Cognitive Neuroscience Neuroimaging Repository for the Adult Lifespan

With recent advances in neuroimaging technology, it is now possible to image human brain function in vivo, which revolutionized the cognitive neuroscience field. However, like any other newly developed technique, the acquisition of neuroimaging data is costly and logistically challenging. Furthermore, studying human cognition requires acquiring a large amount of neuroimaging data, which might not be feasible to do by every researcher in the field. Here, we describe our group's efforts to acquire one of the largest neuroimaging datasets that aims to investigate the neural substrates of age-related cognitive decline, which will be made available to share with other investigators. Our neuroimaging repository includes up to 14 different functional images for more than 486 subjects across the entire adult lifespan in addition to their 3 structural images. Currently, data from 234 participants have been acquired, including all 14 functional and 3 structural images, which is planned to increased to 375 participants in the next few years. A complete battery of neuropsychological tests was also administered to all participants. The neuroimaging and accompanying psychometric data will be available through an online and easy-to-use data sharing website

Selective Association between Cortical Thickness and Reference Abilities in Normal Aging

A previous study of reference abilities and cortical thickness reported that association between reference abilities and cortical thickness summarized over large ROIs suppressed was suppressed after controlling for mean cortical thickness and global cognition. In this manuscript, we showed that preserving detailed spatial patterns of cortical thickness can identify reference-ability-specific association besides the association explained by global cognition and mean cortical thickness. We identified associations between cortical thickness and 3 cognitive reference abilities after controlling for mean thickness, global cognition, and linear chronological age: (1) memory, (2) perceptual speed, and (3) vocabulary. Global cognition was correlated with mean overall thickness but also was found to have a regionally specific pattern of associations. Nonlinear associations between cortical thickness and cognition were not observed, neither were nonlinear age effects. Age-by-thickness interactions were also absent. This implies that all thickness-cognition relations and age associations are independent of age and that consequently no age range is inherently special, since brain-behavioral findings are invariant across the whole age range

Research Note, March 1968

This is issue 7: Natural Distribution of Western Larch and Subalpine Larchhttps://scholarworks.umt.edu/montana_forestry_notes/1006/thumbnail.jp

Multivariate and Univariate Analysis of Continuous Arterial Spin Labeling Perfusion MRI in Alzheimer's Disease

Continuous arterial spin labeling (CASL) magnetic resonance imaging (MRI) was combined with multivariate analysis for detection of an Alzheimer's disease (AD)-related cerebral blood flow (CBF) covariance pattern. Whole-brain resting CBF maps were obtained using spin echo, echo planar imaging (SE-EPI) CASL in patients with mild AD (n=12, age=70.7+/-8.7 years, 7 males, modified Mini-Mental State Examination (mMMS)=38.7/57+/-11.1) and age-matched healthy controls (HC) (n=20; age=72.1+/-6.5 years, 8 males). A covariance pattern for which the mean expression was significantly higher (P<0.0005) in AD than in HC was identified containing posterior cingulate, superior temporal, parahippocampal, and fusiform gyri, as well as thalamus, insula, and hippocampus. The results from this analysis were supplemented with those from the more standard, region of interest (ROI) and voxelwise, univariate techniques. All ROIs (17/hemisphere) showed significant decrease in CBF in AD (P<0.001 for all ROIs, alphacorrected=0.05). The area under the ROC curve for discriminating AD versus HC was 0.97 and 0.94 for covariance pattern and gray matter ROI, respectively. Fewer areas of depressed CBF in AD were detected using voxelwise analysis (corrected, P<0.05). These areas were superior temporal, cingulate, middle temporal, fusiform gyri, as well as inferior parietal lobule and precuneus. When tested on extensive split-half analysis to map out the replicability of both multivariate and univariate approaches, the expression of the pattern from multivariate analysis was superior to that of the univariat

Functional Network Mediates Age-Related Differences in Reaction Time: A Replication and Extension Study

