Age-related changes in grey and white matter structure throughout adulthood

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.

Cognitive and neuroscientific perspectives of healthy ageing

With dementia incidence projected to escalate significantly within the next 25 years, the United Nations declared 2021-2030 the Decade of Healthy Ageing, emphasising cognition as a crucial element. As a leading discipline in cognition and ageing research, psychology is well-equipped to offer insights for translational research, clinical practice, and policy-making. In this comprehensive review, we discuss the current state of knowledge on age-related changes in cognition and psychological health. We discuss cognitive changes during ageing, including (a) heterogeneity in the rate, trajectory, and characteristics of decline experienced by older adults, (b) the role of cognitive reserve in age-related cognitive decline, and (c) the potential for cognitive training to slow this decline. We also examine ageing and cognition through multiple theoretical perspectives. We highlight critical unresolved issues, such as the disparate implications of subjective versus objective measures of cognitive decline and the insufficient evaluation of cognitive training programs. We suggest future research directions, and emphasise interdisciplinary collaboration to create a more comprehensive understanding of the factors that modulate cognitive ageing.

High-resolution dataset of manual claustrum segmentation

The claustrum has a unique thin sheet-like structure that makes it hard to identify in typical anatomical MRI scans. Attempts have been made to identify the claustrum in anatomical images with either automatic segmentation techniques or using atlas-based approaches. However, the resulting labels fail to include the ventral claustrum portion, which consists of fragmented grey matter referred to as "puddles". The current dataset is a high-resolution label of the whole claustrum manually defined using an ultra-high resolution postmortem MRI image of one individual. Manual labelling was performed by four independent research trainees. Two trainees labelled the left claustrum and another two trainees labelled the right claustrum. For every hemisphere we created a union of the two labels and assessed the label correspondence using dice coefficients. We provide size measurements of the labels in MNI space by calculating the oriented bounding box size. These data are the first manual claustrum segmentation labels that include both the dorsal and ventral claustrum regions at such a high resolution in standard space. The label can be used to approximate the claustrum location in typical in vivo MRI scans of healthy individuals.

Age-related changes in responsiveness to non-invasive brain stimulation neuroplasticity paradigms: A systematic review with meta-analysis

OBJECTIVES

We aimed to summarise and critically appraise the available evidence for the effect of age on responsiveness to non-invasive brain stimulation (NBS) paradigms delivered to the primary motor cortex.

METHODS

Four databases (Medline, Embase, PsycINFO and Scopus) were searched from inception to February 7, 2023. Studies investigating age group comparisons and associations between age and neuroplasticity induction from NBS paradigms were included. Only studies delivering neuroplasticity paradigms to the primary motor cortex and responses measured via motor-evoked potentials (MEPs) in healthy adults were considered.

RESULTS

39 studies, encompassing 40 experiments and eight NBS paradigms were included: paired associative stimulation (PAS; n = 12), repetitive transcranial magnetic stimulation (rTMS; n = 2), intermittent theta burst stimulation (iTBS; n = 8), continuous theta burst stimulation (cTBS; n = 7), transcranial direct and alternating current stimulation ((tDCS; n = 7; tACS; n = 2)), quadripulse stimulation (QPS; n = 1) and i-wave periodic transcranial magnetic stimulation (iTMS; n = 1). Pooled findings from PAS paradigms suggested older adults have reduced post-paradigm responses, although there was considerable heterogeneity. Mixed results were observed across all other NBS paradigms and post-paradigm timepoints.

CONCLUSIONS/SIGNIFICANCE

Whilst age-dependent reduction in corticospinal excitability is possible, there is extensive inter- and intra-individual variability both within and between studies, making it difficult to draw meaningful conclusions from pooled analyses.

Probing Evidence of Cerebral White Matter Microstructural Disruptions in Ischemic Heart Disease Before and Following Cardiac Rehabilitation: A Diffusion Tensor MR Imaging Study

BACKGROUND

Ischemic heart disease (IHD) is linked to brain white matter (WM) breakdown but how age or disease effects WM integrity, and whether it is reversible using cardiac rehabilitation (CR), remains unclear.

PURPOSE

To assess the effects of brain aging, cardiovascular disease, and CR on WM microstructure in brains of IHD patients following a cardiac event.

STUDY TYPE

Retrospective.

POPULATION

Thirty-five IHD patients (9 females; mean age = 59 ± 8 years), 21 age-matched healthy controls (10 females; mean age = 59 ± 8 years), and 25 younger controls (14 females; mean age = 26 ± 4 years).

FIELD STRENGTH/SEQUENCE

3 T diffusion-weighted imaging with single-shot echo planar imaging acquired at 3 months and 9 months post-cardiac event.

ASSESSMENT

Tract-based spatial statistics (TBSS) and tractometry were used to compare fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) in cerebral WM between: 1) older and younger controls to distinguish age-related from disease-related WM changes; 2) IHD patients at baseline (pre-CR) and age-matched controls to investigate if cardiovascular disease exacerbates age-related WM changes; and 3) IHD patients pre-CR and post-CR to investigate the neuroplastic effect of CR on WM microstructure.

STATISTICAL TESTS

Two-sample unpaired t-test (age: older vs. younger controls; IHD: IHD pre-CR vs. age-matched controls). One-sample paired t-test (CR: IHD pre- vs. post-CR). Statistical threshold: P < 0.05 (FWE-corrected).

RESULTS

TBSS and tractometry revealed widespread WM changes in older controls compared to younger controls while WM clusters of decreased FA in the fornix and increased MD in body of corpus callosum were observed in IHD patients pre-CR compared to age-matched controls. Robust WM improvements (increased FA, increased AD) were observed in IHD patients post-CR.

DATA CONCLUSION

In IHD, both brain aging and cardiovascular disease may contribute to WM disruptions. IHD-related WM disruptions may be favorably modified by CR.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Brain elastography in aging relates to fluid/solid trendlines

The relatively new tools of brain elastography have established a general trendline for healthy, aging adult humans, whereby the brain's viscoelastic properties 'soften' over many decades. Earlier studies of the aging brain have demonstrated a wide spectrum of changes in morphology and composition towards the later decades of lifespan. This leads to a major question of causal mechanisms: of the many changes documented in structure and composition of the aging brain, which ones drive the long term trendline for viscoelastic properties of grey matter and white matter? The issue is important for illuminating which factors brain elastography is sensitive to, defining its unique role for study of the brain and clinical diagnoses of neurological disease and injury. We address these issues by examining trendlines in aging from our elastography data, also utilizing data from an earlier landmark study of brain composition, and from a biophysics model that captures the multiscale biphasic (fluid/solid) structure of the brain. Taken together, these imply that long term changes in extracellular water in the glymphatic system of the brain along with a decline in the extracellular matrix have a profound effect on the measured viscoelastic properties. Specifically, the trendlines indicate that water tends to replace solid fraction as a function of age, then grey matter stiffness decreases inversely as water fraction squared, whereas white matter stiffness declines inversely as water fraction to the 2/3 power, a behavior consistent with the cylindrical shape of the axons. These unique behaviors point to elastography of the brain as an important macroscopic measure of underlying microscopic structural change, with direct implications for clinical studies of aging, disease, and injury.

Choir singing is associated with enhanced structural connectivity across the adult lifespan

The global ageing of populations calls for effective, ecologically valid methods to support brain health across adult life. Previous evidence suggests that music can promote white matter (WM) microstructure and grey matter (GM) volume while supporting auditory and cognitive functioning and emotional well-being as well as counteracting age-related cognitive decline. Adding a social component to music training, choir singing is a popular leisure activity among older adults, but a systematic account of its potential to support healthy brain structure, especially with regard to ageing, is currently missing. The present study used quantitative anisotropy (QA)-based diffusion MRI connectometry and voxel-based morphometry to explore the relationship of lifetime choir singing experience and brain structure at the whole-brain level. Cross-sectional multiple regression analyses were carried out in a large, balanced sample (N = 95; age range 21-88) of healthy adults with varying levels of choir singing experience across the whole age range and within subgroups defined by age (young, middle-aged, and older adults). Independent of age, choir singing experience was associated with extensive increases in WM QA in commissural, association, and projection tracts across the brain. Corroborating previous work, these overlapped with language and limbic networks. Enhanced corpus callosum microstructure was associated with choir singing experience across all subgroups. In addition, choir singing experience was selectively associated with enhanced QA in the fornix in older participants. No associations between GM volume and choir singing were found. The present study offers the first systematic account of amateur-level choir singing on brain structure. While no evidence for counteracting GM atrophy was found, the present evidence of enhanced structural connectivity coheres well with age-typical structural changes. Corroborating previous behavioural studies, the present results suggest that regular choir singing holds great promise for supporting brain health across the adult life span.

