Stimulant medication use and apparent cortical thickness development in attention-deficit/hyperactivity disorder: a prospective longitudinal study.

Background: Stimulant medication is commonly prescribed as treatment for attention-deficit/hyperactivity disorder (ADHD). While we previously found that short-term stimulant-treatment influences apparent cortical thickness development in an age-dependent manner, it remains unknown whether these effects persist throughout development into adulthood. Purpose: Investigate the long-term age-dependent effects of stimulant medication use on apparent cortical thickness development in adolescents and adults previously diagnosed with ADHD. Methods: This prospective study included the baseline and 4-year follow-up assessment of the "effects of Psychotropic drugs On the Developing brain-MPH" ("ePOD-MPH") project, conducted between June-1-2011 and December-28-2019. The analyses were pre-registered (https://doi.org/10.17605/OSF.IO/32BHF). T1-weighted MR scans were obtained from male adolescents and adults, and cortical thickness was estimated for predefined regions of interest (ROIs) using Freesurfer. We determined medication use and assessed symptoms of ADHD, anxiety, and depression at both time points. Linear mixed models were constructed to assess main effects and interactions of stimulant medication use, time, and age group on regional apparent cortical thickness. Results: A total of 32 male adolescents (aged mean ± SD, 11.2 ± 0.9 years at baseline) and 24 men (aged mean ± SD, 29.9 ± 5.0 years at baseline) were included that previously participated in the ePOD-MPH project. We found no evidence for long-term effects of stimulant medication use on ROI apparent cortical thickness. As expected, we did find age-by-time interaction effects in all ROIs (left prefrontal ROI: P=.002, right medial and posterior ROIs: P<.001), reflecting reductions in apparent cortical thickness in adolescents. Additionally, ADHD symptom severity (adolescents: P<.001, adults: P=.001) and anxiety symptoms (adolescents: P=0.03) were reduced, and more improvement of ADHD symptoms was associated with higher medication use in adults (P=0.001). Conclusion: We found no evidence for long-term effects of stimulant-treatment for ADHD on apparent cortical thickness development in adolescents and adults. The identified age-dependent differences in apparent cortical thickness development are consistent with existing literature on typical cortical development.

Fetal influence on the human brain through the lifespan.

Human fetal development has been associated with brain health at later stages. It is unknown whether growth in utero, as indexed by birth weight (BW), relates consistently to lifespan brain characteristics and changes, and to what extent these influences are of a genetic or environmental nature. Here we show remarkably stable and lifelong positive associations between BW and cortical surface area and volume across and within developmental, aging and lifespan longitudinal samples (N = 5794, 4-82 y of age, w/386 monozygotic twins, followed for up to 8.3 y w/12,088 brain MRIs). In contrast, no consistent effect of BW on brain changes was observed. Partly environmental effects were indicated by analysis of twin BW discordance. In conclusion, the influence of prenatal growth on cortical topography is stable and reliable through the lifespan. This early-life factor appears to influence the brain by association of brain reserve, rather than brain maintenance. Thus, fetal influences appear omnipresent in the spacetime of the human brain throughout the human lifespan. Optimizing fetal growth may increase brain reserve for life, also in aging.

Genetic evidence for the causal effects of C-reactive protein on self-reported habitual sleep duration.

Inflammatory responses to acute stimuli are proposed to regulate sleep, but the relationship between chronic inflammation and habitual sleep duration is elusive. Here, we study this relation using genetically predicted level of chronic inflammation, indexed by CRP and IL6 signaling, and self-reported sleep duration. By Mendelian randomization analysis, we show that elevated CRP level within <10 mg/L has a homeostatic effect that facilitates maintaining 7-8 h sleep duration per day - making short-sleepers sleep longer (p = 2.42 × 10-2) and long-sleepers sleep shorter (1.87 × 10-7); but it is not associated with the overall sleep duration (p = 0.17). This homeostatic effect replicated in an independent CRP dataset. We observed causal effects of the soluble interleukin 6 receptor and gp130 on overall sleep duration (p = 1.62 × 10-8, p = 2.61 × 10-58, respectively), but these effects disappeared when CRP effects were accounted for in the model. Using polygenic score analysis, we found that the homeostatic effect of CRP on sleep duration stems primarily from the genetic variants within the CRP gene region: when genetic variants outside of this region were used to predict CRP levels, the opposite direction of effect was observed. In conclusion, we show that elevated CRP level may causally facilitate maintaining an optimal sleep duration that is beneficial to health, thus updating our current knowledge of immune regulation on sleep.

