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April 30, 2026
HSE Researchers Compile Scientific Database for Studying Childrens Eating Habits
The database created at HSE University can serve as a foundation for studying children’s eating habits. This is outlined in the study ‘The Influence of Age, Gender, and Social-Role Factors on Children’s Compliance with Age-Based Nutritional Norms: An Experimental Study Using the Dish-I-Wish Web Application.’ The work has been carried out as part of the HSE Basic Research Programme and was presented at the XXVI April International Academic Conference named after Evgeny Yasin.
April 30, 2026
New Foresight Centre Study Identifies the Most Destructive Global Trends for Humankind
A team of researchers from the HSE International Research and Educational Foresight Centre has examined how global trends affect the quality of human life—from life expectancy to professional fulfilment. The findings of the study titled ‘Human Capital Transformation under the Influence of Global Trends’ were published in Foresight.
April 28, 2026
Scientists Develop Algorithm for Accurate Financial Time Series Forecasting
Researchers at the HSE Faculty of Computer Science benchmarked more than 200,000 model configurations for predicting financial asset prices and realised volatility, showing that performance can be improved by filtering out noise at specific frequencies in advance. This technique increased accuracy in 65% of cases. The authors also developed their own algorithm, which achieves accuracy comparable to that of the best models while requiring less computational power. The study has been published in Applied Soft Computing.

 

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Changes in Functional Connectivity of Default Mode Network with Auditory and Right Frontoparietal Networks in Post-Stroke Aphasia.

Brain Connectivity. 2016. Vol. 6. No. 9. P. 714–723.
Balaev V., Petrushevsky A., Martynova O.

To evaluate the influence of poststroke aphasia on the functional association of widespread large-scale neuronal networks, we analyzed functional connectivity (FC) between resting-state brain networks (RSNs) in aphasic patients (N = 15) and in healthy volunteers (N = 17) of the same age using resting-state functional connectivity magnetic resonance imaging. As a result, six RSNs were isolated and cross-correlation matrices were computed for their time courses. Aphasic patients showed decreased correlations between posterior part of the default mode (pDMN) and both auditory (AUD) and right frontoparietal (RFP) networks. Additionally, we calculated regions of interest-based FC (ROI-FC), gray and white matter volumes in the ROIs overlapping with pDMN, AUD, and RFP. ROI-FC analysis showed decreased FC between the right pars triangularis and both right middle frontal and right superior frontal gyri. The decreased pDMN-RFP connectivity in patients is likely to reflect changes in FC of these nodes. The lesion in the regions overlapping with pDMN and AUD networks leads to the significantly decreased pDMN-AUD connectivity. Our results suggest that abnormal FC in stroke patients may reflect the impairment of activity not only in the regions directly affected by stroke lesion in the left hemisphere but also in the homotopic regions of the intact right hemisphere. The increase of gray and white matter volume in the right supramarginal gyrus, the functional hub of pDMN, AUD, and RFP networks, correlated with less speech impairment. This increase might reflect a right hemisphere neuroplasticity process to compensate the impaired function of the homotopic region of left frontoparietal network (LFP), pDMN, and AUD in the left hemisphere. The presented results contribute to the hypothesized compensative role of the transfer of attention and executive functions from the damaged areas in the left hemisphere to the right homotopic areas, accompanied by more preserved language skills at the chronic stroke stage.

Research target: Psychology
Priority areas: humanitarian
Language: English
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Keywords: languagefMRIstrokefunctional connectivityresting state networks aphasia
Publication based on the results of:
Активное и пассивное декодирование нейрональных процессов при выполнении когнитивных и нейроэкономических задач (2016)
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