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October 1, 2026
HSE Researchers Show How Congenital Motor Disorders Affect Brain Development
Researchers from HSE University’s Institute for Cognitive Neuroscience have synthesised the findings of their previous studies on brain development in children with obstetric brachial plexus palsy and arthrogryposis. Their analysis shows that impaired motor function in early childhood not only limits children’s motor experience but also affects memory, categorical thinking, and information processing. The study has been published in Frontiers in Psychology.
October 1, 2026
Window into the Body: Scientists Develop Neural Network to Detect Risk of 15 Diseases from Retinal Images
Russian universities, with the participation of HSE University, Sber, and Z-union, have developed a neural network that can simultaneously assess the risk of 15 types of pathology from retinal photographs, including not only eye diseases but also cardiovascular conditions. The AI system can help clinicians detect potentially concerning changes at an early stage, identify signs reflecting the condition of retinal blood vessels, and determine whether a patient may need further examination. The paper has been published in Frontiers in Medicine.
September 30, 2026
'We Did Not Limit the Time for Questions'
The International Laboratory for Supercomputer Atomistic Modelling and Multi-Scale Analysis at HSE University held a major conference on molecular dynamics. Participants had the opportunity to attend all the presentations, while speakers were given as much time as they needed to answer questions. The HSE News Service interviewed Grigory Smirnov, Head of the Laboratory, and Genri Norman, Chief Research Fellow, about the conference preparations and the discussions it generated.

 

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Classification Approach to Mapping Cultural Differences: An Illustration Using Survey Data from 60 Russian Regions

2025.
Nastina E., Sokolov B.
We argue that a classification-based approach to measuring cultural differences across countries or subnational regions is a promising complement, and sometimes an alternative, to the widely used dimensional method in cross-cultural research. The latter summarises cultural variation using continuous dimensions, for example, Hofstede’s famous individualism-collectivism dimension. However, this approach relies on strong parametric assumptions, which are often violated in aggregate cross-cultural samples – particularly when distributions of individual indicators are multimodal or asymmetric, dimensions are highly correlated, or outlying cultural units are present. Using survey data from 60 Russian regions (N = 18,768), we implement the classification approach through latent profile analysis (LPA) to group these regions into discrete types within a multidimensional cultural space. Comparison with conceptually similar dimensional indices shows that the classification-based measure often demonstrates stronger associations with objective geographical, historical, economic, and social characteristics of Russian regions. Furthermore, it reveals additional details when relationships between culture and its potential antecedents or effects are complex and non-linear. Our take-home message is that this approach is a powerful exploratory tool that can uncover patterns in cultural differences and their correlates that might be overlooked by the dimensional approach alone.
Research target: Social and Economic Geography (including Urban and Transportation Studies) Sociology (including Demography and Anthropology Psychology
Priority areas: sociology
Language: English
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Keywords: РоссияRussiaклассификацияregional cultureрегиональная культураclassificationlatent profile analysisанализ латентных профилейcultural dimensionsflexibility–monumentalismindividualism–collectivismизмерения культурыгибкость - монументализминдивидуализм - коллективизм
Publication based on the results of:
Comparative studies of culture and subjective well-being: differentiation and integration of societies in the context of global challenges (2025)
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