Stability and similarity of the pediatric connectome as developmental measures.

Patterns of functional connectivity are unique at the individual level, enabling test-retest matching algorithms to identify a subject from among a group using only their functional connectome. Recent findings show that accuracies of these algorithms in children increase with age. Relatedly, the persistence of functional connectivity (FC) patterns across tasks and rest also increases with age. This study investigated the hypothesis that within-subject stability and between-subject similarity of the whole-brain pediatric connectome are developmentally relevant outcomes. Using data from 210 help-seeking children and adolescents, ages 6-21 years (Healthy Brain Network Biobank), we computed whole-brain FC matrices for each participant during two different movies (MovieDM and MovieTP) and two runs of task-free rest (all from a single scan session) and fed these matrices to a test-retest matching algorithm. We replicated the finding that matching accuracies for children and youth (ages 6-21 years) are low (18-44%), and that cross-state and cross-movie accuracies were the lowest. Results also showed that parcellation resolution and the number of volumes used in each matrix affect fingerprinting accuracies. Next, we calculated three measures of whole-connectome stability for each subject: cross-rest (Rest1-Rest2), cross-state (MovieDM-Rest1), and cross-movie (MovieDM-MovieTP), and three measures of within-state between-subject connectome similarity for Rest1, MovieDM, and MovieTP. We show that stability and similarity were correlated, but that these measures were not related to age. A principal component analysis of these measures yielded two components that we used to test for brain-behavior correlations with IQ, general psychopathology, and social skills measures (n = 119). The first component was significantly correlated with the social skills measure (r=-0.26, p = 0.005). Post hoc correlations showed that the social skills measure correlated with both cross-rest stability (r=-0.29, p = 0.001) and with connectome similarity during MovieDM (r=-0.28, p = 0.002). These findings suggest that the stability and similarity of the whole-brain connectome relate to the development of social skills. We infer that the maturation of the functional connectome simultaneously achieves patterns of FC that are distinct at the individual subject level, that are shared across individuals, and that are persistent across states and across runs-features which presumably combine to optimize neural processing during development. Future longitudinal work could reveal the developmental trajectories of stability and similarity of the connectome.

Brain age prediction: Cortical and subcortical shape covariation in the developing human brain.

Cortical development is characterized by distinct spatial and temporal patterns of maturational changes across various cortical shape measures. There is a growing interest in summarizing complex developmental patterns into a single index, which can be used to characterize an individual's brain age. We conducted this study with two primary aims. First, we sought to quantify covariation patterns for a variety of cortical shape measures, including cortical thickness, gray matter volume, surface area, mean curvature, and travel depth, as well as white matter volume, and subcortical gray matter volume. We examined these measures in a sample of 869 participants aged 5-18 from the Healthy Brain Network (HBN) neurodevelopmental cohort using the Joint and Individual Variation Explained (Lock et al., 2013) method. We validated our results in an independent dataset from the Nathan Kline Institute - Rockland Sample (NKI-RS; N = 210) and found remarkable consistency for some covariation patterns. Second, we assessed whether covariation patterns in the brain can be used to accurately predict a person's chronological age. Using ridge regression, we showed that covariation patterns can predict chronological age with high accuracy, reflected by our ability to cross-validate our model in an independent sample with a correlation coefficient of 0.84 between chronologic and predicted age. These covariation patterns also predicted sex with high accuracy (AUC = 0.85), and explained a substantial portion of variation in full scale intelligence quotient (R2 = 0.10). In summary, we found significant covariation across different cortical shape measures and subcortical gray matter volumes. In addition, each shape measure exhibited distinct covariations that could not be accounted for by other shape measures. These covariation patterns accurately predicted chronological age, sex and general cognitive ability. In a subset of NKI-RS, test-retest (<1 month apart, N = 120) and longitudinal scans (1.22 ±â€¯0.29 years apart, N = 77) were available, allowing us to demonstrate high reliability for the prediction models obtained and the ability to detect subtle differences in the longitudinal scan interval among participants (median and median absolute deviation of absolute differences between predicted age difference and real age difference = 0.53 ±â€¯0.47 years, r = 0.24, p-value = 0.04).