Understanding Wellbeing Profiles According to White Matter Structural Connectivity Sub-types in Early Adolescents: The First Hundred Brains Cohort from the Longitudinal Adolescent Brain Study

Wellbeing is protective against the emergence of psychopathology. Neurobiological markers associated with mental wellbeing during adolescence are important to understand. Limited research has examined neural networks (white matter tracts) and mental wellbeing in early adolescence specifically. A cross-sectional diffusion tensor imaging analysis approach was conducted, from the Longitudinal Adolescent Brain study, First Hundred Brains cohort (N = 99; 46.5% female; Mage = 13.01, SD = 0.55). Participants completed self-report measures including wellbeing, quality-of-life, and psychological distress. Potential neurobiological profiles using fractional anisotropy, axial, and radial diffusivity were determined via a whole brain voxel-wise approach, and hierarchical cluster analysis of fractional anisotropy values, obtained from 21 major white matter tracts. Three cluster groups with significantly different neurobiological profiles were distinguished. No significant differences were found between the three cluster groups and measures of wellbeing, but two left lateralized significant associations between white matter tracts and wellbeing measures were found. These results provide preliminary evidence for potential neurobiological markers of mental health and wellbeing in early adolescence and should be tracked longitudinally to provide more detailed and robust findings.

Obesity differentially effects the somatosensory cortex and striatum of TgF344-AD rats

Lifestyle choices leading to obesity, hypertension and diabetes in mid-life contribute directly to the risk of late-life Alzheimer's disease (AD). However, in late-life or in late-stage AD conditions, obesity reduces the risk of AD and disease progression. To examine the mechanisms underlying this paradox, TgF344-AD rats were fed a varied high-carbohydrate, high-fat (HCHF) diet to induce obesity from nine months of age representing early stages of AD to twelve months of age in which rats exhibit the full spectrum of AD symptomology. We hypothesized regions primarily composed of gray matter, such as the somatosensory cortex (SSC), would be differentially affected compared to regions primarily composed of white matter, such as the striatum. We found increased myelin and oligodendrocytes in the somatosensory cortex of rats fed the HCHF diet with an absence of neuronal loss. We observed decreased inflammation in the somatosensory cortex despite increased AD pathology. Compared to the somatosensory cortex, the striatum had fewer changes. Overall, our results suggest that the interaction between diet and AD progression affects myelination in a brain region specific manner such that regions with a lower density of white matter are preferentially affected. Our results offer a possible mechanistic explanation for the obesity paradox.

The regional pattern of age-related synaptic loss in the human brain differs from gray matter volume loss: in vivo PET measurement with [11C]UCB-J

PURPOSE

Aging is a major societal concern due to age-related functional losses. Synapses are crucial components of neural circuits, and synaptic density could be a sensitive biomarker to evaluate brain function. [11C]UCB-J is a positron emission tomography (PET) ligand targeting synaptic vesicle glycoprotein 2A (SV2A), which can be used to evaluate brain synaptic density in vivo.

METHODS

We evaluated age-related changes in gray matter synaptic density, volume, and blood flow using [11C]UCB-J PET and magnetic resonance imaging (MRI) in a wide age range of 80 cognitive normal subjects (21-83 years old). Partial volume correction was applied to the PET data.

RESULTS

Significant age-related decreases were found in 13, two, and nine brain regions for volume, synaptic density, and blood flow, respectively. The prefrontal cortex showed the largest volume decline (4.9% reduction per decade: RPD), while the synaptic density loss was largest in the caudate (3.6% RPD) and medial occipital cortex (3.4% RPD). The reductions in caudate are consistent with previous SV2A PET studies and likely reflect that caudate is the site of nerve terminals for multiple major tracts that undergo substantial age-related neurodegeneration. There was a non-significant negative relationship between volume and synaptic density reductions in 16 gray matter regions.

CONCLUSION

MRI and [11]C-UCB-J PET showed age-related decreases of gray matter volume, synaptic density, and blood flow; however, the regional patterns of the reductions in volume and SV2A binding were different. Those patterns suggest that MR-based measures of GM volume may not be directly representative of synaptic density.

Cortical thickness moderates intraindividual variability in prefrontal cortex activation patterns of older adults during walking

OBJECTIVE

Increased intraindividual variability (IIV) in behavioral and cognitive performance is a risk factor for adverse outcomes but research concerning hemodynamic signal IIV is limited. Cortical thinning occurs during aging and is associated with cognitive decline. Dual-task walking (DTW) performance in older adults has been related to cognition and neural integrity. We examined the hypothesis that reduced cortical thickness would be associated with greater increases in IIV in prefrontal cortex oxygenated hemoglobin (HbO2) from single tasks to DTW in healthy older adults while adjusting for behavioral performance.

METHOD

Participants were 55 healthy community-dwelling older adults (mean age = 74.84, standard deviation (SD) = 4.97). Structural MRI was used to quantify cortical thickness. Functional near-infrared spectroscopy (fNIRS) was used to assess changes in prefrontal cortex HbO2 during walking. HbO2 IIV was operationalized as the SD of HbO2 observations assessed during the first 30 seconds of each task. Linear mixed models were used to examine the moderation effect of cortical thickness throughout the cortex on HbO2 IIV across task conditions.

RESULTS

Analyses revealed that thinner cortex in several regions was associated with greater increases in HbO2 IIV from the single tasks to DTW (ps < .02).

CONCLUSIONS

Consistent with neural inefficiency, reduced cortical thickness in the PFC and throughout the cerebral cortex was associated with increases in HbO2 IIV from the single tasks to DTW without behavioral benefit. Reduced cortical thickness and greater IIV of prefrontal cortex HbO2 during DTW may be further investigated as risk factors for developing mobility impairments in aging.

Association between cortical thickness and cognitive ability in very preterm school-age children

Very preterm children, born before 32 weeks of gestation, are at risk for impaired cognitive function, mediated by several risk factors. Cognitive impairment can be measured by various neurodevelopmental assessments and is closely associated with structural alterations of brain morphometry, such as cortical thickness. However, the association between structural alterations and high-order cognitive function remains unclear. This study aimed to investigate the neurodevelopmental associations between brain structural changes and cognitive abilities in very preterm and full-term children. Cortical thickness was assessed in 37 very preterm and 24 full-term children aged 6 years. Cortical thickness analysis of structural T1-weighted images was performed using Advanced Normalization Tools. Associations between cortical thickness and the Wechsler Intelligence Scale for Children were evaluated by regression analysis based on ordinary least square estimation. Compared with full-term children, very preterm children showed significant differences in cortical thickness, variously associated with cognitive abilities in several brain regions. Perceptual reasoning indices were broadly correlated with cortical thickness in very preterm and full-term children. These findings provide important insights into neurodevelopment and its association with cortical thickness, which may serve as a biomarker in predictive models for neurodevelopmental diagnosis of high-order cognitive function.

Obesity differentially effects the somatosensory cortex and striatum of TgF344-AD rats

Lifestyle choices leading to obesity, hypertension and diabetes in mid-life contribute directly to the risk of late-life Alzheimer's disease (AD). However, in late-life or in late-stage AD conditions, obesity reduces the risk of AD and disease progression. To examine the mechanisms underlying this paradox, TgF344-AD rats were fed a varied high-carbohydrate, high-fat (HCHF) diet to induce obesity from nine months of age representing early stages of AD to twelve months of age in which rats exhibit the full spectrum of AD symptomology. We hypothesized regions primarily composed of gray matter, such as the somatosensory cortex (SSC), would be differentially affected compared to regions primarily composed of white matter, such as the striatum. We found increased myelin and oligodendrocytes in the somatosensory cortex of rats fed the HCHF diet with an absence of neuronal loss. We observed decreased inflammation in the somatosensory cortex despite increased AD pathology. Compared to the somatosensory cortex, the striatum had fewer changes. Overall, our results suggest that the interaction between diet and AD progression affects myelination in a brain region specific manner such that regions with a lower density of white matter are preferentially effected. Our results offer a possible mechanistic explanation for the obesity paradox.

