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University of Surrey

Country: United Kingdom

University of Surrey

2 Projects, page 1 of 1
  • Funder: Carlsberg Foundation Project Code: CF23-1309

    Whereas ageing is often portrayed in a stereotypical and homogenizing way, this project studies how older influencers imagine and present ageing in their own words and images on their social media platforms. The aim is to reach a better understanding of contemporary ageing through interviews with older influencers, some of their followers and some of their influencer agencies.What? Why? How?

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  • Funder: Carlsberg Foundation Project Code: CF22-0132

    What? Conscious experiences normally result from the flow of external input into our sensory systems. However, our minds are also able to create percepts in the absence of any sensory stimulation: these internally generated percepts are referred to as mental images. This project aims to understand the links between the human capacity for mental imagery and brain structures in a massive 100,000 participant sample. Why? We use imagery in many activities in everyday life. For example, when we are going from one place to another, we can imagine our route. The experienced vividness of imagery varies greatly in the population, ranging from people incapable of producing imagery at all (1-3% of the population) to people producing such vivid imagery that it can be hard to distinguish from perception (around 5%). The project has the potential to provide important information about abnormalities associated with visual imagery and to reveal the brain basis of aphantasia (the inability to produce mental imagery). How? Although there have been previous investigations into the brain areas involved in mental imagery, these have lacked a sufficient sample size. This project aims to investigate the relationship between mental imagery, related cognitive functions, and neuroarchitectural properties using one of the largest datasets of magnetic resonance imaging (MRI) data ever collected, compromised of data from around 100.000 participants. The project takes advantage of recent advances in our understanding of the micro- and macrostructural aspects of brain anatomy, neuroimaging techniques, and machine learning data analytics.

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