[Show abstract][Hide abstract] ABSTRACT: Children with ADHD are hyper-connected within both the CON and DMN.•More DMN–Visual antagonism supports better attention, particularly in controls.•More DMN–CON antagonism supports better attention only in children with ADHD.•CON–DMN compensation for attention may be due to stimulant medication use.
[Show abstract][Hide abstract] ABSTRACT: A recent interest in resting state functional magnetic resonance imaging
(rsfMRI) lies in subdividing the human brain into functionally distinct regions
of interest. Brain parcellation is often a necessary step for defining the
network nodes used in connectivity studies. While inference has traditionally
been performed on group-level data, there is a growing interest in parcellating
single subject data. However, this is difficult due to the inherent low SNR of
rsfMRI data, combined with short scan lengths. A large number of brain
parcellation approaches employ clustering, which begins with a measure of
similarity between voxels. The goal of this work is to improve the
reproducibility of single-subject parcellation using shrinkage-based estimators
of such measures, allowing the noisy subject-specific estimator to borrow
strength from a larger population of subjects. We present several shrinkage
estimators and outline methods for shrinkage when multiple scans are not
available for each subject. We perform shrinkage on raw inter-voxel correlation
estimates and use both raw and shrinkage estimates to produce parcellations by
performing clustering on the voxels. The proposed method is agnostic to the
choice of clustering method and can be used as a pre-processing step for any
clustering algorithm. Using two datasets - a simulated dataset where the true
parcellation is known and is subject-specific and a test-retest dataset
consisting of two 7-minute resting-state fMRI scans from 20 subjects - we show
that parcellations produced from shrinkage correlation estimates have higher
reliability and validity than those produced from raw correlation estimates.
Application to test-retest data shows that using shrinkage estimators increases
the reproducibility of subject-specific parcellations of the motor cortex by up
to 30 percent.
[Show abstract][Hide abstract] ABSTRACT: In addition to the BOLD scan, quantitative functional MRI studies require measurement of both cerebral blood volume (CBV) and flow (CBF) dynamics. The ability to detect CBV and CBF responses in a single additional scan would shorten the total scan time and reduce temporal variations. Several approaches for simultaneous CBV and CBF measurement during functional MRI experiments have been proposed in two-dimensional (2D) mode covering one to three slices in one repetition time (TR). Here, we extended the principles from previous work and present a three-dimensional (3D) whole-brain MRI approach that combines the vascular-space-occupancy (VASO) and flow-sensitive alternating inversion recovery (FAIR) arterial spin labeling (ASL) techniques, allowing the measurement of CBV and CBF dynamics, respectively, in a single scan. 3D acquisitions are complicated for such a scan combination as the time to null blood signal during a steady state needs to be known. We estimated this using Bloch simulations and demonstrate that the resulting 3D acquisition can detect activation patterns and relative signal changes of quality comparable to that of the original separate scans. The same was found for temporal signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). This approach provides improved acquisition efficiency when both CBV and CBF responses need to be monitored during a functional task.
[Show abstract][Hide abstract] ABSTRACT: Resting-state functional magnetic resonance imaging (rs-fMRI) is used to investigate synchronous activations in spatially distinct regions of the brain, which are thought to reflect functional systems supporting cognitive processes. Analyses are often performed using seed-based correlation analysis, allowing researchers to explore functional connectivity between data in a seed region and the rest of the brain. Using scan-rescan rs-fMRI data, we investigate how well the subject-specific seed-based correlation map from the second replication of the study can be predicted using data from the first replication. We show that one can dramatically improve prediction of subject-specific connectivity by borrowing strength from the group correlation map computed using all other subjects in the study. Even more surprisingly, we found that the group correlation map provided a better prediction of a subject's connectivity than the individual's own data. While further discussion and experimentation is required to understand how this can be used in practice, results indicate that shrinkage-based methods that borrow strength from the population mean should play a role in rs-fMRI data analysis.
