Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Nonlinear complexity analysis of brain fMRI signals in schizophrenia

Sokunbi, Moses, Gradin, Victoria B., Waiter, Gordon D., Cameron, George G., Ahearn, Trevor S., Murray, Alison D., Steele, Douglas J. and Staff, Roger T. 2014. Nonlinear complexity analysis of brain fMRI signals in schizophrenia. PLoS ONE 9 (5) , e95146. 10.1371/journal.pone.0095146

[thumbnail of Sokunbi journal.pone.0095146.pdf]
Preview
PDF - Published Version
Available under License Creative Commons Attribution.

Download (709kB) | Preview

Abstract

We investigated the differences in brain fMRI signal complexity in patients with schizophrenia while performing the Cyberball social exclusion task, using measures of Sample entropy and Hurst exponent (H). 13 patients meeting diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM IV) criteria for schizophrenia and 16 healthy controls underwent fMRI scanning at 1.5 T. The fMRI data of both groups of participants were pre-processed, the entropy characterized and the Hurst exponent extracted. Whole brain entropy and H maps of the groups were generated and analysed. The results after adjusting for age and sex differences together show that patients with schizophrenia exhibited higher complexity than healthy controls, at mean whole brain and regional levels. Also, both Sample entropy and Hurst exponent agree that patients with schizophrenia have more complex fMRI signals than healthy controls. These results suggest that schizophrenia is associated with more complex signal patterns when compared to healthy controls, supporting the increase in complexity hypothesis, where system complexity increases with age or disease, and also consistent with the notion that schizophrenia is characterised by a dysregulation of the nonlinear dynamics of underlying neuronal systems.

Item Type: Article
Date Type: Publication
Status: Published
Schools: MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG)
Cardiff University Brain Research Imaging Centre (CUBRIC)
Medicine
Subjects: R Medicine > R Medicine (General)
Publisher: Public Library of Science
ISSN: 1932-6203
Date of First Compliant Deposit: 30 March 2016
Last Modified: 26 May 2023 13:28
URI: https://orca.cardiff.ac.uk/id/eprint/63780

Citation Data

Cited 80 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics