Cognitive health research group
Our aims include contribution to the development of novel and innovative methods for early detection, prevention, diagnostics, and treatment of neurological diseases associated with cognitive health issues. Another branch of our research is concerned with environmental and biological factors in gender development, and qualitative research into subjective experiences of adolescence gender dysphoria.
Currently, in www.AI-Mind.eu ( 14 million Euro action) and eBrains Health (12 million Euro action), two large scale EU prosjects (2021-2026), our focus is primarily centred on development of accessible and next generation AI-models inn identifying and estimating dementia risk in people with MCI. Also, the group focus on the development of fnovel unctional electrophysiological biomarkers of neurodegeneration by deep learning (DL) and classic machine learning (ML) artificial intelligence methods to identify crucial features of the normal and pathological aging and its changing brain's functional integrity. Furthermore, our group wishes to innovate different predictive algorithms for the prediction of dementia and other neurodevelopmental diseases.
We are an international group of researchers coming from a variety of diverse educational backgrounds, including medicine, psychology, artificial intelligence, mathematics, physics, robotics, and biological science. Our multidisciplinary approach to the brain-behaviour relation unravelling efforts allows us to conduct research across various systems and cognitive levels; from molecules to cells to cognitive systems to behaviours.
Our broad research method portfolio includes Electrophysiological (EEG) source reconstruction and network modelling; event-related potential (ERP) techniques; positron emission tomography (PET) and radiochemistry; neuropsychological assessment; mathematical algorithm development. Additionally, we includes prediction of health economic models when it comes to introducing DL artificial intelligence based tools in supportive medical decision-making.