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Age-related white matter microstructural differences partly mediate age-related decline in processing speed but not cognition
Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
Stockholm University.
Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
2012 (English)In: Biochimica et Biophysica Acta, ISSN 0006-3002, Vol. 1822, no 3, 408-415 p.Article in journal (Refereed) Published
Abstract [en]

Aging is associated with declining cognitive performance as well as structural changes in brain gray and white matter (WM). The WM deterioration contributes to a disconnection among distributed brain networks and may thus mediate age-related cognitive decline. The present diffusion tensor imaging (DTI) study investigated age-related differences in WM microstructure and their relation to cognition (episodic memory, visuospatial processing, fluency, and speed) in a large group of healthy subjects (n=287) covering 6 decades of the human life span. Age related decreases in fractional anisotropy (FA) and increases in mean diffusivity (MD) were observed across the entire WM skeleton as well as in specific WM tracts, supporting the WM degeneration hypothesis. The anterior section of the corpus callosum was more susceptible to aging compared to the posterior section, lending support to the anterior-posterior gradient of WM integrity in the corpus callosum. Finally, and of critical interest, WM integrity differences were found to mediate age-related reductions in processing speed but no significant mediation was found for episodic memory, visuospatial ability, or fluency. These findings suggest that compromised WM integrity is not a major contributing factor to declining cognitive performance in normal aging. This article is part of a Special Issue entitled: Imaging Brain Aging and Neurodegenerative disease.

Place, publisher, year, edition, pages
2012. Vol. 1822, no 3, 408-415 p.
Keyword [en]
white matter, cognition, aging, mediation, DTI
National Category
Neurosciences Physiology
URN: urn:nbn:se:umu:diva-47517DOI: 10.1016/j.bbadis.2011.09.001PubMedID: 21930202OAI: diva2:442727
Available from: 2011-09-22 Created: 2011-09-22 Last updated: 2013-10-28Bibliographically approved
In thesis
1. Decoding the complex brain: multivariate and multimodal analyses of neuroimaging data
Open this publication in new window or tab >>Decoding the complex brain: multivariate and multimodal analyses of neuroimaging data
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Functional brain images are extraordinarily rich data sets that reveal distributed brain networks engaged in a wide variety of cognitive operations. It is a substantial challenge both to create models of cognition that mimic behavior and underlying cognitive processes and to choose a suitable analytic method to identify underlying brain networks.

Most of the contemporary techniques used in analyses of functional neuroimaging data are based on univariate approaches in which single image elements (i.e. voxels) are considered to be computationally independent measures. Beyond univariate methods (e.g. statistical parametric mapping), multivariate approaches, which identify a network across all regions of the brain rather than a tessellation of regions, are potentially well suited for analyses of brain imaging data. A multivariate method (e.g. partial least squares) is a computational strategy that determines time-varying distributed patterns of the brain (as a function of a cognitive task). Compared to its univariate counterparts, a multivariate approach provides greater levels of sensitivity and reflects cooperative interactions among brain regions. Thus, by considering information across more than one measuring point, additional information on brain function can be revealed.

Similarly, by considering information across more than one measuring technique, the nature of underlying cognitive processes become well-understood. Cognitive processes have been investigated in conjunction with multiple neuroimaging modalities (e.g. fMRI, sMRI, EEG, DTI), whereas the typical method has been to analyze each modality separately. Accordingly, little work has been carried out to examine the relation between different modalities. Indeed, due to the interconnected nature of brain processing, it is plausible that changes in one modality locally or distally modulate changes in another modality.

This thesis focuses on multivariate and multimodal methods of image analysis applied to various cognitive questions. These methods are used in order to extract features that are inaccessible using univariate / unimodal analytic approaches. To this end, I implemented multivariate partial least squares analysis in study I and II in order to identify neural commonalities and differences between the available and accessible information in memory (study I), and also between episodic encoding and episodic retrieval (study II). Study I provided evidence of a qualitative differences between availability and accessibility signals in memory by linking memory access to modality-independent brain regions, and availability in memory to elevated activity in modality-specific brain regions. Study II provided evidence in support of general and specific memory operations during encoding and retrieval by linking general processes to the joint demands on attentional, executive, and strategic processing, and a process-specific network to core episodic memory function. In study II, III, and IV, I explored whether the age-related changes/differences in one modality were driven by age-related changes/differences in another modality. To this end, study II investigated whether age-related functional differences in hippocampus during an episodic memory task could be accounted for by age-related structural differences. I found that age-related local structural deterioration could partially but not entirely account for age-related diminished hippocampal activation. In study III, I sought to explore whether age-related changes in the prefrontal and occipital cortex during a semantic memory task were driven by local and/or distal gray matter loss. I found that age-related diminished prefrontal activation was driven, at least in part, by local gray matter atrophy, whereas the age-related decline in occipital cortex was accounted for by distal gray matter atrophy. Finally, in study IV, I investigated whether white matter (WM) microstructural differences mediated age-related decline in different cognitive domains. The findings implicated WM as one source of age-related decline on tasks measuring processing speed, but they did not support the view that age-related differences in episodic memory, visuospatial ability, or fluency were strongly driven by age-related differences in white-matter pathways.

Taken together, the architecture of different aspects of episodic memory (e.g. encoding vs. retrieval; availability vs. accessibility) was characterized using a multivariate partial least squares. This finding highlights usefulness of multivariate techniques in guiding cognitive theories of episodic memory. Additionally, competing theories of cognitive aging were investigated by multimodal integration of age-related changes in brain structure, function, and behavior. The structure-function relationships were specific to brain regions and cognitive domains. Finally, we urged that contemporary theories on cognitive aging need to be extended to longitudinal measures to be further validated.

Place, publisher, year, edition, pages
Umeå: Umeå University, 2012. 94 p.
Umeå University medical dissertations, ISSN 0346-6612 ; 1479
multivariate analysis, univariate analysis, multimodal imaging, episodic memory, aging, functional magnetic resonance imaging, diffusion tensor imaging
National Category
Research subject
biology; Psychology; Computerized Image Analysis
urn:nbn:se:umu:diva-51842 (URN)978-91-7459-362-4 (ISBN)
Public defence
2012-02-24, BiA 201, Biologihuset, Umeå, 09:00 (English)
Available from: 2012-02-03 Created: 2012-02-03 Last updated: 2012-10-19Bibliographically approved

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