Faculty Bibliography

Brain imaging efforts are being increasingly devoted to decode the functioning of the human brain. Among neuroimaging techniques, resting-state fMRI (R-fMRI) is currently expanding exponentially. Beyond the general neuroimaging analysis packages (e.g., SPM, AFNI and FSL), REST and DPARSF were developed to meet the increasing need of user-friendly toolboxes for R-fMRI data processing. To address recently identified methodological challenges of R-fMRI, we introduce the newly developed toolbox, DPABI, which was evolved from REST and DPARSF. DPABI incorporates recent research advances on head motion control and measurement standardization, thus allowing users to evaluate results using stringent control strategies. DPABI also emphasizes test-retest reliability and quality control of data processing. Furthermore, DPABI provides a user-friendly pipeline analysis toolkit for rat/monkey R-fMRI data analysis to reflect the rapid advances in animal imaging. In addition, DPABI includes preprocessing modules for task-based fMRI, voxel-based morphometry analysis, statistical analysis and results viewing. DPABI is designed to make data analysis require fewer manual operations, be less time-consuming, have a lower skill requirement, a smaller risk of inadvertent mistakes, and be more comparable across studies. We anticipate this open-source toolbox will assist novices and expert users alike and continue to support advancing R-fMRI methodology and its application to clinical translational studies.

BACKGROUND: Internet gaming disorder (IGD) has become an increasing mental health problem worldwide. Decreased resting-state functional connectivity (rsFC) between the ventral tegmental area (VTA) and the nucleus accumbens (NAcc) has been found in substance use and is thought to play an important role in the development of substance addiction. However, rsFC between the VTA and NAcc in a non-substance addiction, such as IGD, has not been assessed previously. The current study aimed to investigate: (1) if individuals with IGD exhibit alterations in VTA-NAcc functional connectivity; and (2) whether VTA-NAcc functional connectivity is associated with subjective Internet craving. METHODS: Thirty-five male participants with IGD and 24 healthy control (HC) individuals participated in resting-state functional magnetic resonance imaging. Regions of interest (left NAcc, right NAcc and VTA) were selected based on the literature and were defined by placing spheres centered on Talairach Daemon coordinates. RESULTS: In comparison with HCs, individuals with IGD had significantly decreased rsFC between the VTA and right NAcc. Resting-state functional connectivity strength between the VTA and right NAcc was negatively correlated with self-reported subjective craving for the Internet. CONCLUSIONS: These results suggest possible neural functional similarities between individuals with IGD and individuals with substance addictions.

Working memory (WM) is central to the acquisition of knowledge and skills throughout childhood and adolescence. While numerous behavioral and task-based functional magnetic resonance imaging (fMRI) studies have examined WM development, few have used resting-state fMRI (R-fMRI). Here, we present a systematic R-fMRI examination of age-related differences in the neural indices of verbal WM performance in a cross-sectional pediatric sample (ages: 7-17; n=68), using data-driven approaches. Verbal WM capacity was measured with the digit span task, a commonly used educational and clinical assessment. We found distinct neural indices of digit span forward (DSF) and backward (DSB) performance, reflecting their unique neuropsychological demands. Regardless of age, DSB performance was related to intrinsic properties of brain areas previously implicated in attention and cognitive control, while DSF performance was related to areas less commonly implicated in verbal WM storage (precuneus, lateral visual areas). From a developmental perspective, DSF exhibited more robust age-related differences in brain-behavior relationships than DSB, and implicated a broader range of networks (ventral attention, default, somatomotor, limbic networks) - including a number of regions not commonly associated with verbal WM (angular gyrus, subcallosum). These results highlight the importance of examining the neurodevelopment of verbal WM and of considering regions beyond the "usual suspects".

To date, only one study has examined test-retest reliability of resting state fMRI (R-fMRI) in children, none in clinical developing groups. Here, we assessed short-term test-retest reliability in a sample of 46 children (11-17.9 years) with attention-deficit/hyperactivity disorder (ADHD) and 57 typically developing children (TDC). Our primary test-retest reliability measure was the intraclass correlation coefficient (ICC), quantified for a range of R-fMRI metrics. We aimed to (1) survey reliability within and across diagnostic groups, and (2) compare voxel-wise ICC between groups. We found moderate-to-high ICC across all children and within groups, with higher-order functional networks showing greater ICC. Nearly all R-fMRI metrics exhibited significantly higher ICC in TDC than in children with ADHD for one or more regions. In particular, posterior cingulate and ventral precuneus exhibited group differences in ICC across multiple measures. In the context of overall moderate-to-high test-retest reliability in children, regional differences in ICC related to diagnostic groups likely reflect the underlying pathophysiology for ADHD. Our currently limited understanding of the factors contributing to inter- and intra-subject variability in ADHD underscores the need for large initiatives aimed at examining their impact on test-retest reliability in both clinical and developing populations.

