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<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" article-type="other" dtd-version="1.2" xml:lang="en"><front><journal-meta><journal-id journal-id-type="publisher-id">I.P. Pavlov Journal of Higher Nervous Activity</journal-id><journal-title-group><journal-title xml:lang="en">I.P. Pavlov Journal of Higher Nervous Activity</journal-title><trans-title-group xml:lang="ru"><trans-title>Журнал высшей нервной деятельности им. И.П. Павлова</trans-title></trans-title-group></journal-title-group><issn publication-format="print">0044-4677</issn><issn publication-format="electronic">3034-5316</issn><publisher><publisher-name xml:lang="en">The Russian Academy of Sciences</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">652049</article-id><article-id pub-id-type="doi">10.31857/S0044467723010112</article-id><article-id pub-id-type="edn">GJUMWO</article-id><article-categories><subj-group subj-group-type="toc-heading" xml:lang="en"><subject>ФИЗИОЛОГИЯ ВЫСШЕЙ НЕРВНОЙ (КОГНИТИВНОЙ) &#13;
ДЕЯТЕЛЬНОСТИ ЧЕЛОВЕКА</subject></subj-group><subj-group subj-group-type="toc-heading" xml:lang="ru"><subject>ФИЗИОЛОГИЯ ВЫСШЕЙ НЕРВНОЙ (КОГНИТИВНОЙ) ДЕЯТЕЛЬНОСТИ ЧЕЛОВЕКА</subject></subj-group><subj-group subj-group-type="article-type"><subject></subject></subj-group></article-categories><title-group><article-title xml:lang="en">THETA AND ALPHA BANDS SPECTRAL POWER OF RESTING-STATE EEG IN GROUPS WITH DIFFERENT EFFICIENCY OF JOINT ACTIVITY IN DIADS</article-title><trans-title-group xml:lang="ru"><trans-title>Спектральные характеристики тета- и альфа-ритмов ЭЭГ в покое у групп испытуемых с различной результативностью совместной деятельности в диадах</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Murtazina</surname><given-names>E. P.</given-names></name><name xml:lang="ru"><surname>Муртазина</surname><given-names>Е. П.</given-names></name></name-alternatives><email>e.murtazina@nphys.ru</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Ginzburg-Shic</surname><given-names>Yu. A.</given-names></name><name xml:lang="ru"><surname>Гинзбург-Шик</surname><given-names>Ю. А.</given-names></name></name-alternatives><email>e.murtazina@nphys.ru</email><xref ref-type="aff" rid="aff1"/></contrib></contrib-group><aff-alternatives id="aff1"><aff><institution xml:lang="en">Anokhin Institute of Normal Physiology</institution></aff><aff><institution xml:lang="ru">ФГБНУ НИИ нормальной физиологии им. П.К. Анохина</institution></aff></aff-alternatives><pub-date date-type="pub" iso-8601-date="2023-01-01" publication-format="electronic"><day>01</day><month>01</month><year>2023</year></pub-date><volume>73</volume><issue>1</issue><fpage>24</fpage><lpage>37</lpage><history><date date-type="received" iso-8601-date="2025-02-02"><day>02</day><month>02</month><year>2025</year></date></history><permissions><copyright-statement xml:lang="en">Copyright ©; 2023, Е.П. Муртазина, Ю.А. Гинзбург-Шик</copyright-statement><copyright-statement xml:lang="ru">Copyright ©; 2023, Е.П. Муртазина, Ю.А. Гинзбург-Шик</copyright-statement><copyright-year>2023</copyright-year><copyright-holder xml:lang="en">Е.П. Муртазина, Ю.А. Гинзбург-Шик</copyright-holder><copyright-holder xml:lang="ru">Е.П. Муртазина, Ю.