Understanding the brain through the wrist: Predicting brain function from physical activity

Name of applicant

Christine Ahrends


Postdoctoral Fellow


University of Oxford


DKK 1,000,000



Type of grant

Visiting Fellowships at University of Oxford


Brain activity changes over time in specific temporal patterns, even during short periods of rest. These patterns are related to behaviour, cognition, and psychiatric disease. Physical activity affects the brain on several levels. In this project, I aim to use physical activity measurements to predict the patterns in which an individual's brain activity changes over time.


If this is possible, we could gain crucial insights into a person's brain function without expensive brain scans but using only fitness trackers. This may be useful, e.g., to detect early signs of psychiatric disease and to promote healthy brain function. Understanding how physical activity and sleep relate to brain function will also reveal more about how the brain is fundamentally organised.


The UK Biobank is a large database containing fMRI and wrist-worn activity sensor recordings from 50,000 individuals. Using this dataset, I will develop and apply a machine learning approach to learn how physical activity relates to brain activity. This model can then be used to predict brain activity patterns from wristband measurements of people whose brains have not been scanned.

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