Age-related changes in prefrontal white matter measured by diffusion tensor imaging

Mapping the impact of age and APOE risk factors for late onset Alzheimer's disease on long range brain connections through multiscale bundle analysis

Alzheimer's disease currently has no cure and is usually detected too late for interventions to be effective. In this study we have focused on cognitively normal subjects to study the impact of risk factors on their long-range brain connections. To detect vulnerable connections, we devised a multiscale, hierarchical method for spatial clustering of the whole brain tractogram and examined the impact of age and APOE allelic variation on cognitive abilities and bundle properties including texture e.g., mean fractional anisotropy, variability, and geometric properties including streamline length, volume, and shape, as well as asymmetry. We found that the third level subdivision in the bundle hierarchy provided the most sensitive ability to detect age and genotype differences associated with risk factors. Our results indicate that frontal bundles were a major age predictor, while the occipital cortex and cerebellar connections were important risk predictors that were heavily genotype dependent, and showed accelerated decline in fractional anisotropy, shape similarity, and increased asymmetry. Cognitive metrics related to olfactory memory were mapped to bundles, providing possible early markers of neurodegeneration. In addition, physiological metrics such as diastolic blood pressure were associated with changes in white matter tracts. Our novel method for a data driven analysis of sensitive changes in tractography may differentiate populations at risk for AD and isolate specific vulnerable networks.

Age-related fornix decline predicts conservative response strategy-based slowing in perceptual decision-making

Aging leads to response slowing but the underpinning cognitive and neural mechanisms remain elusive. We modelled older and younger adults' response times (RT) from a flanker task with a diffusion drift model (DDM) and employed diffusion-weighted magnetic resonance imaging and spectroscopy to study neurobiological predictors of DDM components (drift-rate, boundary separation, non-decision time). Microstructural indices were derived from white matter pathways involved in visuo-perceptual and attention processing [optic radiation, inferior and superior longitudinal fasciculi (ILF, SLF), fornix]. Estimates of metabolite concentrations [N-acetyl aspartate (NAA), glutamate (Glx), and γ-aminobutyric acid (GABA), creatine (Cr), choline (Cho), myoinositol (mI)] were measured from occipital (OCC), anterior cingulate (ACC) and posterior parietal cortices (PPC). Age-related increases in RT, boundary separation, and non-decision time were observed with response conservatism acounting for RT slowing. Aging was associated with reductions in white matter microstructure (lower fractional anisotropy and restricted signal fraction, larger diffusivities) and in metabolites (NAA in ACC and PPC, Glx in ACC). Regression analyses identified brain regions involved in top-down (fornix, SLF, ACC, PPC) and bottom-up (ILF, optic radiation OCC) processing as predictors for DDM parameters and RT. Fornix FA was the strongest predictor for increases in boundary separation (beta = -0.8) and mediated the effects of age on RT. These findings demonstrate that response slowing in visual discrimination is driven by the adoption of a more conservative response strategy. Age-related fornix decline may result in noisier communication of contextual information from the hippocampus to anterior decision-making regions and thus contribute to the conservative response strategy shift.

Diffusion MRI data analysis assisted by deep learning synthesized anatomical images (DeepAnat)

Diffusion MRI is a useful neuroimaging tool for non-invasive mapping of human brain microstructure and structural connections. The analysis of diffusion MRI data often requires brain segmentation, including volumetric segmentation and cerebral cortical surfaces, from additional high-resolution T1-weighted (T1w) anatomical MRI data, which may be unacquired, corrupted by subject motion or hardware failure, or cannot be accurately co-registered to the diffusion data that are not corrected for susceptibility-induced geometric distortion. To address these challenges, this study proposes to synthesize high-quality T1w anatomical images directly from diffusion data using convolutional neural networks (CNNs) (entitled "DeepAnat"), including a U-Net and a hybrid generative adversarial network (GAN), and perform brain segmentation on synthesized T1w images or assist the co-registration using synthesized T1w images. The quantitative and systematic evaluations using data of 60 young subjects provided by the Human Connectome Project (HCP) show that the synthesized T1w images and results for brain segmentation and comprehensive diffusion analysis tasks are highly similar to those from native T1w data. The brain segmentation accuracy is slightly higher for the U-Net than the GAN. The efficacy of DeepAnat is further validated on a larger dataset of 300 more elderly subjects provided by the UK Biobank. Moreover, the U-Nets trained and validated on the HCP and UK Biobank data are shown to be highly generalizable to the diffusion data from Massachusetts General Hospital Connectome Diffusion Microstructure Dataset (MGH CDMD) acquired with different hardware systems and imaging protocols and therefore can be used directly without retraining or with fine-tuning for further improved performance. Finally, it is quantitatively demonstrated that the alignment between native T1w images and diffusion images uncorrected for geometric distortion assisted by synthesized T1w images substantially improves upon that by directly co-registering the diffusion and T1w images using the data of 20 subjects from MGH CDMD. In summary, our study demonstrates the benefits and practical feasibility of DeepAnat for assisting various diffusion MRI data analyses and supports its use in neuroscientific applications.

Aging compromises oligodendrocyte precursor cell maturation and efficient remyelination in the monkey brain

Age-associated cognitive decline is common among otherwise healthy elderly people, even in the absence of Alzheimer's disease and neuron loss. Instead, white matter loss and myelin damage are strongly associated with cognitive decline. Myelin is subject to lifelong oxidative stress that damages the myelin sheath, which is repaired by cells of the oligodendrocyte lineage. This process is mediated by oligodendrocyte precursor cells (OPCs) that sense the damage and respond by proliferating locally and migrating to the region, where they differentiate into mature myelinating oligodendrocytes. In aging, extensive myelin damage, in combination with inefficient remyelination, leads to chronically damaged myelin and loss of efficient neuronal conduction. This study used the rhesus monkey model of normal aging to examine how myelin regeneration capacity is affected by age. Results show that older subjects have reduced numbers of new BCAS1 + myelinating oligodendrocytes, which are newly formed cells, and that this reduction is associated with poorer cognitive performance. Interestingly, this does not result from limited proliferation of progenitor OPCs. Instead, the transcription factor NKX2.2, which regulates OPCs differentiation, is significantly decreased in aged OPCs. This suggests that these OPCs have a diminished potential for differentiation into mature oligodendrocytes. In addition, mature oligodendrocytes have reduced RNA expression of two essential myelin protein markers, MBP and PLP. These data collectively suggest that in the normal aging brain, there is a reduction in regenerative OPCs as well as myelin production that impairs the capacity for remyelination.

Diffusion tensor imaging of superficial prefrontal white matter in healthy aging

The prefrontal cortex (PFC) is a heterogenous structure that is highly susceptible to the effects of aging. Few studies have investigated age effects on the superficial white matter (WM) contained within the PFC using in-vivo magnetic resonance imaging (MRI). This study used diffusion tensor imaging (DTI) tractography to examine the effects of age, sex, and intracranial volume (ICV) on superficial WM within specific PFC subregions, and to model the relationships with age using higher order polynomial regression modelling. PFC WM of 140 healthy individuals, aged 18-85, was segmented into medial and lateral orbitofrontal, medial prefrontal, and dorsolateral prefrontal subregions. Differences due to age in microstructural parameters such as fractional anisotropy (FA), axial and radial diffusivities, and macrostructural measures of tract volumes, fiber counts, average fiber lengths, and average number of fibers per voxel were examined. We found that most prefrontal subregions demonstrated age effects, with decreases in FA, tract volume, and fiber counts, and increases in all diffusivity measures. Age relationships were mostly non-linear, with higher order regressions chosen in most cases. Declines in PFC FA began at the onset of adulthood while the greatest changes in diffusivity and volume did not occur until middle age. The effects of age were most prominent in medial tracts while the lateral orbitofrontal tracts were less affected. Significant effects of sex and ICV were also observed in certain parameters. The patterns mostly followed myelination order, with late-myelinating prefrontal subregions experiencing earlier and more pronounced age effects, further supporting the frontal theory of aging.

Automated detection of axonal damage along white matter tracts in acute severe traumatic brain injury

New techniques for individualized assessment of white matter integrity are needed to detect traumatic axonal injury (TAI) and predict outcomes in critically ill patients with acute severe traumatic brain injury (TBI). Diffusion MRI tractography has the potential to quantify white matter microstructure in vivo and has been used to characterize tract-specific changes following TBI. However, tractography is not routinely used in the clinical setting to assess the extent of TAI, in part because focal lesions reduce the robustness of automated methods. Here, we propose a pipeline that combines automated tractography reconstructions of 40 white matter tracts with multivariate analysis of along-tract diffusion metrics to assess the presence of TAI in individual patients with acute severe TBI. We used the Mahalanobis distance to identify abnormal white matter tracts in each of 18 patients with acute severe TBI as compared to 33 healthy subjects. In all patients for which a FreeSurfer anatomical segmentation could be obtained (17 of 18 patients), including 13 with focal lesions, the automated pipeline successfully reconstructed a mean of 37.5 ± 2.1 white matter tracts without the need for manual intervention. A mean of 2.5 ± 2.1 tracts resulted in partial or failed reconstructions and needed to be reinitialized upon visual inspection. The pipeline detected at least one abnormal tract in all patients (mean: 9.1 ± 7.9) and accurately discriminated between patients and controls (AUC: 0.91). The number and neuroanatomic location of abnormal tracts varied across patients and levels of consciousness. The premotor, temporal, and parietal sections of the corpus callosum were the most commonly damaged tracts (in 10, 9, and 8 patients, respectively), consistent with prior histopathological studies of TAI. TAI measures were not associated with concurrent behavioral measures of consciousness. In summary, we provide proof-of-principle evidence that an automated tractography pipeline has translational potential to detect and quantify TAI in individual patients with acute severe TBI.

