Abnormal brain oscillations persist after recovery from bipolar depression

European Psychiatry - Tập 41 - Trang 10-15 - 2017
P. Canali1, S. Casarotto2, M. Rosanova2,3, G. Sferrazza-Papa1, A.G. Casali4, O. Gosseries5,6, M. Massimini2, E. Smeraldi1, C. Colombo1, F. Benedetti1
1Department of clinical neurosciences, scientific institute Ospedale San Raffaele, university Vita-Salute San Raffaele, San Raffaele Turro, 20, via Stamira d’Ancona, 20127 Milano, Italy
2Department of biomedical and clinical sciences “L. Sacco”, università degli Studi di Milano, Milano, Italy
3Fondazione Europea di Ricerca Biomedica, FERB Onlus, Milan, Italy
4Institute of science and technology, Federal university of São Paulo, 330, Rua Talim, São José dos Campos, Brazil
5Coma science group, GIGA research & neurology department, university hospital of Liège, Liège, Belgium
6Center for sleep and consciousness, Postle laboratory, department of psychology and psychiatry, university of Wisconsin, Madison, WI, USA

Tóm tắt

AbstractWhen directly perturbed in healthy subjects, premotor cortical areas generate electrical oscillations in the beta range (20–40 Hz). In schizophrenia, major depressive disorder and bipolar disorder (BD), these oscillations are markedly reduced, in terms of amplitude and frequency. However, it still remains unclear whether these abnormalities can be modulated over time, or if they can be still observed after treatment. Here, we employed transcranial magnetic stimulation (TMS) combined with EEG to assess the frontal oscillatory activity in eighteen BD patients before/after antidepressant treatments (sleep deprivation and light therapy), relative to nine healthy controls. In order to detect dominant frequencies, event related spectral perturbations (ERSP) were computed for each TMS/EEG session in all participants, using wavelet decomposition. The natural frequency at which the cortical circuit oscillates was calculated as the frequency value with the largest power across 300 ms post-stimulus time interval. Severity of depression markedly decreased after treatment with 12 patients achieving response and nine patients achieving remission. TMS/EEG resulted in a significant activation of the beta/gamma band response (21–50 Hz) in healthy controls. In patients, the main frequencies of premotor EEG responses to TMS did not significantly change before/after treatment and were always significantly lower than those of controls (11–27 Hz) and comparable in patients achieving remission and in those not responding to treatment. These results suggest that the reduction of natural frequencies is a trait marker of BD, independent from the clinical status of the patients. The present findings shed light on the neurobiological underpinning of severe psychiatric disorders and demonstrate that TMS/EEG represents a unique tool to develop biomarkers in psychiatry.

Tài liệu tham khảo

10.1007/BF02513307 10.1126/science.1117256 10.1016/j.biopsych.2012.09.032 10.1007/s00401-011-0881-4 10.1016/j.jad.2013.11.023 10.1016/j.npbr.2014.02.001 10.1016/j.neulet.2008.07.081 10.1016/j.tics.2012.12.003 10.1016/j.neuron.2011.06.004 10.1192/bjp.162.3.413 Başar, 2013, Brain oscillations in neuropsychiatric disease, Dialogues Clin Neurosci., 15, 291, 10.31887/DCNS.2013.15.3/ebasar 10.1126/science.274.5288.740 10.1016/j.jad.2011.02.028 10.1016/S0163-7258(00)00038-3 10.1038/npp.2009.168 10.1126/science.1099745 10.1523/JNEUROSCI.0445-09.2009 Rosanova, 2012, Neuronal network analysis concepts and experimental approaches, 435 10.4088/JCP.8125tx12c 10.1067/mcp.2001.113989 10.1016/j.neuroimage.2009.09.026 10.1007/s11481-016-9672-y 10.1093/brain/awu149 10.1017/S1461145710001616 McCulloch, 2008, Generalized, linear, and mixed models 10.1016/S0165-0327(00)00247-0 10.1016/j.bandl.2015.01.003 10.1007/s10548-012-0265-7 10.1111/bdi.12249 10.4088/JCP.13m08455 10.1016/j.jad.2014.12.030 10.1016/B978-0-7020-5307-8.00014-4 Hill, 2006, methods and applications. A comprehensive reference for science, industry, and data mining, General Linear Models, StatSoft, Tulsa (OK)., 18, 245 10.1016/j.bbr.2008.08.049 10.1038/sj.mp.4002130 10.1038/nature07991 10.1016/S0893-133X(01)00225-1 10.1113/jphysiol.2004.074641 10.1126/science.274.5284.109 10.1016/j.schres.2009.06.012 10.1016/j.biopsych.2006.08.048 10.1016/j.neulet.2008.08.080 Uhlhaas, 2013, High-frequency oscillations and the neurobiology of schizophrenia, Dialogues Clin Neurosci., 15, 301, 10.31887/DCNS.2013.15.3/puhlhaas 10.1016/j.euroneuro.2013.07.007 10.1523/JNEUROSCI.2213-07.2007 10.1371/journal.pone.0006755 10.1016/j.jad.2015.05.043 10.1038/35067550 10.1097/HRP.0000000000000007 10.1002/dneu.20814 10.1016/j.biopsych.2011.12.010 10.1016/S0167-8760(00)00136-7 10.1093/schbul/sbn070 10.1038/nrn2044 10.1016/j.neuron.2010.09.017 Buzsaki, 2012, Brain rhythms and neural syntax: implications for efficient coding of cognitive content and neuropsychiatric disease, Dialogues Clin Neurosci., 14, 345, 10.31887/DCNS.2012.14.4/gbuzsaki 10.1001/archpsyc.64.2.179 10.1093/schbul/sbn062 Timm, 2006, Univariate and multivariate general linear models: theory and applications with SAS 10.1016/j.jneumeth.2003.10.009 10.3389/neuro.09.033.2009 10.1371/journal.pone.0010281