Comparison of comprehensive quantitative EEG metrics between typically developing boys and girls in resting state eyes-open and eyes-closed conditions.

Introduction: A majority of published studies comparing quantitative EEG (qEEG) in typically developing (TD) children and children with neurodevelopmental or psychiatric disorders have used a control group (e.g., TD children) that combines boys and girls. This suggests a widespread supposition that typically developing boys and girls have similar brain activity at all locations and frequencies, allowing the data from TD boys and girls to be aggregated in a single group. Methods: In this study, we have rigorously challenged this assumption by performing a comprehensive qEEG analysis on EEG recoding of TD boys (n = 84) and girls (n = 62), during resting state eyes-open and eyes-closed conditions (EEG recordings from Child Mind Institute's Healthy Brain Network (HBN) initiative). Our qEEG analysis was performed over narrow-band frequencies (e.g., separating low α from high α, etc.), included sex, age, and head size as covariates in the analysis, and encompassed computation of a wide range of qEEG metrics that included both absolute and relative spectral power levels, regional hemispheric asymmetry, and inter- and intra-hemispheric magnitude coherences as well as phase coherency among cortical regions. We have also introduced a novel compact yet comprehensive visual presentation of the results that allows comparison of the qEEG metrics of boys and girls for the entire EEG locations, pairs, and frequencies in a single graph. Results: Our results show there are wide-spread EEG locations and frequencies where TD boys and girls exhibit differences in their absolute and relative spectral powers, hemispheric power asymmetry, and magnitude coherence and phase synchrony. Discussion: These findings strongly support the necessity of including sex, age, and head size as covariates in the analysis of qEEG of children, and argue against combining data from boys and girls. Our analysis also supports the utility of narrow-band frequencies, e.g., dividing α, ß, and γ band into finer sub-scales. The results of this study can serve as a comprehensive normative qEEG database for resting state studies in children containing both eyes open and eyes closed paradigms.

NIDM-Terms: community-based terminology management for improved neuroimaging dataset descriptions and query.

The biomedical research community is motivated to share and reuse data from studies and projects by funding agencies and publishers. Effectively combining and reusing neuroimaging data from publicly available datasets, requires the capability to query across datasets in order to identify cohorts that match both neuroimaging and clinical/behavioral data criteria. Critical barriers to operationalizing such queries include, in part, the broad use of undefined study variables with limited or no annotations that make it difficult to understand the data available without significant interaction with the original authors. Using the Brain Imaging Data Structure (BIDS) to organize neuroimaging data has made querying across studies for specific image types possible at scale. However, in BIDS, beyond file naming and tightly controlled imaging directory structures, there are very few constraints on ancillary variable naming/meaning or experiment-specific metadata. In this work, we present NIDM-Terms, a set of user-friendly terminology management tools and associated software to better manage individual lab terminologies and help with annotating BIDS datasets. Using these tools to annotate BIDS data with a Neuroimaging Data Model (NIDM) semantic web representation, enables queries across datasets to identify cohorts with specific neuroimaging and clinical/behavioral measurements. This manuscript describes the overall informatics structures and demonstrates the use of tools to annotate BIDS datasets to perform integrated cross-cohort queries.

A Proposed Human Structural Brain Connectivity Matrix in the Center for Morphometric Analysis Harvard-Oxford Atlas Framework: A Historical Perspective and Future Direction for Enhancing the Precision of Human Structural Connectivity with a Novel Neuroanatomical Typology.

