Faglige interesser
Jeg utvikler statistiske metoder og programvare for dataanalyse, inspirert av mine kollegers spennende datasett og problemstillinger.
Bakgrunn
Master of science, Biologisk fysikk, NMBU, 2011 PhD, Biostatistikk, UiO, 2015.
Emneord:
Kognitiv psykologi og nevropsykologi,
Nevrovitenskap,
Nevropsykologi,
Statistisk analyse,
Metode,
programvare,
Databehandling,
Senter for livsløpsendringer i hjerne og kognisjon
Publikasjoner
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Roe, James Michael; Vidal-Piñeiro, Didac; Sørensen, Øystein; Mowinckel, Athanasia Monika; Walhovd, Kristine B; Fjell, Anders Martin & Westerhausen, Rene (2021). Asymmetric thinning of the cerebral cortex across the adult lifespan is accelerated in Alzheimer’s Disease. Nature Communications.
ISSN 2041-1723.
. doi: https://doi.org/10.1101/2020.06.18.158980
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Normal aging and Alzheimer’s Disease (AD) are accompanied by large-scale alterations in brain organization that undermine brain function. Although hemispheric asymmetry is a global organizing feature of cortex thought to promote brain efficiency, current descriptions of cortical thinning in aging and AD have largely overlooked cortical asymmetry. Consequently, the foundational question of whether and where the cerebral hemispheres change at different rates in aging and AD remains open. First, applying vertex-wise data-driven clustering in a longitudinal discovery sample (aged 20-89; 2577 observations; 1851 longitudinal) we identified cortical regions exhibiting similar age-trajectories of asymmetry across the adult lifespan. Next, we sought replication in 4 independent longitudinal aging cohorts. We show that higher-order regions of cortex that exhibit pronounced asymmetry at age ~20 also show asymmetry change in aging. Results revealed that both leftward and rightward asymmetry is progressively lost on a similar time-scale across adult life. Hence, faster thinning of the (previously) thicker homotopic hemisphere is a feature of aging. This simple organizational principle showed high consistency across multiple aging cohorts in the Lifebrain consortium, and both the topological patterns and temporal dynamics of asymmetry-loss were markedly similar across replicating samples. Finally, we show that regions exhibiting gradual asymmetry-loss over healthy adult life exhibit faster asymmetry-change in AD. 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.06.18.158980; this version posted June 20, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Overall, our results suggest a system-wide breakdown in the adaptive asymmetric organization of cortex across adult life which is further accelerated in AD, and may implicate thickness asymmetry as a viable marker for declining hemispheric specialization in aging and AD.
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Sørensen, Øystein; Brandmaier, Andreas M.; Macià, Dídac; Ebmeier, Klaus; Ghisletta, Paolo; Kievit, Rogier A.; Mowinckel, Athanasia Monika; Walhovd, Kristine B; Westerhausen, Rene & Fjell, Anders Martin (2021). Meta-analysis of generalized additive models in neuroimaging studies. NeuroImage.
ISSN 1053-8119.
224 . doi:
10.1016/j.neuroimage.2020.117416
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Sørensen, Øystein; Mowinckel, Athanasia Monika; Walhovd, Kristine B; Westerhausen, Rene & Fjell, Anders Martin (2021). Meta-analysis of generalized additive models in neuroimaging studies. NeuroImage.
ISSN 1053-8119.
. doi: https://doi.org/10.1016/j.neuroimage.2020.117416
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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.
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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
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Fjell, Anders Martin; Sørensen, Øystein; Amlien, Inge Kasbohm; Bartrés-Faz, David; Brandmaier, Andreas M.; Buchmann, Nikolaus; Demuth, Ilja; Drevon, Christian A; Düzel, Sandra; Ebmeier, Klaus; Ghisletta, Paolo; Idland, Ane-Victoria; Kietzmann, Tim C; Kievit, Rogier A.; Kühn, Simone; Lindenberger, Ulman; Magnussen, Fredrik; Macià Bros, Didac; Mowinckel, Athanasia Monika; Nyberg, Lars Erik; Sexton, Claire E; Sole-Padulles, Cristina; Pudas, Sara; Roe, James Michael; Sederevicius, Donatas; Suri, Sana; Vidal-Piñeiro, Didac; Wagner, Gerd; Watne, Leiv Otto; Westerhausen, Rene; Zsoldos, Eniko & Walhovd, Kristine B (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.
s 1- 17 . doi:
10.1093/cercor/bhaa332
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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.
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Gorbach, Tetiana; Pudas, Sara; Bartrés-Faz, David; Brandmaier, Andreas M.; Düzel, Sandra; Henson, Rik; Idland, Ane-Victoria; Lindenberger, Ulman; Macià Bros, Didac; Mowinckel, Athanasia Monika; Solé-Padullés, Cristina; Sørensen, Øystein; Walhovd, Kristine B; Watne, Leiv Otto; Westerhausen, Rene; Fjell, Anders Martin & Nyberg, Lars Erik (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.
ISSN 2352-8729.
12(1) . doi: https://doi.org/10.1002/dad2.12110
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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.