3DCNN predicting brain age using diffusion tensor imaging

Neuroimaging-based brain age prediction using deep learning is gaining popularity. However, few studies have attempted to leverage diffusion tensor imaging (DTI) to predict brain age. In this study, we proposed a 3D convolutional neural network model (3DCNN) and trained it on fractional anisotropy (FA) data from six publicly available datasets (n = 2406, age = 17-60) to estimate brain age. Implementing a two-loop nested cross-validation scheme with a tenfold cross-validation procedure, we achieved a robust prediction performance of a mean absolute error (MAE) of 2.785 and a correlation coefficient of 0.932. We also employed Grad-Cam++ to visualize the salient features of the proposed model. We identified a few highly salient fiber tracts, including the genu of corpus callosum and the left cerebellar peduncle, among others that play a pivotal role in our model. In sum, our model reliably predicted brain age and provided novel insight into age-related changes in brains' axonal structure.

Predicting executive functioning from brain networks: modality specificity and age effects

Healthy aging is associated with structural and functional network changes in the brain, which have been linked to deterioration in executive functioning (EF), while their neural implementation at the individual level remains unclear. As the biomarker potential of individual resting-state functional connectivity (RSFC) patterns has been questioned, we investigated to what degree individual EF abilities can be predicted from the gray-matter volume (GMV), regional homogeneity, fractional amplitude of low-frequency fluctuations (fALFF), and RSFC within EF-related, perceptuo-motor, and whole-brain networks in young and old adults. We examined whether the differences in out-of-sample prediction accuracy were modality-specific and depended on age or task-demand levels. Both uni- and multivariate analysis frameworks revealed overall low prediction accuracies and moderate-to-weak brain-behavior associations (R2 < 0.07, r < 0.28), further challenging the idea of finding meaningful markers for individual EF performance with the metrics used. Regional GMV, well linked to overall atrophy, carried the strongest information about individual EF differences in older adults, whereas fALFF, measuring functional variability, did so for younger adults. Our study calls for future research analyzing more global properties of the brain, different task-states and applying adaptive behavioral testing to result in sensitive predictors for young and older adults, respectively.

The impact of resistance training on brain-derived neurotrophic factor and depression among older adults aged 60 years or older: A systematic review and meta-analysis of randomized controlled trials

OBJECTIVE

This systematic review and meta-analysis aimed to investigate the impact of resistance training on brain-derived neurotrophic factor (BDNF) and depression among older adults aged 60 years or older.

METHOD

Four electronic databases were systematically searched.

RESULTS

A total of 11 randomized controlled trials, with a pooled sample of 868 participants, met our inclusion criteria. Meta-analysis demonstrated that resistance training significantly improved circulating BDNF levels (mean difference; MD: 0.73 ng/ml; 95% CI [0.04, 1.42]; p = 0.04). Additionally, resistance training was associated with significant improvements in depression (standardized mean difference; SMD: -0.38; 95% CI [- 0.62, -0.14]; p = 0.002).

DISCUSSION

These findings suggest that resistance training may be an effective intervention for improving BDNF levels and reducing depression symptoms in older adults. Further research is needed to confirm these findings and to investigate the underlying mechanisms.

Age But Not Menopausal Status Is Linked to Lower Resting Energy Expenditure

CONTEXT

It remains uncertain whether aging before late adulthood and menopause are associated with fat-free mass and fat mass-adjusted resting energy expenditure (REEadj).

OBJECTIVES

We investigated whether REEadj differs between middle-aged and younger women and between middle-aged women with different menopausal statuses. We repeated the age group comparison between middle-aged mothers and their daughters to partially control for genotype. We also explored whether serum estradiol and FSH concentrations explain REEadj in midlife.

METHODS

We divided 120 women, including 16 mother-daughter pairs, into age groups; group I (n = 26) consisted of participants aged 17 to 21, group II (n = 35) of those aged 22 to 38, and group III (n = 59) of those aged 41 to 58 years. The women in group III were further categorized as pre- or perimenopausal (n = 19), postmenopausal (n = 30), or postmenopausal hormone therapy users (n = 10). REE was assessed using indirect calorimetry, body composition using dual-energy X-ray absorptiometry, and hormones using immunoassays.

RESULTS

The REEadj of group I was 126 kcal/day [95% confidence interval (CI): 93-160] higher than that of group III, and the REEadj of group II was 88 kcal/day (95% CI: 49-127) higher. Furthermore, daughters had a 100 kcal/day (95% CI: 63-138 kcal/day) higher REEadj than their middle-aged mothers (all P < .001). In group III, REEadj was not lower in postmenopausal women and did not vary by sex hormone concentrations.

CONCLUSIONS

We demonstrated that REEadj declines with age in women before late adulthood, also when controlling partially for genetic background, and that menopause may not contribute to this decline.

White matter tract microstructure, macrostructure, and associated cortical gray matter morphology across the lifespan

Characterizing how, when and where the human brain changes across the lifespan is fundamental to our understanding of developmental processes of childhood and adolescence, degenerative processes of aging, and divergence from normal patterns in disease and disorders. We aimed to provide detailed descriptions of white matter pathways across the lifespan by thoroughly characterizing white matter microstructure, white matter macrostructure, and morphology of the cortex associated with white matter pathways. We analyzed 4 large, high-quality, publicly-available datasets comprising 2789 total imaging sessions, and participants ranging from 0 to 100 years old, using advanced tractography and diffusion modeling. We first find that all microstructural, macrostructural, and cortical features of white matter bundles show unique lifespan trajectories, with rates and timing of development and degradation that vary across pathways - describing differences between types of pathways and locations in the brain, and developmental milestones of maturation of each feature. Second, we show cross-sectional relationships between different features that may help elucidate biological changes occurring during different stages of the lifespan. Third, we show unique trajectories of age-associations across features. Finally, we find that age associations during development are strongly related to those during aging. Overall, this study reports normative data for several features of white matter pathways of the human brain that will be useful for studying normal and abnormal white matter development and degeneration.

Improvements of Age-Related Cognitive Decline in Mice by Lactobacillus helveticus WHH1889, a Novel Strain with Psychobiotic Properties

A gradual decline in cognitive function occurs with age. Accumulating evidence suggests that certain probiotic strains exert beneficial effects on age-related cognitive decline. Our previous study revealed that Lactobacillus helveticus WHH1889 attenuated symptoms of anxiety and depression in depressed mice via shaping the 5-hydroxytryptamine (5-HT) and 5-hydroxytryptophan (5-HTP) metabolism and gut microbial community, indicating the psychobiotic potential of WHH1889. In the present study, the effects of WHH1889 on age-related cognitive decline were investigated. WHH1889 was orally administrated (1 × 109 CFU/day) for twelve weeks in aged mice, and their cognitive behaviors, neurochemical factors, cognitive-related gene expressions, neuroinflammation, and serum tryptophan pathway-targeted metabolic profiling, as well as gut microbiome composition were assessed. WHH1889 demonstrated improvement of the cognitive behaviors via the novel object recognition test (NORT), the active shuttle avoidance test (ASAT), the Y-maze test, and the passive avoidance test (PAT). The hippocampal neuronal loss; the declined concentrations of BDNF, 5-HT, and 5-HTP; the decreased gene expressions of neurodegeneration biomarkers; and the increased production of hippocampal inflammatory cytokines in aged mice were restored by WHH1889. In addition, WHH1889 increased the 5-HT/5HTP levels and decreased the serum levels of tryptophan-derived metabolites (e.g., kynurenine, xanthurenic acid, 3-hydroxykynurenine, and 3-hydroxyanthranilic acid). Furthermore, WHH1889 was revealed to shape the gut microbiota community by reversing the relative abundances of Bacteroidota and Firmicutes. The present findings suggest that L. helveticus WHH1889 exerted cognitive improving effects on aged mice, which was associated with the modulation of 5-HT and 5-HTP metabolism and gut microbial composition. The supplementation of WHH1889 may therefore be a promising therapeutic agent for age-related cognitive deficits.

