Maintenance, reserve and compensation: the cognitive neuroscience of healthy ageing.

Cognitive ageing research examines the cognitive abilities that are preserved and/or those that decline with advanced age. There is great individual variability in cognitive ageing trajectories. Some older adults show little decline in cognitive ability compared with young adults and are thus termed 'optimally ageing'. By contrast, others exhibit substantial cognitive decline and may develop dementia. Human neuroimaging research has led to a number of important advances in our understanding of the neural mechanisms underlying these two outcomes. However, interpreting the age-related changes and differences in brain structure, activation and functional connectivity that this research reveals is an ongoing challenge. Ambiguous terminology is a major source of difficulty in this venture. Three terms in particular - compensation, maintenance and reserve - have been used in a number of different ways, and researchers continue to disagree about the kinds of evidence or patterns of results that are required to interpret findings related to these concepts. As such inconsistencies can impede progress in both theoretical and empirical research, here, we aim to clarify and propose consensual definitions of these terms.

Author Correction: Maintenance, reserve and compensation: the cognitive neuroscience of healthy ageing.

In the originally published version of article, there were two errors in the references. The reference "Nilsson, J. & Lövdén, M. Naming is not explaining: future directions for the "cognitive reserve" and "brain maintenance" theories. Alzheimer's Res. Ther. 10, 34 (2018)" was missing. This reference has been added as REF. 14 in the HTML and PDF versions of the article and cited at the end of the sentence "However, over the years, these terms have been used inconsistently, creating confusion and slowing progress." on page 701 and at the end of the sentence "If reserve is defined merely as the factor that individuals with greater reserve have and then this factor is used to explain why some individuals have greater reserve, the argument is clearly circular." on page 704. The reference list has been renumbered accordingly. In addition, in the original reference list, REF. 91 was incorrect. The reference should have read "Cabeza, R. Hemispheric asymmetry reduction in older adults. The HAROLD model. Psychol. Aging 17, 85-100 (2002)". This reference, which is REF. 92 in the corrected reference list, has been corrected in the HTML and PDF versions of the article.

Publisher Correction: Maintenance, reserve and compensation: the cognitive neuroscience of healthy ageing.

In Figure 3b of the originally published article, the colours of the bars were incorrectly reversed. The bars shown in green should have been shown in blue to represent the findings from older adults, whereas the bars shown in blue should have been shown in green to represent the findings from young adults. This has been corrected in the HTML and PDF versions of the article. Images of the original figure are shown in the correction notice.

Functional activation features of memory in successful agers across the adult lifespan.

Much neuroimaging research has explored the neural mechanisms underlying successful cognitive aging. Two different patterns of functional activation, maintenance of youth-like activity and compensatory novel recruitment, have been proposed to represent different brain functional features underlying individual differences in cognitive aging. In this study, we investigated the functional features in individuals across the adult lifespan who appeared to resist age-related cognitive decline, in comparison to those with typical age-related declines, over the course of four years. We first implemented latent mixture modeling, a data-driven approach, to classify participants as successful and average agers in middle-aged, young-old, and very old groups, based on their baseline and longitudinal cognitive performance. Then, using fMRI with a subsequent memory paradigm at the follow-up visit, brain activation specifically related to successful encoding (i.e., subsequent memory effect: subsequently remembered with high confidence > subsequently forgotten) was compared between people who established successful cognitive aging versus average aging in the three age groups. Several differences in the subsequent memory effect were revealed. First, across core task-related regions commonly used during successful encoding, successful agers exhibited high subsequent memory effect, at a level comparable to the young control group, until very old age; in contrast, average agers showed reduced subsequent memory effect, compared to successful agers, beginning in young-old age when memory performance also reduced in average agers, compared to successful agers. Second, additional recruitment in prefrontal clusters, distant from the core task-related regions, were identified in the left superior frontal and right orbitofrontal cortices in successful agers of young-old age, possibly reflecting functional compensation in successful aging. In summary, successful agers demonstrate a pattern of youth-like activation spanning from middle age to young-old age, as well as novel frontal recruitment in young-old age. Overall, our study demonstrated evidence of two neural patterns related to successful cognitive aging, offering an integrated view of functional features underlying successful aging, and suggests the importance of studying individuals across the lifespan to understand brain changes occurring in mid and early-late life.

