Осадчий Алексей Евгеньевич

Different central and autonomic nervous system coupling in the experienced meditators and novices during the Taoist meditation

2021 · CHAPTER · en

Cortical and autonomic responses during staged Taoist meditation: two distinct meditation strategies

2021 · ARTICLE · en

Meditation is a consciousness state associated with specific physiological and neural correlates. Numerous investigations of these correlates reported controversial results which prevented a consistent depiction of the underlying neurophysiological processes. Here we investigated the dynamics of multiple neurophysiological indicators during a staged meditation session. We measured the physiological changes at rest and during the guided Taoist meditation in experienced meditators and naive subjects. We recorded EEG, respiration, galvanic skin response, and photoplethysmography. All subjects followed the same instructions split into 16 stages. In the experienced meditators group we identified two subgroups with different physiological markers dynamics. One subgroup showed several signs of general relaxation evident from the changes in heart rate variability, respiratory rate, and EEG rhythmic activity. The other subgroup exhibited mind concentration patterns primarily noticeable in the EEG recordings while no autonomic responses occurred. The duration and type of previous meditation experience or any baseline indicators we measured did not explain the segregation of the meditators into these two groups. These results suggest that two distinct meditation strategies could be used by experienced meditators, which partly explains the inconsistent results reported in the earlier studies evaluating meditation effects. Our findings are also relevant to the development of the high-end biofeedback systems.

Exploring time interval estimation for familiar and unfamiliar musical pieces

2021 · CHAPTER · en

Motor-Imagery BCI with Low-Count of Optically Pumped Magnetometers

2021 · CHAPTER · en

Propagating Dynamics of Interictal Spikes Reconstructed From MEG Recordings

2021 · CHAPTER · en

Pro-active game-based neurofeedback training of parietal alpha rhythm

2021 · CHAPTER · en

The use of Neurofeedback (NFB) as a therapeutic tool remains controversial. Its efficacy is subject to many factors including subject’s motivation, content of the instruction, restingstate amplitude before the training and subject’s ability to concentrate on the task. Here we introduce a novel proactive neurofeedback paradigm and explore its use for training to increase parietal alpha rhythm power in a visually rich gamified environment. Hybrid control (a keyboard with alpha rhythm), mixed feedback delivery (discrete and continuous), gamified procedure and decreased feedback delay are supposed to engage the subject and positively influence the training outcome. Results show a gradually ascending learning curve and significant differences between baselines in the real feedback group compared to a control group with fake feedback after only 30 minutes of the entertainful training. Overall, as demonstrated by our pilot study with 20 participants, the novel proactive paradigm appeared to be an efficient and engaging tool for conditioning parietal alpha power. The subjects from the experimental group show significant growth in the incidence rate of alpha bursts over the course of training as well as exhibit sustainable changes in the post-training interval. Such a gamified way for conditioning brain activity could pave a road for the future non-pharmacological treatment of a broad range of neurodegenerative disorders and achievement of peak cognitive performance.

Evolution of MEG: a first MEG-feasible fluxgate magnetometer

2021 · ARTICLE · en

Abstract In the current article, we present the first solid-state sensor feasible for magnetoencephalography (MEG) that works at room temperature. The sensor is a fluxgate magnetometer based on yttrium-iron garnet films (YIGM). In this feasibility study, we prove the concept of usage of the YIGM in terms of MEG by registering a simple brain induced field—the human alpha rhythm. All the experiments and results are validated with usage of another kind of high-sensitive magnetometers—optically pumped magnetometer, which currently appears to be well-established in terms of MEG.

