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Complexity analysis of spontaneous brain activity: Effects of depression and antidepressant treatment

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Méndez, María Andreína and Zuluaga Arias, Pilar and Hornero, Roberto and Gómez, Carlos and Escudero, Javier and Rodríguez Palancas, Alfonso and Ortiz, Tomás and Fernández, Alberto (2012) Complexity analysis of spontaneous brain activity: Effects of depression and antidepressant treatment. Journal of psychopharmacology, 26 (5). pp. 636-643. ISSN 0269-8811

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Official URL: http://jop.sagepub.com/content/26/5/636.short




Abstract

Magnetoencephalography (MEG) allows the real-time recording of neural activity and oscillatory activity in distributed neural networks. We applied a non-linear complexity analysis to resting-state neural activity as measured using whole-head MEG. Recordings were obtained from 20 unmedicated patients with major depressive disorder and 19 matched healthy controls. Subsequently, after 6 months of pharmacological treatment with the antidepressant mirtazapine 30 mg/day, patients received a second MEG scan. A measure of the complexity of neural signals, the Lempel–Ziv Complexity (LZC), was derived from the MEG time series. We found that depressed patients showed higher pre-treatment complexity values compared with controls, and that complexity values decreased after 6 months of effective pharmacological treatment, although this effect was statistically significant only in younger patients. The main treatment effect was to recover the tendency observed in controls of a positive correlation between age and complexity values. Importantly, the reduction of complexity with treatment correlated with the degree of clinical symptom remission. We suggest that LZC, a formal measure of neural activity complexity, is sensitive to the dynamic physiological changes observed in depression and may potentially offer an objective marker of depression and its remission after treatment.


Item Type:Article
Uncontrolled Keywords:Depression, dynamical disease, Lempel-Ziv Complexity, mirtazapine, MEG, symptoms' remission
Subjects:Sciences > Mathematics > Applied statistics
Medical sciences > Biology
ID Code:30520
Deposited On:29 May 2015 09:08
Last Modified:13 Jul 2015 11:38

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