Осадчий Алексей Евгеньевич
Институт когнитивных нейронаук
Профессиональные интересы
Должности
- Директор центра — Институт когнитивных нейронаук, Центр биоэлектрических интерфейсов
- Профессор — Факультет компьютерных наук, Департамент анализа данных и искусственного интеллекта
Био
- · Начал работать в НИУ ВШЭ в 2013 году.
- · Научно-педагогический стаж: 21 год.
Образование
- 2023 · Доктор наук: Национальный исследовательский университет "Высшая школа экономики"
- 2003 · PhD: Университет Южной Калифорнии, специальность 01.00.00 «Физико-математические науки» и 03.03.06 «Нейробиология», тема диссертации: Автоматическое неинвазивное обнаружение и анализ взаимодействия эпилептогенных зон на основании МЭГ и ЭЭГ измерений
- 1997 · Специалитет: Московский государственный технический университет им. Н.Э. Баумана, специальность «Автономные информационные и управляющие системы», квалификация «Инженер-радиотехник»
Опыт работы
- · Директор Центра биоэлектрических интерфейсов НИУ ВШЭ Ведущий научный сотрудник Центра познания и принятия решений НИУ ВШЭ Профессор кафедры анализа данных и искусственного интеллекта НИУ ВШЭ Старший научный сотрудник Центра познания и принятия решений НИУ ВШЭ
- · 2007-2013: гг. Доцент див. для высшей нервной деятельности, Биолого-почвенный факультет Санкт-Петербургского государственного университета
- · 2005-2015: гг. Независимый консультант по визуализации сигналов источника, Сан-Диего, Калифорния
- · 2003-2005: гг. Старший ученый. Source Signal Imaging Inc., Сан-Диего, Калифорния
- · 1999 — 2003: 09/ Научный сотрудник. Лаборатория нейровизуализации при USC, адв. Р. Лихи
- · 2002 — 2003: 09/ Научный сотрудник. Отделение MEG в Huntington Medical Res. Inst
- · 2001: 06/ 01/
- · 2002: Консультационный отдел химии, USC
- · 2000: 05/ 08/
- · 2000: Research Intern. Исследовательские лаборатории Хьюза, Малибу, Калифорния
- · 1998: 09/ 08/
- · 1999: Научный сотрудник. Центр интегрированных медиа-систем (IMSC, USC)
- · 1995: 03/ 07/
- · 1998: Научный сотрудник. Исследовательский центр «Модуль», Москва
- · 01.1993 — 03.1995: Научный сотрудник. Кафедра автономных систем управления МГТУ им. Н. Э. Баумана
Награды и поощрения
- · Медаль "Признание - 10 лет успешной работы" НИУ ВШЭ (июль 2025)
- · Благодарность Высшей школы экономики (сентябрь 2021)
- · Благодарность Факультета компьютерных наук НИУ ВШЭ (август 2018)
- · Надбавка за защиту докторской диссертации (2023–2026)
- · Надбавка за публикацию в международном рецензируемом научном издании (2019–2021, 2018–2020, 2017–2018)
- · Надбавка за регулярные публикации в международных рецензируемых научных изданиях (2024–2029, 2023–2028, 2021–2026)
- · Надбавка за статью в зарубежном рецензируемом журнале (2015–2017)
Гранты и проекты
- 1017 · Система регистрации и декодирования биоэлектрической активности мозга человека, госконтракт, Министерство Образования и Науки РФ, совместно с ННГУ. 2014-1017 г.
