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September 11, 2026
How to Assess Students Knowledge in the Age of AI
A researcher at HSE University has proposed a flowchart to help lecturers decide how to assess students who use artificial intelligence. It shows where the use of AI should be restricted and where it can be incorporated into the learning process. The article has been published in IT Professional.
September 9, 2026
‘Balkan Hospitality Opens Doors: Studying Dialects on the Verge of Extinction
You cannot study spoken dialects from books. Instead, you need to go to a village, seek out its elders, and earn the trust of local residents before you can record hours of spontaneous stories. This is how Natalia Muravleva, Associate Professor at the Faculty of Humanities, conducts her research. Her internship in Serbia continued her long-standing study of dialects spoken by Macedonian settlers. In this interview, she discusses how diaspora cultural centres help researchers reach informants, why native speakers need to be interviewed only in their own language (otherwise, as she puts it, they may 'break'), and how a single field season helped her finalise her monograph. She also shares warm memories of autumn in Belgrade and of colleagues with whom grammar can be discussed in three languages at once.
September 9, 2026
Scientists Train Neural Network to Generate Process Plans from 3D Models
Researchers at the HSE FCS AI and Digital Science Institute have developed CAD2TechSpec, a framework that converts 3D models of mechanical parts into machining process plans—step-by-step instructions for machine tools. The solution aims to reduce the time required for the design and preparation of technical process documentation in mechanical engineering, aircraft manufacturing, and other high-tech industries. The study findings have been published in PeerJ Computer Science.

 

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Stability of cortical muscle representations: TMS motor mapping test-retest study

P. 1–2.
Moiseeva V., Nazarova M., Novikov P., Иванина Е. О., Kozlova K., Nikulin V.

Cortical mapping with transcranial magnetic stimulation (TMS) is a promising approach for non-invasive investigation of the motor cortex in humans. However, apart from the parameters reflecting general corticospinal excitability, e.g., resting motor threshold (RMT) and mean amplitude of the motor evoked potentials, the reproducibility of other TMS motor maps metrics remains controversial or unknown. We studied a test-retest reliability of TMS cortical maps corresponding to multiple hand muscles. We took into account both standard size parameters such as map`s areas as well as novel parameters such as intricate muscle-specific excitability profiles. The study included 18 young healthy right-handed male volunteers. We used MRI-navigated TMS to stimulate left motor cortex in two mapping sessions separated by 5-10 days. For the mapping we used a grid of 53-58 points each being stimulated in a pseudo-random order five times. Second day TMS session was an exact repetition of the first day session. An analysis was performed using custom-made software TMSmap (http://tmsmap.ru/). We used intra-class correlation coefficient (ICC) to assess reliability of map areas, volumes and the extent of the different muscles overlap. For the quantative comparison of the cortical excitability profiles of individual muscles we utilized earth mover's distance metrics (EMD). We found that RMT remained the same across two testing sessions in all but two subjects in whom it changed by one percent. ICC for the same muscle representation could be considered as good (0.73-0.85) for areas, moderate for the extent of the different muscles maps overlap (0.7) and poor (0.45-0.49) for volumes. An average shift for hotspots was ~10 mm and for centers of gravity it was ~3 mm. When assessing individual excitability profiles, we found significantly smaller normalized EMD (higher reproducibility) for the same muscle representations across days than for the different muscle representations across days (P<0,0001). The obtained results provide evidence that not only general excitability but also other specific features including standard characteristics (areas, volume) and even excitability profiles of the cortical muscle representation can be reliably traced with TMS motor mapping. This in turn indicates that the existence of the complex TMS cortical representations doesn’t simply indicate stochastic fluctuations in the corticospinal excitability during TMS mapping procedure but rather demonstrates a possibility to probe with TMS cortical organization reflecting intricate descending projections relating to specific muscles.

Language: English
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Keywords: Transcranial magnetic stimulationfunctional brain mappingStability
Publication based on the results of:
Active and Passive Decoding of the Neural Processes During Cognitive Perfoemance and Neuroeconomic Tasks Execution (2018)

In book

2018 Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience, 2018. Online
2018 Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience, 2018. Online
San Diego: Society for Neuroscience, 2018.
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