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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.
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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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Prestimulus beta rhythm influence reaction time during real-time brain-dependent stimuli presentation

P. 6–9.
Aksiotis V., Alexei Ossadtchi

In the present study, a fast and adaptive technique for the presentation of stimuli based on ongoing brain rhythm is described. Sensorimotor cortical mu rhythm (divided by two components: alpha (mu) and beta) was used as target for assessment of prestimulus rhythm’s power influence on the consequent reaction time. The final sample consisted of 15 participants who was instructed to response immediately after change of stimuli color. As a result of the method application, a longer reaction time in the case of highly synchronized beta oscillations compared to desynchronization was achieved in the simple reaction time task. It indicates, firstly, a crucial role of baseline, prestimulus beta in motor action initiation and, secondly, the possibility to change reaction using adaptive processing and timing of presentation in real-time.

Language: English
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Keywords: EEGЭЭГBCIинтерфейсы мозг-компьютерbrain state-dependent presentation
Publication based on the results of:
Двунаправленные электрокортикографические интерфейсы мозг-компьютер для управления, стимуляции и коммуникации (2020)

In book

2022 Fourth International Conference Neurotechnologies and Neurointerfaces (CNN) Kaliningrad, 14-16 Sept. 2022
IEEE, 2022.
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