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May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
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Past tense in the brain’s time: neurophysiological evidence for dual-route processing of past-tense verbs

Neuroimage. 2013. Vol. 1. No. 71. P. 187–195.
Bakker I., MacGregor L. J., Pulvermuller F., Shtyrov Yury

A controversial issue in neuro- and psycholinguistics is whether regular past-tense forms of verbs are stored lexically or generated productively by the application of abstract combinatorial schemas, for example affixation rules. The success or failure of models in accounting for this particular issue can be used to draw more general conclusions about cognition and the degree to which abstract, symbolic representations and rules are psychologically and neurobiologically real. This debate can potentially be resolved using a neurophysiological paradigm, in which alternative predictions of the brain response patterns for lexical and syntactic processing are put to the test. We used magnetoencephalography (MEG) to record neural responses to spoken monomorphemic words ('hide'), pseudowords ('smide'), regular past-tense forms ('cried') and ungrammatical (overregularised) past-tense forms ('flied') in a passive listening oddball paradigm, in which lexically and syntactically modulated stimuli are known to elicit distinct patterns of the mismatch negativity (MMN) brain response. We observed an enhanced ('lexical') MMN to monomorphemic words relative to pseudowords, but a reversed ('syntactic') MMN to ungrammatically inflected past tenses relative to grammatical forms. This dissociation between responses to monomorphemic and bimorphemic stimuli indicates that regular past tenses are processed more similarly to syntactic sequences than to lexically stored monomorphemic words, suggesting that regular past tenses are generated productively by the application of a combinatorial scheme to their separately represented stems and affixes. We suggest discrete combinatorial neuronal assemblies, which bind classes of sequentially occurring lexical elements into morphologically complex units, as the neurobiological basis of regular past tense inflection.

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