Relationship of prefrontal brain lateralization to optimal cognitive function differs with age.

There is considerable debate about whether additional fMRI-measured activity in the right prefrontal cortex readily observed in older adults represents compensatory activation that enhances cognition or whether maintenance of youthful brain activity best supports cognitive function in late adulthood. To investigate this issue, we tested a large lifespan sample of 461 adults (aged 20-89) and treated degree of left-lateralization in ventrolateral and dorsolateral prefrontal cortex during a semantic judgment fMRI task as an individual differences variable to predict cognition. We found that younger adults were highly left-lateralized, but lateralization did not predict better cognition, whereas higher left-lateralization of prefrontal cortex predicted better cognitive performance in middle-aged adults, providing evidence that left-lateralized, youth-like patterns are optimal in middle age. This relationship was reversed in older adults, with lower laterality scores associated with better cognition. The findings suggest that bilaterality in older adults facilitates cognition, but early manifestation of this pattern during middle age is characteristic of low performers. Implications of these findings for current theories of neurocognitive aging are discussed.

Aerobic exercise training and neurocognitive function in cognitively normal older adults: A one-year randomized controlled trial.

BACKGROUND: Current evidence is inconsistent on the benefits of aerobic exercise training for preventing or attenuating age-related cognitive decline in older adults. OBJECTIVE: To investigate the effects of a 1-year progressive, moderate-to-high intensity aerobic exercise intervention on cognitive function, brain volume, and cortical thickness in sedentary but otherwise healthy older adults. METHODS: We randomized 73 older adults to a 1-year aerobic exercise or stretching-and-toning (active control) program. The primary outcome was a cognitive composite score calculated from eight neuropsychological tests encompassing inductive reasoning, long-term and working memory, executive function, and processing speed. Secondary outcomes were brain volume and cortical thickness assessed by MRI, and cardiorespiratory fitness measured by peak oxygen uptake (VO2 ). RESULTS: One-year aerobic exercise increased peak VO2 by ∼10% (p < 0.001) while it did not change with stretching (p = 0.241). Cognitive composite scores increased in both the aerobic and stretching groups (p < 0.001 for time effect), although no group difference was observed. Total brain volume (p < 0.001) and mean cortical thickness (p = 0.001) decreased in both groups over time, while the reduction in hippocampal volume was smaller in the stretching group compared with the aerobic group (p = 0.040 for interaction). Across all participants, improvement in peak VO2 was positively correlated with increases in cognitive composite score (r = 0.282, p = 0.042) and regional cortical thickness at the inferior parietal lobe (p = 0.016). CONCLUSIONS: One-year aerobic exercise and stretching interventions improved cognitive performance but did not prevent age-related brain volume loss in sedentary healthy older adults. Cardiorespiratory fitness gain was positively correlated with cognitive performance and regional cortical thickness.

Cerebrovascular Reactivity Mapping Using Resting-State BOLD Functional MRI in Healthy Adults and Patients with Moyamoya Disease.

