Preservation of limbic and paralimbic structures in aging

A multimodal neuroimaging meta-analysis of functional and structural brain abnormalities in attention-deficit/hyperactivity disorder

BACKGROUND

Numerous neuroimaging studies utilizing resting-state functional imaging and voxel-based morphometry (VBM) have identified variations in distinct brain regions among individuals with attention-deficit/hyperactivity disorder (ADHD). However, the results have been inconsistent.

METHODS

A comprehensive voxel-wise meta-analysis was performed on studies employing resting-state functional imaging and gray matter volume (GMV), examining discrepancies between individuals with ADHD and neurotypical controls (NCs). The analysis utilized the Seed-based d Mapping software.

RESULTS

A systematic review of the literature identified 21 functional imaging studies (595 ADHD and 564 controls) and 50 GMV studies (1907 ADHD and 1611 controls). In general, individuals with ADHD exhibited increased resting-state functional activity in the right parahippocampal gyrus and bilateral orbitofrontal cortex (OFC), as well as decreased resting-state functional activity in the bilateral cingulate cortex (including the posterior cingulate cortex [PCC], median cingulate cortex [MCC], and anterior cingulate cortex [ACC]). The VBM meta-analysis revealed decreased GMV in the bilateral OFC, right putamen (extending to right superior temporal gyrus [STG]), left inferior frontal gyrus (IFG), right superior frontal gyrus (SFG), ACC, and precentral gyrus among individuals with ADHD.

CONCLUSIONS

The multimodal meta-analyses indicated that individuals with ADHD exhibit abnormalities in both function and structure in the bilateral OFC. In addition, a few regions exhibited only functional or only structural abnormalities in ADHD, such as in the limbic, prefrontal, primary sensorimotor regions.

Coupled aging of cyto- and myeloarchitectonic atlas-informed gray and white matter structural properties

A key aspect of brain aging that remains poorly understood is its high regional heterogeneity and heterochronicity. A better understanding of how the structural organization of the brain shapes aging trajectories is needed. Neuroimaging tissue "types" are often collected and analyzed as separate acquisitions, an approach that cannot provide a holistic view of age-related change of the related portions of the neurons (cell bodies and axons). Because neuroimaging can only assess indirect features at the gross macrostructural level, incorporating post-mortem histological information may aid in better understanding of structural aging gradients. Longitudinal design, coupling of gray and white matter (GM, WM) properties, and a biologically informed approach to organizing neural properties are needed. Thus, we tested aging of the regional coupling between GM (cortical thickness, surface area, volume) and WM (fractional anisotropy, mean, axial, and radial diffusivities) structural metrics using linear mixed effects modeling in 102 healthy adults aged 20-94 years old, scanned on two occasions over a four-year period. The association between age-related within-person change in GM morphometry and the diffusion properties of the directly neighboring portion of white matter were assessed, capturing both aspects of neuronal health in one model. Additionally, we parcellated the brain utilizing the histological-staining informed von Economo-Koskinas atlas to consider regional cyto- and myelo-architecture. Results demonstrate several gradients of coupled association in the age-related decline of neighboring white and gray matter. Most notably, gradients of coupling along the heteromodal association to sensory axis were found for several areas (e.g., anterior frontal and lateral temporal cortices, vs pre- and post-central gyrus, occipital, and limbic areas), in line with heterochronicity and retrogenesis theories of aging. Further effort to bridge across data and measurement scales will enhance understanding of the mechanisms of the aging brain.

Exploring the relationship among Alzheimer's disease, aging and cognitive scores through neuroimaging-based approach

Alzheimer's disease (AD) is a fatal neurodegenerative disorder, with the Mini-Mental State Examination (MMSE) and Clinical Dementia Rating (CDR) serving significant roles in monitoring its progression. We hypothesize that while cognitive assessment scores can detect AD-related brain changes, the targeted brain regions may differ. Additionally, given AD's strong association with aging, we propose that specific brain regions are influenced by both AD pathology and aging, exhibiting strong correlations with both. To test these hypotheses, we developed a 3D convolutional network with a mixed-attention mechanism to recognize AD subjects from structural magnetic resonance imaging (sMRI) data and utilize 3D convolutional methods to pinpoint brain regions significantly correlated with the AD, MMSE, CDR and age. All models were trained and internally validated on 417 samples from the Alzheimer's Disease Neuroimaging Initiative (ADNI), and the classification model was externally validated on 382 samples from the Australian Imaging and Lifestyle flagship (AIBL). This approach provided robust support for using MMSE and CDR in assessing AD progression and visually illustrated the relationship between aging and AD. The analysis revealed correlations among the four identification tasks (AD, MMSE, CDR and age) and highlighted asymmetric brain lesions in both AD and aging. Notably, we found that AD can accelerate aging to some extent, and a significant correlation exists between the rate of aging and cognitive assessment scores. This offers new insights into the relationship between AD and aging.

The usefulness of combined analysis using CIScore and VSRAD parameters for differentiating between dementia with Lewy body and Alzheimer's disease

PURPOSE

The Cingulate Island score (CIScore) is useful index for differentiating between dementia with Lewy body (DLB) and Alzheimer's disease (AD) using regional cerebral blood flow (rCBF) SPECT. The Z score standing for medial temporal lobe (MTL) atrophy and the ratio of Z score between dorsal brain stem (DBS) to MTL are useful indices for differentiating between DLB and AD using MRI with VSRAD. The current study investigated the diagnostic ability by the combined use of rCBF SPECT and MRI in the differentiation between AD and DLB.

MATERIALS AND METHODS

In cases with 42 AD and 28 DLB undertaken Tc-99m-ECD SPECT and MRI, we analyzed differential diagnostic ability between AD and DLB among following conditions by single or combined settings. Namely, they were (1) the CIScore as a parameter of rCBF SPECT (DLB ≦ 0.25), (2) Z score value of MTL atrophy (DLB ≦ 2.05), (3) the ratio of Z score of DBS to medial temporal gray matter as a parameter of brain atrophy using VSRAD (DLB ≧ 0.38). Also, we analyzed them both including and omitting the elderly (over 75 years old).

RESULTS

The accuracy of differential diagnosis in this condition was 74% for (1), 69% for (2), and 67% for (3). The accuracy by combination condition was 84% for (1) and (2), 81% for (1) and (3), and 67% for (2) and (3), respectively. The combination method by CIScore and the Z score of MTL showed the best accuracy. When we confined condition to ages younger than 75 years, the accuracy improved to 94% in the combination method.

CONCLUSION

The combined use of CIScore and Z score of MTL was suggested to be useful in the differential diagnosis between DLB and AD particularly in younger than 75 years old.

Integrative molecular and structural neuroimaging analyses of the interaction between depression and age of onset: A multimodal magnetic resonance imaging study

Depression is a neurodevelopmental disorder that exhibits progressive gray matter volume (GMV) atrophy. Research indicates that brain development is influential in depression-induced GMV alterations. However, the interaction between depression and age of onset is not well understood by the underlying molecular and neuropathological mechanisms. Thus, 152 first-episode depression individuals and matched 130 healthy controls (HCs) were recruited to undergo T1-weighted high-resolution magnetic resonance imaging for this study. By two-way ANOVA, age and diagnosis were used as factors when analyzing the interaction of GMV in the participants. Then, spatial correlations between neurotransmitter maps and factor-related volume maps are established. Results illustrate a pronounced antagonistic interaction between depression and age of onset in the right insula, superior temporal gyrus, anterior cingulate gyrus, and orbitofrontal gyrus. Depression-caused reductions in GMV are mainly distributed in thalamic-limbic-cortical regions, regardless of age. For the main effect of age, adults exhibit brain atrophy in frontal, cerebellum, parietal, and temporal lobe structures. Cross-modal correlations showed that GMV changes in the interactive regions were linked with the serotonergic system and dopaminergic systems. Summarily, our results reveal the interaction between depression and age of onset in neurobiological mechanisms, which provide hints for future treatment of different ages of depression.

