Mapping PedsQL™ scores to CHU9D utility weights for children with chronic conditions in a multi-ethnic and deprived metropolitan population.

PURPOSE: The Child Health Utility-9 Dimensions (CHU9D) is a patient-reported outcome measure to generate Quality-Adjusted Life Years (QALYs), recommended for economic evaluations of interventions to inform funding decisions. When the CHU9D is not available, mapping algorithms offer an opportunity to convert other paediatric instruments, such as the Paediatric Quality of Life Inventory™ (PedsQL), onto the CHU9D scores. This study aims to validate current PedsQL to CHU9D mappings in a sample of children and young people of a wide age range (0 to 16 years of age) and with chronic conditions. New algorithms with improved predictive accuracy are also developed. METHODS: Data from the Children and Young People's Health Partnership (CYPHP) were used (N = 1735). Four regression models were estimated: ordinal least squared, generalized linear model, beta-binomial and censored least absolute deviations. Standard goodness of fit measures were used for validation and to assess new algorithms. RESULTS: While previous algorithms perform well, performance can be enhanced. OLS was the best estimation method for the final equations at the total, dimension and item PedsQL scores levels. The CYPHP mapping algorithms include age as an important predictor and more non-linear terms compared with previous work. CONCLUSION: The new CYPHP mappings are particularly relevant for samples with children and young people with chronic conditions living in deprived and urban settings. Further validation in an external sample is required. Trial registration number NCT03461848; pre-results.

Multimodal gradient mapping of rodent hippocampus.

The hippocampus plays a central role in supporting our coherent and enduring sense of self and our place in the world. Understanding its functional organisation is central to understanding this complex role. Previous studies suggest function varies along a long hippocampal axis, but there is disagreement about the presence of sharp discontinuities or gradual change along that axis. Other open questions relate to the underlying drivers of this variation and the conservation of organisational principles across species. Here, we delineate the primary organisational principles underlying patterns of hippocampal functional connectivity (FC) in the mouse using gradient analysis on resting state fMRI data. We further applied gradient analysis to mouse gene co-expression data to examine the relationship between variation in genomic anatomy and functional organisation. Two principal FC gradients along a hippocampal axis were revealed. The principal gradient exhibited a sharp discontinuity that divided the hippocampus into dorsal and ventral compartments. The second, more continuous, gradient followed the long axis of the ventral compartment. Dorsal regions were more strongly connected to areas involved in spatial navigation while ventral regions were more strongly connected to areas involved in emotion, recapitulating patterns seen in humans. In contrast, gene co-expression gradients showed a more segregated and discrete organisation. Our findings suggest that hippocampal functional organisation exhibits both sharp and gradual transitions and that hippocampal genomic anatomy exerts only a subtle influence on this organisation.

Speech Outcomes Following Orticochea Pharyngoplasty in Patients With History of Cleft Palate and Noncleft Velopharyngeal Dysfunction.

OBJECTIVE: To report speech outcomes following Orticochea pharyngoplasty in 43 patients with cleft palate and noncleft velopharyngeal dysfunction. DESIGN: A retrospective surgical audit of patients undergoing Orticochea pharyngoplasty between 2004 and 2012, with speech as a primary outcome measure. SETTING: Patients known to a regional UK cleft center. METHODS: Forty-three patients underwent Orticochea pharyngoplasty by a single surgeon in a UK regional cleft center. Twenty-one patients had undergone a prior procedure for velopharyngeal dysfunction. Pre- and postoperative speech samples were assessed blindly using the Cleft Audit Protocol for Speech-Augmented by a specialist cleft speech and language therapist, external to the team. Speech samples were rated on the following parameters: hypernasality, hyponasality, audible nasal emission, nasal, turbulence, and passive cleft speech characteristics. Statistical differences in pre- and postoperative speech scores were tested using the Wilcoxon matched-pairs signed-ranks test. Inter- and intrareliability scores were calculated using weighted Cohen κ. RESULTS: Whole group: A statistically significant difference in pre- and postoperative scores for hypernasality (P < .001), hyponasality (P < .05), nasal emission (P < .01), and passive cleft speech characteristics (P < .01) were reported. Patients with cleft diagnoses: A statistically significant difference in scores for hypernasality (P < .001), nasal emission (P < .01), and passive cleft speech characteristics (P < .01) were reported for this group of patients. Patients with noncleft diagnoses: The only parameter to demonstrate a statistically significant difference was hypernasality (P < .01) in this group. CONCLUSIONS: Orticochea pharyngoplasty is a successful surgical procedure in treating velopharyngeal dysfunction in both the cleft and noncleft populations.

