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Background: Neuroimaging plays an essential role in epidemiological studies and a special focus is directed towards the employment of versatile MRI acquisition and processing. The proposed multi‐purpose MRI protocol was designed for large‐scale and long‐term population neuroimaging and includes structural, diffusion‐weighted, and functional MRI modalities. It directly links the acquisition of an extensive set of MRI contrasts with fully automated data processing pipelines and quality assurance of the MRI data and image‐derived phenotypes. Method: The MRI acquisition protocol is largely based on in‐house developed MR sequences. With a total scan time below one hour per participant, it allows to acquire multiple MR contrasts at 3T with whole‐brain coverage and high isotropic image resolution, while keeping potential subject discomfort and motion artifacts at manageable levels. Designed to be kept constant, but also adaptive, the scan protocol separates into a core imaging protocol with MR contrasts of high relevance acquired for all study participants, and a free protocol to accommodate alternative promising MRI techniques in smaller sub‐populations. The analysis protocol handles large‐scale imaging data by means of fast and fully automated processing pipelines that incorporate state‐of‐the‐art image analysis tools and innovative machine learning methods, particularly using deep learning. Dedicated quality assessment (QA) includes visual rating and inspection for incidental findings on structural MRI and QA workflows tailored for each postprocessing pipeline to automatically identify problematic data based on the distribution of subject‐specific QA metrics with respect to the population average. Result: The MRI protocol has been successfully applied in the Rhineland Study, a prospective cohort study in Bonn, Germany, with currently over 10,000 participants. Image‐derived phenotypes include: global and regional brain tissue volume, thickness and surface measures from multi‐modal structural MRI, global and regional microstructural measures based on diffusion‐weighted MRI, brain functional connectivity using resting‐state functional MRI, and volumes of subcutaneous and visceral adipose tissue based on a single‐breathhold abdominal MRI (Figure 1). Conclusion: We present a versatile MRI protocol with acquisition and analysis methods that are generally applicable and not geared towards a specific disease or research question. Thus, this protocol may be of specific interest for many neuroimaging applications including population imaging studies. [ABSTRACT FROM AUTHOR]

Background: Neuroimaging plays an essential role in epidemiological studies and a special focus is directed towards the employment of versatile MRI acquisition and processing. The proposed multi‐purpose MRI protocol was designed for large‐scale and long‐term population neuroimaging and includes structural, diffusion‐weighted, and functional MRI modalities. It directly links the acquisition of an extensive set of MRI contrasts with fully automated data processing pipelines and quality assurance of the MRI data and image‐derived phenotypes. Method: The MRI acquisition protocol is largely based on in‐house developed MR sequences. With a total scan time below one hour per participant, it allows to acquire multiple MR contrasts at 3T with whole‐brain coverage and high isotropic image resolution, while keeping potential subject discomfort and motion artifacts at manageable levels. Designed to be kept constant, but also adaptive, the scan protocol separates into a core imaging protocol with MR contrasts of high relevance acquired for all study participants, and a free protocol to accommodate alternative promising MRI techniques in smaller sub‐populations. The analysis protocol handles large‐scale imaging data by means of fast and fully automated processing pipelines that incorporate state‐of‐the‐art image analysis tools and innovative machine learning methods, particularly using deep learning. Dedicated quality assessment (QA) includes visual rating and inspection for incidental findings on structural MRI and QA workflows tailored for each postprocessing pipeline to automatically identify problematic data based on the distribution of subject‐specific QA metrics with respect to the population average. Result: The MRI protocol has been successfully applied in the Rhineland Study, a prospective cohort study in Bonn, Germany, with currently over 10,000 participants. Image‐derived phenotypes include: global and regional brain tissue volume, thickness and surface measures from multi‐modal structural MRI, global and regional microstructural measures based on diffusion‐weighted MRI, brain functional connectivity using resting‐state functional MRI, and volumes of subcutaneous and visceral adipose tissue based on a single‐breathhold abdominal MRI (Figure 1). Conclusion: We present a versatile MRI protocol with acquisition and analysis methods that are generally applicable and not geared towards a specific disease or research question. Thus, this protocol may be of specific interest for many neuroimaging applications including population imaging studies. [ABSTRACT FROM AUTHOR]