Potential brain recovery of frontostriatal circuits in heroin users after prolonged abstinence: A preliminary study

Neuroscientists have devoted efforts to explore potential brain recovery after prolonged abstinence in heroin users (HU). However, not much is known about whether frontostriatal circuits can recover after prolonged abstinence in HU. An eight-month longitudinal study was carried out for HU. Two MRI scans were obtained at baseline (HU1) and 8-month follow-up (HU2). The functional and structural connectivities of dorsal and ventral frontostriatal pathways were measured by resting-state functional connectivity (RSFC) and diffusion tensor imaging (DTI). Correlation analyses were employed to reveal the associations between neuroimaging and behavioral changes. Results suggested that relative to healthy controls (HCs), HU1 showed lower fractional anisotropy (FA) in the right dorsolateral prefrontal cortex (DLPFC)-to-caudate tracts and medial orbitofrontal cortex (mOFC)-to-nucleus accumbens (NAc) tracts as well as decreased RSFC in the left mOFC-NAc circuits. Longitudinal results revealed reduced craving and enhanced cognitive control in HU2 compared with HU1. After prolonged abstinence, HU2 showed increased FA values in the right DLPFC-caudate and mOFC-NAc tracts as well as increased RSFC strength in the bilateral mOFC-NAc circuits compared with HU1. In addition, changes in RSFC and FA values in the right mOFC-NAc circuit were negatively correlated with craving score changes. Similarly, negative correlations were also found between changes of RSFC in the bilateral DLPFC-caudate circuits and TMT-A scores. We provided scientific evidence for brain recovery of the dorsal and ventral frontostriatal circuits in HU after prolonged abstinence, and these circuits may be potential neuroimaging biomarkers for cognition and craving changes.

Volume of the posterior hippocampus mediates age-related differences in spatial context memory and is correlated with increased activity in lateral frontal, parietal and occipital regions in healthy aging

Healthy aging is associated with episodic memory decline, particularly in the ability to encode and retrieve object-context associations (context memory). Neuropsychological and neuroimaging studies have highlighted the importance of the medial temporal lobes (MTL) in supporting episodic memory across the lifespan. However, given the functional heterogeneity of the MTL, volumetric declines in distinct regions may impact performance on specific episodic memory tasks, and affect the function of the large-scale neurocognitive networks supporting episodic memory encoding and retrieval. In the current study, we investigated how MTL structure may mediate age-related differences in performance on spatial and temporal context memory tasks, in a sample of 125 healthy adults aged 19-76 years old. Standard T1-weighted MRIs were segmented into the perirhinal, entorhinal and parahippocampal cortices, as well as the anterior and posterior hippocampal subregions. We observed negative linear and quadratic associations between age and volume of the parahippocampal cortex, and anterior and posterior hippocampal subregions. We also found that volume of the posterior hippocampus fully mediated the association between age and spatial, but not temporal context memory performance. Further, we employed a multivariate behavior partial-least-squares analysis to assess how age and regional MTL volumes correlated with brain activity during the encoding and retrieval of spatial context memories. We found that greater activity within lateral prefrontal, parietal, and occipital regions, as well as within the anterior MTL was related to older age and smaller volume of the posterior hippocampus. Our results highlight the heterogeneity of MTL contributions to episodic memory across the lifespan and provide support for the posterior-anterior shift in aging, and scaffolding theory of aging and cognition.

Overview of (f)MRI Studies of Cognitive Aging for Non-Experts: Looking through the Lens of Neuroimaging

This special issue concerning Brain Functional and Structural Connectivity and Cognition aims to expand our understanding of brain connectivity. Herein, I review related topics including the principle and concepts of functional MRI, brain activation, and functional/structural connectivity in aging for uninitiated readers. Visuospatial attention, one of the well-studied functions in aging, is discussed from the perspective of neuroimaging.

SDnDTI: Self-supervised deep learning-based denoising for diffusion tensor MRI

Diffusion tensor magnetic resonance imaging (DTI) is a widely adopted neuroimaging method for the in vivo mapping of brain tissue microstructure and white matter tracts. Nonetheless, the noise in the diffusion-weighted images (DWIs) decreases the accuracy and precision of DTI derived microstructural parameters and leads to prolonged acquisition time for achieving improved signal-to-noise ratio (SNR). Deep learning-based image denoising using convolutional neural networks (CNNs) has superior performance but often requires additional high-SNR data for supervising the training of CNNs, which reduces the feasibility of supervised learning-based denoising in practice. In this work, we develop a self-supervised deep learning-based method entitled "SDnDTI" for denoising DTI data, which does not require additional high-SNR data for training. Specifically, SDnDTI divides multi-directional DTI data into many subsets of six DWI volumes and transforms DWIs from each subset to along the same diffusion-encoding directions through the diffusion tensor model, generating multiple repetitions of DWIs with identical image contrasts but different noise observations. SDnDTI removes noise by first denoising each repetition of DWIs using a deep 3-dimensional CNN with the average of all repetitions with higher SNR as the training target, following the same approach as normal supervised learning based denoising methods, and then averaging CNN-denoised images for achieving higher SNR. The denoising efficacy of SDnDTI is demonstrated in terms of the similarity of output images and resultant DTI metrics compared to the ground truth generated using substantially more DWI volumes on two datasets with different spatial resolutions, b-values and numbers of input DWI volumes provided by the Human Connectome Project (HCP) and the Lifespan HCP in Aging. The SDnDTI results preserve image sharpness and textural details and substantially improve upon those from the raw data. The results of SDnDTI are comparable to those from supervised learning-based denoising and outperform those from state-of-the-art conventional denoising algorithms including BM4D, AONLM and MPPCA. By leveraging domain knowledge of diffusion MRI physics, SDnDTI makes it easier to use CNN-based denoising methods in practice and has the potential to benefit a wider range of research and clinical applications that require accelerated DTI acquisition and high-quality DTI data for mapping of tissue microstructure, fiber tracts and structural connectivity in the living human brain.

Along-tract analysis of the white matter is more informative about brain ageing, compared to whole-tract analysis

Diffusion Tensor Imaging (DTI) enabled the investigation of brain White Matter (WM), both qualitatively to study the macrostructure, and quantitatively to study the microstructure. The quantitative analyses are mostly performed at the whole-tract level, i.e., providing one measure of interest per tract; however, along-tract approaches may provide finer details of the quality of the WM tracts. In this study, using the DWI data collected from 40 young and 40 old individuals, we compared the DTI measures of FA, MD, AD, and RD, estimated by both whole-tract and along-tract approaches in 18 WM bundles, between the two groups. The results of the whole-tract quantitative analysis showed a statistically significant (p-FWER < 0.05) difference between the old and young groups in 6 tracts for FA, 8 tracts for MD, 1 tract for AD, and 7 tracts for RD. On the contrary, the along-tract approach showed differences between the two groups in 10 tracts for FA, 14 tracts for MD, 8 tracts for AD, and 11 tracts for RD. All the differences between the along-tract measures of the two groups had a large effect size (Cohen'd > 0.80). This study showed that the along-tract approach for the analysis of brain WM reveals changes in some WM tracts which had not shown any changes in the whole-tract approach, and therefore this finding emphasizes the utilization of the along-tract approach along with the whole-tract method for a more accurate study of the brain WM.

Alterations in Diffusion Measures of White Matter Integrity Associated with Healthy Aging

This study aimed to characterize age-related white matter changes by evaluating patterns of overlap between the linear association of age with fractional anisotropy (FA) with mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD). Specifically, we assessed patterns of overlap between diffusion measures of normal appearing white matter by covarying for white matter hyperintensity (WMH) load, as WMHs are thought to increase with age and impact diffusion measures. Seventy-nine healthy adults aged between 18 and 75 years took part in the study. Diffusion tensor imaging (DTI) data were based on 61 directions acquired with a b-value of 2,000. We found five main patterns of overlap: FA alone (15.95%); FA and RD (31.90%); FA and AD (12.99%); FA, RD, and AD (27.93%); and FA, RD, and MD (8.79%). We showed that cognitively healthy aging adults had low WMH load, which subsequently had minimal effect on diffusion measures. We discuss how patterns of overlap may reflect underlying biological changes observed with aging such as loss of myelination, axonal damage, as well as mild microstructural and chronic white matter impairments. This study contributes to understanding the underlying causes of degeneration in specific regions of the brain and highlights the importance of considering the impact of WMHs in aging studies of white matter.