А. Гинзбург-Шик</copyright-holder></permissions><self-uri xlink:href="https://innoscience.ru/0044-4677/article/view/652049">https://innoscience.ru/0044-4677/article/view/652049</self-uri><abstract xml:lang="en"><p id="idm45181323719968">The aim of the study was to compare the spectral characteristics of theta and alpha frequency bands of the resting-state EEG between groups of subjects with different performance of subsequent joint sensorimotor activity in dyads. The study involved 26 men who, in 13 pairs, performed “Columns” trainings with biofeedback from EMG signals from the flexor muscles of the leading hand. According to their performance, the subjects of each pair were assigned to one of 2 groups: “winners” or “losers”. A higher spectral power of the theta rhythm of the EEG with closed eyes was found in the group of “losers” in comparison with the group of “winners” in the frontal, central and temporal zones of the cortex. The “winners” showed a higher level of spectral power of the EEG alpha rhythm with the eyes closed, especially in the alpha-2 frequency range in all 8 zones. The effectiveness of individual and joint training correlated negatively with the theta power and positively with the power of the EEG alpha rhythms in the closed-eyed state.</p></abstract><trans-abstract xml:lang="ru"><p id="idm45181323718208">Цель исследования состояла в сравнительном анализе спектральных характеристик тета- и альфа-ритмов фоновых ЭЭГ между группами испытуемых с различной результативностью последующей совместной сенсомоторной деятельности в диадах. Обследовано 26 мужчин, которые в 13 парах выполняли тренинги “Столбики” с биологической обратной связью от ЭМГ-сигналов мышц сгибателей кисти ведущей руки. По результативности испытуемые каждой пары были отнесены к одной из 2 групп: “победители” или “проигравшие”. Обнаружена более высокая спектральная мощность тета-ритма ЭЭГ с закрытыми глазами в группе “проигравших” по сравнению с группой “победителей”, во фронтальных, центральных и височных зонах коры. У “победителей” выявлен более высокий уровень спектральной мощности альфа-ритма ЭЭГ при закрытых глазах в большинстве зон коры, особенно в альфа2-диапазоне частот. Результативность индивидуальных и совместных тренингов отрицательно коррелировала со спектральными мощностями тета- и положительно с активностью альфа-ритмов ЭЭГ в состоянии с закрытыми глазами.</p></trans-abstract><kwd-group xml:lang="en"><kwd>resting-state EEG</kwd><kwd>theta rhythm</kwd><kwd>alpha rhythm</kwd><kwd>sensorimotor test</kwd><kwd>joint activity</kwd><kwd>competition</kwd><kwd>cooperation</kwd></kwd-group><kwd-group xml:lang="ru"><kwd>ЭЭГ покоя</kwd><kwd>тета-ритм</kwd><kwd>альфа-ритм</kwd><kwd>сенсомоторный тест</kwd><kwd>совместная деятельность</kwd><kwd>конкуренция</kwd><kwd>кооперация</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">Авторы выражают благодарность Н.Ю. Трифоновой, И.С. Буяновой за помощь в проведении исследования и О.В. Сергиенко за помощь в рекрутировании испытуемых.</funding-statement></funding-group></article-meta></front><body></body><back><ref-list><ref id="B1"><label>1.</label><mixed-citation>Гаврон А.А., Araujo Ya.I.D., Шарова Е.В. Смирнов А.С., Князев Г.Г., Челяпина М.В., Фадеева Л.М., Абдулаев А.А., Куликов М.А., Жаворонкова Л.А., Болдырева Г.Н., Верхлютов В.М., Пронин И.Н. Групповой и индивидуальный фМРТ-анализ основных сетей покоя здоровых испытуемых. Журнал высшей нервной деятельности им. И.П. Павлова. 2019. 69 (2): 150–163.</mixed-citation></ref><ref id="B2"><label>2.</label><mixed-citation>Князев Г.Г., Бочаров А.В., Митрофанова Л.Г., Слободской-Плюснин Я.Ю., Пылкова Л.В. ЭЭГ-корреляты агрессивности и тревожности в модели социальных взаимодействий. Журнал высшей нервной деятельности им. И.П. Павлова. 2011. 61 (6): 716–723.</mixed-citation></ref><ref id="B3"><label>3.</label><mixed-citation>Князев Г.Г., Бочаров А.В., Савостьянов А.Н., Левин Е.А. ЭЭГ-корреляты активности дефолт-системы при обработке социально значимой информации. Журнал высшей нервной деятельности им. И.