Assessment and prevention of head motion during imaging of patients with attention deficit hyperactivity disorder

Comparison of MRI head motion indicators in 40,969 subjects informs neuroimaging study design

Head motion during MRI compromises image quality for clinical assessments and research. Active motion reduction strategies are effective but rarely applied due to uncertainty in their value for a given study. The ability to anticipate motion based on group characteristics would aid effective neuroimaging study design. This study compared putative motion indicators for their association to fMRI head motion in a large UK Biobank cohort (n = 40,969, aged 54.9 ± 7.5 years, 53% male). Body Mass Index (BMI; βadj = .050, p < .001) and ethnicity (βadj = 0.068, p < 0.001) were the strongest indicators of head motion. A ten-point increase in BMI, which is the difference between "healthy" and "obese", corresponded to a 51% increase in motion. Findings were similar in a subgroup with no lifetime diagnoses (n = 6858). Motion was not significantly increased in individuals with psychiatric disorders, musculoskeletal disorders, or diabetes. The hypertension subgroup exhibited significantly increased motion (p = 0.048). Cognitive task performance (t = 110.83, p < 0.001) and prior scan experience (t = 7.16, p < 0.001) were associated with increased head motion. Our results inform decision making for implementation of motion reduction strategies in MRI. BMI outweighs other motion indicators, while blood pressure, age, smoking and caffeine consumption are relatively less influential. Disease diagnosis alone is not a good indicator of MRI head motion.

Autism is associated with in vivo changes in gray matter neurite architecture

Postmortem investigations in autism have identified anomalies in neural cytoarchitecture across limbic, cerebellar, and neocortical networks. These anomalies include narrow cell mini-columns and variable neuron density. However, difficulty obtaining sufficient post-mortem samples has often prevented investigations from converging on reproducible measures. Recent advances in processing magnetic resonance diffusion weighted images (DWI) make in vivo characterization of neuronal cytoarchitecture a potential alternative to post-mortem studies. Using extensive DWI data from the Adolescent Brain Cognitive Developmentsm (ABCD®) study 142 individuals with an autism diagnosis were compared with 8971 controls using a restriction spectrum imaging (RSI) framework that characterized total neurite density (TND), its component restricted normalized directional diffusion (RND), and restricted normalized isotropic diffusion (RNI). A significant decrease in TND was observed in autism in the right cerebellar cortex (β = -0.005, SE =0.0015, p = 0.0267), with significant decreases in RNI and significant increases in RND found diffusely throughout posterior and anterior aspects of the brain, respectively. Furthermore, these regions remained significant in post-hoc analysis when the autism sample was compared against a subset of 1404 individuals with other psychiatric conditions (pulled from the original 8971). These findings highlight the importance of characterizing neuron cytoarchitecture in autism and the significance of their incorporation as physiological covariates in future studies.

Transdiagnostic Symptom Domains are Associated with Head Motion During Multimodal Imaging in Children

Background

Head motion is a challenge for neuroimaging research in developmental populations. However, it is unclear how transdiagnostic symptom domains including attention, disruptive behavior (e.g., externalizing behavior), and internalizing problems are linked to scanner motion in children, particularly across structural and functional MRI. The current study examined whether transdiagnostic domains of attention, disruptive behavior, and internalizing symptoms are associated with scanner motion in children during multimodal imaging.

Methods

In a sample of 9,045 children aged 9-10 years in the Adolescent Brain Cognitive Development (ABCD) Study, logistic regression and linear mixed-effects models were used to examine associations between motion and behavior. Motion was indexed using ABCD Study quality control metrics and mean framewise displacement for the following: T1-weighted structural, resting-state fMRI, diffusion MRI, Stop-Signal Task, Monetary Incentive Delay task, and Emotional n-Back task. The Child Behavior Checklist was used as a continuous measure of symptom severity.

Results

Greater attention and disruptive behavior problem severity was associated with a lower likelihood of passing motion quality control across several imaging modalities. In contrast, increased internalizing severity was associated with a higher likelihood of passing motion quality control. Increased attention and disruptive behavior problem severity was also associated with increased mean motion, whereas increased internalizing problem severity was associated with decreased mean motion.

Conclusion

Transdiagnostic domains emerged as predictors of motion in youths. These findings have implications for advancing development of generalizable and robust brain-based biomarkers, computational approaches for mitigating motion effects, and enhancing accessibility of imaging protocols for children with varying symptom severities.

Examining the reliability of brain age algorithms under varying degrees of participant motion

Brain age algorithms using data science and machine learning techniques show promise as biomarkers for neurodegenerative disorders and aging. However, head motion during MRI scanning may compromise image quality and influence brain age estimates. We examined the effects of motion on brain age predictions in adult participants with low, high, and no motion MRI scans (Original N = 148; Analytic N = 138). Five popular algorithms were tested: brainageR, DeepBrainNet, XGBoost, ENIGMA, and pyment. Evaluation metrics, intraclass correlations (ICCs), and Bland-Altman analyses assessed reliability across motion conditions. Linear mixed models quantified motion effects. Results demonstrated motion significantly impacted brain age estimates for some algorithms, with ICCs dropping as low as 0.609 and errors increasing up to 11.5 years for high motion scans. DeepBrainNet and pyment showed greatest robustness and reliability (ICCs = 0.956-0.965). XGBoost and brainageR had the largest errors (up to 13.5 RMSE) and bias with motion. Findings indicate motion artifacts influence brain age estimates in significant ways. Furthermore, our results suggest certain algorithms like DeepBrainNet and pyment may be preferable for deployment in populations where motion during MRI acquisition is likely. Further optimization and validation of brain age algorithms is critical to use brain age as a biomarker relevant for clinical outcomes.

Working and short-term memory in children with ADHD: an examination of prefrontal cortical functioning using functional Near-Infrared Spectroscopy (fNIRS)

Working memory impairments are an oft-reported deficit among children with ADHD, and complementary neuroimaging studies implicate reductions in prefrontal cortex (PFC) structure and function as a neurobiological explanation. Most imaging studies, however, rely on costly, movement-intolerant, and/or invasive methods to examine cortical differences. This is the first study to use a newer neuroimaging tool that overcomes these limitations, functional Near Infrared Spectroscopy (fNIRS), to investigate hypothesized prefrontal differences. Children (aged 8-12) with ADHD (N = 22) and typically developing (N = 18) children completed phonological working memory (PHWM) and short-term memory (PHSTM) tasks. Children with ADHD evinced poorer performance on both tasks, with greater differences observed in PHWM (Hedges' g = 0.67) relative to PHSTM (g = 0.39). fNIRS revealed reduced hemodynamic response among children with ADHD in the dorsolateral PFC while completing the PHWM task, but not within the anterior or posterior PFC. No between-group fNIRS differences were observed during the PHSTM task. Findings suggest that children with ADHD exhibit an inadequate hemodynamic response in a region of the brain that underlies PHWM abilities. The study also highlights the use of fNIRS as a cost-effective, noninvasive neuroimaging technique to localize/quantify neural activation patterns associated with executive functions.

Denoising task-related fMRI: Balancing noise reduction against signal loss

Preprocessing fMRI data requires striking a fine balance between conserving signals of interest and removing noise. Typical steps of preprocessing include motion correction, slice timing correction, spatial smoothing, and high-pass filtering. However, these standard steps do not remove many sources of noise. Thus, noise-reduction techniques, for example, CompCor, FIX, and ICA-AROMA have been developed to further improve the ability to draw meaningful conclusions from the data. The ability of these techniques to minimize noise while conserving signals of interest has been tested almost exclusively in resting-state fMRI and, only rarely, in task-related fMRI. Application of noise-reduction techniques to task-related fMRI is particularly important given that such procedures have been shown to reduce false positive rates. Little remains known about the impact of these techniques on the retention of signal in tasks that may be associated with systemic physiological changes. In this paper, we compared two ICA-based, that is FIX and ICA-AROMA, two CompCor-based noise-reduction techniques, that is aCompCor, and tCompCor, and standard preprocessing using a large (n = 101) fMRI dataset including noxious heat and non-noxious auditory stimulation. Results show that preprocessing using FIX performs optimally for data obtained using noxious heat, conserving more signals than CompCor-based techniques and ICA-AROMA, while removing only slightly less noise. Similarly, for data obtained during non-noxious auditory stimulation, FIX noise-reduction technique before analysis with a covariate of interest outperforms the other techniques. These results indicate that FIX might be the most appropriate technique to achieve the balance between conserving signals of interest and removing noise during task-related fMRI.