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

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

Tracing the development and lifespan change of population-level structural asymmetry in the cerebral cortex.

Cortical asymmetry is a ubiquitous feature of brain organization that is subtly altered in some neurodevelopmental disorders, yet we lack knowledge of how its development proceeds across life in health. Achieving consensus on the precise cortical asymmetries in humans is necessary to uncover the developmental timing of asymmetry and the extent to which it arises through genetic and later influences in childhood. Here, we delineate population-level asymmetry in cortical thickness and surface area vertex-wise in seven datasets and chart asymmetry trajectories longitudinally across life (4-89 years; observations = 3937; 70% longitudinal). We find replicable asymmetry interrelationships, heritability maps, and test asymmetry associations in large-scale data. Cortical asymmetry was robust across datasets. Whereas areal asymmetry is predominantly stable across life, thickness asymmetry grows in childhood and peaks in early adulthood. Areal asymmetry is low-moderately heritable (max h2SNP ~19%) and correlates phenotypically and genetically in specific regions, indicating coordinated development of asymmetries partly through genes. In contrast, thickness asymmetry is globally interrelated across the cortex in a pattern suggesting highly left-lateralized individuals tend towards left-lateralization also in population-level right-asymmetric regions (and vice versa), and exhibits low or absent heritability. We find less areal asymmetry in the most consistently lateralized region in humans associates with subtly lower cognitive ability, and confirm small handedness and sex effects. Results suggest areal asymmetry is developmentally stable and arises early in life through genetic but mainly subject-specific stochastic effects, whereas childhood developmental growth shapes thickness asymmetry and may lead to directional variability of global thickness lateralization in the population.

Is Short Sleep Bad for the Brain? Brain Structure and Cognitive Function in Short Sleepers.

Many sleep less than recommended without experiencing daytime sleepiness. According to prevailing views, short sleep increases risk of lower brain health and cognitive function. Chronic mild sleep deprivation could cause undetected sleep debt, negatively affecting cognitive function and brain health. However, it is possible that some have less sleep need and are more resistant to negative effects of sleep loss. We investigated this using a cross-sectional and longitudinal sample of 47,029 participants of both sexes (20-89 years) from the Lifebrain consortium, Human Connectome project (HCP) and UK Biobank (UKB), with measures of self-reported sleep, including 51,295 MRIs of the brain and cognitive tests. A total of 740 participants who reported to sleep <6 h did not experience daytime sleepiness or sleep problems/disturbances interfering with falling or staying asleep. These short sleepers showed significantly larger regional brain volumes than both short sleepers with daytime sleepiness and sleep problems (n = 1742) and participants sleeping the recommended 7-8 h (n = 3886). However, both groups of short sleepers showed slightly lower general cognitive function (GCA), 0.16 and 0.19 SDs, respectively. Analyses using accelerometer-estimated sleep duration confirmed the findings, and the associations remained after controlling for body mass index, depression symptoms, income, and education. The results suggest that some people can cope with less sleep without obvious negative associations with brain morphometry and that sleepiness and sleep problems may be more related to brain structural differences than duration. However, the slightly lower performance on tests of general cognitive abilities warrants closer examination in natural settings.SIGNIFICANCE STATEMENT Short habitual sleep is prevalent, with unknown consequences for brain health and cognitive performance. Here, we show that daytime sleepiness and sleep problems are more strongly related to regional brain volumes than sleep duration. However, participants sleeping ≤6 h had slightly lower scores on tests of general cognitive function (GCA). This indicates that sleep need is individual and that sleep duration per se is very weakly if at all related brain health, while daytime sleepiness and sleep problems may show somewhat stronger associations. The association between habitual short sleep and lower scores on tests of general cognitive abilities must be further scrutinized in natural settings.

Brain aging differs with cognitive ability regardless of education.

