Cognitive decline is mediated by gray matter changes during middle age

Reduced Cortical Thickness Correlates of Cognitive Dysfunction in Post-COVID-19 Condition: Insights from a Long-Term Follow-up

BACKGROUND AND PURPOSE

There is a paucity of data on long-term neuroimaging findings from individuals who have developed the post-coronavirus 2019 (COVID-19) condition. Only 2 studies have investigated the correlations between cognitive assessment results and structural MR imaging in this population. This study aimed to elucidate the long-term cognitive outcomes of participants with the post-COVID-19 condition and to correlate these cognitive findings with structural MR imaging data in the post-COVID-19 condition.

MATERIALS AND METHODS

A cohort of 53 participants with the post-COVID-19 condition underwent 3T brain MR imaging with T1 and FLAIR sequences obtained a median of 1.8 years after Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) infection. A comprehensive neuropsychological battery was used to assess several cognitive domains in the same individuals. Correlations between cognitive domains and whole-brain voxel-based morphometry were performed. Different ROIs from FreeSurfer were used to perform the same correlations with other neuroimaging features.

RESULTS

According to the Frascati criteria, more than one-half of the participants had deficits in the attentional (55%, n = 29) and executive (59%, n = 31) domains, while 40% (n = 21) had impairment in the memory domain. Only 1 participant (1.89%) showed problems in the visuospatial and visuoconstructive domains. We observed that reduced cortical thickness in the left parahippocampal region (t(48) = 2.28, P = .03) and the right caudal-middle-frontal region (t(48) = 2.20, P = .03) was positively correlated with the memory domain.

CONCLUSIONS

Our findings suggest that cognitive impairment in individuals with the post-COVID-19 condition is associated with long-term alterations in the structure of the brain. These macrostructural changes may provide insight into the nature of cognitive symptoms.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

The neurobiological effects of mind-body exercise: a systematic review and meta-analysis of neuroimaging studies

The neurobiological effects of mind-body exercise on brain activation, functional neural connections and structural changes in the brain remain elusive. This systematic review and coordinate-based meta-analysis investigated the changes in resting-state and task-based brain activation, as well as structural brain changes before and after mind-body exercise compared to waitlist or active controls based on published structural or functional magnetic resonance imaging randomized controlled trials or cross-sectional studies. Electronic database search and manual search in relevant publications yielded 34 empirical studies with low-to-moderate risk of bias (assessed by Cochrane risk-of-bias tool for randomized trials or Joanna Briggs Institute's critical appraisal checklist for analytical cross-sectional studies) that fulfilled the inclusion criteria, with 26 studies included in the narrative synthesis and 8 studies included in the meta-analysis. Coordinate-based meta-analysis showed that, while mind-body exercise enhanced the activation of the left anterior cingulate cortex within the default mode network (DMN), it induced more deactivation in the left supramarginal gyrus within the ventral attention network (uncorrected ps < 0.05). Meta-regression with duration of mind-body practice as a factor showed that, the activation of right inferior parietal gyrus within the DMN showed a positive association with increasing years of practice (voxel-corrected p < 0.005). Although mind-body exercise is shown to selectively modulate brain functional networks supporting attentional control and self-awareness, the overall certainty of evidence is limited by small number of studies. Further investigations are needed to understand the effects of both short-term and long-term mind-body exercise on structural changes in the brain.PROSPERO registration number: CRD42021248984.

Differential response to donepezil in MRI subtypes of mild cognitive impairment

BACKGROUND

Donepezil is an approved therapy for the treatment of Alzheimer's disease (AD). Results across clinical trials have been inconsistent, which may be explained by design-methodological issues, the pathophysiological heterogeneity of AD, and diversity of included study participants. We investigated whether response to donepezil differs in mild cognitive impaired (MCI) individuals demonstrating different magnetic resonance imaging (MRI) subtypes.

METHODS

From the Hippocampus Study double-blind, randomized clinical trial, we included 173 MCI individuals (donepezil = 83; placebo = 90) with structural MRI data, at baseline and at clinical follow-up assessments (6-12-month). Efficacy outcomes were the annualized percentage change (APC) in hippocampal, ventricular, and total grey matter volumes, as well as in the AD cortical thickness signature. Participants were classified into MRI subtypes as typical AD, limbic-predominant, hippocampal-sparing, or minimal atrophy at baseline. We primarily applied a subtyping approach based on continuous scale of two subtyping dimensions. We also used the conventional categorical subtyping approach for comparison.

RESULTS

Donepezil-treated MCI individuals showed slower atrophy rates compared to the placebo group, but only if they belonged to the minimal atrophy or hippocampal-sparing subtypes. Importantly, only the continuous subtyping approach, but not the conventional categorical approach, captured this differential response.

CONCLUSIONS

Our data suggest that individuals with MCI, with hippocampal-sparing or minimal atrophy subtype, may have improved benefit from donepezil, as compared with MCI individuals with typical or limbic-predominant patterns of atrophy. The newly proposed continuous subtyping approach may have advantages compared to the conventional categorical approach. Future research is warranted to demonstrate the potential of subtype stratification for disease prognosis and response to treatment.

TRIAL REGISTRATION

ClinicalTrial.gov NCT00403520. Submission Date: November 21, 2006.

The need to change: Is there a critical role of midlife adaptation in mental health later in life?

Although late-life depression (LLD) is a serious health problem and more common than dementia in people over 60, it is underdiagnosed and undertreated. The cognitive-emotional etiology of LLD is particularly poorly understood. This is in contrast to the now extensive literature from psychology and cognitive neuroscience on the characteristics of emotionally healthy aging. This research consistently shows a change in emotional processing in older adults that is modulated by prefrontal regulation. Lifespan theories explain this change in terms of neurocognitive adaptation to limited opportunities and resources that typically occur in the second half of life. Epidemiological data on an increase in well-being after a low point around age 50 suggest that the majority of people seem quite capable of making this adaptation, even though empirical evidence for a causal modulation of this so called 'paradox of aging' and for the role of the midlife dip is still lacking. Intriguingly, LLD is associated with deficits in emotional, cognitive, and prefrontal functions similar to those shown to be crucial for healthy adaptation. Suspected causes of these deficits, such as white matter lesions or affective instability, become apparent as early as midlife when internal and external changes as well as daily challenges set in. Based on these findings, we propose that some individuals who develop depression at older ages may not have been able to successfully implement self-regulatory adaptation at midlife. Here, we review the current evidence and theories on successful aging, the neurobiology of LLD, and well-being across the lifespan. Drawing on recent advances in lifespan theories, emotion regulation research, and cognitive neuroscience, we propose a model of successful versus unsuccessful adaptation that emphasizes the increasing need for implicit habitual control and resource-based regulatory choice during midlife.

