Longitudinal brain structure and cognitive changes over 8 years in an East Asian cohort

Bilingualism and "brain reserve" in subregions of the hippocampal formation

With aging, the hippocampal formation shows variable structural atrophy, which is associated with a decline in cognitive performance. Bilingualism is related to higher hippocampal gray matter volume (GMV), potentially representing a form of brain reserve in aging. However, the differential influence of bilingualism on hippocampal subregions remains unclear. Thus, we investigated GMV differences and differences in age-GMV relationships between mono- and bilinguals in the hippocampal formation and its subregions, hippocampus proper and subicular complex. We included 661 adults aged 19 to 85 years (257 monolinguals, 404 sequential bilinguals, predominantly native German speakers with variable second language background) from the population-based 1000BRAINS cohort. GMV differences in mono- vs. bilinguals were assessed for six regions of interest (hippocampal formation, hippocampus proper, and subicular complex; each left and right) using analyses of covariance. Effects of bilingualism on age-GMV relationships were investigated via moderation analyses. We found higher GMV in bilinguals in the bilateral subicular complex, while only a trend towards this effect existed for the hippocampal formation. Moderation analyses revealed similar age-GMV relationships between mono- and bilinguals for all regions of interest. Higher GMV in bilinguals' hippocampal formation seems specifically attributable to the subicular complex rather than the hippocampus proper. With similar age-GMV relationships for mono- and bilinguals, bilingual brain reserve in the subicular complex may persist over time. This may be particularly beneficial since subicular atrophy has previously been associated with higher risk for dementia. Altogether, a differential impact of bilingualism on hippocampal subregions has been demonstrated.

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

Structural brain changes underlie cognitive changes and interindividual variability in cognition in older age. By using structural MRI data-driven clustering, we aimed to identify subgroups of cognitively unimpaired older adults based on brain change patterns and assess how changes in cortical thickness, surface area, and subcortical volume relate to cognitive change. We tested (1) which brain structural changes predict cognitive change (2) whether these are associated with core cerebrospinal fluid (CSF) Alzheimer's disease biomarkers, and (3) the degree of overlap between clusters derived from different structural modalities in 1899 cognitively healthy older adults followed up to 16 years. We identified four groups for each brain feature, based on the degree of a main longitudinal component of decline. The minimal overlap between features suggested that each contributed uniquely and independently to structural brain changes in aging. Cognitive change and baseline cognition were associated with cortical area change, whereas higher baseline levels of phosphorylated tau and amyloid-β related to changes in subcortical volume. These results may contribute to a better understanding of different aging trajectories.

Association of open skill exercise and long-chain polyunsaturated fatty acid intake with brain volume changes among older community-dwelling Japanese individuals

Considering that a multifactorial lifestyle approach may prove more effective than a single factor approach to improve or maintain brain health, we evaluated the association of exercise (open skill exercise [OSE] or closed skill exercise [CSE]) combined with long-chain polyunsaturated fatty acid (LCPUFAs) (docosahexaenoic acid [C22:6n-3, DHA], eicosapentaenoic acid [C20:5n-3, EPA], and arachidonic acid [C20:4n-6, ARA]) intake with brain atrophy among older Japanese individuals (n = 795, aged 60-88 years) without a self-reported history of dementia based on the datasets of a two-year longitudinal study. Brain volumes were measured using three-dimensional T1-weighted brain magnetic resonance imaging for follow-up periods of two years. The associations between multivariate-adjusted changes in brain volumes and OSE or CSE frequency (≥ once/month and < once/month) along with LCPUFA intake (≥ median and < median) at the baseline were assessed using a general linear model. Subgroup analysis was performed by restricting DHA and EPA intakes (n = 263; median, 323 mg/d), which represented levels similar to those in countries with low fish consumption. Higher OSE frequencies, ARA intakes, and their combination were inversely associated with decreases in total gray matter and frontal cortex volumes. In subgroup analysis, a combination of higher OSE frequencies and DHA intakes was also associated with a smaller decrease in total gray matter volume. Overall, our findings suggest that regular OSE engagement and appropriate LCPUFA intake may contribute to preventing brain volume decreases in older individuals.

A Method for Multimodal IVA Fusion Within a MISA Unified Model Reveals Markers of Age, Sex, Cognition, and Schizophrenia in Large Neuroimaging Studies

With the increasing availability of large-scale multimodal neuroimaging datasets, it is necessary to develop data fusion methods which can extract cross-modal features. A general framework, multidataset independent subspace analysis (MISA), has been developed to encompass multiple blind source separation approaches and identify linked cross-modal sources in multiple datasets. In this work, we utilized the multimodal independent vector analysis (MMIVA) model in MISA to directly identify meaningful linked features across three neuroimaging modalities-structural magnetic resonance imaging (MRI), resting state functional MRI and diffusion MRI-in two large independent datasets, one comprising of control subjects and the other including patients with schizophrenia. Results show several linked subject profiles (sources) that capture age-associated decline, schizophrenia-related biomarkers, sex effects, and cognitive performance. For sources associated with age, both shared and modality-specific brain-age deltas were evaluated for association with non-imaging variables. In addition, each set of linked sources reveals a corresponding set of cross-modal spatial patterns that can be studied jointly. We demonstrate that the MMIVA fusion model can identify linked sources across multiple modalities, and that at least one set of linked, age-related sources replicates across two independent and separately analyzed datasets. The same set also presented age-adjusted group differences, with schizophrenia patients indicating lower multimodal source levels. Linked sets associated with sex and cognition are also reported for the UK Biobank dataset.

Structural brain correlates of sustained attention in healthy ageing: Cross-sectional findings from the LEISURE study

Sustained attention is important for maintaining cognitive function and autonomy during ageing, yet older people often show reductions in this domain. The role of the underlying neurobiology is not yet well understood, with most neuroimaging studies primarily focused on fMRI. Here, we utilise sMRI to investigate the relationships between age, structural brain volumes and sustained attention performance. Eighty-nine healthy older adults (50-84 years, Mage 65.5 (SD=8.4) years, 74 f) underwent MRI brain scanning and completed two sustained attention tasks: a rapid visual information processing (RVP) task and sustained attention to response task (SART). Independent hierarchical linear regressions demonstrated that greater volumes of white matter hyperintensities (WMH) were associated with worse RVP_A' performance, whereas greater grey matter volumes were associated with better RVP_A' performance. Further, greater cerebral white matter volumes were associated with better SART_d' performance. Importantly, mediation analyses revealed that both grey and white matter volumes completely mediated the relationship between ageing and sustained attention. These results explain disparate attentional findings in older adults, highlighting the intervening role of brain structure.

Disturbances of thalamus and prefrontal cortex contribute to cognitive aging: A structure-function coupling analysis based on KL divergence

Normal aging is accompanied by changes in brain structure and function associated with cognitive decline. Structural and functional abnormalities, particularly the prefrontal cortex (PFC) and subcortical regions, contributed to cognitive aging. However, it remains unclear how the synchronized changes in structure and function of individual brain regions affect the cognition in aging. Using 3D T1-weighted structural data and movie watching functional magnetic resonance imaging data in a sample of 422 healthy individuals (ages from 18 to 87 years), we constructed regional structure-function coupling (SFC) of cortical and subcortical regions by quantifying the distribution similarity of gray matter volume (GMV) and amplitude of low-frequency fluctuation (ALFF). Further, we investigated age-related changes in SFC and its relationship with cognition. With aging, increased SFC localized in PFC, thalamus and caudate nucleus, decreased SFC in temporal cortex, lateral occipital cortex and putamen. Moreover, the SFC in the PFC was associated with executive function and thalamus was associated with the fluid intelligence, and partially mediated age-related cognitive decline. Collectively, our results highlight that tighter structure-function synchron of the PFC and thalamus might contribute to age-related cognitive decline, and provide insight into the substrate of the thalamo-prefrontal pathway with cognitive aging.

