Encoding and storage components of verbal working memory as revealed by a factorial design, an FMRI study

In this fMRI study, the contributions of frontal and posterior brain regions to verbal working memory were investigated. A two-factor design with low and high memory load (2 and 5 letters) and short and long delay (4 and 12 secs.) as factors were used. Based on reports in the literature, we expect activity in the following frontal and parietal brain regions of interest (ROIs): Brodmann areas (BA) 6, 9, 46, 44, 45, 7 and 40. The analysis of collected flvM data involved image processing and statistical analysis methods including realignment, spatial normalization, spatial smoothing, temporal filtering, intensity normalization, statistical tests, and thresholding of results. The design allowed for testing the interaction and main effects of the two factors. The interaction terms revealed involvement in the caudate and BA 6, 9, and 7. The main effects revealed activity in BA 6, 9, 32, 40, 44, cerebellum, thalamus, and caudate. The results of this study support the literature and offer more insight into previous findings

Characterization of mismatch between behavioral stimuli and FRMI data using the Kalman filter

The advance of blood oxygen level dependent function magnetic resonance imaging, (BOLD fMRI), allows researchers to non-invasively investigate the functioning human brain. The BOLD fMRI response to brief stimuli is called the hemodynamic response function (HRF), which can vary across brain regions and across subjects. Models of the HRF are used to increase sensitivity of statistical maps; however, they often don\u27t account for spatial and temporal variance. Physiological effects, such as learning, fatigue or habituation, introduce mismatch between statistical models and the data. Methods that use minimal a priori information and track time varying signals are able to show the processing of information over time and thereby elucidate such effects. The method of Kalman filtering was employed to characterize mismatches occurring between statistical models and BOLD data. The Kalman filter operates on data point by point. This contrasts regression techniques, that use blocks of data to find a single estimate. Functional MRI data was collected from ten subjects at Columbia University while they engaged in three visual experiments and four olfactory experiments. The Kalman filter was used to distinguish between the fMRI response to a 2 second and a 12 second visual stimulus. The results from this analysis showed the extracted responses from the two stimuli significantly differed. The same analysis was also used to distinguish between primary and secondary olfactory cortices. These brain regions have shown differential temporal responses to odorants. The extracted responses were not significantly different. Extracted responses from one stimulus (visual or olfactory) were used to test if this subject specific information would predict the next experimental session, better than standard a priori models of the data. The results of this analysis showed this not to be the case. The extracted response over time to the odorant stimuli were tractable with the Kalman filter, and shown to decay as predicted from the literature. This temporal change was hypothesized to decrease predictability from one session to the next, causing the null result. To alleviate this, models were tested for their predictability across hemisphere, within session. The results showed that inclusion of subject specific information improved this fit over other a priori models. The implications of this analysis are the ability to extract temporally varying fMRI responses over an experiment without knowledge of the expected response to a stimuli. Results of such analyzes offer a look into how the brain responds and processes stimuli over the course of an experiment. This contrasts method that offer summary, or average, results from an experiment

Exploring the Neural Basis of Cognitive Reserve in Aging

The concept of reserve arose from the mismatch between the extent of brain changes or pathology and the clinical manifestations of these brain changes. The cognitive reserve hypothesis posits that individual differences in the flexibility and adaptability of brain networks underlying cognitive function may allow some people to cope better with brain changes than others. Although there is ample epidemiologic evidence for cognitive reserve, the neural substrate of reserve is still a topic of ongoing research. Here we review some representative studies from our group that exemplify possibilities for the neural substrate of reserve including neural reserve, neural compensation, and generalized cognitive reserve networks. We also present a schematic overview of our ongoing research in this area. This article is part of a Special Issue entitled: Imaging Brain Aging and Neurodegenerative disease

The Role of Lifetime Exposures across Cognitive Domains in Barbados Using Data From the SABE Study