[Show abstract][Hide abstract] ABSTRACT: Recent studies have illustrated that motion-related artifacts remain in resting-state fMRI (rs-fMRI) data even after common corrective processing procedures have been applied, but the extent to which head motion distorts the data may be modulated by the corrective approach taken. We compare two different methods for estimating nuisance signals from tissues not expected to exhibit BOLD fMRI signals of neuronal origin: 1) the more commonly used mean signal method and 2) the principal components analysis approach (aCompCor: Behzadi et al., 2007). Further, we investigate the added benefit of ``scrubbing" (Power et al., 2012) following both methods. We demonstrate that the use of aCompCor removes motion artifacts more effectively than tissue-mean signal regression. In addition, inclusion of more components from anatomically defined regions of no interest better mitigates motion-related artifacts and improves the specificity of functional connectivity estimates. While scrubbing further attenuates motion-related artifacts when mean signals are used, scrubbing provides no additional benefit in terms of motion artifact reduction or connectivity specificity when using aCompCor.
[Show abstract][Hide abstract] ABSTRACT: Huntington's disease (HD) is a neurodegenerative disease caused by cytosine-adenine-guanine (CAG)-repeat expansion in the huntingtin (HTT) gene. Early changes that may precede clinical manifestation of movement disorder include executive dysfunction. The aim of this study was to identify functional network correlates of impaired higher cognitive functioning in relation to HD stage. Blood-oxygenation-level-dependent (BOLD) functional-magnetic resonance imaging (fMRI) and structural-MRI were performed in 53 subjects with the HD-mutation (41 prodromals, 12 early affected) and 52 controls. Disease stage was estimated for each subject with HD-mutation based on age, length of the CAG-repeat expansion mutation and also putaminal atrophy. The Tower of London test was administered with three levels of complexity during fMRI as a challenge of executive function. Functional brain networks of interest were identified based on cortical gray matter voxel-clusters with significantly enhanced task-related functional coupling to the medial prefrontal cortex (MPFC) area. While prodromal HD-subjects showed similar performance levels as controls, multivariate analysis of task-related functional coupling to the MPFC identified reduced connectivity in prodromal and early manifest HD-subjects for a cluster including mainly parts of the left premotor area. Secondary testing indicated a significant moderator effect for task complexity on group differences and on the degree of correlation to measures of HD stage. Our data suggest that impaired premotor-MPFC coupling reflects HD stage related dysfunction of cognitive systems involved in executive function and may be present in prodromal HD-subjects that are still cognitively normal. Additional longitudinal studies may reveal temporal relationships between impaired task-related premotor-MPFC coupling and other brain changes in HD.
[Show abstract][Hide abstract] ABSTRACT: Objective:Cognitive dysfunction is a core feature of schizophrenia, and persons at risk for schizophrenia may show subtle deficits in attention and working memory. In this study, we investigated the relationship between integrity of functional brain networks and performance in attention and working memory tasks as well as schizophrenia risk.Methods:A total of 235 adults representing 3 levels of risk (102 outpatients with schizophrenia, 70 unaffected first-degree relatives of persons with schizophrenia, and 63 unrelated healthy controls [HCs]) completed resting-state functional magnetic resonance imaging and a battery of attention and working memory tasks (Brief Test of Attention, Hopkins Verbal Learning Test, and Brief Visuospatial Memory Test) on the same day. Functional networks were defined based on coupling with seeds in the dorsal anterior cingulate cortex, dorsolateral prefrontal cortex (DLPFC), medial prefrontal cortex (MPFC), and primary visual cortex. Networks were then dissected into regional clusters of connectivity that were used to generate individual interaction matrices representing functional connectivity within each network.Results:Both patients with schizophrenia and their first-degree relatives showed cognitive dysfunction compared with HCs. First canonicals indicated an inverse relationship between cognitive performance and connectivity within the DLPFC and MPFC networks. Multivariate analysis of variance revealed multivariate main effects of higher schizophrenia risk status on increased connectivity within the DLPFC and MPFC networks.Conclusions:These data suggest that excessive connectivity within brain networks coupled to the DLPFC and MPFC, respectively, accompany cognitive deficits in persons at risk for schizophrenia. This might reflect compensatory reactions in neural systems required for cognitive processing of attention and working memory tasks to brain changes associated with schizophrenia.
