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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">687575</article-id><article-id pub-id-type="doi">10.31857/S0044467725040061</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">Contribution of intellectual environment of professional activity and STin2VNTR polymorphism of serotonin transporter gene to EEG activity of aging brain: Loreta study</article-title><trans-title-group xml:lang="ru"><trans-title>Вклад интеллектуальной среды профессиональной деятельности и полиморфизма STin2VNTR гена транспортера серотонина в ЭЭГ активность стареющего мозга: LORETA исследование</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Privodnova</surname><given-names>E. Yu.</given-names></name><name xml:lang="ru"><surname>Приводнова</surname><given-names>Е. Ю.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><email>privodnovaeu@neuronm.ru</email><xref ref-type="aff" rid="aff1"/><xref ref-type="aff" rid="aff2"/></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Volf</surname><given-names>N. V.</given-names></name><name xml:lang="ru"><surname>Вольф</surname><given-names>Н. В.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><email>privodnovaeu@neuronm.ru</email><xref ref-type="aff" rid="aff1"/><xref ref-type="aff" rid="aff2"/></contrib></contrib-group><aff-alternatives id="aff1"><aff><institution xml:lang="en">Scientific Research Institute of Neurosciences and Medicine</institution></aff><aff><institution xml:lang="ru">Научно-исследовательский институт нейронаук и медицины</institution></aff></aff-alternatives><aff-alternatives id="aff2"><aff><institution xml:lang="en">Novosibirsk State University</institution></aff><aff><institution xml:lang="ru">Новосибирский государственный университет</institution></aff></aff-alternatives><pub-date date-type="pub" iso-8601-date="2025-08-15" publication-format="electronic"><day>15</day><month>08</month><year>2025</year></pub-date><volume>75</volume><issue>4</issue><issue-title xml:lang="en"/><issue-title xml:lang="ru"/><fpage>462</fpage><lpage>470</lpage><history><date date-type="received" iso-8601-date="2025-07-15"><day>15</day><month>07</month><year>2025</year></date><date date-type="accepted" iso-8601-date="2025-07-15"><day>15</day><month>07</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://transsyst.ru/0044-4677/article/view/687575">https://transsyst.ru/0044-4677/article/view/687575</self-uri><abstract xml:lang="en"><p>Heterogeneity of mental aging is largely determined by the interaction of environmental and genetic factors. Previously, during analysis of age-related changes in the global power of the background EEG, only in elderly subjects we identified differences that were moderated by the STin2VNTR polymorphism of the serotonin transporter gene and training due to the intellectual load of the professional environment (comparison of scientists, SA, and people not associated with professional scientific activity, NSA). For slow rhythms, the greatest differences were observed between homozygous genotypes, with the lowest power values in elderly NSA in the 10/10 group, and in SA – 12/12. The aim of this study was to determine the spatial pattern of current source density (CSD) underlying the identified power decreases in the 10/10 NSA and 12/12 SA genotypes. The study involved elderly subjects (55–80 years; 66 SA and 76 NSA). Voxel-by-voxel analysis using eLORETA showed no local features of the CSD decrease for the 10/10 NSA genotype compared to 12/12 NSA. Thus, the previously noted decrease in the power of slow rhythms in the 10/10 NSA group may be due to a unidirectional diffuse decrease in different areas of the cerebral cortex. In contrast, in 12/12 SA group compared to 10/10 SA, spatial patterns of CSD decrease were revealed in the delta rhythm frequencies mainly in the precuneus, inferior and superior parietal lobule of the left hemisphere, in the alpha2 and alpha3 rhythm frequencies – in the precuneus and superior parietal lobule of the right hemisphere. The data obtained may indicate an adaptive reorganization of neural networks associated with cognitive training in elderly scientists carrying the 12/12 genotype.</p></abstract><trans-abstract xml:lang="ru"><p>Гетерогенность ментального старения в значительной степени определяется взаимодействием средовых и генетических факторов. Ранее нами при анализе возрастных изменений показателей глобальной мощности фоновой ЭЭГ только у пожилых испытуемых были выявлены различия, связанные с полиморфизмом STin2VNTR гена транспортера серотонина и тренингом, обусловленным интеллектуальной насыщенностью среды профессиональной деятельности (сравнение ученых, НД и людей, не связанных с профессиональной научной деятельностью, ННД). Для медленных ритмов наибольшие различия наблюдались между гомозиготными генотипами, при этом самые низкие значения мощности наблюдались у пожилых ННД в группе генотипа 10/10, а у НД – 12/12. Целью настоящего исследования было определение пространственного паттерна плотности источников тока (ПИТ), лежащего в основе выявленных снижений мощности у генотипов 10/10 ННД и 12/12 НД. В исследовании участвовали пожилые испытуемые (55–80 лет; 38 НД и 39 ННД). Повоксельный анализ с использованием eLORETA показал отсутствие локальных особенностей снижения ПИТ для генотипа 10/10 ННД по сравнению с 12/12 ННД. Таким образом, по-видимому, отмеченное ранее снижение мощности медленных ритмов в группе 10/10 ННД обусловлено однонаправленным диффузным снижением в различных областях коры мозга. В отличие от этого, у носителей генотипа 12/12 НД, по сравнению с 10/10 НД, выявлены дифференцированные пространственные паттерны снижения ПИТ на частоте дельта-ритма преимущественно в преклиновидной коре, нижней и верхней париетальной дольке левого полушария, на частотах альфа2 и альфа3 ритмов – в преклиновидной коре и верхней париетальной дольке правого полушария. Полученные данные могут свидетельствовать о связанной с когнитивным тренингом адаптивной реорганизации нейронных сетей у пожилых ученых – носителей генотипа 12/12.</p></trans-abstract><kwd-group xml:lang="en"><kwd>current source density</kwd><kwd>eLORETA</kwd><kwd>aging</kwd><kwd>STin2VNTR polymorphism of the serotonin transporter gene</kwd><kwd>cognitive training</kwd></kwd-group><kwd-group xml:lang="ru"><kwd>плотность источников тока</kwd><kwd>eLORETA</kwd><kwd>старение</kwd><kwd>полиморфизм STin2VNTR гена транспортера серотонина</kwd><kwd>когнитивный тренинг</kwd></kwd-group><funding-group><award-group><funding-source><institution-wrap><institution xml:lang="ru">Министерство науки и высшего образования Российской Федерации</institution></institution-wrap><institution-wrap><institution xml:lang="en">Ministry of Education and Science of the Russian Federation</institution></institution-wrap></funding-source><award-id>075-03-2022-635</award-id></award-group></funding-group></article-meta></front><body></body><back><ref-list><ref id="B1"><label>1.</label><mixed-citation>Вольф Н.В., Приводнова Е.Ю., Базовкина Д.В. 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