Background Cerebrovascular reserve, the potential capacity of brain tissue to receive more blood flow when needed, is a desirable marker in evaluating ischemic risk. However, current measurement methods require acetazolamide injection or hypercapnia challenge, prompting a clinical need for resting-state (RS) blood oxygen level-dependent (BOLD) functional MRI data to measure cerebrovascular reactivity (CVR). Purpose To optimize and evaluate an RS CVR MRI technique and demonstrate its relationship to neurosurgical treatment. Materials and Methods In this HIPAA-compliant study, RS BOLD functional MRI data collected in 170 healthy controls between December 2008 and September 2010 were retrospectively evaluated to identify the optimal frequency range of temporal filtering on the basis of spatial correlation with the reference standard CVR map obtained with CO2 inhalation. Next, the optimized RS method was applied in a new, prospective cohort of 50 participants with Moyamoya disease who underwent imaging between June 2014 and August 2019. Finally, CVR values were compared between brain hemispheres with and brain hemispheres without revascularization surgery by using Mann-Whitney U test. Results A total of 170 healthy controls (mean age ± standard deviation, 51 years ± 20; 105 women) and 100 brain hemispheres of 50 participants with Moyamoya disease (mean age, 41 years ± 12; 43 women) were evaluated. RS CVR maps based on a temporal filtering frequency of [0, 0.1164 Hz] yielded the highest spatial correlation (r = 0.74) with the CO2 inhalation CVR results. In patients with Moyamoya disease, 77 middle cerebral arteries (MCAs) had stenosis. RS CVR in the MCA territory was lower in the group that did not undergo surgery (n = 30) than in the group that underwent surgery (n = 47) (mean, 0.407 relative units [ru] ± 0.208 vs 0.532 ru ± 0.182, respectively; P = .006), which is corroborated with the CO2 inhalation CVR data (mean, 0.242 ru ± 0.273 vs 0.437 ru ± 0.200; P = .003). Conclusion Cerebrovascular reactivity mapping performed by using resting-state blood oxygen level-dependent functional MRI provided a task-free method to measure cerebrovascular reserve and depicted treatment effect of revascularization surgery in patients with Moyamoya disease comparable to that with the reference standard of CO2 inhalation MRI. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Wolf and Ware in this issue.

Socioeconomic status moderates age-related differences in the brain's functional network organization and anatomy across the adult lifespan.

An individual's environmental surroundings interact with the development and maturation of their brain. An important aspect of an individual's environment is his or her socioeconomic status (SES), which estimates access to material resources and social prestige. Previous characterizations of the relation between SES and the brain have primarily focused on earlier or later epochs of the lifespan (i.e., childhood, older age). We broaden this work to examine the relationship between SES and the brain across a wide range of human adulthood (20-89 years), including individuals from the less studied middle-age range. SES, defined by education attainment and occupational socioeconomic characteristics, moderates previously reported age-related differences in the brain's functional network organization and whole-brain cortical structure. Across middle age (35-64 years), lower SES is associated with reduced resting-state system segregation (a measure of effective functional network organization). A similar but less robust relationship exists between SES and age with respect to brain anatomy: Lower SES is associated with reduced cortical gray matter thickness in middle age. Conversely, younger and older adulthood do not exhibit consistent SES-related difference in the brain measures. The SES-brain relationships persist after controlling for measures of physical and mental health, cognitive ability, and participant demographics. Critically, an individual's childhood SES cannot account for the relationship between their current SES and functional network organization. These findings provide evidence that SES relates to the brain's functional network organization and anatomy across adult middle age, and that higher SES may be a protective factor against age-related brain decline.

White Matter Microstructure Predicts Focal and Broad Functional Brain Dedifferentiation in Normal Aging.

Ventral visual cortex exhibits highly organized and selective patterns of functional activity associated with visual processing. However, this specialization decreases in normal aging, with functional responses to different visual stimuli becoming more similar with age, a phenomenon termed "dedifferentiation." The current study tested the hypothesis that age-related degradation of the inferior longitudinal fasciculus (ILF), a white matter pathway involved in visual perception, could account for dedifferentiation of both localized and distributed brain activity in ventral visual cortex. Participants included 281 adults, ages 20-89 years, from the Dallas Lifespan Brain Study who underwent diffusion-weighted imaging to measure white matter diffusivity, as well as fMRI to measure functional selectivity to viewing photographs from different categories (e.g., faces, houses). In general, decreased ILF anisotropy significantly predicted both focal and broad functional dedifferentiation. Specifically, there was a localized effect of structure on function, such that decreased anisotropy in a smaller mid-fusiform region of ILF predicted less selective (i.e., more dedifferentiated) response to viewing faces in a proximal face-responsive region of fusiform. On the other hand, the whole ILF predicted less selective response across broader ventral visual cortex for viewing animate (e.g., human faces, animals) versus inanimate (e.g., houses, chairs) images. This structure-function relationship became weaker with age and was no longer significant after the age of 70 years. These findings indicate that decreased white matter anisotropy is associated with maladaptive differences in proximal brain function and is an important variable to consider when interpreting age differences in functional selectivity.

