Neuroscientists Inflict 'Damage' on Computational Model of Human Brain
An international team of researchers, including neuroscientists at HSE University, has developed a computational model for simulating semantic dementia, a severe neurodegenerative condition that progressively deprives patients of their ability to comprehend the meaning of words. The neural network model represents processes occurring in the brain regions critical for language function. The results indicate that initially, the patient's brain forgets the meanings of object-related words, followed by action-related words. Additionally, the degradation of white matter tends to produce more severe language impairments than the decay of grey matter. The study findings have been published in Scientific Reports.
'Joint Background in Political Science and Anthropology Turned Out to Be Invaluably Useful in Studying the Region'
From April 26 to May 7, a team of professors and students from HSE University-St Petersburg conducted a field study in the Indian Himalayas. Below, Aleksei Sorbale, academic supervisor of the Bachelor's programme 'Political Science and World Politics', and Pavel Bazarov, a student of the Master's programme 'Global and Regional History', speak about their research and share their impressions of the expedition.
‘Compare Viewpoints, Listen to Others, and Try to Make Yourself Heard’
Prof. Olga Volosyuk, Head of the School of International Regional Studies, Faculty of World Economy and International Affairs, spoke to the HSE News Service about international relations, research, and conferences organised by the School.
Scientists Propose Star-Shaped Diffusion Model
Scientists at the AI Research Centre and the Faculty of Computer Science at HSE University, the Artificial Intelligence Research Institute (AIRI), and Sber AI have come up with novel architecture for diffusion neural networks, making it possible to configure eight distinct types of noise distribution. Instead of the classical Markov chain model with Gaussian distribution, the scientists propose a star-shaped model where the distribution type can be selected and preset. This can aid in solving problems across various geometric modalities. The results were presented at the NeurIPS 2023 conference.
HSE Scientists Leverage AI to Accelerate Advancement of 5G and 6G Wireless Communication Systems
The HSE Artificial Intelligence Centre has developed software for modelling radio channels in 5G and 6G wireless networks, based on ray tracing and machine learning techniques. Their software solutions enable modelling radio wave propagation between transmitters and receivers and can convert ray tracing data into a frame sequence format, configure and train neural networks based on this data, and subsequently save the trained models.
New Method Enables Dyslexia Detection within Minutes
HSE scientists have developed a novel method for detecting dyslexia in primary school students. It relies on a combination of machine learning algorithms, technology for recording eye movements during reading, and demographic data. The new method enables more accurate and faster detection of reading disorders, even at early stages, compared to traditional diagnostic assessments. The results have been published in PLOS ONE.
Mongolia's Forests Found to Be Poorly Adapted to Climate Change
Compared to meadows and steppes, the montane forest ecosystems in Northern Mongolia display less self-organisation, making them more susceptible to the impacts of climate change. This is the conclusion of a team of researchers led by Robert Sandlerskiy, Head of the International Laboratory of Landscape Ecology of the HSE Faculty of Geography and Geoinformation Technology. The results of the study have been published in a special issue of Entropy.
Russian Researchers Improve Neural Networks' Spatial Navigation Performance
Researchers at HSE University, MISiS National University of Science and Technology, and the Artificial Intelligence Research Institute (AIRI) have developed an enhanced approach to reinforcement learning for neural networks tasked with navigation in three-dimensional environments. By using the attention mechanism, they managed to improve the performance of a graph neural network by 15%. The study results have been published in IEEE Access.
Parietal Cortex Influences Risk-Taking Behaviour
Making decisions in situations involving risk and uncertainty is an inherent aspect of our daily lives. Should I obtain luggage insurance for my flight, cross the road when the light is red, or leave my current job for a new opportunity? Researchers at the HSE Institute for Cognitive Neuroscience conducted an experiment to clarify the role the parietal cortex plays in decision-making in the context of risk. They found that suppression of activity in the parietal cortex resulted in subjects being less inclined to take risks. A paper with the study findings has been published in Cerebral Cortex.
HSE ‘Mirror Laboratories’ Project Marks Five Years since Start
‘Mirror Laboratories’ is one of the flagship programmes of the HSE University aimed at developing domestic scientific partnerships. During the implementation of the project, 41 research projects were initiated in partnership with 30 regional universities and scientific organisations. A series of round tables timed to coincide with the fifth anniversary of the ‘Mirror Laboratories’ project, were held at the HSE University on April 24–25, 2024.
Deadline for applications to present academic reports - January 20, 2025