Mapping computational cognitive profiles of aging to dissociable brain and sociodemographic factors

Aging is associated with declines in cognition and brain structural integrity. However, there is equivocality over (1) the specificity of affected domains in different people, (2) the location of associated patterns of brain structural deterioration, and (3) the sociodemographic factors contributing to 'unhealthy' cognition. We aimed to identify cognitive profiles displayed by older adults and determine brain and sociodemographic features potentially shaping these profiles. A sample of Southeast-Asian older adults (N = 386) participated in a multi-session study comprising cognitive testing, neuroimaging, and a structured interview. We used computational models to extract latent mechanisms underlying cognitive flexibility and response inhibition. Data-driven methods were used to construct cognitive profiles based on standard performance measures and model parameters. We also investigated grey matter volume and machine-learning derived 'brain-ages'. A profile associated with poor set-shifting and rigid focusing was associated with widespread grey matter reduction in cognitive control regions. A slow responding profile was associated with advanced brain-age. Both profiles were correlated with poor socioeconomic standing and cognitive reserve. We found that the impact of sociodemographic factors on cognitive profiles was partially mediated by total grey and white matter, and dorsolateral prefrontal and cerebellar volumes. This study furthers understanding of how distinct aging profiles of cognitive impairment uniquely correspond to specific vs. global brain deterioration and the significance of socioeconomic factors in informing cognitive performance in older age.

Eight brain structures mediate the age-related alterations of the working memory: forward and backward digit span tasks

Introduction

Working memory (WM) as one of the executive functions is an essential neurocognitive ability for daily life. Findings have suggested that aging is often associated with working memory and neural decline, but the brain structures and resting-state brain networks that mediate age-related differences in WM remain unclear.

Methods

A sample consisting of 252 healthy participants in the age range of 20 to 70years was used. Several cognitive tasks, including the n-back task and the forward and backward digit span tests were used. Also, resting-state functional imaging, as well as structural imaging using a 3T MRI scanner, were performed, resulting in 85 gray matter volumes and five resting-state networks, namely the anterior and posterior default mode, the right and left executive control, and the salience networks. Also, mediation analyses were used to investigate the role of gray matter volumes and resting-state networks in the relationship between age and WM.

Results

Behaviorally, aging was associated with decreased performance in the digit span task. Also, aging was associated with a decreased gray matter volume in 80 brain regions, and with a decreased activity in the anterior default mode network, executive control, and salience networks. Importantly, the path analysis showed that the GMV of the medial orbitofrontal, precentral, parieto-occipital, amygdala, middle occipital, posterior cingulate, and thalamus areas mediated the age-related differences in the forward digit span task, and the GMV of superior temporal gyrus mediated the age-related differences in the backward digit span task.

Discussion

This study identified the brain structures mediating the relationship between age and working memory, and we hope that our research provides an opportunity for early detection of individuals at risk of age-related memory decline.

Clinically feasible automated MRI volumetry of the brain as a prognostic marker in subjective and mild cognitive impairment

Background/aims

The number of patients suffering from cognitive decline and dementia increases, and new possible treatments are being developed. Thus, the need for time efficient and cost-effective methods to facilitate an early diagnosis and prediction of future cognitive decline in patients with early cognitive symptoms is becoming increasingly important. The aim of this study was to evaluate whether an MRI based software, NeuroQuant® (NQ), producing volumetry of the hippocampus and whole brain volume (WBV) could predict: (1) conversion from subjective cognitive decline (SCD) at baseline to mild cognitive impairment (MCI) or dementia at follow-up, and from MCI at baseline to dementia at follow-up and (2) progression of cognitive and functional decline defined as an annual increase in the Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) score.

Methods

MRI was performed in 156 patients with SCD or MCI from the memory clinic at Oslo University Hospital (OUH) that had been assessed with NQ and had a clinical follow-up examination. Logistic and linear regression analyses were performed with hippocampus volume and WBV as independent variables, and conversion or progression as dependent variables, adjusting for demographic and other relevant covariates including Mini-Mental State Examination-Norwegian Revised Version score (MMSE-NR) and Apolipoprotein E ɛ4 (APOE ɛ4) carrier status.

Results

Hippocampus volume, but not WBV, was associated with conversion to MCI or dementia, but neither were associated with conversion when adjusting for MMSE-NR. Both hippocampus volume and WBV were associated with progression as measured by the annual change in CDR-SB score in both unadjusted and adjusted analyses.

Conclusion

The results indicate that automated regional MRI volumetry of the hippocampus and WBV can be useful in predicting further cognitive decline in patients with early cognitive symptoms.

Does resistance training in older adults lead to structural brain changes associated with a lower risk of Alzheimer's dementia? A narrative review

Dementia, particularly Alzheimer's Disease (AD), has links to several modifiable risk factors, especially physical inactivity. When considering the relationship between physcial activity and dementia risk, cognitive benefits are generally attributed to aerobic exercise, with resistance exercise (RE) receiving less attention. This review aims to address this gap by evaluating the impact of RE on brain structures and cognitive deficits associated with AD. Drawing insights from randomized controlled trials (RCTs) utilizing structural neuroimaging, the specific influence of RE on AD-affected brain structures and their correlation with cognitive function are discussed. Preliminary findings suggest that RE induces structural brain changes in older adults that could reduce the risk of AD or mitigate AD progression. Importantly, the impacts of RE appear to follow a dose-response effect, reversing pathological structural changes and improving associated cognitive functions if performed at least twice per week for at least six months, with greatest effects in those already experiencing some element of cognitive decline. While more research is eagerly awaited, this review contributes insights into the potential benefits of RE for cognitive health in the context of AD-related changes in brain structure and function.

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.

Age-related enhancement of the association between episodic memory and gray matter volume in medial temporal and frontal lobes

BACKGROUND

Episodic memory (EM) deteriorates as a result of normal aging as well as Alzheimer's disease. The neural underpinnings of such age-related memory impairments in older individuals are not well-understood. Although previous research has unveiled the association between gray matter volume (GMV) and EM in the elderly population, such findings exhibit variances across distinct age cohorts. Consequently, an investigation into the dynamic evolution of this relationship with advancing age is imperative.

RESULT

The present study utilized a sliding window approach to examine how the correlation between EM and GMV varied with age in a cross-sectional sample of 926 Chinese older adults. We found that both verbal EM (VEM) and spatial EM (SEM) exhibited positive correlations with GMV in extensive areas primarily in the temporal and frontal lobes and that these correlations typically became stronger with older age. Moreover, there were variations in the strength of the correlation between EM and GMV with age, which differed based on sex and the specific type of EM. Specifically, the association between VEM and GMVs in the insula and parietal regions became stronger with age for females but not for males, whereas the association between SEM and GMVs in the parietal and occipital regions became stronger for males but not for females. At the brain system level, there is a significant age-related increase in the correlations between both types of EM and the GMV of both the anterior temporal (AT) system and the posterior medial (PM) system in male group. In females, both types of EM show stronger age-related correlations with the GMV of the AT system compared to males.

CONCLUSIONS

Our study revealed a significant positive correlation between GMV in most regions associated with EM and age, particularly in the frontal and temporal lobes. This discovery offers new insights into the connection between brain structure and the diminishing episodic memory function among older individuals.

Comparison between morphometry and radiomics: detecting normal brain aging based on grey matter

Objective

Voxel-based morphometry (VBM), surface-based morphometry (SBM), and radiomics are widely used in the field of neuroimage analysis, while it is still unclear that the performance comparison between traditional morphometry and emerging radiomics methods in diagnosing brain aging. In this study, we aimed to develop a VBM-SBM model and a radiomics model for brain aging based on cognitively normal (CN) individuals and compare their performance to explore both methods' strengths, weaknesses, and relationships.