This study characterized the effects of aging on individual cognitive domains and how sex, job type, and years of education alter the age effect on older adults from Barbados. This was an analysis of the cross-sectional data collected as part of the SABE Study (Health, Well-being and Ageing) in 2006. The loss of a single point in each of the individual cognitive domains assessed using the mini-mental state exam served as dependent variables. Independent variables included age, sex, years of education, job type, and the interactions with age in a series of logistic regression analyses. The study aimed to identify which factors altered the effect of age on cognitive performance and which directly affected performance. Results demonstrated that the effect of age differed across the cognitive domains. In addition, sex, education, and job type all differentially affected cognitive performance in an additive, formative manner. The most consistent finding was that high years of education coupled with employment requiring mostly mental effort was the best combination for maintaining high levels of cognitive performance in late life. The results demonstrate that adverse age effects on cognitive performance may be minimized or delayed through modifiable lifetime exposures in the people of Barbados

Supporting Performance in the Face of Age-Related Neural Changes: Testing Mechanistic Roles of Cognitive Reserve

Age impacts multiple neural measures and these changes do not always directly translate into alterations in clinical and cognitive measures. This partial protection from the deleterious effects of age in some individuals is referred to as cognitive reserve (CR) and although linked to variations in intelligence and life experiences, its mechanism is still unclear. Within the framework of a theoretical model we tested two potential mechanistic roles of CR to maintain task performance, neural reserve and neural compensation, in young and older adults using functional and structural MRI. Neural reserve refers to increased efficiency and/or capacity of existing functional neural resources. Neural compensation refers to the increased ability to recruit new, additional functional resources. Using structural and functional measures and task performance, the roles of CR were tested using path analysis. Results supported both mechanistic theories of CR and the use of our general theoretical model

The Indirect Effect of Age Group on Switch Costs Via Gray Matter Volume and Task-Related Brain Activity

Healthy aging simultaneously affects brain structure, brain function, and cognition. These effects are often investigated in isolation ignoring any relationships between them. It is plausible that age related declines in cognitive performance are the result of age-related structural and functional changes. This straightforward idea is tested in within a conceptual research model of cognitive aging. The current study tested whether age-related declines in task-performance were explained by age-related differences in brain structure and brain function using a task-switching paradigm in 175 participants. Sixty-three young and 112 old participants underwent MRI scanning of brain structure and brain activation. The experimental task was an executive context dual task with switch costs in response time as the behavioral measure. A serial mediation model was applied voxel-wise throughout the brain testing all pathways between age group, gray matter volume, brain activation and increased switch costs, worsening performance. There were widespread age group differences in gray matter volume and brain activation. Switch costs also significantly differed by age group. There were brain regions demonstrating significant indirect effects of age group on switch costs via the pathway through gray matter volume and brain activation. These were in the bilateral precuneus, bilateral parietal cortex, the left precentral gyrus, cerebellum, fusiform, and occipital cortices. There were also significant indirect effects via the brain activation pathway after controlling for gray matter volume. These effects were in the cerebellum, occipital cortex, left precentral gyrus, bilateral supramarginal, bilateral parietal, precuneus, middle cingulate extending to medial superior frontal gyri and the left middle frontal gyri. There were no significant effects through the gray matter volume alone pathway. These results demonstrate that a large proportion of the age group effect on switch costs can be attributed to individual differences in gray matter volume and brain activation. Therefore, age-related neural effects underlying cognitive control are a complex interaction between brain structure and function. Furthermore, the analyses demonstrate the feasibility of utilizing multiple neuroimaging modalities within a conceptual research model of cognitive aging

Can the Default-Mode Network Be Described with One Spatial-Covariance Network?