Brain age of rhesus macaques over the lifespan

Through the application of machine learning algorithms to neuroimaging data the brain age methodology was shown to provide a useful individual-level biological age prediction and identify key brain regions responsible for the prediction. In this study, we present the methodology of constructing a rhesus macaque brain age model using a machine learning algorithm and discuss the key predictive brain regions in comparison to the human brain, to shed light on cross-species primate similarities and differences. Structural information of the brain (e.g., parcellated volumes) from brain magnetic resonance imaging of 43 rhesus macaques were used to develop brain atlas-based features to build a brain age model that predicts biological age. The best-performing model used 22 selected features and achieved an R2 of 0.72. We also identified interpretable predictive brain features including Right Fronto-orbital Cortex, Right Frontal Pole, Right Inferior Lateral Parietal Cortex, and Bilateral Posterior Central Operculum. Our findings provide converging evidence of the parallel and comparable brain regions responsible for both non-human primates and human biological age prediction.

Exploring potential neuroimaging biomarkers for the response to non-steroidal anti-inflammatory drugs in episodic migraine

BACKGROUND

Non-steroidal anti-inflammatory drugs (NSAIDs) are considered first-line medications for acute migraine attacks. However, the response exhibits considerable variability among individuals. Thus, this study aimed to explore a machine learning model based on the percentage of amplitude oscillations (PerAF) and gray matter volume (GMV) to predict the response to NSAIDs in migraine treatment.

METHODS

Propensity score matching was adopted to match patients having migraine with response and nonresponse to NSAIDs, ensuring consistency in clinical characteristics and migraine-related features. Multimodal magnetic resonance imaging was employed to extract PerAF and GMV, followed by feature selection using the least absolute shrinkage and selection operator regression and recursive feature elimination algorithms. Multiple predictive models were constructed and the final model with the smallest predictive residuals was chosen. The model performance was evaluated using the area under the receiver operating characteristic (ROCAUC) curve, area under the precision-recall curve (PRAUC), balance accuracy (BACC), sensitivity, F1 score, positive predictive value (PPV), and negative predictive value (NPV). External validation was performed using a public database. Then, correlation analysis was performed between the neuroimaging predictors and clinical features in migraine.

RESULTS

One hundred eighteen patients with migraine (59 responders and 59 non-responders) were enrolled. Six features (PerAF of left insula and left transverse temporal gyrus; and GMV of right superior frontal gyrus, left postcentral gyrus, right postcentral gyrus, and left precuneus) were observed. The random forest model with the lowest predictive residuals was selected and model metrics (ROCAUC, PRAUC, BACC, sensitivity, F1 score, PPV, and NPV) in the training and testing groups were 0.982, 0.983, 0.927, 0.976, 0.930, 0.889, and 0.973; and 0.711, 0.648, 0.639, 0.667,0.649, 0.632, and 0.647, respectively. The model metrics of external validation were 0.631, 0.651, 0.611, 0.808, 0.656, 0.553, and 0.706. Additionally, a significant positive correlation was found between the GMV of the left precuneus and attack time in non-responders.

CONCLUSIONS

Our findings suggest the potential of multimodal neuroimaging features in predicting the efficacy of NSAIDs in migraine treatment and provide novel insights into the neural mechanisms underlying migraine and its optimized treatment strategy.

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.

To Be Frail or Not to Be Frail: This Is the Question-A Critical Narrative Review of Frailty

Many factors have contributed to rendering frailty an emerging, relevant, and very popular concept. First, many pandemics that have affected humanity in history, including COVID-19, most recently, have had more severe effects on frail people compared to non-frail ones. Second, the increase in human life expectancy observed in many developed countries, including Italy has led to a rise in the percentage of the older population that is more likely to be frail, which is why frailty is much a more common concern among geriatricians compared to other the various health-care professionals. Third, the stratification of people according to the occurrence and the degree of frailty allows healthcare decision makers to adequately plan for the allocation of available human professional and economic resources. Since frailty is considered to be fully preventable, there are relevant consequences in terms of potential benefits both in terms of the clinical outcome and healthcare costs. Frailty is becoming a popular, pervasive, and almost omnipresent concept in many different contexts, including clinical medicine, physical health, lifestyle behavior, mental health, health policy, and socio-economic planning sciences. The emergence of the new "science of frailty" has been recently acknowledged. However, there is still debate on the exact definition of frailty, the pathogenic mechanisms involved, the most appropriate method to assess frailty, and consequently, who should be considered frail. This narrative review aims to analyze frailty from many different aspects and points of view, with a special focus on the proposed pathogenic mechanisms, the various factors that have been considered in the assessment of frailty, and the emerging role of biomarkers in the early recognition of frailty, particularly on the role of mitochondria. According to the extensive literature on this topic, it is clear that frailty is a very complex syndrome, involving many different domains and affecting multiple physiological systems. Therefore, its management should be directed towards a comprehensive and multifaceted holistic approach and a personalized intervention strategy to slow down its progression or even to completely reverse the course of this condition.

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.

Triiodothyronine Treatment reverses Depression-Like Behavior in a triple-transgenic animal model of Alzheimer's Disease

Alzheimer disease's (AD) is a neurodegenerative disorder characterized by cognitive and behavioral impairment. The central nervous system is an important target of thyroid hormones (TH). An inverse association between serum triiodothyronine (T3) levels and the risk of AD symptoms and progression has been reported. We investigated the effects of T3 treatment on the depression-like behavior in male transgenic 3xTg-AD mice. Animals were divided into 2 groups treated with daily intraperitoneal injections of 20 ng/g of body weight (b.w.) L-T3 (T3 group) or saline (vehicle, control group). The experimental protocol lasted 21 days, and behavioral tests were conducted on days 18-20. At the end of the experiment, the TH profile and hippocampal gene expression were evaluated. The T3-treated group significantly increased serum T3 and decreased thyroxine (T4) levels. When compared to control hippocampal samples, the T3 group exhibited attenuated glycogen synthase kinase-3 (GSK3), metalloproteinase 10 (ADAM10), amyloid-beta precursor-protein (APP), serotonin transporter (SERT), 5HT1A receptor, monocarboxylate transporter 8 (MCT8) and bone morphogenetic protein 7 (BMP-7) gene expression, whereas augmented superoxide dismutase 2 (SOD2) and Hairless gene expression. T3-treated animals also displayed reduced immobility time in both the tail suspension and forced swim tests, and in the latter presented a higher latency time compared to the control group. Therefore, our findings suggest that in an AD mouse model, T3 supplementation promotes improvements in depression-like behavior, through the modulation of the serotonergic related genes involved in the transmission mediated by 5HT1A receptors and serotonin reuptake, and attenuated disease progression.

Interpretation for Individual Brain Age Prediction Based on Gray Matter Volume

The relationship between age and the central nervous system (CNS) in humans has been a classical issue that has aroused extensive attention. Especially for individuals, it is of far greater importance to clarify the mechanisms between CNS and age. The primary goal of existing methods is to use MR images to derive high-accuracy predictions for age or degenerative diseases. However, the associated mechanisms between the images and the age have rarely been investigated. In this paper, we address the correlation between gray matter volume (GMV) and age, both in terms of gray matter themselves and their interaction network, using interpretable machine learning models for individuals. Our goal is not only to predict age accurately but more importantly, to explore the relationship between GMV and age. In addition to targeting each individual, we also investigate the dynamic properties of gray matter and their interaction network with individual age. The results show that the mean absolute error (MAE) of age prediction is 7.95 years. More notably, specific locations of gray matter and their interactions play different roles in age, and these roles change dynamically with age. The proposed method is a data-driven approach, which provides a new way to study aging mechanisms and even to diagnose degenerative brain diseases.