Autism-associated Nf1 deficiency disrupts corticocortical and corticostriatal functional connectivity in human and mouse.

Children with the autosomal dominant single gene disorder, neurofibromatosis type 1 (NF1), display multiple structural and functional changes in the central nervous system, resulting in neuropsychological cognitive abnormalities. Here we assessed the pathological functional organization that may underlie the behavioral impairments in NF1 using resting-state functional connectivity MRI. Coherent spontaneous fluctuations in the fMRI signal across the entire brain were used to interrogate the pattern of functional organization of corticocortical and corticostriatal networks in both NF1 pediatric patients and mice with a heterozygous mutation in the Nf1 gene (Nf1+/-). Children with NF1 demonstrated abnormal organization of cortical association networks and altered posterior-anterior functional connectivity in the default network. Examining the contribution of the striatum revealed that corticostriatal functional connectivity was altered. NF1 children demonstrated reduced functional connectivity between striatum and the frontoparietal network and increased striatal functional connectivity with the limbic network. Awake passive mouse functional connectivity MRI in Nf1+/- mice similarly revealed reduced posterior-anterior connectivity along the cingulate cortex as well as disrupted corticostriatal connectivity. The striatum of Nf1+/- mice showed increased functional connectivity to somatomotor and frontal cortices and decreased functional connectivity to the auditory cortex. Collectively, these results demonstrate similar alterations across species, suggesting that NF1 pathogenesis is linked to striatal dysfunction and disrupted corticocortical connectivity in the default network.

Situating the default-mode network along a principal gradient of macroscale cortical organization.

Understanding how the structure of cognition arises from the topographical organization of the cortex is a primary goal in neuroscience. Previous work has described local functional gradients extending from perceptual and motor regions to cortical areas representing more abstract functions, but an overarching framework for the association between structure and function is still lacking. Here, we show that the principal gradient revealed by the decomposition of connectivity data in humans and the macaque monkey is anchored by, at one end, regions serving primary sensory/motor functions and at the other end, transmodal regions that, in humans, are known as the default-mode network (DMN). These DMN regions exhibit the greatest geodesic distance along the cortical surface-and are precisely equidistant-from primary sensory/motor morphological landmarks. The principal gradient also provides an organizing spatial framework for multiple large-scale networks and characterizes a spectrum from unimodal to heteromodal activity in a functional metaanalysis. Together, these observations provide a characterization of the topographical organization of cortex and indicate that the role of the DMN in cognition might arise from its position at one extreme of a hierarchy, allowing it to process transmodal information that is unrelated to immediate sensory input.

Altered intrinsic functional connectivity of the cingulate cortex in children with severe temper outbursts.

Severe temper outbursts (STO) in children are associated with impaired school and family functioning and may contribute to negative outcomes. These outbursts can be conceptualized as excessive frustration responses reflecting reduced emotion regulation capacity. The anterior cingulate cortex (ACC) has been implicated in negative affect as well as emotional control, and exhibits disrupted function in children with elevated irritability and outbursts. This study examined the intrinsic functional connectivity (iFC) of a region of the ACC, the anterior midcingulate cortex (aMCC), in 5- to 9-year-old children with STO (n = 20), comparing them to children with attention-deficit/hyperactivity disorder (ADHD) without outbursts (ADHD; n = 18). Additional analyses compared results to a sample of healthy children (HC; n = 18) and examined specific associations with behavioral and emotional dysregulation. Compared to the ADHD group, STO children exhibited reduced iFC between the aMCC and surrounding regions of the ACC, and increased iFC between the aMCC and precuneus. These differences were also seen between the STO and HC groups; ADHD and HC groups did not differ. Specificity analyses found associations between aMCC-ACC connectivity and hyperactivity, and between aMCC-precuneus iFC and emotion dysregulation. Disruption in aMCC networks may underlie the behavioral and emotional dysregulation characteristic of children with STO.

Individual differences in functional connectivity during naturalistic viewing conditions.