П. Павлова. 2020. 70 (2): 174–181.</mixed-citation></ref><ref id="B4"><label>4.</label><mixed-citation>Коробейникова И.И., Каратыгин Н.А., Венерина Я.А. Спектральные характеристики альфа-ритма ЭЭГ при различной успешности достижения результата теста “n-back” у человека в обычных условиях и при ритмически организованной оптической стимуляции с частотой 10 Гц. Психическое здоровье. 2021. 16 (1): 3–11.</mixed-citation></ref><ref id="B5"><label>5.</label><mixed-citation>Крижановский С.А., Зима И.Г., Тукаев С.В., Чернинский А.А. Взаимосвязь эффективности деятельности человека с ЭЭГ-характеристиками его исходного состояния покоя. Ученые записки Таврического национального университета имени В.И. Вернадского. Серия: Биология Химия. 2009. 22 (61) (1): 50–58.</mixed-citation></ref><ref id="B6"><label>6.</label><mixed-citation>Муртазина Е.П., Матюлько И.С., Журавлев Б.В. Система поведенческого доминирования: Обзор психофизиологических особенностей и нейробиологических маркеров. Журн. мед.-биол. исследований. 2020. 8 (4): 409–418.</mixed-citation></ref><ref id="B7"><label>7.</label><mixed-citation>Павленко В.Б., Аликина М.А., Махин С.А. Взаимосвязь уровней общего и эмоционального интеллекта с амплитудой альфа- и бета-ритмов ЭЭГ покоя. Ученые записки Крымского федерального университета имени В.И. Вернадского. Биология. Химия. 2018. 4 (70) (3): 134–142.</mixed-citation></ref><ref id="B8"><label>8.</label><mixed-citation>Станкова Е.П., Шеповальников А.Н. Функциональное объединение корковых полей в покое как механизм преднастройки мозга к целенаправленной деятельности. Физиология человека. 2018. 44 (6): 5–14.</mixed-citation></ref><ref id="B9"><label>9.</label><mixed-citation>Al-Ezzi A., Kamel N., Faye I., Gunaseli E. Review of EEG, ERP, and Brain Connectivity Estimators as Predictive Biomarkers of Social Anxiety Disorder. Front Psychol. 2020. 11:730.</mixed-citation></ref><ref id="B10"><label>10.</label><mixed-citation>Babiloni C., Percio C.D., Vecchio F., Sebastiano F., Di Gennaro G., Quarato P.P., Morace R, Pavone L., Soricelli A., Noce G., Esposito V., Rossini P.M., Gallese V., Mirabella G. Alpha, beta and gamma electrocorticographic rhythms in somatosensory, motor, premotor and prefrontal cortical areas differ in movement execution and observation in humans. Clinical Neurophysiology. 2016. 127 (1): 641–654.</mixed-citation></ref><ref id="B11"><label>11.</label><mixed-citation>Balconi M., Mazza G. Lateralisation effect in comprehension of emotional facial expression: a comparison between EEG alpha band power and behavioural inhibition (BIS) and activation (BAS) systems. Laterality. 2010; 15 (3): 361–84.</mixed-citation></ref><ref id="B12"><label>12.</label><mixed-citation>Balconi M., Pagani S. Personality correlates (BAS-BIS), self-perception of social ranking, and cortical (alpha frequency band) modulation in peer-group comparison. Physiol. Behav. 2014. 133: 207–215.</mixed-citation></ref><ref id="B13"><label>13.</label><mixed-citation>Balconi M., Grippa E., Vanutelli M.E. What hemodynamic (fNIRS), electrophysiological (EEG) and autonomic integrated measures can tell us about emotional processing. Brain Cogn. 2015. 95: 67–76.</mixed-citation></ref><ref id="B14"><label>14.</label><mixed-citation>Balconi M., Vanutelli M.E. Competition in the Brain. The Contribution of EEG and fNIRS Modulation and Personality Effects in Social Ranking. Front. Psychol. 2016. 7. 1587.</mixed-citation></ref><ref id="B15"><label>15.</label><mixed-citation>Balconi M., Vanutelli M.E. Empathy in Negative and Positive Interpersonal Interactions. What is the Relationship Between Central (EEG, fNIRS) and Peripheral (Autonomic) Neurophysiological Responses. 