Cortical Volume in the Right Cingulate Cortex Mediates the Increase of Self-Control From Young Adult to Middle-Aged

A high self-control capacity is related to better environmental adaptability and happy and healthy life. Neuroimaging studies have elucidated that the anterior cingulate, the prefrontal cortex, and the orbitofrontal cortex are involved in self-control. However, few studies integrated all three measurements, namely, age, human brain, and self-control, into a single quantitative model and examined whether self-control ability increased or decreased with age. In this study, we collected 65 participants' data including structural MRI and Tangney's Self-Control Scale to explore age dependence of cortical volume (CV) and self-control from young adult to middle-aged, as well as whether a non-linear association in the tridimensional model of age-brain-self-control was necessary to explain all the data in this study. We showed that self-control increased with age, but CV decreased with age. In a linear model, our mediation analyses revealed that CV in the right cingulate cortex mediated the increase of self-control; we also constructed a general non-linear model of age-brain-behavior and proved that the inverted development of human brain morphology and self-control abilities happened when morphology decays with age at a relatively smaller rate. Our study indicated that healthy aging in terms of increasing self-control is achievable, and our quantitative linear model of self-control laid theoretical foundations for studies on non-linear associations in age-brain-behavior.

Fornix volumetric increase and microglia morphology contribute to spatial and recognition-like memory decline in ageing male mice

Ageing displays a low-grade pro-inflammatory profile in blood and the brain. Accumulation of pro-inflammatory cytokines, microglia activation and volumetric changes in the brain correlate with cognitive decline in ageing models. However, the interplay between them is not totally understood. Here, we aimed to globally identify an age-dependent pro-inflammatory profile and microglia morphological plasticity that favors major volume changes in the brain associated with cognitive decline. Cluster analysis of behavioral data obtained from 2-,12- and 20-month-old male C57BL/6 mice revealed age-dependent cognitive decline after the Y-maze, Barnes maze, object recognition (NORT) and object location tests (OLT). Global magnetic resonance imageing (MRI) analysis by deformation-based morphometry (DBM) in the brain identified a volume increase in the fornix and a decrease in the left medial entorhinal cortex (MEntC) during ageing. Notably, the fornix shows an increase in the accumulation of pro-inflammatory cytokines, whereas the left MEntC displays a decrease. Morphological assessment of microglia also confirms an active and dystrophic phenotype in the fornix and a surveillance phenotype in the left MEntC. Finally, biological modeling revealed that age-related volume increase in the fornix was associated with dystrophic microglia and cognitive impairment, as evidenced by failure on tasks examining memory of object location and novelty. Our results propose that the morphological plasticity of microglia might contribute to volumetric changes in brain regions associated with cognitive decline during physiological ageing.

Brain Morphometry and Cognitive Performance in Normal Brain Aging: Age- and Sex-Related Structural and Functional Changes

BACKGROUND

The human brain structure undergoes considerable changes throughout life. Cognitive function can be affected either negatively or positively. It is challenging to segregate normal brain aging from the accelerated one.

OBJECTIVE

To work out a descriptive model of brain structural and functional changes in normal aging.

MATERIALS AND METHODS

By using voxel-based morphometry and lesion segmentation along with linear statistics and machine learning (ML), we analyzed the structural changes in the major brain compartments and modeled the dynamics of neurofunctional performance throughout life. We studied sex differences in lifelong dynamics of brain volumetric data with Mann-Whitney U-test. We tested the hypothesis that performance in some cognitive domains might decline as a linear function of age while other domains might have a non-linear dependence on it. We compared the volumetric changes in the major brain compartments with the dynamics of psychophysiological performance in 4 age groups. Then, we tested linear models of structural and functional decline for significant differences between the slopes in age groups with the T-test.

RESULTS

White matter hyperintensities (WMH) are not the major structural determinant of the brain normal aging. They should be viewed as signs of a disease. There is a sex difference in the speed and/or in the onset of the gray matter atrophy. It either starts earlier or goes faster in males. Marked sex difference in the proportion of total cerebrospinal fluid (CSF) and intraventricular CSF (iCSF) justifies that elderly men are more prone to age-related brain atrophy than women of the same age.

CONCLUSION

The article gives an overview and description of the conceptual structural changes in the brain compartments. The obtained data justify distinct patterns of age-related changes in the cognitive functions. Cross-life slowing of decision-making may follow the linear tendency of enlargement of the interhemispheric fissure because the center of task switching and inhibitory control is allocated within the medial wall of the frontal cortex, and its atrophy accounts for the expansion of the fissure. Free online tool at https://med-predict.com illustrates the tests and study results.

Reserve and Maintenance in the Aging Brain: A Longitudinal Study of Healthy Older Adults

The aging brain undergoes structural changes even in very healthy individuals. Quantifying these changes could help disentangle pathologic changes from those associated with the normal human aging process. Using longitudinal magnetic resonance imaging (MRI) data from 227 carefully selected healthy human cohort with age ranging from 50 to 80 years old at baseline scan, we quantified age-related volumetric changes in the brain of healthy human older adults. Longitudinally, the rates of tissue loss in total gray matter (GM) and white matter (WM) were 2497.5 and 2579.8 mm³ per year, respectively. Across the whole brain, the rates of GM decline varied with regions in the frontal and parietal lobes having faster rates of decline, whereas some regions in the occipital and temporal lobes appeared relatively preserved. In contrast, cross-sectional changes were mainly observed in the temporal-occipital regions. Similar longitudinal atrophic changes were also observed in subcortical regions including thalamus, hippocampus, putamen, and caudate, whereas the pallidum showed an increasing volume with age. Overall, regions maturing late in development (frontal, parietal) are more vulnerable to longitudinal decline, whereas those that fully mature in the early stage (temporal, occipital) are mainly affected by cross-sectional changes in healthy older cohort. This may suggest that, for a successful healthy aging, the former needs to be maximally developed at an earlier age to compensate for the longitudinal decline later in life and the latter to remain relatively preserved even in old age, consistent with both concepts of reserve and brain maintenance.

Proportional Changes in Cognitive Subdomains During Normal Brain Aging

Background: Neuroscience lacks a reliable method of screening the early stages of dementia. Objective: To improve the diagnostics of age-related cognitive functions by developing insight into the proportionality of age-related changes in cognitive subdomains. Materials and Methods: We composed a battery of psychophysiological tests and collected an open-access psychophysiological outcomes of brain atrophy (POBA) dataset by testing individuals without dementia. To extend the utility of machine learning (ML) classification in cognitive studies, we proposed estimates of the disproportional changes in cognitive functions: an index of simple reaction time to decision-making time (ISD), ISD with the accuracy performance (ISDA), and an index of performance in simple and complex visual-motor reaction with account for accuracy (ISCA). Studying the distribution of the values of the indices over age allowed us to verify whether diverse cognitive functions decline equally throughout life or there is a divergence in age-related cognitive changes. Results: Unsupervised ML clustering shows that the optimal number of homogeneous age groups is four. The sample is segregated into the following age-groups: Adolescents ∈ [0, 20), Young adults ∈ [20, 40), Midlife adults ∈ [40, 60) and Older adults ≥60 year of age. For ISD, ISDA, and ISCA values, only the median of the Adolescents group is different from that of the other three age-groups sharing a similar distribution pattern (p > 0.01). After neurodevelopment and maturation, the indices preserve almost constant values with a slight trend toward functional decline. The reaction to a moving object (RMO) test results (RMO_mean) follow another tendency. The Midlife adults group's median significantly differs from the remaining three age subsamples (p < 0.01). No general trend in age-related changes of this dependent variable is observed. For all the data (ISD, ISDA, ISCA, and RMO_mean), Levene's test reveals no significant changes of the variances in age-groups (p > 0.05). Homoscedasticity also supports our assumption about a linear dependency between the observed features and age. Conclusion: In healthy brain aging, there are proportional age-related changes in the time estimates of information processing speed and inhibitory control in task switching. Future studies should test patients with dementia to determine whether the changes of the aforementioned indicators follow different patterns.