Conductance-Based Structural Brain Connectivity in Aging and Dementia

Background: Structural brain connectivity has been shown to be sensitive to the changes that the brain undergoes during Alzheimer's disease (AD) progression. Methods: In this work, we used our recently proposed structural connectivity quantification measure derived from diffusion magnetic resonance imaging, which accounts for both direct and indirect pathways, to quantify brain connectivity in dementia. We analyzed data from the second phase of Alzheimer's Disease Neuroimaging Initiative and third release in the Open Access Series of Imaging Studies data sets to derive relevant information for the study of the changes that the brain undergoes in AD. We also compared these data sets to the Human Connectome Project data set, as a reference, and eventually validated externally on two cohorts of the European DTI Study in Dementia database. Results: Our analysis shows expected trends of mean conductance with respect to age and cognitive scores, significant age prediction values in aging data, and regional effects centered among subcortical regions, and cingulate and temporal cortices. Discussion: Results indicate that the conductance measure has prediction potential, especially for age, that age and cognitive scores largely overlap, and that this measure could be used to study effects such as anticorrelation in structural connections. Impact statement This work presents a methodology and a set of analyses that open new possibilities in the study of healthy and pathological aging. The methodology used here is sensitive to direct and indirect pathways in deriving brain connectivity measures from diffusion-weighted magnetic resonance imaging, and therefore provides information that many state-of-the-art methods do not account for. As a result, this technique may provide the research community with ways to detect subtle effects of healthy aging and Alzheimer's disease.

MRI of healthy brain aging: A review

We present a review of the characterization of healthy brain aging using MRI with an emphasis on morphology, lesions, and quantitative MR parameters. A scope review found 6612 articles encompassing the keywords "Brain Aging" and "Magnetic Resonance"; papers involving functional MRI or not involving imaging of healthy human brain aging were discarded, leaving 2246 articles. We first consider some of the biogerontological mechanisms of aging, and the consequences of aging in terms of cognition and onset of disease. Morphological changes with aging are reviewed for the whole brain, cerebral cortex, white matter, subcortical gray matter, and other individual structures. In general, volume and cortical thickness decline with age, beginning in mid-life. Prevalent silent lesions such as white matter hyperintensities, microbleeds, and lacunar infarcts are also observed with increasing frequency. The literature regarding quantitative MR parameter changes includes T₁ , T₂ , T₂ *, magnetic susceptibility, spectroscopy, magnetization transfer, diffusion, and blood flow. We summarize the findings on how each of these parameters varies with aging. Finally, we examine how the aforementioned techniques have been used for age prediction. While relatively large in scope, we present a comprehensive review that should provide the reader with sound understanding of what MRI has been able to tell us about how the healthy brain ages.

A Frontal Account of False Alarms

Prior research has demonstrated that the frontal lobes play a critical role in the top-down control of behavior, and damage to the frontal cortex impairs performance on tasks that require executive control [Burgess, P. W., & Stuss, D. T. Fifty years of prefrontal cortex research: Impact on assessment. Journal of the International Neuropsychological Society, 23, 755-767, 2017; Stuss, D. T., & Levine, B. Adult clinical neuropsychology: Lessons from studies of the frontal lobes. Annual Review of Psychology, 53, 401-433, 2002]. Across executive functioning tasks, performance deficits are often quantified as the number of false alarms per total number of nontarget trials. However, most studies of frontal lobe function focus on individual task performance and do not discuss commonalities of errors committed across different tasks. Here, we describe a neurocognitive account that explores the link between deficient frontal lobe function and increased false alarms across an array of experimental tasks from a variety of task domains. We review evidence for heightened false alarms following frontal deficits in episodic long-term memory tests, working memory tasks (e.g., n-back), attentional tasks (e.g., continuous performance tasks), interference control tasks (e.g., recent probes), and inhibitory control tasks (e.g., go/no-go). We examine this relationship via neuroimaging studies, lesion studies, and across age groups and pathologies that impact the pFC, and we propose 11 issues in cognitive processing that can result in false alarms. In our review, some overlapping neural regions were implicated in the regulation of false alarms. Ultimately, however, we find evidence for the fractionation and localization of certain frontal processes related to the commission of specific types of false alarms. We outline avenues for additional research that will enable further delineation of the fractionation of the frontal lobes' regulation of false alarms.

Comparing the effect of cognitive vs. exercise training on brain MRI outcomes in healthy older adults: A systematic review

Aging is associated with cognitive decline. Importantly cognition and cerebral health is enhanced with interventions like cognitive (CT) and exercise training (ET). However, effects of CT and ET interventions on brain magnetic resonance imaging outcomes have never been compared systematically. Here, the primary objective was to critically and systematically compare CT to ET in healthy older adults on brain MRI outcomes. A total of 38 studies were included in the final review. Although results were mixed, patterns were identified: CT showed improvements in white matter microstructure, while ET demonstrated macrostructural enhancements, and both demonstrated changes to task-based BOLD signal changes. Importantly, beneficial effects for cognitive and cerebral outcomes were observed by almost all, regardless of intervention type. Overall, it is suggested that future work include more than one MRI outcome, and report all results including null. To better understand the MRI changes associated with CT or ET, more studies explicitly comparing interventions within the same domain (i.e. resistance vs. aerobic) and between domains (i.e. CT vs. ET) are needed.

The Daily Activity Study of Health (DASH): A pilot randomized controlled trial to enhance physical activity in sedentary older adults

Sedentary behavior increases the risk for multiple chronic diseases, early mortality, and accelerated cognitive decline in older adults. Interventions to reduce sedentary behavior among older adults are needed to improve health outcomes and reduce the burden on healthcare systems. We designed a randomized controlled trial that uses a self-affirmation manipulation and gain-framed health messaging to effectively reduce sedentary behavior in older adults. This message-based intervention lasts 6 weeks, recruiting 80 healthy but sedentary older adults from the community, between the ages of 60 and 95 years. Participants are randomly assigned to one of two groups: 1) an intervention group, which receives self-affirmation followed by gain-framed health messages daily or 2) a control group, which receives daily loss-framed health messages only. Objective physical activity engagement is measured by accelerometers. Accelerometers are deployed a week before, during, and the last week of intervention to examine potential changes in sedentary time and physical activity engagement. Participants undertake structural and functional (resting and task-based) MRI scans, neuropsychological tests, computerized behavioral measures, and neurobehavioral inventories at baseline and after the intervention. A 3-month follow-up assesses the long-term maintenance of any engendered behaviors from the intervention period. This study will assess the effectiveness of a novel behavioral intervention at reducing sedentarism in older adults and examine the neurobehavioral mechanisms underlying any such changes.

Generalizing Longitudinal Age Effects on Brain Structure - A Two-Study Comparison Approach

Cross-sectional studies indicate that normal aging is accompanied by decreases in brain structure. Longitudinal studies, however, are relatively rare and inconsistent regarding their outcomes. Particularly the heterogeneity of methods, sample characteristics and the high inter-individual variability in older adults prevent the deduction of general trends. Therefore, the current study aimed to compare longitudinal age-related changes in brain structure (measured through cortical thickness) in two large independent samples of healthy older adults (n = 161 each); the Longitudinal Healthy Aging Brain (LHAB) database project at the University of Zurich, Switzerland, and 1000BRAINS at the Research Center Juelich, Germany. Annual percentage changes in the two samples revealed stable to slight decreases in cortical thickness over time. After correction for major covariates, i.e., baseline age, sex, education, and image quality, sample differences were only marginally present. Results suggest that general trends across time might be generalizable over independent samples, assuming the same methodology is used, and similar sample characteristics are present.

Age- and memory- related differences in hippocampal gray matter integrity are better captured by NODDI compared to single-tensor diffusion imaging

Single-tensor diffusion imaging (DTI) has traditionally been used to assess integrity of white matter. For example, we previously showed that integrity of limbic white matter tracts declines in healthy aging and relates to episodic memory performance. However, multi-compartment diffusion models may be more informative about microstructural properties of gray matter. The current study examined hippocampal gray matter integrity using both single-tensor and multi-compartment (neurite orientation dispersion and density imaging, NODDI) diffusion imaging. Younger (20-38 years) and older (59-84 years) adults also completed the Mnemonic Similarity Task to measure mnemonic discrimination performance. Results revealed age-related declines in both single-tensor (lower fractional anisotropy, higher mean diffusivity) and multi-compartment (higher restricted, hindered and free diffusion) measures of hippocampal gray matter integrity. As expected, NODDI measures (hindered and free diffusion) captured more age-related variance than DTI measures. Moreover, mnemonic discrimination of highly similar lure items in memory was related to hippocampal gray matter integrity in younger but not older adults. These findings support the notion that age-related differences in gray matter integrity are better captured by multi-compartment versus single-tensor diffusion models and show that the relationship between mnemonic discrimination and hippocampal gray matter integrity is moderated by age.

