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August 25, 2026
Scientists Develop Algorithm for More Reliable Processors in Data Centres
Researchers from HSE MIEM and Samara University have developed the LRF-3D algorithm to automatically bypass idle nodes in three-dimensional networks-on-chip. Thanks to its hierarchical architecture, the algorithm outperforms existing solutions in both speed and path accuracy, improving processor reliability for use in data centres, supercomputers, and AI computing. The source code and test results are publicly available.
August 24, 2026
Researchers Develop Method for Direct Generation of Regulatory DNA
Researchers at HSE University have developed a model for generating promoters and enhancers—DNA sequences that regulate gene activity. The model works directly with DNA nucleotides, without first transforming them into a continuous numerical representation. This solution could be useful for applications in synthetic biology and gene therapy. The study results were presented at the ICLR 2026 Workshop ‘Generative AI in Genomics (Gen^2): Barriers and Frontiers.’
August 21, 2026
Social Integration: At the Crossroads of Knowledge and Values
The International Laboratory for Social Integration Research (ILSIR) at HSE University studies the challenges faced by vulnerable groups and explores ways to help them participate fully in everyday life. To develop effective solutions, the laboratory’s researchers combine cutting-edge methods with practical fieldwork. In this interview with the HSE News Service, Laboratory Head Elena Iarskaia-Smirnova discusses the laboratory’s work.

 

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A comprehensive approach to studying motor planning and execution using 3D-printed objects and motion tracking technology

Frontiers in Human Neuroscience. 2025. Vol. 19. Article 1620526.
Alexander Vyazmin, Sangram Behera, Lan See G., Moiseeva V., Feurra M.

Background: Motor planning critically supports efficient hand grasping and object manipulation, involving the precise integration of sensory cues and anticipatory motor commands. Current methods often inadequately separate motor planning from movement execution, thus limiting our understanding of anticipatory motor control mechanisms.

Objective: This study aimed to establish and validate a structured methodological approach to investigate motor planning and execution during grasping tasks, using advanced motion tracking technology and standardized 3D-printed geometric objects.

Methods: Twenty-one participants performed a grasp-and-place task, requiring manipulation of abstract, non-semantic objects under varying rotation angles (0◦ , 90◦ , 180◦ , 270◦ ). High-resolution kinematic data were captured using an infrared motion tracking system (Smart-DX, BTS Bioengineering, Italy). Novel computational analyses segmented each trial into distinct phases: total movement, movement initiation, reaching, maximal grasp aperture, and object placement. Wrist path length and execution time of each phase were statistically analyzed to assess the influence of object rotation on motor planning and execution.

Results: Object rotation significantly impacted motor planning, as evidenced by prolonged initiation times and altered grasp-related temporal parameters. Specifically, movements involving rotation demonstrated increased movement initiation times, greater grasp apertures, extended placement durations, and longer wrist trajectories compared to non-rotated conditions. Interestingly, symmetrical rotations (180◦) facilitated faster and more efficient movements compared to asymmetrical rotations (90◦, 270◦).

Conclusion: Our validated methodological framework enables precise isolation and assessment of motor planning processes during grasping movements. This paradigm provides robust tools for fundamental motor control research and has potential clinical applications for evaluating motor planning deficits in patients with neurological impairments.

Research target: Psychology
Language: English
DOI
Text on another site
Keywords: нейрореабилитацияneurorehabilitationmotor planningмоторное планированиеmotion trackinggrasping kinematicsanticipatory controlmovement segmentation3D-printed objectsкинематика захватыванияпредварительный контрольсементация движениямоторное прослеживаниетрехмерные объекты
Publication based on the results of:
Multidisciplinary study of behavior and decision-making in health population and patients using behavioral, economic, neurocognitive, neuroeconomic, neurocomputational and neural network approaches (2025)
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