Investigating impact of cardiorespiratory fitness in reducing brain tissue loss caused by ageing

Mitigating the loss of brain tissue due to age is a major problem for an ageing population. Improving cardiorespiratory fitness has been suggested as a possible strategy, but the influenceon brain morphology has not been fully characterized. To investigate the dependent shifts in brain tissue distribution as a function of cardiorespiratory fitness, we used a 3D transport-based morphometry approach. In this study of 172 inactive older adults aged 58-81 (66.5 ± 5.7) years, cardiorespiratory fitness was determined by VO 2 peak (ml/kg/min) during graded exercise and brain morphology was assessed through structural magnetic resonance imaging. After correcting for covariates including age (in the fitness model), gender and level of education, we compared dependent tissue shifts with age to those due to V O 2   peak . We found a significant association between cardiorespiratory fitness and brain tissue distribution (white matter, r = 0.30, P = 0.003; grey matter, r = 0.40, P < 0.001) facilitated by direct visualization of the brain tissue shifts due to cardiorespiratory fitness through inverse transformation-a key capability of 3D transport-based morphometry. A strong statistical correlation was found between brain tissue changes related to ageing and those associated with lower cardiorespiratory fitness (white matter, r = 0.62, P < 0.001; grey matter, r = 0.74, P < 0.001). In both cases, frontotemporal regions shifted the most while basal ganglia shifted the least. Our results highlight the importance of cardiorespiratory fitness in maintaining brain health later in life. Furthermore, this work demonstrates 3D transport-based morphometry as a novel neuroinformatic technology that may aid assessment of therapeutic approaches for brain ageing and neurodegenerative diseases.

Connectivity-Based Topographical Changes of the Corpus Callosum During Aging

Background: The corpus callosum (CC) is the most prominent white matter connection for interhemispheric information transfer. It is implicated in a variety of cognitive functions, which tend to decline with age. The region-specific projections of the fiber bundles with microstructural heterogeneity of the CC are associated with cognitive functions and diseases. However, how the CC is associated with the information transfer within functional networks and the connectivity changes during aging remain unclear. Studying the CC topography helps to understand the functional specialization and age-related changes of CC subregions. Methods: Diffusion tractography was used to subdivide the CC into seven subregions from 1,086 healthy volunteers within a wide age range (21-90 years), based on the connections to the cortical parcellations of the functional networks. Quantitative diffusion indices and connection probability were calculated to study the microstructure differences and age-related changes in the CC subregions. Results: According to the population-based probabilistic topography of the CC, part of the default mode network (DMN) and limbic network (LN) projected fibers through the genu and rostrum; the frontoparietal network (FPN), ventral attention network (VA) and somatomotor networks (SM) were interconnected by the CC body; callosal fibers arising from the part of the default mode network (DMN), dorsal attention network (DA) and visual network (VIS) passed through the splenium. Anterior CC subregions interconnecting DMN, LN, FPN, VA, and SM showed lower fractional anisotropy (FA) and higher mean diffusivity (MD) and radial diffusivity (RD) than posterior CC subregions interconnecting DA and VIS. All the CC subregions showed slightly increasing FA and decreasing MD, RD, and axial diffusivity (AD) at younger ages and opposite trends at older ages. Besides, the anterior CC subregions exhibited larger microstructural and connectivity changes compared with the posterior CC subregions during aging. Conclusion: This study revealed the callosal subregions related to functional networks and uncovered an overall "anterior-to-posterior" region-specific changing trend during aging, which provides a baseline to identify the presence and timing of callosal connection states.

Evaluation of Age and Sex-Related Metabolic Changes in Healthy Subjects: An Italian Brain 18F-FDG PET Study

Background: 18F-fluorodeoxyglucose (18F-FDG) positron-emission-tomography (PET) allows detection of cerebral metabolic alterations in neurological diseases vs. normal aging. We assess age- and sex-related brain metabolic changes in healthy subjects, exploring impact of activity normalization methods. Methods: brain scans of Italian Association of Nuclear Medicine normative database (151 subjects, 67 Males, 84 Females, aged 20–84) were selected. Global mean, white matter, and pons activity were explored as normalization reference. We performed voxel-based and ROI analyses using SPM12 and IBM-SPSS software. Results: SPM proved a negative correlation between age and brain glucose metabolism involving frontal lobes, anterior-cingulate and insular cortices bilaterally. Narrower clusters were detected in lateral parietal lobes, precuneus, temporal pole and medial areas bilaterally. Normalizing on pons activity, we found a more significant negative correlation and no positive one. ROIs analysis confirmed SPM results. Moreover, a significant age × sex interaction effect was revealed, with worse metabolic reduction in posterior-cingulate cortices in females than males, especially in post-menopausal age. Conclusions: this study demonstrated an age-related metabolic reduction in frontal lobes and in some parieto-temporal areas more evident in females. Results suggested pons as the most appropriate normalization reference. Knowledge of age- and sex-related cerebral metabolic changes is critical to correctly interpreting brain 18F-FDG PET imaging.

Manual Correction of Voxel Misclassifications in Mesiotemporal Structures Does Not Alter Brain-Behavioral Results in an Episodic Memory Task

Voxel-based morphometry (VBM) is an established method for assessing grey matter volumes across the brain. The quality of magnetic resonance imaging (MRI) and the chosen data preprocessing steps can affect the outcome of VBM analyses. We recognized a lack of publicly available and commonly used protocols, which indicates that standardized and optimized preprocessing protocols are needed. This paper focuses on the time- and resource-consuming manual correction of misclassifications of grey matter voxels in cortical structures important in Alzheimer's dementia. A total of 126 individuals, including 63 patients with very early Alzheimer's disease and 63 cognitively normal participants, received thorough neuropsychological testing and 3-Tesla MRI. Automated preprocessing of T1 MPRAGE images was performed, and misclassifications of grey matter voxels were manually identified and corrected. In a second run, the manual correction step was skipped. Multiple regression analyses using DARTEL in SPM8 were then conducted with the manually corrected and uncorrected sample, respectively. Manual correction of voxel misclassifications did not have a major impact on the correlation between episodic memory performance and structural brain imaging results. We conclude that, although performing all preprocessing steps remains the gold standard, skipping manual correction of voxel misclassifications is permitted when investigating populations on the Alzheimer's disease spectrum.

Elucidating the relationship between white matter structure, demographic, and clinical variables in schizophrenia-a multicenter harmonized diffusion tensor imaging study

White matter (WM) abnormalities are repeatedly demonstrated across the schizophrenia time-course. However, our understanding of how demographic and clinical variables interact, influence, or are dependent on WM pathologies is limited. The most well-known barriers to progress are heterogeneous findings due to small sample sizes and the confounding influence of age on WM. The present study leverages access to the harmonized diffusion magnetic-resonance-imaging data and standardized clinical data from 13 international sites (597 schizophrenia patients (SCZ)). Fractional anisotropy (FA) values for all major WM structures in patients were predicted based on FA models estimated from a healthy population (n = 492). We utilized the deviations between predicted and real FA values to answer three essential questions. (1) "Which clinical variables explain WM abnormalities?". (2) "Does the degree of WM abnormalities predict symptom severity?". (3) "Does sex influence any of those relationships?". Regression and mediator analyses revealed that a longer duration-of-illness is associated with more severe WM abnormalities in several tracts. In addition, they demonstrated that a higher antipsychotic medication dose is related to more severe corpus callosum abnormalities. A structural equation model revealed that patients with more WM abnormalities display higher symptom severity. Last, the results exhibited sex-specificity. Males showed a stronger association between duration-of-illness and WM abnormalities. Females presented a stronger association between WM abnormalities and symptom severity, with IQ impacting this relationship. Our findings provide clear evidence for the interaction of demographic, clinical, and behavioral variables with WM pathology in SCZ. Our results also point to the need for longitudinal studies, directly investigating the casualty and sex-specificity of these relationships, as well as the impact of cognitive resiliency on structure-function relationships.

Brain volume changes after long-term injectable opioid treatment: A longitudinal voxel-based morphometry study

Clinical research has demonstrated the efficacy of injectable opioid treatment for long-term, treatment-refractory opioid-dependent patients. It has been hypothesized that compulsive drug use is particularly associated with neuroplasticity changes in the networks corresponding to withdrawal/negative affect and preoccupation/anticipation rather than binge/intoxication. However, as yet, no study has investigated the effect of long-term opioid treatment on key regions within these networks. Magnetic resonance imaging (MRI) was used to assess brain volumes changes during long-term (approximately 9 years) injectable opioid agonist treatment with diacetylmorphine (DAM) in 22 patients with opioid use disorder. Voxel-based morphometry was applied to detect volumetric changes within the networks of binge/intoxication (ventral/dorsal striatum, globus pallidus and thalamus), withdrawal/negative affect (amygdala and ventral striatum) and preoccupation/anticipation (hippocampus, orbitofrontal and anterior cingulate cortex). The relationships between significant volume changes and features of opioid use disorder were tested using Pearson correlation. Long-term opioid agonist treatment was associated with the enlargement of the right caudate nucleus, which was related to the duration of opioid use disorder. In contrast, reduced volume in the right amygdala, anterior cingulate cortex and orbitofrontal cortex were found that were related to opioid dose, onset of opioid consumption and state anxiety. These findings suggest that long-term opioid agonist treatment is related to structural changes in key brain regions underlying binge/intoxication, withdrawal/negative affect and preoccupation/anticipation, suggesting sustained interaction between these systems.