[Show abstract][Hide abstract] ABSTRACT: Inhibitory control commonly recruits a number of frontal regions: pre-SMA, FEFs, and right-lateralized posterior inferior frontal gyrus (IFG), dorsal anterior insula (DAI), dorsolateral pFC, and inferior frontal junction. These regions may directly implement inhibitory motor control or may be more generally involved in executive control functions. Two go/no-go tasks were used to distinguish regions specifically recruited for inhibition from those that additionally show increased activity with working memory demand. The pre-SMA and IFG were recruited for inhibition in both tasks and did not have greater activation for working memory demand on no-go trials, consistent with a role in inhibitory control. Activation in pre-SMA also responded to response selection demand and was increased with working memory on go trials specifically. The bilateral FEF and right DAI were commonly active for no-go trials. The FEF was also recruited to a greater degree with working memory demand on go trials and may be involved in top-down biasing when stimulus-response mappings change. The DAI responded to increased working memory demand on both go and no-go trials and may be involved in accessing sustained task information, alerting, or autonomic changes when cognitive demands increase. The dorsolateral pFC had increased activation for working memory demand during both go and no-go trials, consistent with a role in working memory retrieval. The inferior frontal junction, on the other hand, had greater activation with working memory specifically for no-go trials and may detect salient stimuli when the task requires frequent updating of working memory representations.
Journal of Cognitive Neuroscience 03/2013; · 4.49 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Independent Component Analysis (ICA) is a computational technique for
revealing latent factors that underlie sets of measurements or signals. It has
become a standard technique in functional neuroimaging. In functional
neuroimaging, so called group ICA (gICA) seeks to identify and quantify
networks of correlated regions across subjects. This paper reports on the
development of a new group ICA approach, Homotopic Group ICA (H-gICA), for
blind source separation of resting state functional magnetic resonance imaging
(fMRI) data. Resting state brain functional homotopy is the similarity of
spontaneous fluctuations between bilaterally symmetrically opposing regions
(i.e. those symmetric with respect to the mid-sagittal plane) (Zuo et al.,
2010). The approach we proposed improves network estimates by leveraging this
known brain functional homotopy. H-gICA increases the potential for network
discovery, effectively by averaging information across hemispheres. It is
theoretically proven to be identical to standard group ICA when the true
sources are both perfectly homotopic and noise-free, while simulation studies
and data explorations demonstrate its benefits in the presence of noise.
Moreover, compared to commonly applied group ICA algorithms, the structure of
the H-gICA input data leads to significant improvement in computational
efficiency. A simulation study comfirms its effectiveness in homotopic,
non-homotopic and mixed settings, as well as on the landmark ADHD-200 dataset.
From a relatively small subset of data, several brain networks were found
including: the visual, the default mode and auditory networks, as well as
others. These were shown to be more contiguous and clearly delineated than the
corresponding ordinary group ICA. Finally, in addition to improving network
estimation, H-gICA facilitates the investigation of functional homotopy via
[Show abstract][Hide abstract] ABSTRACT: Neurological recovery in patients with severe spinal cord injury (SCI) is extremely rare. We have identified a patient with chronic cervical traumatic SCI, who suffered a complete loss of motor and sensory function below the injury for 6 weeks after the injury, but experienced a progressive neurological recovery that continued for 17 years. The extent of the patient's recovery from the severe trauma-induced paralysis is rare and remarkable. A detailed study of this patient using diffusion tensor imaging (DTI), magnetization transfer imaging (MTI), and resting state fMRI (rs-fMRI) revealed structural and functional changes in the central nervous system that may be associated with the neurological recovery. Sixty-two percent cervical cord white matter atrophy was observed. DTI-derived quantities, more sensitive to axons, demonstrated focal changes, while MTI-derived quantity, more sensitive to myelin, showed a diffuse change. No significant cortical structural changes were observed, while rs-fMRI revealed increased brain functional connectivity between sensorimotor and visual networks. The study provides comprehensive description of the structural and functional changes in the patient using advanced MR imaging technique. This multimodal MR imaging study also shows the potential of rs-fMRI to measure the extent of cortical plasticity.