Higher general cognitive ability (GCA) is associated with lower risk of neurodegenerative disorders, but neural mechanisms are unknown. GCA could be associated with more cortical tissue, from young age, i.e. brain reserve, or less cortical atrophy in adulthood, i.e. brain maintenance. Controlling for education, we investigated the relative association of GCA with reserve and maintenance of cortical volume, -area and -thickness through the adult lifespan, using multiple longitudinal cognitively healthy brain imaging cohorts (n = 3327, 7002 MRI scans, baseline age 20-88 years, followed-up for up to 11 years). There were widespread positive relationships between GCA and cortical characteristics (level-level associations). In select regions, higher baseline GCA was associated with less atrophy over time (level-change associations). Relationships remained when controlling for polygenic scores for both GCA and education. Our findings suggest that higher GCA is associated with cortical volumes by both brain reserve and -maintenance mechanisms through the adult lifespan.

Education and Income Show Heterogeneous Relationships to Lifespan Brain and Cognitive Differences Across European and US Cohorts.

Higher socio-economic status (SES) has been proposed to have facilitating and protective effects on brain and cognition. We ask whether relationships between SES, brain volumes and cognitive ability differ across cohorts, by age and national origin. European and US cohorts covering the lifespan were studied (4-97 years, N = 500 000; 54 000 w/brain imaging). There was substantial heterogeneity across cohorts for all associations. Education was positively related to intracranial (ICV) and total gray matter (GM) volume. Income was related to ICV, but not GM. We did not observe reliable differences in associations as a function of age. SES was more strongly related to brain and cognition in US than European cohorts. Sample representativity varies, and this study cannot identify mechanisms underlying differences in associations across cohorts. Differences in neuroanatomical volumes partially explained SES-cognition relationships. SES was more strongly related to ICV than to GM, implying that SES-cognition relations in adulthood are less likely grounded in neuroprotective effects on GM volume in aging. The relatively stronger SES-ICV associations rather are compatible with SES-brain volume relationships being established early in life, as ICV stabilizes in childhood. The findings underscore that SES has no uniform association with, or impact on, brain and cognition.

Associations of circulating C-reactive proteins, APOE ε4, and brain markers for Alzheimer's disease in healthy samples across the lifespan.

The apolipoprotein E gene ε4 allele (APOE ε4) and higher circulating level of C-reactive protein (CRP) have been extensively investigated as risk factors for Alzheimer's disease (AD). Paradoxically, APOE ε4 has been associated with lower levels of blood CRP in middle-aged and older populations. However, few studies have investigated this intriguing relation and its impact on neurological markers for AD in younger ages, nor across the whole lifespan. Here, we examine associations of blood CRP levels, APOE ε4, and biomarkers for AD in a cognitively healthy lifespan cohort (N up to 749; 20-81 years of age) and replicate the findings in UK Biobank (N = 304 322; 37-72 years of age), the developmental ABCD study (N = 10 283; 9-11 years of age), and a middle-aged sample (N = 339; 40-65 years of age). Hippocampal volume, brain amyloid-ß (Aß) plaque levels, cerebrospinal fluid (CSF) levels of Aß and tau species, and neurofilament protein light protein (NFL) were used as AD biomarkers in subsamples. In addition, we examined the genetic contribution to the variation of CRP levels over different CRP ranges using polygenic scores for CRP (PGS-CRP). Our results show APOE ε4 consistently associates with low blood CRP levels across all age groups (p < 0.05). Strikingly, both ε4 and PGS-CRP associated mainly with blood CRP levels within the low range (<5mg/L). We then show both APOE ε4 and high CRP levels associate with smaller hippocampus volumes across the lifespan (p < 0.025). APOE ε4 was associated with high Aß plaque levels in the brain (FDR-corrected p = 8.69x10-4), low levels of CSF Aß42 (FDR-corrected p = 6.9x10-2), and lower ratios of Aß42 to Aß40 (FDR-corrected p = 5.08x10-5). Blood CRP levels were weakly correlated with higher ratio of CSF Aß42 to Aß40 (p = 0.03, FDR-corrected p = 0.4). APOE ε4 did not correlate with blood concentrations of another 9 inflammatory cytokines, and none of these cytokines correlated with AD biomarkers. CONCLUSION: The inverse correlation between APOEε 4 and blood CRP levels existed before any pathological AD biomarker was observed, and only in the low CRP level range. Thus, we suggest to investigate whether APOEε 4 can confer risk by being associated with a lower inflammatory response to daily exposures, possibly leading to greater accumulation of low-grade inflammatory stress throughout life. A lifespan perspective is needed to understand this relationship concerning risk of developing AD.

