Øystein Sørensen

• Hesselberg, Jan Ole; Ulleberg, Pål; Sørensen, Øystein; Fostervold, Knut Inge; Ingvaldsen, Sigrid Hegna & Svege, Ida (2026). Why do reviewers disagree? Evidence from four funders and 134,000 reviews. PLOS ONE. 21(9), p. 1–21. doi: 10.1371/journal.pone.0356108. Full text in Research Archive
• Walhovd, Kristine B; Bråthen, Anne Cecilie Sjøli; Øverbye, Knut Eiliv Ødegård; Kransberg, Jonas Moe; Sørensen, Øystein & Garrido, Pablo F. [Show all 19 contributors for this article] (2026). Feature-specific environmental contributions to human cortical architecture revealed by twin brainprints. Communications Biology. doi: 10.1038/s42003-026-10707-w. Full text in Research Archive Show summary

  Abstract How environmental variation shapes the human cerebral cortex remains incompletely understood. Here we compare cortical brainprints – individual profiles of regional cortical morphology – in 210 twins (age 16-78 years) to distinguish prenatal, adult naturalistic and experimentally induced environmental variation from genetic contributions. Monozygotic twins showed higher brainprint similarity than dizygotic twins, consistent with genetic effects. Lasting influences of early environment were evident in lower brainprint similarity in monozygotic twin-pairs with greater birthweight discordances, driven by surface area across the cortical ribbon. In contrast, within-pair differences in adult weight and lifestyle had minimal influence. Still, a 10-week virtual-reality navigation intervention revealed training-induced changes in the gray-white interface, with curvature and area changes supported by microstructural reconfigurations. Relative brainprint similarity increased in monozygotic but diverged in dizygotic pairs following training. These findings show that distinct environmental influences acting at prenatal and adult stages are reflected in different features of the human cerebral cortex.

• Grødem, Edvard Olaf Sætersdal; Pineiro, Didac Vidal; Sørensen, Øystein; Bartrés-Faz, David; Brandmaier, Andreas M. & Cattaneo, Gabriele [Show all 20 contributors for this article] (2026). Stable individual differences dominate adult brain volume variation until later life. Imaging Neuroscience. 4. doi: 10.1162/IMAG.a.1242. Full text in Research Archive
• Garrido, Pablo Fernandez; Bråthen, Anne Cecilie Sjøli; Falch, Emilie Sogn; Kransberg, Jonas Moe; Fjell, Anders Martin & Sørensen, Øystein [Show all 7 contributors for this article] (2026). Unwrapping the mirror tracing task. Behavior Research Methods. ISSN 1554-351X. 58. doi: 10.3758/s13428-025-02845-6. Full text in Research Archive Show summary

  The Mirror Tracing Task (MTT) is a method used to study visuomotor skills learning. It is traditionally evaluated by counting the number of times a person draws outside of the borders of a figure, typically a star, while looking at its mirror reflection. While insightful for overall performance, this metric lacks a precise analysis of the tracing, such as details on errors in specific regions. We propose a new MTT analysis method that studies the drawing as a function of the angle around the figure’s center. Two new variables are introduced: residuals, which measure deviation from the ideal drawing, and density, which measures how often a specific path is retraced. These variables are defined per angle or region, allowing a more detailed analysis, highlighting the most challenging parts of the drawing for each person, and enabling comparison across trials or finding common patterns between individuals. We applied this approach to the first MTT trial of 210 participants using age as a variable of interest. Residuals and density were summarized as a single value and compared with the traditional approach, providing similar results. When analyzed as a function of the angle, these variables enabled the identification of specific regions of the star where the errors are age-sensitive. Additionally, a time series-like approach enabled us to cluster drawings and quantify their similarity. The code used for this new method has been made openly accessible to make it easier for its applications in new research or the reanalysis of previous projects.

• Kropiunig, Julia & Sørensen, Øystein (2025). Gaining Brain Insights by Tapping into the Black Box: Linking Structural MRI Features to Age and Cognition using Shapley-Based Interpretation Methods. Neuroinformatics. ISSN 1539-2791. 23(4). doi: 10.1007/s12021-025-09737-2. Full text in Research Archive Show summary

  Global interpretability in machine learning holds great potential for extracting meaningful insights from neuroimaging data to improve our understanding of brain function. Although various approaches exist to identify key contributing features at both local and global levels, the high dimensionality and correlations in neuroimaging data require careful selection of interpretability methods to achieve reliable global insights into brain function using machine learning. In this study, we evaluate multiple interpretability techniques such as SHAP, which relies on feature independence, as well as recent advances that account for feature dependence in the context of global interpretability, and inherently global methods such as SAGE. To demonstrate the practical application, we trained XGBoost models to predict age and fluid intelligence using neuroimaging measures from the UK Biobank dataset. By applying these interpretability methods, we found that mean intensities in subcortical regions are consistently and significantly associated with brain aging, while the prediction of fluid intelligence is driven by contributions of the hippocampus and the cerebellum, alongside established regions such as the frontal and temporal lobes. These results underscore the value of interpretable machine learning methods in understanding brain function through a data-driven approach.

• Demnitz, Naiara; Baare, William F.C.; Binnewies, Julia; Brandmaier, Andreas; Fjell, Anders Martin & Gates, Anne T. [Show all 17 contributors for this article] (2025). Public Health. Alzheimer's & Dementia. ISSN 1552-5260. 21, p. e097396–e097396. doi: 10.1002/alz70860_097396. Full text in Research Archive
• Pineiro, Didac Vidal; Sørensen, Øystein; Strømstad, Marie Lorentsen; Amlien, Inge; Baaré, William & Bartrés-Faz, David [Show all 74 contributors for this article] (2025). Vulnerability to memory decline in aging revealed by a mega-analysis of structural brain change. Nature Communications. 16(1). doi: 10.1038/s41467-025-66354-y. Full text in Research Archive Show summary

  Brain atrophy is a key factor behind episodic memory loss in aging, but the nature and ubiquity of this relationship remains poorly understood. This study leverages 13 longitudinal datasets, including 3737 cognitively healthy adults (10,343 MRI scans; 13,460 memory assessments), to determine whether brain change-memory change associations are more pronounced with age and genetic risk for Alzheimer’s Disease. Both factors are associated with accelerated brain decline, yet it remains unclear whethermemory loss is exacerbated beyond what atrophy alone would predict. Additionally, we assess whether memory decline aligns with a global pattern of atrophy or stems from distinct regional contributions. Our mega-analysis reveals a nonlinear relationship between memory decline and brain atrophy, primarily affecting individuals with above-average brain structural decline. The associations are stronger in the hippocampus but also spread across diverse cortical and subcortical regions. The associations strengthen with age, reachingmoderate associations in participants in their eighties. While APOE ε4 carriers exhibit steeper brain and memory loss, genetic risk has no effect on the change-change associations. These findings support the presence of common biological macrostructural substrates underlying memory function in older age which are vulnerable to multiple age-related factors, even in the absence of overt pathological changes.

• Demnitz, Naiara; Baaré, William F.C.; Binnewies, Julia; Brandmaier, Andreas M.; Fjell, Anders Martin & Gates, Anne T. [Show all 17 contributors for this article] (2025). No significant association between self-reported physical activity and brain volumes in women and men from five European cohorts. Scientific Reports. 15(1). doi: 10.1038/s41598-025-98601-z. Full text in Research Archive Show summary

  Various studies have reported an association between physical activity and grey matter volumes. Some studies have suggested that this relationship may be moderated by sex, yet the direction is still under debate. Focusing on hippocampus and dorsolateral prefrontal cortex (dlPFC), we tested whether the association between regional grey matter volumes and self-reported physical activity differs between women and men. We examined this interaction in five European cohorts from the Lifebrain consortium (n = 1809; age range: 18–88 years). Effect sizes were first determined by linear models run separately for each cohort, then pooled across datasets in a random-effects meta-analysis. Contrary to our hypotheses, there was no evidence of a relationship between physical activity and hippocampal or dlPFC volumes, nor was there a moderation by sex. Our null findings raise the question of whether self-report questionnaires of physical activity, which commonly feature in big datasets, are sufficiently sensitive to capture a—presumably modest—association between physical activity levels and grey matter outcomes. We conclude that the reliance on self-report questionnaires of physical activity is sub-optimal for brain-behaviour analyses.

• Fjell, Anders Martin; Røgeberg, Ole Jørgen; Sørensen, Øystein; Amlien, Inge; Bartrés-Faz, David & Brandmaier, Andreas M. [Show all 23 contributors for this article] (2025). Reevaluating the role of education on cognitive decline and brain aging in longitudinal cohorts across 33 Western countries. Nature Medicine. ISSN 1078-8956. 31, p. 2967–2976. doi: 10.1038/s41591-025-03828-y. Full text in Research Archive Show summary

  Why education is linked to higher cognitive function in aging is fiercely debated. Leading theories propose that education reduces brain decline in aging and enhances tolerance to brain pathology or that it does not affect cognitive decline but, rather, reflects higher early-life cognitive function. To test these theories, we analyzed 407,356 episodic memory scores from 170,795 participants older than 50 years, alongside 15,157 brain magnetic resonance imaging scans from 6,472 participants across 33 Western countries. More education was associated with better memory, larger intracranial volume and slightly larger volume of memory-sensitive brain regions. However, education did not protect against age-related decline or weakened effects of brain decline on cognition. The most parsimonious explanation for the results is that the associations reflect factors present early in life, including propensity of individuals with certain traits to pursue more education. Although education has numerous benefits, the notion that it provides protection against cognitive or brain decline is not supported. In a large cross-national study, education was linked to better memory and larger brain volumes but not to slower cognitive or brain decline with age, suggesting that the association reflects early-life factors rather than neuroprotective effects in aging.

