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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">687508</article-id><article-id pub-id-type="doi">10.31857/S0044467725040038</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">Application of the functionally homogeneous regions (FHR) method to identify the most informative regions of the human brain for binary classification of schizophrenia based on resting-state functional MRI data</article-title><trans-title-group xml:lang="ru"><trans-title>Применение метода функционально однородных регионов (FHR) для выделения наиболее информативных регионов головного мозга человека для бинарной классификации шизофрении по данным функциональной МРТ в состоянии покоя</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Poyda</surname><given-names>A. A.</given-names></name><name xml:lang="ru"><surname>Пойда</surname><given-names>А. А.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><email>Poyda_AA@nrcki.ru</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Kozlov</surname><given-names>S. O.</given-names></name><name xml:lang="ru"><surname>Козлов</surname><given-names>С. О.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><email>Poyda_AA@nrcki.ru</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Zhemchuzhnikov</surname><given-names>A. D.</given-names></name><name xml:lang="ru"><surname>Жемчужников</surname><given-names>А. Д.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><email>Poyda_AA@nrcki.ru</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Orlov</surname><given-names>V. A.</given-names></name><name xml:lang="ru"><surname>Орлов</surname><given-names>В. А.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><email>Poyda_AA@nrcki.ru</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Kartashov</surname><given-names>S. I.</given-names></name><name xml:lang="ru"><surname>Карташов</surname><given-names>С. И.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><email>Poyda_AA@nrcki.ru</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Bravve</surname><given-names>L. V.</given-names></name><name xml:lang="ru"><surname>Бравве</surname><given-names>Л. В.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><email>Poyda_AA@nrcki.ru</email><xref ref-type="aff" rid="aff2"/></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Kaydan</surname><given-names>М. A.</given-names></name><name xml:lang="ru"><surname>Кайдан</surname><given-names>М. А.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><email>Poyda_AA@nrcki.ru</email><xref ref-type="aff" rid="aff2"/></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Kostyuk</surname><given-names>G. P.</given-names></name><name xml:lang="ru"><surname>Костюк</surname><given-names>Г. П.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><email>Poyda_AA@nrcki.ru</email><xref ref-type="aff" rid="aff2"/></contrib></contrib-group><aff-alternatives id="aff1"><aff><institution xml:lang="en">National Research Center “Kurtchatov Institute”</institution></aff><aff><institution xml:lang="ru">Национальный исследовательский центр «Курчатовский институт»</institution></aff></aff-alternatives><aff-alternatives id="aff2"><aff><institution xml:lang="en">Psychiatric Hospital no. 1 Named after N.A. Alexeev of the Department of Health of Moscow</institution></aff><aff><institution xml:lang="ru">Государственное бюджетное учреждение здравоохранения города Москвы «Психиатрическая клиническая больница № 1 им. Н.А. Алексеева Департамента здравоохранения г. Москвы»</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>420</fpage><lpage>434</lpage><history><date date-type="received" iso-8601-date="2025-07-14"><day>14</day><month>07</month><year>2025</year></date><date date-type="accepted" iso-8601-date="2025-07-14"><day>14</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/687508">https://transsyst.ru/0044-4677/article/view/687508</self-uri><abstract xml:lang="en"><p>The article presents results of the analysis of the most informative brain regions for diagnosing schizophrenia based on resting-state functional MRI data using method of functionally homogeneous regions (FHR) previously developed by the authors and the CONN functional atlas. The analysis was performed using fMRI data from 32 subjects diagnosed with schizophrenia and 36 subjects from the control group obtained on Siemens tomograph. Data from 19 subjects diagnosed with schizophrenia and 29 subjects from the control group obtained on General Electric MRI scanner were used for verification. Eight most informative regions were identified. The analysis of the identified regions showed that changing the composition of the training group significantly affects the list of the most significant regions. At the same time the analysis of the identified most significant regions for repeatability with varying the composition of subjects showed that out of the eight identified most significant regions, four have repeatability higher than 70%, two have repeatability from 50% to 70%, and two have repeatability from 30% to 50%. This may indicate that the identified regions are not random and opens up prospects for further in-depth analysis and determination of their significance in diagnosing schizophrenia. Verification carried out on data from General Electric MRI scanner partially confirmed the heightened<italic> </italic>importance of the identified regions for the classification of schizophrenia pathology, but no perfect match was achieved on datasets from different MRI scanners.</p></abstract><trans-abstract xml:lang="ru"><p>В статье приведен результат анализа наиболее информативных регионов головного мозга для постановки диагноза шизофрении по данным функциональной магнитно-резонансной томографии (фМРТ) в состоянии покоя с использованием ранее разработанного авторами метода функционально однородных регионов (functionally homogeneous regions – FHR) и функционального атласа CONN. Анализ проведен на данных 32 испытуемых с диагнозом шизофрении и 36 человек из контрольной группы, полученных на томографе Siemens. Для проверки были использованы данные 19 пациентов и 29 человек из контрольной группы, полученные на томографе General Electric. Выявлено 8 наиболее информативных регионов. Проведенный анализ выделенных регионов показал, что изменение состава обучающей группы существенно влияет на список наиболее значимых регионов. В то же время анализ выделенных наиболее значимых регионов на повторяемость при варьировании состава испытуемых показал, что из 8 выделенных наиболее значимых регионов 4 имеют повторяемость выше 70%, 2 – от 50% до 70% и 2 – от 30% до 50%. Это может свидетельствовать о том, что выявленные регионы не случайны, и открывает перспективы для их дальнейшего углубленного анализа и определения значимости при постановке диагноза шизофрении. Проверка, проведенная на данных другого томографа, частично подтвердила повышенную значимость выделенных регионов для классификации патологии шизофрении, но идеального совпадения на наборах с разных томографов достигнуто не было.</p></trans-abstract><kwd-group xml:lang="en"><kwd>automatic classification of schizophrenia</kwd><kwd>fMRI</kwd><kwd>resting state</kwd><kwd>machine learning methods</kwd></kwd-group><kwd-group xml:lang="ru"><kwd>автоматическая классификация шизофрении</kwd><kwd>фМРТ</kwd><kwd>состояние покоя</kwd><kwd>методы машинного обучения</kwd></kwd-group><funding-group><award-group><funding-source><institution-wrap><institution xml:lang="ru">Правительство РФ</institution></institution-wrap><institution-wrap><institution xml:lang="en">Government of the Russian Federation</institution></institution-wrap></funding-source></award-group></funding-group></article-meta></front><body></body><back><ref-list><ref id="B1"><label>1.</label><mixed-citation>Жемчужников А.Д., Карташов С.И., Козлов С.О., Орлов В.А., Пойда А.А., Захарова Н.В., Бравве Л.В., Мамедова Г.Ш., Кайдан М.А. 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