Genetic Risk for Alzheimer\u27s Disease Alters the Five-Year Trajectory of Semantic Memory Activation in Cognitively Intact Elders

Healthy aging is associated with cognitive declines typically accompanied by increased task-related brain activity in comparison to younger counterparts. The Scaffolding Theory of Aging and Cognition (STAC) (Park and Reuter-Lorenz, 2009; Reuter-Lorenz and Park, 2014) posits that compensatory brain processes are responsible for maintaining normal cognitive performance in older adults, despite accumulation of aging-related neural damage. Cross-sectional studies indicate that cognitively intact elders at genetic risk for Alzheimer\u27s disease (AD) demonstrate patterns of increased brain activity compared to low risk elders, suggesting that compensation represents an early response to AD-associated pathology. Whether this compensatory response persists or declines with the onset of cognitive impairment can only be addressed using a longitudinal design. The current prospective, 5-year longitudinal study examined brain activation in APOE ε4 carriers (N = 24) and non-carriers (N = 21). All participants, ages 65–85 and cognitively intact at study entry, underwent task-activated fMRI, structural MRI, and neuropsychological assessments at baseline, 18, and 57 months. fMRI activation was measured in response to a semantic memory task requiring participants to discriminate famous from non-famous names. Results indicated that the trajectory of change in brain activation while performing this semantic memory task differed between APOE ε4 carriers and non-carriers. The APOE ε4 group exhibited greater activation than the Low Risk group at baseline, but they subsequently showed a progressive decline in activation during the follow-up periods with corresponding emergence of episodic memory loss and hippocampal atrophy. In contrast, the non-carriers demonstrated a gradual increase in activation over the 5-year period. Our results are consistent with the STAC model by demonstrating that compensation varies with the severity of underlying neural damage and can be exhausted with the onset of cognitive symptoms and increased structural brain pathology. Our fMRI results could not be attributed to changes in task performance, group differences in cerebral perfusion, or regional cortical atrophy

Self-Ordered Search: A Novel fMRI Task to Study Working Memory in Children with Catastrophic Disease

Children treated for brain tumors are at increased risk for developing cognitive deficits. The self-ordered search (SOS) is a computerized neuropsychological test used to investigate working memory, a cognitive system whose function is integral to many high level cognitive processes. Functional-MRI (fMRI) provides important opportunities to characterize neural correlates of SOSperformance non-invasively. Implementation of the SOStask presents challenges in the unique environment of the MRI scanner. First, SOSrequires participants to select a single stimulus from a set. Second, SOSis a behaviorally driven task that entails variable event timing among participants which complicates group analysis of fMRI data. The work presented here consists of the implementation, validation and application of the SOSfor fMRI and associated analysis techniques. Eye-tracking with a MRI-safe response device was used as an interface for the fMRI task, allowing the participant to select an individual stimulus from a two-dimensional array. Performance information was used to generate individual subject design matrices for fMRI analysis, preserving important behaviorally measures (time to completion). Healthy volunteers and patients treated for childhood brain tumors performed the SOS task and N-back task, a commonly used working memory task for fMRI. The eye-tracking interface performed well after initial problems with equipment and calibration routine were solved. Activation patterns identified by general linear model (GLM) analysis were similar between SOS and N-back tasks and included dorsolateral prefrontal cortex, ventral prefrontal cortex, dorsal cingulate, bilateral premotor, and parietal areas. Independent component analysis identified task-correlated components that were consistent with the GLM. Increasing activation across the general network was associated with fewer errors during the N-back task. Differences in activation between patient group and healthy group were identified in the parietal and retrosplenial cortex. Analysis of the performance data suggests differences between the healthy and patient groups. Our novel eye-tracking interface provides a natural interface that controls for movement and motor planning associated with complex response devices. The SOS for fMRI provides a new tool that will allow us to investigate deficits of working memory in children treated for brain tumors

Experimental Design Modulates Variance in BOLD Activation: The Variance Design General Linear Model

Typical fMRI studies have focused on either the mean trend in the blood-oxygen-level-dependent (BOLD) time course or functional connectivity (FC). However, other statistics of the neuroimaging data may contain important information. Despite studies showing links between the variance in the BOLD time series (BV) and age and cognitive performance, a formal framework for testing these effects has not yet been developed. We introduce the Variance Design General Linear Model (VDGLM), a novel framework that facilitates the detection of variance effects. We designed the framework for general use in any fMRI study by modeling both mean and variance in BOLD activation as a function of experimental design. The flexibility of this approach allows the VDGLM to i) simultaneously make inferences about a mean or variance effect while controlling for the other and ii) test for variance effects that could be associated with multiple conditions and/or noise regressors. We demonstrate the use of the VDGLM in a working memory application and show that engagement in a working memory task is associated with whole-brain decreases in BOLD variance.Comment: 18 pages, 7 figure