• Ravndal, Anne; Fjell, Anders Martin; Vidal-Piñeiro, Didac; Sørensen, Øystein; Falch, Emilie Sogn & Kropiunig, Julia [Show all 21 contributors for this article] (2025). Sex differences in healthy brain aging are unlikely to explain higher Alzheimer’s disease prevalence in women. Proceedings of the National Academy of Sciences of the United States of America (PNAS). ISSN 0027-8424. 122(42). doi: 10.1073/pnas.2510486122. Full text in Research Archive Show summary

  As Alzheimer’s disease (AD) is diagnosed more frequently in women, understanding the role of sex has become a key priority in AD research. However, despite aging being the primary risk factor for AD, it remains unclear whether men and women differ in the extent of brain decline with age. Using 12,638 longitudinal brain MRIs from 4,726 participants aged 17 to 95 y across 14 cohorts, we examined sex differences in structural brain changes over time, controlling for differences in head size. Men showed greater cortical thickness (CT) decline in the cuneus, lingual, parahippocampal, and pericalcarine regions; surface area decline in the fusiform and postcentral regions; and in older adults, greater subcortical decline in the caudate, nucleus accumbens, putamen, and pallidum. In contrast, women only showed greater surface area decline in the banks of the superior temporal sulcus and greater ventricular expansion in older adults. These results suggest that sex differences in age-related brain decline are unlikely to contribute to the higher AD diagnosis prevalence in women, necessitating research into alternative explanations.

• Vidal-Piñeiro, Didac; Sørensen, Øystein; Strømstad, Marie Lorentsen; Amlien, Inge; Anderson, Micael & Baaré, William F.C. [Show all 25 contributors for this article] (2025). Reliability of structural brain change in cognitively healthy adult samples. Imaging Neuroscience. 3, p. 1–25. doi: 10.1162/imag_a_00547. Full text in Research Archive Show summary

  In neuroimaging research, tracking individuals over time is key to understanding the interplay between brain changes and genetic, environmental, or cognitive factors across the lifespan. Yet, the extent to which we can estimate the individual trajectories of brain change over time with precision remains uncertain. In this study, we estimated the reliability of structural brain change in cognitively healthy adults from multiple samples and assessed the influence of follow-up time and number of observations. Estimates of cross-sectional measurement error and brain change variance were obtained using the longitudinal FreeSurfer processing stream. Our findings showed, on average, modest longitudinal reliability with 2 years of follow-up. Increasing the follow-up time was associated with a substantial increase in longitudinal reliability, while the impact of increasing the number of observations was comparatively minor. On average, 2-year follow-up studies require ≈2.7 and ≈4.0 times more individuals than designs with follow-ups of 4 and 6 years to achieve comparable statistical power. Subcortical volume exhibited higher longitudinal reliability than cortical area, thickness, and volume. The reliability estimates were comparable with those estimated from empirical data. The reliability estimates were affected by both the cohort’s age where younger adults had lower reliability of change and the preprocessing pipeline where the FreeSurfer’s longitudinal stream was notably superior than the cross-sectional stream. Suboptimal reliability inflated sample size requirements and compromised the ability to distinguish individual trajectories of brain aging. This study underscores the importance of long-term follow-ups and the need to consider reliability in longitudinal neuroimaging research.

• Grydeland, Håkon; Sneve, Markus Handal; Roe, James Michael; Raud, Liisa; Ness, Hedda Tvedten & Folvik, Line [Show all 12 contributors for this article] (2025). Network segregation during episodic memory shows age-invariant relations with memory performance from 7 to 82 years. Neurobiology of Aging. ISSN 0197-4580. 148, p. 1–15. doi: 10.1016/j.neurobiolaging.2025.01.004. Full text in Research Archive Show summary

  Lower episodic memory capability, as seen in development and aging compared with younger adulthood, may partly depend on lower brain network segregation. Here, our objective was twofold: (1) test this hypothesis using within- and between-network functional connectivity (FC) during episodic memory encoding and retrieval, in two independent samples (n = 734, age 7–82 years). (2) Assess associations with age and the ability to predict memory comparing task-general FC and memory-modulated FC. In a multiverse-inspired approach, we performed tests across multiple analytic choices. Results showed that relationships differed based on these analytic choices and were mainly present in the largest dataset,. Significant relationships indicated that (i) memory-modulated FC predicted memory performance and associated with memory in an age-invariant manner. (ii) In line with the so-called neural dedifferentiation view, task-general FC showed lower segregation with higher age in adults which was associated with worse memory performance. In development, although there were only weak signs of a neural differentiation, that is, gradually higher segregation with higher age, we observed similar lower segregation-worse memory relationships. This age-invariant relationships between FC and episodic memory suggest that network segregation is pivotal for memory across the healthy lifespan.

• Hesselberg, Jan Ole; Ulleberg, Pål; Sørensen, Øystein; Fostervold, Knut Inge; Ingvaldsen, Sigrid Hegna & Svege, Ida (2025). Registered report protocol: Factors associated with inter-rater agreement in grant peer review. PLOS ONE. 20(5). doi: 10.1371/journal.pone.0322696. Full text in Research Archive
• Iakunchykova, Olena; Schirmer, Henrik; Roe, James Michael; Sørensen, Øystein; Wilsgaard, Tom & Hopstock, Laila Arnesdatter [Show all 10 contributors for this article] (2025). Longitudinal and concurrent C-reactive protein and diet associations with cognitive function in the population-based Tromsø study. Journal of Alzheimer's Disease. ISSN 1387-2877. 104(2), p. 403–413. doi: 10.1177/13872877251317624. Full text in Research Archive
• Sadeghi, Neda; Velpen, Isabelle F. van der; Baker, Bradley T.; Batta, Ishaan; Cahill, Kyle J. & Genon, Sarah [Show all 23 contributors for this article] (2025). The interplay between brain and behavior during development: A multisite effort to generate and share simulated datasets. Scientific Data. 12(1). doi: 10.1038/s41597-025-04740-3. Full text in Research Archive
• Fjell, Anders Martin; Sneve, Markus Handal; Amlien, Inge; Grydeland, Håkon; Mowinckel, Athanasia Monika & Vidal-Piñeiro, Didac [Show all 8 contributors for this article] (2025). Stable hippocampal correlates of high episodic memory function across adulthood. Scientific Reports. 15(1). doi: 10.1038/s41598-025-92278-0. Full text in Research Archive
• Capogna, Elettra; Sørensen, Øystein; Watne, Leiv; Roe, James Michael; Strømstad, Marie Lorentsen & Idland, Ane-Victoria [Show all 12 contributors for this article] (2025). Subtypes of brain change in aging and their associations with cognition and Alzheimer’s disease biomarkers. Neurobiology of Aging. ISSN 0197-4580. 147, p. 124–140. doi: 10.1016/j.neurobiolaging.2024.12.009. Full text in Research Archive Show summary

  Structural brain changes underlie cognitive changes and interindividual variability in cognition in older age. By using structural MRI data-driven clustering, we aimed to identify subgroups of cognitively unimpaired older adults based on brain change patterns and assess how changes in cortical thickness, surface area, and subcortical volume relate to cognitive change. We tested (1) which brain structural changes predict cognitive change (2) whether these are associated with core cerebrospinal fluid (CSF) Alzheimer’s disease biomarkers, and (3) the degree of overlap between clusters derived from different structural modalities in 1899 cognitively healthy older adults followed up to 16 years. We identified four groups for each brain feature, based on the degree of a main longitudinal component of decline. The minimal overlap between features suggested that each contributed uniquely and independently to structural brain changes in aging. Cognitive change and baseline cognition were associated with cortical area change, whereas higher baseline levels of phosphorylated tau and amyloid-β related to changes in subcortical volume. These results may contribute to a better understanding of different aging trajectories.

