Gaël Chételat

Study objectives: Aging is associated with increased sleep complaints and changes in sleep architecture, microstructure and rest-activity rhythms. Meditation-based interventions have shown benefits on subjective sleep quality, but their effects on objective sleep parameters remain largely underexplored. This study investigated the effects of an 18-month meditation intervention on sleep combining subjective (questionnaires) and objective (polysomnography and actigraphy) measures in older adults. Methods: A total of 120 cognitively unimpaired older adults (≥65 y) with minimal sleep complaint completed questionnaires, one week of actigraphy and in-home polysomnography at baseline, and again 18 months later. Following the baseline visit, participants were randomly assigned to one of 3 groups: meditation training, non-native language training (active control), or passive control. Group-by-visit interactions were examined using mixed-effects models for sleep questionnaires, actigraphy-derived metrics, sleep architecture and microstructure, including slow waves, spindles, and spectral power. Results: Compared to the passive control group only, meditation training was associated with greater ease of morning awakening (p=0.04). No significant intervention effects were observed for any other sleep parameter, including actigraphy- and polysomnography-derived measures. These findings remained unchanged after adjustment for depressive symptoms and trait anxiety. Conclusion: In cognitively unimpaired older adults, this 18-month meditation intervention yielded only limited improvements in subjective sleep assessment. Meditation may therefore have subtle effects on self-reported sleep quality in this healthy older population, although no effects on objective sleep measures were detected. Future studies should examine whether adapting the content, intensity, or timing of meditation practice and enrolling populations with clinically meaningful sleep disturbances or psychoaffective symptoms may yield greater benefits. Statement of significance: Sleep quality is impaired with age and may contribute to cognitive decline. This randomized controlled trial is the first to assess the effects of an 18-month meditation intervention on both subjective and objective sleep parameters in cognitively unimpaired older adults, compared with active and passive control groups. Meditation improved perceived ease of morning awakening compared to the passive control group, but no other group differences were observed. These findings suggest that meditation, an accessible and low-cost intervention, may modestly improve some aspects of self-reported sleep quality, while having limited effects on objective sleep measures in older adults without sleep complaints. Studies evaluating the effects of meditation on objective sleep measures in more diverse and clinically affected populations are needed. Graphical

Mindfulness meditation has received growing interest in research over the past decades. Mindfulness meditation training (MMT) can be employed as a mental practice to improve cognitive skills such as attention and emotion regulation and may promote well-being. Neuroimaging studies have emerged to understand the effects of MMT on brain functioning. However, no review exists on the effects of MMT on resting-state brain functional connectivity (rsFC) in healthy meditation-naïve adults specifically. We, therefore, aimed to provide an overview of studies that investigated the effects of MMT on rsFC in healthy meditation-naïve adults, as well as their link to cognitive and clinical measures. Several studies reported changes in MMT-induced rsFC within and between regions of the default mode (DMN), salience (SN), and central executive (CEN) networks. Both increases and decreases in rsFC have been observed for brain regions associated with these networks after MMT, each with differential roles in emotion regulation, stress, and cognitive functions. Some studies highlighted associations between changes in rsFC after MMT and modifications in cognitive performance and psycho-affective measures, which may be influenced by MMT-specific characteristics such as practice duration or delivery methods. MMT may induce a reorganization in the brain’s functional architecture by altering rsFC within and between these networks and seems to modify processes related to attention, executive memory, emotional regulation, stress, and resilience. Investigating functional connectivity during rest in key brain networks seems a promising approach to understand the effects of mindfulness meditation on overall well-being.

Severe episodic memory deficits have historically been categorized as diencephalic amnesia, like in Korsakoff’s Syndrome (KS), or as medial temporal lobe (MTL) amnesia, like in Alzheimer’s Disease (AD). However, recent research has highlighted that both MTL and thalamus contribute to episodic memory. We aimed to challenge the traditional distinction by assessing whether subregional volume loss in the MTL and diencephalon reflects the distinct amnesia profiles traditionally associated with KS and AD. This cross-sectional observational study includes 203 subjects, comprising 81 healthy control participants. Of the 122 patients, 42 had amnesia: 18 patients with KS and 24 patients with AD at a dementia stage (dAD); and 80 had mild cognitive disorders: 50 patients with severe alcohol use disorder (AUD) without KS and 30 patients with amnestic mild cognitive impairment (aMCI). High-resolution T1-weighted MRI was used to quantify MTL subregions (anterior/posterior hippocampus, entorhinal cortex, parahippocampal cortex) using the ASHS-T1 pipeline and key diencephalic structures (anterior/mediodorsal thalamic nuclei, mammillothalamic tract) using the HIPS-THOMAS toolbox. Volume loss among patients and regions were compared using a linear mixed model. For each region, correlations between episodic memory and volumes loss were assessed and compared between aMCI/dAD and AUD/KS patients. Results showed no volume difference between patient groups for the anterior and posterior hippocampus and parahippocampal cortex. Entorhinal cortex was more altered in aMCI and dAD than in AUD and KS. KS and AUD patients showed disproportionate structural alterations in thalamic nuclei and mammillothalamic tracts compared with MTL subregions. KS patients showed more severe alterations than all other groups, except for anterior thalamic nuclei for which volume did not differ between KS and dAD. Episodic memory performance of AUD and KS patients correlated with volumes loss in the anterior and mediodorsal thalamic nuclei and mammillothalamic tract, while that of aMCI and dAD patients correlated with volume loss in the anterior hippocampus. Alterations in the MTL and diencephalon are not as clearly dissociated as traditionally proposed in the classification of amnesia. While KS pathology is characterized by more severe diencephalic alterations, only the entorhinal cortex is more damaged in AD than in KS. Neither hippocampal nor anterior thalamic volume loss appears to distinguish between the two types of amnesia, suggesting that structural changes in these two regions jointly participate to the pathophysiology of amnesia whatever the etiology. However, these alterations are not similarly involved in memory deficits, which suggests different architectural and/or functional implications of same-scale volume loss.

