•Literature reports that long-term meditators show altered brain activations and structure.•Post-MBSR, prefrontal cortex, insula, cingulate cortex and hippocampus show similar results to traditional ...meditation.•In addition, the amygdala shows earlier deactivation, less gray matter and better connectivity.•These changes indicate a neuronal working mechanism of MBSR.
The objective of the current study was to systematically review the evidence of the effect of secular mindfulness techniques on function and structure of the brain. Based on areas known from traditional meditation neuroimaging results, we aimed to explore a neuronal explanation of the stress-reducing effects of the 8-week Mindfulness Based Stress Reduction (MBSR) and Mindfulness Based Cognitive Therapy (MBCT) program.
We assessed the effect of MBSR and MBCT (N=11, all MBSR), components of the programs (N=15), and dispositional mindfulness (N=4) on brain function and/or structure as assessed by (functional) magnetic resonance imaging. 21 fMRI studies and seven MRI studies were included (two studies performed both).
The prefrontal cortex, the cingulate cortex, the insula and the hippocampus showed increased activity, connectivity and volume in stressed, anxious and healthy participants. Additionally, the amygdala showed decreased functional activity, improved functional connectivity with the prefrontal cortex, and earlier deactivation after exposure to emotional stimuli.
Demonstrable functional and structural changes in the prefrontal cortex, cingulate cortex, insula and hippocampus are similar to changes described in studies on traditional meditation practice. In addition, MBSR led to changes in the amygdala consistent with improved emotion regulation. These findings indicate that MBSR-induced emotional and behavioral changes are related to functional and structural changes in the brain.
The Rotterdam Study is an ongoing prospective cohort study that started in 1990 in the city of Rotterdam, The Netherlands. The study aims to unravel etiology, preclinical course, natural history and ...potential targets for intervention for chronic diseases in mid-life and late-life. The study focuses on cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, otolaryngological, locomotor, and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. Since 2016, the cohort is being expanded by persons aged 40 years and over. The findings of the Rotterdam Study have been presented in over 1700 research articles and reports. This article provides an update on the rationale and design of the study. It also presents a summary of the major findings from the preceding 3 years and outlines developments for the coming period.
Gyrification of the cerebral cortex changes with aging and relates to development of cognitive function during early life and midlife. Little is known about how gyrification relates to age and ...cognitive function later in life. We investigated this in 4397 individuals (mean age: 63.5 years, range: 45.7 to 97.9) from the Rotterdam Study, a population-based cohort. Global and local gyrification were assessed from T1-weighted images. A measure for global cognition, the g-factor, was calculated from five cognitive tests. Older age was associated with lower gyrification (mean difference per year = −0.0021; 95% confidence interval = −0.0025; −0.0017). Non-linear terms did not improve the models. Age related to lower gyrification in the parietal, frontal, temporal and occipital regions, and higher gyrification in the medial prefrontal cortex. Higher levels of the g-factor were associated with higher global gyrification (mean difference per g-factor unit = 0.0044; 95% confidence interval = 0.0015; 0.0073). Age and the g-factor did not interact in relation to gyrification (p > 0.05). The g-factor bilaterally associated with gyrification in three distinct clusters. The first cluster encompassed the superior temporal gyrus, the insular cortex and the postcentral gyrus, the second cluster the lingual gyrus and the precuneus, and the third cluster the orbitofrontal cortex. These clusters largely remained statistically significant after correction for cortical surface area. Overall, the results support the notion that gyrification varies with aging and cognition during and after midlife, and suggest that gyrification is a potential marker for age-related brain and cognitive decline beyond midlife.
•Older age associates with lower cortical gyrification during and after midlife.•Age and gyrification relate linearly during adulthood, not non-linearly.•Gyrification of the medial prefrontal cortex increases with age after midlife.•Cognitive function associates with gyrification in the frontal and temporal lobes.