• Eielsen, Karl Mikkel Veum; Ulvenes, Pål Gunnar; Melsom, Linne; Wampold, Bruce E.; Røssberg, Jan Ivar & Myhre, Filip [Show all 9 contributors for this article] (2025). Development and psychometric evaluation of a screening instrument for cognitive perceptual disruption (Copeds) in psychotherapy patients. Psychotherapy Research. ISSN 1050-3307. doi: 10.1080/10503307.2025.2495773. Full text in Research Archive Show summary

  Objective Cognitive perceptual disruption (CPD) is an emotion regulation mechanism described in intensive short-term dynamic psychotherapy (ISTDP) that distinguishes fragile patients from resistant ones. CPD functions as an involuntary avoidance-based mechanism that prevents engagement with distressing emotions, making its identification crucial for guiding treatment. Currently, CPD assessment relies solely on clinical psychodiagnostic evaluation, with no available psychometric instruments. This study introduces a cognitive perceptual disruption screening instrument (Copeds), a self-report measure designed to identify CPD and assist in treatment planning for emotion-focused therapies. Method A cross-sectional study was conducted to develop Copeds, evaluate its ability to distinguish between fragile and resistant patients, and examine its preliminary psychometric properties. 112 outpatients underwent clinical psychodiagnostic evaluation and completed Copeds. Regularized regression techniques, receiver operating characteristic (ROC) analysis, and analyses of internal consistency and sensitivity/specificity were performed. Results The final instrument contained 19 psychometric items that strongly discriminated between fragile and resistant patients. ROC analysis yielded an area under the curve (AUC) value of 0.88. Sensitivity was 91.4%, and specificity was 76.4%. Conclusion The study provides promising initial evidence for Copeds as a reliable instrument with strong classification accuracy, supporting its potential use in clinical assessment and treatment planning for emotion-focused therapies.

• Walhovd, Kristine B; Krogsrud, Stine Kleppe; Amlien, Inge; Sørensen, Øystein; Wang, Yunpeng & Bråthen, Anne Cecilie Sjøli [Show all 14 contributors for this article] (2024). Fetal influence on the human brain through the lifespan. eLIFE. 12. doi: 10.7554/eLife.86812. Full text in Research Archive
• Roe, James Michael; Vidal-Piñeiro, Didac; Sørensen, Øystein; Grydeland, Håkon; Leonardsen, Esten Høyland & Iakunchykova, Olena [Show all 35 contributors for this article] (2024). Brain change trajectories in healthy adults correlate with Alzheimer’s related genetic variation and memory decline across life. Nature Communications. 15(1). doi: 10.1038/s41467-024-53548-z. Full text in Research Archive Show summary

  Throughout adulthood and ageing our brains undergo structural loss in an average pattern resembling faster atrophy in Alzheimer’s disease (AD). Using a longitudinal adult lifespan sample (aged 30-89; 2–7 timepoints) and four polygenic scores for AD, we show that change in AD-sensitive brain features correlates with genetic AD-risk and memory decline in healthy adults. We first show genetic risk links with more brain loss than expected for age in early Braak regions, and find this extends beyond APOE genotype. Next, we run machine learning on AD-control data from the Alzheimer’s Disease Neuroimaging Initiative using brain change trajectories conditioned on age, to identify AD-sensitive features and model their change in healthy adults. Genetic AD-risk linked with multivariate change across many AD-sensitive features, and we show most individuals over age ~50 are on an accelerated trajectory of brain loss in AD-sensitive regions. Finally, high genetic risk adults with elevated brain change showed more memory decline through adulthood, compared to high genetic risk adults with less brain change. Our findings suggest quantitative AD risk factors are detectable in healthy individuals, via a shared pattern of ageing- and AD-related neurodegeneration that occurs along a continuum and tracks memory decline through adulthood.

• Sørensen, Øystein (2024). Multilevel Semiparametric Latent Variable Modeling in R with “galamm”. Multivariate Behavioral Research. ISSN 0027-3171. doi: 10.1080/00273171.2024.2385336. Full text in Research Archive
• Grødem, Edvard Olaf Sætersdal; Leonardsen, Esten Høyland; MacIntosh, Bradley; Bjørnerud, Atle; SCHELLHORN, TILL & Sørensen, Øystein [Show all 8 contributors for this article] (2024). A minimalistic approach to classifying Alzheimer's disease using simple and extremely small convolutional neural networks. Journal of Neuroscience Methods. ISSN 0165-0270. 411. doi: 10.1016/j.jneumeth.2024.110253. Full text in Research Archive
• Leonardsen, Esten Høyland; Persson, Karin Ester Torun; Grødem, Edvard Olaf Sætersdal; Dinsdale, Nicola; SCHELLHORN, TILL & Roe, James Michael [Show all 16 contributors for this article] (2024). Constructing personalized characterizations of structural brain aberrations in patients with dementia using explainable artificial intelligence. npj Digital Medicine. 7(1). doi: 10.1038/s41746-024-01123-7. Full text in Research Archive Show summary

  Deep learning approaches for clinical predictions based on magnetic resonance imaging data have shown great promise as a translational technology for diagnosis and prognosis in neurological disorders, but its clinical impact has been limited. This is partially attributed to the opaqueness of deep learning models, causing insufficient understanding of what underlies their decisions. To overcome this, we trained convolutional neural networks on structural brain scans to differentiate dementia patients from healthy controls, and applied layerwise relevance propagation to procure individual-level explanations of the model predictions. Through extensive validations we demonstrate that deviations recognized by the model corroborate existing knowledge of structural brain aberrations in dementia. By employing the explainable dementia classifier in a longitudinal dataset of patients with mild cognitive impairment, we show that the spatially rich explanations complement the model prediction when forecasting transition to dementia and help characterize the biological manifestation of disease in the individual brain. Overall, our work exemplifies the clinical potential of explainable artificial intelligence in precision medicine.

• Fjell, Anders Martin; Sørensen, Øystein; Wang, Yunpeng; Amlien, Inge; Baaré, William F. C. & Bartrés-Faz, David [Show all 24 contributors for this article] (2023). No phenotypic or genotypic evidence for a link between sleep duration and brain atrophy. Nature Human Behaviour. 7, p. 2008–2022. doi: 10.1038/s41562-023-01707-5. Full text in Research Archive Show summary

  Abstract Short sleep is held to cause poorer brain health, but is short sleep associated with higher rates of brain structural decline? Analysing 8,153 longitudinal MRIs from 3,893 healthy adults, we found no evidence for an association between sleep duration and brain atrophy. In contrast, cross-sectional analyses (51,295 observations) showed inverse U-shaped relationships, where a duration of 6.5 (95% confidence interval, (5.7, 7.3)) hours was associated with the thickest cortex and largest volumes relative to intracranial volume. This fits converging evidence from research on mortality, health and cognition that points to roughly seven hours being associated with good health. Genome-wide association analyses suggested that genes associated with longer sleep for below-average sleepers were linked to shorter sleep for above-average sleepers. Mendelian randomization did not yield evidence for causal impacts of sleep on brain structure. The combined results challenge the notion that habitual short sleep causes brain atrophy, suggesting that normal brains promote adequate sleep duration—which is shorter than current recommendations.

• Raud, Liisa; Sneve, Markus Handal; Vidal-Piñeiro, Didac; Sørensen, Øystein; Folvik, Line & Ness, Hedda Tvedten [Show all 10 contributors for this article] (2023). Hippocampal-cortical functional connectivity during memory encoding and retrieval. NeuroImage. ISSN 1053-8119. 279. doi: 10.1016/j.neuroimage.2023.120309. Full text in Research Archive
• Sørensen, Øystein; Fjell, Anders Martin & Walhovd, Kristine B (2023). Longitudinal Modeling of Age-Dependent Latent Traits with Generalized Additive Latent and Mixed Models. Psychometrika. ISSN 0033-3123. 88(2), p. 456–486. doi: 10.1007/s11336-023-09910-z. Full text in Research Archive
• Ghannoum, Salim; Fantini, Damiano; Zahoor, Muhammad; Reiterer, Veronika; Phuyal, Santosh & Netto, Waldir Leoncio [Show all 13 contributors for this article] (2023). A combined experimental-computational approach uncovers a role for the Golgi matrix protein Giantin in breast cancer progression. PLoS Computational Biology. ISSN 1553-734X. 19(4). doi: 10.1371/journal.pcbi.1010995. Full text in Research Archive Show summary

  Our understanding of how speed and persistence of cell migration affects the growth rate and size of tumors remains incomplete. To address this, we developed a mathematical model wherein cells migrate in two-dimensional space, divide, die or intravasate into the vasculature. Exploring a wide range of speed and persistence combinations, we find that tumor growth positively correlates with increasing speed and higher persistence. As a biologically relevant example, we focused on Golgi fragmentation, a phenomenon often linked to alterations of cell migration. Golgi fragmentation was induced by depletion of Giantin, a Golgi matrix protein, the downregulation of which correlates with poor patient survival. Applying the experimentally obtained migration and invasion traits of Giantin depleted breast cancer cells to our mathematical model, we predict that loss of Giantin increases the number of intravasating cells. This prediction was validated, by showing that circulating tumor cells express significantly less Giantin than primary tumor cells. Altogether, our computational model identifies cell migration traits that regulate tumor progression and uncovers a role of Giantin in breast cancer progression.

