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As a neuroimager working with open-source software and tools, you will quickly become familiar with the website GitHub, which is a (for profit) platform for storing, managing, and sharing code, software, and projects. Many of the open-source tools discussed in this book are hosted on GitHub. Although people are generally very familiar with GitHub (or GitLab), they are often less familiar with its foundation - Git. Better understanding Git will help you better manage your own projects and will also help you to better understand GitHub and how to use it optimally. In this chapter, we will first explain Git and how to use it, then we will turn to GitHub. A worked example – a clustering analysis – with open access neuroimaging data is provided, demonstrating utilities such as version control, branching and conflict resolution.

Getting started on any project is often the hardest thing - and when it comes to starting your career in research, just figuring out where and how to start can seem like an insurmountable challenge. This is particularly true at this moment - when there are so many programming languages, programmes, and systems that are freely available to neuroimaging researchers, and even more guides, tutorials, and courses on how to use them. This chapter is intended to set you off on the right foot as you get stuck into the task of learning to work with large neuroimaging data. We will cover a number of processes, systems, and practices that you should adopt to help ensure that your work is efficient, your processing steps traceable and repeatable, your analyses and findings reproducible, and your data and processing scripts amenable to sharing and open science. While this chapter is aimed at those getting started, it will also be of use to established researchers who want to streamline their processes and maximise robustness and reproducibility of their neuroimaging analyses. Finally, this chapter is also intended to help make neuroimaging work practices and processes more environmentally sustainable by reducing demands on computational resources through better planning, efficiency, and awareness of resource use.

1AbstractBy capitalizing on the power of multivariate analyses of large datasets, predictive modeling approaches are enabling progress toward robust and reproducible brain-based markers of neuropsychiatric conditions. While Deep Learning offers a particularly promising avenue to further advance progress, there are challenges related to implementation in 3D (best for MRI) and interpretability. Here, we address these challenges and describe an interpretable predictive pipeline for inferring Autism diagnosis using 3D Deep Learning applied to minimally processed structural MRI scans. We trained 3D Deep Learning models to predict Autism diagnosis using the openly available ABIDE I and II datasets (n = 1329, split into training, validation, and test sets). Importantly, we did not perform transformation to template space, to reduce bias and maximize sensitivity to structural alterations associated with Autism. Our models attained predictive accuracies equivalent to those of previous Machine Learning studies, while side-stepping the time- and resource-demanding requirement to first normalize data to a template, thus minimizing the time required to generate predictions. Further, our interpretation step, which identified brain regions that contributed most to accurate inference, revealed regional Autism-related alterations that were highly consistent with the literature, such as in a left-lateralized network of regions supporting language processing. We have openly shared our code and models to enable further progress towards remaining challenges, such as the clinical heterogeneity of Autism, and to enable the extension of our method to other neuropsychiatric conditions.

Dublin, Ireland, like most other large cities has undergone lockdown due to the outbreak of the coronavirus. Ongoing physical distancing requirements, as cities reopens, has resulted in a collapse to transit’s capacity and ability to meet demand, forcing authorities to reimagine how people can travel in a pandemic/post-pandemic world. For Dublin, campaigns have focused on encouraging those who can walk or cycle to use active transport options if they are close enough to their place of employment, when the city fully reopens. The purpose of this is to ensure adequate physical distancing can occur while alleviating the pressure on public transport systems, thereby freeing up space for those who are unable to commute via active transport and for those beyond a range in which it is feasible. Trinity College Dublin, the University of Dublin (TCD) is located in the city centre of Ireland’s capital. Since less than 1% of staff drive to the campus and students are not permitted to park on the campus, the University community has been working with Dublin City Council (DCC) to advance planning and built environment interventions to enable staff and students to safely return to work and education. This paper presents the results of the “Commuting to Trinity while Covid-19 Social Distancing is Required” Travel Survey for TCD students and staff, conducted in June and July 2020 (n = 2653). Conducted to determine how staff and students would like to travel to TCD, when the campus fully reopens, it identifies which factors influence their mode choice and choice of working locations. The Trinity University campus makes for an interesting case study as it allows us to understand how the reopening of a major employment, educational and cultural site within an urban area, which is primarily served by transit and active transport, can address physical distancing restrictions and decreased capacity of public transport.

