DataScience@BI seminar with Øystein Sørensen

Abstract:

Statistical modeling with messy data: What can we really figure out about human brain and cognition?

Does short sleep lead to poor brain health? Does higher education protect against age-related cognitive decline? Can we detect Alzheimer’s disease with neuroimaging long before symptoms appear? How does the development and decline in different brain regions map to changes in cognitive functioning across the lifespan? And if it wasn’t significant, can we prove the absence of an effect?

Having worked at the Department of Psychology, University of Oslo, over the last eight years, these are some examples of research question which have spurred interesting collaborations and occasionally led to new discoveries. Combining brain imaging with psychological measurement has been necessary in most of these projects, which means merging two domains with low signal-to-noise ratio to make it even lower. Hence, we have needed to gather data collected in labs all over the world to get sufficient statistical power, which again means that a lot of work has gone into harmonizing the data such that the variables mean more or less the same. The second step has been the iterative process of making a good enough statistical model; typically something multilevel and semiparametric.

In this talk I’ll describe the substantial research questions in some detail and describe how we went about answering them. I’ll reflect over the role of data science and the pragmatism you need to get anything done. In my experience, models almost invariably end up simpler than initially planned, mainly due to computational bottlenecks and lack of software. I’ll finally show some examples of how this last aspect can inspire new methodological developments.

Some key references are shown below:

Fjell, A. M., Rogeberg, O., Sørensen, Ø., Amlien, I. K., Bartrés-Faz, D., Brandmaier, A. M., Cattaneo, G., Düzel, S., Grydeland, H., Henson, R. N., Kühn, S., Lindenberger, U., Lyngstad, T. H., Mowinckel, A. M., Nyberg, L., Pascual-Leone, A., Solé-Padullés, C., Sneve, M. H., Solana, J., … Vidal-Piñeiro, D. (2025). Reevaluating the role of education on cognitive decline and brain aging in longitudinal cohorts across 33 Western countries. Nature Medicine, 1–10. https://doi.org/10.1038/s41591-025-03828-y

Fjell, A. M., Sørensen, Ø., Wang, Y., Amlien, I. K., Baaré, W. F. C., Bartrés-Faz, D., Bertram, L., Boraxbekk, C.-J., Brandmaier, A. M., Demuth, I., Drevon, C. A., Ebmeier, K. P., Ghisletta, P., Kievit, R., Kühn, S., Madsen, K. S., Mowinckel, A. M., Nyberg, L., Sexton, C. E., … Walhovd, K. B. (2023). No phenotypic or genotypic evidence for a link between sleep duration and brain atrophy. Nature Human Behaviour, 1–15. https://doi.org/10.1038/s41562-023-01707-5

Roe, J. M., Jagust, W. J., Landau, S. M., Harrison, T. M., Grydeland, H., Slivka, M., Alatorre-Warren, J.-L., Garrido, P. F., Sørensen, Ø., Grødem, E. O. S., Ward, T. J., Leonardsen, E. H., Murphy, A., Lee, J., Fladby, T., Bjørnerud, A., Walhovd, K. B., Fjell, A. M., Vidal-Piñeiro, D., & Wang, Y. (2026). Cortical thickness changes precede high levels of amyloid by at least 7 years. Nature Neuroscience, 1–12. https://doi.org/10.1038/s41593-026-02363-4

Vidal-Piñeiro, D., Sørensen, Ø., Strømstad, M., Amlien, I. K., Baaré, W., Bartrés-Faz, D., Brandmaier, A. M., Cattaneo, G., Düzel, S., Ghisletta, P., Henson, R. N., Kühn, S., Lindenberger, U., Mowinckel, A. M., Nyberg, L., Pascual-Leone, A., Roe, J. M., Solana-Sánchez, J., Solé-Padullés, C., … Fjell, A. M. (2025). Vulnerability to memory decline in aging revealed by a mega-analysis of structural brain change. Nature Communications, 16(1), 11488. https://doi.org/10.1038/s41467-025-66354-y

• Read about the speaker
• Expert fields: Statistics, psychology, physics

The DataScience@BI seminar is organised by the Department of Data Science and Analytics, BI Norwegian Business School.

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