Frontiers in Human Neuroscience 01/2013; 7:290. · 2.90 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Although an extensive literature exists on the neurobiological correlates of dyslexia (DYS), to date no studies have examined the neurobiological profile of those who exhibit poor reading comprehension despite intact word-level abilities (Specific Reading Comprehension Deficits, or S-RCD). Here we investigated for the first time the word-level abilities of S-RCD as compared to typically developing readers (TD) and those with DYS by examining BOLD response to words varying on frequency. Understanding whether S-RCD process words in the same manner as TD, or show alternate pathways to achieve normal word-reading abilities may provide insights into the origin of this disorder. Results showed that as compared to TD, DYS showed abnormal covariance during word processing with right hemisphere homologues of the left hemisphere reading network in conjunction with left occipito-temporal underactivation. In contrast, S-RCD showed intact neurobiological response to word stimuli in occipito-temporal regions (associated with fast and efficient word processing); however, inferior frontal gyrus abnormalities were observed. Using psychophysiological interaction analyses, a coupling-by-reading group interaction was found, such that left inferior frontal gyrus covaried to a greater extent with hippocampal, parahippocampal, and pre-frontal areas in S-RCD than in TD, for low as compared to high frequency words. Given the greater lexical access demands of low frequency as compared to high frequency words, these results may suggest specific weaknesses in accessing lexical-semantic representations during word recognition. These novel findings provide foundational insights into the nature of S-RCD, and set the stage for future investigations of this common but understudied reading disorder.
[Show abstract][Hide abstract] ABSTRACT: Functional magnetic resonance imaging (fMRI) is a powerful tool for the in vivo study of the pathophysiology of brain disorders and disease. In this manuscript, we propose an analysis stream for fMRI functional connectivity data and apply it to a novel study of Alzheimer's disease. In the first stage, spatial independent component analysis is applied to group fMRI data to obtain common brain networks (spatial maps) and subject-specific mixing matrices (time courses). In the second stage, functional principal component analysis is utilized to decompose the mixing matrices into population-level eigenvectors and subject-specific loadings. Inference is performed using permutation-based exact logistic regression for matched pairs data. The method is applied to a novel fMRI study of Alzheimer's disease risk under a verbal paired associates task. We found empirical evidence of alternative ICA-based metrics of connectivity when comparing subjects evidencing mild cognitive impairment relative to carefully matched controls.
PLoS ONE 11/2012; 7(11):e49340. · 3.53 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: A number of behavioral changes occur between late childhood and adulthood, including maturation of social cognition, reward receptivity, impulsiveness, risk-taking and cognitive control. Although some of these abilities show linear improvements with age, some abilities may temporarily worsen, reflecting both the restructuring and/or strengthening of connections within some brain systems. The current study uses resting state functional connectivity to examine developmental differences between late childhood and adulthood in task positive (TP) regions, which play a role in cognitive control functions, and task negative (TN) regions, which play a role in social cognition, self-referential, and internally-directed thought. Within the TP network, developmental differences in connectivity were found with the left dorsolateral prefrontal cortex. Within the TN network, developmental differences in connectivity were found with a broad area of the medial prefrontal cortex and the right parahippocampal gyrus. Connections between the two networks also showed significant developmental differences. Stronger anticorrelations were found in the TN maps of the adult group for the right anterior insula/inferior frontal gyrus, bilateral anterior inferior parietal lobule, bilateral superior parietal lobule and an anterior portion of the right posterior cingulate cortex. There was a significant brain-behavior relationship between the strength of anticorrelation in these regions and inhibitory control performance on two Go/No-go tasks suggesting that the development of anticorrelations between late childhood and adulthood supports mature inhibitory control. Overall, maturation of these networks occurred in specific regions which are associated with cognitive control of goal-directed behavior, including those involved in working memory, social cognition, and inhibitory control.
[Show abstract][Hide abstract] ABSTRACT: Huntington's Disease (HD) is a neurodegenerative disorder caused by a cytosine-adenine-guanine (CAG) triplet repeat-expansion in the Huntingtin (HTT) gene. Diagnosis of HD is classically defined by the presence of motor symptoms; however, cognitive and depressive symptoms frequently precede motor manifestations, and may occur early in the prodromal phase. There are sparse data so far on functional brain correlates of depressive symptoms in prodromal HD. A Stroop color-naming test was administered to 32 subjects in the prodromal phase of HD and 52 expansion-negative controls while performing functional magnetic resonance imaging at 3Tesla. Networks of functional connectivity were identified using group independent component analysis, followed by an analysis of functional network interactions. A contrast of temporal regression-based beta-weights was calculated as a reflection of Stroop-interference related activity and correlated with Center for Epidemiologic Studies Depression (CES-D) scores. For secondary analysis, patients were stratified into two subgroups by median split of CAG repeat-length. Stroop performance was independent of HTT mutation-carrier status and CES-D score. Stroop-interference-related activity of the ventromedial prefrontal cortex-node of the default-mode network, calculated by temporal-regression beta-weights, was more highly correlated with depressive symptoms in subjects in the prodromal phase of HD than in controls, differing significantly. The strength of this correlation and its difference from controls increased when a subgroup of patients with longer CAG repeat lengths was analyzed. These findings suggest that depressive symptoms in prodromal HD subjects may reflect altered functional brain network activity in the context of early HD-related brain alterations.