Histological Study on the Thickness of Gray Matter at the Summit and Bottom of Folium in Different Age Groups of Bangladeshi People

Context The cerebellum is a part of the hindbrain and consists of cortical gray matter (GM) at the surface and a medullary core of white matter (WM). The GM contains a cell body of neurons that helps process and transmit any command type through nerve fibers found in the WM. The main functions of GM in the central nervous system empower persons to control motor activity, recollection, and passion. So, this research aims to assess the thickness of GM at the summit and bottom of folia by histologically studying the cerebellum cortex. Methods The collection of data was a descriptive type of cross-sectional study. The method was the purposive type. This study was conducted from August 2016 to March 2017, and the research was carried out at Mymensingh Medical College's Department of Anatomy, Bangladesh. Specimens containing cerebellum were preserved from Bangladeshi cadavers according to sexes and ages ranging in years. We chose fresh specimens from people who died within the last 12 hours and preserved them in 10% formol saline. The size of the tissue that was collected for the histological study was not more than 2 cm² and not more than 4-5 mm thick. Then the tissue was placed in 10% formol saline. This fluid was used for quick fixation and partial dehydration of the tissue. After dehydration, each tissue segment is processed for infiltration and embedding separately. Every section was stained with hematoxylin and eosin stain (H&E) before being coated with dibutyl phthalate polystyrene xylene (DPX) coverslips on slides. Result The mean (±SD) thickness of GM at the summit of folium was 886.2±29.7µm in Group A, 925.2±25.9µm in Group B, 912.7±22.3µm in Group C, and 839.9±40.7µm in Group D. Mean (±SD) GM thickness at the bottom of the fissure was 395.6±12.2 µm, 403.9±26.0µm, 380.4±23.4 µm, and 375.8±28.8 µm in Groups A, B, C, and D respectively. Conclusion The thickness of the cortex is an essential factor in the normal development process, and it was similar in the current study. Normal aging, Alzheimer's disease, and other dementias cause reduced GM which makes the cortical sheet thin. Huntington's disease, corticobasal degeneration, amyotrophic lateral sclerosis, and schizophrenia are all examples of neurological disorders. Cortical thinning is typically locally localized, and the progression of atrophy can thus disclose much about a disease's history and causal variables. The present study correspondingly found that GM was reduced after the age of 50 years onward. Furthermore, longitudinal investigations of cortical atrophy have the potential to be extremely useful in measuring the efficacy of a wide range of treatments.

Predicting Executive Functioning from Brain Networks: Modality Specificity and Age Effects

Healthy aging is associated with structural and functional network changes in the brain, which have been linked to deterioration in executive functioning (EF), while their neural implementation at the individual level remains unclear. As the biomarker potential of individual resting-state functional connectivity (RSFC) patterns has been questioned, we investigated to what degree individual EF abilities can be predicted from gray-matter volume (GMV), regional homogeneity, fractional amplitude of low-frequency fluctuations (fALFF), and RSFC within EF-related, perceptuo-motor, and whole-brain networks in young and old adults. We examined whether differences in out-of-sample prediction accuracy were modality-specific and depended on age or task-demand levels. Both uni- and multivariate analysis frameworks revealed overall low prediction accuracies and moderate to weak brain-behavior associations (R2 < .07, r < .28), further challenging the idea of finding meaningful markers for individual EF performance with the metrics used. Regional GMV, well linked to overall atrophy, carried the strongest information about individual EF differences in older adults, whereas fALFF, measuring functional variability, did so for younger adults. Our study calls for future research analyzing more global properties of the brain, different task-states and applying adaptive behavioral testing to result in sensitive predictors for young and older adults, respectively.

Superficial white matter across development, young adulthood, and aging: volume, thickness, and relationship with cortical features

Superficial white matter (SWM) represents a significantly understudied part of the human brain, despite comprising a large portion of brain volume and making up a majority of cortico-cortical white matter connections. Using multiple, high-quality datasets with large sample sizes (N = 2421, age range 5-100) in combination with methodological advances in tractography, we quantified features of SWM volume and thickness across the brain and across development, young adulthood, and aging. We had four primary aims: (1) characterize SWM thickness across brain regions (2) describe associations between SWM volume and age (3) describe associations between SWM thickness and age, and (4) quantify relationships between SWM thickness and cortical features. Our main findings are that (1) SWM thickness varies across the brain, with patterns robust across individuals and across the population at the region-level and vertex-level; (2) SWM volume shows unique volumetric trajectories with age that are distinct from gray matter and other white matter trajectories; (3) SWM thickness shows nonlinear cross-sectional changes across the lifespan that vary across regions; and (4) SWM thickness is associated with features of cortical thickness and curvature. For the first time, we show that SWM volume follows a similar trend as overall white matter volume, peaking at a similar time in adolescence, leveling off throughout adulthood, and decreasing with age thereafter. Notably, the relative fraction of total brain volume of SWM continuously increases with age, and consequently takes up a larger proportion of total white matter volume, unlike the other tissue types that decrease with respect to total brain volume. This study represents the first characterization of SWM features across the large portion of the lifespan and provides the background for characterizing normal aging and insight into the mechanisms associated with SWM development and decline.

Brain-age prediction: A systematic comparison of machine learning workflows

The difference between age predicted using anatomical brain scans and chronological age, i.e., the brain-age delta, provides a proxy for atypical aging. Various data representations and machine learning (ML) algorithms have been used for brain-age estimation. However, how these choices compare on performance criteria important for real-world applications, such as; (1) within-dataset accuracy, (2) cross-dataset generalization, (3) test-retest reliability, and (4) longitudinal consistency, remains uncharacterized. We evaluated 128 workflows consisting of 16 feature representations derived from gray matter (GM) images and eight ML algorithms with diverse inductive biases. Using four large neuroimaging databases covering the adult lifespan (total N = 2953, 18-88 years), we followed a systematic model selection procedure by sequentially applying stringent criteria. The 128 workflows showed a within-dataset mean absolute error (MAE) between 4.73-8.38 years, from which 32 broadly sampled workflows showed a cross-dataset MAE between 5.23-8.98 years. The test-retest reliability and longitudinal consistency of the top 10 workflows were comparable. The choice of feature representation and the ML algorithm both affected the performance. Specifically, voxel-wise feature spaces (smoothed and resampled), with and without principal components analysis, with non-linear and kernel-based ML algorithms performed well. Strikingly, the correlation of brain-age delta with behavioral measures disagreed between within-dataset and cross-dataset predictions. Application of the best-performing workflow on the ADNI sample showed a significantly higher brain-age delta in Alzheimer's and mild cognitive impairment patients compared to healthy controls. However, in the presence of age bias, the delta estimates in the patients varied depending on the sample used for bias correction. Taken together, brain-age shows promise, but further evaluation and improvements are needed for its real-world application.

Associations of baseline and longitudinal change in cerebellum volume with age-related changes in verbal learning and memory

The cerebellum is involved in higher-order cognitive functions, e.g., learning and memory, and is susceptible to age-related atrophy. Yet, the cerebellum's role in age-related cognitive decline remains largely unknown. We investigated cross-sectional and longitudinal associations between cerebellar volume and verbal learning and memory. Linear mixed effects models and partial correlations were used to examine the relationship between changes in cerebellum volumes (total cerebellum, cerebellum white matter [WM], cerebellum hemisphere gray matter [GM], and cerebellum vermis subregions) and changes in verbal learning and memory performance among 549 Baltimore Longitudinal Study of Aging participants (2,292 visits). All models were adjusted by baseline demographic characteristics (age, sex, race, education), and APOE e4 carrier status. In examining associations between change with change, we tested an additional model that included either hippocampal (HC), cuneus, or postcentral gyrus (PoCG) volumes to assess whether cerebellar volumes were uniquely associated with verbal learning and memory. Cross-sectionally, the association of baseline cerebellum GM and WM with baseline verbal learning and memory was age-dependent, with the oldest individuals showing the strongest association between volume and performance. Baseline volume was not significantly associated with change in learning and memory. However, analysis of associations between change in volumes and changes in verbal learning and memory showed that greater declines in verbal memory were associated with greater volume loss in cerebellum white matter, and preserved GM volume in cerebellum vermis lobules VI-VII. The association between decline in verbal memory and decline in cerebellar WM volume remained after adjustment for HC, cuneus, and PoCG volume. Our findings highlight that associations between cerebellum volume and verbal learning and memory are age-dependent and regionally specific.