2017. Advances in cognitive psychology, 13 (1). 105–120.</mixed-citation></ref><ref id="B16"><label>16.</label><mixed-citation>Balconi M., Vanutelli M.E. Functional EEG connectivity during competition. BMC Neuroscience, 2018. 19: 63.</mixed-citation></ref><ref id="B17"><label>17.</label><mixed-citation>Cao R., Shi H., Wang X., Huo S., Hao Y., Wang B., Guo H., Xiang J. Hemispheric Asymmetry of Functional Brain Networks under Different Emotions Using EEG Data. Entropy (Basel). 2020. 22 (9): 939.</mixed-citation></ref><ref id="B18"><label>18.</label><mixed-citation>Carver C.S., White T.L. Behavioral Inhibition, Behavioral Activation and Affective Responses to Impending Reward and Punishment: The BIS/BAS Scales. J. Pers. Soc. Psychol. 1994. 67 (2): 319–333.</mixed-citation></ref><ref id="B19"><label>19.</label><mixed-citation>Coomans E., Geraedts I., Keeser D., Pogarell O., Engelbregt H. Intersubject EEG Coherence in Healthy Dyads During Individual and Joint Mindful Breathing Exercise: An EEG-Based Experimental Hyperscanning Study. Advances in Cognitive Psychology, 2021. 17: 250–260.</mixed-citation></ref><ref id="B20"><label>20.</label><mixed-citation>Drigas A.S., Papoutsi C. A New Layered Model on Emotional Intelligence. Behav Sci (Basel). 2018. 8(5): 45.</mixed-citation></ref><ref id="B21"><label>21.</label><mixed-citation>Fox N.A., Bakermans-Kranenburg M.J., Yoo K.H., Bowman L.C. Cannon E.N., Vanderwert R.E., Ferrari P.F., van IJzendoorn M.H. Assessing human mirror activity with EEG mu rhythm: A meta-analysis. Psychol Bull. 2016. 142 (3): 291–313.</mixed-citation></ref><ref id="B22"><label>22.</label><mixed-citation>Karamacoska D., Barry R.J., Steiner G.Z. Electrophysiological underpinnings of response variability in the Go/NoGo task. International Journal of Psychophysiology. 2018. 134: 159–167.</mixed-citation></ref><ref id="B23"><label>23.</label><mixed-citation>Klados M.A., Konstantinidi P., Dacosta-Aguayo R., Kostaridou V.D., Vinciarelli A., Zervakis M. Automatic Recognition of Personality Profiles Using EEG Functional Connectivity During Emotional Processing. Brain sciences, 2020. 10 (5): 278.</mixed-citation></ref><ref id="B24"><label>24.</label><mixed-citation>Knyazev G.G., Savostyanov A.N., Levin E.A. Alpha synchronization and anxiety: implications for inhibition vs. alertness hypotheses. Int J Psychophysiol. 2006. 59 (2): 151–158.</mixed-citation></ref><ref id="B25"><label>25.</label><mixed-citation>Knyazev G., Merkulova E., Savostyanov A., Bocharov A., Saprigyn A. Personality and EEG correlates of reactive social behavior. Neuropsychologia. 2019. 124: 98–107.</mixed-citation></ref><ref id="B26"><label>26.</label><mixed-citation>Konvalinka I., Bauer M., Stahlhut C., Hansen L.K., Roepstorff A., Frith C.D. Frontal alpha oscillations distinguish leaders from followers: multivariate decoding of mutually interacting brains. Neuroimage. 2014. 1. 94: 79–88.</mixed-citation></ref><ref id="B27"><label>27.</label><mixed-citation>Li L., Bachevalier J., Hu X., Klin A., Preuss T.M., Shultz S., Jones W. Topology of the Structural Social Brain Network in Typical Adults. Brain Connect. 2018. 8 (9): 537–548.</mixed-citation></ref><ref id="B28"><label>28.</label><mixed-citation>Lockley S.W., Evans E.E., Scheer F.A., Brainard G.C., Czeisler C.A., Aeschbach D. Short-wavelength sensitivity for the direct effects of light on alertness, vigilance, and the waking electroencephalogram in humans. Sleep. 2006. 29 (2): 161–168.</mixed-citation></ref><ref id="B29"><label>29.