Individual variations in 'brain age' relate to early-life factors more than to longitudinal brain change.

Brain age is a widely used index for quantifying individuals' brain health as deviation from a normative brain aging trajectory. Higher-than-expected brain age is thought partially to reflect above-average rate of brain aging. Here, we explicitly tested this assumption in two independent large test datasets (UK Biobank [main] and Lifebrain [replication]; longitudinal observations ≈ 2750 and 4200) by assessing the relationship between cross-sectional and longitudinal estimates of brain age. Brain age models were estimated in two different training datasets (n ≈ 38,000 [main] and 1800 individuals [replication]) based on brain structural features. The results showed no association between cross-sectional brain age and the rate of brain change measured longitudinally. Rather, brain age in adulthood was associated with the congenital factors of birth weight and polygenic scores of brain age, assumed to reflect a constant, lifelong influence on brain structure from early life. The results call for nuanced interpretations of cross-sectional indices of the aging brain and question their validity as markers of ongoing within-person changes of the aging brain. Longitudinal imaging data should be preferred whenever the goal is to understand individual change trajectories of brain and cognition in aging.

Scientists who study the brain and aging are keen to find an effective way to measure brain health, which could help identify people at risk for dementia or memory problems. One popular marker is 'brain age'. This measurement uses a brain scan to estimate a person's chronological age, then compares the estimated brain age to the person's actual age to determine whether their brain is aging faster or slower than expected for their age. However, since brain age relies on one brain scan taken at one point in time, it is not clear whether it really measures brain aging or if it might capture brain differences that have been present throughout the individual's life. Studies comparing individual brain scans over several years would be necessary to know for sure. Now, Vidal-Piñeiro et al. show that the brain-age measurement does not reflect faster brain aging. In the experiments, the researchers compared repeated brain scans of thousands of individuals over 40 years of age. The experiments showed that deviations from normative brain age detected in a single scan reflected early life differences more than changes in the brain over time. For example, people with older-looking brains were more likely to have had a low birth weight or to have a combination of genes associated with having an older looking brain. Vidal-Piñeiro et al. show that brain age mostly reflects a pre-existing brain condition rather than brain aging. The experiments also suggest that genetics and early brain development likely have a strong impact on brain health throughout life. Future studies trying to test or develop brain-aging measurements should use serial measurements to track brain changes over time.

Relationships between apparent cortical thickness and working memory across the lifespan - Effects of genetics and socioeconomic status.

Working memory (WM) supports several higher-level cognitive abilities, yet we know less about factors associated with development and decline in WM compared to other cognitive processes. Here, we investigated lifespan changes in WM capacity and their structural brain correlates, using a longitudinal sample including 2358 magnetic resonance imaging (MRI) scans and WM scores from 1656 participants (4.4-86.4 years, mean follow-up interval 4.3 years). 8764 participants (9.0-10.9 years) with MRI, WM scores and genetic information from the Adolescent Brain Cognitive Development study were used for follow-up analyses. Results showed that both the information manipulation component and the storage component of WM improved during childhood and adolescence, but the age-decline could be fully explained by reductions in passive storage capacity alone. Greater WM function in development was related to apparent thinner cortex in both samples, also when general cognitive function was accounted for. The same WM-apparent thickness relationship was found for young adults. The WM-thickness relationships could not be explained by SNP-based co-heritability or by socioeconomic status. A larger sample with genetic information may be necessary to disentangle the true gene-environment effects. In conclusion, WM capacity changes greatly through life and has anatomically extended rather than function-specific structural cortical correlates.

The genetic organization of longitudinal subcortical volumetric change is stable throughout the lifespan.

