Aging in the CNS: comparison of gray/white matter volume and diffusion tensor data

Hypothalamic MRI-derived microstructure is associated with neurocognitive aging in humans

The hypothalamus regulates homeostasis across the lifespan and is emerging as a regulator of aging. In murine models, aging-related changes in the hypothalamus, including microinflammation and gliosis, promote accelerated neurocognitive decline. We investigated relationships between hypothalamic microstructure and features of neurocognitive aging, including cortical thickness and cognition, in a cohort of community-dwelling older adults (age range 65-97 years, n=124). Hypothalamic microstructure was evaluated with two magnetic resonance imaging diffusion metrics: mean diffusivity (MD) and fractional anisotropy (FA), using a novel image processing pipeline. Hypothalamic MD was cross-sectionally positively associated with age and it was negatively associated with cortical thickness. Hypothalamic FA, independent of cortical thickness, was cross-sectionally positively associated with neurocognitive scores. An exploratory analysis of longitudinal neurocognitive performance suggested that lower hypothalamic FA may predict cognitive decline. No associations between hypothalamic MD, age, and cortical thickness were identified in a younger control cohort (age range 18-63 years, n=99). To our knowledge, this is the first study to demonstrate that hypothalamic microstructure is associated with features of neurocognitive aging in humans.

The Effects of Computerized Cognitive Training in Older Adults' Cognitive Performance and Biomarkers of Structural Brain Aging

OBJECTIVES

Cognitive training (CT) has been investigated as a means of delaying age-related cognitive decline in older adults. However, its impact on biomarkers of age-related structural brain atrophy has rarely been investigated, leading to a gap in our understanding of the linkage between improvements in cognition and brain plasticity. This study aimed to explore the impact of CT on cognitive performance and brain structure in older adults.

METHODS

One hundred twenty-four cognitively normal older adults recruited from 2 study sites were randomly assigned to either an adaptive CT (n = 60) or a casual game training (active control, AC, n = 64).

RESULTS

After 10 weeks of training, CT participants showed greater improvements in the overall cognitive composite score (Cohen's d = 0.66, p < .01) with nonsignificant benefits after 6 months from the completion of training (Cohen's d = 0.36, p = .094). The CT group showed significant maintenance of the caudate volume as well as significant maintained fractional anisotropy in the left internal capsule and in left superior longitudinal fasciculus compared to the AC group. The AC group displayed an age-related decrease in these metrics of brain structure.

DISCUSSION

Results from this multisite clinical trial demonstrate that the CT intervention improves cognitive performance and helps maintain caudate volume and integrity of white matter regions that are associated with cognitive control, adding to our understanding of the changes in brain structure contributing to changes in cognitive performance from adaptive CT.

CLINICAL TRIAL REGISTRATION

NCT03197454.

Aging pattern of the brainstem based on volumetric measurement and optimized surface shape analysis

The brainstem, a small and crucial structure, is connected to the cerebrum, spinal cord, and cerebellum, playing a vital role in regulating autonomic functions, transmitting motor and sensory information, and modulating cognitive processes, emotions, and consciousness. While previous research has indicated that changes in brainstem anatomy can serve as a biomarker for aging and neurodegenerative diseases, the structural changes that occur in the brainstem during normal aging remain unclear. This study aimed to examine the age- and sex-related differences in the global and local structural measures of the brainstem in 187 healthy adults (ranging in age from 18 to 70 years) using structural magnetic resonance imaging. The findings showed a significant negative age effect on the volume of the two major components of the brainstem: the medulla oblongata and midbrain. The shape analysis revealed that atrophy primarily occurs in specific structures, such as the pyramid, cerebral peduncle, superior and inferior colliculi. Surface area and shape analysis showed a trend of flattening in the aging brainstem. There were no significant differences between the sexes or sex-by-age interactions in brainstem structural measures. These findings provide a systematic description of age associations with brainstem structures in healthy adults and may provide a reference for future research on brain aging and neurodegenerative diseases.

Consensus Paper: Cerebellum and Ageing

Given the key roles of the cerebellum in motor, cognitive, and affective operations and given the decline of brain functions with aging, cerebellar circuitry is attracting the attention of the scientific community. The cerebellum plays a key role in timing aspects of both motor and cognitive operations, including for complex tasks such as spatial navigation. Anatomically, the cerebellum is connected with the basal ganglia via disynaptic loops, and it receives inputs from nearly every region in the cerebral cortex. The current leading hypothesis is that the cerebellum builds internal models and facilitates automatic behaviors through multiple interactions with the cerebral cortex, basal ganglia and spinal cord. The cerebellum undergoes structural and functional changes with aging, being involved in mobility frailty and related cognitive impairment as observed in the physio-cognitive decline syndrome (PCDS) affecting older, functionally-preserved adults who show slowness and/or weakness. Reductions in cerebellar volume accompany aging and are at least correlated with cognitive decline. There is a strongly negative correlation between cerebellar volume and age in cross-sectional studies, often mirrored by a reduced performance in motor tasks. Still, predictive motor timing scores remain stable over various age groups despite marked cerebellar atrophy. The cerebello-frontal network could play a significant role in processing speed and impaired cerebellar function due to aging might be compensated by increasing frontal activity to optimize processing speed in the elderly. For cognitive operations, decreased functional connectivity of the default mode network (DMN) is correlated with lower performances. Neuroimaging studies highlight that the cerebellum might be involved in the cognitive decline occurring in Alzheimer's disease (AD), independently of contributions of the cerebral cortex. Grey matter volume loss in AD is distinct from that seen in normal aging, occurring initially in cerebellar posterior lobe regions, and is associated with neuronal, synaptic and beta-amyloid neuropathology. Regarding depression, structural imaging studies have identified a relationship between depressive symptoms and cerebellar gray matter volume. In particular, major depressive disorder (MDD) and higher depressive symptom burden are associated with smaller gray matter volumes in the total cerebellum as well as the posterior cerebellum, vermis, and posterior Crus I. From the genetic/epigenetic standpoint, prominent DNA methylation changes in the cerebellum with aging are both in the form of hypo- and hyper-methylation, and the presumably increased/decreased expression of certain genes might impact on motor coordination. Training influences motor skills and lifelong practice might contribute to structural maintenance of the cerebellum in old age, reducing loss of grey matter volume and therefore contributing to the maintenance of cerebellar reserve. Non-invasive cerebellar stimulation techniques are increasingly being applied to enhance cerebellar functions related to motor, cognitive, and affective operations. They might enhance cerebellar reserve in the elderly. In conclusion, macroscopic and microscopic changes occur in the cerebellum during the lifespan, with changes in structural and functional connectivity with both the cerebral cortex and basal ganglia. With the aging of the population and the impact of aging on quality of life, the panel of experts considers that there is a huge need to clarify how the effects of aging on the cerebellar circuitry modify specific motor, cognitive, and affective operations both in normal subjects and in brain disorders such as AD or MDD, with the goal of preventing symptoms or improving the motor, cognitive, and affective symptoms.

In vivo microstructural heterogeneity of white matter and cognitive correlates in aging using tissue compositional analysis of diffusion magnetic resonance imaging

BACKGROUND

Age-related cognitive decline is linked to changes in the brain, particularly the deterioration of white matter (WM) microstructure that accelerates after the age of 60. WM deterioration is associated with mild cognitive impairment and dementia, but the origin and role of white matter signal abnormalities (WMSA) seen in standard MRI remain debated due to their heterogeneity. This study explores the potential of single-shell 3-tissue constrained spherical deconvolution (SS3T-CSD), a novel technique that models diffusion data in terms of gray matter (TG ), white matter (Tw ), and cerebrospinal fluid (TC ), to differentiate WMSA from normal-appearing white matter and better understand the interplay between changes in WM microstructure and decline in cognition.

METHODS

A total of 189 individuals from the GENIC cohort were included. MRI data, including T1-weighted and diffusion images, were obtained. Preprocessing steps were performed on the diffusion MRI data, followed by the SS3T-CSD. WMSA were segmented using FreeSurfer. Statistical analyses were conducted to assess the association between age, WMSA volume, 3-tissue signal fractions (Tw , TG , and TC ), and neuropsychological variables.

RESULTS

Participants above 60 years old showed worse cognitive performance and processing speed compared to those below 60 (p < .001). Age was negatively associated with Tw in normal-appearing white matter (p < .001) and positively associated with TG in both WMSA (p < .01) and normal-appearing white matter (p < .001). Age was also significantly associated with WMSA volume (p < .001). Higher processing speed was associated with lower Tw and higher TG , in normal-appearing white matter (p < .01 and p < .001, respectively), as well as increased WMSA volume (p < .001). Similarly, lower MMSE scores correlated with lower Tw and higher TG in normal-appearing white matter (p < .05). High cholesterol and hypertension were associated with higher WMSA volume (p < .05).