Naturalistic viewing paradigms such as movies have been shown to reduce participant head motion and improve arousal during fMRI scanning relative to task-free rest, and have been used to study both functional connectivity and stimulus-evoked BOLD-signal changes. These task-based hemodynamic changes are synchronized across subjects and involve large areas of the cortex, and it is unclear whether individual differences in functional connectivity are enhanced or diminished under such naturalistic conditions. This work first aims to characterize variability in BOLD-signal based functional connectivity (FC) across 2 distinct movie conditions and eyes-open rest (n=31 healthy adults, 2 scan sessions each). We found that movies have higher within- and between-subject correlations in cluster-wise FC relative to rest. The anatomical distribution of inter-individual variability was similar across conditions, with higher variability occurring at the lateral prefrontal lobes and temporoparietal junctions. Second, we used an unsupervised test-retest matching algorithm that identifies individual subjects from within a group based on FC patterns, quantifying the accuracy of the algorithm across the three conditions. The movies and resting state all enabled identification of individual subjects based on FC matrices, with accuracies between 61% and 100%. Overall, pairings involving movies outperformed rest, and the social, faster-paced movie attained 100% accuracy. When the parcellation resolution, scan duration, and number of edges used were increased, accuracies improved across conditions, and the pattern of movies>rest was preserved. These results suggest that using dynamic stimuli such as movies enhances the detection of FC patterns that are unique at the individual level.

Neural mechanisms of individual differences in temporal discounting of monetary and primary rewards in adolescents.

Adolescents are generally characterized as impulsive. However, impulsivity is a multi-dimensional construct that involves multiple component processes. Which of these components contribute to adolescent impulsivity is currently unclear. This study focused on the neural mechanisms underlying individual differences in distinct components of temporal discounting (TD), i.e., the preference for smaller immediate rewards over larger delayed rewards. Participants were 58 adolescents (12-16 years-old) who performed an fMRI TD task with both monetary and snack rewards. Using mixed-effects modeling, we determined participants' average impatience, and further decomposed TD choices into: 1) amount sensitivity (unique contribution of the magnitude of the immediate reward); and 2) delay sensitivity (unique contribution of delay duration). Adolescents' average impatience was positively correlated with frontoparietal and ventral striatal activity during delayed reward choices, and with ventromedial prefrontal cortex activity during immediate reward choices. Adolescents' amount sensitivity was positively associated with ventral striatal and dorsal anterior cingulate cortex activity during immediate reward choices. Delay sensitivity was positively correlated with inferior parietal cortex activity during delayed reward choices. As expected, snacks were discounted more steeply than money, and TD of both reward types was associated with overlapping activation in the inferior parietal cortex. Exploring whether testosterone or estradiol were associated with TD and its neural correlates revealed no significant associations. These findings indicate that distinct components contribute uniquely to TD choice and that individual differences in amount sensitivity are uniquely associated with activation of reward valuation areas, while individual differences in delay sensitivity are uniquely associated with activation of cognitive control areas.

The real-time fMRI neurofeedback based stratification of Default Network Regulation Neuroimaging data repository.

This data descriptor describes a repository of openly shared data from an experiment to assess inter-individual differences in default mode network (DMN) activity. This repository includes cross-sectional functional magnetic resonance imaging (fMRI) data from the Multi Source Interference Task, to assess DMN deactivation, the Moral Dilemma Task, to assess DMN activation, a resting state fMRI scan, and a DMN neurofeedback paradigm, to assess DMN modulation, along with accompanying behavioral and cognitive measures. We report technical validation from n=125 participants of the final targeted sample of 180 participants. Each session includes acquisition of one whole-brain anatomical scan and whole-brain echo-planar imaging (EPI) scans, acquired during the aforementioned tasks and resting state. The data includes several self-report measures related to perseverative thinking, emotion regulation, and imaginative processes, along with a behavioral measure of rapid visual information processing. Technical validation of the data confirms that the tasks deactivate and activate the DMN as expected. Group level analysis of the neurofeedback data indicates that the participants are able to modulate their DMN with considerable inter-subject variability. Preliminary analysis of behavioral responses and specifically self-reported sleep indicate that as many as 73 participants may need to be excluded from an analysis depending on the hypothesis being tested. The present data are linked to the enhanced Nathan Kline Institute, Rockland Sample and builds on the comprehensive neuroimaging and deep phenotyping available therein. As limited information is presently available about individual differences in the capacity to directly modulate the default mode network, these data provide a unique opportunity to examine DMN modulation ability in relation to numerous phenotypic characteristics.