Network segregation varies with neural distinctiveness in sensorimotor cortex.

Normal aging is associated with declines in sensorimotor function. Previous studies have linked age-related behavioral declines to decreases in neural differentiation (i.e., dedifferentiation), including decreases in the distinctiveness of neural activation patterns and in the segregation of large-scale neural networks at rest. However, no studies to date have explored the relationship between these two neural measures and whether they explain the same aspects of behavior. To investigate these issues, we collected a battery of sensorimotor behavioral measures in older and younger adults and estimated (a) the distinctiveness of neural representations in sensorimotor cortex and (b) sensorimotor network segregation in the same participants. Consistent with prior findings, sensorimotor representations were less distinct and sensorimotor resting state networks were less segregated in older compared to younger adults. We also found that participants with the most distinct sensorimotor representations exhibited the most segregated sensorimotor networks. However, only sensorimotor network segregation was associated with individual differences in sensorimotor performance, particularly in older adults. These novel findings link network segregation to neural distinctiveness, but also suggest that network segregation may play a larger role in maintaining sensorimotor performance with age.

The association between BOLD-based cerebrovascular reactivity (CVR) and end-tidal CO2 in healthy subjects.

Cerebrovascular reactivity (CVR) mapping using CO2-inhalation can provide important insight into vascular health. At present, blood-oxygenation-level-dependent (BOLD) MRI acquisition is the most commonly used CVR method due to its high sensitivity, high spatial resolution, and relatively straightforward processing. However, large variations in CVR across subjects and across different sessions of the same subject are often observed, which can cloud the ability of this promising measure in detecting diseases or monitoring treatment responses. The present work aims to identify the physiological components underlying the observed variability in CVR data. When studying the association between CVR value and the subject's CO2 levels in a total of N = 253 healthy participants, we found that CVR was lower in individuals with a higher basal end-tidal CO2, EtCO2 (slope = -0.0036 ±â€¯0.0008%/mmHg2, p < 0.001), or with a greater EtCO2 change (ΔEtCO2) with hypercapnic condition (slope = -0.0072 ±â€¯0.0018%/mmHg2, p < 0.001). In a within-subject setting, when studying the CVR difference between two repeated scans (with repositioning) in relation to the corresponding differences in basal EtCO2 and ΔEtCO2 (n = 11), it was found that CVR values were lower if the basal EtCO2 or ΔEtCO2 during that particular scan session was greater. The present work suggests that basal physiological state and the level of hypercapnic stimulus intensity should be considered in application studies of CVR in order to reduce inter-subject and intra-subject variations in the data. Potential approaches to use these findings to reduce noise and augment sensitivity are proposed.

Age-dependent amyloid deposition is associated with white matter alterations in cognitively normal adults during the adult life span.

INTRODUCTION: Both beta-amyloid (Ab) deposition and decline in white matter integrity, are brain alterations observed in Alzheimer's disease (AD) and start to occur by the fourth and fifth decades. However, the association between both brain alterations in asymptomatic subjects is unclear. METHODS: Amyloid positron emission tomography (PET) and diffusion tensor imaging (DTI) were obtained in 282 cognitively normal subjects (age 30-89 years). We assessed the interaction of age by abnormal amyloid PET status (Florbetapir F-18 PET >1.2 standard uptake value ratio [SUVR]) on regional mean diffusivity (MD) and global white matter hyperintensity (WMH) volume, controlled for sex, education, and hypertension. RESULTS: Subjects with abnormal amyloid PET (n = 87) showed stronger age-related increase in global WMH and regional MD, particularly within the posterior parietal regions of the white matter. DISCUSSION: Sporadic Aß deposition is associated with white matter alterations in AD predilection areas in an age-dependent manner in cognitively normal individuals.

