Structural brain changes in aging: courses, causes and cognitive consequences

Brain-Derived neurotrophic factor and inflammatory biomarkers are unaffected by acute and chronic intermittent hypoxic-hyperoxic exposure in geriatric patients: a randomized controlled trial

BACKGROUND

Animal and human studies have shown that exposure to hypoxia can increase brain-derived neurotrophic factor (BDNF) protein transcription and reduce systematic inflammatory cytokine response. Therefore, the aim of this study was to investigate the acute and chronic effects of intermittent hypoxic-hyperoxic exposure (IHHE) prior to aerobic exercise on BDNF, interleukin-6 (IL-6), and C-reactive protein (CRP) blood levels in geriatric patients.

PATIENTS AND METHODS

Twenty-five geriatric patients (83.1 ± 5.0 yrs, 71.1 ± 10.0 kg, 1.8 ± 0.9 m) participated in a placebo-controlled, single-blinded trial and were randomly assigned to either an intervention (IG) or control group (CG) performing an aerobic cycling training (17 sessions, 20 min·session-1, 3 sessions·week-1). Prior to aerobic cycling exercise, the IG was additionally exposed to IHHE for 30 min, whereas the CG received continuous normoxic air. Blood samples were taken immediately before (pre-exercise) and 10 min (post-exercise) after the first session as well as 48 h (post-training) after the last session to determine serum (BDNFS) and plasma BDNF (BDNFP), IL-6, and CRP levels. Intervention effects were analyzed using a 2 x 2 analysis of covariance with repeated measures. Results were interpreted based on effect sizes with a medium effect considered as meaningful (ηp2 ≥ 0.06, d ≥ 0.5).

RESULTS

CRP was moderately higher (d = 0.51) in the CG compared to the IG at baseline. IHHE had no acute effect on BDNFS (ηp2 = 0.01), BDNFP (ηp2 < 0.01), BDNF serum/plasma-ratio (ηp2 < 0.01), IL-6 (ηp2 < 0.01), or CRP (ηp2 = 0.04). After the 6-week intervention, an interaction was found for BDNF serum/plasma-ratio (ηp2 = 0.06) but not for BDNFS (ηp2 = 0.04), BDNFP (ηp2 < 0.01), IL-6 (ηp2 < 0.01), or CRP (ηp2 < 0.01). BDNF serum/plasma-ratio increased from pre-exercise to post-training (d = 0.67) in the CG compared to the IG (d = 0.51). A main effect of time was found for BDNFP (ηp2 = 0.09) but not for BDNFS (ηp2 = 0.02). Within-group post-hoc analyses revealed a training-related reduction in BDNFP in the IG and CG by 46.1% (d = 0.73) and 24.7% (d = 0.57), respectively.

CONCLUSION

The addition of 30 min IHHE prior to 20 min aerobic cycling seems not to be effective to increase BDNFS and BDNFP or to reduce IL-6 and CRP levels in geriatric patients after a 6-week intervention.The study was retrospectively registered at drks.de (DRKS-ID: DRKS00025130).

Association between telomere length and cognitive function among cognitively unimpaired individuals at risk of Alzheimer's disease

INTRODUCTION

Leukocyte telomere length (LTL) is an objective biomarker of biological aging, and it is proposed to play a crucial role in Alzheimer's disease (AD) risk. We aimed at evaluating the cross-sectional association between LTL and cognitive performance in middle-aged cognitively unimpaired individuals at increased risk of AD.

METHODS

A total of 1520 participants from the ALFA cohort were included. Relative telomere length was measured in leukocytes through qPCR. LTL was residualized against age and sex, and associations with cognitive performance were assessed in short and long groups based on residualized LTL (rLTL). Interactions with sex and genetic risk of AD were tested.

RESULTS

Non-linear associations were found between LTL and episodic memory (EM). Better EM was associated with longer rLTL among women in the short rLTL group.

DISCUSSION

Results suggest a potential role of telomeres in the cognitive aging process with sex-specific patterns.

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.

Towards a neurodevelopmental cognitive perspective of temporal processing

The ability to organize and memorize the unfolding of events over time is a fundamental feature of cognition, which develops concurrently with the maturation of the brain. Nonetheless, how temporal processing evolves across the lifetime as well as the links with the underlying neural substrates remains unclear. Here, we intend to retrace the main developmental stages of brain structure, function, and cognition linked to the emergence of timing abilities. This neurodevelopmental perspective aims to untangle the puzzling trajectory of temporal processing aspects across the lifetime, paving the way to novel neuropsychological assessments and cognitive rehabilitation strategies.

Association of accelerated biological aging with brain volumes: A cross-sectional study

BACKGROUND

Multiple epidemiological studies have observed the connection between aging and brain volumes. The concept of accelerated biological aging (BA) is more powerful for observing the degree of aging of an individual than chronologic age (CA). The objective of this study is to explore the relationship between BA and brain volumes.

METHODS

BA was measured from clinical traits using two blood-chemistry algorithms, the Klemera-Doubal method (KDM) and the PhenoAge. The two age acceleration biomarkers were calculated by the residuals from regressing CA, termed "KDM-acceleration" and "PhenoAge-acceleration". Brain volumes were from brain magnetic resonance imaging (MRI) data. After adjustment for confounding factors, general linear regression models were used to examine associations between KDM-acceleration and PhenoAge-acceleration and brain volumes, respectively. Additionally, we stratified participants by sex, age, and the four quartiles of the Townsend Deprivation Index (TDI) for extra subgroup analysis.

RESULTS

14,725 participants with available information were enrolled. After full adjustment, we observed negative associations between KDM-acceleration and brain volumes, such as gray matter (β = -0.029), white matter (β = -0.021), gray and white matter (β = -0.026), and hippocampus (β = -0.011 for left and β = -0.014 for right). There were also negative associations between PhenoAge-acceleration and brain volumes, such as white matter (β = -0.008), gray and white matter (β = -0.010), thalamus (β = -0.012 for left and β = -0.012 for right). In the subgroup analysis stratified by sex, age, and the four quartiles of TDI, the association between KDM-acceleration and PhenoAge-acceleration and brain volumes still existed. In subgroup analyses, the variation in associations suggests that socioeconomic and biological factors may differentially influence brain aging.

CONCLUSIONS

Our research indicated that more advanced BA was associated with less brain tissue.

Cortical Generators and Connections Underlying Phoneme Perception: A Mismatch Negativity and P300 Investigation

The cortical generators of the pure tone MMN and P300 have been thoroughly studied. Their nature and interaction with respect to phoneme perception, however, is poorly understood. Accordingly, the cortical sources and functional connections that underlie the MMN and P300 in relation to passive and active speech sound perception were identified. An inattentive and attentive phonemic oddball paradigm, eliciting a MMN and P300 respectively, were administered in 60 healthy adults during simultaneous high-density EEG recording. For both the MMN and P300, eLORETA source reconstruction was performed. The maximal cross-correlation was calculated between ROI-pairs to investigate inter-regional functional connectivity specific to passive and active deviant processing. MMN activation clusters were identified in the temporal (insula, superior temporal gyrus and temporal pole), frontal (rostral middle frontal and pars opercularis) and parietal (postcentral and supramarginal gyrus) cortex. Passive discrimination of deviant phonemes was aided by a network connecting right temporoparietal cortices to left frontal areas. For the P300, clusters with significantly higher activity were found in the frontal (caudal middle frontal and precentral), parietal (precuneus) and cingulate (posterior and isthmus) cortex. Significant intra- and interhemispheric connections between parietal, cingulate and occipital regions constituted the network governing active phonemic target detection. A predominantly bilateral network was found to underly both the MMN and P300. While passive phoneme discrimination is aided by a fronto-temporo-parietal network, active categorization calls on a network entailing fronto-parieto-cingulate cortices. Neural processing of phonemic contrasts, as reflected by the MMN and P300, does not appear to show pronounced lateralization to the language-dominant hemisphere.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

DISCUSSION

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

CLINICAL TRIAL REGISTRATION

NCT03197454.

