[ Moscow University ]  [ Lab. for Neurophysiology and Neuro-Computer Interfaces ]

РУССКИЙ

Alexander Ya. Kaplan Александр Яковлевич Каплан Professor, D.Sc. (psychophysiology and psychopharmacology), Ph.D. (neurophysiology) Head of the Laboratory for Neurophysiology and Neuro-Computer Interfaces Department of Human Physiology Faculty of Biology M.V. Lomonosov Moscow State University Moscow 119991, Russia Tel: +7 (495) 939 13 73 Fax: +7 (495) 939 43 09 E-mail: Web: http://brain.bio.msu.ru/   Research Projects Current projects Brain Computer Interfaces (BCI), Grant #1110034 from Skolkovo foundation. Nonstationarity of EEG. Experimental and theoretical analysis of mechanisms underlying human brain microstates during mental activity and in pathological states. Algorithms and software for the segmental analysis of EEG. Classification of the EEG patterns based on normal and pathological (schizophrenia) teaching sets. Previous projects (main topics) EEG assisted neurotropic drug design (new nootropic SEMAX - Government prize first category) EEG-based automatic sleep staging and microstructure analysis High precision EEG processing Fundamentals and applications of Brain Computer Interfaces (BCI), with emphasis on: - two or three-dimensional EEG control of external moving objects - instrumental learning for skills acquisition in the BCI framework - unconscious mode of neurofeedback

Click here to view many PHOTOS with colleagues, collaborators, and other EEG experts: Old Album XX (EEG Nonstationarity) New Album XXI (The BCI Millenium)

 
For more details on research projects, see Research of the Human Brain Research Group.
 

 
Alexander Kaplan received his M.S., Ph.D., and D.Sci. degrees from the M.V. Lomonosov Moscow State Universuty (Faculty of Biology), Russia. After spending ten years in the department of Higher Nervous Activity as Senior Research Scientist, he joined Department of Human Physiology, where he became Leading Research Scientist and Professor in Psychophysiology, Head of the Human Brain Research Group and later, Head of the Laboratory for Neurophysiology and Neuro-Computer Interfaces.

In 2003, he received Russian Government Science and Technology Prize (the top governmental science award).
 

PhD Graduates
supervised at Human Brain Research Group by A.Kaplan:

• Arina G. Kochetova (1997) Inter-hemispheric asymmetry and visual-motor processes in humans during operator mnestic activity.
• Sergei L. Shishkin (1997) A study of synchronization of instants of abrupt changes in human EEG alpha activity.
• Lotfali M. Massoumi (Islamic Republic of Iran) (1997) Experimental analysis of caffeine and sydnocarb influence on memory recollection in humans.
• Alexander A. Fingelkurts (1998) Some regularities of human EEG spectral patterns dynamics during cognitive activity.
• Andrew A. Fingelkurts (1998) Time-spatial organization of human EEG segmental structure.
• Anastasia V. Kovaleva (1999) Physiological and psychological prerequisites of adaptation disruptions in children of 1-3 school year.
• Sergei V. Borisov (2002) Investigation of the phasic structure of human EEG alpha-rhythm.
• Ekaterina V. Levichkina (2007) EEG investigation of the mechanisms of visual image development in human.
• Alexander Yu. Zhigalov (2009) A study of human EEG alpha activity dynamics in the brain computer interface loop.
• Andrey S. Romanov (2012) A study of spatial synchronization of human evoked brain electrical activity in response to acoustic stimuli using wavelet analysis.
• Ilya P. Ganin (2013) The P300 based brain-computer interface: a study of the repetition and stimulus movement effects.
• Anatoly N. Vasilyev (2018) Activation patterns of human sensorimotor cortex during motor imagery.
• Sofya P. Liburkina (2018) Ideomotor training with brain-computer interface in neurorehabilitation.