DeepDTI: High-fidelity six-direction diffusion tensor imaging using deep learning

Diffusion tensor magnetic resonance imaging (DTI) is unsurpassed in its ability to map tissue microstructure and structural connectivity in the living human brain. Nonetheless, the angular sampling requirement for DTI leads to long scan times and poses a critical barrier to performing high-quality DTI in routine clinical practice and large-scale research studies. In this work we present a new processing framework for DTI entitled DeepDTI that minimizes the data requirement of DTI to six diffusion-weighted images (DWIs) required by conventional voxel-wise fitting methods for deriving the six unique unknowns in a diffusion tensor using data-driven supervised deep learning. DeepDTI maps the input non-diffusion-weighted (b ​= ​0) image and six DWI volumes sampled along optimized diffusion-encoding directions, along with T1-weighted and T2-weighted image volumes, to the residuals between the input and high-quality output b = 0 image and DWI volumes using a 10-layer three-dimensional convolutional neural network (CNN). The inputs and outputs of DeepDTI are uniquely formulated, which not only enables residual learning to boost CNN performance but also enables tensor fitting of resultant high-quality DWIs to generate orientational DTI metrics for tractography. The very deep CNN used by DeepDTI leverages the redundancy in local and non-local spatial information and across diffusion-encoding directions and image contrasts in the data. The performance of DeepDTI was systematically quantified in terms of the quality of the output images, DTI metrics, DTI-based tractography and tract-specific analysis results. We demonstrate rotationally-invariant and robust estimation of DTI metrics from DeepDTI that are comparable to those obtained with two b ​= ​0 images and 21 DWIs for the primary eigenvector derived from DTI and two b ​= ​0 images and 26-30 DWIs for various scalar metrics derived from DTI, achieving 3.3-4.6 × ​acceleration, and twice as good as those of a state-of-the-art denoising algorithm at the group level. The twenty major white-matter tracts can be accurately identified from the tractography of DeepDTI results. The mean distance between the core of the major white-matter tracts identified from DeepDTI results and those from the ground-truth results using 18 ​b ​= ​0 images and 90 DWIs measures around 1-1.5 ​mm. DeepDTI leverages domain knowledge of diffusion MRI physics and power of deep learning to render DTI, DTI-based tractography, major white-matter tracts identification and tract-specific analysis more feasible for a wider range of neuroscientific and clinical studies.

Microstructure of Human Corpus Callosum across the Lifespan: Regional Variations in Axon Caliber, Density, and Myelin Content

The myeloarchitecture of the corpus callosum (CC) is characterized as a mosaic of distinct differences in fiber density of small- and large-diameter axons along the anterior-posterior axis; however, regional and age differences across the lifespan are not fully understood. Using multiecho T2 magnetic resonance imaging combined with multi-T2 fitting, the myelin water fraction (MWF) and geometric-mean of the intra-/extracellular water T2 (geomT2IEW) in 395 individuals (7-85 years; 41% males) were examined. The approach was validated where regional patterns along the CC closely resembled the histology; MWF matched mean axon diameter and geomT2IEW mirrored the density of large-caliber axons. Across the lifespan, MWF exhibited a quadratic association with age in all 10 CC regions with evidence of a positive linear MWF-age relationship among younger participants and minimal age differences in the remainder of the lifespan. Regarding geomT2IEW, a significant linear age × region interaction reflected positive linear age dependence mostly prominent in the regions with the highest density of small-caliber fibers-genu and splenium. In all, these two indicators characterize distinct attributes that are consistent with histology, which is a first. In addition, these results conform to rapid developmental progression of CC myelination leveling in middle age as well as age-related degradation of axon sheaths in older adults.

A Systematic Review of the Application of Functional Near-Infrared Spectroscopy to the Study of Cerebral Hemodynamics in Healthy Aging

Positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) studies have shown that healthy aging is associated with functional brain deterioration that preferentially affects the prefrontal cortex. This article reviews the application of an alternative method, functional near-infrared spectroscopy (fNIRS), to the study of age-related changes in cerebral hemodynamics and factors that influence cerebral hemodynamics in the elderly population. We conducted literature searches in PudMed and PsycINFO, and selected only English original research articles that used fNIRS to study healthy individuals with a mean age of ≥ 55 years. All articles were published in peer-reviewed journals between 1977 and May 2019. We synthesized 114 fNIRS studies examining hemodynamic changes that occurred in the resting state and during the tasks of sensation and perception, motor control, semantic processing, word retrieval, attentional shifting, inhibitory control, memory, and emotion and motivation in healthy older adults. This review, which was not registered in a registry, reveals an age-related reduction in resting-state cerebral oxygenation and connectivity in the prefrontal cortex. It also shows that aging is associated with a reduction in functional hemispheric asymmetry and increased compensatory activity in the frontal lobe across multiple task domains. In addition, this article describes the beneficial effects of healthy lifestyles and the detrimental effects of cardiovascular disease risk factors on brain functioning among nondemented older adults. Limitations of this review include exclusion of gray and non-English literature and lack of meta-analysis. Altogether, the fNIRS literature provides some support for various neurocognitive aging theories derived from task-based PET and fMRI studies. Because fNIRS is relatively motion-tolerant and environmentally unconstrained, it is a promising tool for fostering the development of aging biomarkers and antiaging interventions.

Changes Over Time of Diffusion MRI in the White Matter of Aging Brain, a Good Predictor of Verbal Recall

Objective: Extensive research using water-diffusion MRI reported age-related modifications of cerebral White Matter (WM). Moreover, water-diffusion parameter modifications have been frequently associated with cognitive performances in the elderly sample, reinforcing the idea of aging inducing microstructural disconnection of the brain which in turn impacts cognition. However, only few studies really assessed over-time modifications of these parameters and their relationship with episodic memory outcome of elderly. Materials and Methods: One-hundred and thirty elderly subjects without dementia (74.1 ± 4.1 years; 47% female) were included in this study. Diffusion tensor imaging (DTI) was performed at two-time points (3.49 ± 0.68 years apart), allowing the assessment of changes in water-diffusion parameters over time using a specific longitudinal pipeline. White matter hyperintensity (WMH) burden and gray matter (GM) atrophy were also measured on FLAIR and T1-weighted sequences collected during these two MRI sessions. Free and cued verbal recall scores assessed at the last follow-up of the cohort were used as episodic memory outcome. Changes in water-diffusion parameters over time were included in serial linear regression models to predict retrieval or storage ability of elderly. Results: GM atrophy and an increase in mean diffusivity (MD) and WMH load between the two-time points were observed. The increase in MD was significantly correlated with WMH load and the different memory scores. In models accounting for the baseline cognitive score, GM atrophy, or WMH load, MD changes still significantly predict free verbal recall, and not total verbal recall, suggesting the specific association with the retrieval deficit in healthy aging. Conclusion: In elderly, microstructural WM changes are good predictors of lower free verbal recall performances. Moreover, this contribution is not only driven by WMH load increase. This last observation is in line with studies reporting early water-diffusion modification in WM tissue during aging, resulting lately in the appearance of WMH on conventional MRI.

Altered diffusion in motor white matter tracts in psychosis patients with catatonia

Catatonia is a complex psychomotor symptom frequently observed in schizophrenia. Neural activity within the motor system is altered in catatonia. Likewise, white matter (WM) is also expected to be abnormal. The aim of this study was to test, if schizophrenia patients with catatonia show specific WM alterations. Forty-eight patients with schizophrenia and 43 healthy controls were included. Catatonia was currently present in 13 patients with schizophrenia. Tract-Based Spatial Statistics was used to test for differences in fractional anisotropy (FA) in the whole brain between the three groups. We detected a group effect (F-test) of WM within the corpus callosum (CC). In the t-test, patients with catatonia showed higher FA in many left lateralized WM clusters involved in motor behaviour compared to patients without catatonia, including the CC, internal and external capsule, superior longitudinal fascicle (SLF) and corticospinal tract (CST). Similarly, patients with catatonia showed also higher FA in the left internal capsule and left CST compared to healthy controls. In contrast, the group comparison between patients without catatonia and healthy controls revealed lower FA in many right lateralized clusters, comprising the CC, internal capsule, SLF, and inferior longitudinal fascicle in patients without catatonia. Our results are in line with the notion of an altered motor system in catatonia. Thus, our study provides evidence for increased WM connectivity, especially in motor tracts in schizophrenia patients with catatonia.