Linkage and association analysis of ADHD endophenotypes in extended and multigenerational pedigrees from a genetic isolate.

Attention-deficit/hyperactivity disorder (ADHD) is a heritable, chronic, neurodevelopmental disorder with serious long-term repercussions. Despite being one of the most common cognitive disorders, the clinical diagnosis of ADHD is based on subjective assessments of perceived behaviors. Endophenotypes (neurobiological markers that cosegregate and are associated with an illness) are thought to provide a more powerful and objective framework for revealing the underlying neurobiology than syndromic psychiatric classification. Here, we present the results of applying genetic linkage and association analyses to neuropsychological endophenotypes using microsatellite and single nucleotide polymorphisms. We found several new genetic regions linked and/or associated with these endophenotypes, and others previously associated to ADHD, for example, loci harbored in the LPHN3, FGF1, POLR2A, CHRNA4 and ANKFY1 genes. These findings, when compared with those linked and/or associated to ADHD, suggest that these endophenotypes lie on shared pathways. The genetic information provided by this study offers a novel and complementary method of assessing the genetic causes underpinning the susceptibility to behavioral conditions and may offer new insights on the neurobiology of the disorder.

APOE*E2 allele delays age of onset in PSEN1 E280A Alzheimer's disease.

Alzheimer's disease (AD) age of onset (ADAOO) varies greatly between individuals, with unique causal mutations suggesting the role of modifying genetic and environmental interactions. We analyzed ~50 000 common and rare functional genomic variants from 71 individuals of the 'Paisa' pedigree, the world's largest pedigree segregating a severe form of early-onset AD, who were affected carriers of the fully penetrant E280A mutation in the presenilin-1 (PSEN1) gene. Affected carriers with ages at the extremes of the ADAOO distribution (30s-70s age range), and linear mixed-effects models were used to build single-locus regression models outlining the ADAOO. We identified the rs7412 (APOE*E2 allele) as a whole exome-wide ADAOO modifier that delays ADAOO by ~12 years (ß=11.74, 95% confidence interval (CI): 8.07-15.41, P=6.31 × 10(-8), PFDR=2.48 × 10(-3)). Subsequently, to evaluate comprehensively the APOE (apolipoprotein E) haplotype variants (E1/E2/E3/E4), the markers rs7412 and rs429358 were genotyped in 93 AD affected carriers of the E280A mutation. We found that the APOE*E2 allele, and not APOE*E4, modifies ADAOO in carriers of the E280A mutation (ß=8.24, 95% CI: 4.45-12.01, P=3.84 × 10(-5)). Exploratory linear mixed-effects multilocus analysis suggested that other functional variants harbored in genes involved in cell proliferation, protein degradation, apoptotic and immune dysregulation processes (i.e., GPR20, TRIM22, FCRL5, AOAH, PINLYP, IFI16, RC3H1 and DFNA5) might interact with the APOE*E2 allele. Interestingly, suggestive evidence as an ADAOO modifier was found for one of these variants (GPR20) in a set of patients with sporadic AD from the Paisa genetic isolate. This is the first study demonstrating that the APOE*E2 allele modifies the natural history of AD typified by the age of onset in E280A mutation carriers. To the best of our knowledge, this is the largest analyzed sample of patients with a unique mutation sharing uniform environment. Formal replication of our results in other populations and in other forms of AD will be crucial for prediction, follow-up and presumably developing new therapeutic strategies for patients either at risk or affected by AD.

