. (2020). Phenotype network and brain structural covariance network of anxiety. In Advances in Experimental Medicine and Biology (pp. 21-34). (Advances in Experimental Medicine and Biology; Vol. 1191). Springer. https://doi.org/10.1007/978-981-32-9705-0_2