Methods

967 CN participants were included in this study. Subjects were classified into the middle-aged group (n = 302) and the old-aged group (n = 665) according to the age of 66. The data of 360 subjects from the Alzheimer's Disease Neuroimaging Initiative were used for training and internal test of the VBM-SBM and radiomics models, and the data of 607 subjects from the Australian Imaging, Biomarker and Lifestyle, the National Alzheimer's Coordinating Center, and the Parkinson's Progression Markers Initiative databases were used for the external tests. Logistics regression participated in the construction of both models. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were used to evaluate the two model performances. The DeLong test was used to compare the differences in AUCs between models. The Spearman correlation analysis was used to observe the correlations between age, VBM-SBM parameters, and radiomics features.

Results

The AUCs of the VBM-SBM model and radiomics model were 0.697 and 0.778 in the training set (p = 0.018), 0.640 and 0.789 in the internal test set (p = 0.007), 0.736 and 0.737 in the AIBL test set (p = 0.972), 0.746 and 0.838 in the NACC test set (p < 0.001), and 0.701 and 0.830 in the PPMI test set (p = 0.036). Weak correlations were observed between VBM-SBM parameters and radiomics features (p < 0.05).

Conclusion

The radiomics model achieved better performance than the VBM-SBM model. Radiomics provides a good option for researchers who prioritize performance and generalization, whereas VBM-SBM is more suitable for those who emphasize interpretability and clinical practice.

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.

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.

Behavioral and Neuronal Characterizations, across Ages, of the TgSwDI Mouse Model of Alzheimer's Disease

Alzheimer's disease (AD) is a neurodegenerative disorder that currently affects as many as 50 million people worldwide. It is neurochemically characterized by an aggregation of β-amyloid plaques and tau neurofibrillary tangles that result in neuronal dysfunction, cognitive decline, and a progressive loss of brain function. TgSwDI is a well-studied transgenic mouse model of AD, but no longitudinal studies have been performed to characterize cognitive deficits or β-amyloid plaque accumulation for use as a baseline reference in future research. Thus, we use behavioral tests (T-Maze, Novel Object Recognition (NOR), Novel Object Location (NOL)) to study long-term and working memory, and immunostaining to study β-amyloid plaque deposits, as well as brain size, in hippocampal, cerebellum, and cortical slices in TgSwDI and wild-type (WT) mice at 3, 5, 8, and 12 months old. The behavioral results show that TgSwDI mice exhibit deficits in their long-term spatial memory starting at 8 months old and in long-term recognition memory at all ages, but no deficits in their working memory. Immunohistochemistry showed an exponential increase in β-amyloid plaque in the hippocampus and cortex of TgSwDI mice over time, whereas there was no significant accumulation of plaque in WT mice at any age. Staining showed a smaller hippocampus and cerebellum starting at 8 months old for the TgSwDI compared to WT mice. Our data show how TgSwDI mice differ from WT mice in their baseline levels of cognitive function and β-amyloid plaque load throughout their lives.

Longitudinal alterations in brain morphometry mediated the effects of bullying victimization on cognitive development in preadolescents

Bullying victimization is associated with a doubled risk of attempting suicide in adulthood. Two longitudinal brain morphometry studies identified the fusiform gyrus and putamen as vulnerable to bullying. No study identified how neural alterations may mediate the effect of bullying on cognition. We assessed participants with caregiver-reported bullying (N = 323) and matched non-bullied controls (N = 322) from the Adolescent Brain Cognitive Development Study dataset to identify changes in brain morphometry associated with ongoing bullying victimization over two years and determine whether such alterations mediated the effect of bullying on cognition. Bullied children (38.7% girls, 47.7% racial minorities, 9.88 ± 0.62 years at baseline) had poorer cognitive performance (P < 0.05), larger right hippocampus (P = 0.036), left entorhinal cortex, left superior parietal cortex, and right fusiform gyrus volumes (all P < 0.05), as well as larger surface areas in multiple other frontal, parietal, and occipital cortices. Thinner cortices were also found in the left hemisphere, particularly in the left temporal lobe, and right frontal region (all P < 0.05). Importantly, larger surface area in the fusiform cortices partially suppressed (12-16%), and thinner precentral cortices partially mitigated, (7%) the effect of bullying on cognition (P < 0.05). These findings highlight the negative impact of prolonged bullying victimization on brain morphometry and cognition.

Cross-sectional associations between cortical thickness and physical activity in older adults with spontaneous memory complaints: The MAPT Study

BACKGROUND

Age-related changes in brain structure may constitute the starting point for cerebral function alteration. Physical activity (PA) demonstrated favorable associations with total brain volume, but its relationship with cortical thickness (CT) remains unclear. We investigated the cross-sectional associations between PA level and CT in community-dwelling people aged 70 years and older.

METHODS

A total of 403 older adults aged 74.8 ± 4.0 years (mean ± SD) who underwent a baseline magnetic resonance imaging examination and who had data on PA and confounders were included. PA was assessed with a questionnaire. Participants were categorized according to PA levels. Multiple linear regressions were used to compare the brain CT (mm) of the inactive group (no PA at all) with 6 active groups (growing PA levels) in 34 regions of interest.

RESULTS

Compared with inactive persons, people who achieved PA at a level of 1500-1999 metabolic equivalent task-min/week (i.e., about 6-7 h of brisk walking for exercise and those who achieved it at 2000-2999 metabolic equivalent task-min/week (i.e., 8-11 h of brisk walking for exercise) had higher CT in the fusiform gyrus and the temporal pole. Additionally, dose-response associations between PA and CT were found in the fusiform gyrus (B = 0.011, SE = 0.004, adj. p = 0.035), the temporal pole (B = 0.026, SE = 0.009, adj. p = 0.048), and the caudal middle frontal gyrus, the entorhinal, medial orbitofrontal, lateral occipital, and insular cortices.

CONCLUSION

This study demonstrates a positive association between PA level and CT in temporal areas such as the fusiform gyrus, a brain region often associated to Alzheimer's disease in people aged 70 years and older. Future investigations focusing on PA type may help to fulfil remaining knowledge gaps in this field.

Functional activity level reported by an informant is an early predictor of Alzheimer's disease

BACKGROUND

Loss of autonomy in day-to-day functioning is one of the feared outcomes of Alzheimer's disease (AD), and relatives may have been worried by subtle behavioral changes in ordinary life situations long before these changes are given medical attention. In the present study, we ask if such subtle changes should be given weight as an early predictor of a future AD diagnosis.

METHODS

Longitudinal data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were used to define a group of adults with a mild cognitive impairment (MCI) diagnosis remaining stable across several visits (sMCI, n=360; 55-91 years at baseline), and a group of adults who over time converted from having an MCI diagnosis to an AD diagnosis (cAD, n=320; 55-88 years at baseline). Eleven features were used as input in a Random Forest (RF) binary classifier (sMCI vs. cAD) model. This model was tested on an unseen holdout part of the dataset, and further explored by three different permutation-driven importance estimates and a comprehensive post hoc machine learning exploration.

RESULTS

The results consistently showed that measures of daily life functioning, verbal memory function, and a volume measure of hippocampus were the most important predictors of conversion from an MCI to an AD diagnosis. Results from the RF classification model showed a prediction accuracy of around 70% in the test set. Importantly, the post hoc analyses showed that even subtle changes in everyday functioning noticed by a close informant put MCI patients at increased risk for being on a path toward the major cognitive impairment of an AD diagnosis.