- — · Новая неинвазивная экспериментально-математическая парадигма предоперационного магнитоэнцефалографического картирования речевой коры головного мозга, Грант РФФИ 14-02-00917
- — · РФФИ 16-04-01863 Эндогенное повышение эффективности работы интерфейсов мозг-компьютер
Конференции (10)
Показать все
- · 2024: 27th European Conference on Artificial Intelligence (ECAI 2024) (Сантьяго-де-Компостела). Доклад: EEG-Based fMRI Digital Twin: Towards a Cheap and Ecological Approach to Measure Subcortical Brain Activity
- · 2023: The Fifth International Conference «Neurotechnologies and Neurointerfaces» (CNN 2023) (Kaliningrad). Доклад: Interpretable neural networks in neurointerfaces and neuroimaging methods
- · 2023: Volga Neuroscience Meeting 2023 (Нижний Новгород). Доклад: Diagnostic approaches for precision medicine in epilepsy
- · 2016: IEEE International Symposium «Video and Audio Signal Processing in the Context of Neurotechnologies» (Санкт-Петербург). Доклад: MEG correlates of internalization of social influence
- · 2016: Biomag 2016 (Сеул). Доклад: Power and shift invariant imaging of coherent sources from MEG data (PSIICoS)
- · 2015: V Международная конференция по биотехнологиям и фармацевтике ФизтехБио — 2015 (Москва). Доклад: MEG and EEG based neuroimaging of transient networks
- · 2015: Методические проблемы оценки функциональной синхронизации зон коры мозга на основании ЭЭГ-/МЭГ данных» (Москва). Доклад: МЭГ как результат активности и взаимодействия динамических сетей: метод порождающей модели
- · 2014: International conference on biomagnetism, Biomag 2014 (Галифакс). Доклад: Interaction Space RAP-MUSIC for estimation of transient networks from MEG data
- · 2014: 9th FENS Forum of Neuroscience (Милан). Доклад: MPFC activity varies with differences in social conformity: MEG study
- · 2014: Научная сессия "Проблемы мозга" Российской Академии Наук (Москва). Доклад: Эффективное нейробиоуправление на основе пространственно-временных динамических моделей
Идентификаторы исследователя
- ORCID:
0000-0001-8827-9429 - ResearcherID:
M-9067-2013 - SPIN РИНЦ:
5631-4743 - Google Scholar: https://scholar.google.ru/citations?user=uVunrzkAAAAJ&hl=en
- Scopus AuthorID:
6603011121
Публикации (98)
Self-face viewing attenuates cardiac modulation of corticospinal excitability
2026 · ARTICLE · en
Introduction: While self-referential attention is thought to enhance interoceptive sensitivity, its effect on cardiac modulation of corticospinal excitability remains unexplored. This pilot study investigated how viewing one’s own face (self-face processing) modulates the cardiac-phase coupling of motor output and whether this heart-brain coupling depends on interoceptive accuracy (heartbeat perception). Methods: In 15 healthy adults, motor-evoked potentials (MEPs) were elicited via transcranial magnetic stimulation (TMS) at three fixed time points following the R-peak (0, 250, and 500 m) during presentation of either self-face or other-face pictures. A Modulation Index was derived from log-transformed MEPs to quantify cardiac-phase modulation strength. Interoceptive accuracy was assessed via a heartbeat-counting task. Results: Contrary to the hypothesis that self- face viewing would enhance cardiac–motor coupling through inward attentional focus, self-face processing significantly reduced the overall magnitude of cardiac-phase modulation. This attenuation was most pronounced at 0 m and 250 m post-R-peak, corresponding to systolic phase. Across conditions, higher interoceptive accuracy predicted stronger modulation, though this relationship showed a tendency toward attenuation during self-face viewing (interaction p = 0.059). Discussion: The results of this pilot TMS study suggest that, in a task requiring explicit evaluation of facial stimuli, self-face viewing acts as a potent exteroceptive stimulus that diverts attention away from interoceptive signals, thereby weakening the cardiac-cycle influence on motor excitability. These findings highlight the context-dependency of self-processing effects and suggest a possible link between HCT-based interoceptive accuracy and heart-brain- body coupling.
Hardware-enabled low latency rhythmic brain state tracking for brain stimulation applications
2025 в печати · ARTICLE · en
Objective: Upcoming neuroscientific research will require bidirectional and context dependent interaction with nervous tissue. To facilitate the future neuroscientific discoveries we have created HarPULL, a genuinely real-time system for tracking oscillatory brain state. Approach: The HarPULL technology ensures reliable, accurate and affordable real-time phase and amplitude tracking based on the state-space estimation framework operationalized by Kalman filtering. To avoid data transfer delays and to obtain a truly real-time system the algorithm is implemented on the computational core of an EEG amplifier controlled by a real-time operating system. Systems performance is tested with simulated and real data both online and offline and within a real-time state dependent TMS using a phantom and human subjects. Main results: We show that taking into account the nature of the brain noise and the use of the steady state colored Kalman filter further improves phase tracking performance in both simulated and real data. We use HarPULL to trigger the TMS device contingent upon the target phase and amplitude combination and demonstrate minimal delay (2 ms) between the occurrence of the predetermined rhythm phase in the cortex and the corresponding magnetic stimulus. Using this setup in the real-time setting we observe a significant modulation of the motor evoked potentials (MEP) by the sensorimotor rhythm’s state. Finally, we use HarPULL and for the first time obtain phase-dependent muscle cortical representation (MCR) maps in real-time. We show better delineation between the representations of several muscles when the stimulation is performed in the excitation state. Significance: HarPULL is the first truly real-time technology for the instantaneous tracking of the brain’s rhythmic activity. Our technological solution establishes a nearly instantaneous non-invasive contact with a living brain which has a broad range of clinical, diagnostic and scientific applications.