[Show abstract][Hide abstract] ABSTRACT: Resting state functional connectivity MRI (rsfc-MRI) reveals a wealth of information about the functional organization of the brain, but poses unique challenges for quantitative image analysis, mostly related to the large number of voxels with low signal-to-noise ratios. In this study, we tested the idea of using a prior spatial parcellation of the entire brain into various structural units, to perform an analysis on a structure-by-structure, rather than voxel-by-voxel, basis. This analysis, based upon atlas parcels, potentially offers enhanced SNR and reproducibility, and can be used as a common anatomical framework for cross-modality and cross-subject quantitative analysis. We used Large Deformation Diffeomorphic Metric Mapping (LDDMM) and a deformable brain atlas to parcel each brain into 185 regions. To investigate the precision of the cross-subject analysis, we computed inter-parcel correlations in 20 participants, each of whom was scanned twice, as well as the consistency of the connectivity patterns inter- and intra-subject, and the intersession reproducibility. We report significant inter-parcel correlations consistent with previous findings, and high test-retest reliability, an important consideration when the goal is to compare clinical populations. As an example of the cross-modality analysis, correlation with anatomical connectivity is also examined.
[Show abstract][Hide abstract] ABSTRACT: Huntington's Disease (HD) is a neurodegenerative disease caused by a CAG triplet-repeat expansion-mutation in the Huntingtin gene. Subjects at risk for HD can be identified by genetic testing in the prodromal phase. Structural changes of basal-ganglia nuclei such as the caudate nucleus are well-replicated findings observable early in prodromal-HD subjects and may be preceded by distinct functional alterations of cortico-striatal circuits. This study aims to assess functional integrity of the motor system as a cortico-striatal circuit with particular clinical relevance in HD. Ten subjects in the prodromal phase of HD and ten matched controls were administered blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) at rest (3T). Functional connectivity was measured as synchrony of BOLD activity between the caudate nucleus and thirteen cortical brain regions (seeds). Basal-ganglia volumes were assessed as established markers of disease progression in prodromal-HD. Linear regression analysis was performed to test for a relationship between structural changes and group differences in functional connectivity. Prodromal-HD subjects showed reduced BOLD synchrony between two seeds in the premotor cortex (BA6) and the caudate nucleus. While similar effect sizes could be observed for reduced basal-ganglia volumes and differences in functional connectivity, coefficients of determination indicate a moderate relationship between functional connectivity and striatal atrophy. Our data show reduced cortico-striatal functional connectivity at rest in prodromal-HD and suggest a relation to early structural brain changes. Additional longitudinal studies are necessary to elucidate the temporal relationship between functional alterations and earliest structural brain changes in prodromal-HD.
[Show abstract][Hide abstract] ABSTRACT: Skilled reading depends upon successfully integrating orthographic, phonological, and semantic information; however, the process of becoming a skilled reader with efficient neural circuitry is not fully understood. Short-term learning paradigms can provide insight into learning mechanisms by revealing differential responses to training approaches. To date, neuroimaging studies have primarily focused on effects of teaching novel words either in isolation or in context, without directly comparing the two. The current study compared the behavioral and neurobiological effects of learning novel pseudowords (i.e., pronouncing and attaching meaning) trained either in isolation or in sentential context. Behavioral results showed generally comparable pseudoword learning for both conditions, but sentential context-trained pseudowords were spoken and comprehended slightly more quickly. Neurobiologically, fMRI activity for reading trained pseudowords was similar to real words; however, an interaction between training approach and reading proficiency was observed. Specifically, highly skilled readers showed similar levels of activity regardless of training approach. However, less skilled readers differentiated between training conditions, showing comparable activity to highly skilled readers only for isolation-trained pseudowords. Overall, behavioral and neurobiological findings suggest that training approach may affect rate of learning and neural circuitry, and that less skilled readers may need explicit training to develop optimal neural pathways.