Tooth loss, body mass index and cognitive function among middle-aged and older adults in China: Does gender matter?

BACKGROUND

Previous studies have shown a longitudinal association between tooth loss and cognitive function. Body mass index (BMI) is an essential applicable indicator of health status screening. However, the underlying mechanism among these factors remains unclear. This study aimed to determine the mediating role of BMI in the tooth loss-cognition relationship by gender among Chinese middle-aged and older adults.

METHODS

This is a prospective and cohort study. We used three waves of follow-up data (2011, 2013, and 2015) from the China Health and Retirement Longitudinal Survey, including 10,013 participants aged 45 years or above. Cognitive function was evaluated by Telephone Interview of Cognitive Status, words recall, and figure drawing. The cross-lagged panel model was applied to test the hypothesized model.

RESULTS

Tooth loss is associated with higher BMI and lower level of cognitive function. We found significant total effects (B = -0.017, P = 0.008), direct effect (B = -0.015, P = 0.022) and indirect effects (B = -0.002, P = 0.010) of tooth loss on cognition mediated through BMI only among middle-aged and older men. For middle-aged and older women, the total effect (B = -0.010, P = 0.125) and direct effect (B = -0.007, P = 0.249) were no more significant.

CONCLUSIONS

The longitudinal association between tooth loss and cognition was primarily indirect through BMI among middle-aged Chinese males but not women. Public health authorities should remind middle-aged and older males with tooth loss and high BMI to participate in timely medical checkups for improving cognition.

Evidence of validity based on the relation to other variables and inter-rater reliability of the Cognitive Screening (TRIACOG) for adults with cerebrovascular diseases

This study presents evidence of validity and reliability of the results obtained with the Cognitive Screening (TRIACOG) to evaluate post-stroke adults. The TRIACOG assesses orientation memory, language, arithmetic, praxis, information processing speed, and executive functions. A total of 126 post-stroke adults (M = 63.50; SD = 13.28 years old) and 126 neurologically healthy adults (M = 61.97; SD = 11.48 years old) participated in the study. Performance on the TRIACOG was positively correlated with scores on the Montreal Cognitive Assessment-Basic (MoCA-B), schooling, and reading and writing habits, and negatively correlated with the NIHSS and Rankin scales. Post-stroke adults scored lower and took longer to complete the instrument than neurologically healthy adults. Inter-rater agreement was achieved in scoring the TRIACOG. The TRIACOG presents evidence of validity based on its relationships to other variables (criterion and convergent) and on response processes, in addition to presenting reliability evidence established by inter-rater agreement. We expect that the TRIACOG will be employed by health workers in hospital settings, health units, and medical offices.

The block design subtest of the Wechsler adult intelligence scale as a possible non-verbal proxy of cognitive reserve

Objectives

To investigate the potential of the Block design subtest of the Wechsler Adults Intelligence Scale as a non-verbal proxy of cognitive reserve.

Method

A total of 391 cognitively unimpaired participants were included in this study. The association between the Block design subtest and the Information subtest (an established verbal proxy of cognitive reserve) from the WAIS, as well as the association of the two subtests with a Cognitive Reserve Questionnaire (CRQ) were tested. In addition, multiple linear regression models were conducted to investigate the association of the Block design and Information subtests with cognitive performance. The capacity of the Block design subtest to minimize the negative effect of an older age over cognitive performance was also assessed and this effect was compared with that of the Information subtest. The four cognitive domains included were: verbal memory, visual-visuospatial memory, executive-premotor functions and processing speed.

Results

The Block design subtest correlated positively with both the Information subtest and the CRQ. A statistically significant association was observed between the Block design subtest and all four cognitive domains. Higher scores in the Block design subtest minimized the negative effect of aging on the cognitive domains of visual-visuospatial memory and executive-premotor functions, in a similar way to the results obtained for the Information subtest.

Conclusion

The Block design subtest is significantly correlated with two established proxies of cognitive reserve: it correlates with cognitive performance and high scores in Block design have the capacity to minimize the negative effect of an older age on cognitive performance. Therefore, the results suggest that the corrected Block design subtest could be considered as a non-verbal proxy of cognitive reserve.

Navigational Experience and the Preservation of Spatial Abilities into Old Age Among a Tropical Forager-Farmer Population

Navigational performance responds to navigational challenges, and both decline with age in Western populations as older people become less mobile. But mobility does not decline everywhere; Tsimané forager-farmers in Bolivia remain highly mobile throughout adulthood, traveling frequently by foot and dugout canoe for subsistence and social visitation. We, therefore, measured both natural mobility and navigational performance in 305 Tsimané adults, to assess differences with age and to test whether greater mobility was related to better navigational performance across the lifespan. Daily mobility was measured by GPS tracking, regional mobility through interview, navigational performance through pointing accuracy and perspective taking in environmental space, and mental rotation by a computerized task. Although mental rotation and spatial perspective taking declined with age, mobility and pointing accuracy remained high from mid-life through old age. Greater regional mobility was associated with greater accuracy at pointing and perspective taking, suggesting that spatial experience at environmental scales may help maintain navigational performance in later adulthood.

Proportional Changes in Cognitive Subdomains During Normal Brain Aging

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

Predicting Age From Behavioral Test Performance for Screening Early Onset of Cognitive Decline

Background: Neuronal reactions and cognitive processes slow down during aging. The onset, rate, and extent of changes vary considerably from individual to individual. Assessing the changes throughout the lifespan is a challenging task. No existing test covers all domains, and batteries of tests are administered. The best strategy is to study each functional domain separately by applying different behavioral tasks whereby the tests reflect the conceptual structure of cognition. Such an approach has limitations that are described in the article. Objective: Our aim was to improve the diagnosis of early cognitive decline. We estimated the onset of cognitive decline in a healthy population, using behavioral tests, and predicted the age group of an individual. The comparison between the predicted ("cognitive") and chronological age will contribute to the early diagnosis of accelerated aging. Materials and Methods: We used publicly available datasets (POBA, SSCT) and Pearson correlation coefficients to assess the relationship between age and tests results, Kruskal-Wallis test to compare distribution, clustering methods to find an onset of cognitive decline, feature selection to enhance performance of the clustering algorithms, and classification methods to predict an age group from cognitive tests results. Results: The major results of the psychophysiological tests followed a U-shape function across the lifespan, which reflected the known inverted function of white matter volume changes. Optimal values were observed in those aged over 35 years, with a period of stability and accelerated decline after 55-60 years of age. The shape of the age-related variance of the performance of major cognitive tests was linear, which followed the trend of lifespan gray matter volume changes starting from adolescence. There was no significant sex difference in lifelong dynamics of major tests estimates. The performance of the classification model for identifying subject age groups was high. Conclusions: ML models can be designed and utilized as computer-aided detectors of neurocognitive decline. Our study demonstrated great promise for the utility of classification models to predict age-related changes. These findings encourage further explorations combining several tests from the cognitive and psychophysiological test battery to derive the most reliable set of tests toward the development of a highly-accurate ML model.