• Capogna, Elettra; Watne, Leiv; Sørensen, Øystein; Guichelaar, Carlijn Jamila; Idland, Ane-Victoria & Halaas, Nathalie Bodd [Show all 11 contributors for this article] (2023). Associations of neuroinflammatory IL-6 and IL-8 with brain atrophy, memory decline, and core AD biomarkers – in cognitively unimpaired older adults. Brain, Behavior, and Immunity. ISSN 0889-1591. 113, p. 56–65. doi: 10.1016/j.bbi.2023.06.027. Full text in Research Archive Show summary

  Concentrations of pro-inflammatory cytokines –interleukin-6 (IL-6) and interleukin-8 (IL-8) – are increased with age and in Alzheimer’s disease (AD). It is not clear whether concentrations of IL-6 and IL-8 in the central nervous system predict later brain and cognitive changes over time nor whether this relationship is mediated by core AD biomarkers. Here, 219 cognitively healthy older adults (62–91 years), with baseline cerebrospinal fluid (CSF) measures of IL-6 and IL-8 were followed over time – up to 9 years – with assessments that included cognitive function, structural magnetic resonance imaging, and CSF measurements of phosphorylated tau (p-tau) and amyloid-β (Aβ-42) concentrations (for a subsample). Higher baseline CSF IL-8 was associated with better memory performance over time in the context of lower levels of CSF p-tau and p-tau/Aβ-42 ratio. Higher CSF IL-6 was related to less CSF p-tau changes over time. The results are in line with the hypothesis suggesting that an up-regulation of IL-6 and IL-8 in the brain may play a neuroprotective role in cognitively healthy older adults with lower load of AD pathology.

• Fjell, Anders Martin; Sørensen, Øystein; Wang, Yunpeng; Amlien, Inge; Baaré, William F C & Bartrés-Faz, David [Show all 21 contributors for this article] (2023). Is Short Sleep Bad for the Brain? Brain Structure and Cognitive Function in Short Sleepers. Journal of Neuroscience. ISSN 0270-6474. 43(28), p. 5241–5250. doi: 10.1523/JNEUROSCI.2330-22.2023. Full text in Research Archive Show summary

  Many sleep less than recommended without experiencing daytime sleepiness. According to prevailing views, short sleep increases risk of lower brain health and cognitive function. Chronic mild sleep deprivation could cause undetected sleep debt, negatively affecting cognitive function and brain health. However, it is possible that some have less sleep need and are more resistant to negative effects of sleep loss. We investigated this using a cross-sectional and longitudinal sample of 47,029 participants of both sexes (20–89 years) from the Lifebrain consortium, Human Connectome project (HCP) and UK Biobank (UKB), with measures of self-reported sleep, including 51,295 MRIs of the brain and cognitive tests. A total of 740 participants who reported to sleep <6 h did not experience daytime sleepiness or sleep problems/disturbances interfering with falling or staying asleep. These short sleepers showed significantly larger regional brain volumes than both short sleepers with daytime sleepiness and sleep problems ( n = 1742) and participants sleeping the recommended 7–8 h ( n = 3886). However, both groups of short sleepers showed slightly lower general cognitive function (GCA), 0.16 and 0.19 SDs, respectively. Analyses using accelerometer-estimated sleep duration confirmed the findings, and the associations remained after controlling for body mass index, depression symptoms, income, and education. The results suggest that some people can cope with less sleep without obvious negative associations with brain morphometry and that sleepiness and sleep problems may be more related to brain structural differences than duration. However, the slightly lower performance on tests of general cognitive abilities warrants closer examination in natural settings. SIGNIFICANCE STATEMENT Short habitual sleep is prevalent, with unknown consequences for brain health and cognitive performance. Here, we show that daytime sleepiness and sleep problems are more strongly related to regional brain volumes than sleep duration. However, participants sleeping ≤6 h had slightly lower scores on tests of general cognitive function (GCA). This indicates that sleep need is individual and that sleep duration per se is very weakly if at all related brain health, while daytime sleepiness and sleep problems may show somewhat stronger associations. The association between habitual short sleep and lower scores on tests of general cognitive abilities must be further scrutinized in natural settings.

• Bråthen, Anne Cecilie Sjøli; Sørensen, Øystein; Lange, Ann-Marie Glasø de; Mowinckel, Athanasia Monika; Fjell, Anders Martin & Walhovd, Kristine B (2022). Cognitive and hippocampal changes weeks and years after memory training. Scientific Reports. 12(1). doi: 10.1038/s41598-022-11636-4. Full text in Research Archive
• Walhovd, Kristine B; Nyberg, Lars; Lindenberger, Ulman; Amlien, Inge; Sørensen, Øystein & Wang, Yunpeng [Show all 20 contributors for this article] (2022). Brain aging differs with cognitive ability regardless of education. Scientific Reports. 12(1). doi: 10.1038/s41598-022-17727-6. Full text in Research Archive
• Vidal-Piñeiro, Didac; Sørensen, Øystein; Blennow, Kaj; Capogna, Elettra; Halaas, Nathalie Bodd & Idland, Ane-Victoria [Show all 12 contributors for this article] (2022). Relationship between cerebrospinal fluid neurodegeneration biomarkers and temporal brain atrophy in cognitively healthy older adults. Neurobiology of Aging. ISSN 0197-4580. 116, p. 80–91. doi: 10.1016/j.neurobiolaging.2022.04.010. Full text in Research Archive Show summary

  It is unclear whether cerebrospinal fluid (CSF) biomarkers of neurodegeneration predict brain atrophy in cognitively healthy older adults, whether these associations can be explained by phosphorylated tau181 (p-tau) and the 42 amino acid form of amyloid-β (Aβ42) biomarkers, and which neural substrates may drive these associations. We addressed these questions in 2 samples of cognitively healthy older adults who underwent longitudinal structural MRI up to 7 years and had baseline CSF levels of heart-type fatty-acid binding protein (FABP3)=, total-tau, neurogranin, and neurofilament light (NFL) (n = 189, scans = 721). The results showed that NFL, total-tau, and FABP3 predicted entorhinal thinning and hippocampal atrophy. Brain atrophy was not moderated by Aβ42 and the associations between NFL and FABP3 with brain atrophy were independent of p-tau. The spatial pattern of cortical atrophy associated with the biomarkers overlapped with neurogenetic profiles associated with expression in the axonal (total-tau, NFL) and dendritic (neurogranin) components. CSF biomarkers of neurodegeneration are useful for predicting specific features of brain atrophy in older adults, independently of amyloid and tau pathology biomarkers.

• Ljøsne, Isabelle Sylvie Budin; Mowinckel, Athanasia Monika; Friedman, Barbara Bodorkos; Ebmeier, Klaus P; Drevon, Christian A & Carver, Rebecca Bruu [Show all 22 contributors for this article] (2022). Public perceptions of brain health: an international, online cross-sectional survey. BMJ Open. 12(4). doi: 10.1136/bmjopen-2021-057999. Full text in Research Archive Show summary

  Objectives To investigate public perspectives on brain health. Design Cross-sectional multilanguage online survey. Setting Lifebrain posted the survey on its website and social media and shared it with stakeholders. The survey was open from 4 June 2019 to 31 August 2020. Participants n=27 590 aged ≥18 years from 81 countries in five continents completed the survey. The respondents were predominantly women (71%), middle aged (41–60 years; 37%) or above (>60 years; 46%), highly educated (69%) and resided in Europe (98%). Main outcome measures Respondents’ views were assessed regarding factors that may influence brain health, life periods considered important to look after the brain and diseases and disorders associated with the brain. We run exploratory linear models at a 99% level of significance to assess correlates of the outcome variables, adjusting for likely confounders in a targeted fashion. Results Of all significant effects, the respondents recognised the impact of lifestyle factors on brain health but had relatively less awareness of the role socioeconomic factors might play. Most respondents rated all life periods as important for the brain (95%–96%), although the prenatal period was ranked significantly lower (84%). Equally, women and highly educated respondents more often rated factors and life periods to be important for brain health. Ninety-nine per cent of respondents associated Alzheimer’s disease and dementia with the brain. The respondents made a connection between mental health and the brain, and mental disorders such as schizophrenia and depression were significantly more often considered to be associated with the brain than neurological disorders such as stroke and Parkinson’s disease. Few respondents (<32%) associated cancer, hypertension, diabetes and arthritis with the brain. Conclusions Differences in perceptions of brain health were noted among specific segments of the population. Policies providing information about brain-friendly health behaviours and targeting people less likely to have relevant experience may be needed.

• Leonardsen, Esten Høyland; Peng, Han; Kaufmann, Tobias; Agartz, Ingrid; Andreassen, Ole & Celius, Elisabeth Gulowsen [Show all 19 contributors for this article] (2022). Deep neural networks learn general and clinically relevant representations of the ageing brain. NeuroImage. ISSN 1053-8119. 256. doi: 10.1016/j.neuroimage.2022.119210. Full text in Research Archive Show summary

  The discrepancy between chronological age and the apparent age of the brain based on neuroimaging data — the brain age delta — has emerged as a reliable marker of brain health. With an increasing wealth of data, approaches to tackle heterogeneity in data acquisition are vital. To this end, we compiled raw structural magnetic resonance images into one of the largest and most diverse datasets assembled (n=53542), and trained convolutional neural networks (CNNs) to predict age. We achieved state-of-the-art performance on unseen data from unknown scanners (n=2553), and showed that higher brain age delta is associated with diabetes, alcohol intake and smoking. Using transfer learning, the intermediate representations learned by our model complemented and partly outperformed brain age delta in predicting common brain disorders. Our work shows we can achieve generalizable and biologically plausible brain age predictions using CNNs trained on heterogeneous datasets, and transfer them to clinical use cases.