A complete structural definition of the human nervous system must include delineation of its wiring diagram (e.g., Swanson LW. Brain architecture: understanding the basic plan, 2012). The complete formulation of the human brain circuit diagram (BCD [Front Neuroanat. 2020;14:18]) has been hampered by an inability to determine connections in their entirety (i.e., not only pathway stems but also origins and terminations). From a structural point of view, a neuroanatomic formulation of the BCD should include the origins and terminations of each fiber tract as well as the topographic course of the fiber tract in three dimensions. Classic neuroanatomical studies have provided trajectory information for pathway stems and their speculative origins and terminations [Dejerine J and Dejerine-Klumpke A. Anatomie des Centres Nerveux, 1901; Dejerine J and Dejerine-Klumpke A. Anatomie des Centres Nerveux: Méthodes générales d'étude-embryologie-histogénèse et histologie. Anatomie du cerveau, 1895; Ludwig E and Klingler J. Atlas cerebri humani, 1956; Makris N. Delineation of human association fiber pathways using histologic and magnetic resonance methodologies; 1999; Neuroimage. 1999 Jan;9(1):18-45]. We have summarized these studies previously [Neuroimage. 1999 Jan;9(1):18-45] and present them here in a macroscale-level human cerebral structural connectivity matrix. A matrix in the present context is an organizational construct that embodies anatomical knowledge about cortical areas and their connections. This is represented in relation to parcellation units according to the Harvard-Oxford Atlas neuroanatomical framework established by the Center for Morphometric Analysis at Massachusetts General Hospital in the early 2000s, which is based on the MRI volumetrics paradigm of Dr. Verne Caviness and colleagues [Brain Dev. 1999 Jul;21(5):289-95]. This is a classic connectional matrix based mainly on data predating the advent of DTI tractography, which we refer to as the "pre-DTI era" human structural connectivity matrix. In addition, we present representative examples that incorporate validated structural connectivity information from nonhuman primates and more recent information on human structural connectivity emerging from DTI tractography studies. We refer to this as the "DTI era" human structural connectivity matrix. This newer matrix represents a work in progress and is necessarily incomplete due to the lack of validated human connectivity findings on origins and terminations as well as pathway stems. Importantly, we use a neuroanatomical typology to characterize different types of connections in the human brain, which is critical for organizing the matrices and the prospective database. Although substantial in detail, the present matrices may be assumed to be only partially complete because the sources of data relating to human fiber system organization are limited largely to inferences from gross dissections of anatomic specimens or extrapolations of pathway tracing information from nonhuman primate experiments [Front Neuroanat. 2020;14:18, Front Neuroanat. 2022;16:1035420, and Brain Imaging Behav. 2021;15(3):1589-1621]. These matrices, which embody a systematic description of cerebral connectivity, can be used in cognitive and clinical studies in neuroscience and, importantly, to guide research efforts for further elucidating, validating, and completing the human BCD [Front Neuroanat. 2020;14:18].

Quantitative MRI Characterization of the Extremely Preterm Brain at Adolescence: Atypical versus Neurotypical Developmental Pathways.

Background Extremely preterm (EP) birth is associated with higher risks of perinatal white matter (WM) injury, potentially causing abnormal neurologic and neurocognitive outcomes. MRI biomarkers distinguishing individuals with and without neurologic disorder guide research on EP birth antecedents, clinical correlates, and prognoses. Purpose To compare multiparametric quantitative MRI (qMRI) parameters of EP-born adolescents with autism spectrum disorder, cerebral palsy, epilepsy, or cognitive impairment (ie, atypically developing) with those without (ie, neurotypically developing), characterizing sex-stratified brain development. Materials and Methods This prospective multicenter study included individuals aged 14-16 years born EP (Extremely Low Gestational Age Newborns-Environmental Influences on Child Health Outcomes Study, or ELGAN-ECHO). Participants underwent 3.0-T MRI evaluation from 2017 to 2019. qMRI outcomes were compared for atypically versus neurotypically developing adolescents and for girls versus boys. Sex-stratified multiple regression models were used to examine associations between spatial entropy density (SEd) and T1, T2, and cerebrospinal fluid (CSF)-normalized proton density (nPD), and between CSF volume and T2. Interaction terms modeled differences in slopes between atypically versus neurotypically developing adolescents. Results A total of 368 adolescents were classified as 116 atypically (66 boys) and 252 neurotypically developing (125 boys) participants. Atypically versus neurotypically developing girls had lower nPD (mean, 557 10 × percent unit [pu] ± 46 [SD] vs 573 10 × pu ± 43; P = .04), while atypically versus neurotypically developing boys had longer T1 (814 msec ± 57 vs 789 msec ± 82; P = .01). Atypically developing girls versus boys had lower nPD and shorter T2 (eg, in WM, 557 10 × pu ± 46 vs 580 10 × pu ± 39 for nPD [P = .006] and 86 msec ± 3 vs 88 msec ± 4 for T2 [P = .003]). Atypically versus neurotypically developing boys had a more moderate negative association between T1 and SEd (slope, -32.0 msec per kB/cm3 [95% CI: -49.8, -14.2] vs -62.3 msec per kB/cm3 [95% CI: -79.7, -45.0]; P = .03). Conclusion Atypically developing participants showed sexual dimorphisms in the cerebrospinal fluid-normalized proton density (nPD) and T2 of both white matter (WM) and gray matter. Atypically versus neurotypically developing girls had lower WM nPD, while atypically versus neurotypically developing boys had longer WM T1 and more moderate T1 associations with microstructural organization in WM. © RSNA, 2022 Online supplemental material is available for this article.

Is Neuroscience FAIR? A Call for Collaborative Standardisation of Neuroscience Data.