Among Gerontogens, Heavy Metals Are a Class of Their Own: A Review of the Evidence for Cellular Senescence

Advancements in modern medicine have improved the quality of life across the globe and increased the average lifespan of our population by multiple decades. Current estimates predict by 2030, 12% of the global population will reach a geriatric age and live another 3-4 decades. This swelling geriatric population will place critical stress on healthcare infrastructures due to accompanying increases in age-related diseases and comorbidities. While much research focused on long-lived individuals seeks to answer questions regarding how to age healthier, there is a deficit in research investigating what aspects of our lives accelerate or exacerbate aging. In particular, heavy metals are recognized as a significant threat to human health with links to a plethora of age-related diseases, and have widespread human exposures from occupational, medical, or environmental settings. We believe heavy metals ought to be classified as a class of gerontogens (i.e., chemicals that accelerate biological aging in cells and tissues). Gerontogens may be best studied through their effects on the "Hallmarks of Aging", nine physiological hallmarks demonstrated to occur in aged cells, tissues, and bodies. Evidence suggests that cellular senescence-a permanent growth arrest in cells-is one of the most pertinent hallmarks of aging and is a useful indicator of aging in tissues. Here, we discuss the roles of heavy metals in brain aging. We briefly discuss brain aging in general, then expand upon observations for heavy metals contributing to age-related neurodegenerative disorders. We particularly emphasize the roles and observations of cellular senescence in neurodegenerative diseases. Finally, we discuss the observations for heavy metals inducing cellular senescence. The glaring lack of knowledge about gerontogens and gerontogenic mechanisms necessitates greater research in the field, especially in the context of the global aging crisis.

Fast three-dimensional image generation for healthy brain aging using diffeomorphic registration

Predicting brain aging can help in the early detection and prognosis of neurodegenerative diseases. Longitudinal cohorts of healthy subjects scanned through magnetic resonance imaging (MRI) have been essential to understand the structural brain changes due to aging. However, these cohorts suffer from missing data due to logistic issues in the recruitment of subjects. This paper proposes a methodology for filling up missing data in longitudinal cohorts with anatomically plausible images that capture the subject-specific aging process. The proposed methodology is developed within the framework of diffeomorphic registration. First, two novel modules are introduced within Synthmorph, a fast, state-of-the-art deep learning-based diffeomorphic registration method, to simulate the aging process between the first and last available MRI scan for each subject in three-dimensional (3D). The use of image registration also makes the generated images plausible by construction. Second, we used six image similarity measurements to rearrange the generated images to the specific age range. Finally, we estimated the age of every generated image by using the assumption of linear brain decay in healthy subjects. The methodology was evaluated on 2662 T1-weighted MRI scans from 796 healthy participants from 3 different longitudinal cohorts: Alzheimer's Disease Neuroimaging Initiative, Open Access Series of Imaging Studies-3, and Group of Neuropsychological Studies of the Canary Islands (GENIC). In total, we generated 7548 images to simulate the access of a scan per subject every 6 months in these cohorts. We evaluated the quality of the synthetic images using six quantitative measurements and a qualitative assessment by an experienced neuroradiologist with state-of-the-art results. The assumption of linear brain decay was accurate in these cohorts (R2  ∈ [.924, .940]). The experimental results show that the proposed methodology can produce anatomically plausible aging predictions that can be used to enhance longitudinal datasets. Compared to deep learning-based generative methods, diffeomorphic registration is more likely to preserve the anatomy of the different structures of the brain, which makes it more appropriate for its use in clinical applications. The proposed methodology is able to efficiently simulate anatomically plausible 3D MRI scans of brain aging of healthy subjects from two images scanned at two different time points.

The multifaceted role of neurofilament light chain protein in non-primary neurological diseases

The advancing validation and exploitation of CSF and blood neurofilament light chain protein as a biomarker of neuroaxonal damage has deeply changed the current diagnostic and prognostic approach to neurological diseases. Further, recent studies have provided evidence of potential new applications of this biomarker also in non-primary neurological diseases. In the present review we summarize the state of the art, future perspectives, but also limitations, of neurofilament light chain protein as a CSF and blood biomarker in several medical fields, including intensive care medicine, surgery, internal medicine and psychiatry. In particular, neurofilament light chain protein is associated with the degree of neurological impairment and outcome in patients admitted to intensive care units or in the perioperative phase and it seems to be highly interconnected with cardiovascular risk factors. Beyond that, interesting diagnostic and prognostic insights have been provided by the investigation of neurofilament light chain protein in psychiatric disorders as well as in the current coronavirus disease-19 pandemic and in normal ageing. Altogether, current data outline a multifaceted applicability of CSF and blood neurofilament light chain protein ranging from the critical clinical setting to the development of precision medicine models suggesting a strict interplay between the nervous system pathophysiology and the health-illness continuum.

Peripheral Regulation of Central Brain-Derived Neurotrophic Factor Expression through the Vagus Nerve

The brain-derived neurotrophic factor (BDNF) is an extensively studied neurotrophin es sential for both developing the brain and maintaining adult brain function. In the adult hippocampus, BDNF is critical for maintaining adult neurogenesis. Adult hippocampal neurogenesis is involved not only in memory formation and learning ability, but also mood regulation and stress responses. Accordingly, decreased levels of BDNF, accompanied by low levels of adult neurogenesis, occurs in brains of older adults with impaired cognitive function and in those of patients with major depression disorder. Therefore, elucidating the mechanisms that maintain hippocampal BDNF levels is biologically and clinically important. It has been revealed that signalling from peripheral tissues contribute to the regulation of BDNF expression in the brain across the blood-brain barrier. Moreover, recent studies indicated evidence that neuronal pathways can also be a mechanism by which peripheral tissues signal to the brain for the regulation of BDNF expression. In this review, we give an overview of the current status in the regulation of central BDNF expression by peripheral signalling, with a special interest in the regulation of hippocampal BDNF levels by signals via the vagus nerve. Finally, we discuss the relationship between signalling from peripheral tissues and age-associated control of central BDNF expression.

Diffusion tensor imaging of superficial prefrontal white matter in healthy aging

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

A fronto-insular-parietal network for the sense of body ownership

Neuropsychological disturbances in the sense of limb ownership provide unique opportunities to study the neurocognitive basis of body ownership. Previous small sample studies that showed discrete cortical lesions cannot explain why multisensory, affective, and cognitive manipulations alter disownership symptoms. We tested the novel hypothesis that disturbances in the sense of limb ownership would be associated not only with discrete cortical lesions but also with disconnections of white-matter tracts supporting specific functional networks. We drew on an advanced lesion-analysis and Bayesian statistics approach in 49 right-hemisphere patients (23 with and 26 without limb disownership). Our results reveal that disturbances in the sense of ownership are associated with lesions in the supramarginal gyrus and disconnections of a fronto-insular-parietal network, involving the frontal-insular and frontal inferior longitudinal tracts, confirming previous disconnection hypotheses. Together with previous behavioral and neuroanatomical results, these findings lead us to propose that the sense of body ownership involves the convergence of bottom-up, multisensory integration, and top-down monitoring of sensory salience based on contextual demands.

Is gray-white matter ratio in out-of-hospital cardiac arrest patients' really early predictor of neurological outcome?

OBJECTIVE

This study aimed to evaluate the association between neurological outcome and gray-white ratio (GWR) in brain computed tomography (CT) in patients with return of spontaneous circulation (ROSC) who were brought to the emergency department (ED) due to out-of-hospital cardiac arrest (OHCA).

METHODS

This study has a retrospective design. Patients with ROSC who were brought to the ED due to OHCA and who underwent brain CT in the first 24 h were included in the study. Demographic data, brain CT results (intensities of gray matter and white matter in Hounsfield units and calculated GWR), and hospital outcome were recorded. The cerebral Performance Categories (CPC) score was used as the outcome of the study.

