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  • 1.
    Gorbach, Tetiana
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Methods for longitudinal brain imaging studies with dropout2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    One of the challenges in aging research is to understand the brain mechanisms that underlie cognitive development in older adults. Such aging processes are investigated in longitudinal studies, where the within-individual changes over time are observed. However, several methodological issues exist in longitudinal analyses.  One of them is loss of participants to follow-up, which occurs when individuals drop out from the study. Such dropout should be taken into account for valid conclusions from longitudinal investigations, and this is the focus of this thesis. The developed methods are used to explore brain aging and its relation to cognition within the Betula longitudinal study of aging.

    Papers I and II consider the association between changes in brain structure and cognition. In the first paper, regression analysis is used to establish the statistical significance of brain-cognition associations while accounting for dropout. Paper II develops interval estimators directly for an association as measured by partial correlation, when some data are missing. The estimators of Paper II may be used in longitudinal as well as cross-sectional studies and are not limited to brain imaging. 

    Papers III and IV study functional brain connectivity, which is the statistical dependency between the functions of distinct brain regions. Typically, only brain regions with associations stronger than a predefined threshold are considered connected. However, the threshold is often arbitrarily set and does not reflect the individual differences in the overall connectivity patterns.  Paper III proposes a mixture model for brain connectivity without explicit thresholding of associations and suggests an alternative connectivity measure. Paper IV extends the mixture modeling of Paper III to a longitudinal setting with dropout and investigates the impact of ignoring the dropout mechanism on the quality of the inferences made on longitudinal connectivity changes.

  • 2.
    Gorbach, Tetiana
    et al.
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    de Luna, Xavier
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Inference for partial correlation when data are missing not at random2018In: Statistics and Probability Letters, ISSN 0167-7152, E-ISSN 1879-2103, Vol. 141, p. 82-89Article in journal (Refereed)
    Abstract [en]

    We introduce uncertainty regions to perform inference on partial correlations when data are missing not at random. These uncertainty regions are shown to have a desired asymptotic coverage. Their finite sample performance is illustrated via simulations and real data example. (C) 2018 Elsevier B.V. All rights reserved.

  • 3.
    Gorbach, Tetiana
    et al.
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Lundquist, Anders
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    de Luna, Xavier
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Salami, Alireza
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Wallenberg Centre for Molecular Medicine at Umeå University (WCMM). Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden; .
    A Hierarchical Bayesian Mixture Modeling Approach for Analysis of Resting-State Functional Brain Connectivity: An Alternative to ThresholdingManuscript (preprint) (Other academic)
  • 4.
    Gorbach, Tetiana
    et al.
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Lundquist, Anders
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    de Luna, Xavier
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Salami, Alireza
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Wallenberg Centre for Molecular Medicine at Umeå University (WCMM). Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden..
    Bayesian mixture modeling for longitudinal fMRI connectivity studies with dropoutManuscript (preprint) (Other academic)
  • 5.
    Gorbach, Tetiana
    et al.
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Pudas, Sara
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Lundquist, Anders
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Orädd, Greger
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Josefsson, Maria
    Umeå University, Faculty of Social Sciences, Centre for Demographic and Ageing Research (CEDAR).
    Salami, Alireza
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
    de Luna, Xavier
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Longitudinal association between hippocampus atrophy and episodic-memory decline2017In: Neurobiology of Aging, ISSN 0197-4580, E-ISSN 1558-1497, Vol. 51, p. 167-176Article in journal (Refereed)
    Abstract [en]

    There is marked variability in both onset and rate of episodic-memory decline in aging. Structural magnetic resonance imaging studies have revealed that the extent of age-related brain changes varies markedly across individuals. Past studies of whether regional atrophy accounts for episodic-memory decline in aging have yielded inconclusive findings. Here we related 15-year changes in episodic memory to 4-year changes in cortical and subcortical gray matter volume and in white-matter connectivity and lesions. In addition, changes in word fluency, fluid IQ (Block Design), and processing speed were estimated and related to structural brain changes. Significant negative change over time was observed for all cognitive and brain measures. A robust brain-cognition change-change association was observed for episodic-memory decline and atrophy in the hippocampus. This association was significant for older (65-80 years) but not middle-aged (55-60 years) participants and not sensitive to the assumption of ignorable attrition. Thus, these longitudinal findings highlight medial-temporal lobe system integrity as particularly crucial for maintaining episodic-memory functioning in older age. 

  • 6.
    Ruotsalainen, Ilona
    et al.
    Department of Psychology, Centre for Interdisciplinary Brain Research, University of Jyväskylä.
    Renvall, Ville
    Department of Neuroscience and Biomedical Engineering, Aalto University.
    Gorbach, Tetiana
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics. Department of Mathematics and Statistics, University of Jyväskylä, Jyväskylä, Finland.
    Syväoja, Heidi J.
    LIKES Research Centre for Physical Activity and Health, Jyväskylä, Finland.
    Tammelin, Tuija H.
    LIKES Research Centre for Physical Activity and Health, Jyväskylä, Finland.
    Karvanen, Juha
    Department of Mathematics and Statistics, University of Jyväskylä.
    Parviainen, Tiina
    Department of Psychology, Centre for Interdisciplinary Brain Research, University of Jyväskylä,.
    Aerobic fitness, but not physical activity, is associated with grey matter volume in adolescents2019In: Behavioural Brain Research, ISSN 0166-4328, E-ISSN 1872-7549, Vol. 362, p. 122-130Article in journal (Refereed)
    Abstract [en]

    Higher levels of aerobic fitness and physical activity are linked to beneficial effects on brain health, especially in older adults. The generalizability of these earlier results to young individuals is not straightforward, because physiological responses (such as cardiovascular responses) to exercise may depend on age. Earlier studies have mostly focused on the effects of either physical activity or aerobic fitness on the brain. Yet, while physical activity indicates the amount of activity, aerobic fitness is an adaptive state or attribute that an individual has or achieves. Here, by measuring both physical activity and aerobic fitness in the same study, we aimed to differentiate the association between these two measures and grey matter volume specifically. Magnetic resonance imaging scans were used to study volumes of 30 regions of interest located in the frontal, motor and subcortical areas of 60 adolescents (12.7–16.2 years old). Moderate-to-vigorous intensity physical activity (MVPA) was measured with hip-worn accelerometers and aerobic fitness was assessed with a 20-m shuttle run. Multiple regression analyses revealed a negative association between aerobic fitness and left superior frontal cortex volume and a positive association between aerobic fitness and the left pallidum volume. No associations were found between MVPA and any brain region of interest. These results demonstrate unequal contribution of physical activity and aerobic fitness on grey matter volumes, with inherent or achieved capacity (aerobic fitness) showing clearer associations than physical activity.

  • 7. Ruotsalainen, Ilona
    et al.
    Syväoja, Heidi
    Gorbach, Tetiana
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Karvanen, Juha
    Parviainen, Tiina
    Renvall, Ville
    Perkola, Jaana
    Physical activity, aerobic fitness and brain white matter: their role for executive functions in adolescenceManuscript (preprint) (Other academic)
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