Alexey Ossadtchi
- Director: Institute for Cognitive Neuroscience / Centre for Bioelectric Interfaces
- Professor: Faculty of Computer Science / School of Data Analysis and Artificial Intelligence
- Alexey Ossadtchi has been at HSE University since 2013.
Education and Degrees
University of Southern California
Thesis Title: Noninvasive Automatic Detection of Epileptogenic Regions and Networks Using MEG Measurements
Bauman Moscow State Technical University
A post-doctoral degree called Doctor of Sciences is given to reflect second advanced research qualifications or higher doctorates in ISCED 2011.
Courses (2024/2025)
- Mathematical Aspects of EEG and MEG Based Neuroimaging (Mago-Lego; 3 module)Eng
- Mathematical Aspects of EEG and MEG Based Neuroimaging (Master’s programme; Institute for Cognitive Neuroscience; 1 year, 3 module)Eng
- Past Courses
Courses (2023/2024)
- Mathematical Aspects of EEG and MEG Based Neuroimaging (Master’s programme; Institute for Cognitive Neuroscience; 1 year, 3 module)Eng
- Mathematical Aspects of EEG and MEG Based Neuroimaging (Mago-Lego; 3 module)Eng
Courses (2022/2023)
- Mathematical Aspects of EEG and MEG Based Neuroimaging (Master’s programme; Institute for Cognitive Neuroscience; 1 year, 3 module)Eng
- Mathematical Aspects of EEG and MEG Based Neuroimaging (Mago-Lego; 3 module)Eng
Courses (2021/2022)
- Mathematical Aspects of EEG and MEG Based Neuroimaging (Master’s programme; Institute for Cognitive Neuroscience; 1 year, 3 module)Eng
Courses (2020/2021)
- Mathematical Aspects of EEG and MEG Based Neuroimaging (Master’s programme; Institute for Cognitive Neuroscience; 1 year, 3 module)Eng
Editorial board membership
Grants
Recording and decoding system for analysis of bioelectrical activity of the human brain, Ministry of Education, 2014-2017
|
A novel non-invasive experimental and computational paradigm for presurgical magnetoencephalographic mapping of speech cortex
|
Conferences
- 2023
The Fifth International Conference «Neurotechnologies and Neurointerfaces» (CNN 2023) (Kaliningrad). Presentation: Interpretable neural networks in neurointerfaces and neuroimaging methods
Volga Neuroscience Meeting 2023 (Нижний Новгород). Presentation: Diagnostic approaches for precision medicine in epilepsy
- 2016
IEEE International Symposium «Video and Audio Signal Processing in the Context of Neurotechnologies» (Санкт-Петербург). Presentation: MEG correlates of internalization of social influence
Biomag 2016 (Сеул). Presentation: Power and shift invariant imaging of coherent sources from MEG data (PSIICoS)
- 2015
V Международная конференция по биотехнологиям и фармацевтике ФизтехБио — 2015 (Москва). Presentation: MEG and EEG based neuroimaging of transient networks
Методические проблемы оценки функциональной синхронизации зон коры мозга на основании ЭЭГ-/МЭГ данных» (Москва). Presentation: МЭГ как результат активности и взаимодействия динамических сетей: метод порождающей модели
- 2014
International conference on biomagnetism, Biomag 2014 (Галифакс). Presentation: Interaction Space RAP-MUSIC for estimation of transient networks from MEG data
9th FENS Forum of Neuroscience (Милан). Presentation: MPFC activity varies with differences in social conformity: MEG study
Научная сессия "Проблемы мозга" Российской Академии Наук (Москва). Presentation: Эффективное нейробиоуправление на основе пространственно-временных динамических моделей
Okorokova E., Lebedev M., Linderman M. and Ossadtchi A. (2015). A dynamical model improves reconstruction of handwriting from multichannel electromyographic recordings Front. Neurosci. 9 : 389 doi: 10.3389/fnins.2015.00389
Kozunov VV and Ossadtchi A (2015) GALA: group analysis leads to accuracy, a novel approach for solving the inverse problem in exploratory analysis of group MEG recordings. Front. Neuroscience 9 : 107. doi: 10.3389/fnins.2015.00107
A. Ossadtchi, P. Pronko, M. Pflieger, T. Stroganova, Mutual information spectrum – a new tool for detection of event related components in spatial decompositions and its application to M1 cerebral zone localization, Frontiers in Human Neuroscience, In Press
Shtyrov, Y., Goryainova, G., Tugin, S., Ossadtchi, A., Shestakova, A., Automatic processing of unattended lexical information in visual oddball presentation: neurophysiological evidence. Frontiers in Human Neuroscience, 7:421, doi: 10.3389/fnhum.2013.00421, 2013 .