Norms for Automatic Estimation of Hippocampal Atrophy and a Step Forward for Applicability to the Italian Population

INTRODUCTION

Hippocampal volume is one of the main biomarkers of Alzheimer's Dementia (AD). Over the years, advanced tools that performed automatic segmentation of Magnetic Resonance Imaging (MRI) T13D scans have been developed, such as FreeSurfer (FS) and ACM-Adaboost (AA). Hippocampal volume is considered abnormal when it is below the 5th percentile of the normative population. The aim of this study was to set norms, established from the Alzheimer's Disease Neuroimaging Initiative (ADNI) population, for hippocampal volume measured with FS v.6.0 and AA tools in the neuGRID platform (www.neugrid2.eu) and demonstrate their applicability for the Italian population.

METHODS

Norms were set from a large group of 545 healthy controls belonging to ADNI. For each pipeline, subjects with segmentation errors were discarded, resulting in 532 valid segmentations for FS and 421 for AA (age range 56-90 years). The comparability of ADNI and the Italian Brain Normative Archive (IBNA), representative of the Italian general population, was assessed testing clinical variables, neuropsychological scores and normalized hippocampal volumes. Finally, percentiles were validated using the Italian Alzheimer's disease Repository Without Borders (ARWiBo) as external independent data set to evaluate FS and AA generalizability.

RESULTS

Hippocampal percentiles were checked with the chi-square goodness of fit test. P-values were not significant, showing that FS and AA algorithm distributions fitted the data well. Clinical, neuropsychological and volumetric features were similar in ADNI and IBNA (p > 0.01). Hippocampal volumes measured with both FS and AA were associated with age (p < 0.001). The 5th percentile thresholds, indicating left/right hippocampal atrophy were respectively: (i) below 3,223/3,456 mm3 at 56 years and 2,506/2,415 mm3 at 90 years for FS; (ii) below 4,583/4,873 mm3 at 56 years and 3,831/3,870 mm3 at 90 years for AA. The average volumes computed on 100 cognitively intact healthy controls (CN) selected from ARWiBo were close to the 50th percentiles, while those for 100 AD patients were close to the abnormal percentiles.

DISCUSSION

Norms generated from ADNI through the automatic FS and AA segmentation tools may be used as normative references for Italian patients with suspected AD.

Dissecting the midlife crisis: disentangling social, personality and demographic determinants in social brain anatomy

In any stage of life, humans crave connection with other people. In midlife, transitions in social networks can relate to new leadership roles at work or becoming a caregiver for aging parents. Previous neuroimaging studies have pinpointed the medial prefrontal cortex (mPFC) to undergo structural remodelling during midlife. Social behavior, personality predisposition, and demographic profile all have intimate links to the mPFC according in largely disconnected literatures. Here, we explicitly estimated their unique associations with brain structure using a fully Bayesian framework. We weighed against each other a rich collection of 40 UK Biobank traits with their interindividual variation in social brain morphology in ~10,000 middle-aged participants. Household size and daily routines showed several of the largest effects in explaining variation in social brain regions. We also revealed male-biased effects in the dorsal mPFC and amygdala for job income, and a female-biased effect in the ventral mPFC for health satisfaction.

Hannah Kiesow et al. combine 40 behavioral indicators and neuroimaging data from the UK Biobank to investigate how the transitions in midlife in the domains of social, personality, and demographic determinants impact brain anatomy. Through Bayesian analyses, the authors were able to disentangle which specific traits, relative to other considered candidate traits, contributed the most to explaining differences in social brain volume.

Accelerating Structural Degeneration in Temporal Regions and Their Effects on Cognition in Aging of MCI Patients

Age is the major risk factor for Alzheimer's disease (AD) and for mild cognitive impairment (MCI). However, there is limited evidence about MCI-specific aging-related simultaneous changes of the brain structure and their impact on cognition. We analyzed the brain imaging data from 269 subjects (97 MCI patients and 172 cognitively normal [CN] elderly) using voxel-based morphometry and tract-based spatial statistics procedures to explore the special structural pattern during aging. We found that the patients with MCI showed accelerated age-related reductions in gray matter volume in the left planum temporale, thalamus, and posterior cingulate gyrus. The similar age×group interaction effect was found in the fractional anisotropy of the bilateral parahippocampal cingulum white matter tract, which connects the temporal regions. Importantly, the age-related temporal gray matter and white matter alterations were more significantly related to performance in memory and attention tasks in MCI patients. The accelerated degeneration patterns in the brain structure provide evidence for different neural mechanisms underlying aging in MCI patients. Temporal structural degeneration may serve as a potential imaging marker for distinguishing the progression of the preclinical AD stage from normal aging.

Large-Scale Morphological Network Efficiency of Human Brain: Cognitive Intelligence and Emotional Intelligence

Network efficiency characterizes how information flows within a network, and it has been used to study the neural basis of cognitive intelligence in adolescence, young adults, and elderly adults, in terms of the white matter in the human brain and functional connectivity networks. However, there were few studies investigating whether the human brain at different ages exhibited different underpins of cognitive and emotional intelligence (EI) from young adults to the middle-aged group, especially in terms of the morphological similarity networks in the human brain. In this study, we used 65 datasets (aging 18–64), including sMRI and behavioral measurements, to study the associations of network efficiency with cognitive intelligence and EI in young adults and the middle-aged group. We proposed a new method of defining the human brain morphological networks using the morphological distribution similarity (including cortical volume, surface area, and thickness). Our results showed inverted age × network efficiency interactions in the relationship of surface-area network efficiency with cognitive intelligence and EI: a negative age × global efficiency (nodal efficiency) interaction in cognitive intelligence, while a positive age × global efficiency (nodal efficiency) interaction in EI. In summary, this study not only proposed a new method of morphological similarity network but also emphasized the developmental effects on the brain mechanisms of intelligence from young adult to middle-aged groups and may promote mental health study on the middle-aged group in the future.

Coupling of cerebral blood flow and functional connectivity is decreased in healthy aging

Aging leads to cerebral perfusion and functional connectivity changes that have been assessed using various neuroimaging techniques. In addition, a link between these two parameters has been demonstrated in healthy young adults. In this work, we employed arterial spin labeling (ASL) fMRI to measure global and voxel-wise differences in cerebral blood flow (CBF) and intrinsic connectivity contrast (ICC) in the resting state in a group of cognitively normal elderly subjects and a group of cognitively normal young subjects, in order to assess the effects of aging on CBF-ICC coupling, which had not been previously evaluated. Our results showed age-related global and regional CBF decreases in prefrontal mesial areas, lateral frontal regions, insular cortex, lateral parietal areas, precuneus and occipital regions. Subcortically, perfusion was reduced in the medial thalamus and caudate nucleus. ICC was also found reduced with age in prefrontal cortical areas and insular cortex, affecting key nodes of the default mode and salience networks. Areas of ICC and CBF decrease partially overlapped, however, the CBF reduction was more extensive and encompassed more areas. This dissociation was accompanied by a decrease in CBF-ICC coupling. These results suggest that aging leads to a disruption in the relationship between CBF and intrinsic functional connectivity that could be due to neurovascular dysregulation.

