Background: It is increasingly recognized that the complex functions of human cognition are not accurately represented by arbitrarily-defined anatomical brain regions. Given the considerable functional specialization within such regions, more fine-grained studies of brain structure could capture such localized associations. However, such analyses/studies in a large community-dwelling population are lacking. Objective: To perform a fine-mapping of cognitive ability to cortical and subcortical grey matter on magnetic resonance imaging (MRI). Methods: In 3,813 stroke-free and non-demented persons from the Rotterdam Study (mean age 69.1 (±8.8) years; 55.8% women) with cognitive assessments and brain MRI, we performed voxel-based morphometry and subcortical shape analysis on global cognition and separate tests that tapped into memory, information processing speed, fine motor speed, and executive function domains. Results: We found that the different cognitive tests significantly associated with grey matter density in differential but also overlapping brain regions, primarily in the left hemisphere. Clusters of significantly associated voxels with global cognition were located within multiple anatomic regions: left amygdala, hippocampus, parietal lobule, superior temporal gyrus, insula and posterior temporal lobe. Subcortical shape analysis revealed associations primarily within the head and tail of the caudate nucleus, putamen, ventral part of the thalamus, and nucleus accumbens, more equally distributed among the left and right hemisphere. Within the caudate nucleus both positive (head) as well as negative (tail) associations were observed with global cognition. Conclusions: In a large population-based sample, we mapped cognitive performance to cortical and subcortical grey matter density using a hypothesis-free approach with high-dimensional neuroimaging. Leveraging the power of our large sample size, we confirmed well-known associations as well as identified novel brain regions related to cognition.

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.

Purpose: To investigate the association between N-terminal pro-Btype natriuretic peptide (NT-proBNP), which is a marker of heart disease, and markers of subclinical brain damage on magnetic resonance (MR) images in community-dwelling middle-aged and elderly subjects without dementia and without a clinical diagnosis of heart disease. Materials and Methods: This prospective population-based cohort study was approved by a medical ethics committee overseen by the national government, and all participants gave written informed consent. Serum levels of NT-proBNP were measured in 2397 participants without dementia or stroke (mean age, 56.6 years; age range, 45.7-87.3 years) and without clinical diagnosis of heart disease who were drawn from the population-based Rotterdam Study. All participants were examined with a 1.5-T MR imager. Multivariable linear and logistic regression analyses were used to investigate the association between NT-proBNP level and MR imaging markers of subclinical brain damage, including volumetric, focal, and microstructural markers. Results: A higher NT-proBNP level was associated with smaller total brain volume (mean difference in z score per standard deviation increase in NT-proBNP level, -0.021; 95% confidence interval [CI]: -0.034, -0.007; P = .003) and was predominantly driven by gray matter volume (mean difference in z score per standard deviation increase in NT-proBNP level, -0.037; 95% CI: -0.057, -0.017; P < .001). Higher NT-proBNP level was associated with larger white matter lesion volume (mean difference in z score per standard deviation increase in NT-proBNP level, 0.090; 95% CI: 0.051, 0.129; P < .001), with lower fractional anisotropy (mean difference in z score per standard deviation increase in NT-proBNP level, -0.048; 95% CI: -0.088, -0.008; P = .019) and higher mean diffusivity (mean difference in z score per standard deviation increase in NT-proBNP level, 0.054; 95% CI: 0.018, 0.091; P = .004) of normal-appearing white matter. Conclusion: In community-dwelling persons, higher serum NT-proBNP levels are associated with volumetric and microstructural MR imaging markers of subclinical brain damage.

White matter lesions play a role in cognitive decline and dementia. One presumed pathway is through disconnection of functional networks. Little is known about location-specific effects of lesions on functional connectivity. This study examined location-specific effects within anatomically-defined white matter tracts in 1584 participants of the Rotterdam Study, aged 50–95. Tracts were delineated from diffusion magnetic resonance images using probabilistic tractography. Lesions were segmented on fluid-attenuated inversion recovery images. Functional connectivity was defined across each tract on resting-state functional magnetic resonance images by using gray matter parcellations corresponding to the tract ends and calculating the correlation of the mean functional activity between the gray matter regions. A significant relationship between both local and brain-wide lesion load and tract-specific functional connectivity was found in several tracts using linear regressions, also after Bonferroni correction. Indirect connectivity analyses revealed that tract-specific functional connectivity is affected by lesions in several tracts simultaneously. These results suggest that local white matter lesions can decrease tract-specific functional connectivity, both in direct and indirect connections.