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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="research-article" 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">682789</article-id><article-id pub-id-type="doi">10.31857/S0044467725010061</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>Research Article</subject></subj-group></article-categories><title-group><article-title xml:lang="en">Peculiarities of EEG activity parameters during implicit learning of artificial grammar rules</article-title><trans-title-group xml:lang="ru"><trans-title>Особенности параметров ЭЭГ-активности при имплицитном научении правилам искусственной грамматики</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Batalova</surname><given-names>V. A.</given-names></name><name xml:lang="ru"><surname>Баталова</surname><given-names>В. А.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><email>ksp55@yandex.ru</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Petrov</surname><given-names>V. V.</given-names></name><name xml:lang="ru"><surname>Петров</surname><given-names>В. В.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><email>ksp55@yandex.ru</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Abramova</surname><given-names>S. R.</given-names></name><name xml:lang="ru"><surname>Абрамова</surname><given-names>С. Р.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><email>ksp55@yandex.ru</email><xref ref-type="aff" rid="aff2"/></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Kozhevnikov</surname><given-names>S. P.</given-names></name><name xml:lang="ru"><surname>Кожевников</surname><given-names>С. П.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><email>ksp55@yandex.ru</email><xref ref-type="aff" rid="aff2"/></contrib></contrib-group><aff-alternatives id="aff1"><aff><institution xml:lang="en">Sirius University of Science and Technology</institution></aff><aff><institution xml:lang="ru">Научно-технологический университет "Сириус"</institution></aff></aff-alternatives><aff-alternatives id="aff2"><aff><institution xml:lang="en">Udmurt State University</institution></aff><aff><institution xml:lang="ru">Удмуртский государственный университет</institution></aff></aff-alternatives><pub-date date-type="pub" iso-8601-date="2025-01-15" publication-format="electronic"><day>15</day><month>01</month><year>2025</year></pub-date><volume>75</volume><issue>1</issue><issue-title xml:lang="ru"/><fpage>68</fpage><lpage>77</lpage><history><date date-type="received" iso-8601-date="2025-06-04"><day>04</day><month>06</month><year>2025</year></date></history><permissions><copyright-statement xml:lang="en">Copyright ©; 2025, Russian Academy of Sciences</copyright-statement><copyright-statement xml:lang="ru">Copyright ©; 2025, Российская академия наук</copyright-statement><copyright-year>2025</copyright-year><copyright-holder xml:lang="en">Russian Academy of Sciences</copyright-holder><copyright-holder xml:lang="ru">Российская академия наук</copyright-holder></permissions><self-uri xlink:href="https://innoscience.ru/0044-4677/article/view/682789">https://innoscience.ru/0044-4677/article/view/682789</self-uri><abstract xml:lang="en"><p>We studied changes in the bioelectrical activity of the brain during implicit learning. The study showed that implicit learning is associated with an increase in amplitude in the α1-, α2- and θ-frequency ranges, mainly in the frontotemporal areas of the cortex. In the higher frequency β range, there is also an increase in amplitude, most significantly in the parieto-occipital and partially frontal areas of the cortex. The observed changes suggest that implicit learning is based on the interaction of two relatively independent neural networks in the brain. The frontotemporal cortex and α1- and θ-frequency oscillatory systems are responsible for processing information and identifying relevant sequences. Whereas the parieto-occipital regions and the oscillatory systems of β2- and α3-rhythms are likely to provide processes for anticipating and preparing a response to relevant sequences and ignoring irrelevant ones.</p></abstract><trans-abstract xml:lang="ru"><p>Исследовали изменение показателей биоэлектрической активности мозга при имплицитном (неосознаваемом) научении. В ходе исследования показано, что имплицитное научение сопровождается увеличением амплитуды в α1-, α2- и θ-частотных диапазонах преимущественно в лобно-височных областях коры. В более высокочастотном β-диапазоне амплитуда также возрастает, причем наиболее значительно – в теменно-затылочных и частично фронтальных областях коры. Наблюдаемые изменения позволяют предположить, что имплицитное научение строится на основе взаимодействия двух относительно независимых нейронных сетей мозга. Лобно-височные отделы коры и осцилляторные системы α1- и θ-частотных диапазонов обеспечивают процессы обработки информации и выявление релевантных последовательностей, тогда как теменно-затылочные отделы и осцилляторные системы β2- и α3- ритмов, вероятно, обеспечивают процессы ожидания и подготовки ответной реакции на релевантные последовательности и игнорирование нерелевантных. Процесс имплицитного научения наиболее специфично связан изменения в диапазоне θ-ритма.</p></trans-abstract><kwd-group xml:lang="en"><kwd>implicit learning</kwd><kwd>attention processes</kwd><kwd>EEG</kwd></kwd-group><kwd-group xml:lang="ru"><kwd>имплицитное научение</kwd><kwd>внимание</kwd><kwd>ЭЭГ</kwd></kwd-group><funding-group/></article-meta></front><body></body><back><ref-list><ref id="B1"><label>1.</label><mixed-citation>Агафонов А.Ю., Крюкова А.П, Бурмистров С.Н. Имплицитное научение искусственным грамматикам: установка vs обратная связь. Известия Самарского научного центра Российской академии наук. 2015. 17(1–3): 620–625.</mixed-citation></ref><ref id="B2"><label>2.</label><mixed-citation>Крюкова А.П., Агафонов А.Ю., Бурмистров С.Н. Эффект переноса при селективном воспроизведении имплицитной последовательности. Российский психологический журнал. 2022. 19(1): 89–100.</mixed-citation></ref><ref id="B3"><label>3.</label><mixed-citation>Русалова М.Н. 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