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Complexity analysis of spontaneous brain activity in mood disorders: A magnetoencephalography study of bipolar
Alberto Fernández1, Ali H Al-Timemy2, Francisco Ferre3
1Department of Psychiatry, Faculty of Medicine, Complutense University, Madrid, Spain; Laboratory of Cognitive and Computational Neuroscience, Centre for Biomedical Technology (CTB), Technical University and Complutense University, Madrid, Spain.
Background And Purpose:
The lack of a biomarker for Bipolar Disorder (BD) causes problems in the differential diagnosis with other mood disorders such as major depression (MD), and misdiagnosis frequently occurs. Bearing this in mind, we investigated non-linear magnetoencephalography (MEG) patterns in BD and MD.
Methods:
Lempel-Ziv Complexity (LZC) was used to evaluate the resting-state MEG activity in a cross-sectional sample of 60 subjects, including 20 patients with MD, 16 patients with BD type-I, and 24 control (CON) subjects. Particular attention was paid to the role of age. The results were aggregated by scalp region.
Results:
Overall, MD patients showed significantly higher LZC scores than BD patients and CONs. Linear regression analyses demonstrated distinct tendencies of complexity progression as a function of age, with BD patients showing a divergent tendency as compared with MD and CON groups. Logistic regressions confirmed such distinct relationship with age, which allowed the classification of diagnostic groups.
Conclusions:
The patterns of neural complexity in BD and MD showed not only quantitative differences in their non-linear MEG characteristics but also divergent trajectories of progression as a function of age. Moreover, neural complexity patterns in BD patients resembled those previously observed in schizophrenia, thus supporting preceding evidence of common neuropathological processes.
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