Author(s)

M. O. Sokunbi, V. B. Gradin, G. D. Waiter, G. G. Cameron, T. S. Ahearn, A. D. Murray, D. J. Steele, R. T. Staff

ISBN

1932-6203 (Electronic) 1932-6203 (Linking)

Publication year

2014

Periodical

PLoS One

Periodical Number

5

Volume

9

Pages

e95146

Author Address

Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, United Kingdom; Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, United Kingdom; Institute of Psychological Medicine and Clinical Neurosciences, Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Cardiff School of Medicine, Cardiff University, Cardiff, United Kingdom. Medical Research Institute, University of Dundee, Dundee, United Kingdom; Centre for Basic Research in Psychology, Universidad de la Republica, Montevideo, Uruguay. Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, United Kingdom. Medical Research Institute, University of Dundee, Dundee, United Kingdom. Department of Nuclear Medicine, Aberdeen Royal Infirmary, Aberdeen, United Kingdom.

Full version

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.