Background Childhood maltreatment is associated with lifelong psychiatric sequelae. However, our understanding of neurobiological mechanisms responsible for this association is limited. Childhood maltreatment may confer risk for psychopathology by altering neurodevelopmental trajectories during childhood and adolescence. Longitudinal research, which is essential for examining this question, has been limited. Methods We investigated maltreatment-associated alterations in the development of neural circuitry. Associations between cumulative childhood maltreatment (assessed using a dimensional measure of abuse and neglect via the Childhood Trauma Questionnaire) and the longitudinal development of resting-state functional connectivity (rsFC) were examined in 130 community-residing adolescents. Functional magnetic resonance imaging data were acquired at age 16 (T1; mean ± SD age, 16.46 ± 0.52 years; 66 females) and age 19 (T2; mean follow-up period, 2.35 years; n = 90 with functional magnetic resonance imaging data at both time points). Results We found maltreatment to be associated with widespread longitudinal increases in rsFC, primarily between default mode, dorsal attention, and frontoparietal systems. We also found sex-dependent increased maltreatment-associated rsFC in male participants in salience and limbic circuits. Cross-sectional analyses revealed a shift in maltreatment-related rsFC alterations, which were localized to subcortical and sensory circuits at T1 and to frontal circuits at T2. Finally, longitudinal increases in rsFC connectivity mediated the relationship between childhood maltreatment and increased depressive symptoms. Conclusions To our knowledge, this is the first study to examine longitudinal maltreatment-related alterations in rsFC in adolescents. Our findings shed light on the neurodevelopmental consequences of childhood maltreatment and provide evidence for their role in risk for depression.

Early years education in England is in crisis. This article looks at what is needed to better provide the kind of education and care that young children need outside the home, from birth to school-starting age. It explores: the current arrangements and varieties of provision and approaches in England; educational and developmental research about young children's development and early learning; the current national early years curriculum and how it contrasts to other international models and pedagogical approaches; the importance of play-based learning; the role of adults in observing, recording, assessing and supporting young children's learning; and the holistic nature of children's learning - which makes education and care inseparable in young children's lives. Neoliberal governments have had little interest in these questions: they have been focused instead on marketising the sector, which has led to great inequality of provision; and they have been unwilling to provide the necessary funding to train staff and maintain appropriate learning environments; most fundamentally, they have engaged in an ideological drive to impose on very small children a narrow and formal curriculum that ignores all the evidence about good practice in the sector, and is focused on making them 'school ready' - that is, ready to fit into the rigid frameworks they have already imposed on primary school education.

Neuroscience has cast new light on the nature of human morality by exploiting simplified paradigms. To enhance our understanding of everyday moral decisions, the field should complement computational approaches with naturalistic paradigms and a focus on narratives and stories.

Task-free functional connectivity in animal models provides an experimental framework to examine connectivity phenomena under controlled conditions and allows comparison with invasive or terminal procedures. To date, animal acquisitions are performed with varying protocols and analyses that hamper result comparison and integration. We introduce StandardRat, a consensus rat functional MRI acquisition protocol tested across 20 centers. To develop this protocol with optimized acquisition and processing parameters, we initially aggregated 65 functional imaging datasets acquired in rats from 46 centers. We developed a reproducible pipeline for the analysis of rat data acquired with diverse protocols and determined experimental and processing parameters associated with a more robust functional connectivity detection. We show that the standardized protocol enhances biologically plausible functional connectivity patterns, relative to pre-existing acquisitions. The protocol and processing pipeline described here are openly shared with the neuroimaging community to promote interoperability and cooperation towards tackling the most important challenges in neuroscience.