Development and aging of the cerebral cortex show similar topographic organization and are governed by the same genes. It is unclear whether the same is true for subcortical regions, which follow fundamentally different ontogenetic and phylogenetic principles. We tested the hypothesis that genetically governed neurodevelopmental processes can be traced throughout life by assessing to which degree brain regions that develop together continue to change together through life. Analyzing over 6000 longitudinal MRIs of the brain, we used graph theory to identify five clusters of coordinated development, indexed as patterns of correlated volumetric change in brain structures. The clusters tended to follow placement along the cranial axis in embryonic brain development, suggesting continuity from prenatal stages, and correlated with cognition. Across independent longitudinal datasets, we demonstrated that developmental clusters were conserved through life. Twin-based genetic correlations revealed distinct sets of genes governing change in each cluster. Single-nucleotide polymorphisms-based analyses of 38,127 cross-sectional MRIs showed a similar pattern of genetic volume-volume correlations. In conclusion, coordination of subcortical change adheres to fundamental principles of lifespan continuity and genetic organization.

The Functional Foundations of Episodic Memory Remain Stable Throughout the Lifespan.

It has been suggested that specific forms of cognition in older age rely largely on late-life specific mechanisms. Here instead, we tested using task-fMRI (n = 540, age 6-82 years) whether the functional foundations of successful episodic memory encoding adhere to a principle of lifespan continuity, shaped by developmental, structural, and evolutionary influences. We clustered regions of the cerebral cortex according to the shape of the lifespan trajectory of memory activity in each region so that regions showing the same pattern were clustered together. The results revealed that lifespan trajectories of memory encoding function showed a continuity through life but no evidence of age-specific mechanisms such as compensatory patterns. Encoding activity was related to general cognitive abilities and variations of grey matter as captured by a multi-modal independent component analysis, variables reflecting core aspects of cognitive and structural change throughout the lifespan. Furthermore, memory encoding activity aligned to fundamental aspects of brain organization, such as large-scale connectivity and evolutionary cortical expansion gradients. Altogether, we provide novel support for a perspective on memory aging in which maintenance and decay of episodic memory in older age needs to be understood from a comprehensive life-long perspective rather than as a late-life phenomenon only.

Poor Self-Reported Sleep is Related to Regional Cortical Thinning in Aging but not Memory Decline-Results From the Lifebrain Consortium.

We examined whether sleep quality and quantity are associated with cortical and memory changes in cognitively healthy participants across the adult lifespan. Associations between self-reported sleep parameters (Pittsburgh Sleep Quality Index, PSQI) and longitudinal cortical change were tested using five samples from the Lifebrain consortium (n = 2205, 4363 MRIs, 18-92 years). In additional analyses, we tested coherence with cell-specific gene expression maps from the Allen Human Brain Atlas, and relations to changes in memory performance. "PSQI # 1 Subjective sleep quality" and "PSQI #5 Sleep disturbances" were related to thinning of the right lateral temporal cortex, with lower quality and more disturbances being associated with faster thinning. The association with "PSQI #5 Sleep disturbances" emerged after 60 years, especially in regions with high expression of genes related to oligodendrocytes and S1 pyramidal neurons. None of the sleep scales were related to a longitudinal change in episodic memory function, suggesting that sleep-related cortical changes were independent of cognitive decline. The relationship to cortical brain change suggests that self-reported sleep parameters are relevant in lifespan studies, but small effect sizes indicate that self-reported sleep is not a good biomarker of general cortical degeneration in healthy older adults.

Analysis of task-based functional MRI data preprocessed with fMRIPrep.

Functional magnetic resonance imaging (fMRI) is a standard tool to investigate the neural correlates of cognition. fMRI noninvasively measures brain activity, allowing identification of patterns evoked by tasks performed during scanning. Despite the long history of this technique, the idiosyncrasies of each dataset have led to the use of ad-hoc preprocessing protocols customized for nearly every different study. This approach is time consuming, error prone and unsuitable for combining datasets from many sources. Here we showcase fMRIPrep (http://fmriprep.org), a robust tool to prepare human fMRI data for statistical analysis. This software instrument addresses the reproducibility concerns of the established protocols for fMRI preprocessing. By leveraging the Brain Imaging Data Structure to standardize both the input datasets (MRI data as stored by the scanner) and the outputs (data ready for modeling and analysis), fMRIPrep is capable of preprocessing a diversity of datasets without manual intervention. In support of the growing popularity of fMRIPrep, this protocol describes how to integrate the tool in a task-based fMRI investigation workflow.

The genetic architecture of the human cerebral cortex.

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.

Anterior and posterior hippocampus macro- and microstructure across the lifespan in relation to memory-A longitudinal study.

