The Default Mode Network in Healthy Aging and Alzheimer's Disease

In the past decade, a “default mode network” (DMN) has been highlighted in neuroimaging studies as a set of brain regions showing increased activity in task-free state compared to cognitively demanding task, and synchronized activity at rest. Changes within this network have been described in healthy aging as well as in Alzheimer's disease (AD) and populations at risk for AD, that is, amnestic Mild Cognitive Impairment (aMCI) patients and APOE-ε4 carriers. This is of particular interest in the context of early diagnosis and more generally for our understanding of the physiopathological mechanisms of AD. This paper gives an overview of the anatomical and physiological characteristics of this network as well as its relationships with cognition, before focusing on changes in the DMN over normal aging and Alzheimer's disease. While perturbations of the DMN have been consistently reported, especially within the posterior cingulate, further studies are needed to understand their clinical implication

Longitudinal brain metabolic changes from amnestic mild cognitive impairment to Alzheimer's disease.

International audienceA sensitive marker for monitoring progression of early Alzheimer's disease would help to develop and test new therapeutic strategies. The present study is aimed at investigating brain metabolism changes over time, as a potential monitoring marker, in patients with amnestic mild cognitive impairment, according to their clinical outcome (converters or non-converters), and in relation to their cognitive decline. Seventeen amnestic mild cognitive impairment patients underwent magnetic resonance imaging and 18FDG-positron emission tomography scans both at inclusion and 18 months later. Baseline and follow-up positron emission tomography data were corrected for partial volume effects and spatially normalized using magnetic resonance imaging data, scaled to the vermis and compared using SPM2. 'PET-PAC' maps reflecting metabolic per cent annual changes were created for correlation analyses with cognitive decline. In the whole sample, the greatest metabolic decrease concerned the posterior cingulate-precuneus area. Converters had significantly greater metabolic decrease than non-converters in two ventro-medial prefrontal areas, the subgenual (BA25) and anterior cingulate (BA24/32). PET-PAC in BA25 and BA24/32 combined allowed complete between-group discrimination. BA25 PET-PAC significantly correlated with both cognitive decline and PET-PAC in the hippocampal region and temporal pole, while BA24/32 PET-PAC correlated with posterior cingulate PET-PAC. Finally, the metabolic change in BA8/9/10 was inversely related to that in BA25 and showed relative increase with cognitive decline, suggesting that compensatory processes may occur in this dorso-medial prefrontal region. The observed ventro-medial prefrontal disruption is likely to reflect disconnection from the hippocampus, both indirectly through the cingulum bundle and posterior cingulate cortex for BA24/32, and directly through the uncinate fasciculus for BA25. Altogether, our findings emphasize the potential of 18FDG-positron emission tomography for monitoring early Alzheimer's disease progression

Effect of cognitive reserve on the association between slow wave sleep and cognition in community-dwelling older adults

Sleep, especially slow wave sleep (SWS), is essential for cognitive functioning and is reduced in aging. The impact of sleep quality on cognition is variable, especially in aging. Cognitive reserve (CR) may be an important modulator of these effects. We aimed at investigating this question to better identify individuals in whom sleep disturbances might have greater behavioral consequences. Polysomnography and neuropsychological assessments were performed in 135 cognitively intact older adults (mean age ± SD: 69.4 ± 3.8y) from the Age-Well randomized controlled trial (baseline data). Two measures of cognitive engagement throughout life were used as CR proxies. Linear regression analyses were performed between the proportion of SWS, and executive function and episodic memory composite scores. Then, interaction analyses between SWS and CR proxies on cognition were conducted to assess the possible impact of CR on these links. SWS was positively associated with episodic memory, but not with executive function. CR proxies modulated the associations between SWS and both executive and episodic memory performance. Specifically, individuals with higher CR were able to maintain cognitive performance despite low amounts of SWS. This study provides the first evidence that CR may protect against the deleterious effects of age-related sleep changes on cognition

Exposure to negative socio-emotional events induces sustained alteration of resting-state brain networks in older adults.

peer reviewedBasic emotional functions seem well preserved in older adults. However, their reactivity to and recovery from socially negative events remain poorly characterized. To address this, we designed a 'task-rest' paradigm in which 182 participants from two independent experiments underwent functional magnetic resonance imaging while exposed to socio-emotional videos. Experiment 1 (N = 55) validated the task in young and older participants and unveiled age-dependent effects on brain activity and connectivity that predominated in resting periods after (rather than during) negative social scenes. Crucially, emotional elicitation potentiated subsequent resting-state connectivity between default mode network and amygdala exclusively in older adults. Experiment 2 replicated these results in a large older adult cohort (N = 127) and additionally showed that emotion-driven changes in posterior default mode network-amygdala connectivity were associated with anxiety, rumination and negative thoughts. These findings uncover the neural dynamics of empathy-related functions in older adults and help understand its relationship to poor social stress recovery