Subjective-Objective Sleep Discrepancy in a Predominately White and Educated Older Adult Population: Examining the Associations With Cognition and Insomnia

OBJECTIVES

This study examined associations between various cognitive domains and sleep discrepancy (self-reported vs objectively measured sleep), and evaluated interactive associations with insomnia status (non-insomnia vs insomnia).

METHODS

Older adults (N = 65, Mage = 68.72, SD = 5.06, 43 insomnia/22 non-insomnia) aged 60+ reported subjective sleep (7 days of sleep diaries), objective sleep assessment (one-night polysomnography, PSG, via Sleep Profiler during the 7-day period), and completed cognitive tasks (National Institutes of Health Toolbox-Cognition Battery) measuring attention and processing speed, working memory, inhibitory control, cognitive flexibility, and episodic memory. The sleep diary variable corresponding to the same one night of PSG was used to calculate the sleep discrepancy (diary minus PSG parameter) variables for total sleep time (TST), sleep onset latency, wake after sleep onset, and sleep efficiency. Regression analyses determined independent and interactive (with insomnia status) associations between cognition and sleep discrepancy, controlling for age, sex, apnea-hypopnea index, and sleep medication usage.

RESULTS

Working memory interacted with insomnia status in associations with sleep discrepancy related to TST and sleep efficiency. In those with insomnia, worse working memory was associated with shorter self-reported TST (p = .008) and lower sleep efficiency (p = .04) than PSG measured.

DISCUSSION

In older adults with insomnia, worse working memory may be a contributing factor to sleep discrepancy. Future investigations of underlying neurophysiological factors and consideration of other objective sleep measures (actigraphy) are warranted. Prospective findings may help determine whether sleep discrepancy is a potential marker of future cognitive decline.

Sex as a Determinant of Age-Related Changes in the Brain

The notion of notable anatomical, biochemical, and behavioral distinctions within male and female brains has been a contentious topic of interest within the scientific community over several decades. Advancements in neuroimaging and molecular biological techniques have increasingly elucidated common mechanisms characterizing brain aging while also revealing disparities between sexes in these processes. Variations in cognitive functions; susceptibility to and progression of neurodegenerative conditions, notably Alzheimer's and Parkinson's diseases; and notable disparities in life expectancy between sexes, underscore the significance of evaluating aging within the framework of gender differences. This comprehensive review surveys contemporary literature on the restructuring of brain structures and fundamental processes unfolding in the aging brain at cellular and molecular levels, with a focus on gender distinctions. Additionally, the review delves into age-related cognitive alterations, exploring factors influencing the acceleration or deceleration of aging, with particular attention to estrogen's hormonal support of the central nervous system.

Population clustering of structural brain aging and its association with brain development

Structural brain aging has demonstrated strong inter-individual heterogeneity and mirroring patterns with brain development. However, due to the lack of large-scale longitudinal neuroimaging studies, most of the existing research focused on the cross-sectional changes of brain aging. In this investigation, we present a data-driven approach that incorporate both cross-sectional changes and longitudinal trajectories of structural brain aging and identified two brain aging patterns among 37,013 healthy participants from UK Biobank. Participants with accelerated brain aging also demonstrated accelerated biological aging, cognitive decline and increased genetic susceptibilities to major neuropsychiatric disorders. Further, by integrating longitudinal neuroimaging studies from a multi-center adolescent cohort, we validated the "last in, first out" mirroring hypothesis and identified brain regions with manifested mirroring patterns between brain aging and brain development. Genomic analyses revealed risk loci and genes contributing to accelerated brain aging and delayed brain development, providing molecular basis for elucidating the biological mechanisms underlying brain aging and related disorders.

The Advanced BRain Imaging on ageing and Memory (ABRIM) data collection: Study design, data processing, and rationale

To understand the neurocognitive mechanisms that underlie heterogeneity in cognitive ageing, recent scientific efforts have led to a growing public availability of imaging cohort data. The Advanced BRain Imaging on ageing and Memory (ABRIM) project aims to add to these existing datasets by taking an adult lifespan approach to provide a cross-sectional, normative database with a particular focus on connectivity, myelinization and iron content of the brain in concurrence with cognitive functioning, mechanisms of reserve, and sleep-wake rhythms. ABRIM freely shares MRI and behavioural data from 295 participants between 18-80 years, stratified by age decade and sex (median age 52, IQR 36-66, 53.20% females). The ABRIM MRI collection consists of both the raw and pre-processed structural and functional MRI data to facilitate data usage among both expert and non-expert users. The ABRIM behavioural collection includes measures of cognitive functioning (i.e., global cognition, processing speed, executive functions, and memory), proxy measures of cognitive reserve (e.g., educational attainment, verbal intelligence, and occupational complexity), and various self-reported questionnaires (e.g., on depressive symptoms, pain, and the use of memory strategies in daily life and during a memory task). In a sub-sample (n = 120), we recorded sleep-wake rhythms using an actigraphy device (Actiwatch 2, Philips Respironics) for a period of 7 consecutive days. Here, we provide an in-depth description of our study protocol, pre-processing pipelines, and data availability. ABRIM provides a cross-sectional database on healthy participants throughout the adult lifespan, including numerous parameters relevant to improve our understanding of cognitive ageing. Therefore, ABRIM enables researchers to model the advanced imaging parameters and cognitive topologies as a function of age, identify the normal range of values of such parameters, and to further investigate the diverse mechanisms of reserve and resilience.

Predicting brain age using Tri-UNet and various MRI scale features

In the process of human aging, significant age-related changes occur in brain tissue. To assist individuals in assessing the degree of brain aging, screening for disease risks, and further diagnosing age-related diseases, it is crucial to develop an accurate method for predicting brain age. This paper proposes a multi-scale feature fusion method called Tri-UNet based on the U-Net network structure, as well as a brain region information fusion method based on multi-channel input networks. These methods address the issue of insufficient image feature learning in brain neuroimaging data. They can effectively utilize features at different scales of MRI and fully leverage feature information from different regions of the brain. In the end, experiments were conducted on the Cam-CAN dataset, resulting in a minimum Mean Absolute Error (MAE) of 7.46. The results demonstrate that this method provides a new approach to feature learning at different scales in brain age prediction tasks, contributing to the advancement of the field and holding significance for practical applications in the context of elderly education.

Childhood engagement in cognitively stimulating activities moderates relationships between brain structure and cognitive function in adulthood

Greater engagement in cognitively stimulating activities (CSA) during adulthood has been shown to protect against neurocognitive decline, but no studies have investigated whether CSA during childhood protects against effects of brain changes on cognition later in life. The current study tested the moderating role of childhood CSA in the relationships between brain structure and cognitive performance during adulthood. At baseline (N=250) and 5-year follow-up (N=204) healthy adults aged 20-80 underwent MRI to assess four structural brain measures and completed neuropsychological tests to measure three cognitive domains. Participants were categorized into low and high childhood CSA based on self-report questionnaires. Results of multivariable linear regressions analyzing interactions between CSA, brain structure, and cognition showed that higher childhood CSA was associated with a weaker relationship between cortical thickness and memory at baseline, and attenuated the effects of change in cortical thickness and brain volume on decline in processing speed over time. These findings suggest higher CSA during childhood may mitigate the effects of brain structure changes on cognitive function later in life.

Aging Brain from a Lifespan Perspective

Research during the last two decades has shown that the brain undergoes continuous changes throughout life, with substantial heterogeneity in age trajectories between regions. Especially, temporal and prefrontal cortices show large changes, and these correlate modestly with changes in the corresponding cognitive abilities such as episodic memory and executive function. Changes seen in normal aging overlap with changes seen in neurodegenerative conditions such as Alzheimer's disease; differences between what reflects normal aging vs. a disease-related change are often blurry. This calls for a dimensional view on cognitive decline in aging, where clear-cut distinctions between normality and pathology cannot be always drawn. Although much progress has been made in describing typical patterns of age-related changes in the brain, identifying risk and protective factors, and mapping cognitive correlates, there are still limits to our knowledge that should be addressed by future research. We need more longitudinal studies following the same participants over longer time intervals with cognitive testing and brain imaging, and an increased focus on the representativeness vs. selection bias in neuroimaging research of aging.