Functional Connectivity and Compensation of Phonemic Fluency in Aging

Neural compensatory mechanisms associated with broad cognitive abilities have been studied. However, those associated with specific cognitive subdomains (e.g., verbal fluency) remain to be investigated in healthy aging. Here, we delineate: (a) neural substrates of verbal (phonemic) fluency, and (b) compensatory mechanisms mediating the association between these neural substrates and phonemic fluency. We analyzed resting-state functional magnetic resonance imaging from 133 right-handed, cognitively normal individuals who underwent the Controlled Oral Word Association Test (COWAT) to record their phonemic fluency. We evaluated functional connectivity in an established and extended language network comprising Wernicke, Broca, thalamic and anti-correlated modules. (a) We conducted voxel-wise multiple linear regression to identify the brain areas associated with phonemic fluency. (b) We used mediation effects of cognitive reserve, measured by the Wechsler Adult Intelligence Scale—Information subtest, upon the association between functional connectivity and phonemic fluency tested to investigate compensation. We found that: (a) Greater functional connectivity between the Wernicke module and brain areas within the anti-correlated module was associated with better performance in phonemic fluency, (b) Cognitive reserve was an unlikely mediator in younger adults. In contrast, cognitive reserve was a partial mediator of the association between functional connectivity and phonemic fluency in older adults, likely representing compensation to counter the effect of aging. We conclude that in healthy aging, higher performance in phonemic fluency at older ages could be attributed to greater functional connectivity partially facilitated by higher cognitive reserve, presumably reflecting compensatory mechanisms to minimize the effect of aging.

Two-Year Follow-Up Study of the Relationship Between Brain Structure and Cognitive Control Function Across the Adult Lifespan

Age-related decline in cognitive control and general slowing are prominent phenomena in aging research. These declines in cognitive functions have been shown to also involve age-related decline in brain structure. However, most evidence in support of these associations is based on cross-sectional data. Therefore, the aim of this study is to contrast cross-sectional and longitudinal analyses to re-examine if the relationship between age-related brain structure and cognitive function are similar between the two approaches. One hundred and two participants completed two sessions with an average interval of 2 years. All participants were assessed by questionnaires, a series of cognitive tasks, and they all underwent neuroimaging acquisition. The main results of this study show that the majority of the conclusions regarding age effect in cognitive control function and processing speed in the literature can be replicated based on the cross-sectional data. Conversely, when we followed up individuals over an average interval of 2 years, then we found much fewer significant relationships between age-related change in gray matter structure of the cognitive control network and age-related change in cognitive control function. Furthermore, there was no "initial age" effect in the relationships between age-related changes in brain structure and cognitive function. This finding suggests that the "aging" relationship between brain structure and cognitive function over a short period of time are independent of "initial age" difference at time point 1. The result of this study warrants the importance of longitudinal research for aging studies to elucidate actual aging processes on cognitive control function.

Cortical Networks Underpinning Compensation of Verbal Fluency in Normal Aging

Elucidating compensatory mechanisms underpinning phonemic fluency (PF) may help to minimize its decline due to normal aging or neurodegenerative diseases. We investigated cortical brain networks potentially underpinning compensation of age-related differences in PF. Using graph theory, we constructed networks from measures of thickness for PF, semantic, and executive–visuospatial cortical networks. A total of 267 cognitively healthy individuals were divided into younger age (YA, 38–58 years) and older age (OA, 59–79 years) groups with low performance (LP) and high performance (HP) in PF: YA-LP, YA-HP, OA-LP, OA-HP. We found that the same pattern of reduced efficiency and increased transitivity was associated with both HP (compensation) and OA (aberrant network organization) in the PF and semantic cortical networks. When compared with the OA-LP group, the higher PF performance in the OA-HP group was associated with more segregated PF and semantic cortical networks, greater participation of frontal nodes, and stronger correlations within the PF cortical network. We conclude that more segregated cortical networks with strong involvement of frontal nodes seemed to allow older adults to maintain their high PF performance. Nodal analyses and measures of strength were helpful to disentangle compensation from the aberrant network organization associated with OA.

Comparing different approaches for operationalizing subjective cognitive decline: impact on syndromic and biomarker profiles

Subjective cognitive decline (SCD) has been proposed as a risk factor for future cognitive decline and dementia. Given the heterogeneity of SCD and the lack of consensus about how to classify this condition, different operationalization approaches still need to be compared. In this study, we used the same sample of individuals to compare  different SCD operationalization approaches. We included 399 cognitively healthy individuals from a community-based cohort. SCD was assessed through nine questions about memory and non-memory subjective complaints. We applied four approaches to operationalize SCD: two hypothesis-driven approaches and two data-driven approaches. We characterized the resulting groups from each operationalization approach using multivariate methods on comprehensive demographic, clinical, cognitive, and neuroimaging data. We identified two main phenotypes: an amnestic phenotype characterized by an Alzheimer's Disease (AD) signature pattern of brain atrophy; and an anomic phenotype, which was mainly related to cerebrovascular pathology. Furthermore, language complaints other than naming helped to identify a subgroup with subclinical cognitive impairment and difficulties in activities of daily living. This subgroup also showed an AD signature pattern of atrophy. The identification of SCD phenotypes, characterized by different syndromic and biomarker profiles, varies depending on the operationalization approach used. In this study we discuss how these findings may be used in clinical practice and research.