INTRODUCTION: A functional activation (i.e., ordinal trend) pattern was previously identified in both young and older adults during task-switching performance, the expression of which correlated with reaction time. The current study aimed to (1) replicate this functional activation pattern in a new group of fMRI activation data, and (2) extend the previous study by specifically examining whether the effect of aging on reaction time can be explained by differences in the activation of the functional activation pattern. METHOD: A total of 47 young and 50 older participants were included in the extension analysis. Participants performed task-switching as the activation task and were cued by the color of the stimulus for the task to be performed in each block. To test for replication, two approaches were implemented. The first approach tested the replicability of the predictive power of the previously identified functional activation pattern by forward applying the pattern to the Study II data and the second approach was rederivation of the activation pattern in the Study II data. RESULTS: Both approaches showed successful replication in the new data set. Using mediation analysis, expression of the pattern from the first approach was found to partially mediate age-related effects on reaction time such that older age was associated with greater activation of the brain pattern and longer reaction time, suggesting that brain activation efficiency (defined as "the rate of activation increase with increasing task difficulty" in Neuropsychologia 47, 2009, 2015) of the regions in the Ordinal trend pattern directly accounts for age-related differences in task performance. DISCUSSION: The successful replication of the functional activation pattern demonstrates the versatility of the Ordinal Trend Canonical Variates Analysis, and the ability to summarize each participant's brain activation map into one number provides a useful metric in multimodal analysis as well as cross-study comparisons

White Matter Tract Covariance Patterns Predict Age-Declining Cognitive Abilities

Previous studies investigating the relationship of white matter (WM) integrity to cognitive abilities and aging have either focused on a global measure or a few selected WM tracts. Ideally, contribution from all of the WM tracts should be evaluated at the same time. However, the high collinearity among WM tracts precludes systematic examination of WM tracts simultaneously without sacrificing statistical power due to stringent multiple-comparison corrections. Multivariate covariance techniques enable comprehensive simultaneous examination of all WM tracts without being penalized for high collinearity among observations. METHOD: In this study, Scaled Subprofile Modeling (SSM) was applied to the mean integrity of 18 major WM tracts to extract covariance patterns that optimally predicted four cognitive abilities (perceptual speed, episodic memory, fluid reasoning, and vocabulary) in 346 participants across ages 20 to 79years old. Using expression of the covariance patterns, age-independent effects of white matter integrity on cognition and the indirect effect of WM integrity on age-related differences in cognition were tested separately, but inferences from the indirect analyses were cautiously made given that cross-sectional data set was used in the analysis. RESULTS: A separate covariance pattern was identified that significantly predicted each cognitive ability after controlling for age except for vocabulary, but the age by WM covariance pattern interaction was not significant for any of the three abilities. Furthermore, each of the patterns mediated the effect of age on the respective cognitive ability. A distinct set of WM tracts was most influential in each of the three patterns. The WM covariance pattern accounting for fluid reasoning showed the most number of influential WM tracts whereas the episodic memory pattern showed the least number. CONCLUSION: Specific patterns of WM tracts make significant contributions to the age-related differences in perceptual speed, episodic memory, and fluid reasoning but not vocabulary. Other measures of brain health will need to be explored to reveal the major influences on the vocabulary ability

The Role of Education and Verbal Abilities in Altering the Effect of Age-Related Gray Matter Differences on Cognition

Evidence suggests that individual variability in lifetime exposures influences how cognitive performance changes with advancing age. Brain maintenance and cognitive reserve are theories meant to account for preserved performance despite advancing age. These theories differ in their causal mechanisms. Brain maintenance predicts more advantageous lifetime exposures will reduce age-related neural differences. Cognitive reserve predicts that lifetime exposures will not directly reduce these differences but minimize their impact on cognitive performance. The present work used moderated-mediation modeling to investigate the contributions of these mechanisms at explaining variability in cognitive performance among a group of 39 healthy younger (mean age (standard deviation) 25.9 (2.92) and 45 healthy older adults (65.2 (2.79)). Cognitive scores were computed using composite measures from three separate domains (speed of processing, fluid reasoning, and memory), while their lifetime exposures were estimated using education and verbal IQ measures. T1-weighted MR images were used to measure cortical thickness and subcortical volumes. Results suggest a stronger role for cognitive reserve mechanisms in explaining age-related cognitive variability: even with age-related reduced gray matter, individuals with greater lifetime exposures could perform better given their quantity of brain measures