Alcohol Use Disorder and Dementia: A Review

PURPOSE

By 2040, 21.6% of Americans will be over age 65, and the population of those older than age 85 is estimated to reach 14.4 million. Although not causative, older age is a risk factor for dementia: every 5 years beyond age 65, the risk doubles; approximately one-third of those older than age 85 are diagnosed with dementia. As current alcohol consumption among older adults is significantly higher compared to previous generations, a pressing question is whether drinking alcohol increases the risk for Alzheimer's disease or other forms of dementia.

SEARCH METHODS

Databases explored included PubMed, Web of Science, and ScienceDirect. To accomplish this narrative review on the effects of alcohol consumption on dementia risk, the literature covered included clinical diagnoses, epidemiology, neuropsychology, postmortem pathology, neuroimaging and other biomarkers, and translational studies. Searches conducted between January 12 and August 1, 2023, included the following terms and combinations: "aging," "alcoholism," "alcohol use disorder (AUD)," "brain," "CNS," "dementia," "Wernicke," "Korsakoff," "Alzheimer," "vascular," "frontotemporal," "Lewy body," "clinical," "diagnosis," "epidemiology," "pathology," "autopsy," "postmortem," "histology," "cognitive," "motor," "neuropsychological," "magnetic resonance," "imaging," "PET," "ligand," "degeneration," "atrophy," "translational," "rodent," "rat," "mouse," "model," "amyloid," "neurofibrillary tangles," "α-synuclein," or "presenilin." When relevant, "species" (i.e., "humans" or "other animals") was selected as an additional filter. Review articles were avoided when possible.

SEARCH RESULTS

The two terms "alcoholism" and "aging" retrieved about 1,350 papers; adding phrases-for example, "postmortem" or "magnetic resonance"-limited the number to fewer than 100 papers. Using the traditional term, "alcoholism" with "dementia" resulted in 876 citations, but using the currently accepted term "alcohol use disorder (AUD)" with "dementia" produced only 87 papers. Similarly, whereas the terms "Alzheimer's" and "alcoholism" yielded 318 results, "Alzheimer's" and "alcohol use disorder (AUD)" returned only 40 citations. As pertinent postmortem pathology papers were published in the 1950s and recent animal models of Alzheimer's disease were created in the early 2000s, articles referenced span the years 1957 to 2024. In total, more than 5,000 articles were considered; about 400 are herein referenced.

DISCUSSION AND CONCLUSIONS

Chronic alcohol misuse accelerates brain aging and contributes to cognitive impairments, including those in the mnemonic domain. The consensus among studies from multiple disciplines, however, is that alcohol misuse can increase the risk for dementia, but not necessarily Alzheimer's disease. Key issues to consider include the reversibility of brain damage following abstinence from chronic alcohol misuse compared to the degenerative and progressive course of Alzheimer's disease, and the characteristic presence of protein inclusions in the brains of people with Alzheimer's disease, which are absent in the brains of those with AUD.

Trends in mortality rates and correlations between intracranial injuries and external causes: A Japanese population study

The age-standardized incidence of head trauma in 2016 was 369 per 100,000 people worldwide. The Western Pacific region, including Japan, had the highest incidence. This study aimed to extract ICD-10 code data for intracranial injury (S06) and external causes of morbidity and mortality (V01-Y89), analyze their characteristics and interrelationships, and contribute to these diseases' prevention, treatment, and prognosis. The number of deaths according to injury type and external cause type of intracranial injury published by the Japanese government was statistically analyzed using JoinPoint, and univariate distribution and multivariate correlation were conducted using JMP Software. From 1999-2021, there was a downward trend in the number of deaths because of intracranial injuries: mortality from intracranial injuries was higher among those aged ≥65 years. Conversely, mortality from intracranial injuries was lower among those aged ≤14 years. Among deaths from intracranial injury, mortality from diffuse brain injury and traumatic subdural hemorrhage was more common. Among deaths from external causes of intracranial injury, mortality from falls, transport accidents, and other unforeseen accidents was more common. Mortality because of intracranial injuries increased significantly during the 2011 Great East Japan Earthquake. For some age groups and sexes, there were significant inverse correlations of mortality with traumatic subdural hemorrhage and traumatic subarachnoid hemorrhage for transport accidents, intentional self-harm and assault, and diffuse brain injury and focal brain injury for falls. We believe that the data presented in this study will be useful for preventing and treating intracranial injuries and for developing administrative measures to reduce intracranial injuries.

The Association between Dietary Protein Intake and Sources and the Rate of Longitudinal Changes in Brain Structure

Few studies have examined dietary protein intake and sources, in combination with longitudinal changes in brain structure markers. Our study aimed to examine the association between dietary protein intake and different sources of dietary protein, with the longitudinal rate of change in brain structural markers. A total of 2723 and 2679 participants from the UK Biobank were separately included in the analysis. The relative and absolute amounts of dietary protein intake were calculated using a 24 h dietary recall questionnaire. The longitudinal change rates of brain structural biomarkers were computed using two waves of brain imaging data. The average interval between the assessments was three years. We utilized multiple linear regression to examine the association between dietary protein and different sources and the longitudinal changes in brain structural biomarkers. Restrictive cubic splines were used to explore nonlinear relationships, and stratified and sensitivity analyses were conducted. Increasing the proportion of animal protein in dietary protein intake was associated with a slower reduction in the total hippocampus volume (THV, β: 0.02524, p < 0.05), left hippocampus volume (LHV, β: 0.02435, p < 0.01) and right hippocampus volume (RHV, β: 0.02544, p < 0.05). A higher intake of animal protein relative to plant protein was linked to a lower atrophy rate in the THV (β: 0.01249, p < 0.05) and LHV (β: 0.01173, p < 0.05) and RHV (β: 0.01193, p < 0.05). Individuals with a higher intake of seafood exhibited a higher longitudinal rate of change in the HV compared to those that did not consume seafood (THV, β: 0.004514; p < 0.05; RHV, β: 0.005527, p < 0.05). In the subgroup and sensitivity analyses, there were no significant alterations. A moderate increase in an individual's intake and the proportion of animal protein in their diet, especially from seafood, is associated with a lower atrophy rate in the hippocampus volume.

Microbiota-gut-brain axis: the mediator of exercise and brain health

The brain controls the nerve system, allowing complex emotional and cognitive activities. The microbiota-gut-brain axis is a bidirectional neural, hormonal, and immune signaling pathway that could link the gastrointestinal tract to the brain. Over the past few decades, gut microbiota has been demonstrated to be an essential component of the gastrointestinal tract that plays a crucial role in regulating most functions of various body organs. The effects of the microbiota on the brain occur through the production of neurotransmitters, hormones, and metabolites, regulation of host-produced metabolites, or through the synthesis of metabolites by the microbiota themselves. This affects the host's behavior, mood, attention state, and the brain's food reward system. Meanwhile, there is an intimate association between the gut microbiota and exercise. Exercise can change gut microbiota numerically and qualitatively, which may be partially responsible for the widespread benefits of regular physical activity on human health. Functional magnetic resonance imaging (fMRI) is a non-invasive method to show areas of brain activity enabling the delineation of specific brain regions involved in neurocognitive disorders. Through combining exercise tasks and fMRI techniques, researchers can observe the effects of exercise on higher brain functions. However, exercise's effects on brain health via gut microbiota have been little studied. This article reviews and highlights the connections between these three interactions, which will help us to further understand the positive effects of exercise on brain health and provide new strategies and approaches for the prevention and treatment of brain diseases.

Compensatory brain activity pattern is not present in older adults during the n-back task performance-Findings based on EEG frequency analysis

Introduction

Cognitive ability is one of the most important enablers for successful aging. At the same time, cognitive decline is a well-documented phenomenon accompanying the aging process. Nevertheless, it is acknowledged that aging can also be related to positive processes that allow one to compensate for the decline. These processes include the compensatory brain activity of older adults primarily investigated using fMRI and PET. To strengthen the cognitive interpretation of compensatory brain activity in older adults, we searched for its indicators in brain activity measured by EEG.