In this perspective article, we consider the critical issue of data and other research object standardisation and, specifically, how international collaboration, and organizations such as the International Neuroinformatics Coordinating Facility (INCF) can encourage that emerging neuroscience data be Findable, Accessible, Interoperable, and Reusable (FAIR). As neuroscientists engaged in the sharing and integration of multi-modal and multiscale data, we see the current insufficiency of standards as a major impediment in the Interoperability and Reusability of research results. We call for increased international collaborative standardisation of neuroscience data to foster integration and efficient reuse of research objects.

A Standards Organization for Open and FAIR Neuroscience: the International Neuroinformatics Coordinating Facility.

There is great need for coordination around standards and best practices in neuroscience to support efforts to make neuroscience a data-centric discipline. Major brain initiatives launched around the world are poised to generate huge stores of neuroscience data. At the same time, neuroscience, like many domains in biomedicine, is confronting the issues of transparency, rigor, and reproducibility. Widely used, validated standards and best practices are key to addressing the challenges in both big and small data science, as they are essential for integrating diverse data and for developing a robust, effective, and sustainable infrastructure to support open and reproducible neuroscience. However, developing community standards and gaining their adoption is difficult. The current landscape is characterized both by a lack of robust, validated standards and a plethora of overlapping, underdeveloped, untested and underutilized standards and best practices. The International Neuroinformatics Coordinating Facility (INCF), an independent organization dedicated to promoting data sharing through the coordination of infrastructure and standards, has recently implemented a formal procedure for evaluating and endorsing community standards and best practices in support of the FAIR principles. By formally serving as a standards organization dedicated to open and FAIR neuroscience, INCF helps evaluate, promulgate, and coordinate standards and best practices across neuroscience. Here, we provide an overview of the process and discuss how neuroscience can benefit from having a dedicated standards body.

Biomarkers Based on Comprehensive Hierarchical EEG Coherence Analysis: Example Application to Social Competence in Autism (Preliminary Results).

Electroencephalography (EEG) coherence analysis, based on measurement of synchronous oscillations of neuronal clusters, has been used extensively to evaluate functional connectivity in brain networks. EEG coherence studies have used a variety of analysis variables (e.g., time and frequency resolutions corresponding to the analysis time period and frequency bandwidth), regions of the brain (e.g., connectivity within and between various cortical lobes and hemispheres) and experimental paradigms (e.g., resting state with eyes open or closed; performance of cognitive tasks). This variability in study designs has resulted in difficulties in comparing the findings from different studies and assimilating a comprehensive understanding of the underlying brain activity and regions with abnormal functional connectivity in a particular disorder. In order to address the variability in methods across studies and to facilitate the comparison of research findings between studies, this paper presents the structure and utilization of a comprehensive hierarchical electroencephalography (EEG) coherence analysis that allows for formal inclusion of analysis duration, EEG frequency band, cortical region, and experimental test condition in the computation of the EEG coherences. It further describes the method by which this EEG coherence analysis can be utilized to derive biomarkers related to brain (dys)function and abnormalities. In order to document the utility of this approach, the paper describes the results of the application of this method to EEG and behavioral data from a social synchrony paradigm in a small cohort of adolescents with and without Autism Spectral Disorder.

Meaningful associations in the adolescent brain cognitive development study.

The Adolescent Brain Cognitive Development (ABCD) Study is the largest single-cohort prospective longitudinal study of neurodevelopment and children's health in the United States. A cohort of n = 11,880 children aged 9-10 years (and their parents/guardians) were recruited across 22 sites and are being followed with in-person visits on an annual basis for at least 10 years. The study approximates the US population on several key sociodemographic variables, including sex, race, ethnicity, household income, and parental education. Data collected include assessments of health, mental health, substance use, culture and environment and neurocognition, as well as geocoded exposures, structural and functional magnetic resonance imaging (MRI), and whole-genome genotyping. Here, we describe the ABCD Study aims and design, as well as issues surrounding estimation of meaningful associations using its data, including population inferences, hypothesis testing, power and precision, control of covariates, interpretation of associations, and recommended best practices for reproducible research, analytical procedures and reporting of results.

Understanding the impact of preprocessing pipelines on neuroimaging cortical surface analyses.