• Nyberg, Lars Erik; Magnussen, Fredrik; Lundquist, Anders; Baaré, William; Bartrés-Faz, David & Bertram, Lars [Show all 24 contributors for this article] (2021). Educational attainment does not influence brain aging. Proceedings of the National Academy of Sciences of the United States of America (PNAS). ISSN 0027-8424. 118(18), p. 1–3. doi: 10.1073/pnas.2101644118. Full text in Research Archive
• Sørensen, Øystein; Walhovd, Kristine B & Fjell, Anders Martin (2021). A recipe for accurate estimation of lifespan brain trajectories, distinguishing longitudinal and cohort effects. NeuroImage. ISSN 1053-8119. 226. doi: 10.1016/j.neuroimage.2020.117596. Full text in Research Archive Show summary

  We address the problem of estimating how different parts of the brain develop and change throughout the lifespan, and how these trajectories are affected by genetic and environmental factors. Estimation of these lifespan trajectories is statistically challenging, since their shapes are typically highly nonlinear, and although true change can only be quantified by longitudinal examinations, as follow-up intervals in neuroimaging studies typically cover less than 10% of the lifespan, use of cross-sectional information is necessary. Linear mixed models (LMMs) and structural equation models (SEMs) commonly used in longitudinal analysis rely on assumptions which are typically not met with lifespan data, in particular when the data consist of observations combined from multiple studies. While LMMs require a priori specification of a polynomial functional form, SEMs do not easily handle data with unstructured time intervals between measurements. Generalized additive mixed models (GAMMs) offer an attractive alternative, and in this paper we propose various ways of formulating GAMMs for estimation of lifespan trajectories of 12 brain regions, using a large longitudinal dataset and realistic simulation experiments. We show that GAMMs are able to more accurately fit lifespan trajectories, distinguish longitudinal and cross-sectional effects, and estimate effects of genetic and environmental exposures. Finally, we discuss and contrast questions related to lifespan research which strictly require repeated measures data and questions which can be answered with a single measurement per participant, and in the latter case, which simplifying assumptions that need to be made. The examples are accompanied with R code, providing a tutorial for researchers interested in using GAMMs.

• Roe, James Michael; Vidal-Piñeiro, Didac; Sørensen, Øystein; Brandmaier, Andreas M.; Düzel, Sandra & Gonzalez, Hector A. [Show all 18 contributors for this article] (2021). Asymmetric thinning of the cerebral cortex across the adult lifespan is accelerated in Alzheimer’s disease. Nature Communications. 12:721, p. 1–11. doi: 10.1038/s41467-021-21057-y. Full text in Research Archive Show summary

  Abstract Aging and Alzheimer’s disease (AD) are associated with progressive brain disorganization. Although structural asymmetry is an organizing feature of the cerebral cortex it is unknown whether continuous age- and AD-related cortical degradation alters cortical asymmetry. Here, in multiple longitudinal adult lifespan cohorts we show that higher-order cortical regions exhibiting pronounced asymmetry at age ~20 also show progressive asymmetry-loss across the adult lifespan. Hence, accelerated thinning of the (previously) thicker homotopic hemisphere is a feature of aging. This organizational principle showed high consistency across cohorts in the Lifebrain consortium, and both the topological patterns and temporal dynamics of asymmetry-loss were markedly similar across replicating samples. Asymmetry-change was further accelerated in AD. Results suggest a system-wide dedifferentiation of the adaptive asymmetric organization of heteromodal cortex in aging and AD.

• Fjell, Anders Martin; Grydeland, Håkon; Wang, Yunpeng; Amlien, Inge; Bartrés-Faz, David & Brandmaier, Andreas M. [Show all 24 contributors for this article] (2021). The genetic organization of longitudinal subcortical volumetric change is stable throughout the lifespan running title: Genetics of subcortical lifespan change. eLIFE. 10, p. 1–22. doi: 10.7554/eLife.66466. Full text in Research Archive Show summary

  Development and aging of the cerebral cortex show similar topographic organization and are governed by the same genes. It is unclear whether the same is true for subcortical regions, which follow fundamentally different ontogenetic and phylogenetic principles. We tested the hypothesis that genetically governed neurodevelopmental processes can be traced throughout life by assessing to which degree brain regions that develop together continue to change together through life. Analyzing over 6000 longitudinal MRIs of the brain, we used graph theory to identify five clusters of coordinated development, indexed as patterns of correlated volumetric change in brain structures. The clusters tended to follow placement along the cranial axis in embryonic brain development, suggesting continuity from prenatal stages, and correlated with cognition. Across independent longitudinal datasets, we demonstrated that developmental clusters were conserved through life. Twin-based genetic correlations revealed distinct sets of genes governing change in each cluster. Single-nucleotide polymorphisms-based analyses of 38,127 cross-sectional MRIs showed a similar pattern of genetic volume–volume correlations. In conclusion, coordination of subcortical change adheres to fundamental principles of lifespan continuity and genetic organization.

• Krogsrud, Stine Kleppe; Mowinckel, Athanasia Monika; Sederevicius, Donatas; Vidal-Piñeiro, Didac; Amlien, Inge Kasbohm & Wang, Yunpeng [Show all 9 contributors for this article] (2021). Relationships between apparent cortical thickness and working memory across the lifespan - Effects of genetics and socioeconomic status. Developmental Cognitive Neuroscience. ISSN 1878-9293. 51, p. 1–11. doi: 10.1016/j.dcn.2021.100997. Full text in Research Archive
• Sørensen, Øystein; Brandmaier, Andreas M.; Macià, Dídac; Ebmeier, Klaus; Ghisletta, Paolo & Kievit, Rogier A. [Show all 10 contributors for this article] (2021). Meta-analysis of generalized additive models in neuroimaging studies. NeuroImage. ISSN 1053-8119. doi: 10.1016/j.neuroimage.2020.117416. Full text in Research Archive Show summary

  Analyzing data from multiple neuroimaging studies has great potential in terms of increasing statistical power, enabling detection of effects of smaller magnitude than would be possible when analyzing each study separately and also allowing to systematically investigate between-study differences. Restrictions due to privacy or proprietary data as well as more practical concerns can make it hard to share neuroimaging datasets, such that analyzing all data in a common location might be impractical or impossible. Meta-analytic methods provide a way to overcome this issue, by combining aggregated quantities like model parameters or risk ratios. Most meta-analytic tools focus on parametric statistical models, and methods for meta-analyzing semi-parametric models like generalized additive models have not been well developed. Parametric models are often not appropriate in neuroimaging, where for instance age-brain relationships may take forms that are difficult to accurately describe using such models. In this paper we introduce meta-GAM, a method for meta-analysis of generalized additive models which does not require individual participant data, and hence is suitable for increasing statistical power while upholding privacy and other regulatory concerns. We extend previous works by enabling the analysis of multiple model terms as well as multivariate smooth functions. In addition, we show how meta-analytic p-values can be computed for smooth terms. The proposed methods are shown to perform well in simulation experiments, and are demonstrated in a real data analysis on hippocampal volume and self-reported sleep quality data from the Lifebrain consortium. We argue that application of meta-GAM is especially beneficial in lifespan neuroscience and imaging genetics. The methods are implemented in an accompanying R package metagam, which is also demonstrated.

• Grydeland, Håkon; Sederevicius, Donatas; Wang, Yunpeng; Bartres-Faz, David; Bertram, Lars & Dobricic, Valerija [Show all 16 contributors for this article] (2021). Self-Reported Sleep Relates to Microstructural Hippocampal Decline in β-Amyloid Positive Adults Beyond Genetic Risk. Sleep. ISSN 0161-8105. 44(11). doi: 10.1093/sleep/zsab110. Full text in Research Archive Show summary

  Background To test the hypothesis that worse self-reported sleep relates to memory decay and reduced hippocampal integrity as indexed by increased intra-hippocampal water diffusion, and that the relations are stronger in the presence of β-amyloid (Aβ) accumulation, a marker of Alzheimer’s disease (AD) pathology. Methods Two-hundred and forty-three cognitively healthy participants, aged 19-81 years, completed the Pittsburgh Sleep Quality Index, and 2 diffusion tensor imaging sessions, on average 3 years apart, allowing measures of decline in hippocampal microstructural integrity as indexed by increased mean diffusivity. We measured memory decay using delayed recall from the California Verbal Learning Test. 18F-Flutemetamol positron emission tomography, in 108 participants above 44 years of age, yielded 23 Aβ positive. Genotyping enabled controlling for APOE ε4 status, and polygenic scores for sleep efficiency and AD. Results Worse global sleep quality and sleep efficiency related to more rapid reduction in hippocampal microstructural integrity over time. Focusing on sleep efficiency, the relation was stronger in presence of Aβ accumulation. Sleep efficiency related to memory decay indirectly via hippocampal integrity decline. The results were not explained by genetic risk for sleep efficiency and AD. Conclusions Poor self-reported sleep efficiency related to decline in hippocampal integrity, especially in the presence of Aβ accumulation. Poor sleep and hippocampal microstructural decline may partly explain memory decline in older adults with Aβ pathology. The relationships were not explained by genetic risk. Poor self-reported sleep efficiency might constitute a risk factor for AD, although the causal mechanisms driving the of observed associations remain unknown.