CONCLUSION

The results showed that even subtle changes in everyday functioning should be noticed when reported by relatives in a clinical evaluation of patients with MCI. Information of these changes should also be included in future longitudinal studies to investigate different pathways from normal cognitive aging to the cognitive decline characterizing different stages of AD and other neurodegenerative disorders.

Association between social comparison orientation and hippocampal properties in older adults: A multimodal MRI study

Social comparison orientation (SCO) refers to the tendency to compare oneself with others and has two distinct dimensions: one about opinions and the other about abilities. Although dissociable neural mechanisms underlying the two dimensions of social comparison can be assumed, little is known about how each dimension of SCO is associated with cognitive and brain health among older adults. To investigate this, we analyzed the SCO scale questionnaire data, neuropsychological assessment data, and multimodal MRI data collected from 90 community-dwelling older adults. We found that global cognitive performance was positively correlated with the score of the opinion subscale but not with the score of the ability subscale and the total score. Similarly, hippocampal volume was positively correlated with opinion score alone. Additionally, the resting-state functional connectivity between the hippocampal seed and the default mode network showed a positive correlation only with the opinion score. Moreover, fractional anisotropy in the hippocampal cingulum was positively correlated with opinion score only. These findings suggest that global cognition and hippocampal properties in older age are associated with the SCO of opinion, which could reflect a regular habit of performing the types of cognitively demanding activities involved in evaluation of self and other opinions.

Multimodal imaging of the aging brain: Baseline findings of the LoCARPoN study

We quantified and investigated multimodal brain MRI measures in the LoCARPoN Study due to lack of normative data among Indians. A total of 401 participants (aged 50-88 years) without stroke or dementia completed MRI investigation. We assessed 31 brain measures in total using four brain MRI modalities, including macrostructural (global & lobar volumes, white matter hyperintensities [WMHs]), microstructural (global and tract-specific white matter fractional anisotropy [WM-FA] and mean diffusivity [MD]) and perfusion measures (global and lobar cerebral blood flow [CBF]). The absolute brain volumes of males were significantly larger than those of females, but such differences were relatively small (<1.2% of intracranial volume). With increasing age, lower macrostructural brain volumes, lower WM-FA, greater WMHs, higher WM-MD were found (P = 0.00018, Bonferroni threshold). Perfusion measures did not show significant differences with increasing age. Hippocampal volume showed the greatest association with age, with a reduction of approximately 0.48%/year. This preliminary study augments and provides insight into multimodal brain measures during the nascent stages of aging among the Indian population (South Asian ethnicity). Our findings establish the groundwork for future hypothetical testing studies.

The Aging Patterns of Brain Structure, Function, and Energy Metabolism

The normal aging process brings changes in brain structure, function, and energy metabolism, which are presumed to contribute to the age-related decline in brain function and cognitive ability. This chapter aims to summarize the aging patterns of brain structure, function, and energy metabolism to distinguish them from the pathological changes associated with neurodegenerative diseases and explore protective factors in aging. We first described the normal atrophy pattern of cortical gray matter with age, which is negatively affected by some neurodegenerative diseases and is protected by a healthy lifestyle, such as physical exercise. Next, we summarized the main types of age-related white matter lesions, including white matter atrophy and hyperintensity. Age-related white matter changes mainly occurred in the frontal lobe, and white matter lesions in posterior regions may be an early sign of Alzheimer's disease. In addition, the relationship between brain activity and various cognitive functions during aging was discussed based on electroencephalography, magnetoencephalogram, and functional magnetic resonance imaging. An age-related reduction in occipital activity is coupled with increased frontal activity, which supports the posterior-anterior shift in aging (PASA) theory. Finally, we discussed the relationship between amyloid-β deposition and tau accumulation in the brain, as pathological manifestations of neurodegenerative disease and aging.

Effect of leisure activities on cognitive aging in older adults: A systematic review and meta-analysis

Abnormal cognitive aging in older adults is a growing public health problem. Previous studies showed inconsistent results pertaining to the effects of leisure activities on cognitive function in older adults. We conducted a systematic review and meta-analysis of published observational longitudinal studies to examine and synthesize the effects of leisure activities on cognitive function in older adults. MEDLINE, PubMed, EMBASE, PsycINFO (Ovid), CINAHL (EBSCO), and Web of Science databases were searched from January 2012 to January 2022. Relative risks (RRs) with 95% confidence intervals (CIs) were pooled using random-effects meta-analysis. Most studies found that leisure activities had a positive effect on cognitive function in older adults. The pooled RR for the effect of leisure activity on cognitive function was 0.77 (95% CI: 0.72-0.81, p < 0.01). The effects of leisure activities on cognitive function varied by different cognitive statuses in older adults, with RRs ranging from 0.55 (95% CI: 0.37-0.83) to 1.07 (95% CI: 0.95-1.22). Meta-regression analysis showed that compared with studies with percentage of female ≥50%, studies with female participant percentage <50% had significantly increased RR (p = 0.01). Moreover, studies conducted in European and American countries had significantly lower RR (p = 0.019), compared with those conducted in Asian countries. Our study revealed different effects of various types of leisure activities on different cognitive statuses in older adults. To make innovative recommendations for promoting cognitive function in older adults, more detailed observational longitudinal studies investigating the effects of different types of leisure activities on different cognitive statuses in older adults are needed.

DeepParcellation: A novel deep learning method for robust brain magnetic resonance imaging parcellation in older East Asians

Accurate parcellation of cortical regions is crucial for distinguishing morphometric changes in aged brains, particularly in degenerative brain diseases. Normal aging and neurodegeneration precipitate brain structural changes, leading to distinct tissue contrast and shape in people aged >60 years. Manual parcellation by trained radiologists can yield a highly accurate outline of the brain; however, analyzing large datasets is laborious and expensive. Alternatively, newly-developed computational models can quickly and accurately conduct brain parcellation, although thus far only for the brains of Caucasian individuals. To develop a computational model for the brain parcellation of older East Asians, we trained magnetic resonance images of dimensions 256 × 256 × 256 on 5,035 brains of older East Asians (Gwangju Alzheimer's and Related Dementia) and 2,535 brains of Caucasians. The novel N-way strategy combining three memory reduction techniques inception blocks, dilated convolutions, and attention gates was adopted for our model to overcome the intrinsic memory requirement problem. Our method proved to be compatible with the commonly used parcellation model for Caucasians and showed higher similarity and robust reliability in older aged and East Asian groups. In addition, several brain regions showing the superiority of the parcellation suggest that DeepParcellation has a great potential for applications in neurodegenerative diseases such as Alzheimer's disease.

Nomograms of human hippocampal volume shifted by polygenic scores

Nomograms are important clinical tools applied widely in both developing and aging populations. They are generally constructed as normative models identifying cases as outliers to a distribution of healthy controls. Currently used normative models do not account for genetic heterogeneity. Hippocampal volume (HV) is a key endophenotype for many brain disorders. Here, we examine the impact of genetic adjustment on HV nomograms and the translational ability to detect dementia patients. Using imaging data from 35,686 healthy subjects aged 44-82 from the UK Biobank (UKB), we built HV nomograms using Gaussian process regression (GPR), which - compared to a previous method - extended the application age by 20 years, including dementia critical age ranges. Using HV polygenic scores (HV-PGS), we built genetically adjusted nomograms from participants stratified into the top and bottom 30% of HV-PGS. This shifted the nomograms in the expected directions by ~100 mm3 (2.3% of the average HV), which equates to 3 years of normal aging for a person aged ~65. Clinical impact of genetically adjusted nomograms was investigated by comparing 818 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database diagnosed as either cognitively normal (CN), having mild cognitive impairment (MCI) or Alzheimer's disease (AD) patients. While no significant change in the survival analysis was found for MCI-to-AD conversion, an average of 68% relative decrease was found in intra-diagnostic-group variance, highlighting the importance of genetic adjustment in untangling phenotypic heterogeneity.