R.E. Greenblatt, M.E. Pflieger, A. Ossadtchi, Connectivity measures applied to human brain electrophysiological data, Journal of Neuroscience Methods 207 (2012) 1– 16
A. Shestakova, J. Rieskamp, S. Tugin, A. Ossadtchi, J. Krutitskaya, and V. Klucharev., Electrophysiological precursors of social conformity. Frontiers in Decision Neuroscience, In Press, 2012
I. Ovod, A .Ossadtchi, A. Pupyshev, A. Fradkov, Forming neurofeedback signal based on the adaptive model of the EEG observed human brain activity, Neurocomputers and applications, February, 2012 (in Russian).
A. Shestakova, A. Ossadtchi, O. Kravtsenyuk, O. Getmanenko, V. Klucharev, MEG and optical tomography – modern methods for investigation of cognitive development in babies and older kids., Chapter in “ Modern Methods in Neuroscience”, (ed. Pavlov I. ), SPBSU Press, 2010, 189p., ISBN-978-5-288-05032-9, pp. 126-141 (In Russian)
A. Ossadtchi, R.E. Greenblatt, V.L. Towle, M.H. Kohrman, K. Kamada, Inferring Spatiotemporal Network Patterns from Intracranial EEG Data, Clin, Neurophysiology, June 2010
R.E. Greenblatt, A. Ossadtchi, L. Kurelowech, D. Lawson and J. Criado, Time-Frequency Source Estimation from MEG data,Frontiers in Neuroscience Methods, March 2010
R.E. Greenblatt, A. Ossadtchi, M.E. Pflieger, Non-target interference in MEG beamformer time series estimation, International Congress Series, v. 1300, June 2007, pp. 137-140
R.E. Greenblatt, A. Ossadtchi, M.E. Pflieger, Local Linear Estimators for the Bioelectromagnetic Inverse Problem, IEEE Trans Signal Proc. 2005. v.53/9, 2005
R. E. Greenblatt, A. Ossadtchi, M.E. Pflieger and D.C. Rojas, Local linear estimators and a statistical framework for event related field analysis, Intl J Bioelectromagnetism, v. 7/2, 2005
A. Ossadtchi, J.C. Mosher, W.W. Sutherlin, R.E. Greenblatt, R.M. Leahy, Hidden Markov modeling of spike propagation from interictal MEG data, Phys. Med. Biol. 50 3447-3469, 2005
A. Ossadtchi, S. Baillet, J.C. Mosher, D. Thyerlei, W.W. Sutherling and R.M. Leahy, Automated interictal spike detection and source localization in MEG using ICA and spatial-temporal clustering. Clin. Neurophysiology, 2004; 115/3, 508-522.
D. Thyerlei, A. Ossadtchi, T. Maleeva, A.N. Mamelak and W.W. Sutherling, Using intracranial depth electrode stimulation as a reference source for reconstruction from simultaneous scalp-EEG. NeuroImage 2003;
A. Khan, A. Ossadtchi, R.M. Leahy and D. Smith, Error-correcting microarray design. Genomics2003; 81(2), 157-165
V. Dribinski, A. Ossadtchi, V. Mandelshtam and H. Reisler, Reconstruction of Abel-transformable images: The Basis-Set Expansion Abel Transform, Method. Rev. Sci. Inst., 2002; 73.
V.M. Brown, A. Ossadtchi, A.H. Khan, S. Yee, W.P. Lacan G, Melega, S.R. Cherry, R.M. Leahy and D.J. Smith, Multiplex three-dimensional brain gene expression mapping in a mouse model of Parkinson's disease. Genome Res 2002;12:868-884.