Effects of Meditation Training and Non-Native Language Training on Cognition in Older Adults: A Secondary Analysis of a Randomized Clinical Trial

IMPORTANCE: Nonpharmacological interventions are a potential strategy to maintain or promote cognitive functioning in older adults. OBJECTIVE: To investigate the effects of 18 months' meditation training and 18 months' non-native language training on cognition in older adults. DESIGN, SETTING, AND PARTICIPANTS: This study was a secondary analysis of the Age-Well trial, an 18-month, observer-masked, randomized clinical trial with 3 parallel arms. Eligible participants were community-dwelling adults aged 65 years and older residing in Caen, France. Participants were enrolled from November 24, 2016, to March 5, 2018, and randomly assigned (1:1:1) to meditation training, non-native language (English) training, or no intervention arms. Final follow-up was completed on February 6, 2020. Data were analyzed between December 2021 and November 2022. INTERVENTIONS: The 18-month meditation and non-native language training interventions were structurally equivalent and included 2-hour weekly group sessions, daily home practice of 20 minutes or longer, and 1 day of more intensive home practice. The no intervention group was instructed not to change their habits and to continue living as usual. MAIN OUTCOMES AND MEASURES: Cognition (a prespecified secondary outcome of the Age-Well trial) was assessed preintervention and postintervention via the Preclinical Alzheimer Cognitive Composite 5 (PACC5), and composites assessing episodic memory, executive function, and attention. RESULTS: Among 137 randomized participants, 2 were excluded for not meeting eligibility criteria, leaving 135 (mean [SD] age, 69.3 [3.8] years; 83 female [61%]) eligible for analysis. One participant among the remaining 135 did not complete the trial. In adjusted mixed effects models, no interaction effects were observed between visit and group for PACC5 (F2,131.39 = 2.58; P = .08), episodic memory (F2,131.60 = 2.34; P = .10), executive function (F2,131.26 = 0.89; P = .41), or attention (F2,131.20 = 0.34; P = .79). Results remained substantively unchanged across sensitivity and exploratory analyses. CONCLUSIONS AND RELEVANCE: In this secondary analysis of an 18-month randomized trial, meditation and non-native language training did not confer salutary cognitive effects. Although further analyses are needed to explore the effects of these interventions on other relevant outcomes related to aging and well-being, these findings did not support the use of these interventions for enhancing cognition in cognitively healthy older adults. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02977819

Eigenvector centrality dynamics are related to Alzheimer’s disease pathological changes in non-demented individuals

Amyloid-β accumulation starts in highly connected brain regions and is associated with functional connectivity alterations in the early stages of Alzheimer's disease. This regional vulnerability is related to the high neuronal activity and strong fluctuations typical of these regions. Recently, dynamic functional connectivity was introduced to investigate changes in functional network organization over time. High dynamic functional connectivity variations indicate increased regional flexibility to participate in multiple subnetworks, promoting functional integration. Currently, only a limited number of studies have explored the temporal dynamics of functional connectivity in the pre-dementia stages of Alzheimer's disease. We study the associations between abnormal cerebrospinal fluid amyloid and both static and dynamic properties of functional hubs, using eigenvector centrality, and their relationship with cognitive performance, in 701 non-demented participants from the European Prevention of Alzheimer's Dementia cohort. Voxel-wise eigenvector centrality was computed for the whole functional magnetic resonance imaging time series (static), and within a sliding window (dynamic). Differences in static eigenvector centrality between amyloid positive (A+) and negative (A-) participants and amyloid-tau groups were found in a general linear model. Dynamic eigenvector centrality standard deviation and range were compared between groups within clusters of significant static eigenvector centrality differences, and within 10 canonical resting-state networks. The effect of the interaction between amyloid status and cognitive performance on dynamic eigenvector centrality variability was also evaluated with linear models. Models were corrected for age, sex, and education level. Lower static centrality was found in A+ participants in posterior brain areas including a parietal and an occipital cluster; higher static centrality was found in a medio-frontal cluster. Lower eigenvector centrality variability (standard deviation) occurred in A+ participants in the frontal cluster. The default mode network and the dorsal visual networks of A+ participants had lower dynamic eigenvector centrality variability. Centrality variability in the default mode network and dorsal visual networks were associated with cognitive performance in the A- and A+ groups, with lower variability being observed in A+ participants with good cognitive scores. Our results support the role and timing of eigenvector centrality alterations in very early stages of Alzheimer's disease and show that centrality variability over time adds relevant information on the dynamic patterns that cause static eigenvector centrality alterations. We propose that dynamic eigenvector centrality is an early biomarker of the interplay between early Alzheimer's disease pathology and cognitive decline