RESULTS

A total of 160 patients were included in the study. 55% of the patients were male and the median age was 75.5. The median brain CT time of the patients was 120 min. 16.3% of the patients were in the good neurological outcome group. When attenuation values and GWRs of the patients were compared according to CPC of patients (good-poor), no statistically significant difference was detected in any parameter except MC2 attenuation (P > 0.05 for all values). The patients were separated into groups geriatric and nongeriatric and GWRs were compared. GWRs were lower in the geriatric groups (P < 0.05 for all values).

CONCLUSION

Although it is emphasized in the literature that detection of low GWR in brain CT can help the clinical decision process in patients surviving comatose arrest, we think that it is not valid for especially in geriatric patients and in patients who underwent early brain CT after ROSC.

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.

Alterations of gray and white matter volumes and cortical thickness in treated HIV-positive patients

Brain structural changes in HIV identified by voxel-based morphometry (VBM) alone could arise from a variety of causes that are difficult to distinguish without further information, such as cortical thickness (CT), gyrification index (GI) or sulcal depth (SD). Hence, our goal was to assess these additional metrics in HIV using high-resolution 3D T₁-weighted images and investigate if surface-based morphometric (SBM) analysis would reveal significant changes in the gray matter (GM) and white matter (WM) volumes combined with alterations in cortical thickness (CT), gyrification index (GI), sulcal depth (SD). T1-w magnetization-prepared-rapid-acquisition gradient-echo (MP-RAGE) scans were acquired in 27 HIV-infected individuals on antiretroviral therapy (ART) and 15 HIV-uninfected healthy controls using a 3T MRI scanner equipped with a 16-channel head "receive" and a quadrature body "transmit" coil. Voxel-based and surface-based morphometric analyses were performed using the MATLAB based SPM Computational Anatomy Toolbox (CAT12.7(1700)). HIV-infected patients showed significantly altered GM and WM volumes, CT, GI, and SD, in multiple brain regions. This study showed the association of altered GM and WM volumes in local brain regions with the changes in region-wise CT, GI and SD measures of HIV-infected patients, especially in the parahippocampal and middle frontal regions as compared to uninfected healthy controls. The outcome of this study suggests that the findings of VBM may not necessarily indicate the volumetric shrinkage or increase alone, but might also be due to altered CT, GI, or SD. Correlation analysis showed a significantly accelerated gray matter loss with age in HIV-infected individuals compared to uninfected healthy controls.

Longitudinal White and Gray Matter Response to Precision Medicine-Guided Intervention for Alzheimer's Disease

BACKGROUND

Alzheimer's disease (AD) is a debilitating condition that is widely known to adversely affect gray matter (GM) and white matter (WM) tracts within the brain. Recently, precision medicine has shown promise in alleviating the clinical and gross morphological trajectories of patients with AD. However, regional morphological changes have not yet been adequately characterized.

OBJECTIVE

Investigate regional morphological responses to a precision medicine-guided intervention with regards to white and gray matter in AD and mild cognitive impairment (MCI).

METHODS

Clinical and neuroimaging data were compiled over a 9-month period from 25 individuals who were diagnosed with AD or MCI receiving individualized treatment plans. Structural T1-weighted MRI scans underwent segmentation and volumetric quantifications via Neuroreader. Longitudinal changes were calculated via annualized percent change of WM or GM ratios.

RESULTS

Montreal Cognitive Assessment scores (p < 0.001) and various domains of the Computerized Neurocognitive Screening Vital Signs significantly improved from baseline to 9-month follow-up. There was regional variability in WM and GM atrophy or hypertrophy, but none of these observed changes were statistically significant after correction for multiple comparisons.

White matter hyperintensity load is associated with premature brain aging

BACKGROUND

Brain age is an MRI-derived estimate of brain tissue loss that has a similar pattern to aging-related atrophy. White matter hyperintensities (WMHs) are neuroimaging markers of small vessel disease and may represent subtle signs of brain compromise. We tested the hypothesis that WMHs are independently associated with premature brain age in an original aging cohort.

METHODS

Brain age was calculated using machine-learning on whole-brain tissue estimates from T1-weighted images using the BrainAgeR analysis pipeline in 166 healthy adult participants. WMHs were manually delineated on FLAIR images. WMH load was defined as the cumulative volume of WMHs. A positive difference between estimated brain age and chronological age (BrainGAP) was used as a measure of premature brain aging. Then, partial Pearson correlations between BrainGAP and volume of WMHs were calculated (accounting for chronological age).

RESULTS

Brain and chronological age were strongly correlated (r(163)=0.932, p<0.001). There was significant negative correlation between BrainGAP scores and chronological age (r(163)=-0.244, p<0.001) indicating that younger participants had higher BrainGAP (premature brain aging). Chronological age also showed a positive correlation with WMH load (r(163)=0.506, p<0.001) indicating older participants had increased WMH load. Controlling for chronological age, there was a statistically significant relationship between premature brain aging and WMHs load (r(163)=0.216, p=0.003). Each additional year in brain age beyond chronological age corresponded to an additional 1.1mm3 in WMH load.

CONCLUSIONS

WMHs are an independent factor associated with premature brain aging. This finding underscores the impact of white matter disease on global brain integrity and progressive age-like brain atrophy.

White matter integrity as a mediator between socioeconomic status and executive function

Introduction

Lower socioeconomic status (SES) is associated with poorer executive function, but the neural mechanisms of this association remain unclear. As healthy brain communication is essential to our cognitive abilities, white matter integrity may be key to understanding socioeconomic disparities.

Methods

Participants were 201 African American and White adults (ages 33-72) from the Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) SCAN study. Diffusion tensor imaging was used to estimate regional fractional anisotropy as a measure of white matter integrity. Adjusting for age, analyses examined if integrity of the anterior limb of the internal capsule (ALIC), external capsule (EC), superior longitudinal fasciculus (SLF), and cingulum mediated SES-executive function relations.

Results

Lower SES was related to poorer cognitive performance and white matter integrity. Lower Trails B performance was related to poorer integrity of the ALIC, EC, and SLF, and lower Stroop performance was associated with poorer integrity of the ALIC and EC. ALIC mediated the SES-Trails B relation, and EC mediated the SES-Trails B and SES-Stroop relations. Sensitivity analyses revealed that (1) adjustment for race rendered the EC mediations non-significant, (2) when using poverty status and continuous education as predictors, results were largely the same, (3) at least some of the study's findings may generalize to processing speed, (4) mediations are not age-dependent in our sample, and (5) more research is needed to understand the role of cardiovascular risk factors in these models.

Discussion

Findings demonstrate that poorer white matter integrity helps explain SES disparities in executive function and highlight the need for further clarification of the biopsychosocial mechanisms of the SES-cognition association.

A multicohort geometric deep learning study of age dependent cortical and subcortical morphologic interactions for fluid intelligence prediction

The relationship of human brain structure to cognitive function is complex, and how this relationship differs between childhood and adulthood is poorly understood. One strong hypothesis suggests the cognitive function of Fluid Intelligence (Gf) is dependent on prefrontal cortex and parietal cortex. In this work, we developed a novel graph convolutional neural networks (gCNNs) for the analysis of localized anatomic shape and prediction of Gf. Morphologic information of the cortical ribbons and subcortical structures was extracted from T1-weighted MRIs within two independent cohorts, the Adolescent Brain Cognitive Development Study (ABCD; age: 9.93 ± 0.62 years) of children and the Human Connectome Project (HCP; age: 28.81 ± 3.70 years). Prediction combining cortical and subcortical surfaces together yielded the highest accuracy of Gf for both ABCD (R = 0.314) and HCP datasets (R = 0.454), outperforming the state-of-the-art prediction of Gf from any other brain measures in the literature. Across both datasets, the morphology of the amygdala, hippocampus, and nucleus accumbens, along with temporal, parietal and cingulate cortex consistently drove the prediction of Gf, suggesting a significant reframing of the relationship between brain morphology and Gf to include systems involved with reward/aversion processing, judgment and decision-making, motivation, and emotion.