T.A. Leil, A. Ossadtchi, J. Cortes, R.M. Leahy and D.J. Smith, Finding new candidate genes for learning and memory. J Neurosci Res 2002; 68:127-137.
A. Ossadtchi, V.M. Brown, A.H. Khan, S.R. Cherry, R.M. Leahy, T. Nichols, D.J. Smith, Statistical analysis of multiplex brain gene expression images. Neurochem Res 2002; 27: 1113-1121.
V.M. Brown, A. Ossadtchi, A.H. Khan, S.S. Gambhir, S.R. Cherry, R.M. Leahy and D.J. Smith, Gene expression tomography. Phys. Genomics 2002; 8:159-167.
V.M. Brown, A. Ossadtchi, A.H. Khan, S.R. Cherry, R.M. Leahy and D.J. Smith, High-throughput imaging of brain gene expression. Genome Res. 2002; 12:244-254.
Supervisor of the following Doctoral theses
- 1A. Petrosyan Modern methods of machine learning in the interpretation of electrical activity of the brain, 2023
- 2A. Kuznetsova Regularization of EEG and MEG inverse problem based on physiologically plausible priors, 2022
- 3D. Altukhov Optimal methods for functional connectivity estimation in magnetoencephalography, 2021
- 4K. Volkova Experimental paradigms and data processing algorithms design in real time cognitive neuroimaging, 2021
- 5N. Smetanin Mathematical methods for multidimensional time series processing in application to real-time electrophysiological signals analysis, 2021
Elizaveta Okorokova | M.Sc. student (2nd year) |
Sergey Parsegov | Post-doctoral fellow |
Eugene Kalenkovitch | M.Sc. student (1st year) |
Employment history
Research / Work Experience 2018-Present 2016-Present 2015-Present 2013-Present |
Leading researcher, Center for Cognition and Decision Making , HSE Professor, Data Analysis and Artificial Intelligence Department, HSE |
||
2007-2013 |
Docent at the Div. for Higher Nervous Activity , Biology and Soils Department, St. Petersburg State University |
||
2005-2015 |
Independent Consultant for Source Signal Imaging, San Diego, CA |
||
2003-2005 |
Senior Scientist. Source Signal Imaging Inc., San Diego, CA |
||
09/1999 – 2003 |
Research Assistant. Neuroimaging Laboratory at USC, adv. R. Leahy |
||
09/2002 - 2003 |
Research fellow. MEG unit at Huntington Medical Res. Inst. |
||
06/2001 – 01/2002 |
Consulting Department of Chemistry, USC |
||
05/2000 – 08/2000 |
Research Intern. Hughes Research Laboratories, Malibu, CA |
||
09/1998 – 08/1999 |
Research Assistant. Integrated Media Systems Center (IMSC, USC) |
||
03/1995 – 07/1998 |
Research Fellow. Research Center ‘Module’, Moscow. |
||
01/1993 – 03/1995 |
Research Assistant. Department of autonomous control systems, Bauman Moscow State Technical University. |
||
Teaching Experience |
|
||
2019-Present 2016-Present 2017-Present 2014 – 2017 2008-2014 |
Director, Center for Bioelectric Interfaces Professor, Data Analysis and Artificial Intelligence Department, HSE Senior researcher, Center for Cognition and Decision Making , HSE Docent St. Petersburg State University |
||
2005-2007 |
Docent at St. Petersburg State Polytechnic University. |
||
1998 – 2000 |
Teaching Assistant. Electrical Engineering department, USC |
MEG and EEG-based brain-imaging technology allows us to visualize and study neuronal processes non-invasively, with very high temporal and reasonable spatial resolution. Currently, this method is used not only to localize neuronal activity but also to recover the dynamics of the entire neural network comprised of several distant cortical regions subserving the cognitive phenomenon at hands. The accuracy and reproducibility of such inferences crucially depend on the methods and computational approaches used for analysis of the MEG and EEG sensor data. Development of the novel methods and verification of the existing approaches allow us to ensure that the information present in the data is utilized with maximal efficiency. The use of the subject-specific probabilistic models obtained via data fusion form various modalities including fMRI, DTI, Optical tomography, TMS bear a promise of improving the non-invasively achieved resolution and further open "the non-invasive window" into the brain's function.