CONCLUSION

The microstructural heterogeneity within normal-appearing white matter and WMSA is associated with increasing age and cognitive variation, in cognitively unimpaired individuals. Furthermore, the 3-tissue signal fractions are more specific to potential white matter alterations than conventional MRI measures such as WMSA volume. These findings also support the view that the WMSA volumes may be more influenced by vascular risk factors than the 3-tissue metrics. Finally, the 3-tissue metrics were able to capture associations with cognitive tests and therefore capable of capturing subtle pathological changes in the brain in individuals who are still within the normal range of cognitive performance.

Aging, cingulate cortex, and cognition: insights from structural MRI, emotional recognition, and theory of mind

The cingulate cortex is a limbic structure involved in multiple functions, including emotional processing, pain, cognition, memory, and spatial orientation. The main goal of this structural Magnetic Resonance Imaging (MRI) study was to investigate whether age affects the cingulate cortex uniformly across its anteroposterior dimensions and determine if the effects of age differ based on sex, hemisphere, and regional cingulate anatomy, in a large cohort of healthy individuals across the adult lifespan. The second objective aimed to explore whether the decline in emotional recognition accuracy and Theory of Mind (ToM) is linked to the potential age-related reductions in the pregenual anterior cingulate (ACC) and anterior midcingulate (MCC) cortices. We recruited 126 healthy participants (18-85 years) for this study. MRI datasets were acquired on a 4.7 T system. The cingulate cortex was manually segmented into the pregenual ACC, anterior MCC, posterior MCC, and posterior cingulate cortex (PCC). We observed negative relationships between the presence and length of the superior cingulate gyrus and bilateral volumes of pregenual ACC and anterior MCC. Age showed negative effects on the volume of all cingulate cortical subregions bilaterally except for the right anterior MCC. Most of the associations between age and the cingulate subregional volumes were linear. We did not find a significant effect of sex on cingulate cortical volumes. However, stronger effects of age were observed in men compared to women. This study also demonstrated that performance on an emotional recognition task was linked to pregenual ACC volume, whist the ToM capabilities were related to the size of pregenual ACC and anterior MCC. These results suggest that the cingulate cortex contributes to emotional recognition ability and ToM across the adult lifespan.

Brain age prediction across the human lifespan using multimodal MRI data

Measuring differences between an individual's age and biological age with biological information from the brain have the potential to provide biomarkers of clinically relevant neurological syndromes that arise later in human life. To explore the effect of multimodal brain magnetic resonance imaging (MRI) features on the prediction of brain age, we investigated how multimodal brain imaging data improved age prediction from more imaging features of structural or functional MRI data by using partial least squares regression (PLSR) and longevity data sets (age 6-85 years). First, we found that the age-predicted values for each of these ten features ranged from high to low: cortical thickness (R = 0.866, MAE = 7.904), all seven MRI features (R = 0.8594, MAE = 8.24), four features in structural MRI (R = 0.8591, MAE = 8.24), fALFF (R = 0.853, MAE = 8.1918), gray matter volume (R = 0.8324, MAE = 8.931), three rs-fMRI feature (R = 0.7959, MAE = 9.744), mean curvature (R = 0.7784, MAE = 10.232), ReHo (R = 0.7833, MAE = 10.122), ALFF (R = 0.7517, MAE = 10.844), and surface area (R = 0.719, MAE = 11.33). In addition, the significance of the volume and size of brain MRI data in predicting age was also studied. Second, our results suggest that all multimodal imaging features, except cortical thickness, improve brain-based age prediction. Third, we found that the left hemisphere contributed more to the age prediction, that is, the left hemisphere showed a greater weight in the age prediction than the right hemisphere. Finally, we found a nonlinear relationship between the predicted age and the amount of MRI data. Combined with multimodal and lifespan brain data, our approach provides a new perspective for chronological age prediction and contributes to a better understanding of the relationship between brain disorders and aging.

Grey-matter structure in cortical and limbic regions correlates with general cognitive ability in old age

According to the maintenance hypothesis (Nyberg et al., 2012), structural integrity of the brain's grey matter helps to preserve cognitive functioning into old age. A corollary of this hypothesis that can be tested in cross-sectional data is that grey-matter structural integrity and general cognitive ability are positively associated in old age. Building on Köhncke et al. (2021), who found that region-specific latent factors of grey-matter integrity are positively associated with episodic memory ability among older adults, we examine associations between general factors of grey-matter integrity and a general factor of cognitive ability in a cross-sectional sample of 1466 participants aged 60-88 years, 319 of whom contributed imaging data. Indicator variables based on T1-weighted images (voxel-based morphometry, VBM), magnetization-transfer imaging (MT), and diffusion tensor imaging-derived mean diffusivity (MD) had sufficient portions of variance in common to establish latent factors of grey-matter structure for a comprehensive set of regions of interest (ROI). Individual differences in grey-matter factors were positively correlated across neocortical and limbic areas, allowing for the definition of second-order, general factors for neocortical and limbic ROI, respectively. Both general grey-matter factors were positively correlated with general cognitive ability. For the basal ganglia, the three modality-specific indicators showed heterogenous loading patterns, and no reliable associations of the general grey-matter factor to general cognitive ability were found. To provide more direct tests of the maintenance hypothesis, we recommend applying the present structural modeling approach to longitudinal data, thereby enhancing the physiological validity of latent constructs of brain structure.

Cerebellar EEG source localization reveals age-related compensatory activity moderated by genetic risk for Alzheimer's disease

The apolipoprotein-E (APOE) ε4 allele is the greatest genetic risk factor for late-onset Alzheimer's disease (AD), but alone it is not sufficiently predictive. Because neuropathological changes associated with AD begin decades before cognitive symptoms, neuroimaging of healthy, cognitively intact ε4 carriers (ε4+) may enable early characterization of patterns associated with risk for future decline. Research in the cerebral cortex highlights a period of compensatory recruitment in elders and ε4+, which serves to maintain cognitive functioning. Yet, AD-related changes may occur even earlier in the cerebellum. Advances in electroencephalography (EEG) source localization now allow effective modeling of cerebellar activity. Importantly, healthy aging and AD are associated with declines in both cerebellar functions and executive functioning (EF). However, it is not known whether cerebellar activity can detect pre-symptomatic AD risk. Thus, the current study analyzed cerebellar EEG source localization during an EF-dependent stop-signal task (i.e., inhibitory control) in healthy, intact older adults (Mage  = 80 years; 20 ε4+, 25 ε4-). Task performance was comparable between groups. Older age predicted greater activity in left crus II and lobule VIIb during the P300 window (i.e., performance evaluation), consistent with age-related compensation. Age*ε4 moderations specifically showed that compensatory patterns were evident only in ε4-, suggesting that cerebellar compensatory resources may already be depleted in healthy ε4+ elders. Thus, the posterolateral cerebellum is sensitive to AD-related neural deficits in healthy elders. Characterization of these patterns may be essential for the earliest possible detection of AD risk, which would enable critical early intervention prior to symptom onset.

High-resolution multi-shot diffusion imaging of structural networks in healthy neurocognitive aging

Healthy neurocognitive aging has been associated with the microstructural degradation of white matter pathways that connect distributed gray matter regions, assessed by diffusion-weighted imaging (DWI). However, the relatively low spatial resolution of standard DWI has limited the examination of age-related differences in the properties of smaller, tightly curved white matter fibers, as well as the relatively more complex microstructure of gray matter. Here, we capitalize on high-resolution multi-shot DWI, which allows spatial resolutions < 1 mm3 to be achieved on clinical 3T MRI scanners. We assessed whether traditional diffusion tensor-based measures of gray matter microstructure and graph theoretical measures of white matter structural connectivity assessed by standard (1.5 mm3 voxels, 3.375 μl volume) and high-resolution (1 mm3 voxels, 1μl volume) DWI were differentially related to age and cognitive performance in 61 healthy adults 18-78 years of age. Cognitive performance was assessed using an extensive battery comprising 12 separate tests of fluid (speed-dependent) cognition. Results indicated that the high-resolution data had larger correlations between age and gray matter mean diffusivity, but smaller correlations between age and structural connectivity. Moreover, parallel mediation models including both standard and high-resolution measures revealed that only the high-resolution measures mediated age-related differences in fluid cognition. These results lay the groundwork for future studies planning to apply high-resolution DWI methodology to further assess the mechanisms of both healthy aging and cognitive impairment.