Methods

The study sample comprised 110 volunteers, including 50 older adults (60-75 years old) and 60 young adults (20-35 years old) who performed 1-back, 2-back, and 3-back tasks while recording the EEG signal. The study analyzed (1) the level of cognitive performance, including sensitivity index, the percentage of correct answers to the target, and the percentage of false alarm errors; (2) theta and alpha power for electrodes located in the frontal-midline (Fz, AF3, AF4, F3, F4, FC1, and FC2) and the centro-parietal (CP1, CP2, P3, P4, and Pz) areas.

Results

Cognitive performance was worse in older adults than in young adults, which manifested in a significantly lower sensitivity index and a significantly higher false alarm error rate at all levels of the n-back task difficulty. Simultaneously, performance worsened with increasing task difficulty regardless of age. Significantly lower theta power in the older participants was observed at all difficulty levels, even at the lowest one, where compensatory activity was expected. At the same time, at this difficulty level, cognitive performance was worse in older adults than in young adults, which could reduce the chances of observing compensatory brain activity. The significant decrease in theta power observed in both age groups with rising task difficulty can reflect a declining capacity for efficient cognitive functioning under increasing demands rather than adapting to this increase. Moreover, in young adults, alpha power decreased to some extent with increasing cognitive demand, reflecting adaptation to them, while in older adults, no analogous pattern was observed.

Discussion

In conclusion, based on the results of the current study, the presence of compensatory activity in older adults cannot be inferred.

Effects of chronic daily headache with subclinical depression on brain volume: A systematic review and meta-analysis

BACKGROUND AND OBJECTIVE

The relationship between chronic daily headache (CDH), depression symptoms, and brain volume remains unclear.

METHODS

To investigate the effects of CDH on brain volume and the impact of depressive symptoms (DSs) as well as the effects of demography and medication overuse, PubMed, Embase, and Web of Science databases were systematically searched using appropriate keyword strings to retrieve observational studies from inception to May 2023.

RESULTS

Two distinct comparisons were made in CDH patients: (1) those with DSs versus their pain-free counterparts and (2) those without DSs versus pain-free controls. The first comprised nine studies enrolling 225 CDH patients with DSs and 234 controls. Beck depression inventory, Hamilton depression scale, and Hospital anxiety/depression scale were used to assess DSs, revealing significantly more DSs in CDH patients with DSs compared to their controls (all p < 0.05). Besides, the second analysed four studies involving 117 CDH patients without DSs and 155 comparators. Compared to CDH patients without DSs, those with DSs had a smaller brain volume than controls (p = 0.03). Furthermore, CDH patients with DSs who did not overuse medications showed a smaller right cerebral cortical volume than overusers (p = 0.003). A significant inverse correlation between female prevalence and brain volume (p = 0.02) was revealed using regression analysis.

CONCLUSIONS

Pain-induced persistent depressive symptoms not only incur structural alterations but also encompass affective-motivational changes, involving medication use and gender-specific health concerns.

SIGNIFICANCE

This study highlighted the importance of an integrated CDH treatment, emphasizing psychological interventions for the affective-motivational component alongside pain management.

Neural deformation fields for template-based reconstruction of cortical surfaces from MRI

The reconstruction of cortical surfaces is a prerequisite for quantitative analyses of the cerebral cortex in magnetic resonance imaging (MRI). Existing segmentation-based methods separate the surface registration from the surface extraction, which is computationally inefficient and prone to distortions. We introduce Vox2Cortex-Flow (V2C-Flow), a deep mesh-deformation technique that learns a deformation field from a brain template to the cortical surfaces of an MRI scan. To this end, we present a geometric neural network that models the deformation-describing ordinary differential equation in a continuous manner. The network architecture comprises convolutional and graph-convolutional layers, which allows it to work with images and meshes at the same time. V2C-Flow is not only very fast, requiring less than two seconds to infer all four cortical surfaces, but also establishes vertex-wise correspondences to the template during reconstruction. In addition, V2C-Flow is the first approach for cortex reconstruction that models white matter and pial surfaces jointly, therefore avoiding intersections between them. Our comprehensive experiments on internal and external test data demonstrate that V2C-Flow results in cortical surfaces that are state-of-the-art in terms of accuracy. Moreover, we show that the established correspondences are more consistent than in FreeSurfer and that they can directly be utilized for cortex parcellation and group analyses of cortical thickness.

Subtypes of brain change in aging and their associations with cognition and Alzheimer's disease biomarkers

Structural brain changes underly cognitive changes in older age and contribute to inter-individual variability in cognition. Here, we assessed how changes in cortical thickness, surface area, and subcortical volume, are related to cognitive change in cognitively unimpaired older adults using structural magnetic resonance imaging (MRI) data-driven clustering. Specifically, we tested (1) which brain structural changes over time predict cognitive change in older age (2) whether these are associated with core cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarkers phosphorylated tau (p-tau) and amyloid-β (Aβ42), and (3) the degree of overlap between clusters derived from different structural features. In total 1899 cognitively healthy older adults (50 - 93 years) were followed up to 16 years with neuropsychological and structural MRI assessments, a subsample of which (n = 612) had CSF p-tau and Aβ42 measurements. We applied Monte-Carlo Reference-based Consensus clustering to identify subgroups of older adults based on structural brain change patterns over time. Four clusters for each brain feature were identified, representing the degree of longitudinal brain decline. Each brain feature provided a unique contribution to brain aging as clusters were largely independent across modalities. Cognitive change and baseline cognition were best predicted by cortical area change, whereas higher levels of p-tau and Aβ42 were associated with changes in subcortical volume. These results provide insights into the link between changes in brain morphology and cognition, which may translate to a better understanding of different aging trajectories.

Size or Strength? how components of muscle relate to behavioral and neuroelectric measures of executive function independent of aerobic fitness

While previous research has linked cognitive function with resistance exercise, the nuanced links between muscle strength, mass, and neuroelectric function are less understood. Therefore, this study investigated the association of muscle strength and mass with inhibitory control (IC), working memory (WM), and related neuroelectric activity. A total of 123 18-50-year-old adults completed maximal aerobic capacity and strength tests, a body composition scan, and IC and WM tasks while the N2 and P3 components of event-related potentials were recorded. Bivariate correlations revealed aerobic fitness, strength, and mass were associated with behavioral and neuroelectric outcomes. After accounting for age, sex, and aerobic fitness, strength was associated with intra-individual response time variability, accuracy, and P3 latency during WM. Muscle mass was associated with N2 latency during IC. While relationships with behavioral outcomes did not persist after controlling for the opposite muscle outcome, greater strength and mass were related to shorter P3 latency during WM and shorter N2 latency during IC, respectively. These results provide initial evidence that muscle outcomes are associated with executive function and neuroelectric processing speed, suggesting distinct contributions of strength and mass to cognition. This work highlights the significance of maintaining muscle strength and mass alongside aerobic fitness for optimal cognitive health.

Quantification of mediation effects of white matter functional characteristics on cognitive decline in aging

Cognitive decline with aging involves multifactorial processes, including changes in brain structure and function. This study focuses on the role of white matter functional characteristics, as reflected in blood oxygenation level-dependent signals, in age-related cognitive deterioration. Building on previous research confirming the reproducibility and age-dependence of blood oxygenation level-dependent signals acquired via functional magnetic resonance imaging, we here employ mediation analysis to test if aging affects cognition through white matter blood oxygenation level-dependent signal changes, impacting various cognitive domains and specific white matter regions. We used independent component analysis of resting-state blood oxygenation level-dependent signals to segment white matter into coherent hubs, offering a data-driven view of white matter's functional architecture. Through correlation analysis, we constructed a graph network and derived metrics to quantitatively assess regional functional properties based on resting-state blood oxygenation level-dependent fluctuations. Our analysis identified significant mediators in the age-cognition relationship, indicating that aging differentially influences cognitive functions by altering the functional characteristics of distinct white matter regions. These findings enhance our understanding of the neurobiological basis of cognitive aging, highlighting the critical role of white matter in maintaining cognitive integrity and proposing new approaches to assess interventions targeting cognitive decline in older populations.