Decoding аnd Interpreting Cortical Signals With A Compact Convolutional Neural Network

2021 · ARTICLE · en

Abstract Objective. Brain–computer interfaces (BCIs) decode information from neural activity and send it to external devices. The use of Deep Learning approaches for decoding allows for automatic feature engineering within the specific decoding task. Physiologically plausible interpretation of the network parameters ensures the robustness of the learned decision rules and opens the exciting opportunity for automatic knowledge discovery. Approach. We describe a compact convolutional network-based architecture for adaptive decoding of electrocorticographic (ECoG) data into finger kinematics. We also propose a novel theoretically justified approach to interpreting the spatial and temporal weights in the architectures that combine adaptation in both space and time. The obtained spatial and frequency patterns characterizing the neuronal populations pivotal to the specific decoding task can then be interpreted by fitting appropriate spatial and dynamical models. Main results. We first tested our solution using realistic Monte-Carlo simulations. Then, when applied to the ECoG data from Berlin BCI competition IV dataset, our architecture performed comparably to the competition winners without requiring explicit feature engineering. Using the proposed approach to the network weights interpretation we could unravel the spatial and the spectral patterns of the neuronal processes underlying the successful decoding of finger kinematics from an ECoG dataset. Finally we have also applied the entire pipeline to the analysis of a 32-channel EEG motor-imagery dataset and observed physiologically plausible patterns specific to the task. Significance. We described a compact and interpretable CNN architecture derived from the basic principles and encompassing the knowledge in the field of neural electrophysiology. For the first time in the context of such multibranch architectures with factorized spatial and temporal processing we presented theoretically justified weights interpretation rules. We verified our recipes using simulations and real data and demonstrated that the proposed solution offers a good decoder and a tool for investigating motor control neural mechanisms.

Cortical and autonomic responses during staged Taoist meditation: Two distinct meditation strategies

2021 · ARTICLE · en

Meditation is a consciousness state associated with specific physiological and neural correlates. Numerous investigations of these correlates reported controversial results which prevented a consistent depiction of the underlying neurophysiological processes. Here we investigated the dynamics of multiple neurophysiological indicators during a staged meditation session. We measured the physiological changes at rest and during the guided Taoist meditation in experienced meditators and naive subjects. We recorded EEG, respiration, galvanic skin response, and photoplethysmography. All subjects followed the same instructions split into 16 stages. In the experienced meditators group we identified two subgroups with different physiological markers dynamics. One subgroup showed several signs of general relaxation evident from the changes in heart rate variability, respiratory rate, and EEG rhythmic activity. The other subgroup exhibited mind concentration patterns primarily noticeable in the EEG recordings while no autonomic responses occurred. The duration and type of previous meditation experience or any baseline indicators we measured did not explain the segregation of the meditators into these two groups. These results suggest that two distinct meditation strategies could be used by experienced meditators, which partly explains the inconsistent results reported in the earlier studies evaluating meditation effects. Our findings are also relevant to the development of the high-end biofeedback systems.

Passive Intraoperative Language Mapping Using Electrocorticographic Signals

2021 · CHAPTER · en

Intraoperative brain mapping is an important step in performing neurosurgery because it allows to spare the eloquent areas of the brain and increase the post-operative life quality for patients. However, the gold standard - electrical cortical stimulation - leads to seizures in up to 30% cases when language cortex is mapped intraoperatively in epilepsy patients. Modern neurosurgery is facing the need for a more innocuous method to intraoperatively map functionally critical cortical zones. The goal of this study is to create a setup for passive intraoperative functional mapping, and to compare informativeness and safety of both mapping procedures. We have created and tested a software and hardware setup for a high-resolution passive ECoG-based eloquent cortex mapping in a neurosurgical setting. Also, we have developed a mobile version of this platform that can be used in multiple hospitals and operating rooms across the country. We found precise localization of the Broca’s area overlapping by more than 90% with the results of electrical cortical stimulation mapping in 3 out of 4 patients. In the fourth patient, the language cortex was not localized in the resection area, and the patient did not experience post-operative language deficiency. Passive mapping of the Broca’s area is a safe alternative to direct electrical stimulation. Further development of this approach includes mapping cortical activation in a patient in response to audited speech without the need to name the objects which may allow for mapping under anesthesia