Context-dependent PSIICOS: A novel framework for functional connectivity estimation accounting for task-related power leakage
2025 · ARTICLE · en
Functional connectivity (FC) analysis using non-invasive neuroimaging methods, such as MEG and EEG, is often confounded by artifacts from spatial leakage and task-related power modulations. To address these limitations, we present Context-Dependent PSIICOS (CD-PSIICOS), a novel framework that improves the estimation of FC by incorporating task-specific cortical power distributions into the projection operator applied to the vectorized sensor-space cross-spectrum. Unlike the original PSIICOS (Phase Shift Invariant Imaging of Coherent Sources) approach, designed to suppress spatial leakage from all the sources, CD-PSIICOS dynamically adjusts the projection based on the active source distribution, enabling more accurate suppression of spatial leakage while preserving true zero-phase interactions. We validated CD-PSIICOS using realistic simulations and a multi-subject MEG dataset. The results demonstrate that CD-PSIICOS outperforms the original PSIICOS in suppressing artifacts at the lower projection ranks, maintaining robust detection of functional networks across theta and gamma frequency bands. By requiring lower projection ranks for optimal performance, CD-PSIICOS facilitates the reconstruction of physiologically relevant networks with improved sensitivity and stability.
Towards stimulation-free automatic electrocorticographic speech mapping in neurosurgery patients
2025 · ARTICLE · en
Objective. The precise mapping of speech-related functions is crucial for successful neurosurgical interventions in epilepsy and brain tumor cases. Traditional methods like electrocortical stimulation mapping (ESM) are effective but carry a significant risk of inducing seizures. Methods. To address this, we have prepared a comprehensive ESM + electrocorticographic mapping (ECM) dataset from 14 patients with chronically implanted stereo-EEG electrodes. Then we explored several compact machine learning (ML) approaches to convert the ECM signals to the ground truth derived from the risky ESM procedure. Both procedures involved the standard picture naming task. As features, we used gamma-band power within successive temporal windows in the data averaged with respect to picture and voice onsets. We focused on a range of classifiers, including XGBoost, linear support vector classification (SVC), regularized logistic regression, random forest, k-nearest neighbors, decision tree, multi-Layer perceptron, AdaBoost and Gaussian Naive Bayes classifiers and equipped them with confidence interval estimates, crucial in a real-life application. We validated the ML approaches using a leave-one-patient-out procedure and computed ROC and Precision–Recall curves for various feature combinations. Results. For linear SVC we achieved ROC-AUC and PR-AUC scores of 0.91 and 0.88, respectively, which effectively distinguishes speech-related from non-related iEEG channels. We have also observed that the use of information on the voice onset moment notably improved the classification accuracy. Significance. We have for the first time rigorously compared the ECM and ESM results and mimicked a real-life use of the ECM technology. We have also provided public access to the comprehensive ECM+ESM dataset to pave the road towards safer and more reliable eloquent cortex mapping procedures.
The Tale of Two Rooms: Comparison of QuSpin Zero-Field OPMs’ Operation in Two Magnetically Shielded Environments
2025 · ARTICLE · en
This article addresses several critical aspects of using optically pumped magnetometers (OPMs), focusing on both metrological issues and the enhancement of signal quality. We present a quantitative methodology for OPM measurements standardization and quality evaluation, which is crucial in biomedical applications like magnetoencephalography (MEG). Additionally, we introduce a novel, cost-effective portable active magnetic shielding system—digital adaptive suppression system (DASS)—that represents a significant advancement over traditional analog active shielding. Through comprehensive experimental research, we evaluate first- and third-generation commercial OPMs from QuSpin Inc. in two distinct magnetic environments. Our results demonstrate that the DASS ensures optimal and reliable OPM performance, even in noisy urban settings, surpassing the effectiveness of conventional analog shielding. These findings highlight the need for advanced magnetic shielding solutions to enhance the accuracy and reproducibility of OPM measurements.