Currently Advised:

• Nikolay V. Syrov, PhD project
• Lev V. Yakovlev, PhD project
• Anna S. Pronina, PhD project
• Ivan A. Basul, PhD project (co-advisor: V. A. Barabanschikov)
• Rafael Grigorian, PhD project

• N. Grigorev, A. Savosenkov, M. Lukoyanov, A. Udoratina, N. Shusharina, A. Kaplan, et al. A BCI-based vibrotactile neurofeedback training improves motor cortical excitability during motor imagery. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2021. [ DOI: 10.1101/2021.02.28.433220 ]
• L. Yakovlev, N. Syrov, N. Gortz, A. Kaplan. BCI-Controlled Motor Imagery Training Can Improve Performance in e-Sports. Communications in Computer and Information Science. 2020;1224:581–6.
• N. Syrov, D. Bredichin, A. Kaplan. Processing of Sensory Information is Affected by BCI Feedback Being Perceived. Communications in Computer and Information Science. 2020(1224):575–80.
• Ganin I. P., Kim S. A., Liburkina S. P., Galkina N.V., Luzhin A. O., Mayorova L. A., Malyukova N.G. Shklovsky V.M. Kaplan A.Y. Text typing in patients with post-stroke afasia in the P300 brain-computer interface based "Neurochat" complex. Zhurnal vysshei nervnoi deyatelnosti imeni I.P. Pavlova. 2020. 70(4), 435-445. (In Russian.)
  Ганин И.П., Ким С.А., Либуркина С.П., Галкина Н.В., Лужин А.О., Майорова Л.А., Малюкова Н.Г., Шкловский В.М., Каплан А.Я. Набор текста пациентами с постинсультной афазией в комплексе «НейроЧат» на основе технологии интерфейсов мозг-компьютер на волне P300. Журн. высш. нерв. деят. 2020. 70(4): 435-445. [ DOI: 10.31857/S0044467720040036 ] [ PDF ]
• E.Y. Morozova, D.V. Skvortsov, A.Y. Kaplan. Learning Motor Imagery under EEG-Directed Neuromuscular Stimulation Inducing Congruent and Incongruent Wrist Movements. Human Physiology. 2019;45(4):378–82.
• I.P. Ganin, E.A. Kosichenko, A.V. Sokolov, O.M. Ioannisyanc, I.M. Arefev, A.Y. Basova, et al. Adapting the p300 brain-computer interface technology to assess condition of anorexia nervosa patients. Bulletin of RSMU. 2019(2):32–8.
• K. Volkova, M. Lebedev, A. Kaplan, A. Ossadtchi. Decoding Movement from Electrocorticographic Activity: a Review. Frontiers in Neuroinformatics. 2019;13(74).
• L. Iakovlev, N. Syrov, E. Morozova, J. Lee, A. Kaplan. The study of excitability of motor cortex with motor imagery and simultaneous electrical stimulation. European Neuropsychopharmacology. 2019;29(6):398–9.
• L.V. Yakovlev, N.V. Syrov, E.Y. Morozova, A.Y. Kaplan. Corticospinal Excitability in Humans during Motor Imagery Coupled with Functional Electrical Stimulation. Moscow University Biological Sciences Bulletin. 2019;74(3):183–7.
• N.V. Syrov, K.A. Novichikhina, D.A. Kiryanov, S.Y. Gordleeva, A.Y. Kaplan. The Changes of Corticospinal Excitability During the Control of Artificial Hand Through the Brain–Computer Interface Based on the P300 Component of Visual Evoked Potential. Физиология человека. 2019;45(2):152–7.
• R.K. Grigoryan, D.B. Filatov, A.Y. Kaplan. High-speed brain-computer communication interface based on code-modulated visual evoked potentials. Bulletin of RSMU. 2019(2):26–31.
• Ganin I.P., Kosichenko E.A., Kaplan A.Ya. Properties of EEG Responses to Emotionally Significant Stimuli Using a P300 Wave-Based Brain–Computer Interface. Neuroscience and Behavioral Physiology. 2018; 48(9): 1093-1099. [ DOI: 10.1007/s11055-018-0672-7 ] [ PDF ]