Age-Related Decline in the Topological Efficiency of the Brain Structural Connectome and Cognitive Aging

Brain disconnection model has been proposed as a possible neural mechanism for cognitive aging. However, the relationship between structural connectivity degeneration and cognitive decline with normal aging remains unclear. In the present study, using diffusion MRI and tractography techniques, we report graph theory-based analyses of the brain structural connectome in a cross-sectional, community-based cohort of 633 cognitively healthy elderly individuals. Comprehensive neuropsychological assessment of the elderly subjects was performed. The association between age, brain structural connectome, and cognition across elderly individuals was examined. We found that the topological efficiency, modularity, and hub integration of the brain structural connectome exhibited a significant decline with normal aging, especially in the frontal, parietal, and superior temporal regions. Importantly, network efficiency was positively correlated with attention and executive function in elderly subjects and had a significant mediation effect on the age-related decline in these cognitive functions. Moreover, nodal efficiency of the brain structural connectome showed good performance for the prediction of attention and executive function in elderly individuals. Together, our findings revealed topological alterations of the brain structural connectome with normal aging, which provides possible structural substrates underlying cognitive aging and sensitive imaging markers for the individual prediction of cognitive functions in elderly subjects.

Brain status modeling with non-negative projective dictionary learning

Accurate prediction of individuals' brain age is critical to establish a baseline for normal brain development. This study proposes to model brain development with a novel non-negative projective dictionary learning (NPDL) approach, which learns a discriminative representation of multi-modal neuroimaging data for predicting brain age. Our approach encodes the variability of subjects in different age groups using separate dictionaries, projecting features into a low-dimensional manifold such that information is preserved only for the corresponding age group. The proposed framework improves upon previous discriminative dictionary learning methods by incorporating orthogonality and non-negativity constraints, which remove representation redundancy and perform implicit feature selection. We study brain development on multi-modal brain imaging data from the PING dataset (N = 841, age = 3-21 years). The proposed analysis uses our NDPL framework to predict the age of subjects based on cortical measures from T1-weighted MRI and connectome from diffusion weighted imaging (DWI). We also investigate the association between age prediction and cognition, and study the influence of gender on prediction accuracy. Experimental results demonstrate the usefulness of NDPL for modeling brain development.

Brain structure and cognitive ability in healthy aging: a review on longitudinal correlated change

Little is still known about the neuroanatomical substrates related to changes in specific cognitive abilities in the course of healthy aging, and the existing evidence is predominantly based on cross-sectional studies. However, to understand the intricate dynamics between developmental changes in brain structure and changes in cognitive ability, longitudinal studies are needed. In the present article, we review the current longitudinal evidence on correlated changes between magnetic resonance imaging-derived measures of brain structure (e.g. gray matter/white matter volume, cortical thickness), and laboratory-based measures of fluid cognitive ability (e.g. intelligence, memory, processing speed) in healthy older adults. To theoretically embed the discussion, we refer to the revised Scaffolding Theory of Aging and Cognition. We found 31 eligible articles, with sample sizes ranging from n = 25 to n = 731 (median n = 104), and participant age ranging from 19 to 103. Several of these studies report positive correlated changes for specific regions and specific cognitive abilities (e.g. between structures of the medial temporal lobe and episodic memory). However, the number of studies presenting converging evidence is small, and the large methodological variability between studies precludes general conclusions. Methodological and theoretical limitations are discussed. Clearly, more empirical evidence is needed to advance the field. Therefore, we provide guidance for future researchers by presenting ideas to stimulate theory and methods for development.

Amyloid, Vascular, and Resilience Pathways Associated with Cognitive Aging

OBJECTIVE

To investigate the multifactorial processes underlying cognitive aging based on the hypothesis that multiple causal pathways and mechanisms (amyloid, vascular, and resilience) influence longitudinal cognitive decline in each individual through worsening brain health.

METHODS

We identified 1,230 elderly subjects (aged ≥50 years) with an average of 4.9 years of clinical follow-up and with amyloid positron emission tomography, diffusion tensor imaging, and structural magnetic resonance imaging scans from the population-based Mayo Clinic Study of Aging. We examined imaging markers of amyloid and brain health (white matter microstructural integrity and cortical thinning), systemic vascular health preceding the imaging markers, and early to midlife intellectual enrichment to predict longitudinal cognitive trajectories. We used latent growth curve models for modeling longitudinal cognitive decline.

RESULTS

All the pathways (amyloid, vascular, resilience) converged through their effects on cortical thinning and worsening cognition and together explained patterns in cognitive decline. Resilience and vascular pathways (aging process, sex differences, education/occupation, and systemic vascular health) had significant impact on white matter microstructural integrity. Education/occupation levels contributed to white matter integrity through systemic vascular health. Worsening white matter integrity contributed to significant cortical thinning and subsequently longitudinal cognitive decline. Baseline amyloidosis contributed to a significant proportion of cognitive decline that accelerated with longer follow-up times, and its primary impact was through cortical thinning.

INTERPRETATION

We developed an integrated framework to help explain the dynamic and complex process of cognitive aging by considering key causal pathways. Such an approach is important for both better comprehension of cognitive aging processes and will aid in the development of successful intervention strategies. ANN NEUROL 2019;86:866-877.

White Matter Language Pathways and Language Performance in Healthy Adults Across Ages

The goal of this study was to determine the relationship between age-related white matter changes, with a specific focus on previously identified language pathways, and language functioning in healthy aging. 228 healthy participants (126 female; 146 right-handed), ages 18 to 76, underwent 3.0 Tesla MR diffusion weighted imaging (DWI) and a battery of language assessments including the Boston Naming Test (BNT), the Peabody Picture Vocabulary Test (PPVT), the Controlled Oral Word Association Test (COWAT), Semantic Fluency Test (SFT), and a subset of the Boston Diagnostic Aphasia Examination (CI-BDAE). Using tract based spatial statistics (TBSS), we investigated measurements of fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD). TBSS was used to create a white matter skeleton that was then used to analyze white matter changes (indexed by FA, AD, RD, and MD) with age and language performance. Results focused primarily on significant relationships (p < 0.05, cluster-wise FDR corrected for multiple comparisons) in the canonical language white matter pathways. We found a diffuse linear decrease with age in global white matter FA and a significant focal increase in FA with age within the bilateral superior cerebellar peduncles (SCPs). We observed that increased BNT scores were associated with increased FA within the left SLF, and within the posterior and antero-lateral portions of the right inferior frontal-occipital fasciculus (IFOF). Increased SFT and PPVT scores were associated with increased FA within the posterior portion of the right IFOF and increased FA within the left body of the corpus callosum was associated with lower COWAT scores. We found no association between FA and BDAE. MD, RD, and AD, were found to be inversely proportional to FA within the IFOF, with AD showing a negative correlation with SFT, and RD and MD showing a negative correlation with BNT. There was no association between CI-BDAE and any of the white matter measures. Significant differences between sexes included more pronounced FA decrease with age within the right SLF in males vs. females; there were no differences in language performance scores between sexes. We also found that there was no decline in language testing scores with increasing age in our cohort. Taken together, our findings of varying relationships between DTI metrics and language function within multiple regions of the non-dominant IFOF suggest that more robust language networks with bilateral structural connectivity may contribute to better overall language functioning, regardless of age.

Association of white matter microstructural integrity with cognition and dementia

Late-life measures of white matter (WM) microstructural integrity may predict cognitive status, cognitive decline, and incident mild cognitive impairment (MCI) or dementia. We considered participants of the Atherosclerosis Risk in Communities study who underwent cognitive assessment and neuroimaging in 2011-2013 and were followed through 2016-2017 (n = 1775 for analyses of prevalent MCI and dementia, baseline cognitive performance, and longitudinal cognitive change and n = 889 for analyses of incident MCI, dementia, or death). Cross-sectionally, both overall WM fractional anisotropy and overall WM mean diffusivity were strongly associated with baseline cognitive performance and risk of prevalent MCI or dementia. Longitudinally, greater overall WM mean diffusivity was associated with accelerated cognitive decline, as well as incident MCI, incident dementia, and mortality, but WM fractional anisotropy was not robustly associated with cognitive change or incident cognitive impairment. Both cross-sectional and longitudinal associations were attenuated after additionally adjusting for likely downstream pathologic changes. Increased WM mean diffusivity may provide an early indication of dementia pathogenesis.

Age-Dependent Signal Intensity Changes in the Structurally Normal Pediatric Brain on Unenhanced T1-Weighted MR Imaging

BACKGROUND AND PURPOSE

Various pathologic and nonpathologic states result in brain parenchymal signal intensity changes on unenhanced T1-weighted MR imaging. However, the absence of quantitative data to characterize typical age-related signal intensity values limits evaluation. We sought to establish a range of age-dependent brain parenchymal signal intensity values on unenhanced T1WI in a sample of individuals (18 years of age or younger) with structurally normal brains.

MATERIALS AND METHODS

A single-center retrospective study was performed. Gadolinium-naïve pediatric patients with structurally normal MR brain imaging examination findings were analyzed (n = 114; 50% female; age range, 68 days to 18 years). ROI signal intensity measurements were obtained from the globus pallidus, thalamus, dentate nucleus, pons, and frontal lobe cortex and subcortical white matter. Multivariable linear regression was used to analyze the relationship between signal intensity values and age.