The developmental trajectories of executive function from adolescence to old age

Executive functions demonstrate variable developmental and aging profiles, with protracted development into early adulthood and declines in older age. However, relatively few studies have specifically included middle-aged adults in investigations of age-related differences in executive functions. This study explored the age-related differences in executive function from late childhood through to old age, allowing a more informed understanding of executive functions across the lifespan. Three hundred and fifty participants aged 10 to 86 years-old completed a battery of tasks assessing the specific roles of inhibitory control, working memory, cognitive flexibility, and planning. Results highlighted continued improvement in working memory capacity across adolescence and into young adulthood, followed by declines in both working memory and inhibitory control, beginning from as early as 30-40 years old and continuing into older age. Analyses of planning abilities showed continued improvement across adolescence and into young adulthood, followed by a decline in abilities across adulthood, with a small (positive) change in older age. Interestingly, a dissociation was found for cognitive flexibility; switch costs decreased, yet mixing costs increased across the lifespan. The results provide a description of the developmental differences in inhibitory control, working memory, cognitive flexibility and planning, above any effects of IQ or SES, and highlight the importance of including middle-aged adults in studies seeking to establish a more comprehensive picture of age-related differences in executive function.

Cognitive reserve and network efficiency as compensatory mechanisms of the effect of aging on phonemic fluency

Compensation in cognitive aging is a topic of recent interest. However, factors contributing to cognitive compensation in functions such as phonemic fluency (PF) are not completely understood. Using cross-sectional data, we investigated cognitive reserve (CR) and network efficiency in young (32-58 years) versus old (59-84 years) individuals with high versus low performance in PF. ANCOVA was used to investigate the interaction between CR, age, and performance in PF. Random forest and graph theory analyses were conducted to study the contribution of cognition to PF and efficiency measures, respectively. Higher CR increased performance in PF and reduced age-related differences in PF. A slightly higher number of cognitive functions contributed to performance in high CR groups. The networks were more integrated in high CR individuals, both in the older age and high-performance groups. The strength and segregation of the networks were decreased in high-performance groups with high CR. We conclude that PF decreases less with age in individuals with higher CR, possibly due to a greater capacity to recruit non-linguistic cognitive networks, and efficient use of language networks, thereby integrating information in a rapid way across less fragmented networks. High CR and network efficiency seem to be important factors for cognitive compensation.

Association between tea consumption and cognitive impairment in middle-aged and older adults

Background

Biologic studies have suggested that tea may have neuroprotective activity. However, tea’s protective effect on cognitive function is controversial in human epidemiological studies, and no data, including the middle-aged, are available. The objective of this study was to investigate the association of habit, frequency, and types of tea consumption with incident cognitive impairment in middle-aged and older adults.

Methods

Data from the Asymptomatic Polyvascular Abnormalities in Community study were used (aged over 40y). We gathered information on tea consumption, including habit, frequency, and types, via a standardized questionnaire and assessed cognitive function by Mini-Mental State Examination (MMSE) and/or Montreal Cognitive Assessment (MoCA). Three thousand eight hundred sixty-eight and 806 participants were selected in MMSE and MoCA subgroups. Multivariate logistic regression models were utilized to examine associations between tea consumption and cognitive impairment in middle-aged and older participants.

Results

In MMSE analyses, after adjustment for potential confounding factors, habitual (odds ratio (OR) 0.47, [95% confidence interval (CI) 0.33–0.68], p < 0.001) and high frequency (p trend < 0.001) of tea intake were associated with a lower risk of cognitive impairment. The risk of cognitive impairment was lower in green tea consumption (OR 0.36, [95% CI 0.22–0.61], p < 0.001) than other types (OR 0.59, [95% CI 0.38–0.91], p = 0.017). In MoCA analyses, we got similar results.

Conclusions

Habitual tea consumption, especially high-frequency and green tea consumption, was significantly associated with a lower prevalence of cognitive impairment in middle-aged and older individuals.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-020-01848-6.

Reversal learning in young and middle-age neurotypicals: Individual difference reaction time considerations

Reversal learning is frequently used to assess components of executive function that contribute to understanding age-related cognitive differences. Reaction time (RT) is less characterized in the reversal learning literature, perhaps due to the daunting task of analyzing the entire RT distribution, but has been deemed a generally sensitive measure of cognitive aging. The current study extends our prior work to further characterize distributional properties of the reversal RT distribution and to distinguish groups of individuals with fractionated profiles of performance, which may be of clinical importance within the context of cognitive aging. Participant sample included young (n = 43) and community-dwelling, healthy, middle-aged (n = 139) adults. To explore individual differences, recursive partitioning analysis achieved a high classification rate by specifying decision tree rules that split participants into young and middle-aged groups. Mu (μ, efficient RT) was the most successful parameter in distinguishing age groups while sigma ( σ ) and tau ( τ , ex-Gaussian indices of intra-individual variability) revealed more subtle individual differences. Accuracy measures did not contribute to separating the groups, suggesting that fractionated components of RT, as opposed to accuracy, can distinguish differences between young and middle-aged participants.

Cognitive compensatory mechanisms in normal aging: a study on verbal fluency and the contribution of other cognitive functions

Verbal fluency has been widely studied in cognitive aging. However, compensatory mechanisms that maintain its optimal performance with increasing age are not completely understood. Using cross-sectional data, we investigated differentiation and dedifferentiation processes in verbal fluency across the lifespan by analyzing the association between verbal fluency and numerous cognitive measures within four age groups (N=446): early middle-age (32-45 years), late middle-age (46-58 years), early elderly (59-71 years), and late elderly (72-84 years). ANCOVA was used to investigate the interaction between age and fluency modality. Random forest models were conducted to study the contribution of cognition to semantic, phonemic, and action fluency. All modalities declined with increasing age, but semantic fluency was the most vulnerable to aging. The most prominent reduction in performance was observed during the transition from middle-age to early elderly, when cognitive variables stopped contributing (differentiation), and new cognitive variables started contributing (dedifferentiation). Lexical access, processing speed, and executive functions were among the most contributing functions. We conclude that the association between age and verbal fluency is masked by age-specific influences of other cognitive functions. Differentiation and dedifferentiation processes can coexist. This study provides important data for better understanding of cognitive aging and compensatory processes.

Fully bayesian longitudinal unsupervised learning for the assessment and visualization of AD heterogeneity and progression

Tau pathology and brain atrophy are the closest correlate of cognitive decline in Alzheimer's disease (AD). Understanding heterogeneity and longitudinal progression of atrophy during the disease course will play a key role in understanding AD pathogenesis. We propose a framework for longitudinal clustering that simultaneously: 1) incorporates whole brain data, 2) leverages unequal visits per individual, 3) compares clusters with a control group, 4) allows for study confounding effects, 5) provides cluster visualization, 6) measures clustering uncertainty. We used amyloid-β positive AD and negative healthy subjects, three longitudinal structural magnetic resonance imaging scans (cortical thickness and subcortical volume) over two years. We found three distinct longitudinal AD brain atrophy patterns: one typical diffuse pattern (n=34, 47.2%), and two atypical patterns: minimal atrophy (n=23 31.9%) and hippocampal sparing (n=9, 12.5%). We also identified outliers (n=3, 4.2%) and observations with uncertain classification (n=3, 4.2%). The clusters differed not only in regional distributions of atrophy at baseline, but also longitudinal atrophy progression, age at AD onset, and cognitive decline. A framework for the longitudinal assessment of variability in cohorts with several neuroimaging measures was successfully developed. We believe this framework may aid in disentangling distinct subtypes of AD from disease staging.