Effectiveness of mock scanners and preparation programs for successful magnetic resonance imaging: a systematic review and meta-analysis

This review aimed to summarise the effectiveness of preparation programs for magnetic resonance imaging (MRI) in children using mock scanners and the success rates by systematically reviewing the current literature. We initially identified 67 articles using the search terms "MRI," "mock" and "child" on online databases. All studies involving a preparation programme for MRI on children ages 18 years or younger, healthy children and those with medical diagnoses were included. The authors extracted data on study design, participant data, details of the MRI protocol and the total numbers of patients who underwent preparation programs and were scanned while awake, without sedation or general anesthesia. Twenty-three studies were included in this review. Preparation programs included in-home and hospital/research facility components; these consisted of a mock scanner, explanatory booklets, recorded MRI scan sounds and other educational materials. The success rate of MRI after the preparation programme reported in each study ranged from 40% to 100%. When all participants from studies that specifically assessed the efficacy of preparation programs were combined, participants who underwent a preparation programme (n = 196) were more likely to complete a successful MRI than those who did not undergo a preparation programme (n = 263) (odds ratio [OR] = 1.98). Our results suggest that preparation programs may help reduce the risk of children failing MRI scans.

Structural and diffusion-weighted brain imaging predictors of attention-deficit/hyperactivity disorder and its symptomology in very young (4- to 7-year-old) children

The current study aimed to identify the key neurobiology of attention-deficit/hyperactivity disorder (ADHD), as it relates to ADHD diagnostic category and symptoms of hyperactive/impulsive behaviour and inattention. To do so, we adapted a predictive modelling approach to identify the key structural and diffusion-weighted brain imaging measures and their relative standing with respect to teacher ratings of executive function (EF) (measured by the Metacognition Index of the Behavior Rating Inventory of Executive Function [BRIEF]) and negativity and emotion regulation (ER) (measured by the Emotion Regulation Checklist [ERC]), in a critical young age range (ages 4 to 7, mean age 5.52 years, 82.2% Hispanic/Latino), where initial contact with educators and clinicians typically take place. Teacher ratings of EF and ER were predictive of both ADHD diagnostic category and symptoms of hyperactive/impulsive behaviour and inattention. Among the neural measures evaluated, the current study identified the critical importance of the largely understudied diffusion-weighted imaging measures for the underlying neurobiology of ADHD and its associated symptomology. Specifically, our analyses implicated the inferior frontal gyrus as a critical predictor of ADHD diagnostic category and its associated symptomology, above and beyond teacher ratings of EF and ER. Collectively, the current set of findings have implications for theories of ADHD, the relative utility of neurobiological measures with respect to teacher ratings of EF and ER, and the developmental trajectory of its underlying neurobiology.

Can this data be saved? Techniques for high motion in resting state scans of first grade children

Motion remains a significant technical hurdle in fMRI studies of young children. Our aim was to develop a straightforward and effective method for obtaining and preprocessing resting state data from a high-motion pediatric cohort. This approach combines real-time monitoring of head motion with a preprocessing pipeline that uses volume censoring and concatenation alongside independent component analysis based denoising. We evaluated this method using a sample of 108 first grade children (age 6-8) enrolled in a longitudinal study of math development. Data quality was assessed by analyzing the correlation between participant head motion and two key metrics for resting state data, temporal signal-to-noise and functional connectivity. These correlations should be minimal in the absence of noise-related artifacts. We compared these data quality indicators using several censoring thresholds to determine the necessary degree of censoring. Volume censoring was highly effective at removing motion-corrupted volumes and ICA denoising removed much of the remaining motion artifact. With the censoring threshold set to exclude volumes that exceeded a framewise displacement of 0.3 mm, preprocessed data met rigorous standards for data quality while retaining a large majority of subjects (83 % of participants). Overall, results show it is possible to obtain usable resting-state data despite extreme motion in a group of young, untrained subjects.

Task-Based Functional Connectivity in Attention-Deficit/Hyperactivity Disorder: A Systematic Review

Altered neurocognitive functioning is a key feature of attention-deficit/hyperactivity disorder (ADHD), and increasing numbers of studies assess task-based functional connectivity in the disorder. We systematically reviewed and critically appraised functional magnetic resonance imaging (fMRI) task-based functional connectivity studies in ADHD. A systematic search conducted up to September 2020 found 34 studies, including 51 comparisons. Comparisons were divided into investigations of ADHD neuropathology (37 comparing ADHD and typical development, 2 comparing individuals with ADHD and their nonsymptomatic siblings, 2 comparing remitted and persistent ADHD, and 1 exploring ADHD symptom severity) and the effects of interventions (8 investigations of stimulant effects and 1 study of fMRI neurofeedback). Large heterogeneity in study methodologies prevented a meta-analysis; thus, the data were summarized as a narrative synthesis. Across cognitive domains, functional connectivity in the cingulo-opercular, sensorimotor, visual, subcortical, and executive control networks in ADHD consistently differed from neurotypical populations. Furthermore, literature comparing individuals with ADHD and their nonsymptomatic siblings as well as adults with ADHD and their remitted peers showed ADHD-related abnormalities in similar sensorimotor and subcortical (primarily striatal) networks. Interventions modulated those dysfunctional networks, with the most consistent action on functional connections with the striatum, anterior cingulate cortex, occipital regions, and midline default mode network structures. Although methodological issues limited many of the reviewed studies, the use of task-based functional connectivity approaches has the potential to broaden the understanding of the neural underpinnings of ADHD and the mechanisms of action of ADHD treatments.

Key considerations for child and adolescent MRI data collection

Cognitive neuroimaging researchers' ability to infer accurate statistical conclusions from neuroimaging depends greatly on the quality of the data analyzed. This need for quality control is never more evident than when conducting neuroimaging studies with children and adolescents. Developmental neuroimaging requires patience, flexibility, adaptability, extra time, and effort. It also provides us a unique, non-invasive way to understand the development of cognitive processes, individual differences, and the changing relations between brain and behavior over the lifespan. In this discussion, we focus on collecting magnetic resonance imaging (MRI) data, as it is one of the more complex protocols used with children and youth. Through our extensive experience collecting MRI datasets with children and families, as well as a review of current best practices, we will cover three main topics to help neuroimaging researchers collect high-quality datasets. First, we review key recruitment and retention techniques, and note the importance for consistency and inclusion across groups. Second, we discuss ways to reduce scan anxiety for families and ways to increase scan success by describing the pre-screening process, use of a scanner simulator, and the need to focus on participant and family comfort. Finally, we outline several important design considerations in developmental neuroimaging such as asking a developmentally appropriate question, minimizing data loss, and the applicability of public datasets. Altogether, we hope this article serves as a useful tool for those wishing to enter or learn more about developmental cognitive neuroscience.