Explainable machine learning in outcome prediction of high-grade aneurysmal subarachnoid hemorrhage

OBJECTIVE

Accurate prognostic prediction in patients with high-grade aneruysmal subarachnoid hemorrhage (aSAH) is essential for personalized treatment. In this study, we developed an interpretable prognostic machine learning model for high-grade aSAH patients using SHapley Additive exPlanations (SHAP).

METHODS

A prospective registry cohort of high-grade aSAH patients was collected in one single-center hospital. The endpoint in our study is a 12-month follow-up outcome. The dataset was divided into training and validation sets in a 7:3 ratio. Machine learning algorithms, including Logistic regression model (LR), support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost), were employed to develop a prognostic prediction model for high-grade aSAH. The optimal model was selected for SHAP analysis.

RESULTS

Among the 421 patients, 204 (48.5%) exhibited poor prognosis. The RF model demonstrated superior performance compared to LR (AUC = 0.850, 95% CI: 0.783-0.918), SVM (AUC = 0.862, 95% CI: 0.799-0.926), and XGBoost (AUC = 0.850, 95% CI: 0.783-0.917) with an AUC of 0.867 (95% CI: 0.806-0 .929). Primary prognostic features identified through SHAP analysis included higher World Federation of Neurosurgical Societies (WFNS) grade, higher modified Fisher score (mFS) and advanced age, were found to be associated with 12-month unfavorable outcome, while the treatment of coiling embolization for aSAH drove the prediction towards favorable prognosis. Additionally, the SHAP force plot visualized individual prognosis predictions.

CONCLUSIONS

This study demonstrated the potential of machine learning techniques in prognostic prediction for high-grade aSAH patients. The features identified through SHAP analysis enhance model interpretability and provide guidance for clinical decision-making.

Structure-Function Interactions in the Hippocampus and Prefrontal Cortex Are Associated with Episodic Memory in Healthy Aging

Aging comes with declines in episodic memory. Memory decline is accompanied by structural and functional alterations within key brain regions, including the hippocampus and lateral prefrontal cortex, as well as their affiliated default and frontoparietal control networks. Most studies have examined how structural or functional differences relate to memory independently. Here we implemented a multimodal, multivariate approach to investigate how interactions between individual differences in structural integrity and functional connectivity relate to episodic memory performance in healthy aging. In a sample of younger (N = 111; mean age, 22.11 years) and older (N = 78; mean age, 67.29 years) adults, we analyzed structural MRI and multiecho resting-state fMRI data. Participants completed measures of list recall (free recall of words from a list), associative memory (cued recall of paired words), and source memory (cued recall of the trial type, or the sensory modality in which a word was presented). The findings revealed that greater structural integrity of the posterior hippocampus and middle frontal gyrus were linked with a pattern of increased within-network connectivity, which together were related to better associative and source memory in older adulthood. Critically, older adults displayed better memory performance in the context of decreased hippocampal volumes when structural differences were accompanied by functional reorganization. This functional reorganization was characterized by a pruning of connections between the hippocampus and the limbic and frontoparietal control networks. Our work provides insight into the neural mechanisms that underlie age-related compensation, revealing that the functional architecture associated with better memory performance in healthy aging is tied to the structural integrity of the hippocampus and prefrontal cortex.

Causal relationship between multiparameter brain MRI phenotypes and age: evidence from Mendelian randomization

To explore the causal relationship between age and brain health (cortical atrophy, white matter integrity, white matter hyperintensities and cerebral microbleeds in various brain regions) related multiparameter imaging features using two-sample Mendelian randomization. Age was determined as chronological age of the subject. Cortical volume, white matter micro-integrity, white matter hyperintensity volume and cerebral microbleeds of each brain region were included as phenotypes for brain health. Age and imaging of brain health related genetic data were analysed to determine the causal relationship using inverse-variance weighted model, validated by heterogeneity and horizontal pleiotropy variables. Age is causally related to increased volumes of white matter hyperintensities (β = 0.151). For white matter micro-integrity, fibres of the inferior cerebellar peduncle (axial diffusivity β = -0.128, orientation dispersion index β = 0.173), cerebral peduncle (axial diffusivity β = -0.136), superior fronto-occipital fasciculus (isotropic volume fraction β = 0.163) and fibres within the limbic system were causally deteriorated. We also detected decreased cortical thickness of multiple frontal and temporal regions (P < 0.05). Microbleeds were not related with aging (P > 0.05). Aging is a threat of brain health, leading to cortical atrophy mainly in the frontal lobes, as well as the white matter degeneration especially abnormal hyperintensity and deteriorated white matter integrity around the hippocampus.

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.

Regional cortical thickness recovery with extended abstinence after treatment in those with alcohol use disorder

Several cross-sectional investigations reported widespread cortical thinning in those with alcohol use disorder (AUD). The few longitudinal studies investigating cortical thickness changes during abstinence are limited to the first month of sobriety. Consequently, cortical thickness changes during extended abstinence in those with AUD is unclear. In this study, AUD participants were studied at approximately 1 week (n = 68), 1 month (n = 88), and 7.3 months (n = 40) of abstinence. Forty-five never-smoking controls (CON) completed a baseline study, and 15 were reassessed after approximately 9.6 months. Participants completed magnetic resonance imaging studies at 1.5T, and cortical thickness for 34 bilateral regions of interest (ROI) was quantitated with FreeSurfer. AUD participants demonstrated significant linear thickness increases in 25/34 ROI over 7.3 months of abstinence. The rate of change from 1 week to 1 month was greater than 1 month to 7.3 months in 19/34 ROIs. Proatherogenic conditions were associated with lower thickness recovery in anterior frontal, inferior parietal, and lateral/mesial temporal regions. After 7.3 months of abstinence, AUD participants were statistically equivalent to CON on cortical thickness in 24/34 ROIs; the cortical thickness differences between AUD and CON in the banks superior temporal gyrus, post central, posterior cingulate, superior parietal, supramarginal, and superior frontal cortices were driven by thinner cortices in AUD with proatherogenic conditions relative to CON. In actively smoking AUD, increasing pack-years was associated with decreasing thickness recovery primarily in the anterior frontal ROIs. Widespread bilateral cortical thickness recovery over 7.3 months of abstinence was the central finding for this AUD cohort. The longitudinal and cross-sectional findings for AUD with proatherogenic suggests alterations in perfusion or vascular integrity may relate to structural recovery in those with AUD. These results support the adaptive and beneficial effects of sustained sobriety on brain structural recovery in people with AUD.

Prediction of cognitive performance differences in older age from multimodal neuroimaging data

Differences in brain structure and functional and structural network architecture have been found to partly explain cognitive performance differences in older ages. Thus, they may serve as potential markers for these differences. Initial unimodal studies, however, have reported mixed prediction results of selective cognitive variables based on these brain features using machine learning (ML). Thus, the aim of the current study was to investigate the general validity of cognitive performance prediction from imaging data in healthy older adults. In particular, the focus was with examining whether (1) multimodal information, i.e., region-wise grey matter volume (GMV), resting-state functional connectivity (RSFC), and structural connectivity (SC) estimates, may improve predictability of cognitive targets, (2) predictability differences arise for global cognition and distinct cognitive profiles, and (3) results generalize across different ML approaches in 594 healthy older adults (age range: 55-85 years) from the 1000BRAINS study. Prediction potential was examined for each modality and all multimodal combinations, with and without confound (i.e., age, education, and sex) regression across different analytic options, i.e., variations in algorithms, feature sets, and multimodal approaches (i.e., concatenation vs. stacking). Results showed that prediction performance differed considerably between deconfounding strategies. In the absence of demographic confounder control, successful prediction of cognitive performance could be observed across analytic choices. Combination of different modalities tended to marginally improve predictability of cognitive performance compared to single modalities. Importantly, all previously described effects vanished in the strict confounder control condition. Despite a small trend for a multimodal benefit, developing a biomarker for cognitive aging remains challenging.