• M.V. Lukoyanov, S.Y. Gordleeva, A.S. Pimashkin, N.A. Grigor’ev, A.V. Savosenkov, A. Motailo, et al. THE EFFICIENCY OF THE BRAIN-COMPUTER INTERFACES BASED ON MOTOR IMAGERY WITH TACTILE AND VISUAL FEEDBACK. Human Physiology. 2018;44(2):280–8.
• R.K. Grigoryan, E.U. Krysanova, D.A. Kirjanov, A.Y. Kaplan. Visual Stimuli for P300-Based Brain-Computer Interfaces: Color, Shape, and Mobility. Moscow University Biological Sciences Bulletin. 2018;73(2):92–6.
• S.P. Liburkina, A.N. Vasilyev, L.V. Yakovlev, S.Y. Gordleeva, A.Y. Kaplan. A Motor Imagery-Based Brain–Computer Interface with Vibrotactile Stimuli. Neuroscience and Behavioral Physiology. 2018;48(9):1067–77.
• A. Piryatinska, B. Darkhovsky, A. Kaplan. Binary classification of multichannel-EEG records based on the o-complexity of continuous vector functions. Computer Methods and Programs in Biomedicine. 2017. 152:131-139. [ DOI: 10.1016/j.cmpb.2017.09.001 ]
• A.Vasilyev, S.Liburkina, L.Yakovlev, O. Perepelkina, A.Kaplan. Assessing motor imagery in brain-computer interface training: Psychological and neurophysiological correlates. Neuropsychologia, Pergamon Press Ltd. (United Kingdom). 2017. 97:56-65. [ DOI: 10.1016/j.neuropsychologia.2017.02.005 ]
• A.Kaplan, A.Vasilyev, S.Liburkina,L.Yakovlev. Poor BCI Performers Still Could Benefit from Motor Imagery Training. In Foundations of Augmented Cognition: Neuroergonomics and Operational Neuroscience, Lecture Notes in Computer Science, Springer International Publishing Cham, Switzerland. 2016. 9743:46-56. [ DOI: 10.1007/978-3-319-39955-3_5 ] [ PDF ]
• A.Y.Zhigalov, A.Y. Kaplan, J.M. Palva. Modulation of critical brain dynamics using closed-loop neurofeedback stimulation. Clinical Neurophysiology. 2016. Accepted: 30 April 2016. [ DOI: 10.1016/j.clinph.2016.04.028 ] [ PDF ]
• A.Ya. Kaplan, D.D. Zhigulskaya, D.A. Kirjanov. Studying the ability to control human phantom fingers in P300 brain-computer interface. Vestnik RGMU 2016. 2: 26-30. (In Russian.) [ PDF ]
  А.Я. Каплан, Д.Д. Жигульская, Д.А. Кирьянов. Изучение возможности управления отдельными пальцами фантома кисти руки человека в контуре интерфейса мозг–компьютер на волне P300. Вестник Российского государственного медицинского университета. 2016. 2: 26-30. [ PDF ]
• A.N. Vasilyev, S.P. Liburkina, A.Ya. Kaplan. Lateralization of EEG Patterns in Humans during Motor Imagery of Arm Movements in the Brain–Computer Interface. Zh Vyssh Nerv Deiat Im I P Pavlova 2016. 66(3): 302-312. (In Russian.)
  А.Н. Васильев, С.П. Либуркина, А.Я. Каплан. Латерализация паттернов ЭЭГ у человека при представлении движений руками в интерфейсе мозг-компьютер. Журнал высшей нервной деятельности им. И. П. Павлова. 2016. 66(3): 302-312. [ PDF ]
• A.Ya. Kaplan. Neurophysiological Foundations and Practical Realizations of the Brain-Machine Interfaces the Technology in Neurological Rehabilitation. Fiziologiya cheloveka 2016. 42(1): 118-127. (In Russian.)
  А. Я. Каплан. Нерофизиологические основания и практические реализации технологии мозг-машинных интерфейсов в неврологической реабилитации. Физиология человека. 2016. 42(1): 118-127. [ PDF ]