Age- and sex-related differences in baboon (Papio anubis) gray matter covariation

Age-related changes in cognition, brain morphology, and behavior are exhibited in several primate species. Baboons, like humans, naturally develop Alzheimer's disease-like pathology and cognitive declines with age and are an underutilized model for studies of aging. To determine age-related differences in gray matter covariation of 89 olive baboons (Papio anubis), we used source-based morphometry (SBM) to analyze data from magnetic resonance images. We hypothesized that we would find significant age effects in one or more SBM components, particularly those which include regions influenced by age in humans and other nonhuman primates (NHPs). A multivariate analysis of variance revealed that individual weighted gray matter covariation scores differed across the age classes. Elderly baboons contributed significantly less to gray matter covariation components including the brainstem, superior parietal cortex, thalamus, and pallidum compared to juveniles, and middle and superior frontal cortex compared to juveniles and young adults (p < 0.05). Future studies should examine the relationship between the changes in gray matter covariation reported here and age-related cognitive decline.

Adult lifespan maturation and degeneration patterns in gray and white matter: A mean apparent propagator (MAP) MRI study

The relationship between brain microstructure and aging has been the subject of intense study, with diffusion MRI perhaps the most effective modality for elucidating these associations. Here, we used the mean apparent propagator (MAP)-MRI framework, which is suitable to characterize complex microstructure, to investigate age-related cerebral differences in a cohort of cognitively unimpaired participants and compared the results to those derived using diffusion tensor imaging. We studied MAP-MRI metrics, among them the non-Gaussianity (NG) and propagator anisotropy (PA), and established an opposing pattern in white matter of higher NG alongside lower PA among older adults, likely indicative of axonal degradation. In gray matter, however, these two indices were consistent with one another, and exhibited regional pattern heterogeneity compared to other microstructural parameters, which could indicate fewer neuronal projections across cortical layers along with an increased glial concentration. In addition, we report regional variations in the magnitude of age-related microstructural differences consistent with the posterior-anterior shift in aging paradigm. These results encourage further investigations in cognitive impairments and neurodegeneration.

Compensatory cognition in neurological diseases and aging: A review of animal and human studies

Specialized individual circuits in the brain are recruited for specific functions. Interestingly, multiple neural circuitries continuously compete with each other to acquire the specialized function. However, the dominant among them compete and become the central neural network for that particular function. For example, the hippocampal principal neural circuitries are the dominant networks among many which are involved in learning processes. But, in the event of damage to the principal circuitry, many times, less dominant networks compensate for the primary network. This review highlights the psychopathologies of functional loss and the aspects of functional recuperation in the absence of the hippocampus.

Short superficial white matter and aging: a longitudinal multi-site study of 1293 subjects and 2711 sessions

It is estimated that short association fibers running immediately beneath the cortex may make up as much as 60% of the total white matter volume. However, these have been understudied relative to the long-range association, projection, and commissural fibers of the brain. This is largely because of limitations of diffusion MRI fiber tractography, which is the primary methodology used to non-invasively study the white matter connections. Inspired by recent anatomical considerations and methodological improvements in superficial white matter (SWM) tractography, we aim to characterize changes in these fiber systems in cognitively normal aging, which provide insight into the biological foundation of age-related cognitive changes, and a better understanding of how age-related pathology differs from healthy aging. To do this, we used three large, longitudinal and cross-sectional datasets (N = 1293 subjects, 2711 sessions) to quantify microstructural features and length/volume features of several SWM systems. We find that axial, radial, and mean diffusivities show positive associations with age, while fractional anisotropy has negative associations with age in SWM throughout the entire brain. These associations were most pronounced in the frontal, temporal, and temporoparietal regions. Moreover, measures of SWM volume and length decrease with age in a heterogenous manner across the brain, with different rates of change in inter-gyri and intra-gyri SWM, and at slower rates than well-studied long-range white matter pathways. These features, and their variations with age, provide the background for characterizing normal aging, and, in combination with larger association pathways and gray matter microstructural features, may provide insight into fundamental mechanisms associated with aging and cognition.

Aging and white matter microstructure and macrostructure: a longitudinal multi-site diffusion MRI study of 1218 participants

Quantifying the microstructural and macrostructural geometrical features of the human brain's connections is necessary for understanding normal aging and disease. Here, we examine brain white matter diffusion magnetic resonance imaging data from one cross-sectional and two longitudinal data sets totaling in 1218 subjects and 2459 sessions of people aged 50-97 years. Data was drawn from well-established cohorts, including the Baltimore Longitudinal Study of Aging data set, Cambridge Centre for Ageing Neuroscience data set, and the Vanderbilt Memory & Aging Project. Quantifying 4 microstructural features and, for the first time, 11 macrostructure-based features of volume, area, and length across 120 white matter pathways, we apply linear mixed effect modeling to investigate changes in pathway-specific features over time, and document large age associations within white matter. Conventional diffusion tensor microstructure indices are the most age-sensitive measures, with positive age associations for diffusivities and negative age associations with anisotropies, with similar patterns observed across all pathways. Similarly, pathway shape measures also change with age, with negative age associations for most length, surface area, and volume-based features. A particularly novel finding of this study is that while trends were homogeneous throughout the brain for microstructure features, macrostructural features demonstrated heterogeneity across pathways, whereby several projection, thalamic, and commissural tracts exhibited more decline with age compared to association and limbic tracts. The findings from this large-scale study provide a comprehensive overview of the age-related decline in white matter and demonstrate that macrostructural features may be more sensitive to heterogeneous white matter decline. Therefore, leveraging macrostructural features may be useful for studying aging and could facilitate comparisons in a variety of diseases or abnormal conditions.

Potential Diffusion Tensor Imaging Biomarkers for Elucidating Intra-Individual Age-Related Changes in Cognitive Control and Processing Speed

Cognitive aging, especially cognitive control, and processing speed aging have been well-documented in the literature. Most of the evidence was reported based on cross-sectional data, in which inter-individual age effects were shown. However, there have been some studies pointing out the possibility of overlooking intra-individual changes in cognitive aging. To systematically examine whether age-related differences and age-related changes might yield distinctive patterns, this study directly compared cognitive control function and processing speed between different cohorts versus follow-up changes across the adult lifespan. Moreover, considering that cognitive aging has been attributed to brain disconnection in white matter (WM) integrity, this study focused on WM integrity via acquiring diffusion-weighted imaging data with an MRI instrument that are further fitted to a diffusion tensor model (i.e., DTI) to detect water diffusion directionality (i.e., fractional anisotropy, FA; mean diffusivity, MD; radial diffusivity, RD; axial diffusivity, AxD). Following data preprocessing, 114 participants remained for further analyses in which they completed the two follow-up sessions (with a range of 1-2 years) containing a series of neuropsychology instruments and computerized cognitive control tasks. The results show that many significant correlations between age and cognitive control functions originally shown on cross-sectional data no longer exist on the longitudinal data. The current longitudinal data show that MD, RD, and AxD (especially in the association fibers of anterior thalamic radiation) are more strongly correlated to follow-up aging processes, suggesting that axonal/myelin damage is a more robust phenomenon for observing intra-individual aging processes. Moreover, processing speed appears to be the most prominent cognitive function to reflect DTI-related age (cross-sectional) and aging (longitudinal) effects. Finally, converging the results from regression analyses and mediation models, MD, RD, and AxD appear to be the representative DTI measures to reveal age-related changes in processing speed. To conclude, the current results provide new insights to which indicator of WM integrity and which type of cognitive changes are most representative (i.e., potentially to be neuroimaging biomarkers) to reflect intra-individual cognitive aging processes.

Associations Between Age and Resting State Connectivity Are Partially Dependent Upon Cardiovascular Fitness

Previous research suggests a marked impact of aging on structural and functional connectivity within the frontoparietal control network (FPCN) and default mode network (DMN). As aging is also associated with reductions in cardiovascular fitness, age-related network connectivity differences reported by past studies could be partially due to age-related declines in fitness. Here, we use data collected as part of a 16-week exercise intervention to explore relationships between fitness and functional connectivity. Young and older adults completed baseline assessments including cardiovascular fitness, health and functioning measures, and an fMRI session. Scan data were acquired on a Siemens 3T MRI scanner with a 32-channel head coil. Results from regression analyses indicated that average connectivity did not differ between young and older adults. However, individual ROI-to-ROI connectivity analyses indicated weaker functional correlations for older adults between specific regions in the FPCN and DMN and, critically, many of these differences were attenuated when fitness was accounted for. Taken together, findings suggest that fitness exerts regional rather than global effects on network connectivity.

Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.

Brain aging mechanisms with mechanical manifestations

Brain aging is a complex process that affects everything from the subcellular to the organ level, begins early in life, and accelerates with age. Morphologically, brain aging is primarily characterized by brain volume loss, cortical thinning, white matter degradation, loss of gyrification, and ventricular enlargement. Pathophysiologically, brain aging is associated with neuron cell shrinking, dendritic degeneration, demyelination, small vessel disease, metabolic slowing, microglial activation, and the formation of white matter lesions. In recent years, the mechanics community has demonstrated increasing interest in modeling the brain's (bio)mechanical behavior and uses constitutive modeling to predict shape changes of anatomically accurate finite element brain models in health and disease. Here, we pursue two objectives. First, we review existing imaging-based data on white and gray matter atrophy rates and organ-level aging patterns. This data is required to calibrate and validate constitutive brain models. Second, we review the most critical cell- and tissue-level aging mechanisms that drive white and gray matter changes. We focuse on aging mechanisms that ultimately manifest as organ-level shape changes based on the idea that the integration of imaging and mechanical modeling may help identify the tipping point when normal aging ends and pathological neurodegeneration begins.

Characterizing the canine and feline optic pathways in vivo with diffusion MRI

The visual system is known to be vital for cognition and perception in the feline and canine and much behavioral research for these species has used visual stimuli and focused on visual perception. There has been extensive investigations into the visual pathway in cats and dogs via histological and neurobiological methods, however to date, only one study has mapped the canine optic pathway in vivo. Advanced imaging methods such as diffusion MRI (DTI) have been routinely used in human research to study the visual system in vivo. This study applied DTI imaging methods to assess and characterize the optic pathway of feline and canine subjects in vivo. The optic nerve (ON), optic tract (OT), and optic radiation (OR) were successfully delineated for each species and the average volume and FA for each tract is reported. The application of DTI to map the optic pathway for canine and feline subjects provides a healthy baseline for comparison in future studies.

Ageing-related changes in nap neuroscillatory activity are mediated and moderated by grey matter volume

Ageing‐related changes in grey matter result in changes in the intensity and topography of sleep neural activity. However, it is unclear whether these findings can be explained by ageing‐related differences in sleep pressure or circadian influence. The current study used high‐density electroencephalography to assess how grey matter volume differences between young and older adults mediate and moderate neuroscillatory activity differences during a midday nap following a motor sequencing task. Delta, theta, and sigma amplitude were reduced in older relative to young adults, especially over frontocentral scalp, leading to increases in relative delta frontality and relative sigma lateral centroposteriority. Delta reductions in older adults were mediated by grey matter loss in frontal medial cortex, primary motor cortex, thalamus, caudate, putamen, and pallidum, and were moderated by putamen grey matter volume. Theta reductions were mediated by grey matter loss in primary motor cortex, thalamus, and caudate, and were moderated by putamen and pallidum grey matter volume. Sigma changes were moderated by putamen and pallidum grey matter volume. Moderation results suggested that across frequencies, young adults with more grey matter had increased activity, whereas older adults with more grey matter had unchanged or decreased activity. These results provide a critical extension of previous findings from overnight sleep in a midday nap, indicating that they are not driven by sleep pressure or circadian confounds. Moreover, these results suggest brain regions associated with motor sequence learning contribute to sleep neural activity following a motor sequencing task.

Estimates of brain age for gray matter and white matter in younger and older adults: Insights into human intelligence

Aging entails a multifaceted complex of changes in macro- and micro-structural properties of human brain gray matter (GM) and white matter (WM) tissues, as well as in intellectual abilities. To better capture tissue-specific brain aging, we combined volume and distribution properties of diffusivity indices to derive subject-specific age scores for each tissue. We compared age-related variance between younger and older adults for GM and WM age scores, and tested whether tissue-specific age scores could explain different effects of aging on fluid (Gf) and crystalized (Gc) intelligence in younger and older adults. Chronological age was strongly associated with GM (R2 = 0.73) and WM (R2 = 0.57) age scores. The GM age score accounted for significantly more variance in chronological age in younger relative to older adults (p < 0.001), whereas the WM age score accounted for significantly more variance in chronological age in older compared to younger adults (p < 0.025). Consistent with existing literature, younger adults outperformed older adults in Gf while older adults outperformed younger adults in Gc. The GM age score was negatively associated with Gf in younger adults (p < 0.02), whereas the WM age score was negatively associated with Gc in older adults (p < 0.02). Our results provide evidence for differences in the effects of age on GM and WM in younger versus older adults that may contribute to age-related differences in Gf and Gc.

Brain network analyses of diffusion tensor imaging for brain aging

The approach of graph-based diffusion tensor imaging (DTI) networks has been used to explore the complicated structural connectivity of brain aging. In this study, the changes of DTI networks of brain aging were quantitatively and qualitatively investigated by comparing the characteristics of brain network. A cohort of 60 volunteers was enrolled and equally divided into young adults (YA) and older adults (OA) groups. The network characteristics of critical nodes, path length (Lp), clustering coefficient (Cp), global efficiency (Eglobal), local efficiency (Elocal), strength (Sp), and small world attribute (σ) were employed to evaluate the DTI networks at the levels of whole brain, bilateral hemispheres and critical brain regions. The correlations between each network characteristic and age were predicted, respectively. Our findings suggested that the DTI networks produced significant changes in network configurations at the critical nodes and node edges for the YA and OA groups. The analysis of whole brains network revealed that Lp, Cp increased (p < 0.05, positive correlation), Eglobal, Elocal, Sp decreased (p < 0.05, negative correlation), and σ unchanged (p ≥ 0.05, non-correlation) between the YA and OA groups. The analyses of bilateral hemispheres and brain regions showed similar results as that of the whole-brain analysis. Therefore the proposed scheme of DTI networks could be used to evaluate the WM changes of brain aging, and the network characteristics of critical nodes exhibited valuable indications for WM degeneration.

Cross-Sectional Volumes and Trajectories of the Human Brain, Gray Matter, White Matter and Cerebrospinal Fluid in 9473 Typically Aging Adults

Accurate knowledge of adult human brain volume (BV) is critical for studies of aging- and disease-related brain alterations, and for monitoring the trajectories of neural and cognitive functions in conditions like Alzheimer's disease and traumatic brain injury. This scoping meta-analysis aggregates normative reference values for BV and three related volumetrics-gray matter volume (GMV), white matter volume (WMV) and cerebrospinal fluid volume (CSFV)-from typically-aging adults studied cross-sectionally using magnetic resonance imaging (MRI). Drawing from an aggregate sample of 9473 adults, this study provides (A) regression coefficients β describing the age-dependent trajectories of volumetric measures by sex within the range from 20 to 70 years based on both linear and quadratic models, and (B) average values for BV, GMV, WMV and CSFV at the representative ages of 20 (young age), 45 (middle age) and 70 (old age). The results provided synthesize ~20 years of brain volumetrics research and allow one to estimate BV at any age between 20 and 70. Importantly, however, such estimates should be used and interpreted with caution because they depend on MRI hardware specifications (e.g. scanner manufacturer, magnetic field strength), data acquisition parameters (e.g. spatial resolution, weighting), and brain segmentation algorithms. Guidelines are proposed to facilitate future meta- and mega-analyses of brain volumetrics.

Diffusion tensor-based analysis of white matter in the healthy aging canine brain

White matter dysfunction and degeneration have been a topic of great interest in healthy and pathological aging. While ex vivo studies have investigated age-related changes in canines, little in vivo canine aging research exists. Quantitative diffusion MRI such as diffusion tensor imaging (DTI) has demonstrated aging and neurodegenerative white matter changes in humans. However, this method has not been applied and adapted in vivo to canine populations. This study aimed to test the hypothesis that white matter diffusion changes frequently reported in human aging are also found in aged canines. The study used Tract Based Spatial Statistics (TBSS) and a region of interest (ROI) approach to investigate age related changes in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AxD) and radial diffusivity (RD). The results show that, compared to younger animals, aged canines have significant decreases in FA in parietal and temporal regions as well as the corpus callosum and fornix. Additionally, AxD decreases were observed in parietal, frontal, and midbrain regions. Similarly, an age- related increase in RD was observed in the right parietal lobe while MD decreases were found in the midbrain. These findings suggest that canine samples show commonalities with human brain aging as both exhibit similar white matter diffusion tensor changes with increasing age.