• Walhovd, Kristine Beate; Fjell, Anders Martin; Wang, Yunpeng; Amlien, Inge; Mowinckel, Athanasia Monika & Lindenberger, Ulman [Show all 29 contributors for this article] (2021). Education and income show heterogeneous relationships to lifespan brain and cognitive differences across European and US cohorts. Cerebral Cortex. ISSN 1047-3211. 32(4), p. 839–854. doi: 10.1093/cercor/bhab248. Full text in Research Archive Show summary

  Abstract Higher socio-economic status (SES) has been proposed to have facilitating and protective effects on brain and cognition. We ask whether relationships between SES, brain volumes and cognitive ability differ across cohorts, by age and national origin. European and US cohorts covering the lifespan were studied (4–97 years, N = 500 000; 54 000 w/brain imaging). There was substantial heterogeneity across cohorts for all associations. Education was positively related to intracranial (ICV) and total gray matter (GM) volume. Income was related to ICV, but not GM. We did not observe reliable differences in associations as a function of age. SES was more strongly related to brain and cognition in US than European cohorts. Sample representativity varies, and this study cannot identify mechanisms underlying differences in associations across cohorts. Differences in neuroanatomical volumes partially explained SES–cognition relationships. SES was more strongly related to ICV than to GM, implying that SES–cognition relations in adulthood are less likely grounded in neuroprotective effects on GM volume in aging. The relatively stronger SES–ICV associations rather are compatible with SES–brain volume relationships being established early in life, as ICV stabilizes in childhood. The findings underscore that SES has no uniform association with, or impact on, brain and cognition.

• Sederevicius, Donatas; Vidal-Piñeiro, Didac; Sørensen, Øystein; Leemput, Koen van; Iglesias, Juan Eugenio & Dalca, Adrian V. [Show all 11 contributors for this article] (2021). Reliability and sensitivity of two whole-brain segmentation approaches included in FreeSurfer – ASEG and SAMSEG. NeuroImage. ISSN 1053-8119. 237:118113, p. 1–14. doi: 10.1016/j.neuroimage.2021.118113. Full text in Research Archive
• Sørensen, Øystein; Crispino, Marta; Liu, Qinghua & Vitelli, Valeria (2020). BayesMallows: An R Package for the Bayesian Mallows Model. The R Journal. 12(1), p. 324–342. doi: 10.32614/RJ-2020-026. Full text in Research Archive Show summary

  Abstract BayesMallows is an R package for analyzing preference data in the form of rankings with the Mallows rank model, and its finite mixture extension, in a Bayesian framework. The model is grounded on the idea that the probability density of an observed ranking decreases exponentially with the distance to the location parameter. It is the first Bayesian implementation that allows wide choices of distances, and it works well with a large amount of items to be ranked. BayesMallows handles non-standard data: partial rankings and pairwise comparisons, even in cases including non-transitive preference patterns. The Bayesian paradigm allows coherent quantification of posterior uncertainties of estimates of any quantity of interest. These posteriors are fully available to the user, and the package comes with convienient tools for summarizing and visualizing the posterior distributions.

• Idland, Ane-Victoria; Llonch, Roser Sala; Watne, Leiv; Brækhus, Anne; Hansson, Oskar & Blennow, Kaj [Show all 11 contributors for this article] (2020). Biomarker Profiling Beyond Amyloid and Tau: Cerebrospinal Fluid Markers, Hippocampal Atrophy, and Memory Change in Cognitively Unimpaired Older Adults. Neurobiology of Aging. ISSN 0197-4580. 93, p. 1–15. doi: 10.1016/j.neurobiolaging.2020.04.002. Full text in Research Archive Show summary

  Brain changes occurring in aging can be indexed by biomarkers. We used cluster analysis to identify subgroups of cognitively unimpaired individuals (n = 99, 64-93 years) with different profiles of the cerebrospinal fluid biomarkers beta amyloid 1-42 (Aβ42), phosphorylated tau (P-tau), total tau, chitinase-3-like protein 1 (YKL-40), fatty acid binding protein 3 (FABP3), and neurofilament light (NFL). Hippocampal volume and memory were assessed across multiple follow-up examinations covering up to 6.8 years. Clustering revealed one group (39%) with more pathological concentrations of all biomarkers, which could further be divided into one group (20%) characterized by tauopathy and high FABP3 and one (19%) by brain β-amyloidosis, high NFL, and slightly higher YKL-40. The clustering approach clearly outperformed classification based on Aβ42 and P-tau alone in prediction of memory decline, with the individuals with most tauopathy and FABP3 showing more memory decline, but not more hippocampal volume change. The results demonstrate that older adults can be classified based on biomarkers beyond amyloid and tau, with improved prediction of memory decline

• Fjell, Anders Martin; Sørensen, Øystein; Amlien, Inge Kasbohm; Bartrés-Faz, David; Brandmaier, Andreas M. & Buchmann, Nikolaus [Show all 32 contributors for this article] (2020). Poor Self-Reported Sleep is Related to Regional Cortical Thinning in Aging but not Memory Decline-Results From the Lifebrain Consortium. Cerebral Cortex. ISSN 1047-3211. p. 1–17. doi: 10.1093/cercor/bhaa332. Full text in Research Archive Show summary

  We examined whether sleep quality and quantity are associated with cortical and memory changes in cognitively healthy participants across the adult lifespan. Associations between self-reported sleep parameters (Pittsburgh Sleep Quality Index, PSQI) and longitudinal cortical change were tested using five samples from the Lifebrain consortium (n = 2205, 4363 MRIs, 18–92 years). In additional analyses, we tested coherence with cell-specific gene expression maps from the Allen Human Brain Atlas, and relations to changes in memory performance. “PSQI # 1 Subjective sleep quality” and “PSQI #5 Sleep disturbances” were related to thinning of the right lateral temporal cortex, with lower quality and more disturbances being associated with faster thinning. The association with “PSQI #5 Sleep disturbances” emerged after 60 years, especially in regions with high expression of genes related to oligodendrocytes and S1 pyramidal neurons. None of the sleep scales were related to a longitudinal change in episodic memory function, suggesting that sleep-related cortical changes were independent of cognitive decline. The relationship to cortical brain change suggests that self-reported sleep parameters are relevant in lifespan studies, but small effect sizes indicate that self-reported sleep is not a good biomarker of general cortical degeneration in healthy older adults.

• Walhovd, Kristine B; Bråthen, Anne Cecilie Sjøli; Panizzon, Matthew S.; Mowinckel, Athanasia Monika; Sørensen, Øystein & Lange, Ann-Marie Glasø de [Show all 11 contributors for this article] (2020). Within-session verbal learning slope is predictive of lifespan delayed recall, hippocampal volume, and memory training benefit, and is heritable. Scientific Reports. 10, p. 1–13. doi: 10.1038/s41598-020-78225-1. Full text in Research Archive Show summary

  Memory performance results from plasticity, the ability to change with experience. We show that benefit from practice over a few trials, learning slope, is predictive of long-term recall and hippocampal volume across a broad age range and a long period of time, relates to memory training benefit, and is heritable. First, in a healthy lifespan sample (n = 1825, age 4–93 years), comprising 3483 occasions of combined magnetic resonance imaging (MRI) scans and memory tests over a period of up to 11 years, learning slope across 5 trials was uniquely related to performance on a delayed free recall test, as well as hippocampal volume, independent from first trial memory or total memory performance across the five learning trials. Second, learning slope was predictive of benefit from memory training across ten weeks in an experimental subsample of adults (n = 155). Finally, in an independent sample of male twins (n = 1240, age 51–50 years), learning slope showed significant heritability. Within-session learning slope may be a useful marker beyond performance per se, being heritable and having unique predictive value for long-term memory function, hippocampal volume and training benefit across the human lifespan.

• Gorbach, Tetiana; Pudas, Sara; Bartrés-Faz, David; Brandmaier, Andreas M.; Düzel, Sandra & Henson, Rik [Show all 17 contributors for this article] (2020). Longitudinal association between hippocampus atrophy and episodic‐memory decline in non‐demented APOE ε4 carriers. Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring. 12(1). doi: 10.1002/dad2.12110. Full text in Research Archive Show summary

  Introduction The apolipoprotein E (APOE) ε4 allele is the main genetic risk factor for Alzheimer's disease (AD), accelerated cognitive aging, and hippocampal atrophy, but its influence on the association between hippocampus atrophy and episodic‐memory decline in non‐demented individuals remains unclear. Methods We analyzed longitudinal (two to six observations) magnetic resonance imaging (MRI)–derived hippocampal volumes and episodic memory from 748 individuals (55 to 90 years at baseline, 50% female) from the European Lifebrain consortium. Results The change‐change association for hippocampal volume and memory was significant only in ε4 carriers (N = 173, r = 0.21, P = .007; non‐carriers: N = 467, r = 0.073, P = .117). The linear relationship was significantly steeper for the carriers [t(629) = 2.4, P = .013]. A similar trend toward a stronger change‐change relation for carriers was seen in a subsample with more than two assessments. Discussion These findings provide evidence for a difference in hippocampus‐memory association between ε4 carriers and non‐carriers, thus highlighting how genetic factors modulate the translation of the AD‐related pathophysiological cascade into cognitive deficits.