A pilot voxel-based morphometry study of older adults after the PICMOR intervention program

Background

Age-related decline in cognitive function, such as executive function, is associated with structural changes in the neural substrates, such as volume reductions in the lateral prefrontal cortex. To prevent or delay age-related changes in cognitive function, cognitive intervention methods that employ social activity, including conversations, have been proposed in some intervention studies. Interestingly, previous studies have consistently reported that verbal fluency ability can be trained by conversation-based interventions in healthy older adults. However, little is known about the neural substrates that underlie the beneficial effect of conversation-based interventions on cognitive function. In this pilot study, we aimed to provide candidate brain regions that are responsible for the enhancement of cognitive function, by analyzing structural magnetic resonance imaging (MRI) data that were additionally obtained from participants in our previous intervention study.

Methods

A voxel-based morphometric analysis was applied to the structural MRI data. In the analysis, the regional brain volume was compared between the intervention group, who participated in a group conversation-based intervention program named Photo-Integrated Conversation Moderated by Robots (PICMOR), and the control group, who joined in a control program based on unstructured free conversations. Furthermore, regions whose volume was positively correlated with an increase in verbal fluency task scores throughout the intervention period were explored.

Results

Results showed that the volume of several regions, including the superior frontal gyrus, parahippocampal gyrus/hippocampus, posterior middle temporal gyrus, and postcentral gyrus, was greater in the intervention group than in the control group. In contrast, no regions showed greater volume in the control group than in the intervention group. The region whose volume showed a positive correlation with the increased task scores was identified in the inferior parietal lobule.

Conclusions

Although definitive conclusions cannot be drawn from this study due to a lack of MRI data from the pre-intervention period, it achieved the exploratory purpose by successfully identifying candidate brain regions that reflect the beneficial effect of conversation-based interventions on cognitive function, including the lateral prefrontal cortex, which plays an important role in executive functions.

Trial registration

The trial was retrospectively registered on 7 May 2019 (UMIN Clinical Trials Registry number: UMIN000036667).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-021-02669-x.

Model of brain maintenance reveals specific change-change association between medial-temporal lobe integrity and episodic memory

Brain maintenance has been identified as a major determinant of successful memory aging. However, the extent to which brain maintenance in support of successful memory aging is specific to memory-related brain regions or forms part of a brain-wide phenomenon is unresolved. Here, we used longitudinal brain-wide gray matter MRI volumes in 262 healthy participants aged 55 to 80 years at baseline to investigate separable dimensions of brain atrophy, and explored the links of these dimensions to different dimensions of cognitive change. We statistically adjusted for common causes of change in both brain and cognition to reveal a potentially unique signature of brain maintenance related to successful memory aging. Critically, medial temporal lobe (MTL)/hippocampal change and episodic memory change were characterized by unique, residual variance beyond general factors of change in brain and cognition, and a reliable association between these two residualized variables was established (r = 0.36, p < 0.01). The present study is the first to provide solid evidence for a specific association between changes in (MTL)/hippocampus and episodic memory in normal human aging. We conclude that hippocampus-specific brain maintenance relates to the specific preservation of episodic memory in old age, in line with the notion that brain maintenance operates at both general and domain-specific levels.

Dementia in Southeast Asia: influence of onset-type, education, and cerebrovascular disease

Background

Southeast Asia represents 10% of the global population, yet little is known about regional clinical characteristics of dementia and risk factors for dementia progression. This study aims to describe the clinico-demographic profiles of dementia in Southeast Asia and investigate the association of onset-type, education, and cerebrovascular disease (CVD) on dementia progression in a real-world clinic setting.

Methods

In this longitudinal study, participants were consecutive series of 1606 patients with dementia from 2010 to 2019 from a tertiary memory clinic from Singapore. The frequency of dementia subtypes stratified into young-onset (YOD; <65 years age-at-onset) and late-onset dementia (LOD; ≥65 years age-at-onset) was studied. Association of onset-type (YOD or LOD), years of lifespan education, and CVD on the trajectory of cognition was evaluated using linear mixed models. The time to significant cognitive decline was investigated using Kaplan-Meier analysis.

Results

Dementia of the Alzheimer’s type (DAT) was the most common diagnosis (59.8%), followed by vascular dementia (14.9%) and frontotemporal dementia (11.1%). YOD patients accounted for 28.5% of all dementia patients. Patients with higher lifespan education had a steeper decline in global cognition (p<0.001), with this finding being more pronounced in YOD (p=0.0006). Older patients with a moderate-to-severe burden of CVD demonstrated a trend for a faster decline in global cognition compared to those with a mild burden.

Conclusions

There is a high frequency of YOD with DAT being most common in our Southeast Asian memory clinic cohort. YOD patients with higher lifespan education and LOD patients with moderate-to-severe CVD experience a steep decline in cognition.

A predictive framework based on brain volume trajectories enabling early detection of Alzheimer's disease

We present a framework for constructing predictive models of cognitive decline from longitudinal MRI examinations, based on mixed effects models and machine learning. We apply the framework to detect conversion from cognitively normal (CN) to mild cognitive impairment (MCI) and from MCI to Alzheimer's disease (AD), using a large collection of subjects sourced from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Australian Imaging, Biomarkers and Lifestyle Flagship Study of Aging (AIBL). We extract subcortical segmentation and cortical parcellation from corresponding T1-weighted images using FreeSurfer v.6.0, select bilateral 3D regions of interest relevant to neurodegeneration/dementia, and fit their longitudinal volume trajectories using linear mixed effects models. Features describing these model-based trajectories are then used to train an ensemble of machine learning classifiers to distinguish stable CN from converters to MCI, and stable MCI from converters to AD. On separate test sets the models achieved an average of accuracy/precision/recall score of 69/73/60% for converted to MCI and 75/74/77% for converted to AD, illustrating the framework's ability to extract predictive imaging-based biomarkers from routine T1-weighted MRI acquisitions.

Investigating the effects of healthy cognitive aging on brain functional connectivity using 4.7 T resting-state functional magnetic resonance imaging

Functional changes in the aging human brain have been previously reported using functional magnetic resonance imaging (fMRI). Earlier resting-state fMRI studies revealed an age-associated weakening of intra-system functional connectivity (FC) and age-associated strengthening of inter-system FC. However, the majority of such FC studies did not investigate the relationship between age and network amplitude, without which correlation-based measures of FC can be challenging to interpret. Consequently, the main aim of this study was to investigate how three primary measures of resting-state fMRI signal-network amplitude, network topography, and inter-network FC-are affected by healthy cognitive aging. We acquired resting-state fMRI data on a 4.7 T scanner for 105 healthy participants representing the entire adult lifespan (18-85 years of age). To study age differences in network structure, we combined ICA-based network decomposition with sparse graphical models. Older adults displayed lower blood-oxygen-level-dependent (BOLD) signal amplitude in all functional systems, with sensorimotor networks showing the largest age differences. Our age comparisons of network topography and inter-network FC demonstrated a substantial amount of age invariance in the brain's functional architecture. Despite architecture similarities, old adults displayed a loss of communication efficiency in our inter-network FC comparisons, driven primarily by the FC reduction in frontal and parietal association cortices. Together, our results provide a comprehensive overview of age effects on fMRI-based FC.