Using event-related fMRI to examine sustained attention processes and effects of APOE ε4 in young adults

In this study we investigated effects of the APOE ε4 allele (which confers an enhanced risk of poorer cognitive ageing, and Alzheimer’s Disease) on sustained attention (vigilance) performance in young adults using the Rapid Visual Information Processing (RVIP) task and event-related fMRI. Previous fMRI work with this task has used block designs: this study is the first to image an extended (6-minute) RVIP task. Participants were 26 carriers of the APOE ε4 allele, and 26 non carriers (aged 18–28). Pupil diameter was measured throughout, as an index of cognitive effort. We compared activity to RVIP task hits to hits on a control task (with similar visual parameters and response requirements but no working memory load): this contrast showed activity in medial frontal, inferior and superior parietal, temporal and visual cortices, consistent with previous work, demonstrating that meaningful neural data can be extracted from the RVIP task over an extended interval and using an event-related design. Behavioural performance was not affected by genotype; however, a genotype by condition (experimental task/control task) interaction on pupil diameter suggested that ε4 carriers deployed more effort to the experimental compared to the control task. fMRI results showed a condition by genotype interaction in the right hippocampal formation: only ε4 carriers showed downregulation of this region to experimental task hits versus control task hits. Experimental task beta values were correlated against hit rate: parietal correlations were seen in ε4 carriers only, frontal correlations in non-carriers only. The data indicate that, in the absence of behavioural differences, young adult ε4 carriers already show a different linkage between functional brain activity and behaviour, as well as aberrant hippocampal recruitment patterns. This may have relevance for genotype differences in cognitive ageing trajectories

Introduction to fMRI: experimental design and data analysis

This provides an introduction to functional MRI, experimental design and data analysis procedures using statistical parametric mapping approach

Optimizing Preprocessing and Analysis Pipelines for Single-Subject fMRI: 2. Interactions with ICA, PCA, Task Contrast and Inter-Subject Heterogeneity

A variety of preprocessing techniques are available to correct subject-dependant artifacts in fMRI, caused by head motion and physiological noise. Although it has been established that the chosen preprocessing steps (or “pipeline”) may significantly affect fMRI results, it is not well understood how preprocessing choices interact with other parts of the fMRI experimental design. In this study, we examine how two experimental factors interact with preprocessing: between-subject heterogeneity, and strength of task contrast. Two levels of cognitive contrast were examined in an fMRI adaptation of the Trail-Making Test, with data from young, healthy adults. The importance of standard preprocessing with motion correction, physiological noise correction, motion parameter regression and temporal detrending were examined for the two task contrasts. We also tested subspace estimation using Principal Component Analysis (PCA), and Independent Component Analysis (ICA). Results were obtained for Penalized Discriminant Analysis, and model performance quantified with reproducibility (R) and prediction metrics (P). Simulation methods were also used to test for potential biases from individual-subject optimization. Our results demonstrate that (1) individual pipeline optimization is not significantly more biased than fixed preprocessing. In addition, (2) when applying a fixed pipeline across all subjects, the task contrast significantly affects pipeline performance; in particular, the effects of PCA and ICA models vary with contrast, and are not by themselves optimal preprocessing steps. Also, (3) selecting the optimal pipeline for each subject improves within-subject (P,R) and between-subject overlap, with the weaker cognitive contrast being more sensitive to pipeline optimization. These results demonstrate that sensitivity of fMRI results is influenced not only by preprocessing choices, but also by interactions with other experimental design factors. This paper outlines a quantitative procedure to denoise data that would otherwise be discarded due to artifact; this is particularly relevant for weak signal contrasts in single-subject, small-sample and clinical datasets