• Vidal-Piñeiro, Didac; Sneve, Markus Handal; Amlien, Inge Kasbohm; Grydeland, Håkon; Mowinckel, Athanasia Monika & Roe, James Michael [Show all 10 contributors for this article] (2020). The Functional Foundations of Episodic Memory Remain Stable Throughout the Lifespan. Cerebral Cortex. ISSN 1047-3211. doi: 10.1093/cercor/bhaa348. Full text in Research Archive Show summary

  Abstract It has been suggested that specific forms of cognition in older age rely largely on late-life specific mechanisms. Here instead, we tested using task-fMRI (n = 540, age 6–82 years) whether the functional foundations of successful episodic memory encoding adhere to a principle of lifespan continuity, shaped by developmental, structural, and evolutionary influences. We clustered regions of the cerebral cortex according to the shape of the lifespan trajectory of memory activity in each region so that regions showing the same pattern were clustered together. The results revealed that lifespan trajectories of memory encoding function showed a continuity through life but no evidence of age-specific mechanisms such as compensatory patterns. Encoding activity was related to general cognitive abilities and variations of grey matter as captured by a multi-modal independent component analysis, variables reflecting core aspects of cognitive and structural change throughout the lifespan. Furthermore, memory encoding activity aligned to fundamental aspects of brain organization, such as large-scale connectivity and evolutionary cortical expansion gradients. Altogether, we provide novel support for a perspective on memory aging in which maintenance and decay of episodic memory in older age needs to be understood from a comprehensive life-long perspective rather than as a late-life phenomenon only.

• Vidal-Piñeiro, Didac; Parker, Nadine; Shin, Jean; French, Leon; Grydeland, Håkon & Jackowski, Andrea [Show all 14 contributors for this article] (2020). Cellular correlates of cortical thinning throughout the lifespan. Scientific Reports. 10(1), p. 1–14. doi: 10.1038/s41598-020-78471-3. Full text in Research Archive Show summary

  Abstract Cortical thinning occurs throughout the entire life and extends to late-life neurodegeneration, yet the neurobiological substrates are poorly understood. Here, we used a virtual-histology technique and gene expression data from the Allen Human Brain Atlas to compare the regional profiles of longitudinal cortical thinning through life (4004 magnetic resonance images [MRIs]) with those of gene expression for several neuronal and non-neuronal cell types. The results were replicated in three independent datasets. We found that inter-regional profiles of cortical thinning related to expression profiles for marker genes of CA1 pyramidal cells, astrocytes and, microglia during development and in aging. During the two stages of life, the relationships went in opposite directions: greater gene expression related to less thinning in development and vice versa in aging. The association between cortical thinning and cell-specific gene expression was also present in mild cognitive impairment and Alzheimer’s Disease. These findings suggest a role of astrocytes and microglia in promoting and supporting neuronal growth and dendritic structures through life that affects cortical thickness during development, aging, and neurodegeneration. Overall, the findings contribute to our understanding of the neurobiology underlying variations in MRI-derived estimates of cortical thinning through life and late-life disease.

• Sørensen, Øystein & Westerhausen, René (2020). From observed laterality to latent hemispheric differences: Revisiting the inference problem. Laterality: Asymmetries of Body, Brain and Cognition. ISSN 1357-650X. 25(5), p. 1–24. doi: 10.1080/1357650X.2020.1769124. Full text in Research Archive Show summary

  Researchers interested in hemispheric dominance frequently aim to infer latent functional differences between the hemispheres from observed lateral behavioural or brain-activation differences. To be valid, these inferences may not only rely on the observed laterality measures but also need to account for the antecedent probabilities of the studied latent classes. This fact is frequently ignored in the literature, leading to misclassifications especially when considering low probability classes as, for example, “atypical” right hemispheric language dominance. In the present paper, we revisit this inference problem (a) by outlining a general Bayesian framework for the inferential process and (b) by exemplarily applying this framework on the inference of hemispheric dominance for speech processing from dichotic-listening laterality scores. Utilizing large-scale empirical data sets as well as simulation studies, we show that valid inferences also regarding low probable latent classes can be drawn applying the present framework, although within certain boundaries. We further illustrate that repeated laterality measures of the same person may be used to improve the classification outcome. The article additionally provides R package and Shiny app implementations of the suggested Bayesian framework, which allow to explore the boundaries of valid inference for the present and other examples.

• Fjell, Anders Martin; Sørensen, Øystein; Amlien, Inge Kasbohm; Bartrés-Faz, David; Bros, Didac Macia & Buchmann, Nikolaus [Show all 28 contributors for this article] (2019). Self-reported sleep relates to hippocampal atrophy across the adult lifespan – results from the Lifebrain consortium. Sleep. ISSN 0161-8105. doi: 10.1093/sleep/zsz280. Full text in Research Archive Show summary

  Objectives Poor sleep is associated with multiple age-related neurodegenerative and neuropsychiatric conditions. The hippocampus plays a special role in sleep and sleep-dependent cognition, and accelerated hippocampal atrophy is typically seen with higher age. Hence, it is critical to establish how the relationship between sleep and hippocampal volume loss unfolds across the adult lifespan. Methods Self-reported sleep measures and MRI-derived hippocampal volumes were obtained from 3105 cognitively normal participants (18-90 years) from major European brain studies in the Lifebrain consortium. Hippocampal volume change was estimated from 5116 MRIs from 1299 participants for whom longitudinal MRIs were available, followed up to 11 years with a mean interval of 3.3 years. Cross-sectional analyses were repeated in a sample of 21390 participants from the UK Biobank. Results No cross-sectional sleep – hippocampal volume relationships were found. However, worse sleep quality, efficiency, problems, and daytime tiredness were related to greater hippocampal volume loss over time, with high scorers showing 0.22% greater annual loss than low scorers. The relationship between sleep and hippocampal atrophy did not vary across age. Simulations showed that the observed longitudinal effects were too small to be detected as age-interactions in the cross-sectional analyses. Conclusions Worse self-reported sleep is associated with higher rates of hippocampal volume decline across the adult lifespan. This suggests that sleep is relevant to understand individual differences in hippocampal atrophy, but limited effect sizes call for cautious interpretation.

• Sørensen, Øystein (2019). hdme: High-Dimensional Regression with Measurement Error. Journal of Open Source Software (JOSS). doi: 10.21105/joss.01404. Full text in Research Archive
• Fjell, Anders Martin; Sneve, Markus Handal; Sederevicius, Donatas; Sørensen, Øystein; Krogsrud, Stine Kleppe & Mowinckel, Athanasia Monika [Show all 7 contributors for this article] (2019). Volumetric and microstructural regional changes of the hippocampus underlying development of recall performance after extended retention intervals. Developmental Cognitive Neuroscience. ISSN 1878-9293. 40:100723, p. 1–12. doi: 10.1016/j.dcn.2019.100723. Full text in Research Archive Show summary

  Performance on recall tests improves through childhood and adolescence, in part due to structural maturation of the medial temporal cortex. Although partly different processes support successful recall over shorter vs. longer intervals, recall is usually tested after less than an hour. The aim of the present study was to test whether there are unique developmental changes in recall performance using extended retention intervals, and whether these are related to structural maturation of sub-regions of the hippocampus. 650 children and adolescents from 4.1 to 24.8 years were assessed in total 962 times (mean interval ≈ 1.8 years). The California Verbal Learning Test (CVLT) and the Rey Complex Figure Test (CFT) were used. Recall was tested 30 min and ≈ 10 days after encoding. We found unique developmental effects on recall in the extended retention interval condition independently of 30 min recall performance. For CVLT, major improvements happened between 10 and 15 years. For CFT, improvement was linear and was accounted for by visuo-constructive abilities. The relationships did not show anterior-posterior hippocampal axis differences. In conclusion, performance on recall tests using extended retention intervals shows unique development, likely due to changes in encoding depth or efficacy, or improvements of long-term consolidation processes.

• Vitelli, Valeria; Sørensen, Øystein; Crispino, Marta; Rattalma, Arnoldo Frigessi Di & Arjas, Elja (2018). Probabilistic preference learning with the Mallows rank model. Journal of machine learning research. ISSN 1532-4435. 18, p. 1–49. Full text in Research Archive Show summary

  Ranking and comparing items is crucial for collecting information about preferences in many areas, from marketing to politics. The Mallows rank model is among the most successful approaches to analyse rank data, but its computational complexity has limited its use to a particular form based on Kendall distance. We develop new computationally tractable methods for Bayesian inference in Mallows models that work with any right-invariant distance. Our method performs inference on the consensus ranking of the items, also when based on partial rankings, such as top-k items or pairwise comparisons. We prove that items that none of the assessors has ranked do not influence the maximum a posteriori consensus ranking, and can therefore be ignored. When assessors are many or heterogeneous, we propose a mixture model for clustering them in homogeneous subgroups, with cluster-specific consensus rankings. We develop approximate stochastic algorithms that allow a fully probabilistic analysis, leading to coherent quantifications of uncertainties. We make probabilistic predictions on the class membership of assessors based on their ranking of just some items, and predict missing individual preferences, as needed in recommendation systems. We test our approach using several experimental and benchmark datasets.