Analyses of structural MRI (sMRI) data depend on robust upstream data quality control (QC). It is also crucial that researchers retain the maximum amount of usable data to ensure reproducible, generalisable models. The time-consuming task of manual QC evaluation has prompted the development of tools for the automatic assessment of brain sMRI scans. Such tools are particularly valuable in this age of big data. One limitation of the most commonly used tools is that execution time is long, which poses a challenge in terms of duration and resource usage, particularly when processing large datasets. Further, evaluation is global (pass/fail) rather than localized. Having a tool that localizes areas of low quality could prevent unnecessary data loss. To address these issues, we trained a Deep Learning model, ProtoPNet, to classify minimally preprocessed 2D slices of scans that were manually annotated with a refined quality assessment (ABIDE 1 n = 980 scans). To validate the best model, we assessed 2141 ABCD scans for which gold-standard manual QC annotations were available. We obtained excellent accuracy: 82.4% for good quality scans (Pass), 91.4% for medium to low quality scans (Fail). Further validation using 799 scans from ABIDE 2 and 751 scans from ADHD-200 confirmed the reliability of our model. Accuracy was comparable to or exceeded that of another commonly used tool (MRIQC), but with dramatically reduced processing and prediction time (1 min per scan, GPU machine, CUDA-compatible). To facilitate faster and more accurate QC prediction for the neuroimaging community, we have shared the model that returned the most reliable global quality scores, local predictions of quality, and maps and prototypes of local artifacts as a BIDS-app (https://github.com/garciaml/BrainQCNet).

BackgroundAdults 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 behavior (mediational endophenotypes).MethodsResting-state eyes-open and eyes-closed EEG were 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.ResultsEyes-open absolute and relative EEG power distinguished ADHD from control participants (area under receiver operating characteristic = .71-.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 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 = .68-.72), suggesting that these features may be a mediational endophenotype for adult ADHD.ConclusionsResting-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.

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., NeuroImage, 253, ISSN:1053-8119, ISSN:1095-9572

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., Journal of Child Psychology and Psychiatry, 62 (10), ISSN:0021-9630, ISSN:1469-7610

Autism spectrum disorder is characterized by difficulties with social communication, with a preponderance in males. Evidence supports a relationship between metacognitive executive functions (e.g. planning, working memory) and social communication in autism spectrum disorder, yet relationships with specific metacognitive executive functions and how gender alters the expression of these relationships require further study. We used multiple regression to examine relationships between informant-based measures of metacognitive executive function and social communication in intellectually able (IQ ⩾ 85) female ( n = 111; mean age = 10.2 ± 2.8; 31 autism spectrum disorder) and male youth ( n = 310; mean age = 10.5 ± 1.9; 146 autism spectrum disorder) with and without autism spectrum disorder from the Autism Brain Imaging Data Exchange-II database. Executive function–social communication relationships were different in females and males with autism spectrum disorder. Relationships between the entire metacognitive index and social communication were stronger in males with autism spectrum disorder than without; this pattern was also observed for metacognitive sub-indices ‘monitor’ and ‘working memory’. These patterns were not observed in females. Relationships between executive function and social communication appear different for female and male youth with an autism spectrum disorder diagnosis. To better understand the nature of metacognitive contributions to social communication in autism spectrum disorder, future work should investigate the co-development of monitoring, working memory and social communication, while taking gender into account.