RESULTS

Results demonstrated a statistically significant association between signal intensity values and linear age in all neuroanatomic areas tested, except the frontal gray matter, (P < .01). There were no statistically significant differences attributable to patient sex.

CONCLUSIONS

Age-dependent signal intensity values were determined on unenhanced T1WI in structurally normal pediatric brains. Increased age correlated with increased signal intensity in all brain locations, except the frontal gray matter, irrespective of sex. The biologic mechanisms underlying our results remain unclear and may be related to chronologic changes in myelin density, synaptic density, and water content. Establishing age-dependent signal intensity parameters in the structurally normal pediatric brain will help clarify developmental aberrations and enhance gadolinium-deposition research by providing an improved understanding of the confounding effect of age.

The goddess who spins the thread of life: Klotho, psychiatric stress, and accelerated aging

BACKGROUND

Longevity gene klotho (KL) is associated with age-related phenotypes but has not been evaluated against a direct human biomarker of cellular aging. We examined KL and psychiatric stress, including posttraumatic stress disorder (PTSD), which is thought to potentiate accelerated aging, in association with biomarkers of cellular aging.

METHODS

The sample comprised 309 white, non-Hispanic genotyped veterans with measures of epigenetic age (DNA methylation age), telomere length (n = 252), inflammation (C-reactive protein), psychiatric symptoms, metabolic function, and white matter neural integrity (diffusion tensor imaging; n = 185). Genotyping and DNA methylation were obtained on epi/genome-wide beadchips.

RESULTS

In gene by environment analyses, two KL variants (rs9315202 and rs9563121) interacted with PTSD severity (peak corrected p = 0.044) and sleep disturbance (peak corrected p = 0.034) to predict advanced epigenetic age. KL variant, rs398655, interacted with self-reported pain in association with slowed epigenetic age (corrected p = 0.048). A well-studied protective variant, rs9527025, was associated with slowed epigenetic age (p = 0.046). The peak PTSD interaction term (with rs9315202) also predicted C-reactive protein (p = 0.049), and white matter microstructural integrity in two tracts (corrected ps = 0.005 - 0.035). This SNP evidenced a main effect with an index of metabolic syndrome severity (p = 0.015). Effects were generally accentuated in older subjects.

CONCLUSIONS

Rs9315202 predicted multiple biomarkers of cellular aging such that psychiatric stress was more strongly associated with cellular aging in those with the minor allele. KL genotype may contribute to a synchronized pathological aging response to stress and could be a therapeutic target to alter the pace of cellular aging.

Functional and/or structural brain changes in response to resistance exercises and resistance training lead to cognitive improvements - a systematic review

BACKGROUND

During the aging process, physical capabilities (e.g., muscular strength) and cognitive functions (e.g., memory) gradually decrease. Regarding cognitive functions, substantial functional (e.g., compensatory brain activity) and structural changes (e.g., shrinking of the hippocampus) in the brain cause this decline. Notably, growing evidence points towards a relationship between cognition and measures of muscular strength and muscle mass. Based on this emerging evidence, resistance exercises and/or resistance training, which contributes to the preservation and augmentation of muscular strength and muscle mass, may trigger beneficial neurobiological processes and could be crucial for healthy aging that includes preservation of the brain and cognition. Compared with the multitude of studies that have investigated the influence of endurance exercises and/or endurance training on cognitive performance and brain structure, considerably less work has focused on the effects of resistance exercises and/or resistance training. While the available evidence regarding resistance exercise-induced changes in cognitive functions is pooled, the underlying neurobiological processes, such as functional and structural brain changes, have yet to be summarized. Hence, the purpose of this systematic review is to provide an overview of resistance exercise-induced functional and/or structural brain changes that are related to cognitive functions.

METHODS AND RESULTS

A systematic literature search was conducted by two independent researchers across six electronic databases; 5957 records were returned, of which 18 were considered relevant and were analyzed.

SHORT CONCLUSION

Based on our analyses, resistance exercises and resistance training evoked substantial functional brain changes, especially in the frontal lobe, which were accompanied by improvements in executive functions. Furthermore, resistance training led to lower white matter atrophy and smaller white matter lesion volumes. However, based on the relatively small number of studies available, the findings should be interpreted cautiously. Hence, future studies are required to investigate the underlying neurobiological mechanisms and to verify whether the positive findings can be confirmed and transferred to other needy cohorts, such as older adults with dementia, sarcopenia and/or dynapenia.

Structural integrity in subjective cognitive decline, mild cognitive impairment and Alzheimer's disease based on multicenter diffusion tensor imaging

INTRODUCTION

Subjective cognitive decline (SCD) can represent a preclinical stage of Alzheimer's disease. Diffusion tensor imaging (DTI) could aid an early diagnosis, yet only few monocentric DTI studies in SCD have been conducted, reporting heterogeneous results. We investigated microstructural changes in SCD in a larger, multicentric cohort.

METHODS

271 participants with SCD, mild cognitive impairment (MCI) or Alzheimer's dementia (AD) and healthy controls (CON) were included, recruited prospectively at nine centers of the observational DELCODE study. DTI was acquired using identical protocols. Using voxel-based analyses, we investigated fractional anisotropy (FA), mean diffusivity (MD) and mode (MO) in the white matter (WM). Discrimination accuracy was determined by cross-validated elastic-net penalized regression. Center effects were explored using variance analyses.

RESULTS

MO and FA were lower in SCD compared to CON in several anterior and posterior WM regions, including the anterior corona radiata, superior and inferior longitudinal fasciculus, cingulum and splenium of the corpus callosum (p < 0.01, uncorrected). MD was higher in the superior and inferior longitudinal fasciculus, cingulum and superior corona radiata (p < 0.01, uncorrected). The cross-validated accuracy for discriminating SCD from CON was 67% (p < 0.01). As expected, the AD and MCI groups had higher MD and lower FA and MO in extensive regions, including the corpus callosum and temporal brain regions. Within these regions, center accounted for 3-15% of the variance.

CONCLUSIONS

DTI revealed subtle WM alterations in SCD that were intermediate between those in MCI and CON and may be useful to detect individuals with an increased risk for AD in clinical studies.

Spatial gradients of healthy aging: a study of myelin-sensitive maps

Protracted development of a brain network may entail greater susceptibility to aging decline, supported by evidence of an earlier onset of age-related changes in late-maturing anterior areas, that is, an anterior-to-posterior gradient of brain aging. Here we analyzed the spatiotemporal features of age-related differences in myelin content across the human brain indexed by magnetization transfer (MT) concentration in a cross-sectional cohort of healthy adults. We described age-related spatial gradients in MT, which may reflect the reversal of patterns observed in development. We confirmed an anterior-to-posterior gradient of age-related MT decrease and also showed a lateral-to-ventral gradient inversely mirroring the sequence of connectivity development and myelination. MT concentration in the lateral white matter regions continued to increase up to the age of 45 years and decreased moderately following a peak. In contrast, ventral white matter regions reflected life-long stable MT concentration levels, followed by a rapid decrease at a later age. We discussed our findings in relation with existing theories of brain aging, including the lack of support for the proposal that areas which mature later decline at an accelerated rate.

A Review and Hypothesized Model of the Mechanisms That Underpin the Relationship Between Inflammation and Cognition in the Elderly

Age is associated with increased risk for several disorders including dementias, cardiovascular disease, atherosclerosis, obesity, and diabetes. Age is also associated with cognitive decline particularly in cognitive domains associated with memory and processing speed. With increasing life expectancies in many countries, the number of people experiencing age-associated cognitive impairment is increasing and therefore from both economic and social terms the amelioration or slowing of cognitive aging is an important target for future research. However, the biological causes of age associated cognitive decline are not yet, well understood. In the current review, we outline the role of inflammation in cognitive aging and describe the role of several inflammatory processes, including inflamm-aging, vascular inflammation, and neuroinflammation which have both direct effect on brain function and indirect effects on brain function via changes in cardiovascular function.