Anterior Cingulate Structure and Perfusion is Associated with Cerebrospinal Fluid Tau among Cognitively Normal Older Adult APOEɛ4 Carriers

Evidence suggests the ɛ4 allele of the apolipoprotein E (APOE) gene may accelerate an age-related process of cortical thickening and cerebral blood flow (CBF) reduction in the anterior cingulate cortex (ACC). Although the neural basis of this association remains unclear, evidence suggests it might reflect early neurodegenerative processes. However, to date, associations between cerebrospinal fluid (CSF) biomarkers of neurodegeneration, such as CSF tau, and APOE-related alterations in ACC cortical thickness (CTH) and CBF have yet to be explored. The current study explored the interaction of CSF tau and APOE genotype (ɛ4+, ɛ4-) on FreeSurfer-derived CTH and arterial spin labeling MRI-measured resting CBF in the ACC (caudal ACC [cACC] and rostral ACC [rACC]) among a sample of 45 cognitively normal older adults. Secondary analyses also examined associations between APOE, CTH/CBF, and cognitive performance. In the cACC, higher CSF tau was associated with higher CTH and lower CBF in ɛ4+, whereas these relationships were not evident in ɛ4-. In the rACC, higher CSF tau was associated with higher CTH for both ɛ4+ and ɛ4-, and with lower CBF only in ɛ4+. Significant interactions of CSF tau and APOE on CTH/CBF were not observed in two posterior reference regions implicated in Alzheimer's disease. Secondary analyses revealed a negative relationship between cACC CTH and executive functioning in ɛ4+ and a positive relationship in ɛ4-. Findings suggest the presence of an ɛ4-related pattern of increased CTH and reduced CBF in the ACC that is associated with biomarkers of neurodegeneration and subtle decrements in cognition.

Age-Related Changes in Relaxation Times, Proton Density, Myelin, and Tissue Volumes in Adult Brain Analyzed by 2-Dimensional Quantitative Synthetic Magnetic Resonance Imaging

OBJECTIVES

Quantitative synthetic magnetic resonance imaging (MRI) enables the determination of fundamental tissue properties, namely, T1 and T2 relaxation times and proton density (PD), in a single scan. Myelin estimation and brain segmentation based on these quantitative values can also be performed automatically. This study aimed to reveal the changes in tissue characteristics and volumes of the brain according to age and provide age-specific reference values obtained by quantitative synthetic MRI.

MATERIALS AND METHODS

This was a prospective study of healthy subjects with no history of brain diseases scanned with a multidynamic multiecho sequence for simultaneous measurement of relaxometry of T1, T2, and PD. We performed myelin estimation and brain volumetry based on these values. We performed volume-of-interest analysis on both gray matter (GM) and white matter (WM) regions for T1, T2, PD, and myelin volume fraction maps. Tissue volumes were calculated in the whole brain, producing brain parenchymal volume, GM volume, WM volume, and myelin volume. These volumes were normalized by intracranial volume to a brain parenchymal fraction, GM fraction, WM fraction, and myelin fraction (MyF). We examined the changes in the mean regional quantitative values and segmented tissue volumes according to age.

RESULTS

We analyzed data of 114 adults (53 men and 61 women; median age, 66.5 years; range, 21-86 years). T1, T2, and PD values showed quadratic changes according to age and stayed stable or decreased until around 60 years of age and increased thereafter. Myelin volume fraction showed a reversed trend. Brain parenchymal fraction and GM fraction decreased throughout all ages. The approximation curves showed that WM fraction and MyF gradually increased until around the 40s to 50s and decreased thereafter. A significant decline in MyF was first noted in the 60s age group (Tukey test, P < 0.001).

CONCLUSIONS

Our study showed changes according to age in tissue characteristic values and brain volumes using quantitative synthetic MRI. The reference values for age demonstrated in this study may be useful to discriminate brain disorders from healthy brains.

Age-related changes in chimpanzee (Pan troglodytes) cognition: Cross-sectional and longitudinal analyses

Chimpanzees are the species most closely related to humans, yet age-related changes in brain and cognition remain poorly understood. The lack of studies on age-related changes in cognition in chimpanzees is particularly unfortunate in light of the recent evidence demonstrating that this species naturally develops Alzheimer's disease (AD) neuropathology. Here, we tested 213 young, middle-aged, and elderly captive chimpanzees on the primate cognitive test battery (PCTB), a set of 13 tasks that assess physical and social cognition in nonhuman primates. A subset of these chimpanzees (n = 146) was tested a second time on a portion of the PCTB tasks as a means of evaluating longitudinal changes in cognition. Cross-sectional analyses revealed a significant quadratic association between age and cognition with younger and older chimpanzees performing more poorly than middle-aged individuals. Longitudinal analyses showed that the oldest chimpanzees at the time of the first test showed the greatest decline in cognition, although the effect was mild. The collective data show that chimpanzees, like other nonhuman primates, show age-related decline in cognition. Further investigations into whether the observed cognitive decline is associated with AD pathologies in chimpanzees would be invaluable in understanding the comparative biology of aging and neuropathology in primates.

Elevated Circulating Microparticle Subpopulations in Incidental Cerebral White Matter Hyperintensities: A Multimodal Study

Asymptomatic (or "silent") manifestations of cerebral small vessel disease (CSVD) are widely recognized through incidental findings of white matter hyperintensities (WMHs) as a result of magnetic resonance imaging (MRI). This study aims to examine the potential associations of surrogate markers for the evaluation of white matter integrity in CSVD among asymptomatic individuals through a battery of profiling involving QRISK2 cardiocerebrovascular risk prediction, neuroimaging, neurocognitive evaluation, and microparticles (MPs) titers. Sixty asymptomatic subjects (mean age: 39.83 ± 11.50 years) with low to moderate QRISK2 scores were recruited and underwent neurocognitive evaluation for memory and cognitive performance, peripheral venous blood collection for enumeration of selected MPs subpopulations, and 3T MRI brain scan with specific diffusion MRI (dMRI) sequences inclusive of diffusion tensor imaging (DTI). WMHs were detected in 20 subjects (33%). Older subjects (mean age: 46.00 ± 12.00 years) had higher WMHs prevalence, associated with higher QRISK2 score and reduced processing speed. They also had significantly higher mean percentage of platelet (CD62P)- and leukocyte (CD62L)-derived MPs. No association was found between reduced white matter integrity-especially at the left superior longitudinal fasciculus (LSLF)-with age and neurocognitive function; however, LSLF was associated with higher QRISK2 score, total MPs, and CD62L- and endothelial cell-derived MPs (CD146). Therefore, this study establishes these multimodal associations as potential surrogate markers for "silent" CSVD manifestations in the well-characterized cardiocerebrovascular demographic of relatively young, neurologically asymptomatic adults. Furthermore, to the best of our knowledge, this study is the first to exhibit elevated MP counts in asymptomatic CSVD (i.e., CD62P and CD62L), which warrants further delineation.

Deep learning encodes robust discriminative neuroimaging representations to outperform standard machine learning

Recent critical commentaries unfavorably compare deep learning (DL) with standard machine learning (SML) approaches for brain imaging data analysis. However, their conclusions are often based on pre-engineered features depriving DL of its main advantage — representation learning. We conduct a large-scale systematic comparison profiled in multiple classification and regression tasks on structural MRI images and show the importance of representation learning for DL. Results show that if trained following prevalent DL practices, DL methods have the potential to scale particularly well and substantially improve compared to SML methods, while also presenting a lower asymptotic complexity in relative computational time, despite being more complex. We also demonstrate that DL embeddings span comprehensible task-specific projection spectra and that DL consistently localizes task-discriminative brain biomarkers. Our findings highlight the presence of nonlinearities in neuroimaging data that DL can exploit to generate superior task-discriminative representations for characterizing the human brain.

Recent critical commentaries unfavorably compare deep learning (DL) with standard machine learning (SML) for brain imaging data analysis. Here, the authors show that if trained following prevalent DL practices, DL methods substantially improve compared to SML methods by encoding robust discriminative brain representations.

Glutamine + glutamate level predicts the magnitude of microstructural organization in the gray matter in the healthy elderly

BACKGROUND

Diffusion tensor imaging (DTI), which is a technique for measuring the degree and direction of movement of water molecules in tissue, has been widely used to noninvasively assess white matter (WM) or gray matter (GM) microstructures in vivo. Mean diffusivity (MD), which is the average diffusion across all directions, has been considered as a marker of WM tract degeneration or extracellular space enlargement in GM. Recent lines of evidence suggest that cortical MD can better identify early-stage Alzheimer's disease than structural morphometric parameters in magnetic resonance imaging. However, knowledge of the relationships between cortical MD and other biological factors in the same cortical region, e.g. metabolites, is still limited.

