Explore the vast range of titles available.

Head motion during diffusion magnetic resonance imaging (MRI) scans can cause numerous artifacts and biases subsequent quantification. However, a thorough characterization of motion across multiple scans, cohorts, and consortiums has not been performed. To address this, we designed a study with three aims. First, we aimed to characterize subject motion across several large cohorts, utilizing 13 cohorts comprised of 16,995 imaging sessions (age 0.1–100 years, mean age = 63 years; 7220 females; 3175 cognitively impaired adults; 471 developmentally delayed children) to describe the magnitude and directions of subject movement. Second, we aimed to investigate whether state‐of‐the‐art diffusion preprocessing pipelines mitigate biases in quantitative measures of microstructure and connectivity by taking advantage of datasets with scan‐rescan acquisitions and ask whether there are detectable differences between the same subjects when scans and rescans have differing levels of motion. Third, we aimed to investigate whether there are structural connectivity differences between movers and non‐movers. We found that (1) subjects typically move 1–2 mm/min with most motion as translation in the anterior–posterior direction and rotation around the right–left axis; (2) Modern preprocessing pipelines can effectively mitigate motion to the point where biases are not detectable with current analysis techniques; and (3) There are no apparent differences in microstructure or macrostructural connections in participants who exhibit high motion versus those that exhibit low motion. Overall, characterizing motion magnitude and directions, as well as motion correlates, informs and improves motion mitigation strategies and image processing pipelines. We characterized motion during diffusion MRI scans across 16,995 image sessions and find that (1) modern preprocessing pipelines effectively mitigate motion to the point where biases are not detectable, and (2) that there are no apparent differences in microstructure or connectivity in volunteers who exhibit high motion versus those that exhibit low motion.

Limbic free‐water (FW)–corrected white matter (WM) integrity is heritable in late‐life aging Six genome‐wide loci discovered for limbic WM traits in Alzheimer's disease (AD)–enriched cohorts Chr18 locus implicates CDH19 , linking oligodendrocyte biology to WM microstructure RORA , FAM107B , and KC6 expression tracks cognitive decline and AD neuropathology

Introduction It is unclear how rates of white matter microstructural decline differ between normal aging and abnormal aging. Methods Diffusion MRI data from several well‐established longitudinal cohorts of aging (Alzheimer's Disease Neuroimaging Initiative [ADNI], Baltimore Longitudinal Study of Aging [BLSA], Vanderbilt Memory & Aging Project [VMAP]) were free‐water corrected and harmonized. This dataset included 1723 participants (age at baseline: 72.8 ± 8.87 years, 49.5% male) and 4605 imaging sessions (follow‐up time: 2.97 ± 2.09 years, follow‐up range: 1–13 years, mean number of visits: 4.42 ± 1.98). Differences in white matter microstructural decline in normal and abnormal agers was assessed. Results While we found a global decline in white matter in normal/abnormal aging, we found that several white matter tracts (e.g., cingulum bundle) were vulnerable to abnormal aging. Conclusions There is a prevalent role of white matter microstructural decline in aging, and future large‐scale studies in this area may further refine our understanding of the underlying neurodegenerative processes. HIGHLIGHTS Longitudinal data were free‐water corrected and harmonized. Global effects of white matter decline were seen in normal and abnormal aging. The free‐water metric was most vulnerable to abnormal aging. Cingulum free‐water was the most vulnerable to abnormal aging.

Introduction White matter microstructure may be abnormal along the Alzheimer's disease (AD) continuum. Methods Diffusion magnetic resonance imaging (dMRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI, n = 627), Baltimore Longitudinal Study of Aging (BLSA, n = 684), and Vanderbilt Memory & Aging Project (VMAP, n = 296) cohorts were free‐water (FW) corrected and conventional, and FW‐corrected microstructural metrics were quantified within 48 white matter tracts. Microstructural values were subsequently harmonized using the Longitudinal ComBat technique and inputted as independent variables to predict diagnosis (cognitively unimpaired [CU], mild cognitive impairment [MCI], AD). Models were adjusted for age, sex, race/ethnicity, education, apolipoprotein E (APOE) ε4 carrier status, and APOE ε2 carrier status. Results Conventional dMRI metrics were associated globally with diagnostic status; following FW correction, the FW metric itself exhibited global associations with diagnostic status, but intracellular metric associations were diminished. Discussion White matter microstructure is altered along the AD continuum. FW correction may provide further understanding of the white matter neurodegenerative process in AD. Highlights Longitudinal ComBat successfully harmonized large‐scale diffusion magnetic resonance imaging (dMRI) metrics. Conventional dMRI metrics were globally sensitive to diagnostic status. Free‐water (FW) correction mitigated intracellular associations with diagnostic status. The FW metric itself was globally sensitive to diagnostic status. Multivariate conventional and FW‐corrected models may provide complementary information.

