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News
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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Neural dynamics of inflectional and derivational morphology processing in the human brain

Cortex. 2013. Vol. 49. No. 10. P. 2758–2771.
Leminen A., Leminen M., Kujala T., Shtyrov Y.

We investigated neural distinctions between inflectional and derivational morphology and their interaction with lexical frequency using the mismatch negativity (MMN), an established neurophysiological index of experience-dependent linguistic memory traces and automatic syntactic processing. We presented our electroencephalography (EEG) study participants with derived and inflected words of variable lexical frequencies against their monomorphemic base forms in a passive oddball paradigm, along with acoustically matched pseudowords. Sensor space and distributed source modelling results showed that at 100-150 msec after the suffix onset, derived words elicited larger responses than inflected words. Furthermore, real derived words showed advantage over pseudo-derivations and frequent derivations elicited larger activation than less frequent ones. This pattern of results is fully in line with previous research that explained lexical MMN enhancement by an activation of strongly connected word-specific long-term memory circuits, and thus suggests stronger lexicalisation for frequently used complex words. At the same time, a strikingly different pattern was found for inflectional forms: higher response amplitude for pseudo-inflections than for real inflected words, with no clear frequency effects. This is fully in line with previous MMN results on combinatorial processing of (morpho)syntactic stimuli: higher response to ungrammatical morpheme strings than grammatical ones, which does not depend on the string's surface frequency. This pattern suggests that, for inflectional forms, combinatorial processing route dominates over whole-form storage and access. In sum, our results suggest that derivations are more likely to form unitary representations than inflections which are likely to be processed combinatorially, and imply at least partially distinct brain mechanisms for the processing and representation of these two types of morphology. These dynamic mechanisms, underpinned by perisylvian networks, are activated rapidly, at 100-150 msec after the information arrives at the input, and in a largely automatic fashion, possibly providing neural basis for the first-pass morphological processing of spoken words.

Research target: Philology and Linguistics Psychology Earth Sciences Biology
Priority areas: humanitarian
Language: English
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Keywords: EEGmorphosyntax
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