Neural Interfaces Based on Endogenous Body Rhythms for Optimization of the Functional State of Humans and Cognitive Rehabilitation

Федотчев, А. И.; Парин, С. Б.; Polevaya, S. A.

doi:10.1007/s11055-022-01278-4

Cited by 4 publications

(2 citation statements)

References 83 publications

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“…В статье использованы экспериментальные данные ранних исследований. Подробное описание протоколов психофизиологических экспериментов по динамической фотостимуляции приводится в работах [1,[5][6][7][8][9][10][13][14][15][16][17][18].…”

Section: динамика ээг-сигнала экспериментunclassified

Mathematical model for controlling brain neuroplasticity during neurofeedback

Nuidel,

Kolosov,

Permyakov

et al. 2024

AND

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The purpose of this work is to apply a model of interaction between thalamocortical system modules to control brain neuroplasticity. Methods. Psychophysiological experiments on neurofeedback are being carried out, which consist of light stimulation of the eyes with monofrequency light pulses in the range of 4...20 Hz and recording the bioelectrical activity of the brain. As a characteristic of maturity, brain rhythms use the combination of the presence or absence in the bioelectrical activity of the brain of a dominant peak frequency in the alpha range of the EEG, the effect of assimilation of the rhythms imposed by stimulation, and the presence of a multiplying effect from the rhythms imposed by stimulation. Solutions to the model of an elementary thalamocortical cell, which is described by a system of differential equations, corresponding to a psychophysiological experiment are considered. The model is implemented using the Python. Results. The model parameters are selected in such a way as to achieve a qualitative correspondence of the spectral characteristics of the obtained solutions with the bioelectrical activity of the subject’s brain. Rhythmic maturity is assessed based on the parameters of the thalamocortical cell model. The brightness and frequency characteristics of light stimuli are selected based on the prediction of the model, the input of which is supplied with various variants of pulse sequences. Conclusion. A method has been developed for digital diagnostics of the level of brain rhythm maturity based on a comparison of modeling results and data from a psychophysiological experiment on neurofeedback. The evolution of model solutions depending on its parameters simulates the process of biocontrol of brain neuroplasticity, taking into account the initial level of rhythmic maturity and stress-induced distortions of neurodynamics. Experiments on the model with different parameters of the model and external signal can be used in the development of new neurofeedback protocols.

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Section: динамика ээг-сигнала экспериментunclassified

Mathematical model for controlling brain neuroplasticity during neurofeedback

Nuidel,

Kolosov,

Permyakov

et al. 2024

AND

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“…The method advantages are the high personalization and therapeutic effectiveness due to the feedback from person's own bioelectric characteristics, the involvement of mechanisms of multisensory integration, neuroplasticity and resonance brain mechanisms in the functional state normalization under stimulation; other advantages include automatic, without conscious patient efforts, management of therapeutic sensory effects, which makes it possible to use adaptive neurostimulation to correct adverse state shifts in patients with altered levels of consciousness, the elderly, and children [85,86]. These advantages enabled EEG-controlled light-sound neurostimulation to be successful in stress-induced states correction [87, 88], the functional state optimization [89], and correction of its adverse shifts [90,91], in cognitive rehabilitation of high-tech specialists [92], as well as in clinical studies in cognitive rehabilitation in stroke patients [93] and in the treatment of post-traumatic stress and professional burnout [94].…”

Section: Brain State-dependent Non-invasive Neurostimulation Achievem...mentioning

confidence: 99%

Brain State-Dependent Non-Invasive Neurostimulation with EEG Feedback: Achievements and Prospects

Fedotchev,

Zemlyanaya

2023

Sovrem Tehnol Med

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Non-invasive brain stimulation with electroencephalogram (EEG) feedback is an intensively developing and promising area of neurophysiology. The review considers the literature data over the past 5 years on the achievements and promising directions for the further development of this research line. Modern data on the developed approaches to the practical use of various types of brain state-dependent adaptive neurostimulation with EEG feedback were analyzed. The main attention is paid to the studies using non-invasive magnetic and electrical stimulation, as well as acoustic and audiovisual stimulation. The paper considers the possibilities and prospects for using these technologies in clinical medicine. The results of the authors' own research are presented.

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Exploring the Fusion of Neuroscience and Leadership Through Bibliometric Analysis

Kaur,

Kalra,

Kumari

et al. 2024

Building Organizational Resilience With Neuroleadership

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This study seeks to examine the diverse patterns related to exploring the fusion of neuroscience and leadership through bibliometric analysis based on prior research in this field. It also delves into the primary topic and prospects for forthcoming investigation. The present study used electronic Scopus databases, encompassing all significant previous studies published from 1989 to 2023. Only 803 research papers were retrieved from the Scopus database. This bibliometric analysis employs content analysis that discusses the methodology, year-wise contribution trends, and leading countries in the area of research. Secondly, bibliometric analysis is done using VOS-Viewer software and includes analyses based on bibliographic coupling, co-occurrence, and co-authorship analyses, which give numerous graphical illustrations of the network of research items. Thirdly, thematic mapping is done, which helped identify the different clusters in our topic and the latest contributions, in which new topics emerge and new methodologies are applied to study the fusion of neuroscience with leadership.

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Neural Interfaces Based on Endogenous Body Rhythms for Optimization of the Functional State of Humans and Cognitive Rehabilitation

Cited by 4 publications

References 83 publications

Mathematical model for controlling brain neuroplasticity during neurofeedback

Mathematical model for controlling brain neuroplasticity during neurofeedback

Brain State-Dependent Non-Invasive Neurostimulation with EEG Feedback: Achievements and Prospects

Exploring the Fusion of Neuroscience and Leadership Through Bibliometric Analysis

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