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.

Analysis of structural brain asymmetries in attention-deficit/hyperactivity disorder in 39 datasets.

OBJECTIVE: Some studies have suggested alterations of structural brain asymmetry in attention-deficit/hyperactivity disorder (ADHD), but findings have been contradictory and based on small samples. Here, we performed the largest ever analysis of brain left-right asymmetry in ADHD, using 39 datasets of the ENIGMA consortium. METHODS: We analyzed asymmetry of subcortical and cerebral cortical structures in up to 1,933 people with ADHD and 1,829 unaffected controls. Asymmetry Indexes (AIs) were calculated per participant for each bilaterally paired measure, and linear mixed effects modeling was applied separately in children, adolescents, adults, and the total sample, to test exhaustively for potential associations of ADHD with structural brain asymmetries. RESULTS: There was no evidence for altered caudate nucleus asymmetry in ADHD, in contrast to prior literature. In children, there was less rightward asymmetry of the total hemispheric surface area compared to controls (t = 2.1, p = .04). Lower rightward asymmetry of medial orbitofrontal cortex surface area in ADHD (t = 2.7, p = .01) was similar to a recent finding for autism spectrum disorder. There were also some differences in cortical thickness asymmetry across age groups. In adults with ADHD, globus pallidus asymmetry was altered compared to those without ADHD. However, all effects were small (Cohen's d from -0.18 to 0.18) and would not survive study-wide correction for multiple testing. CONCLUSION: Prior studies of altered structural brain asymmetry in ADHD were likely underpowered to detect the small effects reported here. Altered structural asymmetry is unlikely to provide a useful biomarker for ADHD, but may provide neurobiological insights into the trait.

EEG spectral power, but not theta/beta ratio, is a neuromarker for adult ADHD.

Adults with attention-deficit/hyperactivity disorder (ADHD) have been described as having altered resting-state electroencephalographic (EEG) spectral power and theta/beta ratio (TBR). However, a recent review (Pulini et al. 2018) identified methodological errors in neuroimaging, including EEG, ADHD classification studies. Therefore, the specific EEG neuromarkers of adult ADHD remain to be identified, as do the EEG characteristics that mediate between genes and behaviour (mediational endophenotypes). Resting-state eyes-open and eyes-closed EEG was measured from 38 adults with ADHD, 45 first-degree relatives of people with ADHD and 51 unrelated controls. A machine learning classification analysis using penalized logistic regression (Elastic Net) examined if EEG spectral power (1-45 Hz) and TBR could classify participants into ADHD, first-degree relatives and/or control groups. Random-label permutation was used to quantify any bias in the analysis. Eyes-open absolute and relative EEG power distinguished ADHD from control participants (area under receiver operating characteristic = 0.71-0.77). The best predictors of ADHD status were increased power in delta, theta and low-alpha over centro-parietal regions, and in frontal low-beta and parietal mid-beta. TBR did not successfully classify ADHD status. Elevated eyes-open power in delta, theta, low-alpha and low-beta distinguished first-degree relatives from controls (area under receiver operating characteristic = 0.68-0.72), suggesting that these features may be a mediational endophenotype for adult ADHD. Resting-state EEG spectral power may be a neuromarker and mediational endophenotype of adult ADHD. These results did not support TBR as a diagnostic neuromarker for ADHD. It is possible that TBR is a characteristic of childhood ADHD.

Neural circuitry underlying sustained attention in healthy adolescents and in ADHD symptomatology.