•Greater annual rates of memory decline were associated with greater volume loss in multiple temporal and occipital regions.•Decline in verbal fluency was associated with greater ventricular size and decline in frontal, temporal, and parietal regions.•Decline in visuospatial ability was associated with volume loss in 3 temporal and parietal regions.•Declines in Trail-Making Test-A were associated with volume loss in 4 temporal and parietal regions.•Declines in Trail-Making Test-B were associated with ventricular size and volume loss in 10 regions. Investigation of relationships between age-related changes in regional brain volumes and changes in domain-specific cognition could provide insights into the neural underpinnings of individual differences in cognitive aging. Domain-specific cognition (memory, verbal fluency, visuospatial ability) and tests of executive function and attention (Trail-Making Test Part A and B) and 47 brain volumes of interest (VOIs) were assessed in 836 Baltimore Longitudinal Study of Aging participants with mean follow-up of 4.1 years (maximum 23.1 years). To examine the correlation between changes in domain-specific cognition and changes in brain volumes, we used bivariate linear mixed effects models with unstructured variance-covariance structure to estimate longitudinal trajectories for each variable of interest and correlations among the random effects of these measures. Higher annual rates of memory decline were associated with greater volume loss in 14 VOIs primarily within the temporal and occipital lobes. Verbal fluency decline was associated with greater ventricular enlargement and volume loss in 24 VOIs within the frontal, temporal, and parietal lobes. Decline in visuospatial ability was associated with volume loss in 3 temporal and parietal VOIs. Declines on the attentional test were associated with volume loss in 4 VOIs located within temporal and parietal lobes. Greater declines on the executive function test were associated with greater ventricular enlargement and volume loss in 10 frontal, parietal, and temporal VOIs. Our findings highlight domain-specific patterns of regional brain atrophy that may contribute to individual differences in cognitive aging.

Community detection on graphs constructed from functional magnetic resonance imaging (fMRI) data has led to important insights into brain functional organization. Large studies of brain community structure often include images acquired on multiple scanners across different studies. Differences in scanner can introduce variability into the downstream results, and these differences are often referred to as scanner effects. Such effects have been previously shown to significantly impact common network metrics. In this study, we identify scanner effects in data-driven community detection results and related network metrics. We assess a commonly employed harmonization method and propose new methodology for harmonizing functional connectivity that leverage existing knowledge about network structure as well as patterns of covariance in the data. Finally, we demonstrate that our new methods reduce scanner effects in community structure and network metrics. Our results highlight scanner effects in studies of brain functional organization and provide additional tools to address these unwanted effects. These findings and methods can be incorporated into future functional connectivity studies, potentially preventing spurious findings and improving reliability of results.

•We propose a bipartite graph model to quantify WM-GM FC network and its properties.•We assessed age effects on WM-GM FC network properties (N=1492, age=22–96y).•We found heterogeneous FC changes in lifespan but mainly declines in later years.•We found declined global efficiencies of major networks in lifespan or later years. The effects of normal aging on functional connectivity (FC) within various brain networks of gray matter (GM) have been well-documented. However, the age effects on the networks of FC between white matter (WM) and GM, namely WM-GM FC, remains unclear. Evaluating crucial properties, such as global efficiency (GE), for a WM-GM FC network poses a challenge due to the absence of closed triangle paths which are essential for assessing network properties in traditional graph models. In this study, we propose a bipartite graph model to characterize the WM-GM FC network and quantify these challenging network properties. Leveraging this model, we assessed the WM-GM FC network properties at multiple scales across 1,462 cognitively normal subjects aged 22–96 years from three repositories (ADNI, BLSA and OASIS-3) and investigated the age effects on these properties throughout adulthood and during late adulthood (age ≥70 years). Our findings reveal that (1) heterogeneous alterations occurred in region-specific WM-GM FC over the adulthood and decline predominated during late adulthood; (2) the FC density of WM bundles engaged in memory, executive function and processing speed declined with age over adulthood, particularly in later years; and (3) the GE of attention, default, somatomotor, frontoparietal and limbic networks reduced with age over adulthood, and GE of visual network declined during late adulthood. These findings provide unpresented insights into multi-scale alterations in networks of WM-GM functional synchronizations during normal aging. Furthermore, our bipartite graph model offers an extendable framework for quantifying WM-engaged networks, which may contribute to a wide range of neuroscience research.

