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June 5, 2026
Neural Network Maps as a Method for Constructing Mathematical Models
Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
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.

 

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Exploring the Link Between Interoception and Symptom Severity in Premature Ventricular Contractions

Journal of Clinical Medicine. 2024. Vol. 13. No. 24. Article 7756.
Limonova A., Minenko I., Anastasia A. Sukmanova, Kutsenko V., Sofya P. Kulikova, Maria A. Nazarova, Davtyan K., Drapkina O., Ershova A.

Background/Objectives: The physiological basis underlying symptomatic versus asymptomatic premature ventricular contractions (PVCs) remains poorly understood. However, symptomatic PVCs can significantly impair quality of life. In patients without structural heart disease, symptom intensity is crucial for guiding management strategies and determining the need for medical or surgical intervention. In this study, we aimed, for the first time, to examine the associations between PVC symptoms and cardiac interoception. Methods: This study included 34 participants with PVCs (20 women; median age = 42 years; 17 participants had asymptomatic PVCs) without concomitant disorders. Interoception was assessed through interoceptive accuracy (IA) probed by two behavioral tests—mental tracking (MT) and heartbeat detection (HBD)—and the neurophysiological marker of cardiac interoception, the heartbeat-evoked potentials (HEPs). Symptom intensity scores reported by patients served as the response variable in the regression analysis, with IA and HEP as predictors. Other factors such as sex, age, percent of body fat, trait anxiety, and alexithymia were added to the models as confounding variables. Results: IAMT was significantly higher in patients with symptomatic PVCs. IAMT and HEP modulation for the HBD task were associated with symptom intensity. A combined regression model incorporating both metrics showed the highest predictive accuracy for symptom severity. Adding confounding variables improved model quality (lower AIC); however, only the male sex emerged as a significant negative predictor for symptom intensity. Conclusions: Our findings confirm a significant association between interoception and PVC symptom severity. Integrating behavioral and neurophysiological interoception measures enhances symptom prediction accuracy, suggesting new ways to develop diagnostic and non-invasive treatment strategies targeting interoception in PVC management.

Research target: Medical and Health Sciences
Language: English
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Keywords: интероцепцияЭлектроэнцефалография (ЭЭГ)EEG (electroencephalography)cardiac interoceptionventricular contractions
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