Subjective Cognitive Decline Below and Above the Age of 60: A Multivariate Study on Neuroimaging, Cognitive, Clinical, and Demographic Measures

Subjective cognitive complaints in cognitively normal individuals are a relevant predictor of Alzheimer's disease (AD), cerebrovascular disease, and age-related tauopathy. Complaints starting after the age of 60 increase the likelihood of preclinical AD. However, this criterion is arbitrary and current data show that neurodegenerative disorders likely start before that age. Further, data on the role of subjective complaints below the age of 60 in individuals qualifying for subjective cognitive decline (SCD) are lacking. We investigated the association of subjective cognitive complaints with an extensive number of neuroimaging, demographic, clinical, and cognitive measures in individuals fulfilling criteria for SCD below and above the age of 60. Nine complaints were scored in 416 individuals. Complaints were related to a higher load of white matter signal abnormalities, and this association was stronger the more subclinical changes in personality, interest, and drive were reported. In individuals <60 years, complaints were associated with lower global cognitive performance. In individuals ≥60 years, complaints were related to greater global brain atrophy and smaller total intracranial volume, and this association was stronger the more subclinical difficulties in activities of daily living were reported. Also, complaints were associated with increased depressive symptomatology irrespective of age. We conclude that complaints below the age of 60 may be associated with subtle signs of brain pathology. In the community, screening for risk of future cognitive decline should include subjective cognitive complaints, depressive symptomatology, and subclinical reduced cognition (<60 years)/activities of daily living (≥60 years), supported by basic neuroimaging examinations.

Sleep disturbance-related depressive symptom and brain volume reduction in shift-working nurses

Disturbed sleep is the most common effect of shift work. A large corpus of research indicates an association between sleep disturbance and depressive symptom in shift workers. In this study, we proposed the mediating role of grey matter (GM) structure in the relationship between sleep disturbance and depressive symptom. We collected structural MRI (sMRI) data as well as assessing the level of sleep disturbance and depressive symptom with the Pittsburgh Sleep disturbance Index and Zung Self-Rating Depression Scale, respectively, in 20 shift-working nurses and 19 day-working nurses. The shift-working nurses reported greater severity of sleep disturbance and depressive symptom, and furthermore, they exhibited reduced GM volume in the left postcentral gyrus (PostCG), right PostCG, right paracentral lobule, and left superior temporal gyrus (STG), compared to the day-working nurses. For each of the four brain regions, we formulated a mediation hypothesis by developing a mediation model that represents a causal chain between GM volume, sleep disturbance, and depressive symptom. Tests of the hypothesis on the mediation of GM volume revealed that inter-individual variations in left PostCG volume and left STG volume accounted for the influence of sleep disturbance on depressive symptom. These results suggest that structural alterations in PostCG and STG play an intervening role in the development of depressive symptom following sleep disturbance. We propose the need of considering neuroanatomical abnormalities in explaining and understanding symptomatic changes induced by sleep disturbance.

Cholinergic white matter pathways make a stronger contribution to attention and memory in normal aging than cerebrovascular health and nucleus basalis of Meynert

The integrity of the cholinergic system plays a central role in cognitive decline both in normal aging and neurological disorders including Alzheimer's disease and vascular cognitive impairment. Most of the previous neuroimaging research has focused on the integrity of the cholinergic basal forebrain, or its sub-region the nucleus basalis of Meynert (NBM). Tractography using diffusion tensor imaging data may enable modelling of the NBM white matter projections. We investigated the contribution of NBM volume, NBM white matter projections, small vessel disease (SVD), and age to performance in attention and memory in 262 cognitively normal individuals (39-77 years of age, 53% female). We developed a multimodal MRI pipeline for NBM segmentation and diffusion-based tracking of NBM white matter projections, and computed white matter hypointensities (WM-hypo) as a marker of SVD. We successfully tracked pathways that closely resemble the spatial layout of the cholinergic system as seen in previous post-mortem and DTI tractography studies. We found that high WM-hypo load was associated with older age, male sex, and lower performance in attention and memory. A high WM-hypo load was also associated with lower integrity of the cholinergic system above and beyond the effect of age. In a multivariate model, age and integrity of NBM white matter projections were stronger contributors than WM-hypo load and NBM volume to performance in attention and memory. We conclude that the integrity of NBM white matter projections plays a fundamental role in cognitive aging. This and other modern neuroimaging methods offer new opportunities to re-evaluate the cholinergic hypothesis of cognitive aging.

Subtypes of Alzheimer's Disease Display Distinct Network Abnormalities Extending Beyond Their Pattern of Brain Atrophy

Different subtypes of Alzheimer's disease (AD) with characteristic distributions of neurofibrillary tangles and corresponding brain atrophy patterns have been identified using structural magnetic resonance imaging (MRI). However, the underlying biological mechanisms that determine this differential expression of neurofibrillary tangles are still unknown. Here, we applied graph theoretical analysis to structural MRI data to test the hypothesis that differential network disruption is at the basis of the emergence of these AD subtypes. We studied a total of 175 AD patients and 81 controls. Subtyping was done using the Scheltens' scale for medial temporal lobe atrophy, the Koedam's scale for posterior atrophy, and the Pasquier's global cortical atrophy scale for frontal atrophy. A total of 89 AD patients showed a brain atrophy pattern consistent with typical AD; 30 patients showed a limbic-predominant pattern; 29 patients showed a hippocampal-sparing pattern; and 27 showed minimal atrophy. We built brain structural networks from 68 cortical regions and 14 subcortical gray matter structures for each AD subtype and for the controls, and we compared between-group measures of integration, segregation, and modular organization. At the global level, modularity was increased and differential modular reorganization was detected in the four subtypes. We also found a decrease of transitivity in the typical and hippocampal-sparing subtypes, as well as an increase of average local efficiency in the minimal atrophy and hippocampal-sparing subtypes. We conclude that the AD subtypes have a distinct signature of network disruption associated with their atrophy patterns and further extending to other brain regions, presumably reflecting the differential spread of neurofibrillary tangles. We discuss the hypothetical emergence of these subtypes and possible clinical implications.

