HSE Scientists Develop Application for Diagnosing Aphasia
Specialists at the HSE Centre for Language and Brain have developed an application for diagnosing language disorders (aphasia), which can result from head injuries, strokes, or other neurological conditions. AutoRAT is the first standardised digital tool in Russia for assessing the presence and severity of language disorders. The application is available on RuStore and can be used on mobile and tablet devices running the Android operating system.
Approximately 450,000 stroke cases are reported annually in Russia, with about one-third of patients developing aphasia. Aphasia is an acquired language disorder. A person with aphasia may struggle to understand others, speak, read, or write. Aphasia can result from brain damage caused by stroke, head injury, or tumour removal. Physicians diagnose aphasia based on clinical symptoms and neuropsychological assessment data. Timely diagnosis of aphasia is crucial, as working with a speech therapist and neuropsychologist can significantly accelerate language recovery and improve quality of life.
Researchers at the HSE Centre for Language and Brain have developed a standardised digital tool called AutoRAT (from the Russian Aphasia Test), enabling the detection of aphasia and the assessment of its severity. When creating materials for the application, the developers considered not only the linguistic characteristics of the words, sentences, and texts included in the stimulus set but also psycholinguistic factors. These factors included, for example, the age at which the words were learned, their frequency of use, how easily a person can visualise an object associated with the word, and the complexity of images related to specific stimuli. The AutoRAT application allows diagnostics to be completed in just 60 minutes, providing accurate data for the development of a rehabilitation programme.
The battery of language tests includes 13 different tasks that assess the preservation of all key linguistic levels: phonological, lexico-semantic, syntactic, and discourse. These tasks help identify deficits in comprehension, production, and repetition of speech, provide information about the overall severity of language disorders, and allow comparison of results with age-based norms.
Language comprehension tasks, such as distinguishing sounds and understanding words, sentences, and texts, are automatically processed within the app. To obtain results for tasks involving speech production and repetition—such as naming objects and actions, constructing sentences and stories from drawings, and repeating words and sentences—a detailed manual evaluation system was developed for the user. This allows for the identification of all aspects of language disorders in each participant.
Individual participant profiles are saved in the application for further analysis of the results. AutoRAT enables tracking of the dynamics of language recovery, allowing for the assessment of treatment effectiveness, which is crucial for future prognosis and selecting an appropriate rehabilitation programme. All results are available for download in table format, making them convenient for research purposes.
AutoRAT will be a valuable tool for speech therapists, neuropsychologists, researchers, and clinical specialists. Additionally, it will be useful for healthcare institutions, students, and teachers in medical and linguistic fields, developers of rehabilitation programmes, and research centres focused on cognitive and linguistic processes.
'We aimed to create a tool that would not only help specialists diagnose aphasia but also provide a comprehensive picture of language disorders. AutoRAT is a step toward more precise and personalised patient rehabilitation. This tool combines a strong theoretical linguistic foundation with practical advancements in the field of speech therapy. Our tool enables a detailed description of the core language deficit, making the diagnosis of aphasia even more accurate,' comments Olga Buivolova, one of the project participants and Research Fellow at the HSE Centre for Language and Brain. 'It sets new standards by integrating advanced scientific approaches with practical effectiveness. AutoRAT transforms the aphasia assessment process, making it more convenient, accurate, and highly efficient.'
See also:
HSE University Develops Tool for Assessing Text Complexity in Low-Resource Languages
Researchers at the HSE Centre for Language and Brain have developed a tool for assessing text complexity in low-resource languages. The first version supports several of Russia’s minority languages, including Adyghe, Bashkir, Buryat, Tatar, Ossetian, and Udmurt. This is the first tool of its kind designed specifically for these languages, taking into account their unique morphological and lexical features.
HSE Scientists Uncover How Authoritativeness Shapes Trust
Researchers at the HSE Institute for Cognitive Neuroscience have studied how the brain responds to audio deepfakes—realistic fake speech recordings created using AI. The study shows that people tend to trust the current opinion of an authoritative speaker even when new statements contradict the speaker’s previous position. This effect also occurs when the statement conflicts with the listener’s internal attitudes. The research has been published in the journal NeuroImage.
