[Show abstract][Hide abstract] ABSTRACT: Resting-state functional MRI (rs-fMRI) permits study of the brain's functional networks without requiring participants to perform tasks. Robust changes in such resting state networks (RSNs) have been observed in neurologic disorders, and rs-fMRI outcome measures are candidate biomarkers for monitoring clinical trials, including trials of extended therapeutic interventions for rehabilitation of patients with chronic conditions. In this study, we aim to present a unique longitudinal dataset reporting on a healthy adult subject scanned weekly over 3.5 years and identify rs-fMRI outcome measures appropriate for clinical trials. Accordingly, we assessed the reproducibility, and characterized the temporal structure of, rs-fMRI outcome measures derived using independent component analysis (ICA). Data was compared to a 21-person dataset acquired on the same scanner in order to confirm that the values of the single-subject RSN measures were within the expected range as assessed from the multi-participant dataset. Fourteen RSNs were identified, and the inter-session reproducibility of outcome measures-network spatial map, temporal signal fluctuation magnitude, and between-network connectivity (BNC)-was high, with executive RSNs showing the highest reproducibility. Analysis of the weekly outcome measures also showed that many rs-fMRI outcome measures had a significant linear trend, annual periodicity, and persistence. Such temporal structure was most prominent in spatial map similarity, and least prominent in BNC. High reproducibility supports the candidacy of rs-fMRI outcome measures as biomarkers, but the presence of significant temporal structure needs to be taken into account when such outcome measures are considered as biomarkers for rehabilitation-style therapeutic interventions in chronic conditions.
PLoS ONE 10/2015; 10(10):e0140134. DOI:10.1371/journal.pone.0140134 · 3.23 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Background:
Imitation, which is impaired in children with autism spectrum disorder (ASD) and critically depends on the integration of visual input with motor output, likely impacts both motor and social skill acquisition in children with ASD; however, it is unclear what brain mechanisms contribute to this impairment. Children with ASD also exhibit what appears to be an ASD-specific bias against using visual feedback during motor learning. Does the temporal congruity of intrinsic activity, or functional connectivity, between motor and visual brain regions contribute to ASD-associated deficits in imitation, motor, and social skills?
We acquired resting state functional magnetic resonance imaging scans from 100 8- to 12-year-old children (50 ASD). Group independent component analysis was used to estimate functional connectivity between visual and motor systems. Brain-behavior relationships were assessed by regressing functional connectivity measures with social deficit severity, imitation, and gesture performance scores.
We observed increased intrinsic asynchrony between visual and motor systems in children with ASD and replicated this finding in an independent sample from the Autism Brain Imaging Data Exchange. Moreover, children with more out-of-sync intrinsic visual-motor activity displayed more severe autistic traits, while children with greater intrinsic visual-motor synchrony were better imitators.
Our twice replicated findings confirm that visual-motor functional connectivity is disrupted in ASD. Furthermore, the observed temporal incongruity between visual and motor systems, which may reflect diminished integration of visual consequences with motor output, was predictive of the severity of social deficits and may contribute to impaired social-communicative skill development in children with ASD.
[Show abstract][Hide abstract] ABSTRACT: Objectives: Much recent attention has been paid to quantifying anatomic and
functional neuroimaging on the individual subject level. For optimal individual
subject characterization, specific acquisition and analysis features need to be
identified that maximize inter-individual variability while concomitantly
minimizing intra-subject variability.
Experimental Design: Here we develop a non-parametric statistical metric that
quantifies the degree to which a parameter set allows this individual subject
differentiation. We apply this metric to analysis of publicly available
test-retest resting-state fMRI (rs-fMRI) data sets.
Principal Observations: We find that for the question of maximizing
individual differentiation, (i) for increasing sampling, there is a relative
tradeoff between increased sampling frequency and increased acquisition time;
(ii) for the sizes of the interrogated data sets, only 3-4 min of acquisition
time was sufficient to maximally differentiate each subject; and (iii) brain
regions that most contribute to this individual subject characterization lie in
the default mode, attention, language, and executive control networks.
Conclusions: These findings may guide optimal rs-fMRI experiment design and
may elucidate the neural bases for subject-to-subject differences.
[Show abstract][Hide abstract] ABSTRACT: Several recent studies have reported an inter-individual correlation between regional GABA concentration, as measured by MRS, and the amplitude of the functional blood oxygenation level dependent (BOLD) response in the same region. In this study, we set out to investigate whether this coupling generalizes across cortex. In 18 healthy participants, we performed edited MRS measurements of GABA and BOLD-fMRI experiments using regionally related activation paradigms. Regions and tasks were the: occipital cortex with a visual grating stimulus; auditory cortex with a white noise stimulus; sensorimotor cortex with a finger-tapping task; frontal eye field with a saccade task; and dorsolateral prefrontal cortex with a working memory task. In contrast to the prior literature, no correlation between GABA concentration and BOLD activation was detected in any region. The origin of this discrepancy is not clear. Subtle differences in study design or insufficient power may cause differing results; these and other potential reasons for the discrepant results are discussed. This negative result, although it should be interpreted with caution, has a larger sample size than prior positive results, and suggests that the relationship between GABA and the BOLD response may be more complex than previously thought.
PLoS ONE 02/2015; 10(2):e0117531. DOI:10.1371/journal.pone.0117531 · 3.23 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Intra-subject variability (ISV) is the most consistent behavioral deficit in Attention Deficit Hyperactivity Disorder (ADHD). ISV may be associated with networks involved in sustaining task control (cingulo-opercular network: CON) and self-reflective lapses of attention (default mode network: DMN). The current study examined whether connectivity supporting attentional control is atypical in children with ADHD. Group differences in full-brain connection strength and brain-behavior associations with attentional control measures were examined for the late-developing CON and DMN in 50 children with ADHD and 50 typically-developing (TD) controls (ages 8-12 years).
[Show abstract][Hide abstract] ABSTRACT: A recent interest in resting state functional magnetic resonance imaging
(rsfMRI) lies in subdividing the human brain into anatomically and functionally
distinct regions of interest. For example, brain parcellation is often used for
defining the network nodes 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 low
signal-to-noise ratio of rsfMRI data, combined with typically short scan
lengths. A large number of brain parcellation approaches employ clustering,
which begins with a measure of similarity or distance between voxels. The goal
of this work is to improve the reproducibility of single-subject parcellation
using shrinkage estimators of such measures, allowing the noisy
subject-specific estimator to "borrow strength" in a principled manner from a
larger population of subjects. We present several empirical Bayes shrinkage
estimators and outline methods for shrinkage when multiple scans are not
available for each subject. We perform shrinkage on raw intervoxel correlation
estimates and use both raw and shrinkage estimates to produce parcellations by
performing clustering on the voxels. Our 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 rsfMRI scans from 20 subjects---we show that
parcellations produced from shrinkage correlation estimates have higher
reliability and validity than those produced from raw 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
[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: 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 06/2013; 7:290. DOI:10.3389/fnhum.2013.00290 · 3.63 Impact Factor
[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.
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.
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.
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.