Effects of a brief HIIT intervention on cognitive performance in older women

Cardiorespiratory fitness (CRF) mitigates age-related decline in cognition and brain volume. Little is known, however, about the effects of high-intensity interval training (HIIT) on cognitive aging and the relationship between HIIT, cognition, hippocampal subfield volumes, and cerebral oxygen extraction fraction (OEF). Older sedentary women participated in an 8-week HIIT intervention. We conducted cognitive assessments, fitness assessments (VO2max), MRI scans: asymmetric spin echo oxygen extraction fraction (ASE-OEF), high-resolution multiple image co-registration and averaging (HR-MICRA) imaging, and transcranial Doppler ultrasonography before and after the intervention. VO2max increased from baseline (M = 19.36, SD = 2.84) to follow-up (M = 23.25, SD = 3.61), Z =  - 2.93, p < .001, r = 0.63. Composite cognitive (Z =  - 2.05, p = 0.041), language (Z =  - 2.19, p = 0.028), and visuospatial memory (Z =  - 2.22, p = 0.026), z-scores increased significantly. Hippocampal subfield volumes CA1 and CA3 dentate gyrus and subiculum decreased non-significantly (all p > 0.05); whereas a significant decrease in CA2 (Z =  - 2.045, p = 0.041, r = 0.436) from baseline (M = 29.51; SD = 24.50) to follow-up (M = 24.50; SD = 13.38) was observed. Right hemisphere gray matter was correlated with language z-scores (p = 0.025; r = 0.679). The subiculum was correlated with attention (p = 0.047; r = 0.618) and verbal memory (p = 0.020; r = 0.700). The OEF and CBF were unchanged at follow-up (all p > .05). Although we observed cognitive improvements following 8 weeks of our HIIT intervention, they were not explained by hippocampal, OEF, or CBF changes.

Efficacy of MRI data harmonization in the age of machine learning: a multicenter study across 36 datasets

Pooling publicly-available MRI data from multiple sites allows to assemble extensive groups of subjects, increase statistical power, and promote data reuse with machine learning techniques. The harmonization of multicenter data is necessary to reduce the confounding effect associated with non-biological sources of variability in the data. However, when applied to the entire dataset before machine learning, the harmonization leads to data leakage, because information outside the training set may affect model building, and potentially falsely overestimate performance. We propose a 1) measurement of the efficacy of data harmonization; 2) harmonizer transformer, i.e., an implementation of the ComBat harmonization allowing its encapsulation among the preprocessing steps of a machine learning pipeline, avoiding data leakage by design. We tested these tools using brain T1-weighted MRI data from 1740 healthy subjects acquired at 36 sites. After harmonization, the site effect was removed or reduced, and we showed the data leakage effect in predicting individual age from MRI data, highlighting that introducing the harmonizer transformer into a machine learning pipeline allows for avoiding data leakage by design.

The time-evolving epileptic brain network: concepts, definitions, accomplishments, perspectives

Epilepsy is now considered a network disease that affects the brain across multiple levels of spatial and temporal scales. The paradigm shift from an epileptic focus-a discrete cortical area from which seizures originate-to a widespread epileptic network-spanning lobes and hemispheres-considerably advanced our understanding of epilepsy and continues to influence both research and clinical treatment of this multi-faceted high-impact neurological disorder. The epileptic network, however, is not static but evolves in time which requires novel approaches for an in-depth characterization. In this review, we discuss conceptual basics of network theory and critically examine state-of-the-art recording techniques and analysis tools used to assess and characterize a time-evolving human epileptic brain network. We give an account on current shortcomings and highlight potential developments towards an improved clinical management of epilepsy.

The interaction effects of age, APOE and common environmental risk factors on human brain structure

Mounting evidence suggests considerable diversity in brain aging trajectories, primarily arising from the complex interplay between age, genetic, and environmental risk factors, leading to distinct patterns of micro- and macro-cerebral aging. The underlying mechanisms of such effects still remain unclear. We conducted a comprehensive association analysis between cerebral structural measures and prevalent risk factors, using data from 36,969 UK Biobank subjects aged 44-81. Participants were assessed for brain volume, white matter diffusivity, Apolipoprotein E (APOE) genotypes, polygenic risk scores, lifestyles, and socioeconomic status. We examined genetic and environmental effects and their interactions with age and sex, and identified 726 signals, with education, alcohol, and smoking affecting most brain regions. Our analysis revealed negative age-APOE-ε4 and positive age-APOE-ε2 interaction effects, respectively, especially in females on the volume of amygdala, positive age-sex-APOE-ε4 interaction on the cerebellar volume, positive age-excessive-alcohol interaction effect on the mean diffusivity of the splenium of the corpus callosum, positive age-healthy-diet interaction effect on the paracentral volume, and negative APOE-ε4-moderate-alcohol interaction effects on the axial diffusivity of the superior fronto-occipital fasciculus. These findings highlight the need of considering age, sex, genetic, and environmental joint effects in elucidating normal or abnormal brain aging.

Twelve weeks of physical exercise breaks with coordinative exercises at the workplace increase the sulcal depth and decrease gray matter volume in brain structures related to visuomotor processes

Physical exercise can evoke changes in the brain structure. Consequently, these can lead to positive impacts on brain health. However, physical exercise studies including coordinative exercises are rare. Therefore, in this study, we investigated how 12 weeks of physical exercise breaks (PEBs) with coordinative exercises, focusing mainly on juggling tasks, affected the brain structure. The participants were randomly allocated to an intervention group (IG, n = 16; 42.8 ± 10.2 years) and a control group (CG, n = 9; 44.2 ± 12.3 years). The IG performed the PEBs with coordinative exercises twice per week for 15-20 min per session. Before the intervention, after 6 weeks of the intervention, and after 12 weeks of the intervention, participants underwent a high-resolution 3T T1-weighted magnetic resonance imagining scan. Juggling performance was assessed by measuring the time taken to perform a three-ball cascade. A surface-based analysis revealed an increase in vertex-wise cortical depth in a cluster including the inferior parietal lobe after 6 and 12 weeks of training in the IG. After 12 weeks, the IG showed a decrease in gray matter (GM) volume in a cluster primarily involving the right insula and the right operculum. The changes in the GM volume were related to improvements in juggling performance. No significant changes were found for the CG. To conclude, the present study showed that regular engagement in PEBs with coordinative exercises led to changes in brain structures strongly implicated in visuomotor processes involving hand and arm movements.

The cortical thickness of tricenarian cocaine users assembles features of an octogenarian brain

It has been suggested that substance use disorders could lead to accelerated biological aging, but only a few neuroimaging studies have investigated this hypothesis so far. In this cross-sectional study, structural neuroimaging was performed to measure cortical thickness (CT) in tricenarian adults with cocaine use disorder (CUD, n1  = 30) and their age-paired controls (YC, n1  = 30), and compare it with octogenarian elder controls (EC, n1  = 20). We found that CT in the right fusiform gyrus was similar between CUD and EC, thinner than the expected values of YC. We also found that regarding CT of the right inferior temporal gyrus, right inferior parietal cortex, and left superior parietal cortex, the CUD group exhibited parameters that fell in between EC and YC groups. Finally, CT of the right pars triangularis bordering with orbitofrontal gyrus, right superior temporal gyrus, and right precentral gyrus were reduced in CUD when contrasted with YC, but those areas were unrelated to CT of EC. Despite the 50-year age gap between our age groups, CT of tricenarian cocaine users assembles features of an octogenarian brain, reinforcing the accelerated aging hypothesis in CUD.

A randomized controlled pilot study of a cognitive-behavioral video game intervention for the promotion of active aging

Background

Due to the accessibility barriers of in-person programs for active aging, the development of programs that use innovative technologies is needed. Video games can be an engaging tool for disseminating active aging interventions.

Objective

The objective of this pilot study was to analyze the feasibility of a cognitive-behavioral intervention to promote active aging administered through a video game.

Methods

Fifty-five participants (63.6% women, mean age = 53.0 years) were randomly assigned to a cognitive-behavioral intervention to promote active aging administered through an interactive multimedia online video game with a complementary app (CBI-V; n = 29) or to a control group that received nonspecific online information (CG; n = 26).