Background and objectives: Pediatric settings often use a patient-centered medical home model in caring for patients in the outpatient setting and for attempting to connect inpatient care with outpatient follow-up. This medical home model has proven to be beneficial in many aspects of patient care, but there needs to be a good transition between inpatient and outpatient services. Our goal in this study is to determine the association of particular variables with adherence to outpatient follow-up after a general inpatient stay, in the pediatric population. Methods: In a retrospective sample of 221 patients, we study the association of variables such as demographics, medical history, hospital discharge and appointments, and caregiver information, with patient adherence to outpatient appointments after discharge from pediatric inpatient treatment. Results: We found that increased length of hospital stay and a non English-speaking caregiver were each associated with increased odds for adherence. Discharge diagnosis of respiratory illness and that of neurology/psychiatry/toxicology were associated with decreased odds for adherence. None of the demographic and medical history variables were associated with adherence. Conclusions: Our findings offer guidance to clinicians for the types of patients who may need closer follow-up and interventions set in place to remind these patients of the importance of attending an outpatient appointment. Keywords: Outpatients, Office visits, Patient compliance, Inpatients, Patient appointment, Abbreviations: US, United States, PCP, primary care physician, OPA, outpatient appointment, ED, emergency department, PICU, pediatric intensive care, ANOVA, Analysis of variance, CF, cystic fibrosis

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.

ripple is an experimental visual essay exploring the concept of material glitch, remixing document windows and candid screenshots juxtaposed with architectural windows and physical screens. Positioning itself as a meta-document that organizes diaristic fragments of thoughts and ideas, the work charts the artist’s creative process in preparation for a collaborative exhibition in the muddy middle of the real and virtual space.

In females, pubertal onset appears to signal the opening of a window of increased vulnerability to the effects of stress on neurobehavioral development. What is the impact of pubertal timing on this process? We assessed the effects of pubertal timing and stress on behavior and amygdala functional connectivity (FC) in adolescent female macaques, whose social hierarchy provides an ethologically valid model of chronic psychosocial stress. Monkeys experienced puberty spontaneously (n=34) or pubertal delay via Lupron treatment from age 16-33 months (n=36). We examined the effects of stress (continuous dimension spanning dominant/low-stress to subordinate/high-stress) and experimental pubertal delay (Lupron-treated vs. Control) on socioemotional behavior and FC at 43-46 months, after all animals had begun puberty. Regardless of treatment, subordinate monkeys were more submissive and less affiliative, and exhibited weaker FC between amygdala and dorsolateral prefrontal cortex and stronger FC between amygdala and temporal pole. Regardless of social rank, Lupron-treated monkeys were also more submissive, less affiliative, and explored less in a “Human Intruder” task but were less anxious than untreated monkeys; they exhibited stronger FC between amygdala and orbitofrontal cortex. No interactions between rank and Lupron treatment were observed. These data suggest that some of the effects of chronic subordination stress and delayed puberty overlap behaviorally, such that late-onset puberty-linked exposure to female hormones mimics chronic stress. In the brain, however, delayed puberty and subordination stress had separable effects, suggesting that the overlapping socioemotional outcomes may be mediated by distinct neuroplastic mechanisms. To gain further insights, additional longitudinal studies are required.

ObjectiveAttention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. We aimed to directly compare all three disorders. The ENIGMA consortium is ideally positioned to investigate structural brain alterations across these disorders.MethodsStructural T1-weighted whole-brain MRI of controls (n=5,827) and patients with ADHD (n=2,271), ASD (n=1,777), and OCD (n=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. We examined subcortical volume, cortical thickness and surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults using linear mixed-effects models adjusting for age, sex and site (and ICV for subcortical and surface area measures).ResultsWe found no shared alterations among all three disorders, while shared alterations between any two disorders did not survive multiple comparisons correction. Children with ADHD compared to those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller ICV than controls and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared to adult controls and other clinical groups. No OCD-specific alterations across different age-groups and surface area alterations among all disorders in childhood and adulthood were observed.ConclusionOur findings suggest robust but subtle alterations across different age-groups among ADHD, ASD, and OCD. ADHD-specific ICV and hippocampal alterations in children and adolescents, and ASD-specific cortical thickness alterations in the frontal cortex in adults support previous work emphasizing neurodevelopmental alterations in these disorders.