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Idland, Ane-Victoria; Sala Llonch, Roser; Watne, Leiv; Brækhus, Anne; Hansson, Oskar; Blennow, Kaj; Zetterberg, Henrik; Sørensen, Øystein; Walhovd, Kristine B; Wyller, Torgeir Bruun & Fjell, Anders Martin (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, s 1- 15 . doi:
10.1016/j.neurobiolaging.2020.04.002
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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
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Sørensen, Øystein; Crispino, Marta; Liu, Qinghua & Vitelli, Valeria (2020). BayesMallows: An R Package for the Bayesian Mallows Model. The R Journal.
ISSN 2073-4859.
12(1), s 324- 342 . doi:
10.32614/RJ-2020-026
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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.
s 1- 24 . doi:
10.1080/1357650X.2020.1769124
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Vidal-Piñeiro, Didac; Parker, Nadine; Shin, Jean; French, Leon; Grydeland, Håkon; Jackowski, Andrea; Mowinckel, Athanasia Monika; Patel, Yash; Pausova, Zdenka; Salum, Giovanni; Sørensen, Øystein; Walhovd, Kristine B; Paus, Tomáš & Fjell, Anders Martin (2020). Cellular correlates of cortical thinning throughout the lifespan. Scientific Reports.
ISSN 2045-2322.
10(1), s 1- 14 . doi:
10.1038/s41598-020-78471-3
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Vidal-Piñeiro, Didac; Sneve, Markus Handal; Amlien, Inge Kasbohm; Grydeland, Håkon; Mowinckel, Athanasia Monika; Roe, James Michael; Sørensen, Øystein; Nyberg, Lars; Walhovd, Kristine B & Fjell, Anders Martin (2020). The Functional Foundations of Episodic Memory Remain Stable Throughout the Lifespan. Cerebral Cortex.
ISSN 1047-3211.
. doi:
10.1093/cercor/bhaa348
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Walhovd, Kristine B; Bråthen, Anne Cecilie Sjøli; Panizzon, Matthew S.; Mowinckel, Athanasia Monika; Sørensen, Øystein; de Lange, Ann-Marie Glasø; Krogsrud, Stine Kleppe; Håberg, Asta; Franz, Carol E.; Kremen, William S & Fjell, Anders Martin (2020). Within-session verbal learning slope is predictive of lifespan delayed recall, hippocampal volume, and memory training benefit, and is heritable. Scientific Reports.
ISSN 2045-2322.
10, s 1- 13 . doi:
10.1038/s41598-020-78225-1
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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.
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Fjell, Anders Martin; Sneve, Markus Handal; Sederevicius, Donatas; Sørensen, Øystein; Krogsrud, Stine Kleppe; Mowinckel, Athanasia Monika & Walhovd, Kristine B (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, s 1- 12 . doi:
10.1016/j.dcn.2019.100723
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Fjell, Anders Martin; Sørensen, Øystein; Amlien, Inge Kasbohm; Bartrés-Faz, David; Bros, Didac Macia; Buchmann, Nikolaus; Demuth, Ilja; Drevon, Christian A; duzel, Sandra; Ebmeier, K P; Idland, Ane-Victoria; Kietzmann, Tim C; Kievit, Rogier; Kühn, Simone; Lindenberger, Ulman; Mowinckel, Athanasia Monika; Nyberg, Lars Erik; Price, Darren; Sexton, Claire; Sole-Padulles, Cristina; Pudas, Sara; Sederevicius, Donatas; Suri, Sana; Wagner, Gerd; Watne, Leiv Otto; Westerhausen, René; Zsoldos, Eniko & Walhovd, Kristine B (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
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Sørensen, Øystein (2019). hdme: High-Dimensional Regression with Measurement Error. Journal of Open Source Software (JOSS).
ISSN 2475-9066.
. doi:
10.21105/joss.01404
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Sørensen, Øystein; Hellton, Kristoffer Herland; Frigessi Di Rattalma, Arnoldo & 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), s 739- 749 . doi:
10.1080/10618600.2018.1425626
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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.
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Vitelli, Valeria; Sørensen, Øystein; Crispino, Marta; Frigessi Di Rattalma, Arnoldo & Arjas, Elja (2018). Probabilistic preference learning with the Mallows rank model. Journal of machine learning research.
ISSN 1532-4435.
18, s 1- 49 Fulltekst i vitenarkiv.
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Asprusten, Tarjei Tørre; Fagermoen, Frode Even; Sulheim, Dag; Skovlund, Eva; Sørensen, Øystein; Mollnes, Tom Eirik & Wyller, Vegard Bruun (2015). Study findings challenge the content validity of the Canadian Consensus Criteria for adolescent chronic fatigue syndrome. Acta Paediatrica.
ISSN 0803-5253.
104(5), s 498- 503 . doi:
10.1111/apa.12950
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Sørensen, Øystein; Frigessi, Arnoldo & Thoresen, Magne (2015). Measurement error in Lasso: Impact and likelihood bias correction. Statistica sinica.
ISSN 1017-0405.
25(2), s 809- 829 . doi:
10.5705/ss.2013.180
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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, s 80- 86 . doi:
10.1016/j.bbi.2014.12.025
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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.
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Vitelli, Valeria; Sørensen, Øystein; Frigessi, Arnoldo & Arjas, Elja (2015). Probabilistic preference learning with the Mallows rank model.
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Publisert 22. jan. 2019 15:44
- Sist endret 24. jan. 2019 09:58