Genetic and Environmental Contributions to Functional Connectivity Architecture of the Human Brain.

One of the grand challenges faced by neuroscience is to delineate the determinants of interindividual variation in the comprehensive structural and functional connection matrices that comprise the human connectome. At present, this endeavor appears most tractable at the macroanatomic scale, where intrinsic brain activity exhibits robust patterns of synchrony that recapitulate core functional circuits at the individual level. Here, we use a classical twin study design to examine the heritability of intrinsic functional network properties in 101 twin pairs, including network activity (i.e., variance of a network's specific temporal fluctuations) and internetwork coherence (i.e., correlation between networks' specific temporal fluctuations). Five of 7 networks exhibited significantly heritable (23.3-65.2%) network activity, 6 of the 21 internetwork coherences were significantly heritable (25.6-42.0%), and 11 of the 21 internetwork coherences were significantly influenced by common environmental factors (18.0-47.1%). These results suggest that the source of interindividual variation in functional connectome has a modular architecture: individual modules represented by intrinsic connectivity networks are genetic controlled, while environmental factors influence the interplays between the modules. This work further provides network-specific hypotheses for discovery of the specific genetic and environmental factors influencing functional specialization and integration of the human brain.

Imaging human connectomes at the macroscale.

At macroscopic scales, the human connectome comprises anatomically distinct brain areas, the structural pathways connecting them and their functional interactions. Annotation of phenotypic associations with variation in the connectome and cataloging of neurophenotypes promise to transform our understanding of the human brain. In this Review, we provide a survey of magnetic resonance imaging­based measurements of functional and structural connectivity. We highlight emerging areas of development and inquiry and emphasize the importance of integrating structural and functional perspectives on brain architecture.

Sleep and meal-time misalignment alters functional connectivity: a pilot resting-state study.

Delayed sleep and meal times promote metabolic dysregulation and obesity. Altered coordination of sleeping and eating times may impact food-reward valuation and interoception in the brain, yet the independent and collective contributions of sleep and meal times are unknown. This randomized, in-patient crossover study experimentally manipulates sleep and meal times while preserving sleep duration (7.05±0.44 h for 5 nights). Resting-state functional magnetic resonance imaging scans (2 × 5-minute runs) were obtained for four participants (three males; 25.3±4.6 years), each completing all study phases (normal sleep/normal meal; late sleep/normal meal; normal sleep/late meal; and late sleep/late meal). Normal mealtimes were 1, 5, 11 and 12.5 h after awakening; late mealtimes were 4.5, 8.5, 14.5 and 16 h after awakening. Seed-based resting-state functional connectivity (RSFC) was computed for a priori regions-of-interest (seeds) and contrasted across conditions. Statistically significant (P<0.05, whole-brain corrected) regionally specific effects were found for multiple seeds. The strongest effects were linked to the amygdala: increased RSFC for late versus normal mealtimes (equivalent to skipping breakfast). A main effect of sleep and interaction with meal time were also observed. Preliminary findings support the feasibility of examining the effects of sleep and meal-time misalignment, independent of sleep duration, on RSFC in regions relevant to food reward and interoception.

Differential effects of methylphenidate and atomoxetine on intrinsic brain activity in children with attention deficit hyperactivity disorder.