Feasibility of FreeSurfer Processing for T1-Weighted Brain Images of 5-Year-Olds: Semiautomated Protocol of FinnBrain Neuroimaging Lab

Pediatric neuroimaging is a quickly developing field that still faces important methodological challenges. Pediatric images usually have more motion artifact than adult images. The artifact can cause visible errors in brain segmentation, and one way to address it is to manually edit the segmented images. Variability in editing and quality control protocols may complicate comparisons between studies. In this article, we describe in detail the semiautomated segmentation and quality control protocol of structural brain images that was used in FinnBrain Birth Cohort Study and relies on the well-established FreeSurfer v6.0 and ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) consortium tools. The participants were typically developing 5-year-olds [n = 134, 5.34 (SD 0.06) years, 62 girls]. Following a dichotomous quality rating scale for inclusion and exclusion of images, we explored the quality on a region of interest level to exclude all regions with major segmentation errors. The effects of manual edits on cortical thickness values were relatively minor: less than 2% in all regions. Supplementary Material cover registration and additional edit options in FreeSurfer and comparison to the computational anatomy toolbox (CAT12). Overall, we conclude that despite minor imperfections FreeSurfer can be reliably used to segment cortical metrics from T1-weighted images of 5-year-old children with appropriate quality assessment in place. However, custom templates may be needed to optimize the results for the subcortical areas. Through visual assessment on a level of individual regions of interest, our semiautomated segmentation protocol is hopefully helpful for investigators working with similar data sets, and for ensuring high quality pediatric neuroimaging data.

Restoring statistical validity in group analyses of motion-corrupted MRI data

Motion during the acquisition of magnetic resonance imaging (MRI) data degrades image quality, hindering our capacity to characterise disease in patient populations. Quality control procedures allow the exclusion of the most affected images from analysis. However, the criterion for exclusion is difficult to determine objectively and exclusion can lead to a suboptimal compromise between image quality and sample size. We provide an alternative, data‐driven solution that assigns weights to each image, computed from an index of image quality using restricted maximum likelihood. We illustrate this method through the analysis of quantitative MRI data. The proposed method restores the validity of statistical tests, and performs near optimally in all brain regions, despite local effects of head motion. This method is amenable to the analysis of a broad type of MRI data and can accommodate any measure of image quality.

Associations among Household and Neighborhood Socioeconomic Disadvantages, Resting-state Frontoamygdala Connectivity, and Internalizing Symptoms in Youth

Exposure to socioeconomic disadvantages (SED) can have negative impacts on mental health, yet SED are a multifaceted construct and the precise processes by which SED confer deleterious effects are less clear. Using a large and diverse sample of preadolescents (ages 9-10 years at baseline, n = 4038, 49% female) from the Adolescent Brain Cognitive Development Study, we examined associations among SED at both household (i.e., income-needs and material hardship) and neighborhood (i.e., area deprivation and neighborhood unsafety) levels, frontoamygdala resting-state functional connectivity, and internalizing symptoms at baseline and 1-year follow-up. SED were positively associated with internalizing symptoms at baseline and indirectly predicted symptoms 1 year later through elevated symptoms at baseline. At the household level, youth in households characterized by higher disadvantage (i.e., lower income-to-needs ratio) exhibited more strongly negative frontoamygdala coupling, particularly between the bilateral amygdala and medial OFC (mOFC) regions within the frontoparietal network. Although more strongly positive amygdala-mOFC coupling was associated with higher levels of internalizing symptoms at baseline and 1-year follow-up, it did not mediate the association between income-to-needs ratio and internalizing symptoms. However, at the neighborhood level, amygdala-mOFC functional coupling moderated the effect of neighborhood deprivation on internalizing symptoms. Specifically, higher neighborhood deprivation was associated with higher internalizing symptoms for youth with more strongly positive connectivity, but not for youth with more strongly negative connectivity, suggesting a potential buffering effect. Findings highlight the importance of capturing multilevel socioecological contexts in which youth develop to identify youth who are most likely to benefit from early interventions.

Coregistration of magnetic resonance spectroscopy and polysomnography for sleep analysis in human subjects

We developed a protocol for simultaneous magnetic resonance spectroscopy (MRS) and polysomnography (PSG) recordings while subjects are in sleep. The approach is useful to estimate plasticity-stability balances by measuring neurochemical changes in the brain during sleep. We detail the steps needed to minimize artifacts in PSG recordings and the setup and coregistration of MRS data to sleep stages. We also describe useful information for various types of electroencephalogram (EEG) experiments in magnetic resonance imaging (MRI) environments. For complete details on the use and execution of this protocol, please refer to Tamaki et al. (2020b).

Predicting multiscan MRI outcomes in children with neurodevelopmental conditions following MRI simulator training

Pediatric brain imaging holds significant promise for understanding neurodevelopment. However, the requirement to remain still inside a noisy, enclosed scanner remains a challenge. Verbal or visual descriptions of the process, and/or practice in MRI simulators are the norm in preparing children. Yet, the factors predictive of successfully obtaining neuroimaging data remain unclear. We examined data from 250 children (6–12 years, 197 males) with autism and/or attention-deficit/hyperactivity disorder. Children completed systematic MRI simulator training aimed to habituate to the scanner environment and minimize head motion. An MRI session comprised multiple structural, resting-state, task and diffusion scans. Of the 201 children passing simulator training and attempting scanning, nearly all (94%) successfully completed the first structural scan in the sequence, and 88% also completed the following functional scan. The number of successful scans decreased as the sequence progressed. Multivariate analyses revealed that age was the strongest predictor of successful scans in the session, with younger children having lower success rates. After age, sensorimotor atypicalities contributed most to prediction. Results provide insights on factors to consider in designing pediatric brain imaging protocols.

Practical Aspects of Functional Magnetic Resonance Imaging in Children

Functional magnetic resonance imaging (fMRI) has become a broadly accepted presurgical mapping tool for pediatric populations with brain pathology. The aim of this article is to provide general guidelines on the pragmatic aspects of performing and processing fMRI, as well as interpreting its results across children of all age groups. Based on the author's accumulated experience of more than 20 years on this specific field, these guidelines consider many factors that include the particular physiology and anatomy of the child's brain, and how specific peculiarities may pose disadvantages or even certain advantages when performing fMRI procedures. The author carefully details the various challenges that the practitioner might face in dealing with limited volitional behavior and language comprehension of infants and small children and remedial strategies. The type and proper choice of task-based paradigms in keeping with the age and performance of the patient are discussed, as well as the appropriate selection and dosage of sedative agents and their inherent limitations. Recommendations about the scanner and settings for specific sequences are provided, as well as the required devices for appropriate stimulus delivery, response, and motion control. Practical aspects of fMRI postprocessing and quality control are discussed. Finally, given the relevance of resting-state-fMRI for use in noncooperative patients, a praxis-oriented guide to obtain, classify, and understand the spontaneous neural networks (utilizing independent component analysis) is also provided. The article concludes with a thorough discussion about the possible pitfalls at different stages of the fMRI process.

Ecological stress, amygdala reactivity, and internalizing symptoms in preadolescence: Is parenting a buffer?

Ecological stress during adolescent development may increase the sensitivity to negative emotional processes that can contribute to the onset and progression of internalizing behaviors during preadolescence. Although a small number of studies have considered the link among the relations between ecological stress, amygdala reactivity, and internalizing symptoms in childhood and adolescence, these studies have largely been small, cross-sectional, and often do not consider unique roles of parenting or sex. In the current study, we evaluated the interrelations between ecological stress, amygdala reactivity, subsequent internalizing symptoms, and the moderating roles of parenting and sex among 9- and 10-year-old preadolescents from the Adolescent Brain Cognitive Development (ABCD) Study ®. A subset of participants who met a priori quality control criteria for bilateral amygdala activation during the EN-back faces versus places contrast (N = 7,385; Mean Age = 120 months, SD = 7.52; 49.5% Female) were included in the study. A confirmatory factor analysis was performed to create a latent variable of ecological stress, and multiple structural equation models were tested to evaluate the association among baseline ecological stress and internalizing symptoms one year later, the mediating role of amygdala reactivity, and moderating effects of parental acceptance and sex. The results revealed a significant association between ecological stress and subsequent internalizing symptoms, which was greater in males than females. There was no association between amygdala reactivity during the Faces versus Places contrast and ecological stress or subsequent internalizing symptoms, and no mediating role of amygdala or moderating effect of parental acceptance on the association between ecological stress and internalizing symptoms. An alternative mediation model was tested which revealed that there was a small mediating effect of parental acceptance on the association between ecological stress and internalizing symptoms, demonstrating lower internalizing symptoms among preadolescents one year later. Given the lack of association in brain function, ecological stress and internalizing symptoms in preadolescents in this registered report, effects from comparable small studies should be reconsidered in larger samples.