</label><mixed-citation>Mahjoory K., Cesnaite E., Hohlefeld F.U., Villringer A., Nikulin V.V. Power and temporal dynamics of alpha oscillations at rest differentiate cognitive performance involving sustained and phasic cognitive control. NeuroImage. 2019. 188: 135–144.</mixed-citation></ref><ref id="B30"><label>30.</label><mixed-citation>Miskovic V., Ashbaugh A.R., Santesso D.L., McCabe R.E., Antony M.M., Schmidt L.A. Frontal brain oscillations and social anxiety: a cross-frequency spectral analysis during baseline and speech anticipation. Biol. Psychol. 2010. 83: 125–132.</mixed-citation></ref><ref id="B31"><label>31.</label><mixed-citation>Mu Y., Fan Y., Mao L., Han S. Event-related theta and alpha oscillations mediate empathy for pain. Brain Res. 2008. 1234: 128–136.</mixed-citation></ref><ref id="B32"><label>32.</label><mixed-citation>Palacios-García I., Silva J., Villena-González M., Campos-Arteaga G., Artigas-Vergara C., Luarte N., Rodríguez E., Bosman C.A. Increase in Beta Power Reflects Attentional Top-Down Modulation After Psychosocial Stress Induction. Front Hum Neurosci. 2021. 15: 630813.</mixed-citation></ref><ref id="B33"><label>33.</label><mixed-citation>Papo D. Why should cognitive neuroscientists study the brain’s resting state? Front. Hum. Neurosci. 2013. 7 (45): 1.</mixed-citation></ref><ref id="B34"><label>34.</label><mixed-citation>Perry A., Stein L., Bentin S. Motor and attentional mechanisms involved in social interaction-Evidence from mu and alpha EEG suppression. Neuroimage. 2011. 58: 895–904.</mixed-citation></ref><ref id="B35"><label>35.</label><mixed-citation>Petit S., Badcock N.A., Grootswagers T., Woolgar A. Unconstrained multivariate EEG decoding can help detect lexical-semantic processing in individual children. Sci Rep. 2020. 10 (1): 10849.</mixed-citation></ref><ref id="B36"><label>36.</label><mixed-citation>Prat C.S., Yamasaki B.L., Kluender R.A., Stocco A. Resting-state qEEG predicts rate of second language learning in adults. Brain and Language. 2016. 157–158: 44–50.</mixed-citation></ref><ref id="B37"><label>37.</label><mixed-citation>Rizzolatti G., Sinigaglia C. Mirrors in the brain: how our minds share actions and emotions – Oxford University Press, 2008. 242 p.</mixed-citation></ref><ref id="B38"><label>38.</label><mixed-citation>Sadaghiani S., Hesselmann G., Kleinschmidt A. Distributed and antagonistic contributions of ongoing activity fluctuations to auditory stimulus detection. J Neurosci. 2009. 29 (42): 13410–13417.</mixed-citation></ref><ref id="B39"><label>39.</label><mixed-citation>Sadaghiani S., Scheeringa R., Lehongre K., Morillon B., Giraud A.L., Kleinschmidt A. Intrinsic connectivity networks. α oscillations. and tonic alertness: A simultaneous electroencephalography/functional magnetic resonance imaging study. J. Neurosci. 2010. 30 (30): 10243–10250.</mixed-citation></ref><ref id="B40"><label>40.</label><mixed-citation>Sargent K., Chavez-Baldini U., Master S.L., Verweij K.J.H., Lok A., Sutterland A.L., Vulink N.C., Denys D., Smit D.J.A., Nieman D.H. Resting-state brain oscillations predict cognitive function in psychiatric disorders: A transdiagnostic machine learning approach. Neuroimage Clin. 2021. 30: 102617.</mixed-citation></ref><ref id="B41"><label>41.</label><mixed-citation>Zhao G., Zhang Y., Ge Y. Frontal EEG Asymmetry and Middle Line Power Difference in Discrete Emotions. Frontiers in Behavioral Neuroscience. 2018. 12.</mixed-citation></ref><ref id="B42"><label>42.</label><mixed-citation>Zinchenko O., Savelo O., Klucharev V. Role of the prefrontal cortex in prosocial and self-maximization motivations: An rTMS study. Scientific Reports, 2021. 11 (1): 22 334.</mixed-citation></ref></ref-list></back></article>