Encoding Multi-Resolution Brain Networks Using Unsupervised Deep Learning

The main goal of this study is to extract a set of brain networks in multiple time-resolutions to analyze the connectivity patterns among the anatomic regions for a given cognitive task. We suggest a deep architecture which learns the natural groupings of the connectivity patterns of human brain in multiple time-resolutions. The suggested architecture is tested on task data set of Human Connectome Project (HCP) where we extract multi-resolution networks, each of which corresponds to a cognitive task. At the first level of this architecture, we decompose the fMRI signal into multiple sub-bands using wavelet decompositions. At the second level, for each sub-band, we estimate a brain network extracted from short time windows of the fMRI signal. At the third level, we feed the adjacency matrices of each mesh network at each time-resolution into an unsupervised deep learning algorithm, namely, a Stacked De- noising Auto-Encoder (SDAE). The outputs of the SDAE provide a compact connectivity representation for each time window at each sub-band of the fMRI signal. We concatenate the learned representations of all sub-bands at each window and cluster them by a hierarchical algorithm to find the natural groupings among the windows. We observe that each cluster represents a cognitive task with a performance of 93% Rand Index and 71% Adjusted Rand Index. We visualize the mean values and the precisions of the networks at each component of the cluster mixture. The mean brain networks at cluster centers show the variations among cognitive tasks and the precision of each cluster shows the within cluster variability of networks, across the subjects.Comment: 6 pages, 3 figures, submitted to The 17th annual IEEE International Conference on BioInformatics and BioEngineerin

Using fMRI in experimental philosophy: Exploring the prospects

This chapter analyses the prospects of using neuroimaging methods, in particular functional magnetic resonance imaging (fMRI), for philosophical purposes. To do so, it will use two case studies from the field of emotion research: Greene et al. (2001) used fMRI to uncover the mental processes underlying moral intuitions, while Lindquist et al. (2012) used fMRI to inform the debate around the nature of a specific mental process, namely, emotion. These studies illustrate two main approaches in cognitive neuroscience: Reverse inference and ontology testing, respectively. With regards to Greene et al.’s study, the use of Neurosynth (Yarkoni 2011) will show that the available formulations of reverse inference, although viable a priori, seem to be of limited use in practice. On the other hand, the discussion of Lindquist et al.’s study will present the so far neglected potential of ontology-testing approaches to inform philosophical questions

fMRI biomarkers of social cognitive skills training in psychosis: Extrinsic and intrinsic functional connectivity.

Social cognitive skills training interventions for psychotic disorders have shown improvement in social cognitive performance tasks, but little was known about brain-based biomarkers linked to treatment effects. In this pilot study, we examined whether social cognitive skills training could modulate extrinsic and intrinsic functional connectivity in psychosis using functional magnetic resonance imaging (fMRI). Twenty-six chronic outpatients with psychotic disorders were recruited from either a Social Cognitive Skills Training (SCST) or an activity- and time-matched control intervention. At baseline and the end of intervention (12 weeks), participants completed two social cognitive tasks: a Facial Affect Matching task and a Mental State Attribution Task, as well as resting-state fMRI (rs-fMRI). Extrinsic functional connectivity was assessed using psychophysiological interaction (PPI) with amygdala and temporo-parietal junction as a seed region for the Facial Affect Matching Task and the Mental State Attribution task, respectively. Intrinsic functional connectivity was assessed with independent component analysis on rs-fMRI, with a focus on the default mode network (DMN). During the Facial Affect Matching task, we observed stronger PPI connectivity in the SCST group after intervention (compared to baseline), but no treatment-related change in the Control group. Neither group showed treatment-related changes in PPI connectivity during the Mental State Attribution task. During rs-fMRI, we found treatment-related changes in the DMN in the SCST group, but not in Control group. This study found that social cognitive skills training modulated both extrinsic and intrinsic functional connectivity in individuals with psychotic disorders after a 12-week intervention. These findings suggest treatment-related changes in functional connectivity as a potential brain-based biomarker of social cognitive skills training

Age of second language acquisition affects nonverbal conflict processing in children : an fMRI study

Background: In their daily communication, bilinguals switch between two languages, a process that involves the selection of a target language and minimization of interference from a nontarget language. Previous studies have uncovered the neural structure in bilinguals and the activation patterns associated with performing verbal conflict tasks. One question that remains, however is whether this extra verbal switching affects brain function during nonverbal conflict tasks. Methods: In this study, we have used fMRI to investigate the impact of bilingualism in children performing two nonverbal tasks involving stimulus-stimulus and stimulus-response conflicts. Three groups of 8-11-year-old children - bilinguals from birth (2L1), second language learners (L2L), and a control group of monolinguals (1L1) - were scanned while performing a color Simon and a numerical Stroop task. Reaction times and accuracy were logged. Results: Compared to monolingual controls, bilingual children showed higher behavioral congruency effect of these tasks, which is matched by the recruitment of brain regions that are generally used in general cognitive control, language processing or to solve language conflict situations in bilinguals (caudate nucleus, posterior cingulate gyrus, STG, precuneus). Further, the activation of these areas was found to be higher in 2L1 compared to L2L. Conclusion: The coupling of longer reaction times to the recruitment of extra language-related brain areas supports the hypothesis that when dealing with language conflicts the specialization of bilinguals hampers the way they can process with nonverbal conflicts, at least at early stages in life