Neural Basis of Biased Competition in Development: Sensory Competition in Visual Cortex of School-Aged Children

The fundamental receptive field (RF) architecture in human visual cortex becomes adult-like by age 5. However, visuo-spatial functions continue to develop until teenage years. This suggests that, despite the early maturation of the RF structure, functional interactions within and across RFs may mature slowly. Here, we used fMRI to investigate functional interactions among multiple stimuli in the visual cortex of school children (ages 8 to 12) in the context of biased competition theory. In the adult visual system, multiple objects presented in the same visual field compete for neural representation. These competitive interactions occur at the level of the RF and are therefore closely linked to the RF architecture. Like in adults, we found suppression of evoked responses in children's visual cortex when multiple stimuli were presented simultaneously. Such suppression effects were modulated by the spatial distance between the stimuli as a function of RF size across the visual system. Our findings suggest that basic competitive interactions in the visual cortex of children above age 8 operate in an adult-like manner, with subtle differences in early visual areas and area MT. Our study establishes a paradigm and provides baseline data to investigate the neural basis of visuo-spatial processing in typical and atypical development.

Detecting microstructural white matter abnormalities of frontal pathways in children with ADHD using advanced diffusion models

Studies using diffusion tensor imaging (DTI) have documented alterations in the attention and executive system in children and adolescents with attention-deficit/hyperactivity disorder (ADHD). While abnormalities in the frontal lobe have also been reported, the associated white matter fiber bundles have not been investigated comprehensively due to the complexity in tracing them through fiber crossings. Furthermore, most studies have used a non-specific DTI model to understand white matter abnormalities. We present results from a first study that uses a multi-shell diffusion MRI (dMRI) data set coupled with an advanced multi-fiber tractography algorithm to probe microstructural measures related to axonal/cellular density and volume of fronto-striato-thalamic pathways in children with ADHD (N = 30) and healthy controls (N = 28). Head motion was firstly examined as a priority in order to assure that no group difference existed. We investigated 45 different white matter fiber bundles in the brain. After correcting for multiple comparisons, we found lower axonal/cellular packing density and volume in ADHD children in 8 of the 45 fiber bundles, primarily in the right hemisphere as follows: 1) Superior longitudinal fasciculus-II (SLF-II) (right), 2) Thalamus to precentral gyrus (right), 3) Thalamus to superior-frontal gyrus (right), 4) Caudate to medial orbitofrontal gyrus (right), 5) Caudate to precentral gyrus (right), 6) Thalamus to paracentral gyrus (left), 7) Caudate to caudal middlefrontal gyrus (left), and 8) Cingulum (bilateral). Our results demonstrate reduced axonal/cellular density and volume in certain frontal lobe white matter fiber tracts, which sub-serve the attention function and executive control systems. Further, our work shows specific microstructural abnormalities in the striato-thalamo-cortical connections, which have not been previously reported in children with ADHD.

Race, Socioeconomic Status, and Cerebellum Cortex Fractional Anisotropy in Pre-Adolescents

Introduction

Cerebellum cortex fractional anisotropy is a proxy of the integrity of the cerebellum cortex. However, less is known about how it is shaped by race and socioeconomic status (SES) indicators such as parental education and household income.

Purpose

In a national sample of American pre-adolescents, this study had two aims: to test the effects of two SES indicators, namely parental education and household income, on cerebellum cortex fractional anisotropy, and to explore racial differences in these effects.

Methods

Using data from the Adolescent Brain Cognitive Development (ABCD) study, we analyzed the diffusion Magnetic Resonance Imaging (dMRI) data of 9565, 9-10-year-old pre-adolescents. The main outcomes were cerebellum cortex fractional anisotropy separately calculated for right and left hemispheres using dMRI. The independent variables were parental education and household income; both treated as categorical variables. Age, sex, ethnicity, and family marital status were the covariates. Race was the moderator. To analyze the data, we used mixed-effects regression models without and with interaction terms. We controlled for propensity score and MRI device.

Results

High parental education and household income were associated with lower right and left cerebellum cortex fractional anisotropy. In the pooled sample, we found significant interactions between race and parental education and household income, suggesting that the effects of parental education and household income on the right and left cerebellum cortex fractional anisotropy are all significantly larger for White than for Black pre-adolescents.

Conclusions

The effects of SES indicators, namely parental education and household income, on pre-adolescents' cerebellum cortex microstructure and integrity are weaker in Black than in White families. This finding is in line with the Marginalization-related Diminished Returns (MDRs), defined as weaker effects of SES indicators for Blacks and other racial and minority groups than for Whites.

Low-motion fMRI data can be obtained in pediatric participants undergoing a 60-minute scan protocol

Performing functional magnetic resonance imaging (fMRI) scans of children can be a difficult task, as participants tend to move while being scanned. Head motion represents a significant confound in fMRI connectivity analyses. One approach to limit motion has been to use shorter MRI protocols, though this reduces the reliability of results. Hence, there is a need to implement methods to achieve high-quality, low-motion data while not sacrificing data quantity. Here we show that by using a mock scan protocol prior to a scan, in conjunction with other in-scan steps (weighted blanket and incentive system), it is possible to achieve low-motion fMRI data in pediatric participants (age range: 7-17 years old) undergoing a 60 min MRI session. We also observe that motion is low during the MRI protocol in a separate replication group of participants, including some with autism spectrum disorder. Collectively, the results indicate it is possible to conduct long scan protocols in difficult-to-scan populations and still achieve high-quality data, thus potentially allowing more reliable fMRI findings.

Re-imagining fMRI for awake behaving infants

Thousands of functional magnetic resonance imaging (fMRI) studies have provided important insight into the human brain. However, only a handful of these studies tested infants while they were awake, because of the significant and unique methodological challenges involved. We report our efforts to address these challenges, with the goal of creating methods for awake infant fMRI that can reveal the inner workings of the developing, preverbal mind. We use these methods to collect and analyze two fMRI datasets obtained from infants during cognitive tasks, released publicly with this paper. In these datasets, we explore and evaluate data quantity and quality, task-evoked activity, and preprocessing decisions. We disseminate these methods by sharing two software packages that integrate infant-friendly cognitive tasks and eye-gaze monitoring with fMRI acquisition and analysis. These resources make fMRI a feasible and accessible technique for cognitive neuroscience in awake and behaving human infants.

Head motion during fMRI tasks is reduced in children and adults if participants take breaks

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In children, fMRI data acquisition split into multiple sessions reduces head motion.

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In adults, fMRI data acquisition split by inside-scanner breaks reduces head motion.

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In both children and adults, motion increases over the duration of a study.

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In both children and adults, motion increases over the duration of a run.