Proposal for a hierarchical, multidimensional, and multivariate approach to investigate cognitive aging

Cognitive aging is highly complex. We applied a data-driven statistical method to investigate aging from a hierarchical, multidimensional, and multivariate approach. Orthogonal partial least squares to latent structures and hierarchical models were applied for the first time in a study of cognitive aging. The association between age and a total of 316 demographic, clinical, cognitive, and neuroimaging measures was simultaneously analyzed in 460 cognitively normal individuals (35-85 years). Age showed a strong association with brain structure, especially with cortical thickness in frontal and parietal association regions. Age also showed a fairly strong association with cognition. Although a strong association of age with executive functions and processing speed was captured as expected, the association of age with visual memory was stronger. Clinical measures were less strongly associated with age. Hierarchical and correlation analyses further showed these associations in a neuroimaging-cognitive-clinical order of importance. We conclude that orthogonal partial least square and hierarchical models are a promising approach to better understand the complexity in cognitive aging.

Cognitive Variability during Middle-Age: Possible Association with Neurodegeneration and Cognitive Reserve

Objective: Increased variability in cognition with age has been argued as an indication of pathological processes. Focusing on early detection of neurodegenerative disorders, we investigated variability in cognition in healthy middle-aged adults. In order to understand possible determinants of this variability, we also investigated associations with cognitive reserve, neuroimaging markers, subjective memory complaints, depressive symptomatology, and gender.

Method: Thirty-one 50 ± 2 years old individuals were investigated as target group and deviation was studied in comparison to a reference younger group of 30 individuals 40 ± 2 years old. Comprehensive neuropsychological and structural imaging protocols were collected. Brain regional volumes and cortical thickness were calculated with FreeSurfer, white matter hyperintensities with CASCADE, and mean diffusivity with FSL.

Results: Across-individuals variability showed greater dispersion in lexical access, processing speed, executive functions, and memory. Variability in global cognition correlated with, reduced cortical thickness in the right parietal-temporal-occipital association cortex, and increased mean diffusivity in the cingulum bundle and right inferior fronto-occipital fasciculus. A trend was also observed for the correlation between global cognition and hippocampal volume and female gender. All these associations were influenced by cognitive reserve. No correlations were found with subjective memory complaints, white matter hyperintensities and depressive symptomatology. Across-domains and across-tasks variability was greater in several executive components and cognitive processing speed.

Conclusion: Variability in cognition during middle-age is associated with neurodegeneration in the parietal–temporal–occipital association cortex and white matter tracts connecting this to the prefrontal dorsolateral cortex and the hippocampus. Moreover, this effect is influenced by cognitive reserve. Studying variability offers valuable information showing that differences do not occur in the same magnitude and direction across individuals, cognitive domains and tasks. These findings may have important implications for early detection of subtle cognitive impairment and clinical interpretation of deviation from normality.

Distinct subtypes of Alzheimer's disease based on patterns of brain atrophy: longitudinal trajectories and clinical applications

Atrophy patterns on MRI can reliably predict three neuropathological subtypes of Alzheimer’s disease (AD): typical, limbic-predominant, or hippocampal-sparing. A method to enable their investigation in the clinical routine is still lacking. We aimed to (1) validate the combined use of visual rating scales for identification of AD subtypes; (2) characterise these subtypes at baseline and over two years; and (3) investigate how atrophy patterns and non-memory cognitive domains contribute to memory impairment. AD patients were classified as either typical AD (n = 100), limbic-predominant (n = 33), or hippocampal-sparing (n = 35) by using the Scheltens’ scale for medial temporal lobe atrophy (MTA), the Koedam’s scale for posterior atrophy (PA), and the Pasquier’s global cortical atrophy scale for frontal atrophy (GCA-F). A fourth group with no atrophy was also identified (n = 30). 230 healthy controls were also included. There was great overlap among subtypes in demographic, clinical, and cognitive variables. Memory performance was more dependent on non-memory cognitive functions in hippocampal-sparing and the no atrophy group. Hippocampal-sparing and the no atrophy group showed less aggressive disease progression. Visual rating scales can be used to identify distinct AD subtypes. Recognizing AD heterogeneity is important and visual rating scales may facilitate investigation of AD heterogeneity in clinical routine.

Effect of educational status on performance of older adults in digital cognitive tasks: A systematic review

As people age, cognitive abilities may decline resulting in serious disabilities. Neuropsychological instruments can provide information on the cognitive state of older adults. Researchers worldwide have been using digital cognitive tests to assess cognitive domains.

OBJECTIVE

To determine whether educational status affects the performance of older adults on digital cognitive tasks.

METHODS

A systematic review of articles in English, Portuguese, or Spanish published in the last 5 years was conducted. The databases searched were SCOPUS, PubMed, Lilacs, Scielo and PsychInfo. The PRISMA method was used.

RESULTS

A total of 7,089 articles were initially retrieved. After search and exclusion with justification, seven articles were selected for further review.

CONCLUSION

The findings revealed that researchers using digital tasks generally employed paper-based tests to compare results. Also, no association between years of education and test performance was found. Finally, a dearth of studies using digital tests published by Brazilian researchers was evident.

Early Age-Related Functional Connectivity Decline in High-Order Cognitive Networks

As the world ages, it becomes urgent to unravel the mechanisms underlying brain aging and find ways of intervening with them. While for decades cognitive aging has been related to localized brain changes, growing attention is now being paid to alterations in distributed brain networks. Functional connectivity magnetic resonance imaging (fcMRI) has become a particularly useful tool to explore large-scale brain networks; yet, the temporal course of connectivity lifetime changes has not been established. Here, an extensive cross-sectional sample (21-85 years old, N = 887) from a public fcMRI database was used to characterize adult lifespan connectivity dynamics within and between seven brain networks: the default mode, salience, dorsal attention, fronto-parietal control, auditory, visual and motor networks. The entire cohort was divided into young (21-40 years, mean ± SD: 25.5 ± 4.8, n = 543); middle-aged (41-60 years, 50.6 ± 5.4, n = 238); and old (61 years and above, 69.0 ± 6.3, n = 106) subgroups. Correlation matrices as well as a mixed model analysis of covariance indicated that within high-order cognitive networks a considerable connectivity decline is already evident by middle adulthood. In contrast, a motor network shows increased connectivity in middle adulthood and a subsequent decline. Additionally, alterations in inter-network interactions are noticeable primarily in the transition between young and middle adulthood. These results provide evidence that aging-related neural changes start early in adult life.