Transcriptomic architecture of nuclei in the marmoset CNS

To understand the cellular composition and region-specific specialization of white matter - a disease-relevant, glia-rich tissue highly expanded in primates relative to rodents - we profiled transcriptomes of ~500,000 nuclei from 19 tissue types of the central nervous system of healthy common marmoset and mapped 87 subclusters spatially onto a 3D MRI atlas. We performed cross-species comparison, explored regulatory pathways, modeled regional intercellular communication, and surveyed cellular determinants of neurological disorders. Here, we analyze this resource and find strong spatial segregation of microglia, oligodendrocyte progenitor cells, and astrocytes. White matter glia are diverse, enriched with genes involved in stimulus-response and biomolecule modification, and predicted to interact with other resident cells more extensively than their gray matter counterparts. Conversely, gray matter glia preserve the expression of neural tube patterning genes into adulthood and share six transcription factors that restrict transcriptome complexity. A companion Callithrix jacchus Primate Cell Atlas (CjPCA) is available through https://cjpca.ninds.nih.gov .

Integrating the Neurodevelopmental and Dopamine Hypotheses of Schizophrenia and the Role of Cortical Excitation-Inhibition Balance

The neurodevelopmental and dopamine hypotheses are leading theories of the pathoetiology of schizophrenia, but they were developed in isolation. However, since they were originally proposed, there have been considerable advances in our understanding of the normal neurodevelopmental refinement of synapses and cortical excitation-inhibition (E/I) balance, as well as preclinical findings on the interrelationship between cortical and subcortical systems and new in vivo imaging and induced pluripotent stem cell evidence for lower synaptic density markers in patients with schizophrenia. Genetic advances show that schizophrenia is associated with variants linked to genes affecting GABA (gamma-aminobutyric acid) and glutamatergic signaling as well as neurodevelopmental processes. Moreover, in vivo studies on the effects of stress, particularly during later development, show that it leads to synaptic elimination. We review these lines of evidence as well as in vivo evidence for altered cortical E/I balance and dopaminergic dysfunction in schizophrenia. We discuss mechanisms through which frontal cortex circuitry may regulate striatal dopamine and consider how frontal E/I imbalance may cause dopaminergic dysregulation to result in psychotic symptoms. This integrated neurodevelopmental and dopamine hypothesis suggests that overpruning of synapses, potentially including glutamatergic inputs onto frontal cortical interneurons, disrupts the E/I balance and thus underlies cognitive and negative symptoms. It could also lead to disinhibition of excitatory projections from the frontal cortex and possibly other regions that regulate mesostriatal dopamine neurons, resulting in dopamine dysregulation and psychotic symptoms. Together, this explains a number of aspects of the epidemiology and clinical presentation of schizophrenia and identifies new targets for treatment and prevention.

Age-associated sex and asymmetry differentiation in hemispheric and lobar cortical ribbon complexity across adulthood: A UK Biobank imaging study

Cortical morphology changes with ageing and age-related neurodegenerative diseases. Previous studies suggest that the age effect is more pronounced in the frontal lobe. However, our knowledge of structural complexity changes in male and female brains is still limited. We measured cortical ribbon complexity through fractal dimension (FD) analysis at the hemisphere and lobe level in 7010 individuals from the UK Biobank imaging cohort to study age-related sex differences (3332 males, age ranged 45-79 years). FD decreases significantly with age and sexual dimorphism exists. With correction for brain size, females showed higher complexity in the left hemisphere and left and right parietal lobes whereas males showed higher complexity in the right temporal and left and right occipital lobes. A nonlinear age effect was observed in the left and right frontal, and right temporal lobes. Differential patterns of age effects were observed in both sexes with relatively more age-affected regions in males. Significantly higher rightward asymmetries at hemisphere, frontal, parietal, and occipital lobe level and higher leftward asymmetry in temporal lobe were observed. There was no age-by-sex-by asymmetry interaction in any region. When controlling for brain size, the leftward hemispheric, and temporal lobe asymmetry decreased with age. Males had significantly lower asymmetry between hemispheres and higher asymmetry in the parietal and occipital lobes than females. This work provides distinct patterns of age-related sex and asymmetry differences that can aid in the future development of sex-specific models of the normal brain to ascribe cognitive functional significance of these patterns in ageing.

Investigating the contribution of cytoarchitecture to diffusion MRI measures in gray matter using histology

Postmortem studies are currently considered a gold standard for investigating brain structure at the cellular level. To investigate cellular changes in the context of human development, aging, or disease treatment, non-invasive in-vivo imaging methods such as diffusion MRI (dMRI) are needed. However, dMRI measures are only indirect measures and require validation in gray matter (GM) in the context of their sensitivity to the underlying cytoarchitecture, which has been lacking. Therefore, in this study we conducted direct comparisons between in-vivo dMRI measures and histology acquired from the same four rhesus monkeys. Average and heterogeneity of fractional anisotropy and trace from diffusion tensor imaging and mean squared displacement (MSD) and return-to-origin-probability from biexponential model were calculated in nine cytoarchitectonically different GM regions using dMRI data. DMRI measures were compared with corresponding histology measures of regional average and heterogeneity in cell area density. Results show that both average and heterogeneity in trace and MSD measures are sensitive to the underlying cytoarchitecture (cell area density) and capture different aspects of cell composition and organization. Trace and MSD thus would prove valuable as non-invasive imaging biomarkers in future studies investigating GM cytoarchitectural changes related to development and aging as well as abnormal cellular pathologies in clinical studies.

Age-related increases in reaction time result from slower preparation, not delayed initiation

Recent work indicates that healthy younger adults can prepare accurate responses faster than their voluntary reaction times would suggest, leaving a seemingly unnecessary delay of 80-100 ms before responding. Here, we examined how the preparation of movements, initiation of movements, and the delay between them are affected by aging. Participants made planar reaching movements in two conditions. The "free reaction time" condition assessed the voluntary reaction times with which participants responded to the appearance of a stimulus. The "forced reaction time" condition assessed the minimum time actually needed to prepare accurate movements by controlling the time allowed for movement preparation. The time taken to both initiate movements in the free reaction time and to prepare movements in the forced response condition increased with age. Notably, the time required to prepare accurate movements was significantly shorter than participants' self-selected initiation times; however, the delay between movement preparation and initiation remained consistent across the lifespan (∼90 ms). These results indicate that the slower reaction times of healthy older adults are not due to an increased hesitancy to respond, but can instead be attributed to changes in their ability to process stimuli and prepare movements accordingly, consistent with age-related changes in brain structure and function.NEW & NOTEWORTHY Previous research argues that older adults have slower response times because they hesitate to react, favoring accuracy over speed. The present results challenge this proposal. We found the delay between the minimum time required to prepare movements and the self-selected time at which they initiated remained consistent at ∼90 ms from ages 21 to 80. We therefore suggest older adults' slower response times can be attributed to changes in their ability to process stimuli and prepare movements.

Quantitative susceptibility atlas construction in Montreal Neurological Institute space: towards histological-consistent iron-rich deep brain nucleus subregion identification

Iron-rich deep brain nuclei (DBN) of the human brain are involved in various motoric, emotional and cognitive brain functions. The abnormal iron alterations in the DBN are closely associated with multiple neurological and psychiatric diseases. Quantitative susceptibility mapping (QSM) provides the spatial distribution of the magnetic susceptibility of human brain tissues. Compared to traditional structural imaging, QSM provides superiority for imaging the iron-rich DBN owing to the susceptibility difference existing between brain tissues. In this study, we constructed a Montreal Neurological Institute (MNI) space unbiased QSM human brain atlas via group-wise registration from 100 healthy subjects aged 19-29 years. The atlas construction process was guided by hybrid images that were fused from multi-modal magnetic resonance images (MRI). We named it as Multi-modal-fused magnetic Susceptibility (MuSus-100) atlas. The high-quality susceptibility atlas provides extraordinary image contrast between iron-rich DBN with their surroundings. Parcellation maps of DBN and their subregions that are highly related to neurological and psychiatric pathology were then manually labeled based on the atlas set with the assistance of an image border-enhancement process. Especially, the bilateral thalamus was delineated into 64 detailed subregions referring to the Schaltenbrand-Wahren stereotactic atlas. To our best knowledge, the histological-consistent thalamic nucleus parcellation map is well defined for the first time in the MNI space. Compared with existing atlases that emphasizing DBN parcellation, the newly proposed atlas outperforms on the task of atlas-guided individual brain image DBN segmentation both in accuracy and robustness. Moreover, we applied the proposed DBN parcellation map to conduct detailed identification of the pathology-related iron content alterations in subcortical nuclei for Parkinson's Disease (PD) patients. We envision that the MuSus-100 atlas can play a crucial role in improving the accuracy of DBN segmentation for the research of neurological and psychiatric disease progress and also be helpful for target planning in deep brain stimulation surgery.