Moment-to-moment reaction time variability on tasks of attention, often quantified by intra-individual response variability (IRV), provides a good indication of the degree to which an individual is vulnerable to lapses in sustained attention. Increased IRV is a hallmark of several disorders of attention, including Attention-Deficit/Hyperactivity Disorder (ADHD). Here, task-based fMRI was used to provide the first examination of how average brain activation and functional connectivity patterns in adolescents are related to individual differences in sustained attention as measured by IRV. We computed IRV in a large sample of adolescents (n = 758) across 'Go' trials of a Stop Signal Task (SST). A data-driven, multi-step analysis approach was used to identify networks associated with low IRV (i.e., good sustained attention) and high IRV (i.e., poorer sustained attention). Low IRV was associated with greater functional segregation (i.e., stronger negative connectivity) amongst an array of brain networks, particularly between cerebellum and motor, cerebellum and prefrontal, and occipital and motor networks. In contrast, high IRV was associated with stronger positive connectivity within the motor network bilaterally and between motor and parietal, prefrontal, and limbic networks. Consistent with these observations, a separate sample of adolescents exhibiting elevated ADHD symptoms had increased fMRI activation and stronger positive connectivity within the same motor network denoting poorer sustained attention, compared to a matched asymptomatic control sample. With respect to the functional connectivity signature of low IRV, there were no statistically significant differences in networks denoting good sustained attention between the ADHD symptom group and asymptomatic control group. We propose that sustained attentional processes are facilitated by an array of neural networks working together, and provide an empirical account of how the functional role of the cerebellum extends to cognition in adolescents. This work highlights the involvement of motor cortex in the integrity of sustained attention, and suggests that atypically strong connectivity within motor networks characterizes poor attentional capacity in both typically developing and ADHD symptomatic adolescents.

Circulating adipokines are associated with pre-eclampsia in women with type 1 diabetes.

AIMS/HYPOTHESIS: The incidence of pre-eclampsia, a multisystem disorder of pregnancy, is fourfold higher in type 1 diabetic than non-diabetic women; it is also increased in women with features of the metabolic syndrome and insulin resistance. In a prospective study of pregnant women with type 1 diabetes, we measured plasma levels of adipokines known to be associated with insulin resistance: leptin, fatty acid binding protein 4 (FABP4), adiponectin (total and high molecular weight [HMW]; also known as high molecular mass), retinol binding protein 4 (RBP4) and resistin and evaluated associations with the subsequent development of pre-eclampsia. METHODS: From an established prospective cohort of pregnant type 1 diabetic women, we studied 23 who developed pre-eclampsia and 24 who remained normotensive; for reference values we included 19 healthy non-diabetic normotensive pregnant women. Plasma adipokines were measured (by ELISA) in stored samples from three study visits (Visit 1- Visit 3) at different gestational ages (mean ± SD): Visit 1, 12.4 ± 1.8 weeks; Visit 2, 21.7 ± 1.4 weeks; and Visit 3, 31.4 ± 1.5 weeks. All the women were free of microalbuminuria and hypertension at enrolment. All study visits preceded the clinical onset of pre-eclampsia. RESULTS: In all groups, leptin, the ratio of leptin to total or HMW adiponectin, FABP4 concentration, ratio of FABP4 to total or HMW adiponectin and resistin level increased, while total and HMW adiponectin decreased, with gestational age. At Visit 1: (1) in diabetic women with vs without subsequent pre-eclampsia, leptin, ratio of leptin to total or HMW adiponectin, and ratio of FABP4 to total or HMW adiponectin, were increased (p < 0.05), while total adiponectin was decreased (p < 0.05); and (2) in normotensive diabetic vs non-diabetic women, total adiponectin was elevated (p < 0.05). At Visits 2 and 3: (1) the primary findings in the two diabetic groups persisted, and FABP4 also increased in women with subsequent pre-eclampsia (p < 0.05); and (2) there were no differences between the two normotensive groups. By logistic regression analyses after covariate adjustment (HbA1c, insulin kg-1 day-1 and gestational age), the best predictive models for pre-eclampsia were as follows: Visit 1, doubling of leptin, OR 9.0 (p < 0.01); Visit 2, doubling of the leptin:total adiponectin ratio, OR 3.7 (p < 0.05); and Visit 3, doubling of FABP4 concentration, OR 25.1 (p < 0.01). The associations were independent of BMI. CONCLUSIONS/INTERPRETATION: As early as the first trimester in type 1 diabetic women, adipokine profiles that suggest insulin resistance are associated with subsequent pre-eclampsia, possibly reflecting maternal characteristics that precede pregnancy. These associations persist in the second and third trimesters, and are independent of BMI. Insulin resistance may predispose women with type 1 diabetes to pre-eclampsia.