• I.A.Basyul, A.Y. Kaplan. Changes in the N200 and P300 Components of Event-Related Potentials on Variations in the Conditions of Attention in a Brain–Computer Interface System. Neuroscience and Behavioral Physiology. 2015. 45(9): 1038-1042. [ HTML ] [ PDF ]
• Ganin I.P., Kaplan A.Ya. The P300-based brain-computer interface: presentation of the complex "flash + movement" stimuli. Zh Vyssh Nerv Deiat Im I P Pavlova 2014. 64(1): 32-40. (In Russian.)
  Ганин И.П., Каплан А.Я. Интерфейс мозг-компьютер на основе волны P300: предъявление комплексных стимулов "подсветка + движение". Журнал высшей нервной деятельности. 2014. 64(1): 32-40. [ PDF ]
• I.P.Ganin, S.L.Shishkin, A.Y.Kaplan. A P300-based brain-computer interface with stimuli on moving objects: four-session single-trial and triple-trial tests with a game-like task design. PLOS ONE. 2013. 8(10): e77755. [ HTML ]
• A.Y.Kaplan, S.L.Shishkin, I.P.Ganin, I.A.Basyul, A.Y.Zhigalov. Adapting the P300-based brain-computer interface for gaming: a review. IEEE Transactions on Computational Intelligence and AI in Games (Special Issue on Brain/Neuronal-Computer Games Interfaces and Interaction). 2013. 5(2): 141-149. [ DOI: 10.1109/TCIAIG.2012.2237517 ] [ PDF ] [ Top accessed ]
• O.Yu.Panischev, S.A.Demin, A.Ya.Kaplan, N.Yu.Varaksina. Use of Cross-Correlation Analysis of EEG Signals for Detecting Risk Level for Development of Schizophrenia. Biomedical Engineering. 2013. 47(3): 153-156. [ PDF ]
• I.P.Ganin, S.L.Shishkin, A.G.Kochetova, A.Y.Kaplan. Experimental and theoretical foundations and practical implementation of brain-computer interface technology. Bulletin of Siberian medicine. 2013. 12(2): 21-29. (In Russian.)
  Каплан А.Я., Кочетова А.Г., Шишкин С.Л., Басюл И.А., Ганин И.П., Васильев А.Н., Либуркина С.П. Экспериментально-теоретические основания и практические реализации технологии «интерфейс мозг – компьютер». Бюллетень сибирской медицины. 2013. 12(2): 21-29. [ PDF ]
• И.П.Ганин, С.Л.Шишкин, А.Г.Кочетова, А.Я.Каплан. Интерфейс мозг-компьютер “на волне P300”: исследование эффекта номера стимулов в последовательности их предъявления. Физиология человека. 2012;38(2):5-13. [ PDF ]
  English version: I.P.Ganin, S.L.Shishkin, A.G.Kochetova, A.Ya.Kaplan. P300-based brain-computer interface: the effect of the stimulus position in a stimulus train. Human Physiology. 2012;38(2):121-128. [ DOI: 10.1134/S0362119712020041 ] [ PDF ]
• S.F.Timashev, O.Yu.Panischev, Y.S.Polyakov, S.A.Demin, A.Ya.Kaplan. Analysis of cross-correlations in electroencephalogram signals as an approach to proactive diagnosis of schizophrenia. Physica A. 2012;391(4):1179-1194. [ DOI: 10.1016/j.physa.2011.09.032 ] [ PDF ]
• S.L.Shishkin, I.P.Ganin, A.Y.Kaplan. Event-related potentials in a moving matrix modification of the P300 brain–computer interface paradigm. Neuroscience Letters. 2011;496(2):95-99. [ DOI: 10.1016/j.neulet.2011.03.089 ] [ PDF ]
• Kaplan A.Ya., Zhigalov A.Yu. The dynamic of human EEG alpha-activity in the loop of brain-computer interface during trigger photo stimulation. Bulletin of Siberian medicine. 2010;9(2):7-11.
  Каплан А.Я., Жигалов А.Ю. Динамика альфа-активности электроэнцефалографии у человека при триггерной фотостимуляции в контуре интерфейса мозг-компьютер. Бюллетень сибирской медицины. 2010;9(2):7-11. [ DOC ]