Impact of emotionally negative information on attentional processes in normal aging and Alzheimer's disease

Impairments of emotional processing have been reported in Alzheimer's disease (AD), consistently with the existence of early amygdala atrophy in the pathology. In this study, we hypothesized that patients with AD might show a deficit of orientation toward emotional information under conditions of visual search. Eighteen patients with AD, 24 age-matched controls, and 35 young controls were eye-tracked while they performed a visual search task on a computer screen. The target was a vehicle with implicit (negative or neutral) emotional content, presented concurrently with one, three, or five non-vehicle neutral distractors. The task was to find the target and to report whether a break in the target frame was on the left or on the right side. Both control groups detected negative targets more efficiently than they detected neutral targets, showing facilitated engagement toward negative information. In contrast, patients with AD showed no influence of emotional information on engagement delays. However, all groups reported the frame break location more slowly for negative than for neutral targets (after accounting for the last fixation delay), showing a more difficult disengagement from negative information. These findings are the first to highlight a selective lack of emotional influence on engagement processes in patients with AD. The involvement of amygdala alterations in this behavioral impairment remains to be investigated.

Age-dependent changes in the medial prefrontal cortex and medial amygdala structure, and elevated plus-maze performance in the healthy male Wistar rats

Aging affects different parts of the brain structure and function. These changes are associated with several age-related emotional alterations like anxiety that is regulated by the amygdala and medial prefrontal cortex (mPFC). Thus, this study aimed to explore the effects of aging on the morphology changes in these regions. Twenty male Wistar rats were assigned to young and old groups. The anxiety level was evaluated by elevated plus-maze. Then, their brains were removed, fixed, cut, and stained with Cresyl Violet or Golgi-Cox. In addition to the estimation of stereological parameters, dendrite complexity, and spatial distribution of the neurons in the mPFC and amygdala were evaluated. Aging increased the medial amygdala volume and its total number of neurons, but it did not have a significant effect on these parameters in the mPFC. Furthermore, the size of the neurons in the mPFC increased, whereas the total length of the dendrite and its complexity significantly decreased with aging in this structure and increased in the amygdala. Although aging did not significantly change the dendritic spine density in both regions, old rats showed a more mature spine in the mPFC and more anxiety-like behavior. In conclusion, the increase of anxiety in the old individuals could be attributed to structural changes in the morphology of the dendrite and neuron and its spatial distribution in the mPFC and amygdala. The findings of this study partly support this hypothesis.

Morphology of perivascular spaces and enclosed blood vessels in young to middle-aged healthy adults at 7T: Dependences on age, brain region, and breathing gas

Perivascular spaces (PVSs) are fluid-filled spaces surrounding penetrating blood vessels in the brain and are an integral pathway of the glymphatic system. A PVS and the enclosed blood vessel are commonly visualized as a single vessel-like complex (denoted as PVSV) in high-resolution MRI images. Quantitative characterization of the PVSV morphology in MRI images in healthy subjects may serve as a reference for detecting disease related PVS and/or blood vessel alterations in patients with brain diseases.

To this end, we evaluated the age dependences, spatial heterogeneities, and dynamic properties of PVSV morphological features in 45 healthy subjects (21–55 years old), using an ultra-high-resolution three-dimensional transverse relaxation time weighted MRI sequence (0.41 × 0.41 × 0.4 mm³) at 7T. Quantitative PVSV parameters, including apparent diameter, count, volume fraction (VF), and relative contrast to noise ratio (rCNR) were calculated in the white matter and subcortical structures. Dynamic changes were induced by carbogen breathing which are known to induce vasodilation and increase the blood oxygenation level in the brain.

PVSV count and VF significantly increased with age in basal ganglia (BG), so did rCNR in BG, midbrain, and white matter (WM). Apparent PVSV diameter also showed a positive association with age in the three brain regions, although it did not reach statistical significance. The PVSV VF and count showed large inter-subject variations, with coefficients of variation ranging from 0.17 to 0.74 after regressing out age and gender effects. Both apparent diameter and VF exhibited significant spatial heterogeneity, which cannot be explained solely by radio-frequency field inhomogeneities. Carbogen breathing significantly increased VF in BG and WM, and rCNR in thalamus, BG, and WM compared to air breathing.

Our results are consistent with gradual dilation of PVSs with age in healthy adults. The PVSV morphology exhibited spatial heterogeneity and large inter-subject variations and changed during carbogen breathing compared to air breathing.

Brain structure changes over time in normal and mildly impaired aged persons

Structural brain changes in aging are known to occur even in the absence of dementia, but the magnitudes and regions involved vary between studies. To further characterize these changes, we analyzed paired MRI images acquired with identical protocols and scanner over a median 5.8-year interval. The normal study group comprised 78 elders (25M 53F, baseline age range 70–78 years) who underwent an annual standardized expert assessment of cognition and health and who maintained normal cognition for the duration of the study. We found a longitudinal grey matter (GM) loss rate of 2.56 ± 0.07 ml/year (0.20 ± 0.04%/year) and a cerebrospinal fluid (CSF) expansion rate of 2.97 ± 0.07 ml/year (0.22 ± 0.04%/year). Hippocampal volume loss rate was higher than the GM and CSF global rates, 0.0114 ± 0.0004 ml/year (0.49 ± 0.04%/year). Regions of greatest GM loss were posterior inferior frontal lobe, medial parietal lobe and dorsal cerebellum. Rates of GM loss and CSF expansion were on the low end of the range of other published values, perhaps due to the relatively good health of the elder volunteers in this study. An additional smaller group of 6 subjects diagnosed with MCI at baseline were followed as well, and comparisons were made with the normal group in terms of both global and regional GM loss and CSF expansion rates. An increased rate of GM loss was found in the hippocampus bilaterally for the MCI group.

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.

Is the Retina a Mirror of the Aging Brain? Aging of Neural Retina Layers and Primary Visual Cortex Across the Lifespan

How aging concomitantly modulates the structural integrity of the brain and retina in healthy individuals remains an outstanding question. Given the strong bottom-up retinocortical connectivity, it is important to study how these structures co-evolve during healthy aging in order to unravel mechanisms that may affect the physiological integrity of both structures. For the 56 participants in the study, primary visual cortex (BA17), as well as frontal, parietal and temporal regions thicknesses were measured in T1-weighted magnetic resonance imaging (MRI), and retinal macular thickness (10 neuroretinal layers) was measured by optical coherence tomography (OCT) imaging. We investigated the statistical association of these measures and their age dependence. We found an age-related decay of primary visual cortical thickness that was significantly correlated with a decrease in global and multiple layer retinal thicknesses. The atrophy of both structures might jointly account for the decline of various visual capacities that accompany the aging process. Furthermore, associations with other cortical regions suggest that retinal status may index cortical integrity in general.

Brain glucose and ketone utilization in brain aging and neurodegenerative diseases

To meet its high energy demands, the brain mostly utilizes glucose. However, the brain has evolved to exploit additional fuels, such as ketones, especially during prolonged fasting. With aging and neurodegenerative diseases (NDDs), the brain becomes inefficient at utilizing glucose due to changes in glia and neurons that involve glucose transport, glycolytic and Krebs cycle enzyme activities, and insulin signaling. Positron emission tomography and magnetic resonance spectroscopy studies have identified glucose metabolism abnormalities in aging, Alzheimer's disease (AD) and other NDDs in vivo. Despite glucose hypometabolism, brain cells can utilize ketones efficiently, thereby providing a rationale for the development of therapeutic ketogenic interventions in AD and other NDDs. This review compares available ketogenic interventions and discusses the potential of the potent oral Ketone Ester for future therapeutic use in AD and other NDDs characterized by inefficient glucose utilization.

Biosignals to Detect the Imbalance of Explicit and Implicit Affect in Dementia: A Pilot Study

BACKGROUND

We assessed implicit and explicit emotion in older patients with dementia using biosignals.

METHODS

Fifty patients with dementia and 34 healthy individuals watched 3 videos that aimed to elicit various emotional responses. Electroencephalogram and heart rate variability were recorded.

RESULTS

Patients with dementia experienced less fun and more fear than controls. The high frequency (HF) from the baseline in response to funny stimulation as well as HF from neutral to fear stimulation in the dementia group increased further than in the control group. The slow wave (SW)-fast wave (FW) ratio from neutral to funny stimulation in the control group increased further than in the dementia group. The SW-FW from neutral to fear stimulation was further decreased in the dementia group than in the control group.