There is evidence for a hippocampal long axis anterior-posterior (AP) differentiation in memory processing, which may have implications for the changes in episodic memory performance seen across development and aging. The hippocampus shows substantial structural changes with age, but the lifespan trajectories of hippocampal sub-regions along the AP axis are not established. The aim of the present study was to test whether the micro- and macro-structural age-trajectories of the anterior (aHC) and posterior (pHC) hippocampus are different. In a single-center longitudinal study, 1,790 cognitively healthy participants, 4.1-93.4 years of age, underwent a total of 3,367 MRI examinations and 3,033 memory tests sessions over 1-6 time points, spanning an interval up to 11.1 years. T1-weighted scans were used to estimate the volume of aHC and pHC (macrostructure), and diffusion tensor imaging to measure mean diffusion (MD, microstructure) within each region. We found that the macro- and microstructural lifespan-trajectories of aHC and pHC were clearly distinguishable, with partly common and partly unique variance shared with age. aHC showed a protracted period of microstructural development, while pHC microstructural development as indexed by MD was more or less completed in early childhood. In contrast, pHC showed larger unique aging-related changes. An aHC-pHC difference was also observed for volume, with pHC changing relatively more with higher age. All regions showed age-dependent relationships with episodic memory. aHC micro- and macrostructure was significantly related to verbal memory independently of age, but the relationships were still strongest among the older participants. We suggest that memory processes supported by each sub-region improve or decline in concert with volumetric and microstructural changes in the same age-period. Future research should disentangle the lifespan relationship between changes in these structural properties and different memory processes, encoding versus retrieval in particular, as well as other cognitive functions depending on the hippocampal long-axis specialization.

Self-reported sleep relates to hippocampal atrophy across the adult lifespan: results from the Lifebrain consortium.

OBJECTIVES: Poor sleep is associated with multiple age-related neurodegenerative and neuropsychiatric conditions. The hippocampus plays a special role in sleep and sleep-dependent cognition, and accelerated hippocampal atrophy is typically seen with higher age. Hence, it is critical to establish how the relationship between sleep and hippocampal volume loss unfolds across the adult lifespan. METHODS: Self-reported sleep measures and MRI-derived hippocampal volumes were obtained from 3105 cognitively normal participants (18-90 years) from major European brain studies in the Lifebrain consortium. Hippocampal volume change was estimated from 5116 MRIs from 1299 participants for whom longitudinal MRIs were available, followed up to 11 years with a mean interval of 3.3 years. Cross-sectional analyses were repeated in a sample of 21,390 participants from the UK Biobank. RESULTS: No cross-sectional sleep-hippocampal volume relationships were found. However, worse sleep quality, efficiency, problems, and daytime tiredness were related to greater hippocampal volume loss over time, with high scorers showing 0.22% greater annual loss than low scorers. The relationship between sleep and hippocampal atrophy did not vary across age. Simulations showed that the observed longitudinal effects were too small to be detected as age-interactions in the cross-sectional analyses. CONCLUSIONS: Worse self-reported sleep is associated with higher rates of hippocampal volume decline across the adult lifespan. This suggests that sleep is relevant to understand individual differences in hippocampal atrophy, but limited effect sizes call for cautious interpretation.

Elaboration Benefits Source Memory Encoding Through Centrality Change.

Variations in levels of processing affect memory encoding and subsequent retrieval performance, but it is unknown how processing depth affects communication patterns within the network of interconnected brain regions involved in episodic memory encoding. In 113 healthy adults scanned with functional MRI, we used graph theory to calculate centrality indices representing the brain regions' relative importance in the memory network. We tested how communication patterns in 42 brain regions involved in episodic memory encoding changed as a function of processing depth, and how these changes were related to episodic memory ability. Centrality changes in right middle frontal gyrus, right inferior parietal lobule and left superior frontal gyrus were positively related to semantic elaboration during encoding. In the same regions, centrality during successful episodic memory encoding was related to performance on the episodic memory task, indicating that these centrality changes reflect processes that support memory encoding through deep elaborative processing. Similar analyses were performed for congruent trials, i.e. events that fit into existing knowledge structures, but no relationship between centrality changes and congruity were found. The results demonstrate that while elaboration and congruity have similar beneficial effects on source memory performance, the cortical signatures of these processes are probably not identical.