BACKGROUND: Methylphenidate and atomoxetine are commonly prescribed for treating attention deficit hyperactivity disorder (ADHD). However, their therapeutic neural mechanisms remain unclear. METHOD: After baseline evaluation including cognitive testing of the Cambridge Neuropsychological Test Automated Battery (CANTAB), drug-naive children with ADHD (n = 46), aged 7-17 years, were randomly assigned to a 12-week treatment with methylphenidate (n = 22) or atomoxetine (n = 24). Intrinsic brain activity, including the fractional amplitude of low-frequency fluctuations (fALFF) and regional homogeneity (ReHo), was quantified via resting-state functional magnetic resonance imaging at baseline and week 12. RESULTS: Reductions in inattentive symptoms were related to increased fALFF in the left superior temporal gyrus and left inferior parietal lobule for ADHD children treated with methylphenidate, and in the left lingual gyrus and left inferior occipital gyrus for ADHD children treated with atomoxetine. Hyperactivity/impulsivity symptom reductions were differentially related to increased fALFF in the methylphenidate group and to decreased fALFF in the atomoxetine group in bilateral precentral and postcentral gyri. Prediction analyses in the atomoxetine group revealed negative correlations between pre-treatment CANTAB simple reaction time and fALFF change in the left lingual gyrus and left inferior occipital gyrus, and positive correlations between pre-treatment CANTAB simple movement time and fALFF change in bilateral precentral and postcentral gyri and left precuneus, with a negative correlation between movement time and the fALFF change in the left lingual gyrus and the inferior occipital gyrus. CONCLUSIONS: Our findings suggest differential neurophysiological mechanisms for the treatment effects of methylphenidate and atomoxetine in children with ADHD.

Annual Research Review: Discovery science strategies in studies of the pathophysiology of child and adolescent psychiatric disorders--promises and limitations.

BACKGROUND: Psychiatric science remains descriptive, with a categorical nosology intended to enhance interobserver reliability. Increased awareness of the mismatch between categorical classifications and the complexity of biological systems drives the search for novel frameworks including discovery science in Big Data. In this review, we provide an overview of incipient approaches, primarily focused on classically categorical diagnoses such as schizophrenia (SZ), autism spectrum disorder (ASD), and attention-deficit/hyperactivity disorder (ADHD), but also reference convincing, if focal, advances in cancer biology, to describe the challenges of Big Data and discovery science, and outline approaches being formulated to overcome existing obstacles. FINDINGS: A paradigm shift from categorical diagnoses to a domain/structure-based nosology and from linear causal chains to complex causal network models of brain-behavior relationship is ongoing. This (r)evolution involves appreciating the complexity, dimensionality, and heterogeneity of neuropsychiatric data collected from multiple sources ('broad' data) along with data obtained at multiple levels of analysis, ranging from genes to molecules, cells, circuits, and behaviors ('deep' data). Both of these types of Big Data landscapes require the use and development of robust and powerful informatics and statistical approaches. Thus, we describe Big Data analysis pipelines and the promise and potential limitations in using Big Data approaches to study psychiatric disorders. CONCLUSIONS: We highlight key resources available for psychopathological studies and call for the application and development of Big Data approaches to dissect the causes and mechanisms of neuropsychiatric disorders and identify corresponding biomarkers for early diagnosis.

The influence of two reciprocating single-file and two rotary-file systems on the apical extrusion of debris and its biological relationship with symptomatic apical periodontitis. A systematic review and meta-analysis.

This systematic review and meta-analysis investigated the influence of the number of files (full-sequence rotary-file versus reciprocating single-file systems) used during root canal preparation on the apical extrusion of debris and its biological relationship with the occurrence of symptomatic apical periodontitis. An extensive literature research was carried out in the Medline, ISI Web of Science and Cochrane databases, for relevant articles with the keyword search strategy. Based on inclusion and exclusion criteria, two reviewers independently rated the quality of each study determining the level of evidence of the articles selected. The primary outcome for the meta-analysis was determined by the amount of debris extruded into the periapical tissue during root canal preparation with multiple- or single-file systems in four laboratory studies. Analysis of in vivo release of neuropeptides (SP and CGRP) after root canal preparation with single- or multiple-file systems was also carried out. Amongst the 128 articles initially found, 113 were excluded for being nonrelevant or not fulfilling the selection criteria. Another four articles were excluded after methodology evaluation. Finally, nine laboratory studies and two in vivo studies were included in the systematic review. Four of the laboratory studies were further included for meta-analysis that revealed greater debris extrusion after the use of single-file techniques when compared to multiple-file systems. Analysis of in vivo neuropeptide expression in the periodontal ligament suggests that the design of the instrument is more important than the number of files used. Both rotary and reciprocating single-file systems generate apical extrusion of debris in laboratory studies, or expression of neuropeptides in vivo. Available evidence is limited, but supports the fact that this inflammatory reaction is not influenced by the number of files but the type of movement and the instrument design.

