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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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Cognitive Trajectories and Dementia Risk: A Comparison of Two Cognitive Reserve Measures

Frontiers in Aging Neuroscience. 2021. Vol. 13. Article 737736.
Gallo F., Kalpouzos G., Laukka E. J., Wang R., Qiu C., Bäckman L., Marseglia A., Fratiglioni L., Dekhtyar S.

Background and Objectives:  Cognitive reserve (CR) is meant to account for the mismatch between brain damage and cognitive decline or dementia. Generally, CR has been operationalized using proxy variables indicating exposure to enriching activities ( activity-based  CR). An alternative approach defines CR as residual variance in cognition, not explained by the brain status ( residual-based  CR). The aim of this study is to compare  activity-based  and  residual-based  CR measures in their association with cognitive trajectories and dementia. Furthermore, we seek to examine if the two measures modify the impact of brain integrity on cognitive trajectories and if they predict dementia incidence independent of brain status.

Methods: We used data on 430 older adults aged 60+ from the Swedish National Study on Aging and Care in Kungsholmen, followed for 12 years. Residual-based reserve was computed from a regression predicting episodic memory with a brain-integrity index incorporating six structural neuroimaging markers (white-matter hyperintensities volume, whole-brain gray matter volume, hippocampal volume, lateral ventricular volume, lacunes, and perivascular spaces), age, and sex. Activity-based reserve incorporated education, work complexity, social network, and leisure activities. Cognition was assessed with a composite of perceptual speed, semantic memory, letter-, and category fluency. Dementia was clinically diagnosed in accordance with DSM-IV criteria. Linear mixed models were used for cognitive change analyses. Interactions tested if reserve measures modified the association between brain-integrity and cognitive change. Cox proportional hazard models, adjusted for brain-integrity index, assessed dementia risk.

Results: Both reserve measures were associated with cognitive trajectories [β × time (top tertile, ref.: bottom tertile) = 0.013; 95% CI: –0.126, –0.004 (residual-based) and 0.011; 95% CI: –0.001, 0.024, (activity-based)]. Residual-based, but not activity-based reserve mitigated the impact of brain integrity on cognitive decline [β (top tertile × time × brain integrity) = –0.021; 95% CI: –0.043, 0.001] and predicted 12-year dementia incidence, after accounting for the brain-integrity status [HR (top tertile) = 0.23; 95% CI: 0.09, 0.58].

Interpretation: The operationalization of reserve based on residual cognitive performance may represent a more direct measure of CR than an activity-based approach. Ultimately, the two models of CR serve largely different aims. Accounting for brain integrity is essential in any model of reserve.

Research target: Psychology
Language: English
DOI
Keywords: structural equation modeling (SEM)agingstructural MRIcognitive reserve
Publication based on the results of:
Fundamental study of the mechanisms of brain activity in the performance of cognitive and neuroeconomic tasks in health and disease using psychophysiological, neuroanatomical, neurocomputational and behavioral approaches (2021)
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