Language Mapping in the Operating Room: HSE Neurolinguists Assist Surgeons in Complex Brain Surgery
Researchers from the HSE Center for Language and Brain took part in brain surgery on a patient who had been seriously wounded in the SMO. A shell fragment approximately five centimetres long entered through the eye socket, penetrated the cranial cavity, and became lodged in the brain, piercing the temporal lobe responsible for language. Surgeons at the Burdenko Main Military Clinical Hospital removed the foreign object while the patient remained conscious. During the operation, neurolinguists conducted language tests to ensure that language function was preserved.
AI Overestimates How Smart People Are, According to HSE Economists
Scientists at HSE University have found that current AI models, including ChatGPT and Claude, tend to overestimate the rationality of their human opponents—whether first-year undergraduate students or experienced scientists—in strategic thinking games, such as the Keynesian beauty contest. While these models attempt to predict human behaviour, they often end up playing 'too smart' and losing because they assume a higher level of logic in people than is actually present. The study has been published in the Journal of Economic Behavior & Organization.
Scientists Discover One of the Longest-Lasting Cases of COVID-19
An international team, including researchers from HSE University, examined an unusual SARS-CoV-2 sample obtained from an HIV-positive patient. Genetic analysis revealed multiple mutations and showed that the virus had been evolving inside the patient’s body for two years. This finding supports the theory that the virus can persist in individuals for years, gradually accumulate mutations, and eventually spill back into the population. The study's findings have been published in Frontiers in Cellular and Infection Microbiology.
HSE Scientists Use MEG for Precise Language Mapping in the Brain
Scientists at the HSE Centre for Language and Brain have demonstrated a more accurate way to identify the boundaries of language regions in the brain. They used magnetoencephalography (MEG) together with a sentence-completion task, which activates language areas and reveals their functioning in real time. This approach can help clinicians plan surgeries more effectively and improve diagnostic accuracy in cases where fMRI is not the optimal method. The study has been published in the European Journal of Neuroscience.
For the First Time, Linguists Describe the History of Russian Sign Language Interpreter Training
A team of researchers from Russia and the United Kingdom has, for the first time, provided a detailed account of the emergence and evolution of the Russian Sign Language (RSL) interpreter training system. This large-scale study spans from the 19th century to the present day, revealing both the achievements and challenges faced by the professional community. Results have been published in The Routledge Handbook of Sign Language Translation and Interpreting.
HSE Scientists Develop DeepGQ: AI-based 'Google Maps' for G-Quadruplexes
Researchers at the HSE AI Research Centre have developed an AI model that opens up new possibilities for the diagnosis and treatment of serious diseases, including brain cancer and neurodegenerative disorders. Using artificial intelligence, the team studied G-quadruplexes—structures that play a crucial role in cellular function and in the development of organs and tissues. The findings have been published in Scientific Reports.
New Catalyst Maintains Effectiveness for 12 Hours
An international team including researchers from HSE MIEM has developed a catalyst that enables fast and low-cost hydrogen production from water. To achieve this, the scientists synthesised nanoparticles of a complex oxide containing six metals and anchored them onto various substrates. The catalyst supported on reduced graphene layers proved to be nearly three times more efficient than the same oxide without a substrate. This development could significantly reduce the cost of hydrogen production and accelerate the transition to green energy. The study has been published in ACS Applied Energy Materials. The work was carried out under a grant from the Russian Science Foundation.
HSE Researchers Offer Guidance to Prevent Undergraduate Burnout
Researchers at the HSE Institute of Education have identified how much time students should ideally devote to their studies, extracurricular activities, and personal life to maintain strong academic performance without compromising their mental health. An analysis of responses from 2,753 students, combined with their actual academic results, revealed several risk factors—such as excessive homework—as well as positive factors, including sufficient sleep, regular exercise, and moderate participation in projects. Based on these findings, the researchers developed practical recommendations for both students and universities. The paper has been published in the European Journal of Education.