ASL-MRICloud: An online tool for the processing of ASL MRI data.

Arterial spin labeling (ASL) MRI is increasingly used in research and clinical settings. The purpose of this work is to develop a cloud-based tool for ASL data processing, referred to as ASL-MRICloud, which may be useful to the MRI community. In contrast to existing ASL toolboxes, which are based on software installation on the user's local computer, ASL-MRICloud uses a web browser for data upload and results download, and the computation is performed on the remote server. As such, this tool is independent of the user's operating system, software version, and CPU speed. The ASL-MRICloud tool was implemented to be compatible with data acquired by scanners from all major MRI manufacturers, is capable of processing several common forms of ASL, including pseudo-continuous ASL and pulsed ASL, and can process single-delay and multi-delay ASL data. The outputs of ASL-MRICloud include absolute and relative values of cerebral blood flow, arterial transit time, voxel-wise masks indicating regions with potential hyper-perfusion and hypo-perfusion, and an image quality index. The ASL tool is also integrated with a T1 -based brain segmentation and normalization tool in MRICloud to allow generation of parametric maps in standard brain space as well as region-of-interest values. The tool was tested on a large data set containing 309 ASL scans as well as on publicly available ASL data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study.

Michigan Neural Distinctiveness (MiND) study protocol: investigating the scope, causes, and consequences of age-related neural dedifferentiation.

BACKGROUND: Aging is often associated with behavioral impairments, but some people age more gracefully than others. Why? One factor that may play a role is individual differences in the distinctiveness of neural representations. Previous research has found that neural activation patterns in visual cortex in response to different visual stimuli are often more similar (i.e., less distinctive) in older vs. young participants, a phenomenon referred to as age-related neural dedifferentiation. Furthermore, older people whose neural representations are less distinctive tend to perform worse on a wide range of behavioral tasks. The Michigan Neural Distinctiveness (MiND) project aims to investigate the scope of neural dedifferentiation (e.g., does it also occur in auditory, motor, and somatosensory cortex?), one potential cause (age-related reductions in the inhibitory neurotransmitter gamma-aminobutyric acid (GABA)), and the behavioral consequences of neural dedifferentiation. This protocol paper describes the study rationale and methods being used in complete detail, but not the results (data collection is currently underway). METHODS: The MiND project consists of two studies: the main study and a drug study. In the main study, we are recruiting 60 young and 100 older adults to perform behavioral tasks that measure sensory and cognitive function. They also participate in functional MRI (fMRI), MR spectroscopy, and diffusion weighted imaging sessions, providing data on neural distinctiveness and GABA concentrations. In the drug study, we are recruiting 25 young and 25 older adults to compare neural distinctiveness, measured with fMRI, after participants take a placebo or a benzodiazepine (lorazepam) that should increase GABA activity. DISCUSSION: By collecting multimodal imaging measures along with extensive behavioral measures from the same subjects, we are linking individual differences in neurochemistry, neural representation, and behavioral performance, rather than focusing solely on group differences between young and old participants. Our findings have the potential to inform new interventions for age-related declines. TRIAL REGISTRATION: This study was retrospectively registered with the ISRCTN registry on March 4, 2019. The registration number is ISRCTN17266136 .

Resting-State Network Topology Differentiates Task Signals across the Adult Life Span.