Constrained by our connections: white matter's key role in interindividual variability in visual working memory capacity.

Visual working memory (VWM) plays an essential role in many perceptual and higher-order cognitive processes. Despite its reliance on a broad network of brain regions, VWM has a capacity limited to a few objects. This capacity varies substantially across individuals and relates closely to measures of overall cognitive function (Luck and Vogel, 2013). The mechanisms underlying these properties are not completely understood, although the amplitude of neural signal oscillations (Vogel and Machizawa, 2004) and brain activation in specific cortical regions (Todd and Marois, 2004) have been implicated. Variability in VWM performance may also reflect variability in white matter structural properties. However, data based primarily on diffusion tensor imaging approaches remain inconclusive. Here, we investigate the relationship between white matter and VWM capacity in human subjects using an advanced diffusion imaging technique, diffusion kurtosis imaging. Diffusion kurtosis imaging provides several novel quantitative white mater metrics, among them the axonal water fraction (f(axon)), an index of axonal density and caliber. Our results show that 59% of individual variability in VWM capacity may be explained by variations in f(axon) within a widely distributed network of white matter tracts. Increased f(axon) associates with increased VWM capacity. An additional 12% in VWM capacity variance may be explained by diffusion properties of the extra-axonal space. These data demonstrate, for the first time, the key role of white matter in limiting VWM capacity in the healthy adult brain and suggest that white matter may represent an important therapeutic target in disorders of impaired VWM and cognition.

Inscapes: A movie paradigm to improve compliance in functional magnetic resonance imaging.

The examination of functional connectivity in fMRI data collected during task-free "rest" has provided a powerful tool for studying functional brain organization. Limitations of this approach include susceptibility to head motion artifacts and participant drowsiness or sleep. These issues are especially relevant when studying young children or clinical populations. Here we introduce a movie paradigm, Inscapes, that features abstract shapes without a narrative or scene-cuts. The movie was designed to provide enough stimulation to improve compliance related to motion and wakefulness while minimizing cognitive load during the collection of functional imaging data. We compare Inscapes to eyes-open rest and to age-appropriate movie clips in healthy adults (Ocean's Eleven, n=22) and a pilot sample of typically developing children ages 3-7 (Fantasia, n=13). Head motion was significantly lower during both movies relative to rest for both groups. In adults, movies decreased the number of participants who self-reported sleep. Intersubject correlations, used to quantify synchronized, task-evoked activity across movie and rest conditions in adults, involved less cortex during Inscapes than Ocean's Eleven. To evaluate the effect of movie-watching on intrinsic functional connectivity networks, we examined mean functional connectivity using both whole-brain functional parcellation and network-based approaches. Both inter- and intra-network metrics were more similar between Inscapes and Rest than between Ocean's Eleven and Rest, particularly in comparisons involving the default network. When comparing movies to Rest, the mean functional connectivity of somatomotor, visual and ventral attention networks differed significantly across various analyses. We conclude that low-demand movies like Inscapes may represent a useful intermediate condition between task-free rest and typical narrative movies while still improving participant compliance. Inscapes is publicly available for download at headspacestudios.org/inscapes.

Quantile rank maps: a new tool for understanding individual brain development.

We propose a novel method for neurodevelopmental brain mapping that displays how an individual's values for a quantity of interest compare with age-specific norms. By estimating smoothly age-varying distributions at a set of brain regions of interest, we derive age-dependent region-wise quantile ranks for a given individual, which can be presented in the form of a brain map. Such quantile rank maps could potentially be used for clinical screening. Bootstrap-based confidence intervals are proposed for the quantile rank estimates. We also propose a recalibrated Kolmogorov-Smirnov test for detecting group differences in the age-varying distribution. This test is shown to be more robust to model misspecification than a linear regression-based test. The proposed methods are applied to brain imaging data from the Nathan Kline Institute Rockland Sample and from the Autism Brain Imaging Data Exchange (ABIDE) sample.

The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism.

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.