BACKGROUND: Resting-state functional magnetic resonance imaging (R-fMRI) is a promising tool in clinical application, especially in presurgical mapping for neurosurgery. This study aimed to investigate the sensitivity and specificity of R-fMRI in the localization of hand motor area in patients with brain tumors validated by direct cortical stimulation (DCS). We also compared this technique to task-based blood oxygenation level-dependent (BOLD) fMRI (T-fMRI). METHODS: R-fMRI and T-fMRI were acquired from 17 patients with brain tumors. The cortex sites of the hand motor area were recorded by DCS. Site-by-site comparisons between R-fMRI/T-fMRI and DCS were performed to calculate R-fMRI and T-fMRI sensitivity and specificity using DCS as a "gold standard". R-fMRI and T-fMRI performances were compared statistically RESULTS: A total of 609 cortex sites were tested with DCS and compared with R-fMRI findings in 17 patients. For hand motor area localization, R-fMRI sensitivity and specificity were 90.91 and 89.41 %, respectively. Given that two subjects could not comply with T-fMRI, 520 DCS sites were compared with T-fMRI findings in 15 patients. The sensitivity and specificity of T-fMRI were 78.57 and 84.76 %, respectively. In the 15 patients who successfully underwent both R-fMRI and T-fMRI, there was no statistical difference in sensitivity or specificity between the two methods (p = 0.3198 and p = 0.1431, respectively) CONCLUSIONS: R-fMRI sensitivity and specificity are high for localizing hand motor area and even equivalent or slightly higher compared with T-fMRI. Given its convenience for patients, R-fMRI is a promising substitute for T-fMRI for presurgical mapping.

Autism spectrum disorders (ASDs) represent a formidable challenge for psychiatry and neuroscience because of their high prevalence, lifelong nature, complexity and substantial heterogeneity. Facing these obstacles requires large-scale multidisciplinary efforts. Although the field of genetics has pioneered data sharing for these reasons, neuroimaging had not kept pace. In response, we introduce the Autism Brain Imaging Data Exchange (ABIDE)-a grassroots consortium aggregating and openly sharing 1112 existing resting-state functional magnetic resonance imaging (R-fMRI) data sets with corresponding structural MRI and phenotypic information from 539 individuals with ASDs and 573 age-matched typical controls (TCs; 7-64 years) (http://fcon_1000.projects.nitrc.org/indi/abide/). Here, we present this resource and demonstrate its suitability for advancing knowledge of ASD neurobiology based on analyses of 360 male subjects with ASDs and 403 male age-matched TCs. We focused on whole-brain intrinsic functional connectivity and also survey a range of voxel-wise measures of intrinsic functional brain architecture. Whole-brain analyses reconciled seemingly disparate themes of both hypo- and hyperconnectivity in the ASD literature; both were detected, although hypoconnectivity dominated, particularly for corticocortical and interhemispheric functional connectivity. Exploratory analyses using an array of regional metrics of intrinsic brain function converged on common loci of dysfunction in ASDs (mid- and posterior insula and posterior cingulate cortex), and highlighted less commonly explored regions such as the thalamus. The survey of the ABIDE R-fMRI data sets provides unprecedented demonstrations of both replication and novel discovery. By pooling multiple international data sets, ABIDE is expected to accelerate the pace of discovery setting the stage for the next generation of ASD studies.Molecular Psychiatry advance online publication, 18 June 2013; doi:10.1038/mp.2013.78.

Perspectives of human brain functional connectivity continue to evolve. Static representations of functional interactions between brain regions are rapidly giving way to dynamic perspectives, which emphasize non-random temporal variations in intrinsic functional connectivity (iFC) patterns. Here, we bring this dynamic perspective to our understanding of iFC patterns for posteromedial cortex (PMC), a cortical hub known for its functional diversity. Previous work has consistently differentiated iFC patterns among PMC subregions, though assumed static iFC over time. Here, we assessed iFC as a function of time utilizing a sliding-window correlation approach, and applied hierarchical clustering to detect representative iFC states from the windowed iFC. Across subregions, five iFC states were detected over time. Although with differing frequencies, each subregion was associated with each of the states, suggesting that these iFC states are "common" to PMC subregions. Importantly, each subregion possessed a unique preferred state(s) and distinct transition patterns, explaining previously observed iFC differentiations. These results resonate with task-based fMRI studies suggesting that large-scale functional networks can be flexibly reconfigured in response to changing task-demands. Additionally, we used retest scans (~1week later) to demonstrate the reproducibility of the iFC states identified, and establish moderate to high test-retest reliability for various metrics used to quantify switching behaviors. We also demonstrate the ability of dynamic properties in the visual PMC subregion to index inter-individual differences in a measure of concept formation and mental flexibility. These findings suggest functional relevance of dynamic iFC and its potential utility in biomarker identification over time, as d-iFC methodologies are refined and mature.