Cognitive and MRI trajectories for prediction of Alzheimer's disease

The concept of Mild Cognitive Impairment (MCI) is used to describe the early stages of Alzheimer's disease (AD), and identification and treatment before further decline is an important clinical task. We selected longitudinal data from the ADNI database to investigate how well normal function (HC, n= 134) vs. conversion to MCI (cMCI, n= 134) and stable MCI (sMCI, n=333) vs. conversion to AD (cAD, n= 333) could be predicted from cognitive tests, and whether the predictions improve by adding information from magnetic resonance imaging (MRI) examinations. Features representing trajectories of change in the selected cognitive and MRI measures were derived from mixed effects models and used to train ensemble machine learning models to classify the pairs of subgroups based on a subset of the data set. Evaluation in an independent test set showed that the predictions for HC vs. cMCI improved substantially when MRI features were added, with an increase in [Formula: see text]-score from 60 to 77%. The [Formula: see text]-scores for sMCI vs. cAD were 77% without and 78% with inclusion of MRI features. The results are in-line with findings showing that cognitive changes tend to manifest themselves several years after the Alzheimer's disease is well-established in the brain.

Effects of choral singing versus health education on cognitive decline and aging: a randomized controlled trial

We conducted a randomized controlled trial to examine choral singing’s effect on cognitive decline in aging. Older Singaporeans who were at high risk of future dementia were recruited: 47 were assigned to choral singing intervention (CSI) and 46 were assigned to health education program (HEP). Participants attended weekly one-hour choral singing or weekly one-hour health education for two years. Change in cognitive function was measured by a composite cognitive test score (CCTS) derived from raw scores of neuropsychological tests; biomarkers included brain magnetic resonance imaging, oxidative damage and immunosenescence. The average age of the participants were 70 years and 73/93 (78.5%) were female. The change of CCTS from baseline to 24 months was 0.05 among participants in the CSI group and -0.1 among participants in the HEP group. The between-group difference (0.15, p=0.042) became smaller (0.12, p=0.09) after adjusting for baseline CCTS. No between-group differences on biomarkers were observed. Our data support the role of choral singing in improving cognitive health in aging. The beneficial effect is at least comparable than that of health education in preventing cognitive decline in a community of elderly people. Biological mechanisms underlying the observed efficacy should be further studied.

Correlation Between Hippocampal Enlarged Perivascular Spaces and Cognition in Non-dementic Elderly Population

Background and aims: The pathophysiology of hippocampal enlarged perivascular spaces (H-EPVS) and its relationship to cognitive impairment is largely unknown. This study aimed to investigate the relationship between H-EPVS and cognition in non-dementic elderly population.

Methods: A total of 109 subjects were prospectively enrolled. The eligibilities for inclusion were age from 55 to 85 years and Mini-Mental Status Examination score of ≥26. The Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog), Montreal Cognitive Assessment, transcranial Doppler (TCD), and brain magnetic resonance imaging results were evaluated. H-EPVS was categorized in a three-degree scale: degree 0 (no), degree 1 (1,2), and degree 2 (>2). The associations between H-EPVS and TCD parameters/cognitive test profiles were analyzed.

Results: The mean age was 65.2 years, and 52.3% subjects were men. H-EPVS was found to be associated with age (degree 2 vs. degree 1 vs. degree 0, 69.20 ± 6.93 vs. 65.70 ± 5.75 vs. 63.80 ± 5.43; p = 0.030) and ADAS-Cog memory score (degree 2 vs. degree 1 vs. degree 0, 14.88 ± 4.27 vs. 12.49 ± 4.56 vs. 11.4 ± 4.23; p = 0.037). However, the pulsatility index was not related to the degree of H-EPVS. Multivariate analysis revealed medial temporal atrophy (MTA) scale score was independently associated with ADAS-Cog memory score (MTA scale sum ≥4, p = 0.011) but not with the degree of H-EPVS. MTA scale score showed correlation with H-EPVS (r = 0.273, p = 0.004).

Conclusions: Aging was associated with the development of H-EPVS in non-dementic elderly population. Memory function was found to be associated with MTA but not with the degree of H-EPVS.

Longitudinal trajectories of hippocampal volume in middle to older age community dwelling individuals

Understanding heterogeneity in brain aging trajectories is important to estimate the extent to which aging outcomes can be optimized. Although brain changes in late life are well-characterized, brain changes in middle age are not well understood. In this study, we investigated hippocampal change in a generally healthy community-living population of middle (n = 421, mean age 47.2 years) and older age (n = 411, mean age 63.0 years) individuals, over a follow-up of up to 12 years. Manually traced hippocampal volumes were analyzed using multilevel models and latent class analysis to investigate longitudinal aging trajectories and laterality and sex effects, and to identify subgroups that follow different aging trajectories. Hippocampal volumes decreased on average by 0.18%/year in middle age and 0.3%/year in older age. Men tended to experience steeper declines than women in middle age only. Three subgroups of individuals following different trajectories were identified in middle age and 2 in older age. Contrary to expectations, the subgroup containing two-thirds of older age participants maintained stable hippocampal volumes across the follow-up.

Cognitive and neuroimaging profiles of older adults with dual decline in memory and gait speed

We previously showed that dual decline in memory and gait speed was associated with an increased risk of dementia compared to memory or gait decline only or no decline. We now characterized cognitive and neuroimaging profiles of dual decliners by comparing longitudinal rates of change in various cognitive domains (n = 664) and brain volumes (n = 391; selected frontal, temporal, parietal, subcortical, and cerebellar areas) in Baltimore Longitudinal Study of Aging participants who experienced age-related dual decline to others. Compared to others, dual decliners had steeper declines in verbal fluency, attention, and sensorimotor function by Pegboard nondominant hand performance. Dual decliners had greater brain volume loss in superior frontal gyrus, superior parietal gyrus, precuneus, thalamus, and cerebellum (all p ≤ 0.01). Participants with age-related dual decline experienced steeper declines in multiple cognitive domains and greater brain volume loss in cognitive, sensorimotor, and locomotion areas. Impaired sensorimotor integration and locomotion are underlying features of dual decline. Whether these features contribute to the increased risk of dementia should be investigated.

Comparing language samples of Bangla speakers using a colour photograph and a black-and-white line drawing

BACKGROUND

A comprehensive aphasia assessment is necessary to diagnose the type and severity of aphasia differentially and guide appropriate interventions. One component of an aphasia assessment is the picture description task (PDT), designed to probe spontaneous speech fluency and information content. Most aphasia assessments use black-and-white line drawings (LD) to elicit spontaneous language samples from people with aphasia (PWA). However, recent studies reported two visuographic variables: (1) colour (over black and white) and (2) photograph (over LD), that tended to encourage easier and faster comprehension and increased overall naturalistic language production from neurologically healthy individuals as well as PWA. Additionally, a suitable stimulus for a PDT should always be culturally relevant to the target population. Therefore, we suggest that a new PDT must include a culturally appropriate colour photograph (CP).

AIMS

To investigate if a culturally appropriate CP elicits longer and more complex utterances than a culturally appropriate black-and-white LD from neurologically healthy native Bangla speakers.

METHODS & PROCEDURES

A total of 30 participants (mean age = 36.03 years) were recruited based on self-reports of no known impairments in cognition, language, vision and hearing. All were of middle socioeconomic status with at least 12 years of formal education. A culturally appropriate CP was selected showing multiple characters performing various functions. Later, an artist prepared the black-and-white LD of that CP. The elicited language samples using these two pictures were transcribed and coded following preset transcription and coding guidelines. The transcribed samples were further analysed using the Bangla adaptation of Systematic Analysis of Language Transcripts (SALT) software. To identify the differences in language production between these two picture types, investigators used four measurement variables: mean length of utterances (MLU), complexity index (CI), total number of words (TNW) and words per minute (WPM).

OUTCOMES & RESULTS

Of the four measures, only MLU showed a statistically significant difference between the CP and the black-and-white LD. CI demonstrated a strong correlation with MLU for the CP, which indicates that the participants who produced higher MLU for the CP also produced a higher CI for the CP. There were no significant differences between the two picture types for CI, TNW and WPM.