Individual differences in slow wave sleep architecture relate to variation in white matter microstructure across adulthood

Sleep plays a key role in supporting brain function and resilience to brain decline. It is well known that sleep changes substantially with aging and that aging is associated with deterioration of brain structure. In this study, we sought to characterize the relationship between slow wave slope (SWslope)—a key marker of sleep architecture and an indirect proxy of sleep quality—and microstructure of white matter pathways in healthy adults with no sleep complaints. Participants were 12 young (24–27 years) and 12 older (50–79 years) adults. Sleep was assessed with nocturnal electroencephalography (EEG) and the Pittsburgh Sleep Quality Index (PSQI). White matter integrity was assessed using tract-based spatial statistics (TBSS) on tensor-based metrics such as Fractional Anisotropy (FA) and Mean Diffusivity (MD). Global PSQI score did not differ between younger (n = 11) and older (n = 11) adults (U = 50, p = 0.505), but EEG revealed that younger adults had a steeper SWslope at both frontal electrode sites (F3: U = 2, p < 0.001, F4: U = 4, p < 0.001, n = 12 younger, 10 older). There were widespread correlations between various diffusion tensor-based metrics of white matter integrity and sleep SWslope, over and above effects of age (n = 11 younger, 9 older). This was particularly evident for the corpus callosum, corona radiata, superior longitudinal fasciculus, internal and external capsule. This indicates that reduced sleep slow waves may be associated with widespread white matter deterioration. Future studies should investigate whether interventions targeted at improving sleep architecture also impact on decline in white matter microstructure in older adults.

Motion, Relation, and Passion in Brain Physiological and Cognitive Aging

The aim of the current paper was to present important factors for keeping the basic structures of a person’s brain function, i.e., the grey and white matter, intact. Several lines of evidence have shown that motion, relation, and passion are central factors for preserving the neural system in the grey and white matter during ageing. An active lifestyle has shown to contribute to the development of the central nervous system and to contrast brain ageing. Interpersonal relationships, and interactions, have shown to contribute to complex biological factors that benefit the cognitive resilience to decline. Furthermore, the current scientific literature suggests that passion, strong interest, could be the driving factor motivating individuals to learn new things, thus influencing the development and maintenance of the neural functional network over time. The present theoretical perspective paper aims to convey several key messages: (1) brain development is critically affected by lifestyle; (2) physical training allows one to develop and maintain brain structures during ageing, and may be one of the keys for good quality of life as an older person; (3) diverse stimuli are a key factor in maintaining brain structures; (4) motion, relation, and passion are key elements for contrasting the loss of the grey and white matter of the brain.

A new multimodality fusion classification approach to explore the uniqueness of schizophrenia and autism spectrum disorder

Schizophrenia (SZ) and autism spectrum disorder (ASD) sharing overlapping symptoms have a long history of diagnostic confusion. It is unclear what their differences at a brain level are. Here, we propose a multimodality fusion classification approach to investigate their divergence in brain function and structure. Using brain functional network connectivity (FNC) calculated from resting-state fMRI data and gray matter volume (GMV) estimated from sMRI data, we classify the two disorders using the main data (335 SZ and 380 ASD patients) via an unbiased 10-fold cross-validation pipeline, and also validate the classification generalization ability on an independent cohort (120 SZ and 349 ASD patients). The classification accuracy reached up to 83.08% for the testing data and 72.10% for the independent data, significantly better than the results from using the single-modality features. The discriminative FNCs that were automatically selected primarily involved the sub-cortical, default mode, and visual domains. Interestingly, all discriminative FNCs relating to the default mode network showed an intermediate strength in healthy controls (HCs) between SZ and ASD patients. Their GMV differences were mainly driven by the frontal gyrus, temporal gyrus, and insula. Regarding these regions, the mean GMV of HC fell intermediate between that of SZ and ASD, and ASD showed the highest GMV. The middle frontal gyrus was associated with both functional and structural differences. In summary, our work reveals the unique neuroimaging characteristics of SZ and ASD that can achieve high and generalizable classification accuracy, supporting their potential as disorder-specific neural substrates of the two entwined disorders.

The Role of Neurotrophin Signaling in Age-Related Cognitive Decline and Cognitive Diseases

Neurotrophins are a family of secreted proteins expressed in the peripheral nervous system and the central nervous system that support neuronal survival, synaptic plasticity, and neurogenesis. Brain-derived neurotrophic factor (BDNF) and its high affinity receptor TrkB are highly expressed in the cortical and hippocampal areas and play an essential role in learning and memory. The decline of cognitive function with aging is a major risk factor for cognitive diseases such as Alzheimer’s disease. Therefore, an alteration of BDNF/TrkB signaling with aging and/or pathological conditions has been indicated as a potential mechanism of cognitive decline. In this review, we summarize the cellular function of neurotrophin signaling and review the current evidence indicating a pathological role of neurotrophin signaling, especially of BDNF/TrkB signaling, in the cognitive decline in aging and age-related cognitive diseases. We also review the therapeutic approach for cognitive decline by the upregulation of the endogenous BDNF/TrkB-system.

Effect of senescence on the tyrosine hydroxylase and S100B immunoreactivity in the nigrostriatal pathway of the rat

Senescence is a natural and progressive physiological event that leads to a series of morphophysiological alterations in the organism. The brain is the most vulnerable organ to both structural and functional changes during this process. Dopamine is a key neurotransmitter for the proper functioning of the brain, directly involved in circuitries related with emotions, learning, motivation and reward. One of the main dopamine- producing nuclei is the substantia nigra pars compacta (SNpc), which establish connections with the striatum forming the so-called nigrostriatal pathway. S100B is a calcium binding protein mainly expressed by astrocytes, involved in both intracellular and extracellular processes, and whose expression is increased following injury in the nervous tissue, being a useful marker in altered status of central nervous system. The present study aimed to analyze the impact of senescence on the cells immunoreactive for tyrosine hydroxylase (TH) and S100B along the nigrostriatal pathway of the rat. Our results show an decreased expression of S100B⁺ cells in SNpc. In addition, there was a significant decrease in TH immunoreactivity in both projection fibers and TH⁺ cell bodies. In the striatum, a decrease in TH immunoreactivity was also observed, as well as an enlargement of the white matter bundles. Our findings point out that senescence is related to the anatomical and neurochemical changes observed throughout the nigrostriatal pathway.

Effects of aging on functional connectivity in a neurodegenerative risk cohort: resting state versus task measurement using near-infrared spectroscopy

Changes in functional brain organization are considered to be particularly sensitive to age-related effects and may precede structural cognitive decline. Recent research focuses on aging processes determined by resting state (RS) functional connectivity (FC), but little is known about differences in FC during RS and cognitive task conditions in elderly participants. The purpose of this study is to compare FC within and between the cognitive control (CCN) and dorsal attention network (DAN) at RS and during a cognitive task using functional near-infrared spectroscopy (fNIRS). In a matched, neurodegenerative high-risk cohort comprising early (n = 98; 50–65 y) and late (n = 98; 65–85 y) elder subjects, FC was measured at RS and during performance of the Trail Making Test (TMT) via fNIRS. Both, under RS and task conditions our results revealed a main effect for age, characterized by reduced FC for late elder subjects within the left inferior frontal gyrus. During performance of the TMT, negative correlations of age and FC were confirmed in various regions of the CCN and DAN. For the whole sample, FC of within-region connections was elevated, while FC between regions was decreased at RS. The results confirm a reorganization of functional brain connectivity with increasing age and cognitive demands.