Results

Only 3.6% of the participants dropped out of the study (6.9% in CBI-V and 0.0% in CG; without significant differences between groups). The mean number of modules completed was 7.6 (SD = 0.9) out of 8 in the CBI-V and 7.9 (SD = 0.5) in the control group (CG), without significant between-group differences. In the CBI-V, the mean total time dedicated to the game was 516.8 min (SD = 94.3), including 143.2 min (SD = 31.6) of cognitive training tasks, and the mean of completed tasks was 206.2 (SD = 33.7) out of 259. Participants were highly engaged (M = 39.9, SD = 8.6) and satisfied (M = 25.8, SD = 4.5) with the intervention. After the intervention, the CBI-V group significantly improved on SF-36 dimensions of General Health (p = .0386), Vitality (p = .0283), Social Functioning (p = .0130), and Physical Summary Index (p = .0370) compared to the CG, with medium effect sizes (d = 0.56-0.75).

Conclusions

The results demonstrate the feasibility of the video game intervention to promote active aging and encourage conducting a large-scale randomized controlled trial.

Changes in memory and attention during and after occupational rehabilitation: A longitudinal study

BACKGROUND

There is need for more knowledge about the relationship between work and cognitive functioning in sick-listed individuals.

OBJECTIVE

This study investigated whether the degree of work participation is relevant for recovery of cognitive functioning in sick-listed individuals.

METHODS

177 occupational rehabilitation participants and 70 controls participated in a non-randomised, longitudinal study. Participants completed computerised cognitive tests targeting sustained attention and working memory at start and end of rehabilitation and 3 and 12 months after rehabilitation. The change score performance in attention and memory between start and end, start and 3 months and 12 months was compared in individuals on sick leave 100-75%, 74-40% and 39-0% (three sick leave groups) of the time in the year after rehabilitation, and a control group not being on sick leave. Fixed effect analysis of covariance adjusting for education and work ability was used.

RESULTS

The sick leave group 100-75% had significantly lower score on work ability compared to the other groups at baseline. The main findings indicated that the sick leave group 39-0% improved significantly more in sustained attention compared to the sick leave group 100-75% between start and end of rehabilitation and from start of rehabilitation to 3 and 12 months after.

CONCLUSION

The degree of work participation seems relevant to recovery of the cognitive function sustained attention in sick-listed individuals. These findings encourage work rehabilitation clinicians, work consultants and employers to develop RTW plans which take into account that graded employment influence cognitive functioning.

Investigating the impact of healthy aging on memory for temporal duration and order

Temporal information, including information about temporal order and duration, is a fundamental component of event sequence memory. While previous research has demonstrated that aging can have a detrimental effect on memory for temporal order, there has been limited insight into the effect of aging on memory for durations, particularly within the context of sequences. In the current study, neurologically healthy young and older participants were administered two temporal match-mismatch tasks: one in which they were instructed on each trial to compare the temporal order or duration information of stimulus sequences presented first in a study phase and then, after a short delay, in a test phase (event sequence task); and a second in which participants were required to compare single durations or sequences of durations across study and test phases of each trial (pinwheel task). Consistent with the literature, the older participants were significantly poorer compared to their younger counterparts at making temporal order match-mismatch judgments in the event sequence task. In addition to this, data from both tasks suggested that the older adults were also less accurate at match-mismatch judgments based on duration information, with tentative evidence from the pinwheel task to suggest that this age-related effect was most prominent when the duration information was presented within a sequence. We suggest that age-related changes to medial temporal and frontal lobe function may contribute to changes in memory for temporal information in older adults, given the importance of these regions to event sequence memory.

A systematic review of (semi-)automatic quality control of T1-weighted MRI scans

PURPOSE

Artifacts in magnetic resonance imaging (MRI) scans degrade image quality and thus negatively affect the outcome measures of clinical and research scanning. Considering the time-consuming and subjective nature of visual quality control (QC), multiple (semi-)automatic QC algorithms have been developed. This systematic review presents an overview of the available (semi-)automatic QC algorithms and software packages designed for raw, structural T1-weighted (T1w) MRI datasets. The objective of this review was to identify the differences among these algorithms in terms of their features of interest, performance, and benchmarks.

METHODS

We queried PubMed, EMBASE (Ovid), and Web of Science databases on the fifth of January 2023, and cross-checked reference lists of retrieved papers. Bias assessment was performed using PROBAST (Prediction model Risk Of Bias ASsessment Tool).

RESULTS

A total of 18 distinct algorithms were identified, demonstrating significant variations in methods, features, datasets, and benchmarks. The algorithms were categorized into rule-based, classical machine learning-based, and deep learning-based approaches. Numerous unique features were defined, which can be roughly divided into features capturing entropy, contrast, and normative measures.

CONCLUSION

Due to dataset-specific optimization, it is challenging to draw broad conclusions about comparative performance. Additionally, large variations exist in the used datasets and benchmarks, further hindering direct algorithm comparison. The findings emphasize the need for standardization and comparative studies for advancing QC in MR imaging. Efforts should focus on identifying a dataset-independent measure as well as algorithm-independent methods for assessing the relative performance of different approaches.

Age-related vulnerability of the human brain connectome

Multifactorial models integrating brain variables at multiple scales are warranted to investigate aging and its relationship with neurodegeneration. Our aim was to evaluate how aging affects functional connectivity of pivotal regions of the human brain connectome (i.e., hubs), which represent potential vulnerability 'stations' to aging, and whether such effects influence the functional and structural changes of the whole brain. We combined the information of the functional connectome vulnerability, studied through an innovative graph-analysis approach (stepwise functional connectivity), with brain cortical thinning in aging. Using data from 128 cognitively normal participants (aged 20-85 years), we firstly investigated the topological functional network organization in the optimal healthy condition (i.e., young adults) and observed that fronto-temporo-parietal hubs showed a highly direct functional connectivity with themselves and among each other, while occipital hubs showed a direct functional connectivity within occipital regions and sensorimotor areas. Subsequently, we modeled cortical thickness changes over lifespan, revealing that fronto-temporo-parietal hubs were among the brain regions that changed the most, whereas occipital hubs showed a quite spared cortical thickness across ages. Finally, we found that cortical regions highly functionally linked to the fronto-temporo-parietal hubs in healthy adults were characterized by the greatest cortical thinning along the lifespan, demonstrating that the topology and geometry of hub functional connectome govern the region-specific structural alterations of the brain regions.

Aging and urinary control: Alterations in the brain-bladder axis

Age-associated alterations in bladder control affect millions of older adults, with a heavy burden added to families both economically and in quality of life. Therapeutic options are limited with poor efficacy in older adults, lending to a growing need to address the gaps in our current understanding of urinary tract aging. This review summarizes the current knowledge of age-associated alterations in the structure and function of the brain-bladder axis and identifies important gaps in the field that have yet to be addressed. Urinary aging is associated with decreased tissue responsiveness, decreased control over the voiding reflex, signaling dysfunction along the brain-bladder axis, and structural changes within the bladder wall. Studies are needed to improve our understanding of how age affects the brain-bladder axis and identify genetic targets that correlate with functional outcomes.

Do non-traumatic stressful life events and ageing negatively impact working memory performance and do they interact to further impair working memory performance?

Stress and normal ageing produce allostatic load, which may lead to difficulties with cognition thereby degrading quality of life. The current study's objective was to assess whether ageing and cumulative stress interact to accelerate cognitive decline. With 60 participants, Marshall et al. found that ageing and cumulative stress interact significantly to impair working memory performance in older adults, suggesting vulnerability to the cumulative effects of life events beyond 60 years old. To replicate and extend this finding, we increased the sample size by conducting 3 independent studies with 156 participants and improved the statistical methods by conducting an iterative Bayesian meta-analysis with Bayes factors. Bayes factors deliver a more comprehensive result because they provide evidence for either the null hypothesis (H0), the alternative hypothesis (H1) or for neither hypothesis due to evidence not being sufficiently sensitive. Young (18-35 yrs) and older (60-85 yrs) healthy adults were categorised as high or low stress based on their life events score derived from the Life Events Scale for Students or Social Readjustment Rating Scale, respectively. We measured accuracy and reaction time on a 2-back working memory task to provide: a) Bayes factors and b) Bayesian meta-analysis, which iteratively added each study's effect sizes to evaluate the overall strength of evidence that ageing, cumulative stress and/or the combination of the two detrimentally affect working memory performance. Using a larger sample (N = 156 vs. N = 60) and a more powerful statistical approach, we did not replicate the robust age by cumulative stress interaction effect found by Marshall et al.. The effects of ageing and cumulative stress also fell within the anecdotal range (⅓ Collapse