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.

The effect of complex workplace dietary interventions on employees' dietary intakes, nutrition knowledge and health status: a cluster controlled trial.

BACKGROUND: Evidence on effective workplace dietary interventions is limited. The comparative effectiveness of a workplace environmental dietary modification and an educational intervention both alone and in combination was assessed versus a control workplace on employees' dietary intakes, nutrition knowledge and health status. METHODS: In the Food Choice at Work cluster controlled trial, four large, purposively selected manufacturing workplaces in Ireland were allocated to control (N=111), nutrition education (Education) (N=226), environmental dietary modification (Environment) (N=113) and nutrition education and environmental dietary modification (Combined) (N=400) in 2013. Nutrition education included group presentations, individual consultations and detailed nutrition information. Environmental dietary modification included menu modification, fruit price discounts, strategic positioning of healthier alternatives and portion size control. Data on dietary intakes, nutrition knowledge and health status were obtained at baseline and follow-up at 7-9months. Multivariate analysis of covariance compared changes across the four groups with adjustment for age, gender, educational status and other baseline characteristics. RESULTS: Follow-up data at 7-9months were obtained for 541 employees (64% of 850 recruited) aged 18-64years: control: 70 (63%), Education: 113 (50%), ENVIRONMENT: 74 (65%) and Combined: 284 (71%). There were significant positive changes in intakes of saturated fat (p=0.013), salt (p=0.010) and nutrition knowledge (p=0.034) between baseline and follow-up in the combined intervention versus the control. Small but significant changes in BMI (-1.2kg/m(2) (95% CI -2.385, -0.018, p=0.047) were observed in the combined intervention. Effects in the education and environment alone workplaces were smaller and generally non-significant. CONCLUSION: Combining nutrition education and environmental dietary modification may be an effective approach for promoting a healthy diet and weight loss at work.

Barriers to and facilitators of implementing complex workplace dietary interventions: process evaluation results of a cluster controlled trial.

BACKGROUND: Ambiguity exists regarding the effectiveness of workplace dietary interventions. Rigorous process evaluation is vital to understand this uncertainty. This study was conducted as part of the Food Choice at Work trial which assessed the comparative effectiveness of a workplace environmental dietary modification intervention and an educational intervention both alone and in combination versus a control workplace. Effectiveness was assessed in terms of employees' dietary intakes, nutrition knowledge and health status in four large manufacturing workplaces. The study aimed to examine barriers to and facilitators of implementing complex workplace interventions, from the perspectives of key workplace stakeholders and researchers involved in implementation. METHODS: A detailed process evaluation monitored and evaluated intervention implementation. Interviews were conducted at baseline (27 interviews) and at 7-9 month follow-up (27 interviews) with a purposive sample of workplace stakeholders (managers and participating employees). Topic guides explored factors which facilitated or impeded implementation. Researchers involved in recruitment and data collection participated in focus groups at baseline and at 7-9 month follow-up to explore their perceptions of intervention implementation. Data were imported into NVivo software and analysed using a thematic framework approach. RESULTS: Four major themes emerged; perceived benefits of participation, negotiation and flexibility of the implementation team, viability and intensity of interventions and workplace structures and cultures. The latter three themes either positively or negatively affected implementation, depending on context. The implementation team included managers involved in coordinating and delivering the interventions and the researchers who collected data and delivered intervention elements. Stakeholders' perceptions of the benefits of participating, which facilitated implementation, included managers' desire to improve company image and employees seeking health improvements. Other facilitators included stakeholder buy-in, organisational support and stakeholder cohesiveness with regards to the level of support provided to the intervention. Anticipation of employee resistance towards menu changes, workplace restructuring and target-driven workplace cultures impeded intervention implementation. CONCLUSIONS: Contextual factors such as workplace structures and cultures need to be considered in the implementation of future workplace dietary interventions. Negotiation and flexibility of key workplace stakeholders plays an integral role in overcoming the barriers of workplace cultures, structures and resistance to change. TRIAL REGISTRATION: Current Controlled Trials: ISRCTN35108237. Date of registration: 02/07/2013.