Many medical image segmentation methods are based on the supervised classification of voxels. Such methods generally perform well when provided with a training set that is representative of the test ...images to the segment. However, problems may arise when training and test data follow different distributions, for example, due to differences in scanners, scanning protocols, or patient groups. Under such conditions, weighting training images according to distribution similarity have been shown to greatly improve performance. However, this assumes that a part of the training data is representative of the test data; it does not make unrepresentative data more similar. We, therefore, investigate kernel learning as a way to reduce differences between training and test data and explore the added value of kernel learning for image weighting. We also propose a new image weighting method that minimizes maximum mean discrepancy (MMD) between training and test data, which enables the joint optimization of image weights and kernel. Experiments on brain tissue, white matter lesion, and hippocampus segmentation show that both kernel learning and image weighting, when used separately, greatly improve performance on heterogeneous data. Here, MMD weighting obtains similar performance to previously proposed image weighting methods. Combining image weighting and kernel learning, optimized either individually or jointly, can give a small additional improvement in performance.
Cerebral small vessel disease is increasingly linked to dementia.
We systematically searched Medline, Embase, and Cochrane databases for prospective population-based studies addressing associations ...of white matter hyperintensities, covert brain infarcts (i.e., clinically silent infarcts), and cerebral microbleeds with risk of all-dementia or Alzheimer's disease and performed meta-analyses.
We identified 11 studies on white matter hyperintensities, covert brain infarcts, or cerebral microbleeds with risk of all-dementia or Alzheimer's disease. Pooled analyses showed an association of white matter hyperintensity volume and a borderline association of covert brain infarcts with risk of all-dementia (hazard ratio: 1.39 95% confidence interval: 1.00; 1.94, N = 3913, and 1.47 95% confidence interval: 0.97; 2.22, N = 8296). Microbleeds were not statistically significantly associated with an increased risk of all-dementia (hazard ratio: 1.25 95% confidence interval: 0.66; 2.38, N = 8739).
White matter hyperintensities are associated with an increased risk of all-dementia and Alzheimer's disease in the general population. However, studies are warranted to further determine the role of markers of cerebral small vessel disease in dementia.
Structural brain markers are studied extensively in the field of neurodegeneration, but are thought to occur rather late in the process. Functional measures such as functional connectivity are ...gaining interest as potentially more subtle markers of neurodegeneration. However, brain structure and function are also affected by ‘normal’ brain ageing. More information is needed on how functional connectivity relates to aging, particularly in the absence of overt neurodegenerative disease. We investigated the association of age with resting-state functional connectivity in 2878 non-demented persons between 50 and 95 years of age (54.1% women) from the population-based Rotterdam Study. We obtained nine well-known resting state networks using data-driven methodology. Within the anterior default mode network, ventral attention network, and sensorimotor network, functional connectivity was significantly lower with older age. In contrast, functional connectivity was higher with older age within the visual network. Between resting state networks, we found patterns of both increases and decreases in connectivity in approximate equal proportions. Our results reinforce the notion that the aging brain undergoes a reorganization process, and serves as a solid basis for exploring functional connectivity as a preclinical marker of neurodegenerative disease.
•The aging brain undergoes a complex functional reorganization process.•Age is related to decreases in within-network functional connectivity and to widespread increases and decreases in (anti-)correlations between different networks.•This study forms a basis for exploring functional connectivity as a preclinical marker of neurodegenerative disease.
Imaging plays an essential role in research on neurological diseases in the elderly. The Rotterdam Scan Study was initiated as part of the ongoing Rotterdam Study with the aim to elucidate the causes ...of neurological disease by performing imaging of the brain in a prospective population-based setting. Initially, in 1995 and 1999, random subsamples of participants from the Rotterdam Study underwent neuroimaging, whereas from 2005 onwards MRI has been implemented into the core protocol of the Rotterdam Study. In this paper, we discuss the background and rationale of the Rotterdam Scan Study. Moreover, we describe the imaging protocol, image post-processing techniques, and the main findings to date. Finally, we provide recommendations for future research, which will also be topics of investigation in the Rotterdam Scan Study.
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