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July 20, 2026
Scientists Create Open Dataset for Studying Concentration
A team of Russian researchers, including scientists from HSE University–St Petersburg, has developed the first open multimodal dataset containing recordings of brain activity, heart function, and video observations to help researchers understand what happens in the human brain during deep concentration. In the future, the dataset could accelerate the development of neural interfaces, rehabilitation technologies, and AI systems. The article has been published in Scientific Data.
July 20, 2026
‘Science Is Universal-It Knows No Borders
Fuad Aleskerov, Tenured Professor and Director of the International Centre of Decision Choice and Analysis at HSE University, together with his colleagues, has developed methods of network analysis in bibliometrics that have made it possible to identify patterns in the appearance and citation of publications in academic journals, as well as their influence on each other. When one or a number of studies are frequently cited by a wide range of journals, this is an indicator that the research is of high quality. By contrast, extensive cross-citation within a limited group of journals increases the likelihood of identifying a network of predatory publications.
July 20, 2026
Scientists Propose Method for More Efficient Resource Use in Machine Learning
An international group of researchers, including mathematicians from the AI and Digital Science Institute at the HSE Faculty of Computer Science, has provided a theoretical justification for a simple and computationally efficient method of estimating uncertainty in Stochastic Gradient Descent (SGD). The paper has been published on the scientific preprint server arXiv.org and presented at AISTATS 2026.

 

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Диагностические возможности транскраниальной магнитной стимуляции для прогнозирования двигательного восстановления после инсульта

Нервно-мышечные болезни. 2020. Т. 10. № 1. С. 64–74.
Nazarova M., Novikov P., Nikulin V., Иванова Г. Е.

Transcranial magnetic stimulation is a method of focal non-invasive brain stimulation, characterized by high spatial and temporal resolution. To date, diagnostic transcranial magnetic stimulation has been used in clinical practice primarily to assess an involvement of the upper motor neurons and to measure the velocity of the neuronal impulse propagation. However, in the last 10 years, a possible range of transcranial magnetic stimulation diagnostic applications has significantly expanded. Many transcranial magnetic stimulation approaches are coming from scientific laboratories to clinical practice due to an increased availability of transcranial magnetic stimulation equipment, in particular, magnetic resonance imaging navigation for transcranial magnetic stimulation and a combination of the transcranial magnetic stimulation with electroencephalography and also due to an increased awareness of the clinicians. The diagnostic potential of transcranial magnetic stimulation in relation to motor recovery after a stroke can be classified into 4 directions:

1) assessment of the vertical tracts integrity (primarily, the cortico-spinal tract); 2) an assessment of the cortical excitation-inhibition balance;

3) probing of the functional and effective connectivity among brain regions (primarily, cortical convexity and cerebellum);

4) motor mapping to evaluate cortical reorganization.

In this article we will present these 4 directions of the transcranial magnetic stimulation application to study motor system pathophysiology and to predict motor outcome in stroke, including both existing and developing approaches.

Research target: Biology Medical Technologies Basic Medicine Clinical Medicine
Priority areas: humanitarian
Language: Russian
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Keywords: инсульттранскраниальная магнитная стимуляцияstrokeTranscranial magnetic stimulationmotor rehabilitationmotor recovery prognosisдвигательное восстановлениепрогноз двигательного восстановления
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