The clinical portion of this work is done in close collaboration with the Moscow MEG center, Burdenko Institute of Neurosurgery and the Institute for problems of Mechanical Engineering, RAS, and is supported by an RFFI grant.
Real-time EEG: neurofeedback and neurointerfaces
Neurofeedback is a promising tool for non-pharmacological therapy for depression, ADHD, epilepsy and other psychiatric diseases and syndromes. This technique is also used for peak performance training and in relaxation practices. Within the neurofeedback paradigm a person is put into a closed loop where his/her brain state is presented as a feedback signal via one of the sensory modalities and is used to consciously (or not so consciously) modify the dynamics of his/her brain rythms. In this project we will consider this closed-loop system from the standpoint of control theory (both continuous and discrete) and will focus on developing novel model-based techniques to improve the efficiency and spatial specificity of neurofeedback therapy. This research will pave the way towards a new generation of more efficient and more natural brain-computer interfaces
Published an article in the journal NeuroImage!
Article: «Representational dissimilarity component analysis (ReDisCA)».
Authors: Alexey Ossadtchi, Ilya Semyonkov, Anna Zhuravleva, Vladimir Kozunov, Oleg Serikov, Ekaterina Voloshina.
Our article has been published in the Scientific Reports!
The article "Short-term meditation training alters brain activity and sympathetic responses at rest, but not during meditation" was published in the journal Scientific Reports.
Authors: Anna Rusinova, Maria Volodina, Alexei Ossadtchi.
'While it May Sound Futuristic, It Holds Great Promise': Olga Dragoy Shares Her Thoughts on Language Function Restoration and the Future of Neurotechnology
In the spring of 2023, the fifth strategic project of the Priority 2030 programme, 'Human Brain Resilience: Neurocognitive Technologies for Adaptation, Learning, Development and Rehabilitation in a Changing Environment,' was launched at HSE University. The strategic project brings together researchers from all campuses of HSE University. In her interview with the HSE News Service, Olga Dragoy, head of the strategic project and Director of the HSE Centre for Language and Brain, shares an overview of the advanced technologies neuroscientists are creating today, the underlying inspiration driving these efforts, and the operational dynamics of interdisciplinary applied projects.
Alexei Ossadtchi gave a lecture as part of the "Theory of Perspective" meeting series.
The topic of the lecture: Mathematical methods in brain research: from neuroimaging to expanding human abilities.
Journal "Правила жизни" included BRAINSTART with iNeurofeedback technology in "7 Technology Startups from Russia to Watch"
The startup is involved in developing the next generation of EEG-based biofeedback technology (neurofeedback).
The courses "Neurointerfaces" and "Mathematical Aspects of EEG and MEG Based Neuroimaging" have been released on our YouTube channel!
Предлагаем вашему вниманию курсы лекций Алексея Евгеньевича Осадчего!
Our article was published in the NeuroImage!
The article "PSIICOS projection optimality for EEG and MEG based functional coupling detection" was published in the journal NeuroImage.
Authors: Dmitrii Altukhov, Daria Kleeva, Alexei Ossadtchi.
Alexey Ossadtchi became a guest of a new episode of Sergey Mezentsev's podcast!
Alexey spoke about invasive and non-invasive interfaces, brain empowerment and what diseases will be able to treat in the future.
New Technologies for Preserving Brain Functions: ‘Not Magic, but Normal Engineering’
New methods of brain mapping will make it easier to identify the cortex areas responsible for speech functions and to perform operations on the brain, as well as reduce the likelihood of damage to important areas. In addition, this will allow for more frequent use of non-invasive methods for restoring speech and other functions lost due to injuries and illnesses.
‘We Are Developing Technologies to Support People and Strengthen the Intellect’
HSE News Service spoke to Director of the Institute of Cognitive Neurosciences, Head of the Centre for Cognition and Decision Making at HSE University, Anna Shestakova about the achievements and goals of the new HSE University’s strategic project ‘Human Brain Resilience: Neurocognitive Technologies for Adaptation, Learning, Development, and Rehabilitation in a Changing Environment’.