An Event-Related fMRI Study of the Neurobehavioral Impact of Sleep Deprivation on Performance of a Delayed-Match-to-Sample Task

Eighteen subjects (ages 18-35) underwent event-related functional magnetic resonance imaging (efMRI) while performing a delayed-match-to-sample (DMS) task before and immediately after 48 h of sustained wakefulness. The DMS trial events were: a 3-s study period of either a one-, three-, or six-letter visual array; a 7-s retention interval; and a 3-s probe period, where a button press indicated whether the probe letter was in the study array. Ordinal Trend Canonical Variates Analysis (OrT CVA) was applied to the data from the probe period for trials with six-letter study lists prior to and immediately following sleep deprivation to find an activation pattern whose expression decreased with sleep deprivation in as many subjects as possible, while being present in both conditions. The first principal component of the OrT analysis identified a covariance pattern whose expression decreased as a function of sleep deprivation in 17 of 18 subjects (p<0.001). While overall expression of the pattern showed a systematic decrease with sleep deprivation, the brain regions that make up the pattern show covarying increases and decreases in activation. Regions that decreased their activation were noted in the parietal (BA 7 and 40), temporal (BA 37, 38 and 39) and occipital (BA 18 and 19) lobes; regions that increased their activation were noted in the cerebellum, basal ganglia, thalamus and the anterior cingulate gyrus (BA 32). The reduction in pattern expression with sleep deprivation for each subject was related to the change in performance on the DMS task. Subject decreases in pattern expression were correlated with reductions in recognition accuracy (p<0.05), increased intra-individual variability in reaction time (p<0.005) and increased lapsing (p<0.005)

Cognitive Reserve and Brain Maintenance: Orthogonal Concepts in Theory and Practice

Cognitive Reserve and Brain Maintenance have traditionally been understood as complementary concepts: Brain Maintenance captures the processes underlying the structural preservation of the brain with age, and might be assessed relative to age-matched peers. Cognitive Reserve, on the other hand, refers to how cognitive processing can be performed regardless of how well brain structure has been maintained. Thus, Brain Maintenance concerns the "hardware," whereas Cognitive Reserve concerns "software," that is, brain functioning explained by factors beyond mere brain structure. We used structural brain data from 368 community-dwelling adults, age 20-80, to derive measures of Brain Maintenance and Cognitive Reserve. We found that Brain Maintenance and Cognitive were uncorrelated such that values on one measure did not imply anything about the other measure. Further, both measures were positively correlated with verbal intelligence and education, hinting at formative influences of the latter to both measures. We performed extensive split-half simulations to check our derived measures' statistical robustness. Our approach enables the out-of-sample quantification of Brain Maintenance and Cognitive Reserve for single subjects on the basis of chronological age, neuropsychological performance and structural brain measures. Future work will investigate the prognostic power of these measures with regard to future cognitive status

Breadth and Age-Dependency of Relations between Cortical Thickness and Cognition

Recent advances in neuroimaging have identified a large number of neural measures that could be involved in age-related declines in cognitive functioning. A popular method of investigating neural-cognition relations has been to determine the brain regions in which a particular neural measure is associated with the level of specific cognitive measures. Although this procedure has been informative, it ignores the strong interrelations that typically exist among the measures in each modality. An alternative approach involves investigating the number and identity of distinct dimensions within the set of neural measures and within the set of cognitive measures before examining relations between the 2 types of measures. The procedure is illustrated with data from 297 adults between 20 and 79 years of age with cortical thickness in different brain regions as the neural measures and performance on 12 cognitive tests as the cognitive measures. The results revealed that most of the relations between cortical thickness and cognition occurred at a general level corresponding to variance shared among different brain regions and among different cognitive measures. In addition, the strength of the thickness-cognition relation was substantially reduced after controlling the variation in age, which suggests that at least some of the thickness-cognition relations in age-heterogeneous samples may be attributable to the influence of age on each type of measure