CONCLUSIONS & IMPLICATIONS

This study found that the grammatical complexity, as measured by MLU, of spontaneous language production of neurologically healthy adults was higher when a CP was used in a PDT. A CP may also be beneficial for PWA to produce complex language samples. What this paper adds What is already known on the subject There are studies on neurologically healthy individuals as well as on PWA that identified the impact of using different visuographic variables (colour and photograph) separately, which enhanced the picture comprehension and improved performances on associated language production tasks. To our knowledge, no studies have identified the combined impact of these two visuographic variables on spontaneous language production. Therefore, this initial study on neurologically healthy Bangla adults reports the impact of using a CP as a stimulus item for a PDT task to elicit spontaneous language samples. What this paper adds to existing knowledge This study reports that using a culturally appropriate CP for a PDT enhances the grammatical complexity of spontaneous language production of neurologically healthy adults. To our knowledge, this is the first study in Bangla that used the MLU as a measurement variable to analyse adults' spontaneous language production. What are the potential or actual clinical implications of this work? The development of future aphasia assessments should consider incorporating CPs as stimuli for PDTs, which may guide speech-language pathologists to provide accurate diagnoses for aphasia and related language disorders.

Visual rating versus volumetry of regional brain atrophy and longitudinal changes over a 5-year period in an elderly population

INTRODUCTION

The purpose of our study was to compare visual rating and volumetry of brain atrophy in an elderly population over a 5-year period and compare findings with cognitive test results.

MATERIALS AND METHODS

Two hundred and one subjects were examined with magnetic resonance imaging (MRI) of the brain. Visual rating and volumetry were performed in all subjects at ages 75 and 80. Cognitive function at both time points was assessed with the Mini-Mental State Examination (MMSE) and Trail Making Tests A and B (TMT-A and TMT-B). Changes in visual rating and volumetry were compared with changes in cognitive test.

RESULTS

A correlation was found between visual rating of medial temporal lobe atrophy (MTA) and hippocampal volumetry at both time points (rs = -.42 and rs = -.49, p < .001, respectively). The correlation between visual rating of posterior atrophy (PA); frontal atrophy (F-GCA) and volumetry of these brain regions was significant only at age 80 (rs = -.16, p = .02 for PA and rpb = .19, p = .006 for F-GCA). Visual rating showed only a minimal progression of regional atrophy at age 80, whereas volumetry showed 2%-5% decrease in volume depending on brain region. Performance in the MMSE, TMT-A, and TMT-B was virtually unchanged between ages 75 and 80.

CONCLUSION

We found a mild age-associated decrease in regional brain volumes in this healthy cohort with well-preserved cognitive functions. Visual assessment may not be sufficient for detecting mild progression of brain atrophy due to normal aging, whereas volumetry is more sensitive to capture these subtle changes.

Recollection-related hippocampal fMRI effects predict longitudinal memory change in healthy older adults

Prior fMRI studies have reported relationships between memory-related activity in the hippocampus and in-scanner memory performance, but whether such activity is predictive of longitudinal memory change remains unclear. Here, we administered a neuropsychological test battery to a sample of cognitively healthy older adults on three occasions, the second and third sessions occurring one month and three years after the first session. Structural and functional MRI data were acquired between the first two sessions. The fMRI data were derived from an associative recognition procedure and allowed estimation of hippocampal effects associated with both successful associative encoding and successful associative recognition (recollection). Baseline memory performance and memory change were evaluated using memory component scores derived from a principal components analysis of the neuropsychological test scores. Across participants, right hippocampal encoding effects correlated significantly with baseline memory performance after controlling for chronological age. Additionally, both left and right hippocampal associative recognition effects correlated negatively with longitudinal memory decline after controlling for age, and the relationship with the left hippocampal effect remained after also controlling for left hippocampal volume. Thus, in cognitively healthy older adults, the magnitude of hippocampal recollection effects appears to be a robust predictor of future memory change.

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

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

The quandary of covarying: A brief review and empirical examination of covariate use in structural neuroimaging studies on psychological variables

Although covarying for potential confounds or nuisance variables is common in psychological research, relatively little is known about how the inclusion of covariates may influence the relations between psychological variables and indices of brain structure. In Part 1 of the current study, we conducted a descriptive review of relevant articles from the past two years of NeuroImage in order to identify the most commonly used covariates in work of this nature. Age, sex, and intracranial volume were found to be the most commonly used covariates, although the number of covariates used ranged from 0 to 14, with 37 different covariate sets across the 68 models tested. In Part 2, we used data from the Human Connectome Project to investigate the degree to which the addition of common covariates altered the relations between individual difference variables (i.e., personality traits, psychopathology, cognitive tasks) and regional gray matter volume (GMV), as well as the statistical significance of values associated with these effect sizes. Using traditional and random sampling approaches, our results varied widely, such that some covariate sets influenced the relations between the individual difference variables and GMV very little, while the addition of other covariate sets resulted in a substantially different pattern of results compared to models with no covariates. In sum, these results suggest that the use of covariates should be critically examined and discussed as part of the conversation on replicability in structural neuroimaging. We conclude by recommending that researchers pre-register their analytic strategy and present information on how relations differ based on the inclusion of covariates.

Age-Related Differences in Brain Morphology and the Modifiers in Middle-Aged and Older Adults

Brain structural morphology differs with age. This study examined age-differences in surface-based morphometric measures of cortical thickness, volume, and surface area in a well-defined sample of 8137 generally healthy UK Biobank participants aged 45-79 years. We illustrate that the complexity of age-related brain morphological differences may be related to the laminar organization and regional evolutionary history of the cortex, and age of about 60 is a break point for increasing negative associations between age and brain morphology in Alzheimer's disease (AD)-prone areas. We also report novel relationships of age-related cortical differences with individual factors of sex, cognitive functions of fluid intelligence, reaction time and prospective memory, cigarette smoking, alcohol consumption, sleep disruption, genetic markers of apolipoprotein E, brain-derived neurotrophic factor, catechol-O-methyltransferase, and several genome-wide association study loci for AD and further reveal joint effects of cognitive functions, lifestyle behaviors, and education on age-related cortical differences. These findings provide one of the most extensive characterizations of age associations with major brain morphological measures and improve our understanding of normal structural brain aging and its potential modifiers.

Meta-analysis of cognitive functioning in patients following kidney transplantation

Background

There is mixed evidence regarding the nature of cognitive function in patients who have undergone renal transplantation. The aim of this meta-analysis was to examine which cognitive domains are impacted following kidney transplantation and how performance compares with non-transplanted patients or healthy controls/normative data.

Method

A systematic search was conducted using keywords within three databases (Embase, MEDLINE and PsychINFO), yielding 458 unique studies, 10 of which met the inclusion criteria. Neuropsychological tests were grouped into nine cognitive domains and three separate analyses were undertaken within each domain: (i) within subjects pre- versus post-transplant, (ii) transplanted versus non-transplanted patients and (iii) transplanted versus healthy matched controls and standardized normative data.

Results

Transplanted patients showed moderate to large improvements in the domains of general cognitive status (g = 0.526), information and motor speed (g = 0.558), spatial reasoning (g = 0.376), verbal memory (g = 0.759) and visual memory (g = 0.690) when compared with their pre-operative scores. Test scores in the same five domains were significantly better in post-transplanted patients when compared with dialysis-dependant or conservatively managed chronic kidney disease patients. However, post-transplanted patients’ performance was significantly low compared with that of healthy controls (and standardized normative data) in the domains of executive functioning (g = −0.283), verbal fluency (g = −0.657) and language (g = −0.573).