METHODS

Thirty-three healthy elderly individuals [aged 50-77 years (mean, 63.8±7.4 years); 11 males and 22 females] were enrolled. We estimated the associations between cortical MD and neurotransmitter levels. Specifically, we measured levels of γ-aminobutyric acid (GABA) and glutamate + glutamine (Glx), which are inhibitory and excitatory neurotransmitters, respectively, in medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC) using MEGA-PRESS magnetic resonance spectroscopy, and we measured regional cortical MD using DTI.

RESULTS

Cortical MD was significantly negatively associated with Glx levels in both mPFC and PCC. No significant association was observed between cortical MD and GABA levels in either GM region.

CONCLUSION

Our findings suggest that degeneration of microstructural organization in GM, as determined on the basis of cortical MD measured by DTI, is accompanied by the decline of Glx metabolism within the same GM region.

Brain Substrates of Time-Based Prospective Memory Decline in Aging: A Voxel-Based Morphometry and Diffusion Tensor Imaging Study

Time-based prospective memory (TBPM) allows us to remember to perform intended actions at a specific time in the future. TBPM is sensitive to the effects of age, but the neural substrates of this decline are still poorly understood. The aim of the present study was thus to better characterize the brain substrates of the age-related decline in TBPM, focusing on macrostructural gray matter and microstructural white matter integrity. We administered a TBPM task to 22 healthy young (26 ± 5.2 years) and 23 older (63 ± 5.9 years) participants, who also underwent volumetric magnetic resonance imaging and diffusion tensor imaging scans. Neuroimaging analyses revealed lower gray matter volumes in several brain areas in older participants, but these did not correlate with TBPM performance. By contrast, an age-related decline in fractional anisotropy in several white-matter tracts connecting frontal and occipital regions did correlate with TBPM performance, whereas there was no significant correlation in healthy young subjects. According to the literature, these tracts are connected to the anterior prefrontal cortex and the thalamus, 2 structures involved in TBPM. These results confirm the view that a disconnection process occurs in aging and contributes to cognitive decline.

Auditory and Visual System White Matter Is Differentially Impacted by Normative Aging in Macaques

Deficits in auditory and visual processing are commonly encountered by older individuals. In addition to the relatively well described age-associated pathologies that reduce sensory processing at the level of the cochlea and eye, multiple changes occur along the ascending auditory and visual pathways that further reduce sensory function in each domain. One fundamental question that remains to be directly addressed is whether the structure and function of the central auditory and visual systems follow similar trajectories across the lifespan or sustain the impacts of brain aging independently. The present study used diffusion magnetic resonance imaging and electrophysiological assessments of auditory and visual system function in adult and aged macaques to better understand how age-related changes in white matter connectivity at multiple levels of each sensory system might impact auditory and visual function. In particular, the fractional anisotropy (FA) of auditory and visual system thalamocortical and interhemispheric corticocortical connections was estimated using probabilistic tractography analyses. Sensory processing and sensory system FA were both reduced in older animals compared with younger adults. Corticocortical FA was significantly reduced only in white matter of the auditory system of aged monkeys, while thalamocortical FA was lower only in visual system white matter of the same animals. Importantly, these structural alterations were significantly associated with sensory function within each domain. Together, these results indicate that age-associated deficits in auditory and visual processing emerge in part from microstructural alterations to specific sensory white matter tracts, and not from general differences in white matter condition across the aging brain.SIGNIFICANCE STATEMENT Age-associated deficits in sensory processing arise from structural and functional alterations to both peripheral sensory organs and central brain regions. It remains unclear whether different sensory systems undergo similar or distinct trajectories in function across the lifespan. To provide novel insights into this question, this study combines electrophysiological assessments of auditory and visual function with diffusion MRI in aged macaques. The results suggest that age-related sensory processing deficits in part result from factors that impact the condition of specific white matter tracts, and not from general decreases in connectivity between sensory brain regions. Such anatomic specificity argues for a framework aimed at understanding vulnerabilities with relatively local influence and brain region specificity.

Hippocampal and Parahippocampal Gray Matter Structural Integrity Assessed by Multimodal Imaging Is Associated with Episodic Memory in Old Age

Maintained structural integrity of hippocampal and cortical gray matter may explain why some older adults show rather preserved episodic memory. However, viable measurement models for estimating individual differences in gray matter structural integrity are lacking; instead, findings rely on fallible single indicators of integrity. Here, we introduce multitrait–multimethod methodology to capture individual differences in gray matter integrity, based on multimodal structural imaging in a large sample of 1522 healthy adults aged 60–88 years from the Berlin Aging Study II, including 333 participants who underwent magnetic resonance imaging. Structural integrity factors expressed the common variance of voxel-based morphometry, mean diffusivity, and magnetization transfer ratio for each of four regions of interest: hippocampus, parahippocampal gyrus, prefrontal cortex, and precuneus. Except for precuneus, the integrity factors correlated with episodic memory. Associations with hippocampal and parahippocampal integrity persisted after controlling for age, sex, and education. Our results support the proposition that episodic memory ability in old age benefits from maintained structural integrity of hippocampus and parahippocampal gyrus. Exploratory follow-up analyses on sex differences showed that this effect is restricted to men. Multimodal factors of structural brain integrity might help to improve our biological understanding of human memory aging.

Predicting brain age with complex networks: From adolescence to adulthood

In recent years, several studies have demonstrated that machine learning and deep learning systems can be very useful to accurately predict brain age. In this work, we propose a novel approach based on complex networks using 1016 T1-weighted MRI brain scans (in the age range 7-64years). We introduce a structural connectivity model of the human brain: MRI scans are divided in rectangular boxes and Pearson's correlation is measured among them in order to obtain a complex network model. Brain connectivity is then characterized through few and easy-to-interpret centrality measures; finally, brain age is predicted by feeding a compact deep neural network. The proposed approach is accurate, robust and computationally efficient, despite the large and heterogeneous dataset used. Age prediction accuracy, in terms of correlation between predicted and actual age r=0.89and Mean Absolute Error MAE =2.19years, compares favorably with results from state-of-the-art approaches. On an independent test set including 262 subjects, whose scans were acquired with different scanners and protocols we found MAE =2.52. The only imaging analysis steps required in the proposed framework are brain extraction and linear registration, hence robust results are obtained with a low computational cost. In addition, the network model provides a novel insight on aging patterns within the brain and specific information about anatomical districts displaying relevant changes with aging.

Neuroanatomical changes associated with age-related hearing loss and listening effort

Age-related hearing loss is associated with a decrease in hearing abilities for high frequencies and therefore leads to impairments in understanding speech—in particular, under adverse listening conditions. Growing evidence suggests that age-related hearing loss is related to various neural changes, for instance, affecting auditory and frontal brain regions. How the decreased auditory input and the increased listening effort in daily life are associated with structural changes is less clear, since previous evidence is scarce and mostly involved low sample sizes. Hence, the aim of the current study was to investigate the impact of age-related untreated hearing loss and subjectively rated daily life listening effort on grey matter and white matter changes in a large sample of participants (n = 71). For that aim, we conducted anatomical MRI and diffusion tensor imaging (DTI) in elderly hard-of-hearing and age-matched normal-hearing participants. Our results showed significantly lower grey matter volume in the middle frontal cortex in hard-of-hearing compared to normal-hearing participants. Further, higher listening effort was associated with lower grey matter volume and cortical thickness in the orbitofrontal cortex and lower grey matter volume in the inferior frontal cortex. No significant relations between hearing abilities or listening effort were obtained for white matter integrity in tracts connecting auditory and prefrontal as well as visual areas. These findings provide evidence that hearing impairment as well as daily life listening effort seems to be associated with grey matter loss in prefrontal brain regions. We further conclude that alterations in cortical thickness seem to be linked to the increased listening effort rather than the hearing loss itself.

Cerebellar and prefrontal-cortical engagement during higher-order rule learning in older adulthood

To date most aging research has focused on cortical systems and networks, ignoring the cerebellum which has been implicated in both cognitive and motor function. Critically, older adults (OA) show marked differences in cerebellar volume and functional networks, suggesting it may play a key role in the behavioral differences observed in advanced age. OA may be less able to recruit cerebellar resources due to network and structural differences. Here, 26 young adults (YA) and 25 OA performed a second-order learning task, known to activate the cerebellum in the fMRI environment. Behavioral results indicated that YA performed significantly better and learned more quickly compared to OA. Functional imaging detailed robust parietal and cerebellar activity during learning (compared to control) blocks within each group. OA showed increased activity (relative to YA) in the left inferior parietal lobe in response to instruction cues during learning (compared to control); whereas, YA showed increased activity (relative to OA) in the left anterior cingulate to feedback cues during learning, potentially explaining age-related performance differences. Visual interpretation of effect size maps showed more bilateral posterior cerebellar activation in OA compared to YA during learning blocks, but early learning showed widespread cerebellar activation in YA compared to OA. There were qualitatively large age-related differences in cerebellar recruitment in terms of effect sizes, yet no statistical difference. These findings serve to further elucidate age-related differences and similarities in cerebellar and cortical brain function and implicate the cerebellum and its networks as regions of interest in aging research.

