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  • Динамика спектрально-когерентных параметров ЭЭГ в процессе терапии эндогенной депрессии у пациенток молодого возраста
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June 5, 2026
‘In the Age of Technology, It Is Interesting to Look into the Past and Think about What We Can Take from It
Polina Tabakova decided to apply for a Philology degree at HSE in Nizhny Novgorod because she grew up in Mari El and did not want to move far away from the Russian forests. In an interview for the Young Scientists of HSE University project, she spoke about the genre of the campus novel, the existential drama of Kolobok, and a blackout version of Eugene Onegin.
June 5, 2026
HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a new compression method for large language models such as GPT and LLaMA that reduces their size by 25–36% without additional training or significant loss of accuracy. This is the first approach to use mathematical transformations—specifically, rotations of model weights—to make models more amenable to compression with structured matrices. The study results have been published in ACL Findings 2025. The code is available on GitHub.
June 4, 2026
Machine Learning Models Can Help Reduce Volatility and Boost Stock Market Returns
The use of machine learning models makes it possible to achieve greater accuracy in predicting risks in the Russian stock market compared to classical econometric approaches. The predictive power of these models increases by 23%, while the average investor’s return can reach up to 13% per annum. These conclusions were drawn by Nikita Lysenok from the Department of Financial Market Infrastructure at the HSE Faculty of Economic Sciences. The paper has been published in Fundamental and Applied Mathematics.

 

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Динамика спектрально-когерентных параметров ЭЭГ в процессе терапии эндогенной депрессии у пациенток молодого возраста

Психиатрия. 2024. Т. 22. № 6. С. 27–33.
Изнак Е. В., Дамянович Е. В., Береснева А. Ф., Shishkovskaya T., Олейчик И. В., Изнак А. Ф.

Background: the need to study and clarify the neurobiological basis of depression is due to the widespread prevalence and heavy socioeconomic burden of this disease. In order to prevent relapses, it is recommended to continue treatment for depression for a long time after the relief of the main depressive symptoms. The study of neurobiological pathways of depression showed a significance of EEG parameters for diagnosis and prognosis. However, delayed EEG changes have been almost completely unstudied. The aim of the study was to analyze the dynamics of spectral-coherent EEG parameters during long-term therapy for endogenous depression in young female patients. Patients and Methods: The study included 20 female patients aged 16-25 years who underwent quantitative clinical (using the HDRS-17 and GAF scales) and neurophysiological (multichannel resting EEG with subsequent analysis of absolute spectral power (SP) and EEG coherence). Examination underwent three times: upon admission to hospital for treatment before the start of the course of therapy (at visit 1), upon discharge from the hospital at the stage of establishing remission (at visit 2) and one year after discharge from the hospital on maintenance therapy (at visit 3).

Methods: clinical-psychopathological, psychometric, neurophysiological, statistical.

Results: after the course of stopping therapy (at visit 2), there was a significant (p < 0.01) reduction in depressive symptoms with further improvement in the clinical condition (according to the HDRS-17 scale) and social functioning (according to the GAF scale) a year later (at visit 3). This was associated with an EEG slowdown in the form of a generalized increase in the SP of theta-delta activity, which was significant (p < 0.05) in the frontal-central leads, and a significant (p < 0.05) decrease in the alpha2 and alpha3 components of the alpha rhythm in the occipital zones. The same EEG pattern, including a significantly increased SP of theta2 sub-band in the centralparietal-occipital leads, persists a year later (at visit 3).

Conclusion: the observed EEG changes are assessed as a re ection of a complex restructuring of brain activity into a mode more adequate for these patients, ensuring the suppression of depressive symptoms and restoration of the social functioning of patients.

Research target: Basic Medicine
Language: Russian
DOI
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Keywords: депрессия
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