INTRODUCTION: The locus coeruleus (LC), the first region to contain tau pathology in Alzheimer's disease (AD), releases norepinephrine, which has a neuroprotective role. We examined whether LC integrity relates to whole‐brain integrity and how AD biomarkers may moderate this relationship. METHODS: LC intensity and volume were estimated using automatic segmentation on neuromelanin‐sensitive magnetic resonance imaging acquired in n = 71 cognitively unimpaired elderly from the Age‐Well randomized controlled trial. We investigated the associations between LC integrity and whole‐brain gray matter volume (GMV) and glucose metabolism, as well as the interactions with amyloid positron emission tomography and plasma phosphorylated tau231, neurofilament light chain and glial fibrillary acidic protein. RESULTS: While only LC intensity was directly associated with GMV, both LC measures (intensity and volume) interacted positively with AD biomarkers to predict GMV and glucose metabolism. DISCUSSION: Our results support concomitant LC and gray matter alterations in the context of aging and elevated AD biomarker levels. CLINICAL TRIAL REGISTRATION: Age‐Well randomized clinical trial of the Medit‐Ageing European Project. Trial registration number: EudraCT:2016–002,441–36; IDRCB:2016‐A01767–44; ClinicalTrials.gov Identifier: NCT02977819.

White matter hyperintensities (WMH) are common in older adults and are associated with cognitive disorders. They typically arise from small vessel disease, leading to demyelination and axonal loss. WMH are thus considered markers of cerebrovascular changes. However, other pathophysiological processes can lead to WMH, particularly in Alzheimer’s disease (AD). Understanding the diverse origins of WMH could enhance the diagnosis and treatment of AD patients. We hypothesize that multimodal neuroimaging could help understand the heterogeneity of WMH and pinpoint their specific origin. We included 142 older adults from the community and memory clinic (with an emphasis on patients within the Alzheimer’s continuum), and tested if multimodal neuroimaging signal within regional WMH (including T1w, T2w, ¹⁸F-florbetapir [AV45] and ¹⁸F-fluorodeoxyglucose [FDG] PET), is associated with amyloid load and cognition. We showed that intra-WMH T1w and T2w signal in the parietal and frontal lobes were linked to amyloid status; intra-WMH T2w signal in all regions negatively correlated with amyloid load, while intra-WMH T1w signals in the parietal lobe positively correlated with amyloid load; finally, intra-WMH T1w signal negatively correlated with cognition while T2w and marginally AV45 signals positively correlated with cognition. This study demonstrates the potential of multimodal neuroimaging to unravel the heterogeneity of WMH, which could enhance their interpretation and improve clinical decision-making.

Meditation is thought to promote healthy aging by improving mental health, preserving brain integrity and reducing Alzheimer’s disease risk. We examined the impact of long-term meditation expertise and an 18-month meditation training on brain aging in older adults using machine learning. We included 25 Older Expert Meditators (OldExpMed) with > 20 years of practice and 135 Cognitively Unimpaired Older Adults (CUOA) from the Age-Well randomized controlled trial. CUOA were randomized (1:1:1) into an 18-month meditation training, a non-native language training, and a no intervention group. Brain age was predicted using a machine learning model trained on gray and white matter volume and glucose metabolism data from ADNI and replicated with a second model. Brain Predicted Age Difference (BrainPAD) was computed as the gap between predicted and chronological age. We assessed meditation expertise effects on BrainPAD, its links with meditation hours, cognitive, and affective measures, and the impact of 18-month training. Compared to CUOA, OldExpMed exhibited significantly lower/more negative BrainPAD, linked to meditation hours, mental imagery, and prosocialness. No significant effect of 18-month training was observed. Results were consistent across the replication model. Long-term meditation is associated with younger brain age, but 18-month training has no effect, emphasizing the need for sustained practice to support healthy brain aging.