Stratifying major depressive disorder by polygenic risk for schizophrenia in relation to structural brain measures

BACKGROUND

Substantial clinical heterogeneity of major depressive disorder (MDD) suggests it may group together individuals with diverse aetiologies. Identifying distinct subtypes should lead to more effective diagnosis and treatment, while providing more useful targets for further research. Genetic and clinical overlap between MDD and schizophrenia (SCZ) suggests an MDD subtype may share underlying mechanisms with SCZ.

METHODS

The present study investigated whether a neurobiologically distinct subtype of MDD could be identified by SCZ polygenic risk score (PRS). We explored interactive effects between SCZ PRS and MDD case/control status on a range of cortical, subcortical and white matter metrics among 2370 male and 2574 female UK Biobank participants.

RESULTS

There was a significant SCZ PRS by MDD interaction for rostral anterior cingulate cortex (RACC) thickness (β = 0.191, q = 0.043). This was driven by a positive association between SCZ PRS and RACC thickness among MDD cases (β = 0.098, p = 0.026), compared to a negative association among controls (β = -0.087, p = 0.002). MDD cases with low SCZ PRS showed thinner RACC, although the opposite difference for high-SCZ-PRS cases was not significant. There were nominal interactions for other brain metrics, but none remained significant after correcting for multiple comparisons.

CONCLUSIONS

Our significant results indicate that MDD case-control differences in RACC thickness vary as a function of SCZ PRS. Although this was not the case for most other brain measures assessed, our specific findings still provide some further evidence that MDD in the presence of high genetic risk for SCZ is subtly neurobiologically distinct from MDD in general.

The Montreal Cognitive Assessment (MoCA) and Brain Structure

Abstract. MoCA is a short cognitive screening tool. We examined the relationship of MoCA performance to white matter integrity, gray matter volume, and surface-based measurements at normal aging in a study in which older and younger cognitively unaffected subjects participated. The sample was split according to MoCA performance, and the data were analyzed using a general linear model (Age × MoCA). We found effects in the expected direction for all methods. The main effects on age and performance as well as interactions occurred for regions associated with aging, pathological and nonpathological. Older low-performing subjects showed structural deficits compared to older high-performing subjects. Therefore, the global index of cognitive status reflects relevant features of the brain structure.

Age-related structural and functional variations in 5,967 individuals across the adult lifespan

Exploring brain changes across the human lifespan is becoming an important topic in neuroscience. Though there are multiple studies which investigated the relationship between age and brain imaging, the results are heterogeneous due to small sample sizes and relatively narrow age ranges. Here, based on year-wise estimation of 5,967 subjects from 13 to 72 years old, we aimed to provide a more precise description of adult lifespan variation trajectories of gray matter volume (GMV), structural network correlation (SNC), and functional network connectivity (FNC) using independent component analysis and multivariate linear regression model. Our results revealed the following relationships: (a) GMV linearly declined with age in most regions, while parahippocampus showed an inverted U-shape quadratic relationship with age; SNC presented a U-shape quadratic relationship with age within cerebellum, and inverted U-shape relationship primarily in the default mode network (DMN) and frontoparietal (FP) related correlation. (b) FNC tended to linearly decrease within resting-state networks (RSNs), especially in the visual network and DMN. Early increase was revealed between RSNs, primarily in FP and DMN, which experienced a decrease at older ages. U-shape relationship was also revealed to compensate for the cognition deficit in attention and subcortical related connectivity at late years. (c) The link between middle occipital gyrus and insula, as well as precuneus and cerebellum, exhibited similar changing trends between SNC and FNC across the adult lifespan. Collectively, these results highlight the benefit of lifespan study and provide a precise description of age-related regional variation and SNC/FNC changes based on a large dataset.

Volumetric reduction of cerebellar lobules associated with memory decline across the adult lifespan

Background

The human cerebellum plays an essential role in motor control, is involved in cognitive function and helps to regulate emotional responses. However, little is known about the relationship between cerebellar lobules and age-related memory decline. We aimed to investigate volume alterations in cerebellar lobules at different ages and assess their correlations with reduced memory recall abilities.

Methods

A sample of 275 individuals were divided into the following four groups: 20-35 years (young), 36-50 years (early-middle age), 51-65 years (late-middle age), and 66-89 years (old). Volumes of the cerebellar lobules were obtained using volBrain software. Analysis of covariance and post hoc analysis were used to analyze group differences in cerebellar lobular volumes, and multiple comparisons were performed using the Bonferroni method. Spearman correlation was used to investigate the relationship between lobular volumes and memory recall scores.

Results

In this study, we found that older adults had smaller cerebellar volumes than the other subjects. Volumetric decreases in size were noted in bilateral lobule VI and lobule crus I. Moreover, the volumes of bilateral lobule crus I, lobule VI, and right lobule IV were significantly associated with memory recall scores.

Conclusions

In the present study, we found that some lobules of the cerebellum appear more predisposed to age-related changes than other lobules. These findings provide further evidence that specific regions of the cerebellum could be used to assess the risk of memory decline across the adult lifespan.

Brain Age Prediction With Morphological Features Using Deep Neural Networks: Results From Predictive Analytic Competition 2019

Morphological changes in the brain over the lifespan have been successfully described by using structural magnetic resonance imaging (MRI) in conjunction with machine learning (ML) algorithms. International challenges and scientific initiatives to share open access imaging datasets also contributed significantly to the advance in brain structure characterization and brain age prediction methods. In this work, we present the results of the predictive model based on deep neural networks (DNN) proposed during the Predictive Analytic Competition 2019 for brain age prediction of 2638 healthy individuals. We used FreeSurfer software to extract some morphological descriptors from the raw MRI scans of the subjects collected from 17 sites. We compared the proposed DNN architecture with other ML algorithms commonly used in the literature (RF, SVR, Lasso). Our results highlight that the DNN models achieved the best performance with MAE = 4.6 on the hold-out test, outperforming the other ML strategies. We also propose a complete ML framework to perform a robust statistical evaluation of feature importance for the clinical interpretability of the results.

MR-based age-related effects on the striatum, globus pallidus, and thalamus in healthy individuals across the adult lifespan

While numerous studies have used magnetic resonance imaging (MRI) to elucidate normative age-related trajectories in subcortical structures across the human lifespan, there exists substantial heterogeneity among different studies. Here, we investigated the normative relationships between age and morphology (i.e., volume and shape), and microstructure (using the T1-weighted/T2-weighted [T1w/T2w] signal ratio as a putative index of myelin and microstructure) of the striatum, globus pallidus, and thalamus across the adult lifespan using a dataset carefully quality controlled, yielding a final sample of 178 for the morphological analyses, and 162 for the T1w/T2w analyses from an initial dataset of 253 healthy subjects, aged 18-83. In accordance with previous cross-sectional studies of adults, we observed age-related volume decrease that followed a quadratic relationship between age and bilateral striatal and thalamic volumes, and a linear relationship in the globus pallidus. Our shape indices consistently demonstrated age-related posterior and medial areal contraction bilaterally across all three structures. Beyond morphology, we observed a quadratic inverted U-shaped relationship between T1w/T2w signal ratio and age, with a peak value occurring in middle age (at around 50 years old). After permutation testing, the Akaike information criterion determined age relationships remained significant for the bilateral globus pallidus and thalamus, for both the volumetric and T1w/T2w analyses. Our findings serve to strengthen and expand upon previous volumetric analyses by providing a normative baseline of morphology and microstructure of these structures to which future studies investigating patients with various disorders can be compared.

Differences in topological progression profile among neurodegenerative diseases from imaging data

The spatial distribution of atrophy in neurodegenerative diseases suggests that brain connectivity mediates disease propagation. Different descriptors of the connectivity graph potentially relate to different underlying mechanisms of propagation. Previous approaches for evaluating the influence of connectivity on neurodegeneration consider each descriptor in isolation and match predictions against late-stage atrophy patterns. We introduce the notion of a topological profile - a characteristic combination of topological descriptors that best describes the propagation of pathology in a particular disease. By drawing on recent advances in disease progression modeling, we estimate topological profiles from the full course of pathology accumulation, at both cohort and individual levels. Experimental results comparing topological profiles for Alzheimer's disease, multiple sclerosis and normal ageing show that topological profiles explain the observed data better than single descriptors. Within each condition, most individual profiles cluster around the cohort-level profile, and individuals whose profiles align more closely with other cohort-level profiles show features of that cohort. The cohort-level profiles suggest new insights into the biological mechanisms underlying pathology propagation in each disease.

