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September 25, 2026
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Research conducted by economists at HSE University has revealed a significant correlation between the regular use of GenAI in the workplace and higher pay among Russian employees. The study found that individuals who frequently use GenAI in their professional activities earn notably more than those who reject these new tools or resort to them occasionally. The salary premium for highly qualified specialists reaches 41.8%. The article was published in the Voprosy Ekonomiki journal.
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A researcher at HSE University analysed data on 1,539 doctoral students from 161 Russian universities to identify which features of a thesis topic are associated with academic success and engagement. The most important factor was found to be personal interest in the research topic, which was associated with almost all key aspects of doctoral programme experience—from engaging with the academic supervisor to research activity and confidence about successfully defending the thesis. The findings have been published in Higher Education.

 

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Identifying the Speech Production Stages in Early and Late Adulthood by Using Electroencephalography

Frontiers in Human Neuroscience. 2019. Vol. 13. P. 1–21.
den Hollander J., Jonkers R., Mariën P., Bastiaanse R.

Structural changes in the brain take place throughout one’s life. Changes related to cognitive decline may delay the stages of the speech production process in the aging brain. For example, semantic memory decline and poor inhibition may delay the retrieval of a concept from the mental lexicon. Electroencephalography (EEG) is a valuable method for identifying the timing of speech production stages. So far, studies using EEG mainly focused on a particular speech production stage in a particular group of subjects. Differences between subject groups and between methodologies have complicated identifying time windows of the speech production stages. For the current study, the speech production stages lemma retrieval, lexeme retrieval, phonological encoding, and phonetic encoding were tracked using a 64-channel EEG in 20 younger adults and 20 older adults. Picture-naming tasks were used to identify lemma retrieval, using semantic interference through previously named pictures from the same semantic category, and lexeme retrieval, using words with varying age of acquisition. Non-word reading was used to target phonological encoding (using non-words with a variable number of phonemes) and phonetic encoding (using non-words that differed in spoken syllable frequency). Stimulus-locked and response-locked cluster-based permutation analyses were used to identify the timing of these stages in the full time course of speech production from stimulus presentation until 100 ms before response onset in both subject groups. It was found that the timing of each speech production stage could be identified. Even though older adults showed longer response times for every task, only the timing of the lexeme retrieval stage was later for the older adults compared to the younger adults, while no such delay was found for the timing of the other stages. The results of a second cluster-based permutation analysis indicated that clusters that were observed in the timing of the stages for one group were absent in the other subject group, which was mainly the case in stimulus-locked time windows. A z-score mapping analysis was used to compare the scalp distributions related to the stages between the older and younger adults. No differences between both groups were observed with respect to scalp distributions, suggesting that the same groups of neurons are involved in the four stages, regardless of the adults’ age, even though the timing of the individual stages is different in both groups.

Research target: Philology and Linguistics
Priority areas: humanitarian
Language: English
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Keywords: артикуляцияЭЭГword retrievalстарениеelectroencephalographyspeech productionagingarticulation
Publication based on the results of:
Язык и мозг: предотвращение, диагностика и коррекция речевых расстройств (2020)
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