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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
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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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Differential neural basis for different levels of metacognitive evaluations

P. 90–91.
Martín-Luengo B., Seungah L., Mikhailova L., Kapitsyn M., Myachykov A., Shtyrov Y.

Metacognitive monitoring is a powerful tool that supports our ongoing cognitive processes (Flavell, 1976). In applied settings, such as when we are trying to learn a new language, monitoring the learning progress may determine the difference between success and failure. One way to measure metacognitive monitoring in relation to learning new material is the so-called Judgments of Learning (JOLs). JOLs are estimations of future success in recalling recently learned information. Depending on the confidence that we have in remembering the new information later, we may decide to keep rehearsing it or just move on. Existing research shows that several variables can mislead our JOLs in relation to the subsequent recall accuracy; at the same time, other variables that influence the recall itself do not affect JOLs. Perceptual fluency, manipulated in different sensory modalities by e.g. font size or presentation volume, leads to differences in JOLs (e.g., higher JOLs for bigger font size), although recall accuracy remains the same regardless of the manipulation. On the other and, the animacy manipulation (e.g., dog vs. table) does not affect JOLs but animate words are remembered better.
Our main aim was to study JOL brain correlates for variables that differently affect JOLs and memory. Participants were presented with words in an easy- or difficult to-read font that referred to animate or inanimate objects while EEG was recorded. For each word, participants had to choose on a 0-100% scale the confidence they had in remembering it in near future. We found a higher P2 response for high- (70–100%) than to medium- JOLs (40–60%) ratings, which may reflect attentional recruitment resulting in modulation of perceptual processing. Furthermore, we found a  greater P600 response for medium- than high-JOLs, suggesting a deeper reanalysis of these type of “less confident” answers. When animacy and perceptual fluency are split between medium and high-JOLs, we found LPC (late positive component) only for animacy, being showing a higher amplitude for the high- than medium-JOLs.. This might indicate a higher involvement of memory processes during the processing of animacy-related information. Finally, when comparing difficult type font words rated with medium and high-JOLs, we obtained larger P3b for high-JOLs rated words, which may attributed to their deeper evaluation. This is the first evidence of differential brain signatures for JOLs depending on their ratings level and different experimental manipulations. Our results highlight the relevance
of metacognitive evaluations in the cognitive processing.

The work was supported by the Russian Science Foundation (project No. 19-18-00534).

Language: English
Full text
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Keywords: EEGmetacognitionEEGJOLsmetacognitionJOLs
Publication based on the results of:
Investigations of neuronal mechanisms of cognition and decision making: neuroimaging, computational models and non-invasive brain stimulation (2019)

In book

Proceedings of the 3rd International Conference Neurobiology of Speech and Language
Proceedings of the 3rd International Conference Neurobiology of Speech and Language
Scifiya-print, 2019.
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