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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.
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Effortful verb retrieval from semantic memory drives beta suppression in mesial frontal regions involved in action initiation

Human Brain Mapping. 2019. Vol. 40. No. 12. P. 3669–3681.
Pavlova A., Butorina A. V., Nikolaeva A. Y., Prokofyev A. O., Ulanov M., Bondarev D. P., Stroganova T.

The contribution of the motor cortex to the semantic retrieval of verbs remains a subject of debate in neuroscience. Here, we examined whether additional engagement of the cortical motor system was required when access to verbs semantics was hindered during a verb generation task. We asked participants to produce verbs related to presented noun cues that were either strongly associated with a single verb to prompt fast and effortless verb retrieval, or were weakly associated with multiple verbs and more difficult to respond to. Using power suppression of magnetoencephalography beta oscillations (15–30 Hz) as an index of cortical activation, we performed a whole‐brain analysis in order to identify the cortical regions sensitive to the difficulty of verb semantic retrieval. Highly reliable suppression of beta oscillations occurred 250 ms after the noun cue presentation and was sustained until the onset of verbal response. This was localized to multiple cortical regions, mainly in the temporal and frontal lobes of the left hemisphere. Crucially, the only cortical regions where beta suppression was sensitive to the task difficulty, were the higher order motor areas on the medial and lateral surfaces of the frontal lobe. Stronger activation of the premotor cortex and supplementary motor area accompanied the effortful verb retrieval and preceded the preparation of verbal responses for more than 500 ms, thus, overlapping with the time window of verb retrieval from semantic memory. Our results suggest that reactivation of verb‐related motor plans in higher order motor circuitry promotes the semantic retrieval of target verbs.

Research target: Psychology Biology
Priority areas: humanitarian
Language: English
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Keywords: embodied cognitionbeta oscillationsmagnetoencephalography (MEG)verb generationmotor systemsupplementary motor area (SMA)
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