A reliable and reproducible real-time access to sensorimotor rhythm with a small number of optically pumped magnetometers
2025 · ARTICLE · en
Objective. Recent advances in biomagnetic sensing have led to the development of compact, wearable devices capable of detecting weak magnetic fields generated by biological activity. Optically pumped magnetometers (OPMs) have shown significant promise in functional neuroimaging. Brain rhythms play a crucial role in diagnostics, cognitive research, and neurointerfaces. Here we demonstrate that a small number of OPMs can reliably capture sensorimotor rhythms (SMRs). Approach. We conducted movement execution and motor imagery (MI) experiments with nine participants in two distinct magnetically shielded rooms (MSRs), each equipped with different ambient field suppression systems. We used only 4 OPMs located above the sensorimotor region and standard common-spatial-patterns (CSPs) based processing to decode the real and imaginary movement intentions of our participants. We evaluated reproducibility of the CSP components’ spectral profiles and assessed the decoding accuracy deterioration with reduction of OPM’s count. We also assessed the influence of the magnetic field orientation on the decoding accuracy and implemented a real-time MI brain–computer interface (BCI) solution. Main results. Under optimal conditions, OPM sensors deliver informative signals suitable for practical MI BCI applications. Those subjects who participated in the experiments in both MSRs exhibit highly reproducible SMR spectral patterns across two different magnetically shielded environments. The magnetic field components with radial orientation yield higher decoding accuracy than their tangential counterparts. In some subjects we observed more than 80% of binary decoding accuracy using a single OPM sensor. Finally we demonstrate real-time performance of our system along with clearly pronounced and behaviorally relevant fluctuations of the SMR power. Significance. For the first time, we demonstrated reliable and reproducible tracking of SMR components using a small number of contactless OPM sensors during movement execution and MI. Our findings pave the way for more efficient post-stroke neurorehabilitation by enabling MI-based BCI solutions to accelerate functional recovery.
Hardware powered ultra-low latency (HarPULL) brain-body state dependent TMS technology for investigation of the motor system
2025 · CHAPTER · en
Сortico-spinal neuron excitability can be tracked using rhythmic oscillations whose phase plays a pivotal role in assessing the state of the pertinent neural network. Brain’s oscillatory activity can be non-invasively registered with electroencephalography (EEG) and magnetoencephalography (MEG). Using transcranial magnetic stimulation (TMS) contingent upon the parameters of the ongoing brain activity was shown to have numerous applications in both research and clinics. Despite the potential, the described closed-loop studies often deliver inconclusive results due to real-time phase tracking errors and unaccounted for movement related contextual factors. We present a novel truly real-time hardware-software complex for the low latency brain and body state dependent transcranial magnetic stimulation (TMS). The real-time part of the software is implemented on-board of a digital EEG-recording device controlled by a real-time operating system. High fidelity phase estimation is achieved by Kalman filter-based state-space modeling of brain rhythm using the parameters estimated from the pre-recorded segment of data. To get a better grip on the state of the specific muscles and to add the associated contingency to the TMS pulse triggering process we employ electromyographic (EMG) data channels and track their envelope. The trigger moment is contingent upon a set of user specified conditions accounting for brain rhythm phase, amplitude and EMG signal strength. The circular standard deviation of the phase tracking error is below 6 degrees. The delay from the user specified combination to the arrival of the magnetic field pulse at the recording electrode is below 5 milliseconds. Using this technology, for the first time, we performed adaptive motor mapping of a healthy subject in the agonist-antagonist ERD/ERS motor task with the possibility of triggering stimulation at the certain phase of movement according to the EMG activity ratio of several hand muscles, which opens broad opportunity for studying lateral inhibition in the motor cortex.