Alexey Ossadtchi gave a lecture at a seminar of the Artificial Intelligence Research Institute
On February 15, the director of the Center for Bioelectrical Interfaces, Alexey Ossadtchi, gave a lecture at a scientific seminar on artificial intelligence with the topic "Data analysis methods for studying brain activity in closed-loop paradigms.
Opponent: Sergey Shishkin, MSPU.
Second Congress of Young Scientists: Students Are Ready to Implement Breakthrough Projects
The 2nd Congress of Young Scientists was held at the Sirius Park of Science and Art in Sochi. HSE University representatives took an active part in it, working at various venues where a wide range of topics were discussed—from university development to machine learning and scientific cinema.
Alexey Ossadtchi took part in the Business Program of the Young Scientists Congress, "Neurotechnology: Fixing and Augmenting the Brain
The program addressed the following questions:
How will neurotechnology change our near future?
What areas of human activity will become the drivers of development?
What obstacles are standing in the way of neurotechnology development?
How are neurotechnologies changing modern medicine?
Alexey Ossadtchi and Alexey Voskoboynikov gave a lecture on modern advances in speech decoding from brain electrical activity using brain-computer interfaces
Alexey Ossadtchi, PhD, director of the Center for Bioelectrical Neurointerfaces at the Higher School of Economics, presented a report on modern approaches in signal decoding in speech prostheses with a small number of implantable electrodes.
Alexey Voskoboynikov, trainee researcher of the Center for Bioelectrical Interfaces of the HSE, researcher of the Laboratory of Medical Neurointerfaces and Artificial Intelligence, FMBA CMNT, discussed speech zone mapping, which is one of the most important stages of neurosurgical intervention in the cerebral cortex.
RT TV channel's website published an interview with Alexey Osadtchi about the development of neurointerface technology and prosthetics
Alexei Osadtchi discussed progress in creating bionic prostheses capable of reading nerve signals.
The First Medical Channel released an episode with Alexey Ossadtchi, director of the Center for Bioelectrical Interfaces
The issue of Marina Astvatsaturyan's program "Medicine in Context" with Alexey is devoted to the topic of magnetoencephalography and its application in medicine and brain research.
Congratulations to Ossadtchi Alexey on the successful pre-defense of his doctoral dissertation!
On October 05, 2022 at the Department of Data Analysis and Artificial Intelligence, the preliminary defense of the doctoral dissertation "Methods for processing, decoding and interpretation of electrophysiological activity of the brain for problems of diagnosis, neurorehabilitation and therapy of neurocognitive disorders" by Alexey Ossadtchi was held.
HSE Neural Interface Technology to Be Introduced in Hospitals
The Federal Brain and Neural Technology Centre at the Federal Medical and Biological Agency is launching the Laboratory of Medical Neural Interfaces and Artificial Intelligence for Clinical Applications, which has been created by employees of HSE University. Read below to find out about the Laboratory and its objectives.
Russian Scientists Create Biomimetic Algorithm to Find Epileptogenic Areas of the Brain
Researchers from the HSE University Centre for Bioelectric Interfaces have designed a new method for detecting diagnostic markers of epilepsy, called interictal spikes, using EEG and MEG. Capable of accounting for various errors and artefacts, this method constitutes a valuable addition to the arsenal of means for automatic analysis of electrophysiological recordings in epilepsy patients, especially when the data are noisy. Precise localisation of epileptogenic cortical structures can enhance the effectiveness of neurosurgical interventions. The study was published in the Journal of Neural Engineering.
Alexey Ossadtchi gave a lecture at the BCI & NEUROTECHNOLOGY SPRING SCHOOL 2022
Topic: "ECoG and MEG for Speech Display and Decoding and Closed Loop Motor Interfaces"
We are waiting for a researcher at the Center for Bioelectrical Interfaces!
A competition for the Russian Postdoc Program is currently open at HSE. You can apply for a postdoc position until May 20, 2022.
As part of the competition, a vacancy for a postdoc (researcher) at the Center for Bioelectric Interfaces is open.
We are opening a laboratory of medical neurointerfaces and artificial intelligence for clinical applications at the FMBA Center for Brain and Neurotechnology!