Age-related alterations in axonal microstructure in the corpus callosum measured by high-gradient diffusion MRI

Cerebral white matter exhibits age-related degenerative changes during the course of normal aging, including decreases in axon density and alterations in axonal structure. Noninvasive approaches to measure these microstructural alterations throughout the lifespan would be invaluable for understanding the substrate and regional variability of age-related white matter degeneration. Recent advances in diffusion magnetic resonance imaging (MRI) have leveraged high gradient strengths to increase sensitivity toward axonal size and density in the living human brain. Here, we examined the relationship between age and indices of axon diameter and packing density using high-gradient strength diffusion MRI in 36 healthy adults (aged 22-72) in well-defined central white matter tracts in the brain. A recently validated method for inferring the effective axonal compartment size and packing density from diffusion MRI measurements acquired with 300 mT/m maximum gradient strength was applied to the in vivo human brain to obtain indices of axon diameter and density in the corpus callosum, its sub-regions, and adjacent anterior and posterior fibers in the forceps minor and forceps major. The relationships between the axonal metrics, corpus callosum area and regional gray matter volume were also explored. Results revealed a significant increase in axon diameter index with advancing age in the whole corpus callosum. Similar analyses in sub-regions of the corpus callosum showed that age-related alterations in axon diameter index and axon density were most pronounced in the genu of the corpus callosum and relatively absent in the splenium, in keeping with findings from previous histological studies. The significance of these correlations was mirrored in the forceps minor and forceps major, consistent with previously reported decreases in FA in the forceps minor but not in the forceps major with age. Alterations in the axonal imaging metrics paralleled decreases in corpus callosum area and regional gray matter volume with age. Among older adults, results from cognitive testing suggested an association between larger effective compartment size in the corpus callosum, particularly within the genu of the corpus callosum, and lower scores on the Montreal Cognitive Assessment, largely driven by deficits in short-term memory. The current study suggests that high-gradient diffusion MRI may be sensitive to the axonal substrate of age-related white matter degeneration reflected in traditional DTI metrics and provides further evidence for regionally selective alterations in white matter microstructure with advancing age.

Generalizing age effects on brain structure and cognition: A two-study comparison approach

Normal aging is accompanied by an interindividually variable decline in cognitive abilities and brain structure. This variability, in combination with methodical differences and differences in sample characteristics across studies, pose a major challenge for generalizability of results from different studies. Therefore, the current study aimed at cross-validating age-related differences in cognitive abilities and brain structure (measured using cortical thickness [CT]) in two large independent samples, each consisting of 228 healthy older adults aged between 65 and 85 years: the Longitudinal Healthy Aging Brain (LHAB) database (University of Zurich, Switzerland) and the 1000BRAINS (Research Centre Jülich, Germany). Participants from LHAB showed significantly higher education, physical well-being, and cognitive abilities (processing speed, concept shifting, reasoning, semantic verbal fluency, and vocabulary). In contrast, CT values were larger for participants of 1000BRAINS. Though, both samples showed highly similar age-related differences in both, cognitive abilities and CT. These effects were in accordance with functional aging theories, for example, posterior to anterior shift in aging as was shown for the default mode network. Thus, the current two-study approach provides evidence that independently on heterogeneous metrics of brain structure or cognition across studies, age-related effects on cognitive ability and brain structure can be generalized over different samples, assuming the same methodology is used.

White matter abnormalities predict residual negative self-referential thinking following treatment of late-life depression with escitalopram: A preliminary study

BACKGROUND

Negative self-referential thinking is a common symptom of depression associated with poor treatment response. In late-life depression, white matter abnormalities may contribute to negative self-referential thoughts following antidepressant treatment. We investigated the association of fractional anisotropy (FA) in select regions of the negative valence system (NVS) with residual negative self-referential thoughts following treatment with escitalopram for late-life depression.

METHODS

The participants were older adults with major depression and psychiatrically normal controls. Depressed participants received 12 weeks of treatment with escitalopram. To assess self-referential thinking, participants completed a Trait Adjective Task at baseline and at week 12. Baseline MRI scans included a diffusion imaging sequence for FA analyses.

RESULTS

Participants with late-life depression differed from controls on all performance measures of the Trait Adjective Task at baseline and at 12 weeks. Depressed participants endorsed fewer negative personality traits and more positive personality traits at week 12 compared to baseline. Lower FA in the dorsal anterior cingulate and in the uncinate fasciculus in depressed participants was correlated with residual negative self-referential thinking (e.g., more endorsed negative adjectives, fewer rejected negative adjectives) at treatment end.

LIMITATIONS

The sample size is modest so the findings are preliminary. FA analyses were restricted to predetermined regions.

CONCLUSIONS

Negative self-referential thinking improved in depressed older adults following 12 weeks of treatment with escitalopram. Baseline FA in select white matter regions of the NVS was associated with residual negative self-referential thinking. These findings may help identify treatment targets for residual negative self-referential thoughts.

Biospectroscopic Imaging Provides Evidence of Hippocampal Zn Deficiency and Decreased Lipid Unsaturation in an Accelerated Aging Mouse Model

Western society is facing a health epidemic due to the increasing incidence of dementia in aging populations, and there are still few effective diagnostic methods, minimal treatment options, and no cure. Aging is the greatest risk factor for memory loss that occurs during the natural aging process, as well as being the greatest risk factor for neurodegenerative disease such as Alzheimer's disease. Greater understanding of the biochemical pathways that drive a healthy aging brain toward dementia (pathological aging or Alzheimer's disease), is required to accelerate the development of improved diagnostics and therapies. Unfortunately, many animal models of dementia model chronic amyloid precursor protein overexpression, which although highly relevant to mechanisms of amyloidosis and familial Alzheimer's disease, does not model well dementia during the natural aging process. A promising animal model reported to model mechanisms of accelerated natural aging and memory impairments, is the senescence accelerated murine prone strain 8 (SAMP8), which has been adopted by many research group to study the biochemical transitions that occur during brain aging. A limitation to traditional methods of biochemical characterization is that many important biochemical and elemental markers (lipid saturation, lactate, transition metals) cannot be imaged at meso- or microspatial resolution. Therefore, in this investigation, we report the first multimodal biospectroscopic characterization of the SAMP8 model, and have identified important biochemical and elemental alterations, and colocalizations, between 4 month old SAMP8 mice and the relevant control (SAMR1) mice. Specifically, we demonstrate direct evidence of Zn deficiency within specific subregions of the hippocampal CA3 sector, which colocalize with decreased lipid unsaturation. Our findings also revealed colocalization of decreased lipid unsaturation and increased lactate in the corpus callosum white matter, adjacent to the hippocampus. Such findings may have important implication for future research aimed at elucidating specific biochemical pathways for therapeutic intervention.

Maintenance, reserve and compensation: the cognitive neuroscience of healthy ageing

Cognitive ageing research examines the cognitive abilities that are preserved and/or those that decline with advanced age. There is great individual variability in cognitive ageing trajectories. Some older adults show little decline in cognitive ability compared with young adults and are thus termed 'optimally ageing'. By contrast, others exhibit substantial cognitive decline and may develop dementia. Human neuroimaging research has led to a number of important advances in our understanding of the neural mechanisms underlying these two outcomes. However, interpreting the age-related changes and differences in brain structure, activation and functional connectivity that this research reveals is an ongoing challenge. Ambiguous terminology is a major source of difficulty in this venture. Three terms in particular - compensation, maintenance and reserve - have been used in a number of different ways, and researchers continue to disagree about the kinds of evidence or patterns of results that are required to interpret findings related to these concepts. As such inconsistencies can impede progress in both theoretical and empirical research, here, we aim to clarify and propose consensual definitions of these terms.

Incremental rate of prefrontal oxygenation determines performance speed during cognitive Stroop test: the effect of ageing

Cognitive function declines with age. The underlying mechanisms responsible for the deterioration of cognitive performance, however, remain poorly understood. We hypothesized that an incremental rate of prefrontal oxygenation during a cognitive Stroop test decreases in progress of ageing, resulting in a slowdown of cognitive performance. To test this hypothesis, we identified, using multichannel near-infrared spectroscopy, the characteristics of the oxygenated-hemoglobin concentration (Oxy-Hb) responses of the prefrontal cortex to both incongruent Stroop and congruent word-reading test. Spatial distributions of the significant changes in the three components (initial slope, peak amplitude, and area under the curve) of the Oxy-Hb response were compared between young and elderly subjects. The Stroop interference time (as a difference in total periods for executing Stroop and word-reading test, respectively) approximately doubled in elderly as compared to young subjects. The Oxy-Hb in the rostrolateral, but not caudal, prefrontal cortex increased during the Stroop test in both age groups. The initial slope of the Oxy-Hb response, rather than the peak and area under the curve, had a strong correlation with cognitive performance speed. Taken together, it is likely that the incremental rate of prefrontal oxygenation may decrease in progress of ageing, resulting in a decline in cognitive performance.

Maintenance, reserve and compensation: the cognitive neuroscience of healthy ageing

Cognitive ageing research examines the cognitive abilities that are preserved and/or those that decline with advanced age. There is great individual variability in cognitive ageing trajectories. Some older adults show little decline in cognitive ability compared with young adults and are thus termed 'optimally ageing'. By contrast, others exhibit substantial cognitive decline and may develop dementia. Human neuroimaging research has led to a number of important advances in our understanding of the neural mechanisms underlying these two outcomes. However, interpreting the age-related changes and differences in brain structure, activation and functional connectivity that this research reveals is an ongoing challenge. Ambiguous terminology is a major source of difficulty in this venture. Three terms in particular - compensation, maintenance and reserve - have been used in a number of different ways, and researchers continue to disagree about the kinds of evidence or patterns of results that are required to interpret findings related to these concepts. As such inconsistencies can impede progress in both theoretical and empirical research, here, we aim to clarify and propose consensual definitions of these terms.