Measuring Psychological Mechanisms in Meditation Practice: Using a Phenomenologically Grounded Classification System to Develop Theory-Based Composite Scores

peer reviewedObjectives: Deepening our understanding of the mechanisms by which meditation practices impact well-being and human flourishing is essential for advancing the science of meditation. A recent phenomenologically grounded classification system distinguishes attentional, constructive, and deconstructive forms of meditation based on the psychological mechanisms these practices primarily target or necessitate. Our main aim was to understand whether this theory-based taxonomy could be used as a guiding principle for combining established psychological self-report measures of meditation-related mechanisms into psychometrically adequate composite scores. Methods: We used cross-sectional data to compute meditation composite scores in three independent samples, namely meditation-naïve healthy older adults from the Age-Well trial (n = 135), meditation-naïve older adults with subjective cognitive decline from the SCD-Well trial (n = 147), and healthy long-term meditators (≥ 10,000 h of practice including one 3-year meditation retreat) from the Brain & Mindfulness project (n = 29). The psychometric properties of the composite scores were assessed via floor and ceiling effects, composite intercorrelations, interpretability, and convergent validity in relation to well-being, anxiety, and depression. Results: Three theoretically derived meditation composite scores, reflecting mechanisms involved in attentional, constructive, and deconstructive practices, displayed adequate psychometric properties. Separate secondary confirmatory factor analyses empirically corroborated the theoretically predicted three-factor structure of this classification system. Conclusions: Complementing data-driven approaches, this study offers preliminary support for using a theoretical model of meditation-related mechanisms to create empirically meaningful and psychometrically sound composite scores. We conclude by suggesting conceptual and methodological considerations for future research in this area.MEDIT-AGEING - Investigating the impact of meditation training on mental health and wellbeing in the ageing populationBRAINANDMINDFULNESS - Impact of Mental Training of Attention and Emotion Regulation on Brain and Behavior: Implications for Neuroplasticity, Well-Being and Mindfulness Psychotherapy Research

Exposure to negative socio-emotional events induces sustained alteration of resting-state brain networks in older adults

Basic emotional functions seem well preserved in older adults. However, their reactivity to and recovery from socially negative events remain poorly characterized. To address this, we designed a ‘task–rest’ paradigm in which 182 participants from two independent experiments underwent functional magnetic resonance imaging while exposed to socio-emotional videos. Experiment 1 (N = 55) validated the task in young and older participants and unveiled age-dependent effects on brain activity and connectivity that predominated in resting periods after (rather than during) negative social scenes. Crucially, emotional elicitation potentiated subsequent resting-state connectivity between default mode network and amygdala exclusively in older adults. Experiment 2 replicated these results in a large older adult cohort (N = 127) and additionally showed that emotion-driven changes in posterior default mode network–amygdala connectivity were associated with anxiety, rumination and negative thoughts. These findings uncover the neural dynamics of empathy-related functions in older adults and help understand its relationship to poor social stress recovery

The Open-Access European Prevention of Alzheimer's Dementia (EPAD) MRI dataset and processing workflow

The European Prevention of Alzheimer Dementia (EPAD) is a multi-center study that aims to characterize the preclinical and prodromal stages of Alzheimer's Disease. The EPAD imaging dataset includes core (3D T1w, 3D FLAIR) and advanced (ASL, diffusion MRI, and resting-state fMRI) MRI sequences. Here, we give an overview of the semi-automatic multimodal and multisite pipeline that we developed to curate, preprocess, quality control (QC), and compute image-derived phenotypes (IDPs) from the EPAD MRI dataset. This pipeline harmonizes DICOM data structure across sites and performs standardized MRI preprocessing steps. A semi-automated MRI QC procedure was implemented to visualize and flag MRI images next to site-specific distributions of QC features - i.e. metrics that represent image quality. The value of each of these QC features was evaluated through comparison with visual assessment and step-wise parameter selection based on logistic regression. IDPs were computed from 5 different MRI modalities and their sanity and potential clinical relevance were ascertained by assessing their relationship with biological markers of aging and dementia. The EPAD v1500.0 data release encompassed core structural scans from 1356 participants 842 fMRI, 831 dMRI, and 858 ASL scans. From 1356 3D T1w images, we identified 17 images with poor quality and 61 with moderate quality. Five QC features - Signal to Noise Ratio (SNR), Contrast to Noise Ratio (CNR), Coefficient of Joint Variation (CJV), Foreground-Background energy Ratio (FBER), and Image Quality Rate (IQR) - were selected as the most informative on image quality by comparison with visual assessment. The multimodal IDPs showed greater impairment in associations with age and dementia biomarkers, demonstrating the potential of the dataset for future clinical analyses