Meditation practice has been shown to impact resting‐state EEG activity in expert meditators, but its benefits on sleep, which is particularly affected with age, are poorly understood. Our aim was to better understand the effects of long‐term meditation practice on resting‐state EEG and sleep in older adults. Twenty‐seven elderly expert meditators (mean age ± SD: 70.7 ± 5.0 years) were compared to meditation‐naive controls (69.3 ± 3.8 years) for sleep questionnaires ( n = 135), polysomnography ( n = 47) and resting‐state EEG ( n = 73). Sleep microstructure (slow waves and spindles) and EEG features (power, Kolmogorov complexity and permutation entropy (PE)) during resting‐state, NREM, and REM sleep were compared between groups. Correlations were tested between the metrics that differed between the two groups and the level of meditation expertise within the meditator group. At rest, expert meditators exhibited lower delta power and higher delta PE than controls. Self‐reported sleep quality did not differ between groups, but expert meditators slept longer, had reduced %N1, and higher %N2. During NREM sleep, they exhibited reduced delta power, increased alpha power, and greater theta PE. During REM sleep, they tended to show greater theta power. Finally, the composite score of meditation expertise was negatively associated with %N1, and tended to be positively associated with %N2 and REM sleep theta power. Overall, these results suggest that expert meditators showed more preserved brain activity at rest and sleep architecture, and exhibited EEG features suggesting higher cognitive states during NREM sleep. Clinical Trial Information: Name: Study in Cognitively Intact Seniors Aiming to Assess the Effects of Meditation Training (Age‐Well). Registration: EudraCT: 2016‐002441‐36; IDRCB: 2016‐A01767‐44; ClinicalTrials.gov Identifier: NCT02977819. ( https://clinicaltrials.gov/ct2/show/NCT02977819?term=Age‐Well&draw=2&rank=1 ).

Meditation training in older adults has been proposed as a non-pharmacological intervention to promote healthy aging and lower the risks of developing Alzheimer’s disease (AD). Resting-state dynamic functional network connectivity (dFNC) highlighted two brain states, the “strongly connected” and “default mode network (DMN)-negatively connected” states, associated with protective factors for dementia including AD, and two states, the “weakly connected” and “salience-negatively connected” states, associated with risk factors for dementia. In this study, we aimed at assessing the impact of an 18-month meditation training on dFNC states in older adults. One hundred and thirty-five healthy older adults were randomized (1:1:1) to 18-month meditation training, 18-month non-native language training, or no intervention. dFNC of the DMN, salience, and executive control networks was assessed in 124 individuals using a sliding window framework, and states were obtained by k-means clustering. Linear mixed models evaluated the change in time spent in different connectivity “states” and the number of transitions between states for each group and between groups. Only participants in the meditation group transitioned significantly more between states (p = 0.008, d = 0.52), with a significant between-group difference with the non-native language training group (p = 0.001). Moreover, only the meditation group showed a change in time spent in specific states, spending less time in the “weakly connected” state (p = 0.009, d = -0.44) and more time in the “strongly connected” state (p = 0.03, d = 0.46), but there was no difference between groups. Brain states at rest were significantly impacted by an 18-month meditation intervention, with increased number of transitions between states, an increased time spent in the “strongly connected” state, and decreased time spent in the “weakly connected” state. While only the first change differed significantly between groups, these results suggest a beneficial effect of meditation through a reduction in dFNC metrics associated with AD risk factors and an increase in dFNC metrics associated with protective factors. However, the absence of a significant group-by-time interaction for time spent in states, the small effect sizes, and the fact that the sample size was not powered for this outcome limit the interpretation of the findings. Additionally, unmeasured factors such as genetic predisposition and lifestyle could have influenced the results. Future studies should identify the specific active mechanisms of meditation underlying these effects to optimize interventions. Trial Registration: The Age-Well randomized controlled trial (RCT) was approved by the local ethics committee (CPP Nord-Ouest III, Caen; trial registration number: EudraCT: 2016-002441-36; IDRCB: 2016-A01767-44; ClinicalTrials.gov Identifier: NCT02977819; registration date: 2016-11-25).

With aging, slight changes in some cognitive processes can be observed. Therefore, we aimed to assess if meditation expertise is associated with preserved cognition in key domains affected in aging. We used data from two older-adult samples of the Medit-Ageing Age-well Study: 135 non-meditators and 27 expert meditators. We examined group differences in four objective cognitive domains (attention, executive functioning, episodic memory, and global cognition) and three subjective scores: Cognitive Difficulties Scale (CDS) total score as well as Attentional Style Questionnaire (ASQ) internal and external scores using generalized mixed effect models, controlling for age, sex, and education. We did not observe group differences on attentional, executive and global cognitive scores or on ASQ internal score and CDS total score. However, meditators reported less external distraction (ASQ external score) and had better memory than non-meditators. These cross-sectional results indicate a better management of external stimuli and higher memory performance in expert meditators. Memory difficulties and distractions being the main complaints of older people, prolonged meditation practice could lead them to greater cognitive capacities important for healthy aging. Trial registration: NCT02977819 (ClinicalTrials.gov)