BACKGROUND: The choice of preprocessing pipeline introduces variability in neuroimaging analyses that affects the reproducibility of scientific findings. Features derived from structural and functional MRI data are sensitive to the algorithmic or parametric differences of preprocessing tasks, such as image normalization, registration, and segmentation to name a few. Therefore it is critical to understand and potentially mitigate the cumulative biases of pipelines in order to distinguish biological effects from methodological variance. METHODS: Here we use an open structural MRI dataset (ABIDE), supplemented with the Human Connectome Project, to highlight the impact of pipeline selection on cortical thickness measures. Specifically, we investigate the effect of (i) software tool (e.g., ANTS, CIVET, FreeSurfer), (ii) cortical parcellation (Desikan-Killiany-Tourville, Destrieux, Glasser), and (iii) quality control procedure (manual, automatic). We divide our statistical analyses by (i) method type, i.e., task-free (unsupervised) versus task-driven (supervised); and (ii) inference objective, i.e., neurobiological group differences versus individual prediction. RESULTS: Results show that software, parcellation, and quality control significantly affect task-driven neurobiological inference. Additionally, software selection strongly affects neurobiological (i.e. group) and individual task-free analyses, and quality control alters the performance for the individual-centric prediction tasks. CONCLUSIONS: This comparative performance evaluation partially explains the source of inconsistencies in neuroimaging findings. Furthermore, it underscores the need for more rigorous scientific workflows and accessible informatics resources to replicate and compare preprocessing pipelines to address the compounding problem of reproducibility in the age of large-scale, data-driven computational neuroscience.

Psychiatric Symptomatology, Mood Regulation, and Resting State Functional Connectivity of the Amygdala: Preliminary Findings in Youth With Mood Disorders and Childhood Trauma.

BACKGROUND: As mood dysregulation and hyperarousal are overlapping and prominent features of posttraumatic stress disorder (PTSD), and mood disorders (MD) including bipolar disorder (BD), we aimed to clarify the role of trauma and MD on the resting state functional connectivity (RSFC) of amygdala in MD youth with or without trauma exposure, and healthy controls (HC). METHODS: Of 23 subjects, 21 completed the magnetic resonance imaging (MRI) protocol, 5 were excluded for subject motion, leaving final sample size of 16: nine subjects with MD (5/9 with trauma), and 7 HC. Youth were assessed with Schedule for Affective Disorders and Schizophrenia for School Aged Children-Present and Lifetime Version (K-SADS-PL), and other behavioral measures including Young Mania Rating Scale (YMRS). Imaging data were acquired using functional MRI in 3-T scanner. Imaging included T1-weighted structural MRI and 6-min resting state acquisition. RESULTS: In between group analysis, the average correlation coefficients between left anterior cingulate cortex (Acc) and left insula cortex with left amygdala regions were significantly larger in HC compared to the patient population. Connectivity between left amygdala and left cingulate cortex shows a significant negative correlation with YMRS severity. CONCLUSIONS: In this preliminary study, MD with trauma youth had more manic symptoms and difficulties regulating anger. While MD youth showed reduced RSFC of left amygdala with left acc and left insula, no significant difference between the subgroups of children with MD was observed. However, when looking at both clinical groups together, we observed a significant correlation of RSFC of left amygdala to left acc, and YMRS scores.

An assessment of the autism neuroimaging literature for the prospects of re-executability.

Background: The degree of reproducibility of the neuroimaging literature in psychiatric application areas has been called into question and the issues that relate to this reproducibility are extremely complex. Some of these complexities have to do with the underlying biology of the disorders that we study and others arise due to the technology we apply to the analysis of the data we collect. Ultimately, the observations we make get communicated to the rest of the community through publications in the scientific literature. Methods: We sought to perform a 're-executability survey' to evaluate the recent neuroimaging literature with an eye toward seeing if the technical aspects of our publication practices are helping or hindering the overall quest for a more reproducible understanding of brain development and aging. The topic areas examined include availability of the data, the precision of the imaging method description and the reporting of the statistical analytic approach, and the availability of the complete results. We applied the survey to 50 publications in the autism neuroimaging literature that were published between September 16, 2017 to October 1, 2018. Results: The results of the survey indicate that for the literature examined, data that is not already part of a public repository is rarely available, software tools are usually named but versions and operating system are not, it is expected that reasonably skilled analysts could approximately perform the analyses described, and the complete results of the studies are rarely available.  Conclusions: We have identified that there is ample room for improvement in research publication practices. We hope exposing these issues in the retrospective literature can provide guidance and motivation for improving this aspect of our reporting practices in the future.

Everything Matters: The ReproNim Perspective on Reproducible Neuroimaging.