Background: The human brain is a large‐scale network, which contains multiple segregated and functionally specialized systems. The organization of brain systems has been reported to change in a dedifferentiated way with increasing age. We investigated how age and sex are associated with brain system segregation during resting‐state in a large population‐based sample. Further, we analysed whether interindividual differences in the amount of brain system segregation are associated with cognitive and eye movement performance. Method: The analyses were based on 3,256 participants (30‐95 years) of the Rhineland Study, a community‐based cohort study in Bonn, Germany. Functional connectivity (FC) was extracted from 200 ROIs within 7 systems (control, default, visual, somatomotor, dorsal attention, ventral attention and limbic) using resting‐state functional MRI acquired from 3T Siemens MAGNETOM Prisma MRI scanners. Segregation index was calculated using a previously established measurement taking the difference between mean within‐system FC and mean between‐system FC as a portion of mean within‐system FC. We assessed cognitive performance with tests for memory, processing speed, executive function and crystallized intelligence and an eye movement test battery. We used multivariable regression models to assess the relation between brain segregation index and cognitive and eye movement performance with adjustment for possible confounders. Result: The global system segregation index decreased by 0.17 standard deviations (sd) per 10 years increase in age (95% confidence interval (CI): ‐0.19 – ‐0.14). Men had on average a 0.08 sd higher global system segregation index than women (95% CI: 0.02 – 0.15). Higher global system segregation was associated with higher performance in global cognition, processing speed, executive function, working memory and episodic verbal memory, and with lower crystallized intelligence. Additionally, higher global system segregation was associated with faster initiation of prosaccades and antisaccades. Conclusion: Higher system segregation is beneficial for cognitive and eye movement tasks that place demands on processing speed, executive function and working memory, but crystallized intelligence is better when segregation is lower. [ABSTRACT FROM AUTHOR]

Background: The human brain is a large‐scale network, which contains multiple segregated and functionally specialized systems. The organization of brain systems has been reported to change in a dedifferentiated way with increasing age. We investigated how age and sex are associated with brain system segregation during resting‐state in a large population‐based sample. Further, we analysed whether interindividual differences in the amount of brain system segregation are associated with cognitive and eye movement performance. Method: The analyses were based on 3,256 participants (30‐95 years) of the Rhineland Study, a community‐based cohort study in Bonn, Germany. Functional connectivity (FC) was extracted from 200 ROIs within 7 systems (control, default, visual, somatomotor, dorsal attention, ventral attention and limbic) using resting‐state functional MRI acquired from 3T Siemens MAGNETOM Prisma MRI scanners. Segregation index was calculated using a previously established measurement taking the difference between mean within‐system FC and mean between‐system FC as a portion of mean within‐system FC. We assessed cognitive performance with tests for memory, processing speed, executive function and crystallized intelligence and an eye movement test battery. We used multivariable regression models to assess the relation between brain segregation index and cognitive and eye movement performance with adjustment for possible confounders. Result: The global system segregation index decreased by 0.17 standard deviations (sd) per 10 years increase in age (95% confidence interval (CI): ‐0.19 – ‐0.14). Men had on average a 0.08 sd higher global system segregation index than women (95% CI: 0.02 – 0.15). Higher global system segregation was associated with higher performance in global cognition, processing speed, executive function, working memory and episodic verbal memory, and with lower crystallized intelligence. Additionally, higher global system segregation was associated with faster initiation of prosaccades and antisaccades. Conclusion: Higher system segregation is beneficial for cognitive and eye movement tasks that place demands on processing speed, executive function and working memory, but crystallized intelligence is better when segregation is lower. [ABSTRACT FROM AUTHOR]

Background: Neurofilament light (NfL) protein level is considered a non‐specific marker of neurodegeneration. NfL levels have been associated with established, non‐blood based neurodegenerative markers, including cognitive performance and reduced brain volume. However, most studies were small (N<300), and compared levels in patients (MCI, Alzheimer's disease) with those in healthy controls. We investigated to what extent NfL levels are associated with cognitive performance and MRI measures of brain volume and microstructure, in a large non‐demented population‐based sample. Method: The analyses were based on 4,578 participants (30‐95 years) of the Rhineland Study, a community‐based cohort study in Bonn, Germany. Plasma NfL levels were measured on the SIMOA platform. We assessed cognitive performance with tests for memory, processing speed, executive function and crystallized intelligence and an eye movement (EM) test battery. 3,206 persons underwent structural and diffusion weighted MR imaging. Imaging outcomes included volumetric measures (total brain, grey matter, white matter, hippocampus); diffusion tensor measures (fractional anisotropy; mean, radial, and axial diffusivity); and neurite orientation dispersion and density imaging (NODDI) measures. We used multivariable regression models to assess the relation between NfL levels and cognitive performance and MRI measures with adjustment for possible confounders. Result: Across all participants, we found only negligibly small associations between NfL levels and cognitive performance, brain volumetric and diffusion tensor measures. However, age‐stratified analyses revealed that in age 40‐49 and from age 60 onwards higher NfL levels were associated with lower orientation dispersion index (ODI). In the 70‐ to 79‐year‐olds, higher NfL levels were additionally associated with higher prosaccade accuracy, higher mean, axial and radial diffusivity, higher extracellular and lower intracellular volume fraction and a lower neurite density index. In the 80+‐year‐olds, NfL levels were negatively associated with hippocampal and white matter volume and positively associated with fractional anisotropy and radial diffusivity. Conclusion: Higher NfL levels were associated with smaller hippocampal volume and diffusion tensor and NODDI measures in older subjects. In younger persons (up to age 70 years), NfL levels were only associated with ODI. This suggests that NfL level is a sensitive marker of subtle changes in brain microstructure, especially in old age. [ABSTRACT FROM AUTHOR]