Different reserve proxies confer overlapping and unique endurance to cortical thinning in healthy middle-aged adults

AIM

To investigate different proxies of brain and cognitive reserve as potential mediators of the effect of cortical thinning on cognition in healthy middle-aged adults.

METHODS

Eighty-two middle-aged individuals were included (mean(SD) age=45.1(3.9)years). Cortical thickness was calculated for multiple brain regions using FreeSurfer. Cognitive measures sensitive to early cognitive decline were selected, including Block Design from the Wechsler Adult Intelligence Scale-III (WAIS-III), Judgment of Line Orientation Test (JLOT), Color Trails Test (CTT), and first learning trial of TAVEC (the Spanish version of the California Verbal Learning Test, CVLT). Brain reserve was operationalized as total intracranial volume (TIV); and cognitive reserve was estimated by means of Years of Education, WAIS-III Vocabulary subtest, WAIS-III Information subtest, and a Cognitive Reserve Questionnaire (CRQ). Mediation effects were investigated with multiple linear regression and bootstrapping analysis.

RESULTS

Information and Vocabulary showed the greatest mediation capacity. All the observed mediations were positive indicating that higher levels of reserve attenuate the effect of reduced cortical thickness on cognition. Information, Vocabulary and TIV buffered the effect of frontal thinning on Block Design; Vocabulary and Years of Education buffered the effect of frontal thinning on JLOT; and CRQ buffered the effect of temporal thinning on CTT.

CONCLUSION

Higher reserve buffers the effect of cortical thinning on cognition in healthy middle-aged adults. The investigated proxies might be underpinned by slightly different neural networks. Advancing in the understanding of the influences of reserve in healthy middle-aged adults is crucial to facilitate early interventions.

Relationship between grey matter integrity and executive abilities in aging

This cross-sectional study was designed to investigate grey matter changes that occur in healthy aging and the relationship between grey matter characteristics and executive functioning. Thirty-six young adults (18-30 years old) and 43 seniors (60-75 years old) were included. A general executive score was derived from a large battery of neuropsychological tests assessing three major aspects of executive functioning (inhibition, updating and shifting). Age-related grey matter changes were investigated by comparing young and older adults using voxel-based morphometry and voxel-based cortical thickness methods. A widespread difference in grey matter volume was found across many brain regions, whereas cortical thinning was mainly restricted to central areas. Multivariate analyses showed age-related changes in relatively similar brain regions to the respective univariate analyses but appeared more limited. Finally, in the older adult sample, a significant relationship between global executive performance and decreased grey matter volume in anterior (i.e. frontal, insular and cingulate cortex) but also some posterior brain areas (i.e. temporal and parietal cortices) as well as subcortical structures was observed. Results of this study highlight the distribution of age-related effects on grey matter volume and show that cortical atrophy does not appear primarily in "frontal" brain regions. From a cognitive viewpoint, age-related executive functioning seems to be related to grey matter volume but not to cortical thickness. Therefore, our results also highlight the influence of methodological aspects (from preprocessing to statistical analysis) on the pattern of results, which could explain the lack of consensus in literature.

Measuring Information Processing Speed in Mild Cognitive Impairment: Clinical Versus Research Dichotomy

A substantial body of research evidence is indicative of disproportionately slowed information processing speed in a wide range of multi-trial, computer-based, neuroimaging- and electroencephalography-based reaction time (RT) tests in Alzheimer's disease and mild cognitive impairment (MCI). However, in what is arguably a dichotomy between research evidence and clinical practice, RT associated with different brain functions is rarely assessed as part of their diagnosis. Indeed, often only the time taken to perform a single, specific task, commonly the Trail making test (TMT), is measured. In clinical practice therefore, there can be a failure to assess adequately the integrity of the rapid, serial information processing and response, necessary for efficient, appropriate, and safe interaction with the environment. We examined whether a typical research-based RT task could at least match the TMT in differentiating amnestic MCI (aMCI) from cognitively healthy aging at group level. As aMCI is a heterogeneous group, typically containing only a proportion of individuals for whom aMCI represents the early stages of dementia, we examined the ability of each test to provide intra-group performance variation. The results indicate that as well as significant slowing in performance of the operations involved in TMT part B (but not part A), individuals with aMCI also experience significant slowing in RT compared to controls. The results also suggest that research-typical RT tests may be superior to the TMT in differentiating between cognitively healthy aging and aMCI at group level and in revealing the performance variability one would expect from an etiologically heterogeneous disorder such as aMCI.

Quantitative validation of a visual rating scale for frontal atrophy: associations with clinical status, APOE e4, CSF biomarkers and cognition

OBJECTIVES

To validate a visual rating scale of frontal atrophy with quantitative imaging and study its association with clinical status, APOE ε4, CSF biomarkers, and cognition.

METHODS

The AddNeuroMed and ADNI cohorts were combined giving a total of 329 healthy controls, 421 mild cognitive impairment patients, and 286 Alzheimer's disease (AD) patients. Thirty-four patients with frontotemporal dementia (FTD) were also included. Frontal atrophy was assessed with the frontal sub-scale of the global cortical atrophy scale (GCA-F) on T1-weighted images. Automated imaging markers of cortical volume, thickness, and surface area were evaluated. Manual tracing was also performed.

RESULTS

The GCA-F scale reliably reflects frontal atrophy, with orbitofrontal, dorsolateral, and motor cortices being the regions contributing most to the GCA-F ratings. GCA-F primarily reflects reductions in cortical volume and thickness, although it was able to detect reductions in surface area too. The scale showed significant associations with clinical status and cognition.

CONCLUSION

The GCA-F scale may have implications for clinical practice as supportive diagnostic tool for disorders demonstrating predominant frontal atrophy such as FTD and the executive presentation of AD. We believe that GCA-F is feasible for use in clinical routine for the radiological assessment of dementia and other disorders.

KEY POINTS

• The GCA-F visual rating scale reliably reflects frontal brain atrophy. • Orbitofrontal, dorsolateral, and motor cortices are the most contributing regions. • GCA-F shows significant associations with clinical status and cognition. • GCA-F may be supportive diagnostic tool for disorders demonstrating predominant frontal atrophy. • GCA-F may be feasible for use in radiological routine.