Key Words Collapse

MESH Headings

• Humans
• Aged
• Middle Aged
• Memory, Short-Term
• Bayes Theorem
• Quality of Life
• Cognition
• Aging

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Grants Collapse

Affiliation(s)

Denise Wallace Department of Psychology and Centre for Brain Science, University of Essex, Colchester, Essex, United Kingdom
Nicholas R. Cooper Department of Psychology and Centre for Brain Science, University of Essex, Colchester, Essex, United Kingdom
Alejandra Sel Department of Psychology and Centre for Brain Science, University of Essex, Colchester, Essex, United Kingdom
Riccardo Russo Department of Psychology and Centre for Brain Science, University of Essex, Colchester, Essex, United Kingdom Department of Behavioral and Brain Sciences, University of Pavia, Pavia, Italy

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Exploring the Role of Neuroplasticity in Development, Aging, and Neurodegeneration

Neuroplasticity refers to the ability of the brain to reorganize and modify its neural connections in response to environmental stimuli, experience, learning, injury, and disease processes. It encompasses a range of mechanisms, including changes in synaptic strength and connectivity, the formation of new synapses, alterations in the structure and function of neurons, and the generation of new neurons. Neuroplasticity plays a crucial role in developing and maintaining brain function, including learning and memory, as well as in recovery from brain injury and adaptation to environmental changes. In this review, we explore the vast potential of neuroplasticity in various aspects of brain function across the lifespan and in the context of disease. Changes in the aging brain and the significance of neuroplasticity in maintaining cognitive function later in life will also be reviewed. Finally, we will discuss common mechanisms associated with age-related neurodegenerative processes (including protein aggregation and accumulation, mitochondrial dysfunction, oxidative stress, and neuroinflammation) and how these processes can be mitigated, at least partially, by non-invasive and non-pharmacologic lifestyle interventions aimed at promoting and harnessing neuroplasticity.

Quantitative susceptibility mapping of brain iron in healthy aging and cognition

Quantitative susceptibility mapping (QSM) is a magnetic resonance imaging (MRI) technique that can assess the magnetic properties of cerebral iron in vivo. Although brain iron is necessary for basic neurobiological functions, excess iron content disrupts homeostasis, leads to oxidative stress, and ultimately contributes to neurodegenerative disease. However, some degree of elevated brain iron is present even among healthy older adults. To better understand the topographical pattern of iron accumulation and its relation to cognitive aging, we conducted an integrative review of 47 QSM studies of healthy aging, with a focus on five distinct themes. The first two themes focused on age-related increases in iron accumulation in deep gray matter nuclei versus the cortex. The overall level of iron is higher in deep gray matter nuclei than in cortical regions. Deep gray matter nuclei vary with regard to age-related effects, which are most prominent in the putamen, and age-related deposition of iron is also observed in frontal, temporal, and parietal cortical regions during healthy aging. The third theme focused on the behavioral relevance of iron content and indicated that higher iron in both deep gray matter and cortical regions was related to decline in fluid (speed-dependent) cognition. A handful of multimodal studies, reviewed in the fourth theme, suggest that iron interacts with imaging measures of brain function, white matter degradation, and the accumulation of neuropathologies. The final theme concerning modifiers of brain iron pointed to potential roles of cardiovascular, dietary, and genetic factors. Although QSM is a relatively recent tool for assessing cerebral iron accumulation, it has significant promise for contributing new insights into healthy neurocognitive aging.

Matrix metalloproteinases are associated with brain atrophy in cognitively unimpaired individuals

Matrix metalloproteinases (MMPs) and their tissue inhibitors (TIMPs) have been linked to age-related neurodegeneration and Alzheimer's disease (AD), but their role in normal aging is poorly understood. We used linear mixed models to determine if baseline or rate of yearly change in cerebrospinal fluid (CSF) levels of MMP-2; MMP-3; MMP-10; TIMP-123 (composite of TIMP-1, TIMP-2, and TIMP-3); or TIMP-4 predicted changes in bilateral entorhinal cortex thickness, hippocampal volume, or lateral ventricle volume in cognitively unimpaired individuals. We also assessed effects on the CSF AD biomarkers amyloid-β42 and phosphorylated tau181. Low baseline levels of MMP-3 predicted larger ventricle volumes and more entorhinal cortex thinning. Increased CSF MMP-2 levels over time predicted more entorhinal thinning, hippocampal atrophy, and ventricular expansion, while increased TIMP-123 over time predicted ventricular expansion. No MMP/TIMPs predicted changes in CSF AD biomarkers. Notably, we show for the first time that longitudinal increases in MMP-2 and TIMP-123 levels may predict age-associated brain atrophy. In conclusion, MMPs and TIMPs may play a role in brain atrophy in cognitively unimpaired aging.

No phenotypic or genotypic evidence for a link between sleep duration and brain atrophy

Short sleep is held to cause poorer brain health, but is short sleep associated with higher rates of brain structural decline? Analysing 8,153 longitudinal MRIs from 3,893 healthy adults, we found no evidence for an association between sleep duration and brain atrophy. In contrast, cross-sectional analyses (51,295 observations) showed inverse U-shaped relationships, where a duration of 6.5 (95% confidence interval, (5.7, 7.3)) hours was associated with the thickest cortex and largest volumes relative to intracranial volume. This fits converging evidence from research on mortality, health and cognition that points to roughly seven hours being associated with good health. Genome-wide association analyses suggested that genes associated with longer sleep for below-average sleepers were linked to shorter sleep for above-average sleepers. Mendelian randomization did not yield evidence for causal impacts of sleep on brain structure. The combined results challenge the notion that habitual short sleep causes brain atrophy, suggesting that normal brains promote adequate sleep duration-which is shorter than current recommendations.

Structural brain changes in emotion recognition across the adult lifespan

Emotion recognition (ER) declines with increasing age, yet little is known whether this observation is based on structural brain changes conveyed by differential atrophy. To investigate whether age-related ER decline correlates with reduced grey matter (GM) volume in emotion-related brain regions, we conducted a voxel-based morphometry analysis using data of the Human Connectome Project-Aging (N = 238, aged 36-87) in which facial ER was tested. We expected to find brain regions that show an additive or super-additive age-related change in GM volume indicating atrophic processes that reduce ER in older adults. The data did not support our hypotheses after correction for multiple comparisons. Exploratory analyses with a threshold of P < 0.001 (uncorrected), however, suggested that relationships between GM volume and age-related general ER may be widely distributed across the cortex. Yet, small effect sizes imply that only a small fraction of the decline of ER in older adults can be attributed to local GM volume changes in single voxels or their multivariate patterns.

Causal associations between blood lipids and brain structures: a Mendelian randomization study

The potential causal association between dyslipidemia and brain structures remains unclear. Therefore, this study aimed to investigate whether circulating lipids are causally associated with brain structure alterations using Mendelian randomization analysis. Genome-wide association study summary statistics of blood lipids and brain structures were obtained from publicly available databases. Inverse-variance weighted method was used as the primary method to assess causality. In addition, four additional Mendelian randomization methods (MR-Egger, weighted median, simple mode, and weighted mode) were applied to supplement inverse-variance weighted. Furthermore, Cochrane's Q test, MR-Egger intercept test, MR-PRESSO global test, and leave-one-out analysis were performed for sensitivity analyses. After Bonferroni corrections, two causal associations were finally identified: elevated non-high-density lipoprotein cholesterol level leads to higher average cortical thickness (β = 0.0066 mm, 95% confidence interval: 0.0045-0.0087 mm, P = 0.001); and elevated high-density lipoprotein cholesterol level leads to higher inferior temporal surface area (β = 18.6077 mm2, 95% confidence interval: 11.9835-25.2320 mm2, P = 0.005). Four additional Mendelian randomization methods indicated parallel results. Sensitivity tests demonstrated the stability. Overall, the present study showed causal relationships between several lipid profiles and specific brain structures, providing new insights into the link between dyslipidemia and neurological disorders.