Head motion remains a challenging confound in functional magnetic resonance imaging (fMRI) studies of both children and adults. Most pediatric neuroimaging labs have developed experience-based, child-friendly standards concerning e.g. the maximum length of a session or the time between mock scanner training and actual scanning. However, it is unclear which factors of child-friendly neuroimaging approaches are effective in reducing head motion. Here, we investigate three main factors including (i) time lag of mock scanner training to the actual scan, (ii) prior scan time, and (iii) task engagement in a dataset of 77 children (aged 6–13) and 64 adults (aged 18–35) using a multilevel modeling approach. In children, distributing fMRI data acquisition across multiple same-day sessions reduces head motion. In adults, motion is reduced after inside-scanner breaks. Despite these positive effects of splitting up data acquisition, motion increases over the course of a study as well as over the course of a run in both children and adults. Our results suggest that splitting up fMRI data acquisition is an effective tool to reduce head motion in general. At the same time, different ways of splitting up data acquisition benefit children and adults.

Identifying Cross-individual Correspondences of 3-hinge Gyri

Human brain alignment based on imaging data has long been an intriguing research topic. One of the challenges is the huge inter-individual variabilities, which are pronounced not only in cortical folding patterns, but also in the underlying structural and functional patterns. Also, it is still not fully understood how to link the cross-subject similarity of cortical folding patterns to the correspondences of structural brain wiring diagrams and brain functions. Recently, a specific cortical gyral folding pattern was identified, which is the conjunction of gyri from multiple directions and termed a "gyral hinge". These gyral hinges are characterized by the thickest cortices, the densest long-range fibers, and the most complex functional profiles in contrast to other gyri. In addition to their structural and functional importance, a small portion of 3-hinges found correspondences across subjects and even species by manual labeling. However, it is unclear if such cross-subject correspondences can be found for all 3-hinges, or if the correspondences are interpretable from structural and functional aspects. Given the huge variability of cortical folding patterns, we proposed a novel algorithm which jointly uses structural MRI-derived cortical folding patterns and diffusion-MRI-derived fiber shape features to estimate the correspondences. This algorithm was executed in a group-wise manner, whereby 3-hinges of all subjects were simultaneously aligned. The effectiveness of the algorithm was demonstrated by higher cross-subject 3-hinges' consistency with respect to structural and functional metrics, when compared with other methods. Our findings provide a novel approach to brain alignment and an insight to the linkage between cortical folding patterns and the underlying structural connective diagrams and brain functions.

Resting State fMRI: Going Through the Motions

Resting state functional magnetic resonance imaging (rs-fMRI) has become an indispensable tool in neuroscience research. Despite this, rs-fMRI signals are easily contaminated by artifacts arising from movement of the head during data collection. The artifacts can be problematic even for motions on the millimeter scale, with complex spatiotemporal properties that can lead to substantial errors in functional connectivity estimates. Effective correction methods must be employed, therefore, to distinguish true functional networks from motion-related noise. Research over the last three decades has produced numerous correction methods, many of which must be applied in combination to achieve satisfactory data quality. Subject instruction, training, and mild restraints are helpful at the outset, but usually insufficient. Improvements come from applying multiple motion correction algorithms retrospectively after rs-fMRI data are collected, although residual artifacts can still remain in cases of elevated motion, which are especially prevalent in patient populations. Although not commonly adopted at present, “real-time” correction methods are emerging that can be combined with retrospective methods and that promise better correction and increased rs-fMRI signal sensitivity. While the search for the ideal motion correction protocol continues, rs-fMRI research will benefit from good disclosure practices, such as: (1) reporting motion-related quality control metrics to provide better comparison between studies; and (2) including motion covariates in group-level analyses to limit the extent of motion-related confounds when studying group differences.

Puberty and functional brain development in humans: Convergence in findings?

Although there is a long history of studying the influence of pubertal hormones on brain function/structure in animals, this research in human adolescents is young but burgeoning. Here, we provide a comprehensive review of findings from neuroimaging studies investigating the relation between pubertal and functional brain development in humans. We quantified the findings from this literature in which statistics required for standard meta-analyses are often not provided (i.e., effect size in fMRI studies). To do so, we assessed convergence in findings within content domains (reward, facial emotion, social information, cognitive processing) in terms of the locus and directionality (i.e., positive/negative) of effects. Face processing is the only domain with convergence in the locus of effects in the amygdala. Social information processing is the only domain with convergence of positive effects; however, these effects are not consistently present in any brain region. There is no convergence of effects in either the reward or cognitive processing domains. This limited convergence in findings across domains is not the result of null findings or even due to the variety of experimental paradigms researchers employ. Instead, there are critical theoretical, methodological, and analytical issues that must be addressed in order to move the field forward.

Brain circuitry, behavior, and cognition: A randomized placebo-controlled trial of donepezil in fragile X syndrome

BACKGROUND

Fragile X syndrome, the most common inherited cause for intellectual disability, is associated with alterations in cholinergic among other neurotransmitter systems. This study investigated the effects of donepezil hydrochloride, a cholinesterase inhibitor that has potential to correct aberrant cholinergic signaling.

METHOD

Forty-two individuals with fragile X syndrome (mean age=19.61 years) were randomized to receive 2.5-10.0 mg of donepezil (n=20, seven females) or placebo (n=22, eight females) per day. One individual in the active group withdrew at week 7. Outcomes included the contingency naming test, the aberrant behavior checklist, and behavior and brain activation patterns during a functional magnetic resonance imaging gaze discrimination task.

RESULTS

There were no significant differences between active and placebo groups on cognitive (contingency naming task) or behavioral (total score or subscales of the aberrant behavior checklist) outcomes. At baseline, the active and placebo groups did not differ in functional magnetic resonance imaging activation patterns during the gaze task. After 12 weeks of treatment the active group displayed reduced activation in response to the averted vs direct gaze contrast, relative to the placebo group, in the left superior frontal gyrus.

CONCLUSIONS

Reduced functional brain activation for the active group may represent less arousal in response to direct eye gaze, relative to the placebo group. Change in functional magnetic resonance imaging activation patterns may serve as a more sensitive metric and predictor of response to treatment when compared to cognitive and behavioral assessments. Our results suggest that donepezil may have an impact on brain functioning, but longer term follow-up and concomitant behavioral intervention may be required to demonstrate improvement in cognition and behavior.

Structural and functional abnormalities of vision-related brain regions in cirrhotic patients: a MRI study

Purpose

Previous studies have focused on global cerebral alterations observed in cirrhosis. However, little was known about the specific abnormalities of vision-related brain regions in cirrhotic patients. In this study, we sought to explore neurological alterations of vision-related regions by measuring brain resting-state network connectivity, based on the structural investigation in cirrhotic patients without clinical sign of hepatic encephalopathy (HE).

Methods

Structural and functional magnetic resonance image (MRI) data were collected from 20 hepatitis B virus (HBV)-related cirrhotic patients without clinical sign of HE and from 20 healthy controls (HC). Voxel-based morphometric (VBM) analysis and brain functional network analysis were performed to detect abnormalities in cerebral structure and function.

Results

Cirrhotic patients showed regions with the most significant gray matter reduction primarily in vision-related brain regions, including the bilateral lingual gyri, left putamen, right fusiform gyrus, and right calcarine gyrus, and other significant gray matter reductions were distributed in bilateral hippocampus. Based on structural investigation focused on vision-related regions, brain functional network analysis revealed decreased functional connectivity between brain functional networks within vision-related regions (primary visual network (PVN), higher visual network (HVN), visuospatial network (VSN)) in the patient group compared with HC group.

Conclusion

These results indicate that structural and functional impairment were evident in the vision-related brain regions in cirrhotic patients without clinical sign of hepatic encephalopathy. The physiopathology and clinical relevance of these changes could not be ascertained from the present study, which provided a basis for further evolution of the disease.