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.

Neurophysiological investigation of spontaneous correlated and anticorrelated fluctuations of the BOLD signal.

Analyses of intrinsic fMRI BOLD signal fluctuations reliably reveal correlated and anticorrelated functional networks in the brain. Because the BOLD signal is an indirect measure of neuronal activity and anticorrelations can be introduced by preprocessing steps, such as global signal regression, the neurophysiological significance of correlated and anticorrelated BOLD fluctuations is a source of debate. Here, we address this question by examining the correspondence between the spatial organization of correlated BOLD fluctuations and correlated fluctuations in electrophysiological high γ power signals recorded directly from the cortical surface of 5 patients. We demonstrate that both positive and negative BOLD correlations have neurophysiological correlates reflected in fluctuations of spontaneous neuronal activity. Although applying global signal regression to BOLD signals results in some BOLD anticorrelations that are not apparent in the ECoG data, it enhances the neuronal-hemodynamic correspondence overall. Together, these findings provide support for the neurophysiological fidelity of BOLD correlations and anticorrelations.

A multivariate distance-based analytic framework for connectome-wide association studies.

The identification of phenotypic associations in high-dimensional brain connectivity data represents the next frontier in the neuroimaging connectomics era. Exploration of brain-phenotype relationships remains limited by statistical approaches that are computationally intensive, depend on a priori hypotheses, or require stringent correction for multiple comparisons. Here, we propose a computationally efficient, data-driven technique for connectome-wide association studies (CWAS) that provides a comprehensive voxel-wise survey of brain-behavior relationships across the connectome; the approach identifies voxels whose whole-brain connectivity patterns vary significantly with a phenotypic variable. Using resting state fMRI data, we demonstrate the utility of our analytic framework by identifying significant connectivity-phenotype relationships for full-scale IQ and assessing their overlap with existent neuroimaging findings, as synthesized by openly available automated meta-analysis (www.neurosynth.org). The results appeared to be robust to the removal of nuisance covariates (i.e., mean connectivity, global signal, and motion) and varying brain resolution (i.e., voxelwise results are highly similar to results using 800 parcellations). We show that CWAS findings can be used to guide subsequent seed-based correlation analyses. Finally, we demonstrate the applicability of the approach by examining CWAS for three additional datasets, each encompassing a distinct phenotypic variable: neurotypical development, Attention-Deficit/Hyperactivity Disorder diagnostic status, and L-DOPA pharmacological manipulation. For each phenotype, our approach to CWAS identified distinct connectome-wide association profiles, not previously attainable in a single study utilizing traditional univariate approaches. As a computationally efficient, extensible, and scalable method, our CWAS framework can accelerate the discovery of brain-behavior relationships in the connectome.

Strengthening connections: functional connectivity and brain plasticity.