The default-mode network (DMN) has become a well accepted concept in cognitive and clinical neuroscience over the last decade, and perusal of the recent literature attests to a stimulating research field of cognitive and diagnostic applications (for example, (Andrews-Hanna et al., 2010; Koch et al., 2010; Sheline et al., 2009a; Sheline et al., 2009b; Uddin et al., 2008; Uddin et al., 2009; Weng et al., 2009; Yan et al., 2009)). However, a formal definition of what exactly constitutes a functional brain network is difficult to come by. In recent contributions, some researchers argue that the DMN is best understood as multiple interacting subsystems (Buckner et al., 2008) and have explored modular components of the DMN that have different functional specialization and could to some extent be identified separately (Fox et al., 2005; Uddin et al., 2009). Such conception of modularity seems to imply an opposite construct of a 'unified whole', but it is difficult to locate proponents of the idea of a DMN who are supplying constraints that can be brought to bear on data in rigorous tests. Our aim in this paper is to present a principled way of deriving a single covariance pattern as the neural substrate of the DMN, test to what extent its behavior tracks the coupling strength between critical seed regions, and investigate to what extent our stricter concept of a network is consistent with the already established findings about the DMN in the literature. We show that our approach leads to a functional covariance pattern whose pattern scores are a good proxy for the integrity of the connections between a medioprefrontal, posterior cingulate and parietal seed regions. Our derived DMN network thus has potential for diagnostic applications that are simpler to perform than computation of pairwise correlational strengths or seed maps

Contrasting Visual Working Memory for Verbal and Non-Verbal Material with Multivariate Analysis of fMRI

We performed a Delayed-Item-Recognition task to investigate the neural substrates of non-verbal visual working memory with event-related fMRI ('Shape task'). 25 young subjects (mean age: 24.0 years; STD=3.8 years) were instructed to study a list of either 1, 2 or 3 unnamable nonsense line drawings for 3s ('stimulus phase' or STIM). Subsequently, the screen went blank for 7s ('retention phase' or RET), and then displayed a probe stimulus for 3s in which subjects indicated with a differential button press whether the probe was contained in the studied shape-array or not ('probe phase' or PROBE). Ordinal Trend Canonical Variates Analysis (Habeck et al., 2005a) was performed to identify spatial covariance patterns that showed a monotonic increase in expression with memory load during all task phases. Reliable load-related patterns were identified in the stimulus and retention phase (p<0.01), while no significant pattern could be discerned during the probe phase. Spatial covariance patterns that were obtained from an earlier version of this task (Habeck et al., 2005b) using 1, 3, or 6 letters ('Letter task') were also prospectively applied to their corresponding task phases in the current non-verbal task version. Interestingly, subject expression of covariance patterns from both verbal and non-verbal retention phases correlated positively in the non-verbal task for all memory loads (p<0.0001). Both patterns also involved similar frontoparietal brain regions that were increasing in activity with memory load, and mediofrontal and temporal regions that were decreasing. Mean subject expression of both patterns across memory load during retention also correlated positively with recognition accuracy (d(L)) in the Shape task (p<0.005). These findings point to similarities in the neural substrates of verbal and non-verbal rehearsal processes. Encoding processes, on the other hand, are critically dependent on the to-be-remembered material, and seem to necessitate material-specific neural substrates

Neuroimaging Explanations of Age-Related Differences in Task Performance

Advancing age affects both cognitive performance and functional brain activity and interpretation of these effects has led to a variety of conceptual research models without always explicitly linking the two effects. However, to best understand the multifaceted effects of advancing age, age differences in functional brain activity need to be explicitly tied to the cognitive task performance. This work hypothesized that age-related differences in task performance are partially explained by age-related differences in functional brain activity and formally tested these causal relationships. Functional MRI data was from groups of young and old adults engaged in an executive task-switching experiment. Analyses were voxel-wise testing of moderated-mediation and simple mediation statistical path models to determine whether age group, brain activity and their interaction explained task performance in regions demonstrating an effect of age group. Results identified brain regions whose age-related differences in functional brain activity significantly explained age-related differences in task performance. In all identified locations, significant moderated-mediation relationships resulted from increasing brain activity predicting worse (slower) task performance in older but not younger adults. Findings suggest that advancing age links task performance to the level of brain activity. The overall message of this work is that in order to understand the role of functional brain activity on cognitive performance, analysis methods should respect theoretical relationships. Namely, that age affects brain activity and brain activity is related to task performance