Customized head molds reduce motion during resting state fMRI scans

Head motion causes artifacts in functional magnetic resonance imaging (fMRI) scans, a problem especially relevant for task-free resting state paradigms and for developmental, aging, and clinical populations. In a cohort spanning 7-28 years old (mean age 15) we produced customized head-anatomy-specific Styrofoam molds for each subject that inserted into an MRI head coil. We scanned these subjects under two conditions: using our standard procedure of packing the head coil with foam padding about the head to reduce head motion, and using the customized molds to reduce head motion. In 12 of 13 subjects, the molds reduced head motion throughout the scan and reduced the fraction of a scan with substantial motion (i.e., volumes with motion notably above baseline levels of motion). Motion was reduced in all 6 head position estimates, especially in rotational, left-right, and superior-inferior directions. Motion was reduced throughout the full age range studied, including children, adolescents, and young adults. In terms of the fMRI data itself, quality indices improved with the head mold on, scrubbing analyses detected less distance-dependent artifact in scans with the head mold on, and distant-dependent artifact was less evident in both the entire scan and also during only low-motion volumes. Subjects found the molds comfortable. Head molds are thus effective tools for reducing head motion, and motion artifacts, during fMRI scans.

Clinical application of advanced MR methods in children: points to consider

The application of both functional MRI and diffusion MR tractography prior to a neurosurgical operation is well established in adults, but less so in children, for several reasons. For this review, we have identified several aspects (task design, subject preparation, actual scanning session, data processing, interpretation of results, and decision-making) where pediatric peculiarities should be taken into account. Further, we not only systematically identify common issues, but also provide solutions, based on our experience as well as a review of the pertinent literature. The aim is to provide the clinician as well as the imaging scientist with information that helps to plan, conduct, and interpret such a clinically-indicated exam in a way that maximizes benefit for, and minimizes the burden on the individual child.

Advances, challenges, and promises in pediatric neuroimaging of neurodevelopmental disorders

Recent years have witnessed the proliferation of neuroimaging studies of neurodevelopmental disorders (NDDs), particularly of children with autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and Tourette's syndrome (TS). Neuroimaging offers immense potential in understanding the biology of these disorders, and how it relates to clinical symptoms. Neuroimaging techniques, in the long run, may help identify neurobiological markers to assist clinical diagnosis and treatment. However, methodological challenges have affected the progress of clinical neuroimaging. This paper reviews the methodological challenges involved in imaging children with NDDs. Specific topics include correcting for head motion, normalization using pediatric brain templates, accounting for psychotropic medication use, delineating complex developmental trajectories, and overcoming smaller sample sizes. The potential of neuroimaging-based biomarkers and the utility of implementing neuroimaging in a clinical setting are also discussed. Data-sharing approaches, technological advances, and an increase in the number of longitudinal, prospective studies are recommended as future directions. Significant advances have been made already, and future decades will continue to see innovative progress in neuroimaging research endeavors of NDDs.

The Adolescent Brain Cognitive Development (ABCD) study: Imaging acquisition across 21 sites

The ABCD study is recruiting and following the brain development and health of over 10,000 9–10 year olds through adolescence. The imaging component of the study was developed by the ABCD Data Analysis and Informatics Center (DAIC) and the ABCD Imaging Acquisition Workgroup. Imaging methods and assessments were selected, optimized and harmonized across all 21 sites to measure brain structure and function relevant to adolescent development and addiction. This article provides an overview of the imaging procedures of the ABCD study, the basis for their selection and preliminary quality assurance and results that provide evidence for the feasibility and age-appropriateness of procedures and generalizability of findings to the existent literature.

Convergence of fMRI and ERP measures of emotional face processing in combat-exposed U. S. military veterans

The late positive potential (LPP) and fMRI blood-oxygen-level dependent (BOLD) activity can provide complementary measures of the processing of affective and social stimuli. Separate lines of research using these measures have often employed the same stimuli, paradigms, and samples; however, there remains relatively little understanding of the way in which individual differences in one of these measures relates to the other, and all prior research has been conducted in psychiatrically healthy samples and using emotional scenes (not faces). Here, 32 combat-exposed U. S. military veterans with varying levels of posttraumatic stress symptomatology viewed affective social stimuli (angry, fearful, and happy faces) and geometric shapes during separate EEG and fMRI BOLD recordings. Temporospatial principal component analysis was used to quantify the face-elicited LPP in a data-driven manner, prior to conducting whole-brain correlations between resulting positivities and fMRI BOLD elicited by faces. Participants with larger positivities to fearful faces (> shapes) showed increased activation in the amygdala; larger positivities to angry and happy faces (> shapes) were associated with increased BOLD activation in the posterior fusiform gyrus and inferior temporal gyrus, respectively. Across all face types, larger positivities were associated with increased activation in the fusiform "face" area. Correlations using mean area amplitude LPPs showed an association with increased activation in the anterior insula for angry faces (> shapes). LPP-BOLD associations were not moderated by PTSD. Findings provide the first evidence of correspondence between face-elicited LPP and BOLD activation across a range of (normal to disordered) psychiatric health.

Children's head motion during fMRI tasks is heritable and stable over time

Head motion during fMRI scans negatively impacts data quality, and as post-acquisition techniques for addressing motion become increasingly stringent, data retention decreases. Studies conducted with adult participants suggest that movement acts as a relatively stable, heritable phenotype that serves as a marker for other genetically influenced phenotypes. Whether these patterns extend downward to childhood has critical implications for the interpretation and generalizability of fMRI data acquired from children. We examined factors affecting scanner motion in two samples: a population-based twin sample of 73 participants (ages 7–12 years) and a case-control sample of 32 non-struggling and 78 struggling readers (ages 8–11 years), 30 of whom were scanned multiple times. Age, but not ADHD symptoms, was significantly related to scanner movement. Movement also varied as a function of task type, run length, and session length. Twin pair concordance for head motion was high for monozygotic twins and moderate for dizygotic twins. Cross-session test-retest reliability was high. Together, these findings suggest that children’s head motion is a genetically influenced trait that has the potential to systematically affect individual differences in BOLD changes within and across groups. We discuss recommendations for future work and best practices for pediatric neuroimaging.

Minimizing noise in pediatric task-based functional MRI; Adolescents with developmental disabilities and typical development

Functional Magnetic Resonance Imaging (fMRI) represents a powerful tool with which to examine brain functioning and development in typically developing pediatric groups as well as children and adolescents with clinical disorders. However, fMRI data can be highly susceptible to misinterpretation due to the effects of excessive levels of noise, often related to head motion. Imaging children, especially with developmental disorders, requires extra considerations related to hyperactivity, anxiety and the ability to perform and maintain attention to the fMRI paradigm. We discuss a number of methods that can be employed to minimize noise, in particular movement-related noise. To this end we focus on strategies prior to, during and following the data acquisition phase employed primarily within our own laboratory. We discuss the impact of factors such as experimental design, screening of potential participants and pre-scan training on head motion in our adolescents with developmental disorders and typical development. We make some suggestions that may minimize noise during data acquisition itself and finally we briefly discuss some current processing techniques that may help to identify and remove noise in the data. Many advances have been made in the field of pediatric imaging, particularly with regard to research involving children with developmental disorders. Mindfulness of issues such as those discussed here will ensure continued progress and greater consistency across studies.

Quality Control of Structural MRI Images Applied Using FreeSurfer-A Hands-On Workflow to Rate Motion Artifacts

In structural magnetic resonance imaging motion artifacts are common, especially when not scanning healthy young adults. It has been shown that motion affects the analysis with automated image-processing techniques (e.g., FreeSurfer). This can bias results. Several developmental and adult studies have found reduced volume and thickness of gray matter due to motion artifacts. Thus, quality control is necessary in order to ensure an acceptable level of quality and to define exclusion criteria of images (i.e., determine participants with most severe artifacts). However, information about the quality control workflow and image exclusion procedure is largely lacking in the current literature and the existing rating systems differ. Here, we propose a stringent workflow of quality control steps during and after acquisition of T1-weighted images, which enables researchers dealing with populations that are typically affected by motion artifacts to enhance data quality and maximize sample sizes. As an underlying aim we established a thorough quality control rating system for T1-weighted images and applied it to the analysis of developmental clinical data using the automated processing pipeline FreeSurfer. This hands-on workflow and quality control rating system will aid researchers in minimizing motion artifacts in the final data set, and therefore enhance the quality of structural magnetic resonance imaging studies.