Brain network connectivity differs across individuals. For example, older adults exhibit less segregated resting-state subnetworks relative to younger adults (Chan et al., 2014). It has been hypothesized that individual differences in network connectivity impact the recruitment of brain areas during task execution. While recent studies have described the spatial overlap between resting-state functional correlation (RSFC) subnetworks and task-evoked activity, it is unclear whether individual variations in the connectivity pattern of a brain area (topology) relates to its activity during task execution. We report data from 238 cognitively normal participants (humans), sampled across the adult life span (20-89 years), to reveal that RSFC-based network organization systematically relates to the recruitment of brain areas across two functionally distinct tasks (visual and semantic). The functional activity of brain areas (network nodes) were characterized according to their patterns of RSFC: nodes with relatively greater connections to nodes in their own functional system ("non-connector" nodes) exhibited greater activity than nodes with relatively greater connections to nodes in other systems ("connector" nodes). This "activation selectivity" was specific to those brain systems that were central to each of the tasks. Increasing age was accompanied by less differentiated network topology and a corresponding reduction in activation selectivity (or differentiation) across relevant network nodes. The results provide evidence that connectional topology of brain areas quantified at rest relates to the functional activity of those areas during task. Based on these findings, we propose a novel network-based theory for previous reports of the "dedifferentiation" in brain activity observed in aging.SIGNIFICANCE STATEMENT Similar to other real-world networks, the organization of brain networks impacts their function. As brain network connectivity patterns differ across individuals, we hypothesized that individual differences in network connectivity would relate to differences in brain activity. Using functional MRI in a group of individuals sampled across the adult life span (20-89 years), we measured correlations at rest and related the functional connectivity patterns to measurements of functional activity during two independent tasks. Brain activity varied in relation to connectivity patterns revealed by large-scale network analysis. This relationship tracked the differences in connectivity patterns accompanied by older age, providing important evidence for a link between the topology of areal connectivity measured at rest and the functional recruitment of these areas during task performance.

Age-related changes in cerebrovascular reactivity and their relationship to cognition: A four-year longitudinal study.

Although cerebrovascular factors are the second leading cause of cognitive impairment and dementia in elderly, the precise spatial and temporal trajectories of vascular decline in aging have not been fully characterized. With an advanced cerebrovascular reactivity (CVR) MRI technique that specifically informs vascular stiffness and dilatory ability of cerebral vessels, we present four-year longitudinal CVR data measured in 116 healthy individuals (20-88 years of age). Our data revealed a spatial heterogeneity in vascular decline in aging (p = 0.003), in that temporal lobe showed the fastest rate of longitudinal CVR decline, followed by parietal and frontal lobes. The rate of CVR decline was also age-dependent. Middle age, not older age, manifested the fastest rate of longitudinal CVR decline (p < 0.05). Longitudinal changes in CVR were associated with changes in processing speed (p = 0.031) and episodic memory (p = 0.022), but not with working memory or reasoning. The rate of longitudinal CVR change was not different between hypertensive and normotensive participants. However, cross-sectionally, individuals with hypertension revealed in a lower CVR compared to normotensive participants (p = 0.016). These findings help elucidate age-related decline in brain hemodynamics and support CVR as a non-invasive biomarker in evaluating cerebrovascular conditions in elderly individuals.

Arterial-spin-labeling (ASL) perfusion MRI predicts cognitive function in elderly individuals: A 4-year longitudinal study.

BACKGROUND: With the disappointing outcomes of clinical trials on patients with Alzheimer's disease or mild cognitive impairment (MCI), there is increasing attention to understanding cognitive decline in normal elderly individuals, with the goal of identifying subjects who are most susceptible to imminent cognitive impairment. PURPOSE/HYPOTHESIS: To evaluate the potential of cerebral blood flow (CBF) as a biomarker by investigating the relationship between CBF at baseline and cognition at follow-up. STUDY TYPE: Prospective longitudinal study with a 4-year time interval. POPULATION: 309 healthy subjects aged 20-89 years old. FIELD STRENGTH/SEQUENCE: 3T pseudo-continuous-arterial-spin-labeling MRI. ASSESSMENT: CBF at baseline and cognitive assessment at both baseline and follow-up. STATISTICAL TESTS: Linear regression analyses with age, systolic blood pressure, physical activity, and baseline cognition as covariates. RESULTS: Linear regression analyses revealed that whole-brain CBF at baseline was predictive of general fluid cognition at follow-up. This effect was observed in the older group (age ≥54 years, ß = 0.221, P = 0.004), but not in younger or entire sample (ß = 0.018, P = 0.867 and ß = 0.089, P = 0.098, respectively). Among major brain lobes, frontal CBF had the highest sensitivity in predicting future cognition, with a significant effect observed for fluid cognition (ß = 0.244 P = 0.001), episodic memory (ß = 0.294, P = 0.001), and reasoning (ß = 0.186, P = 0.027). These associations remained significant after accounting for baseline cognition. Voxelwise analysis revealed that medial frontal cortex and anterior cingulate cortex, part of the default mode network (DMN), are among the most important regions in predicting fluid cognition. DATA CONCLUSION: In a healthy aging cohort, CBF can predict general cognitive ability as well as specific domains of cognitive function. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 3 J. MAGN. RESON. IMAGING 2018;48:449-458.