The Effects of Lutein and Zeaxanthin Supplementation on Brain Morphology in Older Adults: A Randomized, Controlled Trial

A growing literature emphasizes the importance of lifestyle factors such as nutrition in successful aging. The current study examined if one year of supplementation with lutein (L) and zeaxanthin (Z), two nutrients with known antioxidative properties and cognitive benefits, impacted structural brain outcomes in older adults using a double-blind, randomized, placebo-controlled trial design. Community-dwelling older adults (20 males and 27 females) aged 65–87 years (M = 71.8 years, SD = 6.04 years) were randomized into supplement (N = 33) and placebo groups (N = 14) using simple randomization. The supplement group received 10 mg L + 2 mg Z daily for 12 months while the placebo group received a visually identical, inert placebo. L and Z were measured via retinal concentrations (macular pigment optical density or MPOD). Structural brain outcomes, focusing on global and frontal-temporal lobe regions, were acquired using both T1-weighted and DTI MRI sequences. We hypothesized that the supplement group would increase, maintain, or show attenuated loss in hypothesized regions-of-interest (ROIs) while the placebo group would show age-related declines in brain structural integrity over the course of the trial. While results showed age-related declines for frontal and temporal gray and white matter volumes, as well as fornix white matter microstructure across both groups, only minimal differences were found between the supplement and placebo groups. However, exploratory analyses showed that individuals who responded better to supplementation (i.e., showed greater increases in MPOD) showed less decline in global and prefrontal gray matter volume than supplement “nonresponders.” While results suggest that one year of L and Z supplementation may have limited effects on structural brain outcomes overall, there may be a subsample of individuals for whom supplementation of L and Z provides greater benefits. ClinicalTrials.gov number, NCT02023645.

Individual identification for different age groups using functional connectivity strength

BACKGROUND AND PURPOSE

Many studies demonstrate individual differences in functional network, especially those with age. Meanwhile, aging is one of the potential risk factors for Alzheimer's disease. Therefore, it is important to explore the discrepant pattern in aging population.

METHODS

Most existing methods mostly target ancient atlas for the extraction of the classification features and not consider the effect of global signal. We use two novel atlases for the extraction of classification features and then use the whole and intra-hemispheric functional connectivity strength (FCS) as classification parameters to classify different age groups, respectively. Meanwhile, the regression of global signal or not during the preprocessing has been considered. Next, the support vector machine-recursive feature elimination (SVM-RFE) method is applied for feature selection and the SVM method is applied for classification. In addition, the receiver operating characteristic curve and area under the curve are drawn to evaluate the robustness of classifier. Finally, the discriminative features are related to the physiological mechanism of aging.

RESULTS

The promising classification performance exhibits that the FCS can effectively distinguish different age groups. Moreover, the SVM-RFE method can increase the accuracy and extract the discriminative features. The classifiers constructed by the features derived from different atlas receive similar classification performance.

CONCLUSION

This study successfully distinguishes the young group, middle-aged group, and elderly group through FCS parameter, indicating the functional pattern of the network exists difference between three groups. Moreover, the results received by the SVM-RFE method and SVM classifier have the very good robustness and not specific to particular atlas and not affected by global signal and appropriate for the FCS of the whole brain or intra-hemisphere, which suggests that we can apply them to disease diagnosis in the future.

Fatigue Is Associated With Global and Regional Thalamic Morphometry in Veterans With a History of Mild Traumatic Brain Injury

OBJECTIVE

Fatigue is a complex, multidimensional phenomenon that commonly occurs following traumatic brain injury (TBI). The thalamus-a structure vulnerable to both primary and secondary injuries in TBI-is thought to play a pivotal role in the manifestation of fatigue. We explored how neuroimaging markers of local and global thalamic morphometry relate to the subjective experience of fatigue post-TBI.

METHODS

Sixty-three Veterans with a history of mild TBI underwent structural magnetic resonance imaging and completed questionnaires related to fatigue and psychiatric symptoms. FMRIB's Software (FSL) was utilized to obtain whole brain and thalamic volume estimates, as well as to perform regional thalamic morphometry analyses.

RESULTS

Independent of age, sex, intracranial volume, posttraumatic stress disorder, and depressive symptoms, greater levels of self-reported fatigue were significantly associated with decreased right (P = .026) and left (P = .046) thalamic volumes. Regional morphometry analyses revealed that fatigue was significantly associated with reductions in the anterior and dorsomedial aspects of the right thalamic body (P < .05). Similar trends were observed for the left thalamic body (P < .10).

CONCLUSIONS

Both global and regional thalamic morphometric changes are associated with the subjective experience of fatigue in Veterans with a history of mild TBI. These findings support a theory in which disruption of thalamocorticostriatal circuitry may result in the manifestation of fatigue in individuals with a history of neurotrauma.

The association between white matter and sleep spindles differs in young and older individuals

Study Objectives

Sleep is a reliable indicator of cognitive health in older individuals. Sleep spindles (SS) are non-rapid eye movement (NREM) sleep oscillations implicated in sleep-dependent learning. Their generation imply a complex activation of the thalamo-cortico-thalamic loop. Since SS require neuronal synchrony, the integrity of the white matter (WM) underlying these connections is of major importance. During aging, both SS and WM undergo important changes. The goal of this study was to investigate whether WM integrity could predict the age-related reductions in SS characteristics.

Methods

Thirty young and 31 older participants underwent a night of polysomnographic recording and a 3T magnetic resonance imaging acquisition including a diffusion sequence. SS were detected in NREM sleep and EEG spectral analysis was performed for the sigma frequency band. WM diffusion metrics were computed in a voxelwise design of analysis.

Results

Compared to young participants, older individuals showed lower SS density, amplitude, and sigma power. Diffusion metrics were correlated with SS amplitude and sigma power in tracts connecting the thalamus to the frontal cortex for the young but not for the older group, suggesting a moderation effect. Moderation analyses showed that diffusion metrics explained between 14% and 39% of SS amplitude and sigma power variance in the young participants only.

Conclusion

Our results indicate that WM underlying the thalamo-cortico-thalamic loop predicts SS characteristics in young individuals, but does not explain age-related changes in SS. Other neurophysiological factors could better explain the effect of age on SS characteristics.

APOE modifies the interaction of entorhinal cerebral blood flow and cortical thickness on memory function in cognitively normal older adults

OBJECTIVE

The ε4 allele of the apolipoprotein E (APOE) gene increases risk for cognitive decline in normal and pathologic aging. However, precisely how APOE ε4 exerts its negative impact on cognition is poorly understood. The present study aimed to determine whether APOE genotype (ε4+ vs. ε4-) modifies the interaction of medial temporal lobe (MTL) resting cerebral blood flow (CBF) and brain structure (cortical thickness [CT], volume [Vo]) on verbal memory performance.

METHODS

Multiple linear regression models were employed to investigate relationships between APOE genotype, arterial spin labeling MRI-measured CBF and FreeSurfer-based CT and Vo in four MTL regions of interest (left and right entorhinal cortex and hippocampus), and verbal memory performance among a sample of 117 cognitively normal older adults (41 ε4+, 76 ε4-) between the ages of 64 and 89 (mean age ​= ​73).

RESULTS

Results indicated that APOE genotype modified the interaction of CBF and CT on memory in the left entorhinal cortex, such that the relationship between entorhinal CBF and memory was negative (lower CBF was associated with better memory) in non-carriers with higher entorhinal CT, positive (higher CBF was associated with better memory) in non-carriers with lower entorhinal CT, and negative (higher CBF was associated with worse memory) in ε4 carriers with lower entorhinal CT.

CONCLUSIONS

Findings suggest that older adult APOE ε4 carriers may experience vascular dysregulation and concomitant morphological alterations in the MTL that interact to negatively affect memory even in the absence overt clinical symptoms, providing potential insight into the mechanistic link between APOE ε4 and detriments in cognition. Moreover, findings suggest a distinct multimodal neural signature in ε4 carriers (higher CBF and lower CT in the entorhinal cortex) that could aid in the identification of candidates for future clinical trials aimed at preventing or slowing cognitive decline. Differential findings with respect to ε4 carriers and non-carriers are discussed in the context of neurovascular compensation.