Evaluation of Denoising Strategies to Address Motion-Correlated Artifacts in Resting-State Functional Magnetic Resonance Imaging Data from the Human Connectome Project

Like all resting-state functional connectivity data, the data from the Human Connectome Project (HCP) are adversely affected by structured noise artifacts arising from head motion and physiological processes. Functional connectivity estimates (Pearson's correlation coefficients) were inflated for high-motion time points and for high-motion participants. This inflation occurred across the brain, suggesting the presence of globally distributed artifacts. The degree of inflation was further increased for connections between nearby regions compared with distant regions, suggesting the presence of distance-dependent spatially specific artifacts. We evaluated several denoising methods: censoring high-motion time points, motion regression, the FMRIB independent component analysis-based X-noiseifier (FIX), and mean grayordinate time series regression (MGTR; as a proxy for global signal regression). The results suggest that FIX denoising reduced both types of artifacts, but left substantial global artifacts behind. MGTR significantly reduced global artifacts, but left substantial spatially specific artifacts behind. Censoring high-motion time points resulted in a small reduction of distance-dependent and global artifacts, eliminating neither type. All denoising strategies left differences between high- and low-motion participants, but only MGTR substantially reduced those differences. Ultimately, functional connectivity estimates from HCP data showed spatially specific and globally distributed artifacts, and the most effective approach to address both types of motion-correlated artifacts was a combination of FIX and MGTR.

Aberrant Development of Speech Processing in Young Children with Autism: New Insights from Neuroimaging Biomarkers

From the time of birth, a newborn is continuously exposed and naturally attracted to human voices, and as he grows, he becomes increasingly responsive to these speech stimuli, which are strong drivers for his language development and knowledge acquisition about the world. In contrast, young children with autism spectrum disorder (ASD) are often insensitive to human voices, failing to orient and respond to them. Failure to attend to speech in turn results in altered development of language and social-communication skills. Here, we review the critical role of orienting to speech in ASD, as well as the neural substrates of human voice processing. Recent functional neuroimaging and electroencephalography studies demonstrate that aberrant voice processing could be a promising marker to identify ASD very early on. With the advent of refined brain imaging methods, coupled with the possibility of screening infants and toddlers, predictive brain function biomarkers are actively being examined and are starting to emerge. Their timely identification might not only help to differentiate between phenotypes, but also guide the clinicians in setting up appropriate therapies, and better predicting or quantifying long-term outcome.

Considerations for MRI study design and implementation in pediatric and clinical populations

Human neuroimaging, specifically magnetic resonance imaging (MRI), is being used with increasing popularity to study brain structure and function in development and disease. When applying these methods to developmental and clinical populations, careful consideration must be taken with regard to study design and implementation. In this article, we discuss two major considerations particularly pertinent to brain research in special populations. First, we discuss considerations for subject selection and characterization, including issues related to comorbid conditions, medication status, and clinical assessment. Second, we discuss methods and considerations for acquisition of adequate, useable MRI data. Given that children and patients may experience anxiety with the scanner environment, preventing participation, and that they have a higher risk of motion artifact, resulting in data loss, successful subject compliance and data acquisition are not trivial tasks. We conclude that, as researchers, we must consider a number of issues when using neuroimaging tools to study children and patients, and we should thoughtfully justify our choices of methods and study design.

MRI Customized Play Therapy in Children Reduces the Need for Sedation--A Randomized Controlled Trial

OBJECTIVE

To evaluate the effectiveness of an MRI-specific play therapy intervention on the need for sedation in young children.

METHODS

All children in the age group of 4-10 y, who were advised an MRI scan over a period of one year were randomized. Exclusion criteria included children with neurodevelopmental disorders impairing cognition and children who had previously undergone diagnostic MRI. A total of 79 children were randomized to a control or an intervention condition. The intervention involved familiarizing the child with the MRI model machine, listing the steps involved in the scan to the child in vivid detail, training the child to stand still for 5 min, and conducting several dry runs with a doll or a favorite toy. The study was approved by the Institute ethical committee.

RESULTS

The need for sedation was 41 % (n = 16) in the control group and this declined to 20 % (n = 8) in the intervention group (χ(2) = 4.13; P = 0.04). The relative risk of sedation decreased by 49 % in the intervention group as compared to the control group (RR 0.49; 95 % CI: 0.24-1.01) and this difference was statistically significant (P = 0.04). The absolute risk difference in sedation use between intervention and control group was 21 % (95 % CI 1.3 %-40.8 %). Even on adjusting for age, relative risk of sedation remained significantly lower in children undergoing play therapy as compared to the control (RR 0.57, 95 % CI: 0.32-0.98) with P value of 0.04.

CONCLUSIONS

The use of an MRI customized play therapy with pediatric patients undergoing diagnostic MRI resulted in significant reduction of the use of sedation.

Head Motion and Inattention/Hyperactivity Share Common Genetic Influences: Implications for fMRI Studies of ADHD

Head motion (HM) is a well known confound in analyses of functional MRI (fMRI) data. Neuroimaging researchers therefore typically treat HM as a nuisance covariate in their analyses. Even so, it is possible that HM shares a common genetic influence with the trait of interest. Here we investigate the extent to which this relationship is due to shared genetic factors, using HM extracted from resting-state fMRI and maternal and self report measures of Inattention and Hyperactivity-Impulsivity from the Strengths and Weaknesses of ADHD Symptoms and Normal Behaviour (SWAN) scales. Our sample consisted of healthy young adult twins (N = 627 (63% females) including 95 MZ and 144 DZ twin pairs, mean age 22, who had mother-reported SWAN; N = 725 (58% females) including 101 MZ and 156 DZ pairs, mean age 25, with self reported SWAN). This design enabled us to distinguish genetic from environmental factors in the association between head movement and ADHD scales. HM was moderately correlated with maternal reports of Inattention (r = 0.17, p-value = 7.4E-5) and Hyperactivity-Impulsivity (r = 0.16, p-value = 2.9E-4), and these associations were mainly due to pleiotropic genetic factors with genetic correlations [95% CIs] of rg = 0.24 [0.02, 0.43] and rg = 0.23 [0.07, 0.39]. Correlations between self-reports and HM were not significant, due largely to increased measurement error. These results indicate that treating HM as a nuisance covariate in neuroimaging studies of ADHD will likely reduce power to detect between-group effects, as the implicit assumption of independence between HM and Inattention or Hyperactivity-Impulsivity is not warranted. The implications of this finding are problematic for fMRI studies of ADHD, as failing to apply HM correction is known to increase the likelihood of false positives. We discuss two ways to circumvent this problem: censoring the motion contaminated frames of the RS-fMRI scan or explicitly modeling the relationship between HM and Inattention or Hyperactivity-Impulsivity.

Mapping Individual Brain Networks Using Statistical Similarity in Regional Morphology from MRI

Representing brain morphology as a network has the advantage that the regional morphology of ‘isolated’ structures can be described statistically based on graph theory. However, very few studies have investigated brain morphology from the holistic perspective of complex networks, particularly in individual brains. We proposed a new network framework for individual brain morphology. Technically, in the new network, nodes are defined as regions based on a brain atlas, and edges are estimated using our newly-developed inter-regional relation measure based on regional morphological distributions. This implementation allows nodes in the brain network to be functionally/anatomically homogeneous but different with respect to shape and size. We first demonstrated the new network framework in a healthy sample. Thereafter, we studied the graph-theoretical properties of the networks obtained and compared the results with previous morphological, anatomical, and functional networks. The robustness of the method was assessed via measurement of the reliability of the network metrics using a test-retest dataset. Finally, to illustrate potential applications, the networks were used to measure age-related changes in commonly used network metrics. Results suggest that the proposed method could provide a concise description of brain organization at a network level and be used to investigate interindividual variability in brain morphology from the perspective of complex networks. Furthermore, the method could open a new window into modeling the complexly distributed brain and facilitate the emerging field of human connectomics.