On March 21, there was a working meeting of the Federal Medical and Biological Agency, the National Research University Higher School of Economics, and AIRI (airi.net). Alexey Osadtchi presented a report on the tasks of the laboratory and future research.
The Kultura channel released a film about Alexey Ossadtchi, director of the Center for Bioelectrical Interfaces
Alexey Ossadtchi told about team's success and what results scientists expect in the near future.
“Applied Cognitive Science” Summer School. How was it?
This year the 3d “Applied Cognitive Science” Summer School was held by our Lab. Unfortunately, we were forced to meet via online because of pandemic situation. Nonetheless, these conditions did not affect on shool program: it was intense and engaging.
Artificial Neurons Help Decode Cortical Signals
Russian scientists have proposed a new algorithm for automatic decoding and interpreting the decoder weights, which can be used both in brain-computer interfaces and in fundamental research. The results ofthe study were published in the Journal of Neural Engineering.
Researchers Expand the Capabilities of Magnetoencephalography
Researchers from the HSE Institute for Cognitive Neuroscience have proposed a new method to process magnetoencephalography (MEG) data, which helps find cortical activation areas with higher precision. The method can be used in both basic research and clinical practice to diagnose a wide range of neurological disorders and to prepare patients for brain surgery. The paper describing the algorithm was published in the journal NeuroImage.
How Modern Robots Are Developed
Today, neuroscience and robotics are developing hand in hand. Mikhail Lebedev, Academic Supervisor at HSE University’s Centre for Bioelectric Interfaces, spoke about how studying the brain inspires the development of robots.
Scholars Provide Monkeys with a Virtual Hand
The virtual hand is capable of tactile perception
Center for Bioelectric Interfaces presents at OHBM 2019
We have made four poster presentations at OHBM-2019, a major neuroscience conference held in Rome and sponsored by the Organization for Human Brain Mapping.
Conference «MEG Nord 2019»
CBI Director Prof. Alex Ossadtchi has made a presentation at MEG Nord 2019 to have taken place May 8-10, in Jyväskylä, Finland.
CBI team at Skolkovo Robotics 2019
On April 16, 2019, Alex Ossadtchi and Mikhail Lebedev have made a keynote speech at the Skolkovo Robotics 2019 event. Nickolay Smetanin has also demoed a neurointerface designed at the CBI to control an exoskeleton (made by the Russian company ExoAtlet).
CBI is featured on Russia-24 channel
Russia-24 aired a story in which Alex Ossadtchi, Ksenia Volkova, Nickolay Smetanin, Alexander Belyayev and Alexandra Kuznetsova talk about the CBI and its research: an exoskeleton-controlling neurointerface, myographic interface to control a hand avatar and the main project to develop an invasive neurointerface to be used in clinical settings.
BCI-controlled exoskeleton: neurorehabilitation for patients with impaired lower limb function
At the international symposium ExoRehab Spotlights 2018 held on December 5 in Moscow, researchers of the Center for Bioelectric Interfaces Nikolai Smetanin, Aleksandra Kuznetsova and Alexei Ossadtchi presented Russia's first EEG-based neural interface that uses lower limb motor imagery for exoskeleton control. Alexei Ossadtchi also made a presentation "BCI for walk decoding". This work has been a collaboration with the Russian company ExoAtlet.
Megagrant #14.641.31.0003 "Bi-directional ECoG BCIs for contol, stimulation and communication". Lead scentist: Mikhail Lebedev.
Successful ECoG decoding in real time!
Today marks the successful completion of the first year of our research project funded by Megagrant #14.641.31.0003 "Bi-directional ECoG BCIs for control, stimulation and communication" (lead scientist: Mikhail Lebedev).
Our Center on the international conference Brain-Computer Interface: Science and Practice in Samara
Russian ministry of Education and Science Government grant ag. No 14.641.31.0003, Megagrant to Mikhail Lebedev.
Alexei Ossadtchi made presentation "Towards zero-latency neurofeedback" about the algorithms developing in our Center. Mikhail Lebedev gave a talk "Decoding, but what?" about the invasive neurointerfaces. Moreover, our research assistants Julia Nurislamova, Ignatii Dubishkin and Alexander Belyaev won prizes for best posters.