• Sørensen, Øystein; Hellton, Kristoffer Herland; Rattalma, Arnoldo Frigessi Di & Thoresen, Magne (2018). Covariate Selection in High-Dimensional Generalized Linear Models With Measurement Error. Journal of Computational And Graphical Statistics (JCGS). ISSN 1061-8600. 27(4), p. 739–749. doi: 10.1080/10618600.2018.1425626. Full text in Research Archive Show summary

  In many problems involving generalized linear models, the covariates are subject to measurement error. When the number of covariates p exceeds the sample size n, regularized methods like the lasso or Dantzig selector are required. Several recent papers have studied methods which correct for measurement error in the lasso or Dantzig selector for linear models in the p > n setting. We study a correction for generalized linear models, based on Rosenbaum and Tsybakov’s matrix uncertainty selector. By not requiring an estimate of the measurement error covariance matrix, this generalized matrix uncertainty selector has a great practical advantage in problems involving high-dimensional data. We further derive an alternative method based on the lasso, and develop efficient algorithms for both methods. In our simulation studies of logistic and Poisson regression with measurement error, the proposed methods outperform the standard lasso and Dantzig selector with respect to covariate selection, by reducing the number of false positives considerably. We also consider classification of patients on the basis of gene expression data with noisy measurements. Supplementary materials for this article are available online.

• Sørensen, Øystein; Frigessi, Arnoldo & Thoresen, Magne (2015). Measurement error in Lasso: Impact and likelihood bias correction. Statistica sinica. ISSN 1017-0405. 25(2), p. 809–829. doi: 10.5705/ss.2013.180. Full text in Research Archive Show summary

  Regression with the lasso penalty is a popular tool for performing dimension reduction when the number of covariates is large. In many applications of the lasso, like in genomics, covariates are subject to measurement error. We study the impact of measurement error on linear regression with the lasso penalty, both analytically and in simulation experiments. A simple method of correction for measurement error in the lasso is then considered. In the large sample limit, the corrected lasso yields sign consistent covariate selection under conditions very similar to the lasso with perfect measurements, whereas the uncorrected lasso requires much more stringent conditions on the covariance structure of the data. Finally, we suggest methods to correct for measurement error in generalized linear models with the lasso penalty, which we study empirically in simulation experiments with logistic regression, and also apply to a classification problem with microarray data. We see that the corrected lasso selects less false positives than the standard lasso, at a similar level of true positives. The corrected lasso can therefore be used to obtain more conservative covariate selection in genomic analysis.

• Wyller, Vegard Bruun; Sørensen, Øystein; Sulheim, Dag; Fagermoen, Frode Even; Ueland, Thor & Mollnes, Tom Eirik (2015). Plasma cytokine expression in adolescent chronic fatigue syndrome. Brain, Behavior, and Immunity. ISSN 0889-1591. 46, p. 80–86. doi: 10.1016/j.bbi.2014.12.025. Full text in Research Archive Show summary

  Chronic fatigue syndrome (CFS) is a prevalent and disabling condition among adolescents. The pathophysiology is poorly understood, but low-grade systemic inflammation has been suggested as an important component. This study compared circulating levels of individual cytokines and parameters of cytokine networks in a large set of adolescent CFS patients and healthy controls, and explored associations between cytokines and symptoms in the CFS group. CFS patients (12–18 years old) were recruited nation-wide to a single referral center as part of the NorCAPITAL project (ClinicalTrials ID: NCT01040429). A broad case definition of CFS was applied, requiring three months of unexplained, disabling chronic/relapsing fatigue of new onset, whereas no accompanying symptoms were necessary. Thus, the case definition was broader than the Fukuda-criteria of CFS. Healthy controls having comparable distribution of gender and age were recruited from local schools. Twenty-seven plasma cytokines, including interleukins, chemokines and growth factors were assayed using multiplex technology. The results were subjected to network analyses using the ARACNE algorithm. Symptoms were charted by a questionnaire, and patients were subgrouped according to the Fukuda-criteria. A total of 120 CFS patients and 68 healthy controls were included. CFS patients had higher scores for fatigue (p < 0.001) and inflammatory symptoms (p < 0.001) than healthy controls. All cytokine levels and cytokine network parameters were similar, and none of the differences were statistically different across the two groups, also when adjusting for adherence to the Fukuda criteria of CFS. Within the CFS group, there were no associations between aggregate cytokine network parameters and symptom scores. Adolescent CFS patients are burdened by symptoms that might suggest low-grade systemic inflammation, but plasma levels of individual cytokines as well as cytokine network measures were not different from healthy controls, and there were no associations between symptoms and cytokine expression in the CFS group. Low-grade systemic inflammation does not appear to be a central part of adolescent CFS pathophysiology.

• Asprusten, Tarjei Tørre; Fagermoen, Frode Even; Sulheim, Dag; Skovlund, Eva; Sørensen, Øystein & Mollnes, Tom Eirik [Show all 7 contributors for this article] (2015). Study findings challenge the content validity of the Canadian Consensus Criteria for adolescent chronic fatigue syndrome. Acta Paediatrica. ISSN 0803-5253. 104(5), p. 498–503. doi: 10.1111/apa.12950. Full text in Research Archive

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• Grødem, Edvard Olaf Sætersdal; Vidal-Piñeiro, Didac; Sørensen, Øystein; Garrido, Pablo F.; Nyberg, Lars Erik & Walhovd, Kristine B [Show all 8 contributors for this article] (2025). Distinguishing Lifelong Individual Differences from Divergent Aging Trajectories of Adult Brain Volumes. bioRxiv (preprint article). 2025.05.26.655710. doi: 10.1101/2025.05.26.655710. Full text in Research Archive
• Roe, James Michael; Grydeland, Håkon; Slivka, Maksim; Sørensen, Øystein; Grødem, Edvard Olaf Sætersdal & Walhovd, Kristine B [Show all 8 contributors for this article] (2025). Cortical thickness changes precede high levels of amyloid by at least seven years. bioRxiv (preprint article). doi: 10.1101/2025.08.14.670398. Full text in Research Archive
• Strømstad, Marie Lorentsen; Fjell, Anders Martin; Walhovd, Kristine B; Vidal-Piñeiro, Didac & Sørensen, Øystein (2024). Longitudinal association between structural brain change and episodic memory change. Full text in Research Archive
• Sørensen, Øystein (2024). Nested Sequential Monte Carlo for the Bayesian Mallows Model. Full text in Research Archive
• Sørensen, Øystein (2024). Semiparametric latent variable modeling in R with 'galamm. Full text in Research Archive
• Sørensen, Øystein (2024). Presentasjon-. Online Bayesian Preference Learning. Full text in Research Archive
• Garrido, Pablo F.; Bråthen, Anne Cecilie Sjøli; Falch, Emilie Sogn; Kransberg, Jonas; Sørensen, Øystein & Walhovd, Kristine B (2024). A novel analysis approach to Mirror Tracing Task performance to detect fine-grained age-related differences. Alzheimer's & Dementia. ISSN 1552-5260. 20, p. e092273–e092273. doi: 10.1002/alz.092273. Full text in Research Archive
• Roe, James Michael; Vidal-Piñeiro, Didac; Sørensen, Øystein; Brandmaier, Andreas M.; Düzel, Sandra & Gonzalez, Hector A. [Show all 78 contributors for this article] (2022). Author Correction: Asymmetric thinning of the cerebral cortex across the adult lifespan is accelerated in Alzheimer’s disease (Nature Communications, (2021), 12, 1, (721), 10.1038/s41467-021-21057-y). Nature Communications. 13(1). doi: 10.1038/s41467-022-28514-2. Full text in Research Archive
• Sørensen, Øystein (2021). Longitudinal modeling of age-dependent latent traits. Full text in Research Archive
• Sørensen, Øystein (2021). A gentle introduction to Bayesian statistics. Full text in Research Archive
• Sørensen, Øystein (2021). Generalized additive latent and mixed models. Full text in Research Archive
• Sørensen, Øystein (2021). Longitudinal modeling of age-dependent latent traits with generalized additive latent and mixed models. Full text in Research Archive
• Sørensen, Øystein (2021). Get Your Results Faster With {future}. Full text in Research Archive
• Sørensen, Øystein (2020). Meta analysis of non-parametric models with {metagam}. Full text in Research Archive
• Vitelli, Valeria; Sørensen, Øystein; Frigessi, Arnoldo & Arjas, Elja (2018). Probabilistic preference learning with the Mallows rank model. Journal of Machine Learning Research. Full text in Research Archive

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