Sharing drafts of scientific manuscripts on preprint hosting services for early exposure and pre-publication feedback is a well-accepted practice in fields such as physics, astronomy, or mathematics. The field of neuroscience, however, has yet to adopt the preprint model. A reason for this reluctance might partly be the lack of central preprint services for the field of neuroscience. To address this issue, we announce the launch of Preprints of the R-fMRI Network (PRN), a community funded preprint hosting service. PRN provides free-submission and free hosting of manuscripts for resting state functional magnetic resonance imaging (R-fMRI) and neuroscience related studies. Submissions will be peer viewed and receive feedback from readers and a panel of invited consultants of the R-fMRI Network. All manuscripts and feedback will be freely available online with citable permanent URL for open-access. The goal of PRN is to supplement the "peer reviewed" journal publication system - by more rapidly communicating the latest research achievements throughout the world. We hope PRN will help the field to embrace the preprint model and thus further accelerate R-fMRI and neuroscience related studies, eventually enhancing human mental health.

As researchers increase their efforts to characterize variations in the functional connectome across studies and individuals, concerns about the many sources of nuisance variation present and their impact on resting state fMRI (R-fMRI) measures continue to grow. Although substantial within-site variation can exist, efforts to aggregate data across multiple sites such as the 1000 Functional Connectomes Project (FCP) and International Neuroimaging Data-sharing Initiative (INDI) datasets amplify these concerns. The present work draws upon standardization approaches commonly used in the microarray gene expression literature, and to a lesser extent recent imaging studies, and compares them with respect to their impact on relationships between common R-fMRI measures and nuisance variables (e.g., imaging site, motion), as well as phenotypic variables of interest (age, sex). Standardization approaches differed with regard to whether they were applied post-hoc vs. during pre-processing, and at the individual vs. group level; additionally they varied in whether they addressed additive effects vs. additive+multiplicative effects, and were parametric vs. non-parametric. While all standardization approaches were effective at reducing undesirable relationships with nuisance variables, post-hoc approaches were generally more effective than global signal regression (GSR). Across approaches, correction for additive effects (global mean) appeared to be more important than for multiplicative effects (global SD) for all R-fMRI measures, with the exception of amplitude of low frequency fluctuations (ALFF). Group-level post-hoc standardizations for mean-centering and variance-standardization were found to be advantageous in their ability to avoid the introduction of artifactual relationships with standardization parameters; though results between individual and group-level post-hoc approaches were highly similar overall. While post-hoc standardization procedures drastically increased test-retest (TRT) reliability for ALFF, modest reductions were observed for other measures after post-hoc standardizations-a phenomena likely attributable to the separation of voxel-wise from global differences among subjects (global mean and SD demonstrated moderate TRT reliability for these measures). Finally, the present work calls into question previous observations of increased anatomical specificity for GSR over mean centering, and draws attention to the near equivalence of global and gray matter signal regression.

Functional connectomics is one of the most rapidly expanding areas of neuroimaging research. Yet, concerns remain regarding the use of resting-state fMRI (R-fMRI) to characterize inter-individual variation in the functional connectome. In particular, recent findings that "micro" head movements can introduce artifactual inter-individual and group-related differences in R-fMRI metrics have raised concerns. Here, we first build on prior demonstrations of regional variation in the magnitude of framewise displacements associated with a given head movement, by providing a comprehensive voxel-based examination of the impact of motion on the BOLD signal (i.e., motion-BOLD relationships). Positive motion-BOLD relationships were detected in primary and supplementary motor areas, particularly in low motion datasets. Negative motion-BOLD relationships were most prominent in prefrontal regions, and expanded throughout the brain in high motion datasets (e.g., children). Scrubbing of volumes with FD>0.2 effectively removed negative but not positive correlations; these findings suggest that positive relationships may reflect neural origins of motion while negative relationships are likely to originate from motion artifact. We also examined the ability of motion correction strategies to eliminate artifactual differences related to motion among individuals and between groups for a broad array of voxel-wise R-fMRI metrics. Residual relationships between motion and the examined R-fMRI metrics remained for all correction approaches, underscoring the need to covary motion effects at the group-level. Notably, global signal regression reduced relationships between motion and inter-individual differences in correlation-based R-fMRI metrics; Z-standardization (mean-centering and variance normalization) of subject-level maps for R-fMRI metrics prior to group-level analyses demonstrated similar advantages. Finally, our test-retest (TRT) analyses revealed significant motion effects on TRT reliability for R-fMRI metrics. Generally, motion compromised reliability of R-fMRI metrics, with the exception of those based on frequency characteristics - particularly, amplitude of low frequency fluctuations (ALFF). The implications of our findings for decision-making regarding the assessment and correction of motion are discussed, as are insights into potential differences among volume-based metrics of motion.