CONCLUSIONS

Although patients with dementia were more sensitive to implicit affect, they showed more enhanced imbalance between positive and negative affect in explicit affect assessment.

The Effect of Hapln4 Link Protein Deficiency on Extracellular Space Diffusion Parameters and Perineuronal Nets in the Auditory System During Aging

Hapln4 is a link protein which stabilizes the binding between lecticans and hyaluronan in perineuronal nets (PNNs) in specific brain regions, including the medial nucleus of the trapezoid body (MNTB). The aim of this study was: (1) to reveal possible age-related alterations in the extracellular matrix composition in the MNTB and inferior colliculus, which was devoid of Hapln4 and served as a negative control, (2) to determine the impact of the Hapln4 deletion on the values of the ECS diffusion parameters in young and aged animals and (3) to verify that PNNs moderate age-related changes in the ECS diffusion, and that Hapln4-brevican complex is indispensable for the correct protective function of the PNNs. To achieve this, we evaluated the ECS diffusion parameters using the real-time iontophoretic method in the selected region in young adult (3 to 6-months-old) and aged (12 to 18-months-old) wild type and Hapln4 knock-out (KO) mice. The results were correlated with an immunohistochemical analysis of the ECM composition and astrocyte morphology. We report that the ECM composition is altered in the aged MNTB and aging is a critical point, revealing the effect of Hapln4 deficiency on the ECS diffusion. All of our findings support the hypothesis that the ECM changes in the MNTB of aged KO animals affect the ECS parameters indirectly, via morphological changes of astrocytes, which are in direct contact with synapses and can be influenced by the ongoing synaptic transmission altered by shifts in the ECM composition.

Trajectories of Physiological Brain Aging and Related Factors in People Aged from 20 to over-80

BACKGROUND/OBJECTIVE

In this study, we investigated a long-term trajectory of brain aging (from the 20 s to over-80) in cognitively normal (CN) individuals. We further determined whether differences in sex, education years, and apolipoprotein E ε 4 status affect age-related cortical thinning.

METHODS

A total of 2,944 CN individuals who underwent high-resolution (3.0-Tesla) magnetic resonance imaging were included in this study. Cortical thickness was measured using a surface-based method. Multiple linear regression analyses were performed to evaluate age-related cortical thinning and related factors.

RESULTS

Compared to those in their 20 s/30 s, participants in their 40 s showed thinning primarily in the medial and lateral frontal and inferior parietal regions, and cortical thinning occurred across most of the cortices with increasing age. Notably, the precuneus, inferior temporal and lateral occipital regions were relatively spared until later in life. Male and lower education years were associated with greater cortical thinning with distinct regional specificity.

CONCLUSION

Our findings provide an important clue to understanding the mechanism of age-related cognitive decline and new strategies for preventing the acceleration of pathological brain aging.

Joint contributions of cortical morphometry and white matter microstructure in healthy brain aging: A partial least squares correlation analysis

Cortical atrophy and degraded axonal health have been shown to coincide during normal aging; however, few studies have examined these measures together. To lend insight into both the regional specificity and the relative timecourse of structural degradation of these tissue compartments across the adult lifespan, we analyzed gray matter (GM) morphometry (cortical thickness, surface area, volume) and estimates of white matter (WM) microstructure (fractional anisotropy, mean diffusivity) using traditional univariate and more robust multivariate techniques to examine age associations in 186 healthy adults aged 20–94 years old. Univariate analysis of each tissue type revealed that negative age associations were largest in frontal GM and WM tissue and weaker in temporal, cingulate, and occipital regions, representative of not only an anterior‐to‐posterior gradient, but also a medial‐to‐lateral gradient. Multivariate partial least squares correlation (PLSC) found the greatest covariance between GM and WM was driven by the relationship between WM metrics in the anterior corpus callosum and projections of the genu, anterior cingulum, and fornix; and with GM thickness in parietal and frontal regions. Surface area was far less susceptible to age effects and displayed less covariance with WM metrics, while regional volume covariance patterns largely mirrored those of cortical thickness. Results support a retrogenesis‐like model of aging, revealing a coupled relationship between frontal and parietal GM and the underlying WM, which evidence the most protracted development and the most vulnerability during healthy aging.

Influence of Age on Global and Regional Brain Stiffness in Young and Middle-Aged Adults

BACKGROUND

An understanding of potential age-related changes in brain stiffness and its regional variation is important for further clinical application of MR elastography.

PURPOSE

To investigate the effect of age on global and regional brain stiffness in young and middle-aged adults.

STUDY TYPE

Prospective.

SUBJECTS

Fifty subjects with normal brains and aged in their 20s, 30s, 40s, 50s, or 60s (five men, five women per decade).

FIELD STRENGTH/SEQUENCE

3.0T MRI and elastography with a vibration frequency of 60 Hz.

ASSESSMENT

Stiffness was measured in nine brain regions (cerebrum, temporal lobes, sensorimotor areas, frontotemporal composite region, deep gray matter and white matter (deep GM/WM), parietal lobes, occipital lobes, frontal lobes, and cerebellum) using an atlas-based region-of-interest approach. The influence of age on regional brain stiffness was evaluated.

STATISTICAL TESTS

Multiple linear regression analysis, followed by Dunnett's multiple comparisons test, using subjects in their 20s as controls.

RESULTS

Following adjustment for sex, multiple linear regression revealed a significant negative correlation between age and stiffness of the cerebrum (P < 0.0001), temporal lobes (P < 0.0001), sensorimotor areas (P < 0.0001), frontotemporal composite region (P < 0.0001), deep GM/WM (P = 0.0028), parietal lobes (P < 0.0001), occipital lobes (P = 0.0055), and frontal lobes (P < 0.0001). Dunnett's multiple comparison test showed that the stiffness of the sensorimotor areas, frontotemporal composite region, and frontal lobes was significantly decreased in subjects in their 40s (P < 0.0367), 50s (P < 0.0001), and 60s (P < 0.0001), while that of the cerebrum, temporal lobes, and parietal lobes was significantly decreased only in subjects in their 50s (P < 0.0012) and 60s (P < 0.0031) when compared with the controls.

DATA CONCLUSION

There is an age-related decrease in brain stiffness that varies across the different regions.

LEVEL OF EVIDENCE

1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:727-733.

Age-Related Decline of Low-Spatial-Frequency Bias in Context-Dependent Visual Size Perception

Global precedence has been found to decline or even shift to local precedence with increasing age. Little is known about the consequence of this age-related decline of global precedence on other aspects of older adults’ vision. The global and local processing has been preferentially associated with the low-spatial-frequency (LSF) and high-spatial-frequency (HSF) channels, respectively. Here, we used low- and high-pass filtered faces together with the Ebbinghaus illusion whose magnitude is an index of context sensitivity. The results demonstrated that, relative to HSF faces, prior exposure to LSF faces increased the illusion magnitude for younger participants, but it reduced the illusion magnitude for older participants. Significant age group difference was observed only with prior exposure to LSF faces but not to HSF faces. Moreover, similar patterns of results were observed when the filtered faces were rendered invisible with backward masking, and the magnitude of age-related decline was comparable to the visible condition. Our study reveals that LSF-related enhancement of context sensitivity declines with advancing age, and this age-related decline was independent of the awareness of the spatial frequency information. Our findings support the right hemi-aging model and suggest that the magnocellular projections from subcortical to cortical regions might also be vulnerable to age-related changes.

Dose-dependent atrophy of the amygdala after radiotherapy

BACKGROUND AND PURPOSE

The amygdalae are deep brain nuclei critical to emotional processing and the creation and storage of memory. It is not known whether the amygdalae are affected by brain radiotherapy (RT). We sought to quantify dose-dependent amygdala change one year after brain RT.