Conclusions

Two key issues arise from this review. First, domain-specific cognitive improvement occurs in patients after successful transplantation. Nevertheless, transplanted patients still performed significantly below healthy controls in some domains. Second, there are important shortcomings in existing studies; the length of follow-up is typically short and only limited neuropsychological test batteries are employed. These factors are important in order to support the recovery of cognitive function among patients following renal transplant.

Robust estimation of sulcal morphology

While it is well established that cortical morphology differs in relation to a variety of inter-individual factors, it is often characterized using estimates of volume, thickness, surface area, or gyrification. Here we developed a computational approach for estimating sulcal width and depth that relies on cortical surface reconstructions output by FreeSurfer. While other approaches for estimating sulcal morphology exist, studies often require the use of multiple brain morphology programs that have been shown to differ in their approaches to localize sulcal landmarks, yielding morphological estimates based on inconsistent boundaries. To demonstrate the approach, sulcal morphology was estimated in three large sample of adults across the lifespan, in relation to aging. A fourth sample is additionally used to estimate test–retest reliability of the approach. This toolbox is now made freely available as supplemental to this paper: https://cmadan.github.io/calcSulc/.

Interference Control in Working Memory Is Associated with Ventrolateral Prefrontal Cortex Volume

Goal-irrelevant information may interfere with ongoing task activities if not controlled properly. Evidence suggests that the ability to control interference is connected mainly to the prefrontal cortex (pFC). However, it remains unclear whether gray matter (GM) volume in prefrontal regions influences individual differences in interference control (IC) and if these relationships are affected by aging. Using cross-sectional and longitudinal estimates over a 4- to 5-year period, we examined the relationship between relative IC scores, obtained from a 2-back working memory task, GM volumes, and performance in different cognitive domains. By identifying individuals with either no or high levels of interference, we demonstrated that participants with superior IC had larger volume of the ventrolateral pFC, regardless of participant demographics. The same pattern was observed both at baseline and follow-up. Cross-sectional estimates further showed that interference increased as a function of age, but interference did not change between baseline and follow-up. Similarly, across-sample associations between IC and pFC volume were found in the cross-sectional data, along with no longitudinal change-change relationships. Moreover, relative IC scores could be linked to composite scores of fluid intelligence, indicating that control of interference may relate to performance in expected cognitive domains. These results provide new evidence that a relative IC score can be related to volume of specific and relevant regions within pFC and that this relationship is not modulated by age. This supports a view that the GM volume in these regions plays a role in resisting interference during a working memory task.

Longitudinal Changes in the Cerebral Cortex Functional Organization of Healthy Elderly

Healthy aging is accompanied by disruptions in the functional modular organization of the human brain. Cross-sectional studies have shown age-related reductions in the functional segregation and distinctiveness of brain networks. However, less is known about the longitudinal changes in brain functional modular organization and their associations with aging-related cognitive decline. We examined age- and aging-related changes in functional architecture of the cerebral cortex using a dataset comprising a cross-sectional healthy young cohort of 57 individuals (mean ± SD age, 23.71 ± 3.61 years, 22 males) and a longitudinal healthy elderly cohort of 72 individuals (mean ± baseline age, 68.22 ± 5.80 years, 39 males) with 2-3 time points (18-24 months apart) of task-free fMRI data. We found both cross-sectional (elderly vs young) and longitudinal (in elderly) global decreases in network segregation (decreased local efficiency), integration (decreased global efficiency), and module distinctiveness (increased participation coefficient and decreased system segregation). At the modular level, whereas cross-sectional analyses revealed higher participation coefficient across all modules in the elderly compared with young participants, longitudinal analyses revealed focal longitudinal participation coefficient increases in three higher-order cognitive modules: control network, default mode network, and salience/ventral attention network. Cross-sectionally, elderly participants also showed worse attention performance with lower local efficiency and higher mean participation coefficient, and worse global cognitive performance with higher participation coefficient in the dorsal attention/control network. These findings suggest that healthy aging is associated with whole-brain connectome-wide changes in the functional modular organization of the brain, accompanied by loss of functional segregation, particularly in higher-order cognitive networks.SIGNIFICANCE STATEMENT Cross-sectional studies have demonstrated age-related reductions in the functional segregation and distinctiveness of brain networks. However, longitudinal aging-related changes in brain functional modular architecture and their links to cognitive decline remain relatively understudied. Using graph theoretical and community detection approaches to study task-free functional network changes in a cross-sectional young and longitudinal healthy elderly cohort, we showed that aging was associated with global declines in network segregation, integration, and module distinctiveness, and specific declines in distinctiveness of higher-order cognitive networks. Further, such functional network deterioration was associated with poorer cognitive performance cross-sectionally. Our findings suggest that healthy aging is associated with system-level changes in brain functional modular organization, accompanied by functional segregation loss particularly in higher-order networks specialized for cognition.

Cognitive aging is not created equally: differentiating unique cognitive phenotypes in "normal" adults

Age-related cognitive decline is a public health problem but highly diverse and difficult to predict. We captured nonoverlapping cognitive phenotypes in high-functioning adults and identified baseline factors differentiating trajectories. Three hundred fourteen functionally normal adults (M = 69 y) completed 2+ visits. Participants with sample-based longitudinal slopes in memory or processing speed less than -1 SD were classified as "declining" on that measure; 29 and 50 individuals had slopes less than -1 SD on processing speed or memory, respectively; 2.5% met criteria for both, who were excluded. At baseline, speed decliners demonstrated greater age, inflammation, and cognitive complaints compared with speed-stable adults; memory decliners were more likely to be male and had lower depressive symptoms, gray matter volumes, and white matter hyperintensities compared with memory-stable adults. Baseline speed, TNFα, and cognitive complaints accurately classified 96.3% of future speed decliners; baseline memory, sex, precuneal volume, and white matter hyperintensities accurately classified 88.5% of future memory decliners. There are discrete cognitive aging phenotypes reflecting nonoverlapping vulnerabilities in high-functioning adults. Early markers can predict cognition even within the "normal" spectrum and underscore therapeutic targets.

Lateral ventricle volume trajectories predict response inhibition in older age-A longitudinal brain imaging and machine learning approach

Objective

In a three-wave 6 yrs longitudinal study we investigated if the expansion of lateral ventricle (LV) volumes (regarded as a proxy for brain tissue loss) predicts third wave performance on a test of response inhibition (RI).

Participants and methods

Trajectories of left and right lateral ventricle volumes across the three waves were quantified using the longitudinal stream in Freesurfer. All participants (N = 74;48 females;mean age 66.0 yrs at the third wave) performed the Color-Word Interference Test (CWIT). Response time on the third condition of CWIT, divided into fast, medium and slow, was used as outcome measure in a machine learning framework. Initially, we performed a linear mixed-effect (LME) analysis to describe subject-specific trajectories of the left and right LV volumes (LVV). These features were input to a multinomial logistic regression classification procedure, predicting individual belongings to one of the three RI classes. To obtain results that might generalize, we evaluated the significance of a k-fold cross-validated f1-score with a permutation test, providing a p-value that approximates the probability that the score would be obtained by chance. We also calculated a corresponding confusion matrix.

Results

The LME-model showed an annual ∼ 3.0% LVV increase. Evaluation of a cross-validated score using 500 permutations gave an f1-score of 0.462 that was above chance level (p = 0.014). 56% of the fast performers were successfully classified. All these were females, and typically older than 65 yrs at inclusion. For the true slow performers, those being correctly classified had higher LVVs than those being misclassified, and their ages at inclusion were also higher.

Conclusion

Major contributions were: (i) a longitudinal design, (ii) advanced brain imaging and segmentation procedures with longitudinal data analysis, and (iii) a data driven machine learning approach including cross-validation and permutation testing to predict behaviour, solely from the individual’s brain “signatures” (LVV trajectories).