• Shishkin SL, Ganin IP, Basyul IA, Zhigalov AY, Kaplan AY. N1 wave in the p300 bci is not sensitive to the physical characteristics of stimuli. J Integr Neurosci. 2009 Dec;8(4):471-85. [ PDF ]
• Levichkina E.V., Kaplan A.Ya. Unconscious context control of visual perception of simple stimuli: a study using evoked potentials. Human Physiology. 2009;35(2):152-156. (Transl. from Fiziologiya Cheloveka.) [ PDF ]

• A.Ya. Kaplan, E.V. Levichkina. [Late negativity in visual event-related potentials in humans to changes in topology of simple nonverbal stimuli]. Zh Vyssh Nerv Deiat Im I P Pavlova. 2007;57(5):541-544. Russian.
  А.Я.Каплан, Е.В.Левичкина. Поздняя негативность в зрительных вызванных потенциалах у человека при изменении топологии простых невербальных стимулов. Журнал высш. нервн. деят. 2007;57(5):541-544. [ PDF ]

• Kaplan AIa, Byeon JG, Timashev SF, Vstovskii GV, Park BW. [Functional variability of the autocorrelation structure of the EEG]. Zh Vyssh Nerv Deiat Im I P Pavlova. 2006 May-Jun;56(3):408-11. Russian.
  Каплан А.Я., Бьен Дж.Г., Тимашев С.Ф., Встовский Г.В., Пак Б.У. Функциональная изменчивость автокорреляционной структуры ЭЭГ. Журнал высш. нервн. деят. 2006;56(3):389-392. [ PDF ]

• A.Ya.Kaplan, J.J.Lim, K.S.Jin, B.W.Park, J.G.Byeon, S.U.Tarasova. Unconscious operant conditioning in the paradigm of brain-computer interface based on color perception. Intern. J. Neuroscience. 2005;115:781-802. [ PDF ]

• S.V.Borisov, A.Ya.Kaplan, N.L.Gorbachevskaya, I.A.Kozlova. Analysis of EEG structural synchrony in adolescents with schizophrenic disorders. Human Physiology. 2005;31(3):255-261. (Transl. from Fiziologiya Cheloveka.) [ PDF ]

• A.Ya.Kaplan, Al.A.Fingelkurts, An.A.Fingelkurts, S.V.Borisov, B.S.Darkhovsky. Nonstationary nature of the brain activity as revealed by EEG/MEG: methodological, practical and conceptual challenges. Signal processing. Special Issue: Neuronal Coordination in the Brain: A Signal Processing Perspective. 2005;85:2190–2212. [ PDF ]

• S.L.Shishkin, A.Ya.Kaplan, H.Bakardjian, A.Cichocki. Combining the extremities on the basis of separation: A new approach to EEG/ERP source localization. - Unveiling the Mystery of the Brain: Neurophysiological Investigation of the Brain Function. (Ed. by S. Tsuji et al.). ICS 1278, Elsevier, 2005, pp. 119-122. [ PDF ]

• A.Kaplan, J.J.Lim, K.S.Jin, J.G.Byeon, S.U.Tarasova. The conception of intellectual brain computer interface: fundamentals and experiment. 1st Indian Int. Conf. Artif. Intelligence (IICAI-03). (Ed. by B.Prasad.) IICAI, 2003, pp. 712-721.

• A.Fingelkurts, A.Fingelkurts, C.Krause, A.Kaplan, S.Borisov, M.Sams. Structural (operational) synchrony of EEG alpha activity during an auditory memory task. Neuroimage. 2003;20(1):529-542. [ PDF ]

• P.Landa, A.Kaplan, E.Zhukovskaya. A model for the speed of memory retrieval. Biol. Cybern. 2003;89(4):313-316. [ PDF ]

• Al.A.Fingelkurts, An.A.Fingelkurts, C.M.Krause, A.Ya.Kaplan. Systematic rules underlining spectral pattern variability: experimental results and a review of the evidence. Int. J. Neurosci. 2003;113(10):1447-1473. [ PDF ]

• Al.A.Fingelkurts, An.A.Fingelkurts, A.Ya.Kaplan. The regularities of the discrete nature of multi-variability of EEG spectral patterns. Int. J. Psychophysiol. 2003;47(1):23-41. [ PDF ]

• A.Kaplan, J.Roeschke, B.Darkhovsky, J.Fell. Macrostructural EEG characterization based on nonparametric change-point segmentation: application to sleep analysis. J. Neurosci Methods. 2001;106(1):81-90. [ PDF ]

• A.Ya.Kaplan, S.L.Shishkin. Application of the change-point analysis to the investigation of the brain electrical activity. Chapter 7 in: B.E.Brodsky, B.S.Darkhovsky. Nonparametric Statistical Diagnosis: Problems and Methods. Kluwer Acad. Publ., Dordrecht. 2000. P.333-388. [ HTML ]

• A.Ya.Kaplan. The problem of segmental description of human electroencephalogram. Human Physiology. 1999;25(1):107-114. Translated from Fivologiya Cheloveka. 1999;25(1):125-133. [ PDF ]

• S.L.Shishkin, A.Ya.Kaplan. Certain topographic regularities of the synchrony of shifts in the intensity of alpha-activity in a human EEG. Human Physiology. 1999;25(6):629-638. Translation of paper [Some topographical features of the synchronization of the power shifts in human EEG alpha activity]. Fiziologiya Cheloveka 1999;25(6):5-14. [ MAIK ]

 
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