Cerebrovascular reactivity mapping without gas challenges.

Cerebrovascular reactivity (CVR), the ability of cerebral vessels to dilate or constrict, has been shown to provide valuable information in the diagnosis and treatment evaluation of patients with various cerebrovascular conditions. CVR mapping is typically performed using hypercapnic gas inhalation as a vasoactive challenge while collecting BOLD images, but the inherent need of gas inhalation and the associated apparatus setup present a practical obstacle in applying it in routine clinical use. Therefore, we aimed to develop a new method to map CVR using resting-state BOLD data without the need of gas inhalation. This approach exploits the natural variation in respiration and measures its influence on BOLD MRI signal. In this work, we first identified a surrogate of the arterial CO2 fluctuation during spontaneous breathing from the global BOLD signal. Second, we tested the feasibility and reproducibility of the proposed approach to use the above-mentioned surrogate as a regressor to estimate voxel-wise CVR. Third, we validated the "resting-state CVR map" with a conventional CVR map obtained with hypercapnic gas inhalation in healthy volunteers. Finally, we tested the utility of this new approach in detecting abnormal CVR in a group of patients with Moyamoya disease, and again validated the results using the conventional gas inhalation method. Our results showed that global BOLD signal fluctuation in the frequency range of 0.02-0.04Hz contains the most prominent contribution from natural variation in arterial CO2. The CVR map calculated using this signal as a regressor is reproducible across runs (ICC=0.91±0.06), and manifests a strong spatial correlation with results measured with a conventional hypercapnia-based method in healthy subjects (r=0.88, p<0.001). We also found that resting-state CVR was able to identify vasodilatory deficit in patients with steno-occlusive disease, the spatial pattern of which matches that obtained using the conventional gas method (r=0.71±0.18). These results suggest that CVR obtained with resting-state BOLD may be a useful alternative in detecting vascular deficits in clinical applications when gas challenge is not feasible.

Cognitive Predictors of Everyday Problem Solving across the Lifespan.

BACKGROUND: An important aspect of successful aging is maintaining the ability to solve everyday problems encountered in daily life. The limited evidence today suggests that everyday problem solving ability increases from young adulthood to middle age, but decreases in older age. OBJECTIVES: The present study examined age differences in the relative contributions of fluid and crystallized abilities to solving problems on the Everyday Problems Test (EPT). We hypothesized that due to diminishing fluid resources available with advanced age, crystallized knowledge would become increasingly important in predicting everyday problem solving with greater age. METHOD: Two hundred and twenty-one healthy adults from the Dallas Lifespan Brain Study, aged 24-93 years, completed a cognitive battery that included measures of fluid ability (i.e., processing speed, working memory, inductive reasoning) and crystallized ability (i.e., multiple measures of vocabulary). These measures were used to predict performance on EPT. RESULTS: Everyday problem solving showed an increase in performance from young to early middle age, with performance beginning to decrease at about age of 50 years. As hypothesized, fluid ability was the primary predictor of performance on everyday problem solving for young adults, but with increasing age, crystallized ability became the dominant predictor. CONCLUSION: This study provides evidence that everyday problem solving ability differs with age, and, more importantly, that the processes underlying it differ with age as well. The findings indicate that older adults increasingly rely on knowledge to support everyday problem solving, whereas young adults rely almost exclusively on fluid intelligence.