There has been a recent major upsurge in the concerns about reproducibility in many areas of science. Within the neuroimaging domain, one approach is to promote reproducibility is to target the re-executability of the publication. The information supporting such re-executability can enable the detailed examination of how an initial finding generalizes across changes in the processing approach, and sampled population, in a controlled scientific fashion. ReproNim: A Center for Reproducible Neuroimaging Computation is a recently funded initiative that seeks to facilitate the "last mile" implementations of core re-executability tools in order to reduce the accessibility barrier and increase adoption of standards and best practices at the neuroimaging research laboratory level. In this report, we summarize the overall approach and tools we have developed in this domain.

Functional asymmetry of thalamocortical networks in subjects at ultra-high risk for psychosis and first-episode schizophrenia.

Disrupted functional asymmetry has been implicated in schizophrenia. However, it remains unknown whether disrupted functional asymmetry originates from intra-hemispheric and/or inter-hemispheric functional connectivity (FC) in the patients, and whether it starts at very early stage of psychosis. Seventy-six patients with first-episode, drug-naive schizophrenia, 74 subjects at ultra-high risk for psychosis (UHR), and 71 healthy controls underwent resting-state functional magnetic resonance imaging. The 'Parameter of asymmetry' (PAS) metric was calculated and support vector machine (SVM) classification analysis was applied to analyze the data. Compared with healthy controls, patients exhibited decreased PAS in the left thalamus/pallidum, right hippocampus/parahippocampus, right inferior frontal gyrus/insula, right thalamus, and left inferior parietal lobule, and increased PAS in the left calcarine, right superior occipital gyrus/middle occipital gyrus, and right precentral gyrus/postcentral gyrus. By contrast, UHR subjects showed decreased PAS in the left thalamus relative to healthy controls. A negative correlation was observed between decreased PAS in the right hippocampus/parahippocampus and Brief Visuospatial Memory Test-Revised (BVMT-R) scores in the patients (r = -0.364, p = 0.002). Moreover, the PAS values in the left thalamus could discriminate the patients/UHR subjects from the controls with acceptable sensitivities (68.42%/81.08%). First-episode patients and UHR subjects shared decreased PAS in the left thalamus. This observed pattern of functional asymmetry highlights the involvement of the thalamus in the pathophysiology of psychosis and may also be applied as a very early marker for psychosis.

Making replication prestigious.

Making replication studies widely conducted and published requires new incentives. Academic awards can provide such incentives by highlighting the best and most important replications. The Organization for Human Brain Mapping (OHBM) has led such efforts by recently introducing the OHBM Replication Award. Other communities can adopt this approach to promote replications and reduce career cost for researchers performing them.

Coordination Impairments Are Associated With Falling Among Older Adults.

Background/Study Context: Approximately one third of older adults over the age of 65, and over 40% of those over 80 years, fall each year, leading to fractures, morbidity, and mortality. Annual direct medical costs due to falls in the United States are approximately $19.2 billion. The identification of new treatable risk factors for falls has the potential to advance their prevention and rehabilitation. METHODS: A cross-sectional study of 127 community-dwelling adults aged 67-99 years was conducted. An electronic gait walkway was used to assess gait coordination, measured as the Phase Coordination Index during normal speed walking. A motion capture system was used to assess rhythmic interlimb antiphase ankle coordination, measured as the standard deviation of ankle relative phase. Having fallen in the previous year was self-reported retrospectively. Odds ratios for falling as a function of coordination quartiles were determined using multivariable logistic regression. RESULTS: Adjusting for age, sex, body mass index, number of chronic conditions, Mini-Mental State Examination score, gait speed, and the variability of step length, time, and width, the odds ratios for falling based upon being in the 4th (the poorest) quartiles of gait or ankle coordination were 5.5 (95% confidence interval [CI]: 1.2-24.7) and 8.2 (95% CI: 2.2-31.3), respectively, and 3.7 (95% CI: 1.0-13.8) for the 3rd quartile of gait coordination, compared with the best (the 1st) coordination quartiles. Similar results were found in regression without adjustment for gait characteristics. CONCLUSION: The results support the hypothesis that impaired gait and rhythmic interlimb ankle coordination are associated with a history of falls in the past year. Prospective longitudinal research is needed to determine the possible direction of causality between falls and impaired coordination.

A very simple, re-executable neuroimaging publication.

Reproducible research is a key element of the scientific process. Re-executability of neuroimaging workflows that lead to the conclusions arrived at in the literature has not yet been sufficiently addressed and adopted by the neuroimaging community. In this paper, we document a set of procedures, which include supplemental additions to a manuscript, that unambiguously define the data, workflow, execution environment and results of a neuroimaging analysis, in order to generate a verifiable re-executable publication. Re-executability provides a starting point for examination of the generalizability and reproducibility of a given finding.