The Effect of Age Correction on Multivariate Classification in Alzheimer's Disease, with a Focus on the Characteristics of Incorrectly and Correctly Classified Subjects

The similarity of atrophy patterns in Alzheimer’s disease (AD) and in normal aging suggests age as a confounding factor in multivariate models that use structural magnetic resonance imaging (MRI) data. To study the effect and compare different age correction approaches on AD diagnosis and prediction of mild cognitive impairment (MCI) progression as well as investigate the characteristics of correctly and incorrectly classified subjects. Data from two multi-center cohorts were included in the study [AD = 297, MCI = 445, controls (CTL) = 340]. 34 cortical thickness and 21 subcortical volumetric measures were extracted from MRI. The age correction approaches involved: using age as a covariate to MRI-derived measures and linear detrending of age-related changes based on CTL measures. Orthogonal projections to latent structures was used to discriminate between AD and CTL subjects, and to predict MCI progression to AD, up to 36-months follow-up. Both age correction approaches improved models’ quality in terms of goodness of fit and goodness of prediction, as well as classification and prediction accuracies. The observed age associations in classification and prediction results were effectively eliminated after age correction. A detailed analysis of correctly and incorrectly classified subjects highlighted age associations in other factors: ApoE genotype, global cognitive impairment and gender. The two methods for age correction gave similar results and show that age can partially masks the influence of other aspects such as cognitive impairment, ApoE-e4 genotype and gender. Age-related brain atrophy may have a more important association with these factors than previously believed.

Prediction of brain age suggests accelerated atrophy after traumatic brain injury

Objective

The long-term effects of traumatic brain injury (TBI) can resemble observed in normal ageing, suggesting that TBI may accelerate the ageing process. We investigate this using a neuroimaging model that predicts brain age in healthy individuals and then apply it to TBI patients. We define individuals' differences in chronological and predicted structural "brain age," and test whether TBI produces progressive atrophy and how this relates to cognitive function.

Methods

A predictive model of normal ageing was defined using machine learning in 1,537 healthy individuals, based on magnetic resonance imaging–derived estimates of gray matter (GM) and white matter (WM). This ageing model was then applied to test 99 TBI patients and 113 healthy controls to estimate brain age.

Results

The initial model accurately predicted age in healthy individuals (r * 0.92). TBI brains were estimated to be "older," with a mean predicted age difference (PAD) between chronological and estimated brain age of 4.66 years (±10.8) for GM and 5.97 years (±11.22) for WM. This PAD predicted cognitive impairment and correlated strongly with the time since TBI, indicating that brain tissue loss increases throughout the chronic postinjury phase.

Interpretation

TBI patients' brains were estimated to be older than their chronological age. This discrepancy increases with time since injury, suggesting that TBI accelerates the rate of brain atrophy. This may be an important factor in the increased susceptibility in TBI patients for dementia and other age-associated conditions, motivating further research into the age-like effects of brain injury and other neurological diseases.

Differences in temporal order memory among young, middle-aged, and older adults may depend on the level of interference

Age-related changes in temporal order memory have been well documented in older adults; however, little is known about this ability during middle age. We tested healthy young, middle-aged, and older adults on a previously published visuospatial temporal order memory test involving high and low interference conditions. When interference was low, young and middle-aged adults did not differ, but both groups significantly outperformed older adults. However, when interference was high, significant differences were found among all three age groups. The data provide evidence that temporal order memory may begin to decline in middle age, particularly when temporal interference is high.

Decision making, central coherence and set-shifting: a comparison between Binge Eating Disorder, Anorexia Nervosa and Healthy Controls

BACKGROUND

Several studies have investigated the cognitive profile in patients with Anorexia Nervosa (AN) and Bulimia Nervosa (BN); on the contrary few studies have evaluated it in patients with Binge Eating Disorder (BED). The purpose of this study was to compare decision making, central coherence and set-shifting between BED and AN patients.

METHODS

A battery of neuropsychological tests including the Iowa Gambling Task (IGT), the Rey-Osterrieth Complex Figure Test (RCFT), the Wisconsin Card Sorting Test (WCST), the Trial Making Task (TMT) and the Hayling Sentence Completion Task (HSCT) were administered in a sample of 135 women (45 AN, 45 BED, 45 Healthy Controls [HC]). Furthermore, Beck Depression Inventory (BDI) was administered to evaluate depressive symptoms. Years of education, age, Body Mass Index (BMI) and depression severity were considered as covariates in statistical analyses.

RESULTS

BED and AN patients showed high rates of cognitive impairment compared to HC on the domains investigated; furthermore, the cognitive profile of BED patients was characterised by poorer decision making and cognitive flexibility compared to patients with AN. Cognitive performance was strongly associated with depressive symptoms.

CONCLUSIONS

In the present sample, two different neurocognitive profiles emerged: a strong cognitive rigidity and a central coherence based on the details was predominant in patients with AN, while a lack of attention and difficulty in adapting to changes in a new situation seemed to better describe patients with BED. The knowledge of the different cognitive profiles of EDs patients may be important for the planning their psychotherapeutic intervention.

Application of a MRI based index to longitudinal atrophy change in Alzheimer disease, mild cognitive impairment and healthy older individuals in the AddNeuroMed cohort

Cross sectional studies of patients at risk of developing Alzheimer disease (AD) have identified several brain regions known to be prone to degeneration suitable as biomarkers, including hippocampal, ventricular, and whole brain volume. The aim of this study was to longitudinally evaluate an index based on morphometric measures derived from MRI data that could be used for classification of AD and healthy control subjects, as well as prediction of conversion from mild cognitive impairment (MCI) to AD. Patients originated from the AddNeuroMed project at baseline (119 AD, 119 MCI, 110 controls (CTL)) and 1-year follow-up (62 AD, 73 MCI, 79 CTL). Data consisted of 3D T1-weighted MR images, demographics, MMSE, ADAS-Cog, CERAD and CDR scores, and APOE e4 status. We computed an index using a multivariate classification model (AD vs. CTL), using orthogonal partial least squares to latent structures (OPLS). Sensitivity, specificity and AUC were determined. Performance of the classifier (AD vs. CTL) was high at baseline (10-fold cross-validation, 84% sensitivity, 91% specificity, 0.93 AUC) and at 1-year follow-up (92% sensitivity, 74% specificity, 0.93 AUC). Predictions of conversion from MCI to AD were good at baseline (77% of MCI converters) and at follow-up (91% of MCI converters). MCI carriers of the APOE e4 allele manifested more atrophy and presented a faster cognitive decline when compared to non-carriers. The derived index demonstrated a steady increase in atrophy over time, yielding higher accuracy in prediction at the time of clinical conversion. Neuropsychological tests appeared less sensitive to changes over time. However, taking the average of the two time points yielded better correlation between the index and cognitive scores as opposed to using cross-sectional data only. Thus, multivariate classification seemed to detect patterns of AD changes before conversion from MCI to AD and including longitudinal information is of great importance.