MATERIALS AND METHODS

52 patients with primary brain tumors were retrospectively identified. Study patients underwent high-resolution, volumetric magnetic resonance imaging before RT and 1 year afterward. Images were processed using FDA-cleared software for automated segmentation of amygdala volume. Tumor, surgical changes, and segmentation errors were manually censored. Mean amygdala RT dose was tested for correlation with amygdala volume change 1 year after RT via the Pearson correlation coefficient. A linear mixed-effects model was constructed to evaluate potential predictors of amygdala volume change, including age, tumor hemisphere, sex, seizure history, and bevacizumab treatment during the study period. As 51 of 52 patients received chemotherapy, possible chemotherapy effects could not be studied. A two-tailed p-value <0.05 was considered statistically significant.

RESULTS

Mean amygdala RT dose (r = -0.28, p = 0.01) was significantly correlated with volume loss. On multivariable analysis, the only significant predictor of amygdala atrophy was radiation dose. The final linear mixed-effects model estimated amygdala volume loss of 0.17% for every 1 Gy increase in mean amygdala RT dose (p = 0.008).

CONCLUSIONS

The amygdala demonstrates dose-dependent atrophy one year after radiotherapy for brain tumors. Amygdala atrophy may mediate neuropsychological effects seen after brain RT.

Brain gray matter volume associations with gait speed and related structural covariance networks in cognitively healthy individuals and in patients with mild cognitive impairment: A cross-sectional study

INTRODUCTION

Gait speed is slower in patients with mild cognitive impairment (MCI) compared to cognitively healthy individuals (CHI). We examined the patterns of brain gray matter (GM) volume association and covariance with gait speed in CHI and in patients with MCI.

METHODS

A total of 96 CHI and 99 patients with MCI were recruited in this cross-sectional study. Brain GM volumes measured with voxel-based morphometry and self-paced gait speed were used as outcomes.

RESULTS

The right middle frontal and precentral gyri volumes were positively associated with gait speed in CHI and covariated with frontal cortex. Striatum (i.e. left putamen and bilateral caudate nuclei) volumes were positively associated with gait speed in patients with MCI and covariated with striatal structures.

CONCLUSIONS

Two different patterns of brain GM volume association and covariance with gait speed were found and involving frontal cortex in CHI and the striatum in patients with MCI.

P300, Gray Matter Volume and Individual Characteristics Correlates in Healthy Elderly

We investigated whether P300-ERP and cognitive test performance differ for age, sex, and education in two groups of healthy elderly, and verified whether any correlations exist between P300 amplitude and latency and gray matter volume using whole brain voxel-by-voxel-based mapping, controlling for age, education, sex and Total Intracranial Volume (TIV). We used 32 channel electroencephalograms (EEG) to record the P300 responses and 3T Magnetic Resonance Imaging (MRI) to determine gray matter volume. We recruited 36 native-Dutch speaking healthy older subjects, equally divided in two sub-groups of 52-64 and 65-76 years old, administered a battery of cognitive tests and recorded their demographics, EEGs and task performance; additionally, 16 adults from the second sub-group underwent an MRI scan. We found significant differences between age groups in their cognitive tests performance, P300 amplitudes for the frontal and parietal electrodes for the most difficult task, and P300 latencies for frontal, central and parietal electrodes for all three tasks difficulty levels. Interesting, sex and education affected cognitive and P300 results. Higher education was related to higher accuracy, and P300 amplitudes and shorter latencies. Moreover, females exhibited higher P300 amplitudes and shorter latencies, and better cognitive tasks performance compared to males. Additionally, for the 16 adults underwent to MRI scan, we found positive correlations between P300 characteristics in frontal, central and parietal areas and gray matter volume, controlling for demographic variables and TIV, but also showing that age, sex, and education correlate with gray matter volume. These findings provide support that age, sex, and education affect an individual's cognitive, neurophysiological and structural characteristics, and therefore motivate the need to further investigate these in relation to P300 responses and gray matter volume in healthy elderly.

Emotional Response Inhibition Is Greater in Older Than Younger Adults

Emotional information rapidly captures our attention and also often invokes automatic response tendencies, whereby positive information motivates approach, while negative information encourages avoidance. However, many circumstances require the need to override or inhibit these automatic responses. Control over responses to emotional information remains largely intact in late life, in spite of age-related declines in cognitive control and inhibition of responses to non-emotional information. The goal of this behavioral study was to understand how the aging process influences emotional response inhibition for positive and negative information in older adults. We examined emotional response inhibition in 36 healthy older adults (ages 60–89) and 44 younger adults (ages 18–22) using an emotional Go/No-Go task presenting happy (positive), fearful (negative), and neutral faces. In both younger and older adults, happy faces produced more approach-related behavior (i.e., fewer misses), while fearful faces produced more avoidance-related behavior, in keeping with theories of approach/avoidance-motivated responses. Calculation of speed/accuracy trade-offs between response times and false alarm rates revealed that younger and older adults both favored speed at the expense of accuracy, most robustly within blocks with fearful faces. However, there was no indication that the strength of the speed/accuracy trade-off differed between younger and older adults. The key finding was that although younger adults were faster to respond to all types of faces, older adults had greater emotional response inhibition (i.e., fewer false alarms). Moreover, younger adults were particularly prone to false alarms for happy faces. This is the first study to directly test effects of aging on emotional response inhibition. Complementing previous literature in the domains of attention and memory, these results provide new evidence that in the domain of response inhibition older adults may more effectively employ emotion regulatory ability, albeit on a slower time course, compared to younger adults. Older adults’ enhanced adaptive emotion regulation strategies may facilitate resistance to emotional distraction. The present study extends the literature of emotional response inhibition in younger adulthood into late life, and in doing so further elucidates how cognitive aging interacts with affective control processes.

Age related metabolic modifications in the migraine brain

Purpose

The aim of this study was to evaluate the possibility that migraine patients exhibit specific age-related metabolic changes in the brain, which occur regardless of disease duration or the frequency of attacks.

Methods

We analysed the relation between brain glucose (18F-fluorodeoxyglucose) uptake and age in healthy volunteers (n = 20) and episodic migraine patients (n = 19). In the latter, we additionally compared the correlation between 18F-fluorodeoxyglucose uptake and disease duration and monthly migraine days.

Results

In contrast to controls, in migraine patients advancing age was positively correlated to increased metabolism in the brainstem (especially the posterior pons), hippocampus, fusiform gyrus and parahippocampus. Conversely, no significant correlations between cerebral metabolism and disease duration or migraine days were observed.

Conclusions

Findings of this cross-sectional study show that episodic migraine patients exhibit specific metabolic brain modifications while ageing. As such, age is correlated with metabolic changes in key regions of the brain previously associated with migraine's pathophysiology to a better extent than disease duration or the number of monthly migraine days. More than the repeated headache attacks, the continuous interaction with the environment seemingly models the brain of migraine sufferers in an adaptive manner. A positive control (e.g. chronic pain) is missing in this study and therefore findings cannot be proven to be migraine-specific.

Reduced Gray Matter Volume of the Thalamus and Hippocampal Region in Elderly Healthy Adults with no Impact of APOE ɛ4: A Longitudinal Voxel-Based Morphometry Study

BACKGROUND

Many cross-sectional voxel-based morphometry (VBM) investigations have shown significant inverse correlations between chronological age and gray matter (GM) volume in several brain regions in healthy humans. However, few VBM studies have documented GM decrements in the healthy elderly with repeated MRI measurements obtained in the same subjects. Also, the extent to which the APOE ɛ4 allele influences longitudinal findings of GM reduction in the healthy elderly is unclear.

OBJECTIVE

Verify whether regional GM changes are associated with significant decrements in cognitive performance taking in account the presence of the APOE ɛ4 allele.

METHODS

Using structural MRI datasets acquired in 55 cognitively intact elderly subjects at two time-points separated by approximately three years, we searched for voxels showing significant GM reductions taking into account differences in APOE genotype.

RESULTS

We found global GM reductions as well as regional GM decrements in the right thalamus and left parahippocampal gyrus (p < 0.05, family-wise error corrected for multiple comparisons over the whole brain). These findings were not affected by APOE ɛ4.

CONCLUSIONS

Irrespective of APOE ɛ4, longitudinal VBM analyses show that the hippocampal region and thalamus are critical sites where GM shrinkage is greater than the degree of global volume reduction in healthy elderly subjects.