Anja Leist receives the prestigious "ERC Starting Grant"
Published on Tuesday, 18 September 2018
Researcher Dr Anja Leist, from the University of Luxembourg, receives a Starting Grant from the European Research Council (ERC) to support her work on dementia and cognitive impairment in older ages. In total she will receive 1.5 million euros during five years to build a research team and lead her promising research project. Anja Leist’s research project CRISP – “Cognitive Aging: From Educational Opportunities to Individual Risk Profiles” – aims to provide comprehensive knowledge and techniques to identify risk factors and people at risk of dementia, in order for them to benefit as early as possible from behavioural interventions. Her project is strongly linked to computational sciences. Part 1: How inequalities determine cognitive ageingWe already know that childhood and young adulthood are immensely important for laying the foundations of cognitive functioning over a person’s life course. However, we need to know more about how our environment systematically shapes how much we realise our cognitive potential. This is the first mission of Anja Leist’s research team. “Innate abilities and parental background, but also external factors such as education, social environment, gender equality and professional development shape to what extent we can realise the potential of our brain,” explains Dr Anja Leist. “During our lifetime, these factors contribute to what we call building up cognitive reserve, meaning a kind of cognitive ‘fitness’ or the ability to improvise and find new ways to do the things we need to do. This cognitive reserve helps us in time to buffer or delay cognitive decline.” Part 2: New methods to capture the complexity of cognitive evolutionToday, there are behavioural interventions – designed to stimulate adequate behavior – available that can delay cognitive decline for people at risk. However, scientists and medical staff face a gap of knowledge how to identify people at risk with low-cost, non-invasive procedures. Thus, the second part of the research project aims to step up statistical models currently used in the social sciences with new machine learning techniques. What sounds like an improbable combination is in fact the key to capture the complexity of cognitive decline. “Cognitive evolution doesn’t change in a linear fashion, it varies in speed and power, in its consistency or recoils,” Anja Leist clarifies. “Considering the numerous influences of genetics, social and behavioral factors, traditional statistical methods hardly capture this complexity. “ At the same time, the new machine learning techniques cannot just be blindly adapted from big data applications, but need to be combined with sophisticated causality methods in order to shed light on the complexity of cognitive aging. With the new statistical models, health professionals can better predict the cognitive evolution of a person at risk. Persons at high risk of dementia can then be supported to make those changes in their lives that are necessary to remain stable or to significantly buffer a cognitive pathology. A lifetime of dedication
Photos: © Yaph |
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