Neural response to social rejection in children with early separation experiences

OBJECTIVE

Nonhuman and human studies have documented the adverse effects of early life stress (ELS) on emotion regulation and underlying neural circuitry. Less is known about how these experiences shape social processes and neural circuitry. In this study, we thus investigated how ELS affects children's perception of, and neural response to, negative social experiences in a social exclusion paradigm (Cyberball).

METHOD

Twenty-five foster or adopted children with ELS (age 10.6 ± 1.8 years, 13 male and 12 female) and 26 matched nonseparated controls (age 10.38 ± 1.7 years, 12 male and 14 female) took part in a Cyberball paradigm during functional magnetic resonance imaging (fMRI).

RESULTS

During peer rejection, children with ELS reported significantly more feelings of exclusion and frustration than nonseparated controls. On the neural level, children with ELS showed reduced activation in the dorsal anterior cingulate cortex (dACC) and dorsolateral prefrontal cortex (dlPFC), and reduced connectivity between dlPFC-dACC, areas previously implicated in affect regulation. Conversely, children with ELS showed increased neural activation in brain regions involved in memory, arousal, and threat-related processing (middle temporal gyrus, thalamus, ventral tegmental area) relative to controls during social exclusion. The number of separation experiences before entering the permanent family predicted reductions in fronto-cingulate recruitment. The relationship between early separations and self-reported exclusion was mediated by dlPFC activity.

CONCLUSION

The findings suggest that ELS leads to alterations in neural circuitry implicated in the regulation of socioemotional processes. This neural signature may underlie foster children's differential reactivity to rejection in everyday life and could increase risk for developing affective disorders.

Aberrant face and gaze habituation in fragile x syndrome

OBJECTIVE

The authors sought to investigate neural system habituation to face and eye gaze in fragile X syndrome, a disorder characterized by eye-gaze aversion, among other social and cognitive deficits.

METHOD

Participants (ages 15-25 years) were 30 individuals with fragile X syndrome (females, N=14) and a comparison group of 25 individuals without fragile X syndrome (females, N=12) matched for general cognitive ability and autism symptoms. Functional MRI (fMRI) was used to assess brain activation during a gaze habituation task. Participants viewed repeated presentations of four unique faces with either direct or averted eye gaze and judged the direction of eye gaze.

RESULTS

Four participants (males, N=4/4; fragile X syndrome, N=3) were excluded because of excessive head motion during fMRI scanning. Behavioral performance did not differ between the groups. Less neural habituation (and significant sensitization) in the fragile X syndrome group was found in the cingulate gyrus, fusiform gyrus, and frontal cortex in response to all faces (direct and averted gaze). Left fusiform habituation in female participants was directly correlated with higher, more typical levels of the fragile X mental retardation protein and inversely correlated with autism symptoms. There was no evidence for differential habituation to direct gaze compared with averted gaze within or between groups.

CONCLUSIONS

Impaired habituation and accentuated sensitization in response to face/eye gaze was distributed across multiple levels of neural processing. These results could help inform interventions, such as desensitization therapy, which may help patients with fragile X syndrome modulate anxiety and arousal associated with eye gaze, thereby improving social functioning.

Prediction of compliance with MRI procedures among children of ages 3 years to 12 years

BACKGROUND

A number of children are unable to comply with an MRI procedure and require general anesthetic. However, we lack information about which factors are associated with MRI compliance in young children.

OBJECTIVE

To determine the strongest predictors of MRI compliance, focusing on variables that can be easily rated by patients' parents.

MATERIALS AND METHODS

A sample of 205 children ages 3-11 years (mean age 6.6 years) who were at risk of non-compliance were recruited from a children's hospital. Their parents completed a behavior assessment scale for children as well as a questionnaire that assessed their expectations of compliance and perception of their child's typical medical compliance. The children subsequently completed a mock MRI with an educational play therapist and a clinical MRI, with the quality of the scan scored by the MRI technologist.

RESULTS

Overall, 88.3% of children complied with the clinical scan and achieved diagnostic images, with age unrelated to compliance in this well-prepared patient group. The strongest predictors of MRI compliance were parental expectations and ratings of how well the child typically copes with medical procedures. Non-compliance was related to child attention problems and to poor adaptability among children. A total of 64 preschool-age children (91.4%) and 110 school-age children (95.7%) were correctly classified as compliant or non-compliant based on these predictor variables.

CONCLUSION

A child's temperament, medical experiences and parental expectations provide important information in predicting which children successfully comply with an MRI procedure and which require general anesthesia. Further study is needed to explore the utility of these variables in predicting compliance at sites that do not have access to an MRI simulator.

Heritability of head motion during resting state functional MRI in 462 healthy twins

Head motion (HM) is a critical confounding factor in functional MRI. Here we investigate whether HM during resting state functional MRI (RS-fMRI) is influenced by genetic factors in a sample of 462 twins (65% female; 101 MZ (monozygotic) and 130 DZ (dizygotic) twin pairs; mean age: 21 (SD = 3.16), range 16-29). Heritability estimates for three HM components-mean translation (MT), maximum translation (MAXT) and mean rotation (MR)-ranged from 37 to 51%. We detected a significant common genetic influence on HM variability, with about two-thirds (genetic correlations range 0.76-1.00) of the variance shared between MR, MT and MAXT. A composite metric (HM-PC1), which aggregated these three, was also moderately heritable (h(2) = 42%). Using a sub-sample (N = 35) of the twins we confirmed that mean and maximum translational and rotational motions were consistent "traits" over repeated scans (r = 0.53-0.59); reliability was even higher for the composite metric (r = 0.66). In addition, phenotypic and cross-trait cross-twin correlations between HM and resting state functional connectivities (RS-FCs) with Brodmann areas (BA) 44 and 45, in which RS-FCs were found to be moderately heritable (BA44: h(2) = 0.23 (sd = 0.041), BA45: h(2) = 0.26 (sd = 0.061)), indicated that HM might not represent a major bias in genetic studies using FCs. Even so, the HM effect on FC was not completely eliminated after regression. HM may be a valuable endophenotype whose relationship with brain disorders remains to be elucidated.

Resting state functional connectivity of the nucleus accumbens in youth with a family history of alcoholism

Adolescents with a family history of alcoholism (FHP) are at heightened risk for developing alcohol use disorders (AUDs). The nucleus accumbens (NAcc), a key brain region for reward processing, is implicated in the development of AUDs. Thus, functional connectivity of the NAcc may be an important marker of risk in FHP youth. Resting state functional magnetic resonance imaging (rs-fcMRI) was used to examine the intrinsic connectivity of the NAcc in 47 FHP and 50 family history negative (FHN) youth, ages 10-16 years old. FHP and FHN adolescents showed significant group differences in resting state synchrony between the left NAcc and bilateral inferior frontal gyri and the left postcentral gyrus (PG). Additionally, FHP youth differed from FHN youth in right NAcc functional connectivity with the left orbitofrontal cortex (OFC), left superior temporal gyrus, right cerebellum, left PG, and right occipital cortex. These results indicate that FHP youth have less segregation between the NAcc and executive functioning brain regions, and less integration with reward-related brain areas, such as the OFC. The findings of the current study highlight that premorbid atypical connectivity of appetitive systems, in the absence of heavy alcohol use, may be a risk marker in FHP adolescents.