Studies suggest that concussions may be related to increased risk of neurodegenerative diseases, such as Chronic Traumatic Encephalopathy and Alzheimer's Disease. Most neuroimaging studies show effects of concussions in frontal and temporal lobes of the brain, yet the long-term impacts of concussions on the aging brain have not been well studied. We examined neuroimaging data from 51 participants (mean age at first imaging visit=65.1 ± 11.23) in the Baltimore Longitudinal Study of Aging (BLSA) who reported a concussion in their medical history an average of 23 years prior to the first imaging visit, and compared them to 150 participants (mean age at first imaging visit=66.6 ± 10.97) with no history of concussion. Participants underwent serial structural MRI over a mean of 5.17±6.14 years and DTI over a mean of 2.92±2.22 years to measure brain structure, as well as 15O-water PET over a mean of 5.33±2.19 years to measure brain function. A battery of neuropsychological tests was also administered over a mean of 11.62±7.41 years. Analyses of frontal and temporal lobe regions were performed to examine differences in these measures between the concussion and control groups at first imaging visit and in change over time. Compared to those without concussion, participants with a prior concussion had greater brain atrophy in temporal lobe white matter and hippocampus at first imaging visit, which remained stable throughout the follow-up visits. Those with prior concussion also showed differences in white matter microstructure using DTI, including increased radial and axial diffusivity in the fornix/stria terminalis, anterior corona radiata, and superior longitudinal fasciculus at first imaging visit. In 15O-water PET, higher resting cerebral blood flow was seen at first imaging visit in orbitofrontal and lateral temporal regions, and both increases and decreases were seen in prefrontal, cingulate, insular, hippocampal, and ventral temporal regions with longitudinal follow-up. There were no significant differences in neuropsychological performance between groups. Most of the differences observed between the concussed and non-concussed groups were seen at the first imaging visit, suggesting that concussions can produce long-lasting structural and functional alterations in temporal and frontal regions of the brain in older individuals. These results also suggest that many of the reported short-term effects of concussion may still be apparent later in life.

INTRODUCTION The effects of sex and apolipoprotein E (APOE)—Alzheimer's disease (AD) risk factors—on white matter microstructure are not well characterized. METHODS Diffusion magnetic resonance imaging data from nine well‐established longitudinal cohorts of aging were free water (FW)–corrected and harmonized. This dataset included 4741 participants (age = 73.06 ± 9.75) with 9671 imaging sessions over time. FW and FW‐corrected fractional anisotropy (FAFWcorr) were used to assess differences in white matter microstructure by sex and APOE ε4 carrier status. RESULTS Sex differences in FAFWcorr in projection tracts and APOE ε4 differences in FW limbic and occipital transcallosal tracts were most pronounced. DISCUSSION There are prominent differences in white matter microstructure by sex and APOE ε4 carrier status. This work adds to our understanding of disparities in AD. Additional work to understand the etiology of these differences is warranted. Highlights Sex and apolipoprotein E (APOE) ε4 carrier status relate to white matter microstructural integrity. Females generally have lower free water–corrected fractional anisotropy compared to males. APOE ε4 carriers tended to have higher free water than non‐carriers.

INTRODUCTION White matter (WM) microstructure is essential for brain function but deteriorates with age and in neurodegenerative conditions such as Alzheimer's disease (AD). Diffusion MRI, enhanced by advanced bi‐tensor models accounting for free water (FW), enables in vivo quantification of WM microstructural differences. METHODS To evaluate how AD genetic risk factors affect limbic WM microstructure – crucial for memory and early impacted in disease – we conducted linear regression analyses in a cohort of 2,614 non‐Hispanic White aging adults (aged 50.12 to 100.85 years). The study evaluated 36 AD risk variants across 26 genes, the association between AD polygenic scores (PGSs) and WM metrics, and interactions with cognitive status. RESULTS AD PGSs, variants in TMEM106B, PTK2B, WNT3, and apolipoprotein E (APOE), and interactions involving MS4A6A were significantly linked to WM microstructure. DISCUSSION These findings implicate AD‐related genetic factors related to neurodevelopment (WNT3), lipid metabolism (APOE), and inflammation (TMEM106B, PTK2B, MS4A6A) that contribute to alternations in WM microstructure in older adults. Highlights AD risk variants in TMEM106B, PTK2B, WNT3, and APOE genes showed distinct associations with limbic FW‐corrected WM microstructure metrics. Interaction effects were observed between MS4A6A variants and cognitive status. PGS for AD was associated with higher FW content in the limbic system.