Sparse Sensor Layout Design via Recursive Orthogonalization of the Forward Solution Matrix With a Realistic Noises Environment in MEG
2025 · ARTICLE · en
The trend toward sensor miniaturization has heightened interest in optimizing sensor array configurations across various scientific and industrial applications that imply multichannel measurements. In this article, we present a novel method for sensor array layout optimization for the needs of the modern real-life magnetoencephalographic (MEG) applications. Starting from a superset of potential locations, we form a multisensor probe comprising sensors placed at the given number of distinct locations so that the signal-to-noise ratio (SNR) of the resulting multichannel array is maximized. We achieve this using a fixed number of iterations equal to the number of available sensors. At each step, the method places a sensor to the location that maximizes the region of interest (ROI)-related SNR and then applies the projection operation to the rows of the forward model matrix to orthogonalize the subsequent stereotypic iterations with respect to the sources served by the already-selected sensors. Within a selected ROI, the developed approach allows for the performance comparable to that of 102-sensor industrial standard (Elekta Neuromag MEG system) in terms of SNR that is from −0.83 to 2.13 dB for different types of compact sensors. Our approach requires significantly less computational resources and is 50× – 70× faster as compared to the previously developed methods. Due to high flexibility, RALFE sparse sensor design, demonstrated in application to MEG, is readily applicable to many other multichannel measurement challenges with linear observation models.
Hardware powered ultra-low latency (HarPULL) brain-body state dependent TMS technology for investigation of the motor system
2025 · ARTICLE · en
Сortico-spinal neuron excitability can be tracked using rhythmic oscillations whose phase plays a pivotal role in assessing the state of the pertinent neural network. Brain’s oscillatory activity can be non-invasively registered with electroencephalography (EEG) and magnetoencephalography (MEG). Using transcranial magnetic stimulation (TMS) contingent upon the parameters of the ongoing brain activity was shown to have numerous applications in both research and clinics. Despite the potential, the described closed-loop studies often deliver inconclusive results due to real-time phase tracking errors and unaccounted for movement related contextual factors. We present a novel truly real-time hardware-software complex for the low latency brain and body state dependent transcranial magnetic stimulation (TMS). The real-time part of the software is implemented on-board of a digital EEG-recording device controlled by a real-time operating system. High fidelity phase estimation is achieved by Kalman filter-based state-space modeling of brain rhythm using the parameters estimated from the pre-recorded segment of data. To get a better grip on the state of the specific muscles and to add the associated contingency to the TMS pulse triggering process we employ electromyographic (EMG) data channels and track their envelope. The trigger moment is contingent upon a set of user specified conditions accounting for brain rhythm phase, amplitude and EMG signal strength. The circular standard deviation of the phase tracking error is below 6 degrees. The delay from the user specified combination to the arrival of the magnetic field pulse at the recording electrode is below 5 milliseconds. Using this technology, for the first time, we performed adaptive motor mapping of a healthy subject in the agonist-antagonist ERD/ERS motor task with the possibility of triggering stimulation at the certain phase of movement according to the EMG activity ratio of several hand muscles, which opens broad opportunity for studying lateral inhibition in the motor cortex. Research Category and Technology and Methods Basic Research: 10. Transcranial Magnetic Stimulation (TMS)
Интероцептивные сигналы как модуляторы процесса обучения: исследование роли висцеральных подсказок
2025 · CHAPTER · ru
Современные исследования подчеркивают важность двусторонней связи между центральной нервной системой и периферическими физиологическими процессами, в том числе в контексте взаимодействия сердца и мозга. Интероцептивные сигналы, такие как импульсация от барорецепторов сердца, способны модулировать когнитивные функции и выступать в качестве источника информации при принятии решений. Настоящее исследование направлено на проверку гипотезы о том, что синхронизация предъявления визуальных стимулов с фазами сердечного цикла (систолой и диастолой) может играть роль эндогенного информационного сигнала в процессе перцептивного обучения. Стимулы (решетки различной пространственной частоты) предъявлялись в разные фазы сердечного цикла. Контрольная группа получала синхронизированные стимулы в оба дня, в то время как в экспериментальной группе на второй день последний блок стимулов предъявлялся в случайную фазу сердечного цикла. У участников экспериментальной группы не было выявлено достоверного снижения доли правильных ответов в последнем блоке, в котором была исключена интероцептивная «подсказка». Полученные результаты указывают на преимущественное влияние экстероцептивных сигналов по сравнению с интероцептивными в использованной экспериментальной процедуре. Для выявления вклада интероцепции в процесс перцептивного обучения могут потребоваться модификации протокола и расширение выборки
Курсы (1)
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Mathematical Aspects of EEG and MEG Based Neuroimaging · 5 раза
2025/2026, 2024/2025, 2023/2024, 2022/2023, 2021/2022 · Магистратура / Маго-лего · Анг