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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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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
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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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Neuromagnetic 40 Hz Auditory Steady-State Response in the left auditory cortex is related to language comprehension in children with Autism Spectrum Disorder

Progress in Neuro-Psychopharmacology and Biological Psychiatry. 2023. Vol. 122. Article 110690.
Arutiunian V., Arcara G., Buyanova I., Davydova E., Pereverzeva D., Sorokin A., Tyushkevich S., Mamokhina U., Danilina K., Dragoy O.

Language impairment is comorbid in most children with Autism Spectrum Disorder (ASD), but its neural mechanisms are still poorly understood. Some studies hypothesize that the atypical low-level sensory perception in the auditory cortex accounts for the abnormal language development in these children. One of the potential non-invasive measures of such low-level perception can be the cortical gamma-band oscillations registered with magnetoencephalography (MEG), and 40 Hz Auditory Steady-State Response (40 Hz ASSR) is a reliable paradigm for eliciting auditory gamma response. Although there is research in children with and without ASD using 40 Hz ASSR, nothing is known about the relationship between this auditory response in children with ASD and their language abilities measured directly in formal assessment.

In the present study, we used MEG and individual brain models to investigate 40 Hz ASSR in primary-school- aged children with and without ASD. It was also used to assess how the strength of the auditory response is related to language abilities of children with ASD, their non-verbal IQ, and social functioning. A total of 40 children were included in the study.

The results demonstrated that 40 Hz ASSR was reduced in the right auditory cortex in children with ASD when comparing them to typically developing controls. Importantly, our study provides the first evidence of the as- sociation between 40 Hz ASSR in the language-dominant left auditory cortex and language comprehension in children with ASD. This link was domain-specific because the other brain-behavior correlations were non- significant.

Research target: Philology and Linguistics Psychology
Language: English
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Keywords: магнитоэнцефалография (МЭГ)magnetoencephalography (MEG)расстройства аутистического спектра(РАС)Autism Spectrum Disorder(ASD)auditory gamma oscillationsслуховые гамма осцилляции
Publication based on the results of:
Neuroanatomical foundations of language disorders in children and adults (2023)
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