The ascendancy of functional neuroimaging has facilitated the addition of network-based approaches to the neuropsychologist's toolbox for evaluating the sequelae of brain insult. In particular, intrinsic functional connectivity (iFC) mapping of resting state fMRI (R-fMRI) data constitutes an ideal approach to measuring macro-scale networks in the human brain. Beyond the value of iFC mapping for charting how the functional topography of the brain is altered by insult and injury, iFC analyses can provide insights into experience-dependent plasticity at the macro level of large-scale functional networks. Such insights are foundational to the design of training and remediation interventions that will best facilitate recovery of function. In this review, we consider what is currently known about the origin and function of iFC in the brain, and how this knowledge is informative in neuropsychological settings. We then summarize studies that have examined experience-driven plasticity of iFC in healthy control participants, and frame these findings in terms of a schema that may aid in the interpretation of results and the generation of hypotheses for rehabilitative studies. Finally, we outline some caveats to the R-fMRI approach, as well as some current developments that are likely to bolster the utility of the iFC paradigm for neuropsychology.

The extrinsic and intrinsic functional architectures of the human brain are not equivalent.

The brain's intrinsic functional architecture, revealed in correlated spontaneous activity, appears to constitute a faithful representation of its repertoire of evoked, extrinsic functional interactions. Here, using broad task contrasts to probe evoked patterns of coactivation, we demonstrate tight coupling between the brain's intrinsic and extrinsic functional architectures for default and task-positive regions, but not for subcortical and limbic regions or for primary sensory and motor cortices. While strong correspondence likely reflects persistent or recurrent patterns of evoked coactivation, weak correspondence may exist for regions whose patterns of evoked functional interactions are more adaptive and context dependent. These findings were independent of task. For tight task contrasts (e.g., incongruent vs. congruent trials), evoked patterns of coactivation were unrelated to the intrinsic functional architecture, suggesting that high-level task demands are accommodated by context-specific modulations of functional interactions. We conclude that intrinsic approaches provide only a partial understanding of the brain's functional architecture. Appreciating the full repertoire of dynamic neural responses will continue to require task-based functional magnetic resonance imaging approaches.

Intrinsic functional architecture predicts electrically evoked responses in the human brain.

Adaptive brain function is characterized by dynamic interactions within and between neuronal circuits, often occurring at the time scale of milliseconds. These complex interactions between adjacent and noncontiguous brain areas depend on a functional architecture that is maintained even in the absence of input. Functional MRI studies carried out during rest (R-fMRI) suggest that this architecture is represented in low-frequency (<0.1 Hz) spontaneous fluctuations in the blood oxygen level-dependent signal that are correlated within spatially distributed networks of brain areas. These networks, collectively referred to as the brain's intrinsic functional architecture, exhibit a remarkable correspondence with patterns of task-evoked coactivation as well as maps of anatomical connectivity. Despite this striking correspondence, there is no direct evidence that this intrinsic architecture forms the scaffold that gives rise to faster processes relevant to information processing and seizure spread. Here, we demonstrate that the spatial distribution and magnitude of temporally correlated low-frequency fluctuations observed with R-fMRI during rest predict the pattern and magnitude of corticocortical evoked potentials elicited within 500 ms after single-pulse electrical stimulation of the cerebral cortex with intracranial electrodes. Across individuals, this relationship was found to be independent of the specific regions and functional systems probed. Our findings bridge the immense divide between the temporal resolutions of these distinct measures of brain function and provide strong support for the idea that the low-frequency signal fluctuations observed with R-fMRI maintain and update the intrinsic architecture underlying the brain's repertoire of functional responses.

Connectome-based fingerprinting: reproducibility, precision, and behavioral prediction.

Functional magnetic resonance imaging-based functional connectivity enables the non-invasive mapping of individual differences in brain functional organization to individual differences in a vast array of behavioral phenotypes. This flexibility has renewed the search for neuroimaging-based biomarkers that exhibit reproducibility, prediction, and precision. Functional connectivity-based measures that share these three characteristics are key to achieving this goal. Here, we review the functional connectome fingerprinting approach and discuss its value, not only as a simple and intuitive conceptualization of the "functional connectome" that provides new insights into how the connectome is altered in association with psychiatric symptoms, but also as a straightforward and interpretable method for indexing the reproducibility of functional connectivity-based measures. We discuss how these advantages provide new avenues for strengthening reproducibility, precision, and behavioral prediction for functional connectomics and we consider new directions toward discovering better biomarkers for neuropsychiatric conditions.