electrostimulation therapy application for patients
suffering from depression. The neuro-
electrostimulation procedures were tested in two
modes – multichannel and single-channel
stimulation.
Summarizing the analysis of visualization of the
spectral power density of EEG, it can be concluded
that the most significant changes have been observed
for patients CH794 and CH798. At the same time,
changes for patient CH794 (from the group of
multichannel stimulation) had been more
pronounced, while for patient CH798 (from the
group of single-channel stimulation), the changes
had been asymmetric. In general, for all patients, an
increase in EEG power uniformity has been
observed.
A quantitative method for estimating the level of
activation of brain zones has been proposed. Initial
data (prior to the neuro-electrostimulation
procedures application) were used to estimate the
average level of the EEG spectrogram value in the
zone over the entire time interval for all channels
(activation threshold). Then, for each time epoch,
the proportion of channels that exceed the activation
threshold was estimated. The same activation
threshold was used in the analysis of signals
recorded after neuro-electrostimulation procedures.
Considering the evaluation of the brain areas
activation level, it could be concluded that an
increase in the level of activation was observed for
patients from the group of multichannel stimulation,
this is especially pronounced for patient CH794. It
was noted that for patients from the single-channel
stimulation group there were zones in which a
significant decrease in the level of activation was
observed.
ACKNOWLEDGEMENTS
The EEG signals data acquisition within the study
(Chapter 2) was supported by the Act 211 of the
Government of the Russian Federation (contract no.
02.A03.21.0006). The EEG signals data processing
(Chapter 3) was funded by RFBR (project no, 18-29-
02052).
REFERENCES
Cook, I.A., Abrams, M., and Leuchter, A.F., 2016.
Trigeminal nerve stimulation for comorbid
posttraumatic stress disorder and major depressive
disorder. Neuromodulation: Technology at the Neural
Interface, 19 (3), 299–305.
Culpepper, L., Muskin, P.R., and Stahl, S.M., 2015. Major
depressive disorder: understanding the significance of
residual symptoms and balancing efficacy with
tolerability. The American journal of medicine, 128
(9), S1–S15.
Danilov, Y., Kaczmarek, K., Skinner, K., and Tyler, M.,
2015. Cranial Nerve Noninvasive Neuromodulation:
New Approach to Neurorehabilitation. In: F.H.
Kobeissy, ed. Brain Neurotrauma: Molecular,
Neuropsychological, and Rehabilitation Aspects. Boca
Raton (FL): CRC Press/Taylor & Francis.
Delorme, A. and Makeig, S., 2004. EEGLAB: an open
source toolbox for analysis of single-trial EEG
dynamics including independent component analysis.
Journal of neuroscience methods, 134 (1), 9–21.
Kublanov, V., Babich, M., and Dolganov, A., 2017.
Principles of Organization and Control of the New
Implementation of the “SYMPATHOCOR-01” Neuro-
electrostimulation Device. Presented at the Special
Session on Neuro-electrostimulation in
Neurorehabilitation Tasks, 276–282.
Kupfer, D.J., Frank, E., and Phillips, M.L., 2012. Major
depressive disorder: new clinical, neurobiological, and
treatment perspectives. The Lancet, 379 (9820), 1045–
1055.
Oostenveld, R. and Praamstra, P., 2001. The five percent
electrode system for high-resolution EEG and ERP
measurements. Clinical neurophysiology, 112 (4),
713–719.
Petrenko, T.S., Kublanov, V.S., and Retiunskiy, K.Y.,
2015. Dynamic Correction of the Activity Sympathetic
Nervous System (Dcasns) to Restore Cognitive
Functions. European Psychiatry, 30, 843.
Schmaal, L., Hibar, D.P., Sämann, P.G., Hall, G.B.,
Baune, B.T., Jahanshad, N., Cheung, J.W., van Erp,
T.G.M., Bos, D., and Ikram, M.A., 2017. Cortical
abnormalities in adults and adolescents with major
depression based on brain scans from 20 cohorts
worldwide in the ENIGMA Major Depressive
Disorder Working Group. Molecular psychiatry, 22
(6), 900–909.
Sokolov, A.V., Vorobyev, S.V., Efimtcev, A.Y., Dekan,
V.S., Trufanov, G.E., Lobzin, V.Y., and Fokin, V.A.,
2017. fMRI and Voxel-based Morphometry in
Detection of Early Stages of Alzheimer’s Disease: In:
Proceedings of the 10th International Joint
Conference on Biomedical Engineering Systems and
Technologies. Presented at the 4th International
Conference on Bioimaging, Porto, Portugal:
SCITEPRESS - Science and Technology Publications,
67–71.
Welch, P., 1967. The use of fast Fourier transform for the
estimation of power spectra: a method based on time
averaging over short, modified periodograms. IEEE
Transactions on audio and electroacoustics, 15 (2),
70–73.