Weighted Stochastic Block Models of the Human Connectome across the Life Span

The human brain can be described as a complex network of anatomical connections between distinct areas, referred to as the human connectome. Fundamental characteristics of connectome organization can be revealed using the tools of network science and graph theory. Of particular interest is the network's community structure, commonly identified by modularity maximization, where communities are conceptualized as densely intra-connected and sparsely inter-connected. Here we adopt a generative modeling approach called weighted stochastic block models (WSBM) that can describe a wider range of community structure topologies by explicitly considering patterned interactions between communities. We apply this method to the study of changes in the human connectome that occur across the life span (between 6-85 years old). We find that WSBM communities exhibit greater hemispheric symmetry and are spatially less compact than those derived from modularity maximization. We identify several network blocks that exhibit significant linear and non-linear changes across age, with the most significant changes involving subregions of prefrontal cortex. Overall, we show that the WSBM generative modeling approach can be an effective tool for describing types of community structure in brain networks that go beyond modularity.

Age differences in the neural response to negative feedback

Affective processing is one domain that remains relatively intact in healthy aging. Investigations into the neural responses associated with reward anticipation have revealed that older and younger adults recruit the same midbrain reward regions, but other evidence suggests this recruitment may differ depending on the valence (gain, loss) of the incentive cue. The goal of the current study was to examine functional covariance during gain and loss feedback in younger and healthy older adults. A group of 15 older adults (mean age = 68.5) and 16 younger adults (mean age = 25.4) completed a revised Monetary Incentive Delay task (rMID; Knutson, Westdorp, Kaiser, & Hommer, 2000) while in the fMRI scanner. The rMID is a reaction time task where successful performance, either gaining a reward or avoiding a loss, is defined by hitting a button during the brief presentation of a visual target. Participants receive gain and loss anticipation cues before each trial and feedback after each trial with four possible outcomes: +$5.00, +0.00, -$5.00, and -$0.00. Using seed-voxel partial least squares analyses, with seed voxels in the caudate and ventromedial prefrontal cortex, whole-brain functional covariance revealed that younger and older adults engage the same network of regions to support general feedback processing. However, older adults engaged two additional networks to support processing of negative feedback, gain_miss (+0), loss_miss (-$5), and loss_hit (-0), specifically. These findings are in line with theories of a positivity effect in aging and may have implications for reward-stimulus learning and decision making following performance-contingent negative feedback.

Neuroimaging correlates of narcolepsy with cataplexy: A systematic review

Recent developments in neuroimaging techniques have advanced our understanding of biological mechanisms underpinning narcolepsy. We used MEDLINE to retrieve neuroimaging studies to compare patients with narcolepsy and healthy controls. Thirty-seven studies were identified and demonstrated several replicated abnormalities: (1) gray matter reductions in superior frontal, superior and inferior temporal, and middle occipital gyri, hypothalamus, amygdala, insula, hippocampus, cingulate cortex, thalamus, and nucleus accumbens, (2) decreased fractional anisotropy in white matter of fronto-orbital and cingulate area, (3) reduced brain metabolism or cerebral blood flow in middle and superior frontal, and cingulate cortex (4) increased activity in inferior frontal gyri, insula, amygdala, and nucleus accumbens, and (5) N-acetylaspartate/creatine-phosphocreatine level reduction in hypothalamus. In conclusion, all the replicated findings are still controversial due to the limitations such as heterogeneity or size of the samples and lack of multimodal imaging or follow-up. Thus, future neuroimaging studies should employ multimodal imaging methods in a large sample size of patients with narcolepsy and consider age, duration of disease, age at onset, severity, human leukocyte antigen type, cerebrospinal fluid hypocretin levels, and medication intake in order to elucidate possible neuroimaging characteristic of narcolepsy and identify therapeutic targets.

Age-related early/late variations of functional connectivity across the human lifespan

PURPOSE

Many questions remain regarding how the brain develops, matures, and ages across the lifespan. The functional connectivity networks in the resting-state brain can reflect many of the characteristic changes in the brain that are associated with increasing age. Functional connectivity has been shown to be time-dependent over the course of a lifespan and even over the course of minutes. The lifespan strategies of all cognitive networks and how dynamic functional connectivity is associated with age are unclear.

METHODS

In this paper, studies employing both linear and quadratic models to define new specific lifespan strategies, including early/late increase/decrease models, were conducted to explore the lifespan functional changes. A large data sample was retrieved from the publicly available data from the Nathan Kline Institute (N = 149 and ages 9-85). Both static and dynamic functional connectivity indexes were calculated including the static functional connectivity, the mean of the dynamic functional connectivity and variations in dynamic functional connectivity.

RESULTS

The between-network connectivity results revealed early increases in the default-mode (DF) and cingulo-opercular network (CO)-associated network connectivities and a late increase in the fronto-parietal (FP)-associated network connectivity. These results depicted various lifespan strategies for different development stages and different cognitive networks across the lifespan. Additionally, the static FC and mean dynamic FC exhibited consistent results, and their variation exhibited a constant decrease with age across the entire age range.

CONCLUSION

These results (FDR-corrected p value < 0.05) suggest that the early/late variations in lifespan strategies could reflect an association between varied and complex circumstances and brain development.

Categories, diversity, and relevance of memory strategies reported by community-dwelling seniors

BACKGROUND

Memory strategies help seniors remember information that is essential for the performance of their daily activities and contribute to their independence in the context of declining memory skills. This study aimed to analyze the categories, the diversity, and relevance of memory strategies known by seniors, and to identify individual characteristics that correlated with these variables.

METHODS

The sample consisted of 294 participants aged 60 and over who decided to take part in a cognitive vitality promotion program. An adapted version of the memory situation questionnaire (Troyer, 2001) was administered to identify the memory strategies that seniors would use in five daily life situations. A scoring grid, also adapted from the questionnaire's original version (Troyer, 2001), was used to quantify the relevance of the strategies that were reported by participants.

RESULTS

All participants mentioned at least once that they would use a strategy from the physical category of memory strategies. Out of a possible range of 26 strategies, participants answered an average of 6.14 (SD = 1.7) different answers across the five situations. Based on expert consensus, 67.7% of the mentioned memory strategies were relevant. Diversity and relevance were significantly higher when trying to remember appointments, things to bring or phone numbers (p ≤ 0.05). The level of education, cognitive skills, and participation in leisure activities were related to diversity and relevance of reported strategies.

CONCLUSIONS

Seniors know various and relevant memory strategies to perform daily activities. The advantages of integrating strategies that they already know in cognitive health promotion programs should be considered in further studies.

Statin use and cognitive function in middle-aged adults with type 1 diabetes

AIM

To test associations between statin use and cognitive impairment in adults with childhood-onset type 1 diabetes (T1D).

METHODS

In 2010-13, n = 108 middle-aged participants from ongoing observational Pittsburgh Epidemiology of Diabetes Complications Study underwent neurocognitive assessment (mean age and T1D duration of 49 and 41 years, respectively). All were diagnosed with childhood-onset (i.e., prior to age 18) T1D between 1950 and 1980 and were seen within one year of diagnosis at Children’s Hospital of Pittsburgh. Self-reported statin use (yes/no and if yes, name of statin) was collected biennially from parent study baseline (1986-1988) to time of neurocognitive testing. Logistic regression models tested associations between statin use groups and cognitive impairment (defined as having two or more cognitive test scores 1.5SD or worse than published norms) while linear regression models tested associations between statin use groups and cognitive domain z-scores (domains: Verbal IQ, memory, executive function, psychomotor speed, and visuo-construction). All models controlled for education and age. To address confounding by indication, models were repeated using a propensity score for statin use.

RESULTS

Of the 108 participants, 51 reported never using statins. Median duration of statin use among the 57 ever users was 6 years. These 57 ever statin users were split to create two groups (≤ or > median years of statin use): 1-6 years (n = 25), and 7-12 years (n = 32). Compared with never users, using statins 1-6 years tripled the odds of cognitive impairment (OR = 3.16; 95%CI: 0.93-10.72; P = 0.06) and using statins 7-12 years almost quintupled the odds of cognitive impairment (OR = 4.84; 95%CI: 1.63-14.44; P = 0.005). Compared with never users, using statins 1-6 or 7-12 years was related to worse performance in the memory domain (β = -0.52; P = 0.003, and -0.39; P = 0.014, respectively). Adjusting for coronary artery disease, low density lipoprotein cholesterol, and Apo E4 status did not substantially alter results, and none of these covariates were significantly related to cognitive outcomes (all P > 0.05). Propensity score analyses support that associations between poor cognitive outcomes and statin use were not due merely to confounding by indication.

CONCLUSION

Statin use was associated with cognitive impairment, particularly affecting